bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Design of Assistant Basketball Teaching System Based on Big Data
Authors: Wang Lin , Wei Xiaoyun , Yuan Guoliang
Published: May 2022

Due to the limitations of the current teaching resources searched by the system, it is difficult to achieve good results in basketball teaching. For this reason, an auxiliary basketball teaching system based on big data is designed. On the basis of clarifying the basic principles of teaching system design, JSP (Java Server Pages) dynamic web page back-end technology and Tomcat 7.0 server are used as the system support structure. Take the big data environment as the source of teaching resources and match them to different databases according to the characteristics of the resources. And combined with real-time evaluation to achieve the assessment of teaching effects and the management of teaching resources, the test results show that the average score of the basketball technical action test under the guidance of this system is higher than 7.5 points when the experimental subjects have the same level of basketball skills. In the paired sample t-test and the independent sample t-test of the performance level test scores

P
=
0.001
<
0.05

, there is a significant difference. It shows that the system can effectively improve the teaching effect of basketball and improve students’ basketball test scores.
Privacy Protection Technology Based on Machine Learning and Intelligent Data Recognition
Authors: liu Qiang
Published: May 2022

The machine learning algorithm is gradually being applied to various fields and has become the core technology to achieve artificial intelligence. The success of machine learning cannot be achieved without the support of large amounts of data and computing power, which are usually collected through crowdsourcing and learned online. The data collected for machine learning training often contains some personal and sensitive information, including personal mobile phone numbers, ID numbers, and medical information. How to protect these private data at low cost and efficiently is an important problem. Aiming at this kind of problem, this article starts with the privacy problem in machine learning and the way of being attacked and summarizes the privacy protection methods and characteristics in the machine learning algorithm. Then, for the classification accuracy of the different algorithm that uses noise to protect privacy, a deep difference privacy protection method combined with a convolutional neural network is proposed. This method perfectly integrates the features of difference and Gaussian distribution and can obtain the privacy budget of each layer of the neural network. Finally, the stochastic gradient descent algorithm's gradient value is employed to set the Gaussian noise scale and preserve the data's sensitive information. The experimental results demonstrated that by adjusting the parameters of the depth differential privacy model based on differences in private information in the data, a balance between the availability and privacy protection of the training data set could be reached.
Vehicle Re-Identification System Based on Appearance Features
Authors: Xu Dawei , Yang Yunfan , Zhu Liehuang , Dai Cheng , Chen Tianxin , Zhao Jian
Published: May 2022

Aiming at the low recognition accuracy caused by the problems of angle, illumination, and occlusion in vehicle re-identification based on deep learning, a vehicle re-identification method based on multibranch network feature extraction and two-stage retrieval feature is proposed. The multibranch feature extraction module uses ResNet-50 as the backbone network to extract the vehicle’s attribute features and apparent features, respectively, and uses the attribute features for rough retrieval. On this basis, the attribute features and apparent features are fused for fine retrieval. Through experiments, the accuracy of vehicle re-identification on Veri-776 data set and VehicleID datasets is significantly improved. In addition, based on the improved algorithm, this paper designs and develops a vehicle re-identification system, which realizes the functions of inputting file directory, selecting target image, and querying result image, and provides a visual technical scheme for vehicle re-identification and retrieval in the real scene.
Effect of miR-488 on Colon Cancer Biology and Clinical Applications
Authors: Wu Liangqin , Li Songguo , Shu Peng , Liu Qian
Published: May 2022

Objective. To explore the expression levels of miR-488, miR-29c-3p, and growth differentiation factor 15 (GDF15) in colon cancer tissue and analyze their relationship with clinicopathological features in patients with colon cancer. Methods. The study was conducted from November 2012 to November 2020. A total of 200 patients with colon cancer were treated in our hospital during this period. During the operation, the colon cancer tissues and the adjacent tissues whose distance from the cancer tissues were more than 5 cm were collected, and the expression levels of miR-488, miR-29c-3p, and GDF15 mRNA in colon cancer tissues were detected by qRT-PCR (real-time fluorescence quantitative). The relationship between them and the clinicopathological features and prognosis of patients with colon cancer were analyzed and discussed. Results. The level of miR-488 in colon cancer tissues was lower than that in adjacent tissues, but the levels of miR-29c-3p and GDF15 mRNA in colon cancer tissues were higher than those in adjacent tissues (

P
<
0.05

). Compared with paracancerous tissues, the expression rates of miR-29c-3p and GDF15 protein were higher in colon cancer tissues (

P
<
0.05

). There was no difference in age, sex, tumor location, and tumor diameter between high expression of miR-488 group and low expression of miR-488 group (

P
>
0.05

). The degree of differentiation, depth of invasion, TNM stage, lymph node metastasis, and other factors have a direct impact on the level of miR-488 and the expression of miR-29c-3p (

P
<
0.05

). The depth of invasion, TNM stage, and lymph node metastasis could affect the expression of GDF15 in patients with colon cancer (

