World Journal of Multidisciplinary Studies
World Journal of Multidisciplinary Studies (ISSN: 3049-0855) is a peer-reviewed, open-access journal that was founded in 2024 by WASR Publication. The journal aims to serve as a leading platform for researchers, academicians, and practitioners in various multidisciplinary fields to disseminate high-quality, original research. WJMS is committed to promoting the exchange of ideas and knowledge, fostering academic and professional excellence, and contributing to the advancement of these diverse disciplines.
Arc-Tangent Algorithm for anti-jamming of the GALILEO signals
Due to the diversified applications, GPS i.e Global Positioning System is the most widely used navigation system till date. However, in itself it consumes a number of flaws in terms of accuracy. Later on, with the development of the Global Navigation Satellite System (GLONASS) was designed to overcome these issues, however it failed to meet expectations. Galileo GNSS was the most current and sophisticated development in 2016, and it was released in 2016. It is the most recent satellite navigation system, with higher tracking speed and accuracy superior to both the earlier systems, GPS and GLONASS. This study aims to construct chirp jamming to jam the acquisition signal, then anti-jamming the Galileo GNSS signal using ATSA and ATLMS algorithm to recover the signal that is being provided as an input, which is unavailable in any of the navigation literatures till now. Basically, the objective of the paper is to describe the two arc tangent algorithms, i.e, Arc-tangent Sign Algorithm and Arc-tangent Least Mean Square Algorithm. It is the MATLAB-based simulation for supervising the mitigation techniques using the arc Arc-tangent algorithms. GALILEO signals, their transmission, and reception techniques are also described in the paper.
IMPACTS OF HIGH COST OF FEED ON THE PRODUCTION, MARKETING AND DISTRIBUTION OF BROILER BIRDS IN NORTHERN NIGERIA
Poultry farming has been one of the lucrative businesses common among many people in Northern Nigeria. Apart from those involved in poultry farming for egg production, there are those engaged in broiler farming for meat production. This branch of poultry farming has been lucrative and has provided cash-generating opportunities for hundreds of thousands of male and female farmers who leverage its potential to build sustainable business empires. The cost of feed in the broiler poultry business is, however, one of the most pressing challenges causing hundreds of farmers across the North to shut down their farms. This specific challenge is driven by the scarcity of ingredients used in feed production, insecurity resulting from the activities of armed bandits, desertification affecting the land used for producing farm products like maize and soybeans, and the increased cost of transportation due to the removal of the fuel subsidies. This development has now created uncertainty in the market, increased the cost of broilers for end-users, and led to a general crisis in the production, marketing, and distribution of broiler birds in the Northern region of the country. This paper aimed to evaluate the connection between the high cost of feed and the distribution of broiler birds, as well as to assess the general market visibility and opportunities in the Northern region. The paper adopted a mixed research methodology, combining a literature review and field interviews, with the goal of integrating the data collected from the field with the literature to arrive at findings that may be useful for future planning.
REVISITING THE DYNAMICS OF RANSOM COLLECTION BY ARMED BANDIT’S IN THE NORTH-WEST, NIGERIA
This position paper examines the multi-dynamic nature of ransom collection by some groups of armed bandits in Nigeria’s North-West and its consequential effects on the security and safety of the state's citizens. It provides some historical insights into the trends along which banditry transformed into kidnapping business in Nigeria and why the fight against armed banditry conflict has failed for almost a decade now. It also provides some statistical data about defense budgets and allocations of security votes by some states in Nigeria and why the menace of armed banditry and kidnapping for ransom has not reduced despite the huge investment claimed to have been made by governments in Nigeria. The paper adopted a mixed research methodology of literature review and field interviews with a view to comparing the strengths of the data collected from the field and its connection with the subject matter under discussion.
Nanoparticle Enabled Copper Delivery for Tumor Selective Induction of Cuproptosis
One of oncology's most urgent challenges is the creation of tumor-selective treatment modalities, especially for chemoresistant and refractory cancers. A newly discovered copper-dependent type of controlled cell death called cuproptosis takes advantage of the metabolic weaknesses of cancer cells that have increased expression of lipoylated proteins and mitochondrial respiration. In contrast to ferroptosis, necroptosis, or apoptosis, cuproptosis is caused by the destabilisation of iron-sulfur cluster proteins and the aggregation of lipoylated mitochondrial proteins, which results in selective tumour cell death and proteotoxic stress. The regulated and tumor-selective administration of copper ions is a significant obstacle to the therapeutic exploitation of cuproptosis since systemic copper dysregulation can cause damage in healthy tissues. By increasing tumour accumulation, allowing regulated release, and reducing systemic exposure, nanoparticle-based delivery systems present a viable way to get around this restriction. In this work, we used a core–shell design with a biodegradable polymeric core, polyethylene glycol (PEG) coating, and surface-conjugated targeting ligands (RGD peptides) to create tumor-targeted copper-loaded nanoparticles (Cu-NPs) that improve tumour tropism. The nanoparticles were tailored to release copper in the acidic tumour microenvironment in response to pH. Strong cuproptotic activity was shown in vitro in several tumour cell lines with significant mitochondrial oxidative phosphorylation, as shown by lipoylated protein aggregation, decreased ferredoxin levels, and compromised mitochondrial respiration, but non-transformed cells were spared. Cu-NPs selectively accumulated in xenograft tumours in vivo, causing approximately 75% tumour growth inhibition with no damage. Proteotoxic stress, reduced iron-sulfur cluster stability, and mitochondrial malfunction all supported cuproptosis as the main mechanism of cell death, according to mechanistic research. All things considered, this work shows that copper distribution via nanoparticles can specifically take advantage of tumour metabolic weaknesses to cause cuproptosis, providing a potential treatment approach for refractory malignancies. The study emphasizes the potential of combining nanotechnology with metabolic-targeted oncology and lays the groundwork for the translational development of cuproptosis-targeted treatments.
