40 Articles
Manga Ibrahim, Tami Bitrus Small, Yusufu Gambo
The rapid adoption of Machine Learning (ML) in educational decision-making, particularly scholarship allocation, has raised critical concerns about fairness, bias propagation, and institutional accountability. However, existing research on how bias is detected, measured, and mitigated in these systems remains fragmented across methods, domains, and evaluation practices. This study conducts a PRISMA-guided systematic review to explore machine learning-driven bias detection approaches in education and scholarship, integrating findings from Scopus, Web of Science, IEEE Xplore, and the ACM Digital Library. The synthesis examines bias variants, fairness metrics, methodological trends, and evaluation practices across selected studies. Findings show that representation and measurement bias dominate the literature, while label and deployment biases are less explored. Statistical and group fairness metrics are most commonly used, whereas causal inference and in-model fairness approaches remain underdeveloped. Major methodological limitations identified include the scarcity of high-quality datasets, inconsistent reporting practices, limited reproducibility, and inadequate evaluation of fairness across the entire model lifecycle. To address these issues, the study proposes a domain-specific taxonomy for scholarship allocation that structures fairness analysis across bias source, detection stage, method type, fairness metric, and educational context. The framework consolidates fragmented evidence and highlights research gaps in causal fairness, deployment monitoring, and longitudinal bias analysis.
Baba Mushemi Lawan, Bala Adamu Thliza, Umar Tanko Mamza, Wilson Lamayi Danbature
This study investigates the Antifungal, Antimicrobial and Larvicidal Activities Zinc oxide nanoparticles (ZnO-NPs) produced from the leaf extract of Balanites aegyptiaca. The nanoparticles were characterized using UV-Visible spectrophotometry, FTIR, XRD, and SEM techniques. Their antimicrobial activity was assessed against two Gram-positive bacteria (Staphylococcus aureus, Streptococcus pyogenes), two Gram-negative bacteria (Salmonella typhi, Klebsiella pneumoniae), and two fungi (Candida albicans, Aspergillus niger). The ZnO-NPs demonstrated strong inhibitory effects on Klebsiella pneumoniae, Streptococcus pyogenes and Salmonella typhi. Larvicidal activity against Anopheles mosquito larvae at concentrations of 40, 50, and 60 mg/L showed 100% mortality in first instar larvae, with LC₅₀ values ranging from 36.24 to 38.07 mg/L across instars. These results highlight the strong dose-dependent larvicidal and antimicrobial properties of ZnO-NPs derived from Balanites aegyptiaca leaf extract demonstrating their potential as eco-friendly nanobiopesticides and plant-based therapeutics for controlling disease vectors and pathogens.
Onamah Ojodomo Godwin, PhD
This study examines the role of artificial intelligence (AI) in reducing corruption within Nigeria's public sector, with a specific focus on the Economic and Financial Crimes Commission (EFCC) between 2021 and 2026. Corruption remains one of the most formidable obstacles to Nigeria's economic development, democratic consolidation, and institutional integrity, with billions of dollars lost annually to fraudulent practices across all levels of governance. Traditional anti-corruption methods including manual auditing, whistleblower policies, and investigative journalism have achieved limited success due to systemic weaknesses, political interference, and the increasing sophistication of financial crimes. This study argues that AI technologies offer transformative potential for enhancing corruption detection, investigation, and prevention through advanced data analytics, pattern recognition, predictive modelling, and automated transaction monitoring. Drawing on a qualitative case study design, including document analysis and expert interviews with EFCC officials, technology experts, and anti-corruption practitioners, the study assesses the deployment, effectiveness, and challenges of AI systems including the Eagle Eye platform, forensic accounting software, and machine learning algorithms for suspicious transaction detection. The study identifies significant achievements in asset tracing, financial forensics, and investigative efficiency, alongside persistent challenges including inadequate technical infrastructure, data quality issues, personnel skill gaps, legal framework weaknesses, and resistance from corrupt networks. The study acknowledges important limitations, including restricted access to EFCC operational records, the difficulty of isolating AI's specific contribution from other anti-corruption factors, and the rapidly evolving nature of AI technologies. The paper concludes with actionable recommendations for strengthening AI deployment through institutional capacity building, legal reform, regional cooperation, and sustainable funding.
Dr Priya Mariyat, Dr. Suby Baby
This study examines how AI-driven commerce shapes consumer trust, technology adoption and firm performance across six countries spanning emerging economies (India, Nigeria, Brazil) and developed economies (the United States, the United Kingdom, Germany). Three theoretical frameworks the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT2) and Trust-Risk Theory were combined within a single hierarchical structural equation model (SEM), with each framework contributing distinct constructs: TAM provided the adoption antecedents; UTAUT2 introduced contextual moderators; and Trust-Risk Theory supplied the mediating constructs of consumer trust and perceived risk. Survey data from 847 consumers and 214 firm managers, stratified by gender, age, income quartile and urban-rural status, were analysed alongside 32 semi-structured interviews with industry practitioners and regulators. Perceived usefulness, algorithmic transparency and data privacy assurance emerged as the strongest trust-building predictors across all markets, though their relative weight varied by context. Consumers in emerging markets placed comparatively greater emphasis on performance expectancy and peer endorsement, while those in developed markets prioritised algorithmic explainability and privacy controls differences traceable to cultural profiles and divergent regulatory regimes including the EU’s GDPR, Brazil’s LGPD and Nigeria’s NDPR. At the organisational level, AI adoption improved efficiency, customer retention and revenue, but only where implementation was sufficiently mature and complementary capabilities were in place.
Dr Bhaswati Mahanta, Dr Ratan Medhi, Dr Taniyang Laliyang, Dr. Neizekhotuo Brian Shunyu
Among all the cutaneous malignancy basal cell carcinoma (BCC) is the most prevalent, mainly affecting sun-exposed regions of head and neck. Nasal involvement presents significant reconstructive and cosmetic challenges because of complex anatomical as well as aesthetic prominence. Hereby, we are reporting a his to pathologically confirmed case of fibroepitheliomatous variety of basal cell carcinoma involving left nasal wall in a 70year old male presenting with a slowly enlarging ulcero -proliferative lesion associated with intermittent bleeding. Wide local excision with adequate margins followed by local flap reconstruction achieved satisfactory oncologic and cosmetic outcomes. This case highlights the importance of early diagnosis, histopathological confirmation, and appropriate surgical management in preventing local tissue destruction and recurrence.
