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Objective: To investigate whether Naoxueshu Oral Liquid (NXS) could promote hematoma absorption in post-craniotomy hematoma (PCH) patients. Methods: This is an open-label, multicenter, and randomized controlled trial conducted at 9 hospitals in China. Patients aged 18–80 years with post-craniotomy supratentorial hematoma volume ranging from 10 to 30 mL or post-craniotomy infratentorial hematoma volume less than 10 mL, or intraventricular hemorrhage following cranial surgery were enrolled. They were randomly assigned at a 1:1 ratio to the NXS (10 mL thrice daily for 15 days) or control groups using a randomization code table. Standard medical care was administered in both groups. The primary outcome was the percentage reduction in hematoma volume from day 1 to day 15. The secondary outcomes included the percentage reduction in hematoma volume from day 1 to day 7, the absolute reduction in hematoma volume from day 1 to day 7 and 15, and the change in neurological function from day 1 to day 7 and 15. The safety was closely monitored throughout the study. Moreover, subgroup analysis was performed based on age, gender, history of diabetes, and etiology of intracerebral hemorrhage (ICH). Results: A total of 120 patients were enrolled and randomly assigned between March 30, 2018 and April 15, 2020. One patient was lost to follow-up in the control group. Finally, there were 119 patients (60 in the NXS group and 59 in the control group) included in the analysis. In the full analysis set (FAS) analysis, the NXS group had a greater percentage reduction in hematoma volume from day 1 to day 15 than the control group [median (Q1, Q3): 85% (71%, 97%) vs. 76% (53%, 93%), P<0.05]. The secondary outcomes showed no statistical significance between two groups, either in FAS or per-protocol set (P>0.05). Furthermore, no adverse events were reported during the study. In the FAS analysis, the NXS group exhibited a higher percentage reduction in hematoma volume on day 15 in the following subgroups: male patients, patients younger than 65 years, patients without diabetes, or those with initial cranial surgery due to ICH (all P<0.05). Conclusions: The administration of NXS demonstrated the potential to promote the percentage reduction in hematoma volume from day 1 to day 15. This intervention was found to be safe and feasible. The response to NXS may be influenced by patient characteristics. (Registration No. ChiCTR1800017981) [ABSTRACT FROM AUTHOR]

Uncaria rhynchophylla is an important traditional herbal medicine in China, and the yield and quality of Uncaria rhynchophylla can be improved by suitable soil conditioners because of changing the soil properties. In this paper, Uncaria rhynchophylla associated alkaloids and soil microbial communities were investigated. The field experiment was set up with the following control group: (M1, no soil conditioner) and different soil conditioner treatment groups (M2, biomass ash; M3, water retention agent; M4, biochar; M5, lime powder and M6, malic acid). The results showed that M2 significantly increased the fresh and dry weight and the contents of isorhynchophylline, corynoxeine, isocorynoxeine, and total alkaloids. Acidobacteria, Proteobacteria, Actinobacteria, and Chloroflexi were major bacterial phyla. Correlation analysis showed that fresh and dry weight was significantly positively correlated with Acidobacteria, while alkali-hydrolyzable nitrogen, phosphatase activity, fresh and dry weight, corynoxeine, and isocorynoxeine were significantly negatively correlated with Chloroflexi. The application of soil conditioner M2 increased the abundance of Acidobacteria and decreased the abundance of Chloroflexi, which contributed to improving the soil nutrient content, yield, and quality of Uncaria rhynchophylla. In summary, biomass ash may be a better choice of soil conditioner in Uncaria rhynchophylla growing areas. [ABSTRACT FROM AUTHOR]

The genus Svistella Gorochov, 1987 includes 10 species from Asia, with nine documented in China. In this study, a new species, Svistella yayun He, sp. nov., is described from Xizang, China. Morphologically, it resembles S. rufonotata (Chopard, 1932) but can be distinguished by a smaller inner tympanum, dark-brown setae on the 5th segment of the maxillary palp, and a rounded apex on the ectoparamere. To validate our morphological inferences and support the description of S. yayun sp. nov. as a new species, we performed a PCA based on bioacoustics parameters and molecular analysis. All Svistella species documented in China are distinguished by integrating their songs and DNA barcoding. [ABSTRACT FROM AUTHOR]

In previous taxonomic studies, identification of Atlanticus species was mainly based on male morphological features, such as cercus, tenth abdominal tergum and subgenital plate. In this study, we systematically revise eight Atlanticus species (61 individuals) in East China. We sequence COI genes of all samples for identification, and compare morphologies and male calling songs. The classification based on male cerci, calling songs, and COI genes is consistent. In contrast, the morphologies of male tenth abdominal tergum and subgenital plate varied among species. In addition, we regard A. jiangyei Liu, Wang & Cheng, 2016 as a junior synonym of A. pieli Tinkham, 1941, and A. helleri Liu, Wang & Cheng, 2016 as a junior synonym of A. kiangsu Ramme, 1939. [ABSTRACT FROM AUTHOR]

The industrial sector is China's major element of energy consumption and carbon emissions, and carbon emissions reduction in industrial parks has become an important foothold in carbon reduction work. Predicting the future evolution trend of carbon emissions in industrial parks under different policy orientations is of great significance for China to achieve the carbon emissions peaking and carbon neutrality goals. Based on the current status of electricity consumption and carbon emissions in industrial parks, this paper takes a light industrial park as the research object, analyzes the source of carbon emissions in this park, combines the characteristics of resource endowment and industrial structure, and considers the factors influencing society, load curve, energy supply and carbon sink, thus constructing a system dynamics model of carbon emission evolution for this park. Different influencing factors are selected to set multiple target scenarios, and the GDP, carbon emissions, carbon emissions reduction and near‐zero carbon evaluation coefficient of light industrial parks are used as characterization indicators for simulation analysis. The analysis results revealed that the comprehensive scenario set by increasing the maximum installed capacity of renewable energy units and raising the proportions of environmental and science and technology inputs while adjusting the industrial growth rate of the park performed best. In this scenario, the economic development of the park and the process of carbon emissions reduction are considered. [ABSTRACT FROM AUTHOR]

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013–2022), the first ten-year stage of the lifespan CCNP (2013–2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0–17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the "Chinese Data-sharing Warehouse for In-vivo Imaging Brain" in the Chinese Color Nest Project (CCNP) – Lifespan Brain-Mind Development Data Community (https://ccnp.scidb.cn) at the Science Data Bank. [ABSTRACT FROM AUTHOR]

The radiance of sky brightness differs principally with wavelength passband. Atmospheric scattering of sunlight causes the radiation in the near-infrared band. The Antarctic is a singular area of the planet, marked by an unparalleled climate and geographical conditions, including the coldest temperatures and driest climate on Earth, which leads it to be the best candidate site for observing in infrared bands. At present, there are still no measurements of night-sky brightness at DOME A. We have developed the Near-Infrared Sky Brightness Monitor (NISBM) in the J ,  H , and K s bands for measurements at DOME A. The instruments were installed at DOME A in 2019 and early results of NIR sky brightness from 2019 January–April have been obtained. The variation of sky background brightness with solar elevation and scanning angle is analysed. The zenith sky flux intensity for the early night at DOME A in the J band is in the 600–1100 μJy arcsec−2 range, that in the H band is between 1100 and 2600 μJy arcsec−2, and that in the K s band is in the range ∼200–900 μJy arcsec−2. This result shows that the sky brightness in J and H bands is close to that of Ali in China and Mauna Kea in the USA. The sky brightness in the K s band is much better than that in Ali, China and Mauna Kea, USA. This shows that, from our early results, DOME A is a good site for astronomical observation in the K s band. [ABSTRACT FROM AUTHOR]

Purpose: Inconsistent controlling factors of soil water content (SWC) spatial variation across regions and spatial scales have been acknowledged in previous studies. However, universal principles explaining these inconsistencies are still needed to be explored. The main aim of this study was to conclude the universal principles across regions and scales. Materials and methods: In this study, based on the surface (< 10-cm soil depth) SWC dataset from Meng et al. (2021) (https://doi.org/10.5194/essd-13-3239-2021) and the relevant environmental variables (climate including temperature and precipitation, topography including elevation and slope, soil including sand and clay contents, and vegetation including normalized difference vegetation index or NDVI) in a 1500 km × 1500 km study region in China, we calculated the correlations between them, and identified the controlling factors of surface SWC in different subregions and at different spatial scales. Results and discussion: Local factors like temperature, precipitation, and clay content that controling the vertical soil water replenishment and removal dominated the surface SWC spatial variation in this dry study region (mean SWC ≤ 0.10 m3 m−3). Nonlocal factors like topography (e.g., elevation and slope) and soil porosity (sand content) determining the lateral soil water redistribution had outweighed effects in the representative wet subregion. In addition, topography also exerted considerable effects on SWC in this study region due to its great spatial variability, especially when spatial scale < 800 km. As NDVI was complicatedly controlled by other environmental variables, its effect on SWC performed dramatic regional differentiation. In contrast, effect of slope on SWC was more associated with its spatial variability as it was independent from other environmental variables. Conclusions: This study emphasized that the inconsistencies of controlling factors of SWC spatial variation can be comprehensively explained by different regimes in the dry and wet conditions, spatial variability of environmental variables and the interactions among different environmental variables. These findings can deepen our understanding of the controls on SWC spatial variation across regions and scales. [ABSTRACT FROM AUTHOR]

