bluuebunny/crossref_metadata_2025_split huggingface dataset:
In vitro modulation of seizure-like activity with beta-cyclodextrin-complexed rufinamide
Authors: Kiss Rita-Judit , Nagy Zsolt András , Szentes Ádám , Csüdör Ágnes , Máthé Andrea , Makó Henrietta , Bomher Előd , Berki Ádám József , Gáll Zsolt , Szilágyi Tibor , Orbán-Kis Károly 
Published: October 2024

Abstract

Objective
The global health concern of pharmacoresistant epilepsy necessitates innovative therapeutic strategies. Drug resistance often arises due to complex pharmacokinetic challenges. Beta-cyclodextrin, known for enhancing drug solubility and stability, offers a potential solution for improving the efficacy of antiseizure medications. This study aims to investigate the impact of beta-cyclodextrin-complexed rufinamide on seizure-like activity using an in vitro model of temporal lobe epilepsy.

Methods
Seizure-like neuronal activity was induced using a low-magnesium model. Local field potentials were recorded from transverse rat hippocampal slices. Rufinamide was solubilized using beta-cyclodextrin and administered at 100 micromolar concentration. The impact on various seizure-like parameters and time-resolved phase-amplitude coupling was assessed.

Results
Rufinamide increased the duration of the preictal phase while reducing the duration of ictal and postictal phases. The frequency of seizure-like events was higher in rufinamide. No significant change was observed in the firing rate of the first 10 ictal spikes, but the firing frequency of the second set of 10 ictal spikes was higher during rufinamide perfusion. Time-resolved phase-amplitude coupling maximum analysis did not reveal significant differences between the control and rufinamide treatment.

Conclusions
Beta-cyclodextrin-solubilized rufinamide significantly modulates seizure-like event dynamics, exhibiting both anticonvulsant and proconvulsant effects. While the compound shortened seizure-like activity, it increased the frequency of seizure-like events. Our observations suggest a need for further investigation into the solubilization method and its impact on rufinamide’s bioavailability. Dose-dependent effects and underlying molecular mechanisms should also be explored to enhance the pharmacological properties of antiseizure medications.
Knowledge System Synergy Mechanism of Innovative Entrepreneurial Teams in Universities
Authors: Ma Shaohui 
Published: October 2024

Abstract
The study divides the knowledge system of university students’ innovation and entrepreneurship teams into the main system, resource system, operation system, environment system, and exchange system, constructs the synergistic mechanism model of each subsystem, and accelerates the generation of innovation results. Then, from the perspective of the knowledge ecosystem and social network, an innovation team of University M is selected as the research object to analyze the characteristics of the synergistic network of the knowledge system of the team, to find out the cohesive subgroups, structural holes, edge points, and isolation points in the network, and to validate them by using the social network analysis method. The overall network analysis yielded that the overall network centrality potential of this innovation and entrepreneurship team was 25.52%, the connection between members was not strong, the team was loose, and the knowledge-sharing activities were not active. Individual net analysis reveals that active participants in knowledge synergy activities, whether spreading knowledge or learning knowledge, play an important role in sharing knowledge within the team but can be overly dependent. The analysis of this study will help to discover the characteristics of knowledge synergy behavior of innovation and entrepreneurship teams and the factors affecting the synergy behavior, which can be used as an objective basis for improving the synergy behavior of team knowledge systems.
Particle Batik: Digitalize Traditional Batik through the Particle-driven System
Authors: Feng Qiao , Tang Xin , Song Qichao 
Published: October 2024

Abstract
With the deepening of cultural digitization in recent years, researchers have begun to explore the use of digitization to promote the innovation of traditional culture, trying to seek new paths for the promotion and revitalization of conventional culture under new visions, new disciplines, and new technologies. Based on the development history and current situation of Batik in Malaysia and Indonesia, this paper takes Malaysian Batik works as an example. It develops a Batik particle engine-generated painting system-”Particle Batik.” This system is innovative because it ensures that every particle is accurately set up according to the color samples and position of the Batik works during the creation process. When the search engine loads the next Batik artwork, all the particles will be resampled and generated according to the newly loaded artwork, and the trajectories of the particles and their resulting line traces will be continuously superimposed and fused on the canvas, thus forming a dynamic generative artwork evolving. The Particle Batik system enhances the multidimensional expressiveness of Batik, significantly contributing to the global dissemination and cultural value of Batik art. The system successfully integrates traditional handicrafts and modern digital technology and facilitates the mutual exchange and symbiotic development between traditional culture and modern art forms. Promoting the integration and exchange of Batik culture globally allows it to adapt and integrate more closely with contemporary society and culture.
Improvement path of singing skills under the influence of cross-cultural communication in vocal music education
Authors: Deng Hui 
Published: October 2024

