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The coronavirus disease 2019 (COVID-19) outbreak caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) developed into a global health emergency. Systemic microthrombus caused by SARS-CoV-2 infection is a common complication in patients with COVID-19. Cardiac microthrombosis as a complication of SARS-CoV-2 infection is the primary cause of cardiac injury and death in patietns with severe COVID-19. In this study, we performed single-cell sequencing analysis of the right ventricular free wall tissue from healthy donors, patients who died during the hypercoagulable period of characteristic coagulation abnormality (CAC), and patients who died during the fibrinolytic period of CAC. We collected 61,187 cells enriched in 24 immune cell subsets and 13 cardiac-resident cell subsets. We found that in the course of SARS-CoV-2 infected heart microthrombus, MYO1EhighRASGEF1Bhighmonocyte-derived macrophages promoted hyperactivation of the immune system and initiated the extrinsic coagulation pathway by activating chemokines CCL3, CCL5. This series of events is the main cause of cardiac microthrombi following SARS-CoV-2 infection. In a SARS-CoV-2 infected heart microthrombus, excessive immune activation is accompanied by an increase in cellular iron content, which in turn promotes oxidative stress and intensifies intercellular competition. This induces cells to alter their metabolic environment, resulting in increased sugar uptake via the glycosaminoglycan synthesis pathway. In addition, high levels of reactive oxygen species generated by elevated iron levels promote increased endogenous malondialdehyde synthesis in a subpopulation of cardiac endothelial cells. This exacerbates endothelial cell dysfunction and exacerbates the coagulopathy process. [ABSTRACT FROM AUTHOR]

Tick-borne encephalitis virus (TBEV) represents a pivotal tick-transmitted flavivirus responsible for severe neurological consequences in Europe and Asia. The emergence of TBEV genetic mutations and vaccine-breakthrough infections, along with the absence of effective vaccines and specific drugs for other tick-borne flaviviruses associated with severe encephalitis or hemorrhagic fever, underscores the urgent need for progress in understanding the pathogenesis and intervention strategies for TBEV and related flaviviruses. Here we elucidate cellular alterations in the proteome, phosphoproteome, and acetylproteome upon TBEV infection. Our findings reveal a substantial impact of TBEV infection on the innate immune response, ribosomal biogenesis, autophagy, and DNA damage response (DDR). Mechanically, the non-structural protein NS5 of TBEV impedes DNA damage repair by interacting with SIRT1 to suppress the deacetylation of KAP1 and Ku70. Additionally, the precursor membrane protein prM induces autophagy via associating with AKT1 while constrains autolysosome formation through binding to VPS11. Inhibitors targeting DDR, as well as specific kinases, exhibit potent antiviral activity, suggesting the dysregulated pathways and kinases as potential targets for antiviral intervention. These results from our study contribute to elucidating the pathogenesis and offers insights for developing effective antiviral drugs against TBEV and other tick-borne flaviviruses. Here, Sui et al. use multi-proteomics to analyse tick-borne encephalitis virus-infected cells and identify host cellular pathways perturbed by viral infection. [ABSTRACT FROM AUTHOR]

The instability and failure processes of coal-rock combinations are accompanied by the release of acoustic emission (AE) and infrared radiation (IR) signals. To investigate the characteristics of AE and IR signals during the failure process in coal-rock combinations with different ratios, and to analyze the effectiveness and applicability of the monitoring methods for these two signals in various specimen ratios. In this paper, the uniaxial compression tests were conducted on seven coal-rock combinations with different ratios by using the rock mechanics loading system and the cooperative monitoring platform of infrared and acoustic emission. The results show that (1) the AE counts for failure precursors in coal-rock combinations are positively correlated with the coal-rock ratio, whereas the AE peak counts are negatively correlated. Moreover, as the coal-rock ratio decreases, the slope of the cumulative AE count curve during the peak failure stage approaches 1. (2) During the elastic and yield stages, the maximum infrared radiation temperature (MIRT) curve fluctuates, and just before peak failure, the curve displays a distinctive "V" shape. This "V" shape becomes more pronounced as the coal-rock ratio decreases. (3) In the monitoring of damage precursors of coal-rock combinations, when the ratio of coal to rock is 1:3 or less, IR monitoring is better than AE monitoring. Conversely, when the ratio of coal to rock is greater than 1:3, AE monitoring is more suitable. Consequently, the combined monitoring of AE and IR signals can increase the reliability and precision of early warning signals for coal-rock assemblage damage precursors. [ABSTRACT FROM AUTHOR]

In a market, there are many groups caused by geographical location or other reasons, and consumers in groups have their own brand preferences for a type of products. The diversity of consumers' brand preferences will avoid the phenomenon of brand simplification and monopoly caused by consistent brand reference of consumers, and to some extent, promote the prosperity and development of various brands in each group. For brand diversification in a market, we hope the brand preferences of consumers in each groups are as equilibrious as possible, so Influence Maximization under Equilibrious Groups (IMEG) is proposed to select k nodes to maximize the number of equilibrious groups after information diffusion. This paper proves that the IMEG is NP-hard, and computing the objective function is #P-hard. It also proves that the objective function is neither submodular nor supermodular under Independent Cascade (IC) model and Linear Threshold (LT) model. Then, the Equilibrious Groups Maximization Solution (EGMS) algorithm is presented to solve our problem. And by comparing with baseline algorithms using different datasets (dolphins, wildbird, weaver and hamsterster), it can be found that the EGMS has obvious advantages in time complexity and spatial complexity. In particular, the running time of EGMS is about 3.7 × 10 - 2 , 2.4 × 10 - 2 , 1.1 × 10 - 1 and 1.8 × 10 - 3 times that of the fastest baseline algorithm in dolphins, wildbird, weaver and hamsterster respectively. And the experiments in small-world, scale-free, random and regular network verify the robustness of EGMS with the varying parameters, such as the number of nodes, the probability of adding edges and the number of adjacencies. [ABSTRACT FROM AUTHOR]

Recent studies have indicated that combining oncolytic viruses with CAR-T cells in therapy has shown superior anti-tumor effects, representing a promising approach. Nonetheless, the localized delivery method of intratumoral injection poses challenges for treating metastatic tumors or distal tumors that are difficult to reach. To address this obstacle, we employed HSV-1-infected CAR-T cells, which systemically delivery HSV into solid tumors. The biological function of CAR-T cells remained intact after loading them with HSV for a period of three days. In both immunocompromised and immunocompetent GBM orthotopic mouse models, B7-H3 CAR-T cells effectively delivered HSV to tumor lesions, resulting in enhanced T-cell infiltration and significantly prolonged survival in mice. We also employed a bilateral subcutaneous tumor model and observed that the group receiving intratumoral virus injection exhibited a significant reduction in tumor volume on the injected side, while the group receiving intravenous infusion of CAR-T cells carrying HSV displayed suppressed tumor growth on both sides. Hence, CAR-THSV cells offer notable advantages in the systemic delivery of HSV to distant tumors. In conclusion, our findings emphasize the potential of CAR-T cells as carriers for HSV, presenting significant advantages for oncolytic virotherapy targeting distant tumors. [ABSTRACT FROM AUTHOR]