P
<
0.05

). Conclusion. miR-488, miR-29c-3p, and GDF15 in colon cancer tissue are related to the clinicopathological features of patients in varying degrees and may become markers after early warning of colon cancer, which can provide effective guidance for clinical diagnosis and treatment.
Research on Solving Postdisaster Material Distribution and Scheduling with Improved NSGA-II Algorithm
Authors: Huo Li , Wang Jiayu
Published: May 2022

After the occurrence of major sudden disasters, the dispatching and distribution of disaster relief materials are particularly important, but in the process of distribution, there may be excessive distribution of similar emergency materials, unbalanced distribution volume of relief materials in different disaster-affected points, high distribution cost, and low effective distribution rate. In order to solve the above problems, based on the application of big data, this paper proposes a three-level network postdisaster material scheduling and distribution model and an improved NSGA-II algorithm. The model takes the loss degree of the disaster area and the dynamic change rate of the demand for postdisaster relief materials as the constraints, takes the demand prediction of postdisaster relief materials, the optimization of distribution path, distribution nodes, and the satisfaction of victims as the objectives, and designs the sample average approximation method and the improved NSGA-II algorithm. In order to verify the effectiveness of the proposed model and strategy, through the comparative experiment of NSGA and PSO, it can be seen from the experimental results that the three-level network allocation model and the improved NSGA-II algorithm (nondominated sorting genetic algorithm II) proposed in this paper can not only solve the existing postdisaster relief material allocation and scheduling problem but also reduce the space-time complexity of the problem.
circPTP4A2-miR-330-5p-PDK2 Signaling Facilitates In Vivo Survival of HuMSCs on SF-SIS Scaffolds and Improves the Repair of Damaged Endometrium
Authors: Zheng Yuanyuan , Li Linhao , Bi Xuewei , Xue Ruyue
Published: May 2022

Background. Human umbilical cord mesenchymal stem cells- (HuMSCs-) based therapy has shown promising results in the treatment of intrauterine adhesions (IUA). In this study, we aimed to construct a HuMSCs-seeded silk fibroin small-intestinal submucosa (SF-SIS) scaffold and evaluate its ability to repair the damaged endometrium in an IUA mouse model. Methods. To identify the functional effect of HuMSCs-SF-SIS scaffolds on the repair of damaged endometrium, a mouse IUA model was established. Uterine morphology and fibrosis were evaluated by hematoxylin-eosin staining and Masson staining. CircRNA sequencing, real-time PCR, and RNA fluorescence in situ hybridization were used to screen and verify the potential circRNAs involved in the repair of damaged endometrium by HuMSCs. Real-time integrated cellular measurement of oxygen consumption rate was performed using the Seahorse XF24 Extracellular Flux Analyzer. The potential downstream miRNAs and proteins of circRNAs were analyzed by dual-luciferase reporter assay and western blot. Results. HuMSCs-SF-SIS not only increased the number of glands but also reduced the ulcer area in the IUA model. circPTP4A2 was elevated in the HuMSCs seeded on the SF-SIS scaffolds and was targeted by miR-330-5p-PDK2. It also stabilized the mitochondrial metabolism of HuMSCs. Moreover, miR-330-5p was found to inhibit PDK2 expression through the 3

′

UTR target region. A rescue experiment further showed that circPTP4A2-miR-330-5p-PDK2 signaling was critical to HuMSCs-SF-SIS in decreasing the fibrosis area and increasing the number of glands in the IUA model. Conclusion. We demonstrated that circPTP4A2 was elevated in HuMSCs-seeded on SF-SIS scaffolds and stabilized the mitochondrial metabolism through miR-330-5p-PDK2 signaling, which contributes to endometrial repair progression. These findings demonstrate that HuMSCs-seeded SF-SIS scaffolds have potential for the treatment of IUA.
The Influence of the Different Cementitious Material on Self-Healing of Microcracks in Shotcrete
Authors: Zhang Junru , Dai Yi , Xu Jian , Feng Jimeng , Ma Kaimeng
Published: May 2022

Due to a particular construction process, the shotcrete structure is affected by external load, material aging, and external temperature during use, with cracks inevitably appearing. Cracks are formed from microstate gradually, and thus controlling the development of microcracks in the early phase can effectively improve the strength and impermeability of shotcrete. In this study, the method of laboratory experiment and analysis is adopted to study the effect of ettringite on achieving the self-healing effect of shotcrete. The test results show that: (1) after encountering water, ettringite effectively plays a microexpansion effect to fill the pores, helping shotcrete achieve the effect of waterproofing and self-healing, which is very suitable for single-layer lining structures with water seepage. (2) The content of ettringite is inversely proportional to the change law of pore structure. When the content of ettringite increases, the porosity and harmful pores proportion have a significant decrease. (3) Fly ash and mineral powder with a mixing amount of about 30% will not affect the strength of the concrete, while prolonging the time of the effect of ettringite, will effectively improve the impermeability of the shotcrete.
Design and Simulation of Silicon-Based Suspension Beams for Various MEMS Sensors
Authors: Taj Mohammad , Pitchaiah Telagathoti , Sasikumar Bashyam
Published: May 2022

