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Background: With increasing gaps between the rich and poor, potential risk factors for class conflict have attracted increasing attention from researchers. Although cognitive factors are known to be significant predictors of classconflict behavior, limited attention has been paid to competence stereotypes of the upper class. When considering economic inequality, people pay more attention to competence stereotypes of the upper class, which may have adverse effects. This study aimed to investigate the relationship between competence stereotypes held by the lower class about the upper class and class conflict, and to test the mediating role of intergroup envy in this relationship and the moderating role of upward social mobility belief. Methods: Data were collected from a convenience sample from a comprehensive university in China. Based on scores on subjective and objective class scales, 284 lower-class college students (103 males and 181 females) aged 18-24 were selected to participate (both their subjective and objective scores were lower than 3 points). Their endorsement of upper-class competence stereotypes, intergroup envy, upward social mobility beliefs, and class conflict were measured using a well-validated self-report questionnaire. Results: The main data were analyzed using correlation analysis, the SPSS macro PROCESS (Model 7), and simple slope analysis. The results show a significant positive correlation between competence stereotypes held by lower-class college students toward the higher class and class conflict, and this connection was mediated by intergroup envy. Moreover, the indirect effect of intergroup envy on this link was moderated by upward social mobility beliefs; this effect was stronger for college students with lower upward social mobility beliefs. Conclusion: This study broadens our understanding of how and when competence stereotypes among the lower class concerning the upper class are related to class conflict. Researchers and policymakers should pay special attention to competence stereotypes of the upper class, especially intergroup envy and class conflict among lower-class individuals with lower levels of upward social mobility beliefs. [ABSTRACT FROM AUTHOR]

Urban land use provides essential information about how land is utilized within cities, which is critical for land planning, urban renewal, and early warnings for natural disasters. Although existing studies have utilized multi-source perception data to acquire land use information quickly and at low cost, and some have integrated urban morphological indicators to aid in land use identification, there is still a lack of systematic discussion in the literature regarding the potential of three-dimensional urban morphology to enhance identification effectiveness. Therefore, this paper aims to explore how urban three-dimensional morphology can be used to improve the identification of urban land use types. This study presents an innovative approach called the UMH–LUC model to enhance the accuracy of urban land use identification. The model first conducts a preliminary classification using points of interest (POI) data. It then improves the results with a dynamic reclassification based on floor area ratio (FAR) measurements and a variance reclassification using area and perimeter metrics. These methodologies leverage key urban morphological features to distinguish land use types more precisely. The model was validated in the Pearl River Delta urban agglomeration using random sampling, comparative analysis and case studies. Results demonstrate that the UMH–LUC model achieved an identification accuracy of 81.7% and a Kappa coefficient of 77.6%, representing an 11.9% improvement over a non-morphology-based approach. Moreover, the overall disagreement for UMH–LUC is 0.183, a reduction of 0.099 compared to LUC without urban morphology and 0.19 compared to EULUC-China. The model performed particularly well in identifying residential land, mixed-use areas and marginal lands. This confirms urban morphology's value in supporting low-cost, efficient land use mapping with applications for sustainable planning and management. [ABSTRACT FROM AUTHOR]

During its long service life, an arch dam affected by a combination of factors exhibits a typical time-varying characteristic in terms of its structure and material properties, and the deformation in the dam structure can directly and reliably reflect the health and service status of dams. Therefore, an accurate deformation prediction is an important part of dam safety monitoring. However, due to multiple factors, dam deformation data often tend to be highly volatile, and most existing deformation estimation techniques employ a single algorithm, which may not effectively capture the potential change process. A hybrid model for dam deformation prediction has been proposed to overcome this problem. First, dam deformation data are decomposed into three components by seasonal and trend decomposition using loess. Second, a convolutional neural network–gated recurrent unit (GRU) hybrid model, which optimizes hyperparameters using the sparrow search algorithm, is used to capture the nonlinear relationships that exist in each component. Finally, the final prediction result of dam deformation is the comprehensive output of multiple submodules. The deformation monitoring data (period: 2009–2019) of a parabolic variable-thickness double-curved arch dam located in China are considered as the survey target. The test results indicate that the proposed model is suitable for short-term and long-term prediction and outperforms other models in terms of higher robustness to abnormal sequences than other conventional models (R² differs by 5.50% and 7.87%, respectively, in short-term and long-term predictions for different measurement points, while other models differ by 9.78% to reach 15.71%, respectively). Among the models studied, the GRU shows better robustness to abnormal series than the LSTM with good prediction accuracy, fewer parameters, and a simpler structure. Hence, the GRU can be employed for dam deformation prediction in practical engineering. [ABSTRACT FROM AUTHOR]