Onamah Ojodomo Godwin, PhD
This paper critically examines the tension between bureaucratic discretion and the rule of law in Nigerian public administration, focusing on how administrative decision-making processes uphold or undermine constitutional governance principles. Bureaucratic discretion, defined as the latitude afforded to public officials to exercise judgment in applying laws and regulations to specific cases, is an inherent and necessary feature of modern public administration. No legal framework can anticipate every factual scenario, and rigid prescription would result in administrative paralysis. (Muhammad, 2024) However, discretion generates a fundamental tension with the rule-of-law principle that government action must be governed by fixed, published laws applied equally to all citizens. When discretion is exercised arbitrarily, selectively, or for improper purposes, it violates the rule of law and erodes public trust in administrative institutions. The Nigerian context reveals a persistent pattern of discretionary abuse rooted in structural factors, including weak legal constraints on administrative action, inadequate administrative justice mechanisms, political interference in bureaucratic processes, and the absence of robust judicial review for many administrative decisions. (Badamasiuy & Bello, 2022, pp. 1-10) This study identifies three critical problem areas: the use of discretion to allocate citizenship rights through indigeneship certification, selective enforcement of regulatory policies by street-level bureaucrats, and unfettered executive discretion in clemency decisions that undermine judicial finality. The paper contends that addressing these challenges requires strengthening administrative tribunal independence, codifying discretionary guidelines, establishing judicial review mechanisms for all administrative decisions, and building institutional capacity for transparent decision-making. Notably, the analysis acknowledges that structured discretion has enabled positive governance outcomes during emergencies and humanitarian crises, indicating that the objective is not elimination but the appropriate structuring of discretionary authority.
Ahmad, A., Barau, H., Bello, B. A., Isah, A., Wakkala, A., Yusuf, T., Zaki, U. F.
Industrial flue dust, an abundant byproduct of metallurgical processes, was evaluated as a low-cost CO₂ material for CO2 conversion to calcium carbonate and magnesium carbonate under ambient conditions. Batch system experiments compared CO₂ concentration profiles in a sealed chamber with and without flue dust at 25 °C and 1 atm., using a CO₂ injection rate of 20 mL per 30 s. In the absence of flue dust, CO₂ concentration rose steadily from 407–414 ppm to 1058 ppm at 900 s, reflecting passive accumulation. With flue dust present, CO₂ levels remained near ambient for up to 690 s, with measured concentrations 124–286 ppm lower than the control during 240–690 s. This corresponds to a CO₂ removal capacity of 23.5–41.4%, peaking at 41.4% before declining to 3.5% at 900 s due to reduction of calcium and magnesium oxide.
Dr. Kingsley Chinyere Uzoma, Ekereobong David Ekpo, Prof. Nnaji, Godwin Uche, Prof. Roseta Chizoba Eneje
This study evaluated the correlation between soil structural indices and soil chemical properties as influenced by rainfall patterns in selected flood-prone areas of Akwa Ibom State, Nigeria. The study was conducted in four locations representing upland and coastal environments namely, Uyo, Eket, Eastern Obolo and Ikot Ekpene. Soil samples were collected at two depths of 0-15cm and 15-30cm and analyzed for selected structural properties such as moisture content (MC), infiltration rate (IR), dispersion ratio (DR) and water stable aggregates (WSA) as well as chemical properties such as soil pH, organic carbon (OC), organic matter (OM), total nitrogen (TN), available phosphorus (Av. P), exchangeable bases, exchangeable acidity (EA), effective cation exchange capacity (ECEC) and base saturation (Bs). Correlation analysis was performed using IBM SPSS. The results showed a strong positive relationship between infiltration rate and organic carbon in Uyo (r= 0.992**), Eket (r= 0.975*), Eastern Obolo (r = 0.473) and Ikot Ekpene (r = 0.404), indicating that increased organic matter improved water movement and soil aggregation. Water stable aggregates (WSA) showed strong positive correlations with total exchangeable bases (TEB) in Uyo (r= 1.000**), Eastern Obolo (r = 0.181) and Ikot Ekpene (r= 0.942) but correlated negatively (r = -0.922) in Eket. Dispersion ratio (DR) shows a negative correlation with organic matter (OM) in Eastern Obolo (r= -0.995**) and Ikot Ekpene (r= -0.927), indicating improved aggregate stability with increased organic matter. Exchangeable acidity (EA) negatively correlated with WSA in Eastern Obolo (r= -0.907) and infiltration rate in Uyo (r= -0.993**), indicating that increasing acidity weakened soil structure under intense rainfall conditions. High rainfall intensity increased soil acidity and nutrient leaching, particularly in coastal locations. It is hereby recommended that sustainable soil management practices that enhance organic matter accumulation and nutrient retention are therefore essential for maintaining soil productivity in Akwa Ibom State.
Chukwujekwu John Okafor, Ibeonu Ogochukwu Chinyere, Udeh Chukwuma Callistus
The rapid transformation of payment system using digital platform has offered several advantages like seamless transactions, convenient, and easy to use, however it is also triggered massive digital fraud through credit card. This credit card fraud is an online crime where cyber criminals used unauthorized credit card to carryout financial transaction. To solve this problem, the aim of this paper is deep leaning based credit card fraud detection in electronic payment platforms. This was achieved with using the data of European credit card users with a sample size of 550000 records, including normal and fraudulent transaction cases. The dataset were processed and pre-processed before applying to train hybrid deep learning model of convolutional neural network (CNN) and Long Short-Term Memory (LSTM) respectively. The model was validated through comparative analysis with other individual models like LSTM, CNN. Results achieved reported accuracy over 85% for all models, while the hybrid upon comparism reported 98% accuracy as the best. The model is recommended to companies managing financial transactions to facilitate real-time detection of credit card frauds. Future works can expand this study using dataset from other part of the works, as this work is limited to detect credit card fraud in the European continents only.
Angelica M. Lita, Benedict Bryan Montances, Clariss Mae D. Selisana, Jeneathjoy D. Naturales, Mark Alexis Batis, Mark Andrew S. Naman, Rinoa Colleen Manansala, Shane Mae Z. Gulay, Vince Joshua Talavera
This study looks at the inefficiencies and redundancies in faculty attendance system and management at St. Clare College of Caloocan. Currently, the institution uses a multi-layered approach involving manual log-books, ID-tapping, and an hourly “Learning Guide" signatures which has led to divided data silos, delayed payroll processing, and difficulties resolving attendance disputes. The main objective of the study is to design and implement a web-based QR Code Attendance and Monitoring System to streamline tracking, enhance data accuracy, and improve administrative efficiency. The researchers used a Mixed Methods Research Design along with Evolutionary Prototyping Software Development. Data were gathered from 13 selected respondents consisting of St. Clare College of Caloocan’s faculty members, Attendance Monitoring Team personnel and Department Head who were directly involved in the institution's attendance monitoring processes. This approach helped the development of a 3-Tier Hybrid Client-Server Architecture, using a Local-First Primary Node via Docker for offline resilience and a Cloud Secondary Node via Supabase for remote access and backups. Key features include contactless QR code scanning, a real-time administrative dashboard, and a specialized verification module for hourly monitoring rounds. Results from the quantitative post-survey showed that the system is highly accepted among all respondent groups. Users evaluated the system positively in terms of usability, performance, and overall effectiveness. The study concludes that implementing a web-based QR code attendance system provides a reliable and scalable solution for modernizing attendance management in educational institutions, while also serving as a reference for future system development and research.
