200 Articles
Dr. Alpa Prajapati
This study investigates the influence of social media advertising on the perception of online purchases among Indian students, using a sample size of 287 respondents collected through convenience sampling. Through quantitative analysis, the research examines the relationship between exposure to social media advertisements and attitudes towards online shopping among Indian students. Findings reveal insights into how factors like ad content, frequency of exposure, and perceived trustworthiness of online retailers promoted through social media influence consumer perceptions and behaviours. Additionally, the study highlights the pragmatic use of convenience sampling for data collection in research involving diverse populations. The implications of the study extend to marketers and advertisers, offering guidance on effectively targeting and engaging with the Indian student demographic through social media channels. Ultimately, this research contributes to the understanding of social media marketing and online consumer behaviour, emphasizing the importance of tailored advertising strategies to resonate with Indian students and drive online sales in the competitive digital marketplace.
Dr. Rajeev Bhaiya Maurya
Background: Artificial Intelligence (AI) is revolutionizing healthcare by enhancing diagnostics, decision-making, and personalized medicine. Homoeopathy, being an individualized system of medicine, can benefit significantly from AI-driven innovations for case-taking, repertorization, drug proving, and clinical decision support. Objective: This narrative review aims to explore the applications of AI in homoeopathy, summarize current developments, and highlight future directions for integrative digital healthcare. Methods: A literature search was conducted in PubMed, Scopus, Google Scholar, and AYUSH research databases for studies, reports, and conceptual papers on AI and homoeopathy (2000–2025). In addition, grey literature, conference proceedings, and digital health projects were screened. Relevant examples from mainstream AI in healthcare were extrapolated to homoeopathy. Results: Current applications of AI in homoeopathy include: • AI-based case-taking and symptom analysis using Natural Language Processing (NLP). • Machine learning algorithms for repertorization and individualized prescription support. • Data mining techniques in materia medica and drug proving validation. • AI-assisted systematic reviews and evidence synthesis. • Mobile health applications for patient monitoring, compliance, and outcome tracking. Future possibilities involve precision homoeopathy through integration of patient clinical data, biomarkers, and AI-driven predictive modelling. Challenges include lack of standardized datasets, need for robust validation, and ethical issues related to patient privacy. Conclusion: AI has immense potential to modernize homoeopathy by improving accuracy, efficiency, and evidence generation. Collaborative efforts between homoeopathic practitioners, data scientists, and policymakers are needed to create reliable, validated, and clinically applicable AI models.
Khushi Bhupesh, Mr. Ajit Singh
The heart of Indian education is the Delhi University that moulds the lives of an innumerable number of learners. From the largest companies that seek to employ the brightest of minds to small companies that require some energy to add to theirs, all industries across the country have an interest in students from the University of Delhi. Each year the University of Delhi releases a new batch of students that come from numerous colleges and education areas in the university that mould themselves to the job market. Some are secured through the efforts of the university’s employment department while others seek the university levels to become a part of their effort. It seems to be a numbers game for the university, although the expectations for the numbers are even higher. Students from the University of Delhi have a variety of ways to become aware of the location of their stories. Each student has their own vision of what they would like to do in life, a vision that comes from their traditions and their schools. These influence their students along with the high pressure life of Delhi as some friends push their young counterparts to achieve more in society while others call out to their friends to win in the society around them. The desires of the students come from the lectures they are given by the bastions of education in the city or the visions of the offices around the city while some come from the nightmares that the students share with their friends about the difficulties of attaining their desired jobs from the companies that populate the university campus with their brimming with the skills required for the jobs while some have an understanding of the beats of the companies that their students dream of joining.
Dr. Kyung Ki Eun, Dr. Mrinmoy Roy, Dr. Shradha Vernekar, Dr. Shyam Shukla, Suyesha Shukla
Purpose - Religious tourism is increasingly recognized as a catalyst for regional development, yet its strategic management through dynamic capabilities in emerging pilgrimage destinations remains insufficiently examined. Sacred cities draw upon their cultural heritage, spiritual identity, and evolving infrastructure to attract visitors and stimulate local economies. This study aims to explore how dynamic capabilities specifically sensing, seizing, and transforming shape sustainable tourism development and economic revitalization of JaiSriRam’s Ayodhya amid its recent religious and infrastructural resurgence. Design/methodology/approach - The study uses a qualitative case study approach combining secondary data such as government reports, tourism statistics, policy documents, and institutional publications with primary insights from stakeholder interviews. A dynamic capabilities lens is applied to understand how stakeholders identify opportunities, mobilize resources, and adapt within Ayodhya’s evolving tourism ecosystem. Findings - The findings suggest that Ayodhya’s transformation is underpinned by strong sensing capabilities linked to cultural and religious revival, effective seizing capabilities demonstrated through infrastructure ex-pansion and policy initiatives, and transforming capabilities reflected in broader ecosystem changes such as increased hospitality investments, employment generation, and digital integration. However, the study also highlights emerging challenges related to environmental sustainability, resource pressures, and the need for inclusive stakeholder engagement. Originality/value - This research contributes to the limited body of literature on dynamic capabilities within religious tourism contexts by positioning Ayodhya as an illustrative case of spiritually driven economic trans-formation. It underscores the importance of aligning cultural heritage with adaptive strategic capabilities while advocating for policy interventions that ensure long-term sustainability and balanced regional development
Ananya Chetia, Gargi Medhi, Sibasish Sonowal, Uddipan Das
Effective removal of suspended solids, colloidal turbidity, and organic fractions from surface water matrices is a foundational requirement for potable water production. Conventional water treatment schemes heavily rely on sedimentation processes augmented by synthetic chemical coagulants, predominantly Aluminum Sulfate (Alum), due to its established efficiency in large-scale utilities. However, escalating concerns regarding the environmental footprint of chemical sludge, the economic burden of sludge disposal, and potential neurotoxic health risks associated with residual aluminum have catalyzed research into sustainable biopolymer alternatives. This study systematically evaluates the coagulation performance of four plant-based extracts—Banana Peel (Musa acuminata), Okra (Abelmoschus esculentus), Orange Peel (Citrus sinensis), and Neem Leaves (Azadirachta indica)—and contrasts their efficacy against commercial Alum. Utilizing standard Jar Test apparatus, controlled experiments were conducted on synthetic turbid water stabilized at an initial turbidity of 24 NTU. The empirical results demonstrated that among the natural alternatives, Azadirachta indica (Neem) leaves achieved the highest clarification efficiency at 62.50% (residual turbidity of 9 NTU), followed closely by Abelmoschus esculentus (Okra) at 58.33% (10 NTU). Conversely, Musa acuminata and Citrus sinensis extracts exhibited moderate and identical efficiencies of 45.84% (13 NTU). While commercial Alum maintained superior performance by achieving a 95.83% turbidity reduction down to a baseline of 1 NTU, the findings validate that natural coagulants hold significant promise as eco-friendly, non-toxic, and economically viable alternatives for decentralized, small-scale, and rural water purification systems.
Wing Cheung Tang
The incorporation of Artificial Intelligence (AI) into evaluation processes in education, recruitment, and research has significantly accelerated, propelled by advancements in large language models (LLMs) and machine learning. This critical review amalgamates evidence from systematic reviews, empirical studies, and ethical frameworks published from 2018 to 2026 to assess AI's role in evaluation. The review looks at the technical state of AI-based assessment, talks about the problems of algorithmic bias and fairness, points out the epistemological limitations of machine scoring, talks about the gaps in regulatory and ethical accountability, and thinks about the paradox of using AI to find AI-generated content. Our analysis finds that while AI can grade consistently and quickly, the evidence for its accuracy is shaky. Most performance tests for AI (benchmarks) are not statistically sound, efforts to reduce bias are fragmented, and current quality standards fail to address AI's unique failures. Bias mitigation efforts are disjointed, and current assessment quality criteria do not adequately address AI's distinct failures.
Olanrewaju Akintunde Tanimola, Rotimi Rufus Dinrifo
The objective of this work was to design and construct a manually operated seed drill for small-scale farmers, particularly those cultivating small acreages in urban and peri-urban areas of Lagos, Nigeria. The machine was constructed using readily available materials and standard mechanical components. The low-cost equipment is pushed by a human operator and operates via a ground- wheel-driven chain and sprocket system that transmits motion to a seed metering mechanism. The drill works best in tilled soils where coverage of the sown seed is easier. The drill was tested with the planting of corn seeds. The efficiency of the machine was 72% and the depth of sowing was influenced by the degree of tilth and moisture content of the soil. With no requirement for fuel or electricity, this innovation is poised to enhance agricultural productivity, especially in resource-constrained settings.
Almahden C. Lumidseg, Lyanne T. H. Jover, Roden C. Yumol
The primary raw materials for the manufacturing of the facemasks are non- biodegradable synthetic polymers derived from petrochemicals. Disposable face masks are made of plastic, which does not biodegrade easily. This study aims to determine the effectiveness of the Banana Pseudo Stem Face Mask. Candle testing was conducted to determine the filtering ability. This was attained by blowing a candle while wearing a mask; the amount of air that escapes from your mask determines the result. MuSk Fabric is effective for a strong prevention from a simulation for everyday respiratory exchanges and interactions such as coughs and conversations. Particle filtration is what helps block droplets and particles from traveling through your mask. This test determines if it can preserve the respiratory system against the non-desirable air droplets and aerosols such as the viral or pollution particles. MuSk Fabric particle filtration testing, indicating that the particles did not pass through. It indicates that MuSk Fabric has the potential to preserve the respiratory system against the non- desirable air droplets and aerosols such as the viral or pollution particles. Using a 0.5 mL Pasteur pipette, water was dropped onto the surface of each three MuSk Fabrics and Abaca Face Mask. A 1000x USB Microscope took a close-up photo upon contact. On average, MuSk Fabrics obtained a higher contact angle of 162° over the 131° calculated for the Abaca Face Mask. Independent Sample T-test was confirmed that this difference is statistically significant at an alpha of 0.05. Biodegradability of MuSk Fabric shows significant results which indicates that MuSk Fabric is biodegradable. These results demonstrate that MuSk is effective its use as an alternative face mask.
G.Das, K. B. Panda, M.Sen
This paper proposes a new weighted ratio-cum-product estimator using known coefficient of variation for estimating the finite population mean using two auxiliary variables under Simple Random Sampling Without Replacement (SRSWOR). The bias and mean squared error (MSE) of the proposed estimator are derived up to the first order of approximation. Optimum values of the parameters are obtained by minimizing the MSE. A theoretical comparison with existing estimators is presented along with empirical validation using real data sets. The results reveal that the proposed estimator performs better in terms of efficiency and bias under practical condition.
Heba A M ABUGHALI, Prof. Dr. Utku KOSE
The rapid expansion of digital communication has necessitated the development of advanced cryptographic frameworks capable of securing visual data against sophisticated cryptanalytic threats. This paper introduces a robust, tripartite image cryptosystem designed to address the inherent redundancies and high spatial correlations found in digital images. Unlike traditional pixel-shuffling methods, the proposed architecture operates at the bit-stream level through three integrated stages: Bit-level Recombination and Permutation, Dynamic Multi-Map Chaotic Substitution, and a Multi-round Iterative Diffusion Layer. The permutation phase utilizes a symmetrical interchanging process to effectively neutralize spatial redundancies. A key innovation in the substitution layer is the implementation of a key-driven dynamic selection mechanism that switches between four distinct chaotic systems—Tent, Lorenz, Logistic, and Henon maps—ensuring session-specific unpredictability and resistance to modeling attacks. Security is further fortified by a block-cipher-based iterative diffusion layer incorporating XNOR-based logical masking and feedback loops to propagate minor input variations throughout the entire ciphertext. Empirical validation via MATLAB simulations demonstrates that the proposed scheme achieves near-ideal performance benchmarks, including an information entropy of approximately 7.9993 and a perfectly uniform histogram distribution. Furthermore, the system exhibits exceptional resistance to differential attacks, yielding a high Number of Pixels Change Rate (NPCR) and Unified Average Changing Intensity (UACI) scores that outperform several contemporary methods. Additionally, the cryptosystem demonstrates high computational efficiency, with a linear-time complexity of O(M×N), making it an ideal candidate for real-time secure communication and high-definition video encryption. Comparative analyses confirm that the bit-level granularity and iterative diffusion layers successfully eliminate inter-pixel correlations, providing a secure and computationally efficient solution for real-time image protection in modern communication environments.
C. Shashank Reddy, Dr. Chaitanya Udatha, Y.S.S.K Keerthija
Malware detection is a complex task for signature-based anti-virus software, especially for polymorphic malware and zero-day attacks. However, this project proposes a vision-based static malware detection and classification method that represents raw executable file bytes as fixed-size grayscale images called byte plots and attempts to classify malware families based on these images without executing them. In this project, for the proposed model, the best architecture is Convolutional Neural Networks (CNN) + Random Forest (CNN-RF). Initially, a CNN is trained to learn discriminative feature embeddings for byte plot images. Once this is done, the final softmax classifier is removed, and this CNN is used to generate a 256-dimensional vector for each input. Then, a class-balanced Random Forest is trained to predict the malware family and confidence scores. In this way, this proposed method is able to achieve better results for two different datasets, and the best results obtained are 98.07% for MalImg and 93.07% for MaleVis.
Christian B. Corsiga, Christian Jay B. Damaso, Gerald S. Bolaños, John Patrick S. Pili, Kimberly A. Garna, Mark James T. Artiaga, Mark Joseph A. Bendoy, Raffy Z. Soriano
The transition to online learning has made digital examination systems essential, yet security and integrity remain major challenges. This study developed ACADEMIS, a secure web-based examination portal for St. Clare College, addressing problems of scoring inaccuracy, security vulnerabilities, and inefficient manual processes. The system was developed using the Software Development Life Cycle (SDLC) Waterfall Model with HTML, CSS, JavaScript, PHP, and MySQL. Key features include role-based secure authentication (with bcrypt password hashing), automated grading, tab switching detection with screenshot capture and a three-strike warning system, and real-time activity logging. A quantitative evaluation was conducted with 100 respondents (97 BSCS students, 3 faculty) using a adapted System Usability Scale (SUS) questionnaire. Results showed strong user acceptance (Grand Mean = 4.29, Strongly Agree), with respondents strongly agreeing on the importance of data security (4.47), encryption (4.36), and automatic scoring (4.39). While preliminary testing was conducted with five concurrent users, the system demonstrated stable performance. The study concludes that ACADEMIS provides a viable, secure alternative to paper-based examinations, though future work should include large-scale load testing and AI-based proctoring features.
Barbara D. Ariar, RN, Joan P. Bacarisas, DM, MAN, RN
This quantitative descriptive–correlational study examined the level of adaptive leadership and empowering behaviors among nurse managers in a Level 2 government hospital, as well as their relationship. Data were collected using validated questionnaires covering adaptive leadership dimensions and key empowering behaviors. Findings showed that nurse managers demonstrated a high level of adaptive leadership, particularly in collaborative problem-solving, responsibility sharing, and support for learning, while conflict management ranked lowest. Empowering behavior was rated very high overall, with skill development as the strongest dimension and delegation of authority as the lowest. A strong positive relationship was found between adaptive leadership and empowering behavior, indicating that adaptive leadership significantly enhances staff empowerment. These results support Ronald Heifetz’s Adaptive Leadership Theory and Gretchen Spreitzer’s Psychological Empowerment Theory, highlighting that participative and development-oriented leadership fosters autonomy, competence, and engagement among nurses. Strengthening conflict management and delegation of authority is recommended to further improve empowerment and unit performance.
Dr. James L. Paglinawan, Faith V. Casas
Teacher attrition is a global crisis that uniquely manifests in the Philippine private education sector, where educators frequently migrate to public institutions or overseas for better compensation. This study investigated the influence of administrative support and workplace culture on teacher retention in private basic education institutions in Region IX (Zamboanga Peninsula). Utilizing a quantitative descriptive-correlational design, data were gathered from 489 faculty members through stratified random sampling. Standardized survey instruments, which demonstrated high reliability, were used for data collection. Findings revealed "High" levels of administrative support, a "Supportive" workplace culture, and "Low" attrition levels, Correlation analysis indicated that administrative support and workplace culture are significantly and positively linked to teacher retention. Multiple regression analysis further showed that these variables explain 60.2% of the variance in teacher retention, with "Administrative Assistance in Teaching Duties" emerging as the strongest predictor. The study concludes that while relational factors are vital, tangible assistance in instruction and discipline management is the primary driver of institutional stability.
Joseph O. AREO, Tajudeen O. AJAYI, Thomas B. AKINTUNDE
Rapid urbanisation, widening housing deficits, and uneven regional development continue to threaten sustainable urban transformation, particularly within rapidly urbanising developing economies. This study examines affordable housing as a strategic instrument for sustainable regional development through interdisciplinary collaboration between architecture and urban and regional planning. Using a PRISMA-based systematic review, 519 records were identified from the Scopus and Web of Science databases, of which 55 peer-reviewed journal articles published between 2016 and 2026 met the inclusion criteria. Policy reports from the United Nations Human Settlements Programme, the World Bank, the United Nations, and the Intergovernmental Panel on Climate Change further supported the review. The study employed thematic synthesis, Weighted Frequency Index analysis, regression modelling, and inferential validation derived from coded thematic aggregation and evidence-pattern extraction within the reviewed studies. Quantitative synthesis produced regression outcomes (R² = 0.67) and inferential validation results (χ² = 0.91, p > 0.05; κ = 0.84), indicating strong thematic consistency and analytical reliability. Findings show that integrated housing and planning systems improve urban inclusiveness by 31.4%, reduce spatial inequality by 26.8%, and enhance regional productivity by 24.7%, while fragmented urban growth intensifies environmental and infrastructure pressures. The study contributes to a systems-oriented interdisciplinary framework linking affordable housing, governance coordination, infrastructure integration, and environmental sustainability toward more resilient and inclusive urban development.
Farjana Birajdar, Mustaq Shaikh
Drought is among the most economically damaging and socially regressive hydro-meteorological hazards affecting semi-arid agrarian economies such as the Indian state of Maharashtra. Historically, drought declaration in India relied on the qualitative Anewari–Paisewari–Gridwari system, criticised for subjectivity, temporal lag, and weak reproducibility. Following the Manual for Drought Management (2016), the Government of Maharashtra issued a Government Resolution (GR) dated 07 October 2017 that institutionalised an indicator-based, two-trigger, three-stage scientific protocol. This paper provides an interdisciplinary, technically rigorous, and policy-oriented appraisal of the methodology, integrating climatology, agricultural meteorology, hydrology, groundwater science, geographic information systems (GIS), satellite remote sensing, and disaster governance. Each indicator is deconstructed: the Rainfall Deviation (RFdev) and dry-spell criterion forming Trigger-1; and the impact indicators forming Trigger-2, namely the NDVI deviation, NDWI deviation, Vegetation Condition Index (VCI), Moisture Adequacy Index (MAI), Groundwater Drought Index (GWDI), and Area-Under-Sowing indicator, followed by GPS-geotagged ground-truth verification. The mathematical formulation, physical meaning, sensitivity, and threshold defensibility of each indicator are examined and benchmarked against the India Meteorological Department classification, National Disaster Management Authority guidelines, the U.S. Drought Monitor, the Standardized Precipitation Index, and the European Combined Drought Indicator. While the GR represents a substantive advance over eye-estimation methods, limitations persist, including coarse monthly temporal resolution, spatial-resolution mismatch among inputs, omission of streamflow and reservoir indices, weak socio-economic vulnerability integration, and limited treatment of climate-change non-stationarity. An AI-augmented, IoT-enabled digital drought intelligence framework with a Drought Vulnerability and Resilience Index is proposed to complement the GR.
Hillary Kahu
Artificial intelligence (AI) at this time and era cannot be ignored. However, this paper tries to philosophically take a look, criticizing and analyzing how best we can incorporate the AI tutor with the human teacher by discussing the learning theories and myths surrounding AI. The paper argues that AI has the potential to redefine existing fear and incorporate the AI by using the different learning theories and analyzing how they can be integrated with human and AI tutors. The paper looks at the behavioral theory of learning, which is a psychological perspective, and constructivism and progressivism theories being the foundations of education philosophy and how they relate to the future of education. AI applications like ChatGPT have the potential to provide the learner with adaptive and personalized learning experiences that will help the learner align with these learning theories. However, AI has the potential to redefine future learning, but it should not be allowed to control the human teacher, as it can automate the learning, but the shaping of behavior and class control can only be best done by a human teacher. This paper offers recommendations for how teachers can effectively incorporate AI into teaching. The data collected is from using secondary data analyses. The objective: To critically analyze various learning theories and examine how they can be effectively integrated into teaching and learning practice. The paper uses the philosophical methodology to analyze the findings; hence, it relies on critical analysis to analyze data. This paper concludes by emphasizing the importance of approaching the integration of AI in learning with caution and a critical perspective.
James L. Catedrilla
This research investigates the relationship between workplace culture and employee retention at Patio Pacific Resort Boracay, employing a descriptive-correlational research framework. The study's sample consisted of 60 employees selected based on diverse demographic factors. Both descriptive and inferential statistical techniques were utilized for the analysis. The demographic profile of the respondents revealed a predominantly male workforce (75%) and a notable segment of employees aged between 21 and 30 years (50%). The food and beverage department accounted for the largest share of the workforce (33%), with a significant number of employees having tenure ranging from 1 to 5 years (43%). The results indicated that workplace culture was viewed as extensive across several key dimensions, including recognition, leadership support, job security, working conditions, and opportunities for career advancement. Furthermore, employees expressed high levels of job satisfaction and organizational commitment, along with a strong inclination to remain with the resort, indicating conducive conditions for retention. Notably, a significant positive correlation was identified between perceptions of workplace culture and employee retention, with all five dimensions contributing significantly to enhancing employee satisfaction and commitment. These findings underscore the importance of a robust and supportive organizational culture at Patio Pacific Resort Boracay in fostering employee satisfaction, commitment, and retention.
Allan F. Cipriano, Jaquelyn L. Dacutanan, Jennyrose B. Montillano, Jimpy R. Dela Peña, Laarni T. Molito, Loreto I. Ramirez Jr., Renno Jose B. Gabuya, Ritchelle D. Jabagat
This study aimed to evaluate the suitability of the English Listening Lesson Library Online (ELLLO) application as a supplementary tool for developing listening skills among Senior High School students at Motiong National High School. The study employed a quantitative evaluation research design involving forty (40) randomly selected students from different academic strands. Data were collected using an adapted evaluation rubric and a closed-ended questionnaire utilizing a dichotomous (Yes/No) scale. The collected data were analyzed using descriptive statistical measures such as frequency counts, percentages, and mean scores. Results revealed that the ELLLO application was rated as “Most Suitable” for language learning, with an overall mean score of 2.51. All evaluated categories, including content quality, pedagogical coherence, feedback and self-correction, motivation, usability, customization, and sharing, were interpreted within the same level. Among these, motivation obtained the highest mean score, indicating that the application effectively engages learners. Furthermore, students’ perceptions based on dichotomous responses yielded an overall mean of 0.87, interpreted as “Yes,” indicating that the application is generally perceived as effective, user-friendly, and relevant to students’ listening skill development. However, some respondents reported technical concerns, particularly related to accessibility and connectivity. The findings suggest that the ELLLO application is a suitable and effective supplementary tool for enhancing listening skills among Senior High School students. It is recommended that improvements be made in technical features and accessibility to further enhance its usability and effectiveness in language learning.
Fitriani Yulianti, Linofal Fakhrin, Novia Zalmita, Nurrahma Restia Fatkhiyati, Utami Nurhafsari Putri, Wila Rumina Nento
This community service initiative presents the design and implementation of an integrated empowerment model for the Minang Saiyo Padang Pariaman diaspora community in Malaysia. Drawing on a participatory action research (PAR) framework, the program engaged 63 participants across six months through five interconnected disciplinary components: food processing technology, digital literacy and communication, digital business management, mental health and counseling, and geography education. A mixed-methods evaluation design employing pre-test/post-test instruments and qualitative methods (focus group discussions and exit interviews) was used to assess outcomes. Results indicate statistically meaningful improvements across all domains: food processing knowledge scores increased by a mean of 62.4%, digital marketing self-efficacy rose from 23% to 79%, formal business record-keeping adoption increased from 31% to 71%, psychological distress rates declined from 38% to 19%, and geographical knowledge scores improved by 54.7%. Beyond domain-specific gains, participants demonstrated enhanced community cohesion and initiated self-organized peer support and cooperative structures. The integrated model confirms that holistic, multidisciplinary interventions addressing both economic and psychosocial dimensions produce synergistic outcomes that exceed the sum of their individual components, offering a replicable framework for diaspora community empowerment in Southeast Asia and beyond.
Adelola, M. A, Adewale, O. S, Adewole, D. B., Iwasokun G. B.
The continuous ingestion of high-dimensional, non-stationary physiological telemetry has precipitated a computational paradigm shift in Health Information Systems (HIS). Although deep sequence models have been proven to be highly accurate in clinical settings for pattern discovery, their deployment in real time is often limited by extreme latency of inference and an intrinsic lack of actionable clinical interpretation. In this work, the authors present a novel end-to-end hybrid system that aims to overcome this latency-accuracy dilemma by combining generalized graph theory and a Topology-Preserving Genetic Algorithm (TP-GA). The TP-GA is an intelligent, structural pre-processing filter which acts as a discretization of continuous phase spaces (obtained by empirical mining) to detect mathematically anomalous subgraphs deterministically. A novel Tensor Interface Layer then re-shapes these optimal graph trajectories into highly compressed input tensors that are then evaluated by a Transformer-based deep sequence backend. The integrated model obtained an Area Under the Precision-Recall Curve (AUPRC) of 0.952 and 0.974, respectively, on the low-frequency multi-parameter telemetry (MIMIC-III) and high-frequency univariate signals (MIT-BIH Arrhythmia Database). Importantly, the framework is able to pre-filter the sequence length before a neural network evaluation, avoiding the quadratic complexity problem of self-attention mechanisms. This structural compression achieved less than 19milliseconds of inference latency and compressed the active parameter footprint by more than 80%. In addition, the framework is clinically interpretable ante-hoc, and structurally limits the model's focus to the discrete, mappable transitions of physiological state. This approach creates a very viable, repeatable foundation for deep predictive intelligence to be deployed directly on high-end embedded systems or on resource constrained bedside edge devices.
Christopher Kabwe Mukuka
Cultural identity transformation has become a pressing analytical concern in contemporary African societies, particularly in Zambia, where globalization, urbanization, Western-oriented education, and the expansion of digital media continue to reshape social norms and value systems. This study examines cultural identity change through an interdisciplinary analytical framework that integrates anthropology, sociology, philosophy, and theology. It adopts a structured qualitative literature review with thematic synthesis, drawing on peer-reviewed articles, books, and institutional reports to systematically synthesize evidence on cultural transmission, intergenerational value shifts, and communal identity. The analysis demonstrates that while global and structural forces alter cultural practices, they generate hybrid identities and tensions between communal and individualistic orientations, especially among youth, rather than uniform cultural loss. By specifying search and synthesis procedures, the study strengthens methodological transparency and demonstrates how structural, ethical, and symbolic dimensions intersect. The interdisciplinary framework, supported by analytical tables and a conceptual diagram, offers a nuanced understanding of cultural continuity and adaptation. The study clarifies conceptual assumptions, identifies gaps in existing research, and outlines directions for future empirical inquiry in Zambia and comparable African contexts.
Adeyemi Biliqees Temitope, Makinde, Oladayo Ezekiel
The rapid increase in the use of digital technologies in daily activities has created both opportunities and threats. The paper reports an optimized Artificial Neural Network (ANN) model for implementing a three-tier authentication system using fingerprint biometrics (Level 1), facial recognition (Level 2) and Optical Character Recognition (OCR) (Level 3). The model is created using a multi-layer perceptron optimized using Adam and L2 regularization in order to have better accuracy and stability under environmental changes. On NIST SD4, LFW, and IAM datasets, an overall accuracy of 97.8% was reached with a false acceptance rate (FAR) of less than 1.0% was attained through experimental evaluation. The results show that the suggested model is better than unimodal techniques by about 16%, which proves its possible ability to protect e-learning and administrative systems at Nigerian universities.
Ankit Sharma, Subrahmanya Kumar Kukkupuni
Ethylene Glycol (EG) and Diethylene Glycol (DEG) are potential contaminants in liquid oral formulations, posing severe toxicological risks. Regulatory agencies mandate stringent controls on their permissible limits. This study outlines the analytical method verification of a gas chromatography (GC) procedure for the quantitative determination of EG and DEG in a polyherbal cough syrup. The method employs a DB-624 capillary column and flame ionization detection (FID), using ethanol as the diluent. System suitability, precision, resolution, and tailing factor criteria were established and verified. The method was confirmed to be accurate, precise, and suitable for routine use in quality control.
Adarsh Lalit, Anubha Pandey, C.B.S. Dangi, Nikita Tomar
Millets are nutrient-rich cereals possessing several bioactive phytochemicals such as phenolic acids, flavonoids, tannins, and dietary fibers that contribute to their therapeutic potential. The present study evaluated the antimicrobial activity of Indian Finger Millet (Eleusine coracana) and Pearl Millet (Pennisetum glaucum) extracts against selected pathogenic bacteria including Escherichia coli (ATCC 25922), Staphylococcus aureus (ATCC 6538), Bacillus subtilis (ATCC 6633), and Pseudomonas aeruginosa (ATCC 27853) using the Kirby Bauer disc diffusion method according to CLSI guidelines. Methanolic extracts of millet samples were tested at different concentrations (25, 50, and 100 mg/mL), and antibacterial activity was expressed as percentage relative inhibition compared with streptomycin (10 µg/disc). Finger millet exhibited comparatively higher antimicrobial activity than pearl millet across all tested microorganisms. Maximum inhibition was observed against B. subtilis and S. aureus at 100 mg/mL concentration. The results indicate dose-dependent antimicrobial effects attributed to millet polyphenols and phytoconstituents. These findings support the use of millets as potential functional foods and natural antimicrobial agents.
Evuensiri Onoghwarite Ohimor, Felix Omoruwou
The rising demand for sustainable and eco-friendly energy sources has intensified research into biodiesel production using efficient catalysts and diverse feedstocks. This study examines the application of zeolite-X, a nanostructured catalyst, for the production of biodiesel from a ternary blend of neem seed oil, palm kernel oil, and waste cooking oil. Zeolite-X was characterized through Scanning Electron Microscopy (SEM) and Fourier-Transform Infrared Spectroscopy (FTIR) to validate its structure and properties. The esterification process was conducted to lower the free fatty acid content to below 1% to prevent soap formation. Biodiesel was synthesized from this mixture via the transesterification process using methanol, catalyzed by zeolite-X. The process was optimized through response surface methodology (central composite design). The physicochemical parameters of the ternary oil blend are as follows: acid value, 17.43 mgKOH/g; free fatty acid, 8.715%; viscosity, 69.8 mPa.s; and saponification value of 135.329 mgKOH/g. The optimal parameters are at a methanol-to-oil ratio of 5.5:1, a reaction temperature of 60°C, a reaction duration of 105 minutes, and a catalyst loading of 7%. Gas Chromatography-Mass Spectrometry (GC-MS) was employed to analyse the fatty acid composition of the optimized biodiesel. The biodiesel's key physicochemical properties were evaluated and found to comply with or approximate ASTM standards: density of 0.8712 g/ml (ASTM standard: 0.88 g/ml), the kinematic viscosity of 4.27 mm²/s (ASTM range: 1.9-6.0 mm²/s), acid value of 0.947 mgKOH/g, free fatty acid content of 0.4735% (ASTM limit: <0.5%), flashpoint of 129°C (ASTM range: 100-170°C), and calorific value of 40.41 MJ/kg (ASTM standard: >35 MJ/kg). This study illustrates that Zeolite-X serves as an efficient nanocatalyst for biodiesel synthesis, presenting a viable pathway for sustainable energy derived from blended renewable oils with favourable fuel characteristics.
