The Rise of Smart Courts in China: Opportunities and Challenges to the Judiciary in a Digital Age

Information and communication technology has increasingly played an important role in judicial activities. In recent years, digitalization of courts has been explored actively in theory and practice in China. Generally, digitalization of courts refers to that litigation activities like case-filing, court trial, execution, service and preservation can be carried out online to a certain degree, with the help of modern technology like big data, cloud computing, artificial intelligence and high-tech equipment. Digitalization of courts is considered to help to improve judicial efficiency, contribute to judicial disclosures, provide convenience for people and to establish judicial big data. However, lack of consistent guidelines might undermine the application of digital means in the judiciary. The purpose of this paper is to investigate the progress made so far with regard to digitalization of courts in China, and to analyze the opportunities and challenges during the digitalized process of Chinese courts

The Rise of Smart Courts in China

Information and communication technology has increasingly played an important role in judicial activities. In recent years, digitalization of courts has been explored actively in theory and practice in China. Generally, digitalization of courts refers to that litigation activities like case-filing, court trial, execution, service and preservation can be carried out online to a certain degree, with the help of modern technology like big data, cloud computing, artificial intelligence and high-tech equipment. Digitalization of courts is considered to help to improve judicial efficiency, contribute to judicial disclosures, provide convenience for people and to establish judicial big data. However, lack of consistent guidelines might undermine the application of digital means in the judiciary. The purpose of this paper is to investigate the progress made so far with regard to digitalization of courts in China, and to analyze the opportunities and challenges during the digitalized process of Chinese courts

Modular Blind Video Quality Assessment

Blind video quality assessment (BVQA) plays a pivotal role in evaluating and improving the viewing experience of end-users across a wide range of video-based platforms and services. Contemporary deep learning-based models primarily analyze video content in its aggressively subsampled format, while being blind to the impact of the actual spatial resolution and frame rate on video quality. In this paper, we propose a modular BVQA model and a method of training it to improve its modularity. Our model comprises a base quality predictor, a spatial rectifier, and a temporal rectifier, responding to the visual content and distortion, spatial resolution, and frame rate changes on video quality, respectively. During training, spatial and temporal rectifiers are dropped out with some probabilities to render the base quality predictor a standalone BVQA model, which should work better with the rectifiers. Extensive experiments on both professionally-generated content and user-generated content video databases show that our quality model achieves superior or comparable performance to current methods. Additionally, the modularity of our model offers an opportunity to analyze existing video quality databases in terms of their spatial and temporal complexity.Comment: Accepted by CVPR 2024; Camera-ready versio

Extracorporeal membrane oxygenation for acute pulmonary embolism after postoperative craniocerebral trauma: a case report

IntroductionMassive pulmonary embolism (PE) is a life-threatening complication of major surgery with a mortality rate of up to 50%. Extracorporeal membrane oxygenation (ECMO) is primarily used for respiratory and circulatory support. Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is used to stabilize patients with acute massive PE. Acute brain injury, vascular disease, and immunosuppression are contraindications to ECMO, as stated in the 2021 Extracorporeal Life Support Organization guidelines.Case summaryWe report a case of a patient with craniocerebral trauma whose postoperative course was complicated by massive PE and subsequent cardiac arrest that required urgent VA-ECMO, followed by anticoagulation with heparin. The patient showed hemodynamic improvement and was discharged 68 days after hospitalization.DiscussionECMO has gradually been accepted for patients with craniocerebral injuries. The safety and effectiveness of ECMO in patients with craniocerebral injury, along with the optimal duration of ECMO and anticoagulation strategies, require further study

BPLLDA: Predicting lncRNA-Disease Associations Based on Simple Paths With Limited Lengths in a Heterogeneous Network

