Key Trends Research Articles

Старомонгольская письменность в Байкальском регионе на современном этапе: курс на ревитализацию?

This paper aims to provide an analysis of the development of the Mongolian script in the sociocultural context of the Baikal region in modern times. The main purpose of this article is to characterize the key trends in society from the point of view of sociolinguistic processes. Materials and methods. The research is based on a thorough examination of official data from the Government of the Republic of Buryatia, government departments of the Irkutsk region and Transbaikal region, as well as publications in the media and field materials gathered through an expert survey of heads of educational centers and language activists. The authors have adopted a systematic approach and applied a range of general scientific and special methods, including comparative historical and statistical methods, to conduct this study. Results and conclusions. It has been revealed that the Mongolian script has significant role in performing various socio-cultural functions. Mongolian script has gained widespread popularity in the form of calligraphy in the Baikal region. Furthermore, the language is deeply embedded with ethno cultural symbolism, making it a valuable source for the development of the Buryat language and culture as a whole. There is a growing interest in analyzing the language situation in Mongolia and the Inner Mongolia Autonomous Region of the People’s Republic of China, particularly in terms of the implementation of state language policy in perspective. The status and functional role of Mongolian script in these regions are of utmost importance in understanding its impact on the overall language landscape.

Augmented future: tracing the trajectory of location-based augmented reality gaming for the next ten years

Abstract Location-based games are a highly technology-dependent game genre that has witnessed an exponential increase in popularity with the democratisation of smartphones as well as ubiquitous mobile data and access to satellite navigation. Moving forward into the future, location-based games can be expected to evolve as the technologies underlying the genre improve. In this conceptual work, we review the current state of the art in location-based games, and identify key trajectories and trends. We discovered 12 trends, based on which we jump ten years into the future and evaluate how current technology trends may end up influencing location-based gaming. For example, we propose that in the year 2035 through improvements in map data services and sensor data coverage, we will see locative games that are increasingly connected to elements in the physical world. We also expect to see gameplay that moves away from solely taking place on a smartphone screen to the adoption of multiple forms of interactions with location-based game worlds, especially as head-mounted displays and other wearables become more commonplace.

Crossroads between Big Data and entrepreneurship: current key trends

AbstractEntrepreneurship is vital for economic growth and development, as it fosters innovation, creates jobs, and enhances competition and competitiveness. At the same time, in contemporary society, where the Internet has assumed the role of the primary instrument for both communication and commerce, effective utilisation of vast amounts of data has become imperative for businesses, especially in the entrepreneurial environment. To identify the main connections in two of the currently most trending concepts in business, we undertook a systematic literature review focusing on Big Data, entrepreneurship, and their interconnections in business management through 301 research documents. While numerous studies have already delved individually into Big Data and entrepreneurship, the interconnection between these concepts still has research potential. Our results reflect a growing interest in leading research on these topics, with specific leading authors and countries. Furthermore, we show and discuss a conceptual map consisting of five clusters, unveiling interesting connections such as the impact of blockchain on firms, the correlation between Big Data and firm performance, the role of data science, and the significance of Big Data analytics for operational performance. The article ends by examining how Big Data and entrepreneurship change the business landscape. While entrepreneurs use data for decision-making, innovation, and tailored customer experiences, there are lingering concerns such as data security and privacy. The future of business and innovation will depend, in part, on the crossroads between entrepreneurs and Big Data technologies.

Digital marketing business models: Key stages, types and trends of development

The main goal of the article is to formalize the key business models of marketing of modern companies and substantiate the key stages, types and trends of development. The relevance and need to pay significant attention to the marketing digital business model when organizing a business is substantiated. Using structural and logical analysis and criticism of scientific research, the essence, advantages and disadvantages are determined, the main blocks, stages and key elements of the structure of business models of modern companies are argued. It has been proven that marketing digital business models serve as a logical and visual plan for organizing all business processes of companies from production, marketing, sales and logistics to building a hierarchy of profitability. The key development trends are substantiated and the most popular business models of business organization in modern conditions are structured on the basis of scientific generalization, structural and logical analysis and mathematical modeling. Practical significance is characterized by the fact that the marketing business models of world-class companies are generalized and structured, taking into account their specifics and characteristics. Practical recommendations and key stages of building a company’s business model and its implementation into reality have been formed to achieve strategic business goals.