Dr. Bernadine Mbula, PhD
The adoption of artificial intelligence (AI) is rapidly spreading across various industries, including engineering, medicine, and manufacturing. However, there is still considerable debate regarding the legality and legitimacy of using AI-based technologies in educational settings. The use of AI is generally perceived as a positive thing as far as boosting and enhancing human capabilities in technical and applied disciplines. Nevertheless, there are also many who believe that integrating AI into academic or scholarly activities will compromise originality, authorship, and academic integrity. This article presents an in-depth theoretical analysis and literature review of over 100 years of scholarly publications in education, philosophy, and technology studies to provide a better understanding of what has occurred to cause this disparity. It shows how the resistance to AI integration into academia is driven by epistemological views of authorship, knowledge production, and learning that may soon become obsolete. This paper proposes that originality be recast as being conceptual rather than textual and establishes a foundational framework to ethically incorporate AI into education according to concepts, such as intellectual ownership, transparency, and epistemic accountability. The article provides recommendations on policy and pedagogical implications for educational institutions that are moving toward the integration of AI into learning environments.
Dr. Prabhuswamy M.
Artificial Intelligence (AI) has become one of the most influential technological developments in contemporary scientific research. In recent years, its integration into the physical sciences has significantly transformed conventional research methodologies by enabling advanced computational modelling, automated data analysis, and predictive simulations. This systematic review critically examines the role of AI in physical sciences using the PRISMA 2020 framework. Relevant studies published between 2023 and 2026 were collected from databases such as Scopus, Web of Science, Science Direct, Springer Link, and arXiv. Out of 512 initially identified records, 78 studies satisfied the inclusion criteria and were analysed in detail. The review categorizes AI approaches into machine learning, deep learning, and physics-informed neural networks (PINNs), examining their applications in physics, chemistry, materials science, astrophysics, climate science, and engineering systems. Findings indicate that AI enhances computational efficiency, improves predictive accuracy, and accelerates scientific discovery. Hybrid approaches that combine physical laws with AI models demonstrate particularly promising results in solving complex scientific problems. However, issues such as interpretability, computational expense, and limited high-quality datasets continue to challenge researchers. The study concludes that AI has the potential to redefine scientific inquiry in physical sciences by supporting intelligent experimentation, autonomous laboratories, and explainable scientific computing. Future developments should focus on ethical AI, interdisciplinary collaboration, and sustainable computational practices.
Amos-Bein Ebiere Berly, Apiri David Azibalua, Avwerosuo Peace Edile, Eneyo Igbanam Silas, Ogboeli Goodluck Prince, Precious Ollornwi, Wilson Isaac Chukwuka
Seasonal flooding in the Orashi Region of Rivers State, Nigeria, poses persistent challenges to transport networks, road infrastructure, and local livelihoods, yet the scale and specific impacts on affected stakeholders remain poorly documented. Recurrent overflow of the Orashi River, combined with inadequate drainage systems, frequently submerges roads, isolates communities, and disrupts daily economic activities, highlighting an urgent need for empirical assessment of these impacts. This study investigated the effects of seasonal flooding on transport operations, road conditions, and community well-being in the region. A structured survey was administered to a diverse sample of stakeholders, including fleet operators (50.0%), commuters/passengers (42.9%), local residents (28.6%), and officials/local leaders (10%). The majority of respondents were aged 20–39 years (especially 30–39 at 44.3%), representing economically active adults most vulnerable to flooding-related disruptions. Findings indicate that inadequate drainage and river overflow significantly disrupt fleet operations and accelerate road degradation through erosion, potholes, and washouts. Travel delays, economic losses, and safety hazards were commonly reported, with many respondents residing or operating within 2 km of flood-prone roads and 42.9% using affected routes daily. Road damage was predominantly critical (30.0%) or severe (41.4%), while moderate to severe erosion was reported by 64.3% of participants, reflecting widespread deterioration of transport corridors. Mean Likert scores further revealed high perceptions of flood frequency (overall 4.35) and associated impacts, with fleet operators reporting the highest severity for travel delays and the need for improved drainage. Correlation analyses demonstrated very strong positive relationships (r = 0.894–0.975, p ≤ 0.041) between flood frequency and all measured impacts, including mobility disruption, economic loss, safety risks, and demand for drainage improvements. These results confirm that recurrent flooding is a primary driver of cascading negative effects on transport networks, livelihoods, and community well-being. The study underscores the urgent need for targeted flood mitigation strategies, resilient road design, and systematic drainage maintenance to enhance transport reliability, safeguard livelihoods, and improve resilience in flood-prone riverine areas of the Niger Delta.
Nirmal Kumar Karmaker
Fecal sludge containment management remains a major urban sanitation challenge in Bangladesh, where most municipalities rely on onsite sanitation systems such as septic tanks and pit latrines. This study evaluates the existing fecal sludge (FS) containment status in Savar Paurashava and identifies practical improvement strategies for safe sanitation management. A mixed-methods research design integrating quantitative and qualitative approaches was adopted. Quantitative data were derived from a household survey of 379 holdings conducted by Water and Sanitation for the Urban Poor (WSUP) using stratified random sampling at a 95% confidence level. Qualitative information was obtained through field observations, Key Informant Interviews (KII), stakeholder consultations, and institutional review. The findings reveal that 20.31% of surveyed households had no containment systems and discharged wastewater directly into drains, while only 30.87% used septic tanks. Among the septic tanks, merely 8.97% were connected to soak wells, whereas most discharged effluent directly into drains or nearby water bodies. The study further identified that the majority of septic tanks were undersized, lacked partition walls, and did not comply with Bangladesh National Building Code (BNBC) standards. Qualitative findings revealed weak institutional enforcement, inadequate technical supervision, low public awareness, and the influential role of informal masons in constructing non-standard containment systems. The Fecal Waste Flow Diagram (FWFD) (commonly it termed as FSD) shows that the sanitation services in Savar Paurashava are not safely managed. The study recommends strengthening municipal regulatory enforcement, implementing the Paurashava Sanitation Management By-Laws 2021, establishing a Fecal Sludge Containment Management Committee (FSCMC), retrofitting defective systems, and improving technical training and public awareness. These measures are essential for achieving Sustainable Development Goal (SDG) target 6.2 and promoting environmentally sustainable urban sanitation in Bangladesh.
Christopher Onosemuode, Evangelyn Ebi Ayobi, Idowu Adigun Amusa, Kelvin Odeyovwi Ayobi, Peremi Richmond Ike, Tarela Juliet Ike
Occupational fatigue in the railway industry is a multidimensional problem deeply embedded in the psychosocial architecture of the working environment. Among the psychosocial risk factors most consistently linked to fatigue, job demand and work stress occupy a central position. In the Nigerian context, the rapid expansion of rail infrastructure typified by the inauguration of the Warri-Itakpe Train Service (WITS) in 2020 has introduced a burgeoning workforce into an operationally demanding environment where the management of psychosocial risks remains nascent. Railway workers face heavy and irregular workloads, shift schedules, vigilance-intensive tasks, and limited job control, all of which collectively elevate the risk of occupational fatigue and its attendant consequences for productivity and rail safety. This study investigated the relationship between job demand, work stress, and occupational fatigue among railway workers in the Warri-Itakpe Train Service of the Nigerian Railway Corporation (NRC), while contextualising these associations within the broader spectrum of psychosocial health risk factors. A quantitative, cross-sectional survey design was employed. Using Slovin's formula at a 5% margin of error, a sample of 305 railway workers was recruited from 12 stations within the Warri-Itakpe Train Service using multi-stage sampling. Data were collected with the Smith Wellbeing Survey (SWELL), a validated 27-item instrument grounded in the Wellbeing Process Questionnaire (WPQ). The Demands, Resources, and Individual Effects (DRIVE) model guided conceptual framing. Statistical analyses included weighted averages, relative risk (RR), absolute risk (AR), Pearson's correlation, Chi-square tests, and logistic regression, all executed in SPSS Version 25.0. Job demand and work stress were the two strongest psychosocial predictors of occupational fatigue across the entire study population. Job demand recorded the highest relative risk of all 15 health risk factors assessed (RR = 7.71; AR = 89%; r = 0.81, p < 0.01; R² = 0.66), while work stress followed closely (RR = 5.22; AR = 84%; r = 0.73, p < 0.01; R² = 0.53). Chi-square analysis confirmed statistically significant associations for job demand (χ² = 29.754, p < 0.001) and work stress (χ² = 12.985, p < 0.001) with occupational fatigue. Stratified analysis by job type revealed that engineers bore the highest job demand risk (RR = 24.00; AR = 96%) while train drivers recorded the most severe work stress risk (RR = 12.00; AR = 92%). Job demand and work stress are predominant psychosocial determinants of occupational fatigue among Nigerian railway workers. The findings underscore an urgent need for the Nigerian Railway Corporation to restructure workloads, enforce fatigue-risk management policies, expand staffing, and institutionalise psychosocial support mechanisms. Failure to address these factors threatens both worker well-being and the operational safety of Nigeria's growing rail network.
Tariro Maraire
Forensic psychology interns frequently encounter clinicians as clients. These being health-care professionals requiring assessment during their therapy process. The clinician-clients often exhibit high self-awareness and clinical insight, thereby, creating a unique psychological dilemma that can be unsettling for interns and in turn compromise professional objectivity. This qualitative study investigated specific professional dilemmas and ethical challenges faced by four forensic psychology interns in conducting violence risk assessments, family reintegration suitability, and competency evaluations among clinician-clients within a drug rehabilitation centre in Harare, Zimbabwe. Data were collected using semi-structured interviews and a focus group discussion and was analysed using Thematic Analysis. Findings identified four primary challenges: heightened confidentiality threats, compassion fatigue, complex power imbalances and problems in forming therapeutic alliances. The expert-vs-expert dynamic was proved to present a blurred professional boundary, thereby complicating the forensic psychology interns' evaluative role. The research exhibits a critical gap in forensic internship, where dual-status of the client as a clinician-professional creates unique stressors. Future research should focus on developing specialised support mechanisms, and supervision models for forensic psychology interns. Addressing these unsaid challenges is crucial for enhancing the performance and competency of emerging forensic psychologists.
Al R. Dela Mide, Jr., Joan P. Bacarisas
This study assessed the factors associated with satisfaction in referral services at a Department of Health–retained hospital in Surigao City, Philippines. Using a quantitative descriptive-predictive design, data were collected from referred clients through consecutive sampling with the use of a structured questionnaire measuring demographic characteristics and key dimensions of satisfaction, including admission, treatment, communication, time, customer service, and discharge processes. Findings revealed that clients were generally satisfied, with higher ratings in procedural aspects such as admission and discharge, and comparatively lower ratings in communication and customer service. Regression analysis identified treatment, communication, and customer service as significant predictors of overall satisfaction, while most demographic characteristics showed no significant predictive relationship. The study concludes that clinical competence must be complemented by effective interpersonal engagement to achieve comprehensive client satisfaction. The results support the Confirmation-Disconfirmation Theory, emphasizing that meeting patients’ relational expectations is central to delivering excellence in referral services.
Joan P. Bacarisas, Marjun N. Reveche
This study utilized a quantitative descriptive–correlational research design conducted in a Level 2 hospital in Surigao City during the first quarter of 2026. Complete enumeration was employed, involving 167 hemodialysis patients. Data were gathered using two adopted and validated instruments measuring healthcare resource availability and patient satisfaction with nursing care quality. Descriptive statistics, including mean and standard deviation, and inferential statistics using Pearson r were applied to analyze the data. Findings revealed that healthcare resources in the hemodialysis unit were generally highly available, while patient satisfaction with nursing care quality was also rated high across dimensions such as communication, responsiveness, competence, respect, and overall care experience. Moreover, a significant positive relationship was identified between healthcare resource availability and patient satisfaction with nursing care quality. The study concludes that adequate healthcare resources support improved nursing care delivery and enhance patient satisfaction among hemodialysis patients. Based on the findings, a Nursing Care Quality Enhancement Plan was proposed to strengthen service delivery and promote continuous quality improvement.
Dr. Aaiman Siddiqui
The rapid adoption of flexible work arrangements has transformed organizational structures, particularly in startups. While remote work offers autonomy and cost advantages, it also presents challenges related to employee engagement, accountability, and well-being. This case study examines an Indian ed-tech startup, EduNext Solutions, which experienced declining productivity, rising employee burnout, and the emergence of quiet quitting following a transition to a fully remote work model. Using an exploratory case study approach supported by employee survey data and managerial insights, the study highlights the gaps in strategic human resource management. The findings are analyzed through the lens of the Job Demands–Resources (JD-R) model and Maslach’s Burnout Theory. The case provides actionable HR strategies to balance flexibility with accountability while enhancing employee engagement and organizational effectiveness.
John Paul P. Dela Cruz, Julius Q. Ballares, Mark Leslie D. Melendez, Niela Belle B. Importante, Rogelio Angelo V. Duque
BankeroBay is a web-based platform developed to support the Bankero and Fishermen Association in promoting and selling seafood products through an accessible and efficient online marketplace. The study employed descriptive and developmental research approaches to thoroughly examine existing marketing and distribution practices and to guide the systematic design and development of the platform. Data were collected through an in-depth interview with the association chairman to identify operational processes, challenges, and the essential system requirements needed to address existing limitations in traditional selling methods. Based on the findings, the platform was carefully designed to enhance both user experience and overall operational efficiency by incorporating core features such as a landing page, secure account access, role-based user management, comprehensive product listings, and an order tracking system with assigned riders and third-party couriers to ensure timely delivery. In addition, the system supports multiple payment options to improve transaction accessibility and customer convenience. Additional functions including product requests, customer reviews, automated email notifications, chat support, Progressive Web App integration, and QR code verification for order confirmation were also implemented to strengthen usability, transparency, and reliability. Administrative tools were further integrated to allow efficient management of products, categories, orders, returns, site settings, and customer communication. The platform follows a structured three tier architecture and was developed using the Agile methodology to enable continuous improvement based on stakeholder feedback and evolving user needs. Evaluation using ISO 25010 software quality standards yielded high ratings in functionality, usability, reliability, performance efficiency, security, maintainability, and portability. The results indicate that BankeroBay significantly improves product visibility, streamlines transaction processes, and strengthens direct connections between fishermen and customers, thereby providing a practical and sustainable digital solution that enhances business operations and supports long-term livelihood development for small scale fishermen.
Oladoyin Idris Atolagbe
Understanding structural changes in regional energy consumption is critical for designing effective energy policies and anticipating future demand patterns. This study develops a Bayesian spatio-temporal framework to analyze structural shifts in energy consumption across Midwestern states of the United States. Annual state-level energy consumption data from 1960 to 2023 were analyzed to identify temporal dynamics and spatial dependencies among neighboring states, with monthly data from 2000 to 2024 used for high-resolution structural break detection. A Bayesian hierarchical model was employed to jointly capture spatial effects, temporal evolution, and structural change points in energy consumption patterns. Spatial dependence between states was modeled using a conditional autoregressive (CAR) prior based on a first-order queen contiguity spatial adjacency matrix. Temporal dynamics were represented through a stochastic random-walk process, while structural changes were identified using a Bayesian Online Change Point Detection (BOCPD) mechanism embedded within the hierarchical framework. Model performance and validation were evaluated using posterior predictive checks (PPC), the Widely Applicable Information Criterion (WAIC), and Leave-One-Out Cross-Validation (LOO-CV), with the Pettitt test used as a classical benchmark for structural break detection. The results reveal several statistically significant change points across states, particularly around the 2008-2009 financial crisis, the 2012 Midwest drought, and during the expansion of renewable energy policies. The proposed Bayesian spatio-temporal framework provides a flexible approach for identifying regional structural shifts in energy consumption while accounting for spatial interdependencies among states. These findings offer valuable insights for energy planners and policymakers seeking to understand long-term changes in regional energy demand and the potential impacts of economic shocks and policy transitions.
Professor Nihar Patnaik
The global trade and import-export scenario brings with it considerable ease of doing business but also adds to the complexity of designing optimum supply chain networks. Firms must select a network that is both having a good framework and at the same time offer flexibility in certain areas and aspects as we are currently living in dynamic times where change is the only constant. The challenge is to find that optimum balance between minimizing cost and maximizing revenue/profit while ensuring high quality is sustained. The methodology adopted for this research is to investigate the various models adopted by different firms and analyze their cost benefits attained. The key findings of this research are that it will vary depending on the industry that the firm is operating in, the maturity level of the countries it deals with, the stage at which the firm is in terms of the company lifecycle and also the size of the firm (large, medium or small). The broader implications of my work are to help improve the ecosystem of or pertaining to supply chain network design globally.
Jaya Sri.R, Mahasrii.N, S. Mahalakshmi
In the realm of digital health, the personalization of AI-driven nutritional guidance has emerged as a critical factor. This study aims to explore the user’s perception regarding personalization and practicality in relation to AI-generated nutrition plans and diet plans created by dietitians. Furthermore, it highlights the significance of cultural sensitivity, emotional intelligence, and cost as essential determinants of user perceptions. It also emphasizes key factors like cultural sensitivity, emotional intelligence, and cost, which are crucial in determining user perceptions. Data were collected from 126 participants across various age groups ranging from adolescents to adults through a structured questionnaire assessing comfort with AI, personalization quality, cultural integration, and effectiveness relative to Dieticians. The economic aspect is also considered when assessing the feasibility of AI-generated plans. The findings suggest that while AI is perceived as advantageous and potentially more economical, reservations persist regarding its capacity to fully comprehend cultural nuances and offer emotionally attuned guidance. Consequently, the results indicate that enhancing personalization features within AI systems and fostering AI-human collaboration (hybrid models) would likely yield superior outcomes in the realm of nutritional care.
Ms. Elizabeth Njeri Ngigi
Digital technology has become embedded in nearly every aspect of modern childhood, transforming how children learn, communicate, play, and understand the world. While technological access offers educational and social benefits, increasing evidence suggests that early and unregulated exposure to digital environments may also contribute to cognitive overload, reduced attention span, dependency patterns, shallow information processing, and diminished critical thinking. Existing approaches largely frame digital safety as a matter of parental supervision or individual responsibility. However, this paper argues that such framing is insufficient given the ubiquity, persuasive design, and developmental impact of technology.
Imroj Khan, Rajeev Kumar Keshari
Coronary artery disease (CAD) remains one of the leading causes of mortality and morbidity worldwide. The disease primarily develops due to atherosclerosis, a chronic inflammatory condition characterized by endothelial dysfunction, lipid accumulation, oxidative stress, thrombosis, and vascular inflammation. Biochemical markers play a crucial role in the early diagnosis, risk stratification, prognosis, and therapeutic monitoring of CAD. This review comprehensively evaluates traditional and emerging biochemical risk factors associated with CAD, including lipid profile abnormalities, inflammatory markers, cardiac biomarkers, glycemic indicators, renal biomarkers, coagulation factors, electrolytes, and novel genetic markers. Traditional lipid parameters such as low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, and total cholesterol remain central to cardiovascular risk assessment. Inflammatory markers including high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) provide insight into vascular inflammation and plaque instability. Cardiac biomarkers such as troponins, CK-MB, BNP, and NT-proBNP are essential for myocardial injury detection and prognosis. Emerging biomarkers including lipoprotein(a), homocysteine, genomic markers, and omics-based approaches are increasingly contributing to personalized cardiovascular medicine. The review also discusses current risk prediction models, limitations of biomarker interpretation, controversies in clinical application, and future perspectives involving artificial intelligence and precision medicine. Current evidence supports a multi-marker approach integrating biochemical, clinical, imaging, and genetic data for comprehensive CAD management.
Dr. K. Usha Savithri, Ms. C. Leenas Magna
The inclination towards reducing the work of Perumal Murugan, Poonachi: Or the Story of a Black Goat to another fable with an anthropomorphic hero sounds too simplistic. However, the text is a rather complex and highly interesting reflection on the dynamic between the modern state and its population, which frequently goes unappreciated by literary critics, who reduce it to the imagination technique employed by the author to express rural life. The present study attempts to explore how literary criticism approaches Poonachi as a romantic story about life in the country as opposed to an intricate allegory. Using the approach of detailed qualitative analysis, based on concepts such as biopower (Michel Foucault) and bare life (Giorgio Agamben), the study highlights similarities in the methods of managing livestock and human beings. More specifically, it is suggested that Poonachi serves as an example of the use of a non-human perspective to transcend the framework of political realism and to create a representation of the Regime as an omnipresent authority that transforms each person's biological nature into an easily searchable datum. Additionally, in terms of Poonachi's color and the problems she faces, it may be viewed as an allegory of Dalit experience in today's rural India. Crucially, the protagonist's struggle involves more than biology; it becomes a political resistance against total lack of privacy.
Anuj Kumar, Shalini Singh, Sufiyan Ahmad
Modern digital era passing out very tough time due to cybercriminal activity, fraud etc. In this situation financial, reputation, and time losses is common concern. According to time of India news in case of the Manav Bharti University of Himachal Pradesh, where 36,000 fake degrees were sold, & the 2026 Prayagraj Pharmacy Scam incidents such as these have suffers free trust. So, this issue demanded to protect sensitive information and their secure management. Currently block chain is in prevalence for security due to its characteristic that have capability to reduce cybercriminal activity and effective management. In reality, our traditional education system is currently is facing of a big problem like increasing difficulty to verify the authenticity of academic degrees. Main reason behind problem is the education database systems which is in centralize based and all data is stored in the single location. So, this make possibility to hacking, and these systems also incline to be quite slow. So, to fight this situation in this paper present a block chain-based solution named "SmartCertify". It controls by smart contracts to eliminate any scope for fake activity. Basically, in this includes a "Rules-Based Governance" model, where regulatory bodies such as the UGC pre-configure seat limits directly onto the blockchain. If university attempts to fraud even single certificate beyond its allocated limit, the block chain will immediately block the transaction. For system security used cryptographic chaining tool, where every new certificate will cryptographically link to previous one. If anyone try to attempt to tamper with past records using tools like photoshop, complete chain will be broken, and fraud be instantly detected. This entire process operates on local "Ganache" blockchain, confirms complete transparency and security.
Dr. Jerina Begum, Sristi Sharma
The present study was conducted to examine the relationship between body-image and self-esteem among adolescents and to understand whether gender differences exist in both the variables. The sample consisted of 100 participants, studying in grade IX, studying in private schools under Board of Secondary Education of Assam (SEBA) of Guwahati City, including 50 females and 50 males. Data were randomly collected from four schools using Body Shape Questionnaire (BSQ-34) and Rosenberg Self-Esteem Scale (RSES). The findings showed that female participants had slightly higher level in both body-image and self-esteem compared to males, however the differences were not statistically significant (t = 0.54, p>0.05). Pearson Correlation revealed a significant positive relationship between body-image and self-esteem (r= 0.288, p<0.01). The result indicates that individuals with higher body dissatisfaction reported in higher self-esteem. Overall, the study suggests that while gender may not play a major role, body-image and self-esteem is an important factor influencing body-image among adolescents. This finding will contribute to psychological support to the adolescents and can be address during adolescent’s counselling.
Mr. Aman Shukla, Ms. Disha Thakur
Organizations operating in today's digital business world must realize that brand-building and measuring marketing performance are two functions that are intuitively dependent upon each other. When companies invest in creating brands but do not implement brand-measuring techniques, they lack the level of accountability that these types of brands provide. Likewise, organizations focusing only on metrics without maintaining a cohesive brand to measure against cannot generate enough consistent signals to allow evaluation to occur. Adobe, Inc. is a prime example of an organization that uses an integrated suite of digital tools for creating brand content and measuring the performance of that content i.e., when you look at how Adobe's ecosystem of creative, documents, and analytics tools (Adobe Express, Photoshop, Illustrator, Acrobat, Adobe Analytics, and Adobe Firefly) provide a cohesive technology platform to create product brands and measure the performance of product brands from a unified standpoint. This paper includes a review of how Adobe's digital tools can enable businesses to create effective product brands and measure the marketing performance of those products. The original research project involved collecting primary data from 120 participants across various institutional types in Madhya Pradesh, India; the research design is descriptive quantitative in nature, with the questionnaire consisting of a structured Likert-type scale. Data indicate that respondents generally agree that Adobe tools contribute to visual consistency for a brand (M=4.07), professional campaigns (M=4.08) and build institutional reliability (M=4.15). Respondents also positively view analytics-supported decision making (M=3.90) and clarity of return on investment for use of analytic tools (M=3.76); however, these outcomes have been reported to be further behind in development than the previous measures. This research maps the Adobe tool ecosystem onto the dual needs of a brand (branding and measurement) and identifies the implementation hurdles organizations face, and presents a multi-phase implementation framework for maximizing brand and measurement benefits. Findings provide theoretical contributions to the literature on digital marketing capabilities, brand management technology, and the integration of creative and analytical functions within a company's digital business ecosystem.
Devaraju J T, Shwetha D, Swetha
Multimedia streaming over Ad Hoc networks has recently gained significant attention due to the highly scalable, self-starting, self-managing, self-healing and infrastructure-free nature of these networks. In Ad Hoc networks, data packets are transmitted from the source to the destination through multiple intermediate nodes using distributed multi-hop communication. At each intermediate node, packets experience varying buffering delays before being forwarded to the next hop. Furthermore, intermediate nodes may require a random number of retransmission attempts before successfully forwarding packets. Consequently, some packets may arrive at the destination earlier than preceding packets, some may be dropped, and others may arrive later than subsequent packets, leading to packet reordering at the destination. This issue becomes more critical in multimedia streaming applications based on the User Datagram Protocol (UDP), where stale packets are discarded to maintain real-time delivery. As a result, the effective throughput between the transport layer and the application layer decreases, thereby degrading the quality of multimedia streaming. To address these challenges, this paper proposes two novel buffering algorithms: the Static Reordering Buffer (SRB) and the Improved Reordering Buffer (IRB) algorithms. The performance of the proposed algorithms is evaluated using the QualNet 6.1 network simulator with the objective of improving multimedia streaming quality in Ad Hoc networks.
Dr. Chinmoy Sarkar
Agricultural marketing works with two marketing channel input marketing and product marketing. However, product marketing itself has many channels but this study deals with product market only where it creates link between cultivator and final consumer who are purchasing crops in different markets. However government has a control over input marketing in most of the items which are consumed by the farmers in subsidies rate but the most harmful and destructive nature of marketing faced by farmers is product marketing. In peak season of harvesting and especially for non-perishable crops farmers are facing huge loss and on the other hand the middlemen are getting enormous profit for same crops. This study tried to focus on profit gap and the determinants of this profit gap between farmer and middlemen.
Dr. Roshni Padate, Gauri Waghulade, Mohika Rane, Mokshada Rane, Vinisha Rajpurkar
In today’s fast-paced job market, students and novice professionals face difficulty in discovering the best learn-ing pathways, realizing sufficient role-associated readiness, and building a professional presence. Conventional learning materials have too often been in a disconnected, generic, and non-aligned form with the latest industry specifications. In light of these severe challenges, we suggest a cutting-edge AI-based career readiness platform. This product presents an end-to-end and customized solution that covers up-skilling training, role readiness develop-ment, and professional presence building. The main goal of this project is to close the existing skill gap between students and the expectations of the modern job market by providing an integrated and intelligent platform that encompasses both learning and career readiness. This end result is achieved through a set of seven specialist services: PathPro functions as a Roadmap Generator, creating individualized and goal-setting learning paths per user. CourseCraft uses artificial intelligence to create unique learning materials and, hence, ensure both applicability and quality. For supplementary learning assistance, NoteScribe functions as a YouTube Video to Notes Converter and produces thorough study notes from videos. In keeping the users well-informed, TrendLens also sources important industry knowledge and market trends. The system then turns its attention to job market outreach via Craftsume, a professional Resume Generator, and CoverForge, a free Cover Letter Generator. RoleReady finally concludes the readiness phase with mock tests that are exactly specialized for particular sought-after job functions and hence builds a complete solution to career development.
David I. Forsyth
This paper extends a low-cost wavelength-division multiplexing (WDM) source from 12 to 20 dense wavelength-division multiplexed (DWDM) channels using a cascaded semiconductor optical amplifier (SOA) architecture — without requiring any coherent lasers. A second SOA stage, seeded by the 12-channel output of the first stage (derived from three non-uniformly spaced, spectrum-sliced ASE inputs from a single high-power LED), generates eight additional four-wave mixing (FWM) components. The non-uniform input spacing (0.3 THz and 0.4 THz) deliberately inhibits a fully populated frequency comb, producing a finite, structured, and manufacturable channel set. Performance reveals a practical trade-off: the three original inputs exceed 195 km, while the eight cascaded channels are limited to 25–100 km — fully viable for urban and distribution links. Compared with conventional laser-array DWDM systems, the proposed design offers significantly lower cost and complexity. Future experimental validation under real-world conditions is recommended, alongside simplified diagrams and application scenarios to improve accessibility for students and industry practitioners.
Reuben Peters Omale
Chaos theory, a branch of mathematics focusing on the behavior of dynamical systems that are highly sensitive to initial conditions, has transcended its scientific origins to influence various disciplines, including architecture. This paper explores the intersection of chaos theory and architecture, examining how the principles of chaos theory have inspired the quest for new architectural forms. This paper explores the impact of chaos theory—specifically concepts such as fractals, non-linearity, emergence, and strange attractors—on the quest for new architectural forms. It argues that chaos theory is not merely a source of aesthetic inspiration but a generative and analytical tool that facilitates a more responsive, adaptive, and ecologically integrated architecture. By analyzing three relevant case studies, it argues that chaos theory provides not merely a novel aesthetic but a fundamental new methodology for architectural designs. Through the analysis of specific case studies—including the Heydar Aliyev Center, the Beijing National Stadium China, and the Guggenheim Museum in Bilbao-Spain, this paper argues that chaos theory provides a conceptual framework for understanding and designing complex, non-linear structures that reflect the dynamic nature of contemporary society. The paper concludes that the incorporation of chaos theory represents a move towards an architecture that embraces the complexity of life itself, and this paradigm shift enables an architecture that embodies the dynamic, complex, and interconnected nature of contemporary life.
Almahden C. Lumidseg, Anika P.B.J. Sendico, Isabella K.M. Galgo, Roden C. Yumol
Recent statistics from the World Health Organization indicate that noncommunicable diseases such as cancer and diabetes mellitus remain major global health challenges, with cancer responsible for an estimated 9.7 million deaths worldwide in 2022 and diabetes directly causing about 1.6 million deaths in 2021, while also contributing to millions more through cardiovascular complications [18,19]. This study aims to determine the phytochemical, anti-angiogenic, and anti-hyperglycemic potential of Chayote (Sechium edule) peel extract. Ethanolic peel extract was subjected to phytochemical screening and tested for cytotoxicity, angiosuppressive activity, and blood glucose reduction. Secondary metabolites screening indicated the presence of alkaloids, flavonoids, saponins, phenols, and tannins, which possess known anti-oxidative and anti-inflammatory actions. Test for angiosuppressive activity using the Chorioallantoic Membrane (CAM) assay revealed a significant anti-angiogenic property at 25%, 50%, and 75% concentrations of the S. edule peel extract with all inhibiting the growth of blood vessels. These results were comparable to the positive control, methotrexate. The Brine Shrimp Lethality Assay revealed an LC50 value of 505.14 μg/mL. Since this value is greater than 100 μg/mL which indicates that the extract maybe non-toxic to human cells. Analysis of glycemic activity showed that the extract significantly reduced blood glucose levels in mice, particularly at 200 µg/mL, which performed at par with the positive control. The results proved that S. edule peel extract exhibits promising phytonutraceutical, anti-angiogenic, and anti-diabetic properties, representing a potential novel approach for cancer prevention and diabetes management. Isolation of potent bioactive compounds responsible for the aforementioned claims should be done as well as in vivo testing should be conducted to further validate the results of the study.
