171 Articles
Dr Breeze Tripathi
This study investigates the causal impact of Artificial Intelligence–driven Human Resource (AI-HR) systems on corporate tax structuring efficiency, GST automation accuracy, and regulatory compliance outcomes. Using a balanced panel of 420 firms observed from 2016–2024, we implement a Difference-in-Differences (DiD) framework comparing early AI adopters with non-adopting firms. Results indicate that AI-HR adoption reduces GST filing error rates by 18–24%, lowers compliance penalties by 21%, and improves effective tax planning efficiency by 12% relative to control firms. Event-study estimations confirm no pre-trend differences and reveal statistically significant post-adoption effects within two years. Robustness tests using alternative compliance proxies and placebo reforms validate causal inference. The findings demonstrate that AI-integrated HR systems function as internal governance enhancers, reducing regulatory friction and strengthening fiscal transparency.
Gaurav R. Awagan, Pranav V. Hegu, Pranjal A. Fuke, Prof. Priti P. Tijare, Rohan D. Dahatonde
Efficient management of intercity goods transportation is crucial for ensuring timely deliveries, operational efficiency, and customer satisfaction in logistics operations. Despite the growing demand for streamlined services, many traditional transport agencies continue to rely on manual or semi-digital methods for booking, driver allocation, shipment tracking, and billing. These conventional practices often result in delays, human errors, poor transparency, and suboptimal resource utilization. This paper proposes the Intercity Goods Transportation System (IGTS), a web-based platform developed to digitalize and automate transport agency operations. The system integrates key functionalities, including shipment booking, driver and vehicle allocation, billing management, and real-time shipment status monitoring within a centralized framework. Implemented using React.js for the frontend, Node.js and Express.js for the backend, and MongoDB as the database, IGTS ensures efficient data processing, secure record maintenance, and scalable architecture. By centralizing operations, IGTS enhances coordination among customers, administrators, and drivers while reducing paperwork and operational complexity. The system improves transparency, optimizes resource utilization, and increases overall service reliability in intercity goods transportation.
A. Wong Yoon Khang, David I. Forsyth
The deployment of more economical and cost-effective wavelength division multiplexing (WDM) solutions for access and metro networks still remains a key research focus. This paper reports on significant performance enhancement improvements of an economical, four channel totally incoherent spectrum-sliced DWDM system using a single high-powered LED source and incorporating semiconductor optical amplifiers (SOAs) as pre-amplifiers on each channel. The total length of the link ran for an unsurpassed maximum of 650 km at 10 Gb/s, whilst still yielding reasonable Q-factors and very high signal-to-noise ratios (SNRs).
Gautham. V, Pawan Kumar.V, Sakthi. S
The increasing usage of Artificial Intelligence (AI) tools in academic learning has completely changed the way students build and deliver their creativity. This abstract mainly examines the impact of AI tools on students’ creativity by combining findings from multiple studies taken place in digital learning environments. AI tools are majorly used by students for innovative and unique academic activities such as idea generating, content creation, completion of assignment, and project development. These tools help students by providing quick access to information, give ideas suggestions and support the students in creative and better ways in their academic learning. Research findings showcase that AI tools will have a positive influence on students’ creativity in academic learning when it is used in a limited and purposeful manner. Moderate use of AI tools encourages students to explore new ideas. However, the studies also point out certain negative effects when AI tools are used unthoughtfully or unethically. Excessive dependence in AI tools may limit the creativity and originality in their academic related works and personal contribution will reduce Feedback from students indicates lower personal contribution and reduced ownership of creative work when AI tools are heavily used for academic tasks, The overall findings give suggestions that there should be proper guidance and ethical use of AI tools in academics. AI tools should be a supportive resource rather than substitute for human creativity. Educators should motivate the students to use AI tools responsibly while making the personal contribution remain constant. In conclusion, AI tools have a positive impact on students' creativity in academic learning but balanced and ethical use of AI tools is necessary to sustain the originality of students' thinking in their academic learning.
Johny Lalthafamkima, Lalrintlunga Tlau, Saichampuii Sailo
Emotional intelligence (EI) and self-efficacy are two significant psychological constructs that influence adolescent adjustment, academic performance, and resilience. Emotional intelligence pertains to the capacity to perceive, comprehend, regulate, and utilise emotions effectively, whereas self-efficacy denotes an individual’s confidence in their ability to successfully complete tasks and attain goals. The present study examined the correlation between emotional intelligence and self-efficacy among higher secondary school students in Aizawl, Mizoram, and also investigated gender differences within these constructs. A sample of 265 students (124 males and 141 females) was selected via convenience sampling from three higher secondary educational institutions. Data collection was conducted through the Wong and Law Emotional Intelligence Scale (WLEIS) and the General Self-Efficacy Scale (GSE). Reliability assessments demonstrated satisfactory internal consistency for both scales (α = .79 and α = .76, respectively). Independent samples t-tests and Pearson’s product–moment correlation analysis were employed. The results indicated a moderate positive correlation between emotional intelligence and self-efficacy (r = .41, p < .01). Notably, significant gender differences emerged, with male students scoring higher on both emotional intelligence and self-efficacy. These findings underscore the importance of emotional competence in enhancing adolescents’ efficacy beliefs and imply potential applications for educational interventions.
Ajay Ramteke, Girish Katkar, Lekha Prajapati
The use of facial masks in the real-world setting has made the Masked Face Recognition (MFR) a critical research problem in Pattern Recognition. The classical face recognition technology is highly impaired in performance when the nose and mouth are covered as the main facial features. In this paper, a strong hybrid deep learning model will be suggested, which integrates the EfficientNet-B0 convolutional neural network with a self-attention mechanism to promote the learning of discriminative features on a partially visible part of the face. EfficientNet-B0 is also an efficient and scalable feature extractor, and the self-attention module allows global contextual reasoning and adaptable attention to unoccluded areas of the face, especially the periocular area. The suggested model is tested on the actual MFR2 dataset and has a recognition rate of 0.99, which proves to be better than the traditional CNN-based methods. The experimental test proves that the combination of self-attention can greatly enhance the resilience to the obstruction of the object by obstructing the features of the mask. The findings suggest that the hybrid architecture proposed is quite appropriate in real-time biometric authentication and surveillance and access control systems with masked environments.
Chayammagari Sanjeevani Kumari3, Chiyyati Amrutha, Dr. Venkateswara Reddy Vennapusa, Mangala Pavani, S Raghavendra, Yarragunta Charan Kumar Reddy, Yarraguntla Narayana Reddy
Major obstacles to temperature control in Electric Vehicle (EV) Battery Management Systems (BMS) include battery overheating, delayed cold-temperature charging, energy loss, decreased efficiency, cell imbalance, and long-term durability problems. Continuous monitoring of each cell’s voltage, current, and temperature along with microcontroller-based real-time data processing can successfully reduce these difficulties. Accurate State of Charge (SoC) and State of Health (SoH) estimation, thermal modeling, early fault diagnosis, and defect detection techniques all contribute to further advancements. This work proposes an intelligent and comprehensive BMS ar- chitecture incorporating advanced thermal management, cell balancing, and fire prevention strategies supported by gas and hazard detection sensors. The charging and discharging performance of the proposed system is validated using MATLAB/Simulink simulations. Experimental results from hardware implementation and real-time testing demonstrate significant enhancement in battery lifespan, charging efficiency, thermal stability, and vehicle safety. The system also strengthens fire hazard mitigation and improves battery reliability through effective cell balancing and gas monitoring. By resolving important safety and thermal constraints and enhancing overall charging performance and durability, the suggested design contributes to the development of safer, more intelligent, and more reliable EV battery systems.
Lucy Nneka Ugwu, Ugwu Edith Angella
Plant disease detection is critical for ensuring agricultural productivity and food security, yet the performance of machine learning models is often limited by the quality of input images. This study presents a robust image enhancement system designed to improve plant leaf images for machine learning-based disease detection. The system integrates three complementary techniques such as Non-Local Means (NLM) filtering which was used for noise reduction, then Wiener filtering used for image deblurring and Contrast Limited Adaptive Histogram Equalization (CLAHE) which was finally used for contrast enhancement and haze removal. Plant leaf images were collected from three farms in Uzu-Uwani, Enugu State, Nigeria and they underwent preprocessing steps including resizing, normalization and class balancing using SMOTE. Then the enhanced images were evaluated using a YOLOv5-based plant disease detection model for cassava and maize leaves. The results from the system implementation demonstrate that images processed with the proposed enhancement techniques significantly improved disease detection accuracy, thereby enabling the identification of multiple disease types that were otherwise missed in raw images. The findings highlight the importance of image enhancement in agricultural machine learning pipelines, providing a practical tool for researchers, agronomists, and farmers to improve disease monitoring and crop management.
Adewale Samuel Adeleye, Ayodeji Wasiu Alli-Balogun, Ignatius Adelakun Akerele, Oluwatimilehin Gabriel Oluborode, Oluwatosin Samuel Thomas, Tolulope Joy, Aladetohun
The study focuses on building collapse in Akungba-Akoko, Ondo State, Nigeria, with the aim of providing updated information that could enhance sustainable building development in the local communities of Ondo State. To achieve this, primary and secondary data were sourced for the study. Primary data were retrieved from structured questionnaire, oral interviews as well as field observation. The total number of questionnaires administered were twenty-two (22). A multistage-sampling technique was adopted for the study. The study revealed the top ranked causes of building collapse in Akungba- Akoko. These include the use of unskilled artisans/craftsmen; poor construction work; substandard materials and poor architectural; and structural designs defects. It was further established that poor quality of materials and workmanship accounted for more than 50% of causes of building collapse in the study area. The study concluded that there should be a review of existing building laws that will guide standard code of practice and all professionals in the built environment.
Afreen Begum, Pavan M, Prabhu Konar
This study fully analysing the level of carbon footprint awareness and sustainable behaviour among undergraduate student and postgraduate students. It mainly examines key dimensions that are environmental knowledge, identification of carbon intensive activity, attitudes towards sustainability, personal responsibility, institutional support, and willingness to adopt environment responsible action for the study. Primary data were collected from UG and PG 155 respondent using a structured questionnaire using simple random sampling and the data has been analysed using the statistical tools such as the Regression and the Annova , these indicates strong awareness and favourable attitudes toward sustainable behaviour from this result High levels of awareness observed in particular area such as energy conservation, waste management, environmental consciousness, reflecting the positive impact of academic exposure and campus-based sustainability initiatives. However, lower scores it's related to carbon footprint measurement and consistent sustainable practices it will highlight gaps between awareness and practical implementation. The study shows that environmental education is really important. We need to teach students about the environment in a way. Universities should also try to be sustainable. We should encourage students to behave in ways that help the environment. This is a thing because it will help students develop good habits that the students will keep for a long time. The environment is very important. The students can really help the environment by doing things that help the environment. This way they can help create people who really care about the environment. Which can make an impact on the sustainability in their working organisations which would lead to the development of the country and on how society thinks about the environment.
Dr. Asha John, Mr. Aiden Joseph, Ms. Merin Shijo
Employee motivation and retention are vital for sustaining service quality and competitiveness in the hospitality industry, particularly in five-star hotels where service delivery is highly employee driven. This study examines the factors influencing employee motivation and retention at Holiday Inn Kochi, Kerala, using a descriptive research design based on primary data collected from 60 employees across major operational and guest-facing departments. The results indicate a predominantly young and educated workforce, with 66.7% of respondents below 35 years of age, suggesting a higher vulnerability to attrition. Overall employee motivation was found to be moderate, with a mean score of 3.57 out of 5. Supportive leadership and job security emerged as the most influential motivational factors, while recognition practices, career guidance, and work–life balance were identified as key areas requiring improvement. Work–life balance concerns were particularly evident in guest-contact roles such as front office and sales and marketing, where job demands and stress levels are comparatively high. Nearly 40% of employees reported having considered leaving the organization, a trend closely associated with inconsistent recognition, limited feedback mechanisms, and inadequate communication regarding performance-based incentives. The study highlights the importance of adopting holistic human resource strategies that integrate competitive compensation, structured recognition systems, supportive leadership, effective communication, and flexible work arrangements to enhance employee engagement and retention in the hospitality sector.
Keerthana M, V Divya Jyothi
Mental health is a concern for students in higher education. They face a lot of pressure from academics not knowing what their career will be, issues and what their family and friends expect from them. Many students feel really stressed out and anxious. They have problems balancing college work and their personal life. It can be really tough. They worry about college work and their personal life a lot. These problems, with their health can make it hard for them to pay attention stay motivated and get good grades. So it is very important to understand what makes students feel stressed and how it affects the students. The main goal of this study is to look at how common stress among students What causes this problem. How does it affect the students grades and their mental health. The people who did the study used a list of questions with a simple rating system to get information from the students. The responses where collected from the 106 students in the study because these students and preferred the convenience sampling method to collect the data and it was analysed through a statistical tool using the regression analaysis The students filled out the survey, on the internet using Google Forms. The answers were analysed using statistics to see how stress factors relate to college performance. The questionnaire was tested to make sure it was reliable. The results show that many students have a lot of stress. College work and exams are things that cause stress for students. Family expectations and competition with friends also cause stress for students. Students also get stressed about problems and not knowing what their future job will be. When students have lot of stress it affects how well students focus on college work. It also affects the motivation of students and the emotions of students.
Nayana Shree. L, Sheetal Gowda
Technology has actually brought about a sea change in the way things function in the field of education in India. It is almost a game-changer that can actually help in making education more accessible to people and changing the way things are taught and achieving results in the field of education. Therefore, this paper will discuss how technology has evolved over the years in educational institutions. It will describe the use of concepts such as Learning Management Systems, Artificial Intelligence in Education, Virtual Classrooms and Video Conferencing, Smart Classrooms, Cloud Computing, E-libraries and Digital Resources, Learning Analytics, and Mobile Learning. These technologies can truly help students become more engaged and learn better. The study also examines some of the major challenges such as teachers not being prepared to use these new technologies, lack of appropriate infrastructure, and some people not having access to the internet. According to the paper, we need to enhance our infrastructure, help teachers become better at using technology, and collaborate with the public and private sectors to develop new technologies that will endure. If we harness technology in a manner that it will truly help make the Indian higher education system better and help us compete with other nations. Technology in the education sector, in India, is a very important issue and we should focus on it. Technology can bring a huge change in the Indian education system by providing better access and quality to education, and it will be very helpful for the readiness of the future of the country.
B. Prem Kumar3, Revanna Bhavya, Shruthi. K S
Digital platforms are now a part of college life. College students use mobiles, laptops, learning apps and social media every day for college and personal things. These digital tools make life easy because they can take classes, get college work, turn in homework and talk to teachers and friends without a lot of trouble. Digital platforms make learning easier and faster. Digital platforms also have a downside. When spending much time on digital platforms it can distract their focus. Media can be very distracting. getting a lot of notifications . It is hard for the students to concentrate on the work. If students sit in front of a screen for a time media can make them feel really tired, When they feel tired they don't have time paying attention to their college work. The digital platforms that affect their ability to focus on the studies. This study is, about the platforms and how they affect the ability of the college students to focus on their college work. The study looks at how the digital platforms affect and their ability to focus on their academics. It uses surveys that college students filled out and other research that has already been done to see what is going on with the platforms and college students. The research shows that digital platforms are helpful. The study aims to examine the impact of digital trends. The total sample size for the research design was 232 respondents adopted and primary data were collected using structured questionnaires. The study employed descriptive analysis to examine the relationship between digital platform usage and academic attention.
Bhavana D. S, Chaithra. N., Varsha V.
In recent era, the education system rapidly recognizes the students' wellbeing as a fundamental component in effective teaching. Contemporary teaching does not focus solely on academic performances and students also emotional stability, mental health. Teaching methods focus on creating a supportive learning environment, the students feel safe, motivated, confident, making them more useful and easier to understand. This examines various pedagogical methods which increases students’ wellbeing like positive learning, classroom learning method, teacher student’s healthy relationships. Which motivates the students to actively take part in everything, feel comfortable to communicate, share their opinions, ideas that help to collaborate deeply in the learning process. When teachers incorporate empathy and supportive teaching approaches, students may increase a strong sense of belonging, and trust the classroom. A strong environment fosters emotional resilience and supports students to cope up with effective academic challenges. Students’ wellbeing cantered teaching methods which actively engage and strengthen students cognitive and emotional outcomes. When students feel that they are supported, they are valued and concentrated on having creative problem-solving techniques, which naturally improves the effective learners. The study reinforces for the educational institution to enhance the wellbeing of students as a central component of learning practice. This adaptation helps the students to feel motivated, valued, supported and participated. Moreover, this study focuses on the role of effective classroom interaction and continuous interaction and guidance in maintaining students' engagement. By focusing on well-being and pedagogical methods they can support holistic development, enhance lifelong learning skills. Ultimately, this research concludes the priorities of student’s wellbeing is essential to create inclusive, engaging and cultivates both personal and academic growth.
Adam Tamimi, Faryar Etesami, Gabriel Tamimi, Hadi Khazaei, Majd Oteibi, Yousef Jasemian
Background: Breast cancer remains the most diagnosed cancer among women worldwide. Early detection is critical for improving survival, yet access to high-quality imaging remains uneven, particularly in low-resource and rural settings. Ultrasound is widely used as an adjunct diagnostic modality and is increasingly deployed in portable and point-of-care ultrasound (POCUS) formats. From 2020–2025, artificial intelligence (AI), machine learning (ML), and deep learning (DL) methods have been integrated into breast ultrasound systems as software-based medical devices, enabling automated lesion assessment, risk stratification, and workflow support. Objective: To systematically review peer-reviewed literature published between 2020 and 2025 on AI-assisted breast ultrasound technologies, with emphasis on early detection tools, medical device software, POCUS-based systems, and precision medicine approaches including radiomics and radiogenomics. Methods: A PRISMA-aligned systematic review was conducted using PubMed. Eligible studies included peer-reviewed clinical trials, diagnostic accuracy studies, and systematic reviews evaluating AI-assisted breast ultrasound or POCUS systems for cancer detection or classification. Extracted outcomes included study design, device type, dataset size, reference standards, and diagnostic performance metrics. Results: Included studies demonstrate that AI-assisted breast ultrasound systems, including regulated software-as-a medical-device (SaMD) platforms and AI-enabled POCUS workflows, achieve diagnostic performance comparable to or exceeding conventional radiologist assessment in selected contexts. That said, the existing studies are limited in number. Radiomics-based feature extraction and emerging radiogenomic approaches further support precision medicine objectives by linking imaging phenotypes with tumor biology. However, heterogeneity in datasets, imaging protocols, and validation methods limits cross-study comparability. Conclusion: Between 2020 and 2025, AI-assisted breast ultrasound evolved from experimental CAD tools into clinically evaluated medical device software, including applications in POCUS and low-resource environments. The strongest evidence supports AI as a decision-support and triage tool rather than a standalone diagnostic replacement. Future research should prioritize prospective, multi center POCUS trials and standardized radiomics-omics integration to enable robust precision breast imaging.
M Asif Chishti, Mehwish Iqbal, Muhammad Wajid Khan, Raees Abbas
Cloud computing has transformed the way organizations and individuals access and utilize computational resources by providing scalable, flexible, and cost-effective on-demand services. Efficient resource management is essential in dynamic cloud environments to maximize performance, ensure Quality of Service (QoS), and minimize operational costs. The following paper provides a systematic review of resource optimization methods used in cloud computing, namely, load balancing, task scheduling, and resource allocation. The review gives an extensive analysis of state-of-art algorithms, their merits, shortcomings, and applicability in certain contexts. It points out that there is no single algorithm that can be considered as the best one; the selection will be based on the nature of the application, workload, and infrastructure available. The results are of great use in guiding the researcher, practitioners, and cloud users that would like to optimize the use of resources, improve system performance, and reduce costs in various cloud settings.
Joshua Waithira, Ruth Chweya, Samuel-Soma M. Ajibade
The related advances on the Internet of Things (IoT) have grown vastly. IoT is the most challenging platform, but it holds real promise for revolutionizing all facets of education. Many countries are using digital technologies to provide communication. Introducing IoT technologies like Radio Frequency Identification (RFID) in education will enable connectivity, enhance effectiveness, and create knowledge sharing in the learning environment. However, there is still a need to understand the opportunities and constraints of RFID as an IoT technology in education. Therefore, this paper conducts a review of the significant opportunities and challenges for RFID in education. With the introduction of RFID technology into the education sector, it is significant to understand how RFID can benefit the learning environment and support pedagogy. Hence, we bring out the benefits of RFID in educational environments. The challenges of using RFID, like security and privacy, are also mentioned. The study on RFID will be significant in accelerating its use in learning environments. Lastly, the paper highlights some future suggestions.
Adarsh Kumar, Dr. Komal Tahiliani
Despite the increasing clinical demand for accurate and objective methods to evaluate Parkinsonian tremors, machine learning–based scoring aligned with the Unified Parkinson’s Disease Rating Scale (UPDRS) is still underutilized. This study addresses this gap by employing machine learning algorithms to predict UPDRS scores in a way that mirrors the evaluation approach used by neurologists in clinical practice. Although traditional methods such as Bayesian Networks, Decision Trees, and Artificial Neural Networks have been applied to Parkinson’s Disease (PD) detection, there is room for improvement in terms of classification accuracy and model robustness. In this work, we propose an enhanced classification framework based on Principal Component Analysis (PCA) combined with the K-Nearest Neighbors (KNN) algorithm to improve the diagnostic accuracy of Parkinson’s disease. The proposed methodology is implemented in a Jupyter Notebook environment using Python, which provides a flexible and open-source platform for data preprocessing, model training, and performance evaluation. Li-braries such as Scikit-learn, NumPy, and Matplotlib are utilized for dimensionality reduction, classification, and visualization, respectively. Performance evaluation based on accuracy and precision demonstrates that our PCA-KNN model significantly outperforms conventional methods, highlighting its potential as a reliable and efficient diagnostic approach for Parkinson’s disease. Index Terms—Parkinson’s Disease (PD),Unified Parkin-son’s Disease Rating Scale (UPDRS),Machine Learning,PCA-KNN (Principal Component Analysis – K-Nearest Neigh-bors),Classification ,Dimensionality Reduction Python.
Sumedha Arya
Retrieval-Augmented Generation (RAG) has emerged as an effective technique to reduce hallucinations in large language models (LLMs) but they follow a static retrieve-then-generate pipeline. This process is insufficient for complex financial question answering system that require multi-step reasoning, numerical precision, and factual verification. Therefore, in this research, we proposed an RL-Driven Agentic Multi-HyDE RAG framework designed to improve factual correctness and informativeness through structured reasoning and reinforcement learning optimization. The proposed methodology comprises of six major components: query diversification, hypothetical answer generation (HyDE), dense embedding-based retrieval, quadruple-based atomic knowledge representation, reinforcement learning-based evaluation, and tool-augmented refinement. Experimental evaluation on financial queries using Sentence Transformers, FAISS, and Mistral-7B-Instruct demonstrates that the framework achieves high factual alignment (faithfulness score = 1.0) while maintaining informativeness, without unnecessary calling of the external tools. The results indicate that integrating agentic reasoning, structured knowledge extraction, and reinforcement learning significantly overcomes hallucinations and improves reliability. The proposed architecture provides a scalable and robust solution for high-stakes financial question answering systems.
Le Hoang Nam, Le Ky Dien, Le Thi Kim Mai, Nguyen Van Chuong Tien*
The Vietnamese Mekong Delta is confronting double exposure to global climate change and anthropogenic stressors, notably accelerating land subsidence, sediment depletion, and protracted salinity intrusion. In this context, agricultural land-use transition has emerged as an inevitable livelihood adaptation strategy. Utilizing a systematic review approach integrated with the Sustainable Livelihoods Framework, this paper critically analyzes land-use dynamics in the Vietnamese Mekong Delta to elucidate the acute trade-offs between national food security, short-term economic gains, and long-term ecological integrity. The findings reveal that the legacy rice-first mandate and hard-engineering interventions have eroded natural capital and undermined the livelihood resilience of smallholder farmers, thereby exacerbating their vulnerability. The study also evaluates the paradigm shift in state policy from “controlling nature” toward “flexible adaptation”. By leveraging the transformative provisions of the 2024 Land Law regarding multi-purpose land use and land consolidation, the paper proposes the adoption of Adaptive Agro-Ecological Zoning to resolve fresh-saline water conflicts. These policy instruments provide a timely a legal foundation for reconciling economic development with environmental sustainability, while emphasizing the necessity of building robust social safety nets to protect marginalized communities during this sustainable transition.
Gopala Krishna Murthy H R, S. Shubhakar, Shubha. S
Artificial Intelligence (AI) has emerged as a transformative force in higher education assessment, particularly through automated grading and feedback systems. These AI-powered tools are reshaping higher education by addressing inefficiencies, subjectivity, and scalability limitations associated with traditional assessment methods. The rapid expansion of postgraduate programs, online learning environments, and large-scale digital classrooms has created an urgent need for assessment solutions that are scalable, consistent, and pedagogically effective. AI-based automated grading and feedback systems use machine learning, natural language processing, and deep learning techniques to evaluate student work and provide personalized feedback. This paper presents a comprehensive journal-level review of AI-driven grading systems, examining their historical development, methodological foundations, cross-disciplinary applications, educational benefits, ethical and technical challenges, and emerging research trends. The review finds that, when implemented responsibly with human oversight and transparent evaluation frameworks, AI-based assessment tools can significantly improve efficiency and support formative learning outcomes.