The influence of consumer behavior on sustainable marketing efforts

This concept paper explores the dynamic relationship between consumer behavior and sustainable marketing efforts. As consumers increasingly prioritize environmental and social responsibility, businesses are adapting their marketing strategies to meet these evolving demands. The paper provides insights into the influence of consumer attitudes, beliefs, and values on sustainable purchasing decisions, highlighting the growing market for environmentally friendly products and the importance of transparent communication about sustainability efforts. Through a review of existing literature, the paper identifies key trends, challenges, and opportunities for businesses seeking to align their marketing strategies with sustainability goals. It proposes a model for understanding the influence of consumer behavior on sustainable marketing efforts, emphasizing the role of marketing strategies in shaping consumer perceptions of sustainability and influencing purchasing behavior. While businesses face challenges such as the high cost of sustainable production and the complexity of supply chains, the paper also highlights opportunities to differentiate themselves in the market and build stronger relationships with environmentally conscious consumers. By understanding consumer preferences and values, businesses can develop marketing strategies that resonate with their target audience and drive positive change. In conclusion, consumer behavior has a significant impact on sustainable marketing efforts, and businesses must adapt their strategies to meet the demands of an increasingly socially and environmentally conscious consumer base. The paper provides a foundation for further research and offers practical insights for businesses looking to integrate sustainability into their marketing strategies and achieve long-term success in a rapidly changing market landscape.. Keywords: Consumer Behavior, Sustainability, Marketing.

Cross-Disciplinary Perspectives on Teaching Quality: A Systematic Review

This comprehensive systematic review examines the evolution of teaching quality research globally from 1990 to 2019. Analyzing 182 studies, the review identifies key trends, highlighting a significant rise in academic interest since 2012. Notably, the study underscores the cross-disciplinary nature of teaching quality, emphasizing its departure from isolation. The geographical landscape of research reveals an expanding focus, particularly in Asian countries. The review further explores thematic concentrations, research designs, and authorship patterns, revealing insights into collaboration trends. Journal analysis showcases a diverse academic interest in teaching quality across various disciplines. The conclusion urges researchers to diversify perspectives for continued field development.

Gravitating towards Artificial Intelligence on Anti-Money Laundering A PRISMA Based Systematic Review

In Bangladesh, like many other countries, the implementation of Anti-Money Laundering (AML) measures plays a crucial role in the fight against financial offences and the maintenance of the financial system's integrity. The integration of Artificial Intelligence (AI) is one of the technologies for AML that has emerged as a promising approach to enhance the detection and prevention of financial crimes. The researcher aims to investigate the current state of AML, the impact of AI, the roles involved, and the legislation to achieve economic stability for the transformation of Bangladesh into a smart nation by 2041. In this systematic review study, the PRISMA framework is utilized to provide a comprehensive analysis of existing literature on the application of AI in AML, with a focus on risks, laws, and implications, particularly within the context of Bangladesh. The review synthesizes findings from diverse sources (Web of Sciences, Scopus, PubMed, and DOAJ indexing articles and reports) including academic research, industry reports, and regulatory documents, to assess the effectiveness, challenges, and ethical considerations associated with AI-driven AML solutions. Through a structured search strategy and rigorous selection criteria, the researchers discovered a total of 299 research papers, consisting of 181 latest studies and 117 previous relevant studies identified and analyzed to elucidate key trends, methodologies, and gaps in the current landscape of AI-enabled AML practices. The review also offers insights and recommendations for policymakers, practitioners, and researchers interested in leveraging AI technologies to combat money laundering effectively while navigating regulatory frameworks and safeguarding privacy rights. By critically examining the intersection of AI, AML, and legal frameworks, this study contributes to the ongoing discourse on the role of technology in addressing financial crime challenges in Bangladesh and beyond.

The Influence of Information Cooperation in Central Asia on the Interests and Foreign Policy of the Republic of Kazakhstan

Abstract This article examines how information cooperation influences Kazakhstan’s foreign policy. Through systematic analysis and comparison methods, this article identifies key trends and differences in information cooperation among Central Asian countries. Strengthening regional contacts and Kazakhstan’s engagement in international organizations emerge as pivotal outcomes of this interaction. Diplomatic services, regional initiatives, media projects, and cybercrime counteraction play essential roles in creating a modern information landscape in Kazakhstan. This research provides a foundation for future studies on information cooperation in Central Asia and its broader international implications.

