Research Articles

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Comparison of COVID-19 Severity Between Tropical and Non-Tropical Countries
(International Journal of Infection., 2020-06-13) flor, Tushabe
Abstract Coronavirus disease 2019 (COVID-19) has affected the whole world. However, it is not clear whether the disease affects all countries equally. This paper analyzes the severity of COVID-19 in tropical and temperate countries by comparing the data of infections and deaths registered four months after the onset of the disease. Data were segregated, summarized, visualized, and interpreted. The severity of the disease was quantified in each country and recommendations were made for both categories of countries. The re search found that the severity of the disease in terms of infection or death was six times more in countries located in the temperate region. Keywords: Coronavirus, COVID-19, Tropics, Tropical Countries, Temperate, Temperate Countries
Motion Prediction with Gaussian processes for Safe Human-Robot Interaction in Virtual Environments
(IEEE, 2023) STANLEY, MUGISHA; VAMSI, KRISHNA GUDA; CHRISTINE, CHEVALLEREAU; DAMIEN, CHABLAT; MATTEO, ZOPPI
ABSTRACT Humans use collaborative robots as tools for accomplishing various tasks. The interaction between humans and robots happens in tight shared workspaces. However, these machines must be safe to operate alongside humans to minimize the risk of accidental collisions. Ensuring safety imposes many constraints, such as reduced torque and velocity limits during operation, increasing the time to accomplish manytasks.However,forapplicationssuchasusingcollaborativerobotsashapticinterfaceswithintermittent contacts, speed limitations result in poor user experiences. This research aims to improve the efficiency of a collaborative robot while improving the safety of the human user. We used Gaussian process models to predict human hand motion and developed strategies for human intention detection to improve the time for the robot while improving human security in a virtual environment. We then studied the effect of prediction. Results from comparisons show that the strategies with prediction model improved robot time by 3% and safety by 17%. When used alongside gaze for prediction, the strategy based on the Gaussian process model resulted into an improvement of the robot time by 2% and the safety by 13%.
Prevalence of Aflatoxin Contamination Across the Food Value Chain for Maize and Groundnuts in Uganda
(Acta Scientific AGRICULTURE, 2023-04-11) Florence, Tushabe; Samuel, Mwesige; Okoth, Thomas; Ivan, Kasamba; Areu, David
Abstract Background: Maize and groundnuts are some of the most highly contaminated foods on the Ugandan market. Since 2006 there have been some scattered studies on the prevalence of aflatoxin contamination among these grains. However, there were no recent studies of 2022 to highlight the status of aflatoxin contamination. Methods: Grain samples were collected from two highest producing districts that is Masindi and Soroti districts; and across the value chain, from farmers to wholesalers, retailers, processors and restaurants/homes. The samples were tested using ELISA method and the prevalence calculated. Results: Aflatoxins were detected in 45% and 30% of maize and groundnuts, respectively. Contamination increases over the value chain from 31% at farm level, to 42% at table level. In general, contamination was highest among processors at 43%, followed by restaurants (42%), wholesalers (40%), farmers (31%) and retailers at 29%. Keywords: Aflatoxins; Prevalence; Maize; Corn; Groundnuts; Gnuts; Uganda; Value Chain
Impact of information literacy on the utilization of LMS in Uganda: A Case study of Soroti University
(African Journal of Library and Information Innovations (AJLII), 2026-07-31) Stephen Econyu; Lujja A. Azizi; Hellen Flavia Atai; Barbra Apolot; Ibrahim Kabi; Emmanuel Emwos Opio
Background: Learning Management Systems (LMS) are essential tools in higher education for supporting teaching, learning, and access to digital resources. However, effective utilization depends on users’ information literacy competencies.. Purpose: This study examined impact of information literacy on LMS utilization at Soroti University. Specifically, it assessed the status of LMS, examined users’ information literacy levels, identified challenges affecting LMS usage, and proposed strategies for improving utilization. Methodology: A cross-sectional descriptive research design using quantitative and qualitative approaches was adopted. Data were collected from 45 respondents, including academic, administrative and support staff, and students selected through stratified random and purposive sampling. Data were collected using closed-ended questionnaires and interview schedules. Quantitative data were analyzed using SPSS, while qualitative data were analyzed thematically using ATLAS.ti. Results: The findings revealed that LMS at Soroti University is operational and accessible, although utilization differs across departments. A strong positive and statistically significant relationship existed between information literacy and LMS utilization (r = .729, p = .000). Regression analysis showed that information literacy explained 53.1% of the variation in LMS utilization (R² = .531). Challenges included limited awareness of LMS functionalities, poor internet connectivity, inadequate technical support, insufficient ICT infrastructure, and continued preference for traditional teaching methods. Conclusion: The study concluded that information literacy significantly influences effective LMS utilization in higher education institutions.. Implications: The findings contribute to understanding factors affecting technology adoption in higher education and highlight the need for continuous digital literacy trainings, improved ICT infrastructure, technical support, and institutional awareness programs to strengthen LMS utilization..

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