bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction of a micro-application for full lifecycle data management based on a new-generation electricity consumption information collection system
Authors: Tang Zhu , Yang Tianyu , Liu Heng , Xiao Yuhang , Xu Nan
Published: October 2024

The power consumption information collection system encompasses multiple complex technical relationships, along the data flow chain, numerous data conversion links and processing activities, as well as a multitude of threat exposure surfaces, triggering sources, and uncontrollable factors. This paper proposes a complete lifecycle micro-application management system for the power consumption information collection system, aligning with the objectives and construction programs of the project. The life cycle link of collecting, storing, and sending data about electricity use measures the uncertainty of each piece of information in the binary grid protocol by using the Gini index and information entropy. The characteristics of information data are solved using Bayes’ theorem. By analyzing the users’ behavior patterns, we can prevent them from stealing access rights and other behaviors and dispose of security risks in time. In conjunction with case studies, we conduct simulation experiments to evaluate the power consumption information collection system’s security, complexity, and privacy. In the model without privacy protection, the accuracy rate of member inference attacks is about 68%. This paper’s designed system is more resilient to member inference attacks, with an accuracy rate of less than 50%, demonstrating a superior level of privacy protection for electricity consumption data. The system in this paper uses less time than the other three schemes when the number of users exceeds 2200, peaking at about 700 ms when the number of users reaches 4000.
Research on Civil Engineering Construction Safety Management Methods by Introducing Bayesian Network Modeling
Authors: Tan Jianling , Li Yongli
Published: October 2024

This paper aims to improve the effectiveness of civil engineering construction safety management (CSM)and ensure the safety of civil engineering construction. Firstly, an examination of contemporary CSM methods in the field of civil engineering in China is being undertaken. An innovative Civil Engineering Construction Safety Early Warning System (EWS) based on Bayesian Network (BN) principles addresses the unanticipated emergence of safety incidents during construction endeavors. Finally, a comprehensive evaluation model for civil engineering construction safety has been formulated, using the Bayesian framework to assess the efficacy of the previously mentioned Civil Engineering Construction Safety EWS based on BN. The incidence of safety-related accidents in the Chinese construction industry has consistently declined over the past decade, as the empirical findings indicate. Moreover, compared to international counterparts, the frequency of such incidents in China remains significantly below 600. Additionally, the Civil Engineering Construction Safety EWS created using BN consistently achieves a functional realization score exceeding 75 points, with the highest possible score reaching an impressive 93 points. Notably, through the utilization of the Civil Engineering Construction Safety evaluation model, which integrates Bayesian methodologies, it is discerned that machine tool quality and the placement of construction organization carry a substantial weight, each exceeding 0.3. Remarkably, the indicator of illegal operations is identified as having the highest risk level.
Construction of Electricity Load Forecasting Model Based on Electricity Data Analysis
Authors: He Yue , Zhang Zhi , Chang Yongjuan , Lu Yanyan , Yin Xiaoyu
Published: October 2024

This paper builds a time series prediction model of recurrent neural networks based on time series electricity load forecasting. In this paper, the household electricity consumption record data of some residents in urban area S is taken as the research object, and the laws and characteristics of users’ electricity consumption behavior are analyzed in depth based on the real residential electricity consumption data. External factors such as temperature conditions, holidays, etc. The arithmetic cases are also analyzed using real load data sets. In the short-term continuous electricity data analysis, the smaller the time interval is, the closer its corresponding electricity consumption ratio is to 1. There is a negative correlation between long-term continuous electricity consumption. When the temperature is 30~35oC versus -5~0oC, electricity consumption rises significantly. Comparing and analyzing the time series decomposition-RNN with several models, the time series decomposition-RNN model has the highest fit at 10:00-12:00 and 12:00-14:00, and the result verifies the validity of the model proposed in this paper.
Application and Evaluation of Artificial Intelligence Technology in Collegiate Soccer Sports
Authors: Tang Jingwei
Published: October 2024

