bluuebunny/crossref_metadata_2025 huggingface dataset:
An Empirical Study on the Impact of Economic aid on the Sustainable Development Ability of Impoverished College Students from the Perspective Conservation of Resource Theory Based on Computer Data Analysis
Authors: Fei Sun
Published: January 2025

For some poor students in colleges and universities, they are facing huge economic pressure, which may have a negative impact on their studies and their future sustainable development ability. Therefore, the importance of economic aid to the poor students is self-evident. From the perspective of resource conservation theory, a survey of 682 impoverished students from five universities was conducted based on computer data analysis. The results showed that: (1) economic aid has a positive impact on the sustainable development ability of poor students in colleges and universities; (2) affects the sustainable development ability through the effect of internal and external attribution and self-efficacy; (3) having the necessary resources is the basic condition for the sustainable development of poor students in colleges and universities. The empirical study on the impact of economic aid based on computer data analysis on the sustainable development ability of impoverished students in universities has enlightening significance for adjusting and optimizing the aid policy system and promoting the sustainable development of impoverished students.
Hydrothermal Synthesis and Characterization of C@ZrSiO4 Black Pigment Based on Mesoporous Structure Collapse of Zirconium Silicate
Authors: Junxiong Zhang
Published: January 2025

In this paper, Zirconium silicate inclusion carbon black (C@ZrSiO4) pigment was prepared by mesoporous structure collapse of ZrSiO4. The optimal synthesis process of C@ZrSiO4 pigment was studied. The results show that mesoporous ZrSiO4 with specific surface area of 322.4805 m2/g can be obtained at 180 ℃ hydrothermal temperature. APTES can facilitate the combination of carbon black (CB) and ZrSiO4, and the optimal molar ratio of APTES/Zr is 0.5364. By utilizing the special structure of layered mesopores ZrSiO4, we have successfully synthetized highly chromogenic C@ZrSiO4 pigment with L* value of 27.65.
The Hidden Cost of Automation: How Robot Adoption Impacts Employees' Sus-tainable Behavior and Environmental Practices
Authors: Jianwu Zhou
Published: January 2025

Organizations are increasingly adopting robots, reshaping various aspects of employee behavior. This study examines the impact of robot adoption on employees' green behavior—a vital component of corporate sustainability. Grounded in Conservation of Resources (COR) theory, we propose that resource depletion or threat prompts individuals to prioritize essential tasks, reducing engagement in discretionary behaviors. We identify job stress as a mediator and openness to experience as a moderator in this relationship. Through experimental and survey studies, we find that robot adoption negatively affects employees' green behavior. Study 1 (N = 109), using experimental methods, demonstrates this negative impact. Study 2 (N = 265), conducted in the hospitality industry, further validates these findings via survey methods. Study 2 also reveals that job stress mediates the relationship between robot adoption and green behavior, while openness to experience moderates this effect. Specifically, high openness to experience weakens the positive relationship between robot adoption and job stress, thereby mitigating its negative effect on green behavior. These findings make significant theoretical contributions to the literature on robot adoption and green behavior, while also providing practical guidance for sustainable development in organizations.
Application of Regression model in Analyzing Carbon Emission Reduction Effect of Digital Economy Development: Evidence from China
Authors: Xiaohui Chen
Published: January 2025

This study examines how consumers' psychological requirements influence their purchase intention for new energy vehicles (NEVs). It seeks to determine how exogenous latent variables influence consumers' purchase intentions for NEVs in Guangzhou, China. Understanding these elements is important because they can help drive NEV manufacturers' marketing strategies and product development. To investigate the key factors influencing NEVs purchase intention, the study adopts the Stimulus-Organism-Response (SOR) model, which is combined with the Technology Acceptance Model (TAM) and Customer Perceived Value (CPV) theory. A questionnaire study was administered to Guangzhou residents to gather information about their perceptions of NEVs, such as perceived ease of use, perceived usefulness, perceived product quality, perceived service quality, and considered value of test drives. Structural Equation Modeling (SEM) was used to test the hypotheses and investigate the variables' direct and indirect impacts on purchase intention. The results show that the perceived ease of use had the greatest overall influence on NEVs purchase intentions, followed by perceived product quality, perceived usefulness, and perceived value of test drives. Perceived service quality, while significant, has a relatively little impact. Notably, women are more influenced by perceived ease of use and product quality perception, whereas men's purchase intention is primarily influenced by perceived service quality. Educational levels also have an impact, with highly educated people having a larger association between purchase intention and perceived ease of use. The direct effect of perceived usefulness on purchase intention has also been validated, emphasizing the importance of customers perceiving NEVs as valuable and useful. This study verifies the SOR model's usefulness in assessing purchase intentions for NEVs and demonstrates the important influence of customer psychological needs on purchasing decisions. The study makes specific strategic recommendations to NEV makers and marketers by identifying perceived ease of use, perceived product quality, and perceived usefulness as important factors of purchase intention. These include optimizing product design for ease of use, improving service quality, and promoting the value and use of NEVs through marketing initiatives. Overall, this study contributes to a better understanding of customer perceptions about NEVs and provides recommendations for increasing their acceptance in the Guangzhou market and elsewhere.
The Application of Intelligent Agent-Based Model Method in the Operation Process of the Catering Industry
Authors: Mingtian Wang
Published: January 2025

