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Using the policy package pilot implemented in Hubei Province, China, in April 2020 as a natural experiment, we use the synthetic control (SC) and synthetic difference in differences (SDID) methods to estimate the impact of the Chinese government's support policy on the economic resilience and to analyze the mechanisms by which it impacts. This study finds that the policy package has contributed to the growth of economic resilience in the pilot provinces, with the policy package increasing the average economic resilience of the pilot provinces by 0.062 compared to their potential resilience. The validity and robustness of the above conclusions are objectively confirmed by multidimensional quantitative outcomes such as placebo tests, ranking tests, and replacements in calculating resilience. The mechanism analysis shows that the investment in real estate development, the stimulus for consumption, and the core industry development are virtual channels for the policy package to promote economic resilience growth in the pilot provinces. Moreover, traditional investment in transportation fixed assets plays a minor role. This paper quantitatively corroborates the academic idea that government governance capacity affects regional economic resilience (RER), and research can provide empirical support for regional economic recovery and policy support under a major crisis. [ABSTRACT FROM AUTHOR]

The tomb of Marquis Yi of Zeng was unearthed in 1978 at Leiguudun in Suizhou City, Hubei Province, China. This is the largest wooden coffin in rock pit and vertical cave in the Warring States period in China. The large wooden coffin components provide reliable material data for the study of the feudal burial system in the pre-Qin period and have high value. In this paper, the wooden coffin excavated from the tomb of Marquis Yi of Zeng was studied. By understanding the composition of wood, studying the weight gain rate, shrinkage rate, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and compression resistance, the wood reinforced by rosin and epoxy resin was compared, and the reinforcement effect and principle of the two reinforcement methods were discussed. The study found that the wood properties of rosin reinforced group were better than those of epoxy reinforced group in the aspects of compressive strength, weight gain rate and volume shrinkage rate, and the mechanical properties of wood were significantly improved. In addition, methanol or ethanol can be used to dissolve the rosin shellac in this strengthening process, which can achieve reversible strengthening treatment. The results provide valuable examples and research ideas for the selection of different conservation techniques of large wooden cultural relics unearthed in the middle and lower reaches of the Yangtze River during the Warring States Period. [ABSTRACT FROM AUTHOR]

The Global Investment Report 2023 revealed that after a sharp decline in 2020 and a strong rebound in 2021, global foreign direct investment (FDI) declined by 12 percent to $1.3 trillion in 2022. However, in developing countries, FDI increased by 4% to $916 billion, a record share of more than 70% of global flows. The number of greenfield investment projects in developing countries increased by 37 percent and international project finance transactions by 5 percent. Foreign investment from China, the second largest recipient of foreign investment globally, increased by 5 percent. The service industry has become the mainstream industry in the global FDI structure. The global industry is accelerating its transformation to a "service-based economy," international FDI in productive service industries has become an essential means of industrial transfer in developed countries and a meaningful way to upgrade the industrial structure and high-quality development in emerging economies. As a representative province in central China, Hubei Province has unique advantages in human capital, factor cost, and market potential, which provide preferential conditions to attract foreign investment. This paper first introduced the concept of the productive service industry, based on the relevant statistical data from 2011 to 2022, focused on the current situation of foreign investment utilization in five major sub-sectors of the productive service industry in Hubei Province in the past ten years, and empirically investigated the impact of foreign investment utilization in five major sub-sectors of the productive service industry on the economic growth of Hubei Province, and obtained that the level of foreign investment attraction varied significantly among the regions in Hubei Province. The three productive service industries, namely transportation, storage and postal services, information transmission, software and information technology services, and financial services, played a significant role in the active attraction and optimal utilization of foreign capital and the economic development of Hubei Province. Based on this, it was proposed to build a market-oriented rule of law and internationalized business environment, improve the infrastructure construction in different regions of the province, focus on the training of professional talents for the development of productive service industries, and pay attention to the improvement of independent innovation capacity. [ABSTRACT FROM AUTHOR]

The Chinese government encourages rural economic entities to use farmland management rights as collateral for loans, which helps to alleviate multi-level financing needs in rural areas. Based on the panel data of counties in Hubei Province, this paper adopts the Difference-in-Differences (DID) and the intermediary effect model to evaluate the impact of farmland management rights mortgage loans (FMRML) on the agri-food industrial agglomeration (AIA) in China. The study found that the pilot policy has significantly promoted the AIA. Moreover, the regression results remain robust after conducting the placebo test and the Propensity Score Matching Difference-in-Differences (PSM-DID) model, which demonstrates that the improvement effect is stable and long-lasting. From the heterogeneity analysis, it can be seen that the policy of FMRML has a more significant effect on the AIA in mountainous and hilly areas. By further analysis of the mechanism of action, it can be concluded that the pilot policy promotes the AIA by enhancing agricultural specialized production. The main findings can provide information for policymakers in China. The recommendations we have summarized encompass gradually expanding the scope of the pilot policy of FMRML, advancing the institutionalization and legalization of the policy, and promoting agricultural production specialization. [ABSTRACT FROM AUTHOR]

This paper addresses the reactions of domestic helpers to the Wuhan (Hubei Province) lockdown that began on January 23, 2020. We use a novel dataset containing the information of over 40,000 Chinese domestic helpers registered on a leading professional website from November 2019 to June 2020. The results indicate a declining pattern of short-term labor supply of domestic helpers across 11 major Chinese cities, which shows an increase in the expected monthly wage of domestic helpers in these cities. More importantly, using a difference-in-difference (DID) model, this paper provides some evidence on the existence of labor market discrimination against domestic helpers born in Hubei Province due to employers' fear of infection. [ABSTRACT FROM AUTHOR]

Developing renewable energy has become a major strategy for China to accelerate the energy transition and combat climate change. Accordingly, a guarantee mechanism for renewable energy consumption with renewable portfolio standards (RPS) has been set in China. However, currently, the top-down allocation of regional renewable energy consumption targets often has issues of unfairness and inefficiency. It is necessary to investigate the issue of how to stimulate the renewable energy consumption potential on the demand side and reasonably formulate the consumption responsibility weights of various market entities. This paper aimed to develop a new methodology for the weight allocation of renewable energy consumption responsibilities. In doing so, an integrated model of an evolutionary game and stochastic optimization was constructed between market entities and governments. Then, the equilibrium strategies of market entities and governments were obtained through the evolutionary game. Furthermore, based on the equilibrium strategies, this paper optimized the renewable energy consumption weight of each market entity, which constitutes the optimal allocation scheme of renewable energy consumption responsibility weights. Finally, using the data of 7069 market entities in Hubei Province in 2021, this study simulated the model to verify its effectiveness and practicability. The results indicate that the willingness of market entities to assume more consumption responsibility is positively correlated with the government's incentives and the maturity of the green electricity trading market. This study provides important implications for optimizing government regulations and promoting renewable energy consumption. [ABSTRACT FROM AUTHOR]

