This study presents a comprehensive analysis of recent mental illness research by utilizing an advanced bibliographic method capable of analyzing up to 12,965 papers indexed in the Web of Science database, overcoming the limitations of traditional tools like VOSviewer, which typically analyze fewer than 1,000 papers. By examining a vast dataset, this study identifies key trends, significant keywords, and prominent contributors, including leading researchers, universities, and countries/regions, in the field of mental illness research. Additionally, the study highlights eight major contributors to mental health problems, offering critical insights into the field’s current state. The findings underscore the importance of advanced bibliographic methods in providing a more detailed and accurate overview of mental illness research. This analysis not only enhances the understanding of young scholars entering the field but also uncovers significant trends and identifies notable gaps in the literature. The study advocates for continued innovation and interdisciplinary collaboration to deepen understanding and address unresolved challenges in mental health research.

A biofilm refers to an intricate community of microorganisms firmly attached to surfaces and enveloped within a self-generated extracellular matrix. Machine learning (ML) methodologies have been harnessed across diverse facets of biofilm research, encompassing predictions of biofilm formation, identification of pivotal genes and the formulation of novel therapeutic approaches. This investigation undertook a bibliographic analysis focused on ML applications in biofilm research, aiming to present a comprehensive overview of the field’s current status. Our exploration involved searching the Web of Science database for articles incorporating the term “machine learning biofilm,” leading to the identification and analysis of 126 pertinent articles. Our findings indicate a substantial upswing in the publication count concerning ML in biofilm over the last decade, underscoring an escalating interest in deploying ML techniques for biofilm investigations. The analysis further disclosed prevalent research themes, predominantly revolving around biofilm formation, prediction and control. Notably, artificial neural networks and support vector machines emerged as the most frequently employed ML techniques in biofilm research. Overall, our study furnishes valuable insights into prevailing trends and future trajectories within the realm of ML applied to biofilm research. It underscores the significance of collaborative efforts between biofilm researchers and ML experts, advocating for interdisciplinary synergy to propel innovation in this domain.

The changes implemented in 2005 in the development strategies of Antarctic science carried out by Chile have had a positive impact on the scientific productivity of the Chilean Antarctic Science Program (PROCIEN). We analysed scientometric indicators from between 2009 and 2019. The bibliographic data were extracted from the Web of Science database using search query keywords. We used multiple correspondence analysis to identify specific trends and also network analyses of international collaboration in VOSviewer. The number of Antarctic science publications in Chile has gradually increased from 21 in 2009 to 95 in 2019. The rise in the number of articles was higher in journals for the first impact factor quartile. Research lines showing increased first-quartile impact factor papers corresponded to Antarctic ecosystems, biotechnology and geosciences. The main geographical domains in which such research activities have been carried out corresponded to in the South Shetland Islands and the Antarctic Peninsula. Fieldwork data are the main sources for the production of scientific articles, and there are three science platforms within which most of these papers concentrate. The diversification of funding sources, the implementation of improvements in the selection process and Chile's alignment with Scientific Committee on Antarctic Research programmes have contributed to improving the science that Chile has developed in Antarctica.

The pressure to distinguish high quality from lower quality law journals is intensifying. To contribute to this debate, citation-based and peer review-based ranking of law journals are paralleled in the paper, using qualitative and quantitative analysis. It is found that all law journals that are considered as journals of the highest quality by legal experts are also ranked highly in Web of Science (WoS) and that 40% of the law journals categorised as ‘internationally leading’ by the peers are not listed in WoS. This paper explores what the editors of some of the internationally leading law journals that are not listed in the WoS think about applying to be listed in it. The paper offers data to support the contention that legal scholarship is characterised by regionalism in academic publishing and citation patterns. It is submitted that there is no perfect indicator of quality, and that no evaluation system will ever convince every legal scholar in the world of its value. WoS could be adopted as a rigorous and internationally recognised index for law journals only if it were aligned more closely with the Leiden Manifesto.