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Ten-year development regarding attention techniques, morbidities and emergency regarding very preterm neonates from the Malaysian Countrywide Neonatal Registry: a new retrospective cohort study.
Modeling results show that the largest contribution to the surface ozone in Northeast China is local anthropogenic emissions (exceed 90%); the regional transport of NCP anthropogenic emissions contribute more to the pollutants around 2 km, and account for more than 50% pollutants during highly ozone polluted days; through long-range transport, Siberian biomass burning in the spring also have a nonnegligible effect on the near-ground ozone in Northeast China. Overall, this study provides tropospheric ozone climatology and its source attribution in Northeast China, and highlight the great importance of regional transport of anthropogenic and biomass burning emissions in ozone pollution.Wastewater treatment plants (WWTPs) play an irreplaceable role in eliminating pollutants from domestic and industrial wastewater and contribute to water recycling. Nowadays, the selection of processes configuration of WWTPs mainly depends on the local wastewater treatment standards and the experience of wastewater engineers rather than an intelligent data-driven strategy. In this study, an integrated data-driven strategy consisting of t-distributed stochastic neighbor embedding (t-SNE) and deep neural networks (DNNs) is proposed for optimizing the processes configuration of full-scale WWTP predesign. A large dataset with 14,647 samples collected from 10 full-scale WWTPs with distinct treatment processes is clustered by the t-SNE method based on the influent characteristics, and four meaningful clusters (Clusters I-IV) are identified for the subsequent development of DNN classification models. All four DNN models achieve acceptable classification accuracy (>0.8975) and the maximal testing accuracy is 0.9505. The DNN models are capable of finding the optimized processes configuration of WWTPs under target scenarios. Our results highlight the strength of combining the t-SNE and the DNN models to utilize the relationships between key parameters and processes configuration of WWTPs, and help engineers predesign WWTPs with the optimal processes configuration.Adsorption of arsenate on clay minerals can control the partitioning and mobility of arsenic and subsequent contamination of groundwater. While the effect of ionic strength on arsenic adsorption to phyllosilicate minerals has been evaluated for various clay minerals, the specific ionic composition of the surrounding porewater can play a critical role in promoting adsorption (or desorption) of arsenate (HxAsO4x-4). We conducted a series of adsorption isotherms to evaluate the adsorption of arsenate to various phyllosilicates in the presence of monovalent (K+), divalent (Mg2+, Ca2+), and trivalent (La3+) cations while maintaining constant ionic strength and pH. Adsorption isotherms were combined with surface complexation modeling to examine retention processes of arsenate as a function of ionic composition in the surrounding solution. The higher charge density of greater valent cations results in stronger outer-sphere bridging complexes between negatively charged phyllosilicate mineral surfaces and negatively charged arsenate oxyanions. Higher valent cations thus enhance the propensity for arsenate adsorption on phyllosilicate minerals. We further deciphered surface complexation processes by conducting adsorption isotherms on various clay minerals including smectite, illite, and pyrophyllite to evaluate the role of interlayer, permanent charge, and terminal edge sites. We conclude that arsenate is most likely retained largely on the planar surface where structural negative charge emanates allowing cation bridging complexes to develop. Our findings illustrate that clay mineralogy of soils and sediments can combine with porewater ionic composition (and specifically the proportion of divalent cations) to describe arsenic transport, particularly in iron- or aluminum-oxide poor systems.Large dams on rivers have substantial impacts on the flow process, sediment transport, and river morphology. The flow-sediment regimes and river morphology in the Yangtze River downstream of the Three Gorges Dam (TGD) have undergone significant adjustments owing to the impoundment of the TGD. Different methods have been adopted to assess the spatiotemporal variations in characteristic discharge in the reaches downstream of the TGD, which can quantitatively assess the channel-forming capacity of flow-sediment regimes. However, agreement on the spatiotemporal variations in characteristic discharge in a long-distance reach downstream of the TGD does not exist thus far. Alvelestat in vitro Therefore, in this study, the effective discharge, dominant discharge, and bankfull discharge were calculated to assess the spatiotemporal variations in the characteristic discharge from Yichang to Datong. It was found that, after the impoundment of the TGD, the attenuation of the flow process, bedload coarsening, and changes in the water surface slope together led to a decrease in dominant discharge, which was consistent with the adjustment of the main deformation area from the bankfull channel to the medium-flow channel. This indicates that the dominant discharge is most representative of the characteristic discharges in the reaches downstream of the TGD. Results show that the post-dam characteristic discharge at each station from Yichang to Datong was reduced by 700-5700 m3/s. Spatially, owing to the tributaries along the main stem, the characteristic discharge decreased from Yichang to Jianli and then increased from Jianli to Datong in the pre- and post-dam periods. This study serves as a valuable reference for quantitatively assessing the channel-forming capacity of flow-sediment regimes for other rivers worldwide. Moreover, it facilitates the prediction of the evolution of river morphology.Water availability is important for survival of millions of people living in the Himalayan region of Upper Indus Basin and adequate monitoring system is for better water resources management. In the present study, groundwater recharge appraisals in the Neelum watershed (Upper Indus Basin) were investigated by using water balance and geospatial modeling techniques on monthly time-scale climate data from 1989 to 2015. Results demonstrated that on an average out of total annual rainfall (i.e., 2028 mm), about 46% of the rainfall convert to surface runoff and 35% loss to atmosphere via evapo-transpiration (ET), while the remaining 18% contribute to infiltrate the groundwater recharge. Groundwater recharge enhanced during snow-melt from December to March and the rainfall infiltration increased during July and August months. Similarly, the infiltration ranges 106-177 mm from January to March and 45-51 mm from December to July. The groundwater discharge in the form of oozing from the spring occurred during the remaining six months, which ultimately contributed to the baseflow of the stream.
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