bluuebunny/crossref_metadata_2025 huggingface dataset:
Safety Monitoring Network Architecture of Water Release Structures Based on Intelligent Sensing Equipment for Concrete Abrasion
Authors: Li Zongmei , Su Xin
Published: October 2022

The concrete abrasion monitoring of water launch constructions is the key and hard factor in hydraulic engineering. With the development of technology, the present concrete abrasion monitoring techniques have made excellent progress; however, there are still some problems, such as the small monitoring range, and it is hard to totally mirror the diploma of abrasion damage. The smart sensing tools based totally on concrete abrasion is greater and extra used in engineering dimension due to the fact of its excessive precision and robust anti-interference ability. Based on the alive analysis accessory for accurate abrasion, this cardboard establishes the aegis ecology association anatomy of baptize barrage structures, selects the abstinent chafe advice of the project, incorporates out coaching modelling thru the education set, and forecasts the take a look at set. Through theoretical evaluation and accuracy verification test, it can be concluded that the smart sensing tools based totally on concrete abrasion can be used to measure the floor modifications of concrete materials, the size accuracy can attain 0.1 mm level, and the monitoring accuracy price can attain 95%, which can meet the necessities of concrete abrasion depth monitoring in hydraulic engineering.
Clinical Evaluation of Unilateral Vertebroplasty for OVCF
Authors: Wen Xiaoming , Zhang Yan , Jiang Wei , An Wenbo , Zhang Binggang , Liu Jianjun
Published: October 2022

Objective. To investigate the clinical evaluation of unilateral vertebroplasty for OVCF. Methods. A retrospective analysis was performed on 60 patients treated with PVP from January 2020 to December 2021. Patients were divided into two groups according to the treatment method, 30 patients in the PVP group received PVP and 30 patients in the PCVP group received PCVP. The VAS score, ODI score, bone cement dosage, and leakage were compared between the two groups preoperatively, immediately postoperatively, and 7 and 30 days postoperatively. Results. VAS scores in the PCVP and PVP groups before, immediately after, and 7 days after surgery were

P
>
0.05

, and the difference was not statistically significant; ODI score in group 1 before surgery was not statistically significant (

P
>
0.05

); bone cement injection volume in the PVP group was significantly higher than that in the PCVP group (

P
<
0.05

), and the difference was statistically significant; the difference in bone cement leakage between the two groups was not statistically significant (

P
>
0.05

). Conclusion. Under the same puncture conditions, the PCVP group used the method of injection while retreating to achieve a better bone cement dispersion effect by using less bone cement and achieving uniform dispersion of bone cement. It can relieve the patients’ back pain and improve the back function.
Parameter Optimization of Educational Network Ecosystem Based on BERT Deep Learning Model
Authors: Tao Sha
Published: October 2022

The key sentimental words in the text cannot be paid attention to effectively, and language knowledge such as the text information and the sentimental resources are relied on. Therefore, it is necessary to make full use of this unique sentimental information to achieve the best performance of the model. In order to solve the problems, a method based on the fusion of the convolutional neural network and the bidirectional GRU network text sentiment analysis capsule model to analyze the ideological and political education of public opinion is put forward. In this model, each sentiment category is combined with the attention mechanism to generate feature vectors to construct sentiment capsules. Finally, the text sentiment categories are judged according to the attributes of the capsules. The model is tested on MR, IMDB, SST-5, and the data set of the ideological and political education review. Experimental results show that compared with MC-CNN-LSTM, the readiness rate of the proposed model is improved by 5.1%, 2.8%, 2.8%, and 1.6% on four public Chinese and English data sets, respectively. Compared with LR-Bi-LSTM, NSCL, and multi-Bi-LSTM models, the accuracy of the proposed MC-BiGRU-Capsule model on MR and SST-5 data are 3.2%, 2.4%, and 3.4% higher than that of the LR-Bi-LSTM, NSCL, and multi-Bi-LSTM models, respectively. It also shows a better classification effect on multiclassification data sets. It is concluded that compared with other baseline models, this method has a better classification effect.
Research on Animated GIFs Emotion Recognition Based on ResNet-ConvGRU
Authors: Zhang Qian , Qing-Dao-Er-Ji Ren , Li Na
Published: October 2022

Animated Graphics Interchange Format (GIF) images have become an important part of network information interaction, and are one of the main characteristics of analyzing social media emotions. At present, most of the research on GIF affection recognition fails to make full use of spatial-temporal characteristics of GIF images, which limits the performance of model recognition to a certain extent. A GIF emotion recognition algorithm based on ResNet-ConvGRU is proposed in this paper. First, GIF data is preprocessed, converting its image sequences to static image format for saving. Then, the spatial features of images and the temporal features of static image sequences are extracted with ResNet and ConvGRU networks, respectively. At last, the animated GIFs data features are synthesized and the seven emotional intensities of GIF data are calculated. The GIFGIF dataset is used to verify the experiment. From the experimental results, the proposed animated GIFs emotion recognition model based on ResNet-ConvGRU, compared with the classical emotion recognition algorithms such as VGGNet-ConvGRU, ResNet3D, CNN-LSTM, and C3D, has a stronger feature extraction ability, and sentiment classification performance. This method provides a finer-grained analysis for the study of public opinion trends and a new idea for affection recognition of GIF data in social media.
How Electronic Cigarette Affects the Vascular System
Authors: Damay Vito Anggarino , Setiawan Setiawan , Lesmana Ronny , Akbar Mohammad Rizki , Lukito Antonia Anna , Bittoun Renee
Published: October 2022