Deformations in dam structures can have a critical impact on dam safety and life. Accurate methods for dam deformation prediction and safety evaluation are thus highly needed. Dam deformations can be predicted based on many factors. The analysis of these influences on the deformation of the dam reveals a problem that deserves further attention: dam deformation lags behind environmental factors of the water level and temperature as well as the time lag of the temporal dam deformation data. In this paper, a hybrid deep learning model is proposed to enhance the accuracy of dam deformation forecasting based on lag indices of these factors. In particular, dam deformations are predicted using deep networks based on gated recurrent units (GRUs), which can effectively capture the temporal characteristics of dam deformation. In addition, an improved particle swarm optimization (IPSO) algorithm is used for optimizing the GRU hyperparameters. Furthermore, the complete ensemble empirical mode decomposition with adaptive noise algorithm (CEEMDAN) and the partial autocorrelation function (PACF) are exploited to select the lag factor indices. The accuracy and effectiveness of the proposed CEEMDAN–PACF–IPSO–GRU hybrid model were evaluated and compared with those of other existing models in terms of four different evaluation indices (MAE, MSE, R2 , and RMSE) and using 9-year historical data for the case of a pulp-masonry arch dam in China. The experimental results show that our model outperforms other models in terms of the deformation prediction accuracy (R2 increased by 0.16%–9.74%, while the other indices increased by 14.55% to reach 96.69%), and hence represents a promising framework for general analysis of dam deformations and other types of structural behavior. [ABSTRACT FROM AUTHOR]

Logistics is the booster of economic development, and it is imperative to further improve the logistics energy efficiency and adjust its development model. This paper is an attempt to investigate the logistics energy efficiency and main influencing factors of the Yangtze River Economic Belt, which is the most economically intensive region that spans East, Central, and West China. The input-oriented SBM-DEA model is employed to identify factors such as energy input, undesirable output, and service capacity output as well as the logistics energy efficiency of Yangtze River Economic Belt. Energy efficiency is then further decomposed into pure technical efficiency, scale efficiency, and technical efficiency, from the perspective of which provinces and cities are compared. The research results show that the logistics energy efficiency of Yangtze River Economic Belt needs to be further improved and that energy efficiency differs greatly among cities and provinces, indicating that the development is quite unbalanced in different areas. Therefore, the local government should develop development strategies according to the main influencing factors and constraints to the local logistics industry, so as to optimize and upgrade the energy structure of the logistics industry. [ABSTRACT FROM AUTHOR]

Since the Internet is currently being utilized in initial public offerings (IPOs), there has been a fundamental change in how IPOs can be distributed. Through the Internet, firms issue shares to a wider range of smaller investors. From the perspective of online marketing, we focus on the influences of information disclosure on IPO performance and corporate governance. We analyze if a higher degree of IPO firm performance in the IPO aftermarket is related to corporate governance. We build a corporate governance index CG for IPO firms, composed of equity structure, board characteristics, management style and disclosure quality. Through empirical evidence, we confirm that the threshold of information disclosure has positively effect on IPO firms performance. In particular, IPO firms with higher CG experience significant increases in EPS and ROA in the post-marketing. The impact of corporate governance on IPO firm performance is significant in the economic boom and non-significant in the economic recession. [ABSTRACT FROM AUTHOR]

