Background Understanding the student’s perspective of their clinical learning environment (CLE) might assist todiscover solutions to improve the learning process and increase engagement. However, there is a lack of informationon this issue, particularly in Ethiopia. The purpose of this study was to assess the satisfaction of undergraduatemedical and health science students with their clinical learning environment, as well as to identify the factors thataffect it.Methods Institutional-based cross-sectional study was conducted using a self-administered questionnaire among412 medical and health science students from Debre Markos University in 2023 through a simple random samplingtechnique. Mean, median, frequencies, and percentages were used to describe the data. A multivariate logisticregression model was fitted to test the association of dependent and independent variables. The Hosmer-Lemeshowgoodness-of-fit test was used to check the fitness of the model. Variables with a p-value < 0.05 with a 95% confidenceinterval were considered statistically significant.Results The questionnaire was completed by 394 individuals in total, generating a response rate of 95.63%.Approximately half (49.7%) of the participants were satisfied with their CLE. Age (AOR = 1.12; 95%CI = 1.02, 1.22),university positive perceptions (AOR = 1.60; 95%CI = 1.04, 2.43) and curriculum positive perception (AOR = 2.70;95%CI = 1.73, 4.10) were all positively associated with CLE satisfaction.Conclusion In this study, approximately half of the respondents were satisfied with their CLE. Age, positiveperceptions of the university and positive perceptions of the curriculum were all positively associated with CLEsatisfaction. The university and clinical facilitators should work together to improve infrastructure, and the facilities
 

Heavy metals pose a significant threat to public health and economic stability in Ethiopia,contaminating various environmental media, including water, soil, and air. This paper aimed toprovide an overview of the public health and economic burden of heavy metals in Ethiopia.Exposure to heavy metals such as lead, mercury, cadmium, and arsenic has been linked tonumerous adverse health effects, including neurological disorders, renal failure, cardiovasculardiseases, and cancer. In Ethiopia, populations are particularly vulnerable to heavy metal exposuredue to various factors, such as artisanal mining, industrial activities, agricultural practices, andinadequate waste management systems. The economic burden of heavy metal contaminationmanifests through increased healthcare costs, loss of productivity, and environmental remedia-tion expenses. Furthermore, the impact extends to sectors such as agriculture and tourism,affecting national development goals and exacerbating poverty levels. Efforts to mitigate thepublic health and economic burdens of heavy metals in Ethiopia require multidisciplinary ap-proaches, including policy interventions, regulatory enforcement, public awareness campaigns,and investment in sustainable development practices. Strengthening monitoring systems,implementing pollution control measures, and promoting research on alternative technologies forwaste management are essential steps toward addressing this pressing issue. In conclusion,addressing the public health and economic challenges posed by heavy metal contamination inEthiopia necessitates concerted efforts from the government, industry, academia, and civil societyto safeguard human health, preserve the environment, and promote sustainable development.
Keywords: Economic burden, Heavy metals, Lead, Public health, Strategies

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.

This study investigates how effectively Intergovernmental Authority on Development (IGAD) has addressed the crisis in Somalia since 1991, using realism theory as its analytical framework. It employs a qualitative case study approach to delve into IGAD's interventions and their implications, conducting an in-depth analysis of IGAD's official documents, resolutions, and crisisrelated reports concerning Somalia. By applying realism theory, the study scrutinizes IGAD's actions and motivations from a perspective centered on power politics, highlighting the significance of state interests and regional stability. It suggests that IGAD member states may resist to cooperate when they perceive IGAD's engagement in Somalia is regarded as a threat to their security interests. Despite IGAD's numerous peace initiatives, achieving sustainable peace in Somalia remains elusive. The paper asserts that while IGAD has made substantial efforts to resolve the Somalia conflict, its effectiveness has been constrained by the complexity of the conflict, external influences, and divergent interests among member states. To enhance IGAD's effectiveness, the study recommends various actions, including promoting regional economic integration, mobilizing external resources, improving transparency and accountability, fostering regional identity and solidarity, and maintaining a balanced power dynamic to prevent dominance by any single entity. Applying these measures could significantly improve IGAD's capacity to support peace and stability in Somalia and the entire East Africa region.
 