Salinity and alkalinity are among the important factors affecting the distribution, survival, growth and physiology of aquatic animals. Chinese sea bass (Lateolabrax maculatus) is an important aquaculture fish species in China that can widely adapt to diverse salinities from freshwater (FW) to seawater (SW) but moderately adapt to highly alkaline water (AW). In this study, juvenile L. maculatus were exposed to salinity change (SW to FW) and alkalinity stress (FW to AW). Coordinated transcriptomic responses in L. maculatus gills were investigated and based on the weighted gene co-expression network analysis (WGCNA), 8 and 11 stress-responsive modules (SRMs) were identified for salinity change and alkalinity stress, respectively, which revealed a cascade of cellular responses to oxidative and osmotic stress in L. maculatus gills. Specifically, four upregulated SRMs were enriched with induced differentially expressed genes (DEGs) for alkalinity stress, mainly corresponding to the functions of "extracellular matrix" and "anatomical structure", indicating a strong cellular response to alkaline water. Both "antioxidative activity" and "immune response" functions were enriched in the downregulated alkaline SRMs, which comprised inhibited alkaline specific DEGs, revealing the severely disrupted immune and antioxidative functions under alkalinity stress. These alkaline-specific responses were not revealed in the salinity change groups with only moderately inhibited osmoregulation and induced antioxidative response in L. maculatus gills. Therefore, the results revealed the diverse and correlated regulation of the cellular process and stress response in saline-alkaline water, which may have arisen through the functional divergence and adaptive recruitment of the co-expression genes and will provide vital insights for the development of L. maculatus cultivation in alkaline water. [ABSTRACT FROM AUTHOR]

The distribution of heavy metals in the agricultural areas from a cattle-producing area near the Zhangbei Dam grassland, Hebei province, China, was investigated for providing the basis for the control of pollution in a rural farmland. Fifty-three surface soil samples including 28 soils of potato and 25 soils of oats were collected and analyzed for the distribution of Cd, Cu, Pb, Zn, Cr, As, Hg, and Ni. Furthermore, the ecological risk of soils contaminated with heavy metals was evaluated by employing the single factor index, the Nemerow comprehensive pollution index and geo-accumulation index, and potential ecological hazard index. The results showed that the contents of the eight heavy metals in soil planted with potato were below the risk screening values. The single factor index in soils planted with hulless oats showed that the concentrations of Cd, Hg, and Ni surpassed the Chinese screening limits by 8%, 4%, and 8%, respectively. According to the geo-accumulation index, 4% of samples reached the level of medium ecological risk for Cd. According to the results of ecological risk assessment, the studied soils generally showed a mild pollution degree. According to the health risks assessment results, the carcinogenic risks should be considered non-negligible. Arsenic is the dominant carcinogenic pollutant for human beings in the county. The main sources of pollution are mining and application of fertilizers. [ABSTRACT FROM AUTHOR]

Once the sludge was directly used in the farmland, it will have a negative impact on human health through the food chain because sludge contains pollutants. Sewage sludge pyrolysis into biochar is an effective way to realize sludge harmless and resourceful utilization. This research used hydrothermal carbonization method to convert sludge into sludge biochar (SLBC) to reduce the types and contents of pharmaceuticals and personal care products (PPCPs) and available heavy metals. Furthermore, migration of the residual caffeine (Caf), acetaminophen (Ace), and heavy metals (Cr, Pb, Cu, Zn) released from the SLBC in the wheat was assessed. The results showed that the levels of Caf, Ace, Pb, Cu, and Zn accumulated in the shoots were lower than the limit regulated by Drug and Food Additive Use Standard in China (Caf: 150 mg/kg; Ace: 2.5 ~ 5 mg/kg; Pb: 0.3 mg/kg; Cu: 10 mg/kg; Zn: 20 mg/kg). The migration of Cr from roots to shoots was also significantly controlled by SBLC. SBLC delayed the germination time of wheat seeds with increasing in hydrothermal temperature, the germination rate and root length showed a decreasing trend. Evans blue and O2− fluorescence staining of root tips also confirmed this conclusion. When the wheat was exposed to the low temperature and dose of SLBC, the chlorophyll contents and growth of wheat can be significantly increased; the oxidative damage of cell plasma membrane and net photosynthetic rate were reduced. However, 0.8 g/L of SLBC made plants suffer abiotic stress and caused oxidative damage to plants, and decreased membrane system stability. The study provides some parameters for sludge to realize resource utilization in the agricultural system. [ABSTRACT FROM AUTHOR]

Purpose: To develop and validate a risk prediction model for coronary heart disease (CHD) in snorers with hypertension, including traditional and new risk factors. Patients and Methods: Twenty factors were evaluated in the records of 2810 snorers with hypertension. Training (70%) and validation (30%) sets were created by random allocation of data, and a new nomogram model was developed. The model's discrimination and calibration were measured by calculating the area under the receiver operating curve (AUC) and creating calibration charts. The performance of the nomogram model was compared with that of the Prediction for ASCVD Risk in China (China-PAR) and Framingham models by decision curve analysis. An optimal cutoff point for the risk score in the training set was computed to stratify patients. Results: In the nomogram model, the AUCs for predicting CHD at 5, 7 and 9 years in the training set were 0.706 (95% confidence interval [CI] 0.649– 0.763), 0.703 (95% CI 0.655– 0.751) and 0.669 (95% CI 0.593– 0.744), respectively. The respective AUCs were 0.682 (95% CI 0.607– 0.758), 0.689 (95% CI 0.618– 0.760) and 0.664 (95% CI 0.539– 0.789) in the validation set. The calibration chart showed that the predicted events from the nomogram score were close to the observed events. Decision curve analysis indicated that the nomogram score was slightly better than the Prediction for ASCVD Risk in China (China-PAR) and Framingham models for predicting the risk of CHD in snorers with hypertension. A cutoff point was identified for being CHD-free (a nomogram score of ≤ 121), which could be helpful for the early identification of individuals at high-risk of CHD. Conclusion: The nomogram score predicts the risk probability of CHD in snorers with hypertension at 5, 7 and 9 years, and shows good capability in terms of discrimination and calibration. It may be a useful tool for identifying individuals at high risk of CHD. [ABSTRACT FROM AUTHOR]

Purpose: Traditional measurement for soil properties is time-consuming and costly, while visible–near-infrared spectroscopy enables the rapid prediction of soil properties. In this study, visible–near-infrared spectroscopy was used to predict these four soil properties including OC (organic carbon) content, TN (total nitrogen) content, pH value, and clay content in rare earth mining areas based on different spectral transformation and calibration methods. Materials and methods: A total of 232 soil samples were collected from unexploited, in situ leaching, and heap leaching mining areas in southern Jiangxi Province, China. The chemical properties and reflectance spectra of air-dried samples were measured. Spectral transformations including first-order derivative (FOD), continuum removal (CR), and continuous wavelet transform (CWT) were selected to improve the prediction accuracy of the model. Partial least-squares regression (PLSR), the support vector machine (SVM), and extreme gradient boosting (XGBoost) were used to construct prediction models. Results and discussion: The highest prediction accuracies in terms of the coefficient of determination (R2), root mean square error (RMSE), and relative prediction deviation (RPD) were obtained using CWT spectra with XGBoost for organic carbon content (R2 = 0.89, RMSE = 0.24, RPIQ = 4.67), total nitrogen content (R2 = 0.86, RMSE = 0.01, RPIQ = 4.14), and pH value (R2 = 0.73, RMSE = 0.19, RPIQ = 1.66). The best prediction result for clay content was obtained using CWT spectra with the SVM (R2 = 0.67, RMSE = 6.45, RPIQ = 2.75). Conclusions: The CWT coupled with a non-linear model, such as XGBoost, is an effective method for the accurate prediction of soil properties in rare earth mining areas. [ABSTRACT FROM AUTHOR]

