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Purpose: This study aimed to assess the health-related quality of life (HRQoL) of the Chinese population by using the Chinese medicine quality of life-11 dimensions (CQ-11D) questionnaire and to identify factors associated with HRQoL. Methods: The data was derived from a survey conducted by the Institute of Pharmacoeconomics Evaluation at Beijing University of Chinese Medicine on the quality of life of the Chinese population. The sex and age of respondents were considered through quota sampling. Demographic, socioeconomic, and health indicators were collected using the structured questionnaire. We performed bivariate analyses first to examine the associations between the above factors and the HRQoL of respondents measured by the CQ-11D. Multivariate linear regression and ordinal logistic regression models were established to analyze the factors (demographic, socioeconomic, and health indicators) differences in HRQoL, as well as the risk of each group reporting problems across the 11 dimensions of CQ-11D. Results: From February 2021 to November 2022, a total of 7,604 respondents were involved and 7,498 respondents were included. The sample approximated the general adult Chinese population in terms of age, sex, and district of residence, and each geographic distribution ranged from 9.71 to 25.54%. Of the respondents, 45.84% were male, and 89.82% were Han ethnicity. The mean utility score ranged from 0.796 to 0.921 as age increased. According to the respondents, most health problems were identified in the PL (fatigue) (70.16%) and SM (quality of sleep) (63.63%) dimensions. The CQ-11D index scores varied with the demographic and socioeconomic characteristics of respondents, except for ethnicity (p > 0.05) and income (p > 0.05). The multivariate analysis revealed significant negative associations between health utility scores and various factors. These factors include sex (female), age over 65, belonging to ethnic minorities, rural household registration, being widowed or divorced, having a primary school education or below, being a student or unemployed, having a low income of 0–1,300, engaging in smoking or drinking, limited participation in physical activities, experiencing changes in self-perceived health status compared to the previous year, and having chronic diseases. The odds of respondents reporting problems in 11 dimensions varied among different socio-demographic groups. Conclusions: This study reports the first Chinese population norms for the CQ-11D derived using a representative sample of the Chinese general population. Self-reported health status measured by the CQ-11D varies among different socio-economic groups. In addition to participation a physical activity and the presence of chronic disease, smoking and drinking also significantly influence HRQoL. [ABSTRACT FROM AUTHOR]

Cistanche tubulosa (Schenk) R. Wight is a valuable herbal medicine in China. The study aimed to explore the potential mechanisms of C. tubulosa on antioxidant activity using spectrum-effect relationship and network pharmacology and the possibilities of utilizing herbal dregs. In this work, different extracts of C. tubulosa, including herbal materials, water extracts, and herbal residues, were evaluated using high-performance liquid chromatography (HPLC) technology. In addition, the antioxidant activities were estimated in vitro, including 2, 2-diphenyl-1-picrylhydrazyl; superoxide anion; and hydroxyl radical scavenging assays. The spectrum-effect relationships between the HPLC fingerprints and the biological capabilities were analyzed via partial least squares regression, bivariate correlation analysis, and redundancy analysis. Furthermore, network pharmacology was used to predict potential mechanisms of C. tubulosa in the treatment of antioxidant-related diseases. According to the results, eleven common peaks were shared by different extracts. Geniposidic acid, echinacoside, verbascoside, tubuloside A, and isoacteoside were quantified and compared among different forms of C. tubulosa. The spectrum-effect relationship study indicated that peak A6 might be the most decisive component among the three forms. Based on network pharmacology, there were 159 target genes shared by active components and antioxidant-related diseases. Targets related to antioxidant activity and relevant pathways were discussed. Our results provide a theoretical basis for recycling the herbal residues and the potential mechanisms of C. tubulosa in the treatment of antioxidant-related diseases. [ABSTRACT FROM AUTHOR]

The multiple-probability decision-making method for earthquake hazards considers multiple performance indicators and can be used to effectively estimate the seismic risk of structures. The seismic vulnerability model directly affects the development of the earthquake risk distribution in regional structures. This paper innovatively developed a bivariate intensity measurement method based on macroscopic and instrumental seismic intensities. An optimized instrument intensity calculation model was established considering the actual monitoring data of historical earthquakes in China. A hybrid seismic vulnerability quantification method based on empirical, expert judgement and analysis has been proposed and applied to evaluate the vulnerability levels of three types of building clusters in two typical earthquakes in Qinghai Province, China (the 2008 Dachaidan (DCD) earthquake and the 2009 Haixi (HX) earthquake). A structural hybrid vulnerability matrix and surface for nine zones based on bivariate intensity measures were developed. A synthetic vulnerability membership index considering fuzzy failure criteria and decision theory was proposed, and vulnerability membership curves for different vulnerability levels were established. An improved earthquake economic loss prediction function is proposed, and synthetic economic vulnerability index prediction models for three typical buildings in different regions are established. The estimated and calculated results of the developed multiscale variable parameter synthetic vulnerability model are highly consistent with the actual earthquake loss observations. • This paper proposes a bivariate intensity measure to estimate the seismic fragility of buildings. • An optimized hybrid vulnerability matrix and surface of typical buildings were established. • The 2008 and 2009 Dachaidan and Haixi earthquakes in Qinghai Province, China, were reported. [ABSTRACT FROM AUTHOR]

Background: Rupture of intracranial aneurysms (RIA) leads to subarachnoid hemorrhage (SAH) with severe consequences. Although risks for RIA are established, the results vary between ethnic groups and were never studied in Kazakhstan. This study aimed to establish the risk factors of RIA in the Kazakh population.  METHODS: Retrospective analysis of 762 patients with single IAs, who attended the neurosurgical center from 2008 until 2018, was conducted. Demographic characteristics, such as age, sex, smoking status, and hypertension were considered. Descriptive and bivariate analyses were performed. A multivariable logistic regression model was built to identify factors correlated with RIA.Results: The mean age of participants was 48.49 ± 0.44 years old. The majority (68.37%) of IAs have ruptured. Of the ruptured aneurysms, 43.76% were < 6 mm, and 38.39% were located on the anterior cerebral and anterior communicating arteries (ACA). Logistic regression model indicates younger age group (16-40 years), smoking, having stage 3 hypertension, smaller IA size and its location on ACA increase the odds of rupture.Conclusions: This study has revealed that younger, smoking patients with stage 3 arterial hypertension are at higher risk for RIA. Small aneurysms (< 6 mm) and location on ACA had increased odds of rupture, while larger aneurysms on internal carotid arteries had lower odds. [ABSTRACT FROM AUTHOR]

Data on hepatitis B virus (HBV) pregenomic (pgRNA) levels in HIV/HBV coinfected patients pre‐ and post‐combined antiretroviral therapy (cART) are limited. This study aimed to evaluate the distribution of HBV pgRNA levels in treatment‐naive coinfected patients and explore the changes that occur after the initiation of cART by examining patients from multicentre cohort studies performed in China. We included HIV/HBV coinfected subjects from the China AIDS Clinical Trial cohorts established from 2008 to 2014. Clinical and serological markers of HIV and HBV infection and biochemical data were acquired at baseline and after 96 and 240–480 weeks of cART. The correlations between HBV pgRNA and HBV DNA levels as well as HBsAg levels were calculated using Spearman's bivariate correlation analysis, and multivariate regression analysis was performed to determine factors associated with undetectable HBV pgRNA levels before cART and HBeAg loss after cART. A total of 132 HIV/HBV coinfected patients were enrolled, and 100 individuals were HBeAg‐negative. A total of 34.4% (32/93) of patients were positive for HBV pgRNA, and the median HBV pgRNA level was 4.92 (IQR: 4.21–6.12) log10 copies/mL before cART. The median HBV pgRNA level was significantly lower in HBeAg‐negative individuals than in HBeAg‐positive individuals (4.22 (IQR: 2.70–4.84) log10 copies/mL vs. 5.77 (IQR: 4.63–6.55) log10 copies/mL, p = 0.002). HBV pgRNA was moderately correlated with HBsAg (r = 0.594, p = 0.001), and positively associated with HBV DNA (r = 0.445, p = 0.011). The factors independently associated with undetectable HBV pgRNA level before cART were HBV DNA (OR: 5.61, 95% CI: 1.50–20.96, p = 0.01) and HBeAg status (OR: 5.95, 95% CI: 1.52–23.25, p = 0.01). A total of 87.5% (28/32) of patients were followed for a median duration of 138 (IQR: 54–240) weeks, and the HBV pgRNA levels became undetectable in seven patients. The 132 patients were observed for 695.5 person‐years, and no HBsAg loss occurred. Thirteen individuals achieved HBeAg loss, four patients had undetectable levels of HBV pgRNA pre‐cART, and the level of six individuals became undetectable during the 48‐week (IQR: 48–264) follow‐up period. HBeAg status was significantly associated with HBV pgRNA level in HIV/HBV coinfected patients pre‐ and post‐cART. Additionally, undetectable HBV pgRNA level may be associated with HBeAg loss after cART. [ABSTRACT FROM AUTHOR]

