Debark University

Iron-Folic Acid (IFA) is a crucial process indicator, that helps to halt the burden of iron deficiency anemia worldwide, especially in low and middle income countries like Ethiopia. Iron-folic acid supplementation is a crucial method in Ethiopia to reduce maternal deaths from anemia and poor birth outcomes. Despite these initiatives, there is still extremely little adherence to IFA consumption for the 90-day or more WHO-recommended timeframe. Therefore, the aim of this study was to use the DHS 2016 information to create a predictive model for IFA consumption and figure out the key factors influencing it among Ethiopian pregnant women. A secondary data analysis of Ethiopian DHS from 2016 was performed. A total weight of sample of 3109 women (15–49) was included in this study. Data were extracted using STATA version 17 software, and imported to a Jupyter notebook for further analysis. Machin learning algorithm using different classification models were implemented. All analysis and calculation were performed using Python 3 programming language in Jupyter Notebook using imblearn, sklearn, xgboost, and shap packages. Random Forest demonstrated the best performance with accuracy of 92.93%, precision of 91.32%, recall of 94.77%, F1-score of 93.99% and AUC 94%. Region, distance to health facility, age at first marriage, household head, number of ANC visit, media exposure, community literacy, husband occupation, gravidity, family size were top predicting factors of IFA utilization among women in Ethiopia. Random Forest were best predictive models with improved performance. Highly predicting factors of IFA utilization were identified using machine learning algorithms particularly random forest. These findings can guide policymakers and program managers to target interventions more effectively, promote ANC attendance, enhance community literacy and address household-level determinants to improve IFA supplementation rates. However, as the analysis is based on cross-sectional survey data, causal inferences cannot be made.

ABSTRACT Energy poverty remains a major challenge of the 21st century. It reflects a trade‐off between satisfying current energy demands and protecting the environment. Similarly, in North Gondar, the sector continues to challenge socioeconomic development and adversely affects household health and the environment, with limited progress in switching to clean energy sources. Household fuel preference plays a central role in shaping this transition. This study examined the extent of solid biofuel usage and household energy choice behavior in Northwest Ethiopia, using data collected from 384 randomly selected households and a multivariate probit model to capture the interrelated nature of fuel choices. The results indicate a heavy reliance on solid biomass, which accounts for 90% of cooking energy use and 76% of lighting energy consumption. Empirical findings reveal that households living in urban areas, with higher incomes and better educational backgrounds, are more likely to adopt cleaner energy sources. Older households, those living far from markets, and households with larger livestock holdings continue to rely on traditional biomass fuels. The study concludes that household energy choice in the area follows a fuel‐stacking pattern rather than a simple linear transition along the energy ladder. On the basis of the insights, the study recommends strengthening public awareness campaigns, prioritizing pro‐poor energy transition measures, supporting afforestation efforts, and promoting environmentally friendly biomass practices to improve household energy use and accelerate the transition to clean energy sources in Northwest Ethiopia.

Dry forests in Ethiopia, spanning 55 million hectares, are vital for local livelihoods through resin resources, particularly frankincense from Boswellia papyrifera. However, unsustainable harvesting, compounded by socio-economic pressures and limited regeneration, has led to a significant population decline. This study, conducted in Ethiopia's Metema District, examines the ecological status of Boswellia papyrifera and compares harvesting practices between cooperatives and private enterprises to identify management sustainability challenges. A forest inventory utilized 22 plots (400 m2 each) and a survey was administered to 80 harvesters selected by stratified random sampling. The chi-squared test and the independent samples t-test were applied for categorical and continuous variables respectively. The population structure showed a marked instability and limited regeneration potential. Tree density of Boswellia papyrifera was significantly higher in cooperative forests (146.6 stems/ha) than in private concessions (126.57 stems/ha) (p = 0.010). Private sector harvesters exhibited significantly more damaging practices, including a higher proportion of tapping small trees (DBH < 15 cm), lower tapping height, and more dead trees, suggesting a focus on short-term gain over ecological preservation. Specifically, 65% of private sector trees had over 12 tapping spots, compared to 25.1% in the cooperative sector (p = 0.004). Furthermore, 86% of private tappers reported not allowing trees to rest (p = 0.001). The commercial sector's intensive practices and harvesters' limited knowledge (only 42.9% of private employees formally trained) are major obstacles. To ensure the long-term survival of Boswellia papyrifera, we recommend strict enforcement of harvesting quotas, mandatory training for private sector tappers, and the establishment of statutory resting periods for tapped trees.

Dortinia barnimiana is an indigenous plant celebrated for its traditional medicinal uses, especially in treating infectious diseases. Rich in bioactive compounds like phenolics and flavonoids, it exhibits notable antioxidant and antibacterial properties. As interest in indigenous plants grows, D. barnimiana stands out as a promising candidate for addressing modern health challenges, including antibiotic resistance and the pursuit of sustainable healthcare solutions. This study examines how different solvents (ethanol, ethyl acetate, and petroleum ether) impact the extraction of phenolics, flavonoids, and the antioxidant and antibacterial properties of D. barnimiana. Crude plant extracts were prepared using the maceration technique. Total phenolic content was assessed using the Folin-Ciocalteu method, while total flavonoid content was measured through the aluminum chloride complex formation assay. The antioxidant activity was evaluated using the DPPH free radical scavenging method and ferric reducing power assay. Antibacterial efficacy was tested against both Gram-positive and Gram-negative strains using the agar well diffusion method, with minimum inhibitory concentrations (MIC) and minimum bactericidal concentrations (MBC) determined via broth microdilution. Data were analyzed using Analysis of Variance (ANOVA). Ethanol extracts exhibited the highest phenolic content (185.16 ± 0.65mg GAE/g dry weight) and flavonoid content (141.1 ± 0.75mg CE/g dry weight). The highest DPPH radical scavenging activity was also found in the ethanol extract (78.46 ± 0.41µg/mL). Notably, the highest antibacterial activity was against Staphylococcus aureus (20.66 ± 0.57mm) at 50mg/mL, while Pseudomonas aeruginosa showed the lowest inhibition zone (0.33 ± 0.57mm) at 6.25mg/mL. The extracts demonstrated significant inhibitory effects, particularly against S. aureus, with an MIC of 6.25mg/mL. Ethanol emerged as the most effective solvent for extracting D. barnimiana leaves, showcasing impressive antioxidant and antibacterial properties that suggest potential applications in pharmaceuticals. Further research is essential to isolate and characterize the active compounds for the development of new therapeutic agents.

Abstract Despite the importance of common bean as a cash crop, research and development have given limited attention to the indeterminate climbing bean. As a result, its productivity has remained low due to a lack of improved varieties. Hence this study was undertaken to estimate the extent of genetic variability, heritability, genetic advance, and associations of yield and yield contributing to 12 quantitative traits of indeterminate climbing common bean genotypes. The study used forty-nine genotypes of indeterminate- climbing type of common beans with a 7x7 triple lattice design. Variance analysis revealed a highly significant difference among 49 genotypes of beans for twelve morphological traits (&lt; 0.01) under study. The coefficient of variation, both at the phenotypic and genotypic levels, indicated significant differences among the genotypes for measured traits. The result revealed that estimates of heritability (%) in a broad sense for 12 traits studied, ranged from (23.73%) to (85.85%) for seed per plant and hundred seed weight respectively. Genetic advance estimation in this study revealed that plant height, pod per plant, branches per plant, biological yield, harvest index, 100-seed weight, and grain yield had high heritability estimates coupled with high genetic advance as a percentage of the mean. The correlation analysis revealed that grain yield had a highly significant and positive phenotypic correlation with plant height, pod length, pod per plant, seed per pod, seed per plant, branch per plant, hundred seed weight, biological yield, and significant positive phenotypic correlation with harvest index. Path coefficient analysis demonstrated that higher positive direct effects were exerted by biological yield harvest index and hundred seed weight on grain yield at phenotypic and genotypic levels. The study reveals significant genetic variability in indeterminate climbing common bean genotypes, highlighting the potential for selective breeding to enhance yield-related traits. By identifying high-performing genotypes, the research supports targeted breeding programs aimed at increasing productivity and benefiting smallholder farmers in Ethiopia.

Convolutional neural networks (CNNs) classify inverted eyelid images related to active trachoma. However, using these complex networks in medical service centers faces challenges due to computational resource constraints. To overcome this challenge, we propose a quantified feature map-based filter pruning framework (FSIM-SVD) that relies on feature similarity and feature map contributions. Based on these insights, our approach involves quantifying redundant feature maps using feature similarity (FSIM) and assessing the contribution of each feature map through singular value decomposition (SVD). By analyzing the impact of each component on the overall model performance, less significant filters can be identified and pruned. The experiment uses VGG16, ResNet56, and ResNet110 on the active trachoma and CIFAR10 datasets. The results reveal that VGG16 achieved an accuracy of 86.9% (+0.43% from the baseline) for active trachoma classification while reducing FLOPs by 28.6% and parameters by 33.4%. In the CIFAR10 classification, ResNet110 achieved an accuracy of 94.31% (+0.73% from the baseline) with a 43.8% reduction in FLOPs and a 43.1% reduction in parameters. Compared to state-of-the-art compression techniques, the proposed approach achieves a higher pruning rate and improved classification performance.

Abstract The ecological and financial effects of tapping methods are the main emphasis of this study, which examines the sustainability of frankincense production from Boswellia papyrifera in Ethiopia's Metema District. The region's resin resources, especially those derived from Boswellia, are essential for local livelihoods because Ethiopia's dry woods span 55 million hectares. However, Boswellia populations have significantly declined as a result of unsustainable tapping practices, endangering their ecological viability. Plots measuring 400 m2 were placed in a transect line for the forest inventory. Eighty respondents were chosen using the stratified random sampling technique. The chi-squared test and the independent samples t-test were applied. The demographic structure showed a limited ability for regeneration, as the study reveals. In the Boswelliya forest, the tree densities harvested by private companies and cooperatives were, respectively, 126.57 and 146.6 stems/ha. Data show concerning patterns of over-tapping, with private sector trees frequently undergoing excessive incisions and improper tapping heights, which raises mortality rates. While 53.8% of cooperative members receive formal training, just 42.9% of private sector employees do, indicating a serious knowledge gap among harvesters about sustainable practices, according to the report. Knowledge gaps, cultural resistance, and financial limitations are some of the obstacles to implementing sustainable practices. Cooperatives are essential for training and resource provision, but the commercial sector's emphasis on short-term gains makes sustainability issues worse. In order to guarantee the long-term survival of Boswellia papyrifera, the study emphasizes the critical necessity for focused conservation initiatives and the application of sustainable harvesting practices.