Dr R Anitha, Sabarinathan C, Sikkandar badusha A
Finding people who have gone missing is a very important problem for both the public and police. The usual ways of looking – manually going through lots of pictures and reports – take a long time and aren’t usually very good when there are big collections of images and information from the public. This paper describes an AI Missing Person Identification System, which uses deep learning and computer vision to find and pair faces in pictures people put in, with the faces in a database of people reported missing. The system combines face finding, getting the key features of faces, and comparing how alike faces are, all using convolutional neural networks. There is a website which lets people put up photos, put in reports about missing people, and do the automated matching. Testing showed the system is very good at finding matches, even if the light, how the person is turned, or the picture’s size isn’t ideal. This is a cheap solution, can be increased in size, and is good for organisations and the community to use.
Ankush Kumar, Siddhartha Negi, Tarunim Sharma, Vinita Tomar
In today’s competitive marketplace, accurately forecasting sales is crucial for business success. This article explores how artificial intelligence (AI) can transform digital marketing by utilizing advanced IT systems to collect and analyze customer feedback, providing valuable insights into consumer preferences and behaviors. The proposed method combines Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) to identify potential customers and uncover meaningful patterns in feedback. By integrating machine learning techniques, businesses can make data-driven decisions to refine marketing strategies, improve customer targeting, and personalize communication. This AI-powered approach enhances marketing performance by enabling more effective promotional strategies and better customer engagement, ultimately improving competitive positioning. By leveraging AI algorithms like SVMs and ANNs, companies can discover hidden patterns within large datasets, leading to better decision-making and increased customer satisfaction. The result is improved marketing efficiency and the ability to thrive in a more competitive environment, driving growth and fostering long-term success.
Alhaji Idi Babate, Aliyu Musa Bade, Musa Wakil Bara
The rapid expansion of Nigeria’s digital economy driven by fintech innovation, mobile banking, e-commerce, and post–COVID-19 digital transformation has been accompanied by a corresponding rise in sophisticated cyber threats. Artificial intelligence (AI) has emerged as a dual-use technology, enabling both advanced cyberattacks and innovative defensive mechanisms. This literature review synthesizes existing research on AI-driven cyber threats and AI-based defense strategies within the context of Nigeria’s evolving digital ecosystem. Drawing on nearly one hundred scholarly and institutional sources, the study examines the nature of AI-enabled attack vectors, criminal actors, sectoral vulnerabilities, and the socio-economic drivers shaping cybercrime in Nigeria. Key threats identified include AI-assisted phishing, deepfake impersonation, automated malware deployment, ransomware-as-a-service, and intrusion detection evasion, with the fintech, telecommunications, healthcare, and government sectors remaining the most exposed. The review further evaluates the role of AI in cybersecurity defense, including machine learning–based anomaly detection, intrusion prevention, incident response, and recovery systems. Governance challenges, regulatory gaps, workforce capacity limitations, and infrastructural constraints affecting effective AI adoption are also analyzed. Findings reveal that while Nigeria mirrors global cybercrime trends, unique local factors such as unemployment, digital financial inclusion, and limited enforcement capacity intensify cyber risks. The study highlights significant research gaps, particularly in AI ethics, data sovereignty, and localized cybersecurity frameworks. It concludes that sustained investment in AI-driven defenses, policy reform, and capacity building is essential for strengthening cyber resilience and safeguarding Nigeria’s digital economy.
Ali Baba Dauda, Barka Piyinkir Ndahi, Mohammed Shamsudeen Mamman, Onuche Gideon Atabo
Mobile Global Positioning System (GPS) tracking plays a critical role in navigation, logistics, personal security, and asset monitoring applications. However, continuous GPS polling on mobile devices leads to excessive battery consumption and increased network communication overhead. This paper presents the architectural design and prototype implementation of an adaptive mobile tracking framework developed for the Android platform. The proposed approach integrates motion-state detection using accelerometer-based Signal Vector Magnitude (SVM), velocity-adaptive sampling intervals, battery-aware modulation, and spatiotemporal filtering for GNSS data validation. The system is formulated as a multi-objective control framework balancing positioning accuracy, energy consumption, and network utilization. A controlled prototype implementation validates the functional feasibility and subsystem integration of the proposed optimization mechanisms within a real mobile environment. The work establishes a practical foundation for energy-aware and network-efficient mobile tracking systems, with comprehensive quantitative benchmarking reserved for future large-scale evaluation.
Guhan S, Milind Mallikarjun Kawachale, Sathish Kumar K
In this study, comparisons will be made between graduate students' reactions to semicircle seating and row seating, and an exploration will be made of the implications of each seating arrangement for participation, engagement, and democratic learning. This study will apply an evaluation of learning based on a 3D learning model that includes design, discipline, and participation. The primary data was collected from postgraduate students using a structured Google Forms survey. The research was descriptive in nature and centered on the meanings, experiences, and preferences of students in relation to seating arrangement configurations. In the questionnaire, students were asked questions concerning visibility of the teacher, interaction with other students, opportunity to speak with other students, degree of comfort to share ideas, and opportunity to work with other people. Most postgraduates reported a semicircular configuration of seating to be preferred to the conventional row setting. They indicated an improvement in the view of both the teacher and teaching aids, and thus understanding of a discussion topic was facilitated. Semi-circle seating made students talk more easily. It sparked more class discussion and made the room feel inclusive. It felt more democratic, one student said, and several others also said they now were more comfortable sharing their own thoughts in lectures and even classes. Some students mentioned limited classroom space for larger groups, yet they still preferred semi-circle seating. Participants said strong engagement and interaction outweighed the study’s limits. The study links semi-circle seating for postgraduates to stronger engagement, more participation, and better group learning. In grad seminars, flexible seating helps students join talks and decisions as equals. It helps instructors choose methods that boost participation and learning.
Asavari Barshikar, Harshada Wasade, Khushi Gelda, Pratiksha Sayam, Rajas Mudey, Vedanti Bhure
Background: Patellofemoral pain (PFP) is one of the most common causes of anterior knee pain in physically active individuals and young adults. Altered lower-limb biomechanics, proximal muscle weakness, poor neuromuscular control, and faulty movement patterns along the kinetic chain contribute to abnormal patellofemoral joint loading. Conventional physiotherapy approaches focusing solely on the knee may fail to address these contributing factors. Objective: To evaluate the effectiveness of an individualized kinetic-chain–based physiotherapy protocol on pain intensity, functional capacity, and movement quality in individuals with patellofemoral pain. Methods: A prospective interventional study was conducted on 40 participants aged 18–35 years diagnosed with patellofemoral pain. Participants underwent a 6-week individualized kinetic-chain–based physiotherapy protocol focusing on hip and trunk strengthening, lower-limb alignment, movement retraining, and patellar loading control. Outcome measures included the Numerical Pain Rating Scale (NPRS), Kujala Anterior Knee Pain Scale (AKPS), and single-leg squat quality assessment. Pre- and post-intervention scores were analyzed using paired statistical tests. Results: A significant reduction in pain intensity (NPRS) and improvement in functional outcomes (AKPS) were observed post-intervention (p < 0.05). Movement quality during single-leg tasks showed marked improvement, with reduced dynamic knee valgus and better trunk control. Conclusion: An individualized kinetic-chain–based physiotherapy protocol is effective in reducing pain and improving function and movement quality in individuals with patellofemoral pain. Addressing proximal and distal contributors within the kinetic chain enhances rehabilitation outcomes beyond knee-focused interventions alone.
Dr. Bhawanipal Singh Rathore, Dr. Kapil Kesari, Ms. Neha Sankhala
Sedentary service-sector work (banking, finance, information technology, public administration) is marked by sustained cognitive load, time pressure, and screen-mediated demands that can produce chronic stress with downstream autonomic imbalance, sleep disruption, and low-grade inflammation. Workplace yoga programs show promise for reducing perceived stress; however, mechanistically explicit models that also integrate feasible naturopathy elements are uncommon. This paper proposes an Integrated Yoga-Naturopathy Psychoneuroimmunology (IYN-PNI) framework for workplace stress. A theory-building narrative synthesis was conducted across psychoneuroimmunology, autonomic physiology, respiration science, chronobiology, and complementary lifestyle interventions. The model posits that yoga components (asana, slow-paced breathing, and meditation) primarily operate through vagal engagement and improved heart rate variability (HRV), reduced hypothalamic-pituitary-adrenal axis reactivity, and strengthened attentional control. Adjunct naturopathy components that can be implemented in routine work life (meal-timing strategies such as time-restricted eating, basic hydrotherapy such as warm footbaths, and morning daylight exposure) are positioned as modulators of metabolic-inflammation pathways, thermoregulatory relaxation, and circadian alignment, respectively. The framework specifies measurable mediators, moderators, and testable hypotheses suitable for pragmatic workplace trials, including dismantling and optimization designs. A tiered dose-sequence logic is presented to support scalable implementation in organizations with minimal disruption to operations.
Ilo Hammed Owolabi, Shoyanbo Moshood Olarewanju
Network analysis makes use of critical path method to effectively manage and execute projects. Every project must be properly planned, scheduled and its completion time accurately estimated. As a result critical path method (CPM) is useful tool in project management and scheduling. This study employed critical path method to estimate the duration of a project in a building construction project using a case study of KLM Building Firm. The research design adopted was analytical, as it was suitable for the nature of the work. Secondary data on project activities were obtained from the construction site and used for the analysis. The (TORA) software were used to run the analysis. The result shows that the CPM is high efficient in estimating project completion time. The initial completion time of 45 weeks were reduced to 31 weeks by applying the CPM techniques. Based on this findings, it is recommended that management adopt CPM for proper decision-making, as its helps to save labour cost, reduce project during and increase organizational productivity.
Hosne Ara Sharmin, Jowaher Raza, Muhammad Qumrul Hassan
Urban and industrial development, along with anthropogenic activities, lead to numerous threats to Bangladesh's water bodies. Over the years, Tongi Khal has been identified as being in a threatened condition due to these activities. This research presents dynamic changes in land use and land cover (LULC) and the condition of Tongi Khal by using GIS and remote sensing techniques. The LULC changes in the study area are illustrated using Landsat satellite images from 1990, 2000, 2010, 2015, 2020, and 2025 obtained through unsupervised classification and the Normalized Difference Vegetation Index (NDVI) method in ArcGIS 10.3. From 1990 to 2025, the LULC classification in the study area shows a reduction in water bodies and vegetation from 1990 to 2015, followed by an increase in vegetation in 2020 due to COVID19. In 2025, due to excessive industrial development, construction projects, canal infilling, and urban expansion, the waterbody was reduced, resulting in deterioration of the environmental conditions of Tongi Khal. Extensive urban development has led to the conversion of trees into grassland, bare land, and housing to accommodate population growth from 1990 to 2025. This study will enhance understanding of effective measures to control excessive anthropogenic activities and canal infilling, and to maintain water quantity and support natural restoration processes, such as at Tongi Khal. It will also contribute to future urban land-use planning and river management to tackle the ongoing, alarming pollution and unplanned industrialization.
Dr. Anjani Bhartiam, Dr. Arvind Kumar Sah
This study applies the quasi-lattice model (QLM) incorporating temperature- and composition-dependent parameters to predict the thermodynamic properties of liquid binary alloys. By focusing on key alloys such as Cu-Pb and In-Tl, the model effectively captures temperature-induced variations in free energy, entropy, heat of mixing, and concentration fluctuations. Validation against experimental data demonstrates the model’s capability to describe non-ideal mixing and phase stability, offering valuable insights for alloy design and processing optimization.
Adaobi Uchenna Onyecher, Andrew Wenibo, Ogechi Mercy Okorocha, Okorie Kelechi Blessing, Okuwa Joel Agwu
The declining productivity of agricultural soils in Nekede, Imo State, necessitates a functional assessment of their fertility status for sustainable crop production. This study evaluated and classified the fertility capability of soils in the Nekede area using the Fertility Capability Classification (FCC) system. Soil samples were collected from five distinct locations at two depths (0–20 cm and 20–40 cm) using a stratified systematic sampling design. Samples were analyzed for key physical and chemical properties following standard laboratory procedures. Results indicated that soils are predominantly sandy loam with high sand content (>75%) across both depths. Chemically, soils were strongly acidic, with mean topsoil pH of 5.1 and subsoil pH of 4.9. Low inherent fertility was observed, characterized by low organic carbon (1.2% in topsoil), deficient available phosphorus (9.5 mg/kg), low exchangeable potassium (0.15 cmol/kg), and a very low cation exchange capacity (<6.1 cmol/kg). Analysis of variance (ANOVA) revealed statistically significant differences (p < 0.05) between topsoil and subsoil for all major properties, including increased clay content with depth. Based on these properties, soils were classified under the FCC system as SBe⁺-ac-nk, indicating sandy topsoil with low CEC, a subsoil with higher clay content, aluminum toxicity, and deficiencies in nitrogen and potassium. Recommendations include the application of organic manure to ameliorate acidity, integrated use of organic and inorganic fertilizers to improve nutrient levels and retention, and adoption of conservation practices like mulching. This research provides a foundation for sustainable soil fertility management in the region.
Ejieta Julius Owhe
Microplastic contamination in urban river systems represents a growing environmental concern with implications for freshwater quality, ecosystem health, and downstream marine pollution. This study presents a systematic review of microplastic occurrence, distribution, and transport mechanisms in urban river catchments in the United Kingdom. Following PRISMA 2020 guidelines, 97 peer-reviewed studies published between 2012 and 2024 were systematically conducted, incorporating inter-reviewer validation, quality assessment criteria, and bias control measures to ensure methodological robustness. The results reveal pronounced spatial and temporal heterogeneity in microplastic contamination driven by urban land use, wastewater infrastructure, hydrological variability, and methodological inconsistency. Elevated concentrations were consistently associated with wastewater discharge points, combined sewer overflows, and high-flow events, while riverbed sediments act as long-term sinks and secondary sources. Polymer composition was dominated by polyethylene, polypropylene, and polyethylene terephthalate, with microfibres particularly prevalent in urbanised catchments. Analytical synthesis demonstrates that variation in sampling design, particle size thresholds, and polymer identification techniques significantly influences reported abundances and limits cross-study comparability. Interpreting the findings through a source–pathway–receptor and catchment systems framework highlights the need for integrated monitoring strategies and infrastructure-focused mitigation. The review emphasises the prioritisation of wastewater and stormwater controls within catchment management frameworks to reduce microplastic inputs to freshwater systems.
Nok Singh, Prof. (Dr) Shashi Punam
Malnutrition continues to be a significant societal issue in the country of India particularly among the vulnerable population groups, such as women and young children. The current research paper measures the nutrition of young children (0 to 6 years old) and women, and surveyed the awareness and uptake of the selected government nutrition and welfare programmes across the households of Below Poverty Line (BPL) and middle income in Dehra Block of Kangra District in Himachal Pradesh. A cross-sectional research design based on community was used. The 30 households that were used to provide primary data were selected through a structured questionnaire comprising socio-demographic factors, dietary habits, medical conditions, and awareness and use of welfare programs such as the Integrated Child Development Services (ICDS), POSHAN Abhiyaan and the Public Distribution System (PDS). The anthropometric indicators were height, weight and mid-upper arm circumference (MUAC), which are all measured under the standardized protocols and the outcomes were compared with child growth standards developed by the World Health Organization. The analyses performed were descriptive and comparative statistics to determine differences between the BPL and middle-income households. Findings reveal the gaps in knowledge and access to particular welfare programs, especially the POSHAN Abhiyaan, and permanent threats of anemia and malnutrition in children and women. Such results highlight the need to promote awareness initiatives, strengthen service provision through Anganwadi and ASHA employees, and interventions that would help to increase the impact of nutrition-related welfare programs at the community level.
Mae Shayne S. Mapatac
This study investigated the pedagogical approaches employed by criminology faculty members in higher education institutions across Cebu Province, Philippines, focusing on the implementation and effectiveness of these methods. As the criminology profession undergoes significant transformation, the adoption of sophisticated teaching strategies is essential to cultivate critical thinking and meet contemporary professional standards. Utilizing a quantitative, descriptive-correlational research design, the study systematically evaluated the implementation of learning objectives, faculty content knowledge, teaching strategies, instructional materials, and assessment techniques. The findings demonstrated that while faculty members possess a strong foundation in establishing clear learning objectives and exhibit a commendable mastery of their subject matter, significant pedagogical challenges persist. Specifically, the data revealed critical gaps in curriculum alignment and student engagement. Notably, the study established a significant positive correlation between the level of implementation and the perceived effectiveness of teaching strategies, confirming that the quality of instructional delivery is a primary driver of student outcomes. To address these challenges, the research proposes a framework for ongoing professional development and the strategic integration of educational technology. By advocating for a shift from traditional, lecture-based models toward more dynamic, studentcentered strategies—such as project-based learning and flipped classrooms—this study provides actionable insights for improving educational practices. Ultimately, the research emphasizes that pedagogical reform is necessary to bridge the gap between academic instruction and the complex, real-world demands facing future criminologists.
Mahima Chaudhary
Inclusive education seeks to ensure equitable and meaningful learning opportunities for all students, including those with disabilities, within mainstream educational settings. Although global advocacy frameworks and progressive legislative reforms have strengthened the rights-based foundation of inclusion, effective implementation remains complex and uneven across contexts. Literature published between 2000 and 2024 was analysed from major academic databases including ERIC, Scopus, Google Scholar, and Web of Science. The synthesis identifies recurring structural challenges such as inadequate teacher preparation, limited resources, rigid curriculum structures, attitudinal resistance, and weak policy implementation mechanisms. The review further highlights emerging issues such as digital exclusion, post-pandemic learning disparities, and evolving debates on inclusive pedagogy. Findings suggest that barriers operate as interconnected systems rather than isolated obstacles, reinforcing the gap between inclusive policy commitments and classroom realities. The analysis highlights interconnected obstacles, including inadequate pre-service and in-service teacher preparation, rigid curricula and assessment systems, insufficient infrastructure and funding, negative attitudes and stigma, parental and community resistance, and weak monitoring and accountability mechanisms. The literature further indicates that institutional constraints and socio-cultural biases reinforce one another, contributing to a persistent gap between policy commitments and classroom practice. The review concludes that meaningful inclusion requires coordinated, multi-level reforms encompassing professional development, curriculum flexibility, resource allocation, leadership capacity-building, community sensitization, and strengthened governance frameworks. Rather than isolated interventions, inclusive education demands holistic systemic restructuring aligned with principles of equity, social justice, and sustainable development.
Arisekola Akeem Akande, Olawale Basheer Akanbi
Financial markets rely on asset prices, which are often distorted by market frictions, liquidity constraints, and transaction costs, all of which influence a country’s structural credit risk. Traditional Markov Chain Monte Carlo (MCMC) estimation converges slowly and may not reliably capture rare, high-impact risks. To address this, the study develops a Bayesian structural credit risk model using Markov Chain Quasi-Monte Carlo (MCQMC) techniques, explicitly accounting for microstructure noise to improve the accuracy of asset value and default risk estimates in Nigeria. Comparative analysis shows that MCQMC achieves faster convergence, lower variance, and greater computational efficiency than MCMC, highlighting the benefits of noise-adjusted modeling for reliable credit risk assessment. The findings suggest that financial institutions should adopt MCQMC methods, while policymakers may consider incorporating noise-aware credit risk models into regulatory frameworks, offering a more robust and efficient approach to credit risk management in Nigerian financial practice.
Anu Dahiya
This paper advances the hypothesis that religion in Indian literature operates less as a theological inquiry into the nature of the “divine” and more as a socio-ethical arena in which the tension between individual agency and collective obligation is negotiated. Within the Indian intellectual and cultural context, the concept of Dharma (duty or righteousness) emerges as the central site of friction. Rather than functioning purely as a spiritual principle, Dharma frequently becomes the measure by which social conformity and moral deviation are judged. Through a comparative reading of classical and modern texts—from the ancient epics Mahabharata and Ramayana to modern Dalit narratives and the fiction of R. K. Narayan and U. R. Ananthamurthy—this study contends that “God” often functions as a literary device that personifies societal expectations rather than as an object of mystical contemplation. Divine authority in these works frequently mirrors the voice of tradition, community, and inherited norms. Thus, in these texts the divine is articulated within the social and cultural norms rather than standing apart from them.
Moon Das, S.N. Mohapatra
The ongoing research centres on the flow of tangent hyperbolic nanofluid over a Riga surface, affected by heat dissipation and radiative thermal effects. In the present study, the influence of nanofluid arises from the joint effects of Brownian motion and thermophoresis, driven by cross-diffusion phenomena and thermal radiation. As a novel approach, the bioconvection-induced motile microorganism, combined with higher-order chemical reactions, enriches the flow characteristics. The mathematical model obtained with the aforesaid assumptions is formulated and transmuted into dimensionless form by utilizing standard transformation rules. Moreover, the formulated problem is addressed numerically by utilizing the fourth-order Runge-Kutta approach via MATLAB’s embedded bvp4c solver. The distinctive response of diverse variables governing the flow dynamics is depicted through graphical representations, subsequent to corroborating the findings with prior studies.
Aditi Kaushik, Richa Mor, Sushila Kaura, Ujjwal Bhardwaj
Current dementia prevention strategies frequently rely on a generalized “one-size-fits-all” framework for risk assessment and clinical evaluation. However, it is evident that substantial biological, hormonal, and socio-behavioral differences between males and females influence both dementia risk and diagnostic accuracy. In this context, the effectiveness of the Brain Care Score (BCS), a 21-point modifiable lifestyle and health assessment tool is evaluated. By synthesizing data from large longitudinal cohort studies involving more than 250,000 participants, we highlight how incremental improvements in modifiable risk factors are associated with measurable reductions in the risk of dementia, stroke, and depression. Conventional diagnostic frameworks may underestimate early cognitive impairment in women. Studies indicate that women often demonstrate higher baseline memory performance and greater cognitive reserve, which can mask early disease manifestations during standard neuropsychological testing. This phenomenon may delay diagnosis despite the presence of underlying neuropathology. Integrating lifestyle-based risk metrics such as BCS with sex-specific biomarker interpretation, including patterns of Amyloid beta deposition and Tau pathology provides a more accurate assessment of early disease trajectories. Together, these findings support a more integrated framework for dementia prevention that combines lifestyle-based risk scoring with biologically informed, sex-specific diagnostic approaches. Such a strategy aligns with the broader goals of precision medicine by acknowledging that dementia risk and progression are shaped not only by modifiable lifestyle factors but also by sex-dependent neurobiological mechanisms. Incorporating both dimensions into clinical and research paradigms may improve early detection, refine risk stratification, and ultimately guide more effective prevention strategies tailored to individual patient profiles.
Maitri U. Patel, Neha Nakshiwala, Vaidehi J Mehta
Introduction: Elizabethkingia meningoseptica (EM) is a gram-negative aerobic organism commonly found in environment that can cause, outbreaks of neonatal meningitis and septicemia in immunocompromised children and adults. Although the incidence is higher in developing countries, having been isolated on contaminated medical equipments, especially in neonates. Case report: We have reported the case of a male neonate, born late preterm at 35 weeks and 3 days of gestation, diagnosed with hydrocephalus, underwent a surgical intervention for hydrocephalus in the early neonatal period. On the 28th day of life, the infant presented with fever and increased irritability. He was admitted to the NICU and commenced on intravenous amikacin. Blood cultures remained sterile; however, due to clinical suspicion of central nervous system infection, CSF culture was sent. CSF culture revealed growth of Elizabethkingia meningoseptica, identified via the VITEK automated system, confirming neonatal meningitis and timely managed with antibiotic therapy based on susceptibility testing. Conclusions: Elizabethkingia meningoseptica is associated with high morbidity and mortality, particularly in neonates. Early identification of the causative organism is critical for improving clinical outcomes.
Lee Zee Ang, Mohamad Noor Azeem Saini, Muhammad Aiman Haiqal Azizul, Nor Ain Nabihah Ahmad, Norhazren Izatie Mohd, Tan Yan Nee
Quotation management is a core pre-contract responsibility of quantity surveyors; however, in current construction practice, it remains predominantly manual, fragmented across emails, paper records, and isolated spreadsheets. Such practices contribute to processing delays, inconsistent data, limited cost transparency, and a higher risk of errors during the pre-contract stage. Despite the growing availability of digital tools in the construction industry, quotation management in quantity surveying continues to lack affordable, structured systems tailored to the operational needs of small- and medium-scale practices. To address this gap, this study proposes a centralized quotation management system in Microsoft Excel, integrated with Visual Basic for Applications (VBA). A system development methodology was adopted, comprising workflow mapping, identification of process weaknesses, system design, and prototype implementation. The proposed system design consolidates supplier quotations, material specifications, unit rates, and basic project indicators within a single platform, incorporating limited automation and data verification features to reduce duplication and improve record traceability. While the system was not empirically tested through live project deployment or formal user evaluation, the prototype demonstrates the practical feasibility of using spreadsheet-based tools to improve the organization, consistency, and accessibility of quotation data. The findings suggest that, although not a substitute for fully integrated commercial software, a structured Excel-VBA solution can offer a low-cost, transitional digital approach for enhancing quotation management in resource-constrained quantity surveying environments.