This paper discusses the development of school soccer with the help of artificial intelligence. Propose a machine learning-based action feature extraction method for students in school soccer. Obtain action images of students playing soccer and identify the actions of students in school soccer based on the threshold recognition algorithm. The Harris 3D operator is used to establish the potential function of the action sequence, and based on the potential function of the action sequence, the AdaBoost algorithm is used to filter the action feature data of the students in soccer, which is used as the training sample to realize the action feature extraction of the students in soccer. To extract the effective feature values and improve the recognition accuracy of the algorithm, a soccer action recognition model based on SVM was constructed. The feasibility of the DTW scoring method in the field of soccer action recognition has been verified. The SVM algorithm model has the strongest denoising ability, and its feature action recognition rate is maintained between 80% and 90% and the recognition rate of features with large action amplitude is higher, which is suitable for the recognition of soccer actions in this study.
Research on 3D urban landscape digital modeling method based on image processing technology
Authors: Tian Tian
Published: October 2024

The development of digital modeling technology opens up endless possibilities for three-dimensional modeling of urban landscapes. Based on computer vision methods such as stereovision and optical flow, this paper investigates how to carry out three-dimensional digital modeling of urban landscapes. We utilize the method of combining UAV and ground shooting to obtain image data of urban landscapes, then process the collected data with image smoothing, enhancement, edge detection, and segmentation. The Moravec operator and Hough variation are used to extract point and line features from the cityscape image, respectively. The beam leveling algorithm is used to reconstruct the cityscape in three dimensions, and it is optimized by combining the Kalman filter correction. This paper uses the landscape of Li City, Quanzhou City, as the experimental object for digital modeling. A comparative analysis of the three groups of experiments, A, B, and C, shows that the digital modeling technology of urban landscapes, based on image processing technology, achieves the highest degree of restoration of the original image. The errors for landscape elevation and non-elevation are 0.69% and 0.37%, respectively, which are the smallest errors among the three groups of experiments.
The Use of Intelligent Computing in Teaching Model Innovation in Higher Education
Authors: Zheng Min
Published: October 2024

In the field of education and teaching, adaptive learning is generally considered to be superior to non-adaptive learning, and intelligent computing is regarded as a valuable tool in terms of building adaptive learning platforms. In this paper, we intelligently calculate students’ neighbor totals in terms of knowledge point competencies and learning resources through a collaborative filtering recommendation algorithm to get the similarity between students in higher education teaching and generate a learning resource recommendation dataset. Subsequently, an adaptive learning system is constructed based on this collaborative filtering algorithm to assist teaching and promote innovation in higher education teaching modes. The average MAE value (1.90) of the collaborative filtering recommendation algorithm in this paper is lower than that of other algorithms, indicating that the improved collaborative filtering recommendation algorithm in this paper has better prediction accuracy. The experimental study of teaching practice shows that there is a significant difference in the level of students’ posttest learning ability in different teaching modes at the end of the experiment (P=0.002), and the posttest learning anxiety score of students in the group applying innovative teaching modes (M=10.48) is lower than that of the control group. This paper’s adaptive system serves as a guide for the comprehensive, innovative reform of higher education teaching in the future, as well as provides research value and direction for intelligent computing to enter education teaching.
Content Innovation and Strategy Dynamic Adjustment of College Students’ Civic and Political Education Based on the Empowerment of Intelligent Algorithm
Authors: Lu Debing
Published: October 2024

Students’ ideology is mainly developed in the college period, so the ideological and political education work in colleges and universities should be strengthened in order to help students improve their ideological and moral qualities. In this paper, after the introduction of data mining, through the comparison of two algorithms of COBWEB clustering and K-means clustering based on the model method, we chose to use the K-means clustering method to carry out the learning characteristics mining clustering for the students of logistics management majoring in the school of management of a university in Zhengzhou City, Henan Province, and 220 students were selected as the research object. The students were divided into four categories for integration from six dimensions: learning foundation, learning interest, independent learning ability, collaborative learning ability, beginning of Civics learning, and advanced Civics learning. and. then, the purpose of students’ learning Civics education was studied in terms of learning motivation. In all dimensions, students in the first category did well, and 135 students in each category aimed to improve their academic qualifications while learning Civics courses. The innovative path for the content of Civic and Political Education is proposed based on the learning characteristics of the students. 180 students were selected as examples of logistics management class students, divided into experimental and comparison groups, and explored in terms of cultural self-confidence level, academic level, and motivation for learning using the difference analysis method. It was found that after applying the proposed content to the Civic and Political Education classroom, the experimental group and the comparison group showed significant improvement in all dimensions except for learning motivation. It indicates that the content innovation strategy of Civic and Political Education proposed in this paper has a better impact on the teaching effect.
Research on Visual Design and Realization Path of Educational Value of Nature Study Activities in Zhejiang Province under the Perspective of Culture and Tourism Integration
Authors: Guo Wei , Gyu Oh Chi
Published: October 2024

Today, in the information age, digital technological innovation is changing rapidly, and the in-depth development of digitization, networking, and intelligence has revitalized the living heritage of natural heritage and provided a new direction for the development of the field of natural heritage study tours. In this paper, a Monte Carlo rendering method based on deep learning is used to improve the image output quality of the virtual model by analyzing the characteristics of the output image of the natural heritage model. The digital display of nature study activities features Zhejiang Nature Museum as the design object. Its educational value can be demonstrated through virtual characters, storylines, interactive games, and other methods. Through the survey statistics, it can be concluded that the visual design program for nature studies has a better practical application effect. Based on the SOR theory, a model for analyzing research experience satisfaction is established based on the perception transfer of the research place and the research activity scenario. In this research activity, the regression coefficients of the quality of the virtual scenario and the perception of the educational value are the highest, which are 0.238 and 0.226, respectively, indicating that the two have the greatest role in the satisfaction of the students.
The Evolution and Impact of Information Exchange Standards in International Tax Law Based on an Information Theory Perspective
Authors: Huang Yuxiang
Published: October 2024

With the development of economic globalization, international tax problems such as international double taxation and international tax evasion continue to emerge, and global tax governance is receiving increasing attention and focus from the international community. This paper, based on the standard framework of information exchange in international tax law, provides a preliminary analysis of the effectiveness and function of international tax law. The linear transformation of the data input sequence leads to the acquisition of corresponding vector values, and the international tax law topic faceted tree is constructed based on the knowledge extraction results. Using the BERT model, the semantic information text matrix for international tax law is obtained. Extract and mark the relevant elements of the international tax law information exchange standard, combined with element feature marking. The extraction results are analyzed in terms of evolution and outcome: from 2008 to 2019, China signed the Convention and tax information exchange agreements with 33 and 10 countries, respectively, accounting for no more than 50% of the total. Between 0.0178 and 0.0187 is the size of the coefficient of the policy effect of information exchange agreements on cross-border tax avoidance of businesses. This means that it can stop businesses from avoiding cross-border taxes after the agreements go into effect, but it has a pretty small effect.
Strategies for Improving the Effectiveness of Party Building Informatization Construction in Higher Vocational Colleges and Universities Driven by Big Data
Authors: Li Ping , Chen Xiuli
Published: October 2024

Party building, as an important part of party work, has also begun to gradually develop towards the trend of efficiency and informationization. The research constructs the party-building information system of higher vocational colleges and universities on the basis of designing and realizing the party-building portal module, party affairs management module, assessment and evaluation module, and party members’ training and learning module. The party-building information system is thoroughly evaluated using the AHP-fuzzy comprehensive evaluation method. The functions of the party-building information management system constructed in this paper are tested by analyzing the average response time of the system, user concurrency, and system throughput. Construct the evaluation index system for party-building information management systems in higher vocational colleges and calculate the index weights. The five subsystems of the party-building information management system are evaluated comprehensively, according to which the suggestions of party-building informationization construction strategies for higher vocational colleges are put forward. The system response time for 10 types of requests of the party building information system in higher vocational colleges designed in this paper is between 36~113ms. The average response time is 1.32 seconds when the number of concurrent users of the system is 750. The throughput of the system is about 900 per second. The operational effectiveness scores of the five subsystems in the party-building information management system lie between 3.554 and 3.709. The scores of the 4 indicators of each subsystem are also average and good. Based on the results of the study, the construction of party-building information sessions in higher vocational colleges and universities should establish a scientific construction awareness, strengthen the synergy, improve the efficiency of party building, and establish a standardized management system.
Optimization of Simulation Effect of Advanced Parametric Modeling Techniques on Foundation Structure in Revit Environment
Authors: Liu Bingyue , Ke Pu , Zhao Lingyi
Published: October 2024

