Search Results (30)

Advances in technology and changes in the way people entertain themselves have made video games a cultural agent on a par with more traditional games, including language learning. In addition, the use of video games in education is becoming increasingly common and numerous benefits associated with their use have been discovered. The aim of this article is to analyze the search trends in studies dealing with the use of video games in language learning. To this end, a bibliometric analysis was carried out by applying the traditional laws of bibliometrics (Price’s law, Bradford’s law of concentration, Lotka’s law, Zipf’s law and h-index) to documents published in journals indexed in the Core Collection of the Web of Science (WoS). Annual publications between 2009 and 2022 show an exponential growth R2 = 86%. The journals with the most publications are Computer assisted language learning (Taylor & Francis) and Computers and Education (Elsevier). Jie Chi-Yang and Gwo Jen-Hwan were the most cited authors. The United States and Taiwan were the countries with the highest scientific output. The use of video games in language learning has been of particular interest in recent years, with benefits found for students who use them in their classes, although more research is needed to establish criteria and requirements for each video game for its intended purpose. Full article

Isometric training is a method focused on muscle strengthening without joint movement and has gained attention in recent years due to its applicability in rehabilitation and sports medicine. However, no comprehensive bibliometric analysis focused exclusively on adult populations has been performed. This study aimed to analyze the scientific production related to isometric training in adults; identify prominent authors, journals, and thematic trends; and evaluate the evolution of interest in this field over time. A bibliometric review was performed using the Web of Science Core Collection (SCI-E, SSCI, and ESCI). A specific search strategy was applied to identify articles and reviews focused on isometric training in adult populations. A total of 238 records met the inclusion criteria. Data were analyzed using Excel 2016 and VOSviewer software1.6.20. Bibliometric indicators such as Price’s Law, Bradford’s Law, Lotka’s Law, h-index, and co-occurrence and co-authorship network analysis were applied. The results showed a steady increase in publications in the last decade, highlighting the categories of Sports Science, Physiology, and Cardiovascular. The Journal of Applied Physiology was the most frequent source, and Springer Nature was the most prolific publisher. The h-index identified 21 highly cited papers, and Lotka’s Law confirmed the existence of a small group of prolific authors. VOSviewer analysis revealed clear thematic clusters, mainly around blood pressure regulation, rehabilitation, and aging. International collaboration was evident, with the United States, Canada, and the United Kingdom leading the co-authorship networks. Scientific interest in isometric training for adult populations is growing, particularly in relation to cardiovascular health and rehabilitation. Despite this, gaps remain in terms of methodological consistency and standardized protocols. Addressing these issues could improve the applicability and scientific impact of this training modality. Full article

Background/Objectives: Physical activity allows the enjoyment of personal health benefits in those who practice it, including the possibility of modifying behavioral risk factors such as tobacco and alcohol consumption. These risk factors are responsible for the development of non-communicable diseases, which are preventable and controllable. The scientific field on this object of study has grown in recent years. The main objective of this study was to perform a scientific mapping to explore the trend of annual publications, and to analyze and identify the thematic categories, the authors, countries and journals with the highest number of papers, the most referenced papers and authors, and the most used keywords in research related to physical activity and tobacco and/or alcohol consumption. Methods: Through a bibliometric analysis based on traditional bibliometric laws on the scientific documentation related to the subject and indexed in the Main Collection of the Web of Science. The DeSolla Price Law was used to analyze the trend of annual publications, using the coefficient of determination R². Lotka’s law was applied to identify prolific authors, Bradford’s law to highlight the most frequent publication sources, the h-index to identify the most cited articles and Zipf’s law to highlight the keywords most used in research. Results: A total of 538 documents were analyzed. The trend followed by annual publications is in an exponential growth phase. Adrian Taylor and Michael Ussher were identified as prolific authors. USA and Preventive Medicine were the country and journal with the highest number of publications. The most frequently used words were physical activity, smoking, exercise, alcohol, obesity, and smoking cessation. Conclusions: This bibliometric review identified an exponential growth from 1994 to date of research related to physical activity and tobacco and/or alcohol consumption. It allowed us to identify trends and guide the development of future research in these or new related areas. Full article

