http://ir.mu.ac.ke:8080/jspui/handle/123456789/61 Sun, 28 Jun 2026 05:55:47 GMT 2026-06-28T05:55:47Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/10268 Predicting hypertension Medication Uptake using explainable Artificial Intelligence: Evidence from a Kenyan Population-based Study Koech, Eliud; Mutai, Charles Kipkoech; Kerich, Gregory Hypertension is a major contributor to cardiovascular morbidity and mortality worldwide, more so in Kenya, with limited progress towards achieving Africa's 2030 fast-track hypertension targets, especially in management. This study aimed to build a machine learning model to predict hypertension medication uptake in Kenya. Using data from 4,687 female and 5,269 male respondents from the 2022 Kenya Demographic and Health Survey, we applied Extreme Gradient Boosting, Support Vector Machine, Random Forest, and Elastic Net models. Data from 15 counties were split into training (80%) and testing (20%) sets, with class imbalance addressed using the Synthetic Minority Oversampling Technique and validation through leave-one-countyout cross-validation. The best-performing model, based on mean f1-score, was retrained using features selected through Sequential Forward Floating Selection. SHapley Additive exPlanations were used to interpret feature importance and directionality by sex. Treatment coverage remained suboptimal, with 26.6% of hypertensive males and 32.4% of females untreated. The XGBoost model achieved the best performance (78% males; 81% females). The most predictive features in both sexes were age, household size, sedentary time, income, exercise, wealth, residence duration, television viewership, and reproductive preferences among females. Interpretable machine learning revealed distinct sex-specific socio-behavioural predictors of hypertension treatment uptake in Kenya. Incorporating such data-driven insights can inform targeted, equitable interventions and strengthen hypertension control, especially in resource-limited settings where routine survey data can complement clinical assessments. Mon, 01 Jun 2026 00:00:00 GMT http://ir.mu.ac.ke:8080/jspui/handle/123456789/10268 2026-06-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/10266 Investigation of electronic and optical properties in bismuth/antimony co-doped methylammonium lead bromide Machiri, David; Mule, Gloria; Isoe, Wycliffe; Madallah, Yusuf; Awino, Celline Lead halide perovskites, exemplified by methylammonium lead bromide (MAPbBr3 ), represent a cornerstone in the pursuit of next-generation photovoltaic materials owing to their tunable optoelectronic properties, defect tolerance, and cost-effective synthesis. However, their intrinsic bandgap limitations and carrier recombination pathways necessitate advanced doping strategies to enhance performance. Herein, den- sity functional theory calculations were employed, utilizing the Perdew–Burke–Ernzerhof functional for structural optimization and the Heyd–Scuseria–Ernzerhof hybrid functional for precise electronic structure determination. Computations were conducted in a 2 × 2 × 2 cubic supercell, probing a spectrum of substitutional configurations at Pb2+ sites, including single-dopant systems (MAPb0.875 Sb0.125 Br3 and MAPb0.875 Bi0.125 Br3 ) and co-doped variants up to high concentrations, such as MAPb0.5 Sb0.125 Bi0.375 Br3 and MAPb0.5 Sb0.375 Bi0.125 Br3 . Band structures, interpolated via maximally localized Wannier functions using the selected columns of the density matrix with k-point sampling method, reveal a pristine direct bandgap of 2.32 eV at the Γ point, which narrows non-rigidly upon doping due to the introduction of deep donor states from heterovalent Sb3+ and Bi3+ impurities. These states manifest as midgap impurity bands, shifting the conduction band minimum downward while preserving valence band integrity. Optical properties, derived from time-dependent density functional pertur- bation theory via the Lanczos recursion algorithm, exhibit a pronounced redshift in the absorption onset and an enhanced intensity in the imaginary dielectric function (ε2 ) across the visible spectrum, attributed to broadened interband transitions and synergistic dopant-induced polarizability. Formation energy calculations confirm the thermodynamic accessibility of these co-doped configurations Thu, 01 Jan 2026 00:00:00 GMT http://ir.mu.ac.ke:8080/jspui/handle/123456789/10266 2026-01-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/10260 A review on tomato Fusarium wilt and integrated approaches for its management Mwaka, Odilo; Ramkat, Rose; Makumba, Billy A.; Pili, Njira N.; Makatiani, Jacqueline Fusarium wilt of tomato (Solanum lycopersicum L.) is a destructive vascular disease affecting tomatoes, caused by the fungal pathogen Fusarium oxysporum f. sp. lycopersici (Fol). It is a soil-borne pathogen that penetrates the host plant and infects the vascular tissues, causing wilting and plant death, resulting in significant yield losses. Despite difficulties in controlling the disease, this review presents an integrated disease management (IDM) framework that adopts a stage-specific and mechanism driven approach targeting critical stages in the Fol disease cycle for sustainable management. Specifically, an integrated approach combining compatible strategies such as regulatory measures, the use of resistant cultivars, crop rotation, soil or planting material heat sterilization, maintenance of proper nutrient balance, application of organic soil amendments, use of botanical extracts, utilization of beneficial or non-pathogenic microorganisms as growth promoters or biological agents, as well as minimal fungicide use, has been reported to be effective in suppressing the disease. Additionally, IDM offers an eco-friendly approach that reduces disease pressure, minimizes yield losses, protects the environment and human health, and decreases dependence on a single technique. Therefore, adoption of IDM strategies is essential in controlling Fusarium wilt for sustainable tomato production. Moreover, challenges in managing Fusarium wilt are discussed, including issues related to climate change, concerns about chemical use, the effectiveness of biological control agents in the field, and breakdowns in host resistance. Consequently, increased efforts by researchers, policymakers, regulatory agencies, and other agricultural stakeholders are needed to overcome these challenges, enhance Fusarium wilt control, and improve food security. Thu, 01 Jan 2026 00:00:00 GMT http://ir.mu.ac.ke:8080/jspui/handle/123456789/10260 2026-01-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/9987 Occurrence and removal of pharmaceutical residues in water: A case study of the Lake Victoria basin-Kenya Kandie, Faith Jebiwot; K'Oreje, Kenneth; Krauss, Martin; Kristof, D. D.; Torto, Baldwyn; Brack, Werner In the recent years, global concerns have increased on the environmental occurrence of Pharmaceutically Active Compounds (PhACs) due to their pronounced ecotoxicological risk. Several studies have shown their presence in different environmental matrices including water, sediments and biota. Whereas the occurrence of these compounds has been widely studied in the western world, few studies have been done in Africa. Additionally, the fate of PhACs during wastewater treatment by stabilization ponds and trickling filters commonly used in low- income countries, is not well known. To narrow this knowledge gap, this study investigated the occurrence of PhACs in water, snail tissues and sediments in 48 surface water systems and their removal in four selected wastewater treatment plants (WWTPs) within the Lake Victoria Basin, Kenya. Water samples from surface water were directly injected into the Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) for chemical analysis while wastewater samples were first processed using solid-phase extraction before analysis. Extraction of chemicals in snail tissues was done using QuEChERS (quick, easy, cheap, effective, rugged and safe) method while pressurized liquid extraction was applied to sediment samples prior to chemical analysis. Sat, 01 Jan 2022 00:00:00 GMT http://ir.mu.ac.ke:8080/jspui/handle/123456789/9987 2022-01-01T00:00:00Z