Search Results (163)

Racket sports are very popular not only in professional sports but also among recreational players. As a result, their impact on the field of education has grown significantly in recent years. Table tennis (TT) offers significant advantages in terms of skill acquisition and health improvement. Nevertheless, its application within physical education (PE) curricula remains undetermined. The aim of this systematic review was to analyze the use of TT as educational content in the subject of PE in primary school. The PRISMA 2020 methodology was used to conduct the systematic review. Six databases (ERIC, Pubmed, ScienceDirect, Scopus, Sport Discus, and Web of Science) were used during the search process. The search cutoff date was December 31, 2024. After applying the eligibility criteria, 3595 articles were found. Only seven studies were selected for the final analysis and the data included 1526 students from primary school. The results indicate that TT is rarely used in primary education during PE classes. Research indicates interest among teachers and students in playing it during PE. Furthermore, due to the benefits, motivation, and interest this sport generates, educational experiences have been developed, such as roundtable discussions, table top tennis, balloon TT, and TT triathlon. A lack of materials, facilities, and teacher training for teaching this sport is notable. The teaching experiences analyzed in this review confirm that TT is a highly versatile and interesting sport as a subject matter in school PE. The use of TT allows for innovative, comprehensive, and inclusive PE, thanks to the sport’s multiple possibilities. Given its adaptability and low entry barrier, TT could serve as an effective tool for increasing children’s physical activity levels, improving motor skills, and fostering social–emotional development. However further research is needed to quantify its impact on health outcomes such as cardiovascular fitness or obesity prevention. Full article

The concept of the 15-minutes city [15 MC] focuses on providing important services within proximity and accessibility through active travel like walking or biking. While this model is becoming popular in urban planning and academic discourse, its implementation faces challenges in both densely populated developing and developed countries. This study aims to conduct a systematic review of recent literature to (1) identify the core components of the 15 MC model, (2) examine planning tools and strategies used in its implementation, (3) compare successes and challenges across global contexts, particularly in densely populated and resource-constrained areas, and (4) offer practical recommendations for adapting the model to meet local needs. The study reviewed 33 research papers published in the last five years [2019–2024]. Following PRISMA guidelines, a structured screening and selection process was conducted using databases such as Scopus, Web of Science, and Google Scholar. Thematic analysis revealed major challenges for implementing the 15 MC in the Global South, including urban informality, gaps in infrastructure, and complex governance issues. Moreover, the review points out the potential risks of exclusion and gentrification if the specific needs of different contexts are not considered. While high-income countries tend to focus on sustainability and making neighborhoods walkable, developing countries struggle with deeper structural problems that make equitable implementation harder. This study emphasizes the need for locally adaptive frameworks in planning 15 MCs and aims to develop inclusive urban policies that support Sustainable Development Goal 11, which seeks to make cities inclusive, safe, resilient, and sustainable. Full article

Due to the rise in emerging strategic industries and the widespread application of new and improved technology, the global demand for strategic mineral resources has rapidly increased. Among these, fluorite is one of the most crucial strategic mineral resources in the world. However, so far, there are few comprehensive reviews of the progress in technology supporting the utilization of fluorite resources. In this work, the Bibliometrix package (version 4.5.0), VOSviewer (version 1.6.20), CiteSpace (version 6.4.R1), and the Web of Science Core Collection database were employed, and 2472 publications related to fluorite resource utilization technology (published from 1999 to 2024) were studied via a detailed analysis of the following four aspects: 1. the characteristics of the publications; 2. journal distribution, co-cited journals, and co-cited references; 3. active countries, institutions, and authors; and 4. popular research topics, including theme evolution, keyword co-occurance, and keyword burst analysis. In this work, an outline of the research and progress in fluorite resource utilization technology over the past 25 years is presented, which supports systematic evaluations of the trends in science and technology in related fields and contributes to the development of technology enabling the utilization of fluorite resources. Full article

The linguistic summarization of data is one of the study trends in data mining because it has many useful practical applications. A linguistic summarization of data aims to extract an optimal set of linguistic summaries from numeric data. The blended learning format is now popular in higher education at both undergraduate and graduate levels. A lot of techniques in machine learning, such as classification, regression, clustering, and forecasting, have been applied to evaluate learning activities or predict the learning outcomes of students. However, few studies have been examined to transform the data of blended learning courses into the knowledge represented as linguistic summaries. This paper proposes a method of linguistic summarization of blended learning data collected from a learning management system to extract compact sets of interpretable linguistic summaries for understanding the common rules of blended learning courses by utilizing enlarged hedge algebras. Those extracted linguistic summaries in the form of sentences in natural language are easy to understand for humans. Furthermore, a method of detecting the exceptional cases or outliers of the learning courses based on linguistic summaries expressing common rules in different scenarios is also proposed. The experimental results on two real-world datasets of two learning courses of Discrete Mathematics and Introduction to Computer Science show that the proposed methods have promising practical applications. They can help students and lecturers find the best way to enhance their learning methods and teaching style. Full article

The paper explores the pressing issue of energy consumption in machine learning (ML) models and their environmental footprint. As ML technologies, especially large-scale models, continue to surge in popularity, their escalating energy demands and corresponding CO₂ emissions are drawing critical attention. The article dives into innovative strategies to curb energy use in ML applications without compromising—and often even enhancing—model performance. Key techniques, such as model compression, pruning, quantization, and cutting-edge hardware design, take center stage in the discussion. Beyond operational energy use, the paper spotlights a pivotal yet often overlooked factor: the substantial emissions tied to the production of ML hardware. In many cases, these emissions eclipse those from operational activities, underscoring the immense potential of optimizing manufacturing processes to drive meaningful environmental impact. The narrative reinforces the urgency of relentless advancements in energy efficiency across the IT sector, with machine learning and data science leading the charge. Furthermore, deploying ML to streamline energy use in other domains like industry and transportation amplifies these benefits, creating a ripple effect of positive environmental outcomes. The paper culminates in a compelling call to action: adopt a dual-pronged strategy that tackles both operational energy efficiency and the carbon intensity of hardware production. By embracing this holistic approach, the artificial intelligence (AI) sector can play a transformative role in global sustainability efforts, slashing its carbon footprint and driving momentum toward a greener future. Full article

Zinc oxide nanoparticles (ZnO NPs) have garnered significant attention across various scientific and technological domains due to their unique physicochemical properties, including high surface area, photostability, biocompatibility, and potent antimicrobial activity. These attributes make ZnO NPs highly versatile, enabling their application in biomedicine, environmental science, industry, and agriculture. They serve as effective antimicrobial agents in medical treatments and as catalysts in environmental purification processes, owing to their ability to generate reactive oxygen species (ROS) and exhibit photocatalytic activity under UV light. Moreover, ZnO NPs are being increasingly employed in advanced drug delivery systems and cancer therapies, highlighting their potential in modern medicine. Their growing popularity is further supported by their ease of synthesis, cost-effectiveness, and capacity for diverse functionalization, which expand their utility across multiple sectors. This review focuses on research from the past five years (2020–2025) on the practical uses of ZnO nanoparticles in the biomedical, environmental, industrial, and agricultural fields. It also highlights current trends, existing challenges, and future perspectives. By examining these aspects, the article provides a comprehensive understanding of the versatile roles of ZnO NPs and their emerging significance in science and technology. Full article

Social media (SM) platforms allow users to communicate rapidly, exchange information, and create and share real-time content. Currently, 4.5 billion people use social media worldwide, making it an influential part of daily life. Beyond information sharing, social media facilitates communication, transfers information, and serves as a platform for advertising and shaping public opinion. Researchers analyse these aspects to understand and describe societal realities. The primary purpose of this paper is to analyse social media’s impact on global research. The research included an analysis of the most popular social platforms, considering the number of Web of Science (WoS) articles relating to them and the year in which the platform was established or the Monthly Active Users (MAU) factor. Data were collected based on the WoS database in the topic (which contains texts of title, abstract, author keywords, and Keywords Plus) of the articles, where phrases containing names of SM platforms were used. Quantitative research is a type of research that analyses data numerically to find relationships and statistical regularities of searched phrases. The impact of social media on the dissemination of research and findings was analysed based on the results of the study and also on the literature data. This research reveals a lack of correlation between the number of articles indexed in the WoS and the MAU of individual social media platforms. This observation raises an important question: do social media researchers focus on studying the platforms used by the majority, thereby providing a more accurate representation of current social dynamics? This article is helpful for researchers, policymakers, and social media platform developers seeking to understand the role of social media in shaping modern communication and public discourse. The most important finding of the paper is the low correlation between the number of SM users and the impact of social media platforms on learning, as exemplified by the Twitter (Note: Twitter was an American social networking service rebranded as X in 2023. As the period of data analysed in this paper covered the years up to 2022, the authors decided to stay with the name Twitter) platform, which is the 17th largest SM platform but is the 2nd (after Facebook) in implications for science. Full article

As machine learning becomes more integrated into atmospheric science, XGBoost has gained popularity for its ability to assess the relative contributions of influencing factors in the atmospheric boundary layer height. To examine how these factors vary across seasons, a seasonal analysis is necessary. However, dividing data by season reduces the sample size, which can affect result reliability and complicate factor comparisons. To address these challenges, this study replaces default parameters with grid search optimization and incorporates cross-validation to mitigate dataset limitations. Using XGBoost with four years of data from the atmospheric radiation measurement (ARM) (Southern Great Plains (SGP) C1 site, cross-validation stabilizes correlation coefficient fluctuations from 0.3 to within 0.1. With optimized parameters, the R value can reach 0.81. Analysis of the C1 site reveals that the relative importance of different factors changes across seasons. Lower tropospheric stability (LTS, ~0.53) is the dominant factor at C1 throughout the year. However, during DJF, latent heat flux (LHF, 0.44) surpasses LTS (0.22). In SON, LTS (0.58) becomes more influential than LHF (0.18). Further comparisons among the four long-term SGP sites (C1, E32, E37, and E39) show seasonal variations in relative importance. Notably, during JJA, the differences in the relative importance of the three factors across all sites are lower than in other seasons. This suggests that boundary layer development in the summer is not dominated by a single factor, reflecting a more intricate process likely influenced by seasonal conditions such as enhanced convective activity, higher temperatures, and humidity, which collectively contribute to a balanced distribution of parameter impacts. Furthermore, the relative importance of LTS gradually increases from morning to noon, indicating that LTS becomes more significant as the boundary layer approaches its maximum height. Consequently, the LTS in the early morning in autumn exhibits greater relative importance compared to other seasons. This reflects a faster development of the mixing layer height (MLH) in autumn, suggesting that it is easier to retrieve the MLH from the previous day during this period. The findings enhance understanding of boundary layer evolution and contribute to improved boundary layer parameterization. Full article

Background/Objectives: The species Mikania glomerata and Mikania laevigata are commonly referred to as guaco. Their preparations are used in traditional Brazilian medicine, mainly to address respiratory conditions affecting the upper airways. Considering the wide popular use of this species, the present study aims to survey the biological activities of guaco that have already been proven in the literature and to generate an evidence gap map for these biological activities. Methods: A scoping review was conducted using the electronic databases PubMed, Scopus, and Web of Science (7 October 2024), which included all studies that have evaluated the biological activities of the leaves of the M. glomerata or M. laevigata species. Results: A total of 57 studies (31 assessed only M. glomerata, 17 assessed only M. laevigata, and 9 assessed both species) evaluating 38 different biological activities demonstrated that preclinical studies reported 23 biological activities for M. glomerata and 24 for M. laevigata. The most extensively researched activity for both species is their anti-inflammatory properties, which have been associated with their efficacy in treating bronchoconstriction and their popular uses as an antiophidic agent. The gap map illustrates the lack of evidence to support the biological activity of these species, which may explain some of their popular uses, such as their use as expectorants, antipyretics, for arthritis, rheumatism, neuralgia, and as an antisyphilitic. Conclusions: Considering these findings, there is a clear need for further studies to evaluate the activity of these species for these purposes, mainly through clinical studies. Full article

