Abstract Over the years, agriculture in the Amhara region has faced challenges due to climate variability and change. In this regard, this paper aims to develop and adapt a crop selection dataset model for resilience to climate change. Wheat, maize, and teff data were investigated from the Central Statistics Agency of Ethiopia (CSA). Climate parameter data were taken from reanalysis models, satellites, and in situ sources. An Artificial Neural Network (ANN) model was applied to predict El Niño and La Niña events. The results reveal that the presence of El Niño leads to a reduction in wind speed and an increase in cloud base height (CBH), resulting in a precipitation deficiency. El Niño is weakening the trend winds and enhancing the cloud base height, leading to a deficiency of summer Precipitation. The crop selection model is developed to select a climate change resilience crop. The occurrences of El Niño enhance maize production in the midland farm areas. The average value of the crop selection dataset model parameters (slope ‘n’, intercept ‘a’, and the magnitude of the error ‘ ’) is found to be -1.937, 28.498, and 0.168, respectively, that satisfy the developed model requirements. The average error between the actual crop data and the model value is found to be -0.156 quintals per hectare. In general, the impact of El Niño on teff in middlealtitude areas is affected by 25.36%, while on wheat production in lowland areas is affected by 18.44%. However, maize production in the midland region is enhanced by 21.90%. In this sense, farmers in the middle-altitude areas use vast farmlands for maize during the El Niño phase. In the future, researchers made improvements on the draft crop selection dataset model and tailored it for use across the country via various scenarios. Keywords: Altitude, Artificial intelligence, Climate change, Crop model, El Niño-La Niña

Background: Managing chronic illness requires navigating a complex trajectory from diagnosis to end-of-life, with each phase necessitating specific nursing approaches. Effective management throughout these phases is vital for improving patient outcomes and quality of life.
Objective: This study aims to explore nursing approaches in managing chronic illness across its trajectory, from diagnosis to end-of-life care, focusing on phase-specific care, emotional support, education, interdisciplinary collaboration, and the challenges faced by nurses.
Methods: A qualitative research design using a grounded theory approach was employed to construct a theoretical framework grounded with the insights and experience of nurses' approaches across the chronic illness trajectory within Western Amhara, Ethiopia. The study comprised 24 nurses who were selected through the process of purposeful and theoretical sampling methods. Data was collected via in-depth interviews. Data analysis followed a constant comparative method, involving open, axial, and selective coding to identify key strategies and challenges across the illness trajectory.
Results: The primary finding of this study emphasizes the evolving and adaptive role of nurses in chronic illness management, highlighting their ability to provide personalized care, emotional support, and education throughout the illness trajectory. Central to the investigation is the theory of nurses' evolving and adaptive role in chronic illness management, where they adjust their strategies to address the physical, emotional, and psychological needs of patients and families, from pre-diagnosis to end-of-life care. The study identifies key adaptive strategies, including fostering resilience, facilitating interdisciplinary collaboration, and managing fluctuating symptoms. Despite challenges such as heavy workloads and emotional strain, nurses require training for continuous professional development, technological integration, and collaborative platforms to reinforce their critical role in optimizing patient outcomes in chronic illness management.
Conclusion: This study highlights nurses' adaptive role in chronic illness care, focusing on phase-specific interventions, emotional support, interdisciplinary collaboration, and education across entire illness trajectory to meet diverse needs of patients and their families. Despite challenges such as heavy workloads and emotional strain, the study recommends ongoing professional development and technological integration to optimize patient outcomes.

Keywords: chronic illness trajectory; diagnosis; end-of-life; grounded theory; nursing approaches.

This paper presents a novel approach to modeling and controlling a solar photovoltaic conversionsystem(SPCS) that operates under real-time weather conditions. The primary contribution is theintroduction of an uncertain model, which has not been published before, simulating the SPCS’sactual functioning. The proposed robust control strategy involves two stages: first, modifying thestandard Perturb and Observe (P&O) algorithm to generate an optimal reference voltage usingreal-time measurements of temperature, solar irradiance, and wind speed. This modification leadsto determining and linearizing the nonlinear current-voltage (I-V) characteristics of the photovoltaic(PV) array near standard test conditions (STC), resulting in an uncertain equivalent resistance used tosynthesize an overall model. In the second stage, a robust fixed-order H∞ controller is designed basedon this uncertain model, with frequency-domain specifications framed as a weighted-mixed sensitivityproblem. The optimal solution provides the controller parameters, ensuring good reference trackingdynamics, noise suppression, and attenuation of model uncertainties. Performance assessments atSTC compare the standard and robust P&O-MPPT strategies, demonstrating the proposed method’ssuperiority in performance and robustness, especially under sudden meteorological changes andvarying loads. Experiment results confirm the new control strategy’s effectiveness over the standardapproach.