This paper mainly concentrates on finding maximum displacement and Eigen frequency for microelectromechanical system (MEMS) inertial sensors with various beam structures. In this work, six different shapes of beams are attached with one set of electrodes to find which structure exhibits the maximum displacement with less cross-axis displacement and to observe the operating frequency. The momentum of the beams is directly proportional to the thickness and length, which provides the maximum flexibility to produce momentum on proof mass. The beam thickness is 5 um for all proposed sensors and the momentum has been observed by changing different shapes of beam structures. The momentum occurred on proof mass due to applied physical energy. The same amount of physical energy is applied to all structure and the momentum, quality factor, and displacement are measured which had been compared and the table is given.
Measurement, Evaluation, and Model Construction of Mathematical Literacy Based on IoT and PISA
Authors: Chen Yunfeng
Published: May 2022

“Mathematics Curriculum Standard for Ordinary Senior High School” points out that mathematical modelling literacy is the literacy of abstracting real problems mathematically, expressing problems with mathematical language, and building models with mathematical methods to solve problems. It assesses the amount to which students who are about to finish compulsory schooling have the knowledge and aptitude to deal with future life issues, based on the notion of lifelong learning. The usage of a local integrated development environment requires a number of complex processes, including installation and setup, as well as the procurement of necessary hardware. In reality, in order to nurture students, the core literacy of mathematics is to completely execute quality education, further identify the training and development direction of talents, and infiltrate the core literacy material into junior high school mathematics classroom instruction. For such a large-scale international education measurement project, the research and development of test questions is very important. Therefore, detailed technical consideration has been carried out and test volumes have been designed that are relatively suitable for different countries. The test questions are closely related to life, while there are few questions related to real situational problems in the test, which are mathematically processed first. Due to the international background of evaluation, it is a great challenge for researchers to realize the localization of evaluation on the basis of adapting to the domestic situation. At the same time, there is no scientific and perfect mathematical modelling literacy evaluation system in China’s basic education research. How can middle school front-line teachers better evaluate students’ mathematical modelling literacy? As a result, it is critical to develop a scientific and quantitative mathematical literacy measurement model that will aid in the teaching and research of mathematical modelling by middle school front-line teachers, as well as contributing theoretically to the evaluation and research of mathematical modelling literacy in China. Therefore, based on mathematics literacy evaluation, this paper studies the hierarchy of the IoT and the measurement and evaluation model of mathematics literacy based on the IoT, as well as its enlightenment to the compilation of mathematics academic test questions in China.
Analysis of Teaching Effect of English Classroom Mind Map Based on a Logistic Regression Model
Authors: Deng Yan , Zhu Rui
Published: May 2022

In order to improve the effect of English classroom teaching, this paper combines the pulse neural network to identify the teaching process of English classroom and conducts real-time supervision of classroom dynamics in combination with the actual situation. Moreover, this paper constructs an intelligent system, uses the recognition method based on the spiking neural network image to collect the real-time dynamics of classroom teaching, and combines the logistic regression model to evaluate the teaching effect. After constructing the system framework, the system process analysis is carried out. This paper combines experimental research to verify the model of this paper. The experimental research results show that the analysis model of teaching effect of mind map in English classroom based on the logistic regression model proposed in this paper has good results, which also verifies that the mind map teaching can play an important role in English classroom teaching.
Link Security Situation Identification Method Based on the Ad Hoc Network of Medical Units
Authors: Zeng Yifu , Chen Qingquan , Yao Ling , Zhuang Jiajing , Huang Zhixuan , Huang Shuhan , Zeng Honghua , Zhong Riguang
Published: May 2022

In order to strengthen the management and security status monitoring of the internal network of medical units and make up for security vulnerabilities in time, an ad hoc network link security situation identification method is proposed. According to the architecture of the ad hoc network, it is analyzed that it has the advantages of strong persistence and its own protocol. Combined with the data of detection equipment and security log, the hierarchical acquisition model is used to obtain the situation elements such as port scanning attack and flood attack. The transmission rate factor, forwarding rate factor, dispersion factor, and node aggregation factor are regarded as eigenvectors. We determine the relationship between identity, difference, and opposition, identify the security situation through the description of the node state, and conduct quantitative processing to obtain the final identification result. The experimental results show that the weight value of this method is the same as the standard weight, which can identify the security situation level, obtain the specific situation value, and present a more intuitive identification result.
Prefix-Pruning-Based Distributed Frequent Trajectory Pattern Mining Algorithm
Authors: Ding Jiaman , Li Yunpeng , Li Ling , Jia Lianyin
Published: May 2022

An important problem to be solved in smart city construction is how to improve the efficiency of mining frequent patterns that can be used for location prediction and location-based services of massive trajectory datasets. Owing to uncertain personal trajectory and non-explicit trajectory items, the existing sequence mining algorithms cannot be used directly. To solve this problem, this study proposes a distributed trajectory frequent pattern mining algorithm (SparkTraj) based on prefix pruning. First, a grouping and partitioning technique is used to abstract the original trajectory data and convert them into a common time series.Then, the generation of a redundant trajectory pattern is avoided by using the path adjacency pruning method. Second, to improve mining efficiency, SparkTraj is designed and implemented in Spark, which employs cluster memory computing. Finally, experiments on common datasets show that the proposed algorithm can effectively extract frequent trajectory patterns, and, in particular, deal with the massive amounts of trajectory data. Compared with common trajectory pattern mining algorithms, the SparkTraj algorithm not only improves the overall performance but also has good scalability.
Toxicological Assessments of a Proprietary Blend of Punica granatum Fruit Rind and Theobroma cacao Seed Extracts: Acute, Subchronic, and Genetic Toxicity Studies
Authors: Madireddy Ravi Kumar , Alluri Krishnaraju Venkata , Somepalli Venkateswarlu , Golakoti Trimurtulu , Sengupta Krishanu
Published: May 2022