Visible–near‐infrared (Vis‐NIR) spectroscopy is increasingly used to predict soil organic carbon (SOC) content. However, the prediction accuracy of this technology is dependent on model selection and study scale. This study explored the roles of spectral variable selection and stratified calibration based on soil type in Vis‐NIR spectroscopy for predicting SOC content at a provincial scale. A total of 490 samples, collected in Jiangxi Province (southeast China), were used for modeling with partial least squares regression, support vector machine, random forests, and back‐propagation neural network (BPNN). The feature wavebands of soil samples were selected by competitive adaptive reweighted sampling (CARS), and a stratified calibration was conducted based on soil type. The results showed that CARS‐based models outperformed models with full wavebands in predicting the SOC content. The CARS‐BPNN model combined with stratified calibration showed the best prediction performance for total soils (validation set R2 =.82, which was.21 higher than that of BPNN based on global calibration). This study established an accurate method to predict SOC content from provincial‐scale spectral data using the CARS‐BPNN model coupled with stratified calibration based on soil type. Core Ideas: Four models were used for large‐scale SOC content prediction in Jiangxi Province, China.The feature wavebands of red soils and paddy soils were extracted by the CARS procedure.CARS‐based models achieved higher prediction accuracy than models using full wavebands.CARS‐BPNN with stratified calibration based on soil type predicted SOC content accurately. [ABSTRACT FROM AUTHOR]

Purpose. In the Chinese population, we looked at the relationship between the hepatic steatosis index (HSI) and the risk of type 2 diabetes mellitus (T2DM). Methods. To evaluate the association between HSI and the risk of T2DM, Cox regression models were employed. Hazard ratios (HR) and 95 percent confidence intervals (CI) were computed. A stratified analysis with interaction testing was also carried out. Additionally, we evaluated the incremental predictive value of the HSI over the established risk factors using the C-statistic, the IDI, and the NRI. Results. During a median follow-up period of 2.97 years, 433 (1.97%) participants developed new-onset T2DM. The smoothing curve fit plot showed a positive correlation between HSI and the risk of T2DM. After adjusting for all noncollinear variables, the risk of T2DM increased by 62% for every 1 standard deviation (SD) increase in HSI. Subgroup analysis indicated that higher HSI levels were associated with a higher risk of T2DM in those aged < 40 years. The addition of HSI enhanced the reclassification and discrimination of established risk factors, with an IDI of 0.027 and an NRI of 0.348 (both P < 0.001). Conclusion. Our findings suggest that an elevated HSI is substantially associated with a greater risk of T2DM in the Chinese population. HSI has the potential to be an available and supplementary monitoring method for the management of T2DM risk stratification in the Chinese population. [ABSTRACT FROM AUTHOR]

This article effectively identifies the high and low volatility state of asset prices in China by constructing the MS-AR model, and further investigates the relationship between different dimensions of liquidity and asset price volatility. Moreover, we try to incorporate liquidity into the analytical framework and adopt the TVP-SV-VAR model to study the time-varying characteristics between monetary policy, liquidity, asset price volatility and macroeconomy. The results are as follows: firstly, it shows that the high or low volatility state of China's stock market and real estate market can be clearly divided, and display the consistency with the trend of asset price volatility. Secondly, liquidity has a strong ability to explain the high and low volatility state of asset prices, but it shows some hysteresis effects. Thirdly, the time-varying results reveal that monetary policy has a regulating effect on liquidity, and the response cycle of quantitative monetary policy is relatively short, which reflects the effects of macroeconomy precisely. However, price-based monetary policy has a longer response cycle and plays a vital role in the anticipatory adjustment and fine-tuning of asset price volatility. These conclusions can provide an explanation for the attention to asset price bubbles and potential financial risks, and offer decision-making references for the central bank to implement differentiated and dynamic monetary policy choices. [ABSTRACT FROM AUTHOR]

Steroidogenesis controls the conversion of cholesterol into steroid hormones through the complex cascade reaction of various enzymes, which play essential roles in sexual differentiation and gonadal development in vertebrates, including teleosts. Japanese flounder (Paralichthys olivaceus) and Chinese tongue sole (Cynoglossus semilaevis) are important marine cultured fishes in China and have remarkable sexual dimorphism with bigger females and sex reversal scenarios from female to neo-male. Several steroidogenic genes have been analyzed individually in the two species, but there is a lack of information on the coordinated interaction of steroidogenic gene regulation. Therefore, in this study, through genomic and transcriptomic analysis, 39 and 42 steroidogenic genes were systematically characterized in P. olivaceus and C. semilaevis genomes, respectively. Phylogenetic and synteny analysis suggested a teleost specific genome duplication origin for cyp19a1a/cyp19a1b, hsd17b12a/hsd17b12b, ara/arb and esr2a/esr2b but not for star/star2 and cyp17a1/cyp17a2. Comparative transcriptome analysis revealed conserved expression patterns for steroidogenic genes in P. olivaceus and C. smilaevis gonads; star/star2, cyp11a/cyp11c, cyp17a1/cyp17a2, cyp21a, hsd3b1, hsd11b and hsd20b were strongly expressed in testis, while cyp19a1a and hsd17b genes were highly expressed in ovaries. Only a few genes were differentially expressed between male and neo-male testis of both P. olivaceus and C. semilaevis, and even fewer genes were differentially regulated in the brains of both species. Network analysis indicated that cyp11c, cyp17a1 and hsd3b1 actively interacted with other steroidogenic genes in P. olivaceus and C. semilaevis, and may play a more sophisticated role in the steroid hormone biosynthesis cascade. The coordinated interaction of steroidogenic genes provided comprehensive insights into steroidogenic pathway regulation with a global biological impact, as well as sexual development in teleost species. [ABSTRACT FROM AUTHOR]

Economic losses due to snow‐related disasters in pastoral areas of China have become severe in recent decades. Terrain and wind play prominent roles in determining snow distribution patterns. As complex topography and dynamic wind conditions are strong nonlinear multivariables with many uncertain factors, it is difficult to predict elevation‐ and wind‐affected snow depth distribution. The complex characteristics of the snow accumulation process call for highly reliable comprehensive simulation for disaster management. The accuracy of these simulations mainly depends on the integration of multiple models for multi‐stage snow accumulation processes. Focusing on coupling wind‐affected snowdrift and snowmelt processes, we put forward a virtual geographical environment snow accumulation simulation approach. The approach consists of three main steps: (1) computational fluid dynamics prediction of 3D dynamic wind‐flow fields; (2) wind‐affected snowdrift simulation; and (3) snowmelt simulation based on degree‐day model. To check its reliability and efficiency, this approach has been validated by reconstructing a historical snow event at Tacheng City, Xinjiang Province, China. The results have characterized the elevation‐ and wind‐induced snowdrift patterns and their specific levels of risk under various conditions. The comprehensive simulation method described here can be applied to help the government and the public examine future events, and stimulate consideration of appropriate policies and techniques for snow risk mitigation. [ABSTRACT FROM AUTHOR]

Background: The delta variant (B.1.617.2) of SARS-CoV-2 was the dominant viral strain causing COVID-19 in China, 2021. We reported a SARS-CoV-2 delta variant outbreak in Jingmen City, Hubei Province, China. Methods: The data of epidemiological, clinical, laboratorial, and vaccination of COVID-19 cases were collected through field investigation and analyzed. Results: During the outbreak from 4 to 20 August 2021, 58 cases of the SARS-CoV-2 delta variant (B.1.617.2) were identified with 15 (25.9%) asymptomatic and 43 (74.1%) symptomatic (mild and moderate) patients. The mean serial interval was 2.6 days (standard deviation: 2.0, 95% CI: 1.9–3.6). The median age of the patients was 39 years (ranging from 1 to 60 years) with the high proportion in children (19.0%). The secondary attack rate was 9.8% higher from parents to their children (<18 years) (46.2%, 95% CI: 14.8–77.5%) than that between spouses (36.4%, 95% CI: 14.5–58.2%), but no significant difference was observed (p > 0.05). Approximately half (27; 46.6%) of cases were vaccine breakthrough infections. In vaccine breakthrough cases (fully vaccinated), viral loads decreased 1.9–3.4-folds (p < 0.05), duration of viral shedding shortened 5 days (p < 0.05), and the risk of becoming symptomatic from asymptomatic decreased 33% (95% CI: 5–53%) (aged ≥12 years) than those in unvaccinated infections. Conclusions: Children are highly susceptible to the SARS-CoV-2 delta variant in the COVID-19 outbreak in Jingmen City in 2021. Inactivated vaccine derived from wide-type strain can effectively reduce the viral load, duration of viral shedding, and clinical severity in vaccine breakthrough cases. Our study indicates that protective measures that include full vaccination against COVID-19, especially in children, should be strengthened. [ABSTRACT FROM AUTHOR]

