Artificial Intelligence and Challenges in Ayurveda Pharmaceutics: A Review

Ayurveda, the science of life is used for maintenance of health from ancient time. Aim: The most important aim was to prolong lifespan of human subjects as well as to maintain and promote their positive health and the equivalent is the motto of Ayurveda science. Pharmaceutical department in Ayurveda with more than five thousand permutation and combinations are utilized in day today practice for cure the various diseases. Data Sources: As per the title and reference taken from the online publications of articles and some of the literatures. Study Selection: This traditional medical system along with established annals of several centuries is becoming one of the most popular sciences with safety and efficacy. With raise demand of Ayurveda medicine and acceptance of Ayurveda in the whole world, there is need of modernization and use of progress methodology in Ayurveda Pharmaceutics. Now a day’s newly advanced branch called as Artificial Intelligence (AI) can be used to meet increasing demands of Ayurveda medicines and to face the challenges faced during drug manufacturing. Result: AI is used to combine engineering principles into the drug development to overcome challenges faced in Ayurveda Pharmaceutics. This can be achieved by way of applicability of AI in the different sectors of Ayurveda pharmaceutics. Conclusion: An attempt has been made in this article to examine challenges with probable solutions by using Artificial Intelligence for global acceptance of Ayurveda.

With the continuous development of science and technology, exploration in the field of life sciences has become increasingly profound, encompassing the understanding of human beings themselves and the exploration of disease etiology and treatment methods.Artificial intelligence is defined as the intelligence exhibited by artificially created systems. The application of artificial intelligence is quite extensive and can replace humans in various aspects of work, significantly enhancing efficiency in daily life and work. Artificial intelligence has a dual nature, as it could provide convenience to human society but could also bring about various adverse effects.This paper summarizes the current applications of artificial intelligence in the field of life sciences. By analyzing the applications of artificial intelligence in areas such as gene editing, drug development, and bioinformatics, it demonstrates the potential of artificial intelligence in the field of life sciences. At the same time, this paper also points out the ethical, technical, social, and various challenges that the application of artificial intelligence technology in the field of life sciences faces, with the aim of providing reference for research in related fields.

This study evaluates the impact of Artificial Intelligence (AI) applications in power systems on energy security and to determine relevant policy implications. We use a mixed methods approach to analyze the benefits and risks associated with AI implementation on the European power grid, focusing on four key dimensions of energy security: availability, affordability, accessibility, and acceptability. We investigated the benefits of AI using PyPSA, a Python-based model of the European electricity system. Three AI applications were parametrized: load reduction, load shifting, and wind wake steering. We compared scenarios in which these AI applications are widely deployed against a baseline scenario without these applications to determine if AI improves energy security. The study also analyzes risks associated with AI deployment in the power grid. We developed a risk taxonomy centered around six high-level categories: cybersecurity, jurisdictional or sovereignty issues, unexplained or unexpected actions by the model, unethical or illegal decision-making, reliance and trust in decision-making, and supplier dependency and vendor lock-in. Additionally, we conducted a back-casting exercise with subject-matter experts to determine positive and negative future outcomes of AI deployment and identify actions to create positive outcomes and avoid negative ones. The paper presents a set of policy implications for AI on the European synchronous grid. We find that AI applications can improve energy security in power systems. In the scenarios we tested, behind-the-meter applications have a greater impact on energy security than front-of-meter applications. The results suggest that AI applications targeting energy consumption may significantly improve energy security metrics. Keywords: Energy Security, AI, Power Grid, European Electricity System

