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Recurrence of postoperative adhesions is one of the most important factors for poor reproductive outcomes after hysteroscopic surgery, particularly in cases diagnosed with severe intrauterine adhesions (IUAs), where the recurrence rate is significantly higher. This study aims to explore the effectiveness of the electrical muscle stimulation combined with ultrasound acupuncture therapy in preventing the recurrence of IUAs and improving reproductive outcomes after operative hysteroscopy.This study is a single-center, randomized controlled trial. A total of 210 patients with IUAs will be randomly assigned into 2 groups according to the ratio of 1:1, as the treatment group and the control group. Participants will receive the electrical muscle stimulation combined with ultrasound acupuncture therapy and oral hormone supplementation or receive oral hormone supplementation only. The primary outcome was the clinical response rate. There were 3 menstrual cycles of treatment and 3 menstrual cycles of follow-up in this study.This study protocol was approved by the Ethics Committee of the Reproductive Hospital of Guangxi Zhuang Autonomous Region (approval number: KY-LL-2022-06). This trial will be conducted in accordance with the principles of the Declaration of Helsinki as well as Good Clinical Practice. Study results will be disseminated at academic presentations and publications in peer-reviewed journals.Registry name: Clinical value of electroultrasonic instrument in the treatment of IUAs and changes of related protein expression; Registry number: ChiCTR2200058901; registration date: April 19th, 2022; http://www.chictr.org.cn/showproj.aspx?proj=166155.

Background:Recurrence of postoperative adhesions is one of the most important factors for poor reproductive outcomes after hysteroscopic surgery, particularly in cases diagnosed with severe intrauterine adhesions (IUAs), where the recurrence rate is significantly higher. This study aims to explore the effectiveness of the electrical muscle stimulation combined with ultrasound acupuncture (ULTRA-EMS) therapy in preventing the recurrence of IUAs and improving reproductive outcomes after operative hysteroscopy.Methods:This study is a single-center, randomized controlled trial. A total of 210 patients with intrauterine adhesions will be randomly assigned into two groups according to the ratio of 1:1, as the treatment group and the control group. Participants will receive the ULTRA-EMS therapy and oral hormone supplementation or receive oral hormone supplementation only. The primary outcome was the clinical response rate. There were three menstrual cycles of treatment and three menstrual cycles of follow-up in this study.Ethics and Dissemination: This study protocol was approved by the Ethics Committee of the Reproductive Hospital of Guangxi Zhuang Autonomous Region (approval number: KY-LL-2022-06). This trial will be conducted in accordance with the principles of the Declaration of Helsinki as well as Good Clinical Practice. Study results will be disseminated at academic presentations and publications in peer-reviewed journals.Trial Registration: Registry name: Clinical value of electroultrasonic instrument in the treatment of intrauterine adhesions and changes of related protein expression; Registry number: ChiCTR2200058901; registration date: April 19th, 2022; http://www.chictr.org.cn/showproj.aspx?proj=166155.

Using the nonparametric causality-in-quantiles approach, we investigate the causal effects of oil price uncertainty on the returns and volatility of clean energy metal stocks under different market conditions in China. The results suggest that there is a causal relationship between oil price uncertainty and the returns and volatility of Chinese clean energy metal stocks. The effect differs slightly between returns and volatility. Specifically, the causal effect of oil price uncertainty on returns is mainly observed for lower quantiles, whereas the effect on volatility exists for all quantiles. In addition, the effects of change of market environment in China on the causal relationship are tested. The results show that change in market environment has significantly weakened the causal relationship between oil price uncertainty and clean energy metal stocks, suggesting that the structure of the Chinese clean energy metal stock market has undergone major changes.

Based on the output data of the oil industry chain from February 2006 to June 2017, we construct a time‐varying parameter structural vector auto‐regression with stochastic volatility (TVP‐SVAR‐SV) model and specifically analyse the time‐varying effects and structural change of oil price shocks on China's output at each stage of the oil industrial chain. The results show that the effects of oil price shocks on output from upstream to downstream in the oil industrial chain are time‐varying, and the dynamic impacts vary under different lag lengths. The increase in oil price driven by oil demand shocks is the major factor affecting output at each stage of the oil industrial chain. In addition, there is a structural change in the impacts of oil price shocks before and after the international financial crisis. With the decline in external demand and the implementation of policies to expand domestic demand, the responses of China's output at each stage of the oil industrial chain to oil price shocks have decreased significantly since the international financial crisis.