The Intelligent Agent-Based Model method, by modeling many interacting individuals and simulating the behavior of individual agents, demonstrates the operation of complex multi-agent systems from a micro to a macro level. It can be effectively utilized to study the operational process of the catering industry surrounding rural scenic spots. This study takes the catering industry surrounding a tourism scenic spot in the southern countryside of Guizhou, China as an example. The emergence and development process of the catering industry is analyzed and the interaction process between tourists and restaurants is modeled. The consistency between the simulation results of restaurant customer flow and the field survey findings indicates that this model could be used to simulate the actual operation of the restaurant. The simulations shows that when the tourist traffic is high, the Matthew Effect on the distribution of customer flow among restaurants is not significant, and the impact of restaurant location is limited. However, when the tourist traffic at the scenic spot is low such as during the off-peak season, the location of restaurants has great influence on the customer flow. Furthermore, establishing partnerships with travel agencies represents an alternative solution for restaurants.
Optimization of Reverse Logistics Network for Electric Vehicle Used Battery under Direct Collection Mode of Manufacturer Based on New Energy Low-carbon Background
Authors: Jianjun Wang
Published: January 2025

As the concept of low-carbon travel gradually takes root in the public's mind, the production and sales of electric vehicles are steadily climbing, and due to the limited service life of electric vehicle power batteries, they will be gradually eliminated and replaced. Enhancing the recycling infrastructure for used electric vehicle batteries and developing a systematic and efficient reverse logistics framework is crucial for advancing the sustainability, cost-effectiveness, and operational efficiency within the electric vehicle sector. This paper firstly analyses the direct collection battery recycling mode of the manufacturer, and on this basis, constructs the optimization model of the reverse logistics network of used batteries, as well as the dual objective optimisation model of total network cost minimisation and carbon emission minimisation. Finally, based on relevant data from C Electric Vehicle Manufacturing Company, an example analysis is carried out to derive its optimal solution for the reverse logistics network of used batteries for electric vehicles in Beijing. The research in this paper has a positive effect on reducing the reverse logistics costs of related enterprises and reducing environmental pollution, thus helping to realize the green ecological development of the electric vehicles industry.
A Game Strategy for Getting Electricity Investment Interface Extension in Adaptation to the Construction of Hainan's High-Level Free Trade Port
Authors: Yu Xie
Published: January 2025

This study focuses on the extension of the ' Getting Electricity ' investment interface as its main theme, taking the construction of key parks in the Hainan Free Trade Port ((Hainan Province, China)) as the real-world background. this study constructs an evolutionary model for the cooperative operation mechanism among the power grid company, customers, and government in the extension of the electricity investment interface. It analyzes the strategic interactions among the three parties during the implementation of the interface extension. Furthermore, the study conducts a stability analysis of the equilibrium among the government, power grid enterprises, and park customers under scenarios where value-added services are provided by the power grid enterprises. Different pathways for coordinating the interests of the three parties under various standards of investment interface extension are presented. This provides critical support for formulating targeted policies on ‘Getting Electricity' investment extensions and maximizing the comprehensive efficiency of electric power resources at a broader level.
Design of Urban Waterlogging Emergency Rescue Boat from the Perspective of Human-Computer Interaction
Authors: Dan Yang
Published: January 2025

With the acceleration of the urbanization process, urban waterlogging occurs frequently and the demand for emergency rescue is increasing. However, the existing urban waterlogging emergency rescue boats have deficiencies in human-computer interaction design, such as poor operation convenience and low information visualization, which affect the rescue efficiency. This study aims to improve the rescue efficiency and ease of use. The Delphi method, Analytic Hierarchy Process (AHP), and Decision Making Trial and Evaluation Laboratory (DEMATEL) are used to construct the human-computer interaction design factor system and quantify the factor weights and relationships. The design factors are determined through discussions among experts in multiple fields. The relative weights are calculated by AHP, and the causal relationships are clarified by DEMATEL, and key factors such as safety protection and space layout are obtained. A mother-child rescue boat and auxiliary equipment are designed, including clear functional positioning, optimization of the shape structure and color matching, etc., which improves the comfort and rescue efficiency. This study provides a basis for the human-computer interaction design of rescue boats, improves the deficiencies in related research, provides ideas for similar designs, and can integrate advanced technologies and continue to be optimized in the future to deal with complex rescue scenarios.
Improving Students’ Engagement with Feedback in Mathematics Classrooms: Based on Big Data Analytics
Authors: Fang Yuan
Published: January 2025