Introduction: Cancer treatments frequently lead to cognitive impairments, affecting a substantial global population. Among various approaches, exercise has emerged as a promising strategy for rehabilitation. However, a comprehensive bibliometric analysis of research in this field is lacking. Methods: We conducted a bibliometric analysis of 10,345 articles sourced from the Web of Science database using the R package “bibliometrix”. Our analysis examined publication trends, leading countries, journals, authors, institutions, keywords, and prevalent themes. Results: Over the past two decades, research on exercise interventions for cancer-related cognitive impairments (CRCI) has advanced significantly. Nonetheless, challenges persist in elucidating underlying mechanisms, developing innovative strategies, and creating effective tools. Conclusions: The number of publications notably increased from 1998 to 2023, although there has been a recent decline in citations. The United States (US) leads in both publications and citations, while China is showing increasing influence. Using Lotka’s Law in our bibliometric analysis, we identified 58 key authors in the field of exercise interventions for CRCI. Leading institutions such as the University of Toronto and Duke University are at the forefront of this research. Although the Journal of Clinical Oncology has fewer publications, it remains influential. Current research focuses on exercise interventions to enhance the quality of life for cancer patients, with particular emphasis on cognitive rehabilitation in breast cancer and the challenges faced by survivors. Future research should delve deeper into intervention mechanisms, behavioral strategies, telemedicine, and precise cognitive assessment tools. Full article

The proportion of aged populations is increasing worldwide. Exercise has a palliating effect on some adverse implications of aging. Multicomponent training (MCT) is a recommended form of exercise for the aged population. The aims of this research were to (1) study the number of publications regarding MCT in the aged population following an exponential growth rate; (2) identify the journals, authors, and countries that stand out the most in this area; and (3) describe the most common themes and used keywords in this field. The analysis was performed through the traditional laws of bibliometrics, including, Price’s, Lotka’s, Bradford’s, and Zipf’s law. All documents published in journals indexed in the Web of Science (WoS) Core Collection from 2001 to November 2023 that met the inclusion criteria were included. The 485 documents included in this review revealed that the number of annual publications experienced an exponential growth phase, 15 journals with six or more publications formed the core journals on this topic, and the author Mikel Izquierdo and his collaborative network topped the lists of prominent and prolific co-authors. Spain was the leading country in number of publications. Various thematic lines and keywords regarding strength, sarcopenia, quality of life, falls, balance, dual-task exercise, and cognitive and physical functioning were identified. In conclusion, this work confirmed that research on this topic is going through an exponential growth phase and provided detailed information about the journals, authors, and countries involved in the subject, as well as the keywords most frequently used in the subject matter. Full article

In this work we suggest that the common cause for the development of various power laws is the existence of a suitable exchangeable quantity between the agents of a set. Examples of such exchangeable quantities, leading to eponymous power laws, include money (Pareto’s Law), scientific knowledge (Lotka’s Law), people (Auerbach’s Law), and written or verbal information (Zipf’s Law), as well as less common cases like bullets during deadly conflicts, recognition in social networks, heat between the atmosphere and sea-ice floes, and, finally, mass of water vapors between pores in solids. This last case is examined closely in the present article based on extensive experimental data. It is shown that the transferred mass between pores, which eventually grow towards a power law distribution, may be expressed using different parameters, either transferred surface area, or transferred volume, or transferred pore length or transferred pore anisotropy. These distinctions lead to different power laws of variable strength as reflected by the corresponding exponent. The exponents depend quantitatively on the spread of frequency distribution of the examined parameter and tend to zero as the spread of distribution tends to a single order of magnitude. A comparison between the energy and the entropy of different kinds of pore distributions reveals that these two statistical parameters are linearly related, implying that the system poise at a critical state and the exchangeable quantities are the most convenient operations helping to keep this balance. Full article

Numerous stakeholders concur that tackling the climate change effect requires massive financial mobilization from the public and private sectors to reduce the climate financing gap. Capital markets are among the key players fostering this mobilization by issuing green financial instruments and facilitating capital flows to green investments. The study aimed to conduct a bibliometric analysis to fill a knowledge gap by evaluating the status and linkages in the literature on capital markets’ green financial instrument issuances. We utilized the Bibliometrix R package and VOS viewer to analyze 314 relevant publications from the Web of Science in 2017–2023 following the Sustainable Stock Exchanges’ green finance voluntary action plan. The analysis entailed mapping the scientific production trends, journal significance, author productivity, keyword linkages, emerging and trending topics, and collaborations within social structures. Further, the study assessed the applicability of Bradford’s, Zipf’s, and Lotka’s bibliometric laws. We highlight six conclusions based on the analysis, their relevance to various stakeholders, and future research directions. The findings are essential in enhancing the decision-making process of policymakers, corporations, responsible investors, and researchers interested in understanding the effectiveness and impact of green financial instruments. Full article