The correlation between Renminbi (RMB) internationalization and nonferrous metal prices was studied using the nonlinear Granger causality test and the dynamic conditional correlation-generalized autoregressive conditional heteroskedastic (DCC-GARCH) model. The results indicate that the relationship between RMB internationalization and nonferrous metal prices reflects a complex nonlinear mechanism. There was no mutual influence between RMB internationalization and nonferrous metal prices prior to the trials of the RMB settlement in the cross-border trade in July 2009. Since then, however, a bidirectional causal relationship between RMB internationalization and the price of copper and a unidirectional causal relationship from the price of aluminum to RMB internationalization were examined. In addition, due to the impact of extreme events, such as economic and financial crises, RMB internationalization and nonferrous metal prices are not always positively correlated but are rather occasionally negatively correlated.

Based on a structural vector autoregression (SVAR) model, we investigate the impacts of different types of oil price shocks on industrial producer price index (PPI) in China for the period from 199...

In recent years, increasing attention has been given to the potential supply risks of critical battery materials, such as cobalt, for electric mobility transitions. While battery technology and recycling advancement are two widely acknowledged strategies for addressing such supply risks, the extent to which they will relieve global and regional cobalt demand–supply imbalance remains poorly understood. Here, we address this gap by simulating historical (1998-2019) and future (2020-2050) global cobalt cycles covering both traditional and emerging end uses with regional resolution (China, the U.S., Japan, the EU, and the rest of the world). We show that cobalt-free batteries and recycling progress can indeed significantly alleviate long-term cobalt supply risks. However, the cobalt supply shortage appears inevitable in the short- to medium-term (during 2028-2033), even under the most technologically optimistic scenario. Our results reveal varying cobalt supply security levels by region and indicate the urgency of boosting primary cobalt supply to ensure global e-mobility ambitions.

Tungsten is a widely used metal related to national strategic security. As the world’s largest tungsten producer and exporter, China has restricted tungsten exports over the past decade. Has China acquired the corresponding international market power in the export market after these export restrictions? Based on an expansion of the Song-Marchant-Reed (SMR) model, this paper selects 17 of China’s major tungsten importers and estimates the international market power of Chinese tungsten exports over the period from 1992 to 2016. In addition, the effectiveness of China’s tungsten export control policies is examined. The empirical results show that China has stronger market power relative to the major tungsten importers. Moreover, from the encouragement phase to the restraint phase of China’s export policy, the difference in the export market power between China and the importers has substantially increased from 0.027 to 0.161. This shows that due to the implementation of export restrictions, China has gained more export market power, indicating that its tungsten export control policies are very effective. Based on the empirical results, this paper analyses the reasons for China’s rising market power and the effectiveness of its export policies and proposes corresponding policy recommendations.

Because of the irreversibility of financialization in nonferrous metals markets, the security of nonferrous metals resources has shifted from a supply security mode based on “production-supply” towards an economic security mode based on “trade-finance”. Thus, the pricing mechanism of nonferrous metals has become more complex and presents features such as nonlinearity, dynamic characteristics and structure dissimilation. Based on this background, we construct a theoretical framework for analysing the effects of financial factors on fluctuations in nonferrous metals prices and employ the Markov-switching vector autoregression (MS-VAR) model to conduct a nonlinear empirical analysis based on monthly data of international copper futures prices from August 2004 to October 2016. Further, we include supply and demand factors for a comparative analysis. The results show that copper futures price fluctuations present a regime switching dynamic that can be characterized as “steep drop”, “small drop” and “steady rise” periods. During each period, financial factors can fully explain the price volatility while in different mechanism, and the “Chinese factor” has apparently been exaggerated. In addition, oil price is key to monitoring the short-term volatility risks of copper futures prices in the downward cycle. The conclusions along with the established nonlinear econometric models provide a new intellectual framework and analysis tool for explaining the financialization of commodity markets.