The popularity of the electronic cigarette has soared in the last decades. However, the health effect of smoking electronic cigarettes on the vascular system is unclear. This systematic review examines the electronic cigarettes’ effect on the vascular system from recent evidence. A systematic search was conducted in MEDLINE (PubMed) database from January 2016 to August 2021 for studies assessing the vascular effect of chronic use of electronic cigarettes on human and animal. The Cochrane Risk of Bias 2, NIH Quality Assessment for Cross-Sectional Study, and SYRCLE’s Risk of Bias were used to assess the risk of bias in interventional, observational, and animal study, respectively. A narrative synthesis of evidence is provided to describe results. From 101 retrieved studies related to electronic cigarettes effect on the vascular system, a total of 16 studies are included in this review. The overall results indicated that electronic cigarette use is associated with adverse events in the vascular, including the incident of elevated oxidative stress, endothelial dysfunction, inflammation, arterial stiffness, and the development of atherosclerotic lesion. Further studies should broaden perspectives and reveal more about the mechanism of how electronic cigarettes impact on vascular system.
Impact of Chinese Herbal Medicine on Glucolipid Metabolic Outcomes in Women with Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis
Authors: Li Jie , Zheng Ruqun , Lin Zixin , Hu Fangyuan , Lin Ying , Zeng Guomei , Fang Jieni , Shen Yingyan , Tan Huiyan , Han Mei , Li Juan
Published: October 2022

Objective. This investigation was conducted to analyze and evaluate the impact of Chinese herbal medicine on glucolipid metabolism in women with polycystic ovary syndrome (PCOS). Methods. We used manual and computer-aided search methods, and the search scopes included Chinese databases (China National Knowledge Infrastructure, Wanfang, the China Science and Technology Journal Database, and the Chinese Biomedical Literature Database) and English databases (PubMed, Embase, Web of Science, and the Cochrane Library). We searched these eight databases for randomized controlled trials investigating the effects of Chinese herbal medicine on glucolipid metabolism in women with PCOS, with the retrieval deadline being June 2021. Two reviewers screened, selected, and extracted data and verified the results independently. The NoteExpress software was used to manage and screen the literature, the risk of bias assessment tool was used to evaluate the methodological quality of the included studies, and the RevMan 5.4 software was used for meta-analysis. Results. A total of 13 trials were included, including 825 patients with PCOS. Because the drugs used in the control group were different, we divided the results into two parts, with four trials using placebo and nine trials using metformin as the control. The results of the meta-analysis showed that fasting insulin (MD = −2.45, 95% CI = [−4.74, −0.17], P = 0.04), 2 h fasting plasma glucose (MD = −0.33, 95% CI = [−0.64, −0.02], P = 0.04), serum total cholesterol (MD = −0.38, 95% CI = [−0.58, −0.18], P = 0.0002), triglycerides (MD = −0.36, 95% CI = [−0.58, −0.14], P = 0.001), and low-density lipoprotein cholesterol (MD = −0.58, 95% CI = [−0.75, −0.41], P < 0.00001) were significantly improved in the Chinese herbal medicine group compared with the placebo group. In addition, compared with metformin, body mass index (MD = −1.04, 95% CI = [−1.55, −0.53], P < 0.0001), serum total cholesterol (MD = −0.27, 95% CI = [−0.46, −0.07] P = 0.007), and low-density lipoprotein cholesterol were significantly reduced (MD = −0.12, 95% CI = [−0.22, −0.02], P = 0.02) and high-density lipoprotein cholesterol (MD = 0.09, 95% CI = [0.02, 0.17], P = 0.01) was significantly improved after treatment with Chinese herbal medicine. Conclusion. Compared with the placebo group, Chinese herbal medicine had positive effects on glucolipid metabolism in women with PCOS. Chinese herbal medicine had a positive effect on lipid metabolism when the control group was metformin, but no effect on glucose metabolism. These findings need to be verified in high-quality, large-sample, randomized controlled trials in the future.
Safety Assessment of Tunnel Shield Construction for Existing Adjacent Bridges
Authors: Zhu Lei , Liang Chengcheng
Published: October 2022

Disturbances to the surrounding soil layer from a tunnel shield passing under a viaduct can cause uneven pile foundation settlement, negatively affecting the structure’s normal functionality. Therefore, its safety must be evaluated before tunneling. In this study, a numerical model is developed on Midas to simulate the differential settlement of pile foundations under a viaduct during the entire construction tunneling process. The evaluation basis is derived by verifying the various bearing capacities of the viaduct. The results indicate that when the shield excavation face is 12 m from the pile foundation axis, vertical displacement begins to appear and increases gradually as the excavation face approaches the pile foundation. The bearing capacity of the girder support and midspan section is lower than the section resistance and meets the specifications. In the anti-cracking calculation, when the bearing differential settlement is 5 mm, there is no tensile stress in the normal section of the main beam, and the tensile stress of the oblique section meets the specifications. Furthermore, in situations when the pressure must be verified, tthe calculation results meet the specifications. Based on this evaluation criteria, it is ultimately determined that the viaduct can be used normally after shield construction. This safety assessment method can serve as a reference for similar construction projects.
Muscone with Attenuation of Neuroinflammation and Oxidative Stress Exerts Antidepressant-Like Effect in Mouse Model of Chronic Restraint Stress
Authors: Liu Hua , Liu Lian Lin , Chen Jing , Chen Yue Wen , Chai Yue , Liu Qing Shan , Cheng Yong
Published: October 2022

Major depressive disorder (MDD) is a common mental disorder with high morbidity. Stress negatively affects for MDD development, whereby transport of stress-induced inflammatory mediators to the central nervous system (CNS) is associated with the etiology of mood disorders. Muscone is a pharmacologically active ingredient isolated from musk, with anti-inflammatory and neuroprotective effects. We hypothesized that muscone may ameliorate depression-like behavior by regulating inflammatory responses. To test this hypothesis, we used the chronic restraint stress (CRS) depression model, and CRS mice were treated with muscone (10 mg/kg, i.g., respectively) for 14 days. The effects of the drug on depressive-like behaviors were evaluated via the open field test (OFT), novelty-suppressed feeding test (NSFT), tail suspension test (TST), and forced swimming test (FST). Quantitative reverse transcription-PCR (qRT-PCR) was utilized to assess levels of proinflammatory cytokines (IL-6, TNF-α, COX2, and IL-1) and the anti-inflammatory cytokines (IL-4 and IL-10). We also determined levels of oxidative stress factors (malondialdehyde, superoxide dismutase, and glutathione peroxidase), as well as doublecortin (DCX) expression by immunofluorescence. The results showed that depression-like behavior and inflammatory levels were improved after muscone treatment. Muscone also significantly improved neurogenesis in the CRS mouse hippocampus and decreased oxidative stress in both the central and peripheral nervous systems. In conclusion, this work is the first to demonstrate that muscone has an antidepressant effect using a CRS model. Oxidative stress, neurogenesis, and inflammatory pathways are key factors affected by the drug and may represent new therapeutic targets to treat MDD, in this impact. These results may represent a new therapeutic target for MDD.
Analysis of Human Resource Allocation Scheme for Digital Media Big Data Based on Recurrent Neural Network Model
Authors: Fang Ran , Fang Zhihuai
Published: October 2022

At present, all kinds of computing models used in human society are based on statistics. Due to the large amount of data, conventional statistical methods cannot solve these problems well. In view of the concealment of data, the processing of large data plays a great role in the rational allocation of human resources, training professional talents, improving the operation of human resources, and improving the use and efficiency of human resources. This paper combines the method of human resource allocation based on recurrent neural network and conventional human resource allocation, in order to find a suitable method for personnel position selection and recommendation in the field of talent work. In terms of algorithm test, the F1 value of the proposed method is 0.823, which is 20.1% and 7.4% higher than the previous two methods, respectively, indicating that the method can effectively improve the hidden features, improve the training effect, and improve the performance of the model.
Expression Profiles and Functional Analysis of Plasma Exosomal Circular RNAs in Acute Myocardial Infarction
Authors: He Guo-dong , Li Jie , Nie Zhi-qiang , Sun Shuo , Feng Ying-qing , Huang Yu-qing
Published: October 2022

Acute myocardial infarction (AMI) is a common cardiovascular disease with high rates of morbidity and mortality globally. The dysregulation of circular RNAs (circRNAs) has been shown to be closely related to various pathological aspects of AMI. However, the function of exosomal circRNAs in AMI has yet to be investigated. The purpose of this study was to investigate the expression profiles of plasma exosomal circRNAs in AMI and explore their potential functionality. The expression profiles of plasma exosomal circRNAs in patients with AMI, stable coronary heart atherosclerotic disease (CAD), and healthy controls were obtained from a GEO expression dataset (GSE159657). We also analyzed bioinformatics functionality, potential pathways, and interaction networks related to the microRNAs associated with the differentially expressed circRNAs. A total of 253 exosomal circRNAs (184 up‐ and 69 down‐regulated) and 182 exosomal circRNAs (94 up‐ and 88 down‐regulated) were identified as being differentially expressed between the control group and the AMI and CAD patients, respectively. Compared with the CAD group, 231 different exosomal circRNAs (177 up‐ and 54 down‐regulated) were identified in the AMI group. Functional analysis suggested that the parental genes of exosomal has_circ_0061776 were significantly enriched in the biological process of lysine degradation. Pathway interaction network analysis further indicated that exosomal has_circ_0061776 was associated with has‐miR‐133a, has‐miR‐214, has‐miR‐423, and has‐miR‐217 and may play a role in the pathogenesis of AMI through the MAPK signaling pathway. This study identified the differential expression and functionality of exosomal circRNAs in AMI and provided further understanding of the potential pathogenesis of an exosomal circRNA‐related competing endogenous RNA (ceRNA) network in AMI.
System Analysis of the Learning Behavior Recognition System for Students in a Law Classroom: Based on the Improved SSD Behavior Recognition Algorithm
Authors: Guo Qingmei
Published: October 2022

Classroom teaching activities have always been the focus of research in the field of pedagogy. The main body of classroom teaching activities is students, and students’ classroom behavior status can reflect classroom efficiency to a certain extent, making it an important reference index for classroom quality assessment. With the rapid development of artificial intelligence, school education is gradually becoming more intelligent. At present, most of the classrooms are equipped with video equipment. These videos record the real behavior status of the students in the classroom. For example, by analyzing the data, combining artificial intelligence, deep learning, and other related technologies with education to develop behavioral intelligence, the analysis system has a certain positive effect on helping the reform of classroom education. This study proposes an improved SSD behavior recognition model. The network model is optimized and the model convergence speed is accelerated based on the RMSProp optimization algorithm Through a database of 2,500 images of five behaviors, including raising hands, sitting up, writing, sleeping, and playing with mobile phones, and using them as object detection datasets, we use the OpenCV library to extract frames from classroom screen recording videos as image data sources for student behavior recognition and face recognition. Finally, an improved method is proposed to change the virtual network to MobileNet and complete the fusion function. The results show that compared with the traditional SSD method, the improved model has a significantly improved effect in recognizing small objects and the recognition speed is not significantly reduced.
Mesenchymal Stem Cell-Derived Exosomes Ameliorate Delayed Neurocognitive Recovery in Aged Mice by Inhibiting Hippocampus Ferroptosis via Activating SIRT1/Nrf2/HO-1 Signaling Pathway
Authors: Liu Jie , Huang Jingyao , Zhang Zhenjiang , Zhang Rui , Sun Qijuan , Zhang Zhihao , Liu Yongxin , Ma Baoyu
Published: October 2022

Delayed neurocognitive recovery (dNCR) is a prevalent perioperative neurological complication in older patients and has common characteristics such as acute cognitive dysfunction, impaired memory, and inattention. Mesenchymal stem cell-derived exosomes (MSCs-Exo) are enclosed by a lipid bilayer contain proteins, DNA, miRNA, and other components, which are important mediators of intercellular communication. It has been reported that exosomes could play an important role in the treatment of neurodegenerative diseases, nerve injury, and other neurological diseases. In this study, we examined the effects of MSCs-Exo on dNCR aged mice after exploratory laparotomy and evaluated their potential regulatory mechanisms. We found that MSCs-Exo treatment ameliorated cognitive impairment in dNCR aged mice. MSCs-Exo inhibit hippocampus ferroptosis and increase the expression of silent information regulator 1 (SIRT1), factor nuclear factor-erythroid 2-related factor 2 (Nrf2), and heme oxygenase-1 (HO-1) in dNCR aged mice. Interestingly, the above effects of MSCs-Exo on dNCR aged mice were abolished by SIRT1 selective inhibitor EX-527. In conclusion, these findings indicated that MSCs-Exo can ameliorate cognitive impairment by inhibiting hippocampus ferroptosis in dNCR aged mice via activating SIRT1/Nrf2/HO-1 signaling pathway, providing a potential avenue for the treatment of dNCR.
Resetting Proteostasis of CIRBP with ISRIB Suppresses Neural Stem Cell Apoptosis under Hypoxic Exposure
Authors: Zou Yuankang , Yuan Ziyan , Sun Yafei , Zhai Maodeng , Tan Zhice , Guan Ruili , Aschner Michael , Luo Wenjing , Zhang Jianbin
Published: October 2022

Neurological disorders are often progressive and lead to disabilities with limited available therapies. Epidemiological evidence implicated that prolonged exposure to hypoxia leads to neurological damage and a plethora of complications. Neural stem cells (NSCs) are a promising tool for neurological damage therapy in terms of their unique properties. However, the literature on the outcome of NSCs exposed to severe hypoxia is scarce. In this study, we identified a responsive gene that reacts to multiple cellular stresses, marked cold-inducible RNA-binding protein (CIRBP), which could attenuate NSC apoptosis under hypoxic pressure. Interestingly, ISRIB, a small-molecule modulator of the PERK-ATF4 signaling pathway, could prevent the reduction and apoptosis of NSCs in two steps: enhancing the expression of CIRBP through the protein kinase R- (PKR-) like endoplasmic reticulum kinase (PERK) and activating transcription factor 4 (ATF4) axis. Taken together, CIRBP was found to be a critical factor that could protect NSCs against apoptosis induced by hypoxia, and ISRIB could be acted upstream of the axis and may be recruited as an open potential therapeutic strategy to prevent or treat hypoxia-induced brain hazards.
Machine-Vision-Based Enhanced Deep Genetic Algorithm for Robot Action Analysis
Authors: Wang Guifeng , Zhang Lu-ming , Sheng Yichuan
Published: October 2022

