11,502 research outputs found

    Environmental Epidemiology of Intestinal Schistosomiasis in Uganda: Population Dynamics of Biomphalaria (Gastropoda: Planorbidae) in Lake Albert and Lake Victoria with Observations on Natural Infections with Digenetic Trematodes

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    This study documented the population dynamics of Biomphalaria and associated natural infections with digenetic trematodes, along the shores of Lake Albert and Lake Victoria, recording local physicochemical factors. Over a two-and-a-half-year study period with monthly sampling, physicochemical factors were measured at 12 survey sites and all freshwater snails were collected. Retained Biomphalaria were subsequently monitored in laboratory aquaria for shedding trematode cercariae, which were classified as either human infective (Schistosoma mansoni) or nonhuman infective. The population dynamics of Biomphalaria differed by location and by lake and had positive relationship with pH (P < 0.001) in both lakes and negative relationship with conductivity (P = 0.04) in Lake Albert. Of the Biomphalaria collected in Lake Albert (N = 6,183), 8.9% were infected with digenetic trematodes of which 15.8% were shedding S. mansoni cercariae and 84.2% with nonhuman infective cercariae. In Lake Victoria, 2.1% of collected Biomphalaria (N = 13,172) were infected with digenetic trematodes with 13.9% shedding S. mansoni cercariae, 85.7% shedding nonhuman infective cercariae, and 0.4% of infected snails shedding both types of cercariae. Upon morphological identification, species of Biomphalaria infected included B. sudanica, B. pfeifferi, and B. stanleyi in Lake Albert and B. sudanica, B. pfeifferi, and B. choanomphala in Lake Victoria. The study found the physicochemical factors that influenced Biomphalaria population and infections. The number and extent of snails shedding S. mansoni cercariae illustrate the high risk of transmission within these lake settings. For better control of this disease, greater effort should be placed on reducing environmental contamination by improvement of local water sanitation and hygiene

    Analysis of trends in seasonal electrical energy consumption via non-negative tensor factorization

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    This paper looks at the extraction of trends of household electrical seasonal consumption via load disaggregation. With the proviso that data for several home devices can be embedded in a tensor, non-negative multi-way array factorization is performed in order to extract the most relevant components. In the initial decomposition step the decomposed signals are incorporated in the test signal consisting of the whole-home measured consumption. After this the disaggregated data corresponding to each electrical device is obtained by factorizing the associated matrix through the learned model. Finally, we evaluate the performance of load disaggregation by the supervised method, and study the trends along several years and across seasons. Towards this end, computational experiments were yielded using real-world data from household electrical consumption measurements along several years. While breaking down the whole house energy consumption into appliance level gives less accurate estimates in the late years, we empirically show the adequacy of this method for handling the earlier years and the estimates of the underlying seasonal trend-cycle.info:eu-repo/semantics/acceptedVersio
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