With the increasing international attention paid to environmental issues, the ability to pursue continuous development while protecting the environment and thereby achieving a win-win situation has become a significant issue for developing countries such as China. In previous studies, environmental regulation has been proven to be an effective governance mechanism. However, few studies have attempted to analyse the comprehensive impacts and determine the optimal stringency of environmental regulation, especially for a specific industry, based on the actual situation in China. Therefore, this paper calculates the effects of the current and proposed environmental regulation of China's steel industry from 2006 to 2013 by adopting a pollution treatment approach, and based on this calculation, it constructs a recursive dynamic steel industry chain CGE model to investigate the macroeconomic, market and technology impacts from an industry chain perspective under 3 different levels of environmental regulation of the steel industry. The simulation results show that real GDP and the outputs of the downstream sectors of the steel industry will suffer slightly, while the outputs and exports of the steel industry itself will benefit from stringent environmental regulation over the long term. In addition, the material efficiency of steel use will be improved in the long term through the implementation of environmental regulation of the steel industry. Based on the results, it is recommended that a moderate level of environmental regulation should be adopted initially, which can then be smoothly transformed into more stringent regulation during a period of economic growth to avoid sudden and major shocks. In addition, this paper also provides a reference for other substantial industries in China when choosing the optimal pattern for the implementation of environmental regulations.

Following Bessembinder and Seguins, trading volume is separated into expected and unexpected components. Meanwhile, realized volatility is divided into continuous and discontinuous jump components. We make the empirical research to investigate the relationship between trading volume components and various realized volatility using 1 min high frequency data of Shanghai copper and aluminum futures. Moreover, the asymmetry of volatility–volume relationship is investigated. The results show that there is strong positive correlation between volatility and trading volume when realized volatility and its continuous component are considered. The relationship between trading volume and discontinuous jump component is ambiguous. The expected and unexpected trading volumes have positive influence on volatility. Furthermore, the unexpected trading volume, which is caused by arrival of new information, has a larger influence on price volatility. The findings also show that an asymmetric volatility–volume relationship indeed exists, which can be interpreted by the fact that trading volume has more explanatory power in positive realized semi-variance than negative realized semi-variance. The influence of positive trading volume shock on volatility is larger than that of negative trading volume shock, which reflects strong arbitrage in Chinese copper and aluminum futures markets.

Earthquake and antecedent drought (drought for short) play important roles in triggering landslides, which change the formation condition of landslides by affecting topography, loose solid materials and water content. However, in most cases, landslide early warnings rely on rainfall thresholds or(/and) soil moisture conditions, without considering the effects of earthquake and drought. In this study, an analysis has been carried out on the latest version of Parametric Catalogue of Italian Earthquakes (Italian acronym CPTI15) and standardized precipitation index (SPI) (to represent droughts) and the landslide events in a northern Italian region in the past 116-years period 1901-2016. Based on the quantitative analysis on the relationship in time between landslides, earthquake activities and drought events, the interacting relationship between landslides, seismic activities and droughts were explored. It has been found that the impacts from earthquakes and droughts on landslides do exist. The impacts from earthquakes in the study area was less significant comparing with other regions (such as Wenchuan, China), and droughts play a complementarily minor role on landslides. Finally, a method is proposed for predicting the landslides based on early earthquake and drought monitoring and used on some cases. We expect this study can provide useful information for combining earthquake and drought in the landslide early warnings.

China's mining and quarrying industry is characterized by “high pollution, high energy consumption, and high emissions.” Improving this sector's green total factor productivity (TFP) is of great importance for furthering the sustainable development of China's economy. Using a global data envelopment analysis (DEA), this paper analyzes the green TFP of China's mining and quarrying industry for the period of 1991–2014 with regard to technology, scale, and management. The following results are found. First, during the sample period, the green TFP of China's mining and quarrying industry increased by 71.7%. Technological progress was the most important contributor, and the decline in scale efficiency and management efficiency were two inhibitors. Fortunately, in recent years, management efficiency has gradually improved and become a new impetus for green TFP growth. Second, the characteristics of the green TFPs in the sub-industries vary considerably. During the sample period, the green TFPs of the mining and processing of ferrous metal ores (MPFMO), the mining and processing of non-ferrous metal ores (MPNFMO), and the mining and processing of nonmetal ores (MPNO) grew rapidly and became the benchmarks, whereas those of the mining and washing of coal (MWC) and the extraction of petroleum and natural gas (EPNG) remained very low. Third, the returns to scale of the sub-industries also varied. EPNG, MPNFMO, MPNO were in the stage of increasing returns to scale or constant returns to scale during the entire period, whereas MWC and MPFMO have recently entered the stage of decreasing returns to scale.

