HIV-1 genetic diversity a challenge for AIDS vaccine development: A retrospective bibliometric analysis

Background: Despite recent advances in human immunodeficiency virus-1 (HIV-1) prevention, a fast, safe, and effective vaccine will probably be necessary to end the HIV/AIDS pandemic. This study was conducted to evaluate global research trends and map the key bibliometric indices in HIV-1 genetic diversity from 1998 to 2021.Methods: A comprehensive online search was conducted in the Web of Science Core Collection database to retrieve published literature on HIV-1 genetic diversity. Key bibliometric indicators were calculated and evaluated using HistCiteTM, Bibliometrix: An R-tool, and VOSviewer software for windows.Results: A total of 2,060 documents written by 9,201 authors and published in 250 journals were included in the final analysis. Year 2012 was the most productive year with 121 (5.87%) publications. The most prolific author was Shao Yiming (n = 74, 3.59%) from Chinese Center for Disease Control and Prevention. The United States of America was the highly contributing and influential country (n = 681, 33.05%). AIDS Research and Human Retroviruses was the most productive journal (n = 562, 27.2%). Network visualization shows that HIV-1 was the most widely used author keyword.Conclusion: This study provides global research trends and detailed information on HIV-1 genetic diversity. The amount of scientific literature on HIV-1 genetic diversity research has rapidly increased in the last two decades. The maximum number of articles on HIV-1 genetic diversity was published in developed countries; therefore, a scientific research collaboration among researchers and institutes in low-income countries should be promoted and supported

Research community dynamics behind popular AI benchmarks

[EN] The widespread use of experimental benchmarks in AI research has created competition and collaboration dynamics that are still poorly understood. Here we provide an innovative methodology to explore these dynamics and analyse the way different entrants in these challenges, from academia to tech giants, behave and react depending on their own or others' achievements. We perform an analysis of 25 popular benchmarks in AI from Papers With Code, with around 2,000 result entries overall, connected with their underlying research papers. We identify links between researchers and institutions (that is, communities) beyond the standard co-authorship relations, and we explore a series of hypotheses about their behaviour as well as some aggregated results in terms of activity, performance jumps and efficiency. We characterize the dynamics of research communities at different levels of abstraction, including organization, affiliation, trajectories, results and activity. We find that hybrid, multi-institution and persevering communities are more likely to improve state-of-the-art performance, which becomes a watershed for many community members. Although the results cannot be extrapolated beyond our selection of popular machine learning benchmarks, the methodology can be extended to other areas of artificial intelligence or robotics, and combined with bibliometric studies.F.M.-P. acknowledges funding from the AI-Watch project by DG CONNECT and DG JRC of the European Commission. J.H.-O. and S.O.h. were funded by the Future of Life Institute, FLI, under grant RFP2-152. J.H.-O. was supported by the EU (FEDER) and Spanish MINECO under RTI2018-094403-B-C32, Generalitat Valenciana under PROMETEO/2019/098 and European Union's Horizon 2020 grant no. 952215 (TAILOR).Martínez-Plumed, F.; Barredo, P.; Ó Héigeartaigh, S.; Hernández-Orallo, J. (2021). Research community dynamics behind popular AI benchmarks. Nature Machine Intelligence. 3(7):581-589. https://doi.org/10.1038/s42256-021-00339-6S5815893

Global Ranking of Management- and Clinical-centered E-health Journals

This study presents a ranking list of 35 management- and 28 clinical-centered e-health academic journals developed based on a survey of 398 active researchers from 46 countries. Among the management-centered journals, the researchers ranked Journal of the American Medical Informatics Association and Journal of Medical Internet Research as A+ journals; among the clinical-focused journals, they ranked BMC Medical Informatics and Decision Making and IEEE Journal of Biomedical and Health Informatics as A+ journals. We found that journal longevity (years in print) had an effect on ranking scores such that longer standing journals had an advantage over their more recent counterparts, but this effect was only moderately significant and did not guarantee a favorable ranking position. Various stakeholders may use this list to advance the state of the e-health discipline. There are both similarities and differences between the present ranking and the one developed earlier in 2010

ARTIFICIAL INTELLIGENCE AND AGENT TECHNOLOGY MADE EASY

Artificial intelligence (AI) is the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior. Major AI researchers and textbooks define this field as "the study and design of intelligent agents", in which an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955, defines it as "the science and engineering of making intelligent machines". AI research is highly technical and specialized, and is deeply divided into subfields that often fail to communicate with each other. Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. Some subfields focus on the solution of specific problems. Others focus on one of several possible approaches or on the use of a particular tool or towards the accomplishment of particular applications. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. General intelligence is still among the field's long-term goals. Currently popular approaches include statistical methods, computational intelligence and traditional symbolic AI. There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. The AI field is interdisciplinary, in which a number of sciences and professions converge, including computer science, mathematics, psychology, linguistics, philosophy and neuroscience, as well as other specialized fields such as artificial psychology. This article is prepared based on the Author’s teaching the subject for M.Tech level recent years, keeping in view of VTU Syllabus in particular

Challenges and Opportunities in Applied System Innovation

This book introduces and provides solutions to a variety of problems faced by society, companies and individuals in a quickly changing and technology-dependent world. The wide acceptance of artificial intelligence, the upcoming fourth industrial revolution and newly designed 6G technologies are seen as the main enablers and game changers in this environment. The book considers these issues not only from a technological viewpoint but also on how society, labor and the economy are affected, leading to a circular economy that affects the way people design, function and deploy complex systems

Cognitive Foundations for Visual Analytics

In this report, we provide an overview of scientific/technical literature on information visualization and VA. Topics discussed include an update and overview of the extensive literature search conducted for this study, the nature and purpose of the field, major research thrusts, and scientific foundations. We review methodologies for evaluating and measuring the impact of VA technologies as well as taxonomies that have been proposed for various purposes to support the VA community. A cognitive science perspective underlies each of these discussions