Dr. (Mrs.) Olabisi. B. Odewole, Prof. Tunji. T. Siyanbola, Tirimisiyu Gbadebo Ogunmefun
The integrity of financial statements remains a critical concern in Nigeria following high-profile corporate failures that have eroded investor confidence. The financial reporting users have seen financial reporting as a better way of measuring the firm financial success than mere disclosure of information. This has attracted considerable attention of scholars. While traditional corporate governance research focuses on board composition, this study examined the effect of CEO attributes on financial reporting quality of listed non-financial firms in Nigeria. Theoretically, this study is primarily underpinned by Stakeholder Theory, which posits that CEO attributes serve as a mechanism to balance the interests of diverse stakeholders through transparent financial disclosure. The methodology adopted an ex post facto research design covering all 104 non-financial firms listed on the Nigeria Exchange Group as at December 2024 over a thirteen-year (2015-2024) period. The study selected 80 listed companies in non-financial sector as the appropriate sample size using probability sample technique. To address potential endogeneity, simultaneity, and unobserved heterogeneity common challenges in corporate finance data the study utilized the Two-Step System Generalized Method of Moments (System-GMM) as the primary statistical estimation technique. The study found that the CEO attributes had jointly significant effects on Financial Reporting Quality of the listed non-financial firms in Nigeria with the probability of the f-statistics of 0.000. Findings from the System-GMM analysis revealed a statistically significant relationship between CEO attributes and financial reporting quality. Specifically, CEO financial expertise and gender (female representation) exhibit a significant positive effect on accrual earnings quality and timeliness (p < 0.01), suggesting that technical proficiency and diverse perspectives mitigate aggressive earnings management. Furthermore, CEO tenure showed a significant non-linear relationship with earnings persistence, indicating that while experience enhances quality initially, overly long tenures may lead to entrenchment. CEO nationality was found to significantly influence value relevance, reflecting the impact of diverse cultural and professional backgrounds on market perceptions of accounting information. The control variable, firm size consistently showed a significant positive association with reporting timeliness and value relevance, confirming that larger firms face higher pressure for transparency. The study concluded that CEO specific attributes are fundamental determinants of the integrity of financial disclosures in Nigeria. The integration of Stakeholder and Upper Echelon theories provides a robust framework for understanding how executive "DNA" shapes accounting outcomes. The study recommended that boards of directors prioritize a mix of financial expertise and gender diversity during the CEO succession planning process to enhance the long-term quality and persistence of earnings.
Jacob Anagra Sheehama, Julia Amadhila, Kristofina Tashiya Nambombola, Selma Ingandipewa Uushona
The prevalence of diarrhoea among rural children remain a big problem for the rural Namibian population, living on the verge of poverty. In most cases diarrhoea denotes to the passage of unformed watery, bloody or mucoid stools three or more than three episodes a day. In most developing and rural countries diarrhoea remain one of the leading cause of death among children underage of five globally. This study aimed to assess and establish the knowledge, of the children caregivers on home-based management of diarrhoea among children under the age of five at the outpatient department, Intermediate Hospital Rundu, Kavango East Region. This was a quantitative, descriptive, cross-sectional and analytical designs which employed on 400 caregivers at Intermediate Hospital Rundu Outpatient Department using a systematic sampling method. Knowledge, of caregivers were assessed by means of the five rating Likert’s scaled questionnaires. Data was prepared and entered through SPSS version 29 for analysis. Inferential and descriptive analysis were employed. The study shows, that out of 400 caregivers, 385 (96.3%) had good level of knowledge, 326 (81.5%) had negative attitudes, while 351(87.7%) had poor level of practice on homebased management of diarrhoea. Age was found to be significantly negatively correlated to the practice (r= -0.191; p<0.001). However, there was no significant correlation between age and attitudes and knowledge (r= -0.008; p<0.879) and (r= -0.019; p<0.710) respectively. In addition, attitude was found to be positively correlated to practice (r= 0.341; p<0.001). Knowledge was found to be positively correlated to the attitude (r= 0.206; p<0.001). Furthermore, the study discovered a significant positive correlation among knowledge and practices of the respondents (r= 0.322; p<0.001). In conclusion, it was recommended that the caregivers should be educated on home-based management of diarrhoea, in order to improve their knowledge, attitudes, and practices on homebased management of diarrhoea in children.
Bhawana Dahiya, M.Sc., Dr. J. R. Gaur, M.Sc., Ph.D., Shivani Surve, M.Sc.
An individual having two kinds of blood cell populations or two sets of deoxyribonucleic acid (DNA) types in different body tissues is called Chimeric and the situation is called as chimerism. This makes diagnosis and comparison of tissues for organ transplants and forensic investigations complicated and may lead to erroneous results. A few such cases, highly publicised in the past, have been mentioned in this paper. How chimerism affects DNA profiling results in forensic science and can lead to situations where the accused may be exonerated, and a genuine offspring of one’s parents may be denied parentage has been highlighted. How chimerism can be detected, and flawless reports can be given, the challenges faced in forensic cases have been mentioned in this paper.
Dr. Shubham Banolta, Dr. Shweta Gyanendra Shukla
Alopecia areata is an autoimmune condition marked by the emergence of non-scarring bald patches that impact the hair-bearing regions of the body. The scalp is the most frequently affected area. This condition can be likened to Indralupta in Ayurveda. The pathophysiology of Indralupta involves the disturbed Tridoshas and Rakta, which affect the scalp, along with the obstruction of hair follicles due to the exacerbation of Rakta and Kapha, ultimately hindering hair regrowth. Acharya Vagbhata refers to it as Kapalgata Roga, while Acharya Sushruta and Madhava Nidana classify it as a Kshudra Roga. Management is by the intralesional and topical corticosteroids. Shodhana (Raktamokshana) and Shamana Chikitsa is advised for the Indralupta in ayurveda classics.
Mr. Fardeen A. Khan, Mr. Tushar C. Agarkar, Ms. Dhanashree A. Alhat, Ms. Sanika P. Gole, Parag S. Mohod
In academic programs, especially for students pursuing a degree, projects are essential because they serve as a vital bridge between theoretical knowledge and practical application. It offers students the chance to take on real world problems, which develops their creativity, critical thinking, and problem-solving skills. Centralized platforms revolutionize project-based learning by connecting students and faculty, streamlining management, and fostering innovation. The existing systems provide several features such as task assignment, document sharing, and communication tools. While they facilitate some level of collaboration, these platforms often lack comprehensive functionalities for diverse project exploration, real-time progress tracking, and efficient project allocation. These platforms predominantly rely on traditional methods, often failing to adequately promote student-faculty collaboration and efficient project management. Very often the project management systems in the institute require a lot of paperwork, unable to efficiently track progress of project development and it is a time-consuming process. This platform emerges as an innovative solution to address multiple deficiencies faced by existing systems by providing a comprehensive project management system by fostering collaboration between students and faculty, offering remote accessibility, offering advanced project management tools, and enhancing user engagement through responsive design. It is providing features such as group formation, project tracking, ratings and feedback from faculties. Hence, project hub 's main goal is to transform an institution's project management system by establishing a creative and cooperative environment that improves the educational experience for faculties and students at educational institutions.
Alabi, T, Bosah, P. C, Okeke, C. H
Collective bargaining is an instrument use for conflict resolutions in any corporate organization. Its principal function is ensuring industrial peace especially in an organization that witness regular industrial crisis. The primary aim of this study is to examine factors affecting awareness of collective bargaining in Nigeria. It made use of descriptive survey design. The population was made up of all the workers in Imo state civil with a total population of 11200 and sample of 528 was selected using Blowers proportion allocation method (1967). The findings of this study show that awareness of collective was slightly poor due to many factors that were attributed to the government and union. There is a generally perceived relationship between awareness of collective bargaining and organizational stability. More so, collective bargaining characterised by good faith is still lacking in Nigerias’ public sector organizations. The study culminated with some recommendations among which is management and labour as social partners should also increase their capacities for effective collective bargaining practice by showing willingness and expanding cooperation to bargain in good faith in order to find common ground and resolve conflicts amicably. Also the union must promote inclusiveness and interval democracy in order to endear themselves more to workers.
Chukwuemeka Ifegwu Eke, Lisu Anne Mshelia
Innovation hubs are increasingly promoted as tools for inclusive urban development and poverty reduction, yet their sustainability in informal urban contexts remains uncertain. This article examines the role of community engagement in shaping the sustainability and poverty reduction potential of innovation hubs in urban slum settlements. Using a qualitative research design, the study draws on data from two focus group discussions conducted with residents of Tudun Wada, an informal settlement in Abuja, Nigeria. The discussions explored community perceptions of innovation hubs, forms of local involvement, and factors influencing long term relevance and impact. The findings show that community engagement is central to the success of innovation hubs, influencing local ownership, trust, participation, and collective action. Innovation hubs that are co developed with communities and embedded within existing social structures are more likely to remain relevant, accessible, and responsive to the livelihood realities of slum residents. In contrast, externally driven initiatives with limited community involvement tend to experience weak participation and reduced sustainability. The study demonstrates that community engagement enhances poverty reduction potential by aligning hub services with informal economic practices and strengthening social cohesion. The article concludes that innovation hubs in slum settlements must prioritise participatory governance, local leadership, and community driven decision making to achieve sustained and inclusive development outcomes. These findings contribute to debates on inclusive innovation and provide practical insights for policymakers and practitioners working in informal urban contexts.
Narendra Swaroop, Sunday Dogo
Topography influences soil physicochemical properties, directly impacting land management in the Indo-Gangetic Plains. To understand these effects, this study compared soil profiles from lowland and upland sites in the Mahewa district, Prayagraj, India. Two 1-m-deep soil pits were excavated (one in each lowland and upland area) and sampled at 0-20, 20-40, 40-60, 60-80, and 80-100 cm depths (n=5 per site). The properties analyzed included pH, organic carbon (OC), available nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), electrical conductivity (EC; indicates soluble salt content), and carbonate, using standard methods. Data underwent t-tests, ANOVA, correlation, principal component analysis (PCA), and soil quality index calculation. The results showed that lowland soils were characterized by higher available phosphorus (P; 25.4±1.3 vs 20.0±0.8 mg/kg; P=0.010), calcium (Ca; 2.34±0.12 vs 1.72±0.08 cmol(+) kg⁻¹; P=0.004), iron (Fe; 12.0±0.3 vs 8.64±0.3 mg/kg; P<0.05), and soil quality index (SQI; 0.73 vs 0.59), while potassium was numerically higher in the lowland (K; 119.8±17.9 vs 94.6±6.7 mg/kg) when compared to upland soils. Both locations had a neutral pH (around 7.0), indicating neither acidity nor alkalinity. Strong correlations were observed for organic carbon-nitrogen (OC-N; r=0.98), clay-silt (r=0.82), and pH-phosphorus (pH-P; r=0.71). Principal component analysis (PCA) results distinguished texture/fertility factors (PC1) from depth-related factors (PC2), confirming that topography significantly affected most examined properties (ANOVA, P<0.001). These findings suggest that topography influences soil heterogeneity in Mahewa; lowlands exhibit higher nutrient levels and higher overall SQI. Site-specific management may enhance sustainable agriculture in this region.
Dr Asavari Barshikar, Dr Harshada Wasade, Dr Pratiksha Sayam, Dr Vedanti Bhure, Dr. Khushi Gelda, Dr. Rajas Mudey
Background: Knee osteoarthritis (KOA) is a leading cause of chronic pain and disability globally. Although exercise therapy is recommended as first-line management, outcomes from unsupervised home-based programs are often inconsistent. Supervised multimodal physiotherapy may provide superior clinical benefits through individualized progression and neuromuscular retraining. Objective: To compare the long-term effectiveness of supervised individualized multimodal physiotherapy (MPP) and conventional structured home-based exercise (SHE) in adults with early-stage knee osteoarthritis. Methods: A 12-month prospective observational cohort study was conducted among 200 adults aged 40–70 years with radiographically confirmed Kellgren–Lawrence grade I–II KOA. Participants selected either supervised MPP (n=100) or SHE (n=100). Primary outcomes were WOMAC Pain (0–20) and WOMAC Physical Function (0–68). Secondary outcomes included adherence rate and effect size magnitude. Mixed-effects linear regression models adjusted for baseline age, sex, BMI, and baseline WOMAC scores were used. Effect sizes were calculated using Cohen’s d. Results: At 12 months, MPP demonstrated significantly greater reduction in WOMAC Pain (adjusted mean difference −1.92; 95% CI −2.41 to −1.43; p<0.001; d=0.78) and improvement in WOMAC Function (adjusted mean difference −9.47; 95% CI −13.02 to −5.92; p<0.001; d=1.61). Improvements exceeded established MCID thresholds. Significant group × time interaction confirmed sustained superiority (p<0.001). Conclusion: Supervised individualized multimodal physiotherapy produces clinically meaningful and statistically robust improvements compared to home-based exercise in early KOA.
Nnaoma Ikenna Elvis, Okwuego Peter Obinna, Orakwue Foster Chikeobi, Saater Mstushima Jennifer
Transform Infrared (FTIR) spectroscopy was employed to investigate and compare the caffeine-related functional groups present in different varieties of kola nuts obtained from Oba, Anambra State, Nigeria. The kola nut varieties analyzed include White Hausa kola (Cola nitida), Red Hausa kola (Cola nitida), Four-lobed Igbo kola (Cola acuminata), and Common Igbo kola (Cola acuminata). FTIR spectra were recorded in the range of 4000–650 cm⁻¹ at a resolution of 4 cm⁻¹ using an ATR-FTIR technique, and the results were compared with a standard caffeine spectrum. Characteristic absorption bands corresponding to key caffeine functional groups such as C–H, C=C, C=O, C=N, and C–N were identified across all kola nut varieties, confirming the presence of caffeine. White kola and Common Igbo kola exhibited absorption bands most closely aligned with the standard caffeine spectrum, while Red kola showed minor frequency shifts. The Fourlobed Igbo kola displayed more pronounced deviations, particularly in the C–H stretching region, likely due to interactions with other phytochemical constituents. Overall, the study demonstrates that FTIR spectroscopy is an effective, rapid, and non-destructive technique for identifying and comparing caffeine functional groups in different kola nut varieties, while also revealing varietal differences influenced by their molecular environments.
Afouda Bamidele Imogirie
Recovery after orthopedic surgery largely depends on the quality and effectiveness of rehabilitation. Traditionally, conventional physiotherapy has been the main approach used to restore movement, strength, and functional independence. In recent years, virtual reality (VR)–based rehabilitation has emerged as an innovative alternative that combines therapeutic exercises with interactive digital environments. This review compares the outcomes of conventional physiotherapy and VR-based rehabilitation among post-orthopedic surgery patients, using clinical experiences and available evidence relevant to Awka, Anambra State, Nigeria. The review focuses on functional recovery, patient engagement, balance, pain management, and overall rehabilitation outcomes. Evidence from recent studies suggests that while both approaches improve physical function, VR-based rehabilitation may enhance patient motivation, adherence to therapy, and balance performance. However, challenges such as cost, limited infrastructure, and lack of technical expertise may restrict widespread adoption in low- and middle-income settings. The review highlights the potential of integrating VR into rehabilitation practice in Awka as a complementary tool rather than a replacement for conventional physiotherapy.
Agu Onyebueke Edward, Emmanuel Siman, Madugu Jeremiah Omanga, Saraso David Lami
The increasing integration of information and communication technologies into smart power grids has significantly improved operational efficiency but has also introduced critical cybersecurity vulnerabilities. Among emerging threats, botnet attacks pose a serious risk to smart grid cyber-physical systems due to their distributed, adaptive, and coordinated nature. This study presents a comparative performance analysis of three neural network–based techniques, Artificial Neural Networks (ANN), Deep Neural Networks (DNN), and Long Short-Term Memory (LSTM) networks, for detecting botnet-induced anomalies in smart grid environments. To guarantee fairness and repeatability, the models were trained and assessed using a publicly accessible smart-grid cyberattack dataset under similar preprocessing and experimental settings. Standard assessment measures, such as accuracy, precision, recall, F1-score, convergence behavior, and confusion matrix analysis, were used to gauge performance. The findings show that DNN produces better accuracy and overall classification stability through richer feature representations, whereas ANN offers a robust baseline with good recall. Because it can incorporate temporal relationships in smart-grid data, the LSTM model performs superior to both ANN and DNN on all measures, exhibiting greater accuracy and balanced detection capabilities. These results show that temporally aware deep learning models provide notable benefits for detecting coordinated botnet attacks and emphasize the significance of model architecture choices in cyber-physical intrusion detection. The study provides valuable insights for researchers and practitioners seeking effective data-driven security solutions for protecting critical smart grid infrastructure.
Prashant Modani, Suraj Bharad
In modern steel construction, reducing self-weight while maintaining structural adequacy is a key design objective. Castellated steel beams, fabricated by introducing web openings into rolled I-sections, are widely recognized for their enhanced depth and improved structural efficiency. This study presents a comparative investigation on the weight efficiency of castellated steel beams versus conventional rolled steel beams designed for identical loading and span conditions. Beams with spans of 10 m, 13 m, and 16 m are designed in accordance with IS 800:2007 provisions. Finite Element Analysis (FEA) is carried out using ANSYS to validate structural performance in terms of stress and deflection. The results highlight that castellated beams achieve significant weight reduction—up to 20–25%—without compromising serviceability or strength requirements. The study establishes castellated beams as a structurally efficient and economical alternative to conventional steel beams in long-span applications.
Adebowale T. Odunafolabi, Lere P. Oluwadare, Odutola I. Odetunde, Olubunmi O. Ogein, Oluwaseye F. Oyeniran, Oyindamola O. Aderinto, Pauline K. Akowundu, Sampson C. Aliozor
Background: The neonatal period is defined as the duration from the time of birth to the end of the first 28days of life. Events preceding this period and the perinatal events can have a lasting impact on the outcome of the neonates. The study aimed to describe the indications for neonatal admission and the outcomes at a new tertiary healthcare facility. Materials and Methods: Descriptive, retrospective study which reviewed the electronic medical records of all neonates admitted into the neonatology unit of the Redeemer’s Health Village, Ogun State, Nigeria between June 2024 and November 2025. Data extracted include age (in days), gender and the primary diagnosis at admission. The main outcome was either discharge or death. Results: The total number of neonates admitted during the period reviewed was 41. There were 18 males which accounted for 43.9% of the admission. The male to female ratio was 1.0:1.3. Majority (61%) were inborn. Prematurity accounted for majority of the cases (39.0%), closely followed by neonatal jaundice (34.1%). The least cases that were admitted include infants of diabetic mother (4.9%) and tracheo-esophageal atresia (2.4%). The median duration of admission was 6 days (IQR 3,19 days). The survival rate was 82.9% while mortality accounted for 17.1% of the total admissions. Majority of the neonates that died were outborn and most deaths occurred within the first week of life. Conclusion: Neonatal morbidity and mortality are distinct entities that deserve more attention in order to attain the third item of the sustainable development goal. Prematurity remains a leading cause of admission at neonatal units globally. Extreme prematurity (gestational age at birth < 28weeks) is very challenging to manage especially in resource-limited settings. Neonatal outcomes can be greatly improved upon with adequately supervised obstetric care as a specific intervention measure.
Adit Jha, Dr Shveta Shah, Jitin Kumar, Unnati Gandhi
The rapid growth of the electronic devices market, particularly smartphones, has intensified competition among brands and increased the importance of effective marketing strategies in influencing consumer behaviour. This study examines the impact of marketing strategies on consumer purchasing behaviour toward smartphones, with special reference to product features, pricing, promotional activities, and brand image. The research adopts a quantitative and empirical approach, using primary data collected from 500 smartphone users through a structured questionnaire. The collected data was analysed using the Statistical Package for Social Sciences (SPSS) employing descriptive statistics, correlation analysis, chi-square tests, and multiple regression analysis. The findings reveal that marketing strategies have a significant influence on consumer purchase behaviour, with product features and brand image emerging as the most influential factors. The study also identifies a significant association between demographic variables and smartphone brand preference. Regression results indicate that marketing strategy variables explain a substantial proportion of variance in purchase intention. The study provides valuable insights for marketers and practitioners to design consumer-centric marketing strategies in the highly competitive electronic devices market.
Aira Shane E. Vistal, AJ Mie B. Puerin, Angelo Jet U. Reserva, Honey May L. Betarmos, Jack Paitan, Joselito Y. Bulabos, Joyce Grace T. Selma, Rhona Mae L. Sanico, Vanessa E. Babatuan
This study developed and evaluated the Smart Spray Pest Response System (SSPRS), a solar-powered, automated pest control device designed for smallholder rice farms. The system integrates an ESP32-CAM for real-time image capture and pest detection process, and a relay-controlled centrifugal pump that activates spraying only when pest presence reaches a predefined confidence threshold. An experimental design was employed to compare SSPRS with conventional pest control methods in Barangay Mantalongon, Sagbayan, Bohol. System performance was assessed based on technical reliability and pest mortality. Results indicated that SSPRS achieved a mean mortality of 18.5 golden apple snails (32%), compared to 19.5 snails (39%) in the control group, with no statistically significant difference (p = 0.86). Although SSPRS did not outperform conventional methods in mortality rate, it demonstrated stable power management, reliable logic flow, and precise, event-driven spraying. Variations in environmental conditions, pest density, and detection accuracy likely influenced system performance. Future research should enhance image recognition accuracy, optimize spray timing, and conduct longer field trials to improve effectiveness and scalability.
Eferhi Adakpo
Digital transformation has become a major driver of competitiveness, efficiency, and sustainable economic growth across industries and national economies. This review paper examines the evolution of digital transformation and business systems innovation, with emphasis on the roles of business analysis, agile methodologies, data-driven decision-making, and enterprise system modernization. Drawing from existing literature and industry practices in telecommunications, fintech, and service sectors, the paper explores how technology-enabled solutions enhance organizational performance, promote financial inclusion, and support digital governance. Furthermore, the review discusses the importance of digital transformation to national economic interests in strengthening technological competitiveness and expanding the digital economy. Therefore, by incorporating theoretical frameworks and practical insights, this paper highlights success factors, challenges, and future directions for organizations and policymakers seeking to leverage digital transformation for inclusive and sustainable development.
Agbili Martin Onyedikachukwu, Ogbo Ojiako Godfrey
This study examined distance-based variations in environmental noise levels in residential areas surrounding two major market hubs, Amaenyi and Eke Awka, in Awka South Local Government Area, Anambra State, Nigeria. Anchored on Distance-Decay Theory, the aim was to determine whether noise intensity decreases with increasing radial distance from market cores and to assess compliance with World Health Organization (WHO) and National Environmental Standards and Regulations Enforcement Agency (NESREA) residential limits. A cross-sectional field measurement design was adopted. Ambient noise levels were recorded using a calibrated digital Sound Level Meter, and equivalent continuous sound levels (Leq) were measured across three radial bands: 0–50 m, 50–100 m, and beyond 100 m. Descriptive statistics, percentage attenuation analysis, and linear regression were used to evaluate spatial patterns. Results indicate a clear inverse relationship between distance and mean noise levels. At Amaenyi, mean levels declined from 89.6 dB (0–50 m) to 75.4 dB (>100 m), while Eke Awka showed a reduction from 101.1 dB to 82.5 dB. Regression analysis confirmed strong distance–noise relationships (R² = 0.972 and 0.841, respectively). However, all measured values exceeded WHO (55 dB) and NESREA (50 dB) residential limits across all distance bands. The study concludes that although attenuation occurs with distance, existing spatial separation is inadequate to ensure residential acoustic safety, highlighting the need for improved land-use planning and regulatory enforcement
Gerald Muzaare, Kenneth Okello Otieno
Although the information and communication technology (ICT) sector is key in stimulating innovation and economic growth, gender inequality is still a complex and systemic issue in the industry. This research endeavors to understand the structural, cultural, and institutional mechanisms underlining the gender inequality in the ICT industry that have led to the long-term marginalization of women as well. Based on narrative literature review, the articles are recent and influential work reviewed for the period 2015-2025 taken from the major databases Scopus, Web of Science, IEEE Xplore, ACM Digital Library, and Google Scholar. The results indicate that gender differences in the ICT sector are the result of several intersecting reasons such as the under-representation of women and girls in STEM education, unconscious male biases in recruiting and promoting female employees, work–life balance challenges and motherhood penalties, the majority-male organizational environment, intersectional discrimination, and restricted access to entrepreneurial funding. The paper illustrates that these have all compounded each other and the cycle of inequality in relation to ICT is self-perpetuating. The authors propose that ameliorating gender inequality will demand comprehensive and multi-staged strategies, including educational reform, systemic organizational policies that welcome all employees, bias-informed hiring practices, work-life balance policies, and structured support to support women entrepreneurs. It advocates long-term, context-specific, and intersectional interventions that could drive a more equitable, innovative, and inclusive ICT sector
Bandi Honey, Chilakala Hansika, Dr. M. Ayyavaraiah, Samudrala Amrutha
This paper proposes an improved method for autonomous landing scene detection for drones. The study addresses challenges that arise when similar environments appear different at varying altitudes. Using deep learning methods and a hybrid ensemble technique, the proposed system improves the accuracy and reliability of landing scene recognition. The proposed system achieved approximately 97.65% accuracy using transfer learning models such as ResNet50 and ResNext50 combined with a hybrid Random Forest classifier. Transfer learning techniques using ResNet50 and ResNeXt50 models are applied to the LandingScenes-7 dataset to identify safe landing locations in real time. Thresholding techniques and a novelty detection module enable the system to handle unpredictable environmental conditions and provide confidence-based classification decisions. This research has significant applications in drone technology, particularly in logistics, emergency response, and surveillance. The proposed system enhances drone intelligence and improves operational safety in dynamic environments by enabling reliable autonomous landing decisions.
Abd. Rahman Ahlan, Adeleye Dupe Ayesha, Najhan Muhammad Ibrahim
E-government initiatives in West Africa have expanded over the past decade, yet adoption and implementation remain uneven across the sub-region. This structured narrative review synthesises peer-reviewed scholarship published between January 2015 and December 2025, identified through targeted searches in Scopus, Web of Science, Google Scholar, conference proceedings and authoritative grey literature, including United Nations E-Government Survey reports, World Bank datasets, and national digital strategy documents, to provide policy context. The review is organised around recurring analytical categories in the literature, including digital inclusion and infrastructure, citizen engagement, transparency and anti-corruption, cybersecurity and data protection, service delivery outcomes, and institutional capacity. Across these domains, the literature points to three consistent findings. First, access constraints and high connectivity costs continue to shape who benefits from digital public services. Second, weak institutional capacity and limited interoperability often produce fragmented implementation even where national strategies exist. Third, trust-related factors remain decisive for sustained uptake, particularly cybersecurity governance and data protection enforcement. Comparative indicators further reveal divergent trajectories within the sub-region, with Ghana performing ahead of many peers on the United Nations E-Government Development Index (EGDI), while Nigeria remains in the middle tier despite major reforms. This review consolidates dispersed regional evidence within a single analytical frame, clarifies the determinants most consistently associated with e-government adoption in West Africa, and identifies priorities for both implementation and future research.