With the shift in educational paradigms from “teaching-centered” to “learning-centered”, mathematics classrooms are undergoing significant transformations. Feedback is a crucial factor influencing students’ learning and academic achievement, and students’ active engagement is considered a key prerequisite for effective feedback. However, current research has not fully explored how students engage with feedback in mathematics classrooms or the factors that influence the engagement. Additionally, providing timely and meaningful feedback remains a significant challenge for teachers. This article examines the nature of feedback, analyzes the critical role of student engagement with it, and identifies key factors influencing this engagement in mathematics classrooms. Based on the application of big data analysis, the study proposes strategies to enhance students’ engagement with feedback, aiming to promote mathematics learning and teaching. These findings provide a theoretical basis for improving students’ engagement with feedback and for guiding the strategic design of interventions aimed at improving this engagement.
Effect of Bovine Serum on Quorum Sensing Genes Expression in MDR Resistant P. Aeruginosa
Authors: Noor M. Ghazi,
Published: January 2025

Background: Pseudomonas aeruginosa, similar to several bacteria, use chemical signals for intercellular communication via use of quorum sensing (QS) mechanisms. QS enable the bacteria groups to detect population density and, in reaction to variations in cell density, to synchronize their behaviors. The current study intended to investigatethe effectof bovine serum on quorum sensing genes expression in Pseudomonas aeruginosaduring early stages of growth.
Methodology: Pseudomonas aeruginosa isolates were obtained from burns, wounds, urine, and ears. Bacteria isolates were identified in accordance to their biochemical reactions, then antibiotic susceptibility and The isolates' ability to build biofilms was examined, and each bacterial isolate's genomic DNA was extracted in order to find quorum sensing genes (rhlR, rhlI, lasR, and lasI).
Result: From different clinicalspecimens, twenty-five Pseudomonas aeruginosa isolates were identified,antibiotic resistance was present in these isolates., and it was found that only 10(40%) of these isolates were biofilm producers. Biofilm virulence genes lasR, lasI, rhlR, and rhlI were detected in all Pseudomonas aeruginosa isolates examined. 
Conclusion: lasR, lasI, rhlR, and rhlI genes were common inPseudomonas aeruginosa isolates that have high rate of resistance to all antibiotics, and strong ability in biofilm formation.
Research on Frequency Control Strategy and Standardization based on Virtual Synchronous Charging and Discharging of Electric Vehicles
Authors: Songling Pang
Published: January 2025

With the rapid development of renewable energy, the power system faces increasing frequency fluctuation issues, and traditional synchronous generators are gradually unable to meet the demand for frequency regulation. Electric vehicles (EVs), as an emerging flexible load resource, can participate in grid frequency regulation due to their adjustable charging and discharging characteristics. This paper establishes a model of an EV fleet participating in frequency regulation based on virtual synchronous charging and discharging technology for electric vehicles. First, the basic principles of virtual synchronous charging and discharging and their role in grid frequency regulation are analyzed. Then, a frequency control strategy for electric vehicles based on the virtual synchronous generator model is proposed, and the performance of this strategy under different grid operating conditions is studied. Finally, the paper addresses the standardization issue of virtual synchronous charging and discharging for electric vehicles and proposes corresponding technical requirements and implementation plans. Experimental results show that the virtual synchronous charging and discharging technology for electric vehicles can effectively improve grid stability and lay the foundation for the standardization of EV frequency control.
Research on the Measurement of the Effect of E-Commerce in Promoting Economic Development based on Big Data Analysis
Authors: Wenya Zhao
Published: January 2025

In order to analyze the effect of e-commerce in promoting economic development, based on big data technology, this paper constructs a measurement model of the effect of e-commerce on promoting economic development based on big data technology. Moreover, this paper proposes a method for extracting complex modal parameters of multi-degree-of-freedom structures based on similarity search. This method is based on the complex modal theory of a multi-degree-of-freedom general viscous damping system. The search in the library is the most similar match with the free response data of the structure, so as to realize the parameter identification of the multi-degree-of-freedom structure. In addition, an intelligent analysis system structure is constructed. Through experimental research, it can be seen that the measurement model of the effect of e-commerce on promoting economic development based on big data analysis proposed in this paper has certain effects.
Research on Table Tennis Rotation Prediction Based on Deep Learning and Multi-scale Feature Fusion
Authors: Wujunyu Xu
Published: January 2025