The transformation of the government into a digital entity is imperative, serving not only as a catalyst for the modernization of China's governance system and capacity but also as a cornerstone for advancing the digital economy and the establishment of a digital China. This paper presents a multi-level analytical framework designed to assess the digital transformation performance of local governments. Utilizing a dataset comprising macro-regional and micro-individual data from Hubei province, we conduct an extensive analysis to examine the underlying mechanisms that influence the digital transformation performance of local governments and employ the hierarchical linear model (HLM) as the primary analytical instrument. The results of our analysis show that individual-level government–citizen interactions, government image, and district-level department collaborative capacities exert substantial and positive influences on the digital transformation performance of local governments. Furthermore, it is worth noting that department collaborative capacity plays a significant and positive moderating role in the relationship between government image and the digital transformation performance of local governments. These findings not only offer valuable insights for optimizing policy formulation but also contribute to a more comprehensive understanding of the mechanisms underlying the digital transformation performance of local governments. [ABSTRACT FROM AUTHOR]

The rapid urbanization in China in the past four decades has significantly affected traditional villages, resulting in a series of problems such as limited space, damaged style, weak sense of place, and loss of skills. This paper aims to establish a new paradigm for the sustainable development of village architecture in the Tujia ethnic area of southwestern Hubei province in order to address the issues of development and renovation of village architecture in this region. To achieve this goal, first, through field investigations and records of typical villages in the Tujia ethnic area of southwestern Hubei province, the characteristics of Tujia ethnic villages and the real challenges faced by village architecture are summarized. Secondly, the Delphi method is used to conduct expert interviews, construct a multi-level evaluation index system for sustainable development, and use the analytic hierarchy process to determine the weights of each index. Based on this, four design paradigms for sustainable development are proposed, including flexible layout, integrated interface composition, localized housing construction, and modular unit construction. These four paradigms cover the entire design stage from function to form, and from overall scene to structure. At the same time, multiple modular options are provided for each stage. Compared to the traditional experience-based construction model, the comprehensive benefits and promotability are greatly improved. Therefore, the research findings provide a reference for the sustainable development of traditional village architecture in other ethnic areas of China. [ABSTRACT FROM AUTHOR]

WeChat is a social media widely used in rural China because of its operability and simplicity. This paper contributes to the role of WeChat in rural e-commerce. Based on 406 orange farmers' survey data from Hubei Province, China, we used the Heckman model to analyze the factors that influence farmers' participation in WeChat e-commerce and estimate the impacts of WeChat e-commerce on farmers' sales performance. We found that information literacy and social connections are important factors affecting farmers' participation in WeChat e-commerce. WeChat e-commerce has a positive effect on farmers' sales performance, and the social connections between farmers and consumers can reinforce this effect. Particularly, the beneficial effects are more prominent for farmers with a higher level of Internet development, who operate on a smaller scale, and who are less educated. The results show that WeChat e-commerce improves sales performance mainly by increasing the quantity of sales and the profit rate. These findings will help countries like China to use daily social media to develop rural e-commerce. [ABSTRACT FROM AUTHOR]

Land transfer and its socio-economic impact are key areas of research interest. Such an examination can help to enhance the sustainability of farming livelihoods, maximise livelihood strategies, and achieve sustainable development. This paper establishes a sustainable livelihood evaluation index for rural households based on sustainable livelihood theory. It measures the degree of sustainability in the livelihoods of farmers based on field research data from 650 rural households in Hubei Province, China, and analyses the impact of land transfer using a multiple linear regression model. A number of control variables were identified and introduced into the analysis. It also uses the regression decomposition approach to investigate the impact of each factor on the sustainable livelihoods of rural households. The findings revealed that (1) land transfer can significantly increase the sustainability of rural households' livelihoods; (2) livelihood sustainability increases with the size of the land transfer area; and (3) the primary elements determining the ability of rural households to maintain sustainable living are land transfers, the amount of land transferred, and the size of the family. Based on these findings, this study argues for the need to improve land transfer management, accelerate agricultural industrialisation and promote the transfer of land contract management rights to improve the livelihoods of rural households. [ABSTRACT FROM AUTHOR]

The world is urgently looking for ways to flatten the coronavirus disease 2019 (COVID-19) curve, and many governments have resorted to implementing strict lockdowns, as researchers show the effectiveness of China's approaches in containing the virus. However, this paper argues that the draconian lockdowns instituted in Wuhan, Hubei, China, may have actually contributed to intensifying patient surges and incapacitating local health systems. Medical aids were rushed to Hubei and new hospitals were rapidly built, however, the healthcare system was still unable to match the staggering increase of patients in the early stages of the lockdowns. The paper proposes using patient evacuation to enhance sustainable COVID-19 mitigation during lockdowns. It demonstrates that patients in Hubei could have been transported to other Chinese provinces where hospitals were under-utilized. This could have theoretically saved thousands of lives by reducing inequities between Hubei and the rest of China in healthcare capacity for treating COVID-19 patients. [ABSTRACT FROM AUTHOR]

Online reviews published on the e-commerce platform provide a new source of information for designers to develop new products. Past research on new product development (NPD) using user-generated textual data commonly focused solely on extracting and identifying product features to be improved. However, the competitive analysis of product features and more specific improvement strategies have not been explored deeply. This study fully uses the rich semantic attributes of online review texts and proposes a novel online review–driven modeling framework. This new approach can extract fine-grained product features; calculate their importance, performance, and competitiveness; and build a competitiveness network for each feature. As a result, decision making is assisted, and specific product improvement strategies are developed for NPD beyond existing modeling approaches in this domain. Specifically, online reviews are first classified into redesign- and innovation-related themes using a multiple embedding model, and the redesign and innovation product features can be extracted accordingly using a mutual information multilevel feature extraction method. Moreover, the importance and performance of features are calculated, and the competitiveness and competitiveness network of features are obtained through a personalized unidirectional bipartite graph algorithm. Finally, the importance performance competitiveness analysis plot is constructed, and the product improvement strategy is developed via a multistage combined search algorithm. Case studies and comparative experiments show the effectiveness of the proposed method and provide novel business insights for stakeholders, such as product providers, managers, and designers. History: Accepted by Ram Ramesh, Area Editor for Data Science and Machine Learning. Funding: This work was supported by the National Natural Science Foundation of China [Project 72071151] and the Natural Science Foundation of Hubei Province, China [Grant 2023CFB712]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0333) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0333). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR]

To overcome the difficulty that existing hydrological models cannot accurately simulate hydrological processes with limited information in irrigated paddy areas in southern China, this paper presents a prediction model combining the Ensemble Empirical Mode Decomposition (EEMD) method and the Long Short-Term Memory (LSTM) network. Meteorological factors were set as the multivariate input to the model. Rainfall, regarded as the main variable affecting runoff, was decomposed and reconstructed into a combination of new series with stronger regularity by using the EEMD and K-means algorithm. The LSTM was used to explore the data laws and then to simulate and predict the runoff of the irrigated paddy areas. The Yangshudang (YSD) watershed of the Zhanghe Irrigation System (ZIS) in Hubei Province, China was taken as the study area. Compared with the other models, the results show that the EEMD-LSTM multivariate model had better simulation performance, with an N S E above 0.85. Among them, the R 2 , N S E , R M S E and R A E of the EEMD-LSTM (3) model were the best, and they were 0.85, 0.86, 1.106 and 0.35, respectively. The prediction accuracy of peak flows was better than other models, as well as the performance of runoff prediction in rainfall and nonrainfall events, while improving the N S E by 0.05, 0.24 and 0.24, respectively, compared with the EEMD-LSTM (1) model. Overall, the EEMD-LSTM multivariations model is suited for simulating and predicting the daily-scale rainfall–runoff process of irrigated paddy areas in southern China. It can provide technical support and help decision making for efficient utilization and management of water resources. [ABSTRACT FROM AUTHOR]