LN18178 (Tesnor®) is a standardized, proprietary composition of aqueous ethanol extracts of Punica granatum fruit rind and Theobroma cacao seeds. The present study demonstrates a broad-spectrum toxicological evaluation of LN18178 utilizing in vitro and in vivo preclinical models following the Organization for Economic Cooperation and Development (OECD) guidelines for testing chemicals. Wistar rats did not show any clinical signs of toxicity and morbidity in acute oral and dermal toxicity tests with the median lethal dose (LD50) values of at least 5000 mg/kg and 2000 mg/kg body weight, respectively. LN18178 was nonirritating to the skin and eyes of the treated rabbits. In a ninety-day subchronic repeated oral dose toxicity study, the LN18178-treated Wistar rats did not show dose-related signs of toxicity on their body weight, food consumption, organ weights, hematology, and clinical chemistry parameters. The estimated no-observed-adverse-effect level (NOAEL) of LN18178 in male and female rats was 2500 mg/kg body weight. The observations from the bacterial reverse mutation test, in vitro chromosomal aberration assay, micronucleus assay in mouse bone marrow erythrocytes, and in vitro mouse lymphoma TK+/− gene mutation assay suggest that LN18178 is neither mutagenic nor clastogenic. In summary, the present study demonstrates that oral consumption of the herbal blend LN18178 does not show signs of toxicity; also it does not elicit genetic toxicity in the standard preclinical models.
Design of Online Learning Early Warning Model Based on Artificial Intelligence
Authors: Zhang Tao , Xiao Wenxing , Hu Ping
Published: May 2022

Students have produced a large number of learning logs and a large number of educational data through online learning. In order to extract useful information from these massive information, support teachers’ teaching activities, improve teaching quality, provide learners with personalized learning support, and teach students according to their aptitude, educational big data analysis has attracted extensive attention of educators. Under the impact of informatization, education and information technology are deeply integrated, and network education is in the ascendant. At the same time, the theories and methods of artificial intelligence are gradually applied to the field of education. Learning analysis, data mining, and other analysis methods provide effective analysis methods for online learning process and learning effect. This paper studies the design of online learning early warning model based on artificial intelligence. When the system is implemented, based on the existing evaluation index system, the online learning early warning model of analytic hierarchy process is introduced to give different evaluation indexes unequal weights to ensure the fairness of evaluation. On the basis of understanding the artificial intelligence algorithm, the corresponding detection indicators should also be selected according to the objectives of the online learning early warning model and the needs of the actual work of network operation and maintenance. Then, follow the corresponding data flow of artificial intelligence technology and analyze data preprocessing, feature selection, and model training.
Finite-Time Synchronization of Fractional-Order Complex-Valued Cohen-Grossberg Neural Networks with Mixed Time Delays and State-Dependent Switching
Authors: Li Xiaoxia , Cao Yingzi , Zheng Chi , Feng Zhixin , Xu Guizhi
Published: May 2022

This paper discussed the finite-time synchronization of fractional-order complex-valued Cohen-Grossberg neural networks (FCVCGNNs), which contain mixed time delays and state-dependent switching that make the model more comprehensive. Different from other methods, we use a method of nonseparating real and imaginary parts to get our conclusions. By applying fractional-order inequalities and the Lyapunov function, effective controllers with suitable conditions are derived. Additionally, the maximum time for the drive-response system to reach synchronization is also given. Finally, numerical examples are designed to illustrate the effectiveness of our obtained theoretical results.
Dynamic Risk Assessment of Karst Tunnel Collapse Based on Fuzzy‐AHP: A Case Study of the LianHuaShan Tunnel, China
Authors: Yu Yongyan , He Xiaobin , Wan Fei , Bai Zhe , Fu Chongtao
Published: May 2022