Urban vegetation plays a very important role in regulating urban climate and improving the urban environment. There is an urgent need to construct an effective index to quickly detect urban vegetation quality changes. In this study, a synthetic vegetation quality index (VQI) was proposed using a holistic approach based on the quality of vegetation itself and the spatial relationship with its surroundings, composed of four selected variables: normalized difference vegetation index (NDVI), patch aggregation index (AI), patch density (PD), and percentage of landscape (PLAND). Principal component analysis (PCA) was employed to calculate weights for each variable due to its objectivity. Then, taking Fuzhou City, southeast China as the case study, the scale effects of the VQI under different moving window sizes (500 m, 1 km, 2 km, ..., 5 km) and the spatiotemporal changes were explored. The results showed that a VQI with a window size of 3 km had the highest correlations with all the selected indicators. Meanwhile, the representativeness and the effectiveness of the VQI were validated by the percentage eigenvalues of PC1, as well as Pearson correlation analysis and bivariate spatial autocorrelation analysis. We also revealed that the proposed VQI had the greatest explanatory power for land surface temperature (LST) among all the factors in both studied years (2000 and 2016), with the VQI's interpretation of LST being 0–44% better than any individual indicator except for AI in 2000. Additionally, our work revealed that the location of vegetation has a great impact on the urban thermal environment. The VQI can assess urban vegetation quality effectively and quickly. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this research is to explore whether the location of a citizen's residence is an important source of explanation for nationalistic attitudes in China. Methods: Using data from a nationwide representative survey of Chinese adults and a multidimensional approach to nationalism, analyses include bivariate correlation and multiple regression. Results: Significant support is found for 12 of 16 hypotheses linking "location variables" to specific types of nationalistic attitudes, even when modeling with a substantial set of controls. The hypothesis‐supporting evidence touches on three of the four dimensions of nationalism covered here. Conclusion: In regard to the development of nationalistic attitudes in China, location matters. [ABSTRACT FROM AUTHOR]

Purpose: The correlation of abnormal glucose metabolism and thyroid carcinoma, especially the aggressiveness of thyroid cancer, still remains controversial. We conducted this study to investigate the relationship between abnormal glucose metabolism parameters and differentiated thyroid carcinoma (DTC) in the Chinese population. Materials and Methods: The study was designed as a hospital-based case–control study and was approved by the Ethics Committee of our hospital and registered in the Clinical Trial Protocol Registration and Results System (Registration code: NCT 03006289). From January 1, 2018 to June 30, 2021, a total of 377 DTC patients were enrolled in the study. Demographic and general characteristics, details of thyroid surgery and histopathological results, hematological test indicators were collected. Glucose metabolism parameters were calculated. Variables were analyzed by t-test, ANOVA, chi-squared analysis and Fisher's exact test. Pearson bi-variate correlation and Spearman's correlation analysis were used for bi-variate analysis. Results: More than 40% of patients with DTC were multifocality, more than half were extra-glandular invasion, and nearly 85% complied by lymph node metastasis. The prevalence of diabetes mellitus (DM) was about 10.08% in DTC patients. It was found that the proportion of postprandial 2 h blood glucose ≥11.1mmol/L and HbA1c ≥6.5% was significantly higher than the known proportion of DM (17.8%, 16.7% vs. 10.08%). Additionally, 87.3% of the DTC patients in this study had varying degrees of insulin resistance. Further analysis found that higher T staging was associated with higher levels of area under curve of C-peptide (P = 0.029), insulin sensitivity index (P = 0.012) and C-peptide sensitivity index (P = 0.016). A delayed peak of insulin secretion was found to be positive related with capsule invasion (r = 0.206, P = 0.004). In patients without a DM history, homeostasis model assessment of insulin resistance (P = 0.017), insulin sensitivity index (P = 0.019) and C-peptide sensitivity index (P = 0.020) were statistic associated with T staging. Also, the glucose metabolism parameter at 3-hour after a meal was related to a larger number of metastatic lymph nodes. Conclusion: Abnormal glucose metabolism, namely, DM, hyperinsulinemia and insulin resistance, were significantly associated with the carcinogensis and aggressiveness of DTC. [ABSTRACT FROM AUTHOR]

Water quality and quantity should be paid more attention in regions with arid climate and thick vadose zones since the limited groundwater cannot be replenished rapidly once polluted. This study focused on the Loess Plateau of China to investigate the geochemical mechanism affecting groundwater chemistry and to calculate contribution rates of multiple sources to groundwater solutes. We employed multiple methods (diagrams, bivariate analyses, hierarchical cluster analysis (HCA), sodium adsorption ratio (SAR), water quality index (WQI), correlation analysis, and forward model) for the above purposes. We collected 64 groundwater samples in the thick loess deposits in June 2018 (flood season) and April 2019 (dry season). The average concentrations of cation were in the order of Ca2+ > Na+ > Mg2+ > K+ in the flood season, and Na+ > Ca2+ > Mg2+ > K+ in the dry season. The order of anions contents in the flood season and the dry season were HCO3- > SO42- > Cl- > NO3-. The major hydrochemical facies were Ca-HCO3 and Ca·Mg-HCO3 in the flood season and Na·Ca-HCO3·SO4 and Na-HCO3 in the dry season, respectively. Most of the groundwater (95% in the flood season and 96% in the dry season) was suitable for drinking, and the overall water quality was acceptable for irrigation. Mineral dissolution and cation exchange were important natural processes affecting groundwater chemistry. The forward model showed that the contribution of atmospheric input, anthropogenic input, evaporite dissolution, silicate weathering, and carbonate weathering to solutes in groundwater was 2.3±1.5%, 5.0±7.1%, 19.3±21.4%, 42.8±27.3%, and 30.6±27.1% in the flood season, and 9.1±6.4%, 3.4±5.2%, 20.3±15.9, 56.6±23.2%, and 10.7±15.4% in the dry season, respectively. Obviously, silicate and carbonate weathering contribute the most to groundwater chemistry in the flood season, while silicate weathering and evaporite dissolution contribute the most in the dry season. Although the overall contribution of anthropogenic inputs was insignificant, it was the dominant source of solutes for local groundwater. This study provides fundamental information for water management in arid areas. [ABSTRACT FROM AUTHOR]

Banxia Baizhu Tianma decoction (BBTD), a six-herb Chinese medicine formula first described approximately 1732 AD, is commonly prescribed for Hypertension with Phlegm-dampness Stagnation (HPDS) as an adjuvant therapy in China. Obesity is an important risk factor for the increasing prevalence of hypertension year by year in China. In Traditional Chinese medicine, obesity is often differentiated as the syndrome of excessive phlegm-dampness.Vascular endothelial cell injury plays an important role in the development and occurrence of HPDS. In this study, the protective effects of 18 batches of BBTD samples from different origins on HUVEC cells were evaluated, including antioxidant and anti-inflammatory activities. Ultrahigh performance liquid chromatography (UPLC) was used to establish fingerprints, and combined with pharmacodynamic indexes, the protective components of BBTD on endothelial cells were analyzed. Antioxidant and anti-inflammatory activities were evaluated by ROS and Hs-CRP models, respectively. Hierarchical cluster analysis (HCA) and Bivariate correlation analysis (BCA) were used to investigate the potential correlation between chemical components and endothelial cell protection. The results indicated that BBTD could reduce ROS and hs-CRP levels in HUVEC cells, and the pharmacological activities in 18 batches of BBTD samples were significantly different. The results of BCA indicated that Gastrodin, Liquiritin, Hesperidin, Isoliquiritin, Hesperetin, and Isoliquiritigenin might be the active constituents to activate ROS and suppress hs-CRP as determined by spectrum-effect relationships. The antioxidant and anti-inflammatory activities of the 6 components at different concentration were verified, and the results showed that all of them had good antioxidant and anti-inflammatory activities in a concentration-dependent manner. This study showed that activity determination and spectral correlation can be used to search for active substances in Chinese medicine formula and provide data support for quality control of Traditional Chinese medicine (TCM). [ABSTRACT FROM AUTHOR]

Research on ecosystem services has a significant positive impact on ecosystem management, conservation, and the creation of ecological compensating systems. For the purpose to explore the characteristics of the geographical and temporal evolution and the driving forces behind the value of ecosystem services in Changsha, Hunan province, China, the four phases of land use data for the city from 2005 to 2020 were employed and analyzed by using geographic information systems and spatial statistics. The findings revealed that: (1) Forest land was the primary type of land used in Changsha. The area of construction land, wetland, and unused land increased, while the area of forest land, paddy field, dry land, and grassland decreased, and the area of water area was stable. (2) From 2005 to 2020, the value of ecosystem services showed a decreasing trend year by year. The forest land had the greatest impact on ecosystem service value (ESV) of all the land use types and the functions of hydrological regulation accounted for the largest share of the various ecosystem service functions. In terms of space, the high-value areas were mainly distributed in the east and west parts and rivers, while the low-value areas were mainly distributed in the middle which had the characteristics of positive agglomeration. (3) The results of the Geodetector revealed that spatial and temporal differences in ecosystem service values in Changsha were influenced by a combination of regional natural factors and socio-economic factors with a greater contribution from factors of Human Impact Index (HAI), Digital Elevation Model (DEM), and mean annual temperature. The interaction types were bivariate enhancement and nonlinear enhancement. The results of this study may serve as a scientific reference for the rational utilization of land resources and ecological environment protection in Changsha, Hunan, China. [ABSTRACT FROM AUTHOR]

Background: A growing body of literature suggests that early life circumstances can influence mental health throughout the lifespan. However, how these early life circumstances cumulatively contribute to depression in old age is not completely understood. The aim of this study was to examine the associations of eight factors with depression among community-dwelling older adults.Methods: Data were from the China Health and Retirement Longitudinal Study. We included 8,239 community-dwelling individuals who were ≥60 years, completed the life history questionnaire, and had assessment of depression. An early life disadvantage index was established using risk factors that were significantly associated with depression. Logistic regression was used to examine the association of each early life risk factor and the index with depression.Results: Of 8239 individuals included, 2,055 (24.9%) had depression. In bivariate analysis, each of eight early life risk factors was significantly associated with depression. Except for maternal and paternal education, all risk factors persisted to be associated with depression after multivariable adjustment. In the multivariable-adjusted model, a one-point higher in the early life disadvantage index (range: 0-6) was associated with a 45% (95% CI: 37%, 53%) higher odds of depression.Limitations: Depressive symptoms were measured in our study only by the CES-D scale. Some early life experiences might not be fully reliable due to recall bias.Conclusion: There was a strong association between early life environments and depressive symptoms among Chinese community-dwelling older adults. Adverse early life circumstances could contribute cumulatively to depression in old age. [ABSTRACT FROM AUTHOR]

Investigating the existence and causes of idiosyncratic volatility premium puzzle in developing stock market can enrich the research on this asset pricing puzzle. To investigate the existence and whether limits to arbitrage in China's A-share market can explain the idiosyncratic volatility premium puzzle, this paper uses listed stocks in China's A-share market from 2002 to 2019 as a sample. We calculate three individual measures and one comprehensive measure of limits to arbitrage based on Chinese specific regulations. After that, we conduct univariate portfolios analysis, regression analysis, and bivariate portfolios analysis to obtain evidence. We prove that idiosyncratic volatility premium puzzle exists in China's A-share market and is robust and that limits to arbitrage in this market can partly explain this asset pricing puzzle. This paper enriches research on asset pricing anomaly and can help us evaluate the effect of China's A-share market reform. [ABSTRACT FROM AUTHOR]

• HPV vaccine awareness and knowledge is limited in general population. • HPV vaccine uptake is still low in China despite high willingness to be vaccinated. • Safety, lack of knowledge and high price are main obstacles to be vaccinated. • Safety concern, lack of knowledge, and high price of HPV vaccines are main obstacles for general population to get vaccinated. Human papillomavirus (HPV) vaccine has been increasingly discussed in mainland China since its first approval in 2016. To date, nearly all studies assessing HPV vaccine perceptions and attitudes were implemented during pre-licensure period. Therefore, the nationwide post-marketing survey was conducted to update knowledge, attitudes and practice on HPV vaccine among general population in mainland China. Participants aged 18–45 years living in mainland China were recruited in April 2019 by multi-stage non-randomized sampling. Sociodemographic factors, HPV and HPV vaccine related awareness, knowledge, attitudes, vaccine uptake and potential obstacles were assessed in questionnaires. Bivariate analysis and multivariate regression were used to identify disparity among subgroups with different sociodemographic characteristics. 4,000 women (32.1 ± 7.81y) and 1,000 men (31.8 ± 7.96y) were included in final analysis. Less than one third of participants had heard of HPV (female: 31%; male: 22%) and HPV vaccine (female: 34%; male: 23%). Knowledge score was also unfavorable on HPV (female: 3 out of 13; male: 1.8 out of 13) and HPV vaccine (female: 3 out of 6; male: 2 out of 5). Only 3% females had been vaccinated three years after HPV licensure in China, although willingness to get vaccinated among those unvaccinated were high (mean willingness score ± SD: female: 3.3 ± 0.97; male: 3.0 ± 0.98). Industry of employment and household income were the major factors related to awareness and knowledge of vaccine, whereas HPV and HPV vaccine awareness were key influential factors for willingness. The main obstacles of vaccination were safety concerns, lack of knowledge, and high price of HPV vaccines. Findings highlight a lack of vaccine awareness, knowledge, and poor uptake in mainland China and underscore the necessity of health education campaigns. The identified priority groups, contents to be delivered and practical obstacles could furthermore provide insight into health education to reduce disparities and accelerate HPV vaccine roll-out in China. [ABSTRACT FROM AUTHOR]

Climate change will not only affect a single hydrological series but also may affect the dependence structure. However, traditional hydrological approaches often fail to analyse the multiple characteristics of runoff within a bivariate framework under climate change. This study explores the influence of future climate change (2031 − 2080) on the runoff volume series in spring, summer and autumn as well as their dependence structures in the Luanhe River Basin, China. The results indicate that the time-varying dependence structure between spring and summer runoff series, as well as that between the summer and autumn runoff series, are mainly related to the summer precipitation. The differences between copula models with constant dependence parameters and those with time-varying dependence parameters are presented under different cases. This study incorporates the impacts of climate change on the bivariate frequency analysis of seasonal runoff series, which may provide important guidance for water resource management under climate change. [ABSTRACT FROM AUTHOR]

This paper aims to discover the mechanism behind the positive correlation between local fiscal expenditure and industrial land price in China, a stylized fact discovered by bivariate and regression analyses. The model shows that if the positive externality of government expenditure on growth is sufficiently high, the local government has an incentive to increase public spending in exchange for the reduced demand for industrial land by charging a higher markup and driving up the industrial land price. Therefore, we observe a positive correlation between the local fiscal expenditure and industrial land price. [ABSTRACT FROM AUTHOR]

An estimation of daily suspended sediment concentration (SSC) is required for water resource and environmental management. The traditional methods for simulating daily SSC focus on modeling the SSCs themselves, whereas the cross-correlation structure between SSC and streamflow has received only minor attention. To address this issue, we propose a stochastic method to generate long-term daily SSC using multivariate copula functions that account for temporal and cross dependences in daily SSCs. We use the conditional copula method to construct daily multivariate distributions to alleviate the complications and workload of parameter estimations using high-dimensional copulas. The observed daily streamflow and SSC data are normalized using the normal quantile transform method to relax the computationally intensive model of building daily marginal distributions. Daily SSCs can thus be simulated through the multivariate conditional distribution using previous daily SSC and concurrent daily streamflow values. The proposed method is rigorously examined by application to a case study at the Pingshan station in the Jinsha River Basin, China, and compared with the bivariate copula method. The results show that the proposed method has a high degree of accuracy, in preserving the statistics and temporal correlation of daily SSC observations, and better preserves the lag-0 cross correlation compared with the bivariate copula method. The multivariate copula framework proposed here can accurately and efficiently generate long-term daily SSC data for water resource and environmental management, which play a critical role in accurately estimating the frequency and magnitude of extreme SSC events. [ABSTRACT FROM AUTHOR]

Objectives: Oral sex and its associated factors among low-tier female sex workers (FSWs) have not been documented in the Chinese literature. Here, we report this perspective in this group. Methods: The data were derived from a large cross-sectional study conducted among low-tier FSWs using a structured questionnaire in 21 counties in Zhejiang province, China. The prevalence of oral sex and its associated factors among 2645 low-tier FSWs were analyzed using bivariate and multivariate analysis. Results: Of all participants, 579 (21.9%) had performed oral sex with clients over the previous month. Multivariate analysis revealed that oral sex is related to being unmarried, low income, early initiation of commercial sex, having conducted commercial sex in more counties, longer duration of commercial sex, larger number of clients, ever having engaged in anal sex, less use of condoms and oral contraceptives during the previous month, low rate of adoption for contraception at the present time, and STI-related symptoms during the previous half year. Conclusion: Oral sex practitioners among low-tier FSWs in China are at a higher risk of STI, HIV, and unwanted pregnancy compared to those who did not engage in oral sex. Behavioral interventions carried out among low-tier FSWs should specifically target low-tier FSWs who practice oral sex, should carefully take into account the characteristics of these FSWs, provide risk awareness education and training for condom use negotiation, and promote the availability of condom and reproductive health care, timely diagnosis, and treatment of STIs. [ABSTRACT FROM AUTHOR]

Objective: The potential challenge for providing occupant protection accompanying seating preferences is an essential safety prerequisite for highly automated vehicle (HAV) popularization. This research is aimed toward identifying Asia-specific individualized seating preferences in HAVs and occupant safety awareness via a national survey in China.Methods: An online questionnaire survey was performed to investigate seating preferences (i.e., sitting posture, seating orientation, and position) and occupant safety awareness (i.e., seat belt usage and receptiveness to extended or additional restraints beyond the conventional three-point seat belt). We assessed whether perceptions were modulated by individual characteristics via bivariate and correlation analyses. The possibility of wearing seat belts was estimated by binary logistic regression.Results: The final survey data set includes 1,018 respondents after a rigorous validity check (response rate: 59.2%). The results show that preferred sitting postures and seating orientation were significantly associated with sociodemographic characteristics (e.g., gender, age, city tier) (p < 0.05). The rear seat was preferred in both the conventional (65.6%) and "face-to-face mode" seating configurations (77.6%), largely due to the fact that customers subjectively viewed it as being safer than sitting in a front seat in case of collisions. Despite the current trend of an increasing usage rate of seat belts, 48.5% of respondents preferred to be unrestrained in rear seats, especially for the subgroups who were from less developed cities and with a higher usage rate of public transport (p < 0.01). Low receptiveness to extended restraint and high comfort requirements were confirmed for the young, high-frequency road users, and for those who were from developed areas (p < 0.05).Conclusions: Diversified and specific seating preferences of Chinese occupants were identified facing emerging use of HAVs. Next generation occupant protection systems shall be adapted to account for the individualized expectations and needs on seating designs from certain population groups. Balanced restraint design between safety and comfort was required to exceed the existing strong dependence on exogenous causes of restraint use (e.g., legal restrictions) in Asia. [ABSTRACT FROM AUTHOR]

In China, CO2 emissions from industrial sectors on a larger scale than other end-use sectors. In order to reduce CO2 emissions, it is necessary to study the influencing factors and projection of industrial CO2 emissions. Based on accounting for CO2 emissions from the industrial sectors, this paper carries out bivariate correlation analysis and linear regression analysis on 15 preselected influencing factors and industrial CO2 emissions, removing two factors that have failed the significance test. In order to obtain some potential commonalities among the influencing factors, the remaining 13 influencing factors are divided into four categories, and then factor analysis is performed on each category in order to obtain five latent factors. An extreme learning machine algorithm that uses genetic algorithms to optimize the input weights and bias thresholds – the genetic algorithm extreme learning machine (GA-ELM) algorithm – to predict industrial CO2 emissions, the empirical results show that the GA-ELM algorithm using five factors as inputs has a higher prediction accuracy and performance for industrial CO2 emissions than the extreme learning machine, back propagation neural network, and back propagation neural network optimized by the genetic algorithm. It also shows that the five influencing factors have a significant impact on industrial CO2 emissions. Finally, based on the analysis of five influencing factors, some policy recommendations are proposed for the CO2 emissions reduction path in the industrial sectors. [ABSTRACT FROM AUTHOR]

Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio (FR) method is one of the most popular. However, the results of such assessments are dominated by the number of classes and bounds of landslide-related causative factors, and the optimal assessment is unknown. This paper optimizes the frequency ratio method as an example of bivariate statistical analysis for landslide susceptibility mapping based on a case study of the Caiyuan Basin, a region with frequent landslides, which is located in the southeast coastal mountainous area of China. A landslide inventory map containing a total of 1425 landslides (polygons) was produced, in which 70% of the landslides were selected for training purposes, and the remaining were used for validation purposes. All datasets were resampled to the same 5 m × 5 m/pixel resolution. The receiver operating characteristic (ROC) curves of the susceptibility maps were obtained based on different combinations of dominating parameters, and the maximum value of the areas under the ROC curves (AUCs) as well as the corresponding optimal parameter was identified with an automatic searching algorithm. The results showed that the landslide susceptibility maps obtained using optimal parameters displayed a significant increase in the prediction AUC compared with those values obtained using stochastic parameters. The results also showed that one parameter named bin width has a dominant influence on the optimum. In practice, this paper is expected to benefit the assessment of landslide susceptibility by providing an easy-to-use tool. The proposed automatic approach provides a way to optimize the frequency ratio method or other bivariate statistical methods, which can further facilitate comparisons and choices between different methods for landslide susceptibility assessment. [ABSTRACT FROM AUTHOR]

Coupling of the bivariate copula function and likelihood function was utilized for parameter estimation in precipitation frequency analysis. In this method, data of various lengths in a homogeneous region were incorporated into a multivariate framework. Therefore, the information contained in one series can be employed to improve the accuracies of the design values of other series. Annual precipitation data collected from 36 stations in the Guanzhong region, China, were used as a case study. To obtain more reliable estimates, the stationarity and serial independence of each series were tested first. Then, the entire study region was divided into four homogeneous sub-regions, and frequency analyses were carried out in each sub-region. Two measures, the standard error of fit (SEF) and the maximum absolute relative deviation (MARD), were used to compare the goodness-of-fit of the copula-based composite likelihood approach with the univariate method. Results showed that the SEF and MARD values of the design precipitation values obtained from the copula-based composite likelihood approach were lower than those from the univariate method, and the decrease became more significant for stations with a shorter series in the bivariate composite case. Therefore, this study indicates the advantage of the use of a copula-based composite likelihood approach for improving the accuracy of design precipitation values. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the main cause of the greenhouse effect. With the rapid development of the economy in China, CO2 emissions have increased dramatically. To reduce CO2 emissions, ensure the sustainability of China's economy and implement the Paris International Convention, it is important to investigate the main factors affecting CO2 emissions and use those factors to accurately forecast CO2 emissions. In order to achieve accurate prediction of CO2, this paper proposes a CO2 emission prediction model based on principal component analysis (PCA) and particle swarm optimization for least squares support vector machine (PSO-LSSVM). Through data 1990-2016 in Hebei Province of China, this paper identifies 24 influencing factors though the bivariate correlation analysis. After applying PCA to reduce the dimensions of the influencing factors, two principal components were extracted as input variables. Then the parameters of the LSSVM model are obtained by PSO and the forecast model is established. By comparing the prediction results with actual values, it is proved that the prediction error of the PSO-LSSVM prediction model is 0.663%, which is smaller than that of the traditional BPNN and LSSVM models. [ABSTRACT FROM AUTHOR]

Drought projection is of critical significance for designing long-term drought adaptation strategies to cope with changing climate. This study presents an application of multi-class models for characterizing future droughts in the Yellow River basin (YRB). Using meteorological observations and simulations of three CMIP5 climatic models as input into VIC hydrologic model, the standardized Palmer drought index-based joint drought index (SPDI-JDI) is calculated to investigate spatiotemporal patterns and possible changes of future drought in the YRB, through an approach of bivariate modeling and analysis. It is concluded that moderate drought will be alleviated with decreased duration and severity, but extreme drought risk is likely to increase for future climate scenarios (2021–2050) relative to baseline period (1961–2000). From the perspective of bivariate analyses, the concurrence probability of drought events with extreme duration and severity might rise in the future, while increasing variability and heterogeneity of duration, severity and bivariate joint/concurrent return period would also increase the stochastic occurrence of extreme drought over time and space. These findings can provide insights into projection of climate change impacts on drought trends for the next 30 years, and help to preparations for strict control of socio-economic water consumption as well as eco-environmental protection and restoration in the YRB. [ABSTRACT FROM AUTHOR]