Abstract
Colleges and universities are not rich enough in initiatives on singing skills influenced by intercultural communication and need to further improve their relevance. This paper uses structural equation modeling to explore the influence of singing skills on vocal education. Initially, it outlines the significance of cross-cultural communication for vocal education in colleges and universities and summarizes the factors that influence cross-cultural communication. After selecting the survey respondents, the questionnaire questions are designed, the survey is collected with research data, and the results of the survey are examined for reliability and validity. The research hypothesis is proposed, and the structural equation modeling task is completed using both the measurement model and the structural model together. Combined with the data collected in the previous section, vocal singing that integrates cross-cultural concepts is empirically analyzed. The data show that the Spearman correlation coefficients of language, music theory, music skills, comprehension, interpretation, and cultural background with the effect of vocal singing skill enhancement are 0.632 (0.016), 0.203 (0.008), 0.651 (0.027), 0.637 (0.008), 0.246 (0.048), 0.588 (0.046), all of which are significantly correlated below 0.05. Among the six influencing factors, the structural path coefficient between musical skill and vocal singing skill improvement effect is 0.376, which has the greatest influence on vocal singing skill improvement. Through a quantitative analysis of vocal singing that integrates the concept of intercultural communication, this study provides a clearer understanding of how singing skills can be enhanced under the influence of intercultural communication.
Research on Optimization of Traffic Management in Smart Tourism Cities for Sustainable Development
Authors: Liu Min 
Published: October 2024

Abstract
In order to accelerate the efficiency of urban traffic operation in tourism and maximize the efficiency of urban traffic operation. This paper conducts systematic research on urban traffic conditions and proposes the construction of an intelligent urban traffic management system. First of all, the system structure is designed from the whole, and the system is divided into the information collection stage, the information processing stage, and the information release stage to clarify the functions that the system needs to realize. The design of the system includes queries for road conditions, bus transfer, walking navigation, and background management of each functional module. By building a good system development environment, system functions can be realized in code. Visitor satisfaction was evaluated using the fuzzy comprehensive evaluation method, and simulation experiments were carried out to evaluate the system’s optimization effect. The satisfaction of tourists in terms of convenience and comfort is improved compared with that before the use of the system. After the implementation of the intelligent traffic management system, the delay time of the intersection with the most complex road conditions in peak hour E is reduced by 19.8 s. The delay time in the peak hour is reduced by 4 s. It shows that the system improves the satisfaction of tourists in terms of convenience and comfort reduces the possibility of congestion for the tourists and the residents to travel, and improves the utilization rate of the road. The utilization rate of the road.
Research on the application of BP neural network model in the construction of performance evaluation index system
Authors: Xie Yushan , Luo Miaohua , Xie Peifeng , Liu Xiaolin 
Published: October 2024

Abstract
BP neural network is able to model and predict complex nonlinear relationships by learning and adjusting weight parameters, which shows great potential in performance evaluation. After optimizing the BP neural network model by using the particle swarm algorithm, the article proposes a new model for performance evaluation using the BP neural network as the basic model and conducts an empirical study with data from 10 enterprises. The results of the study show that in the implicit layer node trial-and-error method experiments, the overall error of the model shrinks with the increase in the number of neurons. When the number of neurons is 9, the “V-MSE” is the smallest among all the hidden layers with the value of 0.00051, and the value of R2 is 0.9631, which shows that the model has a good convergence and fitting effect.
An in-depth analysis and prediction study of consumer buying behavior for digital marketing
Authors: Ma Xiaoyan , Wang Peng 
Published: October 2024