Artificial Intelligence–Driven Design of Selective Apoptosis Re-activators Targeting Unendurable Cancer Proteins
Malignant cells lack appropriate binding sites and adaptive resistance mechanisms, the creation of specific apoptotic re-activators for unendurable cancer proteins continues to be a major problem in precision oncology. Recently, the discovery of new molecular scaffolds, the prediction of protein–ligand interactions, and the optimization of therapeutic specificity have all been made possible by artificial intelligence (AI)-driven methods. In this work, we propose selective apoptotic re-activators that target unendurable oncogenic proteins like KRAS, MYC, and mutant p53 by utilizing AI-powered computational platforms, such as generative modelling, virtual screening, and deep learning-based protein structure prediction. High-resolution structural data, ligand-protein docking simulations, and multi-parametric optimization for binding affinity, selectivity, and pharmacokinetic characteristics are all included into the suggested methodology. Effective reactivation of apoptotic pathways, such as caspase-3/7 activation and mitochondrial membrane depolarization, while sparing normal cells is demonstrated by in vitro validation in apoptosis-resistant cancer cell lines. Additionally, negligible off-target interactions are shown by in silico calculations, suggesting great treatment specificity. According to mechanistic studies, the AI-designed compounds overcome compensatory anti-apoptotic pathways and disrupt protein–protein interactions essential for oncogenic survival in order to restore apoptotic signaling. This comprehensive AI-driven system offers a platform for the logical design of next-generation treatments in refractory tumors and speeds up the identification of promising drug candidates against targets that were previously untreatable. The results show how computational intelligence and experimental validation can be used to overcome major drug development barriers and provide a promising path toward precision-targeted cancer treatments. Overall, this work opens the door for translational applications in personalized oncology by establishing a strong paradigm for AI-guided drug design that permits the specific induction of apoptosis in resistant cancers.
Trends and Patterns of FDI Inflows in India
The purpose of this paper is to examine the trends, growth, and patterns of Foreign Direct Investment (FDI) inflows into India, with special focus on how inflation influences FDI growth. The study also identifies key sectoral and macroeconomic factors that shape foreign investment decisions, and evaluates the effects of FDI at both sectoral and national levels. Using secondary data, line graphs, and pie charts, the project analyses a decade of FDI inflow trends and compares major economic indicators to understand their impact on investment. Forecasted FDI values are also generated based on historical patterns. The findings highlight the major industries attracting substantial FDI and the factors influencing investor behaviour, while also showing how FDI contributes to India’s overall economic growth through technology transfer, job creation, and productivity gains. Based on these insights, the study proposes measures such as regulatory reforms, investment facilitation, and sector-specific strategies to strengthen India’s investment climate. The recommendations aim to guide policymakers, investors, and stakeholders in designing effective policies to enhance and sustain FDI inflows into the Indian economy.
SECULARISM IN THE CAMEROONIAN EDUCATIONAL SYSTEM: PHILOSOPHICAL FOUNDATIONS AND CONTEMPORARY CHALLENGES
Cameroon's educational system is characterized by a complex interplay of state and religious influences. This paper examines the concept of secularism in Cameroon's educational system, exploring its historical roots, current challenges, and implications for national unity. The paper argues that secularism is essential for promoting inclusivity, tolerance, and academic freedom in a multi-ethnic and multi-religious society like Cameroon. The paper discusses the constitutional provisions and laws governing secularism in education, highlighting the state's efforts to promote neutrality and inclusivity. However, it also examines the challenges posed by the growing influence of religious groups and the need for effective regulation. The paper concludes that a robust secular framework is necessary to ensure equal access to quality education for all Cameroonians, regardless of their religious affiliations. The paper recommends strengthening the regulatory framework, promoting interfaith dialogue, and enhancing teacher training on secularism to address the challenges. It also calls for increased efforts to promote critical thinking and media literacy to counter extremist ideologies. By upholding secularism, Cameroon's educational system can foster a culture of tolerance, mutual respect, and national cohesion.
John Rawls' theory of justice as fairness has profound implications for educational justice. This paper examines Rawls' principles of justice and their application to education, focusing on fairness, equality, and opportunity. Rawls' difference principle and equal opportunity principle are particularly relevant to addressing educational inequalities. The paper argues that Rawls' framework provides a robust foundation for advocating for equitable education policies and practices. Rawls' theory emphasizes the importance of ensuring that social and economic inequalities are arranged to benefit the least advantaged members of society. In education, this means prioritizing the needs of marginalized and disadvantaged students. The paper explores how Rawls' principles can inform debates on educational resource allocation, access to quality education, and addressing systemic inequalities. The paper concludes that Rawls' theory of justice offers a valuable framework for promoting educational justice and addressing the needs of the least advantaged students.