In drought analysis, many types of research have applied bivariate analysis. However, a more effective appraisal is achievable by employing three mutually correlated drought variables (i.e., duration, severity, peak) concurrently. This study adopted trivariate copulas for multivariate drought frequency estimation in seven climatic sub-regions and mainland China between 1961 and 2013. The joint distribution is modeled using nine trivariate copula functions, namely Clayton, Ali–Mikhail–Haq (AMH), Gumbel–Hougaard, Frank, M3, M4, M5, M6, and M12. The performance of the different copulas was evaluated using the root mean square error (RMSE), Akaike information criterion (AIC), bias, and graphical test. The results showed that trivariate Clayton copula performed better in modeling joint dependence structure of drought variables in contrast to other class of copulas in sub-regions I–VII and mainland China. Therefore, the Clayton copula–based drought joint distributions were used for the multivariate drought frequency analysis, regarding probabilities and return periods. The joint probabilities in the "OR" cases were greater than that of the "AND" cases in all the seven sub-regions and mainland China. There is every possibility that drought event occurrence will be given for "OR" cases. Accordingly, counter measures of drought hazards need to be set for proactive responses especially in sub-regions III, V, and VI. The trivariate return periods were compared with the univariate and bivariate return periods and discussed the need of multivariate drought frequency analysis. In conclusion, the Clayton trivariate copula is an excellent choice for efficient drought risk evaluation, and results are very handy in the design of water resource hydrologic systems under severe and extreme drought conditions. [ABSTRACT FROM AUTHOR]

This study investigated the characteristics of rainfall-triggered landslides during the Typhoon Bilis in the Dongjiang Reservoir Watershed, China. The comparative shallow landslide susceptibility mappings (LSMs) were produced by the ensemble data-driven statistical models in a GIS environment. At first, the landslide inventory for the study area was prepared from the high-resolution QuickBird images, and China–Brazil Earth Resources Satellite images, and field survey. Other necessary data for landslide susceptibility analysis such as the amount of rainfall, geology, and topography were also collected from the respective agencies. Twelve predisposing factors were then prepared using this available dataset. To reduce the subjectivity of models and caution in the selection of predisposing factors, and to avoid the spatial autocorrelation redundancy, certainty factor approach was attempted to optimize these twelve set of parameters. For validating the accuracy of the model, the original landslide data were randomly divided into two parts: 70% (1545 landslides) for training the model and the remaining 30% (662 landslides) for validation. The verified results showed that using the optimized predisposing factors has a higher performance than using all the original twelve factors. The results of ensemble models also showed that LSM maps prepared using binary logistic regression (accuracy is 0.848) model are more accurate than those prepared using bivariate statistical analysis (accuracy is 0.837) model. Additionally, our analysis concludes that the short duration and high-intensity rainfall, drainage density, lithology, and curvature are the major influencing factors for landslide occurrences in this case study area. This research provides an improved understanding of the mechanism of landslides caused by the typhoons for the adjoining watersheds nearby the reservoir. The preliminary understandings and approach could also be applied in similar geological and rainfall-triggered case study sites in the other parts of the world for risk mitigation. [ABSTRACT FROM AUTHOR]

The middle and lower reaches of the Yangtze River serves as an important grain production base in China. In the context of global climate change, the drought events will directly affect the agriculture production and people's properties and lives in this region and also the national food security. In this study, the meteorological drought events have been extracted using run theory based on the standardized precipitation index (SPI), which is defined using the gridded dataset of monthly precipitation with a spatial resolution of 0.5° × 0.5° in China from 1961 to 2015. The drought events are characterized by three variables including duration, severity and peak. Exponential and Gamma functions are then selected to describe the marginal distribution of drought duration and severity, respectively. The Clayton Copula is used to construct the joint distribution of drought duration and severity. Based on the above functions, conventional univariate frequency analysis and copula- based bivariate frequency analysis are used to characterize the spatial patterns of the drought events in the study area at various time scales over the past 55 years. While univariate analysis is focused on return levels of selected return periods (5-, 10-, 20-, and 30-year) for the SPI of 3-, 6-, and 12-month time scales, the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of drought duration and severity, where P1 is the probability of "drought duration and severity" exceeding their respective thresholds at the same time and P2 is the probability of "drought duration or severity" exceeding their respective thresholds at the same time. Here, the thresholds denote the duration and severity values corresponding to selected 5-, 10-, 20- and 30- year return periods. The results show that: (1) There are some differences between the spatial patterns of drought characteristics for the 3- month, 6- month, 12- month time scales in the middle and lower reaches of the Yangtze River, and the most serious droughts mainly occur in the lower reaches of the river. (2) Both drought duration and severity are positively correlated at various time scales, that is, the areas with higher drought severity are also associated with longer drought duration and vice versa. (3) Poyang Lake watershed and areas north of the lower Yangtze River are associated with larger values of the joint occurrence probability P1, that is, when the drought duration and severity exceed their corresponding 5, 10, 20 and 30- year return values at the same time, while smaller values of the joint occurrence probability P1 are noted for Southern Shaanxi, Southern Henan, a major portion of Hubei and central-north of Hunan, suggesting a low risk of droughts in these areas. The results of this study can provide theoretical basis for scientific managements of water resource and the risk assessments of drought disaster in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

Highlights • How land tenure arrangements affect the adoption of straw retention in China is examined. • A three-period adoption model for straw retention is constructed. • Probit, bivariate probit and control function approaches have been applied. • Probability of adopting straw retention is found significantly lower on rented plots. Abstract We examine how land tenure arrangements affect Chinese crop farmers' adoption of straw retention, a key conservation practice promoted by the Chinese government in part to curb rising air pollution. Using data from a 2016 farmer household survey covering 1659 crop plots in Henan Province in central China, we analyze whether farmers are less likely to adopt straw retention on rented plots compared to own-contracted plots. To address the potential endogeneity of the choice of renting from others, we use an instrument exploiting the role of remittance income from household members migrated to cities in a bivariate probit model and a control function approach, respectively. Our main results reveal that the Chinese crop farmers' likelihood of adopting straw retention were almost cut in half on rented plots compared to their owned plots, assuming the assumptions for biprobit or control functions hold. This suggests greater attention is needed to examine the spillovers across agricultural and environmental policies as China pushes for both a nationwide land rental market and more sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

Hydrological risk analysis is essential and provides useful information for dam safety management and decision-making. This study presents the application of bivariate flood frequency analysis to risk analysis of dam overtopping for Geheyan Reservoir in China. The dependence between the flood peak and volume is modelled with the copula function. A Monte Carlo procedure is conducted to generate 100,000 random flood peak-volume pairs, which are subsequently transformed to corresponding design flood hydrographs (DFHs) by amplifying the selected annual maximum flood hydrographs (AMFHs). These synthetic DFHs are routed through the reservoir to obtain the frequency curve of maximum water level and assess the risk of dam overtopping. Sensitive analysis is performed to investigate the influence of different AMFH shapes and correlation coefficients of flood peak and volume on estimated overtopping risks. The results show that synthetic DFH with AMFH shape characterized by a delayed time to peak results in higher risk, and therefore highlight the importance of including a range of possible AMFH shapes in the dam risk analysis. It is also demonstrated that the overtopping risk is increased as the correlation coefficient of flood peak and volume increases and underestimated in the independence case (i.e. traditional univariate approach), while overestimated in the full dependence case. The bivariate statistical approach based on copulas can effectively capture the actual dependence between flood peak and volume, which should be preferred in the dam risk analysis practice. [ABSTRACT FROM AUTHOR]