This paper designs a table tennis target detection network based on feature fusion network. In the feature extraction network, the cross-layer connection network (CSPNet) is used to strengthen the learning ability of the convolutional neural network and reduce the number of parameters of the network to improve the detection speed of the network; for the existing network, the detection accuracy of small targets such as table tennis is low and the positioning ability is low. For the problem of poor, this paper uses a feature fusion network, adds a bottom-up connection on the basis of the feature pyramid network, and finally uses an adaptive pooling method to fuse the feature information of each feature map, and the upper-level semantic information rich features the layer and the lower layer are connected with the feature layer rich in target location information to perform feature fusion to enhance the network's ability to locate small targets. Because the network in this paper only needs to detect the table tennis target, and the table tennis target in a single picture is small, resulting in a waste of training costs, this paper proposes a new data augmentation method, which combines the data in each picture during training. Multiple copies of Ping Pong, based on the existing data, further increase the richness of the data set. After adjusting and optimizing the network structure, the network of this paper can complete real-time tracking and accurate positioning of table tennis under different background and lighting conditions.
This paper builds a LSTM-based rotating table tennis trajectory prediction network. By stacking LSTM networks, the task of predicting the trajectory of table tennis can be realized, and real-time and certain accuracy can be met. For different types of spinning balls, there are specific trajectory changes in their trajectories to follow; therefore, this article attempts to infer the general type of ping pong ball rotation based on the flight trajectory of the ping pong ball. This article decomposes the table tennis movement into three coordinate movements, and calculates the movement speed of the table tennis in the three coordinate axis directions through the obtained three-dimensional coordinate information of the first five moments of the table tennis, passing the speed and the set threshold of Compare the type of rotation to judge the general type of rotation, and control the end joint of the robot to hit the ball at a specific angle for the ball of different rotation type, which effectively improves the success rate of the table tennis robot. Compared with the traditional physical model, the network in this paper has higher anti-interference ability and accuracy.
Analysis Model of Influencing Factors of College Students' Entrepreneurial Tendency Combined with SEM Model
Authors: Xue Yang
Published: January 2025

This paper uses the method of combining theory and empirical research to analyze the structural equation model of the influencing factors of college students' entrepreneurial tendency, and explores the effective ways to cultivate college students' entrepreneurial quality, so as to enhance the pertinence and effectiveness of entrepreneurship education in colleges and universities. Based on the conclusions of the tendency study, this paper aims to improve the entrepreneurial tendency of college students by improving their own, society, school and family. From the conclusion of the demonstration, we can see that compared with the previous research on the factors affecting college students' entrepreneurial tendency, the conclusion of this paper is slightly different. In addition, we should see that in the study of college students' online entrepreneurial tendencies, the influencing factors should still take into account the virtual side of entrepreneurship through the form of network, such as the role of social network relations on entrepreneurial tendencies is not significant and so on. Finally, we can conclude that the analysis model of influencing factors of college students' entrepreneurial tendency combined with SEM model can play a certain role in the analysis of college students' entrepreneurial tendencies, and can provide theoretical reference for the formulation of relevant policies.
Research on Grid-Connected Charge-Discharge Control Strategy of Electric Vehicles Based on Clean Energy
Authors: Li Yang
Published: January 2025

Introduction: With the increasingly serious global energy shortage and environmental pollution problems, new energy vehicles have been widely concerned as a clean and efficient way of transportation. Among new energy vehicles, electric vehicles have become the mainstream direction of future transportation development with their advantages of zero emission, low noise and high efficiency. However, the popularity and large-scale application of electric vehicles need to solve the problem of energy management in the charging and discharge process.
Objectives: This paper studies the grid-connected charging and discharge control strategy of electric vehicles based on clean energy, aiming to realize the maximum utilization of clean energy and the stable operation of the power system.
Methods: This paper first introduces the basic principles and key technologies of grid-connected charging and discharging of electric vehicles, and then analyzes the application status and challenges of clean energy in electric vehicle charging. Then, this paper proposes a grid-connected charging and discharge control strategy based on clean energy. This strategy predicts the charging and discharge demand of electric vehicles and the output of clean energy, and makes a reasonable charging plan and discharge control strategy, so as to realize the maximum utilization of clean energy and the stable operation of the power system. Finally, the effectiveness and feasibility of the proposed control strategy are verified by simulation experiments.
Results: The experimental results show that this strategy can significantly reduce the impact of electric vehicles on the power grid and improve the benefits of clean energyWhile ensuring the stable operation of the power system.
Conclusions: In this study, the in-depth discussion and simulation experiment of the grid-connected charging and discharge control strategy of electric vehicles based on clean energy, and verified its effectiveness in balancing the grid load and optimizing the utilization of clean energy..
Energy Conversion Efficiency of Wave Gliders
Authors: Yufeng Qin
Published: January 2025

