http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13049 2026-04-05T17:28:56Z http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13570 Assessing Vaccination Efficacy in Hightreatment Saturation for Meningitis Control Kolawole, Mutairu K.; Popoola, Amos O.; Adegoke, Adebiyi A. The study investigates the effectiveness of vaccination to keep meningitis in check, especially in conditions of high treatment saturation and limited resources. The numerical solution of this model is obtained through the homotopy perturbation method. In this work, we examine how vaccination and treatment are interrelated, but above all, with the basic reproduction number R₀, an important tool that identifies the size of the spread of meningitis. The study performs analyses of local and global stability for disease-free and endemic equilibrium points, providing insight into when and how meningitis can be eradicated or persist within a population. Furthermore, sensitivity analysis provides further light on which parameters have more influence on the disease transmission, thus providing an understanding of what factors would most ensure the control measures are successfully executed. In this paper, we have incorporated vaccination and treatment strategies into the model in order to assess the combined effect of the two methods in reducing the spread of meningitis and the best approaches towards disease control. In this dynamics, we apply the homotopy perturbation method for a comprehensive view of how vaccination and treatment can mitigate the burden of meningitis. These findings realize key lessons for the improvement of meningitis control strategies, particularly in remote settings, and hence contribute to the wider debate on infectious disease control. This in turn shows a way toward better control by demonstrating how a vaccination and treatment strategy that is strategically balanced can reduce the overall burden of the disease over time. 2024-07-20T00:00:00Z http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13340 Agriculture Greenhouse Gas Emissions and Mitigation: Assessing the Disposition of Nigerian Urban Farmers Adewale, Peter Sanjo; Akanmu, Raimot Titilade; Okafor, Chinenye Lilian Agriculture is the sector most vulnerable to climate change (CC), yet it contributes significantly to the problem, directly accounting for approximately 13.5% of global greenhouse gas emissions. Although CC mitigation has gained a lot of attention in research, there is a notable lack of understanding regarding Nigerian farmers’ awareness and perception of greenhouse gas (GHG) emissions mitigation strategies. This study aimed to explore the knowledge of CC and disposition towards adoption of GHG emissions mitigation measures among 358 urban farmers in Nigeria. The participants were randomly selected for online survey questions to ascertain their awareness and dispositions towards agricultural GHG emissions and mitigation. Descriptive statistics and Analysis of Variance (ANOVA) were used to analyze the data. The study found that farmers possess a moderate level of awareness about CC. Motivation of the farmers to adopt strategies for mitigating GHG emissions was moderately high but not as high as expected. No significant difference between the motivations of urban farmers to mitigate GHGs from different states. Urban farmers were willing to adopt climate-friendly practices to reduce GHG emissions. Urban farmers are encouraged to reduce the rate at which they use chemical fertilizers and implement sustainable livestock management practices while the government provide training and extension services for them. 2024-07-15T00:00:00Z http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13054 Optimization of Water Distribution Networks Using Enhanced Heuristic Swarm Intelligence Algorithm Ejieji, Catherine Ngozi; Aina, Ibukun Isaac In this paper, an optimal water distribution network (WDN) model was developed. An existing metaheuristic algorithms, known as the particle swarm optimization (PSO) algorithm was applied on the model to obtain the optimal cost of water distribution. A modified form of PSO called the enhanced heuristic swarm intelligence (EHSI) algorithm was also constructed and used to solve the model. Three case studies were treated. Results obtained show that PSO and EHSI algorithms minimize the total cost of water distribution network using the designed model and the EHSI algorithm performs better than PSO algorithm. present a detailed comparison of result of PSO and HSI algorithm. 2024-07-15T00:00:00Z http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13053 A Review on Life Cycle Assessment of Cotton Denim Jeans: Comparative Analysis on Conventional and Organic Approach Khatun, Mst. Murshida; Haq, Upama Nasrin; Bristy, Bebe Fatema; Sakib, Najmus; Mamtaz, Rowshan Cotton denim jeans are widely known to be among the dirtiest textiles available in the market. Denim jeans consume a significant amount of water, chemicals, and energy during their entire existence, from cultivation to disposal. This literature review examines the environmental impacts of denim production across four important phases: cotton cultivation, raw material processing, finishing, and disposal using conventional and organic methods. The environmental impact is classified into four areas using the life cycle assessment software openLCA 2.0.2. The four impact categories are: global warming, water consumption, freshwater ecotoxicity, and ozone formation in terrestrial ecosystems. Cotton cultivation makes use of a disproportionate number of chemicals (around 25 percent of the world's insecticides). Denim fabric manufacturing consumes 34, 38, 23, and 5 percent of total energy throughout the spinning, chemical process, weaving phase, and other operations, respectively. Besides, consumer use phase is the most resource consumed phase. People frequently discard or burn clothes, contributing to vast amounts of waste and harming the environment by emitting greenhouse gases. Cotton cultivation and conventional raw material processing produce the highest greenhouse emissions and use the most energy. Organic approaches emit 12 percent fewer emissions than conventional approaches. The conventional approach has a bigger environmental impact. 2024-07-15T00:00:00Z