Background Inadequate glycemic management in type 2 diabetes Mellitus patients is a serious public healthissue and a key risk factor for progression as well as diabetes-related complications. The main therapeutic goal ofpreventing organ damage and other problems caused by diabetes is glycemic control. Knowing when to modifyglycemic control in type 2 diabetes Mellitus is crucial for avoiding complications and early drug intensifications.Methods An institutional based retrospective follow-up study was undertaken among 514 eligible adult diabetespatients in Amhara region Comprehensive Specialized Hospitals, Northwest Ethiopia, from January 2017 to January2022. Simple random sampling technique was used to select study participants. The Kaplan Meier curve was usedto assess the survival status of categorical variables, and the log-rank test was used to compare them. The coxproportional hazard model was fitted to identify the predictors of time to first optimal glycemic control. Variables witha p-value < 0.05 were considered to be statistically significance at 95% confidence interval.Results A total of 514 patient records (227 males and 287 females) were reviewed in this study. The median time tofirst optimal glycemic control among the study population was 8.4 months IQR (7.6–9.7). The predictors that affect thetime to first optimal glycemic control were age group ((AHR = 0.63, 95% CI = 0.463, 0.859 for 50–59 years), (AHR = 0.638,95% CI = 0.471, 0.865 for 60–69 years), and (AHR = 0.480, 95% CI = 0.298, 0.774 for > = 70 years)), diabetes neuropathy(AHR = 0.629, 95% CI = 0.441,0.900), hypertension (AHR = 0.667, 95% CI = 0.524, 0.848), dyslipidemia (AHR = 0.561, 95%CI = 0.410, 0.768), and cardiovascular disease (AHR = 0.681, 95% CI = 0.494, 0.938).Conclusion The median time to initial optimal glycemic control in type 2 diabetes Mellitus patients in this study wasshort. Age between 50 and 59 years and 60–69, diabetes neuropathy, hypertension, dyslipidemia, and cardiovascular
disease were predictor’s of time to first glycemic control. Therefore, health care providers should pay extra attentionfor patients who are aged and who have complications or co-morbidities.Keywords: Adults, First optimal glycemic control, Type 2 diabetes mellitus, Ethiopia

BackgroundAdverse drug reaction is one of the emerging challenges in antiretroviral treatment. Deter-mining the incidence rate and predictors among children on antiretroviral treatment (ART) isessential to improve treatment outcomes and minimize harm. And also, evidence regardingthe time to major adverse drug reactions and its predictors among children on antiretroviraltreatment is limited in Ethiopia.ObjectiveThis study aimed to assess the time to major adverse drug reaction and its predictorsamong children on antiretroviral treatment at selected public hospitals in Northwest Amhara,Ethiopia, 2023.MethodA retrospective cohort study was conducted among 380 children on antiretroviral treatmentwho enrolled from June 27, 2017, to May 31, 2022. Data was collected using a structureddata extraction checklist. Data were entered into Epidata 4.6 and analyzed using STATA14. The incidence rate of major adverse drug reactions was determined per person/months.The Cox proportional hazards regression model was used to identify predictors of majoradverse drug responses. A p-value less than 0.05 with a 95% CI was used to declare statisti-cal significance.
ResultThe minimum and maximum follow-up time was 6 and 59 months, respectively. The studyparticipants were followed for a total of 9916 person-months. The incidence rate of majoradverse drug reactions was 3.5 /1000 person–months. Advanced clinical stages of HIV/AIDS (III and IV) [adjusted hazard ratio = 7.3, 95% CI: 2.74–19.60)], poor treatment adher-ence [adjusted hazard ratio = 0.33, 95% CI: 0.21–0.42], taking antiretroviral treatment twiceand more [adjusted hazard ratio = 3.43, 955 CI: (1.26–9.33)] and not taking opportunisticinfection prophylaxis [adjusted hazard ratio = 0.35, 95% CI: 0.23–0.52)] were predictors ofmajor adverse drug reactions.ConclusionThe incidence rate of major adverse drug reactions among children on antiretroviral treat-ment was congruent with studies in Ethiopia. Advanced clinical stages of HIV/AIDS, poortreatment adherence, taking antiretroviral treatment medications twice or more, and not tak-ing opportunistic infection prophylaxis were predictors of major adverse drug reactions.

AbstractThis study investigated the factors influencing growers in the selection of seed suppliers in theAmhara region of Ethiopia. A total of 385 grower were selected using simple random sam-pling method. A mixed logit regression model was used to the analysis data that have 1284observation. The result reveal that high seed purity was negatively related to the selectionof alternative supplier. As the rating of seed purity increased, the probability of selectingvery high-quality seed suppliers also increased. The availability of tree seeds during the desiredtime period had a significant influence. Higher perceived availability, categorized as high orvery high, decreased the likelihood of promptly obtaining seeds from suppliers comparedto when the seeds were not available. The evaluation rating of germination increases the prob-ability of choosing suppliers with high or very high germination rates in the respective cat-egory. Growers with more experience are more likely to choose private enterprise suppliers.The implementation of appropriate quarantine measures has a positive influence on supplierselection for the groups AFE and EFD-CEC. Training in tree seed collection reduces the like-lihood of choosing enterprise and AFE suppliers. Moreover, the successful production of agreater number of tree species in the nursery positively influences the probability of sourcingfrom enterprise suppliers. This analysis highlights the significance of seed purity, germination,quarantine measures, and the number of species produced, as factors that influence the like-lihood of selecting alternative seed suppliers.
Keywords: growers; mixed logit regression; tree seed suppliers; tree seed

Background: An estimated 75.8 under-five deaths per 1000 live births occurred in sub-Saharan Africa. This study aimed to investigate the prevalence and factors associated with under-five mortality in Sub-Saharan Africa. Methods: This study was based on secondary data sources from 33 Sub-Saharan countries’ recent Demography and Health surveys from 2010 to 2020. A weighted sample of 360,397 under-five children was included in the study. Bayesian multilevel binary logistic regression was fitted using the brms R package. Besides, leave one out information criteria was used for model comparison. The adjusted odds ratio (AOR) and its 95% credible interval (CrI) were reported for significant factors associated with under-five mortality. Clinical trial number: not applicable. Results: The prevalence of under-five mortality in sub Saharan Africa was 62 per 1000 live births (95%CI (56.29, 68.29). In sub region of SSA, it was 65 in central, 52 in eastern, 50 in southern and 73 in western region per 1000 live births. Multiple birth (AOR = 5.27; 95%CrI: 4.72, 5.87), number of under-five children 3 to 5 (AOR = 3.31; 95%CrI: 3.01, 3.60), caesarean section delivery (AOR = 1.64; 95%CrI: 1.47, 1.83), being unmarried (AOR = 1.16; 95%CrI 1.08, 1.26), using unimproved toilet (AOR = 1.08;95%CrI: 1.02, 1.16), birth order of 4th to 6th (AOR = 1.18; 95%CrI:1.1, 1.25),were risk factors of under-five mortality. Whereas, being female (AOR = 0.86; 95%CrI: 0.82, 0.91), preceding birth interval of 24–35 months (AOR = 0.61; 95%CrI: 0.57, 0.65) and above 36 months (AOR = 0.48; 95%CrI: 0.43, 0.49), ANC visit (AOR = 0.80; 95%CrI: 0.74 0.86), contraceptive use (AOR = 0.57; 95%CrI: 0.53, 0.61), were preventive factors of under-five mortality. Conclusion: Under-five mortality remains the highest in sub-Saharan Africa. Most of the risk factors of under-five mortality were found to be preventable. Policymakers and other stakeholders should enhance maternal education, lengthen birth interval, ANC visit, improved toilet facilities and, giving special attention to small size child and cesarean section delivery to reduce under-five mortality. Keywords: Under-five mortality, Associated factors, Bayesian, Sub-saharan Africa, DHS

Extreme flood and drought events arise from temporal and spatial variations in the Earth’s water cycle, signif-icantly affecting water resources and the environment. This review aimed to evaluate the effects of climatevariabilities on extreme flood and drought events within the Blue Nile Basin. A systematic literature review andcontent analysis were conducted to understand the hydrological dynamics of floods and droughts. A Scopusdatabase was used to find relevant literature review articles related to flood and drought extreme events usingsearch terms queries. The findings suggest that rising temperatures and fluctuating precipitation patterns areleading to more frequent and severe floods and droughts. Future projections also suggest increased droughtseverity in most basin areas, coupled with more frequent floods. Fluctuations between dry and wet conditionshave intensified these extremes. While insufficient rainfall triggers droughts, excessive and concentrated rainfallcontributes to floods. The wet projection shows more frequent floods, while the dry projection indicates severedroughts throughout most of the basin. This review provides a valuable starting point for further action towards amore climate-resilient and water-secure for sustainable environmental development and management over thebasin.
Keywords: BNB, Climate variability, Hydrological extremes, Water resource