This article extends the HAR‐CJN model proposed by Andersen, Bollerslev, and Huang (Journal of Econometrics, 2011, 160, 176–189) and explores the role of overnight information and leverage effects in improving volatility forecasting. To explore the interaction between different components of daily volatility, this paper attempts to separately model the dynamics of continuous variation, the discontinuous jump, and the overnight return variance by including leverage effects. The findings show that lagged continuous and discontinuous jump variations generate significant impacts on future continuous segments, discontinuous jump segments, and the overnight return variance. Furthermore, in addition to the usual leverage effects, additional leverage effects with respect to overnight returns are found to play a significant role in volatility forecasting. Finally, out‐of‐sample forecasts are investigated; the results show that the new HAR‐CJN model can describe and predict daily volatility more accurately than other HAR models.

The green development of Chinese iron and steel industry with high pollution and energy consumption has become an urgent issue. Under the economic transition of China, this paper first establishes a theoretical mechanism for the differential effects of governance transformation models on the green process innovation (GPI) of Chinese iron and steel enterprises (CISEs). Based on the environmental protection data of 86 key CISEs from 2005 to 2018, the global Malmquist-Luenberger (GML) index is used to measure the total factor environmental governance efficiency (TFEGE) which represents the green development. Then the compound effects of environmental regulation (ER) and governance transformation on the TFEGE of 86 key CISEs are empirically studied. The results show that: (1) there is a U-shaped relationship between ER and the TFEGE. (2) Governance transformation and GPI can significantly improve TFEGE, and governance transformation will advance the inflection point of the U-shaped curve and accelerate the realization of the Porter hypothesis (PH), producing a preliminary compound effect. (3) The interaction of governance transformation and GPI has a positive and significant effect on improving TFEGE, but the heterogeneity analysis of regional economic and manufacturing process shows that it only promotes the inflection point of ER and accelerates the realization of the PH in middle- and short-process CISEs, producing a profound lagging compound effect.

Cities are the main carbon dioxide (CO 2 ) emitters in China, and it is important to explore both the characteristics and reduction potential of their CO 2 emissions. This paper calculates the industrial energy-related CO 2 emissions (IECEs) of 17 cities in China's Yangtze River Delta (YRD) region from 2005 to 2014 and analyses the driving factors of CO 2 emissions using the Logarithmic Mean Divisia Index (LMDI). In addition, this paper predicts the CO 2 reduction potential of this group of cities for the period from 2015 to 2020. The results show that (1) during the sample period, industrial CO 2 emissions in the studied cities increased by a factor of 1.61. Economic output is the greatest contributor, followed by population size. Energy intensity and energy structure are the two main emission mitigation factors; (2) the driving factors of CO 2 emissions in the group of cities exhibit distinct spatial characteristics, indicating that future analyses of cities in this area should have distinctly different foci; and (3) the forecasting results show that under moderate and aggressive scenarios, CO 2 emissions in the studied cities can be reduced by 281.59 Mt and 711.90 Mt, respectively, by 2020.

Copper is one of the most important nonferrous metals for modern society, which should be utilized in a sustainable way because of its non-renewable nature. This paper addresses the relationship between price shocks from the international copper market and China's listed copper companies. International copper market price shocks are disentangled into supply shocks, aggregate demand shocks, and specific demand shocks using the structural vector autoregression method. Then, the asymmetric impact of those shocks on the stock prices of China's listed copper companies is examined. The results indicate that demand shocks are the dominant factor influencing copper price fluctuations, with their impact on stock prices being significantly higher than those of supply shocks. In the long run, supply shocks and demand shocks both have significant asymmetric impacts on stock prices, while in the short run, specific demand shocks have an asymmetric impact on stock prices.

Increasing financial attributes of non-ferrous metals after financialization and higher uncertainty lead to a more complicated stock market of non-ferrous metal industry, while no study has explored the relations among the three under a unified framework. This paper attempted to investigate the effects of non-ferrous metal prices and uncertainty on stock indices of non-ferrous metal industries in China under different market conditions. Results show that: (1) non-ferrous metal prices have positive impacts, indicating that the hedging effects of non-ferrous metals are weaker after financialization; (2) the impacts of uncertainty are negative at the mean level or bearish market, but positive under the bullish markets; (3) the impact strength of non-ferrous metal prices and uncertainty are stronger under lower and upper quantiles than intermediate quantile; (4) effects of non-ferrous metal prices and uncertainty are more significant and stronger after the global financial crisis in 2008. These findings imply the importance of non-ferrous metal prices and uncertainty for coping with fluctuations of non-ferrous metal stock markets, making investment portfolios, formulating targeted strategies, and maintaining financial security under different market conditions.

To achieve sustainable and green development, it is imperative for China, as the world's major metal consumer, to improve utilization efficiency and conservation of metal resources. Thus, understanding the industrial endogenous growth patterns of China regarding metal utilization and technical change becomes the prerequisite. Therefore, this paper regards metal as one of production factors nested with capital and labor, employs normalized supply-side system approach to estimate the elasticity of substitution in constant elasticity of substitution (CES) function and analyzes technical change bias based on the analytical framework built in this paper. Results show that: the optimal nesting structure for most metal-intensive industries are metal-capital composite nested with labor. And the metal input is less efficient than capital or labor in all metal-intensive industries. The technical change biases for metal-intensive industries are diversified, but only metal mining industries and heavy machinery manufacturing industries tend to save metal when expanding the production effectively. Targeted suggestions are made per industry according to the heterogeneity of production factors allocation and technical change biases.

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.

This paper seeks to model and forecast the Chinese nonferrous metals futures market volatility and allows new insights into the time-varying volatility of realized volatility and leverage effects using high-frequency data. The LHAR-CJ model is extended and the empirical research on copper and aluminum futures in Shanghai Futures Exchange suggests the dynamic dependencies and time-varying volatility of realized volatility, which are captured by long memory HAR-GARCH model. Besides, the findings also show the significant weekly leverage effects in Chinese nonferrous metals futures market volatility. Finally, in-sample and out-of-sample forecasts are investigated, and the results show that the LHAR-CJ-G model, considering time-varying volatility of realized volatility and leverage effects, effectively improves the explanatory power as well as out-of sample predictive performance.

In this work, we concentrate on the investigation of the fundamental effects of annealing temperatures on the synthesized polydisperse of ZnO aggregates for the exploration of effective electrode material for dye-sensitized solar cells (DSCs). Systematic characterizations including TEM, SEM, BET analysis, XRD, and r-PL were performed for the ZnO aggregates annealed at various temperatures, and the results revealed that the morphology of aggregates, crystal size of primary particle, crystallinity, specific surface areas and the surface states largely depends on the annealing temperature. The photoelectrical efficiency tests demonstrated that the ZnO aggregates annealed at 450 °C exhibited the highest efficiency of 5.10%. The excellent performance could mainly originate from the more efficient light harvesting property of the resulted ZnO photoanode indicated by the incident photon-to-current efficiency (IPCE) and the accelerated electron transport within the ZnO film testified by electrochemical impedance spectroscopy (EIS). Moreover, the combination of the composition control with the introduction of both a ZnO compact layer (CL) and a TiO 2 protecting layer (PL) was simultaneously integrated into one photoanode film for the first time. As a consequence, an impressive power conversion efficiency of 5.83% was achieved with the new photoanode architecture, an improvement of 39.5% over the unmodified DSC. The synergistically reduced charge-transport resistance and suppressed electron recombination are regarded to be the key element for outstanding performance.

Urban flooding exposure is generally investigated with the assumption of stationary disasters and disaster-hit bodies during an event, and thus it cannot satisfy the increasingly elaborate modeling and management of urban floods. In this study, a comprehensive method was proposed to simulate dynamic exposure to urban flooding considering residents' travel behavior. First, a flood simulation was conducted using the LISFLOOD-FP model to predict the spatiotemporal distribution of flooding. Second, an agent-based model was used to simulate residents' movements during the urban flooding period. Finally, to study the evolution and patterns of urban flooding exposure, the exposure of population, roads, and buildings to urban flooding was simulated using Lishui, China, as a case study. The results showed that water depth was the major factor affecting total urban exposure in Lishui. Urban exposure to fluvial flooding was concentrated along the river, while exposure to pluvial flooding was dispersed throughout the area (independent from the river). Additionally, the population distribution on weekends was more variable than on weekdays and was more sensitive to floods. In addition, residents' response behavior (based on their subjective consciousness) may result in increased overall exposure. This study presents the first fully formulated method for dynamic urban flood exposure simulation at a high spatiotemporal resolution. The quantitative results of this study can provide fundamental information for urban flood disaster vulnerability assessment, socioeconomic loss assessment, urban disaster risk management, and emergency response plan establishment.