The machine-driven products processed by CNC machine tools are divided into multiple parts, which are often transmitted to unqualified processing crystals due to the error of the part’s posture, thus affecting the projection effect. Aiming at handling this problem, we, in this work, propose a method for locating and correcting machine capabilities based on bicycle visual recognition. The robot obtains coordinates and offset points through the vision system. In order to satisfy the requirement of fast sorting of the robot parts, a robot species method (BAS-GA) that supports machine vision and improved genetic algorithm rules is proposed. The rank method first preprocesses the part copies, then uses the Sift feature twin similarity notification algorithm to filter the part idols, and finally uses in-law deformation to place the target parts. Afterward, an particular model is built for the maintenance of the nurtural skill, and the mathematical mold is solved using the BAS-GA algorithmic program authority. The close trail of the robot is maintained to manifest the marijuana of the robot. Experimental inference have shown that the BAS-GA algorithm rule achieves the optimal conclusion similar to the pseudo-annealing algorithmic program plant. Meanwhile, the genetic algorithm rule is modified ant settlement algorithm program. Knife sharpening was also reduced by 7%, inferring that this process can effectively improve the robot’s action success rate.
Parsing Chinese with Combinatory Categorial Grammar: A Linguistic and Computational Study
Authors: Man Haixia , Wan Manyi , Shi Yunbao , Chen Peng
Published: October 2022

Parsing Chinese language with CCG is very difficult because the architecture and assumptions of CCG do not fit well with facts from Chinese. Based on the concept of “realization” proposed by Zhu Dexi (1920–1992), this study sheds light on the discrepancy between CCG and Chinese syntax and puts forward a refined schema for Chinese compositionality. The discussion is supported by the data of Chinese CCGbank (CASS). Furthermore, by activating a function‐based category setting and a noun/verb disambiguating tagging mechanism, we develop a rule‐based mini‐Chinese CCG parser without deep learning. The new NVN parser surpasses existing Chinese CCG parser C&C in parsing effect (LF 85.9 vs. LF 74.6) on a partial PCTB 6.0 test set of 500 sentences.
Effects of a Proposed Unit Based on the STEM Approach in Developing Fundamental Science Processes for Kindergarteners in Makah Al-Mukarramah
Authors: Hassan Ghandourah Ebtehal Saleh
Published: October 2022

This study explored how a proposed unit based on the STEM approach affected the development of some basic science processes among kindergarteners in Makkah Al-Mukarramah. The descriptive-analytical method was thus employed, followed by an experimental approach with semi-experimental design for one group of children. The study tools included an image test for basic science operations. Furthermore, supportive materials were established, consisting of a proposed unit based on the STEM approach that included a teacher’s guide and activities for children. The study tools were tested for validity and reliability, with applications before and after among a sample of 30 children (girls and boys) from Al-Ma’ali kindergarten in Makkah during the first semester of 1443. The most important findings were as follows: there were statistically significant differences between the average scores of children in the pre- and postapplications for testing basic science operations. As all t-test values for scientific operations were statistically significant at the <0.05 level, these differences were in the direction of application in the dimension with a higher arithmetic mean. In light of this evidence, several recommendations and proposals are offered. First, the results emphasized the usefulness of the STEM approach at the kindergarten stage, as this positively affected the development of basic science processes for kindergarten children. Second, this study recommends holding training sessions for kindergarten supervisors and teachers to introduce the STEM approach, its significance, and ways to apply it in the daily kindergarten program. Finally, this study highlights the need for additional research on the effectiveness of the STEM approach in the development of many different variables, including problem-solving skills, creative thinking, and 21st-century skills among kindergarten children.
Application of Nursing Outcome-Oriented Integrated Zero-Defect Nursing Combined with Respiratory Function Training in Long-Term Bedridden Patients Undergoing Stroke
Authors: Xu Shaona , Yu Yanan , Liu Hongling , Qiu Weiwei , Tang Yu , Liu Ying
Published: October 2022

Objective. To explore the application effect of nursing outcome-oriented integrated zero-defect nursing combined with respiratory function training in long-term bedridden patients with stroke. Methods. A total of 120 long-term bedridden patients with stroke were randomly divided into three groups: groups A, B, and C. Group A was given nursing outcome-oriented integrated zero-defect nursing combined with respiratory function training, group B was given nursing outcome-oriented integrated zero-defect nursing, and group C was given routine nursing. Rosenbek aspiration degree classification criteria were used to evaluate the incidence of aspiration; blood oxygen saturation, arterial oxygen partial pressure, and respiratory pressure were compared before and after the intervention. The swallowing function was evaluated by a water swallowing test (WST). The quality of life was assessed using the Generic Quality of Life Inventory-74 (GQOLI-74). Results. After treatment, the Rosenbek aspiration degree of groups A and B were better than those of group C (

P

 < 0.05); the improvement degree of respiratory function indexes in group A was better than those in B and C, and the blood oxygen saturation and arterial blood oxygen partial pressure in group B were better than those in C (

P

 < 0.05). The incidence of complications in groups A and B was lower than that in C, and complications in group A were lower than that in B (

P

 < 0.05). After treatment, the scores of psychological function, social function, and material life status of the three groups were increased, and each score of groups A and B was higher than that of C, and each score of group A was higher than that of B (