Dr. Sanjeev Kumar Jha
Brick kiln emissions contain toxic heavy metals which pose serious threats to soil enzyme activity. Present study was conducted for the evaluation of effect of brick kiln on four soil enzyme activity (dehydrogenase, phosphatase, urease and arylsulfatase). The selected brick kiln was situated in Sulindabad village of Saharsa district. Enzyme activity was tested as a distance of 100m, 200m, 300m, 400m and 500m away from brick kiln. For control, enzyme activity was tested in soil samples collected 1km away from brick kiln. The enzyme activity was lowest at a distance of 100m away from the brick kiln and remain poor up to 500m away from brick kiln.
Asavari Barshikar, Harshada Wasade, Khushi Gelda, Pratiksha Sayam, Rajas Mudey, Vedanti Bhure
Background: Mechanical low back pain (MLBP) is highly prevalent among desk job workers due to prolonged sitting, static postures, and reduced physical activity. Sustained sitting postures lead to muscular fatigue, reduced lumbar mobility, and functional disability. Dynamic sitting exercise has been proposed as a simple workplace-based intervention to counteract these effects. Objective: To evaluate the effect of dynamic sitting exercise on pain intensity, lumbar range of motion, and quality of life in desk job workers with mechanical low back pain.
Asavari Barshikar, Harshada Wasade, Khushi Gelda, Pratiksha Sayam, Rajas Mudey, Vedanti Bhure
Background Upper-limb fracture malunion is a common musculoskeletal complication resulting in persistent pain, altered biomechanics, restricted mobility, and functional disability. Conventional physiotherapy commonly emphasizes range of motion and muscle strengthening but may inadequately address functional performance required for daily activities. Task-oriented rehabilitation, based on motor learning principles, emphasizes repetitive, goal-directed functional tasks and may enhance functional recovery. Objective To evaluate the effect of short-term task-oriented rehabilitation on disability and pain in individuals with post-fracture upper-limb malunion. Methods A single-group pre–post interventional study was conducted on 20 participants aged 18–60 years with upper-limb fracture malunion of ≥3 months duration. Participants underwent a structured 2-week task-oriented rehabilitation program consisting of 45-minute sessions, three times per week. Disability was assessed using the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire, and pain intensity was measured using the Visual Analog Scale (VAS). Pre- and post-intervention outcomes were analysed using the paired t-test, with the level of significance set at p < 0.05. Results Results: DASH scores improved significantly from 52.3 ± 8.7 to 34.6 ± 7.5 (p < 0.001). VAS scores reduced from 6.1 ± 1.2 to 3.2 ± 1.0 (p < 0.001). Conclusion Short-term task-oriented rehabilitation significantly reduces disability and pain in individuals with post-fracture upper-limb malunion and may serve as an effective clinical approach for improving functional performance and independence.
Asavari Barshikar, Harshada Wasade, Khushi Gelda, Pratiksha Sayam, Rajas Mudey, Vedanti Bhure
Background: Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disorder predominantly affecting small joints of the hands, leading to pain, deformity, and functional disability. Conventional physiotherapy focuses primarily on pain relief and strengthening; however, structured task-specific dexterity training targeting functional hand activities remains underexplored. Objective: To evaluate the effect of task-specific hand dexterity circuit training as an adjunct to conventional physiotherapy on pain and functional disability in individuals with rheumatoid arthritis. Methods: A quasi-experimental comparative study was conducted over 12 months in a tertiary care teaching hospital. One hundred participants diagnosed with RA (ACR/EULAR 2010 criteria) were recruited through convenience sampling and allocated into experimental (n=50) and control (n=50) groups. Both groups received supervised physiotherapy sessions (40 minutes/day, 5 days/week) for four weeks. The control group received conventional physiotherapy, while the experimental group received 15 minutes of conventional therapy followed by 25 minutes of task-specific hand dexterity circuit training. Pain intensity was assessed using the Numeric Pain Rating Scale (NPRS) and functional disability using the Health Assessment Questionnaire Disability Index (HAQ-DI). Paired and independent t-tests were used for statistical analysis (p<0.05). Results: Both groups showed significant within-group improvements (p<0.001). The experimental group demonstrated greater reduction in NPRS (6.9±1.2 to 3.1±0.9) compared to the control group (6.8±1.1 to 4.8±1.0). HAQ-DI scores improved significantly in the experimental group (1.86±0.38 to 1.15±0.26) compared to the control group (1.82±0.36 to 1.50±0.32) (p<0.001). Conclusion: Task-specific hand dexterity circuit training combined with conventional physiotherapy provides clinically meaningful improvements in pain and functional disability in individuals with rheumatoid arthritis.
Lisy M Thomas, Sonal Sahai
This analytical review explores the effectiveness of Artificial Intelligent Tutoring Systems (ITS) for academically underprepared learners in STEM higher education. The study synthesises recent advancements in generative AI and ITS, examining their potential to deliver personalised instruction, adaptive feedback, and scalable learning environments. It highlights the architectural components and operational mechanisms of ITS, evaluating their strengths in fostering academic improvement. The paper identifies key limitations including challenges in real-time adaptability, equitable access, and ethical data management, as well as concerns regarding the reliability of online assessments and the ability of ITS to replicate nuanced human guidance. The review calls for future research on emotion-aware computing, collaborative learning, explainable AI, emphasising the necessity for ethical, transparent, and accessible ITS solutions. Ultimately, the article argues that while ITS platforms hold significant promise for transforming STEM education and supporting underprepared learners, their success depend on continual innovation, robust evaluation, and a commitment to educational equity and excellence.
Moh. Awaludin Adam, Salnida Yuniarti Lumbessy, Shahib Daraji Samami
The cultivation of seaweeds under controlled conditions represents an important alternative for achieving stable and high-quality production. Halymenia durvillei is a red seaweed species with considerable potential for cultivation using controlled media. This study aimed to evaluate the effects of different planting distances on the growth performance and survival rate of H. durvillei cultured under controlled conditions. The experiment was conducted from May to July 2025 at the National Research and Innovation Agency (BRIN), Pemenang District, North Lombok Regency, West Nusa Tenggara, Indonesia. An experimental approach was employed using a Completely Randomized Design (CRD) consisting of four planting-distance treatments with three replicates: 30 cm (P1), 25 cm (P2), 20 cm (P3), and 15 cm (P4). The parameters observed included absolute weight gain, specific growth rate, survival rate, thallus length, number of thalli, and water quality. Seedlings with an initial weight of 5 g were cultured for 30 days. The collected data were analyzed using analysis of variance (ANOVA), followed by Duncan’s multiple range test using SPSS software. The results indicated that planting distance significantly affected absolute weight gain and specific growth rate, but had no significant effect on the survival rate of H. durvillei. Planting distances of 30 cm (P1) and 25 cm (P2) produced comparably favorable outcomes, yielding absolute weight gains of 5.20 g and 5.49 g, respectively, and specific growth rates of 2.32% day (P1) and 2.47% day (P2). In both treatments, thallus length reached approximately 1 cm, supported by an average thallus number ranging from 32 to 70. Throughout the cultivation period, water quality parameters remained within optimal ranges across all treatments, with temperatures of 25–26°C, pH values of 7.87–8.13, and salinity levels of 30–31 ppt.
Abu Nasar Md. Aminoor Rahman, Eti Begum, Md. Golam Haider, Md. Taimur Islam
The present study was untaken to use essential oils in Swiss albino mice in the department of Pathobiology. Essential oils (Eos) are concentrated liquids of complex mixtures of volatile compounds. Essential oils are a good source of several bioactive compounds, which have antioxidative and antimicrobial properties. The experiment was carried out on Swiss Albino mice (Mus musculus). Twenty-Five (25) mice of 7 days old were bought from the Animal Resource Center, ICDDR, B. The collected mice had neither any developmental disorders, detectable genital diseases nor other diseases that may cause any problem in the experiment or affect the result of the experiment. Twenty-five (25) mice at 21 days old were randomly used for the experiment and the mice were divided into five groups and each group will consists of five mice. Groups I, II, III & IV received orally Pulmo Gold 1ml/5L water, Activo Powder -100mg/kg feed, Reference liquid-5ml/1L water and Respocare liquid-5ml/1L doses of the essential oils, respectively. Group-V (control group) will be supplied with normal foods and ad libitum water. In case of control group (group-V), the body weight gaining rate is lower than the other treated groups. The highest number of microorganisms are found in control group and 4 samples are contaminated with microbes out of 5 samples incased of kidneys and intestine. On the other hands 5 samples are contaminated incased of liver. The lowest number of organisms are found in group II (Activo Powder) and 1 sample of kidney, liver and intestine are associated with microorganisms.
Dr Bharati Khasnis
In today’s rapidly evolving educational landscape, teachers must be empowered with new competencies to address dynamic classroom challenges. This research explores the role of teacher empowerment in fostering effective 21st-century classroom practices. It examines teacher readiness, professional development strategies, technological fluency, and collaborative learning cultures. Through mixed-method analysis, this study presents key factors that contribute to empowering teachers to enhance student learning and overall school quality.
Harisun Yaakob*, Heeswari A/P Logamoorthy, Norhashimah Hussin, Thathram Palli Adil Mubarak, Wong Hui Lin
This review critically reassesses the analytical dichotomy between Macro and Micro-parameters to propose a validated, synergistic Data Fusion framework that bypasses the “Adulteration Gap” and the “Economic Wall” in global food systems. A systematic review was conducted utilizing a tiered search strategy across Scopus, Web of Science, and Google Scholar. The methodology progressed from macro-level contextual filtering (drivers like the “Three Lethal Cs”) to micro-level technical validation of instrumental data, culminating in a nexus integration that cross-references socio-economic impacts with forensic protocols. The study identifies that traditional Macro analysis (proximate composition) is vulnerable to sophisticated fraud, as demonstrated by the melamine nitrogen loophole in milk. Conversely, Micro analysis (HPLC, IRMS) provides essential forensic specificity, identifying isotopic fingerprints in honey, but is often hindered by high operational costs. Industrial applications reveal that transitioning from “Lab” to “Line” via Process Analytical Technology (PAT) and utilizing Green Chemistry (NADES) effectively mitigates matrix interference and reduces waste. An integrated Nexus approach, employing rapid Macro-sensors as a first line of defense followed by targeted Microverification, provides a legally defensible and commercially viable standard. This framework contributes significantly to socio-economic protection, public health safety, and global environmental sustainability by bridging the divide between bulk composition and trace molecular integrity.
Ugo Donald Chukwuma
This study presents a comparative analysis of three transfer learning-based models such as EfficientNet, Vision Transformer (ViT), and ResNetfor predicting pluvial flood. A flood dataset comprising 144,401 records with eight key conditioning variables was collected from Kaggle repository organized by the United States Geological Survey (USGS) and Copernicus Climate Data Store and was further used for the implementation of this study.Additionally, historical rainfall and meteorological data were obtained from the Nigerian Meteorological Agency (NiMet) through their official data request portal.Subsequently, the dataset was pre-processed by cleaning and normalizing, transforming features and augmenting them, and partitioned into training, validation and testing sets. All the models were pretrained on ImageNet weights and trained to learn flood-specific spatial patterns. As the experimental findings indicate, ViT has the best accuracy (93.1%), F1-score (0.925), and AUC-ROC (0.95) that are used to capture long-range spatial dependencies. EfficientNet was more accurate (92.3) and had the highest F1-score of 0.915; however, it took the least amount of time to be trained, which is acceptable in terms of real-time use. ResNet obtained 91.5% accuracy and 0.905 F1-score, showing stable feature acquisition at a modest computational price. The paper shows the success of transfer learning in improving the flood prediction in low-data areas. Generally, ViT should be used in the context of high-accuracy, EfficientNet in the context of computational efficiency, and ResNet in the context of robust and reliable modeling. These results help to justify the creation of AI-based flood early warning systems to enhance urban flood risk management.
Cheick Abou COULIBALY, Cheick Oumar BAGAYOKO, Hamadoun SANGHO, Oumar SANGHO, Ousmane LY, Safiatou SAMASSA, Salia KEITA, Souleymane DIARRA
Introduction: The District Health Information Software 2 (DHIS2) is a free open-source software platform for data collection, analysis, visualization, and sharing. It is the most widely used platform within the health information system worldwide. It is implemented in Mali for service delivery, monitoring, and evaluation of health programs. The aim is to assess data quality and the effective use of DHIS2 in monitoring malaria and vaccination programs. Materials and Methods: This is a secondary analysis of DHIS2 survey data from a mixed cross-sectional study conducted from September 2023 to September 2024. Results: The use of DHIS2 has improved data quality by enhancing completeness and timeliness to 91.7%. Internet connectivity issues were most frequently identified as a factor preventing the use of DHIS2 at 83.3%. The adoption of the DHIS2 allowed the identification of malaria cases in 30%. DHIS2 made it possible to identify community health centers with low vaccination coverage in 30% and to carry out activities in these districts to raise their level by 20%. It improved the archiving and securing of real-time data in 36.1% and saved time by 43%. Conclusion: The evaluation of DHIS2 made it possible to determine the level of DHIS2 performance and to identify some of its strengths and weaknesses.
Divya Patel, Miralkumar Parmar, Pratibha Sharma, Prof Jay Parmar, Shainesh Shrivastava, Suzan Lakhani
The Evently-AI-Powered College Event Management System is a web-based platform designed to modernize how academic institutions plan, manage, and evaluate college campus events. College event planning can be time consuming and based on manual data processing, which can lead to scattered and broken communication at various stages. These outdated methods lead to delays, miscommunication and limited outreach for organizers and participants. Evently addresses the limitations of traditional, manual event coordination. The proposed system centralizes event-related tasks, minimizes administrative workload, and enhances student engagement through an intuitive, AI-supported interface. It offers role-based dashboards for administrators, faculty, and students, enabling each group to access functions specific to their responsibilities. Key features include event proposal workflows, participant registration, feedback collection, real-time analytics, and media sharing. AI integration will further strengthen the platform through personalized event recommendations and a chatbot assistant for event discovery. Through this platform, users will be able to quickly register online and navigate through current or future events, sign up for the events and get timely reminders, making it efficient and accessible for both students and administrators. The research carried out for this project employed following key strategies: background research and literature review to identify key gaps in the existing systems, technical research, system development, data collection and analysis. Next, project planning, architecture development and system implementation were executed. The end result-Evently-was user-tested both from admin and user side. The technology stack comprises Laravel for backend operations, ReactJS for a dynamic interface, and AI modules for chat and analytics. Overall, the system improves coordination, transparency, and decision-making within campus events. By automating routine tasks and taking advantage of data insights, colleges can promote increased student participation and operational efficiency by taking advantage of Evently, and while doing so, fundamentally shifting how events are managed on campus.
Chelcia B Sangma, Dr. S. Thanigaivelan
The rapid development of artificial intelligence has revived enduring philosophical questions about the nature of consciousness, mind, and moral responsibility. This paper examines whether advanced AI systems could possess forms of awareness comparable to human consciousness. It analyzes the implications of such a possibility through major philosophical perspectives, including dualism, physicalism, functionalism, and panpsychism. By evaluating contemporary debates in philosophy of mind alongside current technological progress, the study investigates whether consciousness is an emergent property of complex computation or a fundamentally non-computational phenomenon. The ethical dimension is central to this inquiry: if AI were to attain conscious states, issues concerning moral status, rights, accountability, and the boundaries between human and machine agency would arise. The paper also considers the risks of prematurely attributing consciousness, which may distort ethical decision-making and public understanding of AI. Ultimately, this study argues that philosophical reflection is essential for guiding responsible AI development, ensuring that technological innovation remains aligned with human values, dignity, and social well-being.
Baby Faith S. Juson, Brent Lee C. Delfino, Divine Mae P. Añasco, Jane Antoneth D. Palma, Jeian B. Doblado, John Carlo C. Divinagracia, Joselito Y. Bulabos, Junel Benedict F. Niñeza, Scarlett Claire A. Buscato
This study investigated the feasibility of Aero-Hydro Generator as a dual system for atmospheric water harvesting and small scale renewable energy generation. Using a research and Development (R&D) approach guided by Engineering Development Model (EDM), a prototype combining mist collection, micro-hydrogenerator, and Arduino -based automation was designed , constructed, and tested in San Agustin, Sagbayan, Bohol. Descriptive statistics (mean, confidence interval and standard deviation) were used to assess performance in water efficiency and power output. Based on the results, the prototype achieved acceptable water efficiency but produced power output was low. Although the prototype has power generation limitations, the results demonstrate functional stability and potential to be a water harvesting system and alternative renewable energy source for rural communities.
Hemlata, Sanjay Issar
In this paper, we introduce and investigate a new subclass of meromorphic p-valent functions, denoted by 〖MS〗_(p,q)^* [b;C], defined in the punctured unit disk U^*. The definition of this class is characterized by a subordination condition involving the q-derivative operator and a specific subordinating function, C(z)=1+4/3 z+2/3 z^2, which maps the unit disk onto a Cardioid-shaped domain . We first establish a necessary and sufficient condition for functions to belong to this class using the Hadamard product (convolution). Subsequently, we derive sharp bounds for the first two initial Taylor-Laurent coefficients |a_(1-p) | and |a_(2-p) |. In addition, we also deal with the Fekete-Szegő functional |a_(2-p)-μa_(1-p)^2 | for both real and complex parameters μ. The results obtained in this work generalize several existing findings in the literature and highlight the geometric impact of the Cardioid-shaped domain on meromorphic p-valent starlike functions.
Jayaprada Dash, Prof. Ganesh Sethi
Odisha, as a culturally rich state, folk media plays an indispensable role in protecting the history and cultural identity from generation to generation. Due to the lack of accessibility and availability of other media, it became very popular in disseminating information, education, and entertainment among rural people. Among all kinds of folk media, folk dance and folk music are the most renowned media for their vibrant music and graceful body movements. In this study, various renowned folk dances, including Gotipua, Dalkhai, Dhemsa, Bagha Nacha, and Mayurbhanj Chhau, are discussed. The study further explores the role of folk dances as agents of social and behavioural change. For this, a qualitative methodology and descriptive method are used to determine the importance of folk dance in shaping social and behavioural change. The research reveals that folk dances are not only for entertainment purposes, but also have major contributions towards national development.
Aminah Awang, Mohamad Faizul Yahya, Suzaini Abdul Ghani
Plastic pollution is a critical environment issue, with significant plastic waste contaminating soil, oceans, and the atmosphere, posing serious health risks. Kibria et al., (2023) emphasize the need for innovative solutions to manage plastic waste. This research analyzes the relationship between textile structure and the physical and mechanical characteristics of plastic bottle yarn and kenaf yarn textiles. Three weave structures—plain weave, twill 2/2, and twill 3/1—were tested by their tensile strength, percentage crimp, weight, and thickness. A control sample made entirely of kenaf yarn was also subjected to analysis for comparison. The statistics were used to analyze the data in order to determine the correlations among these variables. The findings indicate that fabric structure significantly influences mechanical performance. The twill 3/1 weave had the highest thickness (3.84 mm) and weight (8.021 g/cm²) and is therefore the strongest, while the plain weave had the lowest thickness (2.85 mm) and weight (6.544 g/cm²) and is therefore most appropriate for lightweight applications. Tensile strength tests confirmed that twill 3/1 weaving structure was more effective than the other structures. Additionally, percentage crimp differed, with higher percentage crimp in the control sample (100% kenaf) and better dimension stability for fabrics with plastic bottle yarn. These results affirm the influence of fabric construction to determine performance as well as durability. The study also establishes the economic and environmental worth of plastic bottle yarn in sustainable textile production. For example, in Bangladesh, which is becoming a top manufacturer of recycled yarn and fabrics. Future research should examine larger populations and advanced testing methods to further optimize recycled textile applications.
Michael Okyere
This study investigated teachers’ attitudes toward the integration of Information and Communication Technology (ICT) in lesson delivery in basic schools in the Central Region of Ghana. Despite increasing global advocacy for ICT in education, the extent to which basic school teachers adopt and use ICT tools remains uneven. A quantitative research design was employed, using a structured questionnaire administered to 300 teachers selected through stratified random sampling. Data were analyzed with the Statistical Package for the Social Sciences (SPSS), and the reliability of the instrument was confirmed with Cronbach’s alpha values above 0.90 across all sections.
Ajewole K. P, Akinyele T. W, Odukoya E.A, Ogunwale O.D, Olayinka K. P
The paper proposes a new family of continuous distributions called the Gamma-Exponential-Exponential distribution (GEED). It is based on the T X construction of Alzaatreh et al. (2013) by considering Gamma-Exponential distribution for T and the exponential as the distribution of X. Some of useful mathematical and statistical properties such as the moment method, moment generating function, characteristics function skewness and kurtosis, are derived, and a number of important statistical characteristics of this family are investigated the method of maximum likelihood estimation is used to estimate the model parameters. The usefulness of this family of distributions is demonstrated via simulated experiments aiming to assess their performances
Jitendra Kumar, Praveen Kumar
Molecular characterization using protein profiling is a crucial technique for understanding genetic variability among plant accessions. The present study investigates the genetic diversity among five Pisum sativum accessions using protein banding patterns, similarity indices, and statistical analyses. SDS-PAGE was employed to assess the presence or absence of protein bands with different molecular weights. The protein bands were analyzed based on their molecular weights (kDa), and the presence or absence of specific bands was recorded across different accessions. The similarity index was calculated to assess the genetic relationships among the accessions. Our findings provide valuable insights into the genetic diversity of Pisum sativum accessions, which may aid in breeding programs and disease resistance studies. A paired t-test and Pearson correlation matrix were used to analyze statistical significance and genetic relationships. The results indicate both conserved and polymorphic protein bands, highlighting genetic variation among the accessions. The paired t-test showed no statistically significant differences between accessions, while the Pearson correlation analysis suggested varying levels of genetic similarity. These findings provide valuable insights for breeding programs aimed at improving disease resistance and adaptability in Pisum sativum.
Achigbulam Charles, Adewunmi Andrew Adesanmi, Ajayi Oluwajuwon Emmanuel, Biliaminu Samuel Akeem, Mannir Abdu, Olalekan Awolola, Sani Khadijat, Shubham Singh
Nigeria’s electricity sector continues to experience chronic shortages despite abundant natural resources. This study assesses the spatial potential of onshore wind energy across Nigeria through integrated Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA). Hourly wind data from NASA POWER and ERA5 reanalysis were extrapolated to 150 m hub height and combined with topographic, land cover, and socio-environmental datasets to evaluate national wind suitability. The analysis reveals a pronounced north–south gradient in wind resources, with the northern regions exhibiting higher mean wind speeds and more favourable topography for large-scale wind power development. Using the Analytical Hierarchy Process (AHP), suitability was classified into three categories (Most Preferred, Preferred, and Least Preferred) based on wind potential, land-use conflicts, and population pressure. The Most Preferred zone, covering approximately 18 % of Nigeria’s land area, lies predominantly in the northern savanna belt, offering the greatest opportunity for utility-scale deployment. The resulting spatial classification provides a strategic framework for targeted wind energy investment and forms a foundation for subsequent techno-economic and policy assessments.
Prof. Abhijit Dutta
Green finance has emerged as a critical tool for mobilising capital towards climate-friendly and sustainable development goals in India. As the country pursues ambitious targets for renewable energy, net-zero emissions, and sustainable infrastructure, understanding the institutional frameworks, financial instruments, challenges, and opportunities surrounding green finance is essential. This article provides a comprehensive review of the evolution and current landscape of green finance in India, examines key mechanisms such as green bonds and climate finance, and discusses policy initiatives, barriers to growth, and future pathways for sustainable finance.
Tafara Marazi
The article presents a critical analysis of the prevailing paradigm of Information and Communication Technology (ICT) integration within the educational systems of third world countries. It argues that in the 3rd decade of the 21st century implementation models, the use of ICT functions more as a multifaceted curse than a blessing. Moving beyond techno-optimistic narratives, the analysis deconstructs the profound dissonance between the global discourse of ICT as an indispensable catalyst for development and the on-ground realities of systemic failure in the Global South. It examines the concatenation of barriers—including the crippling infrastructure chasm, unsustainable donor-driven projects, and a profound human resource crisis characterised by inadequate teacher training and policy voids—that render most initiatives ineffective. Pedagogically, the article details how ICT can foster cognitive dependency, erode foundational skills like handwriting and critical thinking, and introduce significant distractions and psycho-social risks. Furthermore, it interrogates ICT's role as a vector for a new form of digital neo-colonialism, entrenching economic dependency and facilitating cultural homogenisation that threatens indigenous knowledge systems. While acknowledging the contested terrain of potential benefits, the article contends these are contingent upon optimal conditions conspicuously absent in most third-world contexts. The conclusion is a clarion call for a radical paradigm shift towards context-sensitive, sustainable, and empowering reformation. The shift prioritises foundational human and systemic capacity over hardware procurement, champions locally relevant content and open-source solutions, and re-centres the goal on solving specific educational challenges rather than mimicking Western technological models, thereby transmuting ICT from a latent curse into a genuine tool for endogenous development.