Background: Big health data is a large and complex dataset that the health sector has collected andstored continuously to generate healthcare evidence for intervening the future healthcare un-certainty. However, data use for decision-making practices has been significantly low in devel-oping countries, especially in Ethiopia. Hence, it is critical to ascertain which elements influencethe health sector’s decision to adopt big health data analytics in health sectors. The aim of thisstudy was to identify the level of readiness for big health data analytics and its associated factorsin healthcare sectors.Methods: A cross-sectional study design was conducted among 845 target employees using thestructural equation modeling approach by using technological, organizational, and environ-mental (TOE) frameworks. The target population of the study was health sector managers, di-rectors, team leaders, healthcare planning officers, ICT/IT managers, and health professionals.For data analysis, exploratory factor analysis using SPSS 20.0 and structural equation modelingusing AMOS software were used.Result: 58.85 % of the study participants had big health data analytics readiness. Complexity (CX),Top management support (TMS), training (TR) and government law policies and legislation(GLAL) and government IT policies (GITP) had positive direct effect, compatibility (CT), andoptimism (OP) had negative direct effect on BD readiness (BDR)Conclusion: The technological, organizational, and environmental factors significantly contributedto big health data readiness in the healthcare sector. The Complexity, compatibility, optimism,Top management support, training (TR) and government law and IT policies (GITP) had effect onbig health data analytics readiness. Formulating efficient reform in healthcare sectors, especially
or evidence-based decision-making and jointly working with stakeholders will be more relevantfor effective implementation of big health data analytics in healthcare sectors.
Keywords: Big health data, Data analytics, Data management, Health information revolution, Health sectors, Readiness

Introduction: Currently, mortality by non-communicable diseases is increasing alarmingly. They account for approximately 35 million deaths each year, of which 14% are due to cardiovascular disease and 9.2% occur in Africa. Patients do not have access to healthcare services outside the healthcare setting, resulting in missed follow-ups and appointments and adverse outcomes. This study aimed to assess the willingness to use remote monitoring among cardiovascular patients in a resource-limited setting in Ethiopia.
Method: An institution-based cross-sectional study was conducted from April to June 2021 among cardiovascular patients at referral hospitals in Ethiopia. A structured interview questionnaire was used to collect the data. A systematic random sampling technique was used to select 397 study participants. Binary and multivariable logistic regression analyses were employed and a 95% confidence level with a p-value

Induction motor drives with variable speed applications that employ vector control are quitepopular nowadays because they provide strong dynamic performance and flexible speed control.By decoupling the torque-producing current components of stator current from the rotor flux,Indirect Field Oriented Control is recognized for generating excellent performance in inductionmotor drives. This investigation is being done to show the effectiveness of the novel FPI input-output data-trained ANFIS controller and compare the three controllers’ performance in termsof load variation capabilities, motor parameter variation, and speed tracking. Consequently, acomparison of the three controllers is important to select which controller performs high in in-duction motor drive. Indirect Field Oriented Control of induction motor with Fractional Pro-portional Integral (FPI), Integer Proportional Integral (IPI), and Adaptive Neuro-Fuzzy InferenceSystem (ANFIS) controllers are all discussed in this work along with their designs and compar-ative analysis. The square of error was used as a fitness function to genetically optimize the FPIand IPI controller parameters. The suggested Adaptive Neuro-Fuzzy Inference System (ANFIS)controller uses a hybrid learning approach. It is trained by the FPI controller’s input-output data.Using the results of MATLAB simulations under various operating situations, the performance ofthe ANFIS controller was compared with FPI and IPI controllers. Because of FPI controller in-cludes an extra parameter for adjustment, namely integration order, it performed better than IPIcontroller for speed control of the induction motor. According to the simulation findings, thepercentage peak overshoots while employing ANFIS, FPI, and IPI controllers were 0.495 %,12.062 %, and 14.699 % respectively. As a result, ANFIS exhibits a drastic reduction in overshoot.Additionally, with the ANFIS controlled induction motor drive, the speed achieves the requiredset value at 0.14 s. For no load, constant, and changing loads, the induction motor drive’s per-formance has been examined.
Keywords: Induction motor, Indirect field oriented control, Fractional PI, ANFIS, Integer PI

