bluuebunny/crossref_metadata_2025_split huggingface dataset:
User Experience of a Semi-Immersive Musical Serious Game to Stimulate Cognitive Functions in Hospitalized Older Patients: Questionnaire Study
Authors: Samson Laurent , Carcreff Lena , Noublanche Frédéric , Noublanche Sophie , Vermersch-Leiber Hélène , Annweiler Cédric 
Published: October 2024

Abstract

Background
Reminiscence therapy through music is a psychosocial intervention with benefits for older patients with neurocognitive disorders. Therapies using virtual or augmented reality are efficient in ecologically assessing, and eventually training, episodic memory in older populations. We designed a semi-immersive musical game called “A Life in Songs,” which invites patients to immerse themselves in a past era through visuals and songs from that time period. The game aspires to become a playful, easy-to-use, and complete tool for the assessment, rehabilitation, and prevention of neurocognitive decline associated with aging.

Objective
This study aimed to assess the user experience (UX) associated with the newly designed serious game.

Methods
After one or several sessions of the game guided by the therapist, patients of the geriatric wards were asked to answer questions selected from 2 widely known UX scales (AttrakDiff and meCUE [modular evaluation of the components of user experience]) with the therapist’s help. The internal consistency of the UX dimensions was assessed through Cronbach α to verify the validity of the dimensions. The level of engagement of the patient throughout the experimental session was also assessed following an internally developed scale, which included 5 levels (interactive, constructive, active, passive, and disengaged behaviors). UX mean scores were computed and presented graphically. Verbal feedbacks were reported to support the quantitative results.

Results
Overall, 60 inpatients with a mean age of 84.2 (SD 5.5) years, the majority of whom were women (41/60, 68%), were included. Their score on the Mini-Mental State Examination (MMSE) ranged between 12 and 29. A majority of patients (27/56, 48%) had no major neurocognitive disorder (MNCD), 22/56 (39%) had mild MNCD, and 7/56 (13%) had moderate MNCD. The results revealed very positive UX with mean values beyond the neutral values for every UX dimension of both scales. The overall mean (SD) judgment was rated 3.92 (SD 0.87) (on a scale of −5 to 5). Internal consistency was acceptable to good for the emotional dimensions of the meCUE. Questionable to unacceptable consistency was found for the other UX dimensions. Participants were mostly active (23/60, 38%) and constructive (21/60, 35%).

Conclusions
These findings demonstrated a very good appreciation of the game by geriatric inpatients. Participants’ and health care professionals’ verbal comments strongly aligned with the quantitative results. The poor internal consistency in the UX dimensions reflected the high heterogeneity among the included patients. Further studies are needed to evaluate the potential benefits of clinical factors such as neurocognitive functions, mood, depression, or quality of life.
Automated Real-Time Tool for Promoting Crisis Resource Use for Suicide Risk (ResourceBot): Development and Usability Study
Authors: Coppersmith Daniel DL , Bentley Kate H , Kleiman Evan M , Jaroszewski Adam C , Daniel Merryn , Nock Matthew K 
Published: October 2024

Background
Real-time monitoring captures information about suicidal thoughts and behaviors (STBs) as they occur and offers great promise to learn about STBs. However, this approach also introduces questions about how to monitor and respond to real-time information about STBs. Given the increasing use of real-time monitoring, there is a need for novel, effective, and scalable tools for responding to suicide risk in real time.

Objective
The goal of this study was to develop and test an automated tool (ResourceBot) that promotes the use of crisis services (eg, 988) in real time through a rule-based (ie, if-then) brief barrier reduction intervention.

Methods
ResourceBot was tested in a 2-week real-time monitoring study of 74 adults with recent suicidal thoughts.

Results
ResourceBot was deployed 221 times to 36 participants. There was high engagement with ResourceBot (ie, 87% of the time ResourceBot was deployed, a participant opened the tool and submitted a response to it), but zero participants reported using crisis services after engaging with ResourceBot. The most reported reasons for not using crisis services were beliefs that the resources would not help, wanting to handle things on one’s own, and the resources requiring too much time or effort. At the end of the study, participants rated ResourceBot with good usability (mean of 75.6 out of 100) and satisfaction (mean of 20.8 out of 32).

Conclusions
This study highlights both the possibilities and challenges of developing effective real-time interventions for suicide risk and areas for refinement in future work.
Improving Oral Health in Prisons (PriOH): Protocol for a Randomized Controlled Trial
Authors: Bryne Emilie , Bergum Kathrine Høyvik , Gjedrem William Gilje 
Published: October 2024

Background
People living in prisons often experience poor oral health, which could be attributed to their limited access to (dental) care, financial constraints, and a general lack of awareness and prioritization toward their oral hygiene. A pilot study involving motivational interviewing (MI) has shown promising results for improving the oral health outcomes of people living in prisons.

