bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Influence of Outward Bound Training Based on Data Analysis in College Physical Training
Authors: Wang Diliang , Huang Guoyang
Published: September 2022

The competition for talents in the modern society is constantly intensifying. College students not only have good physical and psychological quality but also bear hardships and stand hard work and adapt to the fast-paced working environment in order to adapt to the development of the times. With the advent of the era of big data, advanced technology has been applied to physical exercise and development, providing opportunities and challenges for the development of sports. Therefore, this paper focuses on the impact of expanding training on college sports training through extensive surveys on college students’ outward bound training. The results show that data are the key data of analysis, which can be used to analyze college students’ physical functions and other indicators scientifically and effectively. Universities should develop appropriate outward bound training according to the characteristics of the students themselves. The project helps to improve the sports performance and psychological and physical quality of college students. We hope to provide theoretical reference for experts and scholars who study the development of college sports.
[Retracted] Meta‐Analysis of Long‐Term Efficacy of Proliferative Diabetic Retinopathy Based on Intelligent Medical Treatment
Authors: Fang Fang , Cao Yanjie , Chen Keyan , Su Xingjie , Qi Yanxiu , Zhang Di , Liu Hongwei
Published: September 2022

In order to solve some problems of subhealth and high chronic diseases, the diagnosis and treatment of value‐added diabetic retinopathy are studied. In particular, diabetes, a high chronic disease, poses a great threat to people’s health. With the continuous improvement of national health awareness, the medical field also begins to pay more attention to the diagnosis and treatment of value‐added diabetic retinopathy. In order to improve the long‐term treatment of value‐added diabetic retinopathy through intelligent medical monitoring and systematic scientific efficacy analysis and evaluation, the purpose of this study is to explore how to effectively achieve the meta‐analysis of long‐term efficacy of proliferative diabetic retinopathy through intelligent medical treatment. Through the study of diabetic retinopathy, the system can help doctors to achieve unlimited further signs of parameter acquisition and transmission and build more mature after treatment of the results of the monitoring platform. At the same time, a conclusion based on vitrectomy was proposed to effectively improve the surgical efficacy of patients with proliferative diabetic retinopathy.
The Design of Critical Care Information System Supporting Clinical Decision Based on Deep Learning Recognition Method
Authors: Lu Qian , Zhao Wei , Li Zhongpeng , Liu Ranfeng
Published: September 2022

In recent years, the clinical decision support system (CDSS) has been gradually improved, which effectively reduces the probability of doctors’ misdiagnosis or missed diagnosis. Therefore, the clinical decision support system has always been a research hotspot, deep learning and collaborative filtering technologies are developing rapidly, and more and more are applied to different fields. Based on the deep learning technology, this paper conducts in-depth research on the methods of assisted diagnosis of clinical diseases and prediction of clinical high-risk diseases in the field of CDSS. Aiming at the problem of clinical decision support system, this article analyzes the deep learning identification method in depth and is committed to applying machine deep learning to clinical decision-making, changing the lack of information and its challenges to clinical decision-making. Based on previous studies, two unsupervised learning methods based on machine learning are proposed, namely user collaborative filtering and RBM, to improve CDSS. The experimental results show that the overall performance of the RBM-based method is the best. When the missing degree of the two data sets is 30.6%, the classification accuracy rate is still more than 92.8%.
Application and Performance Discussion of Fiber-Reinforced Composite Materials in Sports Equipment Based on Image Processing Technology
Authors: Liu Erwei
Published: September 2022

Fiber reinforced composites can meet the needs of lightweight, heavy load, long-span, high strength, and modern structures and work under strict conditions. Therefore, it is widely used in various fields. Sports equipment generally cannot meet the requirements of high-strength use, so there is an urgent need for new fiber materials to make these instruments. Aiming at improving the efficiency of measurement and the reliability of measurement results, this paper studies the quantitative characterization method of the microstructure of short fiber reinforced composites. The swept-frequency OCT system is a newly developed high-resolution biomedical imaging system. The method of this paper is to study the performance parameters of swept frequency OCT system, deduce the application of image processing technology in fiber material detection, and then study the detection of residual strength and residual stiffness of composites, so as to obtain a composite material detection method that can be popularized. On this basis, image processing and performance analysis of the composites were carried out, and the composites were tested. And the prospect of application in this field has been analyzed. The experimental results show that better fiber length can be obtained by this method, and the maximum relative error is only 4.5%, thus ensuring the accurate determination of fiber length. Calculations were carried out using the experimental data, and the results showed that the performance of the sports product increased from 15.4% to 48.6% with the graphite-rubber composite. Using this material can improve the comprehensive performance of sports equipment by 2.1%∼4.5%.
Emei Martial Arts Promotion Model and Properties Based on Neural Network Technology
Authors: Xing Cheng , Abidin N.E. Zainal , Tang Yudong
Published: September 2022

