Soil heavy metal pollution has been becoming serious and widespread in China. To date, there are few studies assessing the nationwide soil heavy metal pollution induced by industrial and agricultural ...activities in China. This review obtained heavy metal concentrations in soils of 402 industrial sites and 1041 agricultural sites in China throughout the document retrieval. Based on the database, this review assessed soil heavy metal concentration and estimated the ecological and health risks on a national scale. The results revealed that heavy metal pollution and associated risks posed by cadmium (Cd), lead (Pb) and arsenic (As) are more serious. Besides, heavy metal pollution and associated risks in industrial regions are severer than those in agricultural regions, meanwhile, those in southeast China are severer than those in northwest China. It is worth noting that children are more likely to be affected by heavy metal pollution than adults. Based on the assessment results, Cd, Pb and As are determined as the priority control heavy metals; mining areas are the priority control areas compared to other areas in industrial regions; food crop plantations are the priority control areas in agricultural regions; and children are determined as the priority protection population group. This paper provides a comprehensive ecological and health risk assessment on the heavy metals in soils in Chinese industrial and agricultural regions and thus provides insights for the policymakers regarding exposure reduction and management.
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•402 industrial and 1041 agricultural sites are reviewed.•Pollution and risks in industrial regions were severer than agricultural regions.•30% of industrial sites pose potential non-carcinogenic risk.•The majority of As carcinogenic risks are at a relatively unacceptable range.•The priority control components were identified.
Heavy metal pollution has pervaded many parts of the world, especially developing countries such as China. This review summarizes available data in the literature (2005–2012) on heavy metal polluted ...soils originating from mining areas in China. Based on these obtained data, this paper then evaluates the soil pollution levels of these collected mines and quantifies the risks these pollutants pose to human health. To assess these potential threat levels, the geoaccumulation index was applied, along with the US Environmental Protection Agency (USEPA) recommended method for health risk assessment. The results demonstrate not only the severity of heavy metal pollution from the examined mines, but also the high carcinogenic and non-carcinogenic risks that soil heavy metal pollution poses to the public, especially to children and those living in the vicinity of heavily polluted mining areas. In order to provide key management targets for relevant government agencies, based on the results of the pollution and health risk assessments, Cd, Pb, Cu, Zn, Hg, As, and Ni are selected as the priority control heavy metals; tungsten, manganese, lead–zinc, and antimony mines are selected as the priority control mine categories; and southern provinces and Liaoning province are selected as the priority control provinces. This review, therefore, provides a comprehensive assessment of soil heavy metal pollution derived from mines in China, while identifying policy recommendations for pollution mitigation and environmental management of these mines.
•This paper reviews soil heavy metal pollution derived from mines in China.•A comprehensive pollution and health risk assessment was conducted.•Soils surrounding the examined mines are seriously polluted by heavy metals.•The soil heavy metal pollution continues to pose high health risks to the public.•The priority control heavy metals, mine types, and provinces were identified.
This paper studies how reduction in trade policy uncertainty affects firm export decisions. Using a firm–product level dataset on Chinese exports to the United States and the European Union in the ...years surrounding China's WTO accession, we provide strong evidence that reduction in trade policy uncertainty simultaneously induced firm entries to and firm exits from export activity within fine product-level markets. In addition, we uncover accompanying changes in export product prices and quality that coincided with this reallocation: firms that provided higher quality products at lower prices entered the export market, while firms that had higher prices and provided lower quality products prior to the changes, exited. To explain the simultaneous export entries and exits, as well as the fact that new entrants are more productive than exiters, we provide a model of heterogeneous firms which incorporates trade policy uncertainty, tracing the effects of the changes in policy uncertainty on firm-level payoffs and the resulting selection effects.
FOXP3＋ regulatory T （Treg） cells are critical in maintaining immune tolerance and homeostasis of the immune system. The molecular mechanisms underlying the stability, plasticity and functional ...activity of Treg cells have been much studied in recent years. Here, we summarize these intriguing findings, and provide insight into their potential use or manipulation during Treg cell therapy for the treatment of autoimmune diseases, graft-versus-host disease （GVHD） and cancer.
