Adventist University of Central Africa

Purpose: The research aimed to understand how small-scale vendors exchange with their customers from various linguistic backgrounds. It particularly sought to explore how language proficiency influences business interactions and customer satisfaction in the Ejoheza Modern Market, Kigali. Methods: Using a qualitative approach, the study investigated the language preferences and communication practices of small-scale vendors. Data were collected through direct observation and interviews with selected vendors to identify the main languages used in daily transactions and coping mechanisms adopted when facing language barriers. Results: The findings revealed that all vendors can easily speak Kinyarwanda, but only a few of them can communicate in English and French. This limitation affects their interaction with non-Kinyarwanda-speaking customers, often leading to communication breakdowns. To address this challenge, vendors rely on translation applications on their phones or seek assistance from interpreters to facilitate exchanges. Conclusion: The study concludes that language proficiency significantly influences vendors’ ability to attract and serve diverse customers, which in turn affects sales and market inclusivity. Limitations: The study was limited to Ejoheza Modern Market and did not include other markets in Kigali, which restricts the generalization of the findings. Contribution: This study highlights the critical role of language skills in enhancing small-scale vendors’ business success. It recommends establishing affordable language training programs to empower vendors, improve customer relations, and promote inclusive economic growth in Rwanda’s urban markets.

Artificial intelligence (AI) is rapidly transforming decision-making across various sectors, introducing both opportunities and ethical challenges for leadership. While AI enhances efficiency and innovation, concerns, such as algorithmic bias, transparency deficits, and accountability gaps, pose significant risks to governance. This study examines these ethical dilemmas through real world cases, including Amazon’s recruiting tool, Olay’s algorithmic audit, IBM Watson for Oncology, and predictive policing via COMPAS, to assess their impact on leadership frameworks and the necessity for proactive ethical oversight. Through a comprehensive interdisciplinary analysis, this paper explores traditional ethical leadership models alongside emerging AI governance frameworks, notably the Ethical Management of Artificial Intelligence (EMMA) model. By synthesizing research across ethics, psychology, and management, this study demonstrates how leaders must integrate technical expertise with ethical sensitivity to align AI adoption with organizational values and societal expectations. These findings underscore the crucial need for explainable AI (XAI), bias audits, and transparent accountability structures to promote trust in AI systems. To address these challenges, this study recommends a multi-stakeholder approach that prioritizes interdisciplinary collaboration, continuous ethical monitoring, and enforceable AI governance policies. Ethical AI leadership necessitates adaptive oversight to ensure that AI innovation benefits humanity without perpetuating systemic biases or ethical blind spots.

ABSTRACTAir pollution spikes pose significant health risks and environmental challenges that demand innovative solutions for effective analysis and mitigation. This paper introduces a groundbreaking approach to revolutionize air pollution spikes analysis using a blockchain‐driven machine learning framework. Leveraging the transparency and immutability of blockchain technology, coupled with the predictive power of machine learning algorithms, our framework offers real‐time monitoring, accurate prediction, and proactive management of air pollution spikes. Our framework provides comprehensive insights into air quality dynamics by integrating data from diverse sources, including IoT sensors. Furthermore, the decentralized nature of blockchain ensures data integrity and enhances trust among stakeholders, including regulatory authorities, industries, and communities. Through case studies and simulations, we demonstrated the efficacy and scalability of our framework in addressing air pollution spikes across diverse geographical regions. The Machine learning techniques for the time series model (RNNs, ARIMA, and Exponential Smoothing) were analyzed and compared using statistical metrics (Mean Absolute Error [MAE], Mean Squared Error [MSE], and R‐squared [R2]). The exponential Smoothing model performed well compared to the other two models for all parameters, while both ARIMA and RNNNN models showed negative R2 values for certain pollutants, particularly SO2. For example, the PM10 scored 82.4% for R2. This research signifies a paradigm shift in air quality management, empowering stakeholders to make informed decisions and mitigate the adverse impacts of air pollution spikes on public health and the environment. This research demonstrated that machine learning and blockchain can be integrated to analyze data on air pollution spikes and predict pollutant emissions. This solution will help prevent harmful exposure to pollutants, protecting human health and the environment.

“Brain organoids”, “cerebral organoids” or “mini-brains” are the terms that have been frequently used to describe self-organizing 3D structures which could be derived from embryonic stem cells (ESCs), adult stem cells, or induced pluripotent stem cells (iPSCs). The fact that certain cell types could be reprogrammed to study some aspects of brain development and certain disease conditions has advanced our understanding of brain development in health and disease. Human brain development is somewhat intriguing, however, complex, sharing close similarities with both primate and rodent brain development, despite species heterogeneity. The in-vivo and in-vitro models have been used over time to study the development of the brain in health and disease states. The in-vitro system being a monolayer system is unable to recapitulate some essential aspects of human brain development and even certain disease conditions like microcephaly, Alzheimer's disease (AD), and Frontotemporal dementia (FTD) to mention a few, because of the complex pathophysiology of these diseases. Based on this premise, recent studies are now beginning to examine the role of patient-derived human tissues reprogrammed into stem cells with the ability to organize into 3D cerebral organoids in studying and understanding the complex nature of neurodegenerative diseases which have been difficult to model in-vitro and in-vivo. Here, we highlight evidence of patient-derived brain organoids in modeling Alzheimer’s disease, providing evidence on the current challenges and prospects in growing cerebral organoids and some approaches that have been developed to overcome these challenges.