Revealing key factors that modulate the regioselectivity in heterogeneous hydroformylation requires identifying and monitoring the dynamic evolution of the truly active center under real reaction conditions. However, unambiguous in situ characterizations are still lacking. Herein, we elaborately construct a series of Rh-POPs catalysts for propylene hydroformylation which exhibited tunable regioselectivity. Multi-technique approaches reveal the unique microenvironment of the diverse HRh(CO)(PPh3-frame)2 sites with distinct P-Rh-P bite angles ranging from 90° to 120° and 158° to 168°, respectively. In situ time-resolved XAFS, FT-IR, and quasi-in situ Solid-state NMR experiments combined with DFT calculations explain the dynamic evolution of the electronic and coordinate state of the distinct active sites induced by hemilabile PPh3-frame ligands and further disclose the regulatory mechanism of regioselectivity. These state-of-the-art techniques and multiscale analysis advance the understanding of how hemilabile coordination influences regioselectivity and will provide a new thought to modulate the regioselectivity in future industrial processes. Unveiling the regulatory mechanism of regioselectivity in hydroformylation has been a significant challenge. Here the authors successfully demonstrate how hemilabile coordination influences regioselectivity by employing various in situ techniques. [ABSTRACT FROM AUTHOR]

With the increasing number of maintenance hemodialysis (MHD) patients, growing attention has been paid to the quality of care. Strengthening care preparedness of family caregivers is essential to improving the nursing quality. The purpose of this study is to explore the care preparedness level of family caregivers of MHD patients and its influencing factors, so as to provide guidance for the development of targeted care interventions. A total of 237 family caregivers of MHD patients were recruited from the hemodialysis room of two tertiary hospitals in Wuhan using the Convenience sampling method. They were surveyed by the general data questionnaire, Care Preparedness Scale and Positive Aspects of Caregiving. Statistical analysis was conducted using IBM SPSS software, version 21.0. The statistical tests conducted in this study were two-tailed, and a significance level of P < 0.05 was deemed as statistically significant. The care preparedness and positive aspects of caregiving scores of family caregivers of MHD patients were 19.05 ± 5.64 and 31.28 ± 7.28 points, respectively. The care preparedness level of family caregivers was significantly positively correlated with positive aspects of caregiving (P < 0.01). The results of multiple linear regression analysis showed that the total nursing time and whether family caregivers had chronic diseases and positive aspects of caregiving were the main factors influencing their care preparedness (all P < 0.05). These three factors accounted for 49.6% of the variance. The care preparedness of family caregivers of MHD patients remains to be continuously improved. Medical staff should emphasize the important role of total nursing time, whether the caregiver has a chronic disease, and positive aspects of caregiving in improving care preparedness in this population. To achieve this end, medical staff can provide targeted support and guidance for caregivers according to the influencing factors, such as implementing group psychological education, strengthening the training, offering social support, remote intervention (including family caregivers’ education through the media), and so on. Meanwhile, caregivers should be evaluated dynamically, and information and emotional support should be provided for them. [ABSTRACT FROM AUTHOR]

The objective of this cross-sectional study was to examine the extent of sleep quality among individuals undergoing maintenance hemodialysis (MHD) and to scrutinize whether hope and family function serve as mediators in the association between anxiety and sleep quality in this cohort. A convenience sampling method was used to recruit 227 patients receiving maintenance hemodialysis from two tertiary hospitals in Wuhan. Participants completed several self-report questionnaires, including the Sociodemographic questionnaire, Hospital Anxiety and Depression Scale, Athens Insomnia Scale, Herth Hope Index, and Family APGAR Index. As per the findings of the chain mediation analysis, it was observed that the sleep quality scores were directly predicted by anxiety. Moreover, anxiety positively predicted sleep quality scores through hope and family function as mediators. The observed types of mediation were partial mediation. The total indirect effect value was 0.354, indicating the mediating effect of hope and family function, while the total effect value was 0.481, representing the overall effect of anxiety on sleep quality. The total effect size was 73.60% (0.354/0.481), indicating that the mediation accounted for a significant portion of the relationship. This study established the chain mediating effect of hope and family function between anxiety and sleep quality in patients receiving maintenance hemodialysis. The findings highlight the importance of addressing anxiety and promoting hope and family function to improve sleep quality in this population. The findings suggest that healthcare professionals should be attentive to the anxiety levels of these patients and implement targeted interventions to help alleviate anxiety, enhance hope, and improve family functioning, with the ultimate goal of improving sleep quality in this population. [ABSTRACT FROM AUTHOR]

Evidence of climate change can be observed in multiple climate variables, including air temperature rises and precipitation pattern changes. To manage water resources and agriculture effectively, it's important to project climate variables' changes at the local level, as these changes can vary depending on the specific area. The baseline weather data trend was analyzed using the percentage change (PC) method and the Innovative Trend Analysis (ITA) technique at three cluster levels: cluster 1 (PC: 0–20%), cluster 2 (PC: 21–80%), and cluster 3 (PC: 81–100%). The precipitation (Prec.), maximum (Tmax), and minimum (Tmin) temperatures showed downward trends in 9, 4, and 6 stations out of 24 stations, respectively. The SDSM model performed best in predicting Prec., while the LARS-WG model was more effective in predicting Tmax, Tmin, and solar radiation (SR). The average monthly Prec. percentage change shows both rising and falling trends in different weather areas for all three time periods (2040, 2060, and 2090) and for both RCPs (RCP4.5 and RCP8.5). In contrast to precipitation, both Tmax and Tmin consistently showed an upward trend across all meteorological stations for both RCPs and three-time frames. Across the four distinct plain regions, the overall projection suggests a slight increase in precipitation. The study predicts the highest increase in precipitation to occur in June across all meteorological stations. Seasonally, the greatest increase in precipitation is projected during summer (JJA) by 5.10%, while the largest decrease is expected during winter (DJF) by 3.29%. Additionally, precipitation variability shows an increase from RCP4.5 to RCP8.5 and from near-term (2040) to long-term (2090), with the northern Jiangsu Plain exhibiting the highest variation. The biggest rise in Tmax/Tmin was observed at RCP 8.5, by 2.69/2.39 °C, and in the long term (2090), by 3.25/2.86 °C. This was compared to RCP 4.5 by 1.73/1.51 °C, in the near term (2040) by 1.24/1.08 °C, and in the mid-term (2060) by 2.14/1.90 °C. The highest increase in Tmax is expected compared to Tmin, leading to the highest diurnal temperature (DTR) at all three periods and both RCPs. Seasonally, the highest increase is projected in the autumn for both Tmax and Tmin. Similar to Tmax and Tmin, the longest time period (2090) exhibits the highest increase in solar radiation, followed by the midterm (2060) and then the short term (2040). Unlike Tmax and Tmin, the highest increase in SR is predicted during the summer season (JJA), while the lowest increase is projected during the winter season (DJF). The future projections highlight the expectation of a wettest and hottest summer, along with the driest and coldest winter. These findings provide valuable insights for water resource planners, agricultural managers, and policymakers, as these climate variables play a significant role in crop production and water allocation decisions. [ABSTRACT FROM AUTHOR]