Tunnel collapse in the karst tunnel occurs suddenly. Dynamic risk assessment for tunnel collapse is more accurate than static analysis, which is not enough at the stage. The study designs a new questionnaire to establish dynamic risk assessment for karst tunnels collapse, by a fuzzy analytic hierarchy process (F‐AHP) method. The characteristics of the cave, dynamic monitoring, and prediction are fully considered in the assessment to strengthen the karst and dynamic characters: (1) the factors of dynamic risk assessment are selected based on advanced geological prediction, collapse investigation, and theoretical analysis as dynamic and static factors. Dynamic factors are classified as the rationality of advanced geological prediction method, reliability of data, the accuracy of data analysis, and timeliness and effectiveness of forecast information transmission. Karst cave characteristic factors are composed of cave scales, locations, and thickness of rock plate, based on collapse investigation and theoretical analysis to strengthen the character of karst. (2) A new questionnaire is designed in the consulting process to express the relative importance of factors by combining a Saaty scale method and a designed three‐scale method. The judgment matrix by the new questionnaire can satisfy the consistency requirement, which is hard to satisfy in the traditional F‐AHP method. (3) The dynamic risk assessment is carried out on different samples in the Lianhuashan tunnel. By comparing the dynamic assessment results with the occurrence of disasters, the rationality of the assessment is verified.
Effects of Glimepiride Combined with Recombinant Human Insulin Injection on Serum IGF-1, VEGF and TRACP-5b Oxidative Stress Levels in Patients with Type 2 Diabetes Mellitus
Authors: Chen Xue , Kang Sheng , Bao Zeqing
Published: May 2022

Objective. This study was designed to explore the effect of glimepiride combined with recombinant human insulin injection on serum insulin-like growth factor 1 (IGF-1), vascular endothelial growth factor (VEGF), tartrate-resistant acid phosphatase 5b (TRACP-5b) and oxidative stress levels in patients with type 2 diabetes. Methods. A total of 217 patients with type 2 diabetes who were treated in our hospital from November 2018 to March 2020 were selected and divided into control group and treatment group. The control group was treated with glimepiride (n = 107). The study group was given glimepiride and recombinant human insulin injection) (n = 107). The levels of blood glucose, blood lipids, IGF-1, VEGF, TRACP-5b, and oxidative stress in the two groups were measured, respectively. We summarize the main results as follows. Insulin resistance index (HOMA-IR), fasting blood glucose (FPG), 2h postprandial blood glucose (2hBG), serum glycated hemoglobin (HbA1c), triglyceride (TG), total cholesterol (TC), serum malondialdehyde (MDA), reactive oxygen species (ROS), VEGF, and TRACP-5b levels were significantly lower than those before treatment, and the degree of reduction in the study group was greater than that in the control group

P
<
0.05

. The levels of insulin (INS), insulin beta cell function index (HOMA-beta), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and IGF-1 were significantly higher than those before treatment. Further, the study group demonstrated better results than the control group

P
<
0.05

. Conclusion. Glimepiride combined with recombinant human insulin injection can improve insulin sensitivity, reduce insulin resistance, significantly reduce glucose and lipids in patients, reduce the occurrence of oxidative stress, promote the secretion of oxidative resistance enzymes, lower the vascular endothelial growth factor (VEGF), reduced the formation of new blood vessels, and inhibit the growth and metastasis of cancer cells. Additionally, we found out that glimepiride combined with recombinant human insulin injection had a good prognosis for patients; it significantly reduced the bone resorption marker TRACP-5b and prevented the occurrence of complications such as osteoporosis. The combined use of the two is more effective than glimepiride alone. In conclusion, glimepiride combined with recombinant human insulin injection has higher application value in the treatment of patients with type 2 diabetes.
Control Algorithm for Trajectory Tracking of an Underactuated USV under Multiple Constraints
Authors: Wang Hongbin , Dong Jiao , Liu Zhikun , Yan Li , Wang Shiqi
Published: May 2022

A trajectory tracking control method based on the cascade of optimal guidance and adaptive control laws was proposed for trajectory tracking of an unmanned surface vehicle under multiple motion constraints including an ocean current disturbance environment. Considering the velocity and acceleration constraints, angular velocity, and angular acceleration constraints in guidance law design, motion planning was conducted with three degrees of freedom using a motion model and predictive control, while optimal guidance law was designed through a rolling optimization strategy to stabilize the position error under multiple constraints. Moreover, the stability of the guidance law was proven. In control law design, an adaptive observer was introduced to estimate and compensate for ocean current disturbance, which affected the precision of control. The course and velocity control laws were designed with the adaptive sliding mode control technology to stabilize the course angle and longitudinal velocity errors; the stability of these control laws was further proven. Based on the system design, the stability of the entire closed-loop control system was proven with the cascade system and Lyapunov theory. Theoretical analysis and simulation experiments demonstrated the effectiveness and advancement of the proposed algorithm.
Berlin and Epworth Surveys to Predict Obstructive Sleep Apnea for Adults on Biomimetic Oral Appliance Therapy: A Nonrandomized Clinical Trial
Authors: Al Mortadi Noor , Khassawneh Basheer , Khasawneh Lina , Alzoubi Osama , Alzoubi Karem H.
Published: May 2022