The aim of this paper is to understand the current situation of the care burden of patients with mental illness in remission and the factors affecting it in order to provide a scientific basis for targeted interventions. This paper reviews the concept of telemedicine, the application of telemedicine in home hospice care, and the remaining problems and improvement strategies of telemedicine in home hospice care, with the aim of providing a reference for the application of telemedicine in home hospice care in China. The Zarit Burden Scale, Family Care Scale, and Social Functioning Scale were used to conduct one-to-one interviews with 201 schizophrenic patients in remission and their primary caregivers in Hubei Province. Among them, 66, 72, and 25 cases (32.8%, 35.9%, and 12.4%) had mild, moderate, and severe burdens, respectively. Caregivers' family care and patients' social functioning were generally poor. The results of multiple linear regression analysis showed that caregiver age, caregiver education, caregiver family care, patient medical costs, and patient social functioning were factors influencing the burden of care for patients with schizophrenia in remission (P < 0.05). The government, mental health centers, and families should understand the level of caregiving burden of patients with schizophrenia in remission and the factors influencing it and provide targeted measures to reduce the caregiving burden. [ABSTRACT FROM AUTHOR]

The impacts of COVID-19 on travel demand, traffic congestion, and traffic safety are attracting heated attention. However, the influence of the pandemic on electric bike (e-bike) safety has not been investigated. This paper fills the research gap by analyzing how COVID-19 affects China's e-bike safety based on a province-level dataset containing e-bike safety metrics, socioeconomic information, and COVID-19 cases from 2017 to 2020. Multi-output regression models are adopted to investigate the overall impact of COVID-19 on e-bike safety in China. Clustering-based regression models are used to examine the heterogeneous effects of COVID-19 and the other explanatory variables in different provinces/municipalities. This paper confirms the high relevance between COVID-19 and the e-bike safety condition in China. The number of COVID-19 cases has a significant negative effect on the number of e-bike fatalities/injuries at the country level. Moreover, two clusters of provinces/municipalities are identified: one (cluster 1) with lower and the other (cluster 2 that includes Hubei province) higher number of e-bike fatalities/injuries. In the clustering-based regressions, the absolute coefficients of the COVID-19 feature for cluster 2 are much larger than those for cluster 1, indicating that the pandemic could significantly reduce e-bike safety issues in provinces with more e-bike fatalities/injuries. [ABSTRACT FROM AUTHOR]

The agricultural marketing behavior of farmers is crucial for the realization of production value. Based on survey data from 406 citrus farmers in Hubei Province, this paper empirically examines the effects of risk aversion and Internet use on farmers' marketing behavior in terms of fresh produce. The results show that, first, farmers are generally reluctant to sell, with reluctant sellers accounting for about one-third of the total sample, and most report high levels of Internet use. Second, risk aversion and Internet use have a significant impact on farmers' reluctance to sell. The higher the level of farmer risk aversion, the lower the reluctance to sell, while Internet use significantly increases the probability of farmers being reluctant to sell. Third, Internet use weakens the inhibiting effect of risk aversion on reluctance to sell. These findings help to clarify the factors influencing farmers' reluctance to sell and provide reference suggestions for promoting high-quality agricultural development and rural industrial revitalization. [ABSTRACT FROM AUTHOR]

Timely and accurate crop yield information can ensure regional food security. In the field of predicting crop yields, deep learning techniques such as long short-term memory (LSTM) and convolutional neural networks (CNN) are frequently employed. Many studies have shown that the predictions of models combining the two are better than those of single models. Crop growth can be reflected by the vegetation index calculated using data from remote sensing. However, the use of pure remote sensing data alone ignores the spatial heterogeneity of different regions. In this paper, we tested a total of three models, CNN-LSTM, CNN and convolutional LSTM (ConvLSTM), for predicting the annual rice yield at the county level in Hubei Province, China. The model was trained by ERA5 temperature (AT) data, MODIS remote sensing data including the Enhanced Vegetation Index (EVI), Gross Primary Productivity (GPP) and Soil-Adapted Vegetation Index (SAVI), and a dummy variable representing spatial heterogeneity; rice yield data from 2000–2019 were employed as labels. Data download and processing were based on Google Earth Engine (GEE). The downloaded remote sensing images were processed into normalized histograms for the training and prediction of deep learning models. According to the experimental findings, the model that included a dummy variable to represent spatial heterogeneity had a stronger predictive ability than the model trained using just remote sensing data. The prediction performance of the CNN-LSTM model outperformed the CNN or ConvLSTM model. [ABSTRACT FROM AUTHOR]

Total phosphorus (TP) concentration is high in countless small inland waterbodies in Hubei province, middle China, which is threating the water environment. However, there are almost no ground-based water quality monitoring points in small inland waterbodies, because the cost of time, labor, and money is high and it does not meet the needs of spatiotemporal dynamic monitoring. Remote sensing provides an effective tool for TP concentration monitoring spatiotemporally. However, monitoring the TP concentration of small inland waterbodies is challenging for satellite remote sensing due to the inadequate spatial resolution. Recently, unmanned aerial vehicles (UAV) have been applied to quantitatively retrieve the spatiotemporal distribution of TP concentration without the challenges of cloud cover and atmospheric effects. Although state-of-the-art algorithms to retrieve TP concentration have been improved, specific models are only used for specific water quality parameters or regions, and there are no robust and reliable TP retrieval models for small inland waterbodies at this time. To address this issue, six machine learning methods optimized by intelligent optimization algorithms (IOA-ML models) have been developed to quantitatively retrieve TP concentration combined with the reflectance of original bands and selected band combinations of UAV multispectral images. We evaluated the performances of models in terms of coefficient of determination (R2), root mean squared error (RMSE), and residual prediction deviation (RPD). The results showed that the R2 of the six IOA-ML models for training, validation, and test sets were 0.8856–0.984, 0.8054–0.8929, and 0.7462–0.9045, respectively, indicating the methods had high precision and transferability. The extreme gradient boosting optimized by genetic algorithm (GA-XGB) performed best, with the highest precision for the validation and test sets. The spatial distribution of TP concentration of each flight derived from different models had similar distribution characteristics. This paper provides a reference for promoting the intelligent and automatic level of water environment monitoring in small inland waterbodies. [ABSTRACT FROM AUTHOR]

Farmers' adoption of green agricultural technologies (GATs) could reduce the negative environmental impacts of traditional agriculture in China. Despite the benefits of GATs, their adoption rate has not been high. While previous studies have examined the information and communication technologies that influence the adoption of GATs, most have selected only one of the GATs and have not distinguished between public and private channels of knowledge acquisition. In this paper, based on a sample of 732 rural households from Hubei Province, we used a negative binomial model to examine the role of knowledge acquisition channels on GATs adoption. Overall, we found that radio and the government (through its face-to-face channels) are positively associated with farmers' adoption of GATs; however, farmers adopted more GATs when they had acquired knowledge from the government than from radio. A possible explanation and a policy implication is that direct communication with farmers and practical demonstration of the benefits of GATs are preferred to passive reception of information. [ABSTRACT FROM AUTHOR]

