bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single-center experience of endovascular treatment for patients with progressive posterior circulation cerebral infarction exceeding 24 h
Authors: Zhao Guangfeng , He Xiongjun , Liu Yajie , Zhang Liang , Li Kaifeng 
Published: September 2023

Abstract

Background
Evidence of endovascular treatment (ET) for patients with progressive infarction of the posterior circulation exceeding 24 h is lacking.

Objective
To evaluate the efficacy and safety of ET for progressive posterior circulation cerebral infarction.

Methods
This retrospective study evaluated the ET for 18 patients with posterior circulation infarction caused by vertebrobasilar artery occlusion from July 2017 to November 2018. The conditions of patients worsened despite receiving intravenous thrombolysis or combination therapy with clopidogrel and aspirin. The time from the onset of cerebral infarction to puncture was >24 h. The preoperative National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), and related risk factors of patients at 3 months were analyzed postoperatively.

Results
The preoperative NIHSS score was 10.6 (IQR: 6.5), and the time from onset to puncture was 163.5 ± 144.7 h. Postoperative blood flow was modified thrombolysis in cerebral infarction (mTICI) grade 2b or above. During the follow-up period, 1 patient died of basilar artery re-occlusion and pulmonary infection, and 1 died of postoperative hyperperfusion hemorrhage, with a mortality rate of 11.1% (2/18). No recurrent ischemic events were observed in any of the 16 patients during the 3-month follow-up period. The mean mRS score was 1.3 (IQR: 2.3), and 75% patients (12/16) had an mRS score of 0–2. There were no significant differences in age, gender, clinical characteristics, and stroke subtype between patients with mRS scores ≤2 and >2.

Conclusion
In patients with progressive posterior circulation cerebral infarction caused by vertebral basilar artery occlusion, ET is effective and safe even if the time from onset to puncture exceeds 24 h.
Acidic environment could modulate the interferon-γ expression: Implication on modulation of cancer and immune cells’ interactions
Authors: Sharma Vishal , Kaur Jagdeep 
Published: September 2023

Abstract

Background
In rapidly growing solid tumors, insufficient vascularization and poor oxygen supply result in an acidic tumor microenvironment, which can alter immune response.

Objective
To investigate the role of the acidic microenvironment in immune response modulation along with cancer and immune cells’ interactions.

Method
To mimic the tumor microenvironment conditions, T cells (Jurkat), macrophages (THP-1), and HeLa (cervical) cells were cultured under acidic conditions (pH 6.9, pH 6.5) and physiological pH (7.4). The HeLa cell culture medium was exploited as a tumor cell conditioned medium. Real-time PCR was carried out to quantify the mRNA levels, while flow cytometry and western blot hybridization was carried out to ascertain the levels of different proteins.

Results
The acidic microenvironment around the T cells (Jurkat) and macrophage cells (THP-1) could lead to the downregulation of the interferon gamma (IFN-γ). An increase in IFN-γ expression was observed when Jurkat and macrophage cells were cultured in HeLa cells conditioned medium (HCM) at low pH (pH 6.9, pH 6.5). The HeLa cells under acidic environment (pH 6.9, pH 6.5) upregulated interleukin 18 levels and secreted it as exosome anchored. Additionally, enhanced nuclear localization of NF-κB was observed in Jurkat and THP-1 cells cultured in HCM (pH 6.9, pH 6.5). Jurkat and THP-1 cultured in HCM revealed enhanced cytotoxicity against the HeLa cells upon reverting the pH of the medium from acidic to physiological pH (pH 7.4).