Assessment and analysis of water resource carrying capacity (WRCC) can provide practical guidance for regional water resources planning and management. Taking Anhui Province as an example, an evaluation indicator system is established from five aspects: water resource, society, economy, eco-environment and disaster, entropy weighting method and CRITIC method is combined to calculate the comprehensive weight of indicators. The GRA-TOPSIS model is adopted to evaluate regional WRCC, and the obstacle diagnosis model is used to identify the main factors limiting the improvement of WRCC. Additionally, this study analyzes the spatio-temporal changes of water resource, water resource use efficiency and population, and also examines whether the frequent drought disasters in Anhui Province pose a significant threat to the WRCC. The results show that: (1) The overall WRCC in Anhui Province shows a fluctuating upward trend, with a widening disparity among cities, particularly in southern Anhui Province. (2) Per capita water resources, surface water resources, groundwater resources, urbanization rate, per capita GDP, ecological water consumption and forest coverage rate are the main obstacles for the indicator layer, water resource is the main obstacle for the subsystem layer. (3) The spatio-temporal distribution of water resources in Anhui province is uneven, but the utilization efficiency of water resources is increasing year by year, and drought disasters impact the WRCC in Anhui Province but do not pose a significant threat. This study can provide scientific reference for the development and transformation mode of different regions in Anhui Province and realize the “five-in-one” sustainable development. [ABSTRACT FROM AUTHOR]

The streamflow process is an crucial information resource for the joint optimal operation of reservoirs. As the length and representativeness of historical streamflow samples are insufficient for practice projects, streamflow stochastic generation approaches are usually used to expand the streamflow series. For the joint operation and management of the multi-reservoir system, the multisite streamflow stochastic generation (MSSG) with high-dimensional temporal-spatial correlation poses a challenge. This paper develops the generative adversarial network as a novel MSSG model. In contrast to the existing literature on MSSG, which solely focuses on a specific case study and provides a comparatively one-sided assessment, this paper evaluates multiple characteristics of streamflow at various time scales from three MSSG models in two instances. Specifically, three MSSG models, namely the seasonal autoregression (SAR) model coupled with the master station method, the Copula model coupled with the master station method, and the deep convolutions generative adversarial network (DCGAN) model, are employed to generate monthly, ten-daily, and daily streamflow series of the two-reservoir and eight-reservoir systems. This study aims to examine the performance of three models and provide recommendations for implementing MSSG approaches in practice. Results show that: (1) the priority should be given to the maximum iterations on the DCGAN model at a large time scale, while at a smaller time scale, the training of the model is directly linked to the setting of batch size; (2) the Copula model is capable for better retaining statistical characteristics of streamflow series for similarity; (3) the SAR model excels in simulating the extremes of streamflow; and (4) the DCGAN model possesses a significant advantage in capturing the temporal-spatial higher-order correlation, especially in systems comprising more than two reservoirs and with small time scales (e.g., daily streamflow). Furthermore, this study presents comprehensive and multi-scale recommendations for selecting MSSG approaches, thereby providing a theoretical foundation and practical value for MSSG in diverse scenarios. [ABSTRACT FROM AUTHOR]

Drug-eluting stents are a commonly used treatment for coronary artery disease. However, the coatings used in drug-eluting stents have some limitations such as poor biocompatibility and drug loading capacity. In recent years, self-assembly methods have emerged as a promising alternative for stent coatings. Self-assembled coatings employ biomaterials and offer several advantages over traditional coatings, including thinner thickness, stronger binding capacity, and better biocompatibility. This review discusses the latest research on self-assembled biomaterial-based coatings for drug-eluting stents. We explore how layer-by-layer coatings and composite coating films have been utilized to load and release drugs with high drug loading capacity and biocompatibility, as well as how they promote endothelial adhesion and growth. Additionally, we examine how self-assembled coatings have been used to release active molecules for anti-coagulation and deliver gene therapy. Moreover, we discuss the potential of self-assembled coatings for future development, including intelligent targeted drug delivery, bionic stent coatings, and 3D printed stent coatings. These advancements have the potential to further improve the effectiveness of drug-eluting stents in treating coronary artery disease. The next-generation coronary artery stent by self-assembled coating: Self-assembled coatings in drug-eluting stents can bind biomaterials and offer several advantages over traditional coatings, including thinner structures, stronger binding capacity, and better biocompatibility. The encouraging achievements of self-assembled stent coatings include corrosion resistance, anti-fouling, anti-thrombogenicity, endothelialization, and targeted gene therapy. Future investigation and development of self-assembly in stent coatings will help improve the functionalities of self-assembled coatings in coronary artery stents and greatly extend their applications. [ABSTRACT FROM AUTHOR]

Coal–rock dynamic disasters often occur under the coupling effect of gas and stress. However, in engineering practice, coal–rock has different types of damage, and so, it is necessary to further study the physical characteristics of coal–rock containing gas under damage conditions. This is even more valuable in guiding relevant practical engineering. Based on this, a self-developed experimental system for monitoring the temperature change of coal–rock containing gas rupture was used to carry out uniaxial compression infrared monitoring experiments on fractured coal under different gas pressures, and in this way, the effects of gas pressure on the mechanical properties and infrared response characteristics of fractured coal were investigated. MATLAB was used for image processing and combined with the principle of statistics to extract the cracks information, and parameters such as crack length–quantity fractal dimension, crack image fractal dimension, and the maximum infrared radiation temperature (MIRT) time-series correlation fractal value were introduced for the characterization, which revealed the influence of gas pressure on it. It was found that, with increase in gas pressure, the NT (the number of surface cracks) increased, and the LA (the average trace length of the cracks) decreased when the crevasse coal was destroyed. Both the DL (the crack length–quantity fractal dimension) and the D (the fractal dimension) of crack images increased with increase in gas pressure; the gas had an inhibitory effect on the sudden change of the temperature field on the surface of coal, but on the contrary, it enhanced its fluctuation, and with increase in gas pressure, the MIRT was transformed from surge to sudden drop when the specimen was damaged, and the DC (the correlation fractal value) was linearly decreasing. The results explain the deterioration mechanism of fractured coal under the gas, reveal the influence of gas pressure on its infrared response, and have certain positive significance for disaster monitoring of similarly damaged coal. [ABSTRACT FROM AUTHOR]

To investigate the effect of teach-back strategy on hemodialysis related knowledge level, self-efficacy and self-management among hemodialysis patients. The research is a quasi-randomized control trial. A total of 92 patients receiving maintenance hemodialysis were randomly divided into observation group (n = 46) and control group (n = 46) by random number table method. The control group received conventional health education, and the observation group received teach-back. The intervention lasted six months. The hemodialysis related knowledge level, self-efficacy and self-management of the two groups were evaluated before and after the intervention. There were no significant difference on hemodialysis related knowledge level, self-efficacy and self-management scores between the two groups before intervention (P > 0.05). After intervention, the scores of hemodialysis knowledge in the observation group was higher than that in the control group and before intervention. The total scores of self-efficacy and items "3,4,5" were higher than those of the control group. The total scores of self-efficacy and item "1~6" in the observation group were higher than before intervention. The total scores of self-management and the three subscales of "problem solving", "partnership" and "emotional processing" were higher than those of the control group and before intervention. All of the above differences were statistically significant (P < 0.05). Teach-back is helpful to improve the hemodialysis related knowledge level, self-efficacy and self-management level of patients receiving maintenance hemodialysis, and it is worth to be popularized clinically. [ABSTRACT FROM AUTHOR]

Automatic combustion control (ACC) system is the main control system of the current municipal solid waste (MSW) incineration power plant. In this work, the artificial neural network (ANN) model was first used for prediction and guiding of operation of the incineration system. Results showed that BP-ANN model was an effective tool for operation parameter prediction, especially the crucial parameters of steam mass flow and furnace temperature. The Log-Sigmoid function was more suitable to be used as the transfer function in hidden layer. Comparison of the input parameter showed that furnace temperature, grate speed, primary air, and secondary air are the most important and relevant parameters for prediction of steam mass flow in MSW incineration system. The genetic algorithm (GA) could be used to optimize the initial weight and threshold values of the BP-ANN network, which largely improved the prediction accuracy. Impact weight analysis results show that furnace temperature and secondary have the largest influence on the steam flow. With regard to furnace temperature, secondary air, primary air, and oxygen concentration in exhaust gas play the leading roles. The largest error for steam mass flow prediction of the real-time operation was lower than 8%. [ABSTRACT FROM AUTHOR]

The rapid expansion of renewable energies asks for great progress of energy-storage technologies for sustainable energy supplies, which raises the compelling demand of high-performance rechargeable batteries. To satisfy the huge demand from the coming energy-storage market, the resource and cost-effectiveness of rechargeable batteries become more and more important. Manganese (Mn) as a key transition element with advantages including high abundance, low cost, and low toxicity derives various kinds (spinels, layered oxides, polyanions, Prussian blue analogs, etc.) of high-performance Mn-based electrode materials, especially cathodes, for rechargeable batteries ranging from Li-ion batteries, Na-ion batteries, aqueous batteries, to multivalent metal-ion batteries. It is anticipated that Mn-based materials with Mn as the major transition-metal element will constitute a flourishing family of Mn-based rechargeable batteries (MnRBs) for large-scale and differentiated energy-storage applications. On the other hand, several critical issues including Jahn-Teller effect, Mn dissolution, and O release greatly hinder the pace of MnRBs, which require extensive material optimizations and battery/system improvements. This review aims to provide an investigation about Mn-based materials and batteries for the coming energy-storage demands, with compelling issues and challenges that must be overcome. [ABSTRACT FROM AUTHOR]

The severe fever with thrombocytopenia syndrome virus (SFTSV) is a tick-borne human-infecting bunyavirus, which utilizes two envelope glycoproteins, Gn and Gc, to enter host cells. However, the structure and organization of these glycoproteins on virion surface are not yet known. Here we describe the structure of SFTSV determined by single particle reconstruction, which allows mechanistic insights into bunyavirus assembly at near-atomic resolution. The SFTSV Gn and Gc proteins exist as heterodimers and further assemble into pentameric and hexameric peplomers, shielding the Gc fusion loops by both intra- and inter-heterodimer interactions. Individual peplomers are associated mainly through the ectodomains, in which the highly conserved glycans on N914 of Gc play a crucial role. This elaborate assembly stabilizes Gc in the metastable prefusion conformation and creates some cryptic epitopes that are only accessible in the intermediate states during virus entry. These findings provide an important basis for developing vaccines and therapeutic drugs. The severe fever with thrombocytopenia syndrome virus (SFTSV, officially named Dabie bandavirus) is a tick-borne human-infecting bunyavirus. Here, the authors report the cryo-EM structure of SFTSV virion, and discuss the mechanisms of viral assembly, membrane fusion and antibody neutralization. [ABSTRACT FROM AUTHOR]

Key message: Two recessive powdery mildew resistance loci pmAeCIae8_2DS and pmAeCIae8_7DS from Aegilops tauschii were mapped and two synthesized hexaploid wheat lines were developed by distant hybridization. Wheat powdery mildew (Pm), one of the worldwide destructive fungal diseases, causes significant yield loss up to 30%. The identification of new Pm resistance genes will enrich the genetic diversity of wheat breeding for Pm resistance. Aegilops tauschii is the ancestor donor of sub-genome D of hexaploid wheat. It provides beneficial genes that can be easily transferred into wheat by producing synthetic hexaploid wheat followed by genetic recombination. We assessed the Pm resistance level of 35 Ae. tauschii accessions from different origins. Accession CIae8 exhibited high Pm resistance. Inheritance analysis and gene mapping were performed using F2 and F2:3 populations derived from the cross between CIae8 and a Pm susceptible accession PI574467. The Pm resistance of CIae8 was controlled by two independent recessive genes. Bulked segregate analysis using a 55 K SNP array revealed the SNPs were mainly enriched into genome regions, i.e. 2DS (13.5–20 Mb) and 7DS (4.0–15.5 Mb). The Pm resistance loci were named as pmAeCIae8_2DS and pmAeCIae8_7DS, respectively. By recombinant screening, we narrowed the pmAeCIae8_2DS into a 370-kb interval flanked by markers CINAU-AE7800 (14.89 Mb) and CINAU-AE20 (15.26 Mb), and narrowed the pmAeCIae8_7DS into a 260-kb interval flanked by markers CINAU-AE58 (4.72 Mb) and CINAU-AE25 (4.98 Mb). The molecular markers closely linked with the resistance loci were developed, and two synthesized hexaploid wheat (SHW) lines were produced. These laid the foundation for cloning of the two resistance loci and for transferring the resistance into common wheat. [ABSTRACT FROM AUTHOR]

Deep Learning-based edge caching networks can accurately infer what to cache based on a user's historical content requests, thereby significantly relieving the burden of the backbone networks. However, the cold-start problem inherent in deep learning may limit the performance of history-based caching strategies. Due to the mobile and dynamic nature of wireless networks, base stations often lack sufficient data to accurately estimate the user's demands and cache the possible requested data. In this context, we adopt self-supervised learning (SSL) into the caching strategies and propose a Simple Self-supervised Graph-based Recommendation framework for edge caching networks (SimSGR). Specifically, we propose two new network layers: the Mixing layer and the Conversion layer. The former replaces the data augmentation of the SSL paradigm to avoid destroying the semantic loss, while the latter greatly simplifies the loss function, which helps to lighten the model structure and facilitates deployment on edge caching networks. Simulation results show that our model outperforms baseline algorithms that are sensitive to augmentation hyper-parameters, particularly when trained in a cold-start environment. [ABSTRACT FROM AUTHOR]