Background. Two questionnaires (Berlin Questionnaire (BQ) and Epworth Sleepiness Scale (ESS)) are the widely used screening instruments for subjects suffering from sleep disorders. Obstructive sleep apnea (OSA) is the most common form of sleep-disordered breathing. The biomimetic oral appliance therapy (BOAT) offers an alternative nonsurgical method, which can improve symptoms and indices of OSA on objective sleep testing. Aim. To describe testing the ability of BQ and EES for prediction of BOAT outcomes during OSA. Methods. Seventeen adults (9 males, 8 females; age, mean (SD): 45.76 (10.31), BMI mean (SD): 33.5(13.43)) who underwent an overnight sleep study were diagnosed by a sleep specialist physician. The BQ and EES were recorded before and after BOAT treatment. Subjects with mild-to-moderate OSA had 2 months of follow-up visits and underwent a final overnight sleep study to measure apnea-hypopnea index (AHI). The subjects were asked to wear the appliance for 10–12 hours/day and at night. Findings were analyzed statistically using paired t-tests. Result. As per sleep test results, pre-BOAT AHI measures versus post-BOAT AHI measures showed significant improvement. Comparing the BQ before versus after treatment showed that at the pretreatment stage, 66.0% of patients had high-risk score, whereas 34% had low-risk score. After treatment, 66.0% of patient had low-risk scores, whereas 34% had high-risk scores. As for the ESS, treatment resulted in significant reduction of total score from 10.43 ± 6.32 to 5.00 ± 5.20 (

P
<
0.01

, paired t-test). Finally, there was a mild negative correlation between AHI and each of the BQ and ESS scores that was not statistically significant (r = −0.420, N = 26,

P
>
0.05

, and r = −0.41, N = 26,

P
>
0.05

, respectively). Conclusion. The BOAT device may provide a useful form of therapy to improve OSA-related PSG parameters such as AHI. Both BQ and ESS were predictive to improvements detected by the sleep study during BOAT device use.
Legal Modeling Approach of Big Data Transaction Management in the Perspective of Digital Economy
Authors: Wang Yi , Yuan Guang
Published: May 2022

The rapid development of digital economy puts forward theoretical and practical requirements for the construction of legal model of big data transaction management (BDTM). The new problems of ambiguous data ownership, privacy leakage, chaotic digital transaction order, and low nationalization in the context of big data transactions have largely restricted the role of China’s big data transaction market and related laws and regulations and are not conducive to promoting the scientific and standardized development of China’s digital economy. In this paper, we firstly analyze the connotation, importance, and necessity of the construction of legal model of big data transaction in the era of digital economy from the basic connotation of legal model. Then, we analyze the need to adhere to the principles of systematization, security, and openness in the construction of legal model of big data transaction management and focus on four methods of contract law, market behavior, replication behavior, and dispute resolution in the construction of legal model of big data transaction management. Finally, we summarized the conclusions of this paper. The conclusions of this paper are important for promoting the transformation of digital resources into effective data elements and advancing the scientific and standardized development of China’s digital economy.
Clinical Efficacy of Modified Yiwei Shengyang Decoction Combined with FOLFOX4 Chemotherapy Regimen in the Treatment of Advanced Gastric Cancer and Its Effect on Tumor Marker Levels
Authors: Wu Hongying , Miao Xiaomei , Liu Yan , Zhang Shu , Li Chaohui , Hao Jie
Published: May 2022

Objective. To study the clinical efficacy of modified Yiwei Shengyang decoction combined with FOLFOX4 chemotherapy regimen in the treatment of advanced gastric cancer and its effect on tumor marker levels. Methods. A total of 106 patients with advanced gastric cancer who were treated in our hospital from September 2019 to September 2021 were recruited and assigned via random number allocation to receive either FOLFOX4 chemotherapy (control group) or modified Yiwei Shengyang decoction plus FOLFOX4 chemotherapy (observation group). Outcome measures included clinical efficacy and tumor marker levels. Results. Modified Yiwei Shengyang decoction plus FOLFOX4 chemotherapy was associated with a significantly higher efficacy (86.79%, including 22 (41.51%) cases of complete response (CR), 24 (45.28%) cases of partial response (PR), 6 (11.32%) cases of stable disease (SD), and 1 (1.89%) case of progressive disease (PD)) compared to FOLFOX4 chemotherapy alone (47.16%, including 10 (18.87%) cases of CR, 15 (28.30%) cases of PR, 21 (39.62%) cases of SD, and 7 (13.21%) cases of PD) (

P
<
0.05

). There was no significant difference in the levels of CEA and CA19-9 between the two groups before treatment (

P
>
0.05

). Modified Yiwei Shengyang decoction plus FOLFOX4 chemotherapy resulted in significantly lower levels of carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) (2.08 ± 0.47, 15.12 ± 6.74) compared to FOLFOX4 chemotherapy alone (5.46 ± 1.84, 31.82 ± 7.48) (

P
<
0.05

). Conclusion. Modified Yiwei Shengyang decoction plus FOLFOX4 chemotherapy regimen is effective in the treatment of advanced gastric cancer. It regulates the levels of various serum tumor markers in patients and controls the disease, so it is worthy of clinical application and promotion.
Image Inpainting via Context Discriminator and U-Net
Authors: Wei Ruifang , Wu Yukun
Published: May 2022

