bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Synergistic Enhancement of Anti-Metabolic Diseases Function of
Morus alba with the Combination of Cha (Camellia sinensis)
Authors: Sato Shinji , Konishi Tetsuya 
Published: May 2024

Background:
Functional foods play an important role in the prevention and ameliora-tion of metabolic syndromes leading to type 2 diabetes. Plant resources that have anti-metabolic syndromes activity, such as Morus alba L. and Cha [Camellia sinensis L.], have been used in functional foods against diabetes. Since Morus and Cha have different mechanisms of action against metabolic syndromes, such as prevention of sugar uptake and lipidosis, respectively, and the combination of both resources will be a reliable approach for developing more efficient functional food against type 2 diabetes because certain synergism is expected in their functions.

Methods:
Male Wister Rats were fed the high fat-high sucrose [HFHS] diet for 12 weeks, with and without supplementation of Morus and Cha alone and their combination, and the effect of their supplementation on the markers of the metabolic syndrome such as obesity, lipidosis, and fatty liver formation, were examined.

Results:
Several metabolic syndrome markers, including body weight gain, lipid deposit, and fatty liver formation, were more significantly prevented by the diet supplemented with Morus and Cha combination compared to Morus or Cha given separately .

Conclusion:
Appropriate formulation of food resources with different functional mechanisms is a promising strategy for developing effective dietary treatment of type 2 diabetes that is a typical Mibyou.
Adverse Events of COVID-19 Vaccines in the United States: Temporal and Spatial Analysis
Authors: Li Yiming , Li Jianfu , Dang Yifang , Chen Yong , Tao Cui 
Published: May 2024

Background
The COVID-19 pandemic, caused by SARS-CoV-2, has had a profound impact worldwide, leading to widespread morbidity and mortality. Vaccination against COVID-19 is a critical tool in controlling the spread of the virus and reducing the severity of the disease. However, the rapid development and deployment of COVID-19 vaccines have raised concerns about potential adverse events following immunization (AEFIs). Understanding the temporal and spatial patterns of these AEFIs is crucial for an effective public health response and vaccine safety monitoring.

Objective
This study aimed to analyze the temporal and spatial characteristics of AEFIs associated with COVID-19 vaccines in the United States reported to the Vaccine Adverse Event Reporting System (VAERS), thereby providing insights into the patterns and distributions of the AEFIs, the safety profile of COVID-19 vaccines, and potential risk factors associated with the AEFIs.

Methods
We conducted a retrospective analysis of administration data from the Centers for Disease Control and Prevention (n=663,822,575) and reports from the surveillance system VAERS (n=900,522) between 2020 and 2022. To gain a broader understanding of postvaccination AEFIs reported, we categorized them into system organ classes (SOCs) according to the Medical Dictionary for Regulatory Activities. Additionally, we performed temporal analysis to examine the trends of AEFIs in all VAERS reports, those related to Pfizer-BioNTech and Moderna, and the top 10 AEFI trends in serious reports. We also compared the similarity of symptoms across various regions within the United States.

Results
Our findings revealed that the most frequently reported symptoms following COVID-19 vaccination were headache (n=141,186, 15.68%), pyrexia (n=122,120, 13.56%), and fatigue (n=121,910, 13.54%). The most common symptom combination was chills and pyrexia (n=56,954, 6.32%). Initially, general disorders and administration site conditions (SOC 22) were the most prevalent class reported. Moderna exhibited a higher reporting rate of AEFIs compared to Pfizer-BioNTech. Over time, we observed a decreasing reporting rate of AEFIs associated with COVID-19 vaccines. In addition, the overall rates of AEFIs between the Pfizer-BioNTech and Moderna vaccines were comparable. In terms of spatial analysis, the middle and north regions of the United States displayed a higher reporting rate of AEFIs associated with COVID-19 vaccines, while the southeast and south-central regions showed notable similarity in symptoms reported.

