Determining The Concentration of Criteria Pollutants in Bonny Island from Industrial Activities
This research paper presented the investigation of the concentration of selected criteria pollutants from Industrial activities in Bonny Island. The research was carried out for a total of two months, each both at the rainy and dry seasons. Readings were taken at a distance of 100meters from the stack emitting gaseous pollutants from the NLNG plant. Air pollutant parameters measured were PM2.5, PM10, CO, NOX, O3 and SO2 in line with international standards. The determination of selected criteria pollutants [CO, NOX, O3, SO2, PM2.5 and PM10] content of Bonny Island environments during dry and wet seasons at selected sampling point for 2 months each in the studied environment showed concentrations ranging from 0.142 to 0.599, 0.005 to 0.013, 0.011 to 0.023, 0.002 to 0.004, 5.80 to 43.45 and 6.32 to 47.25ug/m3 for dry seasons of CO, NOX, O3, SO2, PM2.5, and PM10; and 0.458 to 0.821, 0.002 to 0.013, 0.011 to 0.027, 0.002 to 0.004, 5.0 to 38.29, and 4.84 to 19.76ug/m3 for wet season of CO, NOX, O3, SO2, PM2.5, and PM10 respectively. Results of the analysis conducted showed that CO, NOX, O3, SO2, PM2.5, and PM10 concentration were below World Health Organizations [WHO] allowable limits and are acceptable for human.
Health Risk Assessment of Human Exposures to Radiation Emanating from Radon in Groundwater from Parts of Damaturu Metropolitan Yobe State, Northeastern Nigeria
Groundwater is an important and vital water resources, its demand had increased due to increase in population and enhanced standards of living. In this study a total of 30 water samples from borehole and well water were analyzed using Rad7 (Durrige) radon detector to determine radon concentration from parts of Damaturu metropolitan. The data generated was then used to evaluate radiological hazards posed to the public. The radon (Rn-222) concentration in the surface water varied from 0.35 to 3.08Bq/L with a mean value of 1.23?0.09Bq/L against the global average of 11Bq/L and thoron (Rn-220) was not detected in the ground water. In other to assess hazards due to radon concentration in the water to the people, the annual effective doses (AED) were computed. For ingestion of radon in water the AED varied from 1.14 to 7.86?Sv/y with a mean value of 3.11?0.34 ?Sv/y while inhalation of radon from water varied from 1.03 to 8.57?Sv/y with a mean value 1.26?0.28 ?Sv/y respectively. The total AED due to ingestion and inhalation of radon in water ranged from 1.10 to 5.87?Sv/y with a mean value of 1.14?0.38 ?Sv/y. The results for water radon concentration have shown that people are safe for using the water for drinking, cooking bathing and other domestic purposes.
Fungi Associated with Post-Harvest Diseases of Different Species of Ripe Paw Paw (Carica Papaya)
The aim of this work is to determine the fungi associated with post-harvest diseases of different species of ripe paw paw (Carica papaya). In this study, the fungi associated with post-harvest diseases of different species of ripe paw paw, the result shows the total heterotrophic count of fungi isolated from ripe paw paw shows the fungal count ranges from 1.6?105 to 5.0?105cfu/g. The frequency of occurrences of fungi associated with ripe paw paw showed that of the three fungi species isolated from samples, Rhizopus sp. 6(40%) is the most predominant followed by Penicillium sp. 5(33.3%) and Aspergillus spp. 4(26.7%). It is advisable that ripe paw paw should be disposed instead of being consumed since its consumption could be detrimental to health. In addition, food handlers on our market should handle food product with care by practicing proper hygiene in the market environment, by using clean water to wash food products to avoid contamination by micro-organisms present in the water.
Should Petroleum, Alcohol, And Electricity Be Included Under GST?
The Goods and Services Tax (GST) in India was a major tax reform that aimed at unifying the tax system and making it more transparent. However, some large sectors, such as petroleum, alcohol, and electricity, have been left out, resulting in uneven taxation and loss of input credit benefits. This paper examines their exclusion reasons, estimates the economic and fiscal effects of their inclusion, and identifies the benefits and challenges for the central and state governments. It uses only secondary data from government publications, research papers, and policy reports. In fact, the results indicate that the inclusion may lead to a simpler tax system, greater transparency, and strengthened fiscal coordination, though state compensation and implementation that is done with care are still necessary. The paper ends with the suggestion that a phased-in approach would help achieve a balanced, efficient, and growth-oriented tax framework for ??India.
Bridging STEM and Cross-Cultural Education: Designing Inclusive Pedagogies for Multilingual Classrooms in Sub-Saharan Africa
In the diverse and linguistically rich region of Sub-Saharan Africa, multilingual classrooms are becoming the norm rather than the exception. However, the traditional design of Science, Technology, Engineering, and Mathematics (STEM) education often fails to accommodate the cultural and linguistic realities of these learning environments. This review paper explores the intersection of STEM and cross-cultural education, examining how inclusive pedagogical strategies can bridge the gap between standardized STEM curricula and the dynamic cultural-linguistic identities of learners. Drawing on interdisciplinary research in education, sociolinguistics, and cognitive science, the paper highlights successful models of inclusive teaching, examines barriers to equity in STEM learning, and proposes culturally responsive frameworks tailored to the unique needs of multilingual classrooms in Sub-Saharan Africa. The review further emphasizes teacher training, policy shifts, and the integration of indigenous knowledge systems as central to educational transformation. Ultimately, this paper aims to contribute to the growing discourse on decolonizing STEM education while promoting equity, participation, and cognitive accessibility for all learners.
