bluuebunny/crossref_metadata_2025 huggingface dataset:
Decompositions of functions defined on finite sets in ℝd
Authors: Nurligareev Khaydar , Reshetnikov Ivan
Published: May 2022

A finite subset [Formula: see text] is basic, if for any function [Formula: see text] there exists a collection of functions [Formula: see text] such that for each element [Formula: see text], we have [Formula: see text]. For certain finite sets, we prove a criterion for a set to be basic, and we show that it cannot be extended to the general case. In addition, we interpret the above criterion in terms of doubly-weighted graphs and give an estimation for the number of elements in certain basic and non-basic subsets.
Design of Personalised English Distance Teaching Platform Based on Artificial Intelligence
Authors: Huang Yabin
Published: May 2022

In the application of the existing distance education platform, the server load is often unbalanced, which increases the response time of the platform. This paper designs a personalised English distance teaching platform based on artificial intelligence. Put forward the overall architecture of the platform, and design the platform on this basis. In order to realise the personalised course resource recommendation function, a collaborative filtering personalised recommendation algorithm is designed to get the best course recommendation results. Using artificial intelligence technology to set up multipoint control unit, the task balance is allocated to multiple operation units, and the reasonable allocation of curriculum resources is realised. According to the functional requirements of the platform design, the composition of functional modules is further set to realise the scheduling and management of curriculum resources. The experimental results show that, under the condition of the same number of concurrent users, the average response time of this design platform is less than that of the existing distance teaching platform, which shows that it has certain advantages in server load balancing and resource scheduling, which can improve the rapid response ability of the platform and enhance the stability of the platform.
Evaluating farmers’ credit risk: A decision combination approach based on credit feature
Authors: Chai Nana , Shi Baofeng
Published: May 2022

The existing default discrimination models based on evaluation indicators are difficult to achieve higher credit risk identification performance of farmers’ default status under the situation of insufficient credit information and low correlation between indicators and default risk. Those models are difficult to find out the fundamental causes of farmers’ default risk. A credit risk discrimination model based on credit features strongly with default status is established to evaluate the farmer’s credit risk. Term frequency inverse document frequency and sentiment dictionary analysis method are used to quantify long text indicators, then the K-means method is used to Boolean the numerical data. The APRIORI algorithm is used to mine the credit features strongly associated with the default status. Finally, the default status of farmers is judged based on those credit features. The model is detailed using actual bank data from 2044 farmers within China. According to the five-evaluation criterion of AUC, F1-score, Type II-error, Balance error rate and G-mean, the empirical results show that the ability of the credit risk discrimination model with credit features is higher than that of the model based on evaluation indicators. This finding provides a new idea for commercial banks to measure the default risk of farmers, and provides a reference for the formulation of strategies to enhance farmers’ credit.
Bending behavior of pyramid lattice sandwich beams with non-uniform truss cores
Authors: Lu Fucong , Zhang Kun , Zhu Yilin
Published: May 2022

To improve the three-point bending capacity of the pyramid lattice sandwich beam, a non-uniform pyramid lattice sandwich structure is proposed in this paper by assigning different diameters to the tensile and compressive core rods and setting the ratio of the diameters of the two kinds of core rods as a non-uniform coefficient. The influence of the non-uniform coefficients on the three-point bending performance of the pyramid lattice sandwich beam is analyzed theoretically and numerically. Results show that the introduction of the non-uniform coefficients can significantly improve the bending ultimate bearing capacity of the structure. Compared with the uniform lattice sandwich beam, the optimal non-uniform coefficients increase the bending ultimate bearing capacity by 39%. Moreover, it is revealed that the optimal non-uniform coefficient ([Formula: see text]) decreases with the increase of the total mass of the structure. The research on the three-point bending performance of non-uniform lattice sandwich beams in this paper can provide guidance for the optimal design of lightweight lattice sandwich structures.
The Effects of Temperature on Cellular Physiology
Authors: Knapp Benjamin D. , Huang Kerwyn Casey
Published: May 2022

Temperature impacts biological systems across all length and timescales. Cells and the enzymes that comprise them respond to temperature fluctuations on short timescales, and temperature can affect protein folding, the molecular composition of cells, and volume expansion. Entire ecosystems exhibit temperature-dependent behaviors, and global warming threatens to disrupt thermal homeostasis in microbes that are important for human and planetary health. Intriguingly, the growth rate of most species follows the Arrhenius law of equilibrium thermodynamics, with an activation energy similar to that of individual enzymes but with maximal growth rates and over temperature ranges that are species specific. In this review, we discuss how the temperature dependence of critical cellular processes, such as the central dogma and membrane fluidity, contributes to the temperature dependence of growth. We conclude with a discussion of adaptation to temperature shifts and the effects of temperature on evolution and on the properties of microbial ecosystems.
Telomere-mediated lung disease
Authors: Alder Jonathan K. , Armanios Mary
Published: May 2022