Conclusions
This study provides valuable insights into the temporal and spatial patterns of AEFIs associated with COVID-19 vaccines in the United States. The findings underscore the critical need for increasing vaccination coverage, as well as ongoing surveillance and monitoring of AEFIs. Implementing targeted monitoring programs can facilitate the effective and efficient management of AEFIs, enhancing public confidence in future COVID-19 vaccine campaigns.
Dose-Response Relationship Between Physical Activity and the Morbidity and Mortality of Cardiovascular Disease Among Individuals With Diabetes: Meta-Analysis of Prospective Cohort Studies
Authors: Chen Yang , Jin Xingsheng , Chen Guochong , Wang Ru , Tian Haili 
Published: May 2024

Background
Diabetes, a chronic condition affecting various organs, is frequently associated with abnormal lipid metabolism, notably increased cholesterol and triglyceride levels. These lipid abnormalities are closely linked to the development and advancement of cardiovascular disease (CVD). Although regular physical activity (PA) has consistently shown benefits in reducing CVD risk in the general population, its precise influence on CVD risk among patients with diabetes remains uncertain, particularly regarding dose-response relationships.

Objective
This study aimed to summarize the evidence from prospective studies on the association between PA and CVD morbidity and mortality in individuals with diabetes and explore the optimal levels for public health recommendation.

Methods
We systematically reviewed prospective cohort studies in PubMed, Embase, and Web of Science up to December 2022, with inclusion criteria specifying the studies published in English and included adult participants diagnosed with diabetes. A random effects model was used to pool the relative risk (RR) with the corresponding 95% CI comparing the highest with the lowest PA categories in each study for qualitative evaluation. In addition, linear and spline regression analyses were used to estimate dose-response associations.

Results
The meta-analysis included 12 prospective cohort studies, involving a total of 109,820 participants with diabetes. The combined results revealed that higher levels of PA were associated with a reduced risk of CVD. The RR of CVD for the highest compared with the lowest PA category was 0.62 (95% CI 0.51-0.73). In addition, there were 4 studies describing leisure-time PA, and the pooled RR was 0.68 (95% CI 0.52-0.83) for the highest versus the lowest activity. The linear regression model revealed that each 10 MET (metabolic equivalent of task)-hours per week of incrementally higher PA was associated with a 19% (95% CI 11.6-25.7) and a 6.9% (95% CI 4.5-9.3) reduction in CVD morbidity and mortality. Additionally, spline regression curves showed nonlinear relationships between PA levels and the risk of CVD and CVD mortality (both Pnonlinearity<.001), with a limited reduction in CVD risk and some further reduction in CVD mortality above 20 MET-hours per week of PA levels.

Conclusions
For patients with diabetes, especially type 2 diabetes, there was a dose-response relationship between increased PA and reduced risk of CVD morbidity and mortality. The observed PA threshold is consistent with the recommended level for the general population. Gradually moving from inactivity to a guideline-recommended PA level could therefore significantly reduce the burden of CVD in patients with diabetes.
Cardiovascular Comorbidities in COVID-19: Comprehensive Analysis of Key Topics
Authors: Markovič Rene , Ternar Luka , Trstenjak Tim , Marhl Marko , Grubelnik Vladimir 
Published: May 2024

Background
The interrelation between COVID-19 and various cardiovascular and metabolic disorders has been a critical area of study. There is a growing need to understand how comorbidities such as cardiovascular diseases (CVDs) and metabolic disorders affect the risk and severity of COVID-19.

Objective
The objective of this study is to systematically analyze the association between COVID-19 and cardiovascular and metabolic disorders. The focus is on comorbidity, examining the roles of CVDs such as embolism, thrombosis, hypertension, and heart failure, as well as metabolic disorders such as disorders of glucose and iron metabolism.

Methods
Our study involved a systematic search in PubMed for literature published from 2000 to 2022. We established 2 databases: one for COVID-19–related articles and another for CVD-related articles, ensuring all were peer-reviewed. In terms of data analysis, statistical methods were applied to compare the frequency and relevance of MeSH (Medical Subject Headings) terms between the 2 databases. This involved analyzing the differences and ratios in the usage of these terms and employing statistical tests to determine their significance in relation to key CVDs within the COVID-19 research context.