Catalpol, a natural product mainly existed in plenty of Chinese traditional medicines, is an iridoid compound with the comprehensive effects on neuroprotective, anti-inflammatory, choleretic, hypoglycemic and anticancer. However, there are some disadvantages for catalpol such as a short half-life in vivo, low druggability, stingy binding efficiency to target proteins and so on. It is necessary to make structural modification and optimization which enhance its performance on disease treatments and clinic applications. Pyrazole compounds have been reported to have excellent anticancer activities. Based on the previous research foundation of our research group on iridoids and the anticancer activities of catalpol and pyrazole, a series of pyrazole modified catalpol compounds were synthesized by principle of drug combination for serving as potential cancer inhibitors. These derivatives are characterized by 1H NMR, 13C NMR and HRMS. The efficacy of anti-esophageal cancer and anti-pancreatic cancer activities were evaluated by the MTT assay on two esophageal cancer cells Eca-109 and EC-9706, and two pancreatic cancer cells PANC-1, BxPC-3 and normal pancreatic cell line HPDE6-C7, which showed that the compound 3e had strong inhibitory activity against esophageal cancer cells, this providing a theoretical basis for the discovery of catalpol-containing drugs. [ABSTRACT FROM AUTHOR]

Polydimethylsiloxane containing methacryloyloxy and methoxy silane groups (MAPDMS)-microcapsule-SiO2 (MPMS) functional materials were prepared by constructing micro-nano hierarchical structures on the surface of MAPDMS matrix. Herein, MAPDMS@1,1-stilbene-modified hydrolyzed polyglycidyl methacrylate/graphene oxide/dimethyloctadecyl[3-(trimethoxysilyl) propyl]ammonium chloride (MAPDMS@PGMAm/GO/QC18) self-healing microcapsules with compact multi-shell structure were synthesized and combined with nano-SiO2 to construct the hierarchical structures. Furthermore, ultraviolet (UV)/moisture dual curing mode was introduced into deep curing reaction and efficient self-healing reaction of the MPMS. The results show that the introduction of UV/moisture dual curing mode and micro-nano hierarchical structure gives MPMS functional materials excellent mechanical properties, antifouling properties, self-healing properties, and antibacterial properties. The shear strength and tensile strength of MPMS increase from 3.32 and 4.26 MPa of MAPDMS to 3.81 and 5.06 MPa, respectively. Its static contact angle increases from 115.9° of MAPDMS to 156.5°, and its slide angle decreases from 68.5° of MAPDMS to 7.8°, respectively. The antifouling performance of MPMS against seawater, soy sauce, juice, coffee, protein, and other contaminants is effectively improved compared with MAPDMS matrix. At the same time, the tensile strength and elongation at break of MPMS after healing reach 98.22% and 96.57% of those in original state, respectively. In addition, the antibacterial rates of MPMS against Escherichia coli and Staphylococcus aureus reach 99.85% and 100%, respectively. The MPMS prepared in this paper is expected to be widely used in marine antifouling, pipeline network, anti-icing, microfluidics, wearable devices, medical devices, electrochemical biosensors, and other fields. [ABSTRACT FROM AUTHOR]

Massive amounts of information are generated in various social media and spread across multi-social networks through individual forwarding and sharing, which greatly enhance the speed and scope of transmission, but also bring great challenges to the control and governance of misinformation. The characteristics of the spread of misinformation across multi-social networks are considered, this article investigates the novel problem of misinformation influence minimization by entity protection on multi-social networks, and systematically tackling this problem. We analyse the hardness and the approximation property of the problem. We construct a multi-social networks coupled method and devise a pruning and filtering rule. We develop a two-stage discrete gradient descent (TD-D) algorithm to solve NP-Hard problems. We also construct a two-stage greedy (TG) algorithm with the approximate guarantee to verify the algorithm we developed. Finally, the effectiveness of our proposed methods is analysed in synthetic and real multi-network datasets (contains up to 202K nodes and 2.5M edges). The results show that the ability of the TD-D and TG algorithms to suppress the spread of misinformation is basically the same, but the running time of the TG algorithm is much higher than (far more than 10 times) that of the TD-D algorithm. [ABSTRACT FROM AUTHOR]

Aiming at the damage misjudgment caused by incomplete modal information and unclear physical meaning of parameters in damage identification of long-span spatial structures, a damage identification method based on time-series analysis model established from measured data of structural health monitoring system is proposed. First, the selection method and modeling process of time-series analysis model based on acceleration response data are illustrated through the theoretical derivation. Subsequently, the damage sensitive feature (DSF) constructed by autoregressive parameters and Mahalanobis distance (MD) discriminant function is proposed for structural damage identification, which is dimension reduced by principal component analysis (PCA). Finally, based on the long-span steel structure in Taiyuan Botanical Garden, the effectiveness of damage identification method is studied by numerical simulation method, and the current damage status of the structure is identified through the measured data. The results show that the proposed method can effectively identify the structural damage, accurately locate the damage location and reflect the damage degree. The proposed DSF is sensitive to minor structural damage while reducing the amount of calculation. It is suitable for damage identification of complex structures and has application value in the analysis of health monitoring systems measured response data in practical engineering. [ABSTRACT FROM AUTHOR]

Quantifying the effects of climate change and catchment structure changes (like anthropic activities) on runoff variations effectively and accurately is always a challenge for hydrological community. In this study, three widely used methods: climate elasticity method, Budyko curve decomposition approach, and hydrologic simulation method, were applied in the Tao River basin, a typical first-order tributary of the Yellow River basin. The results indicated that the annual runoff of the Tao River basin dropped significantly, especially after 1986, with the changing rate of −13.66 mm/10a during the research period (1956–2014). According to the attribution results, in the moderate influenced period (1969–1986), the climate change was less influential than watershed structure changes to runoff variations, while after 1986, about 45% of the total decline in mean annual runoff were caused by the decreasing P and the significant rising air temperature, which enhances the watershed evaporation, and about 55% was probably attributed to watershed structure changes. There were systematic deviations between results from two Budyko-based conceptual approaches and hydrologic simulation method. The Budyko-based decomposition method tends to attribute more runoff variations to changes in watershed structure, while the hydrologic modeling approach tends to emphasize the influence of climate change on runoff changes at catchment scale. The difference in effect quantification is attributed to the errors in the mean annual runoff naturalization during the postchange period. The impacts of watershed structure changes induced by climate change (like vegetation condition changes) on runoff variations may fall into the human impact category in attribution calculation. [ABSTRACT FROM AUTHOR]