Parenchymal lung disease is the fourth leading cause of death in the United States; among the top causes, it continues on the rise. Telomeres and telomerase have historically been linked to cellular processes related to aging and cancer, but surprisingly, in the recent decade genetic discoveries have linked the most apparent manifestations of telomere and telomerase dysfunction in humans to the etiology of lung disease: both idiopathic pulmonary fibrosis (IPF) and emphysema. The short telomere defect is pervasive in a subset of IPF patients, and human IPF is the phenotype most intimately tied to germline defects in telomere maintenance. One-third of families with pulmonary fibrosis carry germline mutations in telomerase or other telomere maintenance genes, and one-half of patients with apparently sporadic IPF have short telomere length. Beyond explaining genetic susceptibility, short telomere length uncovers clinically relevant syndromic extrapulmonary disease, including a T-cell immunodeficiency and a propensity to myeloid malignancies. Recognition of this subset of patients who share a unifying molecular defect has provided a precision medicine paradigm wherein the telomere-mediated lung disease diagnosis provides more prognostic value than histopathology or multidisciplinary evaluation. Here, we critically evaluate this progress, emphasizing how the genetic findings put forth a new pathogenesis paradigm of age-related lung disease that links telomere abnormalities to alveolar stem senescence, remodeling, and defective gas exchange.
Role of Exosomes in Chronic Liver Disease Development and Their Potential Clinical Applications
Authors: Wang Chen , Liu Jinwen , Yan Yongmin , Tan Youwen
Published: May 2022

Extracellular vesicles (EVs) are vesicular bodies (40-1000 nm) with double-layer membrane structures released by different cell types into extracellular environments, including apoptosis bodies, microvesicles, and exosomes. Exosomes (30-100 nm) are vesicles enclosed by extracellular membrane and contain effective molecules of secretory cells. They are derived from intracellular multivesicular bodies (MVBs) that fuse with the plasma membrane and release their intracellular vesicles by exocytosis. Research has shown that almost all human cells could secrete exosomes, which have a certain relationship with corresponding diseases. In chronic liver diseases, exosomes release a variety of bioactive components into extracellular spaces, mediating intercellular signal transduction and materials transport. Moreover, exosomes play a role in the diagnosis, treatment, and prognosis of various chronic liver diseases as potential biomarkers and therapeutic targets. Previous studies have found that mesenchymal stem cell-derived exosomes (MSC-ex) could alleviate acute and chronic liver injury and have the advantages of high biocompatibility and low immunogenicity. In this paper, we briefly summarize the role of exosomes in the pathogenesis of different chronic liver diseases and the latest research progresses of MSC-ex as the clinical therapeutic targets.
Machine Learning-Based Radiomics for Prediction of Epidermal Growth Factor Receptor Mutations in Lung Adenocarcinoma
Authors: Lu Jiameng , Ji Xiaoqing , Wang Lixia , Jiang Yunxiu , Liu Xinyi , Ma Zhenshen , Ning Yafei , Dong Jie , Peng Haiying , Sun Fei , Guo Zihan , Ji Yanbo , Xing Jianping , Lu Yue , Lu Degan
Published: May 2022

Identifying an epidermal growth factor receptor (EGFR) mutation is important because EGFR tyrosine kinase inhibitors are the first-line treatment of choice for patients with EGFR mutation-positive lung adenocarcinomas (LUAC). This study is aimed at developing and validating a radiomics-based machine learning (ML) approach to identify EGFR mutations in patients with LUAC. We retrospectively collected data from 201 patients with positive EGFR mutation LUAC (140 in the training cohort and 61 in the validation cohort). We extracted 1316 radiomics features from preprocessed CT images and selected 14 radiomics features and 1 clinical feature which were most relevant to mutations through filter method. Subsequently, we built models using 7 ML approaches and established the receiver operating characteristic (ROC) curve to assess the discriminating performance of these models. In terms of predicting EGFR mutation, the model derived from radiomics features and combined models (radiomics features and relevant clinical factors) had an AUC of 0.79 (95% confidence interval (CI): 0.77-0.82), 0.86 (0.87-0.88), respectively. Our study offers a radiomics-based ML model using filter methods to detect the EGFR mutation in patients with LUAC. This convenient and low-cost method may be of help to noninvasively identify patients before obtaining tumor sample for molecule testing.
Progress in Endoscopic and Interventional Treatment of Esophagogastric Variceal Bleeding
Authors: Liu Bin , Li Gang
Published: May 2022

Esophagogastric variceal bleeding (EGVB) is one of the main complications of portal hypertension, especially in patients with liver cirrhosis, and has a very high fatality rate. At present, the treatment methods for rupture and bleeding of gastroesophageal varices (GV) include drug therapy, compression hemostasis with three-lumen and two-balloon tube, endoscopic therapy, and interventional and surgical operations. Endoscopy and intervention or their combined application is the mainstream treatment modes in clinical practice, especially their combined application has been increasingly recognized by front-line clinicians. This article intends to discuss the application characteristics of the two treatment methods.
Study on Circulating lncRNA Expression Profile in Patients with Cerebral Infarction
Authors: Li Man-tang , Luo Cheng-hong , Xu Peng-jie , Jin Ya
Published: May 2022