Results
The study revealed that “Cardiovascular Diseases” and “Nutritional and Metabolic Diseases” were highly relevant as level 1 Medical Subject Headings descriptors in COVID-19 comorbidity research. Detailed analysis at level 2 and level 3 showed “Vascular Disease” and “Heart Disease” as prominent descriptors under CVDs. Significantly, “Glucose Metabolism Disorders” were frequently associated with COVID-19 comorbidities such as embolism, thrombosis, and heart failure. Furthermore, iron deficiency (ID) was notably different in its occurrence between COVID-19 and CVD articles, underlining its significance in the context of COVID-19 comorbidities. Statistical analysis underscored these differences, highlighting the importance of both glucose and iron metabolism disorders in COVID-19 research.

Conclusions
This work lays the foundation for future research that utilizes a knowledge-based approach to elucidate the intricate relationships between these conditions, aiming to develop more effective health care strategies and interventions in the face of ongoing pandemic challenges.
Training Service Users in the Use of Telehealth: Scoping Review
Authors: Galvin Emer , Desselle Shane , Gavin Blánaid , McNicholas Fiona , Cullinan Shane , Hayden John 
Published: May 2024

Background
The use of telehealth has rapidly increased, yet some populations may be disproportionally excluded from accessing and using this modality of care. Training service users in telehealth may increase accessibility for certain groups. The extent and nature of these training activities have not been explored.

Objective
The objective of this scoping review is to identify and describe activities for training service users in the use of telehealth.

Methods
Five databases (MEDLINE [via PubMed], Embase, CINAHL, PsycINFO, and Web of Science) were searched in June 2023. Studies that described activities to train service users in the use of synchronous telehealth consultations were eligible for inclusion. Studies that focused on health care professional education were excluded. Papers were limited to those published in the English language. The review followed the Joanna Briggs Institute guidelines for scoping reviews and was reported in line with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Titles and abstracts were screened by 1 reviewer (EG). Full texts were screened by 2 reviewers (EG and JH or SC). Data extraction was guided by the research question.

Results
The search identified 8087 unique publications. In total, 13 studies met the inclusion criteria. Telehealth training was commonly described as once-off preparatory phone calls to service users before a telehealth visit, facilitated primarily by student volunteers, and accompanied by written instructions. The training content included guidance on how to download and install software, troubleshoot technical issues, and adjust device settings. Older adults were the most common target population for the training. All but 1 of the studies were conducted during the COVID-19 pandemic. Overall, training was feasible and well-received by service users, and studies mostly reported increased rates of video visits following training. There was limited and mixed evidence that training improved participants’ competency with telehealth.

Conclusions
The review mapped the literature on training activities for service users in telehealth. The common features of telehealth training for service users included once-off preparatory phone calls on the technical elements of telehealth, targeted at older adults. Key issues for consideration include the need for co-designed training and improving the broader digital skills of service users. There is a need for further studies to evaluate the outcomes of telehealth training activities in geographically diverse areas.
Influence of TikTok on Body Satisfaction Among Generation Z in Indonesia: Mixed Methods Approach
Authors: Ariana Hanifa , Almuhtadi Ikmal , Natania Nikita Jacey , Handayani Putu Wuri , Bressan Stéphane , Larasati Pramitha Dwi 
Published: May 2024

Background
As social media platforms gain popularity, their usage is increasingly associated with cyberbullying and body shaming, causing devastating effects.

Objective
This study aims to investigate the impact of social media on Generation Z users’ body image satisfaction. More specifically, it examines the impact of TikTok on body image satisfaction among TikTok users aged between 17 years and 26 years in Indonesia.

Methods
The methodology used mixed-method approaches. Quantitative data were obtained from 507 responses to a questionnaire and analyzed using covariance-based structural equation modeling. Qualitative data were obtained from the interviews of 32 respondents and analyzed through content analysis.

Results
This study reveals that upward appearance comparison is influenced by video-based activity and appearance motivation. Conversely, thin-ideal internalization is influenced by appearance motivation and social media literacy. Upward appearance comparisons and thin-ideal internalization comparisons detrimentally impact users’ body image satisfaction.

