This study aims at exploring the potentials and drawbacks of utilizing social media to promote tourism industry in East Gojjam Zone. The study will be geographically limited to East Gojjam Zone and will not include media platforms other than social media. The research will bring significance to the culture and tourism offices, agencies that work on tourism industry and an input for the government organizations in policy formulation as well as for future researchers. Qualitative research approach with descriptive design will be employed. The population of this study is social media pages of Culture and Tourism Offices of all the woredas found in East Gojjam Zone and of the Zones’ Culture and Tourism Department. The sample will be purposive sampling of all social media pages of the woredas and the zone. Focus group discussion and indepth interview will be conducted in eight selected woredas and zonal culture and tourism office. East Gojjam Zone has 19 woredas including Debre Markos town. The data will be gathered using content analysis of the social media posts, focus group discussion and in-depth interview. In addition, data will also be collected from reports, and publications like newsletters and articles.To collect the data official support letter will be submitted to the Culture and Tourism Department of East Gojjam Zone. The authenticity of social media pages of the woreda tourism offices will be confirmed with the concerned bodies at the zonal level. The collected data using online content, in-depth interview and focus group discussion will be triangulated for data analysis. The researchers expect to find out social media usage patterns and preferences in tourism promotion, social media promotion strategies and implementation, social media regulation and governance in tourism promotion. Atotal budget of 201, 722 ETB will be allocated to conduct the whole study from April to September, 2024.

The work presented in this paper focuses on formulating the development of time-dependent electromagneticfield laws through the application of Gauss’s divergence theorem. The first part of the discussion looks at thebasic ideas of electromagnetism. It focuses on how classical formulations of the laws of electromagnetism can beadapted to account for non-stationary conditions, especially regarding magnetic fluids that don’t conduct elec-tricity. It is suggested that employing Gauss’s divergence theorem could help improve the computational analysisof these generalized equations, which would make them more useful in magnetic fluid dynamics. The paperexamines the intricate interactions between non-conductive particles and conductive fluids under magneticfields. By putting these interactions into a single theoretical framework, this work aims to help us understandnon-stationary electromagnetic phenomena and how they affect many different scientific and engineering fields.The concluding section of the study examines the prospective practical applications of these extended equations.They could enable the development of more advanced electromagnetic devices and systems. Creating a strong setof analytical tools that can find new scientific paths and useful applications is the main goal of the study,particularly in the areas of electromagnetic induction and fluid dynamics. This research offers potential forsubstantial progress in both theoretical comprehension and technological advancement, The proposed method isapplicable to real-world systems such as ferrofluid-based cooling, magnetic dampers, plasma generators, andsmart electromagnetic devices. These applications demonstrate the practical benefits of coupling field behaviorwith boundary dynamics using Gauss’s theorem.
Keywords: Gauss theorem, Non-conductive;Magnetic, Non-stationary, Fluids, Induction

Abstract: Food insecurity in peri-urban areas is exacerbated by high living costs, limited access tohealthy food, and economic inequality. Despite its growing prevalence due to factors like land lossfrom urban expansion, food insecurity has received limited attention. In Ethiopia, drastic urbanizationcreates competition for land between agriculture and urban development, which is becoming extremein peri-urban areas., This study aims to assess the impact of urban expansion on food security amongexpropriated peri-urban households in Ethiopia. Using a calorie intake-based food security line, wecategorize respondents as food-secure or -insecure. The research analyzed data from 350 expropriatedperi-urban households through a structured questionnaire, employing descriptive statistics andbinary logistic regression. About 67% of the respondents were classified as food-insecure. The binarylogit model identified several significant determinants of food security, including compensationamount and type, household head demographics, agricultural land rent participation, irrigationand credit access, off-farm income, and organic fertilizer use. To address food insecurity amongexpropriated households, policymakers must prioritize these factors. Government attention andpolicy consideration are crucial to ensure the well-being of these vulnerable populations.Keywords: urban expansion; food insecurity; calorie intake; expropriation; Ethiopia

