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Prompt-gamma engine performance throughout GEANT4 revisited along with confronted by research.
ased, the degree of overestimation and underestimation became smaller.Incidence rates of hematological malignancies have been constantly increasing over the past 40 years. In parallel, an expanding use of agricultural pesticides has been observed. Only a limited number of studies investigated the link between hematological malignancies risk and passive environmental residential exposure to agricultural pesticides in the general population. The purpose of our review was to summarize the current state of knowledge on that question. A systematic literature search was conducted using PubMed and Scopus databases. We built a scoring scale to appraise relevance of each selected articles. We included 23 publications 13 ecological studies, 9 case-control studies and a cohort study. Positive associations were reported between hematological malignancies and individual pesticides, pesticide groups, all pesticides without distinction, or some crop types. Relevance score was highly various across studies regardless of their design. Children studies were the majority and had overall higher relevance scores. The effect of passive environmental residential exposure to agricultural pesticides on hematological malignancies risk is suggested by the literature. The main limitation of the literature available is the high heterogeneity across studies, especially in terms of exposure assessment approach. Further studies with high methodological relevance should be conducted.The detection of Escherichia coli bacteria is essential to prevent health diseases. According to the laboratory-based methods, 12-48 h is required to detect bacteria in water. The drawback of depending on laboratory-based methods for the detection of E. coli bacteria can be prone to human errors. Hence, the bacterial detection process must be automated to reduce error. We implement an automated E. coli bacteria detection process using convolutional neural network (CNN) to address this issue. We have also proposed a mobile application for the rapid detection of E. coli bacteria in water that uses CNN. The developed CNN model achieved an accuracy of 96% and an error (loss) of 0.10, predicting each sample in only 458ms. The performance of the model was validated using the F-score, precision, sensitivity, and accuracy statistical measures, which shows that the model is reliable and effective in detecting E. coli. The study generates a methodology for predicting E. coli bacteria in water, which can be used to predict hotspots in terms of continuous exposure to water contamination.This study investigated the influence of coal bottom ash (CBA) on the concrete properties and evaluate the effects of combined exposure of sulphate and chloride conditions on the concrete containing CBA. During concrete mixing, cement was replaced with CBA by 10% of cement weight. Initially, concrete samples were kept in normal water for 28 days. Next, the specimens were moved to a combined solution of 5% sodium sulphate (Na2SO4) and 5% sodium chloride (NaCl) solution for a further 28 to 180 days. The experimental findings demonstrated that the concrete containing 10% CBA (M2) gives 12% higher compressive strength than the water cured normal concrete (M1). However, when it was exposed to a solution of 5% Na2SO4 and 5% NaCl, gives 0.2% greater compressive strength with reference to M1. The presence of 10% CBA decreases the chloride penetration and drying shrinkage around 33.6% and 29.2% respectively at 180 days. Hence, this study declared 10% CBA as optimum that can be used for future research.Microplastic pollution is ubiquitous in the marine environment and the consumption of shellfish containing microplastics may pose a risk to human health. This study investigated the occurrence and characteristics of microplastics in three commonly consumed shellfish in the coastal region of Jiangsu Province, China. The average abundance of microplastics in shellfish varied from 0.33 to 9.33 items/individual (0.06-0.92 items/g, wet weight of soft tissue). Microplastic abundance in Jiangsu was relatively low compared to studies from other regions of China and worldwide. Synthetic fibers (66.20%) were predominant and included rayon (34.84%) and polyester (23.23%), indicating that the majority of particles originated from the discharge of clothing fibers in domestic sewage. Transparent (66.20 %) particles were the most common, particle size was generally less than 500 μm (62.30%), and abundance decreased as the particle size increased. The average annual intake of microplastics by Jiangsu coastal residents via the consumption of common bivalves was estimated to be 1088.64 items/person/year. This study provides data to support ecological and health risk assessments for microplastics in the Jiangsu coastal region.Investigating the responses of retention and output of sulfur (S) is significant to understand the impact of atmospheric S deposition on the S cycling in soils and its environmental effects in the karst catchments of Southwest China. This study analyzed the contents and δ34S values of different S forms (total S, carbon-bonded S, ester-bonded SO42-, SO42-, and total reduced inorganic sulfur [TRIS]), the δ34S values of stream SO42-, the δ13C values of soil organic carbon, and sulfate-reducing bacteria (SRB) quantity in limestone soil and yellow soil profiles in a typical small karst catchment of Southwest China. The results showed that under the same acid deposition level, the limestone soil and yellow soil profiles are significantly different from the distribution of contents and δ34S values of different S forms and the number of SRB. At the same time, more than 70% of the SO42- in the stream water draining the sampling slopes came from soils at different depths in limestone soil and yellow soil profiles. These results indicate the different response of retention and output of S in the limestone soil and yellow soil to S deposition input. G Protein antagonist The organic S formation and dissimilatory SO42- reduction (DSR) to form TRIS are S retention processes that exist in both limestone soil and yellow soil profiles. There are processes of transport and accumulation of SO42- at the bottom layer in yellow soil profile; therefore, retaining S as absorbed SO42- is also a main S retention process in yellow soil. At present, the output of SO42- through stream water mainly comes from the deposited SO42- which undergoes DSR reaction driven by SRB, not from organic S mineralization and desorption of adsorbed SO42- in the limestone soil and yellow soil profiles. However, organic S is the main S form in limestone soil and yellow soil. After the annual S deposition flux is significantly reduced, organic S mineralization in limestone soil and yellow soil profiles may release a large amount of SO42- into the surface water.
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