Background: Physical activity, including its organized form, is of key importance in the motor development of children and adolescents. Among the increasingly popular physical activities in this age group are martial arts, particularly judo. In addition to its educational and social values, this discipline, in its assumptions, gives practitioners the opportunity for motor development. This study aims to assess the development of motor competence in children and adolescents up to 15 years of age practicing judo. Methods: The study was conducted using seven databases (Scopus, Web of Science, PubMed, Embase, OVID, CINHAL Ultimate and SPOLIT) across 15 years (from January 2009 to May 2024). The PRISMA methodology was used to include studies, and the CASP protocol was applied to assess the quality of these studies. Inclusion criteria were developed based on PICOS. Finally, 22 studies that met the established criteria were included. Results: Most of the studies (21) were observational, and only one was a randomized controlled trial. The review indicated that regular judo training significantly improved muscle strength, endurance, speed, coordination, flexibility, balance and body posture compared to control groups. In contrast to some other sports, judo demonstrated comparable benefits in the development of motor abilities. Conclusions: Judo is a sport discipline that significantly affects the motor development of children and adolescents. Furthermore, regular participation in training helps to achieve the daily dose of moderate-to-vigorous activity recommended by the World Health Organization in this age group. Full article

One area of study within machine learning and artificial intelligence (AI) seeks to create computer programs with intelligence that can mimic human focal processes in order to produce results. This technique includes data collection, effective data usage system development, conclusion illustration, and arrangements. Analysis algorithms that are learning to mimic human cognitive activities are the most widespread application of AI. Artificial intelligence (AI) studies have proliferated, and the field is quickly beginning to understand its potential impact on medical services and investigation. This review delves deeper into the pros and cons of AI across the healthcare and pharmaceutical research industries. Research and review articles published throughout the last few years were selected from PubMed, Google Scholar, and Science Direct, using search terms like ‘artificial intelligence’, ‘drug discovery’, ‘pharmacy research’, ‘clinical trial’, etc. This article provides a comprehensive overview of how artificial intelligence (AI) is being used to diagnose diseases, treat patients digitally, find new drugs, and predict when outbreaks or pandemics may occur. In artificial intelligence, neural networks and deep learning are some of the most popular tools; in clinical research, Bayesian non-parametric approaches hold promise for better results, while smartphones and the processing of natural languages are employed in recognizing patients and trial monitoring. Seasonal flu, Ebola, Zika, COVID-19, tuberculosis, and outbreak predictions were made using deep computation and artificial intelligence. The academic world is hopeful that AI development will lead to more efficient and less expensive medical and pharmaceutical investigations and better public services. Full article

Background/Objectives: Smartphones, with their widespread popularity and diverse apps, have become essential in our daily lives, and ongoing advancements in information technology have unlocked their significant potential in healthcare. Our goal is to identify the future research directions of mobile health (mHealth) by examining its research trends and emerging hotspots. Methods: This study collected mHealth-related literature published between 2005 and 2024 from the Web of Science database. We conducted a descriptive statistic of the annual publication count and categorized the data by authors and institutions. In addition, we developed visualization maps to display the frequency of keyword co-occurrences. Furthermore, overlay visualizations were created to showcase the average publication year of specific keywords, helping to track the changing trends in mHealth research over time. Results: Between 2005 and 2024, a total of 6093 research papers related to mHealth were published. The data have revealed a rapid increase in the number of publications since 2011. However, it was found that research on mHealth has reached a saturation point since 2021. The University of California was the dominant force in mHealth research, with 248 articles. The University of California, the University of London, Harvard University, and Duke University are actively collaborating, which shows a geographical pattern of collaboration. From the analysis of keyword co-occurrence and timeline, the research focus has gradually shifted from solely mHealth technologies to exploring how new technologies, such as artificial intelligence (AI) in mobile apps, can actively intervene in patient conditions, including breast cancer, diabetes, and other chronic diseases. Privacy protection policies and transparency mechanisms have emerged as an active research focus in current mHealth development. Notably, cutting-edge technologies such as the Internet of Things (IoT), blockchain, and virtual reality (VR) are being increasingly integrated into mHealth systems. These technological convergences are likely to constitute key research priorities in the field, particularly in addressing security vulnerabilities while enhancing service scalability. Conclusions: Although the volume of core research in mobile health (mHealth) is gradually declining, its practical applications continue to expand across diverse domains, increasingly integrating with multiple emerging technologies. It is believed that mobile health still holds enormous potential. Full article