Conclusions
The results of this study are expected to provide valuable insights for social media providers, regulators, and educators in their endeavors to establish a positive and healthy social media environment for users.
Impact of vereda dryness on the insect herbivore diversity in adjacent cerrado areas in Brazilian Protected Areas
Authors:   Universidade Estadual de Montes Claros, de Araújo Walter S. , Silveira Luana T. ,   Universidade Estadual de Montes Claros, Falcão Luiz A. D. ,   Universidade Estadual de Montes Claros, Vieira Thallyta M. ,   Universidade Estadual de Montes Claros, Martins Waldney P. ,   Universidade Estadual de Montes Claros, Nunes Yule R. F. ,   Universidade Estadual de Montes Claros, Grandez-Rios Julio M. ,   Universidade Federal do Rio de Janeiro,   Instituto de Investigaciones de la Amazonía Peruana
Published: May 2024

Unravelling the factors that influence plant-insect interactions remains a fundamental concern in terrestrial ecology. In the present study, we evaluated the impact of varying degrees of drying on cerrado areas adjacent to veredas on the species richness, abundance and composition of the insect herbivore fauna. Additionally, we examined differences in these impacts between various guilds (chewing and sucker insects) and developmental stages (adult and immature insects). The research has been performed in study areas located in three Protected Areas in Brazil. In total, we recorded 106 species of herbivorous insects across five orders (Coleoptera, Hemiptera, Hymenoptera, Lepidoptera, and Orthoptera). Hemiptera and Coleoptera stood out as the orders with the highest species diversity and individual numbers. Among the families, Cicadellidae and Curculionidae exhibited the highest richness in species and abundance of individuals. We found that richness of herbivorous insects was higher in wet zones (20.2 ± 6.5) of the veredas compared to dry zones (12.3 ± 7.5), as well as the abundance of herbivorous insects was higher in wet zones (49.4 ± 25.5) than in the dry zones (15.8 ± 7.9). Whithin insect guilds, the abundance of chewing insects was higher in wet zones (34.0 ± 13.6) than in dry zones (16.3 ± 14.8), but this difference was not observed for the diversity of sucking insects. Regarding developmental stage, immature insects exhibited higher species richness in wet zones (10.4 ± 5.0) compared to dry zones (5.3 ± 2.1), while adult insect diversity did not show differences between the studied zones. Furthermore, the species composition of herbivorous insects, various trophic guilds (chewers and suckers) and developmental stages (adults and immature insect) did not significantly differ among the zones studied within the veredas. According to our findings, herbivorous insects exhibit a preference for wet environments, which provide better conditions and higher-quality food resources for development and reproduction.
Research on the Construction and Application of Dynamic Early Warning Mechanism of Student Civics in Colleges and Universities
Authors: Liu Jia 
Published: May 2024

Abstract
Aiming at the problems of lagging information feedback, imperfect early warning and intervention mechanisms, and weak risk control ability that exist in the current work of ideological education in colleges and universities, this paper establishes a combination of a simple Bayesian algorithm of ideological dynamic early warning mechanism. This study takes school A as an example, collects a large volume of log data features based on user behavior, and after preprocessing, fuses the decision tree algorithm and the plain Bayesian algorithm and integrates them into the early warning classifier to establish a dynamic early warning model for civic education, and carries out experimental simulation and practical application to test its performance and early warning results. The results show that the prediction error indexes of this paper’s algorithm are no more than 0.1, and the abnormal rate of Civics behavior in each dimension is basically within 10%, which shows high adaptability. This study is beneficial for universities to carry out student civic education work and help civic workers better guide students and serve them.
Research on Network Security Technology of Internet of Things Intelligent Information Terminal under the Background of Information Technology
Authors: Liu Lijun , Qian Jin , Zhou Aiping , Zhang Bin 
Published: May 2024