To analyze the difference of circulating lncRNA expression profile between the healthy control group and cerebral infarction (CI) patients and to study the epigenetic pathogenesis of CI. Forty patients with acute CI admitted to our hospital from December 2016 to December 2017 were selected as CI group, and 40 healthy people in physical examination center were selected as healthy group. In the CI group, blood samples were taken 5 mL at fasting in the morning (within 72 hours of CI), and the blood samples from healthy group were also taken 5 mL at fasting in the morning. The circulating lncRNA expression profile of serum sample was determined by high-throughput technique, and its difference was analyzed. Bioinformatics technology was used to explore its functional mechanism, and GO, KEGG analysis, and gene expression network were established for lncRNA with significant differences. Next, lnc-ZNF32-1 : 1 and lnc-PCGF5-2 : 1 were selected for further validation of serum lncRNA expression in ACI and NC groups, and ceRNA interaction network analysis, diagnostic specificity, and sensitivity of lnc-ZNF32-1 : 1 and lnc-PCGF5-2 : 1 were conducted. The results showed that compared with the healthy group, there were 512 known lncRNA expressed differentially in the serum of patients with CI, of which 371 were upregulated and 141 were downregulated, and 421 known mRNA expressed differentially, of which 245 were upregulated and 176 downregulated. The differentially expressed mRNA was mainly enriched in 53 gene functions, and the target gene was enriched in the pathways such as HTLV-I infection and pathways in cancer. In addition, the results explored that lnc-ZNF32-1 : 1 and lnc-PCGF5-2 : 1 have potential value for CI diagnosis. In conclusion, the expression profile of lncRNA in CI group was significantly different from that in healthy group, indicating that lncRNA might be closely related to the occurrence, development, and prognosis of CI.
Application of Long-Term and Short-Term Memory Neural Network in Technical Evaluation of Hurdle Track and Field
Authors: Liu Zhenming
Published: May 2022

In order to study the application of long-term and short-term memory neural networks in the technical evaluation of hurdle track and field, firstly, the related contents of long-term and short-term memory neural networks and hurdle track and field sports are analyzed, the variation characteristics of kinematics and surface electromyography of swinging leg in the landing link of lower hurdle are analyzed, and the relationship between surface electromyography and kinematics parameters is analyzed. Then, the kinematics and surface EMG data of three male hurdlers in the hurdle team and two men in the College of Physical Education were collected when completing the technical link of pressing down and landing. The subject data were processed and analyzed by using the Simi motion video analysis system and DASY lab10.0 EMG analysis software. Finally, SPSS13.0 and origin are used to analyze the average, standard deviation, and correlation of the data results and draw a graph. Experiments show that neural network theory and finite element method, as the new forces of sports biomechanics, have been used to diagnose track and field technology. With the popularization of this method, it will play a greater role in the research of track and field technology.
A Novel TNFSF‐Based Signature Predicts the Prognosis and Immunosuppressive Status of Lower‐Grade Glioma
Authors: Tao Rui , Liu Qi , Huang Ruoyu , Wang Kuanyu , Sun Zhiyan , Yang Pei , Wang Jiangfei
Published: May 2022

Purpose. Tumour necrosis factor (TNF) superfamilies play important roles in cell proliferation, migration, differentiation, and apoptosis. We believe that TNF has a huge potential and might cast new insight into antitumour therapies. Therefore, we established this signature based on TNF superfamilies. Results. A six‐gene signature derived from the TNF superfamilies was established. The Riskscore correlated significantly with the expression of immune checkpoint genes and infiltrating M2 macrophages in the tumour specimen. This signature was also associated with mutations in genes that regulate tumour cell proliferation. Univariate and multivariate regression analyses further confirmed the Riskscore, TNFRSF11b, and TNFRSF12a as independent risk factors in The Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets. Conclusion. Our signature could accurately predict the prognosis of lower‐grade gliomas (LGG). In addition, this six‐gene signature could predict the immunosuppressive status of LGG and provide evidence that TNF superfamilies had correlations with some critical mutations that could be effectively targeted now.
Effective‐Component Compatibility of Bufei Yishen Formula III Combined with Electroacupuncture Suppresses Inflammatory Response in Rats with Chronic Obstructive Pulmonary Disease via Regulating SIRT1/NF‐κB Signaling
Authors: Jin Fanli , Zhang Lanxi , Chen Kai , Miao Yufang , Liu Yang , Tian Yange , Li Jiansheng
Published: May 2022

Objective. To explore more efficient treatments for chronic obstructive pulmonary disease (COPD), effective‐component compatibility of Bufei Yishen formula III (ECC‐BYF III) and electroacupuncture were tested on rats with COPD, and silent information regulator transcript‐1 (SIRT1)/nuclear factor‐kappaB (NF‐κB) signaling was further investigated to interpret the therapy. Methods. In total, 70 rats were randomly divided into control (Control), model (Model), aminophylline (APL), ECC‐BYF III, electroacupuncture (EA), ECC‐BYF III+EA, and sham electroacupuncture (SA) groups. Cigarette smoke exposure combined with repeated bacterial infections was used to establish COPD models in 1–12 weeks. From 13 to 20 weeks, the ECC‐BYF III and APL groups received corresponding drugs; the EA group received electroacupuncture therapy, wherein Dazhui (GV 14), Feishu (BL 13), and Shenshu (BL 23) points were selected; the ECC‐BYF III+EA group received ECC‐BYF III intragastrically combined with electroacupuncture; and the SA group received simulated electroacupuncture (nonacupoint). Pulmonary function, pulmonary histopathology, the expressions of SIRT1/NF‐κB signaling, and inflammation‐related mRNA and protein were detected. Results. Significant deterioration was observed in pulmonary function and pulmonary histopathology in rats with COPD (P < 0.01), and inflammatory state was illustrated by increased levels of interleukin‐ (IL‐) 6 and tumor necrosis factor alpha (TNF‐α) and decreased levels of IL‐10 (P < 0.01). After the intervention of APL, ECC‐BYF III, EA, and ECC‐BYF III+EA, both pulmonary function and pulmonary histopathology were improved (P < 0.05 and P < 0.01), whereas the levels of IL‐6 and TNF‐α were decreased and IL‐10 was increased (P < 0.05 and P < 0.01). Additionally, the mRNA expressions of IL‐6, TNF‐α, NF‐κB, and acetylated NF‐κBp65 (Ac‐NF‐κB) were noted to decrease, and SIRT1 and IL‐10 were increased (P < 0.05 and P < 0.01); the protein expression of SIRT1 was upregulated, and NF‐κBp65 and Ac‐NF‐κB were downregulated (P < 0.05 and P < 0.01). The effect of ECC‐BYF III+EA was better in terms of improving pulmonary function and alleviating inflammation than that of the other treatment groups (P < 0.01 and P < 0.05). Conclusions. ECC‐BYF III, electroacupuncture, and their combination can suppress inflammation, among which the combination therapy has been proven to be the most effective treatment, and the mechanism may be involved in activating SIRT1/NF‐κB signaling.
Support Vector Machine-Based Nonlinear Model and Its Application in Regional Economic Forecasting
Authors: Hu Yili , Wang Zhiyong
Published: May 2022