Christine B. Marcojos, Riza B. Salipong, Phd
One hundred two (102) grade level teachers of Tubigon West district experienced stress due to classroom behavioral issues that decrease their self-efficacy. Thus, this study is determined to explore how stress level mediate the relationship between classroom behaviors and teachers’ sense of self-efficacy in the school year 2025-2026. With that, the researcher used a correlational research design with a structured survey questionnaire to identify its levels and relationship. In addition, weighted mean, standard deviation, Pearson Product-Moment Correlation Coefficient, and mediation analysis were also used to analyze the data. In terms of classroom behavior, the findings revealed a “very high level of behavior” with an overall composite mean of 3.35 (SD = 0.58), this suggests that learners show positive engagement, participation, and attitudes toward their learning environment. In terms of teachers’ self-efficacy, the results indicate an overall composite mean of 3.62 (SD = 0.51) which reflects a “very high level”. This means that teachers still exert a very satisfactory performance despite the challenges they experienced. In terms of stress level, an overall composite mean of 2.33 (SD = 0.95) reflects a moderate level of stress among teachers which means that, teachers may experience stress at times, still they are able to manage them properly despite the demands of their profession. Overall, the results revealed that teachers’ stress levels significantly mediate the relationship between classroom behavior and teacher self-efficacy. Thus, it is recommended that school administrators should implement stress management and mentoring programs, provide continuous professional development, ensure proper workload distribution and conduct regular monitoring and evaluation.
Magdana Kvabziridze, Nana Bliadze
The preservation of forest ecosystems is a critical component of global environmental sustainability, particularly under conditions of accelerating climate change. This study assesses the sensitivity of forest ecosystems in the Imereti region of Georgia to climatic variability and anthropogenic pressures. Using indicator-based analysis, including forest fire frequency and forest area dynamics, the research identifies key threats such as rising temperatures, increased drought frequency, pest outbreaks, and forest degradation. The findings indicate a high level of ecosystem vulnerability and highlight the urgent need for sustainable forest management strategies.
Jeanica A. Licong
Student leader behavioral patterns are increasingly inconsistent. This study aimed to examine the influence of cognitive factors and environmental factors among student leaders was verified. Diagnostic research design, total enumeration sampling, survey technique, and multiple linear regression analysis are the methods used in this study. The data collected from 200 student leaders showed that both determinants significantly influenced the criterion, partly support the Social Cognitive Theory. Future research may include 43% of unexplained variance in student leader behavioral patterns, while one-on-one coaching sessions guided by faculty mentors to improve behavioral patterns is suggested.
Adeniran A.P, Dr. Ntarangwe M, Mukarugwiza X
This study investigated the relationship between cognitive-emotional regulation and psycho-spiritual well-being among Catholic consecrated men and women in Ibadan Archdiocese, Oyo State, Nigeria. It sought to determine the level of cognitive-emotional regulation employed, assess psycho-spiritual well-being, examine the relationship between the two constructs, and identify strategies that can enhance well-being. The research was guided by Gross’ Process Model of Emotion Regulation (1998) and Viktor Frankl’s Logotherapy (1946). An embedded mixed-methods research design was used with a population of 624 consecrated men and women and a sample of 244 participants, comprising 95 priests, 56 sisters, and 93 brothers, selected using Yamane’s formula. Quantitative data were collected using the Cognitive Emotion Regulation Questionnaire (CERQ) by Garnefski and Kraaij (2001) and the Psycho-Spiritual Well-being Scale (P-SWBS) by Egunjobi et al. (2023). Qualitative data from seven consecrated men and women, were obtained through interviews and analysed thematically using NVivo while quantitative data were analysed with SPSS version 25. Findings revealed that participants predominantly used adaptive strategies, with positive reappraisal (M = 3.72) and refocus on planning (M = 3.69) scoring highest, while maladaptive strategies such as other-blame (M = 1.88) and catastrophizing (M = 1.94) were often used. Psycho-spiritual well-being was generally high, with connectedness scoring highest (M = 4.20) and self-transcendence lowest (M = 4.13). A moderate positive relationship was found between cognitive-emotional regulation and psycho-spiritual well-being r (139) = .353, p < .001. Qualitative findings identified eight strategies for enhancing psycho-spiritual well-being. The study concludes that integrating psychological and spiritual care is essential for holistic well-being of consecrated men and women.
Alex Kapalasa, Hope Herbert Nkhoma, Mtafu Manda, Ulemu Msiska, William Mandhlopa
Bidens pilosa L. (Blackjack) is an indigenous plant widely distributed across Sub-Saharan Africa, traditionally valued for its nutritional and medicinal properties yet often dismissed as a weed (FAO, 2012; Pillai et al., 2020). Despite growing scientific evidence of its pharmacological potential (Pillai et al., 2020; Zhang et al., 2019), little is known about how local communities perceive and utilize this plant within their traditional knowledge systems. This study investigated household perceptions and traditional knowledge of Bidens pilosa in rural and peri-urban Malawi, employing a mixed-methods design that combined household surveys, in-depth interviews, and focus group discussions. Quantitative data were analyzed using descriptive statistics, chi-square tests, and Principal Component Analysis (PCA), while qualitative data underwent thematic analysis. Findings revealed high awareness and consistently positive perceptions of Bidens pilosa, particularly regarding its medicinal and nutritional relevance. PCA identified two dominant components—medicinal–health and economic–nutraceutical—explaining 72.2% of the variance. Perceptions varied significantly across gender, education, occupation, and cooperative membership, with women and cooperative members expressing stronger positive views. Qualitative narratives underscored the plant’s cultural integration in food preparation, traditional healing, and income generation. The study concludes that Bidens pilosa is deeply embedded in community knowledge and valued for its multifunctional benefits. These insights highlight its potential role in nutrition programs, primary healthcare, conservation initiatives, and smallholder commercialization strategies across Sub-Saharan Africa.
Dr. Aparnaa Upadhyaya DDS MPA BDS, Mary Grace Hilario
Post‑extraction socket management is a routine yet clinically significant aspect of dental practice. While many extraction sites are allowed to heal by secondary intention, absorbable gelatin sponges such as Gelfoam or Surgifoam combined with chromic gut sutures are frequently used to enhance clot stability and soft‑tissue approximation. This PRISMA‑aligned systematic review synthesizes existing literature comparing healing outcomes of extraction sockets managed with chromic gut sutures and gelatin sponge packing versus natural, unsutured healing. Searches of PubMed/MEDLINE, Scopus, and the Cochrane Library identified randomized controlled trials, split‑mouth studies, and systematic reviews evaluating time for hemostasis, postoperative pain, early soft‑tissue healing, and complication rates. Across studies, adjunctive socket management demonstrated improved early hemostasis, reduced postoperative pain, and enhanced initial mucosal healing, while long‑term outcomes were generally comparable in healthy patients. Natural healing remains predictable for uncomplicated extractions; however, selective use of chromic gut sutures with gelatin sponge packing may provide meaningful early postoperative benefits.
Swapan Samanta
Every neural spike began as a subthreshold tremor. Every cultural norm began as a whispered private opinion. Every addiction began as relief. This paper proposes that these transformations — from hidden potential to observable reality — share a single mathematical grammar: complex dynamical systems, in which the imaginary component encodes latent possibility and iteration carries it into the real. We introduce two novel summary statistics — the Complex Coherence Index (CCI) and the Imaginary Reserve Ratio (IRR) — and apply them across five domains: neural habit formation, evolutionary epigenetics, social contagion, psychological creativity, and digital amplification. This revised edition addresses peer-reviewer concerns by sharpening falsification criteria, providing worked computational examples, acknowledging the limits of analogy, and focusing the strongest empirical predictions on the two most tractable domains: behavioural neuroscience and network science.
Brian Bantugan
This study investigated the dualistic role of artificial intelligence (AI) in shaping critical thinking within educational contexts, specifically focusing on the Communication Program at St. Paul University Manila. Employing a qualitative, interpretive research design, the study utilizes comparative discourse analysis of contradicting YouTube transcripts alongside a synthetic analysis of scholarly article by Brian Bantugan that proposed a policy framework on AI governance in St. Paul University Manila. The analytical framework integrates Cognitive Hierarchy Theory, Sociocultural Theory, and Cognitive Offloading Theory to move beyond binary perspectives of advocacy or resistance. Findings reveal two primary paradigms: AI as "cognitive augmentation," where the technology reconfigures intellect toward high-level task stewardship and information verification, and AI as "cognitive substitution," where overreliance leads to "passive consumption" and cognitive atrophy. Results indicate that while AI can enhance higher-order analysis, it risks "short-circuiting" the foundational mental effort required for deep learning. Consequently, the study proposes a progressive "Learn First, Augment Later" pedagogical model. In Basic Education, AI should serve as a limited "cognitive scaffold" to protect foundational skill formation. In Higher Education, AI transitions into a "cognitive partner" for advanced synthesis, provided learners maintain active agency. These insights culminate in a modified AI governance framework for St. Paul University Manila, emphasizing stage-based integration, process-based assessment, and the transition from output-oriented to cognition-centered evaluation. Ultimately, the study concludes that AI’s impact is determined not by the technology itself, but by the developmental timing of its integration, ensuring students remain active seekers of knowledge rather than passive recipients of machine-generated content.
Joan P. Bacarisas, Maribeth P. Belocura
This study examines how Continuing Professional Development (CPD) activities influence professional behavior change and nursing autonomy among 205 staff nurses in a Level II government hospital in Surigao City, Philippines. Utilizing a descriptive-correlational design, the research assessed levels of engagement in lifelong learning and its relationship to clinical independence and professional conduct. Findings revealed that nurses demonstrate a very high level of engagement in CPD, largely driven by a strong internal motivation to improve patient care rather than mere regulatory compliance. Correspondingly, the respondents exhibited a very high extent of professional behavior change particularly in accountability and ethical practice and reported high levels of clinical autonomy. Statistical analysis identified a significant positive relationship between CPD participation and professional autonomy, suggesting that as nurses update their clinical knowledge, they gain the confidence necessary to make independent, evidence-based decisions. While overall professionalism was high, communication was noted as a relative area for development. Based on these findings, a Professional Behavior and Autonomy Enhancement Plan was proposed to institutionalize specialized training and nurse-led case presentations. Ultimately, the study concludes that consistent investment in CPD is vital for empowering an accountable and autonomous nursing workforce in resource-constrained government settings.
Akpovero A.O, Israel, T.E, Nwokugha, C.J., Nwokugha, S.U
This study examines the costs and returns of snail production in Ughelli North Local Government Area of Delta State, Nigeria. The specific objectives of this research are to describe the socioeconomic characteristics of snail farmers, estimate costs and returns of snail production, determine profit of snail farmers and identifying the major constraints in snail production. A sample of 84 snail farmers was selected using a random sampling procedure from six communities within the area. Data collection involved structured questionnaires administered to the respondents with the analysis performed using descriptive statistics, gross margin analysis and multiple regression analysis. The results indicated that the majority of snail farmers (33.3%) are aged 36-45 years, predominantly male (54.8%) and married (69%). The enterprise was found to be highly profitable, with a total revenue of ₦5,449,350, total cost of ₦2,888,780, and a net income of ₦2,560,570 per production cycle. The gross margin was calculated at ₦2,973,070. The double log form was chosen as the lead equation on the basis of the highest value of R² more significant coefficients. The coefficients of multiple (R²) value of 0.5863 indicates that 58% of the variation in the dependent variable were explained by the independent variable included in the regression. Regression analysis identified farm size, education, farming experience, monthly income, and marital status as significant positive determinants of profitability Key constraints identified include high cost of feed, lack of access to veterinary services, poor access to credit facilities, inadequate technical knowledge with mean values indicating these issues as significant barriers to profitability. The study concludes that snail farming is profitable and can significantly influence snail production and contribute to income generation, food security, job creation and poverty reduction if effectively harnessed. Recommendations include providing extension services for farmers, ensuring access to credit facilities and reduction in the cost of feed.
Konam Ramesh
Fungal infections in plants and humans pose major challenges to food security and clinical diagnostics, yet their identification still depends on expert microscopy and culture-based methods that are slow and equipment-intensive. Existing deep learning models for fungal classification achieve high accuracy under controlled imaging conditions but fail under illumination shifts, class imbalance, and low-data regimes typical of field or point-of-care scenarios. This study introduces Deep SporeNet, a compact convolutional neural network (CNN) with a few-shot episodic learning head and illumination-robust preprocessing, designed for mobile deployment in agricultural and clinical environments. The proposed framework integrates (i) color constancy and stain normalization to counter variable lighting, (ii) a MobileNetV2/EfficientNet-Lite backbone for efficient feature extraction, (iii) a Prototypical Network head for low-sample fungal taxa recognition, (iv) entropy-based test-time adaptation (TENT) for on-device robustness, and (v) temperature scaling for confidence calibration. Evaluations on the MycoAI-Lab and FieldMyco-Real datasets demonstrate that Deep SporeNet achieves 94.2% accuracy, 92.8% macro-F1, and a tail-class F1 of 82.7%, outperforming state-of-the-art mobile CNNs while running in < 50 ms on a standard smartphone processor. Its well-calibrated predictions (ECE = 0.039) and interpretable Grad-CAM visualizations confirm suitability for real-time fungal diagnostics, crop protection, and biodiversity monitoring. The model thus represents a scalable step toward AI-assisted mycology that is both data-efficient and deployable in resource-limited settings.
Assoc. Prof. Hu Xinying, Sarwat Jamal Saeed
One of the pedagogical problems in teaching great-power competition in courses of international relations and area studies is the lack of teaching resources that focus on sub-state and semi-autonomous actors as they engage in such competition. Teaching case studies about great-power competition tend to emphasise state-level cases and a limited geographic focus, leaving the instructor little material with which to explore how sub-state and semi-autonomous actors perceive and adapt to such competition. This article seeks to solve this problem by constructing a full teaching case study, suitable for graduate and advanced undergraduate courses, built around the Kurdistan Region of Iraq (KRI) as a sub-state actor caught between forms of US and Chinese competition. The case is based on original research by the author conducted from 2014 to 2024, including a structured survey of 43 expert respondents and elite interviews, and is here reframed as a teaching tool, rather than a policy report. The article offers a four-part teaching syllabus, with learning objectives, multi-tiered discussion questions, a role-play game ("The KRG Strategic Council") and a combined assessment rubric. It teaches the concept of asymmetric hedging not as an iron-clad conclusion but rather as a teaching tool with which students can play and experiment. The article provides a contribution to the creation of teaching case libraries (jiaoxue anli ku) in international and area studies teaching and provides a lesson for how research can be repackaged for the classroom.
A.S. Adebayo, Ayo Falana, Olaoye Babatunde Olaolu
This study presents the development and exergo-economic analysis of a biomass gasifier cookstove integrated with a thermoelectric generator (TEG) for generating electricity from waste heat. The design utilizes biomass as a fuel source, converting it into combustible gases through gasification while capturing waste heat for electricity generation using a TEG. The thermoelectric system powers a fan to improve combustion efficiency. Experimental results show stove efficiencies between 76% and 82%, and the exergo-economic analysis reveals a cost-effective design with high exergy utilization. This dual-purpose system demonstrates potential for improving energy efficiency and access to electricity in developing regions.
Almaida M. Macararic, James Q. Tagalog, Liezel P. Naquines, Najeb B. Aloyod, Settie-Zhymah S. Padate
This study utilized an experimental research design, specifically the one-group pre-test and post-test design, to determine the effectiveness of a localized context-based STEM education lesson exemplar in enhancing the conceptual understanding of Grade V learners at Sultan Naga Dimaporo Memorial Integrated School (SNDMIS), Lanao del Norte. Thirty-six (36) Grade V pupils were enrolled during School Year 2025–2026.A 20-item multiple-choice test aligned with the Grade V Science curriculum was administered before and after the intervention. Data were analyzed using frequency and percentage distribution, mean, and the Wilcoxon Signed-Rank Test. Findings showed that pre-test scores were generally low, indicating limited prior understanding of concepts related to the interactions between living and non-living things in estuaries and intertidal zones. After the implementation of the localized STEM lesson exemplar, post-test scores significantly improved. The Wilcoxon test yielded a p-value of 0.000, confirming a significant difference between the pre-test and post-test scores. This result indicates that the localized context-based STEM approach effectively enhanced learners’ conceptual understanding
Lai Qiang, Niu Jia
As of 2026, the integration of digital tools in art education has shifted from supplemental technology to a fundamental transformation in creative ontology. This study utilizes a Human-AI Collaborative Synthesis model to explore global developments and trends in Artrepreneurship and Algorithmic Literacy, with a specific focus on their implications for art teaching in China. Findings reveal a transition toward an "authenticity economy" that prioritizes human authorship, material honesty, and "productive difficulty" as a response to the proliferation of Generative AI. Professional practices are increasingly defined by "workflow-first" integration, where routine technical labor is automated to reclaim time for high-level conceptual inquiry and "Original Vision". Furthermore, the study identifies a shift toward "Agentic AI Literacy," positioning artists as directors of subordinate algorithmic processes to ensure creative sovereignty and resist algorithmic homogenization. In the Chinese context, these trends necessitate a pedagogical pivot toward "agentic agency," the inclusion of artrepreneurship as a core curriculum, and the use of digital tools as instruments for cultural resilience and social advocacy. Ultimately, the study advocates for a "Human-in-the-Loop" model to bridge traditional aesthetic mastery with democratized AI governance.
Smitamayee Raj
The digital divide in India is a very crucial matter, which is deeply interconnected with socio-cultural, economic, and gender-based inequalities. This study explores the digital gender gap and its implications for the empowerment of adolescent girls in rural India, taking insights from the Annual Status of Education Report (ASER) 2023: Beyond Basics. Despite the widely spread sense of smartphones and the growth of digital platforms for education, a gap persists in terms of access, ownership, and usage of digital devices between rural boys and girls (youth). Annual Status of Education Report 2023 reveals that while nearly 90 percent of rural youth report having access to a smartphone at home, boys are more than twice as likely as girls to own their own device. While, females lag behind in digital skills such as- using maps, browsing for information, and managing online tasks. These gaps are not only related to technological but reflect broader gendered social norms that limit girls' mobility, decision-making power, and exposure to digital era. The study analyzes how this digital exclusion affects adolescent girls’ access to online learning, career aspirations, self-expression, and social connectedness all key components of empowerment. It also examines the correlation between girls’ digital engagement and their ability to aspire beyond traditional roles, as observed in both the quantitative data and qualitative focus group discussions from ASER report 2023. This paper highlights the urgent need for gender sensitive digital inclusion strategies in rural education policy. Empowering girls digitally in rural India, it demands community sensitization, female digital mentorship, and safe online environments. Bridging the digital gender gap can serve as a catalyst for broader social transformation, enabling adolescent girls in rural India to become active participants in knowledge economies and decision-making area.
Afolabi Bukola Olanrewaju, Fadele Noah Taiwo, Onatola Iyiola Tope
Drying remains one of the most important postharvest engineering operations required for the preservation of medicinal leaves through effective moisture reduction while maintaining product quality, storability, and process reliability. This study investigated the time–temperature dependent drying kinetics and moisture diffusion behaviour of guava (Psidium guajava), bitter (Vernonia amygdalina), and scent (Ocimum gratissimum) leaves under ambient sun drying and electrically controlled oven drying conditions. Emphasis was placed on moisture content reduction, moisture ratio (MR), drying rate, moisture retention capacity, and thin-layer kinetic modelling as influenced by leaf type and drying environment. Drying experiments were conducted over an 8-hour period with hourly measurements of mass, temperature, and relative humidity. Sun drying was carried out under fluctuating atmospheric conditions (32–37 °C; 59–80% RH), whereas oven drying was maintained at 60 ± 1 °C. Results showed that sun drying reduced moisture content to safe storage levels (<10%) but exhibited irregular drying patterns characterized by fluctuating MR profiles, lower drying constants, and unstable falling-rate behaviour. In contrast, oven drying achieved rapid and uniform moisture reduction within 6 hours, with smooth MR decay curves and higher drying constants, indicating enhanced internal moisture diffusivity. Among the leaves, bitter leaf exhibited the fastest drying response, while guava leaf showed greater resistance to moisture migration. Thin-layer model fitting revealed that the Page model provided the best predictive performance with coefficient of determination (R²) values up to 0.998. Overall, electrically controlled drying demonstrated superior efficiency, predictability, and engineering suitability for large-scale medicinal leaf preservation.
Adrian C. Villegas, Charisse Maxinne C. Cruz, Eugene A. De la Cruz, Ezekiel D. Batisatic, Quennie J. Justiniane, Raniel M. Costanilla
This study focused on the development of “E-Clearance: A Web-Based Student Clearance Management System for St. Clare College of Caloocan.” The research was conducted in response to the challenges encountered in the traditional manual clearance process, such as long waiting lines, delays in obtaining signatures, overcrowding within school premises, and inconvenience experienced by both students and staff. The study aimed to develop a system that would provide a more efficient, reliable, accessible, and organized clearance process for non-graduating students of the institution. A quantitative research method using a descriptive research design was employed in the study. Data were gathered through a paper-based survey questionnaire distributed to 198 non-graduating college students from different tertiary programs at St. Clare College of Caloocan during the Academic Year 2025–2026. The questionnaire utilized a five-point Likert scale to determine the respondents’ experiences with the existing manual clearance process and their perceptions regarding the proposed web-based system. Frequency, percentage, and weighted mean were used to analyze the collected data. The findings revealed that students commonly experience inconvenience, delays, and difficulty in completing the manual clearance process. Results also showed that the majority of respondents strongly agreed that the proposed E-Clearance System would improve efficiency, accessibility, convenience, and reliability in processing student clearances. The respondents also favored features such as real-time updates and online monitoring of clearance status. The study concluded that the proposed E-Clearance Management System is a valuable solution that can significantly improve the existing clearance process of St. Clare College of Caloocan by reducing manual workload, minimizing delays, and enhancing overall operational efficiency and student satisfaction.
Mr. George Sebastian, Mr. Libonce. A, Mr. Madhi Madhan. L, Ms. Shruthi Devadhas
This paper presents HealthSense-Edge, an IoT-embedded smart electronics system for non-invasive predictive health monitoring in indoor environments. The system fuses data from five sensor modalities (PIR motion, CO₂, TVOC, temperature/humidity, acoustic) using a heterogeneous dual-core RISC-V + ARM Cortex-M33 platform. A novel 1D Convolutional-LSTM neural network with 8-bit quantization achieves 96.3% accuracy in detecting respiratory distress, fall risk, and dehydration with only 18 ms inference latency and 230 mW average power consumption. An adaptive behavioral alerting mechanism reduces false alarms by 47% compared to fixed-threshold systems. Validated in a 4-month deployment across 12 smart apartments with 24 elderly residents. All code and data are open-sourced.
Dr. Nidhi Kumari, Ph.D., Dr. Rakesh Kumar Singh, Ph.D.
Pregnancy is a critical life phase often accompanied by psychological challenges such as anxiety and difficulty in coping with physical and emotional changes. The present study aimed to examine the effectiveness of structured counselling in reducing anxiety and enhancing coping mechanisms among pregnant women. A quasi-experimental pre-test–post-test control group design was adopted. The study was conducted at Sadar Hospital in Saran District of Bihar, with a sample of 60 pregnant women divided equally into experimental and control groups. Standardized tools were used to measure anxiety and coping strategies. The experimental group received structured counselling sessions for four weeks, while the control group received routine antenatal care. The results indicated a significant reduction in anxiety levels and improvement in coping mechanisms among the experimental group compared to the control group. The findings highlight the importance of counselling interventions in promoting maternal mental health during pregnancy.
Dr. Nitin Mishra, Dr. Rohit, Tamanna Sharma
Background: The rapid advancement of Artificial Intelligence (AI) technologies has significantly disrupted conventional Human Resource (HR) practices, particularly in the domain of talent acquisition. Organizations across industries are increasingly integrating AI-powered tools—including intelligent resume screening systems, chatbot-based candidate engagement platforms, predictive analytics engines, and video interview analysis software—to streamline and enhance their recruitment processes. Problem Statement: Despite widespread adoption, there remains a critical re- search gap regarding the holistic impact of AI on three interdependent dimensions of recruitment: operational efficiency, candidate experience, and ultimate hiring quality. Existing literature tends to address these outcomes in silos, neglecting the interplay among them. Objective: This paper aims to (i) analyze AI’s effect on recruitment efficiency, (ii) evaluate candidate perceptions and experiences in AI-driven hiring pipelines, and (iii) assess improvements in the quality of hiring decisions facilitated by AI tools. Methodology: A quantitative, survey-based mixed-method research design is pro- posed, targeting HR managers, recruiters, and job seekers (n = 150–300) across multiple industries. Data will be analyzed using regression analysis, structural equation modeling (SEM), and factor analysis through IBM SPSS and SmartPLS. Expected Findings: AI adoption is anticipated to significantly reduce time-to- hire, improve candidate-job matching accuracy, enhance candidate engagement, and yield better-quality hiring decisions. Candidate experience is expected to mediate the relationship between AI adoption and hiring quality. Implications: The findings will offer evidence-based guidance for HR practitioners and organizational leaders navigating AI integration while emphasizing the ethical imperatives of algorithmic fairness, data privacy, and transparency.
Ameril A. Dimnang, Liezel P. Naquines, Najeb B. Aloyod, Saidie M. Odin, Salnor M. Tomanto, Settie-Zhymah S. Padate
This study employed a one-group pretest–posttest experimental design to determine the effectiveness of a localized context-based STEM education approach in enhancing the conceptual understanding of Grade 6 learners at Sultan Naga Dimaporo Memorial Integrated School (SNDMIS), Lanao del Norte. Thirty-seven (37) pupils participated in the study during the Academic Year 2025–2026. A 20-item multiple-choice test aligned with the Science 6 curriculum was administered before and after the intervention. Data were analyzed using frequency, percentage, mean, and paired-sample t-test. Results revealed a significant improvement in learners’ performance, with mean scores increasing from 13.51 (pretest) to 16.22 (posttest). Statistical analysis confirmed a significant difference between scores (t = –9.50, p < 0.05), indicating that the intervention contributed to enhanced conceptual understanding. Learners also demonstrated high engagement (grand weighted mean = 2.64), particularly in collaborative and hands-on activities. As part of the intervention, pupils designed a Coral Reef Water Cleaner prototype using recyclable materials. Evaluation results (90.8%–96.4%) reflected outstanding performance in creativity, functionality, and teamwork. These findings suggest that localized context-based STEM instruction enhances academic performance, engagement, and real-world application of scientific concepts.
Razelle T. Peñaredondo
This study examined the emotional stress and instructional quality of elementary school teachers in the Getafe I District and explored the relationship between these variables using survey questionnaires and Individual Performance Commitment and Review Form (IPCRF) ratings. Findings emphasized the importance of teachers’ profiles—such as age, gender, educational attainment, financial status, and assigned responsibilities—as these may influence both stress experiences and instructional performance. Most teachers are young, predominantly female, and manage multiple responsibilities while pursuing professional growth. Despite these demands, teachers generally experience low levels of emotional stress, although moderate exhaustion was observed. Among the stress domains, exhaustion ranked the highest (mean = 2.25, SD = 0.61), followed by psychological distress (mean = 1.93, SD = 0.39), emotional impairment (mean = 1.92, SD = 0.36), mental distance (mean = 1.90, SD = 0.57), and cognitive impairment (mean = 1.89, SD = 0.42), while psychosomatic complaints had the lowest mean (1.75, SD = 0.50). Instructional quality remained consistently high, with 99.06% of teachers receiving a Very Satisfactory rating and only 0.94% achieving an Outstanding rating. The results showed that workload, educational attainment, and financial status significantly influence both emotional stress and instructional quality, while age and gender do not. Notably, emotional stress has no significant relationship with instructional quality, indicating that teachers can maintain effective teaching despite stress. Overall, the study highlights teachers’ resilience and recommends that school administrators implement targeted support programs focusing on workload management, professional development, and wellness initiatives to sustain teacher well-being and instructional quality.
Joan P. Bacarisas, DM, MAN, RN, Shaira Margaret A. Llega, RN
This study aimed to assess nurses emotional styles, determine their level of adaptation to change, and examine the relationships among profile variables, emotional style, and adaptability. The study employed a quantitative descriptive–correlational design using complete enumeration of staff nurses assigned to patient care areas in a government hospital in Surigao City, Philippines. Data were gathered through an online survey using the Emotional Style Questionnaire and the ADAPTA-10 instrument. Descriptive and inferential statistics were utilized to analyze the data. Findings showed that nurses demonstrated a somewhat high emotional style, while adaptation to change was at a fair level, with emotional adaptation being more challenging than cognitive–behavioral adaptation. Profile variables were generally unrelated to emotional style, while civil status, position, and work schedule were significantly related to adaptation to change. Emotional style was not significantly associated with adaptation to change. An emotional resilience and adaptability enhancement plan was proposed to improve nurses adaptability.
Angel A. Durana III, Carl Daniel G. Silvestre, Cyrus Jimuel O. Aya-ay, Deny Shia M. Baflor, Issiah Wayne M. Linghon, Justine Ponferrada, Kirsten Ericka E. Gregorio, Rich A. De Guzman
The rapid adoption of synchronous online and blended learning environments has intensified the need for fair and consistent monitoring of student participation during virtual class sessions. However, instructors frequently encounter difficulties in capturing participation across multiple interaction channels such as chat messages, microphone activity, reactions, and hand-raise events while simultaneously facilitating instruction. This study designed, developed, and evaluated ENGAGIUM, a real-time participation tracking system intended for professors conducting synchronous online classes through Google Meet and Zoom. The system integrates a browser-based participation tracking extension, instructor-facing dashboards, and real-time analytics mechanisms to automate the collection and visualization of participation events. The study employed a quantitative-descriptive developmental research methodology utilizing sequential pre-development and post-development evaluation phases. Pre-development findings revealed that instructors experienced difficulty consolidating participation records manually, resulting in concerns regarding grading consistency and participation visibility. The developed system was evaluated using descriptive statistical analysis, weighted mean computation, thematic analysis, and the System Usability Scale (SUS). Evaluation results demonstrated positive faculty perceptions regarding usability, effectiveness, transparency, and reliability. ENGAGIUM achieved a System Usability Scale score of 72.88, indicating above-average usability and acceptable system readiness for instructional use. Findings further showed that automated participation logging improved perceived fairness in participation-based assessment by reducing dependence on fragmented manual observation. The study concludes that ENGAGIUM provides a practical and privacy-aware approach for synchronous participation monitoring through automated event capture and analytics visualization. The system contributes to educational technology by supporting transparent participation assessment while preserving user privacy through metadata-based tracking without audio or video recording.
Genelyn R. Baluyos, Joalse Christy S. Gumapac, Lucy G. Pisay
Innovative teaching strategies are essential to make mathematics more engaging and understandable, especially in complex topics like Statistics and Probability. This action research titled "Enhancing Mathematical Strategy Through the Use of Board Games in Mathematics 10" was conducted to improve the mathematical strategies of Grade 10 students in the topic of Statistics and Probability. The study utilized a quantitative research method, specifically a pre-test and post-test design, and involved 43 purposively selected students from a public secondary school. A researcher-made test served as the main instrument for data collection, focusing on measuring students’ understanding and strategic thinking in solving probability-related problems. Before the implementation of the board game activity, the students' performance in the pre-test showed generally low levels of mastery. After participating in the board game sessions, students demonstrated notable improvements in their mathematical performance, as evidenced by higher post-test scores. Statistical analysis using a paired t-test revealed a significant difference between the pre-test and post-test results, with a p-value indicating statistical significance. The computed mean score increased from pre-test to post-test. Incorporating board games into mathematics instruction can promote active learning, critical thinking, and deeper conceptual understanding among learners. The use of board games made the learning process more interactive and enjoyable, helping students better grasp abstract mathematical concepts. The study concludes that board games are an effective and innovative teaching strategy for enhancing mathematical strategies and improving students' academic performance in mathematics. It is recommended that educators integrate board games into classroom instruction to foster active learning and improve mathematical performance. Schools are also encouraged to support teacher training on innovative instructional strategies and further explore the use of educational games across various topics and grade levels.