ABSTRACT Background: Blood donation is vital for saving lives, yet Ethiopia faces chronic shortages. Bridging the gap between willingness and actual donation is essential for sustaining blood supplies. This study examined socio-demographic, psychological, and contextual factors influencing blood donation intention and practice in East Gojjam Zone. Methods: A community-based cross-sectional survey of 1,332 urban adults who met inclusion criteria was conducted using multistage cluster sampling. Data were collected via a structured, pre-tested questionnaire. Descriptive statistics summarized donation patterns, while binary logistic and Zero-Inflated Negative Binomial regressions identified predictors of donation intention and frequency, respectively. Structural Equation Modeling (SEM) examined associations among socio-demographic characteristics, psychological factors, donation intention, practice, and behavior. Results: Although 74.8% (95% CI: 72.5–77.1) expressed willingness to donate, only 28.8% (95% CI: 26.4–31.2) had ever donated, and 20.7% (95% CI: 18.5–22.9) had donated in the past two years. Male gender, younger age, higher education, and employment in health or education sectors positively predicted intention and practice. Psychological factors—including self-efficacy (β = 0.53), positive attitudes (β = 0.46), knowledge (β = 0.38), altruism, and social influence (β = 0.28)—were strongly associated with donation. SEM confirmed that intention strongly predicted actual donation (β = 0.62). Barriers included fear of needles, health concerns, and limited awareness. Conclusions: Despite high willingness, actual donation remains low. Multi-sectoral, culturally sensitive strategies—addressing fears, improving knowledge, leveraging social influence, and enhancing accessibility—are critical, especially for women, older adults, and less-educated individuals, to build a resilient, community-driven blood supply. Keywords: Blood donation, intention, practice, socio-demographic factors, psychological determinants, Ethiopia, Structural Equation Modeling

ABSTRACT Background: Blood donation is vital for saving lives, yet Ethiopia faces chronic shortages. Bridging the gap between willingness and actual donation is essential for sustaining blood supplies. This study examined socio-demographic, psychological, and contextual factors influencing blood donation intention and practice in East Gojjam Zone. Methods: A community-based cross-sectional survey of 1,332 urban adults who met inclusion criteria was conducted using multistage cluster sampling. Data were collected via a structured, pre-tested questionnaire. Descriptive statistics summarized donation patterns, while binary logistic and Zero-Inflated Negative Binomial regressions identified predictors of donation intention and frequency, respectively. Structural Equation Modeling (SEM) examined associations among socio-demographic characteristics, psychological factors, donation intention, practice, and behavior. Results: Although 74.8% (95% CI: 72.5–77.1) expressed willingness to donate, only 28.8% (95% CI: 26.4–31.2) had ever donated, and 20.7% (95% CI: 18.5–22.9) had donated in the past two years. Male gender, younger age, higher education, and employment in health or education sectors positively predicted intention and practice. Psychological factors—including self-efficacy (β = 0.53), positive attitudes (β = 0.46), knowledge (β = 0.38), altruism, and social influence (β = 0.28)—were strongly associated with donation. SEM confirmed that intention strongly predicted actual donation (β = 0.62). Barriers included fear of needles, health concerns, and limited awareness. Conclusions: Despite high willingness, actual donation remains low. Multi-sectoral, culturally sensitive strategies—addressing fears, improving knowledge, leveraging social influence, and enhancing accessibility—are critical, especially for women, older adults, and less-educated individuals, to build a resilient, community-driven blood supply. Keywords: Blood donation, intention, practice, socio-demographic factors, psychological determinants, Ethiopia, Structural Equation Modeling

Evidence shows that financial inclusion plays a key role in driving economic growth and social development by strengthen-ing the financial system and reducing poverty and income inequality. However, its impact on the financial performance ofbanks remains inconclusive. This paper explores the relationship between financial inclusion and the financial performanceof commercial banks in Ethiopia, using a sample of 16 banks. We analyse 10 years of data (2013–2022) collected manuallyfrom the National Bank of Ethiopia (NBE) and the annual reports of commercial banks. A two-step system GeneralizedMethod of Moments (GMM) is employed, alongside other linear panel data model estimators. The findings reveal that in-creased financial inclusion has a significant positive impact on the financial performance (ROA and ROE) of commercialbanks in Ethiopia. The GMM estimation result also shows that bank performance indicators (ROA and ROE) are positivelyassociated with their past realizations. Regarding bank-specific control variables, the cost-efficiency ratio has a significantnegative impact on bank profitability. The study recommends that banks improve accessibility by expanding branch net-works and ATMs and by offering innovative financial products to enhance profitability.Keywords: financial inclusion, GMM, bank performance, Ethiopia