The regional economic potential is affected by too many entities and large dynamic changes in the economic structure, resulting in large errors in the prediction obtained by the traditional economic potential development prediction method. Therefore, this paper puts forward the regional economic development potential prediction model with the concept of decision domain, solves the nonlinear characteristics of regional economic impact indicators by using the traditional support vector machine, and obtains the economic prediction data. The decision domain method is introduced in the decision-making process to construct the decision domain of training economic-related data sets. The experimental results show that compared with other prediction models, the model proposed in this paper has higher regional economic prediction accuracy, 2% higher than the baseline method, can quickly and accurately predict the potential trend of regional economic development, and has important application value.
Vehicle Path Recognition Approach Based on Incomplete Automatic Vehicle Identification
Authors: He Meimei , Wu Xianyu , Zhan Zhenxi , Guo Jingxue
Published: May 2022

Vehicle path recognition is one of the key methods used in urban traffic research, such as traffic flow characteristics analysis. Automatic vehicle identification (AVI) is often used for vehicle path recognition and is suitable for mixed traffic flow with connected automated vehicles (CAVs). However, there still remain issues in overcoming the difficulty of vehicle path identification caused by the discontinuity of AVI data and solving the problem of low precision of AVI application. To model the vehicle path, this paper selects the AVI system of Yicheng Town, Linfen City, Shanxi Province, as a test bed. The travel modes of private cars and taxis are discussed, and the quantified indicators of the model are determined. By combining the analytic hierarchy process (AHP) with the entropy weight method (EWM) to get the weights of the indicators, the path recognition model under incomplete AVI data is proposed. Finally, based on the path recognition model proposed in this paper, case studies are carried out for the private car and taxi path recognition, respectively. The validity of the path identification through practical studies and the effect of the number of missing nodes of AVI equipment on the accuracy of the model are discussed. The results show that the recognition of the travel path using the proposed model is consistent with the actual travel path. The accuracy of the proposed model is more than 60% when the number of missing nodes is less than 7 in total 31 nodes. Considering the decision models for private cars and taxis, respectively, the proposed model provides a method for vehicle path recognition based on incomplete AVI data.
Endothelial Dysfunction and Ischemia-Modified Albumin Levels in Males with Diabetic and Nondiabetic Erectile Dysfunction
Authors: Kurt Hasan Anıl , Demirci Emrah , Alan Cabir
Published: May 2022

In this study, we aimed to determine endothelial dysfunction and ischemia-modified albumin (IMA) levels in patients diagnosed with erectile dysfunction (ED) and to examine the relationship between these and diabetes disease. 86 male patients (46 patients with diabetes, age:

51.5
±
9.2

and 40 patients with nondiabetes (control group), age:

54.78
±
12.2

) were included in the study. IMA, a new indicator of tissue ischemia and oxidative stress, was checked. Superoxide dismutase (SOD) activity, another oxidative stress indicator, was examined. Endothelin-1 (ET-1), one of the parameters of endothelial dysfunction, was measured. Additionally, endothelial function was evaluated with flow-mediated vasodilatation (FMD). Student’s

t

-test was used for statistical evaluation.

p

values less than 0.05 were considered statistically significant. SOD activity was significantly lower in the diabetic group than in the control group, and ET-1 was significantly higher (

p
<
0.001

). IMA was found to be significantly higher in the diabetic group than the control group (

p
<
0.001

). FMD was significantly lower in diabetic group compared to the control group (

p
<
0.002

). According to our findings, the co-occurrence of erectile dysfunction and diabetes demonstrates a complex condition that includes endothelial dysfunction, oxidative stress, and tissue ischemia. When the correlation of indicators, which are markers, was examined, the severity of the co-occurrence of diabetes and erectile dysfunction was again demonstrated.
Evaluation of the Effect of Anti‐COVID‐19 Mouthwashes on Shear Bond Strength of Composite Resin Restorations to Dentin and Enamel: An “In Vitro Study”
Authors: Shirani Farzaneh , Mazdak Ali , Mazaheri Peiman , Shirani Mehrangiz , Samimi Pouran
Published: May 2022