Immanuel A. Baiden, Shiphrah O. Adu
Greenhouse farming is a method of growing crops in a controlled environment that can increase the yield, quality and profitability of crops. However, this requires constant monitoring and control of various environmental factors such as temperature, humidity, soil moisture, and light intensity. Traditional methods of monitoring and control involve manual labour and are expensive, time-consuming and error-prone. To overcome these challenges, a Global System for Mobile Communication (GSM)-based smart greenhouse farming monitoring and control system capable of automatically detecting and adjusting environmental parameters using a temperature sensor, humidity sensor, soil moisture sensor, light sensor, fan, heater, water pump, and light-emitting diode (LED) light was designed. This system also used a GSM module to communicate with greenhouse caretakers via Short Message Service (SMS) messages. This system was tested and evaluated in simulation using Proteus software. The proposed system demonstrated correct threshold-based actuation across all tested scenarios, with a total estimated hardware cost of GH¢2,530.00 (approximately USD 225), which is comparably lower than IoT-based systems reported in the literature that typically require cloud subscriptions and higher-end networking hardware [2, 12]. Unlike systems that depend on continuous Internet connectivity, the GSM-based architecture operates reliably in regions with limited or unreliable network access. While a physical prototype has not yet been built, simulation results confirm the functional logic and design feasibility of the system, with real-world validation recommended as a priority for future work.
Olaniyi, C.O., Oriolowo, M., Sabejeje, T.A.
A twelve-month feeding trial was conducted with a view to determine the effects of processed African walnut seeds as feed supplement on the blood profile of African catfish. Ten isonitrogenous diets (T1-T10) of 35% crude protein were formulated to contain powdered samples of the processed seeds as test ingredient at varying inclusion levels of 0.3, 0.5 and 0.8g per 100g. One hundred and eighty juvenile African catfish were selected and divided into ten treatment groups in 50 L circular plastic bowls in a completely randomized design at stocking density of six fish per bowl in the ratio of 3males to 3 females. Each treatment group was replicated thrice. The fish were fed the experimental diet twice a day (morning 8.00hr and evening 17.00hr) for twelve months. At the end of the feeding trial, blood samples of the fish were collected for hematological analysis. Result showed that WBCs, MCV, MCH, MCHC, LYM, BASO and Monophils were not significantly (p<0.05) affected by the dietary treatments of the test ingredient while PCV, Hb, RBCs and Eosinophils were significantly (p>0.05) affected. PCV, Hb, RBC, BASO and PLT recorded their highest value 41.67, 14.07, 4.77, 2.67 and 268.0 respectively in fish fed diet containing SAD seed powder at 0.8g level of inclusion which suggests the suitability of SAD dietary meal of T.conophorum seed powder at higher inclusion level for production of normal and adequate haematological parameters, compared to other processed samples. This implies that the experimental fish, especially those fed SAD diet at higher inclusion level (0.8g) were considered hematologically stable and devoid of toxic factors, thus portraying SAD African walnut seed powder at higher levels of inclusion as the most suitable feed supplement that can yield the desired levels of hematological parameters in the African catfish.
Aminat Muhammed Ali, Itseghosimhe Iyesomi Scholastica, Okhaise Roseline Avedaoya, Onoriode Benjamin Akpobasa
Menopause represents a milestone in women's lives that result from the depletion of ovarian functions. It is a significant physiological transition associated with multiple physical, psychological, and social changes that may affect women’s quality of life This study examined the efficacy of midwife-led health education on knowledge of menopause, coping strategies, and the quality of life of menopausal women in Egor Local Government Area of Edo State. The study adopted a cross-sectional research survey design. A researcher-designed questionnaire was used to collect data among187 menopausal women in the Egor Local Government area of Edo state. The findings of the study showed that 148(79%) were quite knowledgeable of menopause. 165(88.2%) and 121(64.7%) perceived that Midwife-led health education improves their understanding of menopause and quality of life respectively while 129 (69%) perceived that midwife-led health education has a positive effect on their coping strategies. Conclusion: there is a perceived positive effect of midwife-led health education on coping strategies, knowledge of menopause, and quality of life among menopausal women in the studied population. Therefore, there is a need for policymakers for health institutions to develop a periodic training programme for menopausal women on coping strategies
Adebayo, O.T, Gbadamosi O.K, Ojebuola, T.O, Oladipupo T.M, Olanipekun O.O
This study evaluated the effectiveness of lignan extracted from watermelon (Citrullus lanatus) seeds as a hormonal diluent during the artificial propagation of C. gariepinus. A completely randomised design consisting of five treatments was employed: 0% (control), 25%, 50%, 75%, and 100% lignan inclusion levels, each replicated three times. Reproductive performance indices, hormone residue levels, and water quality parameters were assessed. Results showed that lignan significantly influenced reproductive performance (P<0.05). The highest fertilisation rate (92.78%), hatchability (66.42%), and larval survival (52.53%) were obtained at 25% lignan inclusion, compared with 78.52%, 43.57%, and 37.72%, respectively, in the control group. Fecundity and relative fecundity were highest at 75% inclusion, while complete reproductive inhibition was observed at 100% lignan concentration. Hormone residue analysis at 24 and 48 hours revealed no significant differences (P>0.05) among treatments, indicating that lignan did not interfere with hormone metabolism or clearance. Water quality parameters remained within acceptable ranges and were not significantly affected by lignan inclusion. Third-order polynomial regression analysis identified approximately 35% lignan inclusion as the optimum concentration for hatchability enhancement, with a strong model fit (R² = 0.9596). The study demonstrates that lignan possesses reproductive-enhancing properties and can effectively function as a hormonal diluent during artificial propagation of C. gariepinus. Therefore, lignan represents a safe, environmentally friendly, and cost-effective alternative for improving hatchery performance and promoting sustainable aquaculture production.
Dr. Rajinder Kumar, Er. Sukhwinder Kaur, Piyush
The rapid growth of digital misinformation has created an urgent need for computational tools that can identify misleading news content at scale. This paper presents a comparative study of three supervised machine-learning classifiers, Multinomial Naive Bayes, Logistic Regression, and Linear Support Vector Machine (LinearSVC), for binary fake-news classification using TF-IDF text features. The experimental analysis reports values available from the single-split benchmark and dataset description. The cleaned dataset contains 44,898 articles, including 23,481 fake-news articles and 21,417 real-news articles. In the reported 80:20 split, LinearSVC achieves the strongest performance with 99.3% accuracy and approximately 0.99 precision, recall, and F1-score, followed by Logistic Regression at 98.7% accuracy and Multinomial Naive Bayes at 88.5% accuracy. Because very high accuracy on a single dataset may be influenced by dataset-specific lexical or source patterns, the paper discusses reproducibility, explainability, dataset bias, and future external validation requirements before real-world deployment.
Philomena Aku OJOMO
The dominant framework for addressing environmental injustice in the Global South is the concept of climate debt. This framework focuses on historical carbon emissions. It proposes remedies through climate finance, technology transfer, and market-based mechanisms. However, it does not adequately capture the broader ecological destruction experienced in regions such as the Niger Delta. This paper argues that the crisis should be understood as an ecological debt crisis, rather than merely a climate debt problem. The study adopts an Earth-Eco-Socialist theoretical framework and uses the Niger Delta as a case study. It employs qualitative and critical analysis of literature on capitalist exploitation, ecological degradation, environmental justice, and sustainability. The paper examines how oil extraction, gas flaring, pollution, and community dispossession reflect deeper patterns of ecological exploitation affecting both humans and nonhuman nature. The findings show that climate debt discourse is limited. It reduces environmental harm to carbon accounting and promotes market-based solutions that fail to address the root causes of ecological degradation. In contrast, ecological debt captures the impacts of extraction, biodiversity loss, ecosystem destruction, and livelihood displacement. The Niger Delta demonstrates how capitalist accumulation generates long-term ecological and social harm that cannot be resolved through financial compensation alone. The paper concludes that Earth-Eco-Socialism provides a more comprehensive framework for environmental justice and sustainability. Moving from climate debt to ecological debt supports more transformative and reparative responses to ecological crises in the Global South.
Kimah Comfort Sjinkwe, PhD, Shey Fonjoh Ivo, PhD
The escalating confrontation involving the United States, Israel, and Iran has evolved from a regional security crisis into a global geopolitical and economic disruption. The central problem addressed in this article is the rapid transformation of localized military escalation into a complex, multi-level conflict with global consequences, including energy insecurity, proxy warfare proliferation, and economic instability. This study adopts a qualitative research design combining process tracing and thematic content analysis to examine how escalation dynamics have unfolded since January 2026. Data are drawn from policy reports, official statements, security analyses, and recent conflict developments. The study employs an integrated analytical model that links conflict escalation dynamics, deterrence failure, and proxy warfare mechanisms to explain how interactions among state and non-state actors contribute to conflict expansion. The findings reveal that iterative retaliation cycles, strategic misalignment among key actors, and the growing role of proxy forces have reinforced both horizontal and vertical escalation. Furthermore, disruptions to critical energy routes, particularly around the Strait of Hormuz, have amplified global economic vulnerability, transforming a regional confrontation into an international crisis. The analysis also considers alternative interpretations, including the possibility that escalation is driven by strategic signaling and domestic political calculations rather than solely by deterrence failure. The study concludes that the absence of credible diplomatic mechanisms and the entrenchment of hard-line strategic positions significantly hinder de-escalation efforts. Without structured intervention, the conflict risks becoming a protracted and systemic global crisis. The article recommends multi-level de-escalation strategies, including third-party mediation, confidence-building measures, backchannel diplomacy, and the gradual reintroduction of cooperative regional security frameworks.
Dr H S Nagalakshmi, Dr Prakasha Raje Urs, Dr Santhosh Kumar B N
Offline signature verification remains a critical yet challenging task in biometrics and forensic document analysis due to the complete lack of dynamic behavioral trajectories such as velocity, acceleration, and pen pressure. This paper presents a comprehensive study on the architectural paradigm that fuses conventional handcrafted feature-extraction techsniques with modern deep learning representation learning models. While conventional techniques like Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) robustly preserve exact geometric proportions and micro-textures, deep learning models like Convolutional Neural Networks (CNNs) capture highly complex, abstract structural representations. We systematically explore early feature-level fusion, late decision-level fusion, and hybrid metric learning pipelines. Our critical evaluation across benchmarks demonstrates that hybrid models dramatically mitigate the threat of skilled forgeries and generalize exceptionally well under constrained reference environments with limited training templates.
Muojiama, S.O., Obasi C. C., Obidiebube, E. A., Okolie, H., Ubah Blessing Amanda
Organic manure is crucial for enhancing soil fertility and promoting plant growth, particularly in nutrient-deficient soils. This study was conducted at the Teaching and Research Farm of the Crop Science and Horticulture Department, Nnamdi Azikiwe University, Ifite-Ogwari Campus, Anambra State, to evaluate the effects of different types and rates of organic manure on the growth and yield of Bambara groundnut (Vigna subterranea). The experiment employed a completely randomized design (CRD) with treatments consisting of various manure applications: pig manure (PM) at rates of 5t/h, 10t/h, and 15t/h, cow manure (CM) at equivalent rates, and a control (no manure applied), replicated three times. Results revealed that pig manure at 10t/h significantly enhanced the leaf area and branches per plant, with means of 269.0 (cm²) and 89.7 respectively recorded at 12 weeks after sowing (WAS). Furthermore, cow manure at 15t/h showed comparable effects, particularly on leaf area and stem girth, indicating its potential for improving growth metrics. The interaction of pig and cow manure also positively influenced all growth parameters measured at 12 WAS, with notable increases in leaf area (254.9 cm²) and plant height (27.8 cm). Overall, pig manure demonstrated superior efficacy in boosting pod and seed yields, with recorded values of 510 g/plant and 195 g/plant respectively at the highest application rate. The findings suggest that integrating organic manure, particularly pig manure, is effective for optimizing growth and yield in Bambara groundnut cultivation, thereby promoting sustainable agricultural practices in similar agro-ecological zones.
Erlix Rakhmad Purnama, Firas Khaleyla, Nur Kuswanti, Nur Qomariyah
Type 1 diabetes mellitus (T1DM) is characterized by high level of blood sugar, or hyperglycemia. The hyperglycemia condition in T1DM patients results in complication that made patients have higher chance to be infected with various infectious disease. Phyllantus acidus is a local plant usually consumed for its fruit, but other parts of the plant still saw lack of use locally. This study was aimed to examine the potential of Phyllantus acidus leaf extract to be immunomodulator in T1DM-induced animal model. Leaves of P. acidus was extracted using maceration and its content was analyzed using LC-HRMS. T1DM was induced in mice models using alloxan. P. acidus leaf extract was given for 10 days and in the 11th day, mice were injected with Staphylococcus aureus to induce macrophage activity. Phagocytic activity of peritoneal macrophages was evaluated from Giemsa-stained smear, while spleen was prepared into 4 µm histological section using paraffin method and stained with hematoxylin-eosin, then examined of its structure. Results showed that phagocytic activity increased significantly in mice treated with extract compared to negative control, however extract did not significantly improve spleen structure in T1DM mice compared to normal control. The secondary metabolites identified in extract including sorbic acid, L (-)-Pipecolinic acid, and Υ-Aminobutyric acid (GABA). Metabolites contained in the extract possibly affects the innate response of the mice models, however the short period of treatment resulted in insignificant effect to adaptive immunity. Thus, it can be concluded that P. acidus leaf extract was able to increase innate immune response in T1DM mice models, however further study is needed to examine longer period of treatment.