Conclusion
Collectively, these results suggest that the acidic microenvironment acted as a key barrier to cancer and immune cells’ interactions.
New Applications on the Flows of Space-like curves specified by Normal acceleration in Minkowski Space ℝ2,1
Authors: Al Elaiw Abeer , Gaber Samah 
Published: September 2023

Abstract
This paper investigates the kinematic motions of space-like and time-like curves specified by acceleration fields in Minkowski space ℝ2,1. Through the motion, the relationship between the acceleration fields and velocity fields is determined. In this study, we focus on studying the flows of inextensible space-like curves with a space-like principal normal vector specified by a normal acceleration that equals the curvature of the curve. Through the motion of the inextensible space-like curve with normal acceleration, we prove that the position vector of the curve satisfies a one-dimensional wave equation. We present some novel applications and visualize the flows of curves and their curvatures.
A Study on Normal Motion of the Torus of Revolution in ℝ3
Authors: Gaber Samah , Alfadhli Norah , Mahmoud Elsayed I. 
Published: September 2023

Abstract
In the present research paper, we investigate the motion of surfaces in ℝ3 according to their curvatures. We study the motion of the torus of revolution via the normal velocity. We consider two cases: when the normal velocity is a function of both the time and the coordinates of the torus, and when it is a function of time only. We also study how the torus moves under different types of curvature flows, such as inverse mean curvature flow, inverse Gaussian curvature flow, and harmonic mean curvature flow. Moreover, we present some new applications of these flows.
Research on the cultivation mechanism of “double-creative” talents in ethnic regions with the integration of industry and education in the context of the Internet
Authors: Lu Caixiu 
Published: September 2023

Abstract
In the context of the rapid development of the Internet and big data technology, it is both an opportunity and a challenge for cultivating “dual-innovation” talents in ethnic regions. This paper proposes a fuzzy hierarchical analysis-fuzzy comprehensive evaluation model to study the cultivation mechanism of “dual-creative” talents in ethnic regions. The fuzzy hierarchical analysis-fuzzy comprehensive evaluation model consists of the evaluation system, a fuzzy comprehensive evaluation method, and a fuzzy hierarchical analysis. Then, based on the characteristics of fuzzy hierarchical analysis, the factors are organized and stratified to obtain a reasonable index set and build a hierarchical analysis structure. Using the fuzzy comprehensive evaluation method to analyze the school-enterprise cooperation in the integration of industry education in Tibetan higher vocational colleges, the results show that 55.4% of the students chose extremely unsatisfactory and unsatisfactory, indicating that they are not satisfied with the current communication status between the school and the internship enterprises, and another 28.6% of the students chose uncertainty full or unsatisfactory. This study explores the causes of the problems in the integration of industry-education personnel training from four levels: government, enterprises, society, and schools, and proposes guiding reference values for the integration of industry-education personnel training in Tibetan higher education institutions.
Application of biofilm-membrane bioreactor in municipal wastewater treatment
Authors: Li Qi , Qian Yue , Shi Yuhang , Miao Yuyin , Luo Min 
Published: September 2023

Abstract
To verify the feasibility of biofilm-membrane bioreactor in municipal wastewater treatment. In this paper, based on the Fourier series algorithm, the basic configuration of biofilm-membrane bioreactor, the design of membrane bioreactor test index and method, the proposed urban wastewater treatment system based on biofilm-membrane bioreactor, and the creation of experiments to verify the biofilm-membrane bioreactor with the example of urban wastewater in the sewer of residential buildings in the district on the two CODCr and NH4
+-N in urban wastewater in municipal wastewater. The results showed that the removal rate of CODCr in municipal wastewater by the biofilm-membrane bioreactor system increased with time, and the removal rate was stable at about 83%. The NH4
+-N removal rate increased with time and was stable between 85 and 90%. It can be shown that biofilm-membrane bioreactor can sufficiently reduce the concentration of CODCr and NH4
+-N in municipal wastewater, thus promoting municipal wastewater treatment. It also presents a new solution for urban wastewater treatment.
Innovative cultivation path of great craftsmanship based on logistic regression model
Authors: Wang Wenhui 
Published: September 2023

