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101.

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder characterized mainly by qualitative deficiencies in social communication skills, accompanied by repetitive and restricted behavior patterns. This study was conducted to investigate the associations between the risk of ASD development in children and exposure to trace elements (arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), lead (Pb), nickel (Ni), and zinc (Zn)). Two groups of children, including 44 ASD and 35 typically developing (TD) children, were selected, and their fasting urine samples were obtained. The concentration levels of trace elements were assayed using ICP-MS. The results showed that as compared to the TD group, the concentration levels of As (p = 0.002) and Pb (p < 0.001) and also Cr (p < 0.001), Cu (p = 0.001), and Ni (p < 0.001) were significantly higher among ASD children. In terms of gender, boys with ASD showed elevated levels of Cr, Cu, Ni, and Pb, whereas the urine levels of As, Cr, Cu, Ni, and Pb were markedly higher among girls when compared to the non-ASD children. Under the logistic regression model, the risk difference for As, Co, Cr, Cu, Ni, Pb, and Zn remained significant when adjustment was applied for age and gender confounders.

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102.
Environmental Science and Pollution Research - The current study aimed to evaluate the levels of some toxic and essential elements (Pb, Cd, Cu, Ti, Ni, Cr, Co, Fe, Ca, Hg, Mn, Se, and Zn) in the...  相似文献   
103.

The coupling of ever-increasing consumption of fossil fuels around the globe with the decrease in the availability of fossil fuel supplies has led to an increased cost of energy commodities, which together with ever-expanding requirements for reducing the level of environmental pollutions has resulted in an ever-increasing deal of attention to alternative transportation schemes such as electric vehicles (EVs). Since decades ago, national governments and environmental activists have initiated various efforts towards reducing atmospheric pollutions. A part of such effort has been focused on reducing the use of internal combustion vehicles and rather replacing them with EVs. In this research, we attempt to fill in this research gap by presenting a mathematical model for minimizing the sum of traveled distance and recharging cost of EVs per a given period and then solving it by simulated annealing (SA) algorithm. Results of the proposed algorithm were then compared to those of coding in GAMS for 30 different sample problems with different counts of customers, EVs, and charging stations. Numerical results indicated good efficiency of the metaheuristic algorithm in terms of processing time and solution quality. Indeed, with the SA algorithm, the processing time was seen to increase gradually with increasing the problem complexity, while the rate of increase in processing time was much steeper with the GAMS.

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