Objectives. Given the high prevalence of the coronavirus and the high risk of virus transfer to dentists, the use of mouthwashes, which can potentially eliminate this virus, is suggested before dental procedures. Since these mouthwashes may affect the bond strength of composite resin restorations to teeth, this study was conducted to investigate the effect of recommended mouthwashes on the shear bond strength of composite resin restorations to dentin and enamel in selective etch and rinse and two‐step self‐etch bonding systems. Methods. Five groups of posterior teeth (n = 15) were selected for five groups of cetylpyridinium chloride 0.07%, povidone‐iodine 1%, hydrogen peroxide 1%, and chlorhexidine 0.2% as mouthwash and distilled water as the control group. The buccal enamel and lingual dentin of each tooth were rinsed after immersion in a mouthwash. After 20 seconds of enamel acid‐etching and 15 seconds of dentin priming, they were impregnated with an adhesive, and composite cylinders were placed on the dentin and enamel surfaces of the tooth. The shear bond strength test was performed after 24 hours, and results were analyzed by ANOVA and paired t‐test (α = 0.05). Results. The mean shear bond strength of enamel to composite was significantly (p < 0.05) higher than that of dentin to composite in each study group, but no significant difference was found between the mean shear bond strength of composite to enamel (p = 0.199) and to dentin (p = 0.335) after the use of mouthwashes and that of the control group. Conclusion. The use of mouthwashes used in this study did not have negative effects on the shear bond strength of composite to enamel and dentin.
Performance Prediction of Speed Skaters Based on BP Neural Network
Authors: Peng Di , Lian Hongye
Published: May 2022

To better predict the performance of skaters, a BP neural network-based approach is proposed. With the help of the main component factor analysis method, the performance sample of the athletes was reduced, the traditional high-dimensional data set was changed to the new low-dimensional data set, the size of the model input variables was reduced, and the analysis efficiency was increased and improved. Experimental results show that the larger the iteration step, the lower the prediction error, because more a priori information of sports performance is used through multiple iterations, which improves the prediction accuracy. The error of sports performance prediction using this model is less than that of traditional methods, and the maximum difference is 35.98%. It is proved that this method uses factor analysis and neural network training to cluster and fuse the data information of sports performance, improves the prediction accuracy, and has a good performance in convergence and robustness.
Polymer Processing under Microwaves
Authors: Belkhir Kedafi , Riquet Guillaume , Becquart Frédéric
Published: May 2022

Over the last decades, microwave heating has experienced a great development and reached various domains of application, especially in material processing. In the field of polymers, this unusual source of energy showed important advantages arising from the direct microwave/matter interaction. Indeed, microwave heating allows regio-, chemio-, and stereo-selectivity, faster chemical reactions, and higher yields even in solvent-free processes. Thus, this heating mode provides a good alternative to the conventional heating by reducing time and energy consumption, hence reducing the costs and ecological impact of polymer chemistry and processing. This review states some achievements in the use of microwaves as energy source during the synthesis and transformation of polymers. Both in-solution and free-solvent processes are described at different scales, with comparison between microwave and conventional heating.
Accessibility of Rehabilitation Facility: Evaluation Based on Spatial Big Data in Xiamen
Authors: Qiu Tingting , Zhou Daliang , Wang Jie , Lingamuthu Velmurugan
Published: May 2022

With the help of spatial calculation and numerical analysis, this paper reveals the spatial distribution of rehabilitation infrastructures and the accessibility difference in the city Xiamen. The calculation of Moran’s I, Z value, and

P

value are, respectively, −0.229787, −0.122751, and 0.902304 for health facilities and −0.159235, 0.186166, and 0.852315 for fitness facilities. Such calculation results indicate an uneven pattern and varied accessibility numerical values. The reasons for this influence are diverse, but it is worth noting that the two-step floating catchment area (2SFCA) calculation shows that compared to fitness facilities, the standard deviation of accessibility numerical value of health facilities decreased significantly, which indicates that the accessibility of health service facilities is becoming better, while the change of accessibility of fitness facilities is not obvious. It is pointed out this is due to society’s insufficient attention and education on daily health. For better rehabilitation under the pandemic, the importance of fitness facilities should be noticed.
Construction and Application of Virtual Reality-Based Sports Rehabilitation Training Program
Authors: Yan Huijun
Published: May 2022

This paper adopts virtual reality technology to conduct in-depth research and analysis on sports rehabilitation training, designs a corresponding sports rehabilitation training program, and applies it to practice. An AR algorithm based on dynamic target tracking under VSLAM is proposed. The algorithm can effectively reject dynamic targets in static scenes while ensuring that the virtual objects registered based on dynamic template target tracking are still in the world coordinate system of VSLAM. To facilitate patients’ hand function rehabilitation training, this paper uses OpenPose for 2D gesture pose recognition, combines camera pose information and depth information provided by VSLAM to map key points of the hand into the world coordinate system, and then completes the interaction by collision detection algorithm. The virtual interaction module is implemented in this paper to meet the demand for multiuser off-site interaction in virtual training. This paper uses the Unity3D software and Photon Server server to create a VR virtual scene and design a user interaction mechanism to realize a system that supports multiple users to train together online, which effectively extends the application scope of the VR training system. The module utilizes Unity3D’s VR development capabilities to develop VR virtual basketball gym scenes and single-player offline interaction mechanisms such as virtual user single shooter and shooter; then, Photon Server is used to design and implement a multiuser remote login system and a multiuser interpass mechanism, thus achieving the effect of multiplayer remote online interaction in the same VR space. Finally, the proposed module was validated, and the results proved the effectiveness of the sports rehabilitation training program.
[Retracted] Effect of Family Participatory Nursing Model Based on WeChat Platform on Psychological Elasticity and Quality of Life of Patients with Lung Cancer
Authors: Li LingJuan , Xu Fang , Ye Jun
Published: May 2022

