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Identifying trends in research through co-citation or content analysis of journal contents is quite a common practice in LIS research. In this study, however, we proposed the Latent Dirichlet Allocation (LDA), a popular topic-modeling approach for identifying research trends of published articles in three scopus-indexed Indian LIS journals. A total of 1213 titles & their abstracts published between 2011 and 2022 have been considered. From these data, a corpus of frequently used 15 key phrases was identified from each journal using Count Vectorizer and then ten topics having higher coherence scores were extracted from each journal corpus using LDA techniques to understand to what extent these topics are different in these journals. The analysis of the study indicates that 'Library users' studies' especially in academic libraries; and 'bibliometric indicators for measuring research growth are a few common topics in these journals and, technological innovation; utilisation of electronic and print information resources; library management; or network analysis are some of the topics that are journal specific. From the t-SNE visualisation and pyLDAvis diagram, it was seen that the topics of DJLIT are significantly unique with discrete distributions than the other two journals. On analysing the growth of the top ten topics longitudinally, it was seen that research on digital libraries, analysing the global output, online search strategy, ranking universities, etc. are concurrent interests of research among researchers while academic library resources, including electronic resources and its use, open access are among diminishing research interests of authors. Since the topic-modeling approach can provide results devoid of bias, it can be used to identify research land scape longitudinally as well as obsolescence of topic in a domain. [ABSTRACT FROM AUTHOR]

The present study extract, map and compare the lexical and semantic similarity of terms from author-provided keywords with machine extracted terms and topics from titles and abstracts of an inter-disciplinary field like 'digital humanities'. Author-provided terms (keywords) were first extracted and mapped through visualization software like Gephi and then these extracted terms were compared with terms extracted from title and abstract of the research articles through NLP based statistical modules. Also, the interdisciplinary of significant topics were measured through the Brillouin index. A set of 7483 articles downloaded from Scopus database on the domain of digital humanities and its associated fields were used for the purpose. We observed the researches on digital humanities are spread over a considerable number of concepts like 'Industry 4.0', 'topic modelling, 'open science'. Further, the machine algorithm-based extraction compared and identified a larger lexical similarity between these author-provided keywords and title-extracted keywords, rather than abstract-extracted keywords. Jaccard similarity of all author-keywords with machine extracted title keywords came 0.83 and SBERT BiEncoder_score was 0.7374. The top research areas extracted from titles, through unsupervised approach of term extraction resulted in topics like digital humanities approach, digital humanities visualization, indicating a strong connection to the discipline of digital humanities. The average interdisciplinarity index of top significant topics came between 1.217 and 1.284, with the highest index value for 'computational digital humanities'. As this study is based on real-world data, it is highly useful to understand how far machine algorithm-based text extraction can be helpful for information retrieval process. [ABSTRACT FROM AUTHOR]

Keyword extraction is the task of identifying important terms or phrase that are most representative of the source document. Although the process of automatic extraction of keywords from title is an old method, it was mainly for extraction from a single web document. Our approach differs from previous research works on keyword extraction in several aspects. For those who are non-expert of the scientific fields, understating scientific research trends is difficult. The purpose of this study is to develop an automatic method of obtaining overviews of a scientific field for non-experts by capturing research trends. This empirical study excavates significant term extraction using Natural Language Processing (NLP) tools. More than 15000 titles saved in a .csv file was our dataset and scripts written in Python were our process to compare how far significant terms of scientific title corpus are similar or different to the terms available in the abstract of that same scientific article corpus. A light-weight unsupervised title extractor, Yet Another Keyword Extractor (YAKE) was used to extract the results. Based on our analysis, it can be concluded that these algorithms can be used for other fields too by the non-experts of that subject field to perform automatic extraction of significant words and understanding trends. Our algorithm could be a solution to reduce the labour-intensive manual indexing process. [ABSTRACT FROM AUTHOR]

The purpose of this study is to connect the perceptions and understanding of the collaboration of faculty members of NIRF ranked top-performing engineering institutes with the publication they have. The quantitative bibliometric analysis along with the enquiry with authors show that national collaboration, mainly with academic authors of same or other institution, still is a preferred. Despite international collaboration leading to more average citations, there is no significant gain seen. Scholars collaborate for many reasons, but mostly to gain popularity among peers or to receive citation benefits. Collaboration with private or government organizations, although uncommon, is primarily used to test newly developed ideas or to provide consultancy. Most of the respondents believe that funding is important for research collaborations and low commitment of team members to the shared goal is a major barrier in collaboration. We argue that as the share of University-Industry-Government research collaborations is low, a strong congruence between knowledge capital and entrepreneurial capital is needed to develop an entrepreneurial university. [ABSTRACT FROM AUTHOR]

The present study explores the patenting activities of the faculty staff of the top 20 Indian academic and engineering institutes during 2011-2020 by excavating the Indian patent office database. Of the total 963 granted patents, the highest patents were published in 2016, and the academician of IIT Madras invented 167 patents followed by IIT Mumbai with 156 patents during this period. Most of the innovation takes place in the macro-field like chemical engineering, and micro-fields like nano-technology, nano-materials, and nano-complex. Collaboration with inventors of the same academic institution is found as the best choice of the inventors, only a meagre portion of patents was published in collaboration with of industries and organisations around the globe. The tag ‘highest number of patents inventor’ goes to Padma Shri Prof. Thalappil Pradeep of IIT Madras who has contributed 19 Indian patents in the last 10 years. [ABSTRACT FROM AUTHOR]