Objective
The protocol for this study aims to assess the efficacy of integrated MI and oral hygiene packages in improving oral health among people living in prisons, compared to controls without added MI.

Methods
This oral health in prisons study is a multicenter, randomized, double-blinded controlled trial that recruited inmates from 4 prisons in Rogaland County. The trial aimed to recruit 320 participants before randomly allocating them to either a control or intervention group. The intervention group received MI, consisting of a 30-minute session encouraging inmates to discuss their current and desired oral health behaviors and attitudes, highlighting discrepancies to motivate change. Assessments were conducted at 4 and 12 weeks after initiation. The primary outcome measurement is the mucosal-plaque scores to assess oral health behaviors, attitudes, and oral hygiene. Secondary outcome measurements are oral hygiene routines, sugary food and drink intake, oral health perception, and oral health-related questions.

Results
Data collection started in November 2021 and ended in June 2023. A total of 327 participants were recruited, of which 126 received the intervention.

Conclusions
Integrating MI in oral health programs at prisons can significantly improve the oral health of incarcerated individuals. Should the results from this study demonstrate efficacy, it could be valuable insight for policy makers, oral health practitioners, and correctional services in addressing the needs of a traditionally underserved group before being scaled up to enhance dental care practices in prisons.

Trial Registration
ClinicalTrials.gov NCT05695443; https://clinicaltrials.gov/study/NCT05695443

International Registered Report Identifier (IRRID)
DERR1-10.2196/60817
A Study of the Effect of Tourist Experience Quality on Loyalty and Revisit Intention in Tourist Destinations
Authors: Zhong Jieshan 
Published: October 2024

Abstract
This paper divides the quality of tourist experience from the two aspects of tourists’ expectation and satisfaction and establishes a multiple regression model to analyze the quality of tourist experience with product involvement and perceived value as variables. The three factors of tourists’ experience quality: product service quality, environmental quality, and perceived value are proposed. Research hypotheses on the three dimensions of tourism destination loyalty and revisit intention are established. Combined with descriptive statistics, the correlation analysis between tourist experience quality and loyalty is carried out. The structural equation model is selected to construct the relationship model, carry out the validation factor analysis of the quality of tourist experience and the loyalty and revisit intention of tourist destinations, carry out the model estimation and adjust the fitness, and validate the structural model path. These tests showed that the dimensions of tourist experience quality, tourist loyalty, and intention to return were convergent and valid (0.924>0.6), and the average variance extracted (AVE) of these dimensions was 0.689>0.5, which was the same as the test standard. All paths can use the structural equation modeling test. That is, the quality of product and service, environmental quality, and perceived value of tourist destinations all affect tourists’ loyalty and willingness to return to tourist destinations.
Research on new media art exchange and communication driven by artificial intelligence technology
Authors: Zhang Wenting , Wang Xuejiao 
Published: October 2024

Abstract
This paper gathers information on artificial intelligence, art communication, news communication, and other related topics, with the aim of comprehending the role of artificial intelligence in enhancing information and new media art communication. The paper selects information from the “Annual Development Report of China’s News Industry” and “Review of China’s Advertising Market” to analyze and summarize the current state of the gradual intelligentization of news. We examine the browsing data from new-era news media, including today’s headlines, to investigate the impact of intelligent news dissemination. Lastly, we scrutinize the spatial data from actual new media artworks to comprehend the role of intelligence as a catalyst for experiencing a sense of immersion. The results show that by June 2024, the number of Internet users will be as high as 725 million, accounting for 96.8%. The penetration rate of intelligent new media also rises gradually with changes in time. It reached 84.9% in 2023, and almost half of the users are undergoing intelligent migration. And Tencent News, as a new-age news media, tops the list with a monthly activity of 27,042.17. The interactive nature of artificial intelligence technology promotes artistic communication and broadens the scope of communication.
Research on the Effectiveness of Leadership Training and Volunteering Social Practice of College Students Assisted by Artificial Intelligence
Authors: Dong Haiyan 
Published: October 2024