Dr. S. Shanmugavadivu
This study aimed to investigate the effect of Simplified Kundalini Yoga (SKY) on stress levels among college students. A total of 24 undergraduate students from Nallamuthu Gounder Mahalingam College, Pollachi, Coimbatore District, Tamil Nadu, were randomly selected. Among them, 10 were male, and 14 were female students. A pre- and post-intervention survey was conducted to assess changes in stress levels. The participants were specifically advised to practice SKY Yoga for 12 weeks. Stress levels were measured using the Perceived Stress Scale developed by Sheldon Cohen. Results were evaluated using both numerical and categorical scales to determine whether the scores fell into low, medium, or high stress categories. The study revealed significant improvement after 12 weeks of SKY Yoga practice. Before the intervention, the participants’ mean stress score was 28.25. After the intervention, the mean score decreased to 11.33. This reduction indicates a significant decrease in stress levels among the students. The findings suggest that Simplified Kundalini Yoga is an effective approach to reducing stress among college students.
Dr. B. B. Baridam, Ndueso, Etukudo Ekefre, Prof. C. Ugwu
In studying Blockchain Technology, one of its predominant applications that have provided a massive growth in their recent global acceptance and market capitalization in the past few years is cryptocurrencies. Individual investors, notable institutions and corporate firms are readily investing in it. Predicting cryptocurrency prices owing to their volatile nature has been a challenging decision for researchers owing to social and psychological factors that affect price of cryptocurrency. Substantively, the crypto market is highly volatile when compared to the traditional commodity markets and may be affected by factors like sentimental, legal and other technical indicators. The uncertainty and unpredictable nature of cryptocurrency necessitated this study on Improved Intelligent Model for Cryptocurrency Trading in Blockchain Platform. The five cryptocurrencies utilized in this work were Bitcoin (BTC), Ethereum (ETH), XRP, Cadona (ADA), Solana (SOL). This study incorporated Bi-LSTM and Attention Mechanism techniques with trading strategies like buy, sell or hold depending on the choice of the investors. It is depicted that our model yields more accurate and reliable predictions when confirmed alongside with the Live price time-based model. This work provided with guarantee an interface that can be used by investors especially those in cryptocurrency trade for accurate predictions as it will go a long way in extenuating investment risk. This research adopts Object-Oriented Programming (OOP) methodology to design and implement an intelligent cryptocurrency trading system. This study was implemented using C# Programming Language with incorporation of python.NET. The system can be used in real-time scenarios as it is well trained and evaluated using standard data sets. The result depicted that this new system predicts cryptocurrency prices with high accuracy compared to the existing system. The outcome of this study assured us that our approach enhances the necessary assurance on the new system and offers customers a more reliable financial service in cryptocurrency trade.
Asemota E. E., Nnanna-Ekeoma C., Obeagu, A. I., Okore, O. O.*, Ugwuanyi K. C., Ukpai O. M.
Nauclea latifolia has been used locally as herbal remedies for treatment of helminthic infections and other some other ill conditions. In this study, the phytochemical profile and the vermicidal activities of N. latifolia leaf extracts, Stem bark extracts and combination of the two extracts were evaluated in Heligmosomoides bakeri infected mice. Extracts prepared from the plant were subjected to phytochemical and acute toxicity evaluations. For the vermicidal trials, in-vitro study model were employed. The in-vitro study was carried out by applying the extracts to the worms in Petri dishes before larval counts in accordance with standard protocols. Results obtained from the phytochemical tests on the leaves and stem extracts revealed the presence of significant amounts of Saponins, Flavonoids, Terpenoids, Tannins, Alkaloids, Phenolics and Cardiac glycosides. Steroids were obtained from the stem bark extract. Acute toxicity of 3,807.87mg/kg and 2,828.43mg/kg body weight were obtained for the leaf and stem bark extracts. The result obtained in the in-vitro model did not show significant fall in larval count in all the extracts when compared with Albendazole. Therefore, Nauclea latifolia may not be a safe and effective alternative vermicidal agent pending in-vivo trials of the plant.
Dr. Ajay Ramteke, Dr. Girish Katkar, Shalaka Gaikwad
Indian Sign Language (ISL) recognition plays a vital role in bridging the communication gap between the hearing-impaired community and the general population. This research presents an efficient deep learning-based approach for static ISL alphabet recognition using transfer learning with MobileNetV2. A dataset consisting of 26,000 images representing 26 alphabet classes (A–Z) was used. The proposed model leverages a pre-trained MobileNetV2 backbone for feature extraction, followed by custom classification layers. Experimental results demonstrate a high validation accuracy of 99% and test accuracy 99.89%, indicating the effectiveness of the approach for real-world ISL recognition tasks.
Dr. K. Parthasarathy, Laisa Paul
Menarche is a critical developmental milestone for adolescent girls, yet in India, menstruation remains shrouded in silence and stigma. Inadequate menstrual health management (MHM) can transform a normal biological process into a source of anxiety, shame and disruption, potentially affecting mental wellbeing. This study investigates the influence of menstrual health management on the mental health of adolescent girls in Thrissur district, Kerala. A cross-sectional descriptive research design was employed among 660 adolescent girls aged 13–18 years enrolled in secondary and higher secondary schools across Thrissur district. Schools were selected from both urban and rural areas, representing government, private and aided institutions. Data were collected using a structured, validated questionnaire translated into Malayalam, with Cronbach's alpha coefficients ranging from 0.78 to 0.89. Analysis employed descriptive statistics, Chi-square tests, ANOVA, Pearson's correlation and structural equation modeling using SPSS version 26.0. Menstrual problems (97.5%) and health issues (94.0%) were the primary reasons for school absenteeism, with 43.3% reporting irregular attendance. Nearly half (49.3%) of adolescents experienced high mental health impact due to reproductive health concerns, including emotional distress (48.5%), anxiety and stress (45.3%), self-esteem issues (45.2%) and social isolation (42.3%). Significant associations emerged between mental health impact and type of school (χ²=13.286, p<0.05), parent-child communication (χ²=23.303, p<0.01) and age (F=6.826, p<0.01). Path analysis revealed that while mental health impact does not directly influence reproductive health knowledge, attitudes and practices (KAP) (β=-0.009, p=0.875), it strongly predicts social stigma (β=1.344, p<0.001), academic participation (β=0.932, p<0.001) and social participation (β=0.796, p<0.001). Standardized coefficients confirmed the strongest effect on social participation (β=0.817). Correlations revealed that KAP protects against stigma (r=-0.165, p<0.001) and that academic and social participation are closely interconnected (r=0.527, p<0.001). Menstrual health significantly influences adolescent mental health in Thrissur district, with stigma and disrupted participation as critical pathways. Integrated, school-specific interventions combining comprehensive education, accessible counselling, infrastructure improvements, parental engagement and policy support are urgently needed to reduce psychological distress and promote holistic adolescent development.
Asiimwe Specioza, Kenneth Okello Otieno, Niyibizi Kenneth, Twizeere Harrimahh
The paper examined the role of organizational culture on academic performance in Ugandan universities by taking a mixed approach to the study, which involves both quantitative and qualitative data that will provide a more detailed picture. The theoretical frameworks of the study are based on educational policy barriers and institutional failures to examine the leadership practices, stakeholder involvement, organization structure, resources distribution, and technology adoption in the academic environment. A mixture of document review, surveys, and semi-structured interviews with 150 university administrators, academic staff and students were used to collect data. The results indicated that poor leadership, weak stakeholder, inadequate resources, over-centralized governance, and imbalanced adoption of technology, are some of the factors that influence organizational culture in Ugandan universities and result in institutional environments that are typified by low accountability, lack of motivation, poor collaboration, and low levels of staff and student academic support. The research found out that academic performance is not only affected by the personal learner factors but also the broader institutional and policy related conditions which determine the daily culture of the university. The main conclusion of the paper was that the culture in an organization is a key predictor of the academic performance since it impacts teaching quality, staff commitment, student engagement and effectiveness of the university systems. It suggested more participatory leadership, better infrastructure and academic support structures, more stakeholder participation, more innovation and application of technology to enhance an inclusive, accountable, and performance-oriented culture at the university in Uganda.
N. N. Joshua, O. A. T. NAMO
For increased value addition and preference of the cowpea grain, the need to determine the basic sources of genes conditioning, seed coat colour and colour patterns in natural population is desirable. Screen house and field evaluation studies involving landrace cowpeas and their wild relative (Dekindtiana var. pubescens) were carried out in Tafawa Balewa and Bar Arewa in Bauchi Northern Guinea Agroecology of Nigeria, to study the inheritance of seed coat colour in cowpea. Thirty genotypes of cowpea, comprising 10 parents, nine F1, two backcrosses and nine F2 were advanced from collection and hybridization trial. These were laid out in a randomized complete block design with three replications in the wet season (July – October) of 2018. The parental genotypes bred true to type and all the F1 plants of the nine crosses had 1Black: 1Black spotted with brown within locules of a single pod irrespective of the parental seed coat colour. The backcrosses and the F2 population in all the crosses had plants with seed coat colour and colour patterns in the range of five to twelve. The results unveils the genetic bases of seed coat colour in cowpea, where, early introgression of genes between landrace cowpeas and their wild relative (Dekindtiana var. pubescens) accounted for the varying cowpea seed coat colour and colour patterns observed in natural populations. These can deliberately be developed as options for researchers, growers and consumers preference.
Alexander Musa, Professor Bala G. Attah, Professor Thomas D. Bot
Insecurity as it affects education process caused by Boko Haram insurgency poses serious challenges to effective learning, particularly in mathematics. This study therefore, examined the effect of Boko Haram insurgency on senior secondary school students’ attitudes toward mathematics learning in Adamawa State, North East Nigeria. A comparative survey research design was used, with a population of 4828 and sample size of 660 involving students from insurgency-affected and non-affected areas in the state. Data were collected using a validated Mathematics Attitude Questionnaire and analyzed using descriptive statistics and independent samples t-tests. Results revealed a significant difference in attitudes toward mathematics between students in insurgency-affected and non-affected areas (t = 13.27, p < 0.05). Further analyses showed significant differences based on gender (t = 4.18, p < 0.05) and school location (t = 14.02, p < 0.05), with female students and those in rural schools exhibiting more negative attitudes. The findings highlight the need for psychosocial and context-sensitive educational interventions in conflict-affected regions.
Dr. Shipra Saxena, Zuned Rizwan Mansoori
This paper investigates the institutional agency of the Bundelkhand Industrial Development Authority (BIDA) as a catalyst for industrial diversification and sustainable development in the lagging Bundelkhand region of Uttar Pradesh, India. It examines BIDA's foundational vision, strategic objectives, and policy framework, particularly focusing on its role in shifting the region's economic base from traditional agriculture towards emerging sectors like defence manufacturing and renewable energy. While acknowledging the nascent stage of BIDA's operations and the current scarcity of comprehensive quantitative data, this study employs a qualitative methodology, analyzing policy documents, official statements, and news reports to assess BIDA's strategic intent and early contributions. The paper also delves into the inherent challenges and unique opportunities within Bundelkhand's industrial landscape, including critical considerations for water and energy solutions to ensure long-term sustainability. It provides an early assessment of BIDA's potential to replicate the success of established industrial hubs and concludes by highlighting the need for future empirical research to fully evaluate BIDA's long-term socio-economic and environmental impact, offering recommendations for sustained and inclusive development.
Diogu, Daniel Uzoma, Mezieobi, Chukwuemeka Sunday, Onungwa, Uchenna, Onwukwe, Chukwuemeka Ozioma Stanislaus
The residential building sector is a critical driver of global sustainability due to its substantial resource consumption, energy demand, impact on human wellbeing, and economic productivity. Biophilic environmental design, which reconnects occupants with natural systems, has been shown to improve indoor environmental quality (IEQ), psychological well-being, and energy performance. Conversely, smart sensors, artificial intelligence (AI), Internet of Things (IoT), and data-driven building management, which are systems of Fourth Industrial Revolution (4IR) technologies, can optimise operational efficiency and adaptive building performance. Despite their individual merits, the integration of biophilic design with 4IR technologies remains underexplored, while the evidence on their combined environmental and economic outcomes has remained fragmented. A systematic review methodology, as guided by PRISMA, was adopted to coalesce empirical and theoretical evidence published between 2010 and 2025. Relevant peer-reviewed journals, conference papers, and grey literature were retrieved from Scopus, Web of Science, Google Scholar, and ScienceDirect using thematic concepts such as “biophilic design,” “4IR technologies,” “smart residential buildings,” and “sustainability.” Inclusion criteria focused on studies that reported environmental and economic outcomes related to residential architecture. Seventy-seven studies that met the inclusion criteria were examined using a Structured Data Extraction Matrix (SDEM). Findings indicate that biophilic/4IR-integrated residential buildings enhance IEQ, thermal comfort, and occupant wellbeing, while optimising energy efficiency, reducing operational costs, and lowering carbon emissions. Comparative and thematic analyses show that these buildings outperform conventional designs in environmental and economic performance and occupant satisfaction. The study recommends that architects, developers, and policymakers focus on integrating biophilic principles with 4IR technologies to achieve sustainable, human-centred residential design. Further empirical research is needed to assess the long-term economic impacts, cost-effectiveness, and policy integration of place-based and data-driven sustainable residential development.
Dr. B. B. Baridam, Ndueso, Etukudo Ekefre, Prof. C. Ugwu
The continuous operation of cryptocurrency markets generates massive data streams that challenge real-time trading systems. Traditional approaches process every price update equally, leading to substantial computational waste during routine market periods. This study introduces an attention-based mechanism that intelligently filters market activity, triggering predictions only when volatility exceeds dynamically adjusted thresholds. We implemented this approach within a Bidirectional Long Short-Term Memory framework and tested it across Bitcoin, Ethereum, XRP, Cardano, and Solana over a 24-hour monitoring period following extensive training on historical data from 2022 to 2025. Our findings demonstrate that selective processing reduces computational requirements by approximately 72% while maintaining prediction accuracy within 0.1 percentage points of continuous processing approaches. The system generated predictions during only 28% of monitored periods on average, yet achieved Root Mean Square Errors ranging from 0.8% to 2.1% across different cryptocurrencies. Confidence scoring proved well-calibrated, with predicted confidence levels matching actual accuracy within 1.2 percentage points. Notably, the system correctly identified stable market conditions, issuing "Hold" recommendations with 99% confidence when price movements fell within normal variance bands. Alert delivery consistently occurred within 10 seconds of significant market events, enabling timely trading decisions. The dynamic threshold adjustment successfully adapted to varying volatility regimes, preventing false triggers during high-volatility periods while maintaining sensitivity during stable conditions. These results suggest that attention-based filtering offers a practical solution for multi-cryptocurrency monitoring on standard computing hardware.
Lilian Mailafia Okpede
Internal auditing serves as a critical mechanism for ensuring accountability, transparency, and efficiency in public sector institutions. This study examines the relationship between internal audit practices and corporate goal attainment in government establishments, focusing on the College of Education, Akwanga, Nasarawa State, Nigeria. The study reveals that internal control systems are fairly effective, with mean scores ranging from 3.3 to 3.9. However, challenges such as limited resources (4.1) and lack of management support (3.8) hinder internal audit effectiveness. The implementation rate of audit recommendations is moderate, with only 30% being fully implemented. To strengthen accountability mechanisms, it is recommended that management prioritizes resource allocation for internal audit units, provides training for audit staff, and ensures the timely implementation of audit recommendations. Additionally, establishing a robust risk management framework and enhancing communication between audit units and management can improve internal audit effectiveness.
Joan P. Bacarisas, DM, MAN, RN, Princess Mary Lynn R. Sunico, RN
Workplace conflict is a common challenge in healthcare settings, affecting teamwork, communication, and patient care outcomes. This study examined the relationship between intragroup conflict and conflict resolution styles among staff nurses in a government hospital in Surigao City focusing on task, relationship, and process conflicts and how these relate to nurses’ ways of handling disagreements. A quantitative descriptive–correlational research design was used. The respondents were staff nurses from different hospital units, varying in age, sex, educational attainment, years of service, area of assignment, and employment status. Data were gathered using a structured questionnaire composed of an intragroup conflict scale and a conflict resolution styles inventory measuring integrating, obliging, dominating, avoiding, and compromising styles. Descriptive statistics were used to summarize nurses’ characteristics, levels of conflict, and conflict resolution styles, while inferential statistics were applied to determine significant relationships among the variables. The findings showed that nurses’ personal and professional characteristics were significantly related to their levels of intragroup conflict. Relationship and process conflicts were particularly influential in shaping conflict management behaviors. Relationship conflict was significantly associated with the integrating style, while all types of intragroup conflict were significantly related to the dominating style. Process conflict was also significantly related to the compromising style. In contrast, obliging and avoiding styles were not significantly associated with any type of conflict. Intragroup conflict plays a crucial role in how nurses manage workplace disagreements, highlighting the need for effective conflict management programs to strengthen teamwork and support quality patient care.
Afrose Sultana Chamon*, M. N. Mondol, Sayada Kowka Batul Jannat Tajnin
Background: Heavy metals contamination in poultry products are increasing public health concern in Bangladesh, due to rapid industrialization, contaminated irrigation water, and the use of low-quality feed ingredients and tannery waste contribute to metal accumulation in eggs. Objectives: This study evaluated the concentrations of toxic and essential heavy metals in collected Layer feed samples and Layer eggs from major poultry-producing areas of Savar and Dhamrai, Bangladesh, and assessed the potential human health risks associated with their consumption. Methodology: Five commercial and non-branded layer feed samples and eighteen egg samples from two farms were analyzed. Samples underwent acid digestion (HNO₃–HClO₄), followed by metal quantification using AAS and ICP-MS. Health risks were assessed using Average Daily Intake (ADI), Hazard Quotient (HQ), and Hazard Index (HI) models. Key Results: Feed samples showed metal concentrations ranging as follows: Ni (3.95–5.66 mgkg-1), Cd (0.11–0.33 mgkg-1), Pb (0.44–2.83 mgkg-1), Cr (0.00–13.48 mgkg-1), Cu (5.59–24.93 mgkg-1), and Zn (28.19–73.12 mgkg-1). Most of the metals were within permissible limits except Cr exceeded safety limit in several samples, indicating contamination from tannery waste. Egg samples contained significantly elevated concentrations: As (6.41–21.77 mgkg-1), Pb (1.20–6.33 mgkg-1), Cd (0.08–1.67 mgkg-1), Cr (8.76–15.08 mgkg-1), and Ni (0.44–4.62 mgkg-1); all above international limits. Essential elements were also high: Cu (3.48–11.73 mgkg-1), Zn (70.64–208.23 mgkg-1), Co (0.01–0.31 mgkg-1), and Be (0.002–0.013 mgkg-1). ADI values for As (0.035–0.121 mg/person/day) exceeded PMTDI in most samples, and HI values surpassed 1.0 in all sheds, signifying cumulative human health risks. Conclusion: Layer eggs from Savar are heavily contaminated with toxic metals, especially As and Cr, posing significant health risks to consumers.
Chinaka A. I., Ezebunanwa A. C., Mbagwu E. C, Nwugha V. N., Onwuegbuchulam C. O.
In today’s world, field investigation is a necessity to get a detailed overview of any area for civil engineering construction purpose. Precise determination of engineering geological properties is essential to plan for a proper design and successful construction for any civil engineering structure. The traditionally practiced conventional methods for the same are invasive, costly and time consuming. Electrical Resistivity Survey is an attractive tool for delineating subsurface geology without soil disturbance. The investigation involved the use of vertical electrical sounding of schlumberger array. The location is within Ogwashi Formation with latitudes 6°11.155’N to 6°11.171’N and longitudes 6° 48.868’E to 6° 48.883’E with elevation varying between 68m and 79m.The interpretation revealed resistivity range of 396 Ohmm to 746Ohmm from depth of 0.934m to 2.2m for the foundation of structures, while the resistivity and depth to aquifer of the location is 1569Ohmm at 9.44m and 1314Ohmm at 168m for the second zone.. In between these lithologies are mainly clay/shale units. This suggest that the underlying materials has to be treated or soil stabilized with one of the options of recommendation. This will enhance the bearing capacity of the foundation soil. Deep foundation is recommended for the main load bearing foundation to ensure that the load is mounted by the civil structure is transmitted to the hard shale. Failure to follow these procedures could lead to structural failure and economic loss or wastage.
Anarado, C.E, Chris-Okafor P.U, Okeke, O.J
The use of agro-waste materials as fillers in polymer composites offers a sustainable route to reducing environmental impact and production cost while enhancing material performance. This study investigates the influence of guinea corn husk/snail shell hybrid filler on the physical, mechanical, morphological, and biodegradability properties of flexible polyurethane foam intended for nursery farming applications. The hybrid filler, composed of equal proportions of lignocellulosic guinea corn husk and calcium-carbonate-rich snail shell, was incorporated at 0–25 wt%. Results showed that increasing filler loading prolonged foaming reactions and increased density, with rise time increasing from 145 s to 166 s, cure time from 7.5 to 8.8 min, and apparent density from 28.4 to 32.2 kg/m³. Mechanical performance improved progressively, as tensile strength, flexural strength, compressive strength, and hardness increased with filler content, while strain at break decreased, indicating enhanced stiffness but reduced ductility. Scanning electron microscopy revealed a transformation from large, irregular cells in the control foam to smaller, more uniform cells with thicker walls in filled samples. Soil burial testing confirmed the biodegradable nature of the composite material. Overall, the guinea corn husk/snail shell hybrid filler significantly improved structural integrity and load-bearing capacity while maintaining environmental compatibility, demonstrating strong potential for cushioning, root protection, and seedling support in nursery farming systems.
Eirah Jen B. Langi, Jascel Mae B. Padayao, Jenneth Mae V. Rosas, Kent Dhanty A. Lupiba, Kent Dhanty A. Lupiba, Ma. Gina L. Navacilla, Mil Ariel C. Lamban Jr, Nichol Isidore A. Lupian, Rica Jane A. Amparo
This study aimed to develop and evaluate the performance of the Ink Removal and Eradication System (IREASE) device to reduce paper waste and promote paper reuse at San Agustin National High School. The system integrates chemical ink removal using acetone and sodium hypochlorite with a semi-automated process consisting of solvent application, mechanical eradication using rollers, and automated drying to remove ink from printed paper. Using a quantitative research and development (R&D) design with an experimental comparative approach, the device was developed and its performance was compared with a traditional ink removal method. Data on the percentage of ink removed and removal response time were gathered through observation, documentation, and photographic analysis. Results showed that when acetone was used, the IREASE device achieved 77.60% ink removal with a response time of 01:30.00, compared to 50.08% and 01:58.08 for the traditional method. Similarly, using sodium hypochlorite, the IREASE device obtained 74.54% ink removal with a response time of 02:00.00, while the traditional method achieved only 51.16% with 02:27.70. Statistical analysis confirmed significant differences between the two methods, indicating that the IREASE device is more effective and faster than the traditional ink removal method. The findings suggest that the IREASE device has strong potential for application in educational institutions to support sustainable paper reuse practices.
Friday Nguvayasvika Mudondo Kubiku, Simbarashe Kembo, Willard Zendera
Smallholder irrigation schemes in southern Africa have shown mixed results in improving rural livelihoods and food security. Investigations conducted in Zimbabwe's Honde Valley explored the effects of irrigation projects on the productivity and financial stability of local farmers. A cross-sectional study was conducted across five wards using a mixed-methods approach. A total of 100 irrigating farmers were surveyed via structured questionnaires, with further data gathered from five focus group discussions and eleven key informant interviews. The sample selection utilised a combination of multi-stage purposive and simple random sampling methods. Productivity assessment revealed significant variability across crops and schemes, with banana yields ranging from 7-30 tonnes per hectare and bean yields from 1-3 tonnes per hectare. Sprinkler irrigation systems dominated (90%), reflecting lower capital requirements and adaptability to diverse crops. Improved food security and increased income for farmers were the positive outcomes of irrigation schemes. Crop production contributed 36% of household income, with livestock production adding 27%. Increased household food security was reported by 51% of farmers. Farmers acquired various assets, including livestock (15 % farmers), wheelbarrows (20% farmers), and constructed houses (50% farmers). Key skills developed included farming as a business (50%) and plumbing (30%). High educational attainment among participants (80% secondary education) facilitated technology adoption and business skill development. Major challenges included limited access to capital (30%), poor market access (25%), and seasonal water scarcity (25%). While irrigation schemes have demonstrable positive impacts on rural livelihoods and productivity in Honde Valley, sustainability is threatened by financial constraints, market access limitations, and inadequate infrastructure. Targeted interventions addressing these challenges could significantly enhance scheme effectiveness.
Anjali Bijarniya, Dr. Shri Ram Rundla, Komal Tiwari, Tanvi Katoch
Background: Aberrant right subclavian artery (ARSA) is the most common aortic arch variant increasingly recognised during routine fetal echocardiography. Although historically linked to chromosomal abnormalities, emerging evidence shows that isolated ARSA in screen-negative pregnancies has a favourable prognosis. Case: We report a 24-year-old primigravida with a normal Level II ultrasound and a negative quadruple screening test. A routine fetal echocardiogram at 24 weeks demonstrated an isolated ARSA without any other cardiac or extracardiac anomalies. Pregnancy and delivery were uneventful. Postnatal echocardiography confirmed isolated ARSA, and the neonate remained asymptomatic. Conclusion: When identified as an isolated finding in the setting of normal aneuploidy screening, ARSA represents a benign vascular variant with excellent perinatal outcomes. Comprehensive counselling helps avoid unnecessary invasive testing and parental anxiety.
Nithya kalyani M., Seema S., Shobiga K., Sriharini J., Thirisana G., Thirishiga G.
A key component of sustainable agriculture, fish amino acid fertilizer (FAA) is an organic input that is abundant in vital nutrients and advantageous microbes. In this study, the microbial flora found in FAA will be isolated, characterized, and their potential as biofertilizers and biopesticides assessed. Using accepted microbiological techniques, microorganisms were separated and then described according to their morphological and biochemical characteristics. Plant growth-promoting characteristics such nutrient solubilization, phytohormone synthesis, and antagonistic action against plant diseases were further evaluated for the isolated isolates. The findings demonstrated the existence of a variety of advantageous microorganisms that can increase plant development, improve soil microbial activity, and increase nutrient availability. Furthermore, a few isolates had inhibitory effects on dangerous pathogens, suggesting a possible use for them in biological pest control. Applying microbial flora obtained from FAA can boost crop yield, enhance plant health, and lessen reliance on chemical herbicides and fertilizers. As a result, FAA is a viable, economical, and environmentally beneficial resource for creating sustainable biofertilizer and biopesticide formulations for use in agriculture.