SAVING AND SPENDING HABITS OF TRANSGENDER PEOPLE IN KERALA
This study sheds light on the challenges faced by transgender individuals in Kerala, including social inequality, financial instability, and limited access to government schemes. Key findings reveal that 93% of respondents are transwomen, with 44% below 25 years old. Over half rely on self-employment for income, prioritizing essential goods and medical necessities. Notably, 85% of those who underwent Sex Reassignment Surgery (SRS) struggle to meet daily expenses. To address these issues, the study recommends increased awareness of government schemes like Mazhavillu, Saphalam, Karuthal, and PRIDE. Policymakers should focus on mitigating social inequality, financial illiteracy, and unemployment to support the transgender community.
Decisions on Methodological Paths in Final Graduation Projects: Sharing Steps by Step
Objective: To investigate the perceptions of students in the Bachelor's Degree programs in Speech-Language Pathology and Nutrition regarding the level of difficulty they identify according to the type of research selected at a private university from January to March 2026. Materials and methods: This was a descriptive, non-experimental study. It consisted of two stages: the preparation of possible methodological approaches for Final Graduation Projects, and the second stage, a survey of 16 students from two programs within the Faculty of Medical Sciences who had completed or were about to complete their Final Graduation Projects, between January and March 2026. The survey focused on aspects that presented difficulties in their approach, according to the type of research selected. Results: The activities to be developed were defined according to the chosen type of research. Four methodological approaches were designed: literature review, survey research, interview research, and case study. Regarding the results obtained from the survey of advanced students, active and supplementary variables were considered in the Principal Component Analysis. The explained variance reaches almost 80%, which is considered a good fit. Conclusions: The Methodology department is working intensively on designing activities that strengthen the skills necessary for students to continue along the path they must follow to complete their Final Graduation Project.
Effect of Ascorbic Acid, Balanites aegyptiaca, and Strawberry Supplementation on Glycemic Control and Renal Function Biomarkers
This study investigated the effects of ascorbic acid, Balanites aegyptiaca, and strawberry supplementation on glycemic control and renal function biomarkers over a six-week experimental period. Glycated hemoglobin (HbA1c) showed a non-significant reduction among treated groups (P = 0.072). The control group recorded 4.2 ± 0.42%, compared with 3.8 ± 0.22% (ascorbic acid), 3.1 ± 0.44% (Balanites aegyptiaca), and 3.2 ± 0.22% (strawberry). In contrast, serum glucose levels were significantly decreased (P = 0.000). The control value was 114.03 ± 1.55 mg/dl, while levels declined to 107.75 ± 1.91 mg/dl with ascorbic acid, 100.0 ± 3.70 mg/dl with Balanites aegyptiaca, and 102.51 ± 2.08 mg/dl with strawberry, representing a maximal reduction of approximately 14 mg/dl in the Balanites aegyptiaca group. Serum urea levels differed significantly among groups (P = 0.000), decreasing from 41.81 ± 0.71 mg/dl in the control group to 35.36 ± 1.77 mg/dl (ascorbic acid), 39.11 ± 1.09 mg/dl (Balanites aegyptiaca), and 33.78 ± 0.48 mg/dl (strawberry), with the lowest value observed in the strawberry-treated group. Serum creatinine levels were also significantly reduced (P = 0.002), from 0.86 ± 0.10 mg/dl in controls to 0.60 ± 0.017 mg/dl (ascorbic acid), 0.65 ± 0.03 mg/dl (Balanites aegyptiaca), and 0.67 ± 0.08 mg/dl (strawberry). Weekly trend analysis demonstrated gradual and sustained reductions in glucose, urea, and creatinine across treated groups over the six-week period. Overall, Balanites aegyptiaca exhibited the strongest hypoglycemic effect, ascorbic acid produced the greatest reduction in creatinine, and strawberry supplementation showed the most pronounced decrease in urea levels. These findings support the beneficial biochemical effects of these natural interventions on glucose homeostasis and renal function.
Reducing Fertilizer Runoff and Enhancing Crop Yield with Nano-Engineered Nutrients
The sustainability of agricultural practices depends on several types of underutilised fertilizers that are environmentally hazardous and impede agricultural productivity. Conventional fertilizers have low nutrient use efficiency, particularly in nitrogen, where losses are reported between 50 and 70% through runoff, volatilisation, and leaching. A nano-engineered complete nutrient delivery system with biodegradable polymer-coated nanoparticles for macronutrient-controlled release has been proposed in this study, with the evidence that the formulated nano-fertilizers reduce nutrients' runoff compared to conventional fertilizer applications by 65% while increasing crop yields by 28%. Nutrient cycling is optimised together with soil health indicators in multi-site field trials across diverse agricultural systems. Coating technology smartly delivers the proper nutrients at the right time, corresponding to plant growth stages for optimum absorption. Although capital costs are initially high, economic analysis demonstrates favourable cost-benefit ratios compared to traditional methods. Results indicate significantly reduced groundwater contamination and greenhouse gas emissions compared with standard fertilisation methods. This novel multi-nutrient release mechanism for simultaneous applications departs from existing controlled-release mechanisms under soil moisture conditions, pH, and temperature parameters. Statistically analysed data shows that the coefficient of variation for yield parameters has been kept below 15% over three growing seasons.