Red slipped and painted wares (RSW and RPW) were manufactured to cook, serve, or store foods and liquids in the middle Yangtze River valley (MYRV) of China some 8500 and 7800 years ago, respectively. Their primary use narrowed down to serving and drinking in the Upper Qujialing (5300–4500 cal BP) and Shijiahe (4500–4200 cal BP) periods when initial states (bang guo) took shape and developed in the region. The increasing social complexity in MYRV correlated with the formation of community and neighborhood identity through rituals and socio-economic ties involving the widespread use of RSW and RPW. How the two wares were produced and used helps us understand the relationships among productive activities, identity, and social inequality in MYRV. This paper presents the first overview of RSW and RPW in the Neolithic MRYV. It introduces a multi-analytical study of the two wares—mostly dating to the Shijiahe period—unearthed from the site of Fenghuangzui in Xianyang City of Hubei Province, China. Optical microscopic examination revealed that the paint of RPW—50 μm thick on average—was applied using a brush while the slip of RSW is thinner and finer and possibly formed by self-slipping. Handheld X-ray fluorescence (hhXRF) and benchtop micro-XRF analyses ascribed the red paint or slip to iron and iron oxide. Raman and X-ray absorption fine structure analyses confirmed that iron was present in the paint or slip in the form of hematite with a poorly developed crystalline structure. Furthermore, thin-section petrography implied that different pastes were used to produce RPW and RSW, and hhXRF data indicated that the Upper Qujialing and Shijiahe pottery differ in the concentrations of five elements (Zr, Fe, Mn, Ti, and Ba), which might be helpful in future provenance studies of RSW and RPW. Our study discloses the complexity of the manufacture of RSW and RPW at Fenghuangzui. More details of RSW and RPW production and use from our ongoing project shall reveal the role of the two wares in the social dynamics of the Late Neolithic MYRV. [ABSTRACT FROM AUTHOR]

Low-carbon agriculture is essential for protecting the global climate and sustainable agricultural economics. Since China is a predominantly agricultural country, the adoption of low-carbon agricultural technologies by local farmers is crucial. The past literature on low-carbon technologies has highlighted the influence of demographic, economic, and environmental factors, while the psychological factors have been underexplored. A questionnaire-based approach was used to assess the psychological process underlying the adoption of low-carbon agricultural technologies by 1,114 Chinese rice farmers in this paper, and structural equation modeling (SEM) was empirically employed to test our theoretical model. The results indicated that farmers' low-carbon production attitude and behavioral efficiency perception directly and positively affected the adoption of low-carbon agricultural technologies and indirectly affected it via low-carbon production intention. Besides, production implementation cost and socio-environmental factor could moderate the direct effects of low-carbon production attitude, behavioral efficiency perception, and low-carbon production intention on farmers' adoption of low-carbon agricultural technologies. In this respect, socio-environmental factor yielded more significant moderating effects. Additionally, this research provides policy implications for promoting low-carbon agricultural technologies in developing countries and regions. [ABSTRACT FROM AUTHOR]

Forest logging detection is important for sustainable forest management. The traditional optical satellite images with visible and near-infrared bands showed the ability to identify intensive timber logging. However, less intensive logging is still difficult to detect with coarse spatial resolution such as Landsat or high spatial resolution in fewer spectral bands. Although more high-resolution remote sensing images containing richer spectral bands can be easily obtained nowadays, the questions of whether they facilitate the detection of logging patterns and which spectral bands are more effective in detecting logging patterns, especially in selective logging, remain unresolved. Therefore, this paper aims to evaluate the combinations of visible, near-infrared, red-edge, and short-wave infrared bands in detecting three different logging intensity patterns, including unlogged (control check, CK), selective logging (SL), and clear-cutting (CC), in north subtropical plantation forests with the random forest algorithm using Sentinel-2 multispectral imagery. This study aims to explore the recognition performance of different combinations of spectral bands (visual (VIS) and near-infrared bands (NIR), VIS, NIR combined with red-edge, VIS, NIR combined with short-wave infrared bands (SWIR), and full-spectrum bands combined with VIS, NIR, red edge and SWIR) and to determine the best spectral variables to be used for identifying logging patterns, especially in SL. The study was conducted in Taizishan in Hubei province, China. A total of 213 subcompartments of different logging patterns were collected and the random forest algorithm was used to classify logging patterns. The results showed that full-spectrum bands which contain the red-edge and short-wave infrared bands improve the ability of conventional optical satellites to monitor forest logging patterns and can achieve an overall accuracy of 85%, especially for SL which can achieve 79% and 64% for precision and recall accuracy, respectively. The red-edge band (698–713 nm, B5 in Sentinel-2), short-wave infrared band (2100–2280 nm, B12 in Sentinel-2), and associated vegetation indices (NBR, NDre2, and NDre1) enhance the sensitivity of the spectral information to logging patterns, especially for the SL pattern, and the precision and recall accuracy can improve by 10% and 6%, respectively. Meanwhile, both clear-cutting and unlogged patterns could be well-classified whether adding a red-edge or SWIR band or both in VIS and NIR bands; the best precision and recall accuracies for clear-cutting were enhanced to 97%, 95% and 81%, 91% for unlogged, respectively. Our results demonstrate that the optical images have the potential ability to detect logging patterns especially for the clear-cutting and unlogged patterns, and the selective logging detection accuracy can be improved by adding red-edge and short-wave infrared spectral bands. [ABSTRACT FROM AUTHOR]

The external environment has an important impact on farmers' willingness to withdraw from rural homesteads. Based on the data from 392 farmers in Wuhan and Suizhou City from July to November 2021, we explored the significant role that the external environment played in farmers' willingness to withdraw from rural homesteads. The empirical results, according to the binary Logit model, showed that the number of homesteads, location, and economy positively affect farmers' intention to withdraw from their rural homesteads, and the effect in turn decreases. Famers in a village with no tourism resources are more likely to be willing to withdraw from their homesteads. Based on the empirical findings, this paper finally proposed that local governments should adopt a targeted policy to encourage farmers to orderly withdraw from their rural homesteads. [ABSTRACT FROM AUTHOR]

Precipitation prediction is central in hydrology and water resources planning and management. This paper introduces a semi-empirical predictive model to predict monthly precipitation and compares its predictive skill with those of machine learning (ML) methods. The stochastic method presented herein estimates monthly precipitation with one-step-ahead prediction properties. The ML predictive skill of the algorithms is evaluated by predicting monthly precipitation relying on the statistical association between precipitation and environmental and topographic factors. The semi-empirical predictive model features non-negative matrix factorization (NMF) for investigating the influence of multiple predictor variables on precipitation. The semi-empirical predictive model's parameters are optimized with the hybrid genetic algorithm (GA) and Levenberg-Marquardt algorithm (LM), or GALMA, yielding a validated model with high predictive skill. The methodologies are illustrated with data from Hubei Province, China, which comprise 27 meteorological station datasets from 1988–2017. The empirical results provide valuable insights for developing semi-empirical rainfall prediction models. [ABSTRACT FROM AUTHOR]