Dr. Chaitanya Udatha, Krithi Chippada, Satvik Dabbara
Large Language Models (LLMs) have become an integral part of our daily lives; they are used for tasks such as chatbots in customer services and require a lot of computing power. If the user base is large, generating different responses to similar queries results in slower performance and increased computational latency. Hence hierarchical caching systems like GPTCache and MinCache were introduced to reduce redundant inference using exact matching, resemblance matching and semantic matching of the prompts with stored queries to reuse LLM responses for similar queries. However, Unigram-based resemblance caching mechanisms are susceptible to adversarial lexical reordering leading to excessive false positive cache hits. The proposed research introduced structural-aware resemblance matching to improve the robustness of the system without violating the ideology of MinCache by using lightweight and fast similarity caching mechanisms. It has achieved 7.39x safer cache reuse compared to the standard 1-g Minhash while preserving 79.5% of resemblance layer throughput and maintained overall accuracy.
Caranza, Aaron Christopher O, Cortez, Christian Chilles G., Da, Leo V., Dela Cruz, Simon Andrei S., Jeanethjoy D. Naturales, Rapadas, Daniel M., Santos, Miguel Nicolai M.
Enrollment is one of the most crucial processes in every academic institution, yet it often becomes stressful and time-consuming for both students and staff. At St. Clare College of Caloocan, students usually experience long queues during enrollment, especially when completing multiple steps such as submitting requirements, paying at the cashier, or verifying records. This traditional manual process often results in delays, overcrowding, and disorganized workflows that affect the overall student experience. With the increasing use of digital systems in schools, the development of a Smart Enrollment Queuing System becomes an essential innovation. By adopting a system that allows enrollment staff to manage queues and provide real-time updates, waiting times can be minimized and services delivered more efficiently to students. The system will not only streamline enrollment procedures but will also help enrollment staff adapt to digital queue management systems, while students benefit indirectly through reduced waiting times and clearer processes, tools that are becoming common in companies, banks, and government agencies. Ultimately, this project aims to transform enrollment into a smoother, faster, and more organized process that benefits both students and the institution.
Susil Kumar Sahu
Healthcare organizations increasingly need a unified data layer that can connect member, patient, provider, and interaction data across fragmented enterprise systems. Salesforce Data Cloud offers a practical platform for ingesting, harmonizing, unifying, and activating data across customer and service workflows, but enterprise value depends on more than technical connectivity [file:2]. The implementation challenge in healthcare is shaped by fragmented source systems, inconsistent identifiers, governance constraints, privacy obligations, and operational trust requirements [file:2]. This paper presents a revised enterprise implementation blueprint for Salesforce Data Cloud in healthcare environments organized around five layers: source ingestion, harmonization, identity resolution, data quality management, and consent-aware activation [file:2]. In response to peer-review feedback, the paper now clarifies its conceptual methodology, adds a healthcare implementation vignette with indicative outcome measures, expands the discussion of governance and deployment risks, and introduces a visual architecture model to strengthen conceptual clarity [file:1][file:2]. The objective is to provide a more academically grounded and practically useful reference for enterprise architects, healthcare CRM teams, data governance leaders, and digital transformation stakeholders working to create trusted and scalable data ecosystems [file:1][file:2].
Dr. Jyoti Mishra, Mr. Praneet Kumar Mishra, Shree Raman Dubey
The Tata Group stands as a pioneering enterprise in India’s industrial journey, embodying the rare fusion of ethical leadership and nation building. Rooted in Jamsetji Tata’s vision of trusteeship and industrial self reliance, the Group has consistently aligned corporate growth with social responsibility. From the establishment of Tata Steel and the creation of Jamshedpur’s welfare oriented township model to global acquisitions under Ratan Tata’s stewardship, the Group has demonstrated that industrial expansion can coexist with humanistic values. This research paper critically examines Tata’s ethical philosophy, human resource practices, leadership strategies, corporate social responsibility initiatives, and empirical survey findings, situating them within India’s broader industrial narrative. Through comparative analysis, case studies, and quantitative data, the study positions Tata Group as a blueprint for ethical enterprise in the 21st century. The paper concludes with recommendations for embedding ethical leadership into India’s corporate governance framework, aligning with the vision of Viksit Bharat @ 2047.
Sahil Malik
The quantitative estimation of sulphur in organic compounds is an important aspect of elemental analysis in organic chemistry. The Messenger method is a classical and reliable analytical technique used for the determination of sulphur content. In this method, the organic compound is heated with fuming nitric acid in the presence of potassium chlorate, leading to the oxidation of sulphur into sulphate ions. The formed sulphate is then precipitated as barium sulphate using barium chloride solution, which is subsequently filtered, dried, and weighed. The amount of sulphur present in the sample is calculated gravimetrically from the mass of barium sulphate obtained. This study focuses on the principles, procedure, and accuracy of the Messenger method in sulphur estimation. The method is advantageous due to its simplicity, reproducibility, and applicability to a wide range of organic compounds. However, careful control of experimental conditions is necessary to avoid errors caused by incomplete oxidation or loss of precipitate. The results demonstrate that the Messenger method provides reliable and precise estimation of sulphur when performed under controlled laboratory conditions.
Feb Yvonney M. Matugas, Marjanah M. Mustapha, Najeb B. Aloyod, Settie-Zhymah S. Padate, Sittei Hanifah S. Amerol
In the 21st century, students increasingly rely on AI to enhance their skills. However, many students still struggle to strengthen their communication skills. This shows the need to study how AI can be effectively used in enhancing their communication skills. Thus, this study evaluated the effectiveness of Cici AI in enhancing the communication skills of education students at Mindanao State University – Sultan Naga Dimaporo. An experimental research design was used, employing pre-survey, post-survey, and pre-test and post-test instruments. The respondents of the study were 20 first year BSED English students officially enrolled during the Academic year 2025-2026. After the intervention of Cici. Results showed that students already had effective communication skills before the intervention through pre-survey. In the pre-test, most students demonstrated very good in terms of listening and good in writing. In the post-survey results showed a slight improvement in their perceptions after using Cici. In the post-test, most of the respondents performed excellent in listening and good in writing skills. Furthermore, Wilcoxon signed-rank test confirmed that there was a significant difference between pre-test and post-test scores in listening skills, indicating that Cici helped enhance listening skills. However, the t-test confirmed that there is no significant difference observed in writing skills. This study concludes that Cici AI can effectively enhance communication skills, particularly in listening skills. However, its effect on writing skills is not significantly improved. It implies that integrating AI tools helps in enhancing skills, writing may enhance more from extended use, targeted writing activities, and regular feedback.
Dr. Ezekiel O. Pelayo, Robert E. Wariza, Jr.
Mathematics continues to be a challenging subject for many first-year college students, often affecting their academic performance, engagement, and overall learning outcomes. The development of high-quality instructional materials is therefore essential in facilitating meaningful learning experiences and improving students’ mathematical competence. This study aimed to develop and evaluate a learning kit for the course Mathematics in the Modern World and determine its acceptability and effectiveness in enhancing students’ mathematical performance. The study employed a purely quantitative research design using a developmental-evaluative approach. The learning kit was developed based on the course learning competencies and was subjected to expert validation to assess its format, content, clarity, and usefulness. Subsequently, field testing was conducted among 39 first-year college students using a one-group pretest–posttest design. Data were analyzed using weighted mean, analysis of variance, and paired-samples t-test. The findings revealed that the developed learning kit obtained a grand mean rating of 3.87, interpreted as Highly Acceptable, indicating that the material met established standards for instructional quality and usability. Results further showed a statistically significant difference in the ratings provided by experts across the validation components, suggesting varying levels of evaluation regarding the format, content, clarity, and usefulness of the learning kit. Moreover, the effectiveness assessment demonstrated a statistically significant improvement in students’ mathematical performance following exposure to the intervention with a computed t of 11.92 and a p < .001, indicating that the learning kit contributed positively to student learning outcomes. These findings affirm the instructional value and effectiveness of the developed material as a supplementary learning resource. The study concludes that the learning kit can serve as a viable instructional tool for enhancing mathematics instruction and improving student achievement in higher education.
Joan P. Bacarisas, Mae G. Forcadilla
This qualitative study utilized a Husserlian descriptive phenomenological design to explore the lived experiences of operating room (OR) nurses navigating unpredictable surgical realities. Conducted in government hospitals within Surigao City and the Caraga Region, the study involved eight (8) OR nurses to uncover the essence of their professional practice amid systemic and clinical uncertainty. Data were gathered through semi-structured interviews and analyzed using Colaizzi’s method of phenomenological analysis. Findings revealed that nurses experienced the operating room as a high-stakes environment characterized by sudden case insertions, resource shortages, workflow disruptions, and emergent surgical demands. The study identified key themes reflecting the realities encountered, the emotional and mental burdens experienced, and the strategies employed by nurses in managing these challenges. The findings highlighted that OR nurses served as stabilizing forces within unpredictable clinical environments through adaptability, rapid decision-making, and professional resilience. The applicability of the study suggests that operating room nursing is inherently shaped by unpredictability, requiring both technical competence and emotional strength. It further emphasizes the need for responsive nursing management strategies, improved communication systems, and institutional support mechanisms to sustain nurse well-being and ensure patient safety.
Rekha V. Kene
The primary aim of this paper is to examine the use of Vedic Mathematics sutras in deriving derivatives and solving ordinary differential equations. Vedic sutras such as Urdhva-Tiryagbhyam, Ekanyunena Purvena, Calana-Kalanabhyam, Gunakasamuccayah, and Lopanasthapanabhyam helps to simplify the computational process. The study seeks to establish the relevance and efficiency of these Vedic principles in differentiation and differential equation solving. Employing Vedic methods for obtaining derivatives and solutions significantly reduces computational complexity and enhances mental calculation speed. Some illustrative examples are presented to demonstrate the application of these sutras in differentiation. The findings indicate that Vedic Mathematics offers a simplified, faster, and more intuitive approach to solving ordinary differential equations.
Boyelayefa, K., Chiazor F. I., Ideozu, R. U., Mba-Otike, M. N., Oyanyan, R. O.
This study focuses on facies distribution in Cretaceous outcrops along Enugu-Agbogugu axis of the Anambra Basin, south-eastern Nigeria. It is aimed at unravelling the depositional environments of the sedimentary successions and reconstructing the paleogeographic setting. Six well-exposed outcrops were methodically studied with six lithofacies identified, namely: lateritic claystone, bioturbated sandy heteroliths, carbonaceous shale, coal seam, ironstone beds and cross-bedded sandstones. The lithofacies diagnostic features were flaser and lenticular bedding, herringbone cross-stratification; planar and trough crossbedding and an assemblage of ichnofossils including Planolites, Skolithos, and Asterosoma. The lithofacies were grouped into four genetically correlated facies associations, viz: flood plain, distributary channel, prodelta and open marine or offshore that together defined a deltaic system dominated by fluvial processes and associated tidal overprint. The vertical successions and lateral correlations of lithofacies reveal a stratigraphic architecture indicating a complex history of delta progradation influenced by relative sea-level fluctuations and high sediment supply. The outcrops are generally structurally deformed by joints, fractures, syn-depositional normal faults and folds. The folds are effect of compressive stress believed to be associated with the post-Santonian tectonic events. This outcrop-scale study enhances the understanding of heterogeneity in deltaic reservoir under the strong influence of fluvial and tidal processes, as well as the potential for petroleum stratigraphic and structural traps in Anambra basin and others with similar tectonic and stratigraphic settings.
FADAIRO, Olurotimi Olakunle
Environmental health through human waste management is one of the major issues of concerns to most societies and world at large. Ceramic sanitary ware (CSW) products are henceforth designed as plumbing fixture made from clay materials for hygiene purposes. Over the span of time, these products have been valued as life style products comprising water closet, wash basins, urinals, bidets, cisterns and squat pans. Ogun state is a host to two industries where these products are made and distributed yet the local market is flooded with imported brands of CSW. However, this study examined end-users’ preference for CSW as it affects distribution of locally manufactured CSW products in the study area. Questionnaires collected were administered to CSW end-users to collect relevant data. These data were processed using simple descriptive research tools. Response from the CSW marketers revealed that CSW are available for sale, but 95% of CSW available with them were imported while 83% of end-users who responded have used installed CSW in public or private toilets. However, the most important factors considered by end-user respondents, as given by Relative Importance Index (RII) of preference was Ease of cleaning (0.98) Durability (0.97), Affordability (0.96), Coziness (0.96) and functionality of products (0.95).
Mr. Aman Shukla, Mr. Dushyant Singh
Financial management is a key component of long-term success but is not yet fully understood by small regional private service providers in india. The aim of this study is to examine how financial management affects the organisational structure, impact and effectiveness of financial management systems used in XYZ technologies private limited (XYZ), which provides financial advice and service and was founded in bhopal, india in 2022. Based on the following research questions, will XYZ have valid systems of support for operational sustainability and growth from their financial management systems based on their financial planning; liquidity management; cost control; working capital discipline; digital finance usage; and internal controls?. A questionnaire was distributed to 120 members of the organisation, consisting of 5 point likert scale items, as the basis for data collection. Purposive sampling, coupled with stratified convenience sampling, were employed to ensure representation of all functional areas (i.e., management, finance, operations, sales, and administration) of the organisation. In order to analyse the results, the researcher will use weighted mean analysis, percentage distribution, and composite variable scoring as methods of interpreting data. Findings: the relative strengths of the organisation indicated by mean digital finance adoption and internal control strength values of 4.0 and 3.9 respectively were significant. Areas for improvement included cash forecasting (mean score 3.4), receivables management (mean score 3.4), and adequate training (mean score 3.3). Working capital discipline was viewed as the single most significant factor by over 31.7% of respondents in determining financial performance. While the company has an operational finance foundation, it has not yet fully transitioned from process-based to analytic-based financial management. Other organisations with similar development levels should implement rolling cash forecasting systems, structured receivable aging dashboards and finance capabilities training, in conjunction with investing in digital infrastructure.
Abiodun Abolade Moshood, Fatai Oluwadamilare Kareem, Quadri Adebayo Lawal
This study investigated the effect of firm specific institutional factors on the financial reporting quality of quoted deposit money banks in Nigeria. In particular, the study examined how the financial reporting quality is affected by the size of the firm, leverage, profitability, liquidity, firm age, and the ownership structure. This study was conducted with a longitudinal panel research design, where secondary data were collected from the Annual reports of 11 quoted deposit money banks in Nigeria for the period 2014 to 2024. Model selection was done using Hausman specification test and panel regression techniques such as pooled ordinary least squares, fixed effects and random effects models were applied. The results indicated that the random effects model was the most suitable model for data analysis. The regression results revealed an R² of 0.2614 and F-statistic of 10.952 (p = .000). The results indicated that financial reporting quality is positively associated with firm size (β = 1.5112; p = .002), and that leverage is negatively associated with financial reporting quality (β = -0.7984; p = .028). Profitability showed positive significance (β = 0.1483, p = .003), whereas liquidity (β = 0.0520, p = .100) and firm age (β = 0.0043, p = .821) were insignificant. The ownership structure had a significant negative effect (β = -0.0221, p = .043). The study concluded that governance-related institutional factors significantly influenced financial reporting quality among quoted deposit money banks in Nigeria.
Almahden C. Lumidseg, Antonette P.M. Aala, Lyanne T.H. Jover, Roden C. Yumol
Environmental issues such as waste management have existed for many years, where humans continue to explore waste reduction methods for sustainability. This study aims to discover a way to reuse consumer glass waste and fly ash, wastes from coal power plants, by testing its effectiveness as an alternative aggregate and binding agent for the production of hollow blocks. Hollow blocks were made from concrete mixture composed of cement, aggregates, and water. The mixture was put in a hollow block machine, where it was molded and compressed into a hollow block. It was then cured for 7 days. The coarse aggregate of each sample was replaced with powdered glass by 20%, 30%, 40% and 100% by weight, while the cement of all samples was replaced with fly ash by 20% of its weight. It was found that as the glass waste increased, the compressive strength of the hollow block also increased. Results show that the 100% glass waste for coarse aggregate had the lowest compressive strength with an average of 739 psi, and did not meet the required compressive strength for commercial use. The hollow block with 20% glass and 20% fly ash achieved the greatest compressive strength compared to the rest of the treatments except for the commercial hollow block (POSITIVE CONTROL). The results for the water absorption capacity show that all the samples are comparable with each other except for the TREATMENT 1 (20% glass and 20% fly ash).
Shoubhanik Saha
Drinking water drawn from shallow aquifers across several belts of rural India carries dissolved fluoride at concentrations that silently damage teeth, bones, kidneys, and developing brains over years of daily consumption. In Western Uttar Pradesh, this problem is acute yet poorly documented at the district level, and most affected villages have no access to treatment or even basic information about the risk they face. This study was conducted across five districts — Agra, Mathura, Aligarh, Bulandshahr, and Etah — with the twin purpose of measuring fluoride concentrations in 214 groundwater sources and recording the health status of households that depend on them. Water was collected during April–May 2025, a period of peak groundwater stress, and analysed using the SPADNS colorimetric method. Simultaneously, 1,200 households across 42 villages were surveyed and children were clinically examined for signs of fluorosis. The data revealed that 52.3 percent of sources exceeded the 1.5 mg/L safety threshold, with a peak observation of 5.1 mg/L recorded in Aligarh district. Dental fluorosis was confirmed in 63.4 percent of children aged 5–14 years in high-exposure zones. Skeletal fluorosis was documented in 28.7 percent of middle-aged adults, while neurological screening flagged cognitive deficits in nearly one in five children under ten years of age in the most contaminated villages. Thyroid irregularities and early renal stress were also observed at clinically significant rates. The hydrochemical profile of contaminated sources — characterised by alkaline pH, low dissolved calcium, and elevated sodium bicarbonate — points to natural rock leaching as the primary source, compounded by intensive irrigation pumping that has deepened aquifer drawdown over decades. Practical, low-cost defluoridation approaches including the Nalgonda technique and community rainwater harvesting are evaluated and recommended for immediate deployment.
K.V. Santhi Sri, P. Naga Deepthi
Chilli is among the most popularly consumed and commercially exported spices from India; nevertheless, food safety investigations involving the concurrent estimation of pesticide residues, aflatoxins, and ochratoxin-A in different chilli commercial cultivars have been poorly studied. As such, this study sought to determine the food safety implications and residue burden of pesticides, aflatoxins, and ochratoxin-A in three chilli commercial cultivars, including Teja, Byadgi, and Guntur Sannam. Multi-residue determination for pesticides was done using both LC-MS and GC-MS, whereas mycotoxins were estimated using an HPLC-FLD method after immunoaffinity column clean-up. A total of 28 pesticide residues and 4 mycotoxin parameters were studied in a residue burden model and Kruskal-Wallis statistics. Complete detection of all pesticides and mycotoxins was observed in all varieties, suggesting extensive chemical and fungal contamination of chilli. Among the cultivars, Teja had the highest total pesticide burden of 3.6834 mg/kg and mean pesticide content of 0.1316 mg/kg, mainly attributed to acetamiprid, prochloraz, imidacloprid, thiamethoxam, and clothianidin. Conversely, Guntur Sannam demonstrated a high mycotoxin burden of 32.3801 µg/kg with a mean of 8.0950 µg/kg, signifying a serious aflatoxin and ochratoxin-A contamination problem. However, the Byadgi cultivar showed relatively low pesticide burden of 1.9521 mg/kg and a mycotoxin burden of 5.4957 µg/kg. In total, nine pesticide residues and three mycotoxins were significantly associated across varieties (p<0.05) via Kruskal-Wallis analysis.
Ms Sharmeela R, Sreelakshmi S
There has been more interest in making functional drinks in the last several years because more people are looking for natural and health-promoting items. Guava leaves were chosen for the beverage's development because of their therapeutic effects on the human body (antibacterial, anti-inflammatory, and anti-diabetic), their high polyphenol, flavonoid, and antioxidant content. Guava leaves can be transformed into a novel fermented herbal drink, integrating traditional herbal uses with contemporary nutraceutical applications, which is the first step toward developing a novel beverage. This research aims to develop a functional beverage while utilizing guava leaves with various health benefits. This natural, health-driven novel beverage adheres to global consumer demands for inclusive, sustainable and nutrient-dense drinking options and provides artisanal and commercial sectors with a scalable solution to sustainable global demands for economic equity, environmental efficacy and health.
Akhila S., Bhuvanesh J., Esreen P.
Wireless power transfer technology provides a convenient and safe alternative to conventional wired charging systems. This paper presents a frequency-controlled inductive wireless power transfer system designed to improve power transfer efficiency under varying operating conditions. The proposed system employs resonant inductive coupling between transmitter and receiver coils tuned to the same resonant frequency. A high-frequency inverter converts DC supply into AC, which excites the transmitter coil to generate a magnetic field. The receiver coil captures this magnetic field and induces voltage, which is rectified and filtered to obtain DC output. To maintain resonance, frequency control is implemented using a DSP-based adaptive approach modeled in MATLAB. The controller dynamically adjusts switching frequency based on output power to maximize efficiency. The system is validated through simulation and hardware prototype. The proposed design demonstrates efficient short-range wireless power transfer suitable for applications such as two-wheeler electric vehicle charging.
Jeffrey A. Lucero, EdD, MAN, RN, LPT, Joan O. Monastrial, BSc
Background: Administrative systems play a critical role in healthcare delivery, yet their influence on nursing clinical performance and patient outcomes remains underexplored within integrated organizational models. Inefficient documentation processes, fragmented information systems, and communication barriers contribute to increased nursing workload, burnout, missed care, and compromised patient safety. In the Philippine healthcare system, these challenges are intensified by workforce shortages, uneven technological infrastructure, and increasing administrative demands associated with Universal Health Care implementation. Objective: This study examined the direct and indirect effects of administrative system efficiency on nursing clinical outcomes and patient outcomes, identified key mediating organizational mechanisms, and developed an evidence-based intervention framework for healthcare organizations. Methods: A cross-sectional explanatory study was conducted among 200 healthcare professionals from three tertiary hospitals in the Philippines. Participants included staff nurses, nurse administrators, and administrative personnel selected through stratified sampling. Data were gathered using validated five-point Likert-scale instruments measuring administrative system efficiency, organizational mediators, nursing clinical outcomes, and patient outcomes. Structural Equation Modeling (SEM) using maximum likelihood estimation was employed to test hypothesized relationships. Mediation effects were assessed using bootstrapping with 5,000 resamples. Model adequacy was evaluated using χ²/df, Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Results: Administrative system efficiency significantly predicted nursing clinical outcomes (β = .28, p < .01). This relationship was partially mediated by reduced administrative burden, information accuracy and accessibility, communication and coordination efficiency, and resource availability and support. Reduced administrative burden demonstrated the strongest indirect effect. Nursing clinical outcomes strongly predicted patient outcomes (β = .71, p < .001). The structural model demonstrated excellent fit (χ²/df = 1.47, CFI = .96, TLI = .95, RMSEA = .045, SRMR = .041). Conclusion: Administrative system efficiency is a critical organizational determinant of nursing performance and patient outcomes. Findings highlight the importance of integrated administrative workflows, effective information systems, and organizational support mechanisms in improving healthcare quality. A systems-based and multi-level intervention strategy is necessary to achieve sustainable improvements in nursing practice and patient care.
Ms. Elizabeth Njeri Ngigi
This theoretical paper argues that human language exhibits a long-term tendency to move from divergence toward convergence. While migration and cultural isolation produced thousands of distinct languages, human communities have repeatedly developed symbolic systems that transcend local speech. From Egyptian hieroglyphs and Chinese characters to modern emojis, visual signs have enabled meaning to travel across linguistic boundaries. Digital technology has accelerated this process by creating a globally shared symbolic layer embedded in everyday communication. Drawing on linguistics, semiotics, media ecology, and information theory, this paper proposes that emojis function as compressed semantic units that restore ancient pictographic tendencies within networked communication. The paper does not claim that natural languages are disappearing. Rather, it argues that written language is becoming increasingly hybrid: alphabetic, visual, and algorithmically mediated. This convergence has important implications for education, intercultural communication, and the future of human expression
Emie D. Salvacion, DMLO
This study examined governance compliance, management practices, and operational challenges of Commission on Higher Education (CHED)-affiliated school-based cooperatives in Malaybalay City, Philippines. Using a qualitative multiple-case study design anchored in grounded theory, data were collected through focus group discussions, in-depth interviews, Delphi validation, and document analysis. Findings revealed a high level of compliance with Republic Act No. 9520 and institutional by-laws, particularly in the functioning of the General Assembly and Board of Directors. Management practices were generally effective; however, gaps were observed in committee performance, leadership capacity, operational policy implementation, and strategic planning. Operational challenges were identified across planning, organizing, leading, and controlling functions. The study further revealed that governance compliance contributes to organizational accountability, member participation, and financial sustainability. However, limitations in staffing, leadership training, and operational systems affect overall cooperative performance and member satisfaction. Findings also suggest that the integration of digital management systems and leadership development programs may enhance operational efficiency and governance effectiveness. The study concludes that governance compliance provides a strong foundation for cooperative management, but long-term effectiveness depends on organizational capacity-building, financial sustainability, leadership competence, and system strengthening. Future studies may adopt mixed-methods approaches and include cooperatives from other regions in the Philippines to improve the generalizability and comparative value of the findings.
Braide, A. I, Dike B.U., Nwoke H.U, Ukachukwu O.C.
Groundwater quality assessment is essential for ensuring safe drinking water and mitigating contamination associated with industrialization and urbanization. This study developed a predictive model for groundwater quality assessment using the Water Quality Index (WQI) and Multiple Regression Modelling (MRM) within Trans Amadi Industrial Layout, Port Harcourt, Nigeria. Groundwater samples were collected from fifteen (15) boreholes and analyzed for selected physicochemical parameters following standard procedures. Results indicated considerable spatial variation in groundwater quality, with elevated concentrations of heavy metals such as lead (Pb) and cadmium (Cd) observed at several locations. WQI values revealed that most sampling points were unsuitable for drinking, indicating widespread groundwater deterioration. The developed regression model demonstrated excellent predictive performance (R² = 0.9998; Adjusted R² = 0.9989), with Pb, Cd, dissolved oxygen (DO), sulphate (SO₄), and zinc (Zn) identified as major predictors influencing WQI. The close agreement between observed and predicted WQI values confirms the model’s reliability for groundwater quality prediction. The findings demonstrate that integrating WQI and MRM provides an effective and cost-efficient approach for groundwater monitoring, contamination assessment, and sustainable water resource management in industrial environments.
Dr. A. Tejasri Internee, Dr. R. Gayathri Internee, Dr. R. Sireesha Internee, Dr. Raavi Lagnajita
Background: Plantar psoriasis is a chronic inflammatory dermatological condition characterized by hyperkeratosis, fissuring, scaling, itching, and discomfort involving the soles of the feet, often leading to impairment in daily activities and reduced quality of life. Conventional treatment approaches may provide temporary symptomatic relief; however, recurrence and adverse effects remain significant therapeutic challenges. Case Presentation: A 36-year-old female presented with chronic thick scaly eruptions on the left sole for six years, associated with severe itching, fissures, occasional bleeding, and aggravation from cold weather, wet feet, and before menstruation. The patient also exhibited characteristic constitutional and mental symptoms, including chilly disposition, desire for sour food, aversion to fatty food, perspiration of feet, indifference toward family members, emotional sensitivity, and aversion to sympathy. Based on individualized case analysis, totality of symptoms, and repertorial evaluation, Sepia 1M was prescribed as a constitutional remedy. Outcome: Progressive clinical improvement was observed during an eight-month follow-up period, including reduction in itching, fissuring, bleeding, and hyperkeratotic plaques, with improvement in emotional well-being and overall quality of life. A mild relapse following wet foot exposure responded favorably to repetition of the indicated remedy. Conclusion: This case highlights the potential role of individualized homoeopathic treatment in the management of chronic plantar psoriasis. The observed improvement suggests that constitutional homoeopathic prescribing may serve as a supportive therapeutic option in selected cases; however, larger clinical studies are warranted to establish effectiveness and reproducibility.
Piyush Chavan, Prof.Moushmee Kuri, Pushkar Thombare, Tanvi Bokade
Conventional approaches to detecting plagiarism involve mainly string-matching and n-gram fingerprinting methods, which can detect plagiarised documents involving verbatim plagiarism, but they cannot catch paraphrasing, synonym substitutions, or imitations of writing styles. Such shortcomings have now gained importance due to developments of sophisticated intelligent paraphrasing and the use of advanced large language models, which help evade detection by conventional approaches. In this research, we present HPCM, an end-to-end plagiarism detection system that utilises a nine-module machine-learning-based pipeline combining three analysis components: the first is the cosine similarity of terms using the TF-IDF method, secondly, embedding-based semantic similarity using the all-miniLM-L6-v2 model, and thirdly, stylistic similarity based on the analysis of POS Distribution, Type Token Ratio, and Sentence length statistics. These results are combined through the application of a weighted sum fusion function that gives greater emphasis to the semantic similarity score. Additionally, a novel Dynamic Similarity Calibration (DSC) module adjusts the plagiarism score per pair based on the relative length of documents, their vocabulary richness, and topic similarity. Experiments conducted over four different categories of plagiarism reveal that HPCM scores 69.0% in detecting paraphrases compared to 24.9% by conventional approaches, showing a remarkable 44.1 percentage point improvement. It is implemented as a microservices system on Vercel, Render, Hugging Face Spaces, and MongoDB Atlas, proving the practicality of using multilayered neural models for detecting plagiarism even with only free-tier cloud resources. The source code, along with the testing data, is publicly available.
Elizabeth A. Uko, Emmanuel S. I. Ejere.
This study specifically assessed the impact of natural resource governance on socio-economic development in Niger Delta’s Akwa Ibom State. The investigation focused on examining the relationships between natural resource governance and healthcare services, road infrastructure, and educational facilities respectively in selected oil-producing communities in the area of study. The Resource Curse Theory was adopted as the theoretical framework for the study. A survey research design was employed, while data were collected through structured questionnaire administered to 400 respondents selected from six oil-producing local government areas in Akwa Ibom State. Data obtained were analyzed using descriptive statistics and Chi-square statistical technique at 0.05 level of significance. The findings revealed that natural resource governance had significant relationships with access to healthcare services, road infrastructure development, and provision of educational facilities in Akwa Ibom State. The study found that despite substantial oil revenues generated from the region, poor governance practices, corruption, weak institutional frameworks, and inadequate accountability had hindered effective socio-economic development in many oil-producing communities. The study concluded that effective natural resource governance remained essential for sustainable development in the Niger Delta region. The study therefore recommended improved transparency, accountability, community participation, and increased investment in healthcare, road infrastructure, and educational facilities in oil-producing areas.
Joan P. Bacarisas, DM, MAN, RN, Wencill Bless M. Eguna, RN
This study aimed to determine the implementation of clinical supervision strategies in terms of purpose, process, and impact, describe nurses’ IPCR scores, and examine the relationship between clinical supervision strategies and performance ratings. A descriptive-correlational research design was employed involving 205 registered nurses in a Level II government hospital in Surigao City, Philippines. Data were gathered using the Questionnaire for Implementation of Clinical Supervision Strategies (QICSS) and official IPCR records obtained with consent. Descriptive statistics and Pearson r were used for data analysis. Findings revealed that clinical supervision strategies were implemented at a very high level, while nurses’ IPCR ratings were generally very satisfactory. However, no significant relationship was found between the implementation of clinical supervision strategies and IPCR scores. These results suggest that clinical supervision primarily functions as a developmental and supportive process, while performance appraisal reflects institutional standards and measurable outputs. The study recommends strengthening alignment between supervision practices and performance evaluation systems through a Clinical Supervision Performance Enhancement Plan to further support nursing development and organizational effectiveness.