Technological progress, especially in the field of information, has led to reducing the gap between science, information and knowledge. This accelerating change has forced all educational institutions to comply with this new mission by using information technology in the teaching process, as artificial intelligence has become an integral part of the educational and learning process, and a means of Effective in the teaching process, in addition to being research tools in obtaining information and knowledge, the research problem focused on (what are the attitudes of the kindergarten teacher towards using artificial intelligence applications in the effective teaching process in the early education stage in the third Rusafa Education Directorate?), where the importance of The research is considered one of the researches that deals with an important and vital topic (artificial intelligence), as it gains its importance in that it represents the role that kindergarten teachers play in the early education stage in developing the skills and abilities and refining the information of the child through their use of artificial intelligence methods and applications, as well as The positive role of such research in stimulating kindergarten teachers’ motivation to benefit from artificial intelligence applications, which increases the efficiency and effectiveness of their teaching. The aim of the research is to reveal kindergarten teachers’ attitudes towards using artificial intelligence in the effective teaching process in the early education stage, as well as to reveal the most important The challenges facing kindergarten teachers using artificial intelligence in the effective teaching process, and are there any statistically significant differences between the average kindergarten teacher’s attitudes to using artificial intelligence in the effective teaching process in the early education stage according to the research variables? The research reached several conclusions, perhaps the most important of which is the existence of differences. There is statistical significance between the average kindergarten teacher’s attitudes to using artificial intelligence in the effective teaching process in the early education stage according to the research variables. The research recommends holding many workshops and training courses for kindergarten teachers on how to use artificial intelligence in effective teaching, and including programs and rehabilitation plans for kindergarten teachers. About the use of artificial intelligence according to the plans of the Ministry of Education, which are consistent with its vision, and encouraging teachers to proceed and benefit from applications and websites for safe and available artificial intelligence applications in the teaching process

Introduction: In todays rapidly changing technology, artificial intelligence (AI) is changing the way we live, work and create art at an unprecedented speed. As an important part of human culture, dance art has also ushered in new development opportunities and challenges in this scientific and technological revolution. Objectives: This paper aims to explore the innovative application and influence of artificial intelligence (AI) in dance creation and performance. With the rapid development of AI technology, its application is increasingly wide in the field of art, and dance art is no exception Methods: This paper first outlines the application of AI technology in dance creation, including the generation of new dance movements through algorithms, auxiliary choreography, etc. These applications provide unprecedented creative sources and tools for dance creators. Then, this paper analyzes the role of AI in dance performance, such as the accurate movement performance of dance robot, the immersive experience of virtual reality technology in dance performance, etc. Results: These technologies not only enrich the form of dance performance, but also broaden the viewing experience of the audience. In addition, this paper also discusses the application of AI in dance teaching, such as intelligent guidance system, distance dance teaching, etc., which bring convenience and personalization to dance teaching. However, the application of AI in the field of dance also faces technical challenges and art ethical issues, which need further research and discussion. Conclusions: In conclusion, this paper believes that the application of AI technology in dance creation, performance and teaching has broad prospects, but it also needs to pay attention to its potential impact and challenges to promote the harmonious coexistence of dance art and AI technology. The research of this paper provides new perspectives and thoughts in the field of dance art, Provides a reference for future research and practice.

This study investigates the scientific development of Artificial Intelligence (AI) and Machine Learning (ML) applications in Human Resource Management (HRM) through bibliometric analysis. To this end, 522 academic publications indexed in the Scopus database between 2020 and 2024 were analyzed using the R-based bibliometrix package and VOSviewer software. Descriptive analysis, scientific productivity metrics, and content analysis techniques were employed. The findings revealed three main patterns. First, research on AI and ML applications in HRM has grown significantly—particularly between 2022 and 2024—driven by post-pandemic digital transformation. Second, India, China, and the USA lead in research output, while the UK and France demonstrate strong citation impact, indicating a globally expanding research ecosystem. Third, the thematic focus of research is shifting from technical infrastructure toward more human-centered and ethical dimensions. Additionally, keyword co-occurrence network analysis identified three major thematic clusters: HRM functions, AI applications, and machine learning analytics, highlighting the field’s interdisciplinary nature. Compared to the previous studies, this research provides a more comprehensive bibliometric analysis of AI and ML applications in HRM. It is the first extensive study to map the intellectual evolution of the field from a multidisciplinary perspective. Furthermore, it charts research trends and collaboration networks, revealing a shift from technical implementations to strategic integration. In conclusion, this analysis offers new insights to the literature by illustrating the technological evolution in HRM and highlighting the growing significance of cutting-edge approaches such as AI and ML, reaffirming the field as a timely and impactful area of research.