China unanimously believed that Emei Martial Arts has the essence of self-improvement. It is a spiritual force that actively promotes human progress. It should be protected and continuously innovated to make it a spiritual pillar of people. However, its promotion faces huge challenges. In recent years, neural networks have made great progress in various fields, such as speech recognition, computer vision, and natural language understanding. On this basis, the combination of neural networks and traditional recommendation methods is helpful for the better development of Emei Martial Arts promotion. Neural networks have a direct analog interaction function and perform coordinated filtering directly through interactive data. Due to the effectiveness of the structure, the neural network can mine nonlinear implicit relationships from the data and find the martial arts items that users want to promote. In order to enhance the effectiveness of the standard recommendation algorithm, a deep neural network-based recommendation algorithm is paired with a neural network-based recommendation algorithm that is proposed in this article. The recall rate of the upgraded deep neural network recommendation model is up to 80%, whereas the recall rate of the model without enhancement is up to 40%, according to the experimental results of this article. The upgraded deep neural network’s recommendation model has a recall rate that is 4% greater than the baseline model. It showed that the recommendation algorithm combined with a neural network has a better recommendation effect so as to achieve a better effect of Emei Martial Arts promotion so that Emei Martial Arts culture can be carried forward and economic development can be promoted at the same time.
Almost Bronze Structures on Differentiable Manifolds
Authors: Özkan Mustafa , Doğan Seher
Published: September 2022

This study introduces a novel structure that is not included in the metallic structure family. This new structure, which is called an almost bronze structure, has been defined using a (1,1) type tensor field φ which fulfills the requirement φ2 = mφ − Id on a differentiable manifold. We investigated the parallelism and integrability conditions of these almost bronze structures by use of an almost product structure corresponding to them. Also, we have defined an almost bronze Riemannian manifold.
Optimization of Synthesis Conditions of β‐FeOOH Nanorods towards Antimicrobial Benefits
Authors: Mohammadi Fatemeh , Amiri Salme , Mirzaei Esmaeil , Gholami Ahmad
Published: September 2022

FeOOH nanoparticles have recently appealed to wide‐ranging applications due to their physicochemical properties and size‐tunable synthesis; however, a few studies were performed on the antimicrobial potentials of iron oxyhydroxide nanoparticles. In this regard, we aimed to design various synthesis experiments to optimize the fabrication of β‐FeOOH nanorods (NRs) with a desirable size of NRs and high antimicrobial potential. For this purpose, ten experiments were designed by manipulating reaction conditions of the standard hydrolysis method, including the initial concentration of ferric ions, reaction time, reaction temperature, and different concentrations of surfactants of PEI and PEG as process control agents. The structural characteristics of prepared NRs were analyzed using FE‐SEM, FTIR, and XRD. The ImageJ software was also used to measure the length, width, and aspect ratio of NRs. Five microbial species, including the Gram‐positive and Gram‐negative bacteria and fungi species, were applied to investigate the antimicrobial potentials of NRs. The initial concentration of ferric ions revealed a dominant effect in NRs’ morphology, though other reaction conditions also played essential roles. The crystal structure of NRs was preserved in all synthesis experiments (β‐phase) due to using the same iron salt precursors. The synthesized NRs exhibited dose‐dependent antimicrobial activities against all tested microbial species. Additionally, the presence of surfactants exhibited an excellent capability of controlling effects on the size and growth pattern of NR crystals and improving their antimicrobial potentials; PEI could also be more effective on the antimicrobial efficacy of final NRs. Besides, our findings exhibited an inverse correlation between aspect ratio and antimicrobial potentials of β‐FeOOH NRs. To sum up, it seems that optimization of synthesis conditions could provide tunable size and structure patterns of β‐FeOOH NRs to achieve a promising tool for biomedical applications, particularly in combat with resistant microbial species, though further studies are needed in this regard.
Influence of Continuous Nursing Intervention on Treatment Compliance of Patients with Depression
Authors: He Yanfang , He Jie , Hou Xueyuan
Published: September 2022

Objective. This study mainly discusses the influence of the continuous nursing intervention on the treatment compliance of patients with depression. Methods. The clinical data of 120 patients with depression admitted to our hospital were collected by retrospective analysis. According to the different implementation of nursing methods, patients were subordinated to the conventional group (n = 48, conventional nursing) and the continuous group (n = 72, continuous nursing). The treatment compliance, depression degree, quality of life, nursing satisfaction, Insight and Treatment Attitude Questionnaire (ITAQ), and recurrence rate of patients in the two groups were compared. Results. The continuous group had a higher treatment compliance rate, slighter depression, higher physiological function, psychological function, social function, environmental adaptability, total quality of life, nursing satisfaction, and ITAQ score, and lower recurrence rate, with statistically significant differences (

P
<
0.05

). Conclusion. The implementation of continuous nursing intervention for patients with depression could enhance their treatment compliance and relieve depressive symptoms; improve the quality of life and self-awareness; reduce the risk of relapse; and improve nursing satisfaction.
Tribological Behavior of AA7075 Reinforced with Ag and ZrO2 Composites
Authors: Mahesha C. R. , R Suprabha , Sree Jayan M. Mahaveer , Kulkarni Shilpa , Sharma Aman , Al-Ammar Essam A. , Mohammed S. M. A. K. , Subbiah Ram , Alemayehu Agonafir
Published: September 2022

