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Non-motor vehicles are widely used in the urban and rural transportation system for their portability, but the related violations also occur frequently and are difficult to be supervised intelligently, considering their colossal quantity, various styles, and small volumes. To solve this problem, this paper presents a non-motor vehicle violation detection algorithm with efficient target detection and deliberate logical calculation. A target detection network with high speed and accuracy is constructed firstly by fusing two different types of attention mechanism. Specifically, the Squeeze-and-Excitation Network is employed to optimize the extraction of local features, which can effectively reduce the error rate of target detection. Meanwhile, the Transformer Network is adopted to strengthen the extraction of global features, which can improve the target location performance for target tracking in high-density scenarios. As the global and local features are integrated with attention mechanism, the proposed network can accurately identify and locate the numerous small targets in real-time, and avoid identity switching caused by target occlusion. Finally, the violation of non-motor vehicles is recognized in real-time by constructing the logical calculation between the target features and their motion trajectories. Experiments on datasets show that the detection accuracy of the proposed algorithm is better than the current mainstream algorithms, especially the accuracy of small targets such as Head and Helmet is higher than 92.2%. And our ID Switch is dropped by more than 60% compared with the classical Deep SORT algorithm. In real-life scenarios, the proposed algorithm also shows excellent accuracy and real-time performance for non-motor vehicle violations. &nbsp

In order to analyze the four main properties of propellant, the performance prediction model based on BP neural network is established with LM algorithm and CG algorithm as the core algorithm, and the simulation calculation is carried out with the actual production process data and the performance of the model is analyzed. The results show that the mass prediction model based on BP neural network algorithm can quickly predict the properties of propellant. Compared with the prediction model based on CG algorithm, the prediction model based on LM algorithm is more suitable for propellant performance prediction and analysis.

With abundant oil and gas as well as geothermal resources, Songliao Basin is a famous large continental sedimentary basin in China. So far, the research of geothermal resources in North Songliao Basin has mainly concentrated in the shallow layers where low-temperature geothermal resource is mainly developed. However, the research of deep geothermal resource in high-temperature hot dry rock is still in a blank state. Based on the Songliao Basin exploration and research achievements as well as oil exploration well data, this paper further improves geothermal resource exploration and development theories of North Songliao Basin by researching geothermal resources in high-temperature hot dry rock. Hot dry rock distribution is relatively concentrated in the North Songliao Basin, mainly in the central, southern and southeastern part of the study area, where the depth of 150 ℃ isothermal surfaces substantially less than 5km is conducive to the development of hot dry rocks. Studies have shown that two high value areas of terrestrial heat flow in the North Songliao Basin are respectively located in the southern part of the central depression area as well as the junction of three first-order tectonic belts including central depression, southeast and northeast uplift areas, where geothermal resource potential of hot dry rock is great. By using enhanced geothermal system, mining hot dry rock is feasible. This study has some guidance and reference for the development and utilization of deep geothermal resources in hot dry rock of the North Songliao Basin.

Aims Members of the chromogranin family play a role in angiogenesis. One such biologically active peptide, generated through the processing of chromogranin A, is vasostatin-2. This study aimed at assessing the association of serum vasostatin-2 levels with coronary collateral vessels (CCV) in diabetic patients with chronic total occlusions (CTO) and the effects of vasostatin-2 on angiogenesis in diabetic mice with hindlimb or myocardial ischemia. Methods and results Serum levels of vasostatin-2 in 452 diabetic CTO patients were evaluated. The status of CCV was categorized according to the Rentrop score. Vasostatin-2 recombinant protein or phosphate-buffered saline were then injected intraperitoneally in diabetic mouse models of hindlimb or myocardial ischemia, followed by laser Doppler imaging and molecular biology examinations. The effects of vasostatin-2 were also ascertained in endothelial cells and macrophages, with mechanisms clarified using ribonucleic acid (RNA) sequencing. Serum levels of vasostatin-2 were significantly different and progressively higher across Rentrop score 0, 1, 2, and 3 groups (P < .001), with significantly lower levels in patients with poor CCV (Rentrop score 0 and 1) than in those with good CCV (Rentrop score 2 and 3) (P < .05). Vasostatin-2 significantly promoted angiogenesis in diabetic mice with hindlimb or myocardial ischemia. RNA-seq analyzes verified an angiotensin-converting enzyme 2 (ACE2)-mediated vasostatin-2-induction of angiogenesis in ischemic tissues. Conclusion Lower serum levels of vasostatin-2 are associated with poor CCV in diabetic CTO patients compared with patients with good CCV. Vasostatin-2 significantly promotes angiogenesis in diabetic mice with hindlimb or myocardial ischemia. Such effects are mediated by ACE2.

Developing cooling textiles with unidirectional water transport performances and high thermal conductivities is essential for personal thermal and wet comfort in human activities. We report a green, degradable, hygroscopic cooling material and dual-cooling composite fabric (d-CCF). A boron nitride nanosheet/regenerated flax fiber (BNNS/RFF) material with a high thermal conductivity was prepared by dissolving recovered flax fibers with a green, efficient 1-butyl-3-methylimidazole chloride/dimethyl sulfoxide system and adding BNNSs. The 60- wt% BNNS/RFF materials had excellent thermal conductivity and hydrophilicity, the breaking strength reached 120 MPa, and the elongation was 15.8 %. The d-CCF consisted of cool polyester (CPET) yarn (inner layer), CPET/bamboo composite yarn (middle layer), bamboo yarn, and 60- wt% BNNS/RFF (outer layer) with unobstructed heat dissipation and evaporation cooling for effective moisture and thermal management. This d-CCF had distinct advantages, including a high one-way water transport index (468 %), an extremely high evaporation rate (0.3818 g h

Refereed/Peer-reviewed Improving localization performance is one of the critical issues in Wireless Sensor Networks (WSN). As a range-free localization algorithm, Distance Vector-Hop(DV-Hop) is well-known for its simplicity but is hindered by its low accuracy and poor stability. Therefore, it is necessary to improve DV-Hop to achieve a competitive performance. However, the comprehensive performance of WSN is limited by computing and storage capabilities of sensor nodes. In this paper, we propose an algorithm with parallel and compact techniques based on Whale Optimization Algorithm (PCWOA) to improve DV-Hop performance. The compact technique saves memory consumption by reducing the original population. The parallel techniques enhance the ability to jump out of local optimization and improve the solution accuracy. The proposed algorithm is tested on CEC2013 benchmark functions and compared with some popular algorithms and compact algorithms. Experimental results show that the improved algorithm achieves competitive results over compared algorithms. Finally, simulation research is conducted to verify the localization performance of our proposed algorithm.

Aim of the Review. This study aims to summarize the therapeutic effect of luteolin on the pathogenesis of viral pneumonia, explore its absorption and metabolism in the human body, evaluate the possibility of luteolin as a drug to treat viral pneumonia, and provide a reference for future research. Materials and Methods. We searched MEDLINE/PubMed, Web of Science, China National Knowledge Infrastructure, and Google Scholar and collected research on luteolin in the treatment of viral pneumonia and related diseases since 2003. Then, we summarized the efficacy and potential of luteolin in directly inhibiting viral activity, limiting inflammatory storms, reducing pulmonary inflammation, and treating pneumonia complications. Results and Conclusion. Luteolin has the potential to treat viral pneumonia in multiple ways. Luteolin has a direct inhibitory effect on coronavirus, influenza virus, and respiratory syncytial virus. Luteolin can alleviate the inflammatory factor storm induced by multiple factors by inhibiting the function of macrophages or mast cells. Luteolin can reduce pulmonary inflammation, pulmonary edema, or pulmonary fibrosis induced by multiple factors. In addition, viral pneumonia may cause multisystem complications, while luteolin has extensive protective effects on the gastrointestinal system, cardiovascular system, and nervous system. However, due to the first-pass metabolism mediated by phase II enzymes, the bioavailability of oral luteolin is low. The bioavailability of luteolin can be improved, and its potential value can be further developed by changing the dosage form or route of administration.

This paper develops a distributed fixed-time quadratic coordinated control strategy for isolated DC microgrids with time delays. The proposed control scheme based on the droop control strategy is intended to realize bus voltage recovery and current balance distribution under time delays. We first model the isolated DC microgrids as a single integrator system with input delays by the Artstein’s transform. The current balance and voltage recovery are achieved by using fixed time control, which does not depend on the initial state of the system. Based on the Lyapunov functional method, the stability analysis criterion of the system is derived. In order to verify the effectiveness of the proposed control method, the DC microgrid system is simulated in Matlab/Simulink.

How to respond effectively and efficiently to students’ writing and to maximize the potential of feedback to promote student writing skills deserves careful consideration. The use of intelligent algorithms to assist teachers in the manual evaluation of students’ essays is of practical value and importance in the context of "artificial intelligence + education". The existing intelligent evaluation techniques are subject to the interference of many factors such as openness of questions and students' language expression abilities. For this reason, this study conducts a study on comprehensive essay evaluation method with intelligent assistance and manual feedback and on reliability and validity tests. Before the intelligent evaluation, the semantic integrity of students' essays is analyzed, and a semantic integrity analysis model of students' essays based on BERT model is constructed. A fusion similarity algorithm for essay answer key points is proposed by extracting these characteristics that have an impact on the evaluation results, such as technique preferences, paragraph content and paragraph topic of the essays. The Siamese and ESIM networks are combined to propose an intelligent evaluation model for students’ essays, and the model framework and working principle are described in detail. The experimental results verify the effectiveness of the constructed model.

To inhibit the growth of bacteria, the DA-PPI nanozyme with enhanced peroxidase-like activity was synthesized. The DA-PPI nanozyme was obtained by depositing high-affinity element iridium (Ir) on the surface of Pd-Pt dendritic structures. The morphology and composition of DA-PPI nanozyme were characterized using SEM, TEM, and XPS. The kinetic results showed that the DA-PPI nanozyme possessed a higher peroxidase-like activity than that of Pd-Pt dendritic structures. The PL, ESR, and DFT were employed to explain the high peroxidase activity. As a proof of concept, the DA-PPI nanozyme could effectively inhibit E. coli (G−) and S. aureus (G+) due to its high peroxidase-like activity. The study provides a new idea for the design of high active nanozymes and their application in the field of antibacterial.

Diamagnetic levitation is a physical phenomenon that uses the diamagnetism of diamagnetic materials to stably levitate itself in an external strong magnetic field, which has great potential in the areas of sensors, actuators, and biomedicine. In this paper, a typical diamagnetic levitation system composed of a NdFeB permanent magnet array and pyrolytic graphite sheet is built. The levitation mechanism of the diamagnetic levitation system is analyzed theoretically, the main factors affecting the static levitation of the pyrolytic graphite sheet are determined, and the influence of structural parameters on the levitation height of the pyrolytic graphite sheet is studied. Furthermore, the dynamic and numerical simulation models of the diamagnetic levitation system are established, and the dynamic response characteristics of the pyrolytic graphite sheet are analyzed under different vibration excitation. This study provides a reference for developing applications based on the diamagnetic levitation system.