University of Rwanda

Cannabis use among university students is a growing concern, particularly in demanding medical programs. We estimated prevalence, identified predictors, and compared coping strategies among medical students in Uganda. Cross-sectional survey of 318 undergraduates at Kampala International University (Western Campus). Cannabis use and hazardous/disordered use were screened with CUDIT-R (hazardous 8-11; probable use disorder ≥12, DSM-5-TR aligned). Coping was measured with the Brief COPE. Predictors were assessed using logistic regression; coping differences with the Wilcoxon rank-sum test. Cannabis use prevalence was 30.8% (n = 98); 7.6% met criteria for hazardous use and 9.4% for probable cannabis use disorder. Independent predictors of use were being separated (AOR = 12.00), being single (AOR = 3.45), Catholic faith (AOR = 2.76), and longer time at campus (AOR = 1.16 per year). Users reported higher emotion-focused and avoidant coping; problem-focused coping did not differ. Cannabis use among Ugandan medical students is common and associated with relationship status, religion, and time at campus. Coping profiles suggest greater reliance on maladaptive strategies among users. Findings support campus policies and mental-health programs that integrate substance-use screening and strengthen adaptive coping skills.

Bovine mastitis remains a significant challenge to dairy health management worldwide, with substantial economic and public health implications. In Rwanda, where traditional dairy farming is crucial for household livelihoods and the national economy, mastitis reduces milk yield and increases the risk for bacterial contamination, posing serious food safety concerns. This study, conducted in Rwanda's North-Western region from January 2024 to April 2024, aimed to identify key mastitis risk factors, evaluate existing control gaps, and propose evidence-based interventions. This cross-sectional study collected data from 411 smallholder dairy farms in Rwanda, assessing one lactating cow per farm through clinical examination, California Mastitis Test, and structured farmer questionnaires on management and hygiene practices. Logistic regression analysis in R identified significant cow-related and farm-level risk factors, providing a basis for targeted mastitis control and biosecurity recommendations. The overall mastitis prevalence was 60.06% (95% CI: 53.57-66.55), with subclinical cases alone accounting for 56.9%. Poor cow hygiene emerged as the strongest predictor (OR = 85.47, 95% CI: 27.18-268.74; p < 0.001). Other associated factors included exotic pure breeds, late lactation stages, and multiparity. External contributors included inadequate milking practices and limited veterinary access. In zero-grazing systems, poor housing drainage (OR = 109, 95% CI: 26.46-507.18; p < 0.001) and infrequent bedding changes (OR = 6.36, 95% CI: 3.38-12.78; p = 0.014) significantly increased mastitis risk. Identified gaps included lack of farmer knowledge, insufficient access to affordable mastitis control supplies (e.g., disinfectants such as iodine or chlorine dioxide), inappropriate mastitis treatments, poor farm biosecurity, and inefficient quality control in the milk marketing chain. Strengthening farm biosecurity, implementing a national mastitis control program, and enhancing veterinary extension are essential to reduce mastitis and improve milk safety. Coordinated stakeholder action is vital for sustainable dairy development and public health.

This review revealed only modest and statistically non-significant differences in the prevalence of sciatic nerve variations across broad racial and continental groups. In contrast, substantial variation was observed at the regional level, with particularly high prevalence rates in East Asian countries, specifically China and Japan. These findings suggest that regional factors contribute more to the observed variations than racial factors.

This study examined the effect of e-learning on junior secondary school students’ academic achievement in Social Studies in Lafia Local Government Area of Nasarawa State. A quasi-experimental pretest-posttest intact classes’ research design was adopted. A population of 233 JSS II Students from two public secondary school in Lafia will be used. The total Population sampling technique was employed, therefore the whole 233 students drawn from the two schools constituted the respondents. A Social Studies Students Objectives Academic Test (SSSOAT) was the instrument for data collection. The content validity of the instrument was done using a table of specification and the reliability was determined using the test re-test method and a coefficient 0f 0.82 was obtaine. The two research questions were analysed and answered using mean scores and standard deviation, while postulated hypotheses were tested at 0.05 level of significance using independent t-test. The findings revealed that there was a significant difference in the posttest achievement scores between the experimental and control groups (p&lt;0,05). The experimental group had a higher posttest meant score compared to the control group. The result further revealed the difference in posttest scores between male and female students in the experimental group is statistically significant (p&lt;0,05), it showed male students in the experimental group had a higher posttest mean score compared to their female counterparts. The study concluded that e-learning tools has an effect on the academic achievement of junior secondary school students in Lafia Local Government Area of Nasarawa state. The study recommends among others the e-learning tools be implemented in the control group to further assess their impact on achievement scores and ensure a more balanced approach to learning across groups.