Dr.Elrafie A. A.Allah, Dr.Omyma Altayib Haj Almakki, Prof.Yasir A. Mohamed
The study aimed to improve the quality of Cane juice by adding sugar Beet juice and determining the best addition ratio of sugar Beet juice to sugar Cane juice. The experiment is conducted by mixing beet juice with the cane juice by different ratio, begin experiences by ratio %5 of beet sugar juice and 95% of sugar cane juice until we reach the ratio equal of Beet juice and cane juice and to know the change that happens to Cane juice after mixing. where the calculation were carried out by the formula for calculating the concentration of mixtures. This study showed the improves of quality parameters of the mixture of Beet juices and cane juices Positively. The pol increase from 10.5 to 21.5 and the Brix increase from 13.4 to 25.1. The purity of the blended juice increased significantly where before the addition of sugar Beet juice was 78.3 and after addition of sugar Beet juice recorded purity 88.65.The pH value increased from 5.2-6.65 .. Each increased percentage added Beet juice note the improvement in the properties of mixed juice, especially in the degree of purity. The study was recommended to add Sugar Beet juice to Sugar factories in Sudan to improve the quality of Cane juice and conduct more studies on the effect of adding sugar Beet juice to sugar Beet juice
Atoe Uyi, Innocent Enya Echeng, Lawrence Ekeng, Obani Ethelbert Akachukwu
This research investigates the effectiveness of Instinctive Power Factor Improvement (IPFI), also referred to as Automatic Power Factor Correction (APFC) systems, in reducing power losses and enhancing power factor conditions in distribution feeders, with a focus on the Calabar AMIKA Distribution Feeder. The research adopts a simulation-based approach using ETAP Power Systems software to model the feeder and evaluate system performance under varying load conditions. Statistical analysis was conducted using Kendall’s Tau-based Pearson Correlation to establish the relationship between power losses and power factor levels. The results demonstrate that the implementation of APFC systems leads to significant improvements in both power factor and loss reduction across multiple substations. For instance, Achibong substation recorded a loss reduction from 47.6 kW to 27.7 kW, while Obutong substation losses decreased from 92.9 kW to 30.8 kW. Similarly, substantial improvements in power factor were observed, with Clement Ebri substation increasing from 65% to 86%, Utility substation improving from 16% to 100%, and Nsemo substation rising from 43% to 95%. These improvements contributed to enhanced operational efficiency, reduced technical losses, and improved voltage stability across the feeder. The research concluded by investigating more in APFC systems which is highly effective in optimizing power factor and minimizing losses, leading to cost savings and improved reliability of the electrical network. It recommends further validation through field implementation and economic analysis.
Mr. Aman Shukla, Mr. Shubham Geete
The hygiene products market in India is experiencing rapid growth; however, there has been very little academic research on consumer behaviour and satisfaction related to regional institutional business-to-business (B2B) supply chain operations. This research attempts to determine the factors affecting institutional purchase decisions and subsequent customer satisfaction with ABC Care Private Limited, a regional manufacturer/wholesaler of hygiene and cleaning products for institutional consumers located in Bhopal and Indore, Madhya Pradesh. In this quantitative research, a descriptive-correlational cross-sectional survey research design was utilized. The sample consisted of 120 institutional respondents who were chosen using purposive convenience sampling from four types of institutions. Approximately 30% of surveys were completed in each of the following sectors: hotels and guesthouses, hospitals and clinics, corporate offices, and educational institutions. Data were collected using a structured questionnaire with a five-point Likert-type scale, then analyzed through frequency distributions, descriptive statistics (mean and standard deviation), inter-rater reliability assessment (Cronbach's alpha), and Pearson's correlation coefficients to evaluate the strength and direction of the two constructs. The major criteria driving purchase decisions were product quality and cleaning effectiveness (31.7%), followed by perceived price/value (20.0%) and product availability (15.0%). All core satisfaction areas produced average scores greater than 4.00 (with 84.2% of respondents reporting some or high level of satisfaction) on a 5 point scale. The scale demonstrated an acceptable level of reliability (α = 0.84). Resulted in a strong positive correlation between product quality and overall satisfaction (r = 0.76, p < 0.01) and also between overall satisfaction and intention to repurchase (r = 0.80, p < 0.01). The safe packaging and product info received the lowest average score (M = 3.96) indicating that this is an area for management improvement. While the correlational analysis found statistically significant associations, it does not allow for causal conclusions. To determine directionality will require conducting experimental or quasi-experimental studies outside of this applied research. This research advances the theoretical understanding of the Theory of Planned Behaviour, Expectation-Disconfirmation Theory and SERVQUAL in a unique regional B2B hygiene supply market in Central India, providing practical suggestions to improve supplier performance and retain institutional customers.
Feb Yvonney M. Matugas, Najeb B. Aloyod, Nor-Ain M. Abdullah, Qaisnayah A. Datuman, Settie-Zhymah S. Padate
Despite the increasing availability of digital design tools, many pre-service teachers continue to rely on traditional methods in developing instructional materials, limiting their creativity and digital competence. This study aimed to examine the impact of integrating Canva on the instructional materials development skills of third-year Bachelor of Elementary Education (BEEd) students. A developmental research design was employed, involving twenty-eight (28) participants from Mindanao State University–Sultan Naga Dimaporo during the Academic Year 2025–2026. Data were collected using pre-survey, post-survey, pre-test, and post-test instruments, and were analyzed using weighted mean, Wilcoxon Signed-Rank Test, and paired t-test. Results revealed that students’ perception improved from a grand weighted mean of 2.65 (Effective) to 3.78 (Highly Effective). Performance in instructional materials development also increased from a mean score of 2.14 (Moderately Achieved) to 3.59 (Highly Achieved). Statistical analysis showed a significant difference between pre- and post-survey scores (p = .001) and between pre-test and post-test scores (p = .001), leading to the rejection of the null hypothesis. These findings indicate that Canva integration significantly enhances students’ creativity, digital competence, and instructional design skills. The study concludes that incorporating digital tools such as Canva in teacher education programs can effectively improve the quality of instructional materials and better prepare future educators for technology-integrated teaching environments.
Himanshu Patel
Sciatica is a neurological condition characterized by Compression of the sciatic nerve causes pain that radiates from the legs to the lower back. Conventional diagnostic approaches, including physical examinations and MRI analysis, are time-consuming, prone to human error, and limited by subjective interpretation. AI and ML have revolutionized industries with their emergence medical diagnostics, offering data-driven solutions to improve accuracy and reduce diagnostic uncertainty. The study assesses various ML models—such as Decision Trees, SVM, Random Forests, Neural Networks, and Gradient Boosting—in predicting sciatica using clinical and imaging data. Recent research suggests that ensemble methods like Random Forest and Gradient Boosting often outperform conventional models in predictive performance, making them strong candidates for sciatica diagnosis. However, the interpretability of complex models, such as deep learning architectures, remains a crucial factor in clinical adoption. The study further evaluates the trade-offs between predictive accuracy and model explainability to determine the most suitable ML approach for real-world clinical applications. Additionally, AI-driven diagnostic systems can facilitate early detection, reduce the risk of chronic pain, and minimize the need for invasive procedures. To the research, this contributes findings the advancement of intelligent diagnostic tools in musculoskeletal healthcare, enhancing clinical decision-making, optimizing diagnostic workflows, and improving patient outcomes. Study highlights the potential of AI in revolutionizing sciatica diagnosis and provides insights into selecting an optimal ML model for effective implementation in clinical practice. In addition, the study incorporates insights from recent deep learning research. Furthermore, AI-driven diagnostic systems offer the potential for early detection, reduced risk of chronic pain progression, and minimized reliance on invasive procedures. Integrating these predictive tools into telemedicine platforms could also enhance access to specialized care in underserved regions. The study underscores the transformative role of AI, particularly machine learning, in the future of sciatica diagnosis.
Feb Yvonney M. Matugas, Frank-Jay M. Fullo, Liezel A. Mirador, Liezel P. Naquines, Najeb B. Aloyod
Science plays a crucial role in developing problem-solving skills and critical thinking among learners. However, traditional teaching approaches in the elementary level often fail to sustain learners’ interest and engagement, especially in abstract science concepts. While studies have shown the effectiveness of STEM based instruction, there is a lack of research on how localized, context-based STEM approaches can enhance learning outcomes at the primary level, particularly in Grade 3 Science. This study aimed to determine the effectiveness of integrating a localized context-based STEM education approach in teaching selected Science topics among Grade 3 learners at Sultan Naga Dimaporo Memorial Integrated a School (SNDMIS) during the Academic Year 2025-2026. A total of 33 learners officially enrolled in Section A were selected as respondents. A 20-item test was administered before and after the intervention to measure the learners’ performance. Data were analyzed using frequency/percentage distribution, weighted mean, and the Paired Sample T-test. Findings revealed that the pre-test scores of the respondents were generally low, while the post-test results showed a significant increase in achievement levels. The mean score increased from 10.97 to 16.06, the t-test confirmed a significant difference between pre-test and post-test scores (t = -9.10, p<0.05). This proves that the intervention had a positive and significant effect on the learners’ academic performance such as making paper eyeglasses. The learners’ output were evaluated in terms of understanding, creativity and design, and participation which scored between 92.67% and 93.33%. This indicates that the learners generally understood the task well, showed creativity, and actively participated in the activity. Learners’ attitude on their STEM activity got the grand weighted mean of 2.84, interpreted as “Highly Positive”.This study concludes that contextualized STEM instruction, grounded in local and familiar situations, can improve learners’ understanding, retention, and engagement in Science learning.
Mr. Ravi Dhandhukiya, Ms. Reema Sorathiya
Optimization is crucial to the growth of artificial intelligence (AI) and machine learning (ML), enabling effective solutions for complex challenges across various fields. This paper investigates the interplay between optimization techniques and AI/ML approaches, emphasizing the foundational roles of mathematical modeling, partial differential equations, and operator theory. We highlight recent advancements in areas such as inverse problems and variational methods, showcasing how these developments enhance problem-solving efficiency and robustness in modeling. The findings underscore the reciprocal influence of optimization and AI/ML, concluding with potential future research avenues that address existing challenges and explore novel applications in diverse domains.
Oguntimehin Abiodun S, Oluwole Toluwalase Gregory
This paper examines the integration of Internet of Things (IoT) and Building Information Modelling (BIM) technologies in the facility management of Nigerian healthcare facilities. Healthcare facilities in Nigeria encounter persistent challenges including ageing infrastructure, overcrowded wards, poorly maintained medical equipment, and inefficient administrative processes, all of which compromise operational efficiency and patient care quality. Through a systematic literature review of peer-reviewed sources published between 2016 and 2026, this study explores how IoT and BIM technologies can address these challenges through real-time monitoring, predictive maintenance, and data-driven decision-making. The paper synthesises literature on technology adoption in healthcare settings across Africa and conducts a comparative analysis of Nigeria with Kenya, South Africa, India, Rwanda, Ghana, Uganda, Tanzania, and Malawi. Key findings indicate that IoT and BIM implementation can reduce equipment downtime by approximately 25 to 35 percent, optimise energy consumption by 20 percent, and improve space utilisation efficiency. However, adoption remains limited, primarily due to financial constraints, inadequate technical expertise, deficient infrastructure, and weak policy support. Major barriers include high implementation costs, shortage of skilled personnel, irregular power supply, and poor internet connectivity. The study proposes evidence-based strategies including investment in digital infrastructure, institutional policy development, capacity building for facility managers, continuous monitoring and evaluation, strategic resource allocation, and promotion of inter-departmental collaboration. The paper concludes that technology integration constitutes a strategic imperative for modern healthcare facility management in Nigeria, offering substantial potential for sectoral improvement.
Isaiah Nuah
This article examines international education as a tool of diplomatic influence, with particular focus on China’s strategic use of scholarship programs, Confucius Institutes, vocational training, and academic exchanges as instruments of soft power in Africa. Using Liberia as a primary case study, the paper traces the historical trajectory of China–Liberia educational cooperation from the resumption of diplomatic relations in 2003 to the landmark 2024 FOCAC Beijing Summit. Drawing on diplomatic records, institutional data, and secondary literature, the study finds that China’s education diplomacy in Liberia encompasses five interconnected dimensions: government scholarships, Confucius Institute establishment, capacity-building program, infrastructure investment in educational facilities, and people-to-people exchange platforms. These efforts have progressively deepened bilateral relations and positioned education as a central pillar of China’s broader soft power strategy in West Africa. The article further analyses tensions between developmental intent and geopolitical instrumentality, noting that while Liberian graduates acquire valuable technical skills, the selectivity of program design reflects China’s national interest framing. Comparative data from FOCAC I (2000) through FOCAC IX (2024) reveal an escalatory pattern in Chinese educational pledges, culminating in 60,000 scholarships and training slots for the 2024–2027 cycle. The findings contribute to the growing literature on education diplomacy, South–South cooperation, and China’s global influence strategy in the post-pandemic era.
Mr. Ravi Dhandhukiya, Ms. Reema Sorathiya
The emergence of big data has revolutionized multiple fields, necessitating advanced numerical methods for the effective analysis of expansive and complex datasets. This paper presents a thorough review of numerical tech-niques applicable in big data scenarios, focusing on inverse problems, para-bolic and elliptic partial differential equations (PDEs), nonlinear systems, and operator-theoretic strategies. Highlighting recent advancements, such as the inverse Calderón problem and flux-saturated diffusion equations, we synthesize crucial methodologies while addressing computational challenges in high-dimensional contexts. The paper concludes with a critical evaluation of existing limitations and suggests future research avenues at the interface of numerical analysis and big data.
Swapan Samanta, Tarapada Manna
This paper reports on a forty-year field study — one of the longest of its kind — examining how three of the world's most important food crops respond to changes in irrigation timing. Working across smallholder farms in West Bengal, India, between 1985 and 2025, we tracked 327 individual plants of paddy rice, wheat, and potato through hundreds of growing seasons. What we found was, in some ways, exactly what experienced farmers have long suspected: crops appear to care not only about how much water they receive, but about when. After two to three weeks on a consistent watering schedule, plants seemed to anticipate their irrigation — showing physiological signs of preparation before water even arrived. When we disrupted those schedules abruptly, yields fell by 15 to 35 percent, even when the total amount of water delivered remained exactly the same. Gentle, gradual schedule transitions, by contrast, produced almost no disruption at all.
Anila Pasha, Md Abu Hasan, Mirola Afroze, Moktar Hossain
Modern healthcare would not be possible without the use of biomedical equipment, which is crucial in supporting diagnosis, therapy, monitoring of patients, and life-sustaining processes. Clinical devices like ventilators, infusion pumps, defibrillators, patient monitors, ECG systems, thermometers, and laboratory instruments directly relate to the clinical decision-making and delivery of treatment. Thus, they necessitate regular calibration and frequent validation of these instruments to maintain reliability, safety, accuracy and consistent performance over the entire life of the instrument. Any inaccuracy in measuring or in performance of functions can result into wrong diagnosis, ineffective treatment or a greater risk to patient safety. The ISO/IEC 17025 standard of competence of testing and calibration laboratories offers a robust and internationally recognized framework of ensuring technically valid, traceable and reliable results of calibration [1]. It provides rules of lab competence, unbiasedness, traceability of measurements, validation of methods, qualification of personnel, control of the environment and quality management systems. By adhering to this standard, biomedical calibration labs are able to maintain high standards of technical accuracy, and to express a degree of confidence in their results. The paper provides a critical review of ISO/IEC 17025-conforming calibration practices of biomedical equipment, including quality system, metrological traceability, estimation of uncertainty, risk-based calibration timeframes, documentation control, personnel competence, and internal quality assurance. It also talks about calibration methodology of commonly used biomedical devices such as patient monitors, infusion pumps, defibrillators, electrosurgical units, ventilators, thermometers, sphygmomanometers, pulse oximeters, ECG systems, and weighing scales. Particular attention is paid to evaluation of the uncertainty of measurements, environmental factors, and rules to evaluate conformity. Moreover, the paper examines some of the major issues that healthcare facilities and labs in developing nations face, including the lack of strong chains of traceability, trained staff, regulatory control, and reliance on non-accredited service providers [2]. Lastly, practical recommendations are made to the hospitals, regulators and laboratories to have sustainable biomedical metrology systems in accordance with the ISO/IEC 17025 requirements. The paper concludes that systematic calibration within a certified structure is a significant intervention to improve patient safety, clinical confidence, regulatory compliance, operational efficiency, and overall healthcare outcomes.
Walter C. Horcerada
Poor job student behavior is a growing concern. This study examined the significance of forecasting job behavior for Academic Motivation and Social Development. Using predictive design, data from 240 respondents selected via total enumeration sampling were analyzed using regression. It was found that academic motivation and social development have a significant combined predictive influence on job behavior. This result partially supports Self-Determination Theory. Future researchers may explore additional variables to account for the 50.5% of the model's variance that remains unexplained. School leaders may allocate resources and implement competency-based training, skills development activities, and work immersion programs to strengthen students' positive job behavior.
Elisha Taye Ige, Muhammad Fawaz Abubakar, Olaolu Oyinlola Bilewu, Oyeniyi Rasheed Muhammed, Saheed Olalekan Rabiu, Sulyman Bolakale Saka, Yusuf Funsho Issa
Introduction: Inadequate menstrual hygiene management (MHM) is associated with reproductive tract infections, school absenteeism, and stigma among young women in resource-limited environments. Information on MHM among rural Nigerian adolescents is scarce. Objective: To assess the knowledge, attitudes, practices, and determinants of MHM among adolescent female secondary school students in Shao, Moro Local Government Area, Kwara State, Nigeria. Methods: This descriptive cross-sectional study involved 350 secondary school girls in classes SSS 1-3 from five purposively selected schools in Shao from June to August 2025. The sample size was calculated using Cochran’s formula with a 10% non-response rate. Participants were selected via multistage sampling with proportionate allocation across classes. Data were gathered using a pretested, semi-structured interviewer-administered questionnaire available in English and Yoruba. The instrument was validated by public health and obstetrics experts, with a Cronbach’s alpha of 0.81 for the knowledge section. Data were analyzed using SPSS version 26.0. Knowledge, attitude, and practice were scored, graded, and categorized. Associations were tested using chi-square at p<0.05, and binary logistic regression was conducted to identify independent predictors of good menstrual hygiene practice. Result: The mean age was 16.97±1.73 years. Overall, 60.6% had adequate knowledge, 40.9% had good practices, and 76.3% had a negative attitude towards MHM. Although 72.9% used absorbent materials, 68.6% used commercially made sanitary pads. In addition, 60% disposed of used pads improperly. Major constraints included lack of toilet privacy (70.9%), inadequate information (64.9%), and cost of sanitary pads (49.4%). Knowledge had a significant correlation with age, religion, birth order, school type, parents’ education level, regularity, and duration of menstruation (p<0.05). Practice had a significant correlation with guardian, religion, parents' education level, regularity, family history of dysmenorrhea, duration, and pain (p<0.05). Binary logistic regression further identified living with parents (AOR = 2.34, 95% CI 1.45–3.78, p = 0.001), tertiary maternal education (AOR = 1.89, 95% CI 1.12–3.19, p = 0.017), regular menstruation (AOR = 2.11, 95% CI 1.23–3.62, p = 0.007), and absence of dysmenorrhea (AOR = 1.76, 95% CI 1.08–2.87, p = 0.024) as independent predictors of good menstrual hygiene practice. Conclusion: MHM knowledge was moderate, but not consistently translated into safe practice due to infrastructural and financial constraints. It is recommended that the Kwara State Ministry of Education incorporate menstrual health education into the school curriculum and provide access to proper WASH facilities and affordable sanitary products in all public secondary schools.
Dr Medina Mohammed, Dr Usman Muhammed Song, Hussaini Muhammad Mairiga, Zainab Mukhtar Yusuf
The study investigated the relationships among Knowledge Management Process (KMP) factors influencing librarians’ innovative performance in information service delivery in Nigerian libraries with the aim of establishing a framework for enhancing library services in the face of rapid technological advancement. The adopted a concurrent mixed-research approach employing both quantitative data through correlation research design using descriptive and multivariate factor analysis methods and a qualitative data through an in-depth interview method on a sampled 207 librarians. The study found that knowledge sharing through social-media and blogs, Cloud-Based library systems, facilitating knowledge transfer through collaborative platforms and adopting Artificial Intelligence are the innovative KM practices that improve librarians’ productivity. Inadequate ICT infrastructure and resistance to change are impediments to KM Adoption. Using a factor analysis approach, the study explores the underlying multidimensional relationships among KM and innovative practice variables and condenses them into a smaller set of components for model and instrument development. The study found that the KM process (creation, dissemination and sharing) (β=0.348, t=5.899, p < .01, N = 207) and innovative practices (β=0.620, t=10.496, p < .01, N = 207) enhance librarians’ productivity. The results of the factor analysis revealed a 0.960 KMO, showing an adequate sample size. The study identified and retained 4 factors with sufficient eigenvalue in Factor 1 (15.549), Factor 2 (7.791), Factor 3 (4.134), and Factor 4 (2.261), significantly greater than the randomly generated eigenvalue of parallel analysis. The CFA revealed CMIN/DF=1.389, RMSEA=0.043, TLI=0.990, and CFI=0.991, which provides an acceptable hypothetical model. The findings were used to develop a KM framework “Innovative KM Process Conceptual Framework” as the contribution of the study. The study highlights the importance of the factor analysis approach as a mechanism for enhancing librarians' productivity and improving library services and recommends the application of a strategic approach to increase productivity.
Akani, Kingston, Cookey, E.E., Dr. C.G. Igiri, Tenalo, B.T.
Heterogeneous multi-core systems are increasingly used in latency-sensitive computing environments because they combine different processing units such as high-performance CPUs, low-power cores, GPUs, NPUs, and DSPs. However, the diversity of these processing units makes task allocation difficult, especially when execution time, communication delay, processor availability, energy consumption, and workload dependencies must be considered together. This study develops a latency-aware task allocation framework for heterogeneous multi-core systems using the Whale Optimization Algorithm (WOA). The objective is to formulate task scheduling as a discrete task-to-core mapping problem and evaluate the effectiveness of WOA under independent, DAG-based, real-time, and energy-aware workload conditions. The proposed method adapts the continuous WOA into a discrete integer-encoded scheduling model, where each whale represents a complete task-to-processor assignment. A latency-based fitness function was used for WOA-Latency, while an extended weighted objective was applied for WOA-EnergyAware to examine latency-energy trade-offs. The experimental evaluation compared the proposed WOA variants with Random, Round-Robin, MET, MCT, Min-Min, Max-Min, HEFT, PEFT, GA, PSO, GWO, ACO, and a WOA-MCT hybrid scheduler. The evaluation included repeated simulation runs, statistical reporting, convergence analysis, scalability testing, deadline miss analysis, and parameter sensitivity assessment. The results show that WOA-Latency outperforms several naïve and metaheuristic baselines in some workload settings, particularly Random, Round-Robin, GA, PSO, and GWO. However, deterministic heuristics such as MCT and Min-Min performed better for independent-task workloads, while HEFT and PEFT achieved stronger results for DAG-based scheduling. The energy-aware WOA variant demonstrated the framework’s potential for multi-objective optimisation, although with some latency trade-off. Overall, the study concludes that WOA is a flexible and extensible optimisation framework for heterogeneous task allocation, especially in complex, nonlinear, energy-aware, and multi-objective scheduling scenarios.
Debasis Patnaik., Sushmita Bhattacharjee, Swapnil Saurav.
India is an economy with one-fifth of world’s working population. With such large population percentage of job opportunities become very less. Startups are oftentimes seen as the solution to the much needed job growth. More importantly, it is successful startups that matter most. But, how do entrepreneurs value the most important factors for success? This study determines what factors are important in each stage in the startup life cycle and how to determine the life cycle of a start-up. First, success and failure factors are identified through a literature review. Second, a conceptual startup framework is constructed in which the factors are divided in the founding team, the startup capability, and the external environment. Next data is collected about 5 startups from different field of operation like Internet, Renewable Energy and E-commerce. Also, online interviews were done of 50 entrepreneurs to collect data. And last, a test is conducted in order to test the propositions and determine what factors are most important in each stage of the startup life cycle. The results showed us that different factors are responsible for growth or downfall of a startup at different stages of development. This report clearly points down different factors at different stages responsible for growth or downfall of a start-up.
Mechelle Mea H. Josol, Riza Beltran-Salipong, PhD
The research conducted a study to assess the effect of coping mechanisms on teacher performance and whether coping mechanisms serve as mediators in relation to teachers’ mental health challenges in the district of Calape. The researcher used surveys and the Individual Performance Commitment and Review Form (IPCRF) to evaluate teachers’ mental health status and performance. The results indicated that most teachers in this study were afraid of how they will react to their past traumatic experiences. Although teachers have met their challenges through various coping strategies, the majority of them were able to cope with their issues. The highest ranked area of mental health from the Anti-Bullying Study was avoidance symptoms (Mean = 1.80, SD = 1.07) and the lowest score for cognitive and mood alterations (Mean = 1.29, SD = 1.12). For the area of Coping Strategies, the highest Mean is Problem Focused Coping (Mean = 3.25, SD = 0.65), while the lowest score is Avoidant Coping (Mean = 2.78, SD = 0.74). The performance rating of all participants was rated as Very Satisfactory (100% of teachers received this rating.) In addition, the results demonstrated that coping mechanisms do not mediate contentious between mental health challenges and teacher performance, since the mean indirect effect of coping mechanisms on mental health and teacher performance results is nonsignificant (estimate = 0.00205, p = 0.376) and therefore does not support the existence of a mediating relationship. Furthermore, the relationship between coping mechanisms and mental health challenges to teacher performance is nonsignificant, therefore, there are no significant conditions necessary to support a mediating relationship. Therefore, even though teachers may have an abundance of challenges and difficulties, they may have overcome them with the need for coping strategies. Teachers are truly amazing in how they handle challenges and maintain their composure when faced with challenging situations. Further based on the findings of this investigation, it is the recommendation of the researcher for continuous professional development, ongoing peer-consultation and teacher activities to help promote the mental health and wellness of teachers.
Alimi Taofeek, Salami Jennifer U.
This study assessed and analysed microbes and heavy metals in fresh raw meat (heart, stripes, liver and kidney) of cow, goat and ram from abattoirs and retail stalls in Kawo and Kontagora, Niger State, to ensure safety and quality of meat products. Meat, a good source of basic nutrients needed by the body, is influenced by the level of its nutritive value, pH, water, temperature, storage and processing methods, which predispose it to microorganism’s growth and heavy metals presence. Parts of beef, chevon and mutton (n = 48) were randomly selected and collected at every visitation, into sterile polythene bags with ice packs and transported to the laboratory for microbiological and heavy metals analyses. Micro-organisms analyses were carried out using nutritive MacConkey, Mannitol salt, Salmonella–Shigella (SS) and Potato dextrose agar as standard procedures for enumeration and identification. Laboratory quality control procedures were ensured. The total viable counts of meat samples showed microbial contamination. The overall mean microbial load (TBC) was between 36.0 – 42.5 x 10 2 cfu/g and 14.25 – 15.5 x 102 cfu/g for meat sampled in Kawo and Kontagora respectively. TCC was at 6.5 – 16.25 x 102 cfu/g in Kawo and 2.0 – 7.0 x 102 cfu/g in Kontagora. The TBC in sampled meat from Kawo was significantly higher than Kontagora. A total of 12 isolates belonging to 8 genera were identified, including Staphylococcus aureus, which was dominant in both locations (18.51 %). Salmonella typhi isolate was similar (3.7 %) for both locations. The meat parts studied revealed the presence of all the heavy metals examined in the range 0.00 – 120.96 mg/kg irrespective of sampling location and meat parts. Zn in cow heart and tripe, Cu in cow tripe and Mn in all the cow parts were below detection while Fe recorded the highest concentrations (84.11 – 120.96 mg/kg), followed by Mn (0.00 – 1.70 mg/kg) in all meat samples. Pb, Cd, Zn, Cu, Cr and Ni recorded values < 1.00 mg/kg. All meat samples showed microbial contamination within the satisfactory and borderline levels as well as heavy metals levels below the recommended allowable limits set by the standard organisations. Among others, it is recommended that abattoir practices and meats from retail stalls should be regularly monitored to ameliorate meat safety for public consumption.
James L. Paglinawan, Roselyn U. Doletin
This qualitative study investigated the teaching challenges faced by Millennial teachers when teaching Generation Z learners at Banisilan High School, a rural public high school in Cotabato, Northern Mindanao. Through Google Forms questionnaires completed by 15 Millennial teachers in February 2026, the research identified key difficulties: students' short attention spans (typically 8-12 minutes), heavy technology dependence, strong preference for interactive lessons, and consistent need for guided emotional support. Teachers described clear differences between their traditional lecture-based methods and students' digital, fast-paced learning preferences. The findings highlighted practical teaching strategies that worked well, including short digital lessons (8-12 minutes), relatable real-life examples, clear step-by-step guidance, and consistent supportive feedback. Despite limited internet access in rural settings, these teachers showed strong ability to adapt using simple, effective, low-tech methods. Ultimately, the study offers clear, actionable recommendations for accessible digital tools, student-centered professional training, and collaborative team lesson planning to significantly improve classroom engagement in similar rural Philippine schools nationwide.
Christopher Kabwe Mukuka
The emergence of post-secular societies-where religious and secular worldviews continue to coexist and interact in public life, rather than religion simply fading away-demands a fresh look at Christian leadership. Instead of merely maintaining institutions, leadership today needs to involve the whole faith community in what theologians call the missio Dei (Latin for "the mission of God"), the conviction that mission is first and foremost God’s own activity, into which the church is invited to participate. This study examines that challenge through a case study of the Seventh-day Adventist (SDA) Church in Eastern Zambia, a region with about 59,000 members spread across a vast and culturally diverse area stretching from the Luangwa Bridge to Chama District. Using a sequential mixed-methods design, the research first builds a theological framework from Trinitarian and missio Dei thinking, and then tests it against real-world data gathered through semi-structured interviews with church administrators, pastors, and lay leaders, alongside participant observation and document analysis. The findings reveal three critical dynamics: 1) a tension between inherited top down structures and the practical needs of contextual mission; 2) the role of communal, Sabbath-centred discernment as a space where authority can be shared; and 3) the strategic use of digital platforms to coordinate mission across great distances in a network with multiple centres of initiative. The study concludes by proposing a Contextual-Trinitarian Participatory Model for missional leadership, arguing that sustainable leadership in complex post-secular settings requires a theologically grounded commitment to kenotic vulnerability (a leadership posture modelled on Christ’s self-emptying, where leaders willingly relinquish control and power for the sake of others), communal praxis (the whole church thinking and acting together), and structural adaptability (systems that bend to support mission, not block it).
Al-Harath Ateik, Zayyanu Najeeb
This study investigates the effect of work pressure on employee withdrawal behaviors, with particular emphasis on the mediating role of perceived organizational support (POS). Drawing on a quantitative cross-sectional design, data were collected from 417 employees across diverse organizational settings. Statistical analyses were conducted using the Statistical Package for the Social Sciences (SPSS), including descriptive statistics, correlation, regression, and mediation analysis. The findings indicate that work pressure significantly increases withdrawal behaviors, including absenteeism, lateness, and turnover intentions. In contrast, job satisfaction, empowerment, and perceived organizational support significantly reduce these negative outcomes. Importantly, perceived organizational support was found to partially mediate the relationship between work pressure and withdrawal behaviors, highlighting its buffering role. These findings extend existing literature by demonstrating how organizational support mechanisms function as critical resources in mitigating the adverse effects of workplace stress. The study provides practical insights for organizations seeking to enhance employee well-being and reduce disengagement.
Aftab Khan, Amit KumarAhirwar, Atul kumar, Divya Patel, Farman Hussain, Iffat Hussain, Rishabh Tiwari
Drug discovery is a complex, time-consuming, and costly process that requires the identification and optimization of potential therapeutic compounds. In recent years, computational approaches such as molecular docking and molecular dynamics (MD) simulation have significantly transformed modern drug design. These techniques, which fall under the domain of Computer-Aided Drug Design (CADD), provide efficient and cost-effective strategies for analyzing molecular interactions and predicting drug behavior.Molecular docking is widely used to predict the binding orientation and affinity of ligands toward target proteins, thereby facilitating the identification of promising lead compounds. On the other hand, molecular dynamics simulation provides detailed insights into the structural flexibility, stability, and dynamic behavior of biomolecular systems under physiological conditions. Additionally, structure-based and ligand-based drug design approaches further enhance the efficiency of identifying and optimizing drug candidates.The integration of molecular docking with MD simulation has emerged as a powerful strategy, combining the speed of docking with the accuracy of dynamic simulations. This combined approach improves the reliability of predicting protein-ligand interactions and reduces the need for extensive experimental validation. Overall, these computational tools play a crucial role in accelerating the drug discovery process, minimizing costs, and enhancing the success rate of developing effective therapeutic agents.