Abiere Denise PEREKPO, Amona Adah AKPA, Benjoshua Pantuvo DANGANA, Ezekiel HASSAN, Mathias SANNI, Ojomachenwu Christiana AKPA, Tyson Owoicho ONUH
The growth and penetration of financial technology (FinTech) are instrumental to achieving universal financial inclusion and integrating the unbanked population into the financial system. However, this development has intensified competition between traditional and agency banks, thereby posing a threat to commercial banks' performance. This context has motivated several studies examining the impact of FinTech on commercial banks' performance, although notable econometric shortcomings persist in the literature. Against this backdrop, this study employs robust analytical techniques underutilized in prior research. An ex-post facto research design was adopted, using annual time series data spanning from 2012 to 2025. The variables considered include Return on Assets (ROA) as the regressand, while Automated Teller Machines (ATM), Point of Sale (POS), and Mobile Banking (MB) serve as regressors. To determine the appropriate estimation technique, a unit root test was conducted, revealing a mixed order of integration at I(0) and I(1), while the F-bound test confirmed the existence of a cointegrating relationship in the model. Given this mixed order of integration, the Auto Regressive Distributed Lag (ARDL) model was employed, but the established cointegrating relationship suggests a more suitable technique (the Error Correction Mechanism [ECM]) to address disequilibrium in the model. The ECM results indicate that ATM and MB have a significant positive impact on commercial banks' performance in the short run, while POS has a positive but statistically insignificant impact during the period under review. In the long run, however, only MB maintains a significant positive impact, whereas ATM and POS exhibit a negative but insignificant impact on commercial banks’ performance in Nigeria. These findings suggest that although FinTech contributes positively to commercial banks' performance in the short run, the increasing convenience and operational flexibility of agency banking may drive greater adoption among Nigerians in the long run, potentially crowding out traditional banking channels. This backdrop is reflected in the negative performance of ATMs and POS in the long-run. In light of these findings, this study recommends that commercial banks develop innovations that will facilitate the adoption of APIs or open banking to enable service and data sharing through Application Programming Interface, thereby stimulating third-party collaborations and improving performance of commercial bank in Nigeria.
Genelyn R. Baluyos, Georgette Kyle A. Soco, Lydante Denopol
Mathematics plays a vital role in developing students' logical reasoning and problem-solving abilities, particularly in foundational areas like algebra. However, many learners continue to struggle with algebraic concepts, resulting in poor performance and decreased motivation. This classroom-based action research investigated the impact of using Bingo games as a learning intervention to enhance algebraic skills among Grade 7 students at a public secondary school in Ozamiz City during the academic year 2024–2025. The study involved 32 students selected through purposive sampling. A researcher-made pretest and post-test were administered to measure improvement, and the data were analyzed using means, standard deviations, and a paired t-test. Results revealed a significant increase in students' algebraic performance after integrating the Bingo game, with overall performance shifting from "Did Not Meet Expectations" to "Outstanding." The findings indicate that game-based learning strategies, such as Bingo, can significantly improve students' understanding of algebraic concepts, boost engagement, and foster a more positive attitude toward mathematics. The study highlights the importance of incorporating interactive and student-centered approaches in mathematics instruction to address learning gaps and support academic success. It is recommended that teachers regularly incorporate Bingo and similar game-based activities in their lessons to sustain student motivation and enhance algebraic skills.
J. Muzanima, Leigh-Ann T Nehoya, S. K Kalundu
This paper examines cattle marketing behaviour and supply chain performance in Namibia’s Northern Communal Areas, focusing on the Oshikoto and Zambezi regions. Although the NCAs hold a substantial share of the national cattle herd, formal market offtake remains low, limiting rural incomes, value addition, and abattoir utilisation. Using survey data from 116 communal cattle farmers, the study applies descriptive statistics, Principal Component Analysis, cluster analysis, and Random Forest modelling to identify marketing channels, assess drivers of channel choice, and map key supply chain bottlenecks. The findings show that farmers rely strongly on informal marketing channels, particularly in Zambezi, where poor transport infrastructure, high logistics costs, seasonal road challenges, animal health risks, and limited price information constrain formal market participation. The Oshikoto region shows comparatively higher engagement with auctions and abattoirs, reflecting better infrastructure and market access conditions. Transportation cost per head emerges as the strongest determinant of marketing channel choice, followed by herd dynamics, price uncertainty, cattle age, disease outbreaks, and access to market information. Cluster results further reveal that communal cattle farmers face different combinations of constraints, indicating that the NCAs should not be treated as a homogeneous production system. The study concludes that improving formal offtake requires reducing transport and transaction costs, strengthening price information systems, improving veterinary and production support, simplifying formal market procedures, and designing region-specific interventions instead of using an umbrella approach. These measures are essential for improving supply chain efficiency, increasing abattoir utilisation, supporting rural livelihoods, strengthening producer participation, and promoting more inclusive cattle commercialisation in Namibia’s communal areas.
Dr. (Ms.) Phebe Kingsley, Ms. Sakshi Sunil Jadhav
Voltammetric determination of L-Proline (L-Pro) using Cyclic voltammetry and Differential pulse voltammetry were recorded at glassy carbon electrode within the potential window 0.0 V and 2.4 V at the physiological pH. The reference and counter electrode used were Ag/AgCl and Pt wire, respectively.The effect of supporting electrolyte and concentration of electro active species on the interaction were also studied.The results demonstrate that the catalytic oxidation of L-Pro is diffusion-controlled and irreversible Under optimized conditions, the calibration curve for L-Pro concentration was linear in 〖3.5×10 〗^(-8) M to 〖1.5×10 〗^(-3) M with a low Limit of Quantification of 〖9.79×10 〗^(-9) M and a Limit of detection of 〖3.23×10 〗^(-8) M. It is shown that the prepared sensor provides a sensitive and rapid strategy for the detection of L-Proline.
Karim Salim
This study examines the impact of key macroeconomic indicators—namely oil prices and exchange rate—on stock market returns in Morocco. Using monthly data over the period 2002–2022, the analysis applies both Ordinary Least Squares (OLS) and Autoregressive Distributed Lag (ARDL) models to investigate the short-run and long-run relationships between these variables and MASI returns. The empirical results indicate that oil prices and exchange rate exert a statistically significant and negative effect on stock market returns in the OLS framework. However, the ARDL model provides deeper insights by capturing dynamic relationships. The findings reveal that oil prices have a delayed negative impact on stock returns, while the exchange rate exhibits a significant and immediate negative effect. The ARDL bounds test confirms the existence of a long-run equilibrium relationship among the variables, suggesting that stock returns, oil prices, and exchange rate move together over time. Furthermore, the Error Correction Model (ECM) results indicate a strong adjustment mechanism, with deviations from long-run equilibrium corrected rapidly. Overall, the study highlights the importance of macroeconomic indicators as useful tools for understanding and forecasting stock market performance in Morocco. The findings provide valuable implications for policymakers and investors in managing market risks and improving decision-making.
Akpolile A. F., Akpolile D. Franklin, Eki C. E., Ishaya Habila, Stephen D. Pam
Background: Mammography is the most effective imaging modality for early detection of breast cancer, but it involves ionizing radiation exposure to radiosensitive breast tissue. The mean glandular dose (MGD) is the most appropriate metric for assessing radiation risk in mammography. Objective: This study aimed to evaluate patient-specific MGD values from craniocaudal (CC) and mediolateral oblique (MLO) views in selected radiological facilities in Jos Plateau State, Nigeria, and compare them with international safety standards. Methods: Twenty female patients underwent mammography examinations in two facilities (M1 and M2). Compressed breast thickness (CBT), exposure parameters, and incident air kerma were recorded. MGD was calculated using the Dance model with appropriate conversion coefficients. Results: At M1, CBT ranged from 21.0-44.2 mm (mean 29.7 mm) with a mean MGD of 1.14 mGy. At M2, CBT ranged from 21.2-43.4 mm (mean 32.5 mm) with a mean MGD of 1.09 mGy. Both values were below the International Atomic Energy Agency (IAEA) reference level of 1.5 mGy for a 32 mm breast thickness. Conclusion: The evaluated facilities operate within international safety standards, with patient doses comparable to global benchmarks. This study provides the first patient-based MGD assessment in Jos Plateau State and highlights the importance of continuous dose monitoring to optimize mammography practice in Nigeria.
