Estimation of methane generation based on anaerobic digestion and mass balance at Kiteezi Landfill, Kampala, Uganda

Kiteezi landfill site is the main solid waste dumping site in Kampala City (Uganda). In this study, the generation of methane from waste at Kiteezi landfill was measured using laboratory-scale anaerobic digestion experiment and estimated using the Mass balance model. The samples were collected in the wet and dry seasons, with five replicates for each season which were processed for further experiments focused on moisture content analysis and anaerobic digestion. The moisture content analysis results showed a significant change (P < 0.05) between wet season and dry season. Also, the anaerobic digestion revealed that moisture content was a determining factor in gas generation. The average monthly methane production estimate from the mass balance model was 1.63 Gg methane/month and was comparable (within 14%) to the amount estimated by laboratory-scale anaerobic digestion experiment (1.43 Gg methane/month). It is a worthwhile undertaking to further investigate the potential of commercially producing methane from Kiteezi landfill as an alternative source of green and clean energy for urban masses.Keywords: Solid waste management, methane generation, anaerobic digestion and mass balance model

FluNet: An AI-Enabled Influenza-like Warning System

Influenza is an acute viral respiratory disease that is currently causing severe financial and resource strains worldwide. With the COVID-19 pandemic exceeding 153 million cases worldwide, there is a need for a low-cost and contactless surveillance system to detect symptomatic individuals. The objective of this study was to develop FluNet, a novel, proof-of-concept, low-cost and contactless device for the detection of high-risk individuals. The system conducts face detection in the LWIR with a precision rating of 0.98, a recall of 0.91, an F-score of 0.96, and a mean intersection over union of 0.74 while sequentially taking the temperature trend of faces with a thermal accuracy of ± 1 K. While in parallel determining if someone is coughing by using a custom lightweight deep convolutional neural network with a precision rating of 0.95, a recall of 0.92, an F score of 0.94 and an AUC of 0.98. We concluded this study by testing the accuracy of the direction of arrival estimation for the cough detection revealing an error of ± 4.78°. If a subject is symptomatic, a photo is taken with a specified region of interest using a visible light camera. Two datasets have been constructed, one for face detection in the LWIR consisting of 250 images of 20 participants’ faces at various rotations and coverings, including face masks. The other for the real-time detection of coughs comprised of 40,482 cough / not cough sounds. These findings could be helpful for future low-cost edge computing applications for influenza-like monitoring

Nutritional supplement practices of professional Ugandan athletes: a cross-sectional study

Abstract Background The use of nutritional supplements (NS) places athletes at great risk for inadvertent doping. Due to the paucity of data on supplement use, this study aimed to determine the proportion of Ugandan athletes using nutritional supplements and to investigate the athletes’ motivation to use these supplements. Methods A cross-sectional study was conducted in which an interviewer-administered questionnaire was used to collect data from 359 professional athletes participating in individual (boxing, cycling, athletics) and team (basketball, rugby, football, netball, and volleyball) sports. The data were categorized, and a Chi-square test was used for statistical analysis. Results Of the 359 athletes, 48 (13.4%) used nutritional supplements. Carbohydrate supplements, energy drinks, vitamin and mineral supplements, fish oils, and protein supplements were the most common supplements used by athletes. NS use was significantly more common among athletes who played rugby and basketball (X 2 = 61.101, p < 0.0001), athletes who had played the sport for 5-10 years (X 2 = 7.460, p = 0.024), and athletes who had attained a tertiary education (X 2 = 33.377, p < 0.0001). The athletes’ occupation had no bearing on whether they used supplements. Nutritionists/dieticians, retail stores and pharmacies were the most common sources of NS products, whereas health practitioners, online media and teammates were the most common sources of information regarding NS. Most athletes used NS to improve their physical performance and health. Conclusions Compared to NS use by athletes elsewhere, NS use among Ugandan athletes was low. However, determinants of athlete NS use in the current study (category of sport and duration of time spent playing the sport) are similar to those reported elsewhere