Background: Diagnosing pulmonary tuberculosis (pTB) in children is challenging due to the difficulties in acquiring respiratory specimens, which unspecific and paucibacillary disease presentation, and the lack of sensitive diagnostic assays with non-invasive sample collection methods. As a result, millions of children around the world get tuberculosis (TB) each year, which is a leading cause of morbidity and mortality.
Objective: The aim of this study was to assess the diagnostic accuracy of Stool and Respiratory Sample-based Genexpert MTB/RIF assay from presumptive TB among children in Northwest, Ethiopia.
Methods and Materials: Hospital based cross-sectional with diagnostic accuracy study was conducted on consecutively recruited presumptive TB children. Data were collected by sem-structured questionnaires. Single respiratory (5ml) and 3g stool specimen were collected Lowenstein Jensen (LJ) and Xpert assay. Laboratory SOPs were strictly followed to assure the quality of whole procedures. The diagnostic accuracy of stool Xpert was evaluated against respiratory specimen Xpert, culture and composite reference standards (CRS). Sensitivity, specificity, and predictive values for the stool Xpert assay were calculated with a 95% confidence interval (95% CI) with MedCal statistical software. Data were entered in EPIData V4.2 and exported to SPSS 25 for further analysis.
Results: A total of 557 children were recruited; 510 of whom had complete microbiological results. Overall, pTB was diagnosed in 52/510 (10.2%) of the children with presumptive TB. Of these, only four had microbiologically unconfirmed pTB, were clinically diagnosed with positive response to anti-TB and the remaining 48 were microbiologically confirmed (Positive Xeprt and LJ culture). Stool specimen Xpert had sensitivity of 93.8 %( 95%CI: 82.8-98.6) and specificity of 99.8% (95%CI: 98.7–100) compared to culture; however, the sensitivity of stool was 88.5% (72-95.6) and specificity 100% (99.2-100) when compared to CRS. The Xpert on respiratory specimen had sensitivity and specificity of 95.8 % (85.8– 99.5) and 99.8% (98.7–100) to culture and 92.3 %( 81.4-97.9) and 100% (99.2-100) compared to CRS.
Conclusion: The sensitivity and specificity of Xpert assay for stool specimen is almost similar to that of respiratory specimen. Stool specimen is a highly promising alternative specimen in the diagnosis of pTB in children when respiratory specimen is impossible.


Key words: Diagnostic accuracy, pulmonary tuberculosis, Xpert MTB/RIF, Stool, Children

Introduction Protecting digital health data from unauthorized access, alteration, and destruction is a crucial aspectof healthcare digitalization. Currently, digital security breaches are becoming more common. Healthcare databreaches have compromised over 50 million medical records per year. In Ethiopia, health digitization has growngradually. However, there is a limitation of study in digital health security. Studying digital health data security helpsindividuals protect digital data as a baseline and contributes to developing a digital health security policy.Objective To assess the practice of healthcare professionals in digital health data security among specializedteaching referral hospitals in Amhara Region, Ethiopia.Method A cross-sectional study design supplemented by a qualitative purposive sampling method was usedto measure the digital data security practices of health professionals. The sample size was determined via singlepopulation proportion formula. A simple random sampling technique was used for the study participants. Then, self-administered questionnaires were administered. Multivariable logistic analysis was used to identify associated factorsusing STATA software. For the qualitative study, key informant interviews were used and analyzed using thematicanalysis approach via open-code software.Results Out of the 423 health professionals, 95.0% were involved in the survey. The finding indicates digital healthdata security practice of health professionals working at specialized teaching hospitals were 45.0%, CI: (40, 50). Healthprofessionals 41–45-year age group (AOR = 0.107), master’s degree (AOR = 2.45), postmaster’s degree (AOR = 3.87),time to visit the internet for more than two hours (AOR = 2.46), basic computer training (AOR = 2.77), training indigital data security (AOR = 2.14), and knowledge (AOR = 1.76) were associated with the practice of digital health datasecurity. For the qualitative study, three teams were prepared. The findings indicate digital health data security can beimproved through training, advanced knowledge and working with digital security.
Conclusion The practice of digital health data security in specialized teaching hospitals in the Amhara region wasinadequate. Therefore, it can be improved through enhancing education status, increasing the time needed to visitthe internet, providing computer training, and updating health professionals’ knowledge toward digital health datasecurity.Keywords Practice, Digital health, Digital data security, Health profession