Arthrinium has a widespread distribution occurring in various substrates (e.g., air, soil debris, plants, lichens, marine algae and even human tissues). It is characterized by the basauxic conidiogenesis in the asexual morph, with apiospores in the sexual morph. In this study, seventeen isolates of Arthrinium were collected in China. Based on their morphology and phylogenetic characterization, four new species (A. biseriale , A. cyclobalanopsidis , A. gelatinosum , and A. septatum) are described and seven known species (A. arundinis , A. garethjonesii , A. guizhouense , A. hydei , A. neosubglobosa , A. phyllostachium and A. psedoparenchymaticum) are identified, of which the sexual morph of three species (A. guizhouense , A. phyllostachium and A. psedoparenchymaticum) and asexual morph of A. garethjonesii are reported for the first time. The detailed descriptions, illustrations and comparisons with related taxa of these new collections are provided. Phylogenetic analyses of combined ITS, LSU, TUB2, and TEF sequence data support their placements in the genus Arthrinium and justify the new species establishments and identifications of known species. [ABSTRACT FROM AUTHOR]

Despite the significant progress in improving chemical transport models (CTMs), applications of these modeling endeavors are still subject to large and complex model uncertainty. The Model Inter-Comparison Study for Asia III (MICS-Asia III) has provided the opportunity to assess the capability and uncertainty of current CTMs in East Asian applications. In this study, we have evaluated the multi-model simulations of nitrogen dioxide (NO2), carbon monoxide (CO) and ammonia (NH3) over China under the framework of MICS-Asia III. A total of 13 modeling results, provided by several independent groups from different countries and regions, were used in this study. Most of these models used the same modeling domain with a horizontal resolution of 45 km and were driven by common emission inventories and meteorological inputs. New observations over the North China Plain (NCP) and Pearl River Delta (PRD) regions were also available in MICS-Asia III, allowing the model evaluations over highly industrialized regions. The evaluation results show that most models captured the monthly and spatial patterns of NO2 concentrations in the NCP region well, though NO2 levels were slightly underestimated. Relatively poor performance in NO2 simulations was found in the PRD region, with larger root-mean-square error and lower spatial correlation coefficients, which may be related to the coarse resolution or inappropriate spatial allocations of the emission inventories in the PRD region. All models significantly underpredicted CO concentrations in both the NCP and PRD regions, with annual mean concentrations that were 65.4 % and 61.4 % underestimated by the ensemble mean. Such large underestimations suggest that CO emissions might be underestimated in the current emission inventory. In contrast to the good skills for simulating the monthly variations in NO2 and CO concentrations, all models failed to reproduce the observed monthly variations in NH3 concentrations in the NCP region. Most models mismatched the observed peak in July and showed negative correlation coefficients with the observations, which may be closely related to the uncertainty in the monthly variations in NH3 emissions and the NH3 gas–aerosol partitioning. Finally, model intercomparisons have been conducted to quantify the impacts of model uncertainty on the simulations of these gases, which are shown to increase with the reactivity of species. Models contained more uncertainty in the NH3 simulations. This suggests that for some highly active and/or short-lived primary pollutants, like NH3 , model uncertainty can also take a great part in the forecast uncertainty in addition to the emission uncertainty. Based on these results, some recommendations are made for future studies. [ABSTRACT FROM AUTHOR]