Design and Performance Evaluation of a Hybrid Blockchain Credential Verification Architecture for Universities
Learning institutions are increasingly vulnerable to the theft of sensitive information facilitated by the sophisticated capabilities of Large Language Models (LLM) in social engineering attacks. The LLMs are usually aided by the use of social engineering through pretexting, impersonation, and even document-forgery activities. This research focuses on developing a hybrid Blockchain login information verification system that combines permissioned ledger governance with public rooting to ensure tamper evidence and fast revocation propagation, while keeping credentials off-chain. The system is designed for operational verification in learning institutions. It focuses on low-latency API verification, auditable issuance, and secure private information disclosure. Performance is measured by using queuing-based workload modeling and benchmarking parameters to compare the efficiency and security of centralized verification systems against permissioned-only ledgers. The system uses a hybrid model under baseline and adversarial traffic, modelled on LLM-driven phishing attacks. Results show reduced peak verification latency relative to permissioned-only designs, while preserving stronger integrity than centralised systems. The integration of identity management, effective dispute handling, and robust incident response mechanisms is a proof of concept.
Digital Agricultural Management Systems and FISP Performance in Zambia 2017-2024
The delivery, traceability and accountability of public agricultural support programmes are also being improved through the use of digital agricultural management systems. The paper will assume the correlation between the digitization of the district level and production by the Farmer Input Support Programme (FISP) in Zambia in the period between 2017 and 2024. It has been analyzed using the provided dataset of districts by year, which has 110 districts, 9 regions, 8 years and 880 observations. Aggregation on an annual basis, regional analysis, quartiles of technology-intensity and correlation analysis were implemented to measure the change in programme delivery, beneficiary integrity, adoption and cost indicators. The findings demonstrate tremendous administrative changes in the course of time: the average input efficiency rose to 87.44% in 2024 compared to 66.71% in 2017, whereas targeting accuracy grew to 93.67% in 2024, as opposed to 72.92% in 2017. The technology coverage has also increased by 20.00 percent to 86.28 percent, the digital coverage by small farmers has risen to 35.61 percent to 88.38 percent, the duplicate detections have fallen by 45,062 to 9,205, and the cases of fraud have also fallen by 2,086 to 328 within the same period. The administrative cost per registered farmer has decreased by 4.51 to 2.30, while the digital investments per registered farmer have increased by 0.45 to 2.51. The regional analysis has shown that the general performance in terms of delivery and cost was better in Lusaka and Southern provinces as compared to the Western, Luapula, and Northwest provinces. The increase in yield on its part was quite stable, though, which implies that digitization strengthened programme governance more obviously than agronomic output. The article concludes that there was a high correlation between digital management systems and the enhanced targeting, less leakage, widespread adoption, and less administrative costs of the unit, but the degree to which those gains can be transformed into production outcomes remains conditional on agronomy, access to markets, and rural infrastructure.
Assessment of the Renoprotective Potential of Melatonin Against Sodium Arsenite-Induced Nephrotoxicity in Male Rabbits: A Morphological and Biochemical Study
Background: Chronic exposure to arsenic is a global health concern, frequently leading to severe organ damage, particularly nephrotoxicity. This study aimed to evaluate the potential renoprotective effects of Melatonin (Me) against Sodium Arsenite (Sa)-induced renal injury in male rabbits over a 12-week period. Methods: Rabbits were divided into four groups: Control (Con), Melatonin-only (Me), Sodium Arsenite (Sa), and a combination group (Me + Sa). Evaluations included gross morphological analysis of renal tissue and measurement of serum biochemical markers, specifically Urea and Creatinine levels. Results: Morphological analysis revealed that the Sa group suffered profound pathological changes, including significant renal atrophy, discoloration, and irregular surface textures, consistent with ROS-driven oxidative stress and tubular necrosis. In contrast, the Me + Sa group showed a remarkable recovery, with kidneys maintaining a structure and color similar to the control group. Biochemical data supported these findings: the Sa group exhibited significantly elevated levels of Serum Urea (47.88 ±1.395 mg/dl) and Creatinine (1.22 ±0.095 mg/dl) compared to the control (p < 0.05). Co-administration of Melatonin in the Me + Sa group significantly attenuated these elevations, bringing Urea (41.72 ±2.012 mg/dl) and Creatinine (0.87 ±0.076 mg/dl) levels back toward baseline values. Notably, Melatonin alone showed no adverse effects and even slightly improved renal markers compared to the control. Conclusion: The results demonstrate that chronic Sodium Arsenite exposure induces significant nephrotoxicity and structural degradation. However, Melatonin effectively mitigates these damages, likely due to its potent antioxidant properties. This suggests that Melatonin may serve as a promising therapeutic agent in preventing arsenic-induced renal dysfunction.
"Effect of Dietary Moringa oleifera Supplementation on Growth Performance (Body Weight and Length) of Fish"
This study evaluated the effect of dietary supplementation with Moringa oleifera leaf powder on growth performance and morphometric parameters of fish over a 7-week experimental period. Fish were randomly assigned to three dietary treatments: a control group (0% Moringa), 30% Moringa supplementation, and 50% Moringa supplementation. Growth performance was assessed through measurements of body weight, weight gain, relative growth rate (RGR), specific growth rate (SGR), and total body length. The results showed significant differences (P < 0.05) among treatments in final body weight, growth indices, and body length parameters. The 30% supplementation group recorded comparatively improved growth indicators relative to the control and 50% groups, while the 50% inclusion level showed the lowest performance values. Variations were also observed in weight gain, RGR, and SGR, indicating that growth responses were influenced by the dietary inclusion level of Moringa leaf powder. These findings suggest that dietary incorporation of Moringa oleifera leaf powder affects growth performance and morphometric traits in fish, and that optimal inclusion levels are essential to achieve favorable outcomes. The study contributes to ongoing research exploring plant-based feed additives as sustainable alternatives in aquaculture nutrition.
The Protective Role of Alpha-Lipoic Acid against Paracetamol-Induced Hematotoxicity in Male Rabbits
Background: Paracetamol (PAR) is a widely used analgesic that can cause hematological toxicity at high doses through oxidative stress. Alpha-lipoic acid (ALA) is a potent antioxidant known for its cytoprotective properties. Objective: This study aimed to evaluate the protective effects of ALA against PAR-induced hematological alterations in male rabbits. Methods: Male rabbits were divided into four groups: Control, PAR-treated, ALA-treated, and a combination group (PAR+ALA). Hematological parameters, including Red Blood Cells (RBCs), White Blood Cells (WBCs), Hemoglobin (Hb), Hematocrit (HCT), and Platelets (PLAT), were analyzed. Results: The administration of PAR led to a significant decrease in RBC count (5.36 ±0.111 ×106µL) and WBC count (6.9 ±0.37 ×106µL), suggesting myelosuppression or oxidative damage. In contrast, ALA supplementation markedly improved the erythropoietic profile, significantly increasing RBCs ( 6.79 ±0.258 ×106µL) and HCT (45.04 ±0.783%). Interestingly, the PAR+ALA combination group showed a significant recovery in RBC and WBC levels compared to the PAR-only group, indicating a clear protective role for ALA. While Hb and Platelet levels showed no statistically significant differences across groups (p>0.05), a declining trend in platelets was observed in the PAR group, which was stabilized by ALA co-treatment. Conclusion: The findings demonstrate that alpha-lipoic acid effectively mitigates the hematotoxic effects of paracetamol in male rabbits. This protection is likely due to ALA’s antioxidant capacity, which preserves red cell membrane integrity and supports bone marrow function.
Artificial Intelligence and Machine Learning for Critical Infrastructure Risk Mitigation: Applications, Trade-offs, and Governance Challenges
Critical infrastructure systems face unprecedented cybersecurity threats that exceed the capacity of traditional risk mitigation approaches. Artificial intelligence (AI) and machine learning (ML) technologies offer transformative capabilities for real-time threat detection, predictive analysis, and automated risk assessment in operational technology (OT) and industrial control system (ICS) environments. However, the deployment of AI/ML in safety-critical infrastructure introduces complex trade-offs between speed and accuracy, availability and security, explainability and performance, and automation and human control. This article provides a comprehensive analysis of AI/ML applications in critical infrastructure protection, evaluates key trade-offs in system design, and addresses limitations, ethical considerations, and governance frameworks necessary for responsible AI deployment. Drawing on recent literature and empirical evidence, this article demonstrates that while AI/ML significantly enhances threat detection and predictive capabilities, successful implementation requires careful attention to organizational readiness, domain expertise integration, explainable AI techniques, and robust governance structures that balance innovation with safety and accountability.
FOOTBALL AS A PHILOSOPHICAL PHENOMENON: MEANING, PLAY, AND HUMANITY PUT TO THE TEST AT THE AFRICA CUP OF NATIONS
Often relegated to the status of mere popular entertainment, football is nevertheless a philosophical subject in its own right, as a social practice, a physical experience, a symbolic phenomenon, and a space for the production of meaning. Using an approach based on the philosophy of sport, this article analyzes soccer as a total philosophical phenomenon, drawing on classical and contemporary references (Plato, Aristotle, Nietzsche, Camus, Bourdieu, Mbembe). The Africa Cup of Nations (CAN) will serve as an empirical and symbolic framework for examining the ethical, aesthetic, political, and identity dimensions of contemporary African soccer. The hypothesis put forward is that the CAN constitutes a privileged philosophical laboratory where the fundamental tensions of the human condition are revealed: freedom and rules, chance and merit, body and recognition, play and power.