In view of the differences of land use structure and ecological environment changes caused by land consolidation projects with different features and landforms, this paper uses the modified ecosystem service value estimation model to quantitatively evaluate the change patterns of the ecosystem service value (ESV) of land consolidation, development and arrangement projects in Hubei Province under plains, hills and mountains to provide a theoretical basis for the ecological transformation of land consolidation. The results show that, compared with the pre-land consolidation period, (1) the total amount of ESV in the land consolidation project areas has increased, whereas the land development and arrangement project areas have decreased. Under the same nature, the growth rate of land consolidation project areas is as follows: hills < plains < mountains, and the loss rate of land development and arrangement project areas are as follows: mountains > plains > hills and hills > mountains > plains, respectively. Under the same landform, the total loss rate of ESV in land development project areas is slightly lower than that in land arrangement project areas. (2) The total amount of ESV in the land consolidation project areas under different natures and landforms of the supply service function shows a decreasing trend, and the total amount of ESV of the adjustment service, support service and cultural service function shows an increasing trend in the land consolidation project areas, whereas the land development and arrangement project areas show a decreasing trend. There is an obvious value transformation process of "ecology for production" in the land development and arrangement areas. [ABSTRACT FROM AUTHOR]

In China, rural construction land refers to the construction land of townships (town) and villages. The construction land of townships (town) and villages refers to the land used by township (town) and village collective economic organizations and rural individuals to invest or raise funds for various non-agricultural construction. Rural collective construction land is divided into three categories: homestead, land for public welfare public facilities, and land for business. Complete market transaction rules can make the market of rural collective construction land run more openly, fairly, and justly, thus protecting the rights of villagers and collective economic organizations and, at the same time, reducing the transaction cost of the village collective. In this paper, we choose the formal rules of the urban and rural land linking quota trading market in Ezhou, Hubei Province, China, to analyze the three dimensions of the market transaction rules and villagers' willingness. We also provide suggestions for the development of the RCCL market and the improvement of trading rules. The research results of the logistic model show the following: (1) Under the arrangement of the transaction rules of the RCCL, there are high transaction costs, especially labor costs and time costs, so the villagers' willingness to enter the market is not very strong. (2) Asset specificity affects villagers' willingness. The larger the area of RCCL involved in the transaction, the higher the transaction cost, the lower the villagers' willingness to support the RCCL transfer. (3) The greater the uncertainty of the RCCL transaction environment—mainly due to the problems of the openness, equity, and justice of the transaction rules, which lies in the transaction information not being transparent and the income distribution and the pricing being unreasonable, resulting in villagers' rights being denied—the more the villagers are unwilling to support the RCCL entering the market. Therefore, we suggest that more open, fair, and just trading rules of the RCCL market should be formulated to protect the security of villagers' property rights. Moreover, the land value should be displayed reasonably, which can also standardize the good trading order and trading environment, thus making the market development more effective and stable. Our work provides some insights for improving the efficiency of the land market, which will contribute to the development of the worldwide RCCL market. [ABSTRACT FROM AUTHOR]

High spatial resolution (1 km or finer) precipitation data fields are crucial for understanding the Earth's water and energy cycles at the regional scale for applications. The spatial resolution of the Global Precipitation Measurement (GPM) mission (IMERG) satellite precipitation products is 0.1° (latitude) × 0.1° (longitude), which is too coarse for regional-scale analysis. This study combined the Geographically Weighted Regression (GWR) and the Multifractal Random Cascade (MFRC) model to downscale monthly GPM/IMERG precipitation products from 0.1° × 0.1° (approximately 11 km × 11 km) to 1 km in Hubei Province, China. This work's results indicate the following: (1) The original GPM product can accurately express the precipitation in the study area, which highly correlates with the site data from 2015 to 2017 (R2 = 0.79) and overall presents the phenomenon of overestimation. (2) The GWR model maintains the precipitation field's overall accuracy and smoothness, with even improvements in accuracy for specific months. In contrast, the MFRC model causes a slight decrease in the overall accuracy of the precipitation field but performs better in reducing the bias. (3) The GWR-MF combined with the GWR and MFRC model improves the observation accuracy of the downscaling results and reduces the bias value by introducing the MFRC to correct the deviation of GWR. The conclusion and analysis of this paper can provide a meaningful experience for 1 km high-resolution data to support related applications. [ABSTRACT FROM AUTHOR]

This study is the first systematic assessment of the Lower Ordovician microbial carbonates in Songzi, Hubei Province, China. This paper divides the microbial carbonates into two types according to growth patterns, namely nongranular and granular. The nongranular types include stromatolites, thrombolites, dendrolites, leiolites and laminites; the granular types are mainly oncolites and may include a small amount of microbiogenic oolite. According to their geometric features, the stromatolites can be divided into four types: stratiform, wavy, columnar and domal. Additionally, dipyramidal columnar stromatolites are identified for the first time and represent a new type of columnar stromatolite. The thrombolites are divided into three types: speckled, reticulated and banded. The grazing gastropod Ecculiomphalus and traces of bioturbation are observed in the speckled and reticulated thrombolites. This paper considers these two kinds of thrombolites to represent bioturbated thrombolites. These findings not only fill gaps in the field of domestic Ordovician bioturbated thrombolites but also provide new information for the study of thrombolites. Based on the analysis of the sedimentary characteristics of microbialites, the depositional environments of the various types of microbialites are described, and the distribution patterns of their depositional environments are summarized. The relationship between the development of microbialites and the evolution and radiation of metazoans during the Early to Middle Ordovician is discussed. Consistent with the correspondence between the stepwise and rapid radiation of metazoans and the abrupt reduction in the number of microbialites between the late Early Ordovician and the early Middle Ordovician, fossils of benthonic grazing gastropods (Ecculiomphalus) were found in the stromatolites and thrombolite of the study area. It is believed that the gradual reduction in microbialites was related to the rapid increase in the abundance of metazoans. Grazers not only grazed on the microorganisms that formed stromatolites, resulting in a continuous reduction in the number of stromatolites, but also disrupted the growth state of the stromatolites, resulting in the formation of unique bioturbated thrombolites in the study area. Hydrocarbon potential analysis shows that the microbialites in the Nanjinguan Formation represent better source rocks than those in the other formations. [ABSTRACT FROM AUTHOR]

While increased tourist demand has brought economic benefits to tourist destinations, it has also put tremendous pressure on tourism-related ecological environments. Therefore, the relationship between regional urban tourism's economic benefits and tourism ecologies must be considered by increasing the ecological security levels of regional urban tourism and promoting sustainable tourism development. This paper defines the ecological security of regional urban tourism, constructs an indicator system of said ecological security based on a pressure-state-response social-economic-environment (PSR-SEE) model, uses the entropy method to objectively assign weights to the indicator system, constructs a dynamic multi-scenario simulation model to assess ecological security under continuous, economic priority and various ecological protection scenarios, employs ArcGIS software to analyze the spatial distribution patterns of the ecological security of regional urban tourism, and uses a standard deviation ellipse method to analyze the space–time evolutionary track of the ecological security of regional urban tourism. The index system is applied to 16 cities in Hubei Province to measure the ecological security levels and test the viability of the system. The present research focuses on the space–time evolution of the ecological security of regional urban tourism, addresses the contradictions between socioeconomic development and the ecological security of regional urban tourism, provides an important reference for tourism destination planning, and can assist in improving the levels of the ecological security of regional urban tourism to promote sustainable tourism development. [ABSTRACT FROM AUTHOR]