Objective. To explore the effect of family participatory nursing model based on WeChat platform on psychological elasticity and life quality of patients with lung cancer. Methods. One hundred patients with lung cancer treated in our hospital from February 2019 to April 2021 were enrolled. The patients were randomly assigned into control group and study group. The control group received routine nursing and the study group received family participatory nursing model based on WeChat platform. The scores of nursing satisfaction, self‐feeling burden, symptom group assessment scale, family care index, and compliance and life quality were compared. Results. First of all, we compared the nursing satisfaction: the study group was very satisfied in 25 cases, satisfactory in 20 cases, general in 5 cases, the satisfaction rate was 100.00%; the control group was very satisfied in 14 cases, satisfactory in 17 cases, general in 13 cases, dissatisfied in 6 cases, and the satisfaction rate was 88.00%. Compared between the two groups, the nursing satisfaction in the study group was higher compared to the control group (P < 0.05). Secondly, we compared the self‐perceived burden, the emotional burden, physical burden, and economic burden and total scores of the study group were lower compared to the control group (P < 0.05). Comparing the scores of symptom group evaluation scale, the scores of respiratory symptoms, fatigue symptoms, psychological and emotional symptoms, digestive tract symptoms, and nervous system symptoms in the study group were lower compared to the control group (P < 0.05). In terms of the family care index of the two groups, the scores of fitness, cooperation, length, emotion, and intimacy in the study group were higher compared to the control group (P < 0.05). Comparison of compliance, the study group was very compliant in 42 cases, compliant in 7 cases, noncompliant in 1 case, the compliance rate was 98.00%; the control group was very compliant in 24 cases, compliant in 20 cases, noncompliant in 6 cases, the compliance rate was 88.00%. The compliance rate in the study group was higher compared to the control group (P < 0.05). Finally, we compared the scores of qualities of life. Before nursing, there exhibited no significant difference (P > 0.05). The scores of physiological function, psychological function, social function, and health self‐cognition in the study group were lower compared to the control group (P < 0.05). Conclusion. The family participatory nursing model based on WeChat platform helps to facilitate the psychological elasticity and quality of life of patients with lung cancer and further promote patients’ self‐care ability and compliance with lung cancer. It can also effectively enhance family care and nursing satisfaction; the nursing model is worth popularizing and applying in clinic.
ROS-Related miRNAs Regulate Immune Response and Chemoradiotherapy Sensitivity in Hepatocellular Carcinoma by Comprehensive Analysis and Experiment
Authors: Xu Yangtao , He Xiaoqin , Deng Junjian , Xiong Lin , Chen Biao , Chen Jiayu , Zhang Xiaoyu , Chen Wenliang , Liu Xin , Hu Xinyao , Li Jiayi , Jiang Shan , Shen Yang , Xu Ximing
Published: May 2022

Reactive oxygen species (ROS) plays an essential role in the development of cancer. Here, we chose ROS-related miRNAs for consensus clustering analysis and ROS score construction. We find that ROS is extremely associated with prognosis, tumor immune microenvironment (TIME), gene mutations, N6-methyladenosine (m6A) methylation, and chemotherapy sensitivity in hepatocellular carcinoma (HCC). Mechanistically, ROS may affect the prognosis of HCC patients in numerous ways. Moreover, miR-210-3p and miR-106a-5p significantly increased the ROS level and stagnated cell cycle at G2/M in HCC; the results were more obvious in cells after ionizing radiation (IR). Finally, the two miRNAs suppressed cell proliferation, migration, and invasion and promoted apoptosis in huh7 and smmc7721 cells. It indicated that ROS might affect the prognosis of HCC patients through immune response and increase the sensitivity of HCC patients to radiotherapy and chemotherapy.
Research on Speech Enhancement Algorithm of Multiresolution Cochleagram Based on Skip Connection Deep Neural Network
Authors: Lan Chaofeng , Wang YuQiao , Zhang Lei , Liu Chundong , Lin Xiaojia
Published: May 2022

