The present study was conducted to investigate the prevalence of in sheep in Nepal. Blood samples were collected from 235 sheep from three districts of three different eco-zones namely, mountainous Jumla (88), hilly Pokhara (62) and plain/terai Chitwan (85). The samples were tested by using commercial ELISA kit. The overall prevalence of infection in sheep was 36.17% (CI: 30.29-42.49%). The region wise prevalence showed highest in Chitwan (57.65%; CI: 47.04-67.60%), followed by Pokhara (32.94%; CI: 23.88-43.48%) and Jumla (9.41%; CI: 4.85-17.49%). Prevalence of in Jumla was significantly lower than Pokhara and Chitwan (p < 0.05) but no significant difference in seroprevalence was encountered between Pokhara and Chitwan (p > 0.05). Similarly, no significant difference (p > 0.05) in prevalence of was found in sex and age groups (p > 0.05). The result showed that parasite is widely spread in the studied geographical regions of Nepal.
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http://dx.doi.org/10.1016/j.vas.2018.01.001 | DOI Listing |
Land use change can significantly alter the proportion of soil aggregates, thereby influencing aggregate stability and distribution of soil organic carbon (SOC). However, there is minimal research on the variations in the distribution of soil aggregates, aggregate stability, and SOC in soil aggregates following land use change from farmland (FL) to forest and grassland in the Loess Plateau region of China. Select six land use patterns (farmland (FL), abandoned cropland (ACL), Medicago sativa (MS), natural grassland (NG), Picea asperata Mast.
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School of Population Health, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia.
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Department of Electrical Engineering, College of Engineering, Taif University, P.O. BOX 11099, 21944, Taif, Saudi Arabia.
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Department of Geographic Information System, Chinese Academy of Surveying and mapping, Beijing, 100036, China.
Geographic entity matching is an important means for multi-source spatial data fusion and information association and sharing. Corresponding matching methods have been designed by existing studies for different types of entity data characteristics, such as line and area. However, these approaches are often limited in the generalization ability for matching heterogeneous data from multiple sources and the accuracy for complex pattern matching.
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