Urban flooding exposure is generally investigated with the assumption of stationary disasters and disaster-bearing bodies within an event, and thus cannot satisfy the increasingly elaborative modelling and management of urban flood. In this study, a comprehensive method was developed to simulate dynamic exposure to urban flooding considering residents’ travel behavior. First, a flood simulation was conducted using the LISFLOOD-FP model to predict the spatio-temporal distribution of flooding. Second, an agent-based model was used to simulate residents’ movements during the period of urban flooding. Finally, to study the evolution and patterns of urban flooding exposure, the exposure of population, roads, and buildings to urban flooding was simulated using Lishui, China as the case study. The results indicated evident spatio-temporal variations in urban flooding and population distribution. Additionally, the exposure increased with increasing rainfall and flooding severity. The urban area near the Oujiang River was the most severely flooded and indicated the largest amount of exposure of population, roads, and buildings. Furthermore, the impacts of flooding on roads were greater than those on population and on buildings. This study presents the first fully formulated method for dynamic urban flood exposure simulation at high spatio-temporal resolution. The results of this study can provide baseline data for determining urban flood disaster vulnerability, socioeconomic loss assessment, urban disaster risk management, and for establishing emergency response plans.

This paper uses a time-varying parametric vector autoregressive model with random fluctuations to examine the time-varying impacts of oil prices and economic policy uncertainty (EPU) on China's nonferrous metals industry. The findings indicate the following: (a) The impact of oil price shocks on the nonferrous metals industry is positive in the short term and diverse in the long term, while fluctuation trends are heterogeneous at different positions of the industry chain. (b) The impacts of EPU shocks on the industry show fluctuating trends after 2009, while the heterogeneous impacts of EPU shocks at different chain positions exist only on output. (c) Oil prices have a positive short-term effect on EPU, while the short-term effect of EPU on oil prices has gradually turned positive since the financial crisis, highlighting the asymmetric relationship between oil prices and EPU. (d) During the global financial crisis, the impact of oil prices and EPU on industry shocks increased significantly, indicating the importance of a stable economic environment. (e) Monetary and exchange rate policy uncertainty are the main sources of EPU shocks to oil prices, and trade policy uncertainty is the cause of inflationary effects.

Taking the four-stage SBM-DEA as the theoretical tool, this paper evaluates the total factor waste gas treatment efficiency (TFWGTE) of 65 Chinese iron and steel enterprises (CISEs) from 2005 to 2014. Then, after the influences of external environmental factors and statistical noise are eliminated, TFWGTE is decomposed into total factor waste gas managerial efficiency (TFWGME) and total factor waste gas environmental efficiency (TFWGEE), and the differences between TEWGTE, TEWGME and TEWGEE are systematically analysed from regional and enterprise perspectives. The results reveal that: (1) TFWGTE and TFWGEE showed an upward trend from 2005 to 2014, whereas TFWGME showed a downward trend from 2005 to 2014. The elimination of external environmental factors had provincial specific effects on TFWGTE; (2) By comparing the dynamic trends of TFWGTE in eastern, central and western regions, it is found that there are differences among different regions, which indicates that the external environmental factors in the region have an impact on TFWGTE; (3) In 4 provinces, TFWGME increased compared with TFWGTE, while in 23 provinces, TEWGME decreased compared with TFWGTE; (4) The Tobit regression results show that the command-and-control environmental regulation, environmental awareness and manufacturing process have significant effects on the input slacks of waste gas treatment, indicating that the strengthening of command-and-control environmental regulation, the improvement of environmental awareness, and the decline of the proportion of the short process can effectively reduce the input slacks of waste gas treatment.

MicroRNAs are a class of endogenous, small non-coding RNAs which are tightly involved in evolution and progression of human cancers. MicroRNA-497 has been reported as tumor-suppressor in various human cancer. However, the role of miR-497 in ovarian cancer is still poorly known. We investigated the expression level and cellular function of miR-497 in human ovarian cancer. In this study, the expression of miR-497 in ovarian cancer tissues and SKOV3 cells was detected by quantitative reverse‑transcription polymerase chain reaction (qRT-PCR). CCK-8 assay was used to analysis the cell proliferation. Transwell assay was performed to analysis cell migration and invasion. Cell apoptosis was evaluated by flow cytometry. Luciferase assay was performed to verify a putative target site of miR-497 in the 3'UTR of PAX2 mRNA. The results showed that miR-497 was markedly decreased in ovarian cancer tissues and SKOV3 cells. Moreover, overexpression of miR-497 in SKOV3 cells induced PAX2 protein expression and resulted in inhibition of cell proliferation, migration and invasion, and induction of cell apoptosis. In addition, we confirmed that PAX2 is a direct target gene of miR-497. Furthermore, Silencing of PAX2 by RNA interference suppressed cell proliferation and promoted cell apoptosis in vitro. Taken together, our study rationally present that miR-497 has a potential role as a useful diagnostic and therapeutic biomarker for human ovarian cancer.