P

 < 0.05). Conclusion. Nursing outcome-oriented integrated zero-defect nursing combined with respiratory function training can effectively improve aspiration, respiratory function, swallowing function, complication rate, and quality of life in long-term bedridden patients with stroke.
[Retracted] The Influence of Air Pollution on Pulmonary Disease Incidence Analyzed Based on Grey Correlation Analysis
Authors: Jiao Yujiao , Gong Cuike , Wang Shusen , Duan Yuling , Zhang Yang
Published: October 2022

Air pollution is a primary health threat issue worldwide because it is closely concerned with respiratory diseases. A random survey reported that around 7 million people died because of ambient and household air pollution. Especially, the people suffering from asthma and chronic obstructive pulmonary disease (COPD) are highly affected by air pollutants. The air pollution components induce asthma onset and COPD acute exacerbation, which leads to maximized mortality and morbidity rate. Therefore, the influence of air pollution on COPD should be examined continuously to minimize the mortality rate. Several methods are presented in this field to investigate the relationship between health and pollutants. However, the existing approaches are only predicting the short‐term data and have difficulties such as computation time, redundant data in large data analysis, and data continuity. Then, this research introduced the meta‐heuristic optimized grey correlation analysis (MH‐GCA) to solve the research difficulties. The correlation analysis has several models that identify the relationship between the pollution factors with COPD disease. The method analysis of the particulate matter (〖PM〗_10) in air pollution is more relevant to COPD and lung cancer disease. The grey analysis uses the uncertainty concept to identify the particle influence on air pollution. In the analysis, the cuttlefish optimization algorithm was applied to select more relevant features from the pollutant list that reduces the computation time and correlation analysis rate. The introduced system was evaluated using the air quality dataset and COPD dataset developed with the help of the MATLAB tool. The system increases the influence recognition accuracy (2.48%) and MCC (3.11%) and decreases the error rate (55.89%) for different pollutants.
Prediction of Long-term Variation of Ocean Circulation Based on Grey Correlation Clustering
Authors: Ma Na , Yang Guoshu
Published: October 2022

In order to study the change of circulation in the South China Sea, the author puts forward the research on the distribution and change of water masses in the South China Sea based on grey correlation clustering. Based on the wod21 temperature and salt observation data of the South China Sea from 1966 to 2013, this paper uses the grey correlation clustering algorithm to divide the water masses in the whole sea area and 5° ×5° small areas and analyzes the distribution, temperature, salt properties, and seasonal changes of each water mass in the South China Sea combined with the systematic clustering method and T-S point clustering map. The experimental results show that in the vertical division, the South China Sea water mass is divided into five layers: surface water, subsurface water, sub-middle water, middle water, and deep water. The deep water in the South China Sea is mainly distributed in the basin with a depth of 900 m. The temperature value is lower than 5.5°C and the salinity range is 34.30–34.70. The properties and changes of water masses obtained in this paper are consistent with the existing conclusions, which shows that the grey correlation clustering algorithm is efficient and accurate in the division of water masses in the South China Sea.
A Decision Support System Model for Middle School Education Management Based on Sparse Clustering Algorithm
Authors: Peng Bin , Pei Xinhua
Published: October 2022

With the development of China’s economy, education has also been greatly improved, and the enrollment scale has been continuously expanded. It has become increasingly difficult to manage student performance. The traditional manual management of student grades has shortcomings such as low efficiency, poor privacy, difficulty to find and maintain, and incomplete knowledge mining of student grade data resources, so it is impossible to fully test and utilize related technologies. Based on this background, this paper designs and develops a set of decision support systems for middle school education management combined with a sparse clustering algorithm according to the actual needs of middle school education. The article first introduces the concept of sparse clustering algorithm and the four levels of the decision support system for middle school education management, data layer, model layer, application layer, and display layer, and then introduces based on five system models, namely, database design, online analysis process module design, data mining design, model library design, function design, and finally, the system model of educational decision management support is constructed, and the model test is completed. The practice shows that the system proposed in this paper can manage the current educational information of students scientifically, extract the information from the changes in students’ achievements in time, and make certain assistance for teachers’ educational decisions. This paper designs an effective decision support system by studying the sparse clustering algorithm and introducing it into the field of middle school education management.
Environmental Policy Selection and Town Resident Satisfaction Assessment: Under Governance of Localism
Authors: Wang Kuo-Yan , Yu Jing , Ning Chia-Yang
Published: October 2022

Upper authorities have tightly controlled local budgets, especially at the administrative township level. Taiwan has been facing this particular phenomenon for a long period. This article explains how a township, before general elections, sees the choice of an improved environmental administrative work plan as a political advantage and uses simple and easy‐to‐use collective decision‐making to assist. Then, survey residents’ perceptions of implementing the new environmental policy. The research results are discussed not only as suggestions to improve the effectiveness of township public environmental policies and to respond to the needs of civilians appropriately but also to lead future research directions.
Intelligent Algorithm‐Based Ultrasound Images in Evaluation of Therapeutic Effects of Radiofrequency Ablation for Liver Tumor and Analysis on Risk Factors of Postoperative Infection
Authors: Kexin Lou , Ning Chen , Zhihong Li , Shuo Xiao , Rong Wu
Published: October 2022