Agricultural productivity in Rwanda’s semi-arid regions is increasingly challenged by intensified climatic variability, characterized by erratic rainfall, rising evapotranspiration, and recurrent dry spells. These conditions extremely affect agricultural production of different crops. These challenges undermining food security in a country where agriculture supports over 40% of the population. This study integrates two complementary experimental evaluations conducted across two growing seasons in semi-arid regions in Huye district. The research was conducted to assess the influence of drip irrigation management on dry matter yield (DMY) and Water-use Efficiency (WUE). Five key crops: Irish potato, maize, soybean, common bean, and Brachiaria grass were evaluated under both rainfed and drip irrigated system to assess their responsiveness to supplemental irrigation and their resilience to climatic stress, with consideration of their physiological classifications as C₃ and C₄ species. Across both season 1 and 2 drip irrigation showed highly significant effect on DMY and WUE with strong interaction effects between crop species and irrigation management at (P&lt;0.05). Maize exhibited the strongest yield response to irrigation, achieving up to 58.2% yield improvement in Season 1 and maintaining the highest irrigated DMY of 8,334 kg/ha. It also demonstrated superior WUE of 22.6 kg/ha/ mm of DMY confirming its suitability in semi-arid environments. Brachiaria grass, although exhibiting smaller absolute yield increase under irrigation compared to maize crops. It consistently achieved the highest water-use efficiency (WUE) across all treatments, reaching up to 35.2 kg /ha/mm of DM thereby underscoring its strong physiological resilience in semi-arid environment. In contrast, Irish potato remained the least efficient crop under water-limited conditions, recording WUE as low as 7.0 kg/ha/mm of DM confining it as high- drought sensitivity crop in the region. The findings highlight the importance of precision irrigation on different crops for increasing yields and efficient use of scarce water in semi-arid area of Rwanda. These results support effective water management as a key pillar for sustainable intensification and long-term food system stability in Rwanda, which is in line with the country's PSTA 4, NST2, and Vision 2050 goals. Key words: Dry matter yield, water-use efficiency, semi-arid region, Drip irrigation

This study examined the effectiveness of the AI-powered plant classification tool, PlantNet, in enhancing Rwandan secondary school students’ conceptual understanding and engagement in plant classification. Anchored in constructivist learning theory, a sequential explanatory research design was employed involving 149 students (control = 74; experimental = 75) from both rural and urban schools, along with eight biology teachers. Data were collected through pre- and post-tests, a Likert-scale engagement questionnaire, and semi-structured teacher interviews. Quantitative data were analyzed using descriptive and inferential statistics in Statistical Package for the Social Sciences (SPSS), including t-test, while qualitative data were analyzed thematically. Results revealed a statistically significant improvement in students’ conceptual understanding and engagement in the experimental group compared to the control group (p = 0.006; p<0.01), with an effect size of Cohen’s d = 0.61, a practically meaningful (moderate to large) effect in educational research. Subgroup analysis also indicated consistent learning gains across gender and school location. Thematic analysis of teacher interviews supported the quantitative findings, highlighting enhanced student autonomy, curiosity, and confidence when using PlantNet. Although some technical challenges were reported, such as limited accuracy due to unclear images and poor internet access, teachers positively viewed the integration of AI tools into biology instruction. This study provides novel evidence on the pedagogical value of AI-powered plant identification in low-resource contexts, an area rarely explored in African secondary education. Future research should examine long-term learning retention, scalability, and integration of AI tools across other science disciplines to further advance technology-enhanced biology education.

Urban blue–green infrastructure (UBGI) is essential to addressing urbanization challenges. However, its potential to mitigate climate extremes remains unclear. This study assessed biodiversity and water conservation challenges in UBGI using testate amoebae (TA) as indicators of ecosystem health. The studied UBGI consists of 0.67 km 2 of forested hills and 3 668 m 2 of ponds, located in the 55 800-km 2 city cluster in the Pearl River Delta, South China. The analysis incorporated a two-year (June 2021 and June 2022) dataset, comprising TA records from 27 soil samples, 30 pond water samples, and 30 pond sediment samples; 27 microspatial factors, including five factors representing weather conditions (WC), eight factors for air quality (AQ), and 14 factors for water quality (WQ); and four climate extreme scenarios (heatwaves, droughts, typhoons, and floods). Biodiversity and water quality concerns linked to interactions between urban emissions and aquatic ecosystems within UBGI were illuminated in the following three key findings: (1) biotope connectivity enabled redistributions of soil-specific TA (six out of 42 species) along hillslopes (moisture gradient) and pond lengths (hydrological gradient); (2) TA showed strong biotope adaptation, with stochastic processes explaining 69.3% of community variations in water and 78.8% in sediment; and (3) UBGI showed limited effectiveness in mitigating urban emissions, such as CO and NH 3 , particularly when TA were adversely impacted by WC driven by climate extremes and when WQ was adversely influenced by AQ. The findings suggest that TA are reliable bioindicators, informing UBGI performance and supporting climate-resilient interventions to monitor cross-border pollution and its effects at the biotope level.