The University of Gondar, until 2003 known as the Gondar College of Medical Sciences, is the oldest medical school in Ethiopia. Established as the Public Health College in 1954, it is located in Gondar, the former capital of Ethiopia. In 2010, the university offered 42 undergraduate and 17 postgraduate programs. As of 2016, the University offers 56 undergraduate and 64 postgraduate. These are organized under the College of Medicine and Health Sciences, College of Business and Economics, College of Natural and Computational Sciences, College of Social Sciences and Humanities, and Faculty of Veterinary Medicine and Faculty of Agriculture, and three schools (School of Law, School of Technology and School of Education). The current president of the University is Dr. Asrat Atsedeweyn.
Access to quality water is critical for public health; however, Ethiopia is grappling with challenges stemming from inadequate infrastructure and limited resources. This study evaluated the quality of drinking water sourced from large and medium-sized pump-based systems in Central Gondar, comparing the findings against WHO water quality standards. Employing an explanatory mixed methods research design, 415 respondents were selected through systematic sampling. Data were gathered through surveys, focus groups, and key informant interviews, alongside experimental analyses conducted at sample sites.The results indicated a low level of satisfaction with drinking water quality, with only 1.3% of householders reporting very high satisfaction and 18% expressing satisfaction. Regarding water treatment, a mere 0.26% of households were very satisfied, while 53% voiced dissatisfaction, underscoring concerns about the effectiveness of treatment methods. Additionally, approximately 55% of respondents rarely observed changes in water quality due to seasonal variations, reflecting a limited understanding of safety testing protocols.Interestingly, 33.3% of respondents rated the WHO standards for drinking water quality as excellent, which was associated with a perception of a highly reliable water supply system. Experimental results revealed variability in calcium and magnesium levels, with the Dembia-3 sample showing the highest calcium concentration at 110 mg/L. Alarmingly, the Gondar-4 sample tested positive for fecal coliforms (3 colonies/100 mL) and total coliforms (15 colonies/100 mL), raising significant public health concerns.In conclusion, the study highlights the urgent need for improvements in water quality management and emphasizes the importance of raising community awareness regarding water safety issues.
Background Learning organizations possess strong abilities to evolve, transform, and adjust to the rapidly changing environmental factors, sharing this knowledge among members at different levels interactively via computing and networking to address issues. Numerous past studies suggest that a learning organization plays a crucial role in enhancing the competitive advantage of organizations.Objective Therefore, this study explores how innovation and organizational commitment influence the relationship between learning organizations and competitive advantage.Methods The research adopts a positivist philosophy, a quantitative method, and a descriptive-explanatory design. Data was collected from 265 employees at the Awash Bank headquarters through a self-administered questionnaire using simple random sampling. Analysis was conducted using PLS-SEM via Smart PLS software.Results Findings revealed strong positive relationships between learning organization, innovation, and competitive advantage. Innovation was found to partially mediate the relationship between learning organization and competitive advantage. Additionally, organizational commitment significantly moderated the link between innovation and competitive advantage.Conclusion The results validate that innovation greatly improves competitive advantage, whereas organizational commitment amplifies its impact and the mediation process, especially in Ethiopia's evolving banking industry. Overall, the research emphasizes learning organizations as a strategic basis that combines learning, innovation, and commitment for enduring competitive advantage.
Breast cancer is one of the most prevalent and life-threatening diseases affecting women worldwide, where early detection is crucial for improving survival rates. Ultrasound imaging is widely used due to its non-invasive, cost-effective nature and suitability for dense breast tissues. This study introduces Swin-attention-enhanced atrous spatial pyramid pooling (ASPP)-attention-squeeze-and-excitation (SE) uncertainty-aware U-Net++ (SAASU-UNet++), a novel hybrid segmentation framework designed for precise breast tumour segmentation in ultrasound images. The model incorporates a Swin Transformer encoder to capture global context, an attention-enhanced ASPP module for multi-scale feature extraction, and a hybrid U-Net++ decoder embedded with SE blocks for channel recalibration. To improve robustness and uncertainty awareness, Monte Carlo dropout is applied. Training was performed with the Adam optimiser (batch size 32, 100 epochs) on the BUSI dataset containing 780 annotated images (normal, benign, and malignant). Images were resized to 224 & times; 224, normalised, and augmented with flipping, rotation, and zooming. The proposed model achieved a Dice Coefficient of 96.25% and a Jaccard Index of 92.34%, outperforming state-of-the-art approaches. Ablation studies highlighted the effectiveness of each component, and visual results confirmed close alignment with ground truth, even in challenging cases. SAASU-UNet++ demonstrates strong potential for real-world clinical integration in automated breast cancer diagnosis.
Contract farming (CF) is increasingly encouraged for agricultural commercialization and to improve smallholder farmers' welfare in Ethiopia. However, a critical empirical gap exists concerning its causal effect on the smallholders’ livelihood dimensions, including health food security in northwestern Ethiopia. This research investigates the impact of soybean contract farming participation (SCFP) in selected districts: Metema, West Armachio, and Quara. A cross-sectional data is used for the analysis. We employed a multi-stage sampling procedure to select 369 smallholder farmer households (170 participants and 199 non-participants). Data were collected on various issues including farmers’ demographic and socioeconomic characteristics, livelihood capital assets, food security, and well-being to create a composite livelihood index. An Endogenous Switching Regression Model (ESRM) was used to address self-selection bias. The ESRM findings show that extension services (0.201) and market distance (0.036) promote contract farming participation, while labour (− 0.030), household size (− 0.150), and cooperative membership (− 0.469) significantly discourage it. Moreover, the variables influencing both livelihood and participation are household size and cooperative membership. While household size tends to reduce both participation and farmers’ livelihood, cooperative membership reduces participation but significantly increases livelihood. The Average Treatment Effect on the Treated (ATT) shows that participation in soybean CF significantly improves their total livelihood score (ATT = 0.028, p < 0.05) and enhances food security. The transitional heterogeneity value (ATT − ATU = 0.017) indicates that those smallholder farmers who participated were the most likely to expereince positive impacts. This study concludes that CF is an effective system for livelihood enhancement. To fully realize this potential, policymakers must invest heavily in localizing and scaling up agricultural extension services to counteract the cooperative penalty. Furthermore, to address the negative effect of labour role and household size, CF models must be revised to provide group-based, flexible contract terms or promote mechanization.
Youth self-employment is widely promoted as a strategy to address persistent unemployment in developing countries. However, engagement in self-employment is influenced not only by individual initiative but also by broader socio-political and institutional contexts. In Ethiopia, previous studies have largely focused on economic and personal factors while giving limited attention to the socio-political conditions that enable or constrain youth employment choices. Addressing this gap, this study examines the socio-political determinants of youth self-employment in Hosanna City, Ethiopia, using cross-sectional survey data from 437 economically active youth. A multinomial logistic regression model estimates the likelihood of self-employment and wage employment relative to unemployment. The results indicate that human capital and social resources, including prior work experience, family support, exposure to role models, and youth organization membership, significantly increase the likelihood of self-employment. Conversely, limited access to training, inadequate workspaces, parental unemployment, and unfavorable policy environments reduce participation. These findings suggest that youth self-employment is embedded within broader socio-political and institutional ecosystems, rather than being solely an individual or market-driven choice. The study calls for integrated interventions that combine skills development, access to productive infrastructure, strengthened social support systems, and institutional reforms to promote inclusive and sustainable youth employment in urban Ethiopia.