Introduction Post-surgical recovery time is influenced by various factors, including patient demographics, surgicaldetails, pre-existing conditions, post-operative care, and socioeconomic status. Understanding these dynamics iscrucial for improving patient outcomes. This study aims to identify significant predictors of post-surgical recoverytime in a resource-limited Ethiopian hospital setting and to evaluate the variability attributable to individual patientdifferences and surgical team variations.Methods A linear mixed model was employed to analyze data from 490 patients who underwent various surgicalprocedures. The analysis considered multiple predictors, including age, gender, BMI, type and duration of surgery,comorbidities (diabetes and hypertension), ASA scores, postoperative complications, pain management strategies,physiotherapy, smoking status, alcohol consumption, and socioeconomic status. Random effects were included toaccount for variability at the patient and surgical team levels.Results Significant predictors of prolonged recovery time included higher BMI, longer surgery duration, thepresence of diabetes and hypertension, higher ASA scores, and major post-operative complications. Opioid painmanagement was associated with increased recovery time, while inpatient physiotherapy reduced recovery duration.Socioeconomic status also significantly influenced recovery time. The model fit statistics indicated a robust model,with the unstructured covariance structure providing the best fit.Conclusion The findings highlight the importance of individualized patient care and the effective management ofmodifiable factors such as BMI, surgery duration, and postoperative complications. Socioeconomic status emerged asa novel factor warranting further investigation. This study underscores the value of considering patient and surgicalteam variability in post-surgical recovery analysis, and calls for future research to explore additional predictors andalternative modeling techniques to enhance our understanding of the recovery process.Keywords Postsurgical recovery, Linear mixed model, BMI, Surgery duration, Comorbidities, ASA scores,Postoperative complications, Pain management, Physiotherapy, And socioeconomic status

in ethiopia, urbanization and urban violence are recent phenomena dating back to thebeginning of the twentieth century. in the country’s long history, politics and urbanviolence have been bedfellows and reliable means of change, devolution, and reform.Since 1916, ethiopia has essentially experienced more violence in its urban’s than in itsrural areas due to recurrent episodes of political instability at the national level.ironically, ethiopian leaders were amateurs who were unable to draw lessons from theirpast deeds. Nevertheless, ethiopian historiography has devoted little attention to themagnitude of political issues-related urban violence in ethiopia. As a result, the paperattempted to analyse two goals. First, it tries to analyse the historical events of ethiopianurban violence from 1916–1991, and secondly, it tries to explain the tradition ofethiopian leaders to learn from past deeds. to document this extraordinary theme, thepaper grey on both primary sources and published secondary literature that have beenavailable to the writer to date. the collected data was systematically verified, analyzed,and interpreted through qualitative data analysis.
KEYWORDS: history; urban violence; ethiopia; dilettante

Background: Edible oil manufacturing is a labor-intensive sector with significanttechnological demands, where employees face various occupational hazards.The use of personal protective equipment (PPE) is not only a legal obligationbut also a key measure for safeguarding workers against job-related injuriesand health risks. Despite these challenges, this industry often remainsunder-researched and overlooked.Objective: To assess utilization of personal protective equipment and its keyfactors among workers in the WA edible oil factory in Debre Markos town,Ethiopia, in 2024.Methods: A cross-sectional study was conducted among employees of theWA Edible Oil Factory in Debre Markos. Using a simple random samplingmethod, 387 workers were selected to participate. Data were collectedthrough an interviewer-administered structured questionnaire, focusing on theuse of protective equipment, as well as socio-demographic, work-related,environmental, and organizational characteristics. The data were analyzed usingSPSS version 26. Logistic regression analysis was employed to identify factorsinfluencing the use of protective equipment, with the strength of associationsexpressed as odds ratios at a 95% confidence level.Results: Out of the total workforce, 214 individuals (55.3%) reportedusing personal protective equipment while on duty. The study identifiedseveral significant factors influencing personal protective equipment utilization,including receiving safety training, having access to protective equipment,regular occupational health and safety inspections, the presence of workplacesafety protocols, having three or more years of work experience, and abstainingfrom alcohol consumption and smoking.Conclusion: The utilization level of personal protective equipment amongworkers at the WA edible oil factory was found to be moderate when comparedto findings from other developing countries. Key factors influencing personalprotective equipment usage included access to safety training, availability ofprotective gear, workplace supervision, the presence of safety protocols, workexperience, and lifestyle behaviors such as alcohol and tobacco use. To improvepersonal protective equipment utilization, it is recommended to strengthenworkplace supervision, offer comprehensive safety training, and ensure theconsistent availability of safety guidelines.KEYWORDSutilization, personal protective equipment, edible oil factory, factory worker, Ethiopia