Abstract
With the rapid development of the economy, the influence of digital marketing on consumer buying behavior is becoming more and more important. This paper first introduces the consumer purchase behavior regression model (SICAS) for digital marketing. Secondly, a locally weighted linear regression model based on SGD is constructed using nonparametric linear regression, local weighting, and stochastic gradient descent algorithms. This model is used to regression analyze the factors affecting consumer purchase behavior and identify the important factors that affect consumer purchase decisions. Finally, the insights of a digital marketing approach to enhance consumer buying behavior are given. People who buy goods offline account for 30.7%, while the remaining 69.3% choose online shopping. With the development of the digital market economy, online purchases will become mainstream. The reliability coefficient is in the range of 0.851-0.949, the KMO is 0.924, the Bartlett value is 759.766, and the significance is P < 0.05. The variables’ high reliability and correlation make them suitable for factor analysis. The coefficients between the factors and consumer purchase decisions were 0.774, 0.805, 0.832, 0.332, and 0.894 (P < 0.01). The model R2 was 0.868 and F = 225.968 (p<0.05), indicating that the model is valid. Except for gender, there is a significant positive correlation (p<0.05) between all variables and consumer purchase decisions. Obviously, selecting appropriate digital marketing strategies is crucial to understanding consumer purchasing behavior.
Effectiveness of Mental Health Services for Improving Minors’ Behavior in Community Corrections Using Online Platforms
Authors: Shi Mengyi 
Published: October 2024

Abstract
The use of a network platform for the online correction of minors helps to optimize the correction effect. In this paper, we build a network platform for minor community correction, employ TAN Bayes to measure the corrective mental state, and utilize support vector machines to extract corrective content and identify relationships between it after text preprocessing. Next, the feature values are obtained by reducing the number of dimensions using probability matrix decomposition. The gradient descent method is then used to optimize the matrix. The feature matrix is then created, and the improved PMF is added to the ConvMF model. Finally, the Gray Wolf algorithm is used to improve the corrective content recommendation. After the platform construction was completed, the effect of applying this paper’s platform to two corrected minors was analyzed, and it was found that in the group of minors’ community correctional subjects, the correctional content recommended by the three different types of this paper’s platforms would all have different impacts in different dimensions compared to the whole. Before beginning corrective action using this article’s online platform, Case A’s evaluation on the 10 questions averaged 93.41 points, indicating a poor corrective psychological state and a high risk of mental health. After six months of online correction on this paper’s online platform, the psychological state improved significantly, with an average of 48.3 points on the posttest and a reduction of more than 40 points on each topic item. Compared to before the start of correction, the psychological risk has significantly decreased. Case B scored an average of 93.92 points on the 10-topic item pre-test, indicating an unacceptable mental health status that necessitates immediate intervention. After six months of online correction, On this paper’s online platform, the average posttest score was 47.69, with an average decrease of 46.23 points for each item, and significant results were achieved. This paper provides useful exploration for optimizing the method of community correction for minors and improving its effectiveness for minors.
Research on personalized recommendation system for social media marketing content in big data environment
Authors: Zhang Shitao , Zhang Ning , Chu-ke Chun , Kim Hyunjoo 
Published: October 2024

Abstract
A personalized recommendation system is an effective and consistent marketing method that caters to consumer demand for goods. It solves the problem of consumer shopping choices on e-commerce websites and is currently a hot spot in the field of network information services. In this paper, from the perspective of the user’s shopping process, we summarize the four factors that can maximally reflect the consumer’s interest and preference, i.e., product browsing, collection, adding to cart, and purchasing behavior. To achieve static user interest weights, we quantify each index factor and set the corresponding rules. Considering the change in user interest, the decaying interest value over time is designed to compensate for the deficiencies of static system recommendations. We use implicit user feedback data to identify content that truly interests users and then construct a personalized recommendation algorithm for social media marketing content using multi-source data. The test results show that UIPR has an MRR value of more than 0.8 and an NDCG value of more than 0.55 in both the MovieLens and Taobao datasets, compared to the baseline model’s best value. This proves that UIPR consistently performs better and makes better recommendations.
Innovation of Student Quality Evaluation Model in Vocational Education under Cloud Computing Environment
Authors: Chen Sheng 
Published: October 2024

Abstract
This paper takes cloud computing technology as the core, constructs a student quality evaluation model, collects and analyzes students’ learning data through cloud computing technology, proposes the direction of optimization and reform of the educational quality evaluation system, and establishes a comprehensive quality evaluation management system for students. Combining AHP and entropy weight methods, the subjective and objective weights of each index are calculated, and the comprehensive weights are determined through game theory. Based on the evaluation method of students’ comprehensive quality, the cloud model is established, the normal cloud digital features are calculated, and the mapping of qualitative concepts to quantitative representations is realized through the forward cloud generator, which completes the construction of the evaluation index system of students’ comprehensive quality. The evaluation cloud model is obtained by using the digital features calculation, and the cloud is located between levels 8 and 9 because E
x = 8.5265, which has a closer fit with level 8, indicating that the comprehensive quality of the student belongs to the good upper level. In the comparison of the innovation of the student quality evaluation model, the comprehensive theoretical quality of the students in the experimental group is 8.215 points, and the P value is 0, significantly higher than that of the control group students, and the model innovation effect is remarkable.
The Impact of Leadership, Communication, and Teamwork Practices on Employee Trust in the Workplace
Authors: Eva Tamanna Parvin , Afroze Rumana , Sarker Md Atiqur Rahman 
Published: October 2024