Purpose This study examines the extent to which artificial intelligence (AI) applications predict psychological flourishing and sustainable development among Fayoum University students. It further explores gender differences in AI usage, flourishing levels, and sustainability orientations, as well as the interrelationships among the three variables. Methods A quantitative correlational design was employed using validated scales measuring AI application use, psychological flourishing, and sustainable development. The sample consisted of 190 university students from Fayoum University (Egypt) there ages were between 20 and 25 years. The mean age was 22.54 years, with a standard deviation of 3.22 years. Data were analyzed using t-tests, Pearson’s correlation coefficients, and simple linear regression to test the study hypotheses. Results Findings revealed no significant gender differences in AI application use, while significant differences were found in psychological flourishing and sustainable development in favor of male students. Significant positive correlations emerged among AI use, flourishing, and sustainability. Regression analyses showed that AI application use moderately predicted psychological flourishing (R 2 = 0.098) but strongly predicted sustainable development (R 2 = 0.604), indicating that AI plays a substantial role in shaping students’ sustainability-related behaviors. Conclusions The study demonstrates that AI applications contribute meaningfully to enhancing students’ well-being and sustainability practices, with a stronger influence on sustainability outcomes. These findings underscore the growing relevance of AI-driven learning environments in promoting sustainable education and student development. Implications The results highlight the need for integrating AI-based tools into higher education policies, fostering responsible AI use, and developing institutional initiatives that enhance students’ well-being and sustainability competencies.

This research examines what impact the Big Data Processing Framework (BDPF) has on Artificial Intelligence (AI) applications within Corporate Marketing Communication (CMC), and thereby the research question stated is: What is the potential impact of the BDPF on AI applications within the CMC tactical and managerial functions? To fulfill the purpose of this research, a qualitative research strategy was applied, including semi-structured interviews with experts within the different fields of examination: management, AI technology and CMC. The findings were analyzed through performing a thematic analysis, where coding was conducted in two steps. AI has many useful applications within CMC, which currently mainly are of the basic form of AI, so-called rule-based systems. However, the more complicated communication systems are used in some areas. Based on these findings, the impact of the BDPF on AI applications is assessed by examining different characteristics of the processing frameworks. The BDPF initially imposes both an administrative and compliance burden on organizations within this industry, and is particularly severe when machine learning is used. These burdens foremost stem from the general restriction of processing personal data and the data erasure requirement. However, in the long term, these burdens instead contribute to a positive impact on machine learning. The timeframe until enforcement contributes to a somewhat negative impact in the short term, which is also true for the uncertainty around interpretations of the BDPF requirements. Yet, the BDPF provides flexibility in how to become compliant, which is favorable for AI applications. Finally, BDPF compliance can increase company value, and thereby incentivize investments into AI models of higher transparency. The impact of the BDPF is quite insignificant for the basic forms of AI applications, which are currently most common within CMC. However, for the more complicated applications that are used, the BDPF is found to have a more severe negative impact in the short term, while it instead has a positive impact in the long term.

With the rising demand for personalized learning and increased digital natives, the traditional education model is under pressure to reform. the rapid development of artificial intelligence (AI) provides new education solutions, and the application of AI is becoming widespread, from intelligent tutoring to automated grading to learning analytics. However, the application of AI in education is not without challenges. This literature review aims to explore the impact of AI on education, analyze its potential advantages, and propose strategies to address the challenges and provide guidance for the future development of education. Understanding the impact of AI on education is instructive for the future direction of AI in education and reveals the importance of AI for education to the extent that it is important for formulating effective educational policies and cultivating future talents in AI technology. The final results of the study show that although AI in the education industry there are various difficulties and limitations, but AI offers great potential for smarter and more efficient education levels and education systems. In today's era, computer programming education is emerging as a pivotal force in shaping the future, as it not only hones students' logical thinking and innovative capabilities but also lays a solid foundation for their career paths in the digital world. By integrating knowledge across various disciplines, programming education stimulates students' enthusiasm for applying their learning to real-world problems and enhances their sense of social engagement, enabling them to tackle challenges through technological means.