This research aimed to explore the therapeutic effects of radiofrequency ablation (RFA) for liver tumors and to investigate the postoperative infection factors. Specifically, 80 patients with liver tumors undergoing ultrasound‐guided FRA were selected as research subjects. They were diagnosed in the hospital. An intelligent fitting (IF) algorithm was compared with a genetic algorithm (GA) and applied to the RFA of the 80 patients. It was found that the running time of the IF algorithm was about 0.2 times than that of the GA, demonstrating better global searching capabilities. The mean diameter of single liver tumors was (3.45 ± 1.24) cm, and the complete ablation rate of tumors with diameters less than 3 cm was 87.88%, that of tumors with diameters of 3–5 cm was 72.92%, and that of tumors with a diameter of more than 5 cm was 63.33%. Posttreatment, the AST level decreased significantly and the ALB level increased significantly, and the difference was notable (P < 0.05 P<); the TBIL level (36.8 ± 9.7 umol/L) was lower than prior treatment (17.9 ± 8.5 umol/L) and the ALT level (45.2 ± 6.8 g/L) was lower than prior treatment (19.6 ± 5.7 g/L), showing a notable difference (P < 0.05 P<). The diameter, whether there was great vessel invasion, and TNM staging were associated with infection after RFA, and the difference was notable. The ultrasound images can effectively evaluate the therapeutic effects of RFA and the degree of inactivation of liver tumors. In addition, the tumor stage was an independent risk factor for postoperative infection.
An Empirical Analysis of the Impact of Environmental Protection Tax on Corporate Earnings Management
Authors: Zhang Jing , Han Shizhuan , Shan Juan
Published: October 2022

The environmental protection tax (EPT) is an important environmental regulation measure in China and an important guarantee for high-quality economic development. An important measure for the construction of ecological civilization is that local governments promote the construction and improvement of EPT in the way of “Fee-to-Tax.” The EPT regulates pollution control, protects and improves the environment through taxation, and forms an effective mechanism for polluters to promote ecological civilization. This study made use of the data collected from different listed companies in Shanghai and Shenzhen provinces from 2010 to 2019, discussing the impacts of EPT on enterprise earnings management. An enterprise analysis model based on IoT-edge computing is suggested to decrease the processing time. The results of the empirical analysis completed in this study showed a significant positive correlation between EPT and enterprise earnings management. In other words, EPT increases the motivation of enterprise earnings management. Moreover, there is heterogeneity in the driving force of EPT on enterprise earnings management. For example, we observed that state-owned enterprises are significantly higher than non-state-owned enterprises. Moreover, pollution-intensive enterprises are significantly higher than non-pollution-intensive enterprises, and economically developed areas are significantly better than economically underdeveloped areas. In order to give better play to the effectiveness of EPT in modern environmental governance, the government should continue to improve the construction of EPT and speed up the construction process of ecological civilization in the republic of China.
Colchicine Does Not Reduce Abdominal Aortic Aneurysm Growth in a Mouse Model
Authors: Phie James , Thanigaimani Shivshankar , Huynh Pacific , Anbalagan Raghuveeran , Moran Corey S. , Kinobe Robert , Moxon Joseph V. , Field Matt A. , Krishna Smriti M. , Golledge Jonathan
Published: October 2022

Background and Aims. The nacht domain, leucine-rich repeat, and pyrin domain-containing protein 3 (NLRP3) inflammasome is upregulated in human abdominal aortic aneurysm (AAA), but its pathogenic role is unclear. The aims of this study were firstly to examine whether the inflammasome was upregulated in a mouse model of AAA and secondly to test whether the inflammasome inhibitor colchicine limited AAA growth. Methods. AAA was induced in eight-week-old male C57BL6/J mice with topical application of elastase to the infrarenal aorta and oral 3-aminopropionitrile (E-BAPN). For aim one, inflammasome activation, abdominal aortic diameter, and rupture were compared between mice with AAA and sham controls. For aim two, 3 weeks after AAA induction, mice were randomly allocated to receive colchicine (

n
=
28

, 0.2 mg/kg/d) or vehicle control (

n
=
29

). The primary outcome was the rate of maximum aortic diameter increase measured by ultrasound over 13 weeks. Results. There was upregulation of NLRP3 markers interleukin- (IL-) 1β (median, IQR; 15.67, 7.11-22.60 pg/mg protein versus 6.87, 4.54-11.60 pg/mg protein,

p
=
.048

) and caspase-1 (109, 83-155 relative luminosity units (RLU) versus 45, 38-65 RLU,

p
<
.001

) in AAA samples compared to controls. Aortic diameter increase over 80 days (mean difference, MD, 4.3 mm, 95% CI 3.3, 5.3,

p
<
.001

) was significantly greater in mice in which aneurysms were induced compared to sham controls. Colchicine did not significantly limit aortic diameter increase over 80 days (MD -0.1 mm, 95% CI -1.1, 0.86,

p
=
.922

). Conclusions. The inflammasome was activated in this mouse model of AAA; however, daily oral administration of colchicine did not limit AAA growth.
Efficacy and Safety of Glycosides of Tripterygium wilfordii Combined with Renin-Angiotensin System in the Treatment of IgA Nephropathy: A Systematic Review and Meta-Analysis
Authors: Chen Ming , Zhang Peiqing , Li Lianhua , Yu Zhuo , Liu Na , Wang Lifan
Published: October 2022