Barriers and Challenges of Sustainable Logistics in Automobile Industry

Study Background and Objectives The automobile industry is a significant contributor to global environmental concerns. Vehicle production, transportation, and end-of-life management all have substantial environmental footprints. Sustainable logistics practices offer a path towards a greener future for industry. However, implementing these practices faces numerous challenges. This study aims to investigate the barriers and challenges hindering the adoption of sustainable logistics practices within the automobile industry. The specific objectives are: · To identify the key barriers faced by automobile manufacturers and their logistics partners in implementing sustainable practices. · To analyse the impact of these barriers on the environmental performance of the industry's logistics operations. · To develop recommendations for overcoming these barriers and promoting sustainable logistics practices within the automobile sector. Research Design This study employs a literature review methodology to analyze existing research on the barriers and challenges of sustainable logistics in the automobile industry. Relevant academic journals, conference proceedings, and industry reports are reviewed to identify key themes and insights. · Conduct a systematic and comprehensive review of relevant academic journals, industry reports, and government publications. · Utilize appropriate search engines and databases to identify relevant literature. · Analyse the collected data to identify key themes, trends, and research gaps. · Synthesize the findings to provide a comprehensive understanding of the barriers and challenges of sustainable logistics in the automobile industry. Major Findings The study reveals a growing consumer interest in the auto industry's commitment to sustainability. While price, performance, and safety remain significant purchase factors, a significant portion of consumers consider a car manufacturer's environmental practices when deciding. However, a knowledge gap exists, with many consumers lacking awareness of the environmental impact of traditional logistics practices. The research also highlights the importance of collaboration between car manufacturers, logistics companies, and policymakers in achieving significant progress towards sustainable practices. Standardized sustainability metrics and government incentives are seen as crucial factors for long-term success.

Assessing the current landscape of AI and sustainability literature: identifying key trends, addressing gaps and challenges

The United Nations’ 17 Sustainable Development Goals stress the importance of global and local efforts to address inequalities and implement sustainability. Addressing complex, interconnected sustainability challenges requires a systematic, interdisciplinary approach, where technology, AI, and data-driven methods offer potential solutions for optimizing resources, integrating different aspects of sustainability, and informed decision-making. Sustainability research surrounds various local, regional, and global challenges, emphasizing the need to identify emerging areas and gaps where AI and data-driven models play a crucial role. The study performs a comprehensive literature survey and scientometric and semantic analyses, categorizes data-driven methods for sustainability problems, and discusses the sustainable use of AI and big data. The outcomes of the analyses highlight the importance of collaborative and inclusive research that bridges regional differences, the interconnection of AI, technology, and sustainability topics, and the major research themes related to sustainability. It further emphasizes the significance of developing hybrid approaches combining AI, data-driven techniques, and expert knowledge for multi-level, multi-dimensional decision-making. Furthermore, the study recognizes the necessity of addressing ethical concerns and ensuring the sustainable use of AI and big data in sustainability research.

Driving Success: Unveiling Key Trends in Employee Training and Competency Development within the Automotive Industry

Driving Success: Unveiling Key Trends in Employee Training and Competency Development within the Automotive Industry

Improving the Fuel Economy and Energy Efficiency of Train Cab Climate Systems, Considering Air Recirculation Modes