Reliable assessment of landslide susceptibility in broad areas of terrain remains challenging due to complex topography and poor representation of randomly selected negative samples. Assessment in broad areas is now primarily based on grid units, which do not have a clear physical meaning like slope units, and their accuracy is not ideal. Nevertheless, the large amount of manual editing, due to the incorrectly generated horizontal and vertical lines during slope unit partitioning, limits using slope units for rapid assessment over large areas. Hence, this paper proposes a reliable susceptibility assessment approach to solve this problem based on optimal slope units and negative samples involving prior knowledge. Precisely, an algorithm to automatically extract slope units is designed to eliminate fragmented and erroneous units. Second, a samples labeling index (SLI) is defined based on the certainty factors model to select negative samples reasonably. Sichuan Province, China is selected for experimental analysis, with the results demonstrate that the optimized slope unit and the negative samples selection strategy consider prior knowledge achieve better results in the random forest model, support vector machine model, and artificial neural network model. In particular, the composite performance index AUC of artificial neural network model improved from 0.81 to 0.90. [ABSTRACT FROM AUTHOR]

Sugarcane mosaic virus (SCMV; genus Potyvirus) induces maize dwarf mosaic disease that has caused serious yield losses of maize in China. Cross-protection is one of the efficient strategies to fight against severe virus strains. Although many mild strains have been identified, the spontaneous mutation is one of the challenging problems affecting their application in cross-protection. In this study, we found that the substitution of cysteine (C) at positions 57 or 60 in the zinc finger-like motif of HC-Pro with alanine (A; C57A or C60A) significantly reduced its RNA silencing suppression activity and SCMV virulence. To reduce the risk of mild strains mutating to virulent ones by reverse or complementary mutations, we obtained attenuated SCMV mutants with double-mutations in the zinc finger-like and FRNK motifs of HC-Pro and evaluated their potential application in cross-protection. The results showed that the maize plants infected with FKNK/C60A double-mutant showed symptomless until 95 days post-inoculation and FKNK/C60A cross-protected plants displayed high resistance to severe SCMV strain. This study provides theoretical and material bases for the control of SCMV through cross-protection. [ABSTRACT FROM AUTHOR]

Soil moisture is a limiting factor for vegetation restoration on the Loess Plateau, China. Micro-topography may cause heterogeneities in the distribution of soil moisture, but little is known about its effect on deep soil moisture. Our study aims to explore the distribution and impact of soil moisture within the upper 10 m of soil for different microtopographies. Taking undisturbed slope as the control, five micro-topographies were selected. Soil moisture over a depth of 0–10 m from 2017 to 2019 was investigated, and soil particle size and soil organic matter were measured. Variance analysis and multiple comparisons were used to analyze the difference in soil moisture for different microtopographies and multiple-linear regression was used to analyze the influence of micro-topography on soil moisture. There are significant differences in soil moisture within the different layers underlying the examined micro-topographies, while the inter-annual variation in soil water storage for the selected microtopographies increase with increased rainfall. The depth of influence of micro-topographic vegetation on soil moisture exceeded 1000 cm for a gully (GU), 740 cm for a sink hole (SH), 480 cm for a scarp (SC), 360 cm for an ephemeral gully (EG) and 220 cm for a platform (PL). Micro-topography will cause the heterogeneous distribution of soil moisture in the shallower layers, which changes the vegetation distribution differences between micro-topographies. This may be the survival strategy of herbaceous vegetation in response to climate change in the Loess Plateau. For future vegetation restoration efforts, we need to pay attention to the influence of microtopography on soil moisture. [ABSTRACT FROM AUTHOR]

Background: Co‐infections, secondary bacterial or fungal infections, are important risk factors for poor outcomes in viral infections. The prevalence of co‐infection and secondary infection in patients infected with SARS‐CoV‐2 is not well understood. Aims: To investigate the role of co‐infections and secondary infections in disease severity of hospitalized individuals with COVID‐19. Materials and Methods: A retrospective study was carried out between 11 January 2020 and 1 March 2020 among 408 laboratory confirmed COVID‐19 patients in China. These patients were divided into three groups based on disease severity: mild or moderate, severe, or critically ill. Microbiological pathogens in blood, urine, and respiratory tract specimens were detected by the combination of culture, serology, polymerase chain reaction, and metagenomic next‐generation sequencing (mNGS). Results: The median age of participants was 48 years (IQR 34–60 years). Fifty‐two patients (12.7%) had at least one additional pathogen, 8.1% were co‐infected, and 5.1% had a secondary infection. There were 13 Mycoplasma pneumoniae cases, 8 Haemophilus influenzae cases, 8 respiratory viruses, and 3 Streptococcus pneumoniae cases, primarily detected in mild and moderate COVID‐19 patients. Hospital‐acquired infection pathogens were more common in critically ill patients. Compared to those without additional pathogens, patients with co‐infections and/or secondary infections were more likely to receive antibiotics (p < 0.001) and have elevated levels of d‐dimer (p = 0.0012), interleukin‐6 (p = 0.0027), and procalcitonin (p = 0.0002). The performance of conventional culture was comparable with that of mNGS in diagnosis of secondary infections. Conclusion: Co‐infections and secondary infections existed in hospitalized COVID‐19 patients and were relevant to the disease severity. Screening of common respiratory pathogens and hospital infection control should be strengthened. [ABSTRACT FROM AUTHOR]

The near‐surface soil water content (SWC) can reflect the agricultural drought levels. In addition, understanding the historical trends of near‐surface SWC change in China is an important step in combating climate change. The monthly near‐surface SWC data set during 1988–2016 published by the European Space Agency Climate Change Initiative were used in this study to analyse the variations of SWC in whole China and its seven natural divisions. Results indicated South and Central China had higher SWC than others because of their larger precipitation amounts. Significant (p <.05) decreasing trend in temporal SWC was found in Northeast China, which is related to the significant (p <.05) decreasing trend in the aridity index. However, significant (p <.01) increasing trends were found in Northwest China and Qing‐Tibet, which may be associated with the climate change (e.g., the ice and snow melting caused by increase of air temperature) and human activities (e.g., tillage and vegetation restoration). The monthly SWC in all divisions and whole China showed a main period scale (corresponding to peak values of wavelet variance) of about 225 months and 2 dry‐wet cycles. From 2016, the next 5–6 years are likely to be the wet years. The findings are of great significance to the management of soil water resources in China under global change. [ABSTRACT FROM AUTHOR]

Background and Aim: Periprosthetic joint infection (PJI) is one of the most devastating complications after total joint arthroplasty (TJA). However, the antibiotic resistance of infecting pathogens can significantly vary in different parts of the country. In the current study, we analyzed the demographic and microbiological profiles of knee and hip PJI over three years and compared the microbiological differences between them. Methods: A multicenter retrospective study of PJI patients in 34 referral medical centers in mainland China from January 2015 to November 2017 was performed. Results: A total of 925 PJI patients were recruited, 452 were identified as knee PJIs, and 473 were hip PJIs. The most common causative pathogens were Staphylococcus aureus (26.5%) and coagulase-negative staphylococci (14.3%). Methicillin-resistant staphylococci were involved in 25.6% (237/925) of all PJI cases. Mycobacterium and fungus only accounted for 6.5% (61) of all cases. Enteric gram-negative bacilli, anaerobes, and polymicrobial pathogens were more common in hip joint prostheses than in knee PJI (P = 0.014; P = 0.006; P = 0.002, respectively). Conclusion: While the majority of causative pathogens in PJI cases are staphylococcal species, the prevalence of atypical organisms and resistant pathogens should also be given attention and warrant the need for empiric antibiotic treatment. [ABSTRACT FROM AUTHOR]