Background. IgA nephropathy (IgAN) is currently the most common primary glomerular disease, accounting for approximately 36.7% to 58.2% of primary glomerular disease in kidney biopsies in China. Definitive diagnosis depends on immunopathological examination of the kidney. The prognosis of this disease was generally considered to be good, but recent studies have found that about half of patients can progress to end-stage renal disease within 30 years of onset. Because the pathogenesis is unknown, there is no specific treatment. Objective. To evaluate the efficacy and safety of glycosides of Tripterygium wilfordii (GTW) in combination with renin-angiotensin system (RAS) inhibitors for the treatment of IgAN. Methods. Search Embase, Pubmed, Cochrane, CNKI, Web of Science, Wanfang, and VIP for all randomized controlled trials (RCTs) on treating IgAN with RASI from the self-built database to December 2021. Relevant data were searched and collected separately by two reviewers. The Cochrane risk of bias model was used for quality assessment, and RevMan 5.3 was used for data analysis. Results. Thirteen Chinese publications with a total of 958 patients were finally included. There was no statistically significant difference in baseline information (including laboratory data and clinical parameters) between the two groups of patients. The urine protein quantification in both groups showed a significant decreasing trend as the treatment duration increased. At 3, 6, 9, and 12 months after treatment, urine protein was significantly lower than the baseline value in both the observation and control groups (P < 0.05). During the follow-up period, there was no statistical difference in blood creatinine (Scr) and eGFR values between the two groups compared with the baseline values (P > 0.05). Patients with CKD stage 2 achieved a higher remission rate compared with patients with CKD stage 3, with a statistically significant difference (P < 0.05), and the difference between the two groups was not significant for patients in the same stage. There was no statistically significant difference in the total effective rate between the two groups (P > 0.05). During the follow-up period, there was no statistically significant difference in urine protein quantification, Scr, and eGFR between the two groups. In terms of the incidence of adverse reactions, the observation group was less than the control group, and there was a significant difference between the two groups (P < 0.05). Conclusion. GTW combined with RASI is one of the safe and effective treatment modes for IgAN nephropathy. It can not only effectively reduce the excretion of urinary protein in patients and delay the progression of chronic kidney disease but also has less serious side effects and is well tolerated by patients, so it can be a new choice of therapeutic drugs for this group of patients.
A Generalized Definition of Fuzzy Subrings
Authors: An Ying-Ying , Shi Fu-Gui , Wang Lan
Published: October 2022

In this study, under the condition that L is a completely distributive lattice, a generalized definition of fuzzy subrings is introduced. By means of four kinds of cut sets of fuzzy subset, the equivalent characterization of L‐fuzzy subring measures are presented. The properties of L‐fuzzy subring measures under these two kinds of product operations are further studied. In addition, an L‐fuzzy convexity is directly induced by L‐fuzzy subring measure, and it is pointed out that ring homomorphism can be regarded as L‐fuzzy convex preserving mapping and L‐fuzzy convex‐to‐convex mapping. Next, we give the definition and related properties of the measure of L‐fuzzy quotient ring and give a new characterization of L‐fuzzy quotient ring when the measure of L‐fuzzy quotient ring is 1.
A Deep Neural Network-Based Model for Quantitative Evaluation of the Effects of Swimming Training
Authors: Hou Jun-Jie , Tian Hui-Li , Lu Biao
Published: October 2022

This paper analyzes the quantitative assessment model of the swimming training effect based on the deep neural network by constructing a deep neural network model and designing a quantitative assessment model of the swimming training effect. This paper addresses the problem of not considering the influence of the uncertainties existing in the virtual environment when evaluating swimming training and adds the power of the delays in the actual training operation environment, which is used to improve the objectivity and usability of swimming training evaluation results. To better measure the degree of influence of uncertainties, a training evaluation software module is developed to validate the usability of the simulated training evaluation method using simulated case data and compare it with the data after training evaluation using the unimproved evaluation method to verify the correctness and objectivity of the evaluation method in this paper. In the experiments, the feature extractor is a deep neural network, and the classifier is a gradient-boosting decision tree with integrated learning advantages. In the experimental comparison, we can achieve more than 60% accuracy and no more than a 1.00% decrease in recognition rate on DBPNN + GBDT, 78.5% parameter reduction, and 54.5% floating-point reduction on DPBNN. We can effectively reduce 32.1% of video memory occupation. It can be concluded from the experiments that deep neural network models are more effective and easier to obtain relatively accurate experimental results than shallow learning when facing high-dimensional sparse features. At the same time, deep neural networks can also improve the prediction results of external learning models. Therefore, the experimental results of this model are most intuitively accurate when combining deep neural networks with gradient boosting decision trees.