ENVIRONMENTAL ACCOUNTING PRATICES AND FINANCIAL PERFORMANCE OF LISTED MANUFACTURING FIRMS IN NIGERIA
This study investigates the relationship between environmental cost disclosure, corporate social responsibility (CSR) expenditure, and financial performance of quoted manufacturing firms in Nigeria from 2019 to 2026. Using a quantitative research design, secondary data were obtained from company annual reports, sustainability disclosures, and financial statements. The study analyzed environmental costs, CSR expenditure, and the Environmental Disclosure Index (EDI) to assess their effect on profitability. Descriptive statistics, correlation, and panel regression analyses were applied to test the hypotheses. Findings indicate that manufacturing firms with higher environmental investments, such as Seplat and Total Energies, achieved improved EDI scores and enhanced profit margins. Correlation results reveal strong positive relationships between environmental costs and profitability (r = 0.78), CSR expenditure and sustainability disclosure (r = 0.84), and EDI and profit after tax (r = 0.81). Regression analysis further confirms that environmental cost disclosure, CSR expenditure, and EDI significantly predict profitability, suggesting that proactive environmental management aligns with corporate financial objectives. The study concludes that environmental cost disclosure and sustainability practices are strategic tools that enhance financial performance, stakeholder trust, and corporate accountability. These findings offer practical insights for managers, investors, and policymakers seeking to integrate sustainable practices into manufacturing operations.
Microbial Quality and Internal Spoilage Assessment of Persea americana (Avocado pear) Sold at Oba, and Ochanja Markets, in Anambra State, Nigeria.
Persea americana (Avocado pear) fruits are often lost postharvest due to microbial spoilage, with internal decay frequently remaining undetected until the fruit is cut. There is limited recent data, especially under local market conditions on the microbial contamination and internal spoilage status of avocados postharvest. This study evaluated the microbial quality and internal spoilage characteristics of Persea americana (avocado) fruits obtained from Oba and Ochanja markets in Anambra, Nigeria. A total of four (4) spoiled fruits were purchased from Oba and Ochanja markets and were transported in a sterile container, to the laboratory for microbial analysis. Standard microbiological methods were used to enumerate total viable counts (TVC), yeasts and molds. TVC were carried out using pour-plate technique. Detection of yeasts and moulds were carried using microscopic examination. Biochemical characteristics of the isolated organisms were determined using catalase, coagulase, oxidase, motility, sugar fermentation, indole, methyl red(MR), Voges proskuar and citrate tests. Results showed that total bacterial count ranged between1.1 ×103 and 4.7 × 104, with OBM 2 having the highest count, while OBM 1 had the least. Escherichi coli (E. coli ) spp and Salmonella spp were not detected in any of the samples. The total yeast count ranged between 1.1 × 103 and 3.5 × 102. The total mould count ranged between 3.2 x 102 and 4.7 × 104. Microorganisms isolated in this study include: Staphylococcus sp., Streptococci sp. Mucor sp., Saccharomyces sp. and Geotichum sp. Internal browning was the predominant defect. Firmness decreased significantly with increasing spoilage. Overall, the study shows that poor postharvest handling and sanitation in open markets contribute to elevated microbial contamination and high spoilage incidence in avocados. The results highlight the need for improved storage, reduced handling, and better hygienic practices along the supply chain to enhance fruit quality, extend shelf life, and reduce economic losses.
AI-powered generative frameworks for the rational design of synthetic genomes and next-generation cellular architectures
The engineering of synthetic genomes—complete or partial genome constructs designed de novo or heavily modified—represents a frontier in synthetic biology with vast potential for biotechnology, medicine, agriculture and basic science. However, traditional synthetic genome design remains highly labor-intensive, reliant on manual annotation, iterative assembly and trial‑and‑error testing of large sequence spaces. Artificial intelligence (AI) offers a transformative opportunity to augment and accelerate synthetic genome design by learning patterns of genomic architecture, regulatory logic and functional outcomes. In this paper, we explore the development of AI‑based methodologies for designing and engineering synthetic genomes. We propose a workflow integrating generative models (e.g., language‑model architectures trained on genome sequences), predictive deep learning for functional annotation, and optimization algorithms for minimal genome design, modular genome construction and error‑correction. To illustrate potential benefit, we present a hypothetical benchmarking study in which an AI‑augmented design workflow reduced design cycles by ~40 %, increased predicted functional genomic modules by ~30 %, and lowered predicted assembly error rate by ~25 % compared to manual design. Tabulated results highlight comparisons across methods. We discuss methodological elements including feature encoding (e.g., genomic motifs, regulatory elements, three‑dimensional chromatin structure), model architectures (transformer‑based sequence models, graph neural networks for genome assembly graphs), training/validation workflows, and deployment considerations (interpretability, biosafety, ethical oversight). Key challenges include limited training data for synthetic genomes, ensuring viability of AI‑designed genomes in living systems, and governance of biosecurity risks. Looking forward, we delineate future perspectives: foundation‑models for synthetic life, closed‑loop design‑build‑test‑learn pipelines with AI, and integration of synthetic genomes into programmable cellular factories. In conclusion, AI‑driven design and engineering of synthetic genomes provides a promising paradigm to accelerate synthetic biology, but must be advanced with rigorous experimental validation, robust modelling and responsible stewardship.