We use Chinese manufacturing firm data to estimate the causal effect of increased imported intermediate input use on firm export outcomes. To account for the endogeneity of import decisions, we ...pursue an IV strategy that utilizes instruments for import costs connected to intermediate input import tariffs, exchange rates, and firm differences in fixed trade costs. We find that firms that expanded their intermediate input imports expanded the volume and scope of their exports. Further, we find that the benefit of imported inputs differed along a number of dimensions including initial trade status, import source country, export destination, firm ownership, and industry R&D intensity. Although increased imports of intermediates boosted exports by all firms, we find that the effects were largest when they were purchased by private firms or firms that started out as non-traders. In addition, intermediate inputs from the higher-income G7 countries were especially helpful in facilitating firm exports to the presumably more-demanding G7 export markets. Taken together, these results suggest that product upgrading facilitated by technology or quality embedded in imported inputs helped Chinese firms to increase the scale and breadth of their participation in export markets.
This paper examines why credit constraints for domestic and exporting firms arise in a setting where banks do not observe firms' productivities. To maintain incentive compatibility, banks lend below ...the amount that firms need for optimal production. The longer time needed for export shipments induces a tighter credit constraint on exporters than on purely domestic firms. In our application to Chinese firms, we find that the credit constraint is more stringent as a firm's export share grows, as the time to ship for exports is lengthened, and as there is greater dispersion of firms' productivities, reflecting more incomplete information.
As an emerging network paradigm, the space-air-ground integrated network (SAGIN) has garnered attention from academia and industry. That is because SAGIN can implement seamless global coverage and ...connections among electronic devices in space, air, and ground spaces. Additionally, the shortage of computing and storage resources in mobile devices greatly impacts the quality of experiences for intelligent applications. Hence, we plan to integrate SAGIN as an abundant resource pool into mobile edge computing environments (MECs). To facilitate efficient processing, we need to solve the optimal task offloading decisions. In contrast to existing MEC task offloading solutions, we have to face some new challenges, such as the fluctuation of processing capabilities for edge computing nodes, the uncertainty of transmission latency caused by heterogeneous network protocols, the uncertain amount of uploaded tasks during a period, and so on. In this paper, we first describe the task offloading decision problem in environments characterized by these new challenges. However, we cannot use standard robust optimization and stochastic optimization methods to obtain optimal results under uncertain network environments. In this paper, we propose the 'condition value at risk-aware distributionally robust optimization' algorithm for task offloading, denoted as RADROO, to solve the task offloading decision problem. RADROO combines the distributionally robust optimization and the condition value at risk model to achieve optimal results. We evaluated our approach in simulated SAGIN environments, considering confidence intervals, the number of mobile task offloading instances, and various parameters. We compare our proposed RADROO algorithm with state-of-the-art algorithms, such as the standard robust optimization algorithm, the stochastic optimization algorithm, the DRO algorithm, and the Brute algorithm. The experimental results show that RADROO can achieve a sub-optimal mobile task offloading decision. Overall, RADROO is more robust than others to the new challenges mentioned above in SAGIN.
•In this paper, we propose a matching network which builds a connection be- tween template characters and handwritten characters inspired by the human learning process of writing Chinese characters. ...The matching network replace the parameters in the softmax regression layer with the features extracted from the template character images. After the training process has been finished, the powerful discriminative features help us to generalize the predictive power not just to new data, but to entire new classes that never appear in the training set before. Experiments performed on the ICDAR-2013 offline HCCR datasets have shown that the proposed method achieves a comparable performance to current CNN-based classifiers. Besides, the matching network has a very promising gen- eralization ability to the new classes that never appear in the existing training set.
Just like its remarkable achievements in many computer vision tasks, the convolutional neural networks (CNN) provide an end-to-end solution in handwritten Chinese character recognition (HCCR) with great success. However, the process of learning discriminative features for image recognition is difficult in cases where little data is available. In this paper, we propose a matching network which builds a connection between template characters and handwritten characters inspired by the human learning process of writing Chinese characters. The matching network replaces the parameters in the softmax regression layer with the features extracted from the template character images. After the training process has been finished, the powerful discriminative features help us to generalize the predictive power not just to new data, but to entire new Chinese characters that never appear in the training set before. Experiments performed on the ICDAR-2013 offline HCCR datasets have shown that the proposed method achieves a comparable performance to current CNN-based classifiers. Besides, the matching network has a very promising generalization ability to new Chinese characters that never appear in the existing training set.
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