Key message: The QYm.nau-2D locus conferring wheat yellow mosaic virus resistance is an exotic introgression and we developed 11 diagnostic markers tightly linked to QYm.nau-2D. Wheat yellow mosaic virus (WYMV) is a serious disease of winter wheat in China. Breeding resistant varieties is the most effective strategy for WYMV control. A WYMV resistant locus QYm.nau-2D on the chromosome arm 2DL has been repeatedly reported but the mapped region is large. In the present study, we screened recombinants using a biparental population and mapped QYm.nau-2D into an 18.8 Mb physical interval. By genome-wide association studies of 372 wheat varieties for WYMV resistance in four environments, we narrowed down QYm.nau-2D into a 16.4 Mb interval. Haplotype analysis indicated QYm.nau-2D were present as six different states due to recombination during hybridization breeding. QYm.nau-2D was finally mapped into a linkage block of 11.2 Mb. Chromosome painting using 2D specific probes and collinearity analysis among the published sequences corresponding to QYm.nau-2D region indicated the block was an exotic introgression. The Illumina-sequenced reads of four diploid Aegilops species were mapped to the sequence of Fielder, a variety having the introgression. The mapping reads were significantly increased at the putative introgression regions of Fielder. Ae. uniaristata (NN) had the highest mapping reads, suggesting that QYm.nau-2D was possibly an introgression from genome N. We investigated the agronomic performances of different haplotypes and observed no linkage drag of the alien introgression for the 15 tested traits. For marker-assisted selection of QYm.nau-2D, we developed 11 diagnostic markers tightly linked to the locus. This research provided a case study of an exotic introgression, which has been utilized in wheat improvement for WYMV resistance. [ABSTRACT FROM AUTHOR]

Spatiotemporal variations in precipitation are closely related to vertically integrated moisture flux divergence (VIMD), where the extremes further cause natural disasters. Based on precipitation data from 151 meteorological stations in the Yangtze River Basin (YRB) for 1979 to 2019 and the meteorological reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), this paper studied the spatial and temporal characteristics of precipitation and VIMD and investigated their responsive relationship. The variations in precipitation and VIMD were examined using statistical methods, along with three step 'staircases' of terrain clusters dividing the whole basin based on descending altitude from west to the east. The results indicated that (1) the annual precipitation increased at a speed of 6.7 mm/10a during the study period: precipitation in spring, autumn and winter showed increasing trends, especially at the high elevation region (e.g., first step terrain), while a decreasing trend appeared in summer. (2) The VIMD trends in the YRB also varied in space and time, but overall, the summer trend pattern dominated the annual pattern. (3) The spatial distribution of VIMD agreed well with the topography clusters, where the first step terrain was dominated by convergence, and the second and third step terrains were dominated by divergence. (4) The average annual precipitation and seasonal precipitation showed responsive relationship with VIMD in terms of cumulative anomalies. Our results provided information on precipitation variability and revealed the characteristics of water vapor flux distribution as well as improved the understanding of the water transport mechanism in the YRB. [ABSTRACT FROM AUTHOR]

An experimental and theoretical study of CO2 absorption spectroscopy near 4.172 μm was conducted to acquire measurements of gas temperature and CO2 concentration in flames at near-atmospheric pressure. Scanned-wavelength laser absorption spectroscopy measurements were obtained in laminar non-premixed flames produced using either a Hencken burner or inside a fixed-volume combustion vessel. For the Hencken burner flame, the non-uniform distribution of gas conditions along the line-of-sight was estimated from computational fluid dynamics (CFD) simulations and accounted for in simulations of path-integrated absorbance spectra. Gas properties were inferred from measured absorbance spectra using two models: (1) an isolated line model employing the Voigt Profile and (2) a collisional line-mixing model. Regarding the latter, the relaxation matrix for CO2 in the line-mixing model was modified and scaled based on an empirically derived collisional-relaxation matrix for CO2–Ar. The collisional line-mixing model reduced the residuals of the best-fit spectra by approximately a factor of 4. In addition, the flame temperature obtained from the line-mixing model agreed well with that predicted by adiabatic equilibrium calculations and was typically 10% more accurate than those produced by the isolated line model, thereby illustrating the importance of accounting for collisional line mixing at the conditions and wavelengths studied despite the modest gas pressure and high temperature. [ABSTRACT FROM AUTHOR]

Despite the great success achieved by convolutional neural networks in addressing the raindrop removal problem, the still relatively blurry results call for better problem formulations and network architectures. In this paper, we revisited the rainy-to-clean translation networks and identified the issue of imbalanced distribution between raindrops and varied background scenes. None of the existing raindrop removal networks consider this underlying issue, thus resulting in the learned representation biased towards modeling raindrop regions while paying less attention to the important contextual regions. With the aim of learning a more powerful raindrop removal model, we propose learning a soft mask map explicitly for mitigating the imbalanced distribution problem. Specifically, a two stage network is designed with the first stage generating the soft masks, which helps learn a context-enhanced representation in the second stage. To better model the heterogeneously distributed raindrops, a multi-scale dense residual block is designed to construct the hierarchical rainy-to-clean image translation network. Comprehensive experimental results demonstrate the significant superiority of the proposed models over state-of-the-art methods. [ABSTRACT FROM AUTHOR]

To reduce losses from the various disasters, regional water security evaluation and risk control model is studied. The model is built upon different kinds of indices in water security system, proceeding from the whole structure and its parts of evaluation, forewarning and decision making analysis. Based on China's national conditions, this study firstly advances an evaluation index system of regional water security, which includes three subsystems of water resource security, water environment security, and water disaster control security. Secondly, fuzzy analytic hierarchy process based on accelerating genetic algorithm (AGA-FAHP) combines with entropy weight method (EW) to determine the objective weights of evaluation indexes. The subjective and objective weights can be integrated by the principle of minimum relative information entropy. The subsystem weights are obtained by using AGA-FAHP. Then regional water security evaluation model is established. Thirdly, the comparison judging method is adopted to divide warning degree of water security with the comprehensive evaluation index and forewarning standards, and then the local conditions for proposing planning schemes. Finally, decision making analysis is employed to find the effective indices based on projection pursuit technique with the ideal point method in multi-index decision. This study takes Jiangsu province, China as an example. The evaluation results from 2000 to 2015 show that the development trend of water security is increasing on the whole except in several individual years. Risk forewarning doesn't take place in recent years. But risk is always there. So, project and non-project measures are proposed for the corresponding forewarning levels. From light warnings for three times and moderate warning for once in 2000, 2001, 2002, and 2004, index 1, 3, 4, 11, 13, 17, and 18 are selected as the effective indices to decision making analysis in common. Then, the solution schemes are given as the processing method accordingly. This conclusion is reasonable and its method is practical that match the reality. It suggests that the presented model is feasible with theory and application, which can offer advice in regional water security management to some extent. [ABSTRACT FROM AUTHOR]