Abstract
With the deepening of economic globalization, countries around the world have put forward new requirements for talent. College students, being a unique segment of society, must naturally adapt to these significant changes and undergo new enhancements. This paper utilizes undergraduates from a university as the research subject and develops a leadership model for college students by designing specific research variables. We use the questionnaire survey data to empirically investigate the relationship between the antecedent variables of college students’ leadership and their influence. To compare the means of the four antecedent variables, descriptive statistics were used. The levels of social participation were better than medium or above (p > 3.5), while the levels of organizational factors were lower and needed to be improved. Correlation and regression analyses verified the relationship between each dimension of the four antecedent variables and college student leadership. Some aspects of college students’ leadership are associated with the dimensions of social participation, family function, personal endowment, and organizational factors. Among them, the degree of social participation in the dimension of “participation in public affairs” will affect the development of college students’ leadership, and the correlation coefficient of the two is 0.663, which is positively correlated at the 0.01 confidence level. The mediation effect test concludes that social value mediates the influence of college students’ social participation in leadership. Finally, the research results propose a strategy for volunteering that uses artificial intelligence to help college students develop their leadership skills.
Research on Security Governance of Data Elements in the Context of Digitization
Authors: Li Tao , Xu Jiang 
Published: October 2024

Abstract
This paper presents a multi-subject collaborative data security governance system architecture that caters to various aspects of data security governance. It also introduces an attribute-based encryption technology that utilizes multi-subject data, specifically a multi-subject access control policy fusion algorithm scheme from a technical perspective. The neural network is chosen to build the prediction model. The particle speed is changed using the linear decreasing weight strategy. The improved particle swarm algorithm is used to set the initial weight coefficients and bias variables of the BP neural network. This creates the shared information security risk prediction model. In order to derive the maximum number of iterations of the data security risk prediction model, analyze the encryption and decryption overhead of the multi-owner access control strategy. Additionally, analyze the fluctuation amplitude of MAE and MRE that meets the error threshold range, selecting the virus attack industry for analysis. The probability of occurrence of information data risk points is assessed by analyzing the frequency of coding structure for data technology risk, data management risk, and data legal risk, which is combined with the interview data. The statistics show that the data management risk category, with a standard deviation of 32.64, is more volatile than the two core categories of data technology risk and data legal risk. The lack of stability exposes the data security of e-commerce platforms to risky turbulence.
Research on Interactive Product Design Based on User Behavior Data in Virtual Reality Environment
Authors: Liu Zhe 
Published: October 2024

Abstract
This paper designs an interactive product based on the virtual reality environment and related technologies and further optimizes the interactive product based on the user behavior data collected by the interactive product. Based on the ORB-SLAM algorithm, we construct a hand controller degree of freedom model for the interactive product to overcome the limitations of hand controller positioning. By constructing the ORB-SLAM3 jump perception model, the interactive product can be used more smoothly. The collected user interaction behavior data is downsized using PCA principal component analysis and interaction behavior characteristics of different users are classified using the LATM network. The average completion times of the camera proposed in this paper as a hand controller for tasks such as 3D pointing are 14.23, 12.29 and 13.68 seconds, respectively, which all perform well compared to other hand controllers. At the same time, the interactive products designed using the method of this paper have the least abnormalities detected by users during the use process, and the highest abnormal feeling rate is only 37.22%. There are significant differences in the behavioral characteristics of users during the use of interactive products, based on the distribution of feature data can be divided into three categories: virtual exploration, interactive experience, and traditional. Strategic directions for further optimizing interactive products can be provided through the behavioral analysis of users in different categories.
Dynamic Monitoring Mechanism for Management Accounting and ESG Compliance Based on Intelligent Analytics
Authors: Shen Wangqi 
Published: October 2024

Abstract
The world economy is rapidly developing, leading to constant updates and iterations in the environment, technology, and products, thereby exposing many companies to financial risks. Management accounting and ESG theory, as internal decision support tools, play a role in creating value and improving performance in enterprises. The article examines the functions of management accounting and ESG theories in dynamic monitoring mechanisms, based on basic research. Analyzing and predicting the financial status of Chinese A-share listed companies in 2020-2022 is achieved by proposing research hypotheses and designing measurement models and financial risk prediction models. The results show that management accounting and ESG compliance are important parts of the dynamic monitoring system. Because of this, big data statistics need to be used regularly to summarize, analyze, and find the root causes of problems found in the monitoring process and suggest solutions.
Research on Optimization Design of Physical Education Curriculum Structure Based on Genetic Algorithm
Authors: Su Dandan , Wang Zihao , Yan Junhan 
Published: October 2024

