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Background: This study aimed to identify pathogens and factors that predict the outcome of severe COVID-19 by utilizing metagenomic next-generation sequencing (mNGS) technology. Methods: We retrospectively analyzed data from 56 severe COVID-19 patients admitted to our hospital between December 2022 and March 2023. We analyzed the pathogen types and strains detected through mNGS and conventional microbiological testing and collected general patient information. Results: In this study, 42 pathogens were detected using mNGS and conventional microbiological testing. mNGS had a significantly higher detection rate of 90.48% compared to 71.43% for conventional testing (P=0.026). A total of 196 strains were detected using both methods, with a significantly higher detection rate of 70.92% for mNGS compared to 49.49% for conventional testing (P=0.000). The 56 patients were divided into a survival group (33 cases) and a death group (23 cases) based on clinical outcomes. The survival group had significantly lower age, number of pathogens detected by mNGS, number of pathogens detected by conventional testing, APACHE-II score, SOFA score, high-sensitivity troponin, creatine kinase-MB subtype, and lactate dehydrogenase compared to the death group (P

Aiming at the problem of "fast and precise" in the optimization of joint fire strike scheme, a cross-entropy-quantum particle swarm optimization algorithm is designed, and an intelligent optimization method of joint fire strike scheme based on this algorithm is proposed. The algorithm fully combines the good global optimization ability of the cross-entropy algorithm and the efficient operation of the quantum particle swarm algorithm. By constructing a discrete probability matrix, the uncertain motion of the particles is more directional and the cooperative optimization ability of the particles is improved. The experimental results show that the intelligent optimization method of the joint fire strike scheme based on this algorithm can effectively improve the optimization effect and optimization efficiency of the joint fire strike scheme, and has obvious advantages compared with the standard cross-entropy algorithm and the standard quantum particle swarm optimization algorithm.

The Yushuwan fault is located in the transition zone among the Yimeng uplift, Jinxi fold belt and Shanbei slope in the northeastern Ordos basin and marks the boundary between Palaeozoic and Mesozoic strata. According to the field geological survey and geophysical data, this study shows that the Yushuwan fault is a deep-cut northwest-southeast-oriented strike-slip basement fault. A total of 17 apatite and zircon fission track points show that the basin experienced several stages of uplift at 190 Ma, 150–170 Ma, 110–130 Ma, 60–80 Ma, and 20–40 Ma. The characteristics of the Yushuwan fault indicate that the northeastern part of the basin is not a simple slope but rather a step with a large drop. Therefore, in the area to the southwest of the Yushuwan fault, there should be high natural gas resource potential and good exploration prospects. The contour values of the magnetic anomaly on the southwestern side of the fault are high, and the contours are dense; in contrast, the contour values of the northwest magnetic anomaly are low, and the gradient is gentle. Therefore, the fault represents the eastern boundary of the Yimeng uplift, and restricts the eastward extent of the high magnetic anomaly zone in the Yimeng uplift area. [ABSTRACT FROM AUTHOR]

Compressive mechanical properties of thin-walled hollow spheres structure were researched by experiment and finite element method. Ping-Pong balls were selected and bonded together with a linking neck to comprise the ideal model of thinwalled hollow spheres structure. The experimental result validated the effectiveness of the finite element model. The effects of the material and geometry parameters of the hollow spheres and the linking neck were then investigated by finite element method. The results reveal that:（ 1） the deformation process of the structure includes four stages: elastic deformation,axisymmetric buckling,forming non-axisymmetric polygon and transforming to axisymmetric mode;（ 2） the elastic modulus and yield stress basically increase with the hollow sphere wall thickness,linking neck radius and center thickness as well as the Young’s modulus and yield stress of spheres material;（ 3） the strain of structural self-contact behavior increases with the linking neck center thickness and radius.

Backgroud: The association between thrombomodulin gene (THBD) c.1418 C>T polymorphisms and the risk of venous thromboembolism (VTE) is controversial. The purpose of this meta-analysis was to evaluate THBD c.1418 C>T polymorphisms and the risk of VTE. Methods: Computer searches were performed on the CNKI, Wanfang database, VIP database, PubMed, Embase, Web of Science, and Cochrane Library databases. The retrieval time limit was from the establishment of the database to June 2022. Case-control studies and cohort studies of THBD c.1418 C>T polymorphisms associated with VTE were included. The literature was screened according to inclusion and exclusion criteria, data extraction and literature quality evaluation. Meta-analysis was performed using STATA 14.0 software. Results: A total of 12 literature were included, including 2980 cases in the case group and 3649 cases in the control group. The meta-analysis results showed no significant association of the THBD c.1418 C> T polymorphisms with the occurrence of VTE (T vs C: OR = 1.17, 95%CI = 0.93–1.48; TT vs CT+CC: OR = 1.00, 95%CI = 0.75–1.33; TT+CT vs CC: OR = 1.22, 95%CI = 0.94–1.59). Subgroup analyses revealed an increased risk of VTE in Asian populations due to THBD c.1418 C>T polymorphisms (T vs C: OR = 1.48, 95%CI = 1.06–2.07; TT vs CT+CC: OR = 1.80, 95%CI = 1.13–2.85; TT+CT vs CC: OR = 1.58, 95%CI = 1.07–2.32). THBD c.1418 C>T polymorphisms increased the risk of DVT (T vs C: OR = 1.51, 95%CI = 1.24–1.85; TT vs CT+CC: OR = 1.85, 95%CI = 1.10–3.12; TT+CT vs CC: OR = 1.64, 95%CI = 1.28–2.11). THBD c.1418 C>T polymorphisms reduced the risk of VTE in non-Asian populations (TT vs CT+CC: OR = 0.66, 95%CI = 0.45–0.98). Conclusion: THBD c.1418 C>T polymorphisms is associated with VTE in Asian population, which may be a factor in the occurrence of VTE in Asian population. THBD c.1418 C>T polymorphisms increases the risk of DVT. Given the limitations of this meta-analysis, the conclusions require being further supported by large-scale and high-quality studies. [ABSTRACT FROM AUTHOR]

Accurate prediction of network traffic is very important in allocating network resources. With the rapid development of network technology, network traffic becomes more complex and diverse. The traditional network traffic prediction model cannot accurately predict the current network traffic within the effective time. This paper proposes a Network Traffic Prediction Model----NTAM-LSTM, which based on Attention Mechanism with Long and Short Time Memory. Firstly, the model preprocesses the historical dataset of network traffic with multiple characteristics. Then the LSTM network is used to make initial prediction for the processed dataset. Finally, attention mechanism is introduced to get more accurate prediction results. Compared with other network traffic prediction models, NTAM-LSTM prediction model can achieve higher prediction accuracy and take shorter running time.