Melioidosis is a significant health problem in tropical and subtropical regions, especially inSoutheast Asia and Northern Australia. Recurrent melioidosis is a major obstacle to eliminatingthe disease from the community in these nations. This work aims to propose and analyzea human melioidosis model with recurrent phenomena and an optimal control model byincorporating time-dependent control functions. The basic reproduction number (𝑅0) of theuncontrolled model is derived using the method of the next-generation matrix. Using theconstruction of a Lyapunov functional, we present the global asymptotic dynamics of theautonomous model in the presence of recurrent for both disease-free and endemic equilibria. Theglobal asymptotic stability of the model’s equilibria shows the absence of a backward bifurcationfor the model in both cases, whether in the absence or presence of relapse. The sensitivityanalysis aims to identify the parameters that have the most significant impact on the model’sdynamics. Furthermore, qualitative analysis of the model’s global dynamics and the changingeffect of the most influential parameters on 𝑅0 are supported by numerical experiments, with theresults being illustrated graphically. The model with time-dependent controls is analyzed usingoptimal control theory to assess the impact of various intervention strategies on the spread ofthe epidemic. The numerical results of the optimality system are carried out using the Forward–Backward Sweep method in Matlab. We also conducted a cost-effectiveness analysis using twoapproaches: the average cost-effectiveness ratio and the incremental cost-effectiveness ratio.
Keywords: Melioidosis model; B.pseudomallei; Recurrent; Global stability; Optimal control; Cost-effective strategy

Method Twenty inactive males (BMI 27.67 ± 0.88 kg/m2 , age 49.15 ± 2.58 years) participated in an eight-week wererandomly assigned to one of three intervention groups (combined (CT), resistance (RT), and aerobic (AT)) exercisemodalities to assess within-subject and between group changes in glycolipid profile. Data were analyzed usingrepeated measures ANCOVA.Result Pre-post mean values of body fat percentage (%BF), area under the curve (AUC), low density lipoprotein (LDL),high density lipoprotein (HDL) and total cholesterol (TC) decreased in all three groups. The main effect of exercisemodality on the AUC (F (2, 26) = 10.577, P = 0.001, η2 = 0.569) was significant. Post-hoc analyses revealed that the RTgroup (-30.653 ± 6.766, p = 0.001) with 11.53% and the CT group (M = -0.896, SE = 3.347, P = 0.015) with 3.79% exhib-ited significantly greater reductions in AUC compared to the AT group. LDL levels showed significant differentbetween groups (F (2, 26) = 6.33, p = 0.009, η2 = 0.442), specially significantly 3.7% lowered in AT (MD = 4.783, SE = 1.563,P = 0.002) and 3.79% lower in CT (MD = 4.57, SE = 1.284, P = 0.008) groups compared to the RT group. AT significantlyreduced TC by 17.716 ± 5.705 mg/dL (p = 0.02) compared to RT, representing a 7.97% decrease.Conclusion Exercise type significantly influences lipid profiles and glycemic control. Notably, both aerobic and com-bined training demonstrated a superior ability to modulate the lipid profile, and resistance training and combinedtraining were more effective in reducing the AUC.Trial registration May, 31st 2024. Registration no: PACTR202405463745521 “Retrospectively registered”.Keywords Glucose tolerance, Lipid profile, Resistance training, Aerobic training and combind training

Teff, a versatile crop, serves both as a food source and a cash crop in ethiopia. it is recognizedfor its potential to enhance the income of smallholder farmers, improve food security, andcontribute to sustainable development goals. This study aims to assess the impact of Teffcommercialization by smallholder farmers on food security. Both primary and secondary datawere used using the 2020/2021 cropping season. a three-stage sampling procedure was usedto draw 352 sample households. Food security was assessed using proxy indicators: householddietary diversity and food consumption score. The descriptive statistical results showed that182 (51.7%) and 170 (48.3%) sample households were subsistence, and commercializedhousehold heads respectively. notably, commercial farmers exhibited better household dietarydiversity (91.2%), whereas subsistence farmers scored lower in terms of food consumption(29.1%). Male household headship reduced hddS for commercializing farmers (−1.6); creditusage boosted hddS for commercialized groups (1.1), and livestock ownership improvedhddS for subsistence groups (0.21) in the second-stage endogenous switching regression.The model result also showed that, Teff commercialization positively impacted hddS and FcS,with average treatment effects of 3.81 and 4.46, respectively. Transitional heterogeneity resultsshowed that commercialized farmers had lower household dietary diversity (−0.47) and lowerfood consumption score (−14.19) than subsistence households. in light of these findings,encouraging smallholder farmers to transition from subsistence production to commercializationis crucial for supplementing their overall production. additionally, government efforts shouldfocus on raising awareness about nutrition-sensitive agricultural practices.
KEYWORDS: commercialization; endogenous Switching; Regression Model; Food Security; Smallholder; Teff