The speech enhancement effect of traditional deep learning algorithms is not ideal under low signal-to-noise ratios (SNR). Skip connections-deep neural network (Skip-DNN) improves the traditional deep neural network (DNN) by adding skip connections between each layer of the neural network to solve the degradation problem of DNN. In this paper, the Multiresolution Cochleagram (MRCG) features in the gammachirp transform domain are denoised to obtain the improved MRCG (I-MRCG). The noise reduction method adopts the Minimum Mean-Square Error Short-Time Spectral Amplitude Estimator (MMSE-STSA) and takes I-MRCG as the input feature and Skip-DNN as the training network to improve the speech enhancement effect of the model. This paper also proposes an improved source-to-distortion ratio (SDR) loss function. When the loss function uses the improved SDR, it will improve the performance of Skip-DNN speech enhancement model. The experiments in this paper are performed on the Edinburgh dataset. When using I-MRCG as the input feature of Skip-DNN, the average perceptual evaluation of speech quality (PESQ) is 2.9137, and the average short-time objective intelligibility (STOI) is 0.8515. Compared with MRCG as Skip-DNN input features, the improvements are 0.91% and 0.71%, respectively. When the improved SDR is used as the loss function of the speech model, the average PESQ is 2.9699 and the average STOI is 0.8547. Compared with other loss functions, the improved SDR has a better enhancement effect when used as the loss function of the speech enhancement model.
Development of Employer Brand Evaluation Scale Based on Computer Data Mining and Its Relationship with College Students’ Job-Hunting Intention
Authors: Yang Guilin , Yang Wanping , Yang Guihua
Published: May 2022

The inclinations among employees are changed because of the evolutions in the twenty-first century’s workplace. It is consequently critical to decide the elements that workers look for in an organization and their goal conduct to stop from their occupation to work on the issues of high wearing down that occurs in an organization. This study determines the connection between employer branding and turnover intention among employees. Data mining and factor analysis methods are used to extract public factors, design a more concise employer brand evaluation system, and develop a new employer brand evaluation scale. The relationship between the various dimensions of employer brand in China’s banking industry and college students’ job-hunting intentions are examined. Results show that contemporary college student job-seekers in China pay more attention to short-term and directly experienced security and experiential needs. It ignores the long-term and hard-to-feel self-realization needs and respect needs in the short term. These dimensions reflect the perceptions of existing employees regarding their organization. The scale is found to be statistically sound for measuring the employer brand.
Orcinol Glucoside Improves Senile Osteoporosis through Attenuating Oxidative Stress and Autophagy of Osteoclast via Activating Nrf2/Keap1 and mTOR Signaling Pathway
Authors: Gong Wan , Liu Mengqin , Zhang Qi , Zhang Quanlong , Wang Yang , Zhao Qiming , Xiang Lu , Zheng Chengjian , Zhang Qiaoyan , Qin Luping
Published: May 2022

Oxidative stress and autophagy play essential roles in the development of senile osteoporosis which is characterized by disrupted osteoclastic bone resorption and osteoblastic bone formation. Orcinol glucoside (OG), a phenolic glycoside isolated from Curculigo orchioides Gaertn, possesses antiosteoporotic properties. This study examined the protective effects of OG on bone loss in SAMP6 mice and explored the underlying mechanisms. The osteoporotic SAMP6 mice were treated with OG oral administration. RAW264.7 cells were induced to differentiate into osteoclast by RANKL and H2O2 in vitro and received OG treatment. The results demonstrated that OG attenuated bone loss in SAMP6 mice and inhibited the formation and bone resorption activities of osteoclast and reduced levels of oxidative stress in bone tissue of SAMP6 mice and osteoclast. Furthermore, OG activated Nrf2/Keap1 signaling pathway and enhanced the phosphorylation of mTOR and p70S6K which are consequently suppressing autophagy. Of note, the effect of OG on Nrf2/Keap1 signaling was neutralized by the mTOR inhibitor rapamycin. Meanwhile, the inhibitory effect of OG on autophagy was reversed by the Nrf2 inhibitor ML385.Conclusively, OG attenuated bone loss by inhibiting formation, differentiation, and bone resorption activities of osteoclast. Regulation of Nrf2/Keap1 and mTOR signals is a possible mechanism by which OG suppressed oxidative and autophagy of osteoclasts. Thus, OG prevented senile osteoporosis through attenuating oxidative stress and autophagy of osteoclast via activating Nrf2/Keap1 and mTOR signaling pathway.
LARS2 Regulates Apoptosis via ROS-Mediated Mitochondrial Dysfunction and Endoplasmic Reticulum Stress in Ovarian Granulosa Cells
Authors: Feng Shujun , Wan Shan , Liu Shuangying , Wang Wei , Tang Minyue , Bai Long , Zhu Yimin
Published: May 2022

Several studies have indicated that mutations of LARS2 are associated with premature ovarian insufficiency (POI). However, the pathogenic mechanism of LARS2 in POI has not been reported yet. In the present study, the expression levels of LARS2 and E2F1 in granulosa cells (GCs) of POI patients were examined. CCK-8 and Edu assay were performed to determine the effect of LARS2 on cell proliferation. Apoptosis rate, mitochondrial membrane potential, reactive oxygen species (ROS), and cytoplasm Ca2+ levels were analyzed by flow cytometry. Western blot was conducted to evaluate the expression level of genes affected by LARS2. Transmission electron microscopy (TEM) was used to observe mitochondrial structure in GCs. Chromatin immunoprecipitation (ChIP) was used to evaluate the regulatory effect of E2F1 on Mfn-2 expression. Our results showed that LARS2 expression was downregulated in GCs of POI patients. Silencing of LARS2 inhibited cell proliferation and promoted the apoptosis of GCs. Meanwhile, LARS2 knockdown could induce mitochondrial dysfunction and accumulation of ROS levels. Moreover, ROS was found to be involved in the antiproliferation, proapoptotic, and endoplasmic reticulum (ER) stress effects of LARS2 knockdown. Furthermore, we also found that the expression level of E2F1 was positively correlated with LARS2. In addition, E2F1 could bind at the -61/-46 region of Mfn-2 promoter and regulated MFN-2 transcription. These findings demonstrated that LARS2 could promote the expression of E2F1. E2F1 mediated the effect of LARS2 on Mfn-2 expression via targeting the promoter region of Mfn-2, in which subsequently regulated cell proliferation and apoptosis, which resulted in the etiology of POI. This study will provide useful information for further investigations on the LARS2 in the occurrence of POI.
Analysis and Evaluation Research on the Construction of the Music Art Management Curriculum System Based on the Deep Learning Model
Authors: Hu Shichang , Yang Lei
Published: May 2022