Current developments in vehicles have generated great interest in the research and optimization of heating, ventilation, and air conditioning (HVAC) systems as a factor to reduce fuel consumption. One of the key trends for finding solutions is the intensive development of electric transport and, consequently, additional requirements for reducing energy consumption and modifying climate systems. Of particular interest is the optimal functioning of comfort and life support systems during air recirculation, i.e., when there is a complete or partial absence of outside air supply, in particular to reduce energy consumption or when the environment is polluted. This work examines numerical models of airfields (temperature, speed, and humidity) and also focuses on the concentration of carbon dioxide and oxygen in the cabin, which is a critical factor for ensuring the health of the driver and passengers. To build a mathematical model, the Navier–Stokes equations with energy, continuity, and diffusion equations are used to simulate the diffusion of gases and air humidity. In the Ansys Fluent finite volume analysis package, the model is solved numerically using averaged RANS equations and k-ω turbulence models. The cabin of a mainline locomotive with two drivers, taking into account their breathing, is used as a transport model. The problem was solved in a nonstationary formulation for the design scenario of summer and winter, the time of stabilization of the fields was found, and graphs were constructed for different points in time. A comparative analysis of the uniformity of fields along the height of the cabin was carried out with different locations of deflectors, and optimal configurations were found. Energy efficiency values of the climate system operation in recirculation operating modes were obtained. A qualitative assessment of the driver’s blowing directions under different circulation and recirculation modes is given from the point of view of the concentration of carbon dioxide in the breathing area. The proposed solution makes it possible to reduce electricity consumption from 3.1 kW to 0.6 kW and in winter mode from 11.6 kW to 3.9 kW and save up to 1.5 L/h of fuel. The conducted research can be used to develop modern energy-efficient and safe systems for providing comfortable climate conditions for drivers and passengers of various types of transport.

From traditional to innovation: A comprehensive Analysis of Tourism's Evolution and its Global influence on New Era Dynamics

Tourism is a multifaceted phenomenon that has undergone significant evolution over time, transitioning from traditional mass tourism models to more diversified and sustainable approaches. This paper presents a comprehensive analysis of tourism's evolution and its global influence on new era dynamics, drawing on a diverse range of literature and research findings. The study examines key drivers, trends, challenges, and opportunities shaping the contemporary tourism landscape, with a focus on the transition from conventional to innovative practices. The analysis reveals a gradual shift towards innovative tourism models that prioritize authenticity, sustainability, and personalized experiences, driven by changing consumer preferences, technological advancements, and global socio-economic trends. This evolution has profound implications for new era dynamics at the global level, including increased connectivity, cross-cultural exchange, and economic growth, but also challenges such as over tourism, environmental degradation, and socio-cultural tensions. To address these challenges and capitalize on opportunities, stakeholders in the tourism industry are urged to embrace innovation, sustainability, and collaboration as guiding principles for future development. Recommendations include promoting sustainable tourism practices, addressing over tourism through destination management, fostering collaboration and stakeholder engagement, and investing in capacity building and education. By adopting a holistic approach to tourism development that balances economic, environmental, and social considerations, stakeholders can navigate the complexities of the tourism landscape and chart a course towards a more sustainable and inclusive future. The findings of this study contribute to a deeper understanding of the dynamics shaping the tourism industry and provide valuable insights for policymakers, industry practitioners, researchers, and other stakeholders seeking to harness the transformative power of tourism for positive impacts on people, planet, and prosperity.

A bibliometric and visual analysis of research trends and hotspots of familial hypertrophic cardiomyopathy: A review.

Familial hypertrophic cardiomyopathy (FHCM) is an inherited cardiac disease caused by mutations of sarcomere proteins and can be the underlining substrate for major cardiovascular events. Early identification and diagnosis of FHCM are essential to reduce sudden cardiac death. So, this paper summarized the current knowledge on FHCM, and displayed the analysis via bibliometrics method. The relevant literature on FHCM were screened searched via the Web of Science Core Collection database from 2012 to 2022. The literatures were was summarized and analyzed via the bibliometrics method analyzed via CiteSpace and VOSviewer according to topic categories, distribution of spatiotemporal omics and authors, as well as references. Since 2012, there are 909 research articles and reviews related to FHCM. The number of publication for the past 10 years have shown that the development of FHCM research has been steady, with the largest amount of literature in 2012. The most published papers were from the United States, followed by the United Kingdom and Italy. The University of London (63 papers) was the institution that published the most research articles, followed by Harvard University (45 papers) and University College London (45 papers). Keywords formed 3 clusters, focused on the pathogenesis of FHCM, the diagnosis of FHCM, FHCM complications, respectively. The bibliometric analysis and visualization techniques employed herein highlight key trends and focal points in the field, predominantly centered around FHCM's pathogenesis, diagnostic approaches, and its complications. These insights are instrumental in steering future research directions in this area.