In this study, an AA7075 composite material with a varying weight percentage of silver and zirconium oxide reinforcement is examined in terms of its properties. Reinforcement quantities ranging from 0, 4, 8, 12, and 16 wt % were combined with the matrix using the in-situ technique of stir casting in the field. Tensile, mechanical hardness, and compressive strength were assessed in accordance with the standard. The X-ray diffraction and EDS were utilized to analyze AA7075 composites for the distribution and dispersion of particles. Different input parameters such as load (N), composites (wt %), and velocity (m/s) were used to evaluate wear resistance when using the pin-on-disc method. The wear rate (mm/m) was estimated for every weight percent of reinforced mass loss (g). Optimization methods such as Taguchi and analysis of variance were used to determine the AA7075’s optimal processing parameters and composites that were the most significant. In order to identify the best genetic algorithm results, theoretical and experimental results were evaluated.
Performance Analysis of Underwater Wireless Sensor Network by Deploying FTP, CBR, and VBR as Applications
Authors: Sathish K. , Ravikumar C. V. , Srinivasulu Asadi , Gupta Anand Kumar
Published: September 2022

Oceans cover more than 75% of the planet’s land surface, making it the most water-rich place on the Earth. We know very little about oceans because of the extraordinary activities that take place in the depths. Underwater wireless sensors are devices that are able to monitor and record the physical and environmental parameters of their surroundings, as well as transmit these data in a continuous manner to one of the source sensors. The network that is formed by the collection of these underwater wireless sensors is referred to as an underwater wireless sensor network (UWSN). The analysis of performance parameters is thought to be most effectively done with this particular technology. In this paper, we will investigate various performance parameters in a random waypoint mobility model by shifting the maximum speed of a node and altering the number of nodes in the model. These parameters include average transmission delay, average jitter, average pathloss, percentage of utilization, and energy consumed in transmit, receive, and idle modes. The QualNet 7.1 simulator is utilized in order to conduct analyses and performance studies.
Security Analysis on Blockchain-Powered Mobile APPs Connected with In-Vehicle Networks by Context-Based Reverse Engineering
Authors: Wu Xingyu , Qiao Ziyan , Cai Xingjuan , Wang Qian , Xie Zhiqiang , Sun Rui , Zi Dong , Niu Wenjia , Tong Endong
Published: September 2022

The controller area network (CAN) bus for interconnection of electronic control units (ECUs) plays a highly important role in modern intelligent vehicles. To facilitate the CAN Bus accessing to vehicle control or diagnosis, a number of mobile APPs are designed and published by automobile manufacturers to support driving and vehicle-based social network, and some are realized through the in-vehicle infotainment (IVI) middleware. Blockchain technologies are also mature for automobiles to interact service information with the whole industry. Unfortunately, there is a serious threat of command leakage from these mobile APPs, and the reverse engineering (RE) can be exploited by hackers. Previous work has researched this threat by an automatic reverse engineering tool on both automotive android and IOS APPs. However, in such common tool, APP itself-related contexts, including the feature information of CAN Bus commands, vehicle application functions, and control diagnostic protocols, are overlooked, which might be utilized to promote the reverse engineering recall. In this paper, we propose a context-based reverse engineering approach to find deep hidden commands for further revealing security threats for blockchain-powered mobile automotive APPs. For the reverse engineering, we design a context model of four-order tensor to organize multidimensional contexts and establish a continuous updating mechanism. Based on the context model, we further develop two basic analysis algorithms, max-compute (A) and clustering (A), to perform the analysis of CAN Bus commands. Extensive experiments are conducted, and we evaluate it by two metrics, recovered ratio and correctness ratio. Experimental results and the case studied on the familiar APP Carly validate the effectiveness of our approach and reveal the threat of command leakage.
Prevalence and Risk Factors for Allergic Rhinitis in China: A Systematic Review and Meta-Analysis
Authors: Pang Kaiyun , Li Guodong , Li Mouhan , Zhang Lan , Fu Qinwei , Liu Kepu , Zheng Wei , Wang Zhiqiao , Zhong Juan , Lu Lijin , Li Peijia , Zhou Yucan , Zhang Wanling , Zhang Qinxiu
Published: September 2022