Abstract
Factors such as class, class time, teachers, courses, and classrooms influence the optimization of the physical education course structure, making it challenging for the traditional physical education course structure to adapt to the current standards. For this reason, the article uses a genetic algorithm to optimize the structure of the physical education course. Class time, teachers, classrooms, courses, and classes are selected as the variables of the physical education course structure optimization model, and according to the actual situation of physical education course structure in colleges and universities, hard and soft rules for course optimization are formulated, and the construction of the optimization model of physical education course structure is completed based on the principles of physical education course structure optimization. We optimize the traditional genetic algorithm using the simulated annealing algorithm, which addresses the local optimal solution issue in the sports course structure optimization model. Examine the parameters of the improved genetic algorithm, and use the algorithm from this paper to conduct a case study on optimizing the structure of physical education courses. The fitness function value of this algorithm is higher than that of the traditional genetic algorithm from both the students’ and teachers’ points of view. The improved genetic algorithm can get rid of the issue of course structures that don’t work well with each other, which makes the best use of physical education course resources.
User Satisfaction Enhancement Strategies for Intelligent Library and Intelligence Services
Authors: Wang Jing 
Published: October 2024

Abstract
China’s library and intelligence organizations have a long history, rich resources and excellent talents and have played an important role in various consulting services. They are currently facing fierce market competition, making it challenging to meet users’ needs. This paper first establishes the principles of digital information resource services, based on the principles, reference to the ACSI model and considers a number of indicators to establish a scientific user satisfaction measurement model of digital resources in line with the actual development of library intelligence. The relationship between intelligent library intelligence and user satisfaction is investigated by combining a measurement model and structural model. Relevant hypotheses are proposed, research variables are identified, and empirical analysis is utilized to evaluate the model’s practicability. The results of the empirical research show that the hypotheses that library intelligence services can improve user satisfaction are verified through the path significance test, and after analysis, we know that the standardized path coefficients of paths 1, 3-7 are 0.526, 0.395, 0.426, 0.536, 0.163, and 0.168, respectively, which are greater than 0 and the P-value is less than 0.05 so that the hypotheses 1, 3-7 are valid. Intelligent library intelligence-related variables have a positive effect on user satisfaction improvement.
A Study of Informatization and Data-Driven Career Planning in Career Guidance in Colleges and Universities
Authors: Yang Yuanyuan , Wei Zhanjun 
Published: October 2024

Abstract
Traditional career planning education and employment guidance is based on lectures and text reading, with a large amount of subjective coloring, which can’t achieve one person one strategy. This paper constructs a college career guidance information recommendation system based on collaborative filtering and K-means clustering to recommend suitable career information with a high potential success rate for students from both subjective and objective aspects. The weights of students’ features are objectively calculated, and the K-means algorithm is improved with the minimum spanning tree method to spontaneously calculate the initial number of categories and the class center value from the data, avoiding the problem of random generation and enhancing the effect of clustering. The system is tested against other models in the dataset to examine its clustering performance. It is found that on the optimal K-mean-square error, the errors of the model in this paper are all less than 0.96, which is the lowest among the algorithms on all terms, and its clustering performance is again verified. The best results on the dataset are achieved by the proposed algorithm, with an HR@20 of 59.31%, which is almost twice the SVD recommendation method. The experiment confirmed the significance of each module in the recommender system. Compared with the recommendation of graduates’ jobs, the system is easier to recommend industries for graduates, and the HR indicator is greater than 80% at the recommendation list lengths of 3 and 5, while the HR@5 of SVD, BPR is below 50%. This study provides useful insights into the integration of cutting-edge information technology career guidance and data mining to aid in career planning.
A study on the role of hash function in encrypting sensitive information in network security protection
Authors: Wu Ju , Wang Dehong , Peng Xiaoxia 
Published: October 2024

Abstract
The fields of information encryption and privacy protection widely use hash functions, but the traditional hash functions still struggle to handle the increasingly complex encryption tasks of sensitive data. The study enhances the traditional hash function and develops a hash function (SHF) that is based on random and chaotic structures. The SHF random function and SHF chaotic mapping are constructed, respectively. The SHF chaotic hash encryption algorithm encrypts the database, and the choice of encryption method constructs the overall architecture for encrypting and decrypting sensitive information. Finally, we examine the performance of the SHF chaotic hash encryption algorithm from four aspects: security, information entropy, resistance to differential attacks, and encryption and decryption time. The field distribution of the ciphertext encrypted by the SHF chaotic hash algorithm for plaintext is between [-150, 150], and the distribution of the unencrypted plaintext is in the range of [-100, 100]. Compared to plaintext, the distribution of the ciphertext is more dispersed and uniform. The information entropy results of the SHF chaotic hash encryption algorithm consistently exceed 7.998, the NPCR values fall within the standard range of 99.6094%, and the UACI values essentially hover around the standard value of 33.4%, indicating its ability to effectively withstand attacks. The SHF chaotic hash encryption algorithm has an encryption time of 0.398S and a decryption time of 0.398S, making it ideal for use in wireless sensor networks.