• XXT was eluted into 5 fractions by the macroporous absorption resin separation method. The fingerprints of different fractions were built and main chemical components were identified by UPLC-Q-TOF/MS technology. • The rat model of T2DM was successfully established and applied to assess the efficacy of different fractions from XXT. Results showed that XXT-1 and XXT-2 were the most active fractions. • The bioactive constituents of XXT were screened out by spectrum-effect relationship with grey relational analysis and pearson bivariate correlation analysis. Xiexin Tang (XXT) is a classic prescription for treating diabetes in clinical practices for thousands of years in China, which has been also proved by a large number of modern pharmacological studies. However, due to its complex composition, the bioactive ingredients of XXT is still unclear. In present researches, spectrum-effect relationship analysis is widely used to explore the material basis of traditional medical herbs, so this method was adopted in this study. Firstly, the extract of XXT was separated and enriched into 5 fractions by macroporous adsorption resin. Then, UPLC-Q-TOF/MS method was used for qualitative identification of components in each eluting part, and efficacy of each fraction was assessed by the T2DM rat model. Based on grey relational analysis and pearson bivariate correlation analysis, it was found that the components such as berberine, gallic acid, catechin, epicatechin, acteoside, berberastine and 1-O-galloyl-β-D-glucose might be the main effective basis of XXT to improve T2DM. [ABSTRACT FROM AUTHOR]

Haze is a major environmental concern in many cities because it adversely affects people's physiological and psychological well-being. This paper examines the extent of haze in Macao during the period 1986-2016. It identifies the relationships between haze, energy use, and meteorological conditions directly. The haze in Macao changed over the period 1986-2016 with air pollution getting worse and then improving after 2007. Specifically, the number of haze hours increased from 3 in 1986 to 766 in 2007, and then dropped to 57 in 2016, while the total energy use increased from 12,246 TJ in 1986 to 37,144 TJ in 2007, and then to 42,405 TJ in 2016. As per primary energy, Macao used 12,096 TJ in 1986, 21,388 TJ in 2007, and 16,647 TJ in 2016 excluding aviation kerosene. Bivariate correlations show that haze was most positively and significantly associated with annual primary energy use. Multiple regression analysis indicates that the number of hours with haze was significantly, positively related to the consumption of gas oil/diesel, fuel oil, and natural gas in Macao and aviation kerosene. Nevertheless, the improvement in Macao could come at a cost to areas in downwind of Zhuhai's coal power stations supplying Macao's electricity energy. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to evaluate factors affecting e-bike involved crash and license plate use in China. E-bike crashes data were collected from police database and completed through a telephone interview. Noncrash samples were collected by a questionnaire survey. A bivariate probit (BP) model was developed to simultaneously examine the significant factors associated with e-bike involved crash and e-bike license plate and to account for the correlations between them. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results show that several contributory factors, including gender, age, education level, driver license, car in household, experiences in using e-bike, law compliance, and aggressive driving behaviors, are found to have significant impacts on both e-bike involved crash and license plate use. Moreover, type of e-bike, frequency of using e-bike, impulse behavior, degree of riding experience, and risk perception scale are found to be associated with e-bike involved crash. It is also found that e-bike involved crash and e-bike license plate use are strongly correlated and are negative in direction. The result enhanced our comprehension of the factors related to e-bike involved crash and e-bike license plate use. [ABSTRACT FROM AUTHOR]

Rainfall variability during the early-flood season (April-June) in South China is largely controlled by both the 10-20 and 20-70-day intraseasonal oscillations (ISO). In this study, a method is described to monitor the ISO and persistent heavy rainfall in South China. Three existing daily real-time 20-70-day ISO indices are compared. It is found that the regional East Asia-western North Pacific (EAWNP) ISO index best represents the early-flood season 20-70-day ISO in South China. A new bivariate boreal summer ISO index is designed to describe the 10-20-day ISO in the EAWNP region. Composite analysis shows that the rainfall anomaly in South China is well captured by the northward propagation of both the 10-20 and 20-70-day ISO. With different phase combinations of the 10-20 and 20-70-day EAWNP ISO, nine conditions are defined ranging from those favorable to those unfavorable to heavy rainfall in South China that can be used to effectively monitor the early-flood season ISO and persistent heavy rainfall in South China. [ABSTRACT FROM AUTHOR]

China′s economy and transport infrastructure have both experienced rapid development since 1978, and especially since 1990. Today, China is the second-largest economic entity in terms of GDP and has the largest high-speed rail (HSR) network and the second-largest expressway network in the world. This paper explores the relationship between accessibility and economic growth in China from 1990 to 2010. In the study, the basic research units include 333 prefecture-level cities and four municipalities. We explore a bivariate analysis framework of accessibility and economic growth, and their increase rates, to examine this relationship using long-term panel data. The results indicate that, first, accessibility and economic growth show a significant positive relationship using both cross-section and panel data, while the increase rate in accessibility and GDP indicate no significant relationship using cross-section data and a poor significant relationship using panel data. Second, the distributions of local advantage are uneven. Cities with low local advantage with respect to accessibility and GDP are mainly located in China′s eastern coastal region or the provincial capitals, while those with low local advantage in terms of their increase rates are located in the western region. Third, as China′s economic growth and transport networks have evolved, the distribution of local advantage shows little change in terms of accessibility and GDP, but a greater change in terms of their increase rates, which is largely influenced by the distribution of expressway and HSR networks. [ABSTRACT FROM AUTHOR]

In this study, a bivariate hydrologic risk framework is proposed based on a coupled entropy-copula method. In the proposed risk analysis framework, bivariate flood frequency would be analyzed for different flood variable pairs (i.e., flood peak-volume, flood peak-duration, flood volume-duration). The marginal distributions of flood peak, volume, and duration are quantified through both parametric (i.e., gamma, general extreme value (GEV), and lognormal distributions) and nonparametric (i.e., entropy) approaches. The joint probabilities of flood peak-volume, peak-duration, and volume-duration are established through copulas. The bivariate hydrologic risk is then derived based on the joint return period to reflect the interactive effects of flood variables on the final hydrologic risk values. The proposed method is applied to the risk analysis for the Xiangxi River in the Three Gorges Reservoir area, China. The results indicate the entropy method performs best in quantifying the distribution of flood duration. Bivariate hydrologic risk would then be generated to characterize the impacts of flood volume and duration on the occurrence of a flood. The results suggest that the bivariate risk for flood peak-volume would not decrease significantly for the flood volume less than 1000 m/s. Moreover, a flood in the Xiangxi River may last at least 5 days without significant decrease of the bivariate risk for flood peak-duration. [ABSTRACT FROM AUTHOR]

[Display omitted] • This research screened out 8 potential active ingredients of Curcuma wenyujin Y.H. Chen et C. Ling rhizome, which provide a research basis for the clinical application of Curcuma wenyujin Y.H. Chen et C. Ling rhizome. • This research established a new method for screening active ingredients by spectrum-effect relationship analysis and network pharmacology, which provided scientific basis for TCM quality control to ensure its safety and efficacy. • Different from other spectrum-effect relationship research, this study explored the correlation degree between components in plasma and pharmacologic actions by bivariate correlation analysis, which provides a new research strategy for active component screening of TCM. Curcuma wenyujin Y.H. Chen et C. Ling rhizome (also called EZhu in China) has long been used as plant medicine for its traditional effect on promoting blood circulation and remove blood stasis. However, the active components of EZhu are still unclear at present. This research is managed to investigate the pharmacodynamics material basis on removing blood stasis of EZhu by exploring the spectrum-effect relationship between UPLC-Q/TOF-MS fingerprints and pharmacologic actions. Hemorheology and related functional parameters were detected to evaluate the pharmacologic actions of EZhu. Relative content Changes of components in rat plasma were detected by UPLC-Q/TOF-MS. A compound-target-pathway network was built to predict the pharmacological activity of components in plasma. Then, bivariate correlation analysis (BCA) was used to explore the correlation degree between components in plasma and pharmacologic actions of EZhu. In UPLC-Q/TOF-MS fingerprints of rat plasma, 10 prototype components were identified. BCA results show that 8 components were concerned with the pharmacological activity for treating blood stasis syndrome (BSS) in varying degrees (R > 0.5, P < 0.05). Among them, zedoarofuran and curzerenone have shown correlation with more pharmacological indicators. The network predicted that 80 targets were closely related to 10 components, in which 48 targets were connected with 159 metabolic pathways including arachidonic acid metabolism, sphingolipid signaling pathway, and linoleic acid metabolism. Overall, this study provided a scientific basis for TCM quality control to ensure its safety and efficacy. [ABSTRACT FROM AUTHOR]