The prevalence of allergic rhinitis (AR) has increased tremendously in the recent year in China. Evidence-based medicine to objectively evaluate the prevalence and risk factors for AR in China is urgently required. Toward this, we systematically searched four English and four Chinese databases to identify the literature on the same, from the year of website establishment until November 2021. A total of 51 studies were evaluated, and data were obtained through Stata 16 analysis. Overall pooled risk factors for adult AR were smoking (odds ratio [OR] = 1.89, 95% confidence interval [CI]: 1.25, 2.87), asthma (OR = 3.30, 95% CI: 1.48, 7.39), a family history of AR (OR = 3.17, 95% CI: 2.31, 4.34), a family history of asthma (OR = 3.99, 95% CI: 2.58, 6.16), drug allergy (OR = 1.62, 95% CI: 1.38, 1.89), food allergy (OR = 2.29, 95% CI: 1.39, 3.78), pollen allergy history (OR = 2.41, 95% CI: 1.67, 3.46), antibiotic use (OR = 2.08, 95% CI: 1.28, 3.36), occupational dust exposure (OR = 2.05, 95% CI: 1.70, 2.47), home renovation (OR = 1.73, 95% CI: 0.99, 3.02), and middle school education (OR = 1.99, 95% CI: 1.29, 3.06). Overall pooled risk factors for AR in children were passive smoking (OR = 1.70, 95% CI: 1.02, 2.82), asthma (OR = 3.26, 95% CI: 2.42, 4.39), a family history of AR (OR = 2.59, 95% CI: 2.07, 3.24), a family history of allergy (OR = 4.84, 95% CI: 3.22, 7.26), a history of allergic diseases (OR = 2.11, 95% CI: 1.52, 2.94), eczema(OR = 2.29, 95% CI: 1.36, 3.85), owning pets (OR = 1.56, 95% CI: 1.37, 1.77), eating seafood (OR = 1.30, 95% CI: 1.10, 1.55), boys (OR = 1.58, 95% CI: 1.43, 1.74), and breastfeeding (OR = 0.82, 95% CI: 0.55, 1.22). The results of our meta-analysis showed that the prevalence of allergy rhinitis was 19% (95% CI 14–25) among adults and 22% (95% CI 17–27) among children, with boys showing a higher prevalence than girls. The development of AR in China is associated with several factors, including allergic diseases (eczema, asthma, pollen allergy, and food allergy), a family history of allergy (AR, asthma, and other allergies), and dwelling and working environment (smoking or passive smoking, occupational dust exposure, and owning pets); conversely, breastfeeding can reduce the risk.
Validation of a Simple Score for Mortality Prediction in a Cohort of Unselected Emergency Patients
Authors: Busch Jeannette-Marie , Arnold Isabelle , Kellett John , Brabrand Mikkel , Bingisser Roland , Nickel Christian H.
Published: September 2022

Background. Prognostication is an important component of medical decision-making. A patients’ general prognosis can be difficult to measure. The Simple Prognostic Score (SPS) was designed to include patients’ age, mobility, aggregated vital signs, and the treating physician’s decision to admit to aid prognostication. Study Aim. Our study aim is to validate the SPS, compare it with the Emergency Severity Index (ESI) regarding its prognostic performance, and test the interrater reliability of the subjective variable of the decision to admit. Methods. Over a period of 9 weeks all patients presenting to the ED were included, routinely interviewed, final disposition registered, and followed up for one year. The C-statistics of discrimination was used to compare SPS and ESI predictions of 7-day, 30-day, and 1-year mortality. Youden J Statistics and Odds ratio, using logistical regression, were calculated for the Simple Prognostic Score. In a subset, a chart review was performed by senior physicians for a secondary assessment of the decision to admit. Interrater reliability was calculated using percentages and Cohens Kappa. Results. Out of 5648 patients, 3272 (57.9%) had a low SPS (i.e., ≤ 1); none of these patients died within 7 days, 2 (0.1%) died within 30 days after presentation and 19 (0.6%) died within a year. The area under the curve for 1-year mortality of the Simple Prognostic Score was 0.848. Secondary analysis of the interrater agreement for the decision to admit was 92%. Conclusion. In a prospective study of unselected ED patients, the Simple Prognostic Score was validated as a reliable predictor of short- and long-term mortality.
Application of BIM Digital Information Technology in the Economic Optimization Operation of Integrated Energy Systems
Authors: Bu Jingjing
Published: September 2022

Energy is an important support for national economic development, and energy security directly affects national security, sustainable development, and social stability. The Middle East has the largest energy reserves in the world. Saudi Arabia is located in the Middle East and is a big energy country with very rich resources. With the reduction of fossil fuels and the increasingly prominent problem of climate change, the sustainable supply of energy while reducing environmental pollution and economic costs in the process of energy use is a problem facing the world today. In order to fully absorb clean energy, improve energy efficiency, and reduce fuel costs and environmental costs, we studied the impact of BIM digital information technology on the economic optimization of integrated energy systems. The integrated energy system has the characteristics of multienergy input and multienergy output. In terms of energy output, the system uses the principle of energy cascade utilization to recover and utilize the waste heat generated by the traditional generator set and then collects it through absorption. Compared with the traditional single-stage utilization of energy, the integrated energy system uses various forms of power, for example, power, heating, cooling, and natural gas, to achieve economic optimization by improving the comprehensive energy utilization efficiency through multienergy complementation. Through the investigation and comparison of the optimal dispatching operation cost, energy use cost, pollutant treatment cost, and equipment maintenance cost of 3 enterprises, the results show that the comprehensive energy system using BIM digital information technology can reduce the energy use cost by 8.7%. Moreover, the cost of pollutant treatment and the cost of equipment maintenance have been reduced to a certain extent, which has a certain optimization effect on the economy of comprehensive energy of enterprises.
Logistic Distribution Route Optimization Based on RFID and Sensor Technology
Authors: Ma Xuan , Wang Fan
Published: September 2022

In order to solve the problem that the traditional e-commerce logistic distribution path optimization algorithm takes a long time to find the optimal path, this paper presents the best ways for exporting based on RFID and sensor technology. First, the integration algorithm is used to divide the logistic area; then, the purpose of various goals to improve the performance of the export consists of five things: measuring weight, measuring time, measuring the importance of customers, window measuring time, and general measurement method. Finally, determine the weight distribution target and find ways to better the target according to the differences in e-commerce logistics to improve the efficiency of e-commerce logistic distribution methods. Experimental results show that the optimal time to find the optimal method is less than 2 minutes, while the custom algorithm takes 3 minutes to find the optimal method. Conclusion. The logistic distribution optimization algorithm based on RFID and sensor technology takes less time to find a better way than the traditional process and can meet the needs of e-commerce logistic distribution layer standard optimization.
[Retracted] Development of University Music Education Based on Neural Network and the Reform of Music Education in Normal University under the Environment of Ability Education
Authors: Dai Jinlai
Published: September 2022

Competency education has grown in importance as a component of music education in teachers’ colleges in the modern era. This essay conducts a thorough investigation into the evolution of college music education and the reform of music education at teachers’ universities based on the notion of competency education. This essay highlights the crucial role that music education plays in competence education, with aesthetics at its center. It also examines the crucial part that music education plays in developing college students’ all‐round abilities. This study evaluates the reform process and current state of the music education curriculum system in teachers’ universities based on these factors as well as the development trend of modern music curriculum reform, and it suggests various reform avenues. Additionally, a model for assessing the degree of music instruction is built in this research using the NN (Neural network) technique. This work employs MATLAB for empirical research in order to validate the validity of the method. According to experimental findings, this algorithm’s evaluation accuracy can reach 96.11%, which is almost 13% greater than that of the conventional NN technique. The outcomes demonstrate the accuracy and dependability of this methodology. This study is intended to serve as a reference for the advancement of collegiate music education as well as the reform and innovation of music in teacher education programs.
Xiang Qin Kang Gan Granules Treated the Human Coronavirus 229E Induced Pneumonia with Damp-Heat Syndrome in Mice
Authors: Cao Fang , Liu Zhaoheng , Hao Qingxun , Zhao Ronghua , Bao Lei , Cui Xiaolan , Jiao Yang
Published: September 2022

Coronavirus disease 2019 (COVID-19), which causes severe respiratory illness, was first reported in Wuhan, China. The etiology of the disease is a new novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was reported to share the same origin as SARS-CoV, causing severe public health events in 2002. Unlike the SARS-CoV, which was conquered in the early summer of 2003, this virus was still contagious widely and reached a pandemic level. It can still spread fast even if the season’s temperature is raised. Here, we made a model of pneumonia of human coronavirus 229E (HCoV-229E) with damp-heat syndrome treated by Xiangqin Kanggan granules to find a new medicine for treating these kinds of infectious diseases coronaviruses induced.
Exploration of Cross-Border Language Planning Using the Graph Neural Network for Internet of Things-Native Data
Authors: Long Juan
Published: September 2022

This work aims to study applying the graph neural network (GNN) in cross-border language planning (CBLP). Consequently, following a review of the connotation of GNN, it puts forward the research method for CBLP based on the Internet of Things (IoT)-native data and studies the classification of language texts utilizing different types of GNNs. Firstly, the isomorphic label-embedded graph convolution network (GCN) is proposed. Then, it proposes a scalability-enhanced heterogeneous GCN. Subsequently, the two GCN models are fused, and the research model-heterogeneous InducGCN is proposed. Finally, the model performances are comparatively analyzed. The experimental findings suggest that the classification accuracy of label-embedded GNN is higher than that of other methods, with the highest recognition accuracy of 97.37% on dataset R8. The classification accuracy of the proposed heterogeneous InducGCN fusion model has been improved by 0.09% more than the label-embedded GNN, reaching 97.46%.
Differential Privacy Protection for Support Vector Machines for Nonlinear Classification
Authors: Huang Yuxian , Yang Geng , Bai Yunlu , Dai Hua
Published: September 2022

Currently, private data leakage and nonlinear classification are two challenges encountered in big data mining. In particular, few studies focus on these issues in support vector machines (SVMs). In this paper, to effectively solve them, we propose a novel framework based on the concepts of differential privacy (DP) and kernel functions. This framework can allocate privacy budgets and add artificial noise to different SVM locations simultaneously, which makes the perturbation process freer and more delicate. In addition, under this framework, we propose three algorithms, DP SVMs that perturb the training data set, perturb the kernel function, and utilize mixed perturbation (DPSVM-TDP, DPSVM-KFP, and DPSVM-MP, respectively), all of which can realize accurate classification while ensuring that the users’ privacy is not violated. Moreover, we conduct privacy analysis on these algorithms and prove that they all satisfy

ε
,
0

−

DP. Finally, we conduct experiments to evaluate the algorithms in terms of different aspects and compare them with the DPSVM with dual-variable perturbation (DVP) algorithm (DPSVM-DVP) to determine the optimal perturbation method. The results show that DPSVM-KFP can achieve the highest data utility and strictest privacy protection with the shortest running time.
Deep Learning Analysis of English Education Blended Teaching in Virtual Reality Environment
Authors: Wu Wen , Qiu Chen
Published: September 2022

The rapid development of computer software and hardware, network technology, and various Internet platforms has brought mankind into a new era. In recent years, “virtual reality” can be regarded as a huge hot spot, whether in the field of industry, education, or research. At present, although the heat has subsided a little, the technical teams involved in various fields are also working collectively to continuously innovate. Based on the mixed teaching mode of English education, this article conducts in-depth research on deep learning and virtual reality technology, integrates deep learning and virtual reality learning environment, and builds a learning model of English education learning environment based on virtual reality. The teaching design of the course aims to fully combine the main content of deep learning with the virtual reality environment. Through experimental research, it is explored whether the learning environment based on virtual reality can promote deep learning. The relevant data of the experimental class and the control class are collected through questionnaires, starting from the four dimensions of motivation dimension, investment dimension, strategy dimension, and result dimension, and conduct a comparative analysis, and use the auxiliary interview method to understand the experience of students and teachers on virtual reality equipment and put forward relevant suggestions.
Artificial Intelligence-Based Soccer Sports Training Function Extraction: Application of Improved Genetic Algorithm to Soccer Training Path Planning
Authors: Zhang Weiwei
Published: September 2022

Artificial intelligence has given a new dimension to the sport and mentality of soccer by tracking and planning the path of soccer and analyzing the learning process. Along with the rapid development of artificial intelligence technology, it is also used in sports events. Soccer, the world’s number one ball game, has always received worldwide attention. Although soccer is full of realism, it does not mean that its behavior cannot be predicted. By taking advantage of the role of artificial intelligence, model data from training is used to perform a deeper analysis of the correlated role of a soccer team’s players in the game, which is very helpful to improve the team’s training efficiency and tactics. As an emerging intelligent algorithm, the improved genetic algorithm can seek the global optimal solution based on the results of the algorithm execution and apply it to the planning of soccer training paths, which has a strong application value for improving the team’s training level and helping the team to formulate reasonable and effective offensive and defensive strategies. In this paper, we use artificial intelligence as the research background to improve the genetic algorithm by extracting the soccer training function and apply the improved algorithm to the soccer training path planning to get the global optimal solution, so as to help the players find the reasonable and effective optimal path of passing or shooting and help the team to build the tactical planning and winning strategy of offense and defense to meet the earnest expectation of soccer fans.
The Effects of Magnesium Borate Whiskers on the Mechanical Performance of Oil Well Cement
Authors: Gao Xianshu , Zhou Ping , Qin Xiaoliang , Wen Zhaijun , Wang Jing , Wang Hao , Li Ming , Zhuang Jia , Li Chengxin
Published: September 2022

Quasi-brittle behaviors of cement-based material can be reinforced through diverse methods due to its unique multiscale features. Among them, reinforcing agents are the most direct and effective means, such as slag, metakaolin, and fly ash. These materials can improve the performance of cement stone to a certain extent, but their chemical composition is still mainly silica, which does not in essence change the defects of cement. Therefore, in this experiment, magnesium borate whisker (Mg2B2O5) was used as reinforcer of 90°C class G oil well cement and magnesium borate whisker reinforced cement-based material (MBWRC) was prepared. On the one hand, the performance of mechanical strength was controlled, and the resistance to compression, traction, and bending was included. Furthermore, static stress-strain behaviors analysis and toughness behaviors analysis (dynamic multicycle loading test) were further conducted. Second, mercury intrusion porosimetry (MIP) and scanning electron microscope (SEM) were used to test the characteristics of pores and interfaces of cement-based materials. Through multiscale microstructure analysis, MBWRC was found to have excellent 90°C mechanical performances when compared to control sample’s, for which tensile strength increased to 235% of controlled sample’s, and flexural strength increased to 130%, plus a healthy developed compressive performance, and MBWRC showed much denser pore structure, in which harmless micropore increased from 13.3% to 14.40%, porosity decreased from 17.01% to 16.20%, and permeability decreased from 0.2533% to 0.0205%. Furthermore, MBWRC showed resistance capability to mechanical loading, which can be attributed to the formation of denser pore structure and more excellent mechanical performance.
Analysis of the Factors Influencing the Adaptability of College English Learning Based on Artificial Intelligence Teaching Assistance
Authors: Cao Lingmei , Zhu Shuxian
Published: September 2022

Good learning adaptability is the key to ensure students’ learning quality. Learning maladjustment not only affects students’ learning effect but also affects the effectiveness of AI-enabled English learning. Although some studies have found that there is a certain degree of poor learning adaptability in the practice of artificial intelligence (AI) supporting English teaching, most studies only describe the phenomenon and do not further explore the causes of poor learning adaptability. Therefore, the research intends to understand the current situation of college students’ English learning adaptability under the support of AI through the investigation and analysis of college students’ English learning adaptability under the support of AI and clarifies the impact of various influencing factors on learning adaptability as well as the relationship between learning adaptability and various factors, and put forward strategies to improve students’ learning adaptability. This research is a new exploration of learning adaptability in the field of AI English learning. At the same time, it is also an extension of the research environment of learning adaptability in information-based learning and a supplement to the research results. This paper combs the composition structure of college students’ English learning adaptability under the support of AI and constructs the influencing factor model of college students’ English learning adaptability under the support of AI. The research has certain theoretical significance and practical value.
Establishing a Novel Gene Signature Related to Histone Modifications for Predicting Prognosis in Lung Adenocarcinoma
Authors: Liu Mengfeng , Yu Xiran , Xu Shidong , Qu Changfa
Published: September 2022

Background. Epigenetic modifications have been revealed to play an important role in tumorigenesis and tumor development. This study aims to analyze the role of histone modifications and the prognostic values of histone modifications in lung adenocarcinoma (LUAD). The promoters and enhancers of protein encoding genes (PCGs) were the regions of enriched histone modifications. Methods. Expression profiles and clinical information of LUAD samples were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Histone modification data of LUAD cell lines were downloaded from Encyclopedia of DNA Elements (ENCODE) database. Limma R package was used to identify differentially expressed PCGs. To identify molecular subtypes, consensus clustering was conducted based on the expression of dysregulated PCGs with abnormal histone modifications. Univariate Cox regression analysis and stepwise Akaike information criterion (stepAIC) were utilized to establish a prognostic model. Results. We identified a total of 699 epigenetic dysregulated genes with 122 of them significantly correlating with LUAD prognosis. We constructed three molecular subtypes (C1, C2, and C3) based on the 122 prognostic genes. C2 had the longest overall survival while C1 had the worst prognosis. In addition, three subtypes had differential immune infiltration and the response to immune checkpoint inhibitors. Moreover, we identified a risk model containing 5 epi-PCGs that had favorable performance to predict prognosis in different datasets. Conclusions. This study further supported the critical histone modifications in LUAD development. Three subtypes may provide guidance for the immunotherapy of LUAD patients. Importantly, the prognostic model had great potential to predict LUAD prognosis.
A Systematic Review and Meta-Analysis of the Efficacy of Uterine Artery Embolization in the Treatment of Endometriosis
Authors: Ma Li , Wen Bingxin , Wen Zhenhua
Published: September 2022

Objective. To compare the efficacy of uterine artery embolization (UAE) with traditional methods for treating endometriosis. Methods. The randomized controlled trials of uterine artery embolization and other medical treatments for endometriosis in PubMed, Embase, Web of Science, Cochrane Library, China Journal Full-Text Database, Wanfang Database, VIP Database, and China Biomedical Literature Database were retrieved by computer. The search time was up to June 2022. The quality of articles was evaluated by Cochrane ROB 2.0, and meta-analysis was performed by Stata15.1 software. Results. 7 studies were finally included. Meta-analysis showed that the serum CA125 level after uterine artery embolization was significantly lower than that in the control group (SMD = −0.85, 95%CI (−1.12, −0.59)], and the postoperative visual analogue scale (VAS) of dysmenorrhea was significantly lower than that in the control group (SMD = −1.86, 95%CI (−2.21, −1.50)) There was no significant difference in the effective rate, FSH level, E2 level, and LH level between the two groups. Conclusion. UAE can effectively reduce the VAS score of dysmenorrhea and serum CA125 level for treating endometriosis. However, due to the limitation of the quality of included articles, more large sample size and high quality RCTs are needed to provide stronger evidence-based medicine evidence for clinical practice.
A Multiuser Ciphertext Search Scheme Based on Blockchain and SGX
Authors: Wang Lianhai , Liu Fengkai , Meng Lingyun , Shao Wei , Xu Shujiang , Zhang Shuhui , Huang Donghui
Published: September 2022

To ensure the security of data, more and more users encrypt data for storage, which makes the high-efficiency ciphertext search problem in the context of cloud storage a research hotspot. Existing solutions still suffer from many vexatious problems, such as the need to maintain complex index structures and the unsatisfactory application of homomorphic schemes. To solve the above problems, this paper proposes a multiuser ciphertext search scheme based on blockchain and SGX. Our scheme uses blockchain and SGX to protect keywords and data privacy and complete decryption and keywords search of ciphertext data which does not need pregenerated indexes or preselected keywords. Second, for a multiuser scenario, a smart contract is designed to verify authorization requests and manage multiple authorized users. Finally, we give security analysis, function comparison, and performance analysis to prove the security and feasibility of our scheme. Experiments show that our scheme has effectively met practical requirements.
[Retracted] TJZYF Improves Endometrial Receptivity through Regulating VEGF and PI3K/AKT Signaling Pathway
Authors: You Fang , Du Xin , Zhang Taiwei , Wang Yang , Lv Yuxia , Zeng Li
Published: September 2022