Vision-Based Silent Speech Recognition Using Hybrid 3D-CNN and Bi-LSTM Architecture
Silent Speech Recognition (SSR) addresses critical communication challenges in noisy environments and for individuals with speech impairments. This research presents a novel vision-based SSR system employing a Hybrid 3D Convolutional Neural Network (3D-CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM) architecture. Unlike acoustic speech recognition systems that fail in silent or noisy conditions, our approach exclusively leverages visual information from lip movements. The system integrates automated Region-of-Interest (ROI) extraction, spatiotemporal feature learning through 3D convolution, and bidirectional temporal modeling with Connectionist Temporal Classification (CTC) loss. Experimental validation on the GRID Corpus benchmark demonstrates superior performance with Word Error Rate (WER) of 17.06% and Character Error Rate (CER) of 7.12%, representing 44.3% improvement over traditional Hidden Markov Models and 20.3% improvement over 2D- CNN baselines. Ablation studies confirm that 3D convolution con- tributes 4.34 percentage points improvement while bidirectional processing adds 2.14 points. This work establishes a foundation for practical camera-based silent communication systems with applications in assistive technology, military operations, and industrial environments.
Utilization of Pineapple Crowns (Wastes) for Sustainable Paper Production: Climate Change Mitigation and Wastes to Wealth Approach
The paper industry currently depends on forest trees as fibre sources for paper production, contributing to deforestation which destroys ecosystems that are vital to wildlife and humans alike. Deforestation represents a growing threat to all lives on earth, driving dangerous carbon emissions and exacerbating the climate crisis. Like the oceans, forests absorb excess atmospheric carbon dioxide, serving as a much-needed buffer against irreversible climate change. In a bid to address deforestation caused by the paper industry, this study investigated the potentials and suitability of pineapple crowns (wastes) as fibre sources for sustainable paper production. The pineapple crowns were de-fiberized and fibre dimensions were examined. Fibre length, fibre diameter, lumen width and cell wall thickness were found to be 2.54 mm, 35.19 ?m, 36.67 ?m and 5.75 ?m respectively. Pulping was done through soda pulping method, papers were produced with the resulting pulps, the papers exhibited different tensile strength values ranging from 188.667 N/m2 to 248.667 N/m2, elongation @ break and force @ Peak(N) of papers were found to have different values. The chemical components, fibre dimensions, and tensile properties exhibited, all show that pineapple crowns have great potentials for paper production.
Effects of Internal Control Systems on Small and Medium-Sized Enterprises in Ondo State, Nigeria
This study examines how organizational structure or internal control mechanisms affect the effectiveness and efficiency of small and medium-sized businesses (SMEs) in Nigeria's Ondo State. SMEs are essential to economic growth, but because of inadequate internal controls and poorly defined organizational structures, many of them struggle with operational inefficiencies, financial mismanagement, and sustainability issues. Targeting SMEs in a variety of Ondo State sectors, the study used a descriptive survey approach guided by contingency theory. Regression analysis, ANOVA, and descriptive statistics were used to examine 331 valid replies in total. The results show that the financial performance of SMEs is significantly improved by the efficacy of internal control systems, which also improves resource utilization, fraud prevention, and accountability. It was also discovered that organizational structure plays a major impact in decision-making and operational efficiency, with governance frameworks, clear role descriptions, and communication routes enhancing productivity and responsiveness. Additionally, the long-term viability of SMEs was found to be strongly positively correlated with the combined effect of strong internal controls and cohesive organizational structures, which allowed for enhanced competitiveness and flexibility in response to environmental changes. According to the study's findings, SMEs' resilience and growth depend on their internal control systems being in line with appropriate organizational structures. It advises SME owners to codify operational structures, implement proactive internal control measures, and use technology to improve efficiency and governance. Policymakers and development organizations should help SMEs by providing resources, regulatory frameworks, and training to institutionalize efficient control and structure procedures. This study adds to the body of literature by offering empirical data from the local area regarding the relationship between organizational structure, internal controls, and SME performance in a developing economy.
Multi-Agent Debate System for AI-Based Decision-Making: A Framework for Enhanced Reasoning Through Collaborative Intelligence
Single-agent Large Language Models (LLMs) demonstrate limitations in complex decisionmaking scenarios, including domain-specific bias, overconfidence, and inability to integrate diverse perspectives. This paper presents the MultiAgent Debate System (MADS), a collaborative AI architecture leveraging specialized agents to generate robust insights through structured argumentation. Implemented using CrewAI framework with Llama 3 models via Groq's LPU infrastructure, MADS orchestrates three specialized agents (Advocate, Critic, Judge) in sequential debate workflows. Testing on interdisciplinary datasets demonstrates 73% improvement in argument quality over singleagent baselines, with average response generation under 8 seconds. The system produces multi-format outputs (transcripts, summaries, PDF reports) accessible to nontechnical users. By replicating human deliberative processes through agent-based debate, MADS advances interpretable, transparent AI decision-support systems while addressing critical gaps in crossdomain reasoning and perspective integration.