Nitric oxide (NO) and nitrogen dioxide (NO2) are relevant to air quality due to their roles in tropospheric ozone (O3) production. In China, NOx emissions are very high and NOx emissions exhausted from on-road vehicles make up 20 % of total NOx emissions. In order to detect the NO and NO2 emissions on road, a dual-channel cavity ring-down spectroscopy (CRDS) system for NO2 and NO detection has been developed. In the system, NO is converted to NO2 by its reaction with excess O3 in the NOx channel, such that NO can be determined through the difference between two channels. The detection limits of NO2 and NOx for the system are estimated to be about 0.030 (1σ , 1 s) and 0.040 ppb (1 σ , 1 s), respectively. Considering the error sources of NO2 absorption cross section and RL determination, the total uncertainty of NO2 measurements is about 5%. The performance of the system was validated against a chemiluminescence (CL) analyser (42i, Thermo Scientific, Inc.) by measuring the NO2 standard mixtures. The measurement results of NO2 showed a linear correction factor (R2) of 0.99 in a slope of 1.031±0.006 , with an offset of (-0.940±0.323) ppb. An intercomparison between the system and a cavity-enhanced absorption spectroscopy (CEAS) instrument was also conducted separately for NO2 measurement in an ambient environment. Least-squares analysis showed that the slope and intercept of the regression line are 1.042±0.002 and (-0.393±0.040) ppb, respectively, with a linear correlation factor of R2=0.99. Another intercomparison conducted between the system and the CL analyser for NO detection also showed a good agreement within their uncertainties, with an absolute shift of (0.352±0.013) ppb, a slope of 0.957±0.007 and a correlation coefficient of R2=0.99. The system was deployed on the measurements of on-road vehicle emission plumes in Hefei, and the different emission characteristics were observed in the different areas of the city. The successful deployment of the system has demonstrated that the instrument can provide a new method for retrieving fast variations in NO and NO2 plumes. [ABSTRACT FROM AUTHOR]

On 23 August 2017 a Category 3 hurricane, Typhoon Hato, struck southern China. Among the hardest hit cities, Macau experienced the worst flooding since 1925. In this paper, we present a high-resolution survey map recording inundation depths and distances at 278 sites in Macau. We show that one-half of the Macau Peninsula was inundated, with the extent largely confined by the hilly topography. The Inner Harbor area suffered the most, with a maximum inundation depth of 3.1 m at the coast. Using a combination of numerical models, we simulate and reproduce this typhoon and storm surge event. We further investigate the effects of tidal level and sea level rise on coastal inundations in Macau during the landfall of a "Hato-like" event. [ABSTRACT FROM AUTHOR]

Background: There have been some gradual changes in the distribution of renal biopsy pathological diagnoses during recent years. This study aimed to show changes in renal disease prevalence in China by investigating 10 patients diagnosed at our Kidney Disease Centre during the last 15 years. Methods and results: All patients aged 15-year-old or older who underwent renal biopsy at the First Affiliated Hospital, Zhejiang University, from 2001 to 2015 were enrolled. There were 5 common types of primary glomerulonephritis: IgA nephropathy (IgA N), membranous nephropathy (MN), mesangial progressive glomerulonephritis (MsPGN), minimal change disease (MCD), and focal segmental glomerulosclerosis (FSGS), which represented 50%, 16.8%, 15.9%, 8.1% and 2.5% of total cases, respectively. IgA nephropathy was the most common type of primary glomerulonephritis (PGN). Conclusions: Our results mostly showed a new trend that the diagnosis of IgA nephropathy was not increasing and the prevalence of membranous nephropathy had increased, becoming the second most common type of primary glomerulonephritis. Key POINTS: Distinguished with other domestic studies, IgA nephropathy did not show a trend of continuous growth although it still had about the half proportion of PGN, whereas membranous nephropathy kept rising and became the second common PGN. Concerning SGN, LN peaked in the younger-age and middle-age groups with a significant female prevalence, DN, BANS and SV had a male predominance peaking in the middle-age and old-age groups. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau is one of the highest regions in the world, exerting profound influence on the large-scale atmospheric circulation of Asia and the global climate. Here we report ambient concentrations of black carbon (BC), aerosol mass (PM and PM) and associated carbonaceous species and water-soluble inorganic ions from a remote mountain site in the southeastern part of the Tibetan Plateau during spring, in order to characterize the major sources contributing to the ambient aerosol in the background atmosphere of Southeast Asia. Significant build-up of aerosol and BC concentrations was observed during a dry period, accompanied by the occurrence of fires and transport of pollution from the nearby regions of Southeast Asia and the northern part of the Indian Peninsula. The concentrations of BC, PM and PM mass reached maximum hourly values of 1470 ng m, 107 and 117 μg m, respectively. Organic carbon (OC), elemental carbon (EC) and sulfate were the predominant aerosol components. OC showed strong correlations with EC ( R= 0.93 for PM and 0.74 for PM) and non-sea-salt potassium, especially in fine aerosol ( R= 0.95). In addition, the relative change rates of K against OC reached characteristically high values, highlighting the important contributions of biomass-burning smoke. [ABSTRACT FROM AUTHOR]