Wave gliders are a new type of ocean observation platform that can gain forward power by receiving and converting wave energy. The ability of wave gliders to turn waves determines the speed, maneuverability, and precision of wave gliders’ navigation control in various sea conditions. In order to examine their abilities to convert waves at different wave heights and periods, herein, a critical investigation is conducted on the energy efficiency of wave gliders. This article is aimed to introduce the structure, movement mechanism, as well as energy conversion, and transfer form of wave gliders. In addition, an appropriate mechanical model for wave gliders is developed and analyzed and the energy efficiency formula is derived using the numerical analysis approach. The "Blue Whale" wave glider is utilized to carry out energy efficiency experiments to assess the wave conversion ability of wave gliders, and to master the wave conversion efficiency of wave gliders in various sea conditions. Finally, based on the experimental data, the influences of wave height and wave period on the energy conversion efficiency of wave gliders are methodically analyzed. The achieved results reveal that the energy conversion efficiency of the wave glider is not directly correlated with the wave period or the wave period, but it exhibits a specific correlation with the ratio of wave period to wave height, but the correlation coefficient is only 0.78. This issue guides us to further examine the deep mechanism that affects the energy conversion efficiency of wave gliders in the near future.
Automatic Monitoring and Control System of Distribution Network Transformer Energy Consumption Based on Single-Chip Microcomputer
Authors: Yonghui Hou
Published: January 2025

Distribution network transformers are widely used in power systems. Aiming at the problem that high energy consumption is easy to lead to energy waste, an automatic detection and control system of energy consumption of distribution network transformer based on single-chip microcomputer technology is proposed. The control center of the system design is a single-chip microcomputer, which calculates the transformer load through the multi-function meter, and sets the corresponding gear adjustment threshold to adjust the capacity of the transformer, so as to reduce losses and save energy. After case verification, this method can greatly improve the energy-saving effect of distribution network transformers, and at the same time operate stably and reliably.
The Application of the Binary Logistic Regression Mathematical Model in Farmers’ Willingness for Land Transfer: Based on Dual Rationality Theory
Authors: Ke Ding
Published: January 2025

In China’s rural land system, land ownership is collectively held, and households obtain contracting rights through agreements, granting them operational rights over the land. The transfer of these operational rights enhances agricultural productivity and optimizes rural resource allocation, with farmers’ willingness to engage in such transfers being a critical factor in determining the efficiency of land transfer. This study, based on the “dual rationality theory”, constructs a theoretical model of farmers’ land transfer willingness from the dual perspectives of “instrumental rationality” and “value rationality”. A survey of 456 households in 17 typical indigenous villages in Guizhou Province, China, was conducted to investigate their willingness to transfer land. The data were analyzed using a binary logistic regression model and SPSS software, exploring the relationship between the variables of “instrumental rationality” and “value rationality” and the farmers’ willingness to transfer land. The findings reveal that, in terms of “instrumental rationality”, anticipated economic benefits and a high level of trust in rural collective organizations are significant factors influencing farmers’ decisions regarding land transfers. On the other hand, elements of “value rationality”, such as a deep emotional attachment to the land, strong identification with their status as farmers, and the emotional significance of the land, play a crucial role in shaping their willingness to transfer land. To facilitate an orderly and effective land transfer process, it is essential to develop and innovate land transfer models suited to local conditions, implement flexible pricing mechanisms, and establish land transfer platforms primarily managed by village committees. Additionally, reforms in the rural social security system should be prioritized, and the implementation of land transfers should consider cultural nuances.
Analysis of Carbon Emission Reduction Effect and Mechanism of Digital Economy: A Perspective to Protect Environment
Authors: Shaoli Liu
Published: January 2025

In recent years, digital technology has comprehensively empowered the economic and social system, which has undergone earth-shaking and far-reaching changes, and the digital economy has also shown good effects of energy conservation and emission reduction. In order to achieve environmental sustainability as soon as possible, this paper analyzes the theoretical mechanism and transmission process of the digital economy's impact on carbon emission from the perspectives of direct effects, indirect effects and spatial spillover effect. It takes 17 cities in Henan province as research objects to conduct an empirical analysis of their panel data from 2011 to 2019. The main findings are: (1) In the process of promoting the development of digital economy, Henan province indeed reduced carbon emissions on the whole; (2) The development of digital economy in Henan province ultimately reduced carbon emissions by promoting industrial structure upgrading and green technology innovation. (3) The carbon emission reduction effect of the digital economy in Henan province has obvious spatial spillover effect, which can reduce the carbon emissions in the surrounding areas; (4) The development of digital economy indeed increases carbon emissions in the early stage, which is an inevitable phenomenon. This paper not only provides a provincial perspective for systematically understanding the impact of digital economy on carbon emissions, but also provides theoretical foundation for promoting the comprehensive green transformation of economic and social development, actively and steadily promoting carbon neutrality.
Data Asset Information Disclosure and Capital Market Efficiency: Empirical Research Based on Big Data Text Mining
Authors: Shuhui Wang
Published: January 2025