Anshika, Dr. Lakshaya Malhotra, Pooja Gupta
Obsessive-Compulsive Disorder (OCD) is a chronic psychiatric condition marked by intrusive thoughts and repetitive behaviors that impair daily functioning and quality of life. Although Cognitive Behavioral Therapy (CBT), particularly Exposure and Response Prevention (ERP), is considered the gold standard treatment, many patients struggle with adherence due to the distress associated with exposure tasks, leading to high dropout rates. This highlights the need for alternative interventions that are effective and better tolerated. The objective of this study was to evaluate the effectiveness of Mindfulness-Based Cognitive Behavioral Therapy (MBCBT) in reducing OCD symptom severity and its comorbid manifestations of anxiety and depression, while also enhancing mindfulness skills. A pretest-posttest design was employed with 12 clinically diagnosed OCD patients (6 males, 6 females) who participated in 12 weeks of structured MBCBT sessions. The intervention combined mindfulness practices, cognitive restructuring and behavioral experiments. Outcomes were measured using Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Beck Depression Inventory (BDI), Hamilton Anxiety Rating Scale (HAM-A), Five Facet Mindfulness Questionnaire (FFMQ), and Trait Mindfulness Scale (TMS). The results showed significant symptom reduction across domains: Y-BOCS scores decreased by 35%, BDI by 30%, and HAM-A by 28%. Mindfulness skills improved substantially, with FFMQ median scores rising from 55.5 to 128.0 and TMS from 13.0 to 42.0 (p < .01). These findings indicate both short-term clinical benefits and the development of stable mindfulness traits. In conclusion, MBCBT demonstrated promising efficacy in reducing OCD symptoms, alleviating anxiety and depression, and fostering long-term mindfulness skills. Larger and more diverse studies are recommended to validate and extend these results.
Ayinde Yusuf Olarewaju, Hassan Fatai Adesina, Ilo Hammed Owolabi
This study examined the dynamic interdependence between agricultural sub-sectors and economic growth in Nigeria using annual time-series data from 1993 to 2023. The study aimed at investigating the long-run and short-run relationship among Gross Domestic Product (GDP), crop production, livestock, and fishing within the Johansen Vector Error Correction Model (VECM) framework. Forestry was excluded from the multivariate analysis due to its integration of order two, I(2), which violates standard cointegration assumptions. The Augmented Dickey-Fuller (ADF) unit root test revealed that GDP, crop production, livestock, and fishing were integrated of order one, I(1). The Johansen cointegration test confirmed the existence of long-run equilibrium relationships among the variables. The estimated long-run co-efficients showed that livestock and fishing exert significant positive effects on economic growth, with livestock having the strongest growth elasticity. The finding revealed that crop production primarily functions as an intra-sectoral stabilizer rather than a direct long-run driver of GDP growth. The adjustment dynamics indicated that GDP significantly corrects short-run disequilibrium in the macroeconomic system, while crop production adjusts deviations within the agricultural sector. Diagnostic tests confirmed the stability, normality, and overall adequacy of the estimated model. In addition, the robustness of the results was validated using an Error Correction Model (ECM) with Newey-West HAC standard errors. The study concluded that agricultural sub-sectors exert heterogeneous effects on Nigeria’s economic growth and therefore should not be treated as a single aggregate sector in policy formulation. Based on this, some recommendations were suggested, agricultural policies focusing on livestock value-chain development, sustainable fisheries management, and improved crop productivity to enhance economic growth, food security, and sustainable development in Nigeria.
Dr. Jon-Jon T. Martinez, Karen P. Salanguste
This study examined the relationship among workload, overtime hours, work–life balance, occupational strain, and perceived quality of care among dialysis nurses in Samar Island. Anchored on the Job Demand–Resources (JD-R) Model, the study aimed to determine the demographic profile of the respondents, assess the levels of the major study variables, examine significant relationships among selected variables, identify predictors of occupational strain, and determine whether occupational strain significantly predicted perceived quality of care. A quantitative, non-experimental, cross-sectional correlational research design was employed. Data were gathered from 75 dialysis nurses working in dialysis hospitals, centers, and clinics in Samar Island using a structured self-developed questionnaire. Descriptive statistics such as frequency, percentage, mean, and standard deviation were used to describe the respondents’ profile and the levels of the variables. Pearson product-moment correlation and regression analysis were utilized to determine significant relationships and predictive influence among variables. The findings revealed that the respondents were predominantly 31–40 years old, female, married, had 2 to 5 years of dialysis experience, held a Bachelor of Science in Nursing degree, were regular employees, and were assigned in hospital-based dialysis units. The respondents generally agreed that they experienced workload, overtime hours, occupational strain, and perceived quality of care, while work–life balance was rated moderate. Significant positive relationships were found between workload and occupational strain, and between overtime hours and occupational strain. In contrast, work–life balance showed a significant negative relationship with occupational strain, indicating that better balance was associated with lower levels of strain. Regression analysis further revealed that workload, overtime hours, and work–life balance significantly predicted occupational strain, with work–life balance emerging as the strongest predictor. Occupational strain also significantly predicted perceived quality of care, suggesting that higher levels of strain were associated with lower perceived care quality among dialysis nurses. Based on the findings, an Occupational Strain Reduction and Care Quality Enhancement Program was proposed to support nurse well-being and improve care delivery. The study concluded that dialysis nurses in Samar Island work under demanding conditions, and that strengthening work–life balance while reducing excessive workload and overtime may help lessen occupational strain and support quality nursing care.
Abu Kawsar Asif, Hafizur Rahman, Md. Anwar Hossain
The production of eco-friendly fatty acid ethyl esters (FAEEs) has gained significant interest as a cleaner energy pathway that can reduce the environmental pollution associated with conventional fossil fuel. In this context, the present study aims to investigate an optimized approach for improved biodiesel production from a blended feedstock of used cooking oil (UCO) and soybean oil via ethanol-based transesterification. The utilization of UCO provides an effective pathway for waste valorization and cost reduction, while soybean oil contributes to improved reaction stability. Ethanol was utilized as a renewable, bio-sourced solvent to ensure a greener production process, generating improved biodiesel (FAEEs) with superior fuel properties such as higher cetane numbers, elevated flash points (safer handling), enhanced lubricity and better cold flow behavior. Two homogeneous catalysts, sodium hydroxide (NaOH) and sodium methoxide (CH3ONa) were employed to evaluate their catalytic performance. The transesterification process was systematically optimized by varying key reaction parameters. The highest FAEEs yield (90.34 %) was achieved at an ethanol to oil molar ratio (12:1), catalyst loading (0.75 wt%), reaction temperature (50 ℃) and reaction time (50 min) and stirring speed 400 rpm using CH3ONa catalyst. Overall, this study is expected to demonstrate an efficiency and sustainable pathway for improved biodiesel production using a combined waste and edible oil system.
Michael Appiah Frimpong, Theophilus Asiedu Nketiah
Perinatal mental health disorders, including depression and anxiety during pregnancy and postpartum, are a significant global issue of public health concern. Many of these women are not getting adequate care due to hindrances like stigma, lack of mental health care, and service integration of maternal healthcare systems. Peer support has become a potential approach that uses common lived experience to offer emotional and practical support to mothers in the perinatal period. This narrative review identifies and synthesizes the current evidence on peer support interventions in perinatal mental health, on intervention models, implementation strategies, and women lived experiences of participating. Empirical studies, systematic reviews, and qualitative research published in recent years on the topic of peer support programs to pregnant and postpartum women were reviewed. The evidence shows that peer support interventions provided in one-on-one mentoring programs, group-based programs, digital platforms, and peer-counselor models can be used to increase emotional support, social isolation, and coping among women facing perinatal mental health challenges. Qualitative research highlights that shared lived experience promotes trust, emotional validation, and normalization of maternal mental health struggles. However, variations in program design, implementation strategies, and evaluation approaches are common across studies. Peer support provides a low-cost and scalable intervention that can be used to augment current maternal mental health services. The way forward in the future would be to focus on standardized reporting, long-term outcomes assessment, and cultural responsiveness of the implementation to provide equal access and sustainability of the integration of peer support into the perinatal healthcare systems.
Jheffany Yazid, Norliza Arifin, Salmiah Awang, Siti Salmah Mohd Zaid, Tan Yok Mui
Student-centred learning (SCL) plays a critical role in contemporary nursing education. Accurate assessment of SCL implementation requires instruments that are linguistically clear and psychometrically sound within the local context. A preliminary evaluation is essential before the large-scale deployment of adapted tools. This pilot study aimed to examine the content validity, feasibility, and internal consistency reliability of three Malay-adapted instruments measuring SCL application, instructors’ perceptions, and perceived barriers among nurse educators. A cross-sectional pilot study was conducted among 16 nurse educators recruited through random outreach across nursing education settings in Malaysia. The instruments underwent forward translation, followed by expert review involving two subject-matter experts and one language expert. Content validity was assessed using the Content Validity Index (CVI). Internal consistency reliability was evaluated using Cronbach’s alpha. The instrument set achieved a CVI of 1.0, indicating full expert agreement on item relevance and clarity. Reliability analysis demonstrated moderate internal consistency for the refined Application of SCL Scale (α = 0.618), moderate consistency for the Perceptions Scale (α = 0.609), and good internal consistency for the Barriers Scale (α = 0.839). No missing data were recorded. The questionnaire was considered feasible, with an acceptable completion time and minimal wording adjustments. The Malay-adapted SCL instruments demonstrated acceptable preliminary reliability and strong content validity. These findings support their use in a subsequent full-scale study for further psychometric evaluation.
Assoc. Prof. Moses Agaba, Dr. JohnBosco Turyasingura, Jackson Tuhirirwe
Small and Medium Enterprises (SMEs) play a critical role in employment generation, poverty reduction, and local economic development in Uganda. However, many SMEs continue to experience limited access to affordable finance, weak managerial capability, operational instability, and low enterprise sustainability. Savings and Credit Cooperative Organizations (SACCOs) have increasingly emerged as important financial institutions supporting SMEs through savings mobilization, financial literacy programs, and credit extension services. This study examined the influence of SACCO practices on multidimensional SME performance in Kabale District, Uganda. The study adopted a convergent parallel mixed-methods research design integrating quantitative and qualitative approaches. Quantitative data were collected from 336 SME operators using structured questionnaires and analyzed using descriptive statistics, Pearson correlation analysis, multiple regression analysis, and Structural Equation Modeling (SEM). Qualitative data were obtained through interviews with SME owners and SACCO stakeholders and analyzed thematically. The study was guided by Human Capital Theory and Financial Intermediation Theory. The findings revealed that credit extension had the strongest positive and statistically significant effect on SME performance (β = 0.115, p < 0.001; r = 0.567, p < 0.01). Saving mobilization demonstrated a positive relationship with SME performance (r = 0.481, p < 0.01), although regression analysis revealed a significant negative coefficient (β = –0.077, p < 0.001), suggesting temporary liquidity constraints among SMEs with limited working capital. Financial literacy demonstrated a moderate positive relationship with SME performance (r = 0.507, p < 0.01), although its direct regression effect remained statistically insignificant (β = –0.032, p = 0.093). The study concludes that SACCO practices significantly influence multidimensional SME performance through integrated financial and entrepreneurial support mechanisms. It recommends strengthening flexible SACCO lending systems, practical financial literacy programs, and enterprise-responsive saving policies to improve SME sustainability and local economic development in Uganda.
B. Jhansi Kala, B. Sudhakiran, B. Varshitha
Root health plays a vital role in overall plant growth, crop yield, and sustainable agriculture. Early detection of root stress, diseases, and soil-related abnormalities is essential to prevent yield loss and ensure efficient resource utilization. Traditional root monitoring methods are invasive, labor-intensive, and often fail to provide real-time insights into underground conditions. This project proposes a Smart Root Health Monitoring System using low-frequency soil electromagnetic (EM) signals to non-invasively assess root zone conditions. The system employs embedded sensors and signal generation modules to transmit low-frequency EM waves through the soil. Variations in signal response are analyzed to detect changes in soil moisture, root density, root damage, and possible disease presence. Signal preprocessing, noise filtering, feature extraction, and machine learning techniques are applied to interpret soil-root interaction patterns and classify root health status. The proposed model enables continuous, real-time monitoring with minimal soil disturbance. It improves detection accuracy, reduces manual inspection effort, and provides a cost-effective solution for precision agriculture. This system can be integrated with IoT platforms for remote monitoring, data visualization, and smart irrigation management.
Jitendra Binwal, Krishnapal Singh Sisodia, Priyanka
This paper presents an analytical study of four central tendency measures Arithmetic Mean (AM), Geometric Mean (GM), Harmonic Mean (HM), and Median within the framework of fuzzy graph theory, incorporating triangular, trapezoidal, and Gaussian membership functions. Formal definitions and key theorems, including the chain inequality FHM ≤ FGM ≤ FAM, are established with rigorous proofs. A Monte Carlo simulation framework (500 iterations per configuration) is developed to evaluate the statistical behaviour of these measures under varying fuzziness parameters. Results demonstrate that the Harmonic Mean exhibits superior noise-resistance in sparse graphs, the Arithmetic Mean provides the most efficient approximation in dense networks, and the Median is the most robust against membership outliers. The framework is validated through interdisciplinary applications in network reliability, bioinformatics, traffic optimization, epidemiology, and financial portfolio analysis. These findings offer new theoretical insights and practical tools for researchers across mathematics, computer science, and engineering.