Objectives: TORCH infections caused by Toxoplasma gondii (TOX), rubella virus (RV), cytomegalovirus (CMV) and herpes simplex virus 1,2 (HSV-1,2) are associated with congenital anomalies. The study aimed to analyze the characteristics of TORCH screening in reproductive age women.Methods: A total of 18,104 women (2015-2017) from a teaching hospital in Xi'an, China, were enrolled in the study. The characteristics of TORCH screening, i.e., the application of TORCH test, the seroprevalence, the impact of age, periods of gestation and woman with bad obstetric history (BOH) on the serological data were investigated.Results: In the study, 319 women (1.76%) performed dynamic TORCH test. 51.66, 20.44 and 3.83% of the population did the test in the pre-gestation period, the first and third trimester, respectively. Quite a few pre-gestation women (29.74%) ignored screening of IgG antibodies. The overall IgG/IgM seropositvity of TOX, RV, CMV, HSV-1 and HSV-2 was 4.35%/0.35, 90%/0.63, 96.79%/0.97, 81.11%/0.14 and 6.1%/0.19%, respectively. The age-specific distributions and periods of gestation had no significant effect on the seroprevalence of TORCH agents, p>0.05. However, BOH was significantly associated with higher seropositvity of IgM (RV, CMV, HSV-1 and HSV-2) and IgG (CMV and HSV-1) antibodies, p < 0.05.Conclusion: In Xi'an region, more attentions should be paid to TOX, CMV, HSV-2 and the women with BOH for TORCH screening. Meanwhile, a greater emphasis needs to be placed on TORCH test used inappropriately in China. [ABSTRACT FROM AUTHOR]

Abstract This study investigated isotopic signatures of carbon (C), lead (Pb) and strontium (Sr) in PM 2.5 samples collected from two paired sites (urban vs. rural/background) in northern Taiwan during the summer of 2015 and the spring of 2016, respectively. Significant seasonality was revealed in the isotopic signatures of C and Pb, whereas no seasonal difference was observed in 87Sr/86Sr ratio. The values of δ13C, 206Pb/207Pb, and 208Pb/207Pb were more diverse and exhibited local features in summer. However, during the episodes of continental pollution outbreaks in springtime, the δ13C and Pb isotope ratios of PM 2.5 shifted and converged consistently toward the documented characteristics of particulate matters in northern China. Moreover, the results showed that the differences in the Pb and Sr isotopic characteristics between the paired urban and rural sites were statistically insignificant, whereas marginally lower δ13C values were observed at the urban site. It was inferred accordingly that a substantial amount of gaseous hydrocarbons emitted in local urban areas could have been converted to secondary organic aerosols with lower δ13C. On the contrary, the consistency in the spatial and temporal variations of mass concentration and isotope ratios of Pb at the two sites suggested that East-Asian continental pollution outbreak was the major source of Pb-containing particles in the northern Taiwan during springtime. It is noteworthy that there was neither seasonal nor spatial differences in the 87Sr/86Sr ratio observed in this study, which suggested that the Sr-containing particles collected in this study could be originating from a common mixture of sources, including not only natural dust but also the anthropogenic emissions, coal-combustion for instance. This investigation upon the C-Pb-Sr isotopic features evidenced the substantial impacts of the continental pollution outbreaks on the aerosol composition and air quality in the downwind areas of the East-Asian winter monsoons. Graphical abstract Unlabelled Image Highlights • Seasonal and temporal variations of C-Pb-Sr isotopes of PM 2.5 were investigated. • C and Pb in PM 2.5 exhibited significant seasonal isotope signatures. • Isotopic evidences for the impacts of Asian outflows on air quality were revealed. • Consistent Sr isotope ratios were observed from local and distant sources. [ABSTRACT FROM AUTHOR]