Abstract
This paper explores the application of network security technology within intelligent information terminals of the Internet of Things (IoT). It examines existing security issues and proposes a technical framework to address them. The technical framework starts from two aspects of data encryption and intrusion detection technology, in the data encryption technology, the CCA-ANC encryption algorithm is proposed to change the attacker in ANC from pure ciphertext attack to using the method of selective ciphertext attack. In intrusion detection technology, the DAGMM algorithm has been improved and optimized. The WEFS-DAGMM improved intrusion detection algorithm has been proposed, and an intrusion detection firewall has been constructed. In the performance test, the CCA-ANC encryption algorithm completes the encryption after inputting 1024MB of data in 13.6s, and the average speed of encryption reaches 71.54MB/s. The optimized WEFS-DAGMM algorithm achieves an accuracy of 0.952, which is 0.03 higher than the original DAGMM algorithm. The recall and F1 values are 0.03 higher than the original DAGMM algorithm, respectively. The algorithms have been improved by 0.03 and 0.037, respectively. Simulation experiments are conducted on the technical framework constructed in this paper. The success rate of malicious attack detection is greater than 90%, and the security protection rate reaches more than 99% in all of them.
Convergence of Artificial Intelligence Algorithms and Education Fuels Educational Reform in Higher Education Programs
Authors: Nie Jingjing 
Published: May 2024

Abstract
In the realm of higher education management, data mining has emerged as a potent tool for elevating the quality of instruction and administrative operations. This study presents the development of a curriculum validation analysis model utilizing association rule clustering. We collected and processed data from design students at a university, addressing missing values and eliminating outliers. Through data mining, we explored the relationships between students’ coursework, skill acquisition, and the demands of potential employers in society. This analysis underpinned a series of reforms in higher education curricula. To assess the impact of these curricular changes, two instructors conducted both process and outcome evaluations of the revised programs. The evaluations revealed that five student groups achieved scores above 80, one group scored between 70 and 80, and three groups scored between 60 and 70. All student groups scored above 60, demonstrating their competence in fundamental job-related tasks and validating their readiness for professional employment. This research offers valuable insights for the revision of professional training programs and curriculum reform in higher education.
Research on Multi-objective Optimization Model of Physical Education Teaching Enhancement Path in Colleges and Universities
Authors: Shen Delei , Dai Fengjian 
Published: May 2024

Abstract
This study begins by assessing the current state of physical education (PE) teaching in higher education institutions. It establishes an optimization index system for PE teaching, utilizing the entropy weighting method to calculate the weights of the indices. These weights are then incorporated into the objective function to define the constraints for optimizing PE teaching, facilitating the construction of a multi-objective optimization model tailored to enhance PE instruction pathways. The model is solved using the NSGA-II optimization algorithm, and an illustrative analysis is conducted. The results indicate a smooth distribution of the superiority and inferiority degrees within the derived PE teaching optimization scheme, characterized by low overall dispersion (mean superiority and inferiority value of 74.2841) and minimal deviation compared to the current status (mean value of 0.09835). This confirms the effectiveness of the proposed model in improving PE teaching. The implications of this study are significant for elevating the standard and quality of PE teaching in colleges and universities, nurturing more professionals for China’s sports industry, and advancing the nation’s sports sector to unprecedented levels.
Simulation study of inventory cost control based on system dynamics
Authors: Wang Yanhong , Zhao Jun 
Published: May 2024

Abstract
In this study, we employ system dynamics to analyze the interplay between various factors influencing inventory cost control, resulting in a comprehensive subsystem model. The inventory strategy subsystem, based on the pipeline delay function, and the inventory cost subsystems, considering the actual situation of the enterprise, are combined to construct the inventory cost control system dynamics model. According to the validity test of the inventory cost control model, there are less than 10% simulation errors in the total transportation cost and total inventory cost data of the enterprise, and the model’s reliability is high. The simulation experiment of the model on the inventory cost control of the enterprise shows that the total inventory cost decreases to 4,398,330 yuan on the 100th day after shortening the order delay time, and the total inventory cost decreases by 1,160,450 yuan on 32 days after controlling the arrival delay time. This dynamic model proves highly effective and offers a dependable approach to managing inventory costs across various enterprises.