EXECUTIVE SUMMARY Globally, the amount of time children spend using electronic or digital devices—commonly referred to as screen time are increasingly prevalent. This growing prevalence of screen time among children has raised concerns about its impact on their development. Therefore, this study aimed to explore three key themes: (1) the availability and use of electronic devices in households, (2) factors contributing to excessive screen time among children, and (3) the relationship between screen time and children's cognitive, emotional, and social development. The study was conducted in five selected towns within the East Gojjam Administrative Zone, namely Debre Markos, Bichena, Merto Lemariam, Dejen, and Lumame. For the quantitative data, 845 participants were chosen using multistage sampling techniques. Additionally, qualitative data was collected through interviews with 25 participants, 9 focus group discussions, and the collection of 16 diaries. We collected data by using questionnaires, semistructured interviews, focus group discussions, and diary records. For quantitative data analysis, SPSS version 20 was used. To summarize the demographic characteristics of participants, and describe the availability and use of electronic devices, descriptive statistics such as percentage and mean were used. Multiple regression analysis was used to examine the relationship between the total and device-specific screen time and children’s socioemotional and cognitive development. Qualitative data was analyzed using thematic analysis. The study revealed that children ages 2 to 5 had an average screen time of 244 minutes each day. The two most frequently used electronic devices in this age group are televisions, at 80.4%, and smartphones, at 45.2%. The multiple regression analysis indicated that parental screen time, mother’s employment status, and age were significantly and positively associated with children’s screen time. In conclusion, screen time for children aged 2 to 5 years exceeds the recommended limit. To have proper screen time for both parents and children, it is important to establish and implement clear guidelines.

Knowledge of domestic dog ecology and demography has been recognized as central to the designof an effective rabies control program. The study was conducted to assess owned dogs’ ecologyand demography and to identify predictors associated with dog ownership and rabies occurrencein the Amhara region, Ethiopia.Method: ology: The study employed dog census and questionnaire surveys of 907 householdsselected using a multistage sampling technique from six rural and six urban districts of theAmhara region, Ethiopia. The ecology and demography of owned dogs in the selected areas wererecorded and described using descriptive statistics. Mixed-effect logistic regression models wereused to identify factors associated with dog ownership and rabies occurrence.Results: A total of 6609 dogs were estimated from 42 kebeles in the 12 study districts. The male-to-female ratio of dogs was 1.7:1.0, and the mean age of dogs was 3.2 years. The proportion ofhouseholds who owned at least one dog was 5.9 %. The average number of dogs per dog-ownedhousehold was 1.3. Dog to household ratio was 1.0:13.0, and dog to human ratio was 1.0:48.5.The majority of the dog owners (97 %) keep dogs for home guard and livestock herding. Only 57% of the dogs were confined, and 16 % of them were vaccinated. Ninety-one percent of the dogowners did not practice neutering and spaying for dog population control. Religion, livestockownership pattern, and occupation were associated with dog ownership (p < 0.05). Communityresidence and age of respondents were associated with rabies occurrence (p < 0.05), while zonewas associated with both dog ownership and rabies occurrence at p-value

The experiment was carried out to evaluate the agronomic performance and dry matter yield of thePennisetum pedicellatum varieties (areka, kulmsa, and kindonkosha-591) at Debre Markos University,Ethiopia, during 2023 in a RCBD with three replications. The agronomic performance of all varieties wasmeasured from the six plants that were selected randomly from the middle rows of each plot at 105, 119,and 133 days after planting, and dry matter yield was measured at 135 days after planting. The studyshowed that there were significant differences (p < 0.05) in plant height, number of tillers and leaves,leaf length, and dry matter yield, but the number of nodes and leaf width were not significantly different(p > 0.05) among varieties. The highest values of plant height, number of tillers and leaves per plant, andleaf length and width were measured from the areka variety, followed by the kulmsa variety, while theleast was recorded from the kindonkosha-591 variety. The plant height, number of tillers per plant,number of leaves per plant, and dry matter yield of the areka variety were significantly higher (p < 0.05)than the kulmsa and kindonkosha-591 varieties. The highest dry matter yield was also produced fromareka (11.55 t/ha), followed by kulmsa (8.52) and kindonkosha −591 (7.99 t/ha). The areka grass varietyshowed superior agronomic performance and dry matter yield, suggesting its potential for improvingfeed shortage constraints in the study areas.
KEYWORDS: Agronomy; Desho grass; dry matter; Pennisetum pedicellatum; varieties