Introduction Functional disability in older adults refers to difficulties in performing daily activities. It is usuallyevaluated based on an individual’s ability to carry out basic activities of daily living and instrumental activities of dailyliving. Although existing studies provide valuable insights, comprehensive global data on functional disability inbasic and instrumental activities of daily living among older adults remain limited. This study aims to review existingresearch worldwide to estimate the overall pooled prevalence of functional disability in these areas.Methods Systematic searches were conducted across EMBASE, Scopus, PubMed/MEDLINE, and Google Scholar fromMay 5 to July 11, 2024. Cross-sectional studies worldwide on functional disability in basic and instrumental activitiesof daily living among adults aged 60 and older, published in English up to July 11, 2024 were included. Studies wereexcluded if they did not report the outcomes of interest, were inaccessible, case reports, low quality, review articles,or published in languages other than English. Data extraction and cleaning were performed using Microsoft Excel,and STATA version 17 was used to compute the pooled effect size with 95% confidence intervals (CIs) for functionaldisability in both basic activities of daily living and instrumental activities of daily living among older adults. Toderive these estimates, we used weighted averages, where each study’s prevalence was weighted by the inverse ofits variance. Study heterogeneity was assessed using the Cochrane I² statistic and its associated p-value. Subgroupanalysis and meta-regression were conducted to identify sources of heterogeneity. Sensitivity analysis was used toevaluate the impact of individual studies on the overall results. Publication bias was assessed with Egger’s test andfunnel plots, and was addressed through trim-and-fill analysis.Results This review includes 35 studies with a total of 133,827 participants. The pooled prevalence of functionaldisability in basic activities of daily living was estimated at 26.07% (95% CI: 19.04–32.74), while on instrumentalactivities of daily living, it was estimated at 45.15% (95% CI: 36.02–54.29). After applying the trim-and-fill method,the adjusted overall prevalence of disability in basic activities of daily living was 15.12%, (a 95% CI: 11.25–19.13%).
subgroup analysis showed highest prevalence in Africa (BADL: 42.91%, IADL: 69.34%) and lowest in Asia (BADL:19.15%, IADL: 32.66%). Participants aged 65 and above, those in institutional settings, and studies with smaller samplesizes tended to report higher levels of functional disability.Conclusions Nearly one-fourth of the study participants had functional disability related to basic activities of dailyliving, while about half experienced disability in instrumental activities of daily living. This emphasizes the needfor continued effort in improving the quality of life and support systems for individuals facing functional disability,particularly in instrumental activities.Keywords Basic activities of daily living, Functional disability, Instrumental activities of daily living, Older adults.

The goal of natural language processing (NLP), which has recently gained popularity, is to improve the ca-pacity of computers to comprehend and interact with human language. Consequently, to converse usingnatural language, it is crucial that spoken language be grammatically correct, especially for Geéz language.Geéz language sentences must follow certain norms of agreement in terms of number, person, gender, tense,and other factors to be considered grammatically correct. If the input sentence in Geéz language is improper,then it can have problems with subject-verb agreement, object-verb agreement, adjective-noun agreement,and adverb-verb agreement. The goal of the proposed work is to provide a neural machine translation ap-proach for detecting and correcting grammar errors in Geéz sentences. We have prepared manually 11,490Geéz parallel corpuses (Geéz language grammatically incorrect and grammatically correct sentences). Afterwe have prepared a parallel Geéz sentence, we have used normalization, tokenization, padding, and one hotencoding as preprocesses. We have used two deep learning algorithms, including a bidirectional long short-term memory encoder-decoder and a long short-term memory encoder-decoder, for training the proposedmodel. Keras and TensorFlow were used for importing the required libraries, and we used the Python 3.7 en-vironment for implementation. Two test cases are used for the evaluation technique. The first one is for thelong short-term memory encoder-decoder model, and the second one is for the bidirectional long short-termmemory encoder-decoder model. Finally, the bidirectional long short-term memory encoder-decoder modelachieved best results with an accuracy of 82%, recall of 82%, precision of 85%, and F1-measure of 83% withbalanced error type classes.CCS Concepts: • Computing methodologies → Machine translation;Additional Key Words and Phrases: NMT, GSD, GGEH, NLP, DL, LSTM, BILSTM