Alfonso R. Baldonado III, D.M.
The COVID-19 pandemic imposed unprecedented challenges on the educational system and significantly affected the psychological well-being of school personnel. This study determined the level of job stress, mental health conditions, and coping mechanisms of secondary school personnel in the Schools Division of Iloilo Province during School Year 2020–2021 as a basis for developing a school mental health program. The study employed a descriptive–correlational research design involving purposively selected teaching and non-teaching personnel. Data were gathered using a researcher-made questionnaire validated through the Good and Scates Criteria and tested for reliability using the test–retest method. Statistical tools used included frequency and percentage, mean, Mann–Whitney U Test, Kruskal–Wallis H Test, and Spearman’s rho. Results revealed that secondary school personnel were highly stressed overall (M = 3.85), with time management and learners’ behavior identified as the strongest sources of stress. Despite high stress levels, respondents demonstrated good mental health conditions (M = 4.09), indicating resilience and adaptive functioning. The coping mechanisms of school personnel were rated high (M = 4.11), with social and behavioral strategies such as maintaining relationships with colleagues and communicating with family and friends being the most frequently utilized. Significant relationships were found among job stress, mental health conditions, and coping mechanisms. Job stress was negatively correlated with mental health conditions (ρ = –0.68, p < .05) and positively correlated with coping mechanisms (ρ = 0.71, p < .05), while mental health conditions showed a strong positive relationship with coping mechanisms (ρ = 0.75, p < .05). The findings indicate a paradoxical pattern in which school personnel experience high job stress yet maintain good mental health through effective coping strategies. This supports the Cybernetic Theory of Stress and the Inverted-U Theory, which emphasize self-regulation and optimal stress levels for performance. Based on the results, the study proposes the development of a comprehensive school mental health program focusing on workload management, emotional regulation, and strengthening social support systems among school personnel.
Aishwarya Gandhe, Dr. K. Meenarani, Nigama Neligi, Siri Chandana
In Indian philosophy, karma has two main uses: to encourage a person to act ethically and to provide a framework from which people view suffering/moral injustice. Essentially, karma defines an individual’s present and future experiences through good/bad actions or behaviors, due to the belief that whatever an individual does, whether on purpose or by accident (with no intention), will have consequences for that individual, not only in their current life but in future lives as well (by rebirth). "Karma" does not equate to "blind fate," rather karma promotes moral responsibility and agency (i.e., having the ability to choose), therefore all actions, not just physical, have some level of consequence. Karma also serves as a psychological and experiential tool in linking intent/action with consequence, enhancing moral consciousness through self-evaluation, controlling emotions, etc. As such, karmic principles provide an important context through which an individual develops resilience, discipline, and responsibility in daily living. This paper aims to explore karma from various contexts, including how different philosophies interpret karma (Hinduism, Buddhism, and Jainism), and how they relate psychologically and experientially.
Ajah Obinna, Enete Uchenna Oliver, Nnaoma, Ikenna. Elvis
Infertility is a common reproductive health issue, with male factors responsible for 40–50% of cases. This research investigated the impact of aqueous Brachystegia eurycoma (achi) seed extract on lipid levels, antioxidant capacity, and sperm parameters in adult male Wistar rats. Twenty rats (75–130 g) were divided into four groups (n = 5) to receive daily doses of the extract: 0 mg/kg (control), 200 mg/kg, 400 mg/kg, or 800 mg/kg for 14 days. Body weights were recorded and semen samples were collected to evaluate sperm motility, morphology, and count. Serum lipid profiles were analyzed, and antioxidant activity was assessed using DPPH and FRAP assays. The 800 mg/kg dose significantly improved sperm parameters, showing 45% progressive motility and 75% normal morphology. In contrast, the 400 mg/kg dose resulted in 25% motility and 45% normal morphology. Lipid profile analysis indicated increased total cholesterol (299 mg/dL) and triglycerides (442 mg/dL) at the highest dose, with HDL at 33 mg/dL and LDL at 178 mg/dL. The extract demonstrated strong antioxidant activity, achieving 94.42% DPPH inhibition at 80 mg/mL and a FRAP scavenging capacity of 87.99%. Brachystegia eurycoma seed extract may enhance sperm quality, likely due to its antioxidant properties and regulation of lipid metabolism.
Hariom Ingle, Ishwari Gondkar, Jidnyasa Harad, Ravindra Murumkar, Raviraj Joshi, Ronit Ghode
The exponential growth of unstructured digital text has created a pressing need for sophisticated Natural Language Processing (NLP) methods to extract meaningful information. Named Entity Recognition (NER), the task of identifying and classifying named entities in text, is a cornerstone of this effort. While traditional NER has achieved remarkable success on short, self-contained texts, its application to long-form docu-ments—such as legal contracts, clinical records, and scientific literature—presents formidable challenges. This survey provides a comprehensive analysis of the state-of-the-art in Long-Range Named Entity Recognition. We trace the evolution from classical statistical models to the rise of Transformers, detailing the inher-ent quadratic complexity of models like BERT that limits their scalability. We conduct an in-depth exploration of the primary architectural paradigms designed to overcome this bottleneck: efficient Transformers that employ sparse attention mechanisms, and graph-based approaches that model explicit relational struc-tures within documents. Furthermore, we investigate critical challenges, including the data scarcity problem in specialized domains and unique linguistic complexities in multilingual con-texts. Drawing from recent analyses, we synthesize persistent open problems in document-level information extraction, focusing on long-distance coreference resolution and the need for robust, multi-step reasoning. Finally, we chart a course for future research, postulating that the next generation of solutions will be found in hybrid architectures that synergistically combine the strengths of deep sequential encoders with structured reasoning frameworks
Dr. A.A. Tawane
Meteorological and hydrological hazards such as tsunamis and cyclones remain development challenges, especially in the East Coast of Africa, due to the high level of vulnerability and limited adaptive capacity (UNDRR, 2023; IPCC, 2022). Communities already experiencing these disasters often lack the institutional capacity and socio-economic resilience required to implement effective mitigation strategies or engage in comprehensive disaster risk reduction. This study critically examines the complexity of managing tsunamis and cyclones on the East Coast of Africa. It focuses on the vulnerability and risk exposure of areas along the East African coast to weather- and water-related hazards. It evaluates the current systems and institutions responsible for managing these threats and identifies key gaps, including weak infrastructure, limited funding, and poor coordination. Employing a qualitative meta-synthesis grounded in the PRISMA framework, the research delineates seven core vectors in the management of meteorological and hydrological hazards, namely: vulnerability assessment, risk assessment, preparedness, mitigation, response, rehabilitation and reconstruction. Finally, it puts forward recommendations to help strengthen disaster preparedness and response. The overarching aim is to foster a more proactive and unified approach to addressing climate risks in one of the region's most at-risk zones.
Manisha Sharma, Reeta Shrivastava, Seema Sharma
Education is the carrier of human life, just like any flower blooms after getting sunlight and a new energy towards life. After receiving the light of education, human life also blooms like a flower and fame in the form of its image spreads in all four directions. Through education, desirable changes can be brought about in the innate powers of man, knowledge, skill, behaviour, personality and behaviour of human beings. Through this, civilised, cultured and capable citizens can be created. Education for married and unmarried women at the graduate level plays an important role as a basis for developing women towards adult life by ending their primary and secondary. Education helps make other officers capable; at the same time, uneducated women feel difficulty in telling many problems to men, if they are educated, they solve those problems themselves. Women's education is helpful in the growth of national, international, social, family and domestic productivity. Apart from this, it also plays an indelible role in the creation of a well-organised and healthy society. To achieve the objectives of this research paper, the researchers used qualitative and quantitative data and interpreted the data collected from married women studying in the Art, Science and Commerce Stream using the mean test and t-test. After analysis of the data, it was concluded that no significant difference was found between the family problems of married women of the Art and Science Stream, but a significant difference was found between the family problems of married women of the Commerce and Science and Commerce stream. A detailed explanation of the possible reasons for which is presented in this research paper.
Dr. A. Gayathri, N. Rajani
The present study examined the effectiveness of psychoeducational and CBT-based components embedded within clinical psychology coursework in improving mental health awareness and reducing stigma toward mental illness. It evaluated whether structured exposure to abnormal psychology concepts enhances students’ beliefs, understanding, and attitudes regarding mental disorders. A quantitative pre–post design was used with 150 undergraduate students enrolled in a Clinical Psychology course. Participation was voluntary with informed consent. Students completed a demographic form, the Beliefs toward Mental Health Scale, and the Resilience Scale before and after course completion. Statistical analyses assessed changes in awareness, beliefs, and stigma. Findings indicated a statistically significant improvement in mental health awareness and positive beliefs, along with a reduction in stigma. Students showed stronger beliefs in the treatability of mental illness and reduced perceptions of embarrassment and social stigma. Psychoeducational and CBT coursework in clinical psychology effectively promotes awareness, empathy, and evidence-based understanding of mental disorders. Integrating mental health education into academic curricula can reduce stigma, enhance mental health literacy, and contribute to the development of competent professionals and resilient communities.
Mrs. Sharmila A K
Mathematics is the backbone of the innovations in the fields of Artificial Intelligence, Quantum Computing and Epidemiology. Linear algebra, probability and optimization form core tools enabling precise modeling, analysis and computation in these developing technologies. Examples from Machine Learning, Blockchain technology and quantum computing, MRI/CT imaging illustrate recent advancements as of 2026. [1][2].
Dada, Emmanuel Damilo, Dearsly, Emmanuel Markus, Eze, Kingsley Chijioke, Odiba John chubiojo, Ogidigo, Jane Chinwe, Oshatuyi Olukayode
Background: Sirtuin 1 (SIRT1) and sirtuin 3 (SIRT3) are NAD⁺-dependent deacylases that play critical roles in metabolic regulation, oxidative stress control, and aging. Natural products have emerged as promising sources of sirtuin-interacting molecules, yet systematic evaluation of Hyptis verticillata phytochemicals against these targets remains limited. Methods: Selected phytochemicals from Hyptis verticillata were subjected to molecular docking against SIRT1 (PDB ID: 4I5I) and SIRT3 (PDB ID: 3GLS) using AutoDock Vina. Binding affinities and interaction patterns were analyzed, followed by in silico pharmacokinetic and toxicity (ADMET) profiling using SwissADME and admetSAR to assess drug-likeness and safety. Results: Docking analysis revealed binding energies ranging from −5.0 to −9.5 kcal/mol across both targets. Squalene exhibited the strongest predicted affinity for SIRT1 (−9.5 kcal/mol), while oleanolic acid showed the highest affinity for SIRT3 (−8.5 kcal/mol). Several other compounds demonstrated moderate binding to both sirtuins. Interaction analysis indicated predominantly hydrophobic stabilization within the binding pockets. ADMET profiling suggested that while highly lipophilic compounds may face bioavailability limitations, oleanolic acid displayed a comparatively balanced pharmacokinetic and safety profile. Conclusion: The findings indicate that selected H. verticillata phytochemicals exhibit structural compatibility with SIRT1 and SIRT3, supporting their consideration as preliminary sirtuin-interacting candidates. However, the results represent structure-based predictions rather than functional evidence. Further molecular dynamics simulations and experimental validation are required to elucidate binding stability and biological activity.
Dr. B. P Bommanahalli, Dr. Divyashree, Dr. Manika Alexander
Malignant proliferating trichilemmal tumour (MPTT) is a rare cutaneous adnexal neoplasm arising from the outer root sheath of the hair follicle and represents malignant transformation of a proliferating trichilemmal tumour. It accounts for less than 0.1% of cutaneous malignancies and most commonly presents as a solitary scalp lesion in elderly women. A 60-year-old male presented with progressively enlarging painful swellings over the scalp and left scapular region. Histopathological examination revealed a dermal epithelial tumour showing marked cytological atypia with abrupt trichilemmal keratinization. Periodic acid–Schiff staining demonstrated diastase-resistant cytoplasmic positivity. Immunohistochemistry showed focal CD34 expression with strong nuclear p53 and increased Ki-67 labeling index. The findings were diagnostic of malignant proliferating trichilemmal tumour. Multifocal involvement occurring in a male patient is exceedingly rare. Recognition of trichilemmal keratinization and the use of histochemical and immunohistochemical markers are essential to distinguish MPTT from squamous cell carcinoma and guide appropriate management.
Dr. Maya. M. R, Dr. P.Sudha Rani, Harshitha V, Maredugonda Naga Sathwika, Swathy Sankar
Synthetic polymers remain intact in nature for many years after the expire and cannot be included in the natural recycling material in anywhere. Fossil resource-based polymer manufacture is endangering current supplies and has a daily detrimental impact on the circular economy. The harmful consequences of polymers on the environment, biopolymers a class of polymers created by living organisms like plants, animals, and microalgae might be a great substitute. Because of biopolymers that are recyclable, low-emission, or environmentally friendly, a wide range of new subjects are emerging in this field. There are several industries where composite materials based on these biopolymers which function as natural adhesives find use, including the packaging, textile, furniture, and industrial design sectors, as well as architectural and structural insulation design. This composite can replace traditional building materials, which are expensive, nonbiodegradable, and have significant emissions. It also exhibits exceptional mechanical strength, hydrophobic qualities, and thermal stability. The kind of substrate and strain, the length of incubation, and the method of manufacturing are some of the variables influencing the composite's physicochemical properties.
A. Falana, A.A. Adenusi
Starch-based dispersions continue to be of interest as non-Newtonian fluids because of their availability, biodegradability and sensitivity to applied shear stress. It is significant that one understands how their flow behaviour can be altered with the help of particulate additives both in characterizing materials and in feasibility studies due to their applications. The steady-shear rheological behaviour of gelatinized corn starch-water dispersions using locally sourced yellow and white varieties of corn was studied in this work, at a fixed formulation of 20 g starch in 350 mL of water. The loading levels of 0 g, 2 g and 4 g of iron filings were added and the rheological measurements were done under the influence of a static magnetic field using a rotational viscometer. The power-law model was used to analyse the data on apparent viscosity to quantify shear dependence through the flow behaviour index (n) and consistency parameter (lnµ). All fixed formulations of the starch were non-Newtonian and shear thinning, and all flow behaviour indices were found to be less than one under the conditions considered. The iron filings had a quantifiable effect on the viscosity and consistency, and this means that the resistance to flow under shear was increased. These findings offer controlled rheological insight into magnetically modified corn starch systems and also in their plausibility as shear-dependent, energy-dissipating media for further investigation in applied material systems.
F. C. Ebuzoeme
A basic concern of human resource managers in work organisations is to acquire, maintain, and retain a motivated workforce. Nonfinancial compensation is among the variables that have the potential to achieve this goal. Despite its application in organisations, studies that indicate how nonfinancial compensation impacts on the motivation of employees of food and beverages manufacturing companies in Nigeria were scanty. A sample size of 246 represented the number of obtained responses from a population of 460 employees of a food and beverage manufacturing company in Oyo State, Nigeria. Questionnaire, based on a four-point Likert scale, having values that ranged from strongly disagree, 1, to strongly agree, 4, was employed for data collection. Descriptive and inferential statistics were employed for data analysis. Descriptive statistics produced results in means and standard deviations for statements that measured components of nonfinancial compensation as well as for statements that measured employee motivation. The hypotheses of the study were tested and the effects of nonfinancial compensation on employee motivation were determined based on the results of multiple regression analysis. The findings indicate significant positive effect (β1 = .482, t = 4.565, p < .05) of recognition on employee motivation. Career development opportunities had insignificant positive effect (β2= .124, t = 1.192, p > .05) on motivation while promotion had significant positive effect (β3 = .374, t = 4.435, p < .05) on motivation. The conclusion of the study was that nonfinancial compensation was a means of enhancing employee motivation in the studied company. The independent variables had positive effects on employee motivation. Although, recognition and promotion made appreciable contribution to employee motivation, there was need for the company to put in more effort on activities that would provide further boost on the effect of career development opportunities on motivation.
Joan P. Bacarisas, DM, MAN, RN, Jova Christine C. Dagcuta, RN
This study assessed the level of nursing competency and professional attitude among novice nurses and examined their relationships with selected demographic characteristics. A quantitative descriptive–correlational design was employed in government retained hospital in the Surigao del Norte, Philippines. A complete enumeration of 126 newly hired registered nurses engaged in direct patient care participated. Data were collected using the Nursing Competency Scale (NCS) and the Professional Attitude Scale for Nurses (PASN). Descriptive statistics, Chi-square tests, Cramer’s V, and Pearson correlation coefficients analyzed the data. Ethical standards and informed consent were observed throughout the study. Most respondents were 18–35 years old, female, single, and held a bachelor’s degree. Overall, novice nurses demonstrated high nursing competency across all domains, excelling in Helping Role, Teaching-Coaching, and Therapeutic Interventions, with slightly lower performance in Diagnostic Functions. Professional attitude was predominantly high, indicating strong ethical awareness, accountability, and engagement in professional roles. Sex was significantly associated with both competency and professional attitude, while educational attainment correlated with professional attitude. A strong positive relationship was observed between competency and professional attitude (r = 0.692, p < 0.001), suggesting that clinical skills and professional behavior are interdependent. Novice nurses in a DOH-retained hospital exhibit high competency and professional attitude, with gaps in diagnostic interpretation and complex decision-making. Targeted mentorship, structured training, and continuous professional development are recommended to strengthen readiness for high-acuity patient care.
Amoo Isiaka Adekunle*, Josephine Odunayo Ilade, Muraina Mutairu Omoniyi
The consumption of yoghurt is steadily increasing due to its recognized health benefits and versatility. However, the quality and nutritional content of yoghurt can vary depending on the source of milk used in its production. This study investigates the physicochemical, sensory, microbial, risk assessment and functional properties of fresh milk-based yoghurt and powdered milk-based yoghurt. 15 Samples of yoghurts coded: LZS, LZU, FFS, FFU, TYS, TYU, TSS, TJU, CYS, CYU, HYS, LZG, CGY, TJG and LZF were bought from supermarket in Nigeria. The ranges for physicochemical properties were pH (4.49 – 5.23), conductivity (3588 – 4988mS/cm), density (2.09 – 2.26g/cm³), viscosity (422 – 493mPa.S), titratable acidity (0.00011 – 0.00013%), moisture (70.40 – 89.30%), ash (1.37 – 5.70%), fat (4.3 – 4.81%), and protein (5.63 – 28.94%). The average concentration (mg/kg) of Na, Mg, K, Ca, Fe, Zn and Cu are 595.53, 280.00, 395.00, 1956.30, 12.14, 1.31 and 0.27 respectively, while Cd was not detected in all samples. Target Hazard Quotient, (THQ) for Fe, Zn and Cu in all samples were < 1 suggesting no potential health risk for consumers. B-glucan, inulin, pectin, gelatin and sodium alginate ranges from (5.48 – 65.6), (10.9 – 46.7), (8.70 – 28.3), (4.29 – 16.7), and (6.45 – 21.7) respectively. General acceptability ratings were between very good and excellent. Total viable bacterial count (TVBC) ranges from (6 – 79cfu/100mL), total viable lactic acid bacterial count (TVLBC) ranged between (12 – 18cfu/100mL) and total viable yeast and mold count (TVYMC) ranged between (2 – 31cfu/100mL). This study revealed that all yoghurt samples analyzed are safe and reliable sources of protein, minerals and nutrients.
Nathaniel Atansuyi, Ogunkan Stella Kehinde, Oyelakun Temitope A
Gait recognition has emerged as a robust biometric approach for human identification in surveillance, healthcare, and forensic applications. However, the efficiency of deep-learning-based gait recognition largely depends on the optimization algorithm used for model training and hyperparameter tuning. While traditional gradient-based methods such as Stochastic Gradient Descent (SGD) and Adam are widely adopted, their convergence behavior often deteriorates in high-dimensional non-convex spaces. Recent studies employing metaheuristic algorithms such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) have demonstrated performance gains but remain constrained by local optima and unstable convergence dynamics. This study benchmarks a newly introduced metaheuristic; the Hippopotamus Optimization Algorithm (HOA) against four well-established optimizers: Adam, SGD, PSO, and GA, as reported in previous deep learning optimization studies. The developed HOA-CNN-LSTM hybrid model integrates the HOA for global hyperparameter optimization and Adam for fine-tuned gradient updates. Experiments conducted on the TUM-GAID dataset show that HOA achieves 97.4% accuracy and 98.5% Genuine Acceptance Rate (GAR) with a reduced convergence time of 39s per epoch. These results surpass comparative benchmarks reported for Adam [10], SGD [11], PSO [12], and GA [13], confirming HOA’s superior balance between exploration and exploitation. By situating HOA’s performance within a metaheuristic benchmarking framework, this work provides empirical evidence that HOA represents a promising optimization paradigm for next-generation spatiotemporal deep learning and biometric recognition applications.
Fides C. Fosana, RN, Joan P. Bacarisas, DM, MAN, RN
Fair and transparent organizational practices are essential in shaping how nurses view their roles and responsibilities within the healthcare system. While organizational justice and professional identity are well-studied internationally, limited evidence is available at the local level, particularly in government hospital settings. This quantitative research employed a descriptive–correlational design to examine the relationship between personal characteristics, organizational justice, and professional identity among nurses in a government hospital for the first quarter of 2025. Findings showed that most respondents were adults, predominantly female, bachelor's degree holders, and contractual employees with relatively short years of service. Organizational justice was rated high, especially in procedural and interactional aspects, while distributive justice received comparatively lower ratings. Professional identity was very high across all dimensions, reflecting pride in the profession, strong values, consistent professional behavior, active engagement, and high self-efficacy. Personal characteristics were not significantly associated with professional identity, and only educational attainment was related to organizational justice. A significant moderate positive relationship was found between organizational justice and professional identity, indicating that fair treatment and just workplace practices strengthen nurses’ sense of professional identity. Based on these results, an Organizational Justice and Professional Identity Enhancement Plan is proposed.
Neha Thakur Rai, Shalini Jaiswal, Shambhavi Mishra
Background: Neonatal mortality represents a major public health concern characterised by complex survival dynamics and substantial aetiological heterogeneity. Appropriate survival modelling of time-to-event data is essential for elucidating disease-specific risk profile during the critical first 28 days of life. Neonatal mortality in intensive care settings exhibits an early-peak hazard profile inadequately captured by semiparametric methods alone. Comparative evaluation of parametric proportional hazard (PH) models that explicitly parameterise the baseline hazard provides both superior fit diagnostics and direct hazard quantification. Objectives: To compare parametric survival models and identify the optimal distributional fit for neonatal mortality data, and to determine prognostic factors using the best-fitted model for neonatal outcome. Methods: A prospective study design was used to collected the data of 686 neonates admitted to the Neonatal Intensive Care Unit (NICU) and Special Newborn Care Unit (SNCU) at Dr. Ram Manohar Lohia Institute of Medical Sciences (RMLIMS), Lucknow, was followed from admission until death, discharge, transfer, or day 28. Four survival models were fitted and compared by Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The proportional hazards (PH) assumption was assessed via Schoenfeld residuals with global test. Discriminative ability was evaluated using Harrell's C-concordance statistic Results: Among 686 neonates, 155 (22.59%) died during follow-up. The Weibull PH model achieved the best fit (AIC = 827.77; BIC = 927.44). Key independent predictors included extreme prematurity, congenital malformations, perinatal asphyxia, neonatal sepsis, induced labour, and multiparity. The global Schoenfeld test supported the proportional hazards assumption (p = 0.0976). Harrell's C = 0.7948 indicated good discriminative performance. Conclusions: The Weibull PH model provides the best parametric characterisation of neonatal mortality hazard dynamics. Extreme prematurity, critical clinical diagnoses, and induced labour are dominant independent hazard determinants, consistent across all model specifications.
Dr. A. Anita, J. J. Jerlin, J. Jesslin Blessy4, J. Sweety Puspha, R. Nigisha, S. Breeza Roy
Medicinal plants constitute the main source of new pharmaceuticals and healthcare products. Plant based medicinal compounds is long established to be used as traditional treatment for innumerable human diseases from time immemorial in many parts of the world. Phytochemicals are responsible for medicinal activity of plants and these biochemicals are naturally occuring in the plants that have defense mechanisms and protect from various diseases.Their use has been multiplied through various researchers and application due to a number of side effects from use of synthetic drugs, antibiotics and high cost. In the present study, the dried parts of Piper longum was subjected to phytochemical, physicochemical and antimicrobial studies. Phytochemical analysis reveals maximum number of phytochemicals are present in piper longum chloroform leaves and fruit extracts compared to ethanol extract. Physico-chemical analysis showed that the plant contain appropriate amount of silica materials, contaminants and is less affected by microbial attack. Antimicrobial activity performed on bacterial strains also showed significant results. From this it is known that this medicinal plant is pharmaceutically important.