This research provides a comprehensive analysis of the dynamic interplay between agent-based modeling (ABM) and artificial intelligence (AI) through a meticulous bibliometric study. This study reveals a substantial increase in scholarly interest, particularly post-2006, peaking in 2021 and 2022, indicating a contemporary surge in research on the synergy between AI and ABM. Temporal trends and fluctuations prompt questions about influencing factors, potentially linked to technological advancements or shifts in research focus. The sustained increase in citations per document per year underscores the field’s impact, with the 2021 peak suggesting cumulative influence. Reference Publication Year Spectroscopy (RPYS) reveals historical patterns, and the recent decline prompts exploration into shifts in research focus. Lotka’s law is reflected in the author’s contributions, supported by Pareto analysis. Journal diversity signals extensive exploration of AI applications in ABM. Identifying impactful journals and clustering them per Bradford’s Law provides insights for researchers. Global scientific production dominance and regional collaboration maps emphasize the worldwide landscape. Despite acknowledging limitations, such as citation lag and interdisciplinary challenges, our study offers a global perspective with implications for future research and as a resource in the evolving AI and ABM landscape. Full article

All the time, differential dynamical models with delay has witness a tremendous application value in characterizing the internal law among diverse biological populations in biology. In the current article, on the basis of the previous publications, we formulate a new Lotka–Volterra commensal symbiosis system accompanying delay. Utilizing fixed point theorem, inequality tactics and an appropriate function, we gain the sufficient criteria on existence and uniqueness, non-negativeness and boundedness of the solution to the formulated delayed Lotka–Volterra commensal symbiosis system. Making use of stability and bifurcation theory of delayed differential equation, we focus on the emergence of bifurcation behavior and stability nature of the formulated delayed Lotka–Volterra commensal symbiosis system. A new delay-independent stability and bifurcation conditions on the model are presented. By constructing a positive definite function, we explore the global stability. By constructing two diverse hybrid delayed feedback controllers, we can adjusted the domain of stability and time of appearance of Hopf bifurcation of the delayed Lotka–Volterra commensal symbiosis system. The effect of time delay on the domain of stability and time of appearance of Hopf bifurcation of the model is given. Matlab experiment diagrams are provided to sustain the acquired key outcomes. Full article

Artificial neural networks have changed many fields by giving scientists a strong way to model complex phenomena. They are also becoming increasingly useful for solving various difficult scientific problems. Still, people keep trying to find faster and more accurate ways to simulate dynamic systems. This research explores the transformative capabilities of physics-informed neural networks, a specialized subset of artificial neural networks, in modeling complex dynamical systems with enhanced speed and accuracy. These networks incorporate known physical laws into the learning process, ensuring predictions remain consistent with fundamental principles, which is crucial when dealing with scientific phenomena. This study focuses on optimizing the application of this specialized network for simultaneous system dynamics simulations and learning time-varying parameters, particularly when the number of unknowns in the system matches the number of undetermined parameters. Additionally, we explore scenarios with a mismatch between parameters and equations, optimizing network architecture to enhance convergence speed, computational efficiency, and accuracy in learning the time-varying parameter. Our approach enhances the algorithm’s performance and accuracy, ensuring optimal use of computational resources and yielding more precise results. Extensive experiments are conducted on four different dynamical systems: first-order irreversible chain reactions, biomass transfer, the Brusselsator model, and the Lotka-Volterra model, using synthetically generated data to validate our approach. Additionally, we apply our method to the susceptible-infected-recovered model, utilizing real-world COVID-19 data to learn the time-varying parameters of the pandemic’s spread. A comprehensive comparison between the performance of our approach and fully connected deep neural networks is presented, evaluating both accuracy and computational efficiency in parameter identification and system dynamics capture. The results demonstrate that the physics-informed neural networks outperform fully connected deep neural networks in performance, especially with increased network depth, making them ideal for real-time complex system modeling. This underscores the physics-informed neural network’s effectiveness in scientific modeling in scenarios with balanced unknowns and parameters. Furthermore, it provides a fast, accurate, and efficient alternative for analyzing dynamic systems. Full article

This article aims to contribute to the academic knowledge in the field of scientific production regarding decision support tools for investments in the capital market, specifically focusing on fundamental analysis, technical analysis, and Ichimoku dynamics. Bibliometric analysis, following the three main laws (Bradford’s Law, Lotka’s Law, and Zipf’s Law), was employed to evaluate scientific production, identify publication patterns, and uncover gaps and collaboration networks over the last thirty years. To achieve these objectives, 1710 relevant academic publications on the topic were analyzed and retrieved from the Web of Science (WOS) database, pertaining to the last 30 years, between 1990 and 22 May 2023. The significance of this article lies in the contributions of the findings, which advance scientific knowledge by identifying gaps in the knowledge and research, particularly in the limited literature on Ichimoku; our review reveals a growing trend of research in this area. Another notable conclusion is the emergence of new research topics and areas of interest, as well as the identification of collaboration networks among authors, institutions, and countries. Moreover, the article provides valuable insights for financial professionals and investors who are interested in applying these methodologies as methods for price forecasting. The highlighted results support investment decision making, trading strategies, and portfolio management. Full article

This article presents a bibliometric study on different types of risk and bankruptcy, aiming to contribute to academic knowledge in this area. We used the bibliometrix tools in R and VOSviewer, following the main laws of bibliometrics (Bradford’s law, Lotka’s law, and Zipf’s law). We analyzed 7163 relevant academic publications retrieved from the WOS database between 1995 and 2023. The characterization of the literature identified trends, importance, and scientific relevance of works, journals, and authors. This allows for promoting collaborations among researchers and provides insights for strategic decision making, advancing knowledge in the field. The most relevant journal was the “Journal of Banking and Finance”, with Edward Altman as the prominent author. The United States and China were the most active countries in research. The current research highlights terms such as “board size”, “CRS”, “responsibility”, and “governance”, which are commonly found in recent works. The themes of greatest centrality include risk, model, and debt. The bibliometric review revealed gaps in knowledge and research, indicating a growing trend of studies in this area. This article provides valuable information for researchers and managers, supporting decision making in risk management and bankruptcy. Full article

The aim of this study is to present an overview of the current scientific literature pertaining to ocean literacy. We applied a bibliometric method to examine relational patterns among publications in a set of 192 papers indexed from 2004 to 2023 in Web of Science Core Collection, applying Price’s, Lotka’s, Bradford’s, and Zipf’s bibliometric laws to add more validation to VOSviewer and processing both data and metadata. The findings indicate a significant exponential growth in scientific output from 2004 to 2022 (R² = 86%), with a substantial amount of scientific research being focused on ocean literacy. The analysis shows the thematic trends of terminologies such as knowledge and citizen perception of climate change in relation to oceans; the benefits of biodiversity management and ocean conservation; and ocean education and its relation to behavior and attitudes towards and awareness of oceans. The research and its theoretical perspectives prompt an investigation of the impacts of ocean literacy outside of education, thanks to the contributions of authors from more than fifty countries dedicated to the study of these activities. Full article

Unrestrained urbanisation and natural space loss are reducing contact with nature in today’s society, producing negative consequences for people’s mental and physical health and wellbeing. Nature-based therapies, such as physical activity in natural settings, forest bathing, therapeutic hiking, or experiential learning, reduce anxiety and depressive symptoms and improve the quality of life in both general and specific populations. A bibliometric analysis of research on nature-based therapies was performed by applying the traditional laws of bibliometrics (exponential growth law, Bradford’s concentration law, Lotka’s law, Zipf’s law, etc.) to documents published in journals indexed in the Core Collection of the Web of Science (WoS). Graphical visualisation was performed using the VOSviewer software. Annual publications between 2006 and 2021 presented an exponential growth trend (R² = 91%). The International Journal of Environmental Research and Public Health (MDPI) and Urban Forestry & Urban Greening (Elsevier) were the most productive and cited journals. Ikei, Miyazaki, and Song are the most cited prolific authors. The USA and South Korea were the countries with the highest scientific production. In recent years, there has been a growing interest in adventure, nature, and forest therapies among researchers. Nature-based therapies have experienced a growing interest in recent years. Positive effects on mental, physical, and emotional health have been found in different populations and research lines, although more studies with different designs and populations are needed. Full article