A 3D indicator for guiding AI applications in the energy sector

Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a managerial level. To overcome adoption hurdles, HC organizations would benefit from understanding how they can capture AI applications’ potential.We conduct a comprehensive systematic literature review and 11 semi-structured expert interviews to identify, systematize, and describe 15 business objectives that translate into six value propositions of AI applications in HC.Our results demonstrate that AI applications can have several business objectives converging into risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery.We contribute to the literature by extending research on value creation mechanisms of AI to the HC context and guiding HC organizations in evaluating their AI applications or those of the competition on a managerial level, to assess AI investment decisions, and to align their AI application portfolio towards an overarching strategy.

Recent advancements in artificial intelligence (AI) applications in medicine have been significant over the past 30 years. To monitor current research developments, it is crucial to examine the latest trends in AI adoption across various medical fields. This bibliometric analysis focuses on AI applications in cardiology. Unlike existing literature reviews, this study specifically examines journal articles published in the last decade, sourced from both Scopus and Web of Science databases, to illustrate the recent trends in AI within cardiology. The bibliometric analysis involves a statistical and quantitative evaluation of the literature on AI application in cardiovascular medicine over a defined period. A comprehensive global literature review is conducted to identify key research areas, authors, and their interrelationships through published works. The leading institutions and most influential authors in research on the role of AI in cardiology were located in the United States, the United Kingdom, and China. This study also provides researchers with an overview of the evolution of research in AI and cardiology. The main contribution of this study is to highlight the prominent authors, countries, journals, institutions, keywords, and trends in the development of AI in cardiology.

In this paper, the application of Artificial intelligence (AI) methods in power system protection and inspection has been discussed. In this paper particularly AI application of line scout Robot is used. Line scout robot is an inspection based Artificial intelligence Robot. Line Scout robot is able to work on the power lines while they are operating (at very high tension). The robot can patrol in a substation and inspect equipment with a visible-light camera and thermograph. It has possess a vast array of cameras and tools that allow the remote operators to inspect and conduct (albeit minor) repairs on the power lines without needing to put the off-service or risking their lives. It is preventive arrangement for detection of fault (very high temperature). Keywords: Artificial intelligence (AI), artificial general intelligence (AGI), corona pulse, Line Scout Robot, power system

The fast advancement of artificial intelligence (AI) technologies in recent years, especially the deep learning algorithm and transformer neural network, has brought great impacts on scientific researches. As a displine focusing on curation and analysis of life science data, bioinformatics has experienced remarkable changes under the impetus of AI technologies, not only in nowadays, but also throughout its history. In this review, we firstly summarize the historical events of computer-assisted life science data analysis, then assess the features, contributions and changes of AI methods in life science research through bibliometric analysis, and discuss the future challenges for AI methods from the life science research aspects. It is no doubt that AI technologies will continuously accelerate and revolutionize life science research in the future, in the meanwhile, the development of new AI methods more suitable for life science data is also in great needs.

The recent mainstreaming of Artificial Intelligence (AI) applications and tools has significantly enhanced EFL educators’ research writing process. Nevertheless, few studies exist regarding how EFL educators understand AI applications and their integration into research writing processes and techniques. The current study aims to investigate the attitudes and perceptions of (n= 40) EFL teachers at Majmaah University concerning integrating AI tools in the Research writing process, by collecting data from mixed-methods source questionnaires and interviews. Thematic analysis was employed for qualitative data, while descriptive and inferential statistics through SPSS were used for quantitative data analysis. The questionnaire results demonstrated that most respondents have positive perceptions toward integrating AI tools, believing they can improve efficiency and quality in the research writing process. However, more familiarity with existing AI applications is needed to ensure this integration process. Moreover, the study affirms the significant impact of training and support on the effective integration of AI tools. Respondents strongly agree about the benefits of AI applications in streamlining literature reviews, aiding in data analysis, reducing errors, and enhancing overall language quality. Interview responses further emphasize the possible benefits of AI tools in the research writing process, highlighting efficiency gains, assistance in various writing tasks, and improved quality of EFL teachers’ research articles. All the participants stress the importance of ethical utilization, maintaining quality, and vigilance when integrating these tools into the research writing process.