The outbreak of the COVID-19 epidemic has had an adverse effect on China's economy. This paper uses the event study method to test and measure the impact of the open market reverse repo (OMRR) operation on the Chinese stock market. The results show that the OMRR operation generates a positive daily abnormal return and a positive daily cumulative abnormal return on average for all stocks. The impact is larger for non-state-owned enterprise (non-SOE) firms than for SOE firms, stocks of non-Hubei provinces than those of the Hubei province, and for stocks of the information transmission and technology industry than those of other industries. We suggest that our government implement more prudent monetary policies and more proactive fiscal policies. [ABSTRACT FROM AUTHOR]

Fagineura was established by Vikberg & Zinovjev in Shinohara et al. (2000). In this paper, two new species of Fagineura are described and illustrated, F. brevicornis sp. nov. collected in Hubei Province and F. longitangia sp. nov. collected in Hunan Province from China. A key to all species of Fagineura worldwide is provided, now including six species. [ABSTRACT FROM AUTHOR]

Although instructional feedback plays an essential role in regulating learning and improving performance, few studies have systematically investigated the needs of teachers and students for instructional feedback systems or developed designs and experiments, especially at the high school level. To address this research need, the present study investigated the needs of selected students and teachers in a high school in Hubei Province, China, and designed and developed a diagnostic visual feedback system for an experimental study with 125 students from a 10th-grade biology class in the same high school. The results showed that this diagnostic visual feedback report improved student performance (ES = 0.37) and that functions such as misconception location, knowledge diagnosis, and knowledge alert were well received by students. These findings have multiple implications for facilitating the design and development of diagnostic visual feedback systems. [ABSTRACT FROM AUTHOR]

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Ye, M., 2020. Constraints and solutions for harnessing and revitalizing water resources in Hubei Province of China. In: Hu, C. and Cai, M. (eds.), Geo-informatics and Oceanography. Journal of Coastal Research, Special Issue No. 105, pp. 115–118. Coconut Creek (Florida), ISSN 0749-0208. Water is the source of life, the essence of production, and the foundation of ecology. Considering the extreme importance of water resources, this paper takes Hubei Province as an example to study how to effectively solve natural disasters such as flood, drought, and waterlogging in inland river basins in China. Through in-depth analysis of the dialectical relationship between promoting water conservancy and controlling flood disasters, this paper fully demonstrates the great historical opportunities that Hubei Province is afforded under the national ecological civilization construction strategy. Finally, by learning from the successful experience of western developed countries in sustainable utilization of water resources, this paper proposes specific strategies of scientific development of water resources in Hubei Province as follows: constructing flood-control and waterlogging-reduction systems, optimizing water resources allocation structure, speeding up the construction of farmland water conservancy facilities, and strengthening the sustainable development and recycling of water resources, as well as building a modern water conservancy management system, which provides theoretical reference and scientific basis for scientific, orderly, and high-quality development of water resources in Hubei Province under the premise of ecological protection. [ABSTRACT FROM AUTHOR]

The targets of limiting global warming levels below 2°C or even 1.5°C set by Paris Agreement heavily rely on bioenergy with carbon capture and storage (BECCS), which can remove carbon dioxide in the atmosphere and achieve net zero greenhouse gas (GHG) emission. Biomass and coal co‐firing with CCS is one of BECCS technologies, as well as a pathway to achieve low carbon transformation and upgrading through retrofitting coal power plants. However, few studies have considered co‐firing ratio of biomass to coal based on each specific coal power plant's characteristic information such as location, installed capacity, resources allocation, and logistic transportation. Therefore, there is a need to understand whether it is worth retrofitting any individual coal power plant for the benefit of GHG emission reduction. It is also important to understand which power plant is suitable for retrofit and the associated co‐firing ratio. In order to fulfill this gap, this paper develops a framework to solve these questions, which mainly include three steps. First, biomass resources are assessed at 1 km spatial resolution with the help of the Geography Information Science method. Second, by setting biomass collection points and linear program model, resource allocation and supply chain for each power plants are complete. Third, is by assessing the life‐cycle emission for each power plant. In this study, Hubei Province in China is taken as the research area and study case. The main conclusions are as follows: (a) biomass co‐firing ratio for each CCS coal power plant to achieve carbon neutral is between 40% and 50%; (b) lower co‐firing ratio sometimes may obtain better carbon emission reduction benefits; (c) even the same installed capacity power plants should consider differentiated retrofit strategy according to their own characteristic. Based on the results and analysis above, retrofit suggestions for each power plant are made in the discussion. [ABSTRACT FROM AUTHOR]

Grain Scale Management (GSM) is a crucial factor in ensuring national food security. However, in countries facing rigid resource constraints and complex land tenure relationships, the strategy of promoting large-scale grain management through land management rights transfer may not be sustainable. Therefore, based on the traditional agricultural division of labor theory, we analyze the mechanism and rationality of Agricultural Production Socialization Services (APSS) with scale characteristics to promote GSM and propose a new approach to GSM with empirical evidence from China. Using county-level panel data from Hubei province spanning from 2010 to 2021, we construct a multi-period double difference model based on the difference in the time of the establishment of pilot agricultural production socialization service counties in Hubei province. Our empirical results demonstrate the role of APSS in promoting GSM at the macro level. Specifically, the establishment of pilot counties for APSS significantly improves the level of local GSM. Furthermore, our study reveals that the degree of local financial intervention, regional industrial structure, and regional topography have heterogeneous effects on the implementation of the policy. [ABSTRACT FROM AUTHOR]

The carrying capacity of water resources can provide a reference index for regional economic construction and development. Hubei produces 13.2% of China's hydroelectric energy and 4% of China's water resources, highlighting that the reservoir group in Hubei province is relatively developed. In the current research on water resources carrying capacity, only the amount of water resources was considered; the benign mutual feeding effect of regional reservoirs on regional water resources carrying capacity was not reflected upon. In order to guide social and economic activities better, this paper proposes the addition of reservoir water storage to the calculation of water resources carrying capacity as a separate indicator. In this paper, the cloud model method was used to calculate the water resources carrying capacity of Hubei province and the Dematel method was used to determine the degree of importance of reservoir water storage. Finally, the degree of obstacles was also considered to discuss the main factors affecting the water resources carrying capacity of Hubei province. In the system discussed in this paper, the degree of influence and the affected degree of reservoir water storage were found to be 1.2915 and 0.5759, respectively. The calculation results showed that Hubei province's water resources carrying capacity has been increasing every year and the amount of water resources per unit area was the main restricting factor, with the obstacle degree reaching 19.24% of the average annual level. [ABSTRACT FROM AUTHOR]

