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With the increasingly busy operation of civil aviation airspace,how to build an effective and reasonable mathematical model from the perspective of quantitative analysis to quantify the risk of route flight collision and improve the scientific nature of route planning and management is a problem faced by the industry. A risk assessment method of vertical collision during route flight based on improved Event model is proposed. In this method,the cuboid collision box in the original event model is replaced by two spliced elliptic cone collision boxes which conform to the velocity vector distribution of the aircraft in space to calculate the probability of the aircraft passing through the adjacent altitude layers. The vertical collision risk formula of the aircraft in the improved route is derived by using the area size ratio of the improved front and rear collision boxes. The collision risk parameters obtained by formula are verified. The results show that the vertical collision risk calculated by the improved method is about 13% of the original cuboid event model and 67% of the original ellipsoid event model. It is feasible to use this method for quantitative evaluation.

In this paper, a data-driven framework aimed at investigating how weather factors affect the spatio-temporal patterns of air traffic flow in the terminal maneuvering area (TMA) is presented. The framework mainly consists of three core modules, namely, trajectory structure characterization, flow pattern recognition, and association rule mining. To fully characterize trajectory structure, abnormal trajectories and typical operations are sequentially extracted based on a deep autoencoder network with two specially designed loss functions. Then, using these extracted elements as basic components to further construct and cluster per-hour-level descriptions of airspace structure, the spatio-temporal patterns of air traffic flow can be recognized. Finally, the association rule mining technique is applied to find sets of weather factors that often appear together with each flow pattern. Experimental analysis is demonstrated on two months of arrival flight trajectories at Hong Kong International Airport (HKIA). The results clearly show that the proposed framework effectively captures spatial anomalies, fine-grained trajectory structures, and representative flow patterns. More importantly, it also reveals that those flow patterns with non-conforming behaviors result from complex interactions of various weather factors. The findings provide valuable insights into the causal relationships between weather factors and changes in flow patterns, greatly enhancing the situational awareness of TMA. [ABSTRACT FROM AUTHOR]

Current research on apron conflict detection is often limited to the interaction between the aircraft as a whole and other objects, making it difficult to accomplish targeted identification of vulnerable and high‐cost aircraft components. However, the implementation of detailed aircraft identification is of great significance to enhance the safety of airport surface operations. Based on the excellent performance of High‐Resolution Network (HRNet) in keypoint detection, a lightweight end‐to‐end keypoint detection network, namely Squeeze and Excitation High‐Resolution Network (SEHRNet), is proposed in this paper to solve the problems of HRNet's slower computation and more redundancy. First, the errors arising from coordinate transformations in the coding and decoding process are solved by an improved feature map coding and decoding process. Second, replace the BasicBlock in HRNet with the Depthwise separable convolutions based on the Squeeze‐and‐Excitation Networks, which drastically cuts the computational cost of the network. Third, the improved Bottleneck module is used to further enhance the capability of feature extraction. Experimental results prove that, based on the aircraft keypoint detection dataset, the SEHRNet proposed in this paper shows stronger applicability compared to the current mainstream networks. Compared with the original HRNet, the improved network has higher accuracy, faster speed, and lighter model for aircraft keypoint detection. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is an autoimmune disease that significantly impacts quality of life by disrupting CD4+ T cell immune homeostasis. The identification of a low-side-effect drug for RA treatment is urgently needed. Our previous study suggests that Trichinella spiralis paramyosin (Ts-Pmy) has immunomodulatory effects, but its potential effect on CD4+ T cell response in RA remains unclear. In this study, we used a murine model to investigate the role of rTs-Pmy in regulating CD4+ T cell differentiation in collagen-induced arthritis (CIA). Additionally, we assessed the impact of rTs-Pmy on CD4+ T cell differentiation towards the Th1 and Th17 phenotypes, which are associated with inflammatory responses in arthritis, using in vitro assays. The results demonstrated that rTs-Pmy administration reduced arthritis severity by inhibiting Th1 and Th17 response while enhancing Treg response. Prophylactic administration of Ts-Pmy showed superior efficacy on CIA compared to therapeutic administration. Furthermore, in vitro assays demonstrated that rTs-Pmy could inhibit the differentiation of CD4+ T cells into Th1 and Th17 while inducing the production of Tregs, suggesting a potential mechanism underlying its therapeutic effects. This study suggests that Ts-Pmy may ameliorate CIA by restoring the immune balance of CD4+ T cells and provides new insights into the mechanism through which helminth-derived proteins exert their effects on autoimmune diseases. [ABSTRACT FROM AUTHOR]

Narrow-headed softshell turtles constitute a group of critically endangered freshwater turtles that belong to the family Trionychidae. Here, we determine the complete mitogenome of the Burmese narrow-headed softshell turtle Chitra vandijki. The length of the mitochondrial genome was 16,614 bp, composed of 13 protein-coding genes, 22 tRNA genes, two rRNA genes, and twelve noncoding regions. The phylogenetic analysis strongly indicated that C. vandijki is closely related to C. indica. The mitochondrial genome will contribute to the genetic research and conservation of C. vandijki in the future.