Trustworthy and Transparent AI for Genomic Discovery
Artificial intelligence (AI), particularly deep learning, has demonstrated remarkable ability to analyze genomic data, uncover patterns, predict disease associations, and infer regulatory mechanisms. Despite high predictive performance, these models often function as "black boxes," limiting interpretability and trust in biological insights derived from them. Developing methods to interpret AI models trained on genomic data is crucial for biological discovery, clinical translation, and ethical deployment. This paper explores approaches for interpretable AI in genomics, including feature attribution, saliency mapping, attention mechanisms, model distillation, and explainable graph-based models. We demonstrate a framework combining convolutional neural networks (CNNs), transformer-based architectures, and gradient-based attribution methods to identify genomic features that drive model predictions. A hypothetical benchmarking dataset evaluates interpretability techniques on tasks such as predicting gene expression, regulatory element activity, and variant pathogenicity. Results show that integrated interpretation pipelines enhance transparency by highlighting biologically meaningful motifs, regulatory regions, and variant effects, with tabulated comparisons of feature importance and predictive accuracy. We discuss challenges such as handling long genomic sequences, integrating multi-omic data, avoiding spurious correlations, and balancing model performance with interpretability. Future perspectives include development of standardized interpretability metrics, integration of multi-scale genomic features, and creation of interpretable AI platforms for clinical genomics. In conclusion, interpretable AI methods are essential to bridge predictive power and biological insight, enabling responsible use of AI for genomic research, precision medicine, and genome editing.
Intelligent Visualization Frameworks Driven by AI for Multi-Dimensional Genomic Data Exploration and Interpretation
In the era of high‑throughput sequencing and multi‑omics profiling, the volume and complexity of genomic data pose significant challenges for researchers seeking to generate actionable insights. Traditional static visualization tools often fail to accommodate the scale, heterogeneity, and dimensionality of modern genomic datasets. Artificial intelligence (AI) offers transformative potential for advanced visualization: interactive, adaptive, and insight‑driven tools that support exploration, pattern detection and hypothesis generation. This paper presents a comprehensive framework for developing AI‑powered visualization systems tailored to genomic data workflows. We describe key components including data ingestion, feature embedding, dimensionality reduction, graph‑neural network-based layout generation, and interactive UI modules. A prototype application was evaluated on three use‑cases: whole‑genome variant distributions (n = 2,000 samples), transcriptome‑variant integration (n = 500), and 3D chromatin interaction visualization (Hi‑C data, n = 50). The AI‑augmented visualizations enabled users to identify sub‑population clusters 30 % faster than baseline tools, and to detect rare variant hotspots previously overlooked in manual reviews. We discuss challenges such as model interpretability, user‑interface design, real‑time interaction at scale, and dataset bias. Finally, we outline future directions including self‑supervised visualization embedding, immersive VR/AR genomics dashboards, federated collaborative visualization and deployment in clinical genomics settings. In conclusion, AI‑powered visualization tools hold the promise to democratize access to complex genomic data, accelerate discovery and enhance the interpretability of large‑scale genomics studies—provided that rigorous design, user‑centered workflows and open standards are embraced.
INDIGENOUS PRODUCTION AND EXTERNAL DEPENDENCE IN HIGH-TECHNOLOGY MILITARY CAPABILITIES: THE RELATIONSHIP BETWEEN DETERRENCE AND FOREIGN POLICY SUCCESS
This study systematically examines the impact of high-technology military capabilities on foreign policy success through the variables of indigenous production depth and external dependence. In the international relations literature, military power has generally been treated as a given and homogeneous variable, with insufficient scrutiny of its production conditions and supply relationships. However, today's complex technology ecosystems have rendered the political effects of military capacity more indirect and conditional. This study addresses this gap by analyzing the causal chain of "military capability → deterrence credibility → foreign policy success" through a mechanism-based approach. The study employs a qualitative comparative analysis method, conceptualizing indigenous production as a multi-layered structure encompassing control over critical subcomponents, access to software and algorithmic capabilities, and integration capacity. External dependence is assessed through persistent constraint layers including licensing restrictions, export control risks, maintenance monopolies, and software update dependencies. Findings demonstrate that as indigenous production depth increases, deterrence credibility rises, positively correlating with foreign policy success. Conversely, as external dependence intensifies, deterrence becomes conditional and foreign policy performance is constrained. The analysis also emphasizes the critical importance of the temporal dimension, showing that short-term external procurement advantages can deepen dependence channels over the long term. The study offers an original theoretical synthesis by integrating realism's emphasis on power with the network approach of weaponized interdependence literature. Military technology is reconceptualized not merely as an instrument of foreign policy but as a structural condition shaping the foreign policy space itself. The results reveal that defense industry policies are directly related to foreign policy autonomy and that these two domains must be addressed in an integrated manner.
Adaptive Camouflage Networks (ACN): A Real-Time AI-Driven Framework for Dynamic Visual Concealment in Complex Environments
Adaptive Camouflage Networks (ACN) introduce a cyber-physical framework that couples real-time adversarial texture generation with large-area electrochromic textiles to render ground vehicles virtually invisible to CNN-based VIS-LWIR seekers. Fusing on-edge multimodal sensing (RGB, LWIR, depth) within a 256-D latent vector, a quantized StyleGAN2-LC network updates 64×64-pixel drive commands every 198 MS while consuming 2.35 W on average. Across 2.7 million software-in-the-loop frames spanning urban, rural and snowy theatres, ACN suppressed YOLOv5x detection probability from 0.82 (NATO static) to 0.19 (η² = 0.71, p < 0.001), extended median concealment horizon from 1.2 s to 5.9 s, and met < 200 MS latency in 96.7 % of trials. Event-driven refresh saved 62 % energy versus full-frame updates, enabling 4-h mission profiles without alternator upgrade. Manufacturable via roll-to-roll coating (< 50 USD m⁻²), ACN offers a near-term, retrofit-ready survivability multiplier against pervasive drone surveillance.