Image inpainting is one of the research hotspots in the field of computer vision and image processing. The image inpainting methods based on deep learning models had made some achievements, but it is difficult to achieve ideal results when dealing with images with the relationship between global and local attributions. In particular, when repairing a large area of image defects, the semantic rationality, structural coherence, and detail accuracy of results need to be improved. In view of the existing shortcomings, this study has proposed an improved image inpainting model based on a fully convolutional neural network and generative countermeasure network. A novel image inpainting algorithm via network has been proposed as a generator to repair the defect image, and structural similarity had introduced as the reconstruction loss of image inpainting to supervise and guide model learning from the perspective of the human visual system to improve the effect of image inpainting. The improved global and local context discriminator networks had used as context discriminators to judge the authenticity of the repair results. At the same time, combined with the adversarial loss, a joint loss has proposed for the training of the supervision model, which makes the content of the real and natural repair area and has attribute consistency with the whole image. To verify the effectiveness of the proposed image inpainting model, the image inpainting effect is compared with the current mainstream image inpainting algorithm on the CelebA-HQ dataset based on subjective and objective indicators. The experimental results show that the proposed method has made progress in semantic rationality, structural coherence, and detail accuracy. The proposed model has a better understanding of the high-level semantics of image, and a more accurate grasp of context and detailed information.
The Application of Edge Computing Technology in Strength Training in Hip-Hop Training and Teaching under the Background of Artificial Intelligence and Internet of Things
Authors: Liu Jie , Ren Wei
Published: May 2022

Edge computing technology in the context of artificial intelligence and the Internet of Things refers to the integration of network core processing functions, computing functions, storage functions, etc., on the basis of an open platform to one end source that is closer to objects or data. In this way, we can provide the closest and most convenient service. Edge computing technology takes the edge as the starting point to respond to network services and meet the basic requirements of real-time activities, intelligent applications, and information security and privacy in various industries. This paper applies edge computing technology in the context of artificial intelligence and Internet of Things to strength training in hip-hop teaching. First of all, this paper introduces the origin, classification, and concept of strength training of hip-hop and then introduces the edge computing technology. It includes edge computing structure, edge computing characteristics, and strength training algorithm based on edge computing. They are Thomas action, Fresno action, and rebound action. Finally, this paper compares the strength training assisted by edge computing technology with the strength training under traditional teaching and conducts strength tests on three basic hip-hop movements. The final experimental results show that edge computing technology is 1.69% higher than the strength training under traditional teaching in terms of the percentage of movement strength, which verifies its effectiveness and feasibility for hip-hop strength training.
Prevalence of SARS‐CoV‐2 Antibodies in Laboratory Healthcare Workers at Assiut University Hospital, Egypt
Authors: Ezz Eldin Azza M. , Kamal Dalia Tarik , Salah Eldin Samar , Elkhayat Mariam R. , Attia Alaa M. , Abd Elhameed Zeinab Ahmed
Published: May 2022

Background. COVID‐19 is an illness caused by a novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Laboratory healthcare workers (LHCWs) are at highest risk for COVID‐19 infection due to direct exposure to COVID‐19 patients and/or infected samples. Objectives. Our primary objective in this study was to evaluate SARS‐CoV‐2 Ab testing as a screening tool for detecting COVID‐19 infection among asymptomatic LHCWs. Our secondary aims were to establish the relationship between exposure to COVID‐19 infection and subsequent asymptomatic disease and working in different areas of the laboratory. Method. The detection of SARS‐CoV‐2 antibodies was done by different methods (rapid testing, electrochemiluminescence, and chemiluminescent microparticle immunoassay). The study included 199 asymptomatic LHCWs at Assiut University Hospital, Egypt, from different laboratory areas including molecular biology, microbiology, parasitology, and outpatient clinic laboratories in addition to LHCWs involved in automation, phlebotomy, rotating physicians, and those working in the sample receiving area. Results. The incidence of SARS‐CoV‐2 antibodies by rapid testing and immunoassay among asymptomatic LHCWs was 29.6% and 24.4%. Laboratory phlebotomists (55.6%) were most likely to be exposed to positive patients and samples, followed by those working in the sample receiving area (32%), LHCWs in the automation area (29.6%), rotating doctors (28.6%), and LHCWs in the diagnostic molecular biology laboratory (15.4%). The sensitivities of the rapid test and SARS‐CoV‐2 total antibody were 94.1% and 92%, whereas the specificities were 92.6% and 91%. Conclusion. Rapid serological testing is an effective screening method for the detection of SARS‐CoV‐2 infection among asymptomatic LHCWs and the identification of the groups of workers who have a significantly higher seroprevalence than the rest of the laboratory population.
ANCA-Negative Vasculitis in Eosinophilic Granulomatosis with Polyangiitis Complicated with Membranous Nephropathy: A Case Report and Brief Literature Review
Authors: Kasama Eri , Ino Jun , Iemura Fumika , Kumon Saeko , Kodama Mio , Sato Keitaro , Eizumi Hitoshi , Nitta Kosaku , Hoshino Junichi
Published: May 2022