Bread wheat (Triticum aestivum L.) is vital for over a third of the global population but facessignificant production challenges due to limited adaptable varieties, poor management practices,and environmental factors. New wheat varieties often fail in unfamiliar environments, leading tocrop loss. To address this issue, a study was conducted to evaluate the adaptability, performance,and yield stability of recently released high-performing wheat varieties over two years (2020/2021 and 2021/2022) in four districts of the East Gujjar Zone: Machakel, Debre Elias, Gozamin,and Baso-Liben. The trials were set up using a randomized complete block design (RCBD) withthree replications, and data were collected on the main traits such as days to heading, maturity,plant height, tiller number, spike length, spikelet’s per spike, biomass, and grain yield. AMMI andGEE biplot analysis were used to study genotype by environmental interaction. The combinedanalysis of variance for grain yield showed highly significant effects (P < 0.001) due to genotype(4.98 %), environment (66.83 %), and genotype × environment interaction (31.96 %). Grainyield varied across the environments, ranging from 3.72 t ha 1in Baso-Liben to 3.11 t ha 1 inMachakel. Among the genotypes, Ogolcho had the highest mean yield (4.55 t ha 1), whereasWane had the lowest (2.70 t ha 1). Genotype-by-environment interaction biplot analysis groupedthe eight test environments and six genotypes into two mega-environments and three genotypegroups. Wane, Lemu, and Ogolcho were the stable genotypes. This analysis identified the mostfavorable districts for wheat production and highlighted Ogolcho as the most productive wheatvariety in the study area. The results suggest that farmers in these districts should adopt Ogolchoto enhance wheat yield and increase their income.
Keywords: AMMI, GGE, GIE, PCA, Stability, Wheat

Chickpea is a self-pollinated, diploid, and annual plant (2x = 2n = 16). After peas and beans, it is the most important legumein the world. Reduced chickpea production and productivity have been significantly influenced by the lack of improvedand adaptable genotypes, poor management practices, biotic factors such as disease and pests, and abiotic factors includingfluctuating rainfall and temperature. New chickpea genotypes introduced in Northern Ethiopia lack adaptability, stability,and performance evaluation, resulting in crop losses for farmers due to their susceptibility to the new and variable environment. To address these challenges, recently released high-yielding genotypes, alongside a standard check, were evaluatedfor adaptability, performance, and yield stability over 2 years (2022/2023 and 2023/2024) in three districts (Shebel, Awabel,and, Jabitenan) of Northern Ethiopia across six multienvironment field trials each employing a randomized complete blockdesign with three replications. SAS 9.4 and R software were used, showing significant differences in crop phenological stages,growth, and yield parameters across years and locations for test traits. Genotype, location, and year interactions significantlyinfluenced all Kabuli chickpea genotypes. The highest combined mean grain yield was obtained from genotype “Arerti”(2.42 t ha-1) followed by “Yelbie” (2.18 t ha-1), which explained their best performance among the tested genotypes. Analysis ofvariance revealed significant interactions and differences between genotypes and environments, with 15.6% of the variationin grain yield attributed to environmental factors, 6.4% to genotype differences, and 11.4% to genotype-by-environment interactions. The Genotype and Genotype × Environment biplot and Additive Main Effect and Multiplicative Interaction analysisidentified stable genotypes, representative environments, and interesting genotype–environment interactions. GenotypesArerti, Chefe, and Yelbie were identified as stable based on Genotype and Genotype × Environment biplot and Additive MainEffect and Multiplicative Interaction analysis. Environments Shebel and Jabitenan were identified as representative amongall environments considered.