In the era of big data, the significance of data has skyrocketed. It has transformed into a new type of asset and a significant element of production, which contributes immensely to the sustainable development and competitiveness enhancement of enterprises.This research focuses on the A-share listed companies in China over the period of 2007 to 2022, and uses Word2Vec neural network model and deep learning text mining method to investigate the ramifications and mechanism of data asset information disclosure on the effectiveness of corporate capital market. The findings indicate that: 1) data asset information disclosure noticeably enhances the efficiency of corporate capital market; 2) data asset information disclosure have a positive impact on corporate capital market efficiency by enhancing corporate governance, increasing institutional investors’ shareholding and improving stock liquidity; 3) the data asset information disclosure has a more pronounced improvement effect on corporate capital market efficiency in growing and mature firms, and stronger in high-technology, state-owned, media-focused and investor-focused enterprises. The research conclusions are of great significance to improve the behavior of enterprise data assets information disclosure, enhance the capital market operation efficiency, as well as fostering the development of a robust and superior quality capital market.
Trend Events and Lag Coefficients in Time Series Association Rule Discovery
Authors: Zhonglin Sheng
Published: January 2025

Trend events reveal long-term changes in time series data and help capture long-term pattern shifts. Lag coefficients, on the other hand, focus on the impact of past events on the present or future, helping to uncover time delays and causal relationships. In time series association rule discovery, considering trend events and lag coefficients can enhance the model's predictive power and provide more accurate decision support, particularly in fields such as finance, market analysis, and epidemiology. Both of these factors are key elements for effective modelling and rule mining, and are crucial for extracting meaningful time series patterns. This paper analyses those key challenges and introduces a new approach to solve these problems by constructing trend events and solving for lag coefficients. Based on this approach, some algorithms are proposed to improve classic association rule discovery method. The experiment with PM2.5 data set proves the effects of discretization of trend event and shows the hidden frequency pattern considered lag coefficient. This research represents a meaningful attempt to improve the effect of association rules discovery within multiply time series.
Cross-disciplinary Teaching for Chinese College Students Based on Enhanced Graph Neural Network - Taking Piano Class as an Example
Authors: Xiaoyan Chen
Published: January 2025

The aim of this study is to comprehensively understand and optimize the curriculum of interdisciplinary course settings in piano courses for Chinese university music students, with the goal of enhancing educational quality and student learning outcomes. The study proposes an intelligent piano teaching recommendation feedback system based on the Knowledge Graph Enhanced Graph Neural Network (KGEGNN). This system leverages deep learning techniques combined with knowledge graphs to extract features from user learning behaviors, thereby providing personalized teaching recommendations and real-time feedback. Additionally, it utilizes enhanced graph neural networks to extract reinforcement items from indirect interactions among users, aggregates embeddings of users and items, and makes recommendations through prediction functions to offer personalized music teaching suggestions and feedback. In terms of experimental results, the KGEGNN algorithm achieves 94.58% for Top1-Accuracy and 91.29% for Top1-F1 score, while achieving 95.36% for Top5-Accuracy and 92.81% for Top5-F1 score, representing at least a 6% improvement in prediction accuracy. Thus, the Intelligent Piano Teaching Recommendation System constructed in this study demonstrates significant advantages in multi-candidate prediction and recommendation accuracy, with important potential and practical value in enhancing learning outcomes and promoting curriculum optimization.
Optimizing Blended Learning with Digital Technologies: Insights into Faculty Readiness in Higher Vocational Education
Authors: Yi Yang
Published: January 2025

Blended Learning (BL) has emerged as a transformative strategy in higher education, propelled by advancements in educational and computational technologies and the growing demand for flexible learning environments. Based on the framework of Barriers to Technology Integration, this study focuses on China’s higher vocational education sector, specifically at Guangdong Polytechnic of Science and Technology (GPST), where the successful implementation of BL hinges on understanding the interplay between key dimensions influencing teacher readiness: Institutional Culture, Technological Pedagogical and Content Knowledge (TPACK), Affective Factors, and BL Awareness. Utilizing a mixed-methods approach, this research surveyed 370 GPST teachers and conducted in-depth interviews with 10 experienced educators to assess their preparedness for BL. The findings underscore significant challenges in BL readiness, particularly linked to institutional culture, which adversely impacts teachers’ TPACK and emotional readiness for BL. While BL Awareness had a limited direct effect, the synergy between technological and psychological factors was found to be crucial in shaping overall readiness. These insights inform policy development and emphasize the need for enhanced technological infrastructure and robust teacher support systems to foster greater BL readiness in Chinese higher vocational institutions.
Sentiment Analysis Based on Multiscale Convolutional Neural Network and Bidirectional Long Short-Term Memory
Authors: Yan Chen
Published: January 2025