Improving maternal and perinatal outcomes can be achieved by identifying factors affecting successful vaginal delivery following induction of labor, particularly in developing countries with low rates of induction. Besides this, evidence regarding the magnitude of successful vaginal delivery following induction and associated factors is limited in Ethiopia. Therefore, this study aimed to assess the magnitude of vaginal delivery following induction and associated factors among laboring women at South Wollo Zone Public Hospitals of Ethiopia, 2023. An institutional-based cross-sectional study was conducted among 385 from April 1 to June 15, 2023. A systematic random sampling method was used to select each participant. A pretested structured interviewer-administered questionnaire and checklist were used to collect data. Epi-Data version 4.6 and SPSS version 26 software were used for data entry and analysis, respectively. Multivariable binary logistic regression was used to identify associated factors and an adjusted odds ratio with a 95% confidence interval was used to identify significant variables. Model fitness was checked using the Hosmer-Lemeshow goodness of fit test. The study reported that 75.6% of participants gave vaginal delivery following induction with a 95% CI (71.00-79.80). Mid-upper arm circumstance 23-28 cm (AOR = 2.55, 95% CI: 1.19-5.47), multiparty (AOR = 3.01, 95% CI: 1.430-6.33), favorable bishop (AOR = 3.79, 95% CI: 1.74-8.26), oxytocin with cervical ripening method (AOR = 3.74, 95% CI: 1.99-7.04), and birth weight less than 4000gram (AOR = 5.40, 95% CI: 1.54-18.91) were factors significantly associated with successful vaginal delivery following induction. Therefore, obstetric caregivers should consider pre-induction assessments such as bishop score of the cervix and fetal weight estimation and improving the nutritional status of pregnant women.

Keywords: Associated factors; Ethiopia; Induction of labor; Vaginal delivery.

In engineering applications, the bearing faults diagnosis is essential for maintaining reliability andextending the lifespan of rotating machinery, thereby preventing unexpected industrial productiondowntime. Prompt fault diagnosis using vibration signals is vital to ensure seamless operation ofindustrial system avert catastrophic breakdowns, reduce maintenance costs, and ensure continuousproductivity. As industries evolve and machines operate under diverse conditions, traditional faultdetection methods often fall short. In spite of significant research in recent years, there remains apressing need for improve existing methods of fault diagnosis. To fill this research gap, this researchwork aims to propose an efficient and robust system for diagnosing bearing faults, using deep andShallow features. Through the evaluated experiments, our proposed model Multi-Block Histogramsof Local Phase Quantization (MBH-LPQ) showed excellent performance in classification accuracy, andthe audio-trained VGGish model showed the best performance in all tasks. Contributions of this workinclude: Combine the proposed Shallow descriptor, derived from a novel hand-crafted discriminativefeatures MBH-LPQ, with deep features obtained from VGGish pre-trained of Convolutional NeuralNetwork (CNN) using audio spectrograms, by merging at the score level using Weighted Sum (WS).This approach is designed to take advantage of the complementary strengths of both feature models,thus enhancing overall bearing fault diagnostic performance. Furthermore, experiments conductedto verify the approach’s performance is assessed based on fault classification accuracy demonstrateda significant accuracy rate on two different noisy datasets, with an accuracy rate of 98.95% and 100%being reached on the CWRU and PU datasets benchmark, respectively.Keywords: Bearing fault diagnosis, Vibration signals, Transfer learning, Shallow descriptor, Deep features,MBH-LPQ, VGGish, CNN