Among the many structures of foundation pit, the pile-anchor support structure has the characteristics of high safety, low cost, not occupying the space of foundation pit and convenient construction, and is widely used in foundation pit engineering. This study constructs an advanced parametric model of the pit structure and carries out the secondary development of the monitoring data visualization plug-in in the Revit software environment to realize the visualization function of the pit structure data. Subsequently, based on the deformation mechanism of the pit structure, after selecting a suitable land principal model, the pit model was successfully imported into ABAQUS for 3D finite element simulation analysis, and the effect of the simulation was optimized based on orthogonal experiments. The optimization results show that the optimal scheme is 0.60m diameter of row piles, 1.5m spacing of row piles, 200kN prestressing force of anchor rods, 15° inclination of anchor rods, and the length of anchor rods are (19m, 21m, 17m). Compared to the original design scheme, the optimized pit structure scheme reduces pit deformation and reduces project cost, which achieves good economic benefits and achieves the purpose of the optimized design.
A Study on Evaluating the Effectiveness of Higher Vocational English Curriculum Reform and Teaching Suggestions Based on Data Analysis
Authors: Hu Xiaoli
Published: October 2024

College English is the public foundation of vocational schools and colleges and an important course to cultivate students’ English oral communication ability. The study reforms the higher vocational English course under EGP+ESP, and on the basis of designing the index system of the reform effect of the English course, the game theory method is utilized to combine the BWM subjective empowerment method and the improved CRITIC method to calculate the comprehensive weights of the indexes. Taking higher vocational institution A as an example, the cloud model theory of data analysis is introduced into the evaluation. Then, the evaluation grade of the reform effect is calculated. The regression analysis model is used to further explore the degree of influence of factors on the reform effect of the higher vocational English course, and to explore the relevant teaching suggestions. The reform effect of the English curriculum in higher vocational college A is between “medium-high effect” and “high effect”, closer to “medium-high effect”, and the index scores are between (78, 94) and (80). The index scores are between (78 and 94). And the effect of reforming higher vocational English course (Z) = 0.155*course objective + 0.253*course content + 0.441*course implementation. College English teaching should be used to improve students’ English application and oral expression abilities and to strengthen students’ competitiveness in employment from the perspective of language communication.
Innovative Methods and Practical Applications of Civic and Political Education Content in Colleges and Universities for the Digital Era
Authors: Zhou Lihong
Published: October 2024

Digitalization has become the biggest variable in the construction of Civic and Political Science classes in colleges and universities and plays an important role in the teaching of Civic and Political Science classes. Based on digitalization technology, this paper proposes a content innovation method for college Civics education, mainly based on the Civics online teaching platform and virtual Civics classroom. The collaborative filtering algorithm is used in the construction of the Civics online teaching platform to design the course recommendation function, collect user ratings and form a matrix, calculate the similarity between users and courses, and utilize the Bayesian machine learning model to carry out the classification calculation of Civics courses. Based on virtual reality technology, head movement depth information obtained by VR HMD is used to obtain augmented data to improve the accuracy of student movement recognition in virtual Civics classrooms. Civics teaching practice was carried out in a university in Jiangxi Province, China, and the Civics performance of the experimental class after practice was higher than that of the control class by 9.18 points, with a p-value of 0.002<0.05, which is a significant difference. After the practice, all the dimensions of Civics learning effectiveness were higher than the control class and showed a significant difference (P<0.05), and all the dimensions of Civics vegetation were also higher than the control class, with the highest difference of 0.62 in the dimension of science ethics.
Application Research of Pattern Recognition of Fusion Knowledge Graph in Complex Scenarios
Authors: Rong Yili , Zhong Anqi , Wu Haibiao
Published: October 2024

Knowledge graphs serve as an effective mode of organizing and managing knowledge in various fields, such as retrieval, updating, and question and answer. As a result, research on their construction method has gained significant attention. This paper is about pattern recognition. To deal with multimodal features, we combine multimodal data sources and use the structure of synergistic attention mechanisms, which are made up of self-attention mechanisms and guided attention mechanisms. The improved multimodal bilinear method is used for the fusion of modal data. Then, a cross-domain knowledge graph cross-embedding method is proposed to perform multi-semantic interactions for all entities and relationships in multiple domains to achieve cross-domain knowledge graph embedding. Finally, we explore the performance of the constructed knowledge graph fusion model by applying it to the problem of plant disease detection in complex scenarios. When we add 10%, 20%, and 30% noise to the image data captured in complex scenarios, the results demonstrate high detection accuracy and robustness, respectively.
Research on the effect of artificial intelligence-based physical exercise on the regulation of college students’ sleep disorders
Authors: Shen Delei
Published: October 2024

This paper proposes a sleep quality monitoring system based on artificial intelligence, whose basic idea is to collect the relevant data during sleep through the sensors installed in the intelligent devices and analyze the sleep characteristics, which include the data of body movement, respiratory data, snoring, etc. Then, under the synergy of this system, we propose a strategy to regulate sleep disorders by combining “artificial intelligence + physical exercise”. Then, under the synergy of this system, we propose a sleep disorder regulation strategy combining “artificial intelligence + physical exercise”. A total of 500 college students in the freshman and sophomore years of X University were selected as research subjects, and the Pittsburgh Sleep Quality Index (PSQI) and Physical Activity Rating Scale (PARS) were used to investigate the current status of the college students’ sleep quality and physical activity and to explore the specific effects of this control strategy. The results showed that the detection rate of PSQI score ≥8 was 179 (35.80%), and the average PSQI score of college students who participated in physical exercise was 8.31±2.34, which was significantly lower than that of college students who didn’t participate in physical exercise, which was 10.21±3.84. Under the combination of the “Artificial Intelligence + Physical Activity” sleep disorder regulation strategy, after the regulation of sleep quality and physical activity, the results were significantly lower than those of college students who didn’t participate in physical activity, which was significantly lower than those of college students who didn’t participate in physical activity. Under the combination of “artificial intelligence + physical exercise”, the average PSQI score after modulation (8.06±2.84) was also significantly lower than the average PSQI score before modulation (14.39±4.18).
Autonomous learning and adaptation of industrial robots using intelligent control algorithms
Authors: Xu Yicen
Published: October 2024

With the continuous advancement of industrial technology and China’s intelligent technology, industrial robots are widely used not only in production and manufacturing industries. This paper presents an autonomous learning robot system, control algorithm, and simulation experiments to study the autonomous learning and adaptation ability of industrial robots. To experiment on the error and tracking trajectory of the industrial robot, the article uses the fuzzy control PID control method based on the traditional learning control system. The results of simulation experiments show that the fuzzy control method in the X, Y, and Z three axes achieved a good control effect, while the speed of the robot arm in the X-axis floats more, while the speed of the robot arm in the Z-axis can reach a maximum of 0.41 m/s. Secondly, when comparing the performance of control algorithms, the fuzzy control PID method has a relatively accurate and stable tracking effect, and the consumption of time is shorter. Finally, the experimental platform for robotic arms is constructed, and the trajectory tracking experiment is carried out according to the fuzzy control PID. Despite uncertainties, fuzzy control PID can still effectively control the robotic arm according to the experimental results. Fuzzy control PID has a significant effect on the autonomous learning and adaptation ability of industrial robots.
A Study on the Discovery and Effective Configuration of Ideological and Political Elements in College Physical Education Courses under the Background of Big Data
Authors: Zhang Wang , Song Xuefei
Published: October 2024

The discovery and integration of Civics and Politics elements in college teaching has become an important way to implement core literacy, and more importantly, it highlights the importance of value in the process of educating people with moral values. This paper utilizes the Delphi method to collect experts’ opinions and revise the indicators of the Civic and Political Elements explored in the physical education curriculum and then utilizes the hierarchical analysis method to calculate the weights of the indicators of the Civic and Political Elements and to check the consistency. Subsequently, based on the teaching objectives, the explored civic and political elements are effectively configured in college physical education courses, and the optimized teaching mode of college physical education courses using big data is established. The results of the study showed that the students in the optimized teaching mode had significant differences (P<0.05) from the students in the traditional teaching group in the 2 physical fitness indicators of 800m/1000m running and lung capacity. Meanwhile, due to the teachers’ conscious cultivation of beliefs and ideals for the students in the optimized teaching group in the process of physical education teaching, a significant effect of the enhancement of Civic and Political Literacy and Physical Education Skills was achieved. This paper provides an effective method for configuring the elements of civics and politics, which provides more possibilities for the integration and development of civics and politics in physical education courses.
An Efficiency Optimization Study of Data Governance Legal Issues in the Framework of Privacy Computing
Authors: Hu Fei , Chen Tingting
Published: October 2024

