Numerical Simulation and Experimental Research on Coal Ash Collecting and Grading System

The grading separation of coal ash can not only increase its economic value but also decrease its pollution to environment. Based on the jet-attracting flow technology and the gas-solid two-phase flow theory, the force and motion of coal ash particles in airflow were studied firstly. Focused on single coal ash particle, Matlab software was used to simulate the force conditions and separation parameters of various diameter coal ash particles in airflow. Fluent software was used to simulate the nozzle fluidization domain shape and to determine optimal jet flux. According to the theoretical results, a coal ash collecting and grading system was developed. Using the separation efficiency as the evaluation index, the optimal experiment parameters of jet flux, attracting flux, and separation time were obtained. At last, the calculated results and experimental results of coal ash particles median diameter from the first grading separation exit under various attracting fluxes were compared. The reasons that could cause the errors were discussed. This study has significant practical meaning and application value on coal ash collecting and grading separation

Public health and medical care for the world's factory: China's Pearl River Delta Region

While the growth of urbanization, worldwide, has improved the lives of migrants from the hinterland, it also raises health risks related to population density, concentrated poverty and the transmission of infectious disease. Will megacity regions evolve into socially infected breeding grounds for the rapid transmission of disease, or can they become critical spatial entities for the protection and promotion of population health? We address this question for the Pearl River Delta Region (PRD) based on recent data from Chinese sources, and on the experience of how New York, Greater London, Tokyo and Paris have grappled with the challenges of protecting population health and providing their populations with access to health care services. In some respects, there are some important lessons from comparative experience for PRD, notably the importance of covering the entire population for health care services and targeting special programs for those at highest risk for disease. In other respects, PRD's growth rate and sheer scale make it a unique megacity region that already faces new challenges and will require new solutions

An allosteric modulator activates BK channels by perturbing coupling between Ca2+ binding and pore opening

BK type C

Spatio-temporal variations of health costs caused by chemical fertilizer utilization in China from 1990 to 2012

The health impacts caused by chemical fertilizer utilization have challenged long-term sustainable development in many countries, particularly developing countries. Based on the emergy analysis method, we estimated the temporal and spatial variations of the health costs, through atmospheric, water, and soil pathways, of chemical fertilizer utilization in China during the period from 1990 to 2012. The results showed an obvious increasing trend of health costs from 1.8 billion Yuan in 1990 to 23.0 billion Yuan in 2012, while the ratio of health costs to agriculture output value declined slowly and became stable in recent years. Regional differences were remarkable and were significantly correlated to the levels of economic development (r = 0.843 and p < 0.001) and crop-sown area in the region (r = 0.588 and p < 0.001). Economically developed regions, especially the eastern coastal provinces, had much higher costs than the western regions. Meanwhile, fertilizer consumption shifted from the eastern to the northwest region, which was the same as the health costs. This study provides a reference to estimate the health costs of fertilizer utilization, and the results highlight the importance of sustainable development in China

Direct observational evidence of the multi-scale, dynamical mass accretion toward a high-mass star forming hub-filament system

There is growing evidence that high-mass star formation and hub-filament systems (HFS) are intricately linked. The gas kinematics along the filaments and the forming high-mass star(s) in the central hub are in excellent agreement with the new generation of global hierarchical high-mass star formation models. In this paper, we present an observational investigation of a typical HFS cloud, G310.142+0.758 (G310 hereafter) which reveals unambiguous evidence of mass inflow from the cloud scale via the filaments onto the forming protostar(s) at the hub conforming with the model predictions. Continuum and molecular line data from the ATOMS and MALT90 surveys are used that cover different spatial scales. Three filaments (with total mass $5.7\pm1.1\times 10^3~M_{\odot}$) are identified converging toward the central hub region where several signposts of high-mass star formation have been observed. The hub region contains a massive clump ($1280\pm260~M_{\odot}$) harbouring a central massive core. Additionally, five outflow lobes are associated with the central massive core implying a forming cluster. The observed large-scale, smooth and coherent velocity gradients from the cloud down to the core scale, and the signatures of infall motion seen in the central massive clump and core, clearly unveil a nearly-continuous, multi-scale mass accretion/transfer process at a similar mass infall rate of $\sim 10^{-3}~M_{\odot}~yr^{-1}$ over all scales, feeding the central forming high-mass protostar(s) in the G310 HFS cloud.Comment: Accepted to publish in ApJ. 10 pages with 6 figures and 2 table

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC00100