In recent years, it has been increasingly clear that long noncoding RNAs (lncRNAs) play critical roles in many biological processes associated with human diseases. Inferring potential lncRNA-disease associations is essential to reveal the secrets behind diseases, develop novel drugs, and optimize personalized treatments. However, biological experiments to validate lncRNA-disease associations are very time-consuming and costly. Thus, it is critical to develop effective computational models. In this study, we have proposed a method called BPLLDA to predict lncRNA-disease associations based on paths of fixed lengths in a heterogeneous lncRNA-disease association network. Specifically, BPLLDA first constructs a heterogeneous lncRNA-disease network by integrating the lncRNA-disease association network, the lncRNA functional similarity network, and the disease semantic similarity network. It then infers the probability of an lncRNA-disease association based on paths connecting them and their lengths in the network. Compared to existing methods, BPLLDA has a few advantages, including not demanding negative samples and the ability to predict associations related to novel lncRNAs or novel diseases. BPLLDA was applied to a canonical lncRNA-disease association database called LncRNADisease, together with two popular methods LRLSLDA and GrwLDA. The leave-one-out cross-validation areas under the receiver operating characteristic curve of BPLLDA are 0.87117, 0.82403, and 0.78528, respectively, for predicting overall associations, associations related to novel lncRNAs, and associations related to novel diseases, higher than those of the two compared methods. In addition, cervical cancer, glioma, and non-small-cell lung cancer were selected as case studies, for which the predicted top five lncRNA-disease associations were verified by recently published literature. In summary, BPLLDA exhibits good performances in predicting novel lncRNA-disease associations and associations related to novel lncRNAs and diseases. It may contribute to the understanding of lncRNA-associated diseases like certain cancers

Genomic traits of multidrug resistant enterotoxigenic Escherichia coli isolates from diarrheic pigs

Diarrhea caused by enterotoxigenic Escherichia coli (ETEC) infections poses a significant challenge in global pig farming. To address this issue, the study was conducted to identify and characterize 19 ETEC isolates from fecal samples of diarrheic pigs sourced from large-scale farms in Sichuan Province, China. Whole-genome sequencing and bioinformatic analysis were utilized for identification and characterization. The isolates exhibited substantial resistance to cefotaxime, ceftriaxone, chloramphenicol, ciprofloxacin, gentamicin, ampicillin, tetracycline, florfenicol, and sulfadiazine, but were highly susceptible to amikacin, imipenem, and cefoxitin. Genetic diversity among the isolates was observed, with serotypes O22:H10, O163orOX21:H4, and O105:H8 being dominant. Further analysis revealed 53 resistance genes and 13 categories of 195 virulence factors. Of concern was the presence of tet(X4) in some isolates, indicating potential public health risks. The ETEC isolates demonstrated the ability to produce either heat-stable enterotoxin (ST) alone or both heat-labile enterotoxin (LT) and ST simultaneously, involving various virulence genes. Notably, STa were linked to human disease. Additionally, the presence of 4 hybrid ETEC/STEC isolates harboring Shiga-like toxin-related virulence factors, namely stx2a, stx2b, and stx2e-ONT-2771, was identified. IncF plasmids carrying multiple antimicrobial resistance genes were prevalent, and a hybrid ETEC/STEC plasmid was detected, highlighting the role of plasmids in hybrid pathotype emergence. These findings emphasized the multidrug resistance and pathogenicity of porcine-origin ETEC strains and the potential risk of epidemics through horizontal transmission of drug resistance, which is crucial for effective control strategies and interventions to mitigate the impact on animal and human health

A Method of Hybrid Multiple Attributes Group Decision Making with Risk Considering Decision-Makers\u27 Confidence

With respect to different confidence on evaluation result from different decision-makers to the hybrid multi-attribute with risk, an approach to group decision- making based on prospect theory and projection theory is proposed. Firstly, a tuple is established to record the evaluation result and the hybrid decision information. Then the element of the tuple is changed into a single triangular fuzzy number by the transformation rule. Considering the confidence degree from single decision-maker to evaluation information, the group decision information is aggregated and the weights of attributes are calculated based on the intuitionistic fuzzy set theory. The improved projection method and prospect theory are proposed to rank the alternatives respectively. Finally, an application case is given to demonstrate the effectiveness and feasibility of the proposed approach

Development of a DP980 steel with low cooling rate requirement

DP980 is a promising light-weightening material in car body. To avoid high investment of strong cooling system, a new DP980 steel with low cooling rate requirement was developed. The mechanical properties and microstructure were analyzed under different manufacturing process. It could be concluded that the chemical composition design should be reasonable and of low cost to achieve both high strength and also austenite to martensite transformation at low cooling rate. Strength increased with coiling temperature decreasing during hot rolling, and higher annealing temperature and lower over aging temperature were favourable to higher strength. The austenite-martensite transforming could be completed at even lower rapid cooling rate of 20°C/s. Through optimized manufacturing process parameters, the new DP steel product with good mechanical properties could be obtained successfully, which provided a new option for normal production line to produce ultra high strength steel