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Evaluation of the actual nontreponemal IgM antibodies throughout syphilis serofast patients: A new serologic sign with regard to productive syphilis.
With the growing awareness of the linkage among open defecation (OD), environment, and health, it is important to understand the factors responsible for OD. It is a necessary step toward developing a strategy to end open defecation for ensuring a better environment and human health. There is no such study available for Pakistan. The study, therefore, aims to bridge this gap. Using household data of Pakistan Demographic and Health Survey (PDHS) 2017-2018, an association of OD with potential predictors, analysis of variance, and a logistic regression model are employed to develop the evidence. The results suggest that place of residence, education, poverty status, social norms, geopolitical regions, and living space significantly predict the OD behavior in Pakistan. This study recommends two things first is to facilitate the households and communities to own latrines, second is to change the behavior through intervention. However, political commitment and effective administration will be key to ascertain ending OD.Globally, urban has been the major contributor to greenhouse gas (GHG) emissions and thus plays an increasingly important role in its efforts to reduce CO2 emissions. However, quantifying city-level CO2 emissions is generally a difficult task due to lacking or lower quality of energy-related statistics data, especially for some underdeveloped areas. To address this issue, this study used a set of open access data and machine learning methods to estimate and predict city-level CO2 emissions across China. Two feature selection technologies including Recursive Feature Elimination and Boruta were used to extract the important critical variables and input parameters for modeling CO2 emissions. Finally, 18 out of 31 predictor variables were selected to establish prediction models of CO2 emissions. Onalespib We found that the statistical indicators of urban environment pollution (such as industrial SO2 and dust emissions per capita) are the most important variables for predicting the city-level CO2 emissions in China. The XGBduction goal.As well known, mercury is a toxic trace element due to its bioaccumulation and volatility which results in severe effects in health of ecosystems and humans' life. Herein, for the first time, the synthesis of a N and S dual-doped waste-derived graphene-like nanoporous carbon via a facile and single-step route is presented and its capability in mercury vapor removal from gas streams is investigated. To prepare a modified adsorbent, thiourea was utilized as the doping agent to induce nitrogen and sulfur dopants into the nanoporous carbon structure derived from pyrolysis of cabbage (Capitat. var. Brassica oleracea) waste from Brassicaceae family as an inherently S, N-containing precursor, which is produced in noticeable amounts annually. The prepared adsorbents were characterized through FTIR, XRD, BET, SEM, TEM, and CHNOS techniques to get an insight into the structure, morphology, and chemical characteristics of the adsorbents. The structural characterization revealed the successful synthesis of a graphene-like nanoporous carbon sheet which was doped with nitrogen and sulfur atoms. The S, N dual-doped graphene-like carbon nanosheets showed an enhanced activity toward mercury vapor adsorption. For this end, two different dopant to carbon source ratios were considered and it was found that the higher dopant amount results in a better performance. From the adsorption experiments, it was revealed that the pristine graphene-like carbon had a less performance in mercury removal (71%) compared with doped samples (more than 90%) which shows the necessity of reinforcement and surface modification of as mentioned cabbage base graphene. However, the best sample which was prepared with the dopant to carbon ratio of 10 had a performance of 94.5% removal (2100 μg/g) compared with 89% (1980 μg/g) for mercury removal by the sulfur-impregnated commercial activated carbon.In this study, 18S rRNA high-throughput sequencing was applied to investigate the eukaryotic community in a full-scale drinking water treatment plant. Eukaryotic species and microbial functions in raw water and filter biofilms were identified by metagenomic sequencing. The eukaryotic species richness and diversity presented declining trends throughout the treatment process. The lowest eukaryotic species richness was observed in disinfected water. Arthropoda, Ciliophora, Ochrophyta, and Rotifera were the dominant eukaryotic phyla and exhibited high variations in relative abundance among the different treatment units. Sedimentation significantly decreased the abundance of all eukaryotes except Arthropoda. Biological activated carbon (BAC) filtration and chlorine disinfection exerted strong effects on community composition. The eukaryotic communities in water were distinct from those in filter biofilms, as were the communities of different filter biofilms from each other. In contrast, communities were functionally similar among different filter biofilms, with the category metabolism being the dominant category represented, within which amino acid transport and metabolism (E) and energy production and conversion (C) dominated among subcategories. Seventy-one eukaryotic species pathogenic to humans were identified in raw water and filter biofilms. Quantitative PCR (qPCR) results showed that Acanthamoeba spp. and Vermamoeba vermiformis were present during some treatment processes, with concentrations of 12-1.2 × 105 copies/mL and 1 copy/mL, respectively. Neither of the two pathogenic amoebae was found in disinfected water. Canonical correspondence analysis (CCA) showed that pH was the most important environmental factor affecting eukaryotic community composition. Overall, the results provide insights into the eukaryotic community diversity in drinking water treatment plants and the potential eukaryotic hazards involved in drinking water production.With the development of China's economy, pollution has made serious impact on environment and human health. However, environmental protection and residents' health are becoming more and more important along with the country's social and economic transformation. Most existing studies have analyzed the path of economic impact on the environment and the production, pollution, and health in isolation. This research takes panel data of 30 provinces in China (including autonomous regions and municipalities, excluding Tibet, Hong Kong, Macau, and Taiwan) spanning 2014 to 2017 as an example, builds an evaluation indicator system on the basis of the three stages of economic production, wastewater treatment, and human health, and uses the undesirable three-stage dynamic data envelopment analysis model to empirically evaluate the total efficiency, stage efficiency, and the efficiency of various indicators. The research results show the average efficiency of the three stages in most provinces in four years is below 0.5, indicating the poor coordination of each stage; the efficiency gaps among the eastern, central, and western regions are very large because of the resource endowments, geographical environment, industrial structure, strategic adjustment, and other infactors.
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