Emission trading scheme (ETS), the most popular market-based instrument, is widely used to solve carbon emission problems in the world. With the development of carbon market, carbon asset has been a popular financial product to invest and the risk management becomes important for government, regulated enterprises and other investors. As carbon prices have tail characteristics, this paper explores the extremal risks between carbon markets in US, Europe and China using tail dependence correlation coefficients. The empirical analysis demonstrates the tail dependence structure between carbon markets in US. and Europe is the same sign, which indicates that it is unwise to hold these two carbon assets as a portfolio. Moreover, the co-movements between European Union Emission Trade Scheme (EU ETS) and China's carbon markets are partly significant, and the operation mechanisms in China should be improved. In addition, the tail dependence test among the carbon pilots in China shows diversity. Hubei carbon trading pilot, located in central China, has extremal dependence with all other selected pilots for its regulatory program operation. The findings give insight to the carbon market regulars to improve the operation mechanism and are also useful for the investors to manage their portfolios, policymakers to make practically applicable regulations, and relevant organizations to develop procedures. [ABSTRACT FROM AUTHOR]

Currently, a novel coronavirus (2019-nCoV) causes an outbreak of viral pneumonia in Hubei province, China. In this paper, stochastic and deterministic models are proposed to investigate the transmission mechanism of 2019-nCoV from 15 January to 5 February 2020 in Hubei province. For the deterministic model, basic reproduction number R 0 is defined and endemic equilibrium is given. Under R 0 > 1 , quasi-stationary distribution of the stochastic process is approximated by Gaussian diffusion. Residual, sensitivity, dynamical, and diffusion analyses of the models are conducted. Further, control variables are introduced to the deterministic model and optimal strategies are provided. Based on empirical results, we suggest that the first and most important thing is to control input, screening, treatment, and isolation. [ABSTRACT FROM AUTHOR]

We propose a varying coefficient Susceptible-Infected-Removal (vSIR) model that allows changing infection and removal rates for the latest corona virus (COVID-19) outbreak in China. The vSIR model together with proposed estimation procedures allow one to track the reproductivity of the COVID-19 through time and to assess the effectiveness of the control measures implemented since Jan 23 2020 when the city of Wuhan was lockdown followed by an extremely high level of self-isolation in the population. Our study finds that the reproductivity of COVID-19 had been significantly slowed down in the three weeks from January 27th to February 17th with 96.3% and 95.1% reductions in the effective reproduction numbers R among the 30 provinces and 15 Hubei cities, respectively. Predictions to the ending times and the total numbers of infected are made under three scenarios of the removal rates. The paper provides a timely model and associated estimation and prediction methods which may be applied in other countries to track, assess and predict the epidemic of the COVID-19 or other infectious diseases. [ABSTRACT FROM AUTHOR]

The forecasting of carbon emissions trading market price is the basis for improving risk management in the carbon trading market and strengthening the enthusiasm of market participants. This paper will apply machine learning methods to forecast the price of China's carbon trading market. First, the daily average transaction prices of the carbon trading market in Hubei and Shenzhen are collected, and these data are preprocessed by PCAF approach to choose the input variables. Second, a prediction model based on Radical Basis Function (RBF) neural network is established and the parameters of the neural network are optimized by Particle Swarm Optimization (PSO). Finally, the PSO-RBF model is validated by the actual data and proved that the PSO-RBF model has better prediction effect than BP and RBF neural network in China's carbon prices prediction. It is indicated that the prediction model has more significant applicability and deserves further popularization. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19), first reported in December 2019 in Wuhan, China, has progressed to a pandemic associated with substantial morbidity and mortality. Little is known about the healthcare workers who died fighting the disease in China. This paper analyzed the data of 78 Chinese healthcare workers who died in the fight against COVID-19 between 23 January and 2 June, 2020, and revealed the following characteristics. First, compared to the number of deaths directly attributable to COVID-19, more healthcare workers died from pre-existing disease attack induced by excessive fatigue or died from accidents. Second, the median age of the healthcare workers who died directly from COVID-19 was younger than that of the Wuhan non- healthcare workers who died of COVID 19. Third, although more women than men were involved in fighting the pandemic, more men died. Fourth, more healthcare workers died in Hubei than in other provinces. Fifth, most of the healthcare workers who died directly from COVID-19 were non-professionals. [ABSTRACT FROM AUTHOR]

The satellite-retrieved Aerosol Optical Depth (AOD) is widely used to estimate the concentrations and analyze the spatiotemporal pattern of Particulate Matter that is less than or equal to 2.5 microns (PM2.5), also providing a way for the related research of air pollution. Many studies generated PM2.5 concentration networks with resolutions of 3 km or 10 km. However, the relatively coarse resolution of the satellite AOD products make it difficult to determine the fine-scale characteristics of PM2.5 distributions that are important for urban air quality analysis. In addition, the composition and chemical properties of PM2.5 are relatively complex and might be affected by many factors, such as meteorological and land cover type factors. In this paper, an AOD product with a 1 km spatial resolution derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, the PM2.5 measurements from ground sites and the meteorological data as the auxiliary variable, are integrated into the Modified Support Vector Regression (MSVR) model that proposed in this paper to estimate the PM2.5 concentrations and analyze the spatiotemporal pattern of PM2.5. Considering the relatively small dataset and the somewhat complex relationship between the variables, we propose a Modified Support Vector Regression (MSVR) model that based on SVR to fit and estimate the PM2.5 concentrations in Hubei province of China. In this paper, we obtained Cross Correlation Coefficient (R²) of 0.74 for the regression of independent and dependent variables, and the conventional SVR model obtained R² of 0.60 as comparison. We think our MSVR model obtained relatively good performance in spite of many complex factors that might impact the accuracy. We then utilized the optimal MSVR model to perform the PM2.5 estimating, analyze their spatiotemporal patterns, and try to explain the possible reasons for these patterns. The results showed that the PM2.5 estimations retrieved from 1 km MAIAC AOD could reflect more detailed spatial distribution characteristics of PM2.5 and have higher accuracy than that from 3 km MODIS AOD. Therefore, the proposed MSVR model can be a better method for PM2.5 estimating, especially when the dataset is relatively small. [ABSTRACT FROM AUTHOR]

As a developing country with insufficient water resources, China's water environment management and performance evaluation have important research value. The three provinces (Henan, Hubei, and Hunan) in central China with typical significance in geographical location and water resources governance were selected as research objects in this paper. Based on the principal component analysis (PCA) method and the pressure-state-response (PSR) model, a comprehensive evaluation system for the water environment in those three provinces during 2011–2017 was established in this paper. The evaluation results show that: (1) The water environment management and performance evaluation of the three provinces in central China were generally poor in 2011–2012, but the overall trend was rising; (2) in 2013–2014, the situation was improved compared to the previous two years, but needed further enhancement; (3) in 2015–2017, the water environment management and performance of the three provinces showed significant improvement. Among them, the Hubei Province had the highest water environment evaluation value (1.692), and the Henan Province had the most significant progress (from 0.043 to 1.671). The contributions of this paper are: (1) The comprehensive evaluation model based on PCA and the PSR model was constructed to analyze the sustainable development of water environment in central China; (2) the performance evaluation system for water environment management, which could comprehensively evaluate the performance of water environment treatment and effectively reveal the correlation between various indicators, was established. The principal factors in water environment management can be obtained by this evaluation system. Based on the analysis of the reasons underlying the above changes, the corresponding policy recommendations for improving water environment management and performance in central China were suggested in order to provide a reference for further improvement of water environment management in developing countries. [ABSTRACT FROM AUTHOR]