Abstract: Intensive measurements of aerosol (PM10) and associated water-soluble ionic and carbonaceous species were conducted in Guangzhou, a mega city of China, during summer 2006. Elevated levels of most chemical species were observed especially at nighttime during two episodes, characterized by dramatic build-up of the biomass burning tracers levoglucosan and non-sea-salt potassium, when the prevailing wind direction had changed due to two approaching tropical cyclones. High-resolution air mass back trajectories based on the MM5 model revealed that air masses with high concentrations of levoglucosan (43–473 ng m−3) and non-sea-salt potassium (0.83–3.2 μg m−3) had passed over rural regions of the Pearl River Delta and Guangdong Province, where agricultural activities and field burning of crop residues are common practices. The relative contributions of biomass burning smoke to organic carbon in PM10 were estimated from levoglucosan data to be on average 7.0 and 14% at daytime and nighttime, respectively, with maxima of 9.7 and 32% during the episodic transport events, indicating that biomass and biofuel burning activities in the rural parts of the Pearl River Delta and neighboring regions could have a significant impact on ambient urban aerosol levels. [Copyright &y& Elsevier]

Abstract: In this study, the synoptic weather types that have high probability and low probability of producing PM10 episode are referred to as HPE and LPE, respectively. Multiple linear regressions analysis showed that NO2 was the most important contributor (35.61%) to the concentrations of PM10 for HPE weather. For LPE weather, the season factor had the greatest contribution (48.11%) to the concentrations of PM10. Using the correlation coefficients between the concentrations of PM10 and SO2 or NO2 on HPE and LPE to calculate the increase of PM10 from LPE to HPE, we found that the increase of PM10 owing to the increase of SO2 and NO2 from LPE to HPE was 12.93μg/m3 which was about 51% of the total amount of PM10 increased from LPE to HPE. Results of factor analysis showed that the first component could be attributed to the result of local pollution especially for the weather patterns of types P3 and P6, while the secondary component for the weather patterns of types P1 and P4 can be attributed to the long-range transport of SO2 pollutants from China. [Copyright &y& Elsevier]

High and steep slopes which have developed fractures and intercalations are a great threat to the operation of dams and reservoirs. In this work, the geological conditions and potential modes of failure of the slope found in the right bank of Suofengying hydropower station are investigated for the slope stability and the results are presented. In order to strengthen the slope, an innovative stabilization scheme is employed. The stabilization techniques include development of anti-shear tunnels, anti-slide piles, anchor cables, concrete support structure, etc. Further, the slope stability and reinforcement effects using various stabilization techniques are studied by using finite element strength reduction method. Moreover, in situ monitoring is carried out and the data obtained is analyzed. From the results, it is observed that the deformations that are detected using multipoint extensometers have decreased after the installation of remedial reinforcements. From the analysis of remedial reinforcement methods, it is found that the most critical reinforcement is the development of anti-shear tunnels. In order to monitor the stresses in stirrups and the propagation of cracks in the anti-shear tunnels, three levels of safety monitoring index are proposed. The safety monitoring index is developed based on the results obtained by the simulation of the process of failure of the reinforced slope. The developed safety monitoring index is further applied to the Suofengying project in order to evaluate the overall stability of the slope. The results obtained by monitoring indicate that the performance of the reinforcement structures is satisfactory and the slope has better stability. The methodology proposed in this work shall be useful for similar projects to obtain stability of slopes. • The steep slope is huge in geological scale and complex. • Various stabilization measures are presented to strengthen the slope. • Slope stability and effectiveness are studied under different reinforcement measures. • The failure process of the reinforced slope is investigated. • In situ monitoring data is analyzed and three levels of safety monitoring index are proposed. [ABSTRACT FROM AUTHOR]