Ebele Linda Okoye, Harrison Obumseli, Ugochukwu Chukwuma Okafor
This study analyzes the antibacterial activity of Luffa cylindrica leaf extracts, the plasmid profile and molecular characterization of MDR Uropathogenic bacteria obtained from patients from selected hospitals in Asaba. Two hundred (200) samples of urine were collected, microscopic examinations, cultures, and susceptibility tests were performed. Bacterial isolates that exhibited resistance to three or more classes of antibiotics were defined, for the purpose of this study, as Multidrug-Resistant (MDR) uropathogens. Molecular identification was performed using 16S rRNA sequencing, while plasmid extraction and curing analyses were used to determine the role of plasmid-mediated resistance. Series of quantitative and qualitative tests were conducted in order to assess the phytochemistry of the leaf extracts, and the antibacterial properties of the extracts were characterized using the agar-well diffusion method, along with a determination of the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Among the 200 specimens tested, 62 (31%) tested positive in cultures, producing 70 isolates, including Staphylococcus aureus (40%), Escherichia coli (28.6%), Klebsiella pneumonia (18.6%), Proteus mirabilis (7.1%), and Pseudomonas aeruginosa (5.7%). 76% of the isolates were multi-drug resistant (MDR) and Pseudomonas aeruginosa and Proteus mirabilis had 100% resistance. Molecular identification based on 16S rRNA gene sequencing revealed that the isolates were closely related to Escherichia coli, Enterobacter cloacae, and other clinically relevant bacterial species. However, confirmation of uropathogenicity would require further characterization of specific virulence determinants associated with urinary tract infections. All MDR strains had large plasmids (>10 kbp) and in the strains from which plasmids were removed, resistance was decreased, indicating that the resistance was from plasmids. The phytochemical analysis showed that the leaves tested positive for alkaloids, flavonoids, phenols, saponins, tannins, terpenoids, glycosides and steroids. Inhibitory zones of 24-34 mm were produced from ethanolic extracts which also had significant antibacterial activity with Minimum inhibitory concentrations (MICs) of the ethanolic extract ranged from 103.75 ± 4.78 to 310 ± 8.16 mg/mL. Although antibacterial activity was observed, these MIC values are relatively high compared with conventional antibiotics such as ciprofloxacin, suggesting that further purification of active phytochemical constituents may be required to achieve clinically relevant potency. The results suggest that the Luffa cylindrica leaf-extracts have antibacterial qualities and can be used as alternative treatments for resistant strains of uropathogens.
Adeniji Tomiwa Williams, Alao Bolanle Morufat, Odetunde Hezekiah Oluwasegun, Oguntunji Olumide, Oladimeji Boluwatife Christianah, Oyetade Itunu Favour
Klebsiella pneumoniae and Escherichia coli are major extended-spectrum beta-lactamase producing organism. Extended spectrum beta-lactamases (ESBLs) inactivate newer cephalosporins through hydrolysis, increasing therapeutic failure and antibiotic resistance worldwide. This study aimed to determine the prevalence of ESBL-production in clinical Klebsiella pneumoniae and Escherichia coli isolates. A total of one hundred and four (104) Klebsiella pneumoniae and Escherichia coli isolates from various clinical samples were obtained from Medical Microbiology Laboratories of LAUTECH Teaching Hospital. Isolates collected were recovered on MacConkey agar at 35°C and then identified using standard biochemical tests. They were further screened for antimicrobial susceptibility and resistance by disc diffusion method. Isolates that were resistant to at least two of the third-group cephalosporins such as ceftriaxone, cefotaxime and ceftazidime were confirmed as ESBL producers using Double Disks Synergy Test (DDST). Out of the one hundred and four (104) isolates screened, twenty (20) were confirmed by DDST to be ESBL producers. The prevalence rate of ESBL production in clinical Klebsiella pneumoniae and Escherichia coli isolates were observed to be 19.2%. The study established the prevalence of Extended Spectrum Beta-Lactamase producing Klebsiella pneumoniae and Escherichia coli among clinical isolates in the study area. Therefore, monitoring dissemination and transmissions of ESBL producers are highly recommended for optimum patient care and preventing the spread of multidrug resistant (MDR) pathogens.
Dr. Ruchira Ankar, PhD (N), Mrs. J. Vinodhini Zipporah
Background: Stroke is a leading cause of mortality and disability worldwide, disproportionately affecting low- and middle-income countries (LMICs). In India, delayed recognition of warning signs and limited primary prevention strategies contribute to poor outcomes. Frontline health workers (FLWs) are uniquely positioned to identify risk factors and deliver community-based interventions, yet structured training in stroke prevention is limited. Objectives: The primary objective is to assess whether the Adult Stroke Prevention Module (ASPM) improves FLW skill delegation and competency compared to the Nigerian Educational Intervention Module (NEIM). Secondary objectives include evaluating changes in community participants’ modifiable risk factors, knowledge retention, and adherence to preventive behaviors. Methods: This cluster-randomized controlled trial will be conducted across eight community clusters in Wardha district, Maharashtra. Clusters will be randomized using a computer-generated sequence by an independent statistician, with allocation concealment maintained. Stratification will be applied based on population size and FLW density. FLWs will be randomized to ASPM (structured four-session training plus video module) or NEIM (translated video-based education with counseling). Adults aged 40–60 years identified by FLWs will undergo baseline and follow-up assessments at 3, 6, and 9 months, including blood pressure, glucose, cholesterol, waist-to-hip ratio, lifestyle habits, and stress levels. The primary endpoint is FLW skill delegation competency, measured using a validated checklist. Secondary outcomes include biometric and behavioral changes among community participants. Sample size is calculated assuming an effect size of 0.30, intracluster correlation coefficient (ICC) of 0.02, alpha of 0.05, power of 80%, and attrition of 15%, requiring approximately 100 FLWs and 400 community participants. Data will be analyzed using mixed-effects regression models with cluster random effects, baseline adjustment, repeated measures, and multiple imputation for missing data. Results: The trial has been registered in the Clinical Trial Registry of India (CTRI/2025/05/086446). Training materials and video modules have been finalized, and a pilot study with 20 FLWs is yet to be completed to refine tools and procedures. Recruitment is projected to begin in May 2026, with data collection expected to conclude by March 2027. Conclusions: This study will provide evidence on the comparative efficacy of ASPM versus NEIM in enhancing FLW-led stroke prevention. Findings are expected to inform scalable, technology-driven strategies for primary prevention in LMICs, strengthen community health systems, and contribute to policy frameworks aimed at reducing the growing burden of stroke. Trial Registration: CTRI/2025/05/086446 (Registered May 6, 2025)
Abdullah Ghanim Jaber*
The paper presents a new framework, HE-FedStress, with which it is feasible to monitor stress and preserve privacy in an AI-based approach to stress detection through federated learning and homomorphic encryption on wearable edge devices. The proposed system handles the essential privacy issues that come with decentralized health surveillance because the proposed system allows joint model training without exposing uncoded biometric information. The Edge wearable devices are local physiological signal temporal attention models that inference latency can process five-second windows with a latency of just 47 ms, implemented on photoplethysmography, electrodermal activity and accelerator data. The updates of the model are coded using the Pailier cryptosystem and sent to the central server where they could be aggregated securely without decrypting each individual contribution. The WESAD and SWELL-KW datasets have been empirically assessed to verify that HE-FedStress can give F1-scores of 89.7% and 85.2% respectively and retain centralized model performance with 92 and 94 % of this performance under full cryptographic protection against model-inversion attacks (compared to 34.7 % centralization in the standard federated learning case). The structure uses gradient quantization, which cuts down the communication load to 63KB/ round, and uses adaptive batch size to support heterogeneous device capacity. The computational optimizations (depthwise separable convolutions, selective attention pruning, and eight-bit quantization) allow incessant 24 hour execution of commercial wearables with only a 19% power consumption impact over plaintext federated learning. The design of the modular architecture is to meet GDPR and HIPAA data-localization standards and provide the ability to extend it to other healthcare applications. Therefore, this contribution can provide a practical, scalable stress monitoring solution to secure and personalized performance with a robust guarantee on cryptography, and can also indicate that the requirements of resource-constrained edge environments can be satisfied with a robust guarantee alongside real-time performance.
Godwin Joseph Musuku
In many semi-arid and developing countries like Botswana, sustainable delivery of water infrastructure projects remains a persistent challenge exacerbated by climate change, recurrent project delays, cost overruns, and operational failures despite many countries having established policy frameworks. This study analyses the systemic factors influencing water sector project performance in Botswana, concentrating on practitioners’ understanding of national water and environmental frameworks, critical success factors (CSFs), and sustainability-related implementation gaps influencing project delivery. Conceptualising these challenges as manifestations of "project-level friction", the misalignment between policy intent and execution capacity, the study examines where and why such friction emerges. A mixed methods research design was adopted, integrating a structured questionnaire survey sent via email to water sector professionals. The study’s quantitative data were analysed using descriptive statistics, ranking techniques (RII), and correlation analysis, while qualitative data were subjected to thematic analysis utilising NVivo. The study results indicate that there is a considerable level of knowledge among practitioners about regulatory frameworks, and they also underscore insufficient integration of sustainability principles into day-to-day project management practices. The study reveals key challenges that impact water sector project completion through institutional fragmentation, insufficient technical expertise, and inconsistent regulatory enforcement. The study results indicate a strong positive correlation between policy literacy, stakeholder engagement, and perceived project effectiveness (𝜌>0.70). In addition, the study findings indicate that underperformance in project delivery is a result of shortcomings in governance, leadership, and execution, rather than technical inadequacy. The study offers valuable insights to guide policy development, institutional strengthening, and capacity-building efforts. It emphasizes the need for proportional investment in governance and human capital alongside physical infrastructure to achieve water sustainability in Botswana and similar semi-arid contexts.
Guilbert B. Mansueto, Irene S Sangutin, Karen Abegail Cuizon, Paulino V. Pioquinto, Rey Q. Aranzado
This study aimed to explore the Life World of Online Sexual Abuse and Exploitation of Children (OSAEC) Investigator of the Philippine National Police-Women and Children Protection Center. Specifically, it investigated their positive and negative experiences during the investigation, the strategies they used to address challenges, and their aspirations for improving the quality of their work. Using a qualitative phenomenological approach, in-depth interviews and focused group discussions were conducted using an interview guide (IG) with ten (10) investigators as informants. Data were analyzed using Colaizzi’s method to extract significant statements, formulate meanings, and identify clustered and emergent themes that characterized the phenomenon. Findings revealed twelve (12) interconnected themes: Sense of Purpose and Fulfillment in Work, Empathy and Motivation through Human Connection, and Skill and System Empowerment through Training, which reflect the intrinsic and professional rewards derived from child protection efforts. These positive dimensions are tempered by the Psychological and Emotional Toll, Operational Constraints and Resource Gaps, and Accessibility and Environmental Limitations that characterize the demanding landscape of OSAEC investigations. Investigators described strengthening their competence through Adaptive Learning and Technical Skills Development, while sustaining well-being through Psychological Coping and Peer Support. Operational effectiveness was further enhanced by Strategic Collaboration and Resource Mobilization, particularly in complex cybercrime environments. Looking forward, participants emphasized the need for Expansion of Training and Digital Capability, greater Community Engagement and Awareness, and sustained Institutional and Resource Strengthening to improve investigative outcomes and child protection mechanisms. Overall, the study underscores that addressing OSAEC requires not only advanced technical expertise but also trauma-informed organizational support, collaborative networks, and continuous professional development to ensure both investigator resilience and effective protection of vulnerable children. The study revealed that OSAEC investigators within the PNP Women and Children Protection Center develop resilience, specialized skills, and ethical preparedness essential for combating Online Sexual Abuse and Exploitation of Children. Their work requires advanced digital forensic competence, investigative expertise, and victim-centered engagement while navigating complex and high-risk online environments. Investigators face significant psychological and emotional challenges, operational constraints, and resource limitations, emphasizing the need for continuous training, peer support, and institutional strengthening to ensure both their well-being and the effectiveness of child protection efforts.
D. Jayalakshmi, G. Subbiah, M. Teresa Nirmala
In this paper, we study a new concept, (α,β)-level of pythagorean fuzzy subgroup which different from fuzzy groups, intuitionistic fuzzy group, (2,1)-fuzzy subgroups. Also we define a new kind of pythagorean fuzzy subgroup and its level cut sets. Finally, some properties of pythagorean fuzzy subgroups are studied.
Brindha L, Dr. K. Lakshmi, Kanishka I, Kathiresh M
Driver fatigue is a leading cause of road accidents worldwide. Long driving hours, sleep deprivation, night travel, and health conditions significantly reduce the alertness and reaction time of drivers. Traditional safety mechanisms in vehicles focus mainly on collision prevention rather than monitoring the physical condition of the driver. Therefore, this study presents a Real-Time Drowsiness Detection System that continuously monitors the facial features and eye movements of drivers using computer vision and machine learning techniques. The proposed system detects eye closure duration, blinking frequency, and facial fatigue indicators to determine a driver’s alertness level. When drowsiness is detected, the system immediately generates an alert through an alarm or a vibration signal. The system is non-intrusive, cost-effective, and suitable for deployment in real-world settings. The main objective of this study was to develop an accurate, efficient, and real-time monitoring solution that enhances road safety and reduces accident risks.
DR.C.Jayasri, E.Nikitha Rajam, P.Gayathri, R.Aswini, S.Shivaane
Real-time closed captioning is essential for improving accessibility for Deaf and Hard-of-Hearing (DHH) users in live communication. This paper presents a low-latency multilingual closed-captioning system designed for Indian languages. The proposed system integrates streaming Automatic Speech Recognition (ASR), automatic language identification, text simplification, punctuation restoration, and speaker segmentation. It supports code-switching and optional translation or transliteration across scripts. The system is optimized for sub-second end-to-end latency and robustness in noisy environments. Experimental results show that simplified captions significantly improve readability and comprehension while maintaining acceptable recognition accuracy, making the system suitable for real-time educational and public communication applications.
Dr. Sumathy Kingslin, Ms. K. Vaishnavi
The increasing demand for data-driven and transparent agricultural systems has led to the adoption of advanced digital technologies. This paper presents the second phase implementation of a real-time smart farming platform that integrates Internet of Things (IoT), Artificial Intelligence (AI), and blockchain technologies. IoT sensors continuously monitor field conditions and transmit real-time data to a backend server for processing and storage. An AI-based prediction module analyzes sensor data to support timely agricultural decision-making. To ensure fair and transparent trade, blockchain-based smart contracts are employed to record and execute agricultural transactions without intermediaries. Experimental results demonstrate reliable real-time data handling, effective AI prediction performance, and secure trade execution, validating the practicality of the implemented system.
Dr. Paul. K. Kurgat, Mr. Samson Kemboi Koech
Many countries around the world use economic diplomacy to exert their influence. Kenya is a major economy in Africa ranking currently among the biggest economies in East Africa Community. While many studies explore Kenya’s economic growth, few interrogate its efficiency as a tool for economic diplomacy in the EA. This study examined how regional trade stratagems influence Kenya’s diplomatic engagements within the EAC paradigm. The objective of this study was to investigate how regional trade stratagems influence Kenya’s diplomatic engagements within the EAC framework the literature was reviewed thematically guided by Interdependence theory and reinforced by Neoliberal theory. This study used a descriptive research design and its target population included Kenya’s Ministry of Trade and Industrialization. The study used purposive, stratified and random sampling methods to sample its respondents. Quantitative data was collected using questionnaires and coded using SPSS and analyzed using descriptive statistics (frequencies and percentages) and presented in tables. Qualitative data was collected by interviewing Key Informants (KIIs), analyzed using content and thematic analysis and presented in narrative and verbatim format. The study found that trade policies (b=0.245, p<0.001), economic partnerships (b=0.278, p<0.001), and strategic approaches (b=0.289, p<0.001) played a significant role in promoting Kenya in the EAC, whereas the persistent challenges (b=0.236, p=0.001) like tariffs and logistical barriers acted as a limit to progress. The study concludes that Kenya has its regional influence based on good policy alignment, economic integration, and strategic partnerships. The research recommends the harmonization of trade frameworks, investing in regional infrastructure and digital diplomacy as methods to enhance Kenya economic diplomacy in the EAC paradigm.
Intana Patma Laut, Sri Maryati, Tajidan Tajidan
Instant 3-in-1 sachet coffee (Kapal Api, ABC, and Nescafé) is popular in Indonesia for its practicality, influenced by factors such as taste, aroma, price, packaging, availability, and promotion. This study analyzes consumer preferences with customer satisfaction, and their relationship to each other, for the three brands in Mataram City. This quantitative descriptive study involved 90 respondents, selected through quota sampling (30 per location) and accidental sampling in the field, and used both primary (questionnaires) and secondary data. The analysis included descriptive statistics, Customer Satisfaction Index (CSI), and Spearman's rank correlation. The results indicate strong consumer preference (average score of 4.04 on a 5-point scale) and very high consumer satisfaction (CSI of 82.54%), with product availability rated highest and promotion lowest. The correlation between preference with satisfaction is positive and significant (rs = 0.672; p < 0.05). The results indicate that product availability is the most influential attribute in shaping consumer preferences, followed by taste and aroma. Based on the CSI analysis, the overall level of consumer satisfaction falls within the satisfied category. The Spearman correlation results show a positive, significant relationship between consumer preferences with satisfaction, indicating that higher preference levels are associated with greater satisfaction. These findings suggest that ease of product access plays a key role in influencing consumer preferences, while taste and aroma remain important quality considerations. Therefore, producers should ensure consistent product availability while maintaining taste and aroma quality to enhance consumer satisfaction and strengthen market competitiveness.
Dr. Gururaj F Duragannavar, Kumar S.
Retail management refers to overseeing and controlling various activities within a retail environment to ensure the success and sustainability of a business. This paper delves into the key components of retail management, including customer service, inventory control, pricing strategies, store design, marketing, and technology integration. It discusses the impact of globalization and digital transformation on retail, highlighting emerging trends, challenges, and opportunities for retailers. Through this research, the paper offers a comprehensive understanding of how effective retail management practices can foster competitive advantages in a rapidly evolving industry.
Chukwuemeka Ifegwu Eke, Lisu Anne Mshelia
This paper interrogates the idea of “best practice” for innovation hubs through evidence from a slum settlement in Abuja, Nigeria. Drawing on a convergent mixed-methods design, it combines two focus group discussions with 16 residents and a household survey of 83 respondents to examine how global hub models are interpreted, adapted and contested in contexts of multidimensional poverty. The analysis focuses on perceptions of international best practices and localised adaptations, and how these shape current innovation hub usage. Qualitative findings show that residents are keenly aware of global examples from India, Kenya and South Africa, but insist that any hub in Tudunwada must be tailored to local livelihoods, infrastructure constraints and community priorities. Multiple regression results indicate that stronger endorsement of international best-practice models is associated with lower likelihood of current hub use, while perceived localised adaptations are not a significant predictor. The paper argues for rethinking best practice around context-responsive, poverty-oriented hub design
Aishwaryjeet Shrivastava, Ayush Verma, Dr. Divakar Singh, Dr. Kavita Chourasia, Krishnakant Markam, Md. Abid, Ms. Kamini Maheshwari
This paper presents RouterMaster, a full-stack route and logistics management system developed to streamline trans- portation processes including route creation, vehicle assignment, and delivery monitoring. Traditional route management sys- tems rely heavily on manual coordination, leading to delays, inefficiency, and poor tracking. RouterMaster leverages Java Spring Boot for backend development, MySQL for relational data storage, and a modern web frontend to automate logistics workflows. The system provides secure user authentication, CRUD operations for routes and vehicles, driver assignment management, and a centralized dashboard accessible through REST APIs. The application was tested using Postman and validated for correctness, data integrity, and API compliance. RouterMaster demonstrates how modern enterprise Java tech- nologies can replace manual logistics operations with scalable and efficient digital solutions.
Effaliza Misran, Fitrien Husin, Harisun Yaakob
The Sarawak Gold (SG1) pineapple, a premium tropical fruit, has emerged as a symbol of Sarawak's agricultural excellence and Malaysia's diversification into high-value agricultural exports. Renowned for its vibrant golden hue, superior sweetness, and unique aroma, SG1 pineapple combines exceptional sensory qualities with a robust nutritional profile, positioning it as a premium agricultural commodity for international export. This article explores the historical background, unique agronomic features, and cultivation practices that have contributed to the development and success of SG1 pineapple. Emphasizing sustainable farming methods and the pivotal role of smallholder farmers, the article highlights how the SG1 pineapple industry fosters rural economic development and supports the livelihoods of local communities. The branding of SG1 as a premium product has elevated its market demand, enabling expansion into Asia-Pacific and European markets, and solidifying its status as a valuable export commodity for Malaysia. Through its contribution to export revenues, job creation, and rural prosperity, SG1 pineapple not only enhances Sarawak’s economy but also reinforces Malaysia’s position as a global leader in the production of high-quality tropical fruits. However, as SG1 pineapple is a relatively new cultivar, published scientific information remains limited; therefore, this review synthesizes currently available data and identifies key research gaps to guide future studies.
Arun Karthick. B, Harrish. B, Mohamed Naveed. A, Mr.R. Danu
The growing competition in the job market has made career guidance and placement prediction vital for students. This paper proposes an AI-based system that analyzes student profiles to predict campus placement outcomes. Using machine learning, the system evaluates academic performance, technical and soft skills, extracurriculars, and historical placement data. It offers personalized career recommendations and placement probabilities, helping students improve employability. Additionally, it supports educational institutions in refining their placement strategies. This AI-driven approach bridges the gap between student potential and employer expectations, aiming for better placement results
Danny Daniel bin Rahsidin, Hanis Damia binti Roslan, Mohamad Khairul Aizzat bin Rusmami, Muhammad Syafiq bin Ishak, Norhazren Izatie Mohd, Nur Syaranisa Irdina binti Zaidinar
On-site construction safety management continues to face significant challenges due to reliance on manual inspections, paper-based documentation, and reactive safety practices. The absence of automated and data-driven monitoring mechanisms limits timely risk identification and informed decision-making. This paper addresses this gap by proposing a conceptual design of a Smart Safety Monitoring and Decision Support System (DSS) that integrates Internet of Things (IoT) sensors and computer vision technologies. The proposed system is designed to capture real-time environmental data from IoT sensors, detect unsafe behaviours and conditions using computer vision techniques, and consolidate all information in a centralized monitoring dashboard. By enabling continuous data acquisition and real-time analysis, the system aims to support proactive safety management and improve the accuracy of on-site risk identification and safety-related decision-making. Although the study is limited to a conceptual design and does not include empirical implementation or validation, it demonstrates the potential of data-driven technologies to transform construction safety management from a reactive to a proactive approach. The paper contributes to the existing literature by providing a structured conceptual framework for smart, technology-enabled safety monitoring systems in construction environments.
Anuradha Patel, Prof (Dr.) Ashish Upadhyay
Social economics extends conventional economic theory by incorporating social norms, ethics, institutional frameworks, behavioural patterns, and power structures into economic analysis. In agrarian societies such as India, economic behaviour cannot be adequately explained without accounting for caste structures, gender relations, educational inequalities, health access, infrastructural disparities, and governance systems. Despite significant advances in agricultural productivity following the Green Revolution and subsequent modernization phases, rural socio-economic transformation remains uneven and spatially differentiated. This study develops a multidimensional Social Economic Rural Transformation Model (SERTM) integrating agricultural modernization, rural infrastructure, marketing efficiency, small-scale industries, health systems, and educational capital. Using composite index construction, Principal Component Analysis (PCA), multiple regression modelling, and structural equation modelling (SEM), the study evaluates the determinants of rural socio-economic transformation across selected districts. Findings indicate that agricultural modernization alone is insufficient to generate inclusive growth unless accompanied by institutional reforms, rural connectivity, health accessibility, and educational expansion. Infrastructure emerges as a catalytic multiplier, while social capital and institutional accountability significantly moderate economic outcomes. The study contributes to social economics by empirically validating the interdependence between social structures and economic performance in rural contexts.
Gian Carlo Rodillas, Jefferson Suya, Roland Christopher Doctor, Xianne Jhuztin Tubog
This research introduces Sort Out, an Intelligent Inventory Management System tailored to tackle the persistent issues of manual inventory tracking and product management in small grocery stores. Numerous small retailers encounter difficulties like excessive inventory, stockouts, erroneous recordkeeping, and slow reactions to changes in stock levels. To address these challenges, the system combines Descriptive Analytics with a Rule-Based Algorithm to automate essential tasks like product tracking, expiration monitoring, and report creation. The system's design is created according to the System Development Life Cycle (SDLC) approach. Information is collected from chosen mini grocery stores via interviews and observations to identify user needs. The development process employed PHP, MySQL, and XAMPP as main tools, with the interface design refined for ease of use and accessibility.
Dr. B. Umesh Kumar Sharma
Emotional well-being is fundamental to children’s academic engagement, social development, and long-term mental health. The present cross-sectional quantitative study examined the emotional well-being of 264 elementary school students from eight government schools in Bhoirymbong Block, Meghalaya. A validated, child-friendly questionnaire assessed multiple domains including overall emotional status, worry, happiness, loneliness, peer relationships, school perception, fear of teachers, and examination anxiety. Descriptive findings indicated that 74.9% of students demonstrated healthy emotional status; however, emotional vulnerability increased significantly across grade levels. Inferential analyses revealed significant grade differences in emotional vulnerability, F(2, 261) = 9.34, p < .001, and a gender difference in examination anxiety, with girls reporting higher anxiety. Multiple regression analysis showed that fear of teachers (β = .34), examination anxiety (β = .29), and loneliness (β = .21) significantly predicted emotional vulnerability, explaining 32% of the variance, while peer trust functioned as a protective factor. Findings highlight the critical role of school climate and assessment practices in shaping emotional outcomes and underscore the need for emotionally responsive pedagogy and structured social-emotional learning frameworks in elementary education.
Dr P. Kavitha, M Prasanna Vigneshwaran, S Lipika, S Nikitha, T Sanjay
In the modern digital era, sensitive data transmitted over the internet is vulnerable to interception. While Encryption (like AES or RSA) secures the content of a message, it does not hide the fact that a secret message is being sent. This can make the sender a target for attackers. STEGOSECURE solves this by hiding the data in plain sight within image files, providing an extra layer of "Security through Obscurity." STEGOSECURE is a modern web-based application designed to enhance data privacy through Image Steganography. Unlike traditional encryption, which renders data unreadable and draws attention to the existence of a secret, steganography conceals the very presence of information by embedding it within a digital carrier— in this case, an image.
