Intestinal parasitic infection is one of the public health problems in developing countries including Pakistan. Food handlers being major source, therefore effective prevention and control require the identification of local risk factors. Presently occupation based cross sectional study was conducted to assess the prevalence of intestinal parasitic infections and associated risk factors among food handlers of district Swat, Khyber Pakhtunkhwa, Pakistan from January 2011 to December 2013. Study subjects were selected based on random sampling methods. A total of 267 food handlers were enrolled, socio-demographic data and possible factors for the occurrence of intestinal parasitic infection were collected using a pre-tested structured questionnaire. Approximately 10 grams of stool specimens were examined using wet mount and formal ether concentration technique. The overall prevalence of intestinal parasite was 83.1% (n=222/267). Multiple infections were identified in 28.4% (n=76/267) individuals. These infections were given in order of their frequency and percentage as: Ascaris lumbricoides 55.8% (n=149/267) Trichuris trichuira 14.9% (n=40/267), Entamoeba histolytica /dispar 14.2% (38/267), Enterobius vermicularis 9.73% (n=26/267), Hymenolepis nana 9.36% (n=25/267), Taenia saginata 8.98% (n=24/267), Hookworm 5.99% (16/267) and Giardia lamblia 5.61% (n=15/267). Hand washing before food handling, preparing food during suffering from infectious diseases and using common knife for cutting the flesh or vegetable were the most significantly associated factors for the occurrence of intestinal parasite infection. The results highlighted that food handlers with different pathogenic organisms may influence consumers to significant health risks. Routine screening and treatment of food handlers is a proper tool in preventing food-borne parasitic diseases.
Due to unrivaled effectiveness, non-orthogonal multiple access (NOMA) has risen as a promising multiple access scheme for the Internet of things (IoT). In this paper, we provide a new power allocation technique for improving the energy and spectral efficiency of NOMA-enabled IoT devices. The power allocation is performed without compromising the quality of service (QoS) requirements of the network. By considering the transmit power, QoS and successive interference cancellation (SIC) constraints, we use the sequential quadratic programming (SQP) technique to solve the non-convex problem. To assess the performance of our scheme, we compare the proposed SQP-based approach with the conventional KKT-based optimization method. We provide Monte Carlo simulation results to assess our proposed power allocation framework and illustrate the performance improvements against orthogonal multiple access (OMA) scheme. The results uncover that the proposed SQP-based power optimization design substantially improves the performance of the NOMA-enabled IoT network.
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