Abstract
The word “craftsmanship” appeared for the first time in the 2016 Chinese government work report, bringing it back to the public eye. In the Industry 4.0 era, China has accelerated the transformation from manufacturing power to manufacturing energy, and various parties in the society have higher and higher requirements for talent. The “craftsmanship” fits the content of patriotism and professionalism in the core socialist values and the new concept of contemporary China’s development. Therefore, the cultivation of craftsmanship should be vigorously advocated in society, and a new path of cultivating craftsmanship should be explored. This paper analyzes the factors influencing the cultivation of craftsmanship through a logistic regression model based on a large number of vivid cases, and the research on the cultivation path around the cultivation status of “craftsmanship” can more vividly explain the essence of craftsmanship to people; it proposes to use the multiple logistic regression correlation in statistics to estimate Then, the logistic regression algorithm is applied to the product quality assurance, and the success rate of each node is calculated by analyzing the correlation between various characteristic factors and product quality to obtain the best cultivation path of craftsmanship innovation. This study shows that after one month of craftsmanship training, the product perfection rate of CM employees reached 93%, and the defect rate decreased by 13.6%, reflecting that craftsmanship has dramatically improved the product quality and laid a solid foundation for the long-term development and brand influence of the company.
Research on Fault Prevention and Maintenance System of Automatic Substation Primary Equipment Based on Decision Tree Algorithm
Authors: Wang Xinyue 
Published: September 2023

Abstract
Electric power enterprises are developing rapidly in the era of big data information digitization. At this stage, the total number of substations is gradually increasing, the structure of the power engineering system is slowly becoming complicated, and the video monitoring system instantly collects a lot and contains a lot of noisy data information, which affects the power supply system’s access to effective data information and fault detection. To prevent the above phenomenon. This paper selects a decision tree algorithm to obtain and analyze meaningful operation-confirming information from a large amount of data information, and then can quickly and confirm the diagnosis of common fault machines and equipment in substations, reduce the running time of common fault machines, and improve the safety and reliability of primary equipment in substations with automation technology. The paper describes the basic concept of big data mining common algorithm and its data mining algorithm in the automation technology substation primary equipment fault detection, selected the typical alarm signal to start the analysis, and categorization and collocation solution. A decision tree algorithm entity model is built, several classical decision tree algorithms are described, and their data analysis is carried out for each attribute, and then the decision tree algorithm is improved. According to build the decision tree algorithm according to improve the decision tree algorithm under the fuzzy set base theory, mainly by expertise in the four on cannot identify the association, rough set and up close and down close, similar and membership relationship, expertise concise to optimize the calculation method. And the common ID3, C4.5, and CRAT algorithm of each property is compared and analyzed, and the results show that: compared with C4.5 and ID3, the boosted optimization algorithm has higher classification accuracy and can model rate more quickly. The research in this paper can quickly diagnose the automation technology substation primary equipment and fault phenomena, and its establishment of the whole process is easy, the scope of application is relatively high, and it has wide applicability.
The construction of innovation system of college physical education reform based on Bp neural network
Authors: Zhu Liang 
Published: September 2023

Abstract
The substance here is to workshop the current problems of physical education in higher learning institutions and construct a reform and innovation machinery of sports learning style in institutions of higher learning. This paper researches the teaching system of college sports learning style based on BP nervous enlist the services, proposes a majorization network foundation hereditary compute mode for the shortcoming that BP nervous enlist the services to be prone to land oneself in the optimal regional solution, and takes 10 influence element the results of academy sports learning style as the sample features of the data set, uses the optimized GA-BP nervous enlist the services for discipline and compares the test results with the practice price and the dispatch of other algorithms. The average error of the detection of GA-BP nervous enlist the services was 1.23, and the average error rate was 1.85%, which performed better compared with other neural networks. In terms of the poundage of the influencing factors in the export multiple, the diversity of curriculum, the advancement of teaching philosophy and the science of sports skill instruction have significant effects on the amount of sports learning style in institutions of higher learning, with the weights reaching 0.1212, 0.1387 and 0.1453, respectively. The reform and innovation of sports learning style in institutions of higher learning should develop diversified physical education courses according to students’ constitution bases and sports levels and impart scientific methods of the constitution and sports values of enjoying sports.
Exploring the application of composite materials in ceramic design based on fuzzy numerical analysis
Authors: Wang Ruoyu 
Published: September 2023

Abstract
Compared with traditional monolithic carbide ceramics, Cu-based composite ceramics have the advantages of higher hardness, good wear resistance and oxidation resistance and are a new type of structural ceramics with wide application prospects. This paper first proposes a novel bi-directional freezing technique to construct a three-dimensional long-range ordered layer network hierarchical structure based on the pressure infiltration process. Secondly, a composite finite element model based on fuzzy numerical analysis is proposed for the vibroacoustic analysis of the periodic composite coupled system (PCSAS). Finally, thermal analysis experiments and mechanical property tests verify the effectiveness of Cu-based composites applied to ceramic matrices. The experimental results show that the toughness of Cu-based composite ceramics increases with the increase of TiC content, and the toughness increases from 2.15±0.27Mpa.m1/2 to 4.21±0.25Mpa.m1/2 compared with that of conventional monolithic carbide ceramics. The Cu-based composite ceramics designed in this paper give full play to the advantages of the high strength of ceramic particles and high toughness of metal matrix and develop an effective method to prepare structural metal-ceramic composites. This paper has developed an efficient route for preparing structural metal-ceramic composites, which can provide a reference for materials researchers to develop high-toughness composite ceramics.
The application of computer VR technology in physical education
Authors: Shi Yuehong 
Published: September 2023

Abstract
Under the digitalization of big data information, how to use VR technology combined with physical education teaching is a hot topic of concern in the current education sector. Firstly, the intelligent teaching system of VR technology based on genetic algorithms is proposed based on big data technology. Secondly, the system framework and ideas are constructed according to the needs of teachers and students in physical education, and then the debugging and operation of the teaching system are realized. Finally, to ensure more accurate experimental results of VR technology applied in college physical education, the homogeneity of experimental objects is detected through a VR technology intelligent teaching system based on analyzing efficiency values in the application of VR technology in physical education. The results show that the average efficiency values of VR technology in basketball, soccer, volleyball, badminton and table tennis are 21.04%, 19.36%, 19.64%, 20.33% and 19.63%, respectively. This study verifies that VR technology is beneficial to improving physical education teaching efficiency and provides a guiding reference value for improving physical education teaching in colleges and universities.
Gymnastic movement recognition based on support vector machine classification model
Authors: Zhang Xiaolong , Wang Jing , Shi Yuehong 
Published: September 2023

Abstract
The gymnastic movement recognition system is designed to determine the standard degree of trainers’ movements by accurately grasping their body contours and body positions through motion capture to achieve the training effect. This paper proposes an improved LSI-SVM algorithm based on a support vector machine applied to a gymnastic movement recognition system. Firstly, based on the idea of NMFDA, for each class of samples, its intra-class k-nearest neighbor and inter-class k-nearest neighbor local structure information are mined. Secondly, the obtained structural information is introduced into TSVM to obtain a new classification model. Finally, system operation test experiments are conducted to verify the generalization and accuracy of the proposed LSI-TSVM algorithm for the gymnastic movement recognition system. The experimental results show that the average recognition rate of the LST-TSVM algorithm proposed in this paper is 94.1%, which is 5.9% higher than S-TSVM and 14% higher than SVM, and 8.9% higher compared to SRSVM. The gymnastic action recognition system based on the LST-TSVM algorithm can effectively solve the problem of matching the corresponding frames of gymnastic action sequences on the time axis and effectively improve the action recognition rate, which can better assist trainers in learning gymnastic items.
Research on the integration of online teaching resources in higher education institutions under the perspective of industry-education integration
Authors: Shen Yu , Yang Xiaojiang , Wang Libin , Zheng Ruxin 
Published: September 2023

