Molecular Detection of Indigenous Hepatitis E Virus (HEV) from Tibetan Pigs in Tibet,China

Hepatitis E is an important public health concern throughout the world. Many molecular and serological surveys have reported the prevalence and genotypic characteristics of HEV in humans and animals worldwide. However, the genotypic characterization of this virus is very limited in Tibetan pigs. Hence, we aimed to explore the genotype of HEV, prevailing among Tibetan pigs in China. For this purpose, 253 bile samples of Tibetan pigs (free-range animals) were collected from different slaughterhouses during 2017–2018 and subsequently tested for HEV RNA by RT-nPCR. A total of 11 out of 253 (4.35%) samples tested were positive for HEV RNA. Based on the sequence alignment and phylogenetic analysis, all the isolated HEV strains belonged to genotype 4 and clustered into subtype 4b by sharing more than 84.8–95.2% identities with other reported strains. Our results concluded that HEV genotype 4 is prevailing among Tibetan pigs in Tibet, China.     

Comprehensive review on naringenin and naringin polyphenols as a potent anticancer agent

Environmental Science and Pollution Research - Though the incidence of several cancers in Western societies is regulated wisely, some cancers such as breast, lung, and colorectal cancer are...     

Effects of the green supply chain management practices on firm performance and sustainable development

Environmental Science and Pollution Research - The idea of sustainable development and green supply chain management is considered at the underlying stage in the research and academic fields,...     

A method for simulation of vapour cloud explosions based on computational fluid dynamics (CFD)

The effectiveness of the application of CFD to vapour cloud explosion (VCE) modelling depends on the accuracy with which geometrical details of the obstacles likely to be encountered by the vapour cloud are represented and the correctness with which turbulence is predicted. This is because the severity of a VCE strongly depends on the types of obstacles encountered by the cloud undergoing combustion; the turbulence generated by the obstacles influences flame speed and feeds the process of explosion through enhanced mixing of fuel and oxidant. In this paper a CFD-based method is proposed on the basis of the author’s finding that among the various models available for assessing turbulence, the realizable k-? model yields results closer to experimental findings than the other, more frequently used, turbulence models if used in conjunction with the eddy-dissipation model. The applicability of the method has been demonstrated in simulating the dispersion and ignition of a typical vapour cloud formed as a result of a spill from a liquid petroleum gas (LPG) tank situated in a refinery. The simulation made it possible to assess the overpressures resulting from the combustion of the flammable vapour cloud. The phenomenon of flame acceleration, which is a characteristic of combustion enhanced in the presence of obstacles, was clearly observed. Comparison of the results with an oft-used commercial software reveals that the present CFD-based method achieves a more realistic simulation of the VCE phenomena.     

Assessment of Hg accumulation in fish and scalp hair in fishing communities along river Swat,Pakistan

Environmental Science and Pollution Research - Mercury (Hg) bioaccumulation in fish poses severe threats to the food safety and human health. This study was conducted to assess Hg bioaccumulation...     

Adsorption of phosphate on magnetite-enriched particles (MEP) separated from the mill scale

MEP were separated from mill scale at low magnetic intensity i.e., 300 to 500 gauss. The phosphate adsorption capacity of MEP was determined 6.41 mg/g. MEP packed-bed columns were successfully regenerated with alkaline solution. Phosphate is a major pollutant in water, causing serious environmental and health consequences. In present study, the phosphate adsorption on novel magnetite-enriched particles (MEP) was comprehensively investigated. A new method and device were introduced for the separation of MEP from the mill scale at low magnetic intensity. Particles were characterized with different techniques such as XRD, XRF, SEM and EDS. The XRD and XRF analysis of MEP identified the dominant existence of crystalline magnetite. Furthermore, the morphological analysis of MEP confirmed the agglomerate porous morphology of magnetite. Oxygen and iron, the main constituents of magnetite were acknowledged during the elemental analysis using EDS. The phosphate adsorption on MEP is well explained using various isotherm and kinetic models, exhibiting the monolayer adsorption of phosphate on the surface of MEP. The maximum adsorption capacity was determined 6.41 mg/g. Based on particle size (45–75 and 75–150 µm) and empty bed contact time (1 and 2 h), four columns were operated for 54 days. MEP were appeared successful to remove all phosphate concentration from the column influent having 2 mg/L concentration. The operated column reactors were successfully regenerated with alkaline solution. The results indicated potential for practical application of the MEP for phosphate removal.     

Soil Moisture Data Assimilation Using Support Vector Machines and Ensemble Kalman Filter1

Abstract: A hybrid data assimilation (DA) methodology that combines two state‐of‐the‐art techniques, support vector machines (SVMs) and ensemble Kalman filter (EnKF), is applied for soil moisture DA in this work. The SVM methodology provides a statistically sound and robust approach to solving the inverse problem, and thus to building statistical models. EnKF is an extension of the Kalman Filter (KF), a well‐known tool in prediction updating. In the present research, ground measurements were used to build a SVM‐type soil moisture predictor. Subsequent observations and their statistics were assimilated to update predictions from the SVM model by coupling it with EnKF. In this way, both model predictions and ground data, as well as their statistics, are fused thus minimizing the prediction error and making the predictions and observations statistically consistent. The results are shown for two approaches; one in which update is done at every time step and the other which assumes that data is only available at alternate time steps (in window of 10 time steps) and hence update is performed at those occasions. The SVM‐EnKF coupling is shown to improve soil moisture forecasts in an example using data from the Soil Climate Analysis Network site at Ames, Iowa.     

DDT residue in soil and water in and around abandoned DDT manufacturing factory

Dichlorodiphenyltrichloroethane (DDT) belongs to one of the most hazardous groups of chemicals called persistent organic pollutants. Many organochlorine pesticides including p,p(')-DDT are long lasting due to their non-degradability can travel to distant places and being fat soluble can accumulate in animals and human bodies. Due to the persistent nature of p,p(')-DDT, its adverse environmental and health impacts, the present study was undertaken to examine the residual p,p(')-DDT in and around abandoned p,p(')-DDT manufacturing factory in Amman Gharh, Nowshera, NWFP. Samples of soil, sediments and water were collected in and around the factory area, nearby p,p(')-DDT stores, main factory drain leading to river Kabul and nearby villages. Standard procedures were used for the collection, transportation and storage of samples for analyses. Extraction of each sample for p,p(')-DDT analyses was carried out in triplicates using Soxhelt extraction. p,p(')-DDT contents in the samples were analyzed by capillary GC with electron capture detector. Most of the samples collected up to half kilometer distance from the site of the DDT factory were found contaminated. Further the level of p,p(')-DDT decreased with increasing depth from top to bottom and with distance from the site. The results indicate that there is no immediate threat to underground water reservoirs.     

Impact of storm water on groundwater quality below retention/detention basins

Groundwater from 33 monitoring of peripheral wells of Karachi, Pakistan were evaluated in terms of pre- and post-monsoon seasons to find out the impact of storm water infiltration, as storm water infiltration by retention basin receives urban runoff water from the nearby areas. This may increase the risk of groundwater contamination for heavy metals, where the soil is sandy and water table is shallow. Concentration of dissolved oxygen is significantly low in groundwater beneath detention basin during pre-monsoon season, which effected the concentration of zinc and iron. The models of trace metals shown in basin groundwater reflect the land use served by the basins, while it differed from background concentration as storm water releases high concentration of certain trace metals such as copper and cadmium. Recharge by storm water infiltration decreases the concentration and detection frequency of iron, lead, and zinc in background groundwater; however, the study does not point a considerable risk for groundwater contamination due to storm water infiltration.