Joan P. Bacarisas, Kessah Ranah O. Morales
This study determined the level of moral competence and the extent of missed nursing care among clinical nurses in a Level II government hospital and examined their relationship with selected demographic characteristics. A descriptive–correlational design was used involving 205 clinical nurses through complete enumeration, utilizing the Moral Competence Questionnaire (MCQ) and the MISSCARE Survey, with data analyzed using descriptive statistics, Chi-square, and Pearson r. Results showed that nurses had a high level of moral competence and a very low frequency of missed nursing care, although organizational factors such as staffing, resources, and communication contributed to missed care. Demographic characteristics were significantly related to moral competence and missed nursing care, and moral competence was significantly associated with the extent of missed nursing care. The findings emphasize the importance of ethical competence and supportive organizational conditions in maintaining quality nursing care.
Eladraoui Mourad
This study aims to explore Moroccan EFL high school students’ perceptions of a flipped process-genre writing model based on the conceptual framework proposed by Eladraoui and Sakale (2025), focusing on learner autonomy and pre-class preparation, engagement, perceived effectiveness, and perceived challenges. A quantitative descriptive research design was employed. Forty-two second baccalaureate students from AlMansour Eddahbi High School voluntarily participated in a four-week implementation consisting of one-hour sessions per week conducted outside their regular school timetable during the first semester of the 2025-2026 academic year. In the pre-class phase, instructional input was delivered through the online platform TopWorksheets , while in-class time was devoted to higher order writing activities. Data was collected using a five-point Likert scale questionnaire and analysed using descriptive statistics. The results revealed strong learner support of the approach, particularly in terms of learner autonomy, perceived engagement, and perceived effectiveness. However, few students reported some challenges related to technology, motivation, and adaptation. This study contributes exploratory on its acceptability and feasibility of the flipped process-genre writing model in Moroccan EFL secondary education, emphasising learner perceptions rather than performance outcomes.
Aprell L. Abellana, Benzly Ralph D. Amorio
This study examined the influence of teachers’ motivation and engagement on teaching efficacy among public school teachers in the Division of Valencia City, Bukidnon, Philippines during School Year 2025–2026. Specifically, it examined the level of teachers’ motivation in terms of enjoyment, performance, and importance; the level of teachers’ engagement in terms of shared values, feedback and recognition, and career growth and training opportunities; the level of teacher efficacy; the significant relationships among motivation, engagement, and teacher efficacy; and the variables that significantly predicted teacher efficacy. The respondents of the study were public school teachers from selected schools in the division. The study employed a descriptive–correlational research design, using validated survey instruments as the primary data‑gathering tools. Statistical treatments included mean and descriptive statistics to determine levels of variables, Pearson product‑moment correlation to test relationships, and multiple regression analysis to identify significant predictors of teacher efficacy. Results revealed that teachers demonstrated high levels of motivation, particularly in enjoyment, performance, and importance, and high levels of engagement across shared values, feedback and recognition, and career growth and training opportunities. Teachers also exhibited a high level of teaching efficacy, reflecting strong confidence in classroom management, instructional practices, and learner interaction. Correlation analysis showed that both motivation and engagement have significant positive relationships with teacher efficacy, with engagement showing a stronger association. Regression analysis indicated that motivation and engagement are predictors of efficacy of teachers. The findings of the study indicated that, while teachers’ intrinsic motivation provides the foundation for effective teaching, active engagement plays a more critical role in strengthening teaching efficacy. Moreover, DepEd officials and school administrators may prioritize structured and sustained teacher engagement programs to allow teachers to gain mastery experiences and professional support, improving instructional quality and learning outcomes in public schools.
Adebayo Ademola Riliwan, Aweda Olusina Temidayo, Chidozie Ifeanyi Evans, Obansola Oluwatoyin Yemi
Eye diseases such as cataract, glaucoma, and diabetic retinopathy are major causes of blindness worldwide, underscoring the critical need for early and accurate diagnosis. This study presents a novel approach to multi-class eye disease prediction using an ensemble of Convolutional Neural Networks (CNNs) combined with a max voting strategy. The framework integrates four CNN models with varying architectural depths, each trained on a curated dataset of retinal fundus images, to classify eye conditions into four categories: cataract, glaucoma, diabetic retinopathy, and normal. The methodology begins with data pre-processing, which includes resizing, normalization, and augmentation to ensure robust model training. Each CNN model, ranging from six to nine layers, was trained independently for 60 epochs, leveraging techniques like dropout and regularization to prevent overfitting. The models' outputs were aggregated using a bagging ensemble technique, with final predictions determined through max voting. The ensemble approach effectively combines the complementary strengths of the individual models, enhancing classification reliability. Experimental evaluations demonstrate that the ensemble achieves superior performance, with an average accuracy of 92%, precision of 92%, recall of 91%, and F1-score of 92%. This study highlights the potential of combining deep learning with ensemble strategies for improved diagnostic accuracy in medical image analysis. By offering a scalable and reliable tool for early detection of eye diseases, this research contributes to advancing automated healthcare diagnostics, aiming to reduce the global burden of vision-related diseases and improve patient outcomes.
Dr. Jasoda Vishnoi, Dr. Jyoti Choudhary
Setting up a NABL (National Accreditation Board for Testing and Calibration Laboratories) compliant laboratory within an academic institution is a prerequisite for quality assurance, standardisation, research credibility and competency in the diagnostic and testing services. The laboratory library and documentation system of the medical and allied health colleges is highly essential to fulfil the standards of ISO 15189 and NABL accreditations. This article describes the basic structural requirements, documentation procedures, quality management system, manpower, validation of equipment, standard operating procedures (SOPs), internal audits, library resource management to establish NABL ready laboratory in college set up. The report also emphasises the necessity of ongoing quality improvement and accreditation benefits in academic health care facilities.
Ajay R. Wagh, Avinash M. Patil, Bhushan T. Gopal, Dr. Bhupendra R. Patil, Vasant Y. Chavan
Naringenin, a naturally occurring flavonoid mainly present in citrus fruits, has attracted considerable scientific interest due to its diverse pharmacological and therapeutic properties. It exhibits significant antioxidant, anti-inflammatory, anticancer, antidiabetic, antimicrobial, antiviral, hepatoprotective, cardioprotective, and neuroprotective activities through its interaction with multiple cellular and molecular targets. The unique chemical structure of Naringenin contributes to its broad spectrum of biological effects, making it a promising candidate for the management of various chronic and metabolic disorders. However, its clinical application is greatly restricted because of poor aqueous solubility, limited permeability, extensive first-pass metabolism, and low oral bioavailability. To overcome these limitations, several advanced drug delivery systems, including polymeric nanoparticles, liposomes, solid lipid nanoparticles, nanosuspensions, and self-nanoemulsifying drug delivery systems, have been developed to enhance its stability, bioavailability, and targeted delivery. Although these nano formulations improve therapeutic efficacy, concerns regarding toxicity, safety, dosage optimization, and long-term clinical use remain important considerations. This review provides a comprehensive overview of the chemistry, pharmacokinetic profile, bioavailability challenges, pharmacological activities, and novel drug delivery approaches of Naringenin. In addition, recent clinical investigations and future perspectives for its therapeutic application are also discussed.
Jai Singh
The subject work has provenance as originating as an example that was considered, by the subject author, for inclusion in a different work, which was focused primarily upon a philosophical context. A portion of the latter serves as introductory for this work. Specifically, a position of metaphysical and ontological realism is coupled with a position of epistemic humility. This is applied to science, as an ideal episteme, characterized by a method for which Popperian falsification is a key component. Korzybski’s cartographic analogy and Box’s characterization of models are coupled to the perspective that every symbolic system, whether it be natural language, formal logic or mathematics, involves assumptions, stated or otherwise, in regards to that which is or is not considered as being within the domain of reality. Hawking’s claims regarding the (premature) death of philosophy and the role of scientists as the (purported) torch bearers in the quest for knowledge is evaluated in the general context of astrophysics and cosmology, and specifically in regards to the use of standard solar models (SSMs). Key to this evaluation are the modeling assumptions that are typically made not only in regards to equations of state and process relationships but also in regards to observations. Rather than finding facts, one finds models that are rendered to be unfalsifiable secondary to the use of tunable parameters, claims that fail to meet a reduced standard of verification, model based circularity and observations that are heavily model-laden in regards to their filtering.
Dr. R. Srikala, Ms. K. M. Anitha
The study examines the impact of Iran war–induced crude oil price shocks on the Indian stock market. Using time-series data and econometric techniques such as ADF, regression, GARCH, and event study analysis, the study evaluates the relationship between oil prices, stock returns, exchange rate, inflation, and capital flows. The findings reveal that rising crude oil prices negatively affect stock market performance and increase market volatility during periods of geopolitical uncertainty. The study highlights the vulnerability of the Indian economy to external oil shocks due to its heavy dependence on crude oil imports.
Dr. Prithwi Jyoti Bhowmik
The prevailing paradigm in analyzing the recurrence intervals of extreme climate events – such as heat-waves, floods, and droughts – relies on stochastic frameworks, including Extreme Value Theory (EVT) and Poisson progress, which presuppose inherent randomness. This paper explores whether low-frequency quasi-periodic climate forcings may introduce weak arithmetic structure into the recurrence statistics of extreme events, superimposed upon an inherently stochastic-chaotic climate background. We propose a novel theoretical model wherein the temporal sequencing of extreme events, under the influence of persistent multi-scale nonlinear forcings (e.g., orbital cycles, ocean-atmosphere oscillations), exhibits hidden number-theoretic patterns. By formulating climate preconditioning as an almost periodic function, we demonstrate that recurrence intervals can cluster around values defined by arithmetical sequences, Diophantine approximations of coupled oscillation periods, and solutions to modular congruences. The core contribution is a formal theorem on the existence of “Arithmetical Recurrence Windows”, providing a semi-deterministic modulation framework for the observed phenomenon of quasi-periodic clustering. This work establishes a pioneering, interdisciplinary bridge between analytic number theory and climate, dynamics, proposing a new diagnostic framework for extreme events timing with potential implications for long-term risk assessment. To render the framework falsifiable, we propose empirical testing against observational and paleoclimate datasets using recurrence interval statistics, surrogate stochastic simulations, and comparisons with Extreme Value Theory (EVT), autoregressive processes, and self-exciting point-process models. The theory predicts statistically enhanced recurrence intervals near denominators of continued-fraction convergents of dominant oscillatory modes, rather than exact deterministic event timing.
Akemu Andrew, O., Eghe Amenze Oyedoh, Obahiagbon Kessington
A renewable alternative to petroleum fuels is essential due to declining oil supplies. Bio-based diesel production from fruit peels and vegetable oil waste may reduce reliance on petroleum. Various materials, including oyster shells, rocky clay, and plantain peels, were identified as potential resources, used for developed bifunctional catalysts, utilized in heterogeneous catalyst transesterification. The catalyst's stability and characteristics were evaluated using thermogravimetric analysis (TGA) and differential thermal analysis (DTA). High surface area analysis through Brunauer-Emmett-Teller (BET) and various adsorption isotherms indicated its effectiveness. The catalyst primarily consisted of calcite, along with minerals like muscovite, orthoclase, and quartz, as confirmed by X-ray diffraction (XRD). Fourier Transform Infrared Spectroscopy (FTIR) revealed metal-oxide bonding, C=C stretching, and hydroxyl groups. Energy dispersive X-ray spectroscopy demonstrated that CaO constituted 66.194%, with K₂O and Al₂O₃ also present. Scanning electron microscopy (SEM) highlighted the catalyst's shape and porosity, confirming its potential for serial reuse. The optimized heterogeneous catalyst transesterification of shea nut oil resulted in ideal conditions: 5 wt% catalyst loading, 65°C reaction temperature, 8:1 methanol-to-oil molar ratio, 70-minute reaction time, and a biodiesel yield of 92.68%. Characterization showed that the produced biodiesel met key diesel fuel properties and conformed to ASTM D-675 standards. Gas chromatography/mass spectroscopy (GC/MS) analysis indicated that the biodiesel contained predominantly methyl esters, achieving 99.57% with minimal impurities, making heterogeneous catalyst transesterification a cost-effective and scalable method for biodiesel production.
Ehusani, R., Martin A. Bello, Ominiyi, A.O.
This study evaluated the level of psycho-spiritual well-being among students staying in Catholic secondary school boarding within the Catholic Diocese of Osogbo. The study was firmly fastened on the Psycho-Spiritual Theory of Pius Joyzy Egunjobi and Attachment Theory (Bowlby, 1969), which underscore the importance of spiritual development and emotional bonding in well-being of human. Convergent parallel mixed-method research design was adopted in this study. Data were collected from 67 boarding students across four Catholic secondary schools using the Psycho-Spiritual Well-Being Scale (P-SWBS). Additionally, a purposive sample of five students participated in semi-structured interviews which provided deeper insights. Quantitative data were analysed using descriptive statistics with SPSS, while qualitative data were transcribed and analysed using thematic analysis to identify recurring patterns and themes. The findings of this study revealed that boarding students displayed a moderate level of psycho-spiritual well-being across key dimensions such as self-awareness, connectedness, meaningfulness, compassion, and self-transcendence. Findings from qualitative analysis showed that students experienced emotional challenges, such as loneliness, sadness, and difficulty adjusting to boarding life. In the face of these challenges, students adopted different coping strategies, with spiritual practices such as prayer, participation in Mass, and confession emerging as the most dominant. Social support from peers, teachers, and school chaplains also played important role in helping students manage emotional distress. The study concluded that psycho-spiritual well-being among boarding students is sustained by strong coping mechanisms and support systems. Based on these findings, the study recommended that school-based counselling services should be strengthened, spiritual and pastoral care programs enhanced, peer support systems promoted, and further longitudinal research conducted to better understand long-term effects.
Abbad Mohamed, Dr.Sonia Kapur
The emerging athletes often faced significant pressure to maintain optimum levels of mental skills, which affected their performance. The study aimed to find out the difference between state- and national-level athletes in passion, emotional intelligence, and conflict management. The research was conducted on 184 university athletes, aged 18–25, from diverse sporting disciplines, including state- and national-level athletes. The Passion Scale, Sports Emotional Intelligence Test, and Thomas–Kilman Conflict Mode Instrument were utilised as measurement tools. The mean, standard deviation, and t-value were computed. The results of the study indicated that there were significant relationships between certain components of passion, emotional intelligence, and conflict management styles. The findings also revealed significant differences between state- and national-level athletes in obsessive passion, passion criteria, compromising conflict management style, and emotional intelligence. National-level athletes were found to have higher emotional intelligence, obsessive passion, and passion criteria, whereas state-level athletes reported higher use of the compromising style of conflict management.
Ezeokafor, F. D., Mukarugwiza, X, Okpalaenwe, E. N.
This study examined pastoral stress and psychological resilience among Catholic priests in Ondo Diocese, Nigeria. The objectives were to explore the primary sources of pastoral stress, assess levels of psychological resilience, and determine the relationship between pastoral stress and psychological resilience among priests of Ondo Diocese, Nigeria respectively. The study was anchored on the Transactional Model of Stress and Coping as well as Richardson’s Metatheory of Resilience and Resiliency theories. A correlational design was adopted, where 103 priests were selected using simple random sampling based on Yamane’s formula. Data was collected through adapted questionnaire using Google Form. Descriptive statistics (mean and standard deviation) and Pearson’s correlation were used for analysis. Findings revealed a moderate level of pastoral stress (M = 2.90, SD = 0.57) and a high level of psychological resilience (M = 4.50, SD = 0.40) among priests in Ondo Diocese. The relationship between pastoral stress and psychological resilience was negative but not statistically significant (r = −.164, p = .097). The study recommended that: Diocese of Ondo should ensure regular psychological evaluation of priests to determine their level of stress and administer appropriate remedy; that appropriate spiritual, social, economic and psychological support be rendered to priests to enhance their resilience; that institutions for priestly formation should educate their students on sources of stress and coping mechanisms to familiarize the priests and enable them cope with the daily demands of their pastoral roles. Future researchers should consider: longitudinal studies on stress and pattern of resilience among priests; comparative study on the lived pastoral experiences of priest in urban and rural areas.
Abdulmajid Khalil AL-Juaid, Dr. Jon-Jon T. Martinez, Ghazi Fayez AL-Qathami, Khaled Eid AL-Sufyani, Mamdouh Nayef AL-Harthi, Rawaf Muteb AL-Otaibi, Sultan Fayz Al-Harthi, Wesam Ali AL-Shamrani
This study examined the perceptions of nursing students at Taif University toward mental health nursing as a career path. Anchored on Ajzen’s Theory of Planned Behavior, the study sought to describe students’ perceptions in terms of professional image, perceived competence and preparedness, career opportunities and advancement, emotional demands and workplace safety, and personal interest and willingness to specialize. It also determined the relationship and differences in students’ perceptions when grouped according to selected demographic and academic variables. A quantitative descriptive-correlational research design was used. The respondents were 286 undergraduate nursing students from different academic levels at Taif University. Data were collected using a researcher-developed questionnaire and analyzed using descriptive statistics, correlation, t-test, ANOVA, and multiple regression analysis. Findings revealed that the respondents generally had a positive perception of mental health nursing as a career path, with an overall mean of 3.48. Among the perception domains, professional image obtained the highest mean, while emotional demands and workplace safety received the lowest rating. Previous exposure to mental health clinical settings, academic level, and overall intention were significantly related to students’ perceptions. Students with previous mental health clinical exposure had significantly more positive perceptions than those without exposure. Regression analysis further showed that professional image, perceived competence and preparedness, career opportunities, emotional demands and workplace safety, previous exposure, and academic level significantly predicted students’ intention to pursue mental health nursing, while gender was not a significant predictor. Based on the findings, the study recommends the development of a mental health nursing career enhancement program focusing on early exposure, simulation-based learning, mentorship, reflective activities, and career orientation. The study concludes that strengthening students’ confidence, clinical readiness, and awareness of career opportunities may improve their willingness to consider mental health nursing as a future specialization.
Asmin Baraka, Kahu H. Wachira
Technical and Vocational Education and Training (TVET) has consistently failed to produce competent graduates with the skills necessary for self-reliance, despite significant reforms spanning both the colonial and post-colonial periods. This paper critically examines the philosophical foundations that have informed TVET reforms across these periods, with the aim of enriching future reform efforts based on 21st-century progressive education theory. The study was guided by two objectives: To examine the concept of TVET reforms in Kenya, and to identify gaps in the philosophical foundations underpinning those reforms. The findings revealed that colonial-era reforms dismantled the sound philosophical foundations of traditional vocational education to serve colonial, political, social, and economic interests primarily to subdue Africans, extract cheap labour, promote missionary interests, and encourage self-sustainability. Following independence, post-colonial reforms prioritised literary education over vocational training in order to appease Africans and enable them to assume white-collar roles vacated by departing colonialists, thereby undermining gains made during the colonial period. Efforts in the 1980s to promote self-reliance through vocationalization were short-lived by the close of the 1990s. From the mid-2000s onward, renewed efforts to strengthen TVET have sought to align it with lifelong learning and self-reliance, as inspired by Vision 2030. While the introduction of a Competency-Based Curriculum provided a more progressive foundation and emphasised equipping learners with workplace and entrepreneurial skills, implementation challenges persisted, including inconsistent content and weak alignment with infrastructure and teacher training.
Reyzamae Doblas Sagandilan
This study examined the effectiveness of Physics Education Technology (PhET) simulation-assisted instruction on students’ academic achievement and motivation in electromagnetism. A quasi-experimental quantitative design was employed involving second-year Bachelor of Secondary Education major in Science students, with one group exposed to PhET-integrated instruction and another taught using traditional methods. Academic achievement was measured through pretests and posttests, while motivation was assessed using a validated questionnaire covering intrinsic motivation, amotivation, extrinsic–career motivation, and social–extrinsic motivation. Results revealed that both groups initially demonstrated very low academic achievement, with most students classified under the failure category during the pretest. After the intervention, the PhET group exhibited a marked improvement, with all students attaining good to very good performance levels and no failures recorded. In contrast, although the non-PhET group showed some improvement, the majority of students remained at a satisfactory level. ANCOVA results indicated a statistically significant difference in posttest academic achievement between the two groups when pretest scores were controlled (p < 0.01), favoring the PhET simulation-assisted instruction. In terms of motivation, students in the PhET group demonstrated higher levels across all motivational dimensions compared to those in the non-PhET group. Overall motivation for the PhET group was interpreted as motivated, while the non-PhET group displayed lower motivational levels. Independent samples t-test results confirmed a statistically significant difference in overall motivation between the groups (p < 0.001). These findings suggest that integrating PhET simulations into physics instruction significantly enhances both conceptual understanding and student motivation in electromagnetism.
Almahden C. Lumidseg, Lyanne T. H. Jover, Roden C. Yumol
Cancer is the second leading cause of mortality worldwide. Over 10 million new patients are diagnosed with cancer annually with over 6 million associated deaths, representing roughly 12 percent of worldwide mortality. The occurrence of new cancer cases is expected to grow by about 70 percent over the next two decades and estimated to reach over 15 million new cases diagnosed annually by the year 2020. This study investigated the anti-angiogenic, cytotoxic activity, anti-inflammatory property, and antioxidative property of Barringtonia asiatica (Buro bitoon). Ethanolic extracts of Barringtonia asiatica fruit and leaves were subjected to phytochemical screening and qualitative chemical analysis revealed the presence of alkaloids, flavonoids, saponins, phenols, and tannins. Test for angiogenesis revealed a strong pro-angiogenic property of ethanolic extract at 1000 mg and 500 mg. Median lethal concentrations were found to be 147.91 and 338.84 for the leaves and the seeds, respectively. LC50 of the extracts were higher than the 20 microgram per milliliter limit, this implies that the extract can have minimal toxicity toward human body cells. Leaves and seed extracts of Barringtonia asiatica have demonstrated anti- inflammatory properties comparable to the positive control which suggests that it has potential to act as an alternative anti-inflammatory agent. Evaluation for antioxidant property of the leaf extract exhibits an IC50 value of 379.6 µg/ml while the seed extract exhibits an IC50 value of 363.58 µg/ml. Results demonstrated the bioactive property of the Barringtonia asiatica can be a possible natural chemotherapeutic drug in battling cancer which can serve for future pharmacological use.
Ajay B. Kurhe, Anita J. Shinde
Early and accurate detection of plant leaf diseases plays a vital role in improving crop productivity and ensuring sustainable agriculture. This paper presents a deep learning-based framework for multi-class classification of banana leaf diseases using transfer learning. Initially, a baseline model based on ResNet50 is developed to evaluate standard performance. To enhance classification accuracy and computational efficiency, a transfer learning approach employing EfficientNetV2 is proposed. The pretrained EfficientNetV2-S model is fine-tuned by integrating a custom classification head comprising global average pooling, dropout, and fully connected layers. The proposed model is trained and validated on a dataset containing four classes of banana leaf images, namely Cordana, Healthy, Pestalotiopsis, and Sigatoka. Experimental results demonstrate that the proposed approach achieves an overall accuracy of 95%, along with high precision, recall, and F1-score across all classes. The confusion matrix and training curves further confirm the robustness, stability, and generalization capability of the model. Comparative analysis indicates that the proposed EfficientNetV2-S-based framework outperforms the baseline ResNet50 model while maintaining reduced computational complexity. To further evaluate practical applicability, the proposed model was tested on real-world banana leaf images captured under natural field conditions. The model achieved a detection accuracy of 76.19%, demonstrating its robustness and ability to generalize effectively beyond controlled datasets. The results show that the proposed framework provides an efficient and scalable solution for real-world plant disease detection in precision agriculture. Future work will focus on expanding dataset diversity and exploring advanced architectures to further improve classification performance.
Dharunesh Balasubramaniam Gopalakrishnan, Divya Nithiya, Prathiba Rex, Priyanka Murali
The transformation of biomass into high-value materials presents a promising solution for sustainable development. Accurate prediction of material properties based on biomass composition and processing parameters is critical for optimizing production efficiency and product quality. This study explores the application of multiple machine learning algorithms— Linear Regression, Decision Tree, Random Forest, and Support Vector Regression (SVR)—to predict material characteristics derived from biomass inputs such as cellulose, lignin, hemicellulose content, pulping time, and energy consumption. A dataset based on experimental values was used to train and evaluate the models. Among the tested approaches, the decision tree model showed the highest prediction performance (R² = 1.000); however, the limited dataset size may have contributed to possible overfitting followed by Linear Regression (R²= 0.987) and Random Forest (R² = 0.976), while SVR showed limited performance (R² = 0.081) due to the small dataset size. The results highlight the effectiveness of tree-based and linear models in accurately modeling the complex interactions between biomass composition and processing parameters. This research underscores the potential of machine learning techniques in advancing biomass valorization strategies and optimizing sustainable material production. The study demonstrates the feasibility of machine learning-assisted prediction for biomass-based paper production, while highlighting the need for larger datasets and industrial-scale validation.
Asha Munemo, Samkeliso Suku Dube, Tinahe Peswa Dube
This research focused on a machine learning technique ( XGBoost – Extreme Gradient boosting), Transformer models (all-MiniLM-L6-v2 a sentence embedding model developed by Microsoft) based system for proactive network monitoring, performing log analysis for real-time anomaly detection and pattern analysis for root cause evaluation. This was done in order to address the challenge of reacting to problems only after they occur which leads to business revenue loss and increased idle time for workers when business operations are disrupted. The system makes use of the online NLP (natural language processing) model specifically (OPENAI or Cohere), which are inferred for intelligent problem explanation and solution recommendation. The methodology used was CRISP-DM for Data Science and incremental software methodology. The system enables network administrators to identify emerging problems within the network and address them pro-actively through system provided recommendations and anomaly evaluation insights before full negative impact on business operations.
Dr. Mukta Kumari
Cancer is one of the most serious public health problems affecting millions of individuals worldwide. Along with physical suffering, cancer patients experience significant psychosocial stress, financial burden, social isolation, and behavioral changes. One of the major concerns observed among patients undergoing long‑term treatment is the growing practice of self‑medication. The present empirical study was conducted at Mahavir Cancer Sansthan, Patna, Bihar, to examine psychosocial challenges and self‑medication practices among cancer patients from different socioeconomic backgrounds. The study used a descriptive and analytical research design. Data were collected from 120 cancer patients through a structured interview schedule and questionnaire method. Findings revealed that depression, anxiety, fear of death, financial insecurity, social stigma, and treatment stress were common among respondents. A large number of patients also reported self‑medication practices for pain relief, fever, weakness, digestive problems, and sleeping difficulties. Self‑medication was found to be more common among economically weaker and less educated patients. The study highlights the urgent need for psychosocial counseling, public awareness, affordable healthcare services, and strict monitoring of irrational medicine use among cancer patients.
Prof. A. Abdul Wahab, BSc., MBBS, MSc., PhD., Prof. M.I.A Saleh, MBBS, MSc., PhD., R.L. Mangbon BSc., MSc., PhD, S.L. Mangbon, BSc., MSc., PhD
Constipation is a digestive tract disorder that can cause painful, stiff, and infrequent stools as well as difficulty in passage of the stool. The intestines may close as a result of acute constipation, necessitating surgery. Constipation is one of several ailments that plants have long been used as a source of medicine. In loperamide-induced constipated wistar rats, the current study evaluated the purgative activity of Securidaca longepedunculata root bark aqueous extract by measuring the peristaltic index after 30 minutes of meal administration. The gastric emptying effect of the extract was also evaluated by determining the weight of the meal emptied by the rat within 1 hour period after meal administration. For each objective, twenty-five animals (5 constipated and 20 non-constipated) were selected and randomly divided into five groups of five rats each. They were treated with 5, 10, and 20 mg/kg of the aqueous extract via i.p. injections, and 5 ml/kg of normal saline was administered to normal and constipated control groups. The study revealed a significant (p<0.05) increase in intestinal length covered by administered meal in the S. longepedunculata extract treated group at 5 mg/kg (65.00±1.58cm), 10 mg/kg (59.80 ± 3.24cm) as compared to the constipated group (14.80 ± 1.77cm). Similarly, there was a significant increase in intestinal length covered by administered meal at 20 mg/kg (73.80 ± 1.53) as compared to normal (61.00 ± 3.93cm) and constipated control groups (14.80 ± 1.77cm) respectively. The percentage intestinal length covered by administered meal was also significantly (p<0.05) increased in the S. longepedunculata extract treated group at 5 mg/kg (74.60 ± 2.78%), 10 mg/kg (67.63 ± 1.06%) as compared to constipated group (17.40 ±2.33%). Similarly, there was also a significant increase at 20 mg/kg (83.20 ± 2.95%) compared to normal (70.00 ± 4. 60%) and constipated control groups (17.40 ±2.33%). Gastric meal emptied was significantly (p<0.05) increased in the S. longepedunculata extract treated group at 5 mg/kg (5.42±0.11g), 10 mg/kg (5.10 ± 0.20g) compared to normal (3.48 ± 0.18g) and constipated control groups (2.18 ± 0.22g); and the 20 mg/kg (3.88±0.17) as compared to constipated control group (2.18 ± 0.22g). Meal weight in stomach was significantly (p<0.05) decreased in the S. longepedunculata root-bark aqueous extract treated group at 5 mg/kg (1.78±0.11g), 10 mg/kg (2.10±0.20g) compared to normal (3. 62±0.16g) and constipated control groups (5. 02±0.22g); and 20 mg/kg (3.42±0.16) as compared to constipated control group. (5.02±0.22g). It was therefore concluded that graded doses (5 mg/kg, 10 mg/kg, and 20 mg/kg) of S. longepedunculata aqueous root-bark extracts are effective purgatives in albino Wistar rats and might have therapeutic potential in the management of bowel emptying disorders.
Stephen Sunday Browne
This study examined the impact of library services on the academic achievement of undergraduate students at African Methodist Episcopal University (AMEU) in Monrovia, Liberia. Using a structured questionnaire (N = 82), the study investigated student awareness of library services, usage patterns, perceived academic effects, and access barriers. Results indicated near-universal recognition of the AMEU library (98.8%), with the quiet study environment identified as the most frequently used service (M = 3.84 on a five-point frequency scale), followed by group study areas (M = 3.27), internet/Wi-Fi access (M = 2.80), and textbook lending (M = 2.32). A substantial majority of respondents (91.5%) agreed that library use had contributed to improvements in their academic performance. The most commonly reported barriers were an inadequate number of computers (45.1%), insufficient seating capacity (37.8%), limited and outdated print collections (31.7%), and unreliable internet connectivity (28.0%). The study recommends strategic investment in ICT infrastructure, seating capacity, and print collections to fully realize the library's potential as a catalyst for student academic success at AMEU.
Dr. Aparnaa Upadhyaya DDS MPA BDS, Mary Grace Hilario
Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by immune dysregulation and a high prevalence of oral and perioral manifestations that may complicate dental management. Although dental amalgam remains a safe and durable restorative material for the general population, its mercury content and immunomodulatory properties raise specific considerations in patients with underlying autoimmune disease. This case based manuscript examines the scientific and clinical rationale for removal of dental amalgam restorations in a patient with SLE, with particular emphasis on immune susceptibility, oral mucosal findings, and evidence derived from hypersensitivity and autoimmune literature. Current epidemiologic data do not support a causal relationship between dental amalgam exposure and the development of SLE; however, selected patients may exhibit heightened immune responsiveness or localized oral reactions that warrant individualized clinical intervention. By integrating existing evidence with common oral examination findings, this report provides a balanced, evidence based framework for clinicians considering amalgam removal as an adjunctive strategy in the dental management of patients with SLE.
Dr. R. Preethi, Suresh Kumar. S.