This study investigates the dynamics of instability among the Amhara people in Ethiopia following the political reform of 2018. It examines the main causes, key actors, phases of instability, and possible remedies. Employing a mixed-method research design, the study collected data through questionnaires, interviews, focus group discussions, and document analysis. Thematic and descriptive analyses were used to interpret the findings. The research reveals that the ongoing instability in the Amhara region since 2018 involves multiple actors and has both historical and contemporary roots. Deep-seated historical contradictions, coupled with a regressive political culture, have contributed to the persistence of unrest. Left-wing ethnically based political parties that perceive the Amhara as historical adversaries—alongside power struggles within the ruling coalition, merged as central drivers of instability. Beyond external political forces such as the Tigray People’s Liberation Front (TPLF) and the Oromo Liberation Army (OLA), internal factions like the Oromo Democratic Party (ODP) also played direct and indirect roles. Additionally, influential activists have further intensified the region’s instability. Factors such as public euphoria following the 2018 reform, the weakening of state institutions, perceived political dominance of the ODP, divisions among Amhara elites, the outbreak of the Tigray war, and shortages of agricultural inputs like fertiliser have collectively fueled the unrest. By categorising the instability into three distinct phases, the study offers a comprehensive understanding of its evolution. Ultimately, it concludes that inclusive political dialogue, mutual understanding among major actors, and national consensus are essential pathways toward restoring stability and peace in the Amhara region.
Keywords: Amhara, Causes, Instability, actors, Ethiopia, Remedies

Introduction
Dyslipidemia is a major risk factor for cardiovascular disease, with its prevalence steadily rising in both developed and developing nations. An unhealthy lifestyle significantly contributes to the development of dyslipidemia, with smoking being a well-known risk factor.
Methods
A comprehensive search was conducted across several databases, including Google Scholar, Web of Science, African Journals Online (AJOL), HINARI, and PubMed/MEDLINE. Articles published up until June 24, 2024, were considered for inclusion. Data extraction and organization were carried out using Microsoft Excel, while analysis was performed using STATA/MP 17.0. The quality of the included studies was evaluated using the Newcastle–Ottawa Scale (NOS). To analyze the pooled data, a weighted inverse variance random effects model with a 95% confidence interval was applied. Heterogeneity among studies was assessed using Cochrane’s I2 statistics, and Egger’s test was conducted to detect potential publication bias. The association between dyslipidemia and its associated factors was examined using the log odds ratio, with a p-value of less than 0.05 considered statistically significant.
Results
A total of 44 articles involving 12,395 participants were included. The overall pooled prevalence of dyslipidemia in Ethiopia was 56.60% (95% CI 50.40–62.80). Dyslipidemia was observed across various population groups, with notable prevalence rates associated with different risk factors. Among individuals with insufficient physical activity, the prevalence was 30.12% (95% CI 22.53–37.70). In those who smoked cigarettes, it was observed in 6.81% (95% CI 4.27–9.34). Among chronic alcohol consumers, the prevalence of dyslipidemia was 15.75% (95% CI 9.65–21.86). Furthermore, 30.12% (95% CI 22.53–37.70) of dyslipidemia was reported among individuals with inadequate physical exercise.
Conclusions
The prevalence of dyslipidemia in Ethiopia was 56.60%, indicating a significant public health concern. The condition is particularly prevalent among individuals with insufficient physical activity, smoking habits, and chronic alcohol consumption, suggesting strong associations with these modifiable risk factors. To reduce dyslipidemia, public health initiatives should focus on promoting physical activity, anti-smoking campaigns, and educating on the risks of excessive alcohol use. Health professionals should also prioritize early detection and management in high-risk groups to reduce long-term cardiovascular risks.