Abstract
Soft skill practices play an extensive role in creating sustainable and trustworthy relationships between employees and employers in the service sector. Organizational success largely depends on attracting and retaining a talented workforce for which soft skill practices are essential. The banking sector in Bangladesh emphasizes practicing leadership, communication, and teamwork as the most prevalent soft skills for gaining employees’ trust and enhancing the efficient performance of the employees. This study aims to identify the impact of managers' practising these three pivotal soft skills on attaining employees’ trust in the workplace. This study has been conducted by administering a structured questionnaire survey using a convenient sample of 104 employees from different private commercial banks in Bangladesh. Collected data were examined by using Pearson’s correlation and multiple regression analysis to test the hypotheses. The results of the analysis reveal that practising leadership, communication, and teamwork skills create a significant and positive impact on employee trust in the workplace. This paper noticeably contributes by creating awareness among bank managers regarding the selected three skills practices to create employee trust in the workplace, which is considered to be bridging the gap of current managerial practices in the private bank organization of Bangladesh. The findings of this study help practitioners realize the intensive utilization of leadership, communication, and teamwork skills to gain greater employee trust in the workplace.
Applications of Lidar Data Exploitation for Displacement Measurements and Change Detection
Authors: Glonţ Cristiana , Balotă Octavian Laurențiu , Balasz Csaba 
Published: October 2024

Abstract
The denser the Lidar data, the more faithfully it models the terrain. This property of dense Lidar data allows a detection of changes but also their quantification at a level of precision that can highlight even displacements of objects in all three spatial directions. The point cloud has different densities and accuracies depending on the platform on which the scanning system is installed (manned aircraft, drones or ground stations). Density and precision parameters drive different approaches in change detection algorithms. For completing these tasks, two independent applications were developed to highlight both major landscape changes and smaller changes such as displacement of objects, construction settlements, landslides.
Monte Carlo dosimetry for BEBIG Cobalt-60 brachytherapy source with gynecological applicator in the presence of inhomogeneities
Authors: Moradi Farhad , Sani Siti Fairus Abdul , Mahyuddin Azman , Ung Ngie Min , Bradley David Andrew , Almugren Kholoud , Rashid Hairul Azhar Abdul 
Published: October 2024

Abstract

Introduction: High-dose-rate (HDR) 60Co brachytherapy necessitates accurate dose calculations to minimize normal tissue toxicity and late malignancy risks. Conventionally, the American Association of Physicists in Medicine (AAPM) Task Group 43 (TG-43) formalism, utilizing table-based dose superposition, has been employed for dose calculations, overlooking tissue inhomogeneity effects.

Material and methods: This study focuses on characterizing the high-dose-rate BEBIG 60Co brachytherapy source, in combination with a gynecological applicator, using Monte Carlo simulations. The investigation is based on the model of the modified BEBIG 60Co source (Co0.A86) implemented at the University of Malaya Medical Center. Dosimetric properties are evaluated according to AAPM TG-43 formalism, with validation against existing published data.

Results: Our investigation presents comprehensive MC dosimetric properties of the high-dose-rate BEBIG 60Co brachytherapy source, highlighting its accuracy in dose calculations compared to established data. The study also examined the impact of the applicator on depth dose calculations within a Krieger phantom and explored the influence of various tissue inhomogeneities on the depth dose.

Conclusions: Our findings revealed that the applicator had a relatively minimal effect on the delivered dose, with only marginal differences observed. Furthermore, we investigated the depth doses along the central axis of the applicator, within a segment characterized by various tissue inhomogeneities where dose differences of up to 12% were observed, with the lowest and highest doses recorded within bone and adipose tissues, respectively. This study underscores the valuable role of MC simulations in estimating doses at locations where physical measurements are unfeasible, such as the intra-uterine tube surface, as well as in scenarios featuring tissue inhomogeneities.