The endometrium receptivity was impaired by controlled ovarian hyperstimulation (COH), which would then lead to fertility issues and increased abortion clinically. In the present study, to explore the effectiveness of Tiaojing Zhuyun Formula (TJZYF) in improving endometrial receptivity of COH rats and the possible active ingredients and mechanisms, an approach of network pharmacology was performed and a COH animal model was established. As analyzed, stigmasterol and quercetin may be the active ingredients of TJZYF on improving endometrial receptivity and positive regulation of ion transport, the cytokine‐mediated signaling pathway, and endocrine process, and vascular endothelial growth factor receptor signaling pathway may be involved. Eighty female rats were divided into four groups randomly: control, model, TJZYF, and TJZYF+si‐VEGFA. COH rat models were constructed by injecting with human menopausal gonadotropin (HMG) and human chorionic gonadotropin (HCG). We found that both endometrial thickness and number of embryo implantations in model were substantially reduced vs. control. The gene and protein expressions of VEGF, PI3K, and p‐Akt in the uterus were significantly reduced. TJZYF could increase the endometrial thickness and number of embryo implantations and enhance the expressions of VEGF, PI3K, and p‐Akt in the uterus. In the TJZYF+si‐VEGFA group, the effect of TJZYF was impaired. Generally, TJZYF could improve the endometrium receptivity and facilitate embryo implantation of COH rats by upregulating VEGF and enhancing the PI3K/Akt signaling pathway.
Tissue-Welding Device: Considerable Advantages for Spleen Surgery Based on Histological and Cardiorespiratory Investigation
Authors: Gatiņa Linda , Piginka-Vjaceslavova Inga , Bērziņa Dace , Zolovs Maksims
Published: September 2022

During splenic surgery, it is important to control blood loss and the potential risk of cardiac arrhythmia. The best way to prevent complications from surgery is to use the appropriate surgical devices; however, there is no guideline for the use of specific surgical devices for spleen incision. Therefore, the aim of this research was to compare the interactions of various surgical devices with spleen tissue, their cardiorespiratory effects during incision, and subsequent spleen surgical wound healing. A total of 75 rabbits were included in the study. CO2 laser (n = 15), radiofrequency device (n = 15), electrocoagulator (n = 15), tissue-welding device (n = 15), and scalpel (n = 15) were used to make incisions in rabbits' spleens. Spleen biopsies of the incision area were taken from each animal at the day 0, 7, and 14 after surgery. Contactless thermography was performed during surgery. Suturing was not used after incision with the tissue-welding device, but incisions made by other surgical devices were sutured. The results showed that the width of spleen necrosis differed significantly between the various surgical devices used on spleen tissues. There was a positive, strong, and linear association between necrosis width and the tissue temperature of cutting edges. Significant increases in the heart rate were observed during spleen surgery performed with laser, scalpel, and radiofrequency devices. In conclusion, the tissue-welding device confers a significant advantage in spleen surgery, as there is neither a need for sutures nor a significant deviation in the heart rate.
Prevalence, Antimicrobial Resistance, and Associated Factors of Streptococcus pneumoniae Colonization Rate among Old-Age Patients with Respiratory Tract Infection Attending Sheik Hassan Yebere Referral and Karamara General Hospitals, Jigjiga, Ethiopia
Authors: Mekuria Surafel , Seyoum Ayichew , Ataro Zerihun , Abebe Tigist , Urgessa Kedir
Published: September 2022

Background. Streptococcus pneumoniae is part of the normal flora of the upper respiratory tract of humans. Colonization of the upper respiratory tract (carriage of pneumococcus) by S. pneumoniae is considered a prerequisite for pneumococcal infection. It is the major cause of respiratory tract infection and frequent cause of physician visits, hospitalization, and death among old-aged patients because of their low immunity status. However, data on S. pneumoniae among old-aged patients in eastern Ethiopia are limited. This study was undertaken to determine the prevalence, antimicrobial resistance, and associated factor of S. pneumoniae colonization among old-aged patients. Method. A health facility-based cross-sectional study was conducted from 1 March to 15 April 2020, at Sheik Hassan Yebere Referral and Karamara General Hospitals, Jigjiga, eastern Ethiopia. A total of 188 individuals greater than or equal to 60 years suspected of both upper and lower respiratory tract infections were included. Sociodemographic, behavioral, living conditions, and clinical data were collected by trained data collectors. Sputum samples were collected and examined for S. pneumoniae using the culture and biochemical tests as per the standard procedures. The Kirby–Bauer disk diffusion method was used for antimicrobial susceptibility testing. The data were entered on Epi-data version 3.1, and frequencies, crude odds ratio, and adjusted odds ratio were analyzed using SPSS version 20. Results. The prevalence of S. pneumoniae colonization rate among old-aged patients was 13.8% (26/188) (95% CI: 9.6–19.1). Smoking (AOR = 3.3; 95% CI: 1.3–8.3), upper airway problems (AOR = 4.1; 95% CI: 1.1–15), and asthma disease (AOR = 3.1; 95% CI: 1.1–8.9) were the factors associated with S. pneumoniae colonization. The isolated organisms showed high antimicrobial resistance to trimethoprim-sulphamethoxazole (n = 12, 46.2%), tetracycline (n = 11, 42.3%), and ampicillin (n = 9, 34.6%). Conclusion. This study showed that high prevalence of S. pneumoniae and antimicrobial resistance for trimethoprim-sulphamethoxazole, tetracycline, and ampicillin when compared to similar studies. Cigarette smoking, having upper airway problem, and asthma disease were factors associated with S. pneumoniae colonization. The provision of pneumococci conjugate vaccination and avoiding smoking are highly recommended for old aged in the community.