Background: Polled intersex syndrome (PIS) leads to reproductive disorders in goats and exerts a heavy influence on goat breeding. Since 2001, the core variant of an 11.7 kb deletion at ~129 Mb on chromosome 1 (CHI1) has been widely used as a genetic diagnostic criterion. In 2020, a ~0.48 Mb insertion within the PIS deletion was identified by sequencing in XX intersex goats. However, the suitability of this variation for the diagnosis of intersex goats worldwide and its further molecular genetic mechanism need to be clarified. Results: The whole-genome selective sweep of intersex goats from China was performed with whole-genome next-generation sequencing technology for large sample populations and a case–control study on interbreeds. A series of candidate genes related to the goat intersexuality phenotype were found. We further confirmed that a ~0.48 Mb duplicated fragment (including ERG and KCNJ15) downstream of the ~20 Mb PIS region was reversely inserted into the PIS locus in intersex Chinese goats and was consistent with that in European Saanen and Valais black-necked goats. High-throughput chromosome conformation capture (Hi-C) technology was then used to compare the 3D structures of the PIS variant neighborhood in CHI1 between intersex and non-intersex goats. A newly found structure was validated as an intrachromosomal rearrangement. This inserted duplication changed the original spatial structure of goat CHI1 and caused the appearance of several specific loop structures in the adjacent ~20 kb downstream region of FOXL2. Conclusions: Results suggested that the novel complex PIS variant genome was sufficient as a broad-spectrum clinical diagnostic marker of XX intersexuality in goats from Europe and China. A series of private dense loop structures caused by segment insertion into the PIS deletion might affect the expression of FOXL2 or other neighboring novel candidate genes. However, these structures require further in-depth molecular biological experimental verification. In general, this study provided new insights for future research on the molecular genetic mechanism underlying female-to-male sex reversal in goats. [ABSTRACT FROM AUTHOR]

Background and aims: The effects of climate factors and rock fragment content (RFC) on soil nitrous oxide (N2O) emission and mineral N leaching can be important in reducing N losses in different agroecosystems. This study aimed to analyze and quantify the intertwined effects of precipitation intensity, temperature, RFC, and land use on these two kinds of soil N losses. Methods: The DayCent models were calibrated and validated using observed data for the representative tea garden (TG), bamboo forest (BF), and mixed forest (MF) hillslopes in the southeastern hilly region of China. The N2O emissions and mineral N leaching were then simulated under a total of 882 scenarios with the combinations of three land‐use types (TG, BF, and MF), seven precipitation intensities (PI, from 8 to 99.2 mm d−1 but the total precipitation amount maintained), seven temperature conditions (from baseline –1°C to baseline +2°C with 0.5°C increment), and six RFCs (from 0 to 50% in volume with 10% increment). Results: The TG had the greatest soil N2O emission (1.8 and 3.3 times of BF and MF, respectively) and mineral N leaching (5.5 and 36.8 times of BF and MF, respectively). On three land‐use hillslopes, the greatest soil N2O emissions were observed in summer, while great mineral N leaching were generally observed in spring and winter. Peaks of N2O emissions were observed as the PI reached 59.8 mm d−1, while peaks of mineral N leaching were always observed when the PI reached 8.0 and 59.8 mm d−1. With temperature increasing and RFC decreasing, both types of soil N losses increased. The land use and RFC had the primary influences on both types of soil N losses compared to climate factors. Under the same RFCs, the PI had higher influence on soil N2O emission compared to temperature, while those on mineral N leaching were just opposite. Conclusion: Findings of this study would provide scientific bases for designing strategies to reduce soil N losses on the stony‐soil hillslopes. [ABSTRACT FROM AUTHOR]

The purpose of this study is to establish and validate an accurate and personalized nonalcoholic fatty liver disease (NAFLD) prediction model based on the nonobese population in China. This study is a secondary analysis of a prospective study. We included 6,155 nonobese adults without NAFLD at baseline, with a median follow-up of 2.3 years. Univariate and multivariate Cox regression analyses were used to determine independent predictors. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimize the selection of variables. Based on the results of multivariate analysis, a prediction model was established. Harrell's consistency index (C-index) and area under the curve (AUC) were used to determine the discrimination of the proposed model. The goodness of fit of the calibration model was tested, and the clinical application value of the model was evaluated by decision curve analysis (DCA). The participants were randomly divided into a training cohort (n = 4,605) and a validation cohort (n = 1,550). Finally, seven of the variables (HDL-c, BMI, GGT, ALT, TB, DBIL, and TG) were included in the prediction model. In the training cohort, the C-index and AUC value of this prediction model were 0.832 (95% confidence interval (CI), 0.820-0.844) and 0.861 (95% CI, 0.849-0.873), respectively. In the validation cohort, the C-index and AUC values of this prediction model were 0.829 (95% CI, 0.806-0.852) and 0.859 (95% CI, 0.841-0.877), respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. DCA demonstrated a clinically effective predictive model. Our nomogram can be used as a simple, reasonable, economical, and widely used tool to predict the 3-year risk of NAFLD in nonobese populations in China, which is helpful for timely intervention and reducing the incidence of NAFLD. [ABSTRACT FROM AUTHOR]

Background. Hypertension is now common in China. Patients with hypertension and type 2 diabetes are prone to severe cardiovascular complications and poor prognosis. Therefore, this study is aimed at establishing an effective risk prediction model to provide early prediction of the risk of new-onset diabetes for patients with a history of hypertension. Methods. A LASSO regression model was used to select potentially relevant features. Univariate and multivariate Cox regression analyses were used to determine independent predictors. Based on the results of multivariate analysis, a nomogram of the 5-year incidence of T2D in patients with hypertension in mainland China was established. The discriminative capacity was assessed by Harrell's C -index, AUC value, calibration plot, and clinical utility. Results. After random sampling, 1273 and 415 patients with hypertension were included in the derivation and validation cohorts, respectively. The prediction model included age, body mass index, FPG, and TC as predictors. In the derivation cohort, the AUC value and C -index of the prediction model are 0.878 (95% CI, 0.861-0.895) and 0.862 (95% CI, 0.830-0.894), respectively. In the validation cohort, the AUC value and C -index of the prediction model were 0.855 (95% CI, 0.836-0.874) and 0.841 (95% CI, 0.817-0.865), respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. Decision curve analysis shows that nomograms are clinically useful. Conclusion. Our nomogram can be used as a simple, affordable, reasonable, and widely implemented tool to predict the 5-year T2D risk of hypertension patients in mainland China. This application helps timely intervention to reduce the incidence of T2D in patients with hypertension in mainland China. [ABSTRACT FROM AUTHOR]

Objective: Pulmonary tuberculosis (TB) is a severe infectious respiratory disease, the burden of which remains high in China. To provide scientific evidence for developing more targeted prevention and control strategies, this study aimed to determine the incidence trends and explore the epidemiological characteristics of pulmonary TB in Anhui Province, Eastern China between 2013 and 2018. Methods: The retrospective study analyzed information regarding pulmonary TB cases reported by the National Infectious Disease Reporting System and census data collected from the Anhui Provincial Bureau of Statistics. Results: Overall, 211,892 cases of TB patients were reported in Anhui Province, China between 2013 and 2018, with an average annual reported incidence rate of 57.7 per 100,000 persons. A significant decrease in the incidence rate of pulmonary TB (p < 0.001) was observed during the study period. Men had a higher incidence rate of pulmonary TB than women (p < 0.001). The highest annual average reported incidence rate was 204.2 per 100,000 persons in those aged 70–74 years. The number of farmers with pulmonary TB, i.e., 155,415, accounted for 73.4% of all cases. Moreover, the peak period of reported cases was from January to March. Four cities along the Yangtze River—Anqing, Tongling, Chizhou, and Wuhu—reported significantly higher incidence rates of pulmonary TB than other cities (p < 0.001). Conclusions: From 2013 to 2018, there was a significant decline in the incidence rate of pulmonary TB in Anhui Province, with peaks occurring from January to March. Prevention and control strategies targeting men, people aged 70–74 years, farmers, and the four cities along the Yangtze River should be strengthened. [ABSTRACT FROM AUTHOR]

Spatio‐temporal variations of nitrate‐nitrogen (NO3-‐N) leaching is driven by both soil hydrology and biogeochemistry. However, the widely used soil hydrology and biogeochemistry models have their weaknesses in simulating soil N cycling and soil water movement processes, respectively. In this study, we proposed an alternative approach by simply combining the HYDRUS‐3D and DNDC models to investigate the spatio‐temporal variations of NO3-‐N leaching on a representative tea garden hillslope in Taihu Lake Basin, China. Results showed that the soil hydrology and N cycle were well simulated by HYDRUS‐3D and DNDC models, respectively. Based on the leaching equation, the soil water flux simulated by HYDRUS‐3D and soil NO3-‐N content simulated by DNDC were combined to calculate the leachate NO3-‐N concentrations with good accuracy. The accumulative NO3-‐N leaching flux during the simulation year was 71.7 kg N ha−1, with remarkable spatio‐temporal variations on this hillslope. Hot spots of NO3-‐N leaching were observed in blocks 24, 27, 31, 34, 37, and 40 with accumulative leaching fluxes > 82.0 kg N ha−1 y−1. The spatial variation of NO3-‐N leaching was mainly controlled by soil texture and soil hydraulic properties. Hot moments of NO3-‐N leaching were observed after the applications of spring fertilizer (16 March) and basal fertilizer (30 October). The temporal variation of NO3-‐N leaching was mainly controlled by precipitation and the spring fertilization. Methods and findings of this study will be benefit for the risk assessment of non‐point source N loss and the precise agricultural management. [ABSTRACT FROM AUTHOR]