The rapid development of technologies such as big data and cloud computing provides convenience for people’s production and life but also brings hidden dangers for personal privacy. The study clarifies the legal norms and guarantees of personal information protection (privacy) in countries around the world and, on the basis of this law, adopts the key technologies of privacy computation, such as differential privacy, machine learning, and homomorphic encryption to protect the privacy of information data with symmetric encryption, and constructs a privacy protection computational model based on symmetric encryption. To evaluate the efficiency of this paper’s privacy protection computing model, it is necessary to compare its performance with other privacy computing model algorithms. The output of this paper’s privacy-preserving model is stable on the three datasets, DBLP, PUB, and CITESEERX, with minimal result perturbation and good accuracy performance. The accuracy of this paper’s algorithm at θ =0.5 is 99.8% and 96.8%, respectively, and balances the training efficiency and accuracy. The running time of this paper’s model on DBLP and PUB datasets is 47.5 minutes and 39.6 minutes, respectively, which is more efficient. The privacy-preserving computational model in this paper significantly outperforms other algorithms in terms of system throughput and improves the efficiency of the system’s data processing while reducing the consumption and waste of arithmetic resources.
Research on Data-Driven Public Service Innovation Practice of Rural Tourism Culture
Authors: Zhao Huijuan , Meng Qingxuan , Ma Jinju
Published: October 2024

Data-driven approaches gradually accelerate the development of rural tourism, with sound public service becoming an essential requirement for the development of rural tourism culture. This paper first constructs a data-driven AHP model for rural tourism service evaluation based on the optimization process of power methods and hierarchical analysis algorithms. Second, this paper constructs a rural tourism public service driving force evaluation index system with 2 system layers, 8 indicator layers, and 44 measurement layers, as well as a tourist satisfaction evaluation system with 1 target layer, 7 project layers, and 20-factor layers. Next, we conduct a hierarchical analysis of the innovation driving force in rural tourism and cultural public services within the system. Based on the analysis results, we integrate the two evaluation systems to create a comprehensive rural tourism service driving mechanism. Finally, it proposes a strategy for innovation in rural tourism and cultural public service using data-driven approaches. Financial support is a key factor for rural tourism public services at the current stage of development, and special funds for rural tourism development have become the priority indicators to drive rural tourism public services. The average satisfaction value for the 20 factor-level evaluation indicators ranges from 3.85 to 4.22, with a wide variation in their importance. F12 and F2 have significant importance coefficients of 4.38 and 4.34, respectively. The standard deviation values of the satisfaction and importance coefficients fluctuate between 0.32 to 1.76 and 0.47 to 1.24, respectively. This paper emphasizes the importance of the results for innovation in public services in rural tourism.
Research on Intelligent Teaching Methods of Chinese Culture for Emotional Identity Enhancement in Civic and Political Education in Colleges and Universities
Authors: Wang Lili
Published: October 2024

Civic and political education plays an important role in implementing the fundamental task of establishing morality, giving full play to the function of educating people, constructing an all-embracing, all-encompassing and all-encompassing pattern of educating people, and cultivating socialist builders and successors who are all-rounded in morality, intelligence, physicality, aesthetics, and labor. By combining the theory of multiple intelligences, this paper constructs a framework for Civic and Political Education that incorporates emotional identity into the teaching stage of each level. In this context, Chinese cultural and emotional identity is taken as the main point of Civics learning knowledge, and an improved multi-interaction Bayesian model is designed to track the state of students’ Chinese cultural and emotional identity in Civics education and a personalized teaching system is constructed with a recommendation algorithm to realize intelligent teaching of Civics. The Civics teaching class based on the Theory of Multiple Intelligence has an average mastery level of above 80% for each Chinese cultural and emotional identity knowledge point in terms of teaching effectiveness. While the average mastery level of the traditional teaching class for each knowledge point is no more than 68%, the personalized teaching of Civics based on multiple intelligence theory can significantly enhance the emotional identity of Chinese culture in Civics education. The purpose of this study is to provide a reference for improving the teaching effectiveness of ideological and political theory classes in colleges and universities.
A Study on the Practice of Professional Ideological Education for Undergraduate Nursing Students under the Perspective of “Three Comprehensive Education”--Taking the School of Nursing of a Medical University as an Example
Authors: Shang Zhuosen
Published: October 2024