Abstract
The purpose of exploring the development mode of online teaching resources in colleges and universities is to enhance the utilization rate of online teaching resources to promote the diversification of teaching methods. In this paper, based on big data technology, a cloud education platform integrating online teaching resources in colleges and universities is constructed under the perspective of integrating industry and education, and the architecture and functions of the cloud education platform are explained. Then the collaborative filtering algorithm is used to filter and collect the information on online teaching resources, and the Pearson correlation formula is used to pre-process the data and help users to recommend teaching resources. Finally, the pre-processed data are filtered and analyzed using the multilayer perceptron technology under the deep learning model. To verify the practicality of the cloud education platform proposed in this paper, the platform’s performance is evaluated by combining MAE metrics with RMSE metrics. In terms of load capacity, the platform has the best load capacity when the number of users is 200. From the performance test, the average transmission rate of the cloud education platform is 8.1% and 0.93% higher than that of NetEase Cloud Classroom and Tencent Classroom, and the average transmission time is 7.09 s. From the practicality analysis, the average value of the MAE index is 0.317%, and the average value of the RMSE index is 0.232%. This shows that the cloud education platform can effectively integrate university online teaching resources and help universities achieve diversified development of teaching methods.
Application of multiple regression models in the analysis of kinematic parameters in competitive gymnastics
Authors: Wang Jing , Zhang Xiaolong , Shi Yuehong 
Published: September 2023

Abstract
Nowadays, the progress of competitive gymnasts needs more and more help from sports science, and it is from the mechanics perspective that human movement science analyzes this complex system of the human body. In this paper, the back handsprings in gymnastics were tested and recorded with a motion capture system to evaluate the back handsprings’ technical movements quantitatively. A multiple regression model was used to model the dynamics of the human body and carry out simulation calculations to analyze and study the movement patterns and lower limb stresses. The results showed that the maximum load rate through the back handspring experimental stage was (379.91±101.23) BW/s, and the time of appearance of the maximum load rate was (0.025±0.003) s. The maximum load decay rate was (-321.61±107.21) BW/s, and the time of appearance of the maximum load decay rate was (0.043±0.005) s. The difference between the results and the actual test value difference between the results and the actual test values was less than 0.005, indicating the feasibility of applying the multiple regression model to the kinematic parameters analysis of competitive gymnastics. The multiple regression-based kinematic parameter analysis models can effectively solve the problem of force on the bones and joints of difficult gymnastic movements, which can better assist trainers in learning gymnastic items and provide theoretical support and reference basis for the development and training of difficult skills in competitive gymnastics.
Application of Data Mining Algorithms in Power Marketing Predictive Analytics
Authors: Xu Wei , Zhao Jia , Chen Hao , Zhang Hang 
Published: September 2023

Abstract
The electric power industry has accumulated a large amount of historical data, and the analysis based on data mining can provide an effective reference for the electric power marketing of enterprises. In this paper, according to the analysis architecture of electric power marketing and its functional modules, the electric power marketing analysis system based on Bayesian algorithm is constructed through data extraction and transformation, modeling of Bayesian network, and simulation operation. At the same time, for the shortcomings of Bayesian algorithm with the large error of classification results under the condition of strong sample correlation, mutual information is introduced to modify the number of Laplace smoothing. The MI-NB model predicts the probability of electricity risk for company A to be 60% and the probability of electricity risk for company B to be 40%, with an error rate of 9.65% and 8.37%, respectively. In line loss rate analysis, the MI-NB model predicts an average line loss rate of 60.46% for station 1 and 60.43% for station 2, both in the high line loss rate range. The Bayesian algorithm based on mutual information can improve the practicality and intelligence of the power marketing decision analysis system, which makes the decision management of power supply enterprises more scientific and reasonable, and is of great practical significance in reducing the operational risk of enterprises.