• Combing soil survey and literature soil sample data enhanced SOC stock prediction. • ANN and MGWR had their own merits and drawbacks in predicting SOC stock. • Fusing different predicting models improved prediction accuracy of SOC stock. • Fusion model with the spatial autocorrelation considered had stronger adaptability. Soil organic carbon (SOC) is a crucial soil property governing various agricultural, ecological, and environmental processes in the terrestrial ecosystem. However, acquiring accurate and high resolution SOC density (SOCD) map remained a challenge in the current researches. Based on soil samples collected from soil survey and published literatures (952 samples), this study tested different approaches for generating high accuracy dataset of 0–20 cm SOCD with the spatial resolution of 90-m in the Yangtze River Delta. Two spatial prediction methods, including artificial neural network (ANN, represented non-linear), multiscale geographically weighted regression (MGWR, represented linear) were applied to generated the SOCD maps. Then three fusion models, including multiple linear regression fusion (MLR_F), ANN fusion (ANN_F) and a self-developed model (multiscale geographically normalize weighted fusion, MGNW_F), were applied to fuse the prediction results of spatial interpolation methods. Among spatial interpolation methods, the ANN performed better in capturing the SOCD spatial pattern, while the MGWR performed better in accuracy measures of mean square error, mean absolute error and coefficient of determination. After data fusing by the three models, improved accuracy measures than the ANN and MGWR were achieved. The predictions of fusion models also showed better reliability than the soil dataset of high resolution National Soil Information Grids of China, mainly due to that more soil samples were included in the prediction. Among these fusion models, the MGNW_F performed slightly better than the other two and had the strongest adaptability to the overall environment of the study area. Findings of this study highlighted the potentials of acquiring additional soil samples from existing literatures and fusing different methods for enhancing the accuracy in mapping SOCD. [ABSTRACT FROM AUTHOR]

• DISPATCH performed better than RF approach in downscaling microwave-based SSM. • DISPATCH was inapplicable in pixels with weak link between SSM and evapotranspiration. • Combining DISPATCH and RF with seasonality considered achieved improved accuracy. Microwave remote sensing has great potential for capturing surface soil moisture (SSM) but suffers from its coarse spatial resolution. In this study, we combined the disaggregation based on physical and theoretical change (DISPATCH) and random forest (RF) approaches to downscale microwave-based SSM in the Yangtze River Delta region, China. Results showed that downscaled SSM by DISPATCH approach was superior to that by RF approach with Pearson correlation coefficient (R), unbiased root mean square error (ubRMSE), and the mean bias (Bias) of 0.778, 0.022 m3 m-3 and 0.061 m3 m-3, respectively. However, the DISPATCH approach was inapplicable in pixels with weak link between SSM and evapotranspiration, while the RF approach did not have such restriction. Therefore, the DISPATCH approach was supplemented with the RF approach to downscale the SSM for the entire study area. In addition, this downscaling process was conducted for the four different seasons and for the entire study period to test whether considering seasonality was necessary in the downscaling. The downscaled SSM was the best in autumn with R = 0.843, ubRMSE = 0.022 m3 m-3, and Bias = 0.048 m3 m-3, followed by summer and spring, and poorest in winter. However, the seasonally downscaled SSM performed better than that downscaled for the entire period. Moreover, over the entire study period, land surface temperature, land cover heterogeneity, soil texture, and water area percentage exerted significant influences on errors. However, contribution order of these environmental factors on errors varied with seasons. This study would be helpful to widen DISPATCH applicability in the semi-humid/humid region and maximize the potential of various data in generating high accurate and spatiotemporally continuous SSM estimates. [ABSTRACT FROM AUTHOR]

The analysis of aircraft fuel consumption remains an important topic as fuel consumption constitutes a large portion of airline operational costs, and exhaust emissions generated by aircraft gradually have become an essential aspect of urban air pollution, especially during takeoff and descent. Previous studies have focused mainly on optimizing fuel loss and greenhouse gases emission via three key methods: reducing additional aircraft load, using inventive air transfer control methods, and identifying the best-performing aviation systems for all conditions. However, there are few studies that have considered the relationships among fuel consumption, pilot behavior, and flight factors. This study fills this gap by focusing on the relationships between fuel consumption and three factors during the descent phase: altitude, weight, and speed. Further, we propose an improved K-means clustering algorithm to analyze the flight data, conducting clustering analysis on multi-dimensional data based on real flight records of Boeing 737s operated by China Eastern Airlines. We conclude the highlights of this study into three aspects: (1) the relationship between aircraft descent and fuel consumption is investigated through clustering analysis to find a fuel-efficient aircraft descent. (2) an improved K-means clustering algorithm is proposed to analyze flight data. (3) the better aircraft descent is the suggestion for pilots by analyzing the clustering results, which is a good supplement to the Flight Crew Operating Manual (FCOM). In the case study, the improved K-means algorithm is used for the cluster analysis of data from the quick access recorders of two aircraft descending into Chengdu Shuangliu Airport (CTU) in China. Compared with the method that does not use the analysis results for the descending, the average fuel consumption per unit of time decreases by 17.5% when we use our proposed method. In the Shanghai Pudong Airport (PVG), our proposed method reduces average fuel consumption per unit of time by 19.3%. [ABSTRACT FROM AUTHOR]

Anthropogenic disturbances may cause cosmopolitan species to replace endemic species, which will alter both the within‐community diversities and between‐community similarities of stream fish assemblages. In this study, we used data collected from headwater streams within the Xin'an basin, China, to evaluate the effects of low‐head dams on the alpha diversity and community similarity of fish assemblages. Our aims were to determine whether the changes in fish diversities and similarities related to dam‐associated disturbance are dependent on the species category (i.e., indigenous vs. native‐invasive species) or data type (i.e., occurrence‐based vs. abundance‐based indices). We found that low‐head dams significantly decreased the alpha diversity of the indigenous species in the impoundments but increased that of the native‐invasive species. However, the magnitude of this change was weakened if the two categories of fishes were not distinguished. Additionally, low‐head dams significantly decreased the occurrence‐based similarities of the indigenous fishes but increased those of the native‐invasive fishes. Despite the positive correlation between the occurrence‐based and abundance‐based indices, the former significantly overestimated the community similarities. Although most pairs of communities showed the same direction of changes for the two indices, some cases presented contrasting outcomes, including "perceived homogenization" (i.e., occurrence‐based differentiation but abundance‐based homogenization) and "perceived differentiation." Our results suggest the importance of distinguishing indigenous and native‐invasive species and considering both occurrence‐based and abundance‐based indices in future research on how anthropogenic activities affect fish diversities and similarities in streams. [ABSTRACT FROM AUTHOR]

[Display omitted] • The new assessment index could reflect the regional ecological security (RES) status. • RES included three basic characteristics: risk, health, and services. • The multidimensional characteristics of RES had spatial heterogeneity and dependence. • Various drivers impacted the multidimensional characteristics of RES differently. • Main tasks to ensure RES: control urban expansion and enhance vegetation cover. Watershed ecological security (ES), which is fundamental to regional sustainable development, consists of ecological risk (ER), ecosystem health (EH), and ecosystem services (ESs). It remains unclear how to describe the status of regional ES by integrating the three key characteristics, and little is known about the differences among the factors driving ER, EH, ESs, and ES. Here, we established an integrated assessment system of regional ES based on the cause–effect relationship of ER, EH, and ESs. We quantified the ES characteristics in the Huaihe River Basin of China in 2020 and pinpointed the factors (i.e., natural environment, urbanization, accessibility) driving their spatial differentiation using the Geodetector model. Results showed that: (1) in the study area, ER and EH were at the average level, and ESs and ES were at the high level. (2) ER, EH, ESs, and ES had positive spatial correlations (Moran' I > 0.60), with ER and EH having the strongest spatial dependence. (3) Natural environmental factors predominantly influenced ER, EH, and ESs. Slope was the primary driver for ER and ESs (q -value = 0.492 and 0.395, respectively), and vegetation coverage was the major driver for EH (q -value = 0.506). (4) ES was mainly influenced by urbanization factors, the proportion of construction land area exhibiting the highest explanatory power (q -value = 0.751), and the interaction with vegetation coverage being the strongest (q -value = 0.836). This study provides new ideas and methods for the assessment of regional ES, and holds positive implications for the protection and management of regional ecosystems. [ABSTRACT FROM AUTHOR]