In recent years, air pollution has received serious concerns from researchers, media, and the public sectors, but air pollution from agricultural production activities has not received enough attention. This paper focuses on agricultural air pollution in central China, which is aggravated by the ongoing rural labor migration trend. With a set of panel data released from Hubei and Hunan provinces in China, we adopt the mediating effect model to explore the relationship between rural labor migration and air pollution caused by agricultural activity in China. First, we use the inventory analysis method and principal component analysis method to calculate the comprehensive index of the air pollution of agriculture in 152 counties and districts from Hubei and Hunan provinces, and we empirically test the impact of labor migration on air pollution with a mediating effect model as well as carry out regional heterogeneity analysis on the pollution effect of these two provinces mentioned above. The analysis above indicates that the increase of labor migration has intensified the comprehensive index of air pollution caused by agricultural activity by changing the supply of labor force in the agricultural sector, the budget line of rural residents, and the scale of agricultural production and crop planting structure, but there is a difference in the indirect total effect between the two provinces mentioned above according to our regional heterogeneity analysis. This study is a necessary extension to studies on alleviating and controlling air pollution in China. [ABSTRACT FROM AUTHOR]

Under the background of new-type urbanization and rural revitalization strategy, how to promote the development of urban–rural integration has become an important issue in today's society. This paper designed a new evaluation mechanism for the development level of urban–rural integration. Specifically, a three-level evaluation index system of urban–rural integration development level was established from four aspects: spatial integration, economic integration, social integration and living environment integration. By combining the entropy weight method with the ranking method, a combination weighting method was proposed to determine the weight of each index in the index system. Furthermore, an improved TOPSIS method based on relative entropy and grey relational degree was proposed to evaluate the development level of urban–rural integration, which considering proximity from the perspectives of distance and shape and solving the problem that some situations cannot be compared through the original model. Then, the established evaluation mechanism was applied to make an empirical analysis for evaluating the development level of urban–rural integration in Hubei Province, China. Cluster analysis and obstacle factor analysis were used to further analyze the evaluation results. Finally, according to the evaluation results, some effective countermeasures and policy implications were provided to improve the development level of urban–rural integration in Hubei Province. [ABSTRACT FROM AUTHOR]

This paper studies the carbon price fluctuation in China through the adaptive Fourier decomposition (AFD). Apart from the transient time-frequency distribution of the original AFD model, we also reconstruct the mono-components of this model to obtain the components in different time-frequency scales. Our empirical results based on the carbon price in Hubei Province demonstrate that there are three periods when the price fluctuates dramatically, mainly affected by the governmental policies about carbon emission and the development of clean energies, as well as the outbreak of COVID-19. Furthermore, the fluctuations of the price in the three identified periods are reflected in different scales. The comparison of the decomposition results and those of EMD and VMD shows that the AFD performs best in absorbing the price's useful information extracted through all these methods. [ABSTRACT FROM AUTHOR]

Background: Oncomelania hupensis is the exclusive intermediate host of Schistosoma japonicum in China. Snail control is an essential component of schistosomiasis elimination programme. With 70 years of continuous efforts, the range of O. hupensis had reduced significantly, but slowed down in last decades. A large number of levees against flooding were constructed along Yangtze River and its affiliated lakes in the middle and lower reaches, which influenced the hydrology and ecology in the alluvial plains. The purpose of this study was to assess the impact of levees on the distribution of O. hupensis in the middle and lower reaches of the Yangtze River. Methods: The snail habitats were digitalised by hand-held GPS system. The years for discovery and elimination of snail habitats were extracted from historical records. The accumulated snail-infested range for each habitat was calculated on the basis of annual reports. The current distribution of O. hupensis was determined by systematic and environmental sampling. The geographical distribution of levees was obtained from satellite imagery. To assess the impact of levees, the data pertaining to O. hupensis were divided into two parts: inside and outside the Yangtze River. Joinpoint regression was utilised to divide the study time span and further characterise the regression in each period. The 5-year-period moving averages of eliminated area infested by snails were calculated for the habitats inside and outside Yangtze River. The moving routes of corresponding geographical median centres were simulated in ArcGIS. Hotspot analysis was used to determine the areas with statistical significance clustering of O. hupensis density. Results: Three periods were identified according to Joinpoint regression both inside and outside Yangtze River. The area infested by O. hupensis increased in the first two periods. It decreased rapidly outside Yangtze River year over year after 1970, while that inside the Yangtze River did not change significantly. Furthermore, the latter was significantly higher than the former. It was observed that the present density of O. hupensis inside Yangtze River was lower than outside the Yangtze River. The median centre for eliminated ranges inside Yangtze River wavered between the east (lower reach) and the west (middle reach). In contrast, the median centre for eliminated ranges continuously moved from the east to the west. Conclusions: Our findings indicated that the levees had a considerable negative impact on the distribution of O. hupensis outside Yangtze River. Some hotspots observed in the irrigation areas need a sluice system at the inlet of branch for snail control. The major distribution of O. hupensis located in Hubei might be caused by severe waterlogging. The intensive surveillance should be implemented there. The biggest two freshwater lakes, the major endemic regions historically, were identified as cold spots. The long-term impact of Three Gorges Dam on the distribution of O. hupensis in the lakes should be monitored and evaluated. [ABSTRACT FROM AUTHOR]

Introduction: The contamination of farmland soil with the heavy metal cadmium (Cd) has consistently been a globally recognized environmental issue, especially with the rapid development of the central part of the Hanjiang River basin. The Cd contamination has become increasingly serious, and the accumulation and translocation of Cd in the soil-crop system warrant further research. Methods: In this study, representative yellowish-brown soil and limestone soil from Hubei Province in China, as well as five varieties of potato (Solanum tuberosum L), were selected to investigate Cd accumulation and transfer regulation from soil to plants using pot tests at varying Cd concentration levels. Results and discussion: For Eshu-12, Favorita, Huashu-6, Mira, and Zhongshu-5, the accumulation capacity of Cd in different parts exhibits a consistent pattern: Cdroot > Cdstem > Cdleaf > Cdtuber. The potato varieties exhibited distinct differences in Cd concentration, as follows: CdFavorita > CdMira > CdEshu-12 > CdHuashu-6 > CdZhongshu-5. The yellowish-brown soil demonstrated a higher accumulation and lower transport capacity to the plants of Cd, while limestone soil exhibited the opposite trend. The bioconcentration factor and transfer coefficients in yellowish-brown soil revealed significant (p < 0.05) accumulation and transformation of Cd in potatoes. Conclusion and recommendations: This significant accumulation of Cd posed a higher risk of transfer through the food chain. Therefore, in the Hanjiang River basin, where Cd contamination is a concern, the cultivation of potatoes in limestone soil is more advisable than yellowish-brown soil to mitigate food safety risks. [ABSTRACT FROM AUTHOR]