Dr. Mrinmayee Kale, Dr. Shashank Maktedar, Mr. Mayank Bedekar
The study explores tabla pedagogy as more than technical drumming, framing it as a holistic knowledge system that blends oral tradition, acoustical science, lineage, and aesthetic philosophy. Central to this approach is the bol system, which uses mnemonic syllables to guide stroke execution while preserving stylistic heritage. Observations reveal that rhythmic clarity begins with spoken recitation, highlighting oral practice as a cognitive foundation before instrumental mastery. The methodology integrates ethnomusicology, acoustical analysis of the syahi, and computational spectrograms to show how oral pedagogy supports motor learning and adapts within institutional settings. Findings emphasise tabla’s dual role as a musical and cultural system, sustained through embodied practice, oral transmission, and philosophical aesthetics while engaging with global and technological contexts. Ultimately, the research underscores the importance of bridging traditional guru–shishya apprenticeship with modern classrooms, suggesting computational tools can enrich but not replace the embodied knowledge at the heart of tabla education.
Dr. Aluko Kehinde Olugbenga
The study investigated the extent to which secondary school Mathematics teachers use teaching skills in teaching Mathematics contents to improve students’ achievement in Osun State public secondary schools. It also examined the relationship between the use of required skills by secondary school teachers (experienced and non-experienced) and students’ achievement in mathematics. These were with a view to improving students’ academic performance in the schools. The study adopted survey research design. The population of the study comprised all the 4,856 secondary school teachers in the 387 public secondary schools in the State. The sample of the study consisted of 1,100 teachers. The selection of the teachers was based on proportionate stratified random sampling technique in the three education zones in Osun State. The instrument for data collection was titled “Teacher’s Required Teaching Skills Questionnaire” (TRTSQ). The instrument was validated by group of experts and the reliability coefficient of 0.82 was obtained using Cronbach alpha technique. Data collected was analysed using mean score and standard deviation to answer the research question while Pearson-correlation was used to test the hypothesis at 0.05 level of significance. One research question and one null hypothesis were raised and formulated respectively to guide the study. The results showed that secondary school teachers do not employ teaching skills in teaching mathematics content. The result also showed that there is no significant relationship between the extent of use of skills by secondary school teachers (experienced and non-experienced) and students’ achievement in mathematics (r-cal =1.29, r-crit = 3.85, P =0.47). The study concluded that secondary school education is an important stage of educational development in Nigeria and despite the importance of mathematics education to national development, the study of the subject in our schools in Nigeria is bedevilled with poor performance. The study therefore recommended government should continue to re-train the primary school teachers in their capacity building workshops especially in mathematics and sciences with a view to improving their level of competence in all areas of mathematics teaching in secondary schools across the state.
Alvin Morales, Angel Grace C. Sarmiento, Christian Dave B. Sy, Francis Adrian R. Colobong, James Ed L. Pepito, Jeaneth Joy D. Naturales, Jeremy DC. Cervantes, Mark Philip M. Acebes, Sydbert D. Paltingca
The physical storage of hardbound theses presents significant limitations in accessibility, search efficiency, and long-term preservation. This study developed ThesisVault, a web-based smart repository system designed to preserve and improve access to academic research for the Bachelor of Science in Computer Science program at St. Clare College of Caloocan. The system incorporates digital preservation, full-text search and filtering, metadata management, role-based access control (Guest, Student, Moderator, Superadmin), and advanced features including a Plagiarism Checker, Related Studies search, and a bilingual English-Tagalog AI Chatbot. Using a quantitative research approach and Agile methodology, pre-development surveys were administered to 300 students and 6 faculty members to identify challenges and feature preferences, followed by post-development evaluation with hands-on testing. Results showed that students faced significant difficulties with manual searches (WM=3.94) and topic verification (WM=3.88), while faculty cited the lack of a centralized database (WM=4.33) and inefficient retrieval processes (WM=4.33) as primary concerns. Post-development evaluation revealed substantial improvements, with students rating the system at 4.83 (Very Useful) and faculty at 4.65 (Very Useful), up from pre-development ratings of 4.28 and 4.30 respectively. ThesisVault successfully bridges the gap between valuable thesis knowledge and the community's ability to access and utilize that knowledge.
Anishkumar H. Gandhi, Kishan Fuse, Vijaykumar Natvarlal Modi, Vishvesh J. Badheka
In present paper, dual shoulders friction stir welding (DSFSW) tools were used for friction stir welding of lapped Al 6061-T6 workpieces (152 mm X 102 mm X 3 mm) in open air-cooling conditions using different tool rotational speeds and tool feeds. A total of 17 experiments were performed using seven differently designed DSFSW tools, two different fixtures, and two different vertical milling machines to investigate the effect of tool parameters on weld formations with different processing parameters window. Some of the initial tools produced ineffective material flow due to insufficient amount of frictional heat generation and inadequate stirring action, which hindered the material movement towards the horizontal interface of lapped workpieces and reduced intermixing of workpieces material at there. Based on investigations of weld formations, a series of experiments was subsequently performed using the redesigned and modified DSFSW tools with optimized combinations of tool rotational speed and feed rate which was finally resulted in improved frictional heat generation, enhanced plasticized material flow, and sufficient material intermixing at weld interface, thereby producing improved weldments. These experiments demonstrated a progressive improvement in weld quality, ranging from unwelded joints to sound weldments, although a few hole/porosity defects were observed on the advancing side of the weld nugget zone. The investigation led to the successful development of practical DSFSW tool designs capable of producing sound friction stir welds in lapped Al 6061-T6 workpieces.
Alaneme Gloria Chinyere, Kuye Owolabi Lateef, Obasi Nneka Peace
Purpose: The study examined the technology-contingent effects of organizational capability on Sustainable Entrepreneurship (SE) among small and medium-sized enterprises (SMEs). Specifically, it investigated how strategic agility and adaptive capability influence SE and how artificial intelligence (AI) adoption plays a mediating role in this relationship. Design/Methodology: The study adopted a cross-sectional survey research design and was grounded in the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT). Using Taro Yamane’s formula, a sample size of 382 was determined from a population of 8,395 registered SMEs in Lagos State, Nigeria; 311 valid responses were analyzed using a structured questionnaire. Structural Equation Modeling (SEM) with AMOS 23 was employed for data analysis. Four hypotheses were formulated and tested. Findings: The results revealed that both strategic agility and adaptive capability significantly influence SE, and their combined effect strengthens sustainable entrepreneurial outcomes. Notably, artificial intelligence adoption partially mediated the relationship between organizational capabilities and SE, indicating that AI serves as a technological enabler that enhances the translation of internal capabilities into sustainable outcomes. Originality/Value: This study advances sustainable entrepreneurship literature by introducing a technology-contingent capability perspective, demonstrating that artificial intelligence functions as a mediating mechanism linking organizational capabilities to sustainability outcomes. In response to recent calls for more process-oriented and digitally grounded explanations of sustainability in entrepreneurship, the study extends RBV and DCT by positioning AI not merely as a technological tool but as a strategic transformation mechanism in SMEs.