Although mammography (MG) has been widely used for breast cancer screening in the western world, over-diagnosis remains controversial. Milestone studies showed that ultrasound (US) was an effective primary screening test for breast cancer both in the western world and in China. US improves the sensitivity of screening in Chinese women who have denser breasts and develop breast cancer earlier than Caucasian counterparts, and is used as the primary imaging test in the hospital-based opportunistic screening among asymptomatic self-referred women. Our previous work showed that US result might further differentiate the MG-detected breast cancers into low risk (US+) and ultra-low risk (US-). Indeed, most of the MG+/US- breast cancers would be ultra-low risk cancers and almost always present as MG micro-calcifications. Furthermore, majority of the commonest MG+/US- abnormal finding of micro-calcification is usually benign. Biopsy of benign breast disease increases not only the risk of breast cancer, but the expenses of screening and healthcare. Our hypothesis proposes that mammography-positive ultrasound-negative (MG+/US-) asymptomatic micro-calcifications might not need immediate invasive procedures and be safe to observe until the micro-calcifications increase significantly or become US-positive. If this hypothesis is proved, US would serve as the primary imaging test for breast cancer screening in China, with MG as the selective screening test and diagnostic tool for surgical plan. Unnecessary biopsy or surgery might be avoided with screening expenses considerably decrease. [ABSTRACT FROM AUTHOR]

A novel method called knowledge-guided spatio-temporal consistent correlation analysis (KSTCCA) was developed to discover reliable deformation features induced by multiple factors based on multimode landslide monitoring data. Compared to conventional approaches, KSTCCA integrates both temporal and spatial correlation analysis to improve the consistency of deformation patterns and capture the spatio-temporal heterogeneities in multimode monitoring data. KSTCCA considers both the landslide deformation mechanisms and the relationships between different influential factors as knowledge. Moreover, the method extracts the morphological structures of monitoring curves based on a seven-point approach and identifies knowledge rules using the k-means clustering method. Under the guidance of prior knowledge, a spatial correlation analysis is conducted based on support vector regression, and a temporal correlation analysis of the time lag is carried out based on the morphological structure features. Finally, three kinds of typical monitoring data, including deformation, rainfall, and reservoir water level data collected in the Baishuihe landslide area, China, are used for experimental analysis to verify the validity of the proposed method. [ABSTRACT FROM PUBLISHER]

• China experienced large-scale pine wilt disease (PWD) outbreaks in 2020. • PWD outbreaks resulted in strong spatial autocorrelation of PWD distribution. • A principal components analysis (PCA)-based sample filter method was developed. • PWD distributions under current and future climate change condition were predicted. • Carbon stock losses caused by PWD under current and future conditions were estimated. Pine wilt disease (PWD) is a significant threat to forests worldwide. Large-scale PWD outbreaks in China underline the need to understand the current and future distributions of PWD. We constructed a principal components analysis (PCA)-based environmental filter method in a three dimensional (3D) space to correct the sample bias caused by the strong autocorrelation of PWD outbreaks. The MaxEnt model was used to estimate the relationships between PWD occurrence and environmental characteristics and to predict potential PWD risk areas under four shared socioeconomic pathways (SSP) scenarios (SSP126, SSP245, SSP370, and SSP585) over the period 2020–2100. The model showed improved performance by correcting the sampling bias, with high accuracy (area under the curve values of 0.87 and 0.92 for model training and testing, respectively). Isothermality and annual precipitation contributed most strongly to the distribution of PWD. The potential PWD distribution will increase in the near future (2021–2040) and will expand northward in 2061–2100 under the SSP370 and SSP585 scenarios. This study also provides detailed maps of current and future carbon stock losses caused by PWD, which show the current maximum losses (∼24.9% of total forest carbon stocks) and an increase of ∼39,000 km2 in carbon stock losses in the northeast China for the period 2061–2100 under the SSP370 and SSP585 scenarios. Overall, our results show dramatic spatiotemporal shifts in the PWD distribution and forest carbon stock losses under climate change scenarios, and will provide a useful reference for implementing pest control techniques and forest management strategies. [ABSTRACT FROM AUTHOR]

Topsoil (0-20 cm) data of 25 997 sites were analyzed across five land uses in the Jiangsu Province of China. The results showed that the residential/industrial land stored the highest amount of soil organic carbon (SOC) among all the land uses. The polynomial model can best describe the relationship between SOC density (SOCD) and pH, showing that SOCD increases over the pH range of 4.2-6.5, decreasing sharply in the range of 6.5-9.2. The reason may be that microbial activity tends to be maximal at intermediate soil pH levels (pH 6-7). The relationship between SOCD and pH was found to vary substantially with the land use. Soil pH can explain 4.3-63.8% of the variation in SOCD for all land uses, suggesting that this variable should be introduced in SOC models to better predict SOC stock changes in the future. [ABSTRACT FROM AUTHOR]

Two models have been proposed to address the early Paleozoic tectonic evolution of Cathaysia in South China: the intracontinental model and the collisional model. Most geologists favor the intracontinental model because of the apparent absence of early Paleozoic ophiolite or arc igneous activity in Cathaysia. Geologists in favor of the collisional model suggest that the early Paleozoic amphibolite-granulite facies metamorphism and intensive igneous activities in Cathaysia share most features with collisional-type orogens. Here we report a new identification of 443–450 Ma arcrelated mafic intrusions in Songxi, South China. The Ordovician Songxi mafic intrusions, outcropping near the Neoproterozoic Jiangshao suture zone in South China, are composed of pyroxenite, (hornblende) gabbro, and minor diorite. Major-element geochemistry of these rocks exhibits a tholeiitic trend with a wide range of SiO2 contents (41.39%–51.96%). The chemical compositions of the clinopyroxenes suggest an arc-related environment for these intrusions. As for the whole-rock trace elements, the mafic intrusions contain low total rare earth element (REE) contents (30.7–133.4 ppm) and high field strength elements (HFSEs), such as Nb, Ta, Zr, Hf, and Ti, and are systematically enriched in large ion lithophile elements and light rare earth elements (LREEs), leading to low HFSE/ LREE ratios (Nb/La = 0.2–0.7). Trace element compositions share most features of Alaskan-type mafic intrusions. Isotopically, the Songxi mafic intrusions are characterized by negative whole-rock εNd(t) values (24.6 to 26.0) and variably high (87Sr/86Sr)i values (0.7069–0.7115). Zircon εHf(t) values mostly range from -6.0 to 2.3 and form a Gaussian distribution that peaks at ca. 23.0, indicating their broadly coupled Nd and Hf isotope compositions. Chemical compositions of the rock-forming minerals and the presence of primary phlogopite and hornblende suggest that the mafic intrusions were likely formed via crystal fractionation/accumulation of a hydrous tholeiitic mafic magma derived from a metasomatized mantle source in a continental arc environment. The identification of the Ordovician arc-signature mafic intrusions in South China, in combination with early Paleozoic metamorphic features and the widely distributed middle Silurian to early Devonian postorogenic affinity igneous activities, reveals that Cathaysia preserves a tectonic evolution process of plate subduction transitioning to continent-continent collision before the early Silurian, followed by postorogenic collapse during the middle Silurian to early Devonian. This collision event possibly took place at 440–435 Ma, and the final postorogenic collapse at 435–400 Ma produced voluminous granitic intrusions and minor mafic rocks. [ABSTRACT FROM AUTHOR]

Aim Several studies have reported the prevalence of depressive symptoms in the urban population of China, but no study reports the prevalence of depression in rural left-behind elderly. The present study investigated the prevalence of depression and the associated factors that influence depression in the left-behind elderly population in a rural area of China. Methods A cross-sectional study was carried out. A total of 509 participants were surveyed, and all participants completed the Geriatric Depression Scale (long form). Information on sex, age, education level, living situation, number of chronic diseases, amount of economic support received, frequency of children's visits and physical activity was collected. Results The prevalence of depressive symptoms in rural left-behind elderly was 36.94%. The prevalence of depressive symptoms was higher in women (45.10%) than in men (33.43%). The prevalence of severe depression was 1.96%. The prevalence of depressive symptoms in the 71-80 years age group (45.19%) was higher than the 65-70 years (37.44%) and >80 years age groups (5.97%). However, the prevalence of moderate and severe depression was higher in the 65-70 years age group (3.95%) than in other age groups. The frequency of children's visits, living situation, physical activity, number of chronic diseases and education level were the main risk factors of depression. Conclusions The prevalence of depressive symptoms is higher in left-behind elderly in rural areas than in the general elderly population. Psychological intervention is necessary for improving the mental health of elderly people living in rural areas of China. Geriatr Gerontol Int 2016; 16: 638-643. [ABSTRACT FROM AUTHOR]

