Documented Evidence of Agricultural Injury in China

Objective: To describe the documented evidence concerning agricultural injury in China and to identify topics for future research.Method: Literature search and review were conducted to collect publications that were relevant to agricultural injury in China. The process included defining agricultural injury for the purpose of this study, selecting articles according to inclusion criteria and extracting data from each paper. Descriptive methods were used to analyze the contents, research approaches, distribution of authors, and cooperation percentage of agricultural injury studies.Results: After applying the inclusion criteria, 89 articles were included in this study. The author collaboration percentage (number of articles with more than one author divided by number of total articles) and the institutional collaboration percentage (number of articles with more than one organization divided by number of total articles) among the 89 articles were 85.4% and 42.7%, respectively. Most of the authors are affiliated with a Center for Disease Control and Prevention (CDC) or an academic institution located in 10 of the 31 provinces in mainland China. Among the 89 articles, only 6 were on injuries related to agricultural work, the rest (83) dealt with injuries among rural residents with or without clarifying occupations or ongoing activities. Conclusions: Research on agricultural injuries in China is currently in its early stage. More research is needed to obtain evidence that can be used in policy making for agricultural injury control. Our study is the first to describe the documented evidence on agricultural injuries in China and identify topics for future research

A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks

Two-sample tests are important areas aiming to determine whether two collections of observations follow the same distribution or not. We propose two-sample tests based on integral probability metric (IPM) for high-dimensional samples supported on a low-dimensional manifold. We characterize the properties of proposed tests with respect to the number of samples $n$ and the structure of the manifold with intrinsic dimension $d$. When an atlas is given, we propose two-step test to identify the difference between general distributions, which achieves the type-II risk in the order of $n^{-1/\max\{d,2\}}$. When an atlas is not given, we propose H\"older IPM test that applies for data distributions with $(s,\beta)$-H\"older densities, which achieves the type-II risk in the order of $n^{-(s+\beta)/d}$. To mitigate the heavy computation burden of evaluating the H\"older IPM, we approximate the H\"older function class using neural networks. Based on the approximation theory of neural networks, we show that the neural network IPM test has the type-II risk in the order of $n^{-(s+\beta)/d}$, which is in the same order of the type-II risk as the H\"older IPM test. Our proposed tests are adaptive to low-dimensional geometric structure because their performance crucially depends on the intrinsic dimension instead of the data dimension.Comment: 32 pages, 2 figures, 3 tables. Accepted by Information and Inference: A Journal of the IM

Open-Set Facial Expression Recognition

Facial expression recognition (FER) models are typically trained on datasets with a fixed number of seven basic classes. However, recent research works point out that there are far more expressions than the basic ones. Thus, when these models are deployed in the real world, they may encounter unknown classes, such as compound expressions that cannot be classified into existing basic classes. To address this issue, we propose the open-set FER task for the first time. Though there are many existing open-set recognition methods, we argue that they do not work well for open-set FER because FER data are all human faces with very small inter-class distances, which makes the open-set samples very similar to close-set samples. In this paper, we are the first to transform the disadvantage of small inter-class distance into an advantage by proposing a new way for open-set FER. Specifically, we find that small inter-class distance allows for sparsely distributed pseudo labels of open-set samples, which can be viewed as symmetric noisy labels. Based on this novel observation, we convert the open-set FER to a noisy label detection problem. We further propose a novel method that incorporates attention map consistency and cycle training to detect the open-set samples. Extensive experiments on various FER datasets demonstrate that our method clearly outperforms state-of-the-art open-set recognition methods by large margins. Code is available at https://github.com/zyh-uaiaaaa.Comment: Accepted by AAAI202

Benign duodenocolic fistula: A case report and review of the literature

Duodenocolic fistula is a rare upper gastrointestinal fistula that can be benign or malignant. However, benign duodenocolic fistulas are particularly rare. Duodenocolic fistulas are often a complication of advanced colon cancer. The most common cause of benign fistulas is perforation of the duodenal ulcer. We report a case of a benign duodenocolic fistula in a patient who presented with abdominal pain, diarrhea, and weight loss. Gastroscopy and an upper gastrointestinal study confirmed the presence of the fistula. Surgery was performed, and the pathological examination demonstrated that the fistula originated from a duodenal ulcer

Core-sheath structured electrospun nanofibrous membranes for oil-water separation

In recent years, both the increasing frequency of oil spill accidents and the urgency to deal seriously with industrial oil-polluted water, encouraged material scientists to design highly efficient, cost effective oil-water separation technologies. We report on electrospun nanofibrous membranes which are composed of core-sheath structured cellulose-acetate (CA)-polyimide (PI) nanofibers. On the surface of the CA-PI fibers a fluorinated polybenzoxazine (F-PBZ) functional layer, in which silica nanoparticles (SNPs) were incorporated, has been applied. Compared with F-PBZ/SNP modified CA fibers reported before for the separation of oil from water, the PI-core of the core-shell F-PBZ/SNP/CA-PI fibers makes the membranes much stronger, being a significant asset in their use. Nanofibrous membranes with a tensile strength higher than 200 MPa, a high water contact angle of 160 degrees and an extremely low oil contact angle of 0 degrees were obtained. F-PBZ/SNP/CA-PI membranes seemed very suitable for gravity-driven oil-water separation as fast and efficient separation (>99%) of oil from water was achieved for various oil-water mixtures. The designed core-sheath structured electrospun nanofibrous membranes may become interesting materials for the treatment of industrial oil-polluted water

35 años de reformas y desarrollo en China

La rápida evolución de la economía china ha sido uno de los cambios más significativos en el mundo en los últimos treinta y cinco años. China se ha convertido la segunda potencia mundial, según su PIB nominal. El modelo económico chino es un caso particular debido a las peculiaridades de su gobierno y política económica. La finalidad de este trabajo es analizar la evolución de la economía china desde que su apertura económica y las reformas en los sectores productivos impulsaron el desarrollo de la industria y los servicios. La entrada de inversión extranjera ha permitido cubrir las necesidades de capital de las empresas e introducir mayor competencia en el mercado nacional. A su vez se han realizado grandes esfuerzos en materia educativa y en I+D, necesarios para un crecimiento sostenible a largo plazo. El crecimiento ha traído mayor bienestar a la población china, pero ha generado algunos desequilibrios. Uno de los más importantes es “la desigualdad social”. La integración actual de la economía china en el mundo es suficiente para tener un impacto sustancial a escala internacional. Además, a este ritmo de crecimiento, pronto China se convertirá en la primera potencia del mundo