Fossil fuel is considered to be the major cause of CO2 emissions, and it flows across countries through the international energy trade. In this paper, we analyse the impact of energy trade patterns on CO2 emissions for a global sample from 2000 to 2014. We construct an international fossil fuel trade network based on emergy theory and calculate some corresponding structural parameters. Then, we systematically evaluate the impact of energy trade on CO2 emissions from the trade volume and trade relationships perspectives. We obtain the following results: (1) Trade strength mainly affects CO2 emissions through the scale effect, composition effect and technique effect. (2) Trade security and trade-centre status of one country will significantly affect CO2 emissions. (3) For high economic-level (HE) countries, concentrating the trade volume on several finite countries will destroy the environment; low economic-level (LE) countries that are proximal to the important countries of the energy market will experience an increase in pollution. This research also discusses some implications for policy makers.

Human exposure to threats from natural hazards is generally estimated using a static approach with the fixed number of people located in hazard-prone zones; however, in reality this number varies due to population mobility. This study proposes a human–hazard coupled City Model (HazardCM) for accurately calculating city spatiotemporal dynamic exposure to different hazards. It includes four components: an urban environment module, agent-based model, city–hazard coupler, and dynamic exposure assessment. Rainfall-triggered natural hazards under extreme hydrometeorological events were modeled in Lishui, China. Scenarios covering different magnitudes, timings and locations, and return periods of hazards were investigated to derive the spatial distribution and evolution of human exposure. This model is the first that different natural hazards have been analyzed within a unified framework using a dynamic method and offers a new way to investigate exposure's space–time characteristics while considering the dynamic nature of both humans and hazards.

Using a time-varying parameter structural vector autoregression with stochastic volatility (TVP-SVAR-SV) model, we decompose the structural shocks of oil price fluctuations into four types: oil supply shocks, global demand shocks, domestic demand shocks and oil-specific demand shocks. We then analyze the time-varying effects of these oil price shocks on China's inflation at the import, production and consumption stages using monthly data from January 1999 to December 2016. The results show that the pass-through effects of the four types of oil price shocks on China's inflation at each stage are time-varying and that there are significant differences at different time horizons and points in time. The analysis of the variance decomposition shows that the effects of oil price shocks on China's inflation at each stage are incomplete and decrease along the price chain. The increase in oil prices driven by oil-specific demand shocks is the most important cause of China's inflation at the import and production stages during the full sample period, while China's inflation at the consumption stage is mainly affected by domestic demand shocks. In addition, the inflationary effects of oil price shocks have been dramatically weaker since the international financial crisis compared with before the crisis.

This study analyses the dynamics of iron ore's international market power on exports to China by Australia, Brazil, India and South Africa. It uses the residual demand elasticity (RDE) model and rolling window regression model and applies the monthly data for the international iron ore market over the period from January 2006 to December 2016. The results indicate that (1) Australia and Brazil exercise market power in the Chinese iron ore market, but India and South Africa have no market power in the iron ore market; (2) market power has a time-varying nature, particularly in Australia and Brazil; and (3) changes in the pricing regime in the international iron ore market have a profound impact on market power. Furthermore, to maintain the stability of the Chinese iron ore market, exporters are suggested to enhance their competitiveness and gain greater market power on the basis of maintaining market share, and China should optimize its trade structure.

From the perspective of long-term and short-term, the methods of TY causality test, generalized impulse response function, variance decomposition were used to investigate the impacts of international oil prices and macroeconomic variables on Chinese gold, silver and platinum prices, but also the feedback effects of Chinese precious metal prices under this impact. The results show that international oil prices play an important role in precious metal price variation both in long-term and short-term, and exchange rate only has an effect in short-term, while interest rate is ineffective in predicting precious metal prices. In addition, precious metal prices have some feedback effects on international oil prices and interest rate in short-term.