Public libraries to promote public health and wellbeing: a cross-sectional study of community-dwelling adults

BackgroundLibraries in the UK have evolved from traditional book-lending institutions into dynamic community hubs, This study aims to explore the potential of libraries to act as community hubs to promote mental and physical health and wellbeing of community-dwelling adults, drawing on insights from both library users and library staff in England.DesignA mixed-method, cross-sectional study using online survey and interviews with community-dwelling adults and library staff.MethodsWe collected data using a 14-item electronic survey and interviews with library users and staff to gauge perceptions. Descriptive statistics and thematic analysis were used to identify key trends and emergent themes.ResultsWe included 605 respondents from the survey and interviewed 12 library users and staff. Libraries remain popular and are considered a ‘safe place by members of the community, regardless of their frequency of service usage irrespective of whether they are frequent users of services. However, a lack of awareness among library users about community-facing services could act as a hurdle to improving community health and wellbeing. Targeted engagement with residents is needed to increase awareness of libraries’ services, including community interventions to help tackle loneliness and inequalities in digital and health literacy. Library staff often did not feel involved in important decision-making. Various barriers, drivers and practical recommendations were identified to leverage libraries as hubs to promote community health and wellbeing.ConclusionLibraries already offer a variety of resources that directly or indirectly support the health and wellbeing of community-dwelling adults and young people. However, public awareness of these services is limited. As we navigate post-pandemic recovery, libraries can serve as platforms for community engagement, fostering resilience, mental health support and reducing social isolation. Recognising libraries’ untapped potential can lead to healthier communities and improved wellbeing.

A multivariate linear regression model for estimating chlorophyll-a concentration in Quan Son Reservoir (Hanoi, Vietnam) using Sentinel-2B Imagery

Monitoring chlorophyll-a concentration (Chla) in inland waters is vital for environmental assessment. This study develops an empirical multivariate linear regression (MLR) model to directly estimate Chla in Quan Son Reservoir using Sentinel-2B (S2B) Level 2A images. Regression analysis of a 68-point in-situ Chla dataset measured in Quan Son Reservoir between 2021 and 2023, in conjunction with the corresponding S2B reflectance data, reveals a significant correlation between Chla and a combination of the blue (B2), green (B3), and red (B4) bands (coefficient of determination, R² = 0.95). The Chla estimation model is validated using a 30-point in-situ dataset collected on various dates (R² = 0.87; the root-mean-squared error RMSE < 5%). Subsequently, the model is applied to ten S2B images acquired from 2021 to 2023, revealing Chla's spatio-temporal distribution across the reservoir. Two key trends emerge: (1) Chla is lower during winter (November and December) than in summer and early autumn (July and September), and (2) The distribution of Chla undergoes noticeable spatial changes, particularly in July, with elevated levels observed in areas characterized by tourist hotspots. This approach shows promise for monitoring Chla in similar inland waters.

ANALYSIS OF SHARE PRICES OF NYKAA AND PAYTM AFTER THEIR IPO

The Initial Public Offering (IPO) market is a turning point for many businesses as they seek to grow their business, raise capital, and attract public investment. Going public is a huge deal for every party concerned, from the firm itself to the investors who stand to gain from its growth in the future. Investors, experts, and the general public have been captivated by the initial public offerings (IPOs) of two prominent startups in recent years—Nykaa and Paytm. Nykaa, an e-commerce website based in India, made its stock market debut in November 2021. Things related to personal hygiene and cosmetics are the platform's forte. Nykaa, founded in 2012 by Falguni Nayar, a former investment banker, is currently a major player in the booming cosmetics industry in India. An increase in interest in the company's IPO was driven by the growing demand for cosmetics and the allure of online shopping in India's market. Also in November 2021, India's leading digital payment and financial services platform, Paytm, went public for the first time. When Vijay Shekhar Sharma launched his mobile payment system Paytm in 2010, it revolutionised the way Indians handled their money and made online transactions. The IPO marked a watershed moment in the development of digital payment systems and financial technology, both of which have the potential to radically alter the Indian economy. Investor mood, underlying prospects, and market expectations are all gauged by the share prices of Nykaa and Paytm, which have been the topic of extensive investigation and study since their initial public offerings (IPOs). To understand the factors driving these stocks' performance, it's important to look at more than just financial results; you need to look at industry trends, market sentiment, and company advancements as well. This study aims to examine the performance of Nykaa and Paytm since their IPOs, the factors that have influenced their share prices, and the potential future directions of these companies. Our goal is to help investors make sense of the volatile stock market by studying key indicators, market dynamics, and industry trends. The intricacies of investing in these renowned organisations can be better grasped with this information. After that, we'll take a look at the stock prices of Nykaa and Paytm since their IPOs, analyse the factors that have impacted them, and then draw some conclusions about what this means for investors who are trying to make money off of these companies' fast development. In this article, we will provide a comprehensive overview of Nykaa and Paytm's post-IPO process and use quantitative research, qualitative insights, and industry experience to shed light on the benefits and drawbacks of investing in these companies. The initial public offerings (IPOs) of Nykaa and Paytm have wowed investors and industry participants, proving that technology and innovation can propel value creation. As these businesses make their way as publicly traded corporations, share prices will continue to reflect the interplay between basic considerations, market sentiment, and broader economic trends. Investors can benefit from the ever-changing stock market and make informed decisions by closely monitoring their performance following an initial public offering (IPO).