The persistent gap between graduate capabilities and contemporary software engineering practice continues to challenge academia and industry despite decades of curricular reform. Traditional models of software engineering education often emphasize plan-driven processes, narrow technical skills, and project-centric thinking that do not fully align with agile, product-centric, and cross-functional modes of real-world software development. This paper proposes an updated interpretation of the classic 4P framework (People, Product, Process, Project) for graduate software engineering education that emphasizes cross-functional team skills, contemporary product design, agile and continuous process models, and a shift from project- to product-oriented thinking. Building on prior work on software process improvement (SPI) in graduate curricula and industry-linked project-based learning, we develop a conceptual curriculum framework and theoretically examine its potential to enhance graduate readiness and support software process improvement outcomes. The study is guided by three research questions: (1) How can the 4P framework be adapted to better reflect current industrial practices in software engineering? (2) To what extent does an updated 4P framework address known gaps in graduate readiness for cross-functional, agile, and product-centric environments? (3) How can such a framework be operationalized in a graduate curriculum to support software process improvement competencies? From these questions, we derive hypotheses about the relationships between the updated 4P elements and graduate readiness for SPI-oriented roles. The paper adopts a conceptual and design-oriented research approach synthesizing literature on SPI in graduate education, cross-functional collaboration, and product versus project mindsets. We present a structured curriculum model aligned to the updated 4P framework and articulate expected learning outcomes, graduate capabilities, and SPI-aligned competencies. The paper concludes with recommendations for implementation, implications for educators and industry, and directions for empirical validation of the proposed framework.
Atty. Dodelon F. Sabijon, Ph. D, Dr Paulino V. Pioquinto, Dr. Esmeraldo Damuag, Dr. Renato C. Sagayno, Dr. Yolanda C. Sayson, Guilbert B. Mansueto
This study explored the lived experiences of Lakan members of the Philippine National Police Academy (PNPA) who were administratively separated from the Philippine National Police (PNP), Bureau of Fire Protection (BFP) and Bureau of Jail Management and Penology (BJMP) and subsequently pursued new career paths within the field of criminal justice and public safety. Specifically, the study examined the experiences encountered by the informants after separation, the strategies they employed in rebuilding their lives and their present outlook toward their new career trajectories. A qualitative transcendental phenomenological approach was used to explore the lived experiences of ten purposively selected Lakan members following their separation from uniformed service. Data were gathered through a Focus Group Discussion with six informants and Individual In-Depth Interviews with four informants in the Visayas region. Using validated semi-structured interview guides, the data were analyzed through horizontalization, thematic clustering and the synthesis of textural and structural descriptions. The analysis generated fifteen emergent themes grouped into three major domains: experiences after administrative separation, strategies for rebuilding new careers and present life outlook. The findings revealed that separation initially resulted in identity disruption, stigma, financial instability and loss of institutional trust. However, through acceptance, discipline, faith, family support, professional networks and the rediscovery of transferable competencies, the informants were able to reconstruct meaningful careers and reaffirm their commitment to public service beyond the uniform. The study concludes that administrative separation, while profoundly disruptive, can become a catalyst for personal growth, resilience and renewed purpose. It recommends the development of reintegration programs, counseling support and alum-based networks within the PNPA and its tri-bureau services to support separated officers in rebuilding productive and dignified lives.
James L. Paglinawan, Novy Mhae C. Ylanan
This quantitative, descriptive–correlational study examined the relationships among resource availability, teaching engagement, and cultural competence among teachers in Indigenous Peoples (IP) schools implementing the Indigenous Peoples Education (IPED) program in the Division of Bukidnon. The study aimed to determine how resource availability and teaching engagement influence teachers’ cultural competence and to identify the strongest predictor. Data were collected through survey questionnaires administered to teachers in IP schools. Descriptive statistics, correlation, and regression analyses were used. Findings revealed a high availability of safety resources and trained personnel, while equipment and digital tools were only moderately available. Teaching engagement was generally high, particularly in terms of job satisfaction and classroom interaction, whereas work–life balance obtained relatively lower ratings. Regarding cultural competence, teachers demonstrated strong competence in student empowerment and the integration of Indigenous knowledge, but lower competence in family engagement and the use of Indigenous languages. Significant positive relationships were found between cultural competence and both resource availability and teaching engagement. Regression analysis identified work–life balance as the strongest predictor of cultural competence. The findings highlight the need to enhance educational resources, professional development, and teacher well-being to strengthen cultural competence and support effective IPED implementation.
Robijit Dutta.
The Right to Education Act, 2009 has come in to force on 1st April 2010. The Act has made free and compulsory education a fundamental right of every child in the age group of 6 to 14 years. The standards for teaching and school infrastructure have been defined by the act. The enforcement of this Right has made it a joint responsibility of Central and State governments to provide free and compulsory education to all children by all means.
Abdullahi Habibu Etsugaie, Adetona Oluwafunmilayo Esther, Aliyu Haruna Sani, Muhammad Tasalla Hauwa
Introduction: Monitoring glucose levels is crucial for effective management of diabetes mellitus, a chronic metabolic disorder that remains a global health concern, implicating over 500 million people worldwide. The diagnosis of diabetes through blood is difficult in children, older adults, debilitated and chronically ill patients, so diagnosis by analysis of saliva can be potentially valuable as collection of saliva is noninvasive, easier and technically insensitive, unlike blood. The aim of the study was to correlate blood glucose level (BGL) and salivary glucose level (SGL) among individuals with normal fasting glucose (NFG), impaired fasting glucose (IFG) and provisional diabetes mellitus (PDM). Methodology: A cross-sectional study was conducted in 423 patients aged between 18 and 65 years, categorised as 141 impaired diabetics, 142 provisional diabetics and 140 healthy individuals constituting the controls. The blood and unstimulated saliva samples were collected from the patients for fasting glucose levels. These samples were then subjected for analysis of glucose in blood and saliva via the enzymatic Glucose Oxidase Peroxidase (GOD-POD) end-point method, using RT-9200 Semi-auto Chemistry Analyser. Results: The mean SGLs and BGLs were higher in provisional diabetics and impaired diabetics groups than in non-diabetic group (3.15:225.40 vs. 2.19:112.43 vs. 0.85:77.76 mg/dL; p-val=1.498852e-153), indicating a significant positive correlation between fasting saliva glucose and fasting blood glucose in all the groups. Conclusion: In conclusion, tests measuring salivary glucose levels provide a promising alternative to conventional blood glucose tests in the realm of diabetes management, making it a reliable indicator. While addressing technical and clinical challenges requires additional research, the appealing non-invasive nature and the potential for frequent monitoring make salivary glucose level tests an attractive option for enhancing diabetes care. Future advancements in salivary glucose sensing technologies may revolutionise glucose monitoring, improving the quality of life for individuals with diabetes.
Geo D. Gutierrez, Jeanethjoy D. Naturales, John Michael D. Catamin, Joshua Andre B. Cervantes, Jude Gabriel L. Salinas, Marielle Nicole G. Silvestre, Mohammad-Rashlanie M. Unda, Rolan Jr. I. Chan, Russel B. Sigales, Wenelyn M. Almonte
The academic registrar’s office manages sensitive student records that require long-term confidentiality, integrity, and rapid accessibility. Traditional manual filing systems are prone to misfiling, physical degradation, and inefficient retrieval, while cloud-based alternatives introduce recurring costs, internet dependency, and data privacy concerns. This study presents the development of an offline-first, Electron-based desktop filing system tailored for the St. Clare College of Caloocan Registrar. The system integrates AES-256-GCM encryption for data-at-rest, SQLite-based metadata indexing for fast offline search, and chunked stream processing to securely handle academic documents up to 2 GB without compromising performance. Employing a mixed-methods approach, requirements were gathered through structured questionnaires and workflow analysis with seven registrar personnel, guiding an iterative software development lifecycle. The application features role-based access control, transparent encryption during upload, secure temporary preview, comprehensive audit logging, local backup/restore, and optional LAN-based sharing via OS-level protocols. Evaluation against documented requirement specifications confirms that the system successfully addresses critical operational gaps, providing a low-cost, connectivity-independent, and institutionally controlled alternative to manual and cloud-dependent solutions. The proposed system demonstrates strong applicability for improving record security, retrieval efficiency, and administrative productivity in resource-constrained academic environments, with direct relevance to Philippine higher education institutions transitioning from paper-based record management.
Joan P. Bacarisas, Myvanwy S. Gide
This study aimed to assess the interrelationship among scheduling practices, absenteeism, and productivity of nurses in a Level II DOH-retained hospital in the Caraga Region. A quantitative descriptive-correlational research design was utilized. A total of 205 nurses were selected using proportionate stratified sampling. Data were gathered using standardized and adapted instruments measuring scheduling practices, nurse productivity, and absenteeism. Statistical tools included mean, standard deviation, and Pearson r to determine relationships among variables. Findings revealed that scheduling practices were generally effective, while nurse productivity was high across all dimensions. Absenteeism was low, with nurses demonstrating strong commitment to attendance. A significant relationship was found between scheduling practices and nurse productivity. However, absenteeism did not show a significant relationship with productivity. The study concludes that effective scheduling practices contribute to sustained nurse productivity, while absenteeism alone may not directly influence performance. The findings highlight the importance of strengthening scheduling systems to support workforce efficiency. A Nurse Scheduling and Attendance–Productivity Enhancement Plan was proposed.
James L. Paglinawan, PhD, Jorbelyn M. Lo
This study explored the lived experiences of Bachelor of Elementary Education (BEED) graduates handling secondary subjects in the Alternative Learning System (ALS) in Valencia City, Bukidnon. Using a phenomenological research design, the study aimed to understand the motivations, challenges, coping mechanisms, and recommendations of these educators as they navigate teaching beyond their field of specialization. Data were gathered through semi-structured interviews with nine purposively selected ALS teachers and analyzed using thematic analysis. The findings revealed four major themes. First, altruistic commitment amidst systemic gaps highlights teachers’ strong sense of purpose to serve marginalized learners despite limited specialization. Second, the complexity of pedagogical displacement reflects the challenges of content mastery gaps, multi-level instruction, and experiences of impostor syndrome. Third, strategic resilience through self-directed development demonstrates how teachers utilize digital resources, contextualization, and adaptive strategies to address instructional difficulties. Lastly, advocacy for curricular reform and collaborative mentorship emphasizes the need for ALS-specific curriculum design, institutional support, and professional collaboration. The study underscores a significant mismatch between teacher preparation and the demands of ALS secondary instruction, pointing to the need for systemic interventions rather than reliance on individual teacher adaptability alone. It concludes that strengthening professional support systems, integrating foundational skills into secondary modules, and fostering collaborative networks are essential to improving instructional quality and sustaining ALS effectiveness. The findings offer valuable insights for educators, school administrators, curriculum developers, and policymakers in promoting inclusive and equitable education.
Dr. Kyung Ki Eun, Dr. Mrinmoy Roy, Dr. Shradha Vernekar, Dr. Shyam Shukla, Suyesha Shukla
This study examines the implications of El Niño on the Indian industrial economy in the context of climate change, with a focus on sectoral risks, economic disruptions, and emerging growth opportunities. The study adopts a qualitative and analytical approach using historical El Niño trends, secondary economic data, sec-toral performance analysis, and climate-related industrial indicators to evaluate the impact on major indus-tries in India. The findings indicate that El Niño negatively affects agriculture, commodity supply chains, and food inflation due to weak monsoon conditions and rising temperatures. However, industries related to cool-ing appliances, irrigation and water technologies, renewable energy backup systems, healthcare, and consum-er durables show strong growth potential during El Niño years. Climate change is further accelerating the demand for climate-resilient infrastructure and adaptive industrial strategies. This study provides an integrat-ed perspective linking climate phenomena with industrial economics in India. It highlights how El Niño acts not only as an environmental risk but also as a catalyst for industrial transformation, investment opportuni-ties, and climate-resilient economic development.
Awhana Oghenekevwe, Okumoku-Evroro Oniovosa, Omoro Paul Oghenemairo, Osame Ufuoma John
In the rapidly evolving landscape of modern cloud computing, serverless computing is transforming the cloud architecture by allowing developer to develop and run applications excluding handling physical infrastructure. Leading cloud platforms and Medium like AWS Lambda, Google Cloud Functions, and Azure Functions dynamically designate computing resources based on requirement, improving how applications scale efficiently and reliably. This research examined how serverless architecture impact the scalability, cost effectiveness and elasticity of web services, with particular emphasis on real-world deployment scenarios across diverse industries and use cases. It also sites key hurdles such as dependency on particular vendors, delay in responding, and data security concerns, all of which represent significant barriers to widespread adoption. The main focus areas are how these technologies are affecting Africa, specifically Nigeria, as more countries embrace digital technologies as part of national development purposes. To address these dimensions comprehensively, the study employs a structured and systematic review methodology. By evaluating an in-dept examination and recent findings drawn from peer-reviewed literature and industry case studies, key patterns and insights emerge. This document includes that serverless computing provides effective solution for scalable web services, both globally and withing emerging market, positioning it as a strategic enabler of digital transformation and broader economic growth in resource-constrained environments.
Jeseca Mae J. Toledo, RN, Joan P. Bacarisas, DM, MAN, RN
This study aimed to compare the clinical performance of staff nurses working under 8-hour and 12-hour shift patterns in a government hospital in Surigao City, Philippines. A comparative descriptive research design was utilized involving staff nurses assigned to different hospital units. Data were collected using the Six-Dimension Scale of Nursing Performance developed by Schwirian, which measures both the extent and quality of nursing performance across leadership, critical care, teaching or collaboration, planning or evaluation, interpersonal communication, and professional development. Descriptive statistics and inferential statistic measure were used to analyze the data. Findings revealed that nurses demonstrated a generally high level of clinical performance under both shift schedules. Significant differences were observed in the frequency of clinical performance in leadership, critical care, and teaching or collaboration activities, while no significant differences were found in planning or evaluation and interpersonal communication. In terms of performance quality, only leadership showed a significant difference according to shift schedule. The results suggest that nurses maintain effective clinical performance regardless of shift length, although certain aspects of nursing practice may vary depending on shift structure.
Afuye I.T, Olusola J.A
This study investigated the short term effect of magnesium sulphate on the compressive strength of superplasticized laterized concrete with a view to establishing its suitability for use in aggressive environment. It examined the effect of magnesium sulphate and varying Laterite contents with a constant water-cement ratio on the compressive strength of superplasticized laterized content. The percentage replacements of laterite as substitute in fine aggregate were varied in the increment of 0%, 20% and 30% respectively. All cubes were cast and cured in water for 7, 14, 28 days respectively. The cast superplasticized laterite concrete cube size is 100x100x100mm which were crushed using compression testing machine. During its preparation, Superplasticizer was added to improve workability. Part of the cubes were transferred to magnesium sulphate concentrate solution of 1% and 3% after 28days of curing in water for another 28 days making 56 days. It was observed that the concrete cube decreases in strength when exposed to varying percentages of magnesium sulphate concentrate solution. The study concluded that superplasticized laterized concrete is not suitable for use in magnesium sulphate concentrate environment.
Mizanur Rahman, Samiha Binte Abdullah, Tahmidur Rahman Chowdhury
In an era marked by aging populations, increasing chronic disease rates, and ongoing disparities in health services access, healthcare systems across the globe are facing a series of challenges. Healthcare systems around the world are increasingly grappling with a combination of factors, including an aging population, a growing burden of chronic diseases, and persistent inequities in health services access. Current hospital capacity planning models consider demand as constant, only indirectly include equity, and separate simulation from optimization, resulting in sub-optimal and inequitable recommendations. This paper proposes a new integrated simulation-optimization approach that combines stratified discrete event simulation (DES) with a multi-objective evolutionary algorithm (NSGA-II) with explicit equity constraints, which are based on needs, and with spatial access variations. The model framework represents the dynamic demographic demand, Markov chain chronic disease progression (with type 2 diabetes mellitus as the example disease), and travel times by zone in eight geographic zones. The need-weighted absolute wait time deviation is a formal equity metric that is directly used in the optimization loop and is thus treated as a Pareto objective for healthcare capacity planning for the first time, to the best of our knowledge. By applying a semi-synthetic analysis of 500,000 people in a region, Pareto frontier analysis shows that equity constraints reduce the total cost of the system by 9-14% when incorporating accelerated ageing, and targeted telehealth expansion can lower inequity by more than 23% without increasing cost by more than 8%. Equity-neutral optimization is found to be inequitable and to cause up to a 35% increase in wait times for low-socioeconomic status (SES) populations compared with high-SES populations, supporting the need for explicit fairness constraints. The framework is scalable: It takes about 4.9 hours of wall-clock time for 1,000 Pareto evaluations across 20 parallel cores, and generates actionable insights for resilient, fair, evidence-based design of health systems.
Bade Abhishek Rustum, Dr. R. K. Moje, Jadhav Abhishek Vasant, Shiraskar Prathamesh
India's agrarian sector, while central to its economic foundation, continues to grapple with inefficient water management and inadequate soil monitoring. This paper introduces Smart AgroCare, an IoT-based precision farming solution developed to address irrigation inefficiency and soil nutrient degradation in smallholder sugarcane cultivation. An ESP32 microcontroller serves as the processing core, coordinating inputs from eight heterogeneous sensors — including NPK, pH, soil moisture, temperature, float switches, and motor protection sensors — to autonomously regulate a single-phase irrigation pump. Processed readings are rendered locally on a 16×2 LCD module and remotely via a cloud-hosted React-based web interface. Data transmission is handled through MQTT messaging and HTTP REST protocols, while external integrations with OpenWeatherMap and Google Gemini AI enhance the system's predictive and advisory capabilities. A structured 21-day field evaluation conducted in October–November 2025 at Manjari (Bk), Pune, achieved water savings between 34% and 37%, a directional crop yield improvement of approximately 12%, and demonstrated full system reliability — all at a hardware cost below ₹10,000.
Akriti Vyas, Dr. Shivalika, Prikshit Thakur, Priyanshi, Ritika
Artificial intelligence and machine learning are transforming pharmaceutical formulation and drug delivery by shifting traditional trial-and-error approaches towards data-driven, predictive methodologies. This study examines the potential of AI to enhance drug development efficiency, optimise formulation design, and address significant pharmaceutical challenges such as elevated development costs, inadequate drug solubility, and intricate formulation variables. Artificial intelligence techniques, including support vector machines, deep learning models, and artificial neural networks, facilitate the rapid analysis of large datasets to predict critical quality attributes such as stability, bioavailability, and drug release profiles. AI integration in pre-formulation studies diminishes experimental workload and accelerates decision-making by facilitating accurate predictions of physicochemical properties. AI-assisted compatibility analysis and excipient selection also make formulations work better and last longer. Self-emulsifying drug delivery systems, nanomedicine, and controlled-release formulations are advanced uses that show how AI can make treatments work better. AI also cuts down on the time and money needed for traditional methods of drug discovery, target identification, and virtual screening by a large amount. AI-driven methods are more efficient, repeatable, and scalable than human-generated formulations, but issues with data quality, regulatory acceptance, and model interpretability still exist. AI also helps with managing the lifecycle, predicting stability, and optimising drug delivery systems. This makes products better and lowers the number of failures. The combination of AI with digital prototyping and Design of Experiments helps intelligent manufacturing and formulation innovation even more. Despite these drawbacks, hybrid approaches that combine human knowledge with AI capabilities hold the key to the future of pharmaceutical sciences. All things considered, AI-driven formulation techniques have enormous potential to transform pharmaceutical research by increasing precision, shortening development times, and improving patient outcomes.
Dr. N. Renthungo Patton, Dr. Roland K. Kikon
Social entrepreneurship represents a hybrid economic model that blends entrepreneurial principles with a social mission. It has emerged as a critical force in addressing market failures, promoting inclusive development, and fostering sustainable innovation. This paper explores the role of social entrepreneurship in delivering public goods, correcting externalities, and creating inclusive economic value. Drawing from institutional economics, innovation theory, and empirical studies, it highlights how social entrepreneurship contributes to sustainable development. The paper also discusses key challenges such as access to finance, regulatory barriers, and impact measurement, and outlines policy recommendations to support the ecosystem. The findings underscore social entrepreneurship's potential as a vehicle for equitable and sustainable economic growth.
Bhawna Singh, Dr. Shikha Tiwari
Social media has emerged as a low-cost and high-reach communication tool in the 21st century. Globally, platforms such as Facebook, YouTube, Instagram, and WhatsApp are widely used for information sharing, interaction, and engagement among students and teachers. The present study aimed to examine the level of environmental awareness among pre-service teachers through social media. A quantitative research methodology with a descriptive survey design was employed. The sample consisted of 313 pre-service teachers enrolled in B.Ed. programmes in Lucknow, Uttar Pradesh. Data were collected using a self-constructed Environmental Awareness through Social Media Scale based on a five-point Likert format. Descriptive statistics such as mean, standard deviation, and skewness were used for data analysis. The findings revealed that pre-service teachers demonstrated moderate to high levels of social media usage and environmental awareness. The study further indicated that social media serves as an effective tool for promoting environmental awareness and encouraging environmentally responsible behaviour among teacher trainees.
Abdulrahman Musa Adeiza, Chinwe E. Okoli, Enid Godwin, Onwoamaka Miracle Oluchi
Access to safe and reliable drinking water remains a major public health challenge in many urban slum communities in Nigeria. In Abuja, increasing dependence on untreated hand-dug wells exposes households to significant risks of waterborne diseases. This study assessed the socio-demographic and access-related determinants of the use of untreated hand-dug well water among households in selected urban slum communities in Abuja, Nigeria. A community-based cross-sectional study was conducted among 340 households selected from four urban slum communities within the Abuja Municipal Area Council using a multistage sampling technique. Data were collected using a structured interviewer-administered questionnaire adapted from standard Water, Sanitation, and Hygiene (WASH) survey instruments. Descriptive statistics were used to summarize study variables, while Chi-square analysis and binary logistic regression were performed to assess associations and predictors of untreated well-water use. Statistical significance was set at p < 0.05. The prevalence of untreated hand-dug well water use was 51.8%, while 61.8% of respondents reported not treating water before consumption. Educational attainment significantly influenced water source choice, with respondents possessing a tertiary education less likely to rely on untreated wells (AOR = 0.34; 95% CI: 0.21–0.56; p < 0.001). Larger households demonstrated higher dependence on untreated wells, particularly households with ten or more members (AOR = 2.32; 95% CI: 1.38–3.90; p = 0.001). Households located more than 100 meters from water sources were less likely to use untreated wells (AOR = 0.66; 95% CI: 0.46–0.95; p = 0.026). The study demonstrates that reliance on untreated hand-dug well water in Abuja’s urban slums is influenced by socio-demographic and access-related factors. Targeted interventions focusing on safe water infrastructure, household water treatment practices, environmental sanitation, and community-based WASH education are necessary to reduce exposure to unsafe water sources in underserved urban settlements.
Debashis Das
There are huge varieties of soft magnetic alloys having widespread applications in variety aspects of science and technology. However, in this paper we will discuss the X-Ray diffraction pattern of the samples FINEMET (Fe73.5Nb3Cu1Si13.5B9), SAMPLE-1 (Fe81B12Mo7), SAMPLE-2 (Fe80B12Mo7Cu1), SAMPLE-3(Fe82B12Mo7Cu1) & SAMPLE-4(Fe83B12Mo5). The peak intensity (~ 0.16 a.u.) for the amorphous metal is extremely small compared to that for a crystalline substance where the peak intensity ranges up to some thousand a.u. The XRD pattern resembles that the samples are fully amorphous material. We have also Study of the paramagnetic transition temperature of the S1(Fe81B12Mo7), S2(Fe80B12Mo7Cu1), samples. These samples are magnetically soft materials.
Mr. Aman Shukla., Mr. Dev Tiwari., Ms. Alisha Naz, Studen
One of the most significant aspects of sustainable finance discussions today is the incorporation of Environmental/ Social/ Governance (ESG) criteria as part of corporate finance, especially within developing markets. This research focuses on how there could be a link between integrating ESG into corporate finance and the Corporate Financial Performance (CFP) of Indian Stock Exchange-listed companies by addressing both the conflicting evidence as well as non-linear performance trajectories seen in the body of literature. A purposive sample of ten BSE/NSE-listed organizations from five different sectors (Information Technology, Banking, Telecommunications, Energy, and Manufacturing) for the period of FY 2021 through FY 2025 will be used in this research. Descriptive statistics, Spearman rank correlation, and the Mann-Whitney U non-parametric test will be utilized to analyze the FP of high ESG adopters (ESG score ≥ 70) against low ESG adopters (ESG score ≤ 60). ROE, ROA, and CoD will be utilized to measure FP. High ESG adopters show a statistically significant difference in their return on assets (ROA) (Mean=13.18% vs. 4.64%) at the 0.007 level of significance while having a statistically significant difference in their cost of debt (Mean =7.83% vs 11.72%) at the less than 0.001 level of significance. The statistically significant difference in return on equity (ROE) (p=0.005) is also influenced by industry capital intensity and short-term costs associated with transitioning to ESG compliance. The correlation between ESG score and ROA is 0.72 (p=0.003), and the correlation between ESG score and cost of debt is -0.79 (p<0.001), indicating a strong negative relationship between ESG quality and financial risk. The findings provide firm-level results over time and by sector to the sustainable finance literature in India, as well as identifying situations in which the ESG return is non-linear. There are implications for corporate managers, policymakers and investors from these findings.
Aquiline Kathambi
Square planar complexes of cobalt in any of its common oxidation states are rare and attempt to make them either yield tetrahedral or octahedral complexes. The aim of this study was to synthesize and characterize tetrahedral or octahedral complexes of cobalt using selected chelating ligands such as 8-hydroxyquinoline (oxine) expected to have the same action as cis-platin used as anticancer drug. The reactions of CoCl2 with 8-hydroxyquinoline (oxine) were studied under different solvent conditions under inert conditions. Reaction of cobalt (II) chloride with Oxine in tetrahydrofuran (THF) solvent gave unexpected blue crystals of the tetrachloridocobaltate (II) complex [CoCl4]-[C9H7NOH]+ in which protonated oxine is the counter cation. The molecular structure of the complex [CoCl4]-[C9H7NOH]+ was confirmed using single crystal X-ray crystallography. It forms monoclinic crystals in the C2/c space group with respective unit cell parameters being= 90.00, = 91.0900, = 90.00; a = 15.1890(3), b = 7.99120(10), c = 16.6770(3). When the same reaction was carried out in water/ethanol mixture, a yellow non crystalline solid, [Co(oxine)2(H2O)2]Cl2 was obtained. These compounds were characterized by melting point determination, elemental analysis and FTIR spectroscopy
Dr. Jai Pal Sharma, Neha
This study examines the key contributors and trends in customer orientation research within marketing and business management. Analysing 166 documents published between 1993 and 2024, it identifies influential authors, institutions, nations, and journals that have shaped the field. Using bibliometric and mapping techniques, the study highlights essential research trends and provides visualisations of co-occurrence, co-citation, and the evolution of the literature over time. It also offers insights into publication patterns, journal distributions, and academic contributions, making it a valuable resource for understanding the current state of research. Finally, the study outlines potential directions for future research, helping scholars explore new possibilities in customer orientation.
Joyce B. Marcojos, Riza B. Salipong, Phd
This study explored if teachers’ well-being can be a mediating variable towards the relationship between teachers’ workload and learners’ performance. Thus, one hundred nine (109) beginning teachers across the sub-congressional districts (Loon North, Loon South, Calape, Tubigon East and Tubigon West) had their workload (in terms of duties and obligations, energy expenditure and time demands), well-being (in terms of physical, mental, emotional, social and even with work-life balance) and learners’ performance have analyzed for the school year 2025-2026. With that, a correlational research design was used with a structured survey questionnaire. Further, the findings revealed that beginning teachers experienced an overall high level of workload with the mean of 2.75 and a standard deviation 0.72) across all aspects. Moreover, in terms of well-being, beginning teachers experienced an overall composite mean of 3.09 with a standard deviation of 0.62 which gained positive level across all aspects. Further, in terms of learners’ performances, 73 classes (67%) out of 109 (100%) got the very satisfactory level (85-89). This means, despite the challenges nor demands experienced by the beginning teachers, they can still be an effective teacher to their learners. Overall, the results of the Pearson correlation analysis revealed that beginning teachers’ workload shows there is a significant relationship to teachers’ well-being, and there is a significant total effect on learners’ performance. Thus, it is recommended that school administrators should implement structured workload management strategies, provide professional development programs, help teachers maintain their well-being, promote teamwork, implement interventions and improve institutional support systems.
Abadul Haque, Animesh Chandra Roy, Bashudeb Paul, Chhanda Rani Das, Md. Monirul Islam, Md. Sofier Rahman, Shahida Akter, Shipra Roy, Siam Hossain Limon
Delay in recovery from general anesthesia is always hazardous to life. Therefore, this study aims to evaluate the effect of atipamezole in the recovery of rabbits anesthetized with xylazine-ketamine undergoing neutering. Ten male rabbits were randomly assigned to two groups (n = 5 per group), where group XK was treated with xylazine (5 mg/kg bwt) and ketamine (30 mg/kg bwt) intramuscularly without atipamezole, and group XKA was treated with xylazine (5 mg/kg bwt), ketamine (30 mg/kg bwt), and atipamezole (0.5mg/kg bwt) intramuscularly. Atipamezole was administered intramuscularly 30 minutes post-injection of the anesthetic combination. Physiological parameters, induction time, duration of anesthesia, recovery time, hematological, and biochemical parameters were measured. In group XKA, heart rate, temperature, and respiration that decreased during anesthesia, reached almost normalcy during recovery, rather than group XK. Significant differences in induction, duration of anesthesia, and recovery periods were observed between the two groups. Group XKA showed a short recovery time compared to Group XK. The duration of anesthesia was longer in group XK in comparison to group XKA. The recovery period was short in group XKA due to the atipamezole. There was no effect of atipamezole on healing. There were no significant differences in hematological parameters between the two groups. Taken all together, we conclude that the atipamezole has a great role in the reduction of recovery time of the rabbit with xylazine-ketamine induced anesthesia without significant adverse effects in clinical and blood parameters during neutering.
Aibel O. Pelobueno, RN, Joan P. Bacarisas, DM, MAN, RN
This study explores the lived experiences of Emergency Department (ED) nurses in managing patient overcrowding within a public tertiary hospital in the Caraga Region. Utilizing a Husserlian descriptive phenomenological design, the research captures the essence of this phenomenon through in-depth, semi-structured interviews with eight purposively selected registered nurses, with data analyzed using Colaizzi’s systematic method. The findings revealed the following themes and subthemes: Overcrowding at its Finest (comprising Space is Limited, The Unending Arrival, and Prolonged ED Stay); Managing Overcrowding (comprising The Weight of the Shift and The Collective Shield); and Grace Under Pressure (comprising Decision-Making Under Stress and maintaining composure and meaning). Despite facing severe resource constraints and ethical dilemmas in prioritization, nurses demonstrate profound professional resilience by moving beyond mere task performance to establish meaningful human-to-human connections with patients and their families. Regarding the applicability of the study, while adaptive strategies and teamwork allow for functional care delivery, they also mask a hidden vulnerability within the workforce where professional duty often supersedes the nurse's own well-being.
Adaeze Ucheokoro, Chidera G. Nwadike, Ebenezer C. Nwogu, Eberechi Okolie, Emmanuel Menson, Ozadheoghene E. Afieroho, Philip E. Iche, Sunday O. Abali, Victoria C. Obinna
This study focused on evaluating the potentials of two variants of water soluble polyherbal nutraceutical products containing Vernonia amygdalina (Bitter leaf) and Hibiscus sabdariffa (Zobo calyces) in mitigating the toxicity due to dexamethasone a widely used synthetic corticosteroid associated with adverse effects, including hyperglycemia, and oxidative stress among others. The two polyherbal products variants: POWSG-D-(10% w/w bitter leaf decoction and 10% w/w Zobo decoction extract), and POWSG-C-10% w/w bitter leaf cold maceration extract and 10% w/w Zobo decoction extract) were used in this study. Phytochemical analysis and physico-chemical parameters (residue on drying, total ash and loss on drying) were done following standard methods as recommended by the World Health Organization (WHO) for herbal product. In vitro antioxidant assay was done using the DPPH (2,2-diphenyl-1-picrylhydrazyl) spectrophotometric method. Effect on glycemic index (fasting blood sugar) was done in vivo in sub-acute dexamethasone treated mice. phytochemical analyses confirmed the presence of phenolics with the UV-Visible spectra showing corroborating characteristic absorption peaks at 198-202 nm and 273–275 nm, evidence for phenolics. Quality assessments demonstrated good granule flow properties, with cold maceration granules exhibiting superior compressibility. Antioxidant activity was moderate, with IC50 values of 500 µg/mL and 800 µg/mL for POWSG-C and POWSG-D respectively, compared to Vitamin C (IC50: 9 µg/mL). From the result of the bioassay, the high dose (800 mg/kg body weight) decoction successfully mitigated hyperglycemia on the sub-acute dexamethasone induced mice with 1.75mMol/L and 1.80mMol/L on day 18 and 25 respectively compared to the other group of animals. These findings highlight the potential of this polyherbal formulation as a cost-effective, accessible nutraceutical for the treatment of hyperglycemia especially for immuno-compromised subjects undergoing corticosteroid regimen, and for general health and wellbeing with further optimization recommended to enhance efficacy and antioxidant activity.
Feb Yvonney M. Matugas, MA, Jehan G. Naga, Najeb B. Aloyod, MAEd, Nezryne P. Perino, Socio, Settie-Zhymah S. Padate, MAFil
This study examined the effect of an online writing tool on the writing skills of education students at Mindanao State University–Lanao del Norte Agricultural College, addressing the limited research on the direct influence of such tools on students’ writing ability. Specifically, it aimed to determine students’ level of use of the tool, assess its perceived effects on writing skills, and test whether significant relationships exist between student profile variables and the tool’s effects. A descriptive-correlational research design was employed, involving 50 purposively selected education students. Data were collected through a validated questionnaire and analyzed using frequency, percentage, weighted mean, and chi-square tests. Results showed that students reported a high level of use of the tool (grand mean = 3.26) and perceived it as highly effective in improving grammar, sentence construction, and overall writing performance (grand mean = 3.30). However, no significant relationships were found between students’ profile variables (age, gender, year level, and program) and the effects of the tool (p > 0.05). The findings indicate that while the tool is widely used and perceived as beneficial, its effectiveness is consistent across different student groups. The study concludes that online writing tools can support writing development but should be used alongside the development of independent writing skills.
Flowery Francis, Jeena Joseph
In this paper, we came up with the Gaussian-Enhanced Rayleigh Distribution (GERD), a mix of Rayleigh and Gaussian parts, to see if it could do a better job with wind speed data. For testing, we used monthly records from Tokyo between 2000 and 2020. We compared GERD with the Weibull and Rayleigh models, looking at how they fit the data, their statistical measures, some simulations, and what they mean for power output. The Weibull model turned out strongest for extreme wind speeds and gave the highest power values. Rayleigh came out too low. GERD sat between the two, less extreme than Weibull but more realistic than Rayleigh, which makes it a practical option for wind energy studies.
Andrew Kofi Annan, Edmund Nelson Amasah (Ph.D), Kwadwo Agyei Bio
This article provides a critical analysis of the proposed mandatory paternity legislation introduced in the Parliament of Ghana in early 2026. The proposed Private Member’s Bills seek to mandate DNA testing as a prerequisite for birth registration and to criminalize "paternity fraud." This study contends that such measures represent an unprecedented state overreach that undermines the "presumption of legitimacy" established under the Evidence Act 1975. Through a comparative jurisdictional lens, the article examines the legal frameworks of seven advanced economies including France, Germany, and the UK revealing that Ghana’s proposal is a global outlier that prioritizes forensic truth over family stability and the "best interests of the child." The author concludes by recommending a shift toward voluntary mediation and the strengthening of existing family tribunals rather than the implementation of state-mandated genetic surveillance.
Alugani Manish Goud, Daggula Varsha, Najam Uddin Siddiqui
Background: Emerging evidence implicates the gut-brain axis (GBA) as a critical bidirectional communication network influencing neurological and psychiatric health. The gut microbiome, comprising trillions of microorganisms, produces neurotransmitters, neuroactive metabolites, and immune mediators that modulate central nervous system function through neural, endocrine, and immune pathways. Objective: This comprehensive review synthesizes current evidence on the mechanistic relationships between gut microbial dysbiosis and psychiatric disorders, and critically evaluates microbiome-targeted therapeutic strategies including probiotics, prebiotics, fecal microbiota transplantation, and dietary interventions. Methods: A narrative review was conducted using PubMed, PsycINFO, and Scopus databases, covering peer-reviewed literature from 2015 to 2025. Animal model studies, human clinical trials, and population-based observational studies were included. Results: Substantial evidence links alterations in gut microbiota composition to depression, anxiety, schizophrenia, autism spectrum disorder, and neurodegenerative conditions. Psychobiotic interventions probiotics with demonstrated neuropsychiatric benefits — showed effect sizes comparable to conventional anxiolytics in randomized controlled trials, though study heterogeneity limits definitive conclusions. Dietary patterns, particularly the Mediterranean and plant-rich diets, were consistently associated with reduced depression risk via microbiome-mediated mechanisms. Conclusion: The gut-brain axis represents a paradigm-shifting framework for understanding and treating mental illness. While promising, microbiome-based interventions require larger, longitudinal, and mechanistically rigorous clinical trials before integration into standard psychiatric care.
Joana M. Sumalinog
This study examined the relationship between Senior High School (SHS) welding competencies, differentiated instruction, and the academic performance of college welding students at Cebu Technological University–Main Campus enrolled in the Bachelor of Technical-Vocational Teacher Education (BTVTED) major in Welding and Fabrication Technology during the academic year 2025–2026. A descriptive-correlational research design was employed, and data were collected from 46 respondents using a structured questionnaire that assessed SHS welding competencies in terms of academic preparedness, practical skills, and technical knowledge, as well as students’ perceptions of differentiated instruction in terms of content, process, and product. Academic performance was measured using self-reported grades. The findings revealed that respondents demonstrated a moderate level of SHS welding competencies, indicating the presence of foundational skills but insufficient preparation for college-level demands. In contrast, differentiated instruction practices were perceived to be highly evident, reflecting the use of varied teaching strategies to address diverse learner needs in technical-vocational education. Statistical analysis showed a significant moderate positive relationship between SHS welding competencies and differentiated instruction. However, no statistically significant relationship was found between SHS welding competencies and academic performance, nor between differentiated instruction and academic performance. These findings suggest that while prior competencies influence students’ engagement with instructional strategies, academic performance may be affected by other factors beyond SHS preparation and teaching approaches. The study recommends strengthening bridging programs, enhancing hands-on training, improving assessment practices, and sustaining differentiated instruction to better support student learning outcomes.
Andrew Kofi Annan, Ewura Esi Nketsiaba Okyere Baafi, Kwadwo Agyei Bio, Prof. Osei Kofi Akuoko
This article examines the persistent prevalence of child marriage in Ghana, where national rates have stagnated while the Western Region has seen a sharp increase to 36.7%. Despite the 1992 Constitution and the Children’s Act of 1998 (Act 560) explicitly setting the minimum marriage age at 18, a critical discrepancy remains between these robust legal frameworks and grassroots socio-cultural realities. This research investigates why legislative prohibitions have failed to curb the practice, specifically seeking to identify the drivers of early marriage, explore the coping mechanisms of affected women, and evaluate the implementation challenges of existing laws. Grounded in Radical Feminist Theory and a review of legal pluralism, the study analyzes the tension where customary norms often supersede statutory protections. Adopting a qualitative case study approach within the Shama and Tarkwa Nsuaem districts, data was collected from eighty participants including women involved in child marriages, traditional leaders, and state stakeholders using in-depth interviews and focus group discussions. The thematic analysis of this data reveals that child marriage functions as a resilient social and economic institution rather than a mere legal infraction. Key findings highlight that traditional practices such as "Asiwa" (child betrothal) and "bride-service" create deep-seated obligations from as early as age five, compounded by a "menarche metric" that prioritizes physical puberty over chronological age. Furthermore, institutional inadequacies including a lack of birth registration and a "lackadaisical" attitude among enforcement agencies render state interventions "toothless." The article concludes that effective eradication requires a dual-track strategy: the rigorous enforcement of the Criminal Offences Act alongside intensive community-based legal literacy campaigns. Ultimately, the study argues that aligning customary practices with statutory human rights standards is essential to protecting the girl-child from systemic marital exploitation.
James L. Paglinawan, Lyn Lee Mae B. Madulara
This study examined the relationship between professional development and workload management and their influence on the support system of teachers in geographically isolated schools in Bukidnon, specifically in Kitaotao, Quezon, and San Fernando during the school year 2025–2026. The study involved 380 public school teachers. It assessed professional development in terms of seminars, workshops, training, research and extension activities, and advanced academic studies. It also evaluated workload management in relation to non-teaching tasks, support activities, and administrative work, as well as the level of support system in terms of peer, administrative, institutional, and recognition support. Findings revealed that teachers demonstrated high levels of professional development, with seminars and training as the most common. Workload management was also rated high, particularly in administrative tasks. The support system was likewise rated high, with administrative support receiving the highest rating. Further analysis showed a significant relationship among professional development, workload management, and the support system. Both variables significantly predicted support, with workload management emerging as the strongest factor. The results suggest improving workload conditions and expanding professional development opportunities to strengthen teacher support systems.
Suhasini Patil
The integration of Artificial Intelligence (AI) in financial systems is transforming the way organizations manage financial reporting and ensure regulatory compliance. This study investigates the role of AI in enhancing the accuracy, efficiency, and timeliness of financial reporting, while also strengthening regulatory compliance frameworks. Based on primary data collected from 100 financial professionals in Bangalore, the research provides empirical insights into the adoption, benefits, and challenges associated with AI in finance. Findings suggest that AI significantly contributes to data accuracy, anomaly detection, and automation of compliance tasks, although concerns around data privacy, system integration, and high implementation costs remain. The study concludes with recommendations for organizations aiming to leverage AI for financial governance.
Dr. Arati Pradhan, Dr. Sanmati Jain, Mrs. Prangya Prachi Samantaray
Artificial Intelligence (AI) has been identified as a revolutionary technology that has the potential to improve the efficiency and effectiveness of academic library services. This paper examines the use of AI in the modernization of academic libraries by incorporating intelligent systems such as chatbots, recommendation systems, automated cataloguing, and data analytics. These technologies help in the optimization of information retrieval, personalized user services, and automating the routine tasks of the library. The paper discusses how AI-based systems can help librarians in handling massive digital information while allowing them to concentrate on advanced research support services. The results of this paper indicate that the efficient use of AI can help in the transformation of conventional libraries into intelligent knowledge repositories to cater to the changing demands of researchers, students, and academic organizations.
Glenn I. Peñoza
This study determined the levels of grit, academic resilience, and academic burnout among engineering students of Cebu Technological University – Dumanjug Extension Campus and examined the significant relationships among the variables using the descriptive-correlational research design. The study was conducted among 365 engineering students using universal random sampling. Data were gathered through the Triarchic Model of Grit Scale, Academic Resilience Scale-30, and Academic Burnout Scale and analyzed using descriptive statistics and Pearson Product-Moment Correlation. Results revealed that the respondents generally demonstrated high levels of grit and academic resilience despite exhibiting a moderate level of academic burnout characterized by emotional exhaustion, academic inefficacy, and subjective overload. Furthermore, grit and academic resilience both showed significant negative relationships with academic burnout, suggesting that students with stronger perseverance, adaptability, and coping abilities are less likely to experience severe burnout. The study concluded that grit and academic resilience serve as protective factors against academic burnout. Finally, a proposed Guidance and Counseling Program for Engineering Students was recommended to strengthen students’ resilience, coping mechanisms, retention, and academic success.
Elizabeth Njeri Ngigi
Language has historically functioned as both a communicative system and a repository of cultural identity, social memory, and collective belonging. In the contemporary digital era, Artificial Intelligence (AI) technologies increasingly mediate communication practices through predictive text systems, speech recognition software, algorithmic moderation, and Large Language Models (LLMs). Although such technologies have improved efficiency, accessibility, and multilingual interaction, emerging scholarship suggests that AI systems may also reproduce existing linguistic hierarchies by privileging dominant and standardized language forms while marginalizing dialectal and non-standard varieties (Helm et al., 2024; Hofmann et al., 2024). This theoretical paper examines how AI-driven communication systems may contribute to processes of linguistic standardization and dialect marginalization within digital environments. Drawing upon Fricker’s (2007) theory of epistemic injustice, the paper introduces the concept of the Digital Language Divide to explain disparities in computational recognition, linguistic legitimacy, and technological visibility among speech communities. Unlike deterministic arguments that portray technology solely as a force of linguistic erosion, this paper adopts a balanced perspective acknowledging that AI technologies may simultaneously expand communication access while also reinforcing structural inequalities in language representation. Recent empirical studies demonstrate that some AI systems exhibit dialect prejudice, particularly toward speakers of African American English and other non-standard language varieties (Hofmann et al., 2024). Additionally, emerging scholarship on techno-linguistic bias argues that language technologies frequently prioritize dominant linguistic norms embedded within training datasets (Helm et al., 2024). Building upon these findings, this paper theorizes how algorithmic standardization may gradually influence linguistic practices, educational expectations, and communicative participation within digitally mediated societies. This paper seeks to establish a conceptual foundation for future interdisciplinary inquiry into the sociolinguistic consequences of AI-mediated communication. The study concludes by proposing directions for future empirical research, policy development, and inclusive AI design frameworks capable of supporting linguistic diversity within digital ecosystems.
Swapan Samanta, Tarapada Manna
Plants are well known to possess internal biological clocks that regulate daily cycles of growth, water uptake, and gas exchange. What has received far less attention is what happens when cultivated plants become accustomed to the fixed, human-imposed schedules that define modern agriculture and horticulture—and what happens when those schedules are disrupted. This paper reports findings from a 40-year field study (1985–2025) tracking 1,247 individual plants across 68 species, ranging in lifespan from 45-day radishes to long-lived banyan trees estimated to survive several centuries. Plants maintained under consistent daily or weekly care routines for more than 60 days developed recognisable anticipatory behaviour: stomata opened before scheduled irrigation arrived, hydraulic pressure in stems rose ahead of watering events, and metabolic processes were primed in advance of expected inputs. When these routines were abruptly changed—even while water volume and nutrients remained unchanged—physiological stress followed in the majority of observed plants. Among fast-growing herbs, 79% showed measurable decline within approximately two weeks; among seasonal crops, 68% within three weeks; among short-lived perennials, 61% within four weeks. Across the full dataset, the maximum tolerable timing deviation (ΔTcrit) before physiological decline appeared to scale with species characteristic lifespan (L) according to the empirical relationship ΔTcrit ≈ 0.019 × L0.98 (R² = 0.82, p < 0.001, n = 68), a pattern we term the Temporal–Lifespan Scaling Law. This held across all growth forms, photosynthetic pathways, and taxonomic families in the dataset. Crops such as tomato and chilli that are routinely harvested early showed timing tolerances consistent with their full evolutionary lifespan rather than their cultivation period, suggesting that temporal sensitivity reflects developmental programming. These findings point to temporal predictability as a meaningful and underappreciated dimension of plant physiological stability under cultivation. The practical implications span irrigation scheduling, transplantation protocols, urban forestry, climate vulnerability assessment, and plant breeding. We propose that this body of phenomena warrants a dedicated research focus, which we call chronoecology: the systematic study of how plants internalise, anticipate, and depend upon temporal structure in their environments.
Dr. Yogita Shrimali, Nikita Solanki
The present article presents timing and pulse profile study of high-mass X-ray binary Vela X-1 using the observation of the RXTE/PCA in 2008. Vela X-1 is a high-mass X-ray binary system, which is a wind-accreting system and is composed of a neutron star and a giant supergiant companion. The periodic pulsations and high variability of the system are due to accretion of the stellar wind of the companion star. RXTE/PCA data was also analyzed by timing analysis to estimate the pulse period of the source. The optimal pulse period was adjective based on the light curve data with the help of the efsearch task. Pulse profiles were also constructed by deriving the light curves of the various levels and folding them with the pulse period calculated. To examine variations in pulse structure with energy, pulse profiles were formulated as energy dependent profiles in several energy bands. In addition, long-term variability of the source was also studied depended on the data of ASM light curve. The measurements indicate that there are considerable differences in pulse profile morphologies across the different energy bands. Multi-peaked and complex structures were found to be more complex at lower energy and simple at high energy. These changes could have changed accretion processes and geometry of emission of the Vela X-1 system. The article sheds light on the behavior of emission as well as the process of accretion of high-mass X-ray binary systems.
Isimaronkhae, J. E.
The study area, Igarra which is North-West of Edo State, Nigeria, is underlain in the North by Precambrian Basement Complex and in the South by Cretaceous and Tertiary sediments. The ground magnetic study of the area was carried out. The investigation was aimed at studying the total components (i.e. the horizontal magnetic intensities and horizontal magnetic gradients) of the various rock components found in the study area; study the ground magnetic properties of the underlying rocks, delineate the geological structures of the study area, delineate the different rock contacts and geological boundaries that are useful in mapping the basement structures of the area, and determine the depth to magnetic basement. The ground magnetic investigations were conducted on foot using GSM 19T Proton Precision Magnetometer and Garmin Global Positioning System (GPS). Three profiles and measurements were taken in order to know the type of minerals found in the area. Closely spaced stations of 20 m interval were adopted for the magnetic survey to allow high resolution of near surface structures. The magnetic data were analysed using Grapher 11. The study area indicated locations of negative relative magnetic intensity, which suggest regions of no magnetization. It is where magnetic sediments, rocks and minerals are not present. It could be deduced from the study, that parts of the basement terrain is accumulated with mostly granite and quartz due the relative magnetic susceptibility generated from the study area. The nature of the anomalies in this part of the study area suggests that the rocks may be bounded and offset by faults. Although the results provide valuable insights into the subsurface geology, the interpretation of magnetic data is inherently non-unique and primarily reflects shallow subsurface conditions. Therefore, the integration of additional geophysical methods is recommended for more detailed characterization.
Jephias Matunhu, Patience Matunhu, Precious Matunhu, Viola Matunhu
Zimbabwe suffers food and nutrition insecurity due to the effects of climate induced droughts, food waste, and mid-season dry spells. The study was conducted in support of Zimbabwe’s Vision 2030, UN SGDs and Africa Agenda 2063, whose general aim is to ensure food security for all people. The study investigated opportunities for reducing food waste in Zvishavane district by applying the Closed-loop Secular Economy theory. Qualitative data was collected through interviews, observation and documents reviews. Data was gathered from fruit and vegetable vendors, smallholder producers in the rural areas, as well as from food scientists at a local university. Findings confirmed high levels of food waste at fruit and vegetable markets, vending points, as well as at smallholder farms. Mangoes, bananas, amarula fruit, Uapaca kirkiana, guava, watermelons, tomatoes, banana, and cabbage were the worst wasted food. The study recommends low-cost methods of preserving food using solar energy. Value addition and value preservation of food could be in the form snacks, bottled fruit juices or processed animal, poultry, and fish feeds.
Adebimpe, A. T, Ajala, A. O., Famuwagun, O. S., Ogunjimi, S.I., Omah I. F.
Traditional Medicine organically evolved from the quest of indigenous people globally: to maintain a healthy life, prevent diseases, prolong life, diagnose and resolve disease conditions in culturally accepted manner. This practice continues to play a prominent role despite swift civilization and increment of more researched and formulated Orthodox Medicines in Nigeria health care delivery system. This is due to the failure of Orthodox Medicine to meet the basic health problems of the poorest and the most vulnerable population in rural part of Nigeria. Hence the need for a health system that is holistic in function and practice on both Orthodox Medicine and Traditional Medicine. This paper presented a systematic and comparative review of Orthodox Medicine and Traditional Medicine. Their peculiar roles in rural health service delivery were highlighted. The exceptional usefulness of Orthodox Medicine in acute cases requiring urgent and intensive care were mentioned. It identified that the dearth of resources, inadequate and decaying infrastructure, and inequality in resource distribution, workers strikes and excessive levels of health worker migration–rural to urban/abroad have led to a deplorable Orthodox Medicine system in Nigeria. Traditional Medicine characteristics such as -availability, accessibility, affordability and effectiveness made it an indispensable health care delivery for rural dwellers, coupled with being a good source of foreign investment, socio-economic development and national prosperity. The paper concluded that it becomes imperative to infuse Traditional Medicine into Orthodox Medicine to bridge deficiencies and produce a health care system that will ensure safe health for all. It is recommend that Traditional Medicine should be officially recognized, tolerated and integrated into Nigeria’s orthodox health policy to meet the needs of both rural and urban population.
Jessica L. Jimenez, Riza B. Salipong
This study examined the relationship between transformational leadership, teachers’ organizational commitment, and teaching performance in selected schools in the Schools Division of Bohol using survey questionnaires and official IPCR ratings. Findings revealed that school heads are perceived as highly transformational (mean = 3.67, SD = 0.58), with Inspirational Motivation as the highest dimension (mean = 3.71, SD = 0.56), followed by Idealized Influence (mean = 3.70, SD = 0.58), Management by Exception (mean = 3.65, SD = 0.59), and Individualized Consideration (mean = 3.62, SD = 0.59). Teachers obtained a high level of organizational commitment (mean = 3.18, SD = 0.69), led by Affective Commitment (mean = 3.26, SD = 0.66), followed by Continuance Commitment (mean = 3.21, SD = 0.67) and General Commitment (mean = 3.05, SD = 0.73). Most teachers were rated Very Satisfactory (92.33%), with a few rated Outstanding (6.67%). Mediation analysis showed that organizational commitment does not significantly mediate the relationship between transformational leadership and teaching performance (p = 0.409), while transformational leadership has a significant direct effect (p = 0.012) and a significant total effect (p = 0.003). A weak but significant positive relationship was found between transformational leadership and teaching performance (r = 0.25, p = 0.006). The study recommends that school heads further strengthen recognition practices, feedback mechanisms, and supportive leadership behaviors through the implementation of an action plan that focused on strengthening transformational leadership to enhance teachers’ commitment and performance; teachers should sustain active engagement and collaboration to maintain commitment and performance; school administrators and the Schools Division Office should enhance leadership and instructional capacity-building programs; and future researchers should explore additional mediating variables and expand the study scope to other divisions to further strengthen and validate the findings.
Veronica V. Calang
In the pursuit of justice, truth becomes both a guiding light and a contested terrain. Across courts, police precincts, and intelligence units, the challenge of determining who is telling the truth and under what conditions is central to legal and investigative processes. This study aimed to explore the informants’ experiences, aspirations, and the effects of polygraph tests in Investigation and adjudication. This study employed a qualitative exploratory phenomenological research design. The data have been analyzed using Colaizzi’s method of data analysis, which is suited for understanding lived human experiences on polygraph utilization in court proceedings. The study has shown a clear path for future cases and offers a better grasp of the complicated terrain around the admissibility and standards for the use of polygraphs. It demonstrates how present legal frameworks frequently make polygraph results inadmissible in court, a fact that both investigators and legal specialists generally agree upon. Therefore, to fully utilize the polygraph's capabilities, the forensic and legal sectors must collaborate and increase knowledge. Open communication, shared research, and collaborative educational initiatives among polygraph examiners, lawyers, judges, law enforcement, and researchers are crucial for developing comprehensive policies, fostering a deeper understanding of the technology, and ensuring its successful and ethical application within the broader framework of justice.
Angela P. Agohob, Angelene P. Agohob, Feb Yvonney M. Matugas, Liezel P. Naquines, Najeb B. Aloyod
This study used an experimental research design with a one-group pre-test and posttest design to determine the impact of utilizing a context-based STEM education approach on teaching Science to Grade 4 learners of Sultan Naga Dimaporo Memorial Integrated School (SNDMIS), Lanao del Norte. The respondents of the study were thirty-eight (38) Grade 4 pupils from Section A, officially enrolled during the Academic Year 2025–2026. A 20-item multiple-choice test aligned with the Science 4 curriculum was administered before and after the intervention to measure pupils’ performance, and data were analyzed using frequency and percentage distribution and a paired t-test. Findings revealed that pre-test scores were low, with most pupils performing below average, while post-test results showed that most pupils were above average, implying significant improvement from pretest to posttest scores. The mean score increased from 10.92 to 14.32, and the t-test confirmed a significant difference between pre-test and post-test scores (t = 6.83, p < 0.05). This indicates a significant improvement in science performance after utilizing the context-based STEM education approach. Pupils designed and constructed a vertical garden prototype using recyclable and affordable materials, which were evaluated in terms of creativity and neatness, teamwork, and effort, scoring 96.67% and 95.33% respectively and interpreted as Outstanding. These results highlight the efficacy of hands-on learning. The study concludes that the utilization of context-based STEM education and integration of local and relatable situations improves pupils’ motivation, engagement, understanding of scientific concepts, and problem-solving skills in meaningful learning environments.
Reymark R. Cleopas
This study investigated the effect of virtual laboratories on the academic performance and engagement of Senior High School students in General Physics 2. Utilizing a quasi-experimental research design with a pretest–posttest approach, the study involved Grade 12 STEM students from Colegio de San Rafael Arcangel, Inc. for the School Year 2025–2026. The respondents were divided into two groups: an experimental group exposed to virtual laboratory-based learning activity sheets and a control group that received traditional instruction. Data were collected using a validated 50-item teacher-made test to measure academic performance and a survey questionnaire to assess student engagement in terms of behavioral, emotional, and cognitive dimensions. Additionally, the developed instructional material was evaluated using the DepEd LRMDS guidelines. Findings revealed that both groups improved in their posttest scores; however, the experimental group demonstrated significantly higher gains compared to the control group. The paired-samples t-test confirmed a statistically significant difference between pretest and posttest scores in both groups, with a greater effect observed in the experimental group. Moreover, students exposed to virtual laboratories exhibited very high levels of engagement across behavioral, emotional, and cognitive domains. The developed virtual laboratory-based learning activity sheets were rated “very satisfactory,” indicating their quality, relevance, and effectiveness as instructional materials. The study concludes that virtual laboratories significantly enhance students’ academic performance and engagement in science. It highlights the potential of integrating technology-based instructional tools in improving science education, particularly in resource-limited settings. The findings support the adoption of virtual laboratories as an effective supplement to traditional teaching methods in secondary science education.
Abubakar U. Tafida, Hadiza A. Zaku, Innocent E. Bello, Nancy B. Madugu
This study evaluates flood spatial extent and intensity in Lugbe, Abuja, using integrated geospatial techniques and rainfall–flood relationship modeling to inform sustainable urban planning. Employing an interdisciplinary design—combining Remote Sensing, GIS, hydrological modeling, and Google Map WebGIS visualization—the research delineates flood-prone zones, quantifies hazards, and examines governance implications. The findings indicate that 34% of Lugbe lies within moderate-to-high hazard zones, with severe areas experiencing flood depths exceeding 1.5m. Vulnerability is heavily concentrated in low-lying drainage corridors and rapidly expanding estates; high-intensity hotspots impact River Park Estate (21.5 ha; 4.48%), Trademore Estate, the Voice of Nigeria axis, and informal settlements near Lugbe Fruit Market, contrasted by low exposure in FHA Capua (1.59 ha; 1.39%). Spatial overlay analysis reveals that 33–36% of local buildings and infrastructure are exposed. Key drivers include high impervious surface coverage (65–75% in built-up estates) and inadequate or blocked drainage infrastructure affecting roughly 40% of mapped corridors. Rainfall modeling indicates that extreme events (>50 mm/day) trigger over 60% of severe floods, and a projected 10% increase in rainfall intensity could boost runoff by 15–20%. Crucially, integrating WebGIS dashboards improved hazard communication by 40–50% and cut emergency response times by up to 45%. The study advocates for immediate drainage remediation, strict enforcement of zoning laws, and a ban on waterway encroachment to mitigate accelerating climate risks.
Jalila S. Sarip, Melcah P. Sambaan, Najeb B. Aloyod, Princess Hamimah C. Bint Abdullah, Settie-Zhymah S. Padate
This study aimed to determine the effectiveness of Wordscapes, a gamified word puzzle application, in enhancing the vocabulary acquisition and spelling skills of Junior High School students at Mindanao State University – Sultan Naga Dimaporo. Specifically, it sought to determine whether the use of Wordscapes could significantly improve students’ performance in vocabulary and spelling, and whether demographic factors such as age, gender, and grade level had a significant relationship with their post-test results. The study employed an experimental research design using a one-group pre-test and post-test procedure. Fifty (50) Junior High School students served as respondents of the study. Prior to the intervention, a pre-test was administered to assess the students’ baseline knowledge and skills in vocabulary acquisition and spelling. Afterward, the respondents were exposed to the use of Wordscapes as a supplementary learning activity for a specific duration. Following the intervention, a post-test with the same scope and level of difficulty was conducted to measure the students’ improvement. Findings revealed that the respondents had relatively similar levels of performance during the pre-test. However, the post-test results showed a significant improvement in both vocabulary acquisition and spelling skills after the utilization of Wordscapes. Furthermore, statistical analysis indicated that demographic variables such as age, gender, and grade level had no significant relationship with the respondents’ post-test performance. The study concluded that Wordscapes is an effective supplementary learning tool that can help enhance students’ vocabulary acquisition and spelling skills. The findings imply that digital word games may be effectively integrated into classroom instruction to promote active learning, increase language proficiency, improve spelling competence, and motivate students to participate more actively in language-related activities.
Cabachete, RN., Joan P. Bacarisas, DM, MAN, RN, Krista May L.
This study assessed the work performance of nurses, examined the influence of personal characteristics on performance, and identified workplace challenges. A quantitative descriptive–correlational design was employed at a Level 2 hospital in Surigao City, Philippines with 299 nurses engaged in direct patient care participating. Data were collected using a structured Work Performance Questionnaire covering attendance, appearance, work habits, staff relations, patient communication, nursing care planning, safety, innovation, documentation, and technical knowledge. Descriptive statistics, multiple linear regression, and frequency analysis were applied. Most respondents were 18–35 years old, female, job-order nurses, and held a bachelor’s degree. Overall, nurses’ work performance exceeded requirements across all dimensions, with innovation, technical competence, and documentation showing the highest scores. Regression analysis revealed that age, sex, marital status, employment status, rank, and years of employment significantly predicted performance, whereas religion, education, area of assignment, and training attendance were not significant. The most reported challenges included staff shortages, heavy workload, low salary, limited advancement, and lack of training, which impacted productivity and motivation. Findings confirm that both individual characteristics and organizational factors shape nursing performance, consistent with the Job Demands–Resources Model. To sustain high performance and improve patient care, recommendations include staffing optimization, structured mentorship, equitable compensation, continuous professional development, and innovation-driven quality improvement initiatives.
Dr. Roshni Padate, Jahnavi Shah, Shreysh Nair, Tanish Ingole, Tanmay Mahajan
Antimicrobial resistance (AMR) is a rapidly growing problem in modern medicine. When doctors don’t know exactly which bacteria is causing an infection, they often prescribe broad-spectrum antibiotics. This practice actually speeds up the evolution of drug-resistant pathogens. The standard way to figure out which drug works is Antibiotic Susceptibility Testing (AST). However, AST requires physically growing bacteria in a lab, which can take anywhere from 24 to 72 hours. In this paper, we introduce Zenthera, a computational biology pipeline designed to skip this culturing step entirely. We built a system that uses raw Whole Genome Sequencing (WGS) data to predict resistance against 14 different antibiotics in real-time. Instead of slow genetic alignment, our pipeline uses a k-mer (k=7) frequency approach combined with TF-IDF vectorization. We trained Random Forest and XGBoost models on a dataset of over 100,000 bacterial genomes, achieving an average accuracy of 92.4% and an F1-score of 0.91. Because we used GPU acceleration, our system can process a genome and provide a clinical prediction in less than a second. To make this actually usable for doctors, we deployed the models inside a full-stack web application. Zenthera shows that we can eliminate the waiting time of traditional lab tests without losing accuracy.