Under the guidance of “Three Comprehensive Education,” colleges and universities have achieved certain results. However, in their practical operation, they have encountered several problems. These include the insufficient joint generation of “all-staff education,” the weak overall penetration of “whole-process education,” and the low overall linkage of “all-round education.” This paper takes the professional, ideological education of nursing undergraduates in a medical university as the research object, takes the evaluation of the effectiveness of ideological education as the research basis, takes the theory and practice of “three comprehensive education” as the starting point, and deeply studies the shortcomings of the current ideological education in colleges and universities in the main body, process, and direction of education. We constructed the “2+6+N” quality evaluation index system from two components: the ideological education work (i.e., full staff, the whole process, and all-round) and the ideological education effectiveness (direct effect, indirect effect, and spillover effect) in colleges and universities. From an empirical point of view, a complete set of whole-process quality evaluation implementation systems is constructed, and the AHP method and fuzzy comprehensive evaluation method are used in the evaluation. The results showed that the comprehensive value of the evaluation of the effectiveness of ideological education for nursing undergraduates in a medical university was 75.079, and the results were between satisfactory and average. The evaluation results suggest specific improvement measures for undergraduate colleges to implement ideological education in nursing.
Research on the Application of Natural Language Processing Technology and Optimization of Teaching Strategies in English Translation Education in Colleges and Universities
Authors: Zou Long
Published: October 2024

The national strategy and the goal of cultivating comprehensive translation competence require that English translation teaching in colleges and universities should follow the wave of change and participate in the realization of the increasingly changing higher education teaching goals. In this paper, after applying the model of a multiplexed collaborative self-attention mechanism to encode and process the English utterances to be translated, the encoder-decoder attention mechanism is utilized to align the encoding-enhanced processed English sentences into clauses. The CA-CrossAttention mechanism and Softmax layer realize the automatic processing and translation process of English utterances. Subsequently, on the basis of B/S network architecture, an English translation teaching platform based on natural language processing technology is constructed by combining the automatic translation model, and an optimized teaching strategy is designed with the assistance of the platform. It was found that the student’s English language proficiency scores were significantly higher than those of the initial teaching at the 9th week of the implementation of the optimized teaching strategy (p=0.000<0.01), and the student’s overall English translation learning anxiety behavior was also alleviated to some extent. The students’ overall satisfaction with the environment perception and personal cognition of the teaching platform is high, and they are more agreeable to the evaluation and optimization suggestions of the platform’s feedback content. The purpose of this paper is to promote the reform of English translation teaching and the development of English majors, as well as guarantee the output of excellent talents in English translation.
A Comparison of Free and Mapped Meshes for Static Structural Analysis
Authors: Haider Aun
Published: October 2024

This study addresses the challenge faced by Finite Element Analysts when choosing between free and mapped meshes, especially in terms of convergence stability and solution accuracy. The investigation focuses on 3D solid models under static structural loading, analyzed using Ansys® and MSC Patran®. Both free and mapped mesh types, employing equivalent 3D solid elements, are used to assess an aircraft structural component under design load conditions, with fixed boundaries. For free meshes, Tet10 elements in Patran (equivalent to Solid 72 in Ansys) are used, whereas for mapped meshes, CPENTA / CHEXA elements in Patran (equivalent to Wed6 / Hex8 in Ansys) are employed. Mesh convergence studies ensure that discretization does not affect the numerical solution. Notably, a significant stress increase is observed with successive refinement of free meshes, while mapped meshes achieve mesh independence at coarser refinement levels. Comparison of fringe plots indicates the same location for maximum deformation and equivalent stress in both free and mapped mesh models. The findings demonstrate that free meshes tend to underpredict maximum deformation and equivalent stress compared to mapped meshes, with both meshes showing deformation and stress at consistent locations. The findings underscore the importance of carefully choosing the appropriate mesh type, particularly when analyzing critical structural components, to ensure reliability and accuracy in FEA simulations.
Elevated Composite Inflammatory Markers are Associated with Clinical Severity and Long-term Amputation Risk in Patients with Critical Limb Ischemia after Percutaneous Transluminal Angioplasty
Authors: Mureșan Adrian Vasile , Lazăr Nicolae-Alexandru , Bartus Reka , Szanto Ludovic-Alexandru , Cordoș Bogdan Andrei , Bandici Bogdan-Corneliu , Șincaru Suzana-Vasilica , Covalcic Carina Diana , Ilioniu Agatha Maria , Mărginean Lucian
Published: October 2024

Background

Chronic limb-threatening ischemia (CLTI) represents the advanced stages of peripheral arterial disease (PAD) and is caused by atherosclerotic damage in the lower limbs, having a greater risk of major amputation.