• A framework is proposed to investigate the drought hazard propagation. • Drought hazards are quantified by the most-likely scenarios and uncertainty envelope. • Drought hazards tend to ascend from meteorological to hydrological droughts. As a major weather-driven disaster, drought can be assessed from meteorological to hydrological aspects. Although the propagation from meteorological to hydrological droughts has received lots of attention in recent years, the hazard transferability in such a propagation process has been less investigated. In this study, we propose a framework with the incorporation of copulas and a drought hazard propagation ratio (DHPR) to examine the drought propagation process, particularly to investigate the accompanying hazard transferability. Three catchments with few human activities located in two major river basins of China (i.e., the Yangtze River basin and the Yellow River basin) with different hydro-climatic conditions are selected as case studies. First, the standardized precipitation evapotranspiration index (SPEI) and the standardized runoff index (SRI) are calculated to measure meteorological and hydrological droughts for the 1961–2014 period. Subsequently, the drought duration and severity are identified using the theory of run, and then the most-likely scenarios and the corresponding uncertainty ellipse based on copulas are incorporated to appraise meteorological and hydrological drought hazards. Finally, a novel concept of DHPR is proposed to evaluate the hazard transferability from meteorological to hydrological drought. The results show that (1) the drought propagation generally shows lengthened duration, amplified severity, and the time-delay phenomenon among these catchments; (2) drought hazards represented by the most-likely scenarios of duration and severity and the uncertainty ellipse tend to ascend based on the bivariate frequency analysis; and (3) the hazard transferability is stable from meteorological to hydrological droughts, as indicated by the almost unchanged DHPR ranging between 1 and 2 for the most-likely scenarios and varying between 2 and 4 for the uncertainty ellipse under different return periods. The above results imply firm and robust correlations between meteorological and hydrological drought hazards, which can provide a supplement for revealing the drought propagation mechanism and would benefit drought risk assessment. [ABSTRACT FROM AUTHOR]

• Projected changes of bivariate flood quantiles are evaluated over 151 catchments across China. • The uncertainty envelope is quantified with a copula-based parametric bootstrapping uncertainty approach. • Outputs of multi-model ensembles after bias correction are used to drive four hydrological models. • Bivariate flood quantiles and estimation uncertainty of most catchments are increasing under climate warming. As atmospheric moisture capacity is highly sensitive to rising temperatures, precipitation extremes are widely projected to intensify with a warming climate and thus altering the flooding generation regime. Previous works seldomly focused on bivariate flood quantiles under climate change at a national scale, and fewer flooding projections quantified the estimation uncertainty sourced from sample size limitation. This study systematically investigates the changes in bivariate quantiles of flood peak and volume with incorporation of sampling uncertainty for 151 catchments over China, with climate trajectories projected by a set of multi-model ensemble under representative concentration pathway (RCP) 8.5. After correcting the systematical biases of eight CMIP5 GCM outputs, four state-of-the-art hydrological models are driven and validated for each catchment, and the best-simulation model is selected to project future streamflow scenarios. The copula function is employed to construct the joint distribution of flood peak and volume, and then the most likely realizations of bivariate quantiles are derived under different Joint Return Periods (JRPs), with the uncertainty envelope quantified with the area of 90% confidence ellipse by a copula-based parametric bootstrapping uncertainty (C-PBU) approach. Our results project an overall ascending trend of temperature and precipitation over China, and the bivariate flood quantiles and corresponding estimation uncertainty of most catchments in the future period (2056–2100) are much larger than the baseline (1961–2005), despite accompanied by substantial climate model uncertainty and spatial variability in magnitude. Many basins would be subjected to a dramatic increase of flood magnitude by over 50%, while only few basins are projected to experience a decreasing flood risk, suggesting an urgent need to increase societal resilience to a warming climate over China. [ABSTRACT FROM AUTHOR]

Environmental risk assessment (ERA) increasingly relies on speciation modeling of bioavailability. Heavy metals are the most prevalent pollutants globally, and dissolved organic matter (DOM) plays an important role in speciation and bioavailability of heavy metals. Due to the variation of DOM properties in natural aquatic systems, improvements to the standard one-size-fits-all approach to modeling metal-DOM interactions are needed for ERA. In this study, we investigate variations in DOM and lead (Pb)-DOM binding in Lake Tai (Taihu), a large, impacted lake in eastern China that is characterized by a complex drainage network and is an important water resource at a regional level, and we assess implications of our findings within the context of ERA needs. In our study, DOM in water samples collected from across the 2,400 km2 area of Taihu was characterized using three-dimensional excitation-emission matrix and synchronous fluorescence spectroscopy spectra, the latter being used to calculate conditional stability constants for metal binding. Parallel factor analysis and peak picking were used to assess contributions of protein- and humic-like components of DOM, and fluorescence indices indicative of diagenetic processes were calculated. These quantities calculated from spectroscopic studies, in addition to water quality parameters, were analyzed by bivariate and multivariate analysis. Results show that different DOM components are highly variable across different regions of Taihu, and bivariate and multivariate analyses confirm that water quality and DOM characterization parameters are strongly interrelated. This reflects the different inputs, diagenetic and transport processes across the large expanse of Taihu. We find that the conditional stability constant of Pb-DOM binding is strongly affected by the water chemical properties and composition of DOM, though the conditional stability constant is not itself a parameter that differentiates lake water properties in different regions of the lake. The variability of DOM composition and Pb-DOM binding strength across Taihu is consistent with prior findings that a one-size-fits-all approach to metal-DOM binding may lead to inaccuracies in commonly used speciation models, and therefore such generalized approaches need improvement for regional-level ERA in complex watersheds. The approach taken here to obtain site-specific metal-DOM conditional stability constants for use in increasing the accuracy of speciation modeling is fit-for-purpose for ERA applications at regional levels because the approach is relatively simple, inexpensive, and amenable to high throughput analysis. Image 1 • Harmful algal blooms cause large regional variations in DOC composition and reactivity. • Metal reactivity can be predicted by water quality and DOC parameters. • Findings support understanding of watershed processes across an extended, complex drainage area. • Approach to parameter development would be fit for ERA applications at regional levels. [ABSTRACT FROM AUTHOR]

The blockage of foreign Web sites, which is often called the "Great Firewall (GFW)", serves an important part of the Internet censorship in mainland China. This study investigated the inequality of bypassing the GFW in mainland China, and the possible difference in some "capital-enhancing" uses of the Internet (using the Internet for work, learning and political expression) between GFW-bypassing netizens and those still suffer from strict Internet censorship. This study used data from the China Family Panel Studies (CFPS). Although there is no direct measurement of netizens' GFW bypassing, a variable measuring the ownership of Facebook accounts was used as a proxy of the status of GFW bypassing. Firstly, the results of bivariate analyses and multiple correspondence analysis (MCA) suggest that mainland Chinese netizens who can bypass Internet censorship and access blocked foreign Web sites are more socio-economically better off (higher social class, well-educated and urban residing) and younger. Moreover, the results of ordinary least squares (OLS) regression and logistic regression models tell that in general bypassing the GFW is related to more activeness in using the Internet for learning and political expression. After controlling socio-economic and demographic characteristics, GFW bypassing is no longer found to be related to online learning, but is still related to an expression of political views online. [ABSTRACT FROM AUTHOR]

• The impact of influencing factors on injury severity of side crashes at intersections and role of striking and struck vehicles are investigated. • Bayesian bivariate probit model is proposed to accommodate the correlation between the injury severity levels of striking and struck vehicles, and Bayesian approach via Markov Chain Monte Carlo (MCMC) is employed to estimate the model. • The Bayesian bivariate probit model can effectively address the correlation and provide better model fit than Bayesian univariate probit model. • The findings can help designers and management departments improve the safety at intersections. Side crashes between vehicles which usually lead to high casualties and property loss, rank first among total crashes in China. This paper aims to identify the factors associated with injury severity of side crashes at intersections and to provide suggestions for developing countermeasures to mitigate the levels of injuries. In order to investigate the role of striking and struck vehicles in side crashes simultaneously, bivariate probit model was proposed and Bayesian approach was employed to evaluate the model, compared to the corresponding univariate probit model. Crash data from Beijing, China for the period 2009–2012 were used to carry out the statistical analysis. Based on the investigation with vehicles and data analysis on events, 130 intersection side crash cases were selected to form a specific dataset. Then, the influence of human, vehicles, roadway and environmental variables on crash severity was examined by means of bivariate probit regression within Bayesian framework. The effects of the factors on striking vehicle drivers and struck vehicle drivers were considered separately and simultaneously to find more targeted conclusions. The statistical analysis revealed vehicle type, lane number, no non-motorized lane and speeding have the corresponding influence on the injury severity of striking vehicles, while time of day and vehicle type of struck vehicles increased the likelihood of being injured. From the results it can be concluded that there indeed exists correlation between striking and struck vehicles in side crashes, although the correlation is not so strong. Importantly, Bayesian bivariate probit model can address the role of striking and struck vehicles in side crashes simultaneously and can accommodate the correlation clearly, which extends the range of univariate probit analysis. The general and empirical countermeasures are presented to improve the safety at intersections. [ABSTRACT FROM AUTHOR]