Urban microclimate modeling helps to quantitatively understand the fine level urban heat exposure distribution, which would provide an important reference for urban heat management. Fine level continuous sky view factor (SVF) maps are usually needed for modeling how the solar radiation fluxes reach the urban surface and impact the urban microclimate dynamics. However, the estimation of continuous SVF maps is very time-consuming, which limits the urban microclimate modeling to small geographical areas. In this study, we proposed to use graphics processing unit (GPU) parallel computing to accelerate the computing of SVF. The high-resolution digital surface models were used as the input to generate the continuous SVF maps of Philadelphia, PA, USA. Results show that the GPU-accelerated algorithms can reduce the time consumption of SVF computing by more than 99% using one NVIDIA GPU. Based on the computed SVF maps, this study further calculated and examined the spatial distribution of mean radiation temperature (Tmrt) as an indicator of outdoor heat exposure using the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model. There is an uneven distribution of the outdoor heat exposure in Philadelphia, and the eastern and southern parts have a higher heat exposure level. Increasing the tree canopy cover is an effective measure to reduce the heat exposure by providing more shade, especially for the eastern and southern parts of Philadelphia where shade is needed most. [ABSTRACT FROM AUTHOR]

Perception of content and structure in images with rainstreaks or raindrops is challenging, and it often calls for robust deraining algorithms to remove the diversified rainy effects. Much progress has been made on the design of advanced encoder–decoder single image deraining networks. However, most of the existing networks are built in a blind manner and often produce over/under-deraining artefacts. In this paper, we point out, for the first time, that the unsatisfactory results are caused by the highly imbalanced distribution between rainy effects and varied background scenes. Ignoring this phenomenon results in the representation learned by the encoder being biased towards rainy regions, while paying less attention to the valuable contextual regions. To resolve this, a context-enhanced representation learning and deraining network is proposed with a novel two-branch encoder design. Specifically, one branch takes the rainy image directly as input for learning a mixed representation depicting the variation of both rainy regions and contextual regions, and another branch is guided by a carefully learned soft attention mask to learn an embedding only depicting the contextual regions. By combining the embeddings from these two branches with a carefully designed co-occurrence modelling module, and then improving the semantic property of the co-occurrence features via a bi-directional attention layer, the underlying imbalanced learning problem is resolved. Extensive experiments are carried out for removing rainstreaks and raindrops from both synthetic and real rainy images, and the proposed model is demonstrated to produce significantly better results than state-of-the-art models. In addition, comprehensive ablation studies are also performed to analyze the contributions of different designs. Code and pre-trained models will be publicly available at https://github.com/RobinCSIRO/CERLD-Net.git. [ABSTRACT FROM AUTHOR]

Effects of the number of welding passes on microstructure and properties of 2219-C10S aluminum alloy tungsten inert gas (TIG) welded joints were analyzed in detail. The first capping weld had a solid solution effect on the backing weld. The second capping weld had a solid solution effect on the backing weld close to the capping weld and had an aging effect on the backing weld away from the capping weld. The sizes and quantities of the second phases in partially melted zone (PMZ) and over-aged zone (OAZ) increased slightly with the number of welding passes increased. The hardness of OAZ decreased slightly and its width increased slightly. The larger strain distribution range before tensile fractured of the joints was narrower and the range of plastic deformation of the joints was not significantly improved. The eutectic structure and θ phase at weld toes were not conducive to the tensile properties of joints. The tensile properties of double-pass welded joints were relatively ideal. [ABSTRACT FROM AUTHOR]

Engineering the interface plays a vital role in tuning the catalytic properties of supported metal nanocatalysts. Herein the 0.73%Au-4.13%FeOx@SBA-15 catalyst was constructed with SBA-15 as support and FeOx as modifier by interface engineering. It exhibited better catalytic activity than 0.71%Au/SiO2, 0.69%Au@SBA-15 and 0.71%Au/bulk-FeOx under identical conditions as well as higher selectivity towards cinnamyl alcohol for selective hydrogenation of cinnamaldehyde. It was found that the introduction of FeOx fabricated the interfacial area between Au and FeOx for H2 dissociation and consequently led to higher catalytic activity of 0.73%Au-4.13%FeOx@SBA-15. Meanwhile, both the channel of the SBA-15 support and the presence of small-sized FeOx promoted the selectivity for hydrogenation of C = O bond. It demonstrated for the first time that the interface engineering provided an efficient and facile avenue to design Au catalysts of excellent performances for selective hydrogenations. [ABSTRACT FROM AUTHOR]

Background: In China, traditional energy planning is subordinate to city planning, with a primary purpose of meeting the energy demand in urban areas by planning and designing an energy system. However, most of the current energy planning in China pertains to a low-efficient system and proves to be unfriendly to the environment, which is no longer appropriate for the future development of modern industrial parks and cities. Methods: A combined cooling, heating, gas and power energy network with distributed cogeneration units and renewable energy sources provides an effective solution to the related problems. In this paper, a new energy planning method for the Eco-City is proposed, which is based on a Distributed Energy Network (DEN) system. The designed method of a four-stage energy integration mode is implemented, which includes prediction of the energy demand, optimization of the energy utilization, matching of the energy supply and the recovery side. Based on the planning and designing of the DEN, the technical and economic analysis draw reasonable results. Results: As implemented in the practical case of the Sino-German Eco-Park, the procedure of the proposed energy planning method is comprehensively explained. Finally, by reviewing the planning, design and operation, the current state and problems of the Sino-German Eco-Park are described. Conclusions: A new energy design for Eco-Parks is developed as a result of a thorough analysis of the planning process, which integrates city planning and energy planning together and provides energy solutions for high-level cities and industrial parks. The four-stage integrated energy model provides a guideline for the entire process and its detailed steps. Relevant experiences and lessons from the energy planning of the Sino-German Eco-Park are of significance for supporting similar projects in the future. [ABSTRACT FROM AUTHOR]

The North Anhui Province Plain (NAHPP), an important food production plain in China, is prone to frequent droughts and floods. To better understand the extreme events and mitigate their effects, this paper explores the spatiotemporal variation of precipitation extremes in the NAHPP during 1976 and 2018. Variation trends and spatial distributions of the annual maximum 1-day, 3-day, 7-day, and 15-day-rainfall were analyzed, and the probability distribution of rainfall extremes in the NAHPP was calculated by three distribution functions (Gumbel, P-III, and generalized extreme value). The optimal fitting function was selected based on the Kolmogorov–Smirnov test, and the rainfall in different return periods was calculated according to the optimal fitting function. The results indicate that rainfall extreme showed a 2- to 3-year periodicity on the interannual scale and 21-year periodicity on the chronological scale in the NAHPP. The rainfall extremes showed nonsignificant increase trend over the NAHPP, and some stations showed no significant decrease trend. The P-III distribution function best fit to the rainfall extremes (the maximum 1-day rainfall: 59%). The spatial distributions of rainfall extremes were similar in different return periods. As the return period increased, the estimated rainfall by the three distribution functions were slightly larger than that in the empirical return period. The findings will benefit regional water resources management and water-related risk control. [ABSTRACT FROM AUTHOR]