In view of the fact that music courses are seldom offered in schools and lack of management, there are many problems in the management system of music and art. In order to improve the learning effect of students in music courses, this paper proposes to build a music art management curriculum system based on the in-depth learning model. This paper puts forward the requirements of in-depth learning in music and art curriculum indicators and puts forward the model framework of music and art learning. Through the combined application of music courses, first of all, the current music course model is compared with Ghostnet music course, Mobilenet music course, and traditional music course to verify that the current music course model has certain advantages in accuracy, precision, recall, and image recognition performance. This proves that the current music curriculum is more suitable for the construction of this model. Secondly, the proposed model has a high score through the comprehensive application of several indicators in the course. Finally, under the model constructed by deep learning, the opening of music courses in schools has also increased significantly and improves the interest point and the application of people on the music art course so as to achieve the final application effect.
Determination of Risk Factors Associated with the Failure of 12 Weeks of Direct‐Acting Antiviral Therapy in Patients with Hepatitis C: A Prospective Study
Authors: Nguyen Thi Thu Phuong , Ngo Thi Quynh Mai , Pham Van Linh , Nguyen Van Hung , Nguyen Thanh Hoi
Published: May 2022

Introduction. Direct‐acting antivirals (DAAs) have significantly improved the efficacy and tolerability of the treatment of hepatitis C virus (HCV). However, studies conducted on actual patients with the aim of predicting the risk associated with treatment failure are lacking. Methods. Our study enrolled 334 new HCV patients and assessed the effectiveness of treatment and predicted the risk of failure to achieve sustained virological response (SVR) by developing a multiple logistic model. Our study compared the variables between the two groups, those who did (group 0, n = 239) and did not achieve SVR (group 1, n = 95). Results. The cure rate of HCV at 12th week in our study was 71.56%. We found that advanced cirrhosis, HCV genotype, HBV coinfection, rapid virological response (RVR), fibrosis index (FIB‐4) score, serum levels of AST, ALP, hemoglobin, and viral load before treatment were prognostic factors associated with rate of failure to achieve SVR at week 12 of DAA therapy. In the multiple logistic model, eight significant predictors including advanced cirrhosis status, HCV genotype, RVR, AST/ALP levels, FIB‐4 score, and viral load before treatment predicted the risk of failure with excellent model performance (area under the receiver operating characteristic curve (AUCROC) [95% CI] =0.986 (0.971‐0.999)). RVR and advanced cirrhosis were the two strongest predictors with odd ratios (95% CI) =9.72 (2.8, 39.28) and 51.54 (6.39, 139.82), respectively. Conclusion. The multiple logistic regression model included significant factors to estimate the probability of failure to achieve SVR, which could improve HCV treatment strategy.
Urinary Biomarkers of Oxidative Stress in Aging: Implications for Prediction of Accelerated Biological Age in Prospective Cohort Studies
Authors: Mukli Peter , Wu Dee H. , Csipo Tamas , Owens Cameron D. , Lipecz Agnes , Racz Frigyes Samuel , Zouein Fouad A. , Tabak Adam , Csiszar Anna , Ungvari Zoltan , Tsitouras Panayiotis D. , Yabluchanskiy Andriy
Published: May 2022

Background. Aging is a major risk factor for a range of chronic diseases. Oxidative stress theory of aging has been previously proposed as one of the mechanisms responsible for the age-related decline in organ/tissue function and the development of age-related diseases. Urine contains rich biological information on the health status of every major organ system and can be an important noninvasive source for biomarkers of systemic oxidative stress in aging. Aims. The objective of this cross-sectional study was to validate a novel panel of urinary oxidative stress biomarkers. Methods. Nucleic acid oxidation adducts and oxidative damage markers of lipids and proteins were assessed in urine samples from nondiabetic and currently nonsmoking subjects (

n
=
198

) across different ages (20 to 89 years old). Urinary parameters and chronological age were correlated then the biological age of enrolled individuals was determined from the urinary oxidative stress markers using the algorithm of Klemera and Doubal. Results. Our findings showed that 8-oxo-7,8-deoxyguanosine (8-oxoG), 8-oxo-7,8-dihydroguanosine (8-OHdG), and dityrosine (DTyr) positively correlated with chronological age, while the level of an F2-isoprostane (iPF2α-VI) correlated negatively with age. We found that 8-oxoG, DTyr, and iPF2α-VI were significantly higher among accelerated agers compared to nonaccelerated agers and that a decision tree model could successfully identify accelerated agers with an accuracy of >92%. Discussion. Our results indicate that 8-oxoG and iPF2α-VI levels in the urine reveal biological aging. Conclusion. Assessing urinary biomarkers of oxidative stress may be an important approach for the evaluation of biological age by identifying individuals at accelerated risk for the development of age-related diseases.