Estimating underlying mechanisms and dynamics from observed tree patterns can provide guidance for plantation management. Robinia pseudoacacia can reproduce via clonally produced ramets, leading to a complex distribution of stems. Three second generation plots and three third generation plots (each plot 50 m × 50 m) were established across a wide age range after clear-cutting in a Robinia pseudoacacia plantation in central China. We measured spatial coordinates, diameter at breast height (DBH) or diameter at basal stem, and heights of all recruits, as well as the coordinates and base diameter of all stumps, in six plots. The spatial pattern in different plots and the spatial relation between stumps and regenerations after clear-cutting were analyzed. To estimate the underlying processes of the observed patterns, we fitted Matérn and Variance-Gamma cluster processes to the observed dataset. The results revealed that the percentage of ramets from stumps decreasing with age in the two types of stands (from 40.4% to 30.1%, from 57.6% to 35.7%), and trees exhibited an aggregated distribution in all plots, but the degree of aggregation exhibited a decreasing trend with age, and aggregation occurred at different scale. Furthermore, a large proportion of ramets had their nearest neighbor at a short distance (<1 m) based on analysis of the nearest neighbour function. The bivariate analysis revealed that the spatial relation between stumps and ramets changed with age, and a repulsion trend was found between them in all the six plots. The Variance-Gamma process with covariate of Cartesian coordinates fitted the observed patterns better than others. The observed pattern was likely driven by root dispersal limitation, seed dispersal limitation, human disturbance, and intraspecific competition. Spatial patterns are important characteristics in forest stand structure, and understanding the pattern change and its underlying mechanisms could allow for better timing of artificial disturbances to optimize stand structure and promote stand growth. [ABSTRACT FROM AUTHOR]

• This paper proposes a copula-based method for daily stochastic streamflow simulation. • The proposed method can consider lag-2 correlations. • The proposed method preserved the basic statistics of observed data. • The proposed method produced smaller relative errors than the current methods. Daily stochastic streamflow simulation is widely used for the design of reservoirs, evaluation of reservoir operation rules, and risk evaluation of operation of water resources systems. The major difficulties and challenges of daily streamflow are that there are 365 days that need to be simulated, which entails much more calculation than does monthly streamflow simulation. Since lag-2 auto-correlation is usually large, the lag-2 correlations should be considered. This paper therefore proposes a copula-based method for daily stochastic streamflow simulation. The contribution and novelty of this paper are that: (a) the proposed method can consider lag-2 correlations, compared with the currently used copula based method; (b) the conditional copulas are used to build high dimensional copulas, which make calculations easier; and (c) the method can be used for daily streamflow simulation because of the simplified model structure and effective parameter estimation method. Seven gauging stations on the upper Yangtze River and Pearl River in China were selected as case studies. Results demonstrated that the proposed method preserved the basic statistics (including mean daily flow, standard deviation, and coefficient of skewness) of observed data of each day well. Comparison with the currently used seasonal autoregressive model (SAR(2)) and bivariate copula-based method considering lag-1 autocorrelation indicated that the proposed method produced smaller relative errors and was better overall. Therefore, the proposed method can be regarded as an effective way for stochastic daily streamflow simulation, and can be used for the design of reservoirs and risk analysis of water resources systems. [ABSTRACT FROM AUTHOR]

Interactions between financial time series are complex and changeable in both time and frequency domains. To reveal the evolution characteristics of the time-varying relations between bivariate time series from a multi-resolution perspective, this study introduces an approach combining wavelet analysis and complex networks. In addition, to reduce the influence the phase lag between the time series has on the correlations, we propose dynamic time-warping (DTW) correlation coefficients to reflect the correlation degree between bivariate time series. Unlike previous studies that symbolized the time series only based on the correlation strength, the second-level symbol is set according to the correlation length during the coarse-graining process. This study presents a novel method to analyze bivariate time series and provides more information for investors and decision makers when investing in the stock market. We choose the closing prices of two stocks in China's market as the sample and explore the evolutionary behavior of correlation modes from different resolutions. Furthermore, we perform experiments to discover the critical correlation modes between the bull market and the bear market on the high-resolution scale, the clustering effect during the financial crisis on the middle-resolution scale, and the potential pseudo period on the low-resolution scale. The experimental results exactly match reality, which provides powerful evidence to prove that our method is effective in financial time series analysis. [ABSTRACT FROM AUTHOR]

Background: In Xuan Wei, China, the lung cancer mortality rate is rising significantly more than that of the nation overall. However, it remains unclear 1) if improved diagnosis can just partially explain this observation and how other local risk factors may be correlated with the lung cancer mortality rate and 2) how the lung cancer mortality rates differ within Xuan Wei and how these spatiotemporal patterns are linked with local risk factors. To increase etiological knowledge, this study evaluated the spatial and temporal distributions of the health effects (the lung cancer mortality rates) from 2011 to 2015.Methods: Four steps of spatial analysis were applied, as follows: 1) hotspot analysis to determine the geographical patterns of lung cancer mortality, 2) spatially-weighted sum to identify areas with higher health risks, 3) bivariate statistical analysis to assess the overall correlation between coal mines and lung cancer mortality, and 4) geographically-weighted regression to test for correlations among different towns within Xuan Wei.Results: Women had higher lung cancer mortality rates than those in men, with an increasing trend in both sexes over time. The incidence rates in Laibin Town were the highest in Xuan Wei every year. Over the 5-year study period, the lung cancer mortality was increasingly concentrated in Laibin, Shuanglong, and Longchang, where the smoky coal mines are most concentrated. The population-level health risks from the coal mine in Xuan Wei were mapped and divided into five types of risk areas (Type I - Type IV). Correlation analysis revealed that there was no significant correlation between lung cancer mortality as a whole and coal mine distribution during the 5-year study period. However, the geographically-weighted regression revealed a stronger correlation in medium (Type III) and second-lowest (Type IV) health risks.Conclusions: Xuan Wei lung cancer mortality has increased continuously since the third national retrospective surveys on the causes of death by the Ministry of Health of the People's Republic of China (2004-2005), especially for local women and residents over 35 years of age. Geographically, lung cancer in Xuan Wei showed unique spatiotemporal clustering. The local lung cancer mortality was significantly correlated with the smoky coal mine geographically. Some specific towns (Laibin, Shuanglong, and Longchang) within Xuan Wei manifested high correlations between lung cancer mortality and coal mines. The effects of coal mines on lung cancer mortality rates also spread geographically outward from these areas. Public health concern regarding lung cancer in Xuan Wei should prioritize higher-risk towns surrounded by smoking coal mines. Intervention strategies for particular toxic coal types require further studies on their chemical characteristics and mechanisms of carcinogenesis. Additional studies are also warranted to systematically examine the local environmental health risks related to coal industries and combustion air pollution and eventually to conduct early screening of lung cancer for local people who are more exposed to smoky coal in high-risk areas. [ABSTRACT FROM AUTHOR]

With the changing environment, a number of researches have revealed that the assumption of stationarity of flood sequences is questionable. In this paper, we established univariate and bivariate models to investigate nonstationary flood frequency with distribution parameters changing over time. Flood peak Q and one-day flood volume W1 of the Wangkuai Reservoir catchment were used as basic data. In the univariate model, the log-normal distribution performed best and tended to describe the nonstationarity in both flood peak and volume sequences reasonably well. In the bivariate model, the optimal log-normal distributions were taken as marginal distributions, and copula functions were addressed to construct the dependence structure of Q and W1. The results showed that the Gumbel-Hougaard copula offered the best joint distribution. The most likely events had an undulating behavior similar to the univariate models, and the combination values of flood peak and volume under the same OR-joint and AND-joint exceedance probability both displayed a decreasing trend. Before 1970, the most likely combination values considering the variation of distribution parameters over time were larger than fixed parameters (stationary), while it became the opposite after 1980. The results highlight the necessity of nonstationary flood frequency analysis. [ABSTRACT FROM AUTHOR]