Let S be a nonempty semigroup endowed with a binary associative operation ∗ . An element e of S is said to be idempotent if e ∗ e = e . Originated by one question of P. Erdős to D.A. Burgess: If S is a finite semigroup of ordern, does any S -valued sequenceTof lengthncontain a nonempty subsequence the product of whose terms, in some order, is idempotent?, we make a study of the associated invariant, denoted I (S) and called Erdős–Burgess constant which is the smallest positive integer ℓ such that any S -valued sequence T of length ℓ contains a nonempty subsequence the product of whose terms, in some order, is an idempotent. Let S R be the multiplicative semigroup of any commutative unitary ring R. We prove that I (S R) is finite if and only if R is finite, provided that the quotient ring R/J(R) of R modulo its Jacobson radical J(R) is not a direct product of an infinite Boolean unitary ring and finitely many finite fields. As a consequence, if R is Noetherian, then I (S R) is finite if and only if R is finite. [ABSTRACT FROM AUTHOR]

Droughts have caused many damages in many countries and might be aggravated around the world. Therefore, it is urgent to predict and monitor drought accurately. Soil moisture and its corresponding drought index (e.g., soil water deficit index, SWDI) are the key variables to define drought. However, in situ soil moisture observations are inaccessible in many areas. This study applies support vector machine (SVM) by using a new set of inputs to investigate the performance of in situ and remote sensing products (CMORPH-CRT, IMERG V05 and TRMM 3B42V7) for soil moisture and SWDI forecast over the Xiang River Basin. This study also assesses whether the addition of remote sensing soil moisture as input can improve the performance of SWDI prediction. The results are as follows: (1) the new set of inputs is suitable for drought prediction based on SVM; (2) using in situ precipitation as input to SVM shows the best performance for soil moisture prediction, which followed by TRMM 3B42V7, IMERG V05 and CMORPH-CRT; (3) in situ precipitation and IMERG V05 as input are more suitable for indirect SWDI prediction, while CMORPH-CRT and TRMM 3B42V7 are more suitable for direct SWDI prediction; (4) the addition of soil moisture with in situ precipitation or CMORPH-CRT both can improve the performance of direct SWDI prediction; (5) the lead time for drought prediction with SVM over the Xiang River Basin is about 2 weeks. [ABSTRACT FROM AUTHOR]

Evapotranspiration is a key component of the hydrological cycle. It is important to understand the features of the variation of potential evapotranspiration and the impacts of its drivers to estimate regional water consumption. The Huang–Huai–Hai (HHH) River Basin is comprised of three major rivers (the Yellow, Huai and Hai) and has been threatened by water shortages and huge consumption of water for agricultural and industrial development. In this study of the Huang–Huai–Hai (HHH) River Basin, potential evapotranspiration (E0) across the basin was calculated using the Penman–Monteith model, and their changing characteristics were detected by using the Mann–Kendall test. The test was based on the daily climatic variables from 1965 to 2014 at 175 meteorological gauges. In addition, the influential effect of net radiation (Rn), relative humidity (RHU), wind speed (WIN), mean, maximum and minimum air temperature (Ta, Tmax and Tmin) on E0 were analyzed by using the climate elasticity method, with their relative contribution to the changes of E0 quantitatively revealed by using the multiple linear regression method. The results showed that Rn, WIN, RHU and Ta are the predominant climatic predictors that are more influential to E0 while Tmax and Tmin have the least impact. The increase in annual E0 in the period of 1985–2014 in the HHH River Basin was mainly attributed to the significantly increasing Ta, which may greatly offset the effect of decreasing WIN and Rn. The decrease of annual E0 in the period of 1965–2014 in the middle area of the basin was mainly attributed to the falling WIN and Rn. [ABSTRACT FROM AUTHOR]

Traditionally, hydrogen peroxide (H2O2) was formed from cellular oxidative metabolism and often viewed as toxic waste. In fact, H2O2 was a benefit messenger for neuron-glia signaling and synaptic transmission. Thus, H2O2 was a double-edged sword and neuroprotection vs. neurotoxicity produced by H2O2 was difficult to define. Nuclear factor erythroid 2-related factor 2 (Nrf2) has been implicated as an intracellular regulator of neuronal growth. Inactivation of Nrf2 participated in the development of Parkinson's disease (PD). Thus, suitable activation of Nrf2 was essential for the prevention and treatment of PD. This study aimed to explore whether H2O2-conferred neuroprotective effects to support neuronal survival. H2O2 were added into primary neuron-glia, neuron-astroglia and neuron-microglia co-cultures in concentration- and time-dependent manners. H2O2 increased dopamine (DA) neuronal survival in concentration- and time-dependent manners. In addition, glial cells Nrf2 activation involved in H2O2-supported DA neuronal survival with the following phenomenons. First, H2O2 activated Nrf2 signaling pathway. Second, H2O2 generated beneficial neuroprotection in neuron-glia, neuron-astroglia and neuron-microglia co-cultures but not in neuron-enriched cultures. Third, silence of Nrf2 in glial cells abolished H2O2-conferred DA neuronal survival. This study demonstrated that physiological concentration of H2O2-supported DA neuronal survival via activation of Nrf2 signaling in glial cells. Our data permit to re-evaluate the role of H2O2 in the pathogenesis and therapeutic strategies for PD. [ABSTRACT FROM AUTHOR]

River regulation by the construction of reservoirs represents one of the greatest challenges to the natural flow regime and ecological health of riverine systems globally. The Danjiangkou (DJK) Reservoir is the largest reservoir on the Hangjiang River and commenced operations in 1967. The reservoir was upgraded in 2012 to provide water resource for the South–North water transfer project through central China. However, the effect of the reservoir operations on the downstream hydrological regime and ecological health of the Hanjiang River following the upgrade (increase in dam height and reservoir capacity) has not been examined thus far. The daily discharge series from four stations along the main stem of the Hanjiang River, including a site upstream, were examined from 1950 to 2017. The study series was divided into three periods based on the difference stages of the reservoir operation: (1) 1950–1966, (2) 1967–2012 and (3) 2013–2017. The nature of hydrological alteration, ecological flow requirement and potential ecological risk during the different periods were investigated. The results clearly indicate that the DJK reservoir has significantly modified the hydrological regime in the middle and downstream section of the Hanjiang River, with most significant modifications recorded immediately downstream of the reservoir. None of the observed 'Range of Variability Approach' hydrological indicators fell within the expected range at Huangjiagang following the increase in reservoir capacity. As a result, the ecological flow requirements could not be guaranteed, and the frequency and intensity of ecodeficit increased. The river ecosystem immediately downstream of the dam was observed to be at high risk of ecosystem degradation during the post-dam periods considered. [ABSTRACT FROM AUTHOR]

In this work, we have synthesized gold nanoparticles (AuNPs) using flavonoids of Scutellaria barbata as reducing and stabilizing agent. The prepared AuNPs were studied by using various spectroscopic and microscopic techniques. TEM analysis showed the formation of 20 nm sized spherical nanoparticles. XRD analysis confirmed the formation of crystalline face centred cubic structured particles. Further, we studied the as prepared AuNPs for their efficiency to act as a novel class of amyloid-β (Aβ) inhibitors. The results showed that several small and relatively amorphous aggregates validated the exceptional efficiency of AuNPs in inhibiting Aβ40 aggregation. Therefore, the prepared AuNPs has future prosperous towards the treatment of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Given a finite commutative semigroup (written additively), denote by [ABSTRACT FROM AUTHOR]