The landscape of religious leadership has evolved significantly over the past four decades as religious institutions navigate fundamental challenges of secularization, shifting demographics, technological disruption, and growing religious diversity.Amid these pressures, transformational leadership has emerged as a compelling framework through its ability to foster personal growth, promote vision-driven change, and empower communities while maintaining spiritual authenticity and organizational vitality (Ginty, 2024).First conceptualized by Burns (1978) and later expanded by Bass (1985), transformational leadership theory emphasizes the leader's ability to inspire and motivate followers toward higher levels of performance and moral development.In the Christian context, this leadership approach has gained particular attention due to its alignment with biblical principles of personal growth and community transformation (Ginty, 2024).Christian organizations face unique challenges in today's rapidly changing social and cultural environment (Tarte, 2024).These organizations must balance traditional religious values with the need for adaptive leadership approaches that can effectively guide their communities through change (Robinson, 2024).The principles of transformational leadership, with their emphasis on vision, inspiration, and individual development, offer valuable insights for Christian leaders seeking to navigate these challenges while maintaining their spiritual foundations.

Abstract Background Periodontal disease is ranked the second oral health disorder following tooth decay. About 50% of the global adult population suffers from periodontal disease, making it one of the world’s most common disease. The study was carried out to assess the bacterial profiles and Predisposing factors associated with periodontitis among adult patients at Ruhengeri Referral Hospital. Methods This was a cross sectional study carried out between September 2021 and February 2022. A total of 102 participants were recruited for this study. Oral swab samples were collected with sterile cotton stick, and transported to INES Ruhengeri clinical microbiology laboratory for bacterial isolation and identification. Chi-square test was used to test for association, while logistic regression was used to test for the relationship between demographic characteristics and periodontitis. Results Periodontitis was prevalent in the age range of 40–49 years (24%) and the high morbidity was observed among females (68%) compared to males. The most predominant isolated microorganism was Lactobacillus spp. (10.43%). The logistic regression model showed that illiterate (p < 0.00001, 95% CI: 15.909–19.970), primary education level (p < 0.00001, 95% CI: 13.777–17.436), ordinary education level (p < 0.00001, 95% CI: 14.329–18.822), and urban residence (p = 0.018, 95CI: .318-3.422) were demographic characteristics that were significantly associated with periodontitis. The statistical significant association of predisposing factors with periodontitis was observed on smoking (p < 0.00001, 95% CI: 0.5971–0.8305), oral hygiene (p = 0.015, 95% CI: 0.2095–0.5563) and Oral medication (p < 0.00001, 95% CI: 0.2711–0.6049). Ciprofloxacin was the most effective antibiotic while Vancomycin was the least effective antibiotic to isolated bacteria. Pseudomonas aeruginosa was the most resistant among Gram-negative bacteria while Staphylococcus epidermidis was the most resistant bacteria among Gram-positive bacteria. Conclusion Periodontitis affected people of the age range between 40 years and 69 years, and females were the most affected by the disease. The patients should seek for a dentist when they present signs of periodontitis and early detection of the disease is recommended.

<strong>Abstract:</strong> This research project entitled "Effects of the accelerated school construction program on the students' academic achievement in public secondary schools in Gasabo District, Rwanda" was guided with two specific objectives which are to evaluate the school facilities constructed in the accelerated school construction program and to evaluate the relationship existing between the accelerated school construction program and the students' academic achievement in public secondary schools in Gasabo, Rwanda. The total population of this study was composed of 165 from six selected secondary schools including head teachers and teachers in which a sample of 117 respondents was obtained by using Slovin's formula. Correlation research design was employed and IBM/SPSS version 21.0 was used to analyze data. The findings shown that the accelerated school construction program influences students' academic achievements at 50.1% of R-square. It was revealed that constructed schools, playgrounds as well as smart classroom indicates the accelerated school construction program implementation in public secondary schools as it was confirmed by 60 percent of teachers. It was also shown that there is a significant high positive correlation of 0.780 between accelerated school construction program and students’ academic achievement and that every increase on accelerated school construction program implementation leads to effective academic achievement increase between 49.2 percent and 78.2 percent. The study recommends that educational authorities and superseding people should provide accelerated school construction program facilities and establish a well-coordinated maintenance plan of constructed school facilities which integrates each stakeholder’s role. The researcher suggests that further research can be done to examine the influence of accelerated school construction program on students’ academic performance in public secondary schools in Rwanda so as to come up with comparative analysis. <strong>Keywords:</strong> School construction, Accelerated school construction program, Smart classrooms, Academic achievement. <strong>Title:</strong> Effect of the Accelerated School Construction Program on the Students’ Academic Achievement in Public Secondary Schools of Rwanda <strong>Author:</strong> Nyirahabakwiha Charlotte, Mukamazimpaka Marie Claire, Mugiraneza Faustin <strong>International Journal of Recent Research in Social Sciences and Humanities (IJRRSSH)</strong> <strong>ISSN 2349-7831</strong> <strong>Vol. 9, Issue 4, October 2022 - December 2022</strong> <strong>Page No: 10-19</strong> <strong>Paper Publications</strong> <strong>Website: www.paperpublications.org</strong> <strong>Published Date: 08-October-2022</strong> <strong>DOI: https://doi.org/10.5281/zenodo.7162986</strong> <strong>Paper Download Link (Source)</strong> <strong>https://www.paperpublications.org/upload/book/Effect%20of%20the%20Accelerated%20School-08102022-3.pdf</strong>

This special issue of The Journal of Adventist Education® (JAE) is part of a long-standing tradition. Each quinquennium,1 a special General Conference issue featuring education reports from each division of the Seventh-day Adventist world church is produced to inform, inspire, and engender general support for the work of Adventist education.

L’identification de l’étranger est devenue un enjeu déterminant dans un contexte de contrôle strict de l’entrée et du séjour sur le territoire national. Apporter la preuve qu’un jeune est majeur revêt donc, pour l’administration, une telle importance, qu’elle n’hésite pas à recourir à des méthodes d’analyse plus que contestables.