Utilising Comics in Bullying Prevention Education for Primary School Pupils
Bullying among primary school pupils remains a critical concern, affecting students’ emotional well-being, social development, and academic performance. Early intervention is essential to cultivate empathy, respect, and positive social behaviours, thereby fostering a safe and inclusive school environment. This study explores the use of comics as an educational medium for bullying prevention, emphasising their suitability for young learners due to their visual, narrative-based, and reflective nature. Drawing on theoretical frameworks including Bandura’s social learning theory, Piaget’s constructivism, Vygotsky’s socio-cultural theory, and Mayer’s multimedia learning theory, the study highlights how comics can model positive behaviours, contextualise anti-bullying messages, and support cognitive and emotional engagement. The research discusses principles for selecting appropriate comics, strategies for integration into lesson plans and counselling sessions, and the use of both physical and digital platforms to maximise reach and effectiveness. Evaluation methods, including formative assessments, reflective activities, and behavioural observations, are proposed to measure comprehension, value internalisation, and behavioural change. While comics offer advantages such as enhanced engagement, emotional resonance, and visual literacy, limitations related to content depth, learning preferences, and implementation support are acknowledged. Ultimately, this study underscores the potential of comics as a practical, theory-driven, and age-appropriate tool for bullying prevention, promoting ethical character development, empathy, and pro-social behaviours among primary school pupils.
Designing Inclusive Pedagogy for AI Learning: A Framework Based on Universal Design for Learning (UDL), Ethical Guidelines, and Learning Praxes
As artificial intelligence (AI) permeates educational systems, instructors must reconcile the promise of personalization and access with risks of bias, exclusion, and unequal capacity to benefit. This article advances an Inclusive Pedagogy Framework for AI Teaching and Learning (IPFAITL) that integrates Universal Design for Learning (UDL), ethical AI principles, and critical learning praxis into a coherent, implementable model. Drawing from extensive research on inclusive pedagogy (Ybyrayeva, & Yermakhanova, 2022), AI ethics in education, and critical learning theory, this framework addresses the multifaceted challenges of teaching and learning with AI while promoting accessibility, equity, and social justice (Capraro, et al., 2023). The proposed framework provides practical guidance for educators, curriculum developers, and policymakers seeking to implement AI-enhanced education that serves all learners, particularly those from marginalized and historically underrepresented communities.
“PRESERVATIVE SYSTEMS IN HERBAL COSMETICS: A REVIEW OF MARKETED PRESERVATIVES AND THEIR EFFECTIVENESS”
This review explores the various preservation systems used in herbal cosmetics, with a focus on both natural and synthetic preservatives currently available in the market. Natural preservatives such as lemon oil, neem, honey, turmeric, and aloe vera are examined for their antimicrobial properties and compatibility with cosmetic formulations. The article also discusses commonly used synthetic preservatives, including parabens, aldehydes, and glycol ethers, highlighting their mechanisms, effectiveness, and safety concerns. An ideal preservative should be stable, non-toxic, and effective at low concentrations, with broad-spectrum antimicrobial activity. Although synthetic preservatives remain widely used, natural alternatives are gaining popularity due to perceived safety and consumer preference. The review concludes by emphasizing the need for further research into optimized combinations of natural preservatives that meet regulatory standards and consumer expectations.
Awareness and Attitudes Regarding Liquid-Based Cytology vs Conventional Pap Smear among medical student
Background: Cervical cancer remains one of the leading causes of morbidity and mortality among women worldwide, with screening playing a pivotal role in early detection and prevention. The conventional Pap smear is widely practiced, while liquid-based cytology (LBC) offers improved accuracy and specimen adequacy. However, awareness and attitudes toward these screening modalities among AYUSH students have not been adequately explored, despite their emerging role in preventive healthcare. Materials and Methods: A descriptive, questionnaire-based cross-sectional study was conducted among AYUSH undergraduate students from selected colleges. A total of 118 valid responses were collected through a structured Google Form. The questionnaire comprised demographic details and items assessing knowledge, awareness, and attitudes toward Pap smear and LBC. Data were compiled in Google Sheets and analyzed using descriptive statistics. Results: Out of 118 participants, only 28% demonstrated good knowledge regarding cervical cancer screening, while 13% were completely unaware of Pap smear and LBC, with the majority of this group being second-year students. Attitudes were more favorable, with 62% of respondents showing a positive outlook toward the importance of cervical cancer screening. Regarding intended practice, 54% expressed willingness to recommend LBC in future, while 31% favored conventional Pap smear due to cost-effectiveness. Conclusion: The study highlights a considerable knowledge gap among AYUSH students regarding cervical cancer screening methods, despite a generally positive attitude. Integrating cancer screening modules into AYUSH curricula and organizing interprofessional awareness programs are essential to strengthen their role in preventive healthcare and promote wider acceptance of advanced cytological techniques like LBC.