With the prevalence of social media, Weibo has emerged as a crucial platform for individuals to express emotions and opinions, making accurate analysis of its sentiment content significantly meaningful. In order to more effectively capture the semantic and emotional information within Weibo text, a deep learning model that integrates multiscale CNN and BiLSTM is proposed. Firstly, this research utilizes a CNN model with multiscale convolutional kernels to perform feature extraction on Weibo text using various kernel sizes, thereby capturing both local and global information within the text. Subsequently, the incorporation of BiLSTM networks as a component of sequence modeling effectively captures long-distance dependencies within Weibo text. Through the combination of CNN and BiLSTM, the model gains a better understanding of the semantic structure and emotional expressions within Weibo text. Comparative experiments demonstrate that the proposed approach outperforms other sentiment analysis methods, showcasing higher accuracy and better overall effectiveness. This study proposes an innovative model for Chinese microblog sentiment analysis by integrating multi-scale CNN and BiLSTM technologies. It not only enhances the accuracy and efficiency of sentiment recognition but also deepens the theoretical foundation of online sentiment research, exerting significant influence and potential application value in fields such as social media sentiment monitoring and public opinion mining.
Protective effect of Thiocolchicoside against Haloperidol Induced Orofacial Dyskinesia and Catalepsy in Rats
Authors: D. Pore Dipti , B. Velhal Atish , K. Redasani Vivekkumar
Published: January 2025

The goal of the current study was to assess thiocolchicoside's impact on catalepsy and orofacial dyskinesia in wistar male albino rats that had been induced by haloperidol. The neurodegenerative illness known as catalepsy, whose cause is unclear, is typified by motor symptoms such as bradykinesia, tremor, rigidity in the muscles, and instability in one's posture. It's a disorder marked by a tendency to remain motionless, a decrease in reactivity to stimuli and inactivity. The inability to adjust one's posture in response to external signals is known as catalepsy. Tardive dyskinesia is an iatrogenic illness defined by late-onset hyperkinetic involuntary dyskinesia, usually affecting the orofacial region, caused by long-term use of classical neuroleptics. Neuroleptics causes blockade of dopaminergic (DA) transmission produces catalepsy. Haloperidol blocks dopamine D2 receptors and reduces dopaminergic transmission in the basal ganglia, which puts animals in a state of catalepsy. The anticataleptic study was carried out on animal model such as haloperidol induced orofacial dyskinesia and catalepsy. Animals of this model were treated with std. drug levodopa/carbidopa (125mg/kg) and test drug thiocolchicoside low dose (4mg/kg), high dose (8mg/kg). The persistent injection of haloperidol to rats resulted in a considerable increase in catalepsy, tongue protrusions, and vacuous chewing motions (VCMs). These results indicate that thiocolchicoside possess anticataleptic effect against haloperidol induced catalepsy in rats. The results indicated strong anticataleptic efficacy, suggesting that thiocolchicoside may be useful in the treatment of catalepsy.
КУЛЬТУРОМОВНА ОСОБИСТІСТЬ КРІЗЬ ПРИЗМУ УКРАЇНСЬКОЇ ЛІТЕРАТУРИ: ПРИКЛАДНІ АСПЕКТИ В КОНТЕКСТІ ІНФОМЕДІЙНОЇ ГРАМОТНОСТІ
Authors: ГРОНА Н. В. , СЕМЕНОГ О. М.
Published: January 2025

У статті розглянуто сучасні підходи до формування культуромовної особистості засобами української мови в закладах фахової передвищої освіти (ЗФПО) у контексті інфомедійної грамотності. Проаналізовано основні принципи та концептуальні засади медіаосвіти, запропоновано шляхи їхньої ефективної інтеграції в освітній процес. Дослідження підкреслює значущість української літератури як ключового компонента української освіти, що сприяє формуванню національної ідентичності, морально-етичних цінностей, патріотизму та громадянської свідомості. Окрема увага приділяється ролі інфомедійної грамотності в розвитку критичного мислення, читацької компетентності та загальної освітньої продуктивності. Висвітлено досвід інтеграції інфомедійної грамотності у процесі вивчення української літератури, зокрема через застосування інноваційних навчальних технологій, мультимедійних ресурсів та критичного аналізу медіаконтенту. Обґрунтовано необхідність комплексного підходу, що передбачає постійне оновлення змісту навчання, розвиток інформаційно-комунікаційних технологій, а також формування стійкості до інформаційних впливів. У статті узагальнено матеріал про важливість системного впровадження медіаосвітніх підходів для досягнення високих результатів у формуванні культуромовної особистості, здатної активно і свідомо взаємодіяти з інформаційним середовищем, зберігаючи при цьому національні цінності та культурну ідентичність.
ПОЕТИКА ЕРОСУ І ТАНАТОСУ В НОВЕЛАХ ІВАНА ФРАНКА «СОЙЧИНЕ КРИЛО» ТА «НЕНАЧЕ СОН»
Authors: КОВАЛЬЧУК О. С.
Published: January 2025