Renal involvement in eosinophilic granulomatosis with polyangiitis (EGPA) typically occurs in anti-neutrophil cytoplasmic autoantibody (ANCA)-positive cases presenting with rapidly progressive renal insufficiency and urinary abnormalities induced by primarily necrotizing crescentic glomerulonephritis (NCGN). Recently, ANCA-negative EGPA has also been reported to manifest with renal involvement, such as NCGN or non-NCGN, including membranous nephropathy (MN). Herein, we report a 70-year-old female who presented with purpura on the lower legs, upper limb numbness, renal dysfunction (eGFR, 20.5 ml/min/1.73 m2), and eosinophilia (eosinophils, 37,570/μl). MPO-and PR3-ANCA were negative, and urinalysis revealed urine protein (0.63 g/day) but without red blood cells in the urine sediment. Thus, she was diagnosed with ANCA-negative EGPA with rapidly progressive renal dysfunction. A renal biopsy revealed vasculitis in the interlobular arteries without NCGN, with the vasculitis being complicated by MN. Micrograph findings on fluorescence immunostaining contained both primary and secondary characteristics of MN (dominance of IgG subclass 4 more than subclass 1 vs. negativity of PLA2R and THSD7A). After treatment with prednisolone, her eosinophil counts normalized, and renal dysfunction improved. Furthermore, urine protein did not increase above 1.0 g/day during the clinical course. This is a rare case of ANCA-negative EGPA presenting with acute renal dysfunction without NCGN and subclinical MN with unknown etiology. It is important to recognize that EGPA pathology varies widely throughout the disease course, and the clinical course of subclinical MN should be carefully assessed in further follow-ups.
Anthropometric markers of abdominal adiposity and its relation to dyslipidemia and insulin resistance among overweight/obese schoolchildren and adolescents
Authors: Nogueira-de-Almeida Carlos Alberto , Ferraz Ivan Savioli , Ued Fábio da Veiga , Almeida Ane Cristina Fayão , Almeida Maria Eduarda Nogueira de , Biella Diego , Del Ciampo Luiz Antonio
Published: May 2022

Objective: to assess the relationship between anthropometric indicators and laboratorial markers of cardiovascular risk in overweight/obese children and adolescents, in order to verify whether any anthropometric indicator has a better potential for use in screening cardiovascular risk in the population.
Method: retrospective cross-sectional study enrolling 237 individuals aged 7 to 18 years.  Body mass index (BMI), waist circumference (WC), waist circumference/height index (WC/H), glucose, HOMA-IR, total cholesterol (TC), LDL, HDL, triglycerides and TC/HDL and LDL/HDL indexes were obtained. Associations between anthropometric and laboratory markers were tested in contingency tables using the chi-square test. Correlations were tested by Spearman's correlation.
Results: higher WC (Freedman cutoffs) was associated with lower levels of HDL and higher score in the TC/HDL and LDL/HDL indexes, but, using +2 z-scores as the cutoff, there were associations with low HDL and higher HOMA-IR. WC/H indicator (0.5 cutoff) was not associated with any of the outcomes, but, using +2 z-scores, an association was found with HOMA-IR. Z-scores of WC, WC/H and BMI showed positive correlation with HOMA-IR, TC/HDL and HOMA-IR, respectively. Negative correlations were found between WC and WC/H z-scores with HDL. WC and WC/H z-score were related to changes in HDL and HOMA-IR.
Conclusions: there seems to be an advantage in using WC alone as a possible predictor of dyslipidemia and insulin resistance in children and adolescents. It is not possible to state that WC, WC/H or BMI measurements differ in their abilities to identify Brazilian children and adolescents with risk factors for cardiovascular diseases.
COVID-19 e obesidade: dificuldades enfrentadas por pacientes em pré-operatório para cirurgia bariátrica
Authors: Alves Júnior Antônio , Carvalho Julia Maria Salgado , Leal Roberta Kayane Silva , Nepomuceno Aline Lima de Oliveira , Alves Maria Rosa Melo
Published: May 2022

Introdução: A obesidade é uma doença crônica que apresenta risco à saúde e está associada a formas graves da Covid-19. Durante a pandemia, pode haver o surgimento mais acentuado de dificuldades psicológicas nesses pacientes. Objetivo: avaliar possíveis impactos durante o enfrentamento da pandemia em pacientes no pré-operatório para cirurgia bariátrica. Método: Estudo transversal e descritivo, de abordagem qualitativa, com dados coletados através de entrevista semiestruturada. Amostra composta por pacientes em pré-operatório para cirurgia bariátrica. Foram previamente estabelecidos três grandes eixos temáticos e após a transcrição das entrevistas as respostas foram analisadas e classificadas em categorias. Resultados: Foram entrevistados 17 pacientes em pré-operatório para cirurgia bariátrica, sendo dez do sexo feminino e sete do sexo masculino. A média de idade dos participantes foi de 36,7 ± 13,6 anos e o índice de massa corporal médio foi de 43,9 ± 8,4 kg/m2. Os pacientes apresentaram dificuldades em seguir o protocolo nutricional e realizar atividades físicas, importantes na preparação para a cirurgia bariátrica. O momento vivido durante a pandemia da Covid-19 trouxe sequelas principalmente no emocional dos entrevistados. Conclusão: É importante manter assiduamente o acompanhamento por equipes multiprofissionais para esses pacientes durante a pandemia, mesmo que remotamente, a fim de melhorar a gestão da sua saúde física e mental no pré-operatório da cirurgia bariátrica.