Rupesh Chandrasen Londhe
Stewardship management represents a transformative paradigm in organizational leadership, emphasizing responsibility, accountability, trust, and sustainability over short-term efficiency. This research develops a comprehensive theoretical and empirical framework for stewardship management, integrating governance theory, psychological foundations, stakeholder perspectives, and quantitative validation. Using regression modeling, the study demonstrates that stewardship orientation significantly predicts organizational performance, mediated by employee engagement and stakeholder trust. The findings contribute to organizational theory by empirically validating stewardship as a robust governance alternative to agency-based models. Sectoral applications across corporate organizations, higher education institutions, and nonprofit sectors are explored, with specific attention to emerging governance contexts in India.
Dr. Devidutta Maurya, Dr. Rakesh Kumar Rai, Dr. Snigdha Lal
Adenosine analogues continue to attract considerable attention due to their diverse pharmacological potential and strong involvement in enzyme and receptor modulation. In the present study, a comprehensive in silico investigation of the nitrogen-rich adenosine analogue (C₂₀H₂₅N₇O₆) was carried out to elucidate its structural, electronic, and binding characteristics using density functional theory (DFT) and molecular docking approaches. The molecular geometry was fully optimized at an appropriate DFT level, confirming the structural stability of the ligand. Frontier molecular orbital analysis revealed a moderate HOMO–LUMO energy gap, suggesting balanced chemical stability and reactivity. Global reactivity descriptors, including chemical hardness, softness, electronegativity, and electrophilicity index, were computed to assess the molecule’s reactive profile. Molecular electrostatic potential (MEP) mapping identified electron-rich regions localized mainly around oxygen and nitrogen atoms, indicating probable sites for electrophilic and hydrogen-bond interactions.
Ekpunobi, Azubuike J, Muomeliri, Chukwudi B, Okoli, Donald N
This report presents the successful fabrication and characterization of nickel-doped lead telluride (Ni:PbTe) chalcogenide thin films for potential device applications. The films were synthesized using a three-electrode electrodeposition method on fluorine-doped tin oxide (FTO) glass substrates, with lead trinitrate (V), tellurium (IV) oxide, and nickel chloride hexahydrate serving as precursors. Deposition time was varied to optimize film properties. Characterization using UV-Vis spectrometry and X-ray diffraction (XRD) revealed that absorbance increased with deposition time across the visible (VIS) and near-infrared (NIR) regions. The refractive index ranged from 1.5–1.62 at 1-minute deposition, increasing to 2.5–3.25 at 4 minutes, indicating suitability for optoelectronic devices like optical fibers and waveguides. Transmittance decreased with longer deposition times but remained higher in the NIR region. The optical bandgap ranged from 1.3–1.7 eV across different deposition times ideal for photovoltaic and LED applications. Film thickness also increased with deposition time, suggesting that optical properties can be tuned accordingly.XRD analysis confirmed the crystalline nature of the films, with crystallinity improving at longer deposition durations. Structural parameters such as crystallite size, dislocation density, and microstrain supported this trend, reinforcing the films' potential for advanced optoelectronic applications.
Balogun, A.T, Olanipekun, O.S, Omojola A.A
This study investigates the sub-lethal effects of varying concentrations of Paraquat dichloride on biochemical parameters and mortality rates of juvenile Clarias gariepinus over a 28-day exposure period. A controlled laboratory experiment was conducted with five treatment groups (T1 to T5) of juvenile C. gariepinus, each comprising nine fish. The control group (T1) received no Paraquat, while T2 to T5 were exposed to increasing concentrations (0.034 to 0.134 ml/L) of Paraquat dichloride (200 g/L). Mortality rates increased significantly with higher Paraquat concentrations, peaking at 66.67% in T5. Results also revealed the biochemical disruptions caused by Paraquat exposure indicated increased glucose levels, liver dysfunction and altered cholesterol metabolism in C. gariepinus, suggesting physiological stress and toxicity of juvenile C. gariepinus leading to elevated mortality and compromised health. This study emphasized the critical role of biochemical assessments in evaluating health impacts of pollutants on fish
Dr. Koushik Ray
Diagnostic healthcare—clinical laboratories, pathology services, imaging support units, and point-of-care testing—has become indispensable for modern medicine. Yet, the same systems that improve clinical outcomes can impose significant environmental burdens through biomedical waste generation, single-use plastics, chemical hazards, energy-intensive instrumentation, water consumption, and carbon emissions across supply chains. This paper examines the major sustainability challenges in diagnostic healthcare, focusing on environmental risks arising from laboratory operations and the policy responses required to mitigate them. Using a qualitative, policy-analytical approach grounded in environmental health governance, the paper maps key risk pathways: infectious and sharps waste, chemical and pharmaceutical residues, microplastics, wastewater contamination, and greenhouse gas emissions from energy use and logistics. The analysis highlights structural barriers including regulatory gaps, weak enforcement, fragmented waste infrastructure, limited green procurement, cost pressures, inadequate staff training, and insufficient environmental performance measurement. The paper proposes a multi-level policy framework: (i) strengthening regulation and compliance, (ii) implementing circular economy strategies such as extended producer responsibility and sustainable procurement, (iii) accelerating decarbonization through energy efficiency and renewables, (iv) improving segregation and treatment systems, (v) digitizing environmental monitoring, and (vi) building a culture of sustainability through training, accreditation incentives, and transparent reporting. The paper concludes with actionable recommendations and an implementation roadmap for low- and middle-income settings, where diagnostic expansion must be aligned with environmental protection and public health resilience.
Gopala Krishna Murthy H.R
Antibacterial resistance continues to threaten public health worldwide, prompting the development of novel small-molecule antibacterial agents. Herein, we report the synthesis, spectroscopic characterization, and antibacterial activity assessment of a series of novel heterocyclic derivatives. Structural confirmation was achieved through FT-IR, 1H / 13C NMR, and mass spectrometry. Antibacterial efficacy was evaluated against Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) strains. The synthesized compounds exhibited comparable or superior efficacy relative to standard antibiotics, supporting their potential as future therapeutic agents.
Gautam Kardani, Kishan Rathod, Savankumar Donga, Shivani Chaudhary, Sucheta Karande, Tusharkumar Sangada
Cancer remains a global health challenge, and current therapies, including chemotherapy and radiation therapy, are often limited by serious side effects and drug resistance. These limitations have sparked increasing interest in natural alternatives, especially plant-based compounds with diverse biological actions. Several phytochemicals, such as curcumin, epigallocatechin-3-gallate (EGCG), withaferin-A, kaempferol, and quercetin, have been shown to inhibit important signaling pathways that cancer cells rely on for growth, survival, and metastasis. These natural agents, which often target multiple cellular pathways rather than a single target, as many drugs do, are particularly valuable in the fight against drug-resistant cancers. Nevertheless, their clinical use is limited by issues such as low bioavailability, distinct pharmacokinetics, and tumor heterogeneity. In view of these challenges, the utilization of innovative drug delivery methods, such as nano-functionalized formulations, along with combination strategies, has been considered in recent studies. This evidence gives way to the development of network pharmacology and personalized medicine as valuable strategies in maximizing the therapeutic activity of medicinal plants; This review explores the mechanisms by which these agents exert their anticancer activity and highlights progress made in, as well as hurdles remaining toward, the integration of these strategies into contemporary oncology.
Leonard Karshima Shilgba
This paper introduces the Basket Residue Theory (BRT) as a mathematical framework for assessing the real purchasing power of money, prosperity levels, poverty dynamics, and indirect wealth transfers in an economy. The model builds on variations in the prices of a representative basket of goods and services, offering a quantitative measure of real value erosion or enhancement over time. BRT extends beyond conventional inflation indices by integrating fiscal and monetary interactions into the valuation residue concept.
Dr.Suphala Kotian, Nichitha Kumari
Adoption is a complex process that influences not only the lives of adopted children but also the psychological, emotional, and social functioning of adoptive parents. This review critically examines empirical and theoretical literature on the impact of adoption on adoptive parents, with a focus on emotional well-being, parental identity, stress and coping, marital and social relationships, and long-term personal growth. The literature indicates that although adoptive parents often experience profound satisfaction and meaning in parenthood, they also encounter distinctive challenges such as pre-adoption uncertainty, attachment concerns, parenting stress, and societal stigma. The availability of pre-adoption preparation, social support, and post-adoption services significantly moderates parental outcomes. Understanding these dynamics is essential for practitioners, policymakers, and adoption agencies to develop holistic interventions that support adoptive parents throughout the adoption lifecycle.
Md. Ibrahim Hossain
This study looks at how autocratic leadership affects the well-being of employees in small humanitarian NGOs in Bangladesh. Based on interviews with 15 staff members, including project managers, supervisors, and field workers from various NGOs, the research finds that workers face long hours, unpaid salaries, and no clear balance between work and personal life because top leaders make decisions without talking to others. Employees described tough schedules, like working 15 to 16 hours a day without breaks, even during important events like Eid. They also had to do extra tasks without being asked. These conditions caused physical issues like body pain, malnutrition, and sunburn, and mental health problems like depression, anxiety, and even thoughts of suicide. The study also notes that many of these issues are made worse by a lack of funding and resources, which makes exploitation more common in small NGOs. The paper highlights a gap in existing literature, pointing out that not enough research focuses on leadership styles in developing countries like Bangladesh, where traditional cultural structures often support autocratic leadership. To address this, the study introduces the Supportive Leadership and Management (SLM) model. This model promotes a more inclusive and democratic work environment with set working hours, holidays, ongoing training, stable pay that isn't tied to donor funds, and systems for feedback and support. Thematic analysis of the interview data supports the idea that autocratic leadership harms well-being, while supportive leadership improves job satisfaction and productivity. The findings suggest that NGO leaders, policymakers, and donors should put employee well-being first to ensure long-term success. The SLM model can be useful beyond NGOs and in different organizations around the world. Future studies should include quantitative validation of the model and comparisons across different sectors. This research contributes to discussions about ethical leadership, especially in challenging environments, by promoting humane practices that help retain valuable workers and help reach important goals.
Alexandre Costa Sacala, Elisabeth Eduardo da Costa Januário Muanauta, José Mário João
Foreign Direct Investment (FDI) is often considered an engine of economic growth in developing countries, due to its capacity to transfer technology, generate employment, and boost productive sectors. Therefore, this study aims to analyze the impact of Foreign Direct Investment (FDI) on the growth of the Angolan economy from 2014 to 2023. To test the hypothesis, a Linear Regression model was used, considering a Multiple econometric model based on Vector autoregressive, which expresses the relationship between FDI, exchange rate, trade balance, and Angola's GDP from 2014 to 2023. The results indicate that FDI did not have a positive and significant impact on GDP growth. The FDI coefficient showed a negative value (-0.23), meaning that an increase in FDI did not directly translate into economic growth during the analyzed period. However, it is concluded that Angola's economic environment was unfavorable during the period, which contributed little to attracting FDI. This conclusion is consistent with the assumptions presented. Therefore, the increase in Foreign Direct Investment (FDI) in Angola between 2014 and 2023 did not have a significant impact on the country's economic growth. Despite the influx of FDI, internal and external factors neutralized its positive impacts on the Angolan economy during the period 2014-2023. Global events, such as health and economic crises, can influence investment decisions. For this to translate into effective benefits, it is necessary to redirect investment towards strategic non-oil sectors, strengthen local absorption capacities, and ensure greater macroeconomic and institutional stability. Therefore, future research should consider these impacts to better understand how foreign investment reacts to these challenges.
Amoussou Dorothee
This study analyzes the computerization of the management of scientific processes and assesses its impact on institutional development in higher education, taking as a case study the Faculty of Economics of Kimpa Vita University during the period 2022–2025. It is based on the assumption that, in the knowledge society, Information and Communication Technologies (ICT) constitute strategic tools for stimulating scientific research, optimizing academic management, and strengthening institutional positioning. Computerization is not limited to data digitization; rather, it implies a structural and cultural transformation, requiring innovative practices and the appreciation of knowledge as an essential asset for socio-economic progress. The Faculty of Economics faces technological and financial challenges, but also opportunities to strengthen its academic and scientific identity by expanding its national and international visibility and credibility. Methodologically, the research adopts a mixed approach, combining questionnaires administered to the academic community with interviews conducted with lecturers and managers, allowing for a holistic understanding of the impacts of computerization. The results indicate gains in administrative efficiency, promotion of scientific output, knowledge sharing, and improvement in the quality of teaching. It is concluded that computerized scientific management is not only a contemporary requirement but also a necessary condition for the future sustainability of Angolan higher education.
Girly D. Serino, MBA, Leo C. Naparota, PhD
This study examined the innovative work environment and its relationship with the innovative work behavior of employees of the Community Rural Bank of Dapitan City, Inc. during calendar year 2024. A descriptive-correlational design was employed, involving 120 respondents. Weighted mean, standard deviation, and Spearman rank-order correlation (Spearman’s rho) were used for data analysis. Results indicated that employees perceived the innovative work environment as very high, while their innovative work behavior was assessed as high. Correlation analysis revealed a strong, positive, and statistically significant relationship between the innovative work environment and employees’ innovative work behavior. The findings may serve as a reference for the board of directors and managers in strengthening management strategies and workplace conditions that support innovative behavior among employees.
Dinesh Thakur, Prabakaran Raghavendran, Prakash Chand Thakur, Tharmalingam Gunasekar
Heat and wave equations are widely recognized partial differential equations that find applications in fundamental sciences and engineering disciplines. Integral transform techniques offer efficient approaches to address a range of issues encountered in the basic sciences and engineering fields. This chapter introduces the Emad-Sara Integral Transform for solving heat and wave equations expressed in terms of partial differential equations.
Asavari Barshikar, Harshada Wasade, Khushi Gelda, Pratiksha Sayam, Rajas Mudey, Vedanti Bhure
Background: Avascular necrosis (AVN) of the femoral head is a progressive musculoskeletal condition characterized by compromised blood supply leading to bone tissue death, pain, reduced mobility, restricted hip joint range of motion, and functional disability. Early-stage AVN commonly affects young adults and may progress rapidly to femoral head collapse if left untreated. Objective: To evaluate the effectiveness of manual hip mobilization combined with progressive weight-bearing training on pain, hip joint range of motion, and functional disability in young adults with early-stage avascular necrosis of the femoral head. Methods: A quasi-experimental interventional study was conducted on 15 young adults diagnosed with radiographically confirmed early-stage AVN (Ficat–Arlet Stage I–II). Participants underwent a supervised physiotherapy intervention for three weeks consisting of Maitland Grade I, II and III manual hip mobilization combined with progressive weight-bearing training and routine physiotherapy exercises. Pain intensity, hip joint range of motion (ROM), and functional disability were assessed using the Numerical Pain Rating Scale (NPRS), universal goniometry, and Harris Hip Score (HHS). Statistical analysis was performed using paired t-test. Results: Significant improvement in pain, hip joint range of motion, and functional outcomes was observed following the intervention. NPRS scores reduced from 6.2 ± 1.1 to 2.8 ± 0.9, while Harris Hip Score improved from 62.5 ± 6.8 to 84.2 ± 5.7 (p < 0.001). Hip joint range of motion was found to be restricted at baseline due to pain and capsular stiffness; however, following the three-week physiotherapy intervention, an increase in active hip range of motion was observed in all planes of movement as assessed using universal goniometry. Conclusion: A three-week physiotherapy program consisting of Maitland Grade I,II and III manual hip mobilization combined with progressive weight-bearing training significantly reduced pain and improved hip joint range of motion and functional outcomes in young adults with early-stage avascular necrosis of the femoral head, suggesting its effectiveness as a conservative intervention to reduce disability and enhance hip function.
Dr. Princy Patel, Dr. Ratna Bhatt
Tinea corporis, commonly known as ringworm, is a superficial fungal infection of the glabrous skin. While once considered a manageable tropical infection, it has evolved into an epidemic-like, chronic, and difficult-to-treat condition in India over the last decade. Primarily caused by Trichophyton rubrum, Trichophyton mentagrophytes has also emerged as a major pathogen. The infection spreads through direct contact with infected individuals, animals or contaminated objects like towels and clothing. The infection typically manifests after 1-3 weeks as a well-defined, scaly, erythematous annular plaque that spreads outward with central clearing. The diagnosis of tinea corporis is usually clinical, confirmation can be done by microscopic examination of potassium hydroxide (KOH) wet-mount preparations and fungal cultures. Management centers on systemic or topical antifungals, avoiding the misuse of over-the-counter combinations and strictly maintaining personal hygiene to prevent recurrence. Additionally, this article outlines the role of Homoeopathic management utilizing individualized remedies such as Sepia officinalis, Tellurium, Sulphur, etc.
Archana Mishra, Bimal Kumar Mishra
Avian influenza remains a significant zoonotic threat due to its rapid viral evolution, sporadic spillover into human populations, and potential to trigger large-scale outbreaks. Traditional surveillance systems often detect emerging infections only after substantial transmission has occurred, highlighting the need for predictive analytical tools capable of early outbreak detection. In this study, we investigate the transmission dynamics of avian influenza in human populations by integrating artificial intelligence–based data analysis with mathematical epidemic modeling. Historical human case data reported by the World Health Organization and the Centers for Disease Control and Prevention from 2003 to 2024 were analyzed using AI-assisted smoothing, regression-based forecasting, and scenario-based simulations to identify long-term epidemiological patterns and potential future trajectories. To provide a theoretical foundation for these empirical observations, we formulate a SEIR-type compartmental model incorporating an artificial intelligence control parameter that represents enhanced surveillance and intervention capability. Using the next-generation matrix method, the basic reproduction number is derived and analytical results are established for the stability of the disease-free equilibrium. The analysis demonstrates that improvements in AI-supported surveillance reduce the effective transmission rate and consequently decrease the reproduction number, leading to epidemic suppression when a critical threshold is exceeded. Simulation results further illustrate how enhanced surveillance and early detection can significantly alter outbreak trajectories under various epidemiological scenarios. These findings highlight the potential of integrating artificial intelligence with mathematical epidemiology to strengthen early warning systems, improve outbreak preparedness, and support One Health strategies for the control of avian influenza
Althea Faye Fernandez, Frederick A. Soreño, Fritz Leanne T. Requierme, Jamaica Dee C. Dominguez, Marjun Noah P. Polinar, Nancy S. Tajale, Saiha Mae B. Repana, Trisha Eve R. Lapuja
This study aimed to develop and evaluate the Ultrasonic Shield System, a non-chemical pest control device designed to repel rice ear bugs through ultrasonic sound exposure under controlled laboratory conditions. A research and development (R&D) design combined with a one-shot case study approach was employed to establish baseline performance prior to field deployment. The system utilized a microcontroller-based ultrasonic transducer operating at calibrated frequencies and was tested in an isolated setup to minimize environmental interference. Experimental trials were conducted by exposing rice ear bugs to programmed ultrasonic sound cycles, and pest response was measured through direct observation and video verification, focusing on behavioral disturbance and positional movement as indicators of repellency. Descriptive statistical tools were used to analyze pest reduction and consistency of system performance across trials. The findings revealed a measurable and consistent reduction in rice ear bug presence, indicating a moderate level of pest-control efficacy under controlled conditions. Ultrasonic exposure induced observable changes in pest behavior, including movement away from the sound source, demonstrating that the system was capable of influencing rice ear bug activity without the use of chemical agents. Although complete pest elimination was not achieved, the results suggest that the Ultrasonic Shield System has potential as an eco-friendly alternative to conventional chemical pesticides. The controlled testing environment strengthened internal validity by isolating the effects of ultrasonic sound, providing reliable baseline data to support further system optimization, longer testing periods, and real-field validation for sustainable rice pest management.
Dr. Swati Saxena, Unnati Saurabhkumar Gandhi
With an inclination of sustainability people are thinking towards electrifying transportation result to which peoples’ interest sustainable mobility is increasing day by day. This leads tremendous increase in buying and using electric vehicles in their day to day life. As a results potential markets of electric two wheelers are emerging. As in automobile sector in India hold significant potential in markets where two-wheelers dominate personal transportation Electric two wheeler is evidented as preferred in other countries but In India scenario is not the same. Despite strong policy support and technological advancements, adoption rates remain below expectations, indicating the need to understand the Behavioural determinants influencing consumer purchase intention. This study investigates the role of key behavioural constructs—environmental concern, attitude toward electric two-wheelers, subjective norms, perceived behavioural control, and self-identity—in predicting purchase intention, while also examining the mediating influence of demographic factors. A quantitative-Descriptive research design was adopted using data collected from 166 potential electric two-wheeler buyers across Gujarat, India. Reliability analysis demonstrated excellent internal consistency. Exploratory Factor Analysis confirmed construct validity, with five distinct factors explaining 75.98% of total variance. The findings reveal that attitude toward electric two-wheelers is the strongest predictor of purchase intention, followed by environmental concern and perceived behavioural control even though peoples’ perception starts from sustainability more environment concern comes at later stage. Subjective norms and self-identity also show significant positive influence. Demographic variables such as income and education partially strengthen specific psychological relationships, indicating segment-based differences in adoption behaviour. The study contributes to explore and define behavioural and identity based constructs to find its role in purchase intention and electric two-wheeler adoption. The findings provides actionable insight to bridge the gap through designing proper marketing strategy. Also it will be helpful to manufacturers and policy makers to quickening the transportation mobility towards sustainability.
Anagba, Joseph Obidi, Joachim Chukwuma Okafor
This article examines the January 2026 military intervention by the United States that resulted in the capture and detention of President Nicolás Maduro of Venezuela. Drawing on qualitative descriptive analysis of secondary sources and framed within realist power theory, the study interrogates how material capabilities, strategic interests, and geopolitical competition influenced U.S. decision making despite prevailing normative constraints in international law. The intervention, justified by Washington as a response to alleged narco terrorism, human rights abuses, electoral irregularities, and threats to U.S. security, also reflects deeper strategic imperatives linked to control over Venezuela’s hydrocarbon resources and the broader politics of energy security. Historically strained U.S.-Venezuela relations shaped by ideological antagonism, sanctions, diplomatic pressures, and competing alignments with external actors such as Russia, China, and Iran provide the broader context for interpreting this event. The article argues that the U.S. action demonstrates enduring hegemonic behaviour in the Western Hemisphere, where power calculations related to regional influence and access to strategic resources can take precedence over institutional legal norms. By situating the 2026 intervention within debates on great power rivalry, resource geopolitics, and the structure of global power, the study contributes to scholarship on intervention, energy politics, and the persistence of power dynamics in the contemporary international system.
Dr. K. Maheswaran
Software complexity metrics serve as quantitative indicators that help practitioners and researchers evaluate various quality attributes of software systems, including maintainability, testability, reusability, and overall design quality. Numerous researchers have developed various complexity metrics specifically designed for Object-Oriented (OO) design paradigms. Among these contributions, Cognitive Weighted Inheritance Class Complexity (CWICC) and Interface-Based Cognitive Weighted Class Complexity (ICWCC) have emerged as significant measures for assessing the cognitive burden imposed by inheritance hierarchies and interface-based architectural patterns. To establish their scientific validity and practical reliability, these metrics require comprehensive theoretical evaluation against well-established software engineering principles. This research presents a systematic and rigorous evaluation of both CWICC and ICWCC metrics with Briand's validation criteria a widely accepted theoretical frameworks for assessing the effectiveness and soundness of software complexity measurement approaches. Through this comprehensive analysis, the study aims to validate the theoretical foundations of these cognitive complexity metrics and determine their suitability for practical application in object-oriented software quality assessment.
Dr.Binayak Chandra, Jayanti Paul
The current Era is the Digital Era. The education system of this Digital Era is completely different from the traditional education system. We all know that Education is a tool that can change the entire society. An incredible achievement of science and technology is virtual Reality. An important pillar of entire education system is primary education. Currently, in the area of digital technology, Virtual Reality is an excellent aspect in primary Education. This study is a review-based study. The aim of this study is to discuss about virtual Reality in Digital Primary Education in India. And the merits and demerits of various aspects of virtual reality in digital primary education in India has been analysed. This paper shows that, Students get more opportunity to gain knowledge through virtual reality and they can visit geographically distant and inaccessible places and they become more curious about the topic.
Adrian Delos Reyes Placido, Adrian Paano, Josh Venedict Virtucio Mendoza, Kevin Roi Castro, Mhelhenrich Dela Peña, Renz Sydney Yabut
A web-based appointment and record management system titled “Web Appointment and Record System for Tub N Cup Pet Grooming Café Using First-Come, First-Served (FCFS) Scheduling” was designed and developed for Tub N Cup Pet Grooming Café, a local business that offers pet grooming services, to address inefficiencies caused by manual appointment handling, long waiting times, and disorganized customer records. The system enables pet owners to schedule grooming appointments online, maintain digital pet records, and reduce reliance on walk-in scheduling, thereby improving overall service efficiency. The platform was developed using HTML, CSS, and JavaScript for the front-end interface, PHP and Laravel for back-end processing, and MySQL for database management within a XAMPP environment. The First-Come, First-Served (FCFS) scheduling method was implemented to ensure fair and systematic appointment prioritization. The study employed a quantitative descriptive research design and followed the Agile-based System Development Life Cycle (SDLC) in developing and evaluating the system. System evaluation was conducted using the ISO/IEC 25010 software quality model, focusing on functionality, reliability, efficiency, usability, security, and portability. A total of 100 respondents, consisting of 50 user respondents and 50 technical respondents, participated in the evaluation using a structured questionnaire and a 4-point Likert scale. Results showed high levels of acceptance and satisfaction, with overall weighted mean scores of 3.5 from user respondents and 3.3 from technical respondents, both interpreted as Strongly Agree. These findings indicate that the developed system is effective, reliable, and user-friendly, and can serve as a practical digital solution for improving appointment management and customer experience in a pet grooming business environment.