The authors’ goals were to evaluate the psychometric properties of the Chinese version of the Child Social Preference Scale (CSPS; R. J. Coplan, K. Prakash, K. O'Neil, & M. Armer, 2004) and examine the links between both shyness and unsociability and indices of socioemotional functioning in young Chinese children. Participants included of two samples recruited from kindergarten classes in two public schools in Shanghai, China. Both samples included children 3–5 years old (Sample 1:n =350,Mage= 4.72 years,SD= 0.58 years; Sample 2:n= 129,Mage= 4.40 years,SD= 0.58 years). In both samples, mothers rated children's social withdrawal using the newly created Chinese version of the CSPS, and in Sample 2, teachers also provided ratings of socioemotional functioning. Consistent with previous findings from other cultures, results from factor analyses suggested a 2-factor model for the CSPS (shyness and unsociability) among young children in China. In contrast to findings from North America, child shyness and unsociability were associated with socioemotional difficulties in kindergarten. Some gender differences were also noted. Results are discussed in terms of the assessment and implications of social withdrawal in early childhood in China. [ABSTRACT FROM PUBLISHER]

Alkali-catalyzed and supercritical methanol transesterification were used to produce biodiesel from Chinese cottonseed. Fourier transform infrared and gas chromatography/mass spectrometry were used to identify the compositions of cottonseed oil biodiesel samples. Six major compositions of the biodiesel samples were identified by the retention time and the fragmentation pattern data of GC/MS analysis. The yields of biodiesel samples obtained from alkali-catalyzed reaction and supercritical methanol transesterification were 98.4 and 99%, respectively. In comparison to the alkaline transesterification, the supercritical methanol transesterification combining with two-phase extraction was more suitable for biodiesel production due to shorter reaction time, less purification steps, and lower cost. [ABSTRACT FROM PUBLISHER]

We developed a synth esis approach to augment current techniques for seismic hazard evaluation by combining four previously unrelated subjects: the pattern informatics (PI), load/unload response ratio (LURR), state vector (SV), and accelerating moment release (AMR) methods. Since the PI is proposed in the premise that the change in the seismicity rate is a proxy for the change in the tectonic stress, this method is used to quantify localized changes surrounding the epicenters of large earthquakes to objectively quantify the anomalous areas (hot spots) of the upcoming events. On the short-to-intermediate-term estimation, we apply the LURR, SV, and AMR methods to examine the hazard regions derived from the PI hot spots. A predictive study of the 2014 earthquake tendency in Chinese mainland, using the seismic data from 1970-01-01 to 2014-10-01, shows that, during Jan 01 to Oct 31, 2014, most of the M > 5.0 earthquakes, especially the Feb 12 M7.3 Yutian, May 30 M6.1 Yingjiang, Aug. 03 M6.5 Ludian, and Oct 07 M6.6 earthquakes, occurred in the seismic hazard regions predicted. Comparing the predictions produced by the PI and combination approaches, it is clear that, by using the combination approach, we can screen out the false-alarm regions from the PI estimation, without reducing the hit rate, and therefore effectively augment the predictive power of current techniques. This provided evidence that the multi-method combination approach may be a useful tool to detect precursory information of future large earthquakes. [ABSTRACT FROM AUTHOR]

The Chinese Government and citizens face enormous challenges of disaster management as widespread devastation, economic damages, and loss of human lives caused by increasing natural disasters. Disaster management requires a complicated iterative process that includes disaster monitoring, early detection, forecasting, loss assessment, and efficient analysis of disaster reduction. Each task typically involves the use of technologists and multiple geospatial information resources, including sensors, data sources, models, geo-tools, software packages, and computing resources. However, most existing disaster management systems operate in a typical passive data-centric mode, where resources cannot be fully utilized. This impediment is partially being addressed by the increasingly complex application requirements and the growing availability of diverse resources. In this paper, we summarize and analyze the practical problems experienced by the National Disaster Reduction Application System of China. To address the issues of data-centric, centralized, isolated solutions, we propose a novel Focusing Service Mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to dynamically generate collaborative and on-demand disaster information services. We also demonstrate the design and implementation of the Integrated Disaster Information Service System (IDISS). Through the service strategies ofVirtualizing,Wrapping, andIntegrating, disaster-related resources are constructed into services in the IDISS. These services are dynamically aggregated into focusing service chains, for diverse disaster management tasks. Actual applications illustrate that the proposed service system can significantly improve the capability of disaster management in China. [ABSTRACT FROM PUBLISHER]

Soil moisture and its spatial pattern are important for understanding various hydrological, pedological, ecological and agricultural processes. In this study, data of rainfall and soil moisture contents at different depths (10 cm, 20 cm, 40 cm and 60 cm) in forestland and vegetable plot in the Taihu Lake Basin, China were monitored and analyzed for characteristics of soil moisture variation and its response to several typical rainfall events. The following results were observed. First, great temporal variation of soil moisture was observed in the surface layer than in deeper layer in vegetable plot. In contrast, in forestland, soil moisture had similar variation pattern at different depths. Second, initial soil moisture was an important factor influencing the vertical movement of soil water during rainfall events. In vegetable plot, simultaneous response of soil moisture to rainfall was observed at 10- and 20-cm depths due to fast infiltration when initial soil was relatively dry. However, traditional downward response order occurred when initial soil was relatively wet. Third, critical soil horizon interface was an active zone of soil water accumulation and lateral movement. A less permeable W-B soil horizon interface (40-cm depth) in vegetable plot can create perched water table above it and elevate the soil water content at the corresponding depth. Fourth, the land cover was an effective control factor of soil moisture during small and moderate rainfall events. In the forestland, moderate and small rainfall events had tiny influences on soil moisture due to canopy and surface O horizon interception. Fifth, preferential flow and lateral subsurface interflow were important paths of soil water movement. During large and long duration rainfall events, lateral subsurface flow and preferential flow through surface crack or soil pipe occurred, which recharged the deep soil. However, in more concentrated large storm, surface crack or soil pipe connected by soil macropores was the main contributor to the occurrence of preferential flow. Findings of this study provide a theoretical foundation for sustainable water and fertilizer management and land use planning in the Taihu Lake Basin. [ABSTRACT FROM AUTHOR]

Ramping tricks of trade-based stock manipulation have evolved greatly in the fight with stricter market regulation, and can be extremely complicated nowadays. Despite the rigidity and soundness, theoretical models proposed in extant literature can hardly be applied directly to real market data, due to their assumptions being far away from reality. On the other hand, empirical studies of ramping manipulation still lack guidance and support from theories that can better reflect ramping details in practice. This paper addresses this gap by constructing a theoretical model that is closely linked to practical detection, in the framework of behavioral finance. New insights into concrete ramping manipulation tricks are also contributed to the literature. The potential of the model for manipulation detection is demonstrated by applying it to the two most infamous manipulation cases in the history of Chinese stock market. [ABSTRACT FROM AUTHOR]

Agricultural, environmental and ecological modeling requires soil cation exchange capacity (CEC) that is difficult to measure. Pedotransfer functions (PTFs) are thus routinely applied to predict CEC from easily measured physicochemical properties ( e.g., texture, soil organic matter, pH). This study developed the support vector machines (SVM)-based PTFs to predict soil CEC based on 208 soil samples collected from A and B horizons in Qingdao City, Shandong Province, China. The database was randomly split into calibration and validation datasets in proportions of 3:1 using the bootstrap method. The optimal SVM parameters were searched by applying the genetic algorithm (GA). The performance of SVM models was compared to those of multiple stepwise regression (MSR) and artificial neural network (ANN) models. Results show that the accuracy of CEC predicted by SVM improves considerably over those predicted by MSR and ANN. The performance of SVM for B horizon ( R2 = 0.85) is slightly better than that for A horizon ( R2 = 0.81). The SVM is a powerful approach in the simulation of nonlinear relationship between CEC and physicochemical properties of widely distributed samples from different soil horizons. Sensitivity analysis was also conducted to explore the influence of each input parameter on the CEC predictions by SVM. The clay content is the most sensitive parameter, followed by soil organic matter and pH, while sand content has the weakest influence. This suggests that clay is the most important predictor for predicting CEC of both soil horizons. [ABSTRACT FROM AUTHOR]