Aim

The aim of this study was to analyze the impact of systemic immune index (SII), systemic inflammation response index (SIRI), and the aggregate index of systemic inflammation (AISI) on the clinical severity and long-term risk of amputation among patients with CLTI after percutaneous transluminal angioplasty (PTA).

Material and Methods

This is a retrospective observational study involving 104 patients diagnosed with CLTI and treated with PTA. Based on clinical severity, the cohort was divided into two groups: stage III Leriche-Fontaine and stage IV Leriche-Fontaine.

Results

We observed higher levels of SII (p = 0.027), SIRI (p = 0.0008), and AISI (p = 0.0024) in patients with trophic lesions. Kaplan–Meier analysis showed that patients with values of SII (p = 0.008), SIRI (p = 0.022), and AISI (p = 0.006) above the median at the time of admission are at a higher risk of major amputation in the long term following PTA. At the multivariate regression analysis, high baseline values of SIRI (odds ratio (OR) = 2.28; p = 0.017) and AISI (OR = 2.32; p = 0.043) were associated with stage IV Leriche-Fontaine, but not SII (OR = 1.71; p = 0.055). Additionally, in the Cox regression analysis, we found that SII (hazard ratio (HR) = 1.56; p = 0.010), SIRI (HR = 1.63; p = 0.009), and AISI (HR = 1.55; p = 0.016) are predictive factors for long-term risk of major amputation after endovascular treatment.

Conclusions

Elevated levels of SIRI and AISI have been found to be linked with the severity of clinical symptoms and an increased risk of long-term major amputation in patients with CLTI following PTA. Additionally, higher baseline values for SII were associated with a greater risk of major amputation, but not with clinical severity in the same group of patients.
The Impact of Hyponatremia in Aortic Valve Surgery Using Histidine–Tryptophan–Ketoglutarate Cardioplegia
Authors: Ghiragosian Claudiu , Baba Dragos-Florin , Harpa Marius , Puscas Alexandra , Balau Radu , Al Hussein Hussam , Ghiragosian-Rusu Simina Elena , Avram Calin , Neagoe Radu Mircea , Suciu Horatiu
Published: October 2024

Background

Histidine–tryptophan–ketoglutarate (HTK) cardioplegia is one of the most widely used methods of cardioplegia. This solution is hyponatremic compared to blood, and the rapid infusion of a substantial volume of hyponatremic solution will result in a notable reduction in serum natrium (Na) levels. The aim of this study was to analyze changes in serum Na concentration following HTK cardioplegia infusion in aortic valve surgery, and to investigate the association between hyponatremia and postoperative outcomes in patients who underwent aortic valve replacement surgery.

Materials and Methods

This retrospective study involved 302 patients who underwent aortic valve replacement surgery between June 2023 and June 2024 at the Emergency Institute for Cardiovascular Diseases and Transplantation, Tîrgu Mureș, Romania. Based on their preoperative serum Na levels, the patients were divided into a low Na group (Na < 136 mEq/l) and a normal/high Na group (Na ≥136 mEq/l). Outcomes measured were operative short-term mortality, as well as in-hospital postoperative complications such as neurological impairment, surgical reintervention, new onset atrial fibrillation (AFib), and sustained ventricular fibrillation (VF) or ventricular tachycardia (VT).

Results

Before surgery, the mean Na concentration was 134.0 ± 1.3 mmol/l in the low Na group and 140.5 ± 3.2 mmol/l in the normal/high Na group. After surgery, the mean Na concentration decreased to 134.5 ± 3.4 mmol/l in the low Na group and to 135.5 ± 8.1 mmol/l in the normal/high Na group. Logistic regression analysis of the outcomes showed a significant association between low preoperative Na concentrations and surgical reintervention for hemorrhagic cause, being a risk factor (OR = 3.65; 95%CI 1.18–11.34; p = 0.025). The 7-day mortality was 7.6% in the low Na group vs. 1.1% in the normal/high Na group, and 30-day mortality was 10.9% in the low Na group vs. 1.6% in the normal/high Na group. We found a significant association between low preoperative Na levels and 7-day mortality (OR = 7.40; 95% CI 1.57–34.90; p = 0.011), as well as low preoperative Na levels and 30-day mortality (OR =7.36; 95% CI 2.05–26.42; p = 0.002).

Conclusions

Our findings suggest that the occurrence of complications is primarily associated with preoperative rather than postoperative hyponatremia, even when there are minor deviations from the normal range.
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