High-performance computing in healthcare:an automatic literature analysis perspective

The adoption of high-performance computing (HPC) in healthcare has gained significant attention in recent years, driving advancements in medical research and clinical practice. Exploring the literature on HPC implementation in healthcare is valuable for decision-makers as it provides insights into potential areas for further investigation and investment. However, manually analyzing the vast number of scholarly articles is a challenging and time-consuming task. Fortunately, topic modeling techniques offer the capacity to process extensive volumes of scientific literature, identifying key trends within the field. This paper presents an automatic literature analysis framework based on a state-of-art vector-based topic modeling algorithm with multiple embedding techniques, unveiling the research trends surrounding HPC utilization in healthcare. The proposed pipeline consists of four phases: paper extraction, data preprocessing, topic modeling and outlier detection, followed by visualization. It enables the automatic extraction of meaningful topics, exploration of their interrelationships, and identification of emerging research directions in an intuitive manner. The findings highlight the transition of HPC adoption in healthcare from traditional numerical simulation and surgical visualization to emerging topics such as drug discovery, AI-driven medical image analysis, and genomic analysis, as well as correlations and interdisciplinary connections among application domains.

USER PERCEPTION TOWARDS PREDICTIVE ANALYTICS IN CREDIT RISK MANAGEMENT

This comprehensive review explores the dynamic landscape of predictive analytics in credit risk management within the banking sector. Anchored in a qualitative research design, the study synthesizes existing literature and real-world case studies to provide a multifaceted understanding of predictive analytics' role in modern banking. The review identifies key trends, highlighting the integration of predictive analytics across diverse banking operations, the transition to advanced machine learning algorithms, the democratization of predictive analytics tools, and the growing emphasis on ethical and regulatory compliance. It underscores the effectiveness of predictive analytics, showcasing its ability to enhance risk assessment precision, decision-making agility, and overall banking performance. Comparative analyses reveal the varying performance of predictive models across contexts, emphasizing the importance of tailored model selection. However, challenges such as data quality, model interpretability, talent scarcity, ethical considerations, and implementation costs pose significant hurdles. Looking forward, predictive analytics promises to be an indispensable tool for mitigating credit risk in the banking sector, offering refined risk assessments, smarter decisions, and enhanced resilience. The insights from this review provide valuable guidance for banking professionals, regulators, and researchers navigating the evolving landscape of predictive analytics in banking.

A Two-Decade Bibliometric Analysis of Laser in Ophthalmology: From Past to Present.

Laser therapy has been proven as an effective technique for managing ophthalmological disorders. To guide future research, we conducted a bibliometric analysis of laser applications in eye diseases from 1990 to 2022, aiming to identify key themes and trends. We retrieved 3027 publications from the Web of Science Core Collection (WoSCC). Bibliometrix was used for science mapping of the literature, while VOSviewer and CiteSpace were applied to visualize co-authorship, co-citation, co-occurrence, and bibliographic coupling networks. From a co-citation reference network, we identified 52 distinct clusters. Our analysis uncovered three main research trends. The first trend revolves around the potential evolution of corneal laser surgery techniques, shifting from the treatment of refractive errors to broader applications in biomedical optics. The second trend illustrates the advancement of laser applications in treating a range of disorders, from retinal and ocular surface diseases to glaucoma. The third trend focuses on the innovative uses of established technologies. This study offers significant insights into the evolution of laser applications in ophthalmology over the past 30 years, which will undoubtedly assist scientists in directing further research in this promising field.