Introduction: Dietary supplements have become a popular aid for improving training performance. Pre-workout supplements contain a mixture of ingredients used to boost physical performance, with some components having been associated with the promotion of cardiovascular health. However, there is insufficient scientific literature on the effects of pre-workout supplements, and the studies often have conflicting results. Objective: The aim of this review was to analyze the impact of multi-ingredient pre-workout supplements on cardiovascular health, in order to identify the main adverse effects and the roles of the most common substances in these supplements. Methodology: A systematic search was carried out in the Web of Science and PubMed databases by three independent researchers between January 2010 and August 2024. The inclusion criteria were available articles published in English. Articles that did not evaluate cardiovascular outcomes and the use of pre-workout supplements were excluded. Results: The 24 studies analyzed demonstrated an overall increase in supplement intake. Pre-workout supplements were associated with improved physical performance and possible cardiovascular changes, with these effects being classified as adverse or cardioprotective. This discrepancy in the results may be due to the different dosages and populations investigated (including active and non-active participants, and healthy participants or those with a history of cardiovascular diseases), as well as other factors that correlate with deleterious cardiac conditions. Conclusions: Multi-ingredient pre-workout supplements may offer physical and cardiovascular benefits, including increased energy, focus, endurance, and strength during exercise, as well as having potential positive impacts on blood pressure and triglyceride, low-density lipoprotein (LDL), and homocysteine levels. However, due to the conflicting results of the analyzed studies, additional studies are necessary to fill in the knowledge gaps and establish clearer guidelines for the safe and effective use of these supplements. Full article

Edible flowers are becoming a popular addition to diets. As science has progressed, it has been proven that in addition to their aesthetic value, they possess pharmacological effects and health-promoting properties. Several edible flowers are used in medicine, and the available literature data indicate their broad biological activity. This review focuses on pharmacological knowledge about the neuroactive, antioxidant, and anti-inflammatory potential of 15 traditionally used edible flowers. It also describes their traditionally uses and summarizes research findings on their chemical composition. Full article

Background/Objectives: The increasing popularity of acute supplementation among young athletes is concerning, given the limited scientific evidence to guide recommendations specific to this group. Therefore, the aim of this systematic review was to synthesize the available scientific evidence on the acute effects of supplementation in young athletes to understand the impact on physical and cognitive performance. Methods: Following pre-registration on INPLASY (INPLASY202310017) and according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, systematic searches of three electronic databases (Web of Science, PubMed, and Scopus) were conducted by independent researchers from inception until July 2024. Only original studies in English that examined the acute effects of supplementation on young athletes’ physical and/or cognitive performance, specifically when taken on the same day as exercise (before or during), were included. The risk of bias was individually assessed for each study using the revised Cochrane risk of bias tool for randomized trials (RoB 2.0). Results: A total of 16 studies were included in the review. A range of ages, participants, sports, and methodological approaches were involved in the studies included in the current review. The studies mainly used carbohydrates, beetroot juice, and sodium citrate, with carbohydrates being the most used acute supplementation. Carbohydrate supplementation enhanced endurance capacity and increased blood glucose, but mixed results were found for anaerobic performance. Mixed results were found for beetroot juice, with one study finding increases in power production. One study used sodium citrate supplementation, with improvements in technical performance observed. Conclusions: Since this review identified only three substances meeting our eligibility criteria, further research is needed to confirm the acute effects of supplements in young athletes and to better understand their benefits and limitations. Carbohydrate supplementation shows strong evidence for enhancing endurance performance, particularly during prolonged activities, while sodium citrate appears to support the preservation of skill performance. In contrast, the effects of beetroot juice are less consistent. Additional research is required to confirm the acute effects of supplements like beetroot juice in young athletes. Full article