У статті розглянуто особливості поетики Еросу і Танатосу в новелах Івана Франка «Сойчине крило» та «Неначе сон». З’ясовано генезу обраних творів та встановлено чинники, що вплинули на їхню появу. Здійснено поглиблений аналіз теоретичних і методологічних основ художньої філософії І. Франка та висвітлено заплутану взаємодію між життям і смертю, коханням і деструкцією в його творах. Проаналізовано використання символів, що є одними з найвиразніших аспектів функціонального виміру Франкової прози. Особливий фокус уваги спрямовано на концепції Еросу, які знаходимо в описах романтичних і сексуальних стосунків або в проявах життєвої сили, та Танатосу, або потягу до смерті й руйнації, який заслужено вважають однією із наскрізних тем в оповіданнях Франка. Поетика Еросу і Танатосу в малій прозі Франка засвідчує усвідомлення неминучості смерті та її всепроникного впливу на людину, а також демонструє жагу до життя, творення та любові. Результати, отримані в ході аналізу обраних новел, сприяють глибшому розумінню загальної панорами малої прози Франка. Сприйняття та критика творів Франка з часом розвивалися, спочатку зосереджуючись на соціальних і класових конфліктах, але все більше визнаючи психологічну та символічну глибину його прози. Сучасне літературознавство нині оцінює творчий спадок Івана Франка як вагомий внесок не лише в українську, а й у світову літературу, оскільки Франкова проза часто пов’язана із загальнолюдською проблематикою. Таким чином, мала проза Івана Франка виходить за межі традиційного літературознавчого аналізу, даючи багатий матеріал для роздумів над вічними темами Еросу і Танатосу. Це робить Франкові твори актуальними та значущими на всі часи, запрошуючи читачів та дослідників замислитися над складністю людського існування крізь призму майстерності його прозових творів.
МОВНОКОМУНІКАТИВНА КОМПЕТЕНТНІСТЬ СТУДЕНТІВ-МЕДИКІВ: ОСОБЛИВОСТІ СУЧАСНОГО НАУКОВОГО ДИСКУРСУ
Authors: СІЛЕВИЧ Л. І.
Published: January 2025

У статті визначено особливості сучасного наукового дискурсу, який розкриває актуальну різноаспектну проблемно-тематичну специфіку дослідження мовнокомунікативної компетентності студентів вищих медичних закладів освіти. Проаналізовано особливості науково-дослідницьких інтересів викладачів-мовознавців, які беруть участь у підготовці майбутніх спеціалістів сфери охорони здоров’я. Відзначено, що для дослідження використано низку методів, зокрема прес-кліпінгу, бібліографічний, описовий, аналізу й синтезу, що дозволило отримати нову наукову інформацію про тематику сучасних досліджень, об’єднаних поняттям «мовнокомунікативна компетентність». Визначено основні проблемно-тематичні аспекти сучасного наукового дискурсу вказаної проблематики, за якими провадять дослідження мовознавці: формування мовнокомунікативних умінь майбутніх спеціалістів, мовнокомунікативна компетентність та її ефективність, культура професійного спілкування, специфіка комунікації медичних працівників з пацієнтами; мовнокомунікативні тактики спеціалістів, плекання успішної мовної особистості майбутнього медичного фахівця. Наголошено, що професійні вимоги і виклики сьогодення вимагають удосконалення освітнього процесу, покликаного покращувати наявні і формувати нові прийнятні моделі формування мовнокомунікативної компетентності майбутніх медиків. Доведено, що сучасний науковий дискурс мовознавців характеризується багатогранністю обговорюваної проблематики, а отже, сприяє розвитку цієї важливої сфери вивчення української мови за професійним спрямуванням. Відзначено, що здійснений аналіз наукового дискурсу вказаного напряму дозволяє акцентувати складні проблеми, які потребують нагального розгляду та покращання навчального процесу. Підкреслено, що отримані результати в перспективі можуть стати основою практичних рекомендацій мовознавцям для заповнення дослідницьких прогалин у царині удосконалення мовнокомунікативної компетенції студентів-медиків.
2024 IKCS NA - Recommended Abstracts
Authors: Pazhanisamy Senthil
Published: January 2025

These recommended abstracts from 2024 IKCSNA Annual Meeting highlight some of the most important
trends in ongoing trials chosen by Dr. Hutson and reflect the foremost research and strategies from latest clinical trials that impact the current standard of care in renal cancer.
IKCS 2024: Moving Kidney Cancer Care Forward: Insights from the 25th Anniversary Symposium
Authors: Zakharia Yousef
Published: January 2025

The 25th Anniversary International Kidney
Cancer Symposium (IKCS 2024) in Louisville,
Kentucky, brought together leading experts
to discuss the latest advancements in
kidney cancer research and treatment. Key
highlights included presentations on novel
therapeutic approaches, including emerging
immunotherapies and targeted therapies. The
symposium also emphasized the importance
of multidisciplinary care, patient-centered
outcomes, and the role of supportive care in
improving the overall patient experience. This
meeting summary provides a comprehensive
overview of the key findings and discussions
presented at IKCS 2024.