Information and Communication Technology (ICT) has changed the traditional way of learning into digital way of learning. It has enhanced the learning activity of academicians not only of universities but also of colleges. College Libraries have now been subscribing electronic resources for the past few years. Libraries of the colleges are now being automated and they are moving towards virtual libraries/e-libraries. Resources like electronic books, electronic journals, online databases, electronic reference sources etc. have now become an important part of college libraries. College/Academic libraries are fundamental part of higher education system and it must have the relevant resources for their users. This study examines the electronic resources and Internet being consumed by the students and faculty members of Udai Pratap Autonomous College. The core objectives was that how the faculty members and students of this college face the problem while accessing online resources, how they take advantages of online resources, how much they are aware towards online resources and how much more do they prefer online resources than conventional resources. In this regards, a total 200 faculty members and students were selected to fill up the questionnaire prepared on Google form. Out of 200 respondents, only 160 responses had been received. Whatever interesting results were collected was analysed. [ABSTRACT FROM AUTHOR]

This study examines the contributions of women scientists currently working in various research organizations under the Ministry of Science and Technology, India. Women scientists were identified through the official websites of the research laboratories and their publication performance has been tracked using the Scopus database. There are 901 women scientists working in 78 research organizations under the Ministry and have published 21810 publications up to December 2019, almost 65 percent of which has been appeared during 2010 to 2019. The publication per scientist has risen from 6.85 article per year before 2000 to 10.45 paper in 2015-2019 which indicates increasing participation of women in science from India. Women scientists are primarily engaged in biological sciencesresearch, however fields such as materials sciences, nano-technology, and astrophysics are also becoming the preferred subject choices among women. Women scientists mostly published their articles as a member of a team of utmost 10 authors, however, their position in multi-authored articles is mostly as co-authors than that of principal authors. Women in the age group of between 31 to 40 produced maximum publications, and almost 98 percent of publications appeared in collaboration with other scientists. This study confirms that publication productivity does not decline with age. There are women scientists who stay active in research and keep their productivity at a high level until their retirement. The study suggests that the increasing participation of women in Indian science is encouraging, as such more funding opportunities to younger women researchers may be important to give them more lead time to build a strong career. [ABSTRACT FROM AUTHOR]

The present study employs bibliometric methods to examine the pattern of existing collaboration in India's top three ranked academic institutes using publications indexed in the Web of Science for the period 2000 to 2020. The results show although the number of collaborations and the degree of collaboration have increased over time, however, the collaboration coefficient remains almost the same in the three institutes. The lesser negative Pearson correlation between authors and articles with a higher positive Pearson correlation between articles and citations for JNU publications suggests that collaboration with a smaller group is more successful than a larger group for gaining citations. Collaborative publications of Banaras Hindu University (36%) and Indian Institute of Science (33%) are more inclined towards authors of the same department, while for Jawaharlal Nehru University, it is with other authors from different universities (41%). The foreign collaboration for all three institutes is almost the same. The network visualization of collaboration in three institutes suggests that the collaborative research in IISc is more diverse than JNU or BHU and in national collaboration, distance between two national organizations also play an important role for strong collaboration. Overall, theoretical aspects of physics lead in collaborative publications followed by chemical sciences. Agricultural biotechnology, clinical medicine, polymer sciences and nanoscience are some emerging disciplines where organizations are increasing their participation through collaborative research. [ABSTRACT FROM AUTHOR]

This study investigates the effect of scientific position, service tenure, and age of women scientists of various research laboratories of the Ministry of Science and Technology, Government of India on the research productivity. Drawing on a sample of 902 women scientists of various research laboratories, with their 22,617 publications extracted from Web of Science & Scopus databases, the results show that CSIR scientists have more women per laboratory, DST women scientists have more publication per scientists and DBT women scientists received more citations. The majority of the publications were published by scientists who have post-doctoral or doctorate degrees and most of the papers were published by the women scientists between age 31 and 40. However, per scientist publication reveals that there is a continuous increase of publication with the increase of service and physical age. Therefore, better funding opportunities for young researchers and retaining experienced women scientists for more years may be important to increase women's participation in science. [ABSTRACT FROM AUTHOR]

Venous thromboembolic disease presenting with acute pulmonary embolus (PE) can be treated in a variety of ways from anticoagulation as an outpatient to surgical embolectomy with many new interventional therapies being developed. Mortality in these patients can be as high as 50% and many of these treatments are also considered to be high risk. Early involvement of a multidisciplinary team and patient risk stratification can aid management decisions in these complex patients who can suddenly deteriorate. In this review, we summarise the evidence behind new and developing interventional therapies in the treatment of high and intermediate‐high risk PE including catheter‐directed thrombolysis, pharmacomechanical thrombolysis, thromboaspiration and the growing role of extracorporeal membrane oxygenation in the stabilisation and management of this cohort of patients. [ABSTRACT FROM AUTHOR]

Photon radiation induced decolourisation of radiochromic film changes its optical density. The photon dose is thereby evaluated as a function of optical density. The detection limit of common radiochromic films lies between 1 cGy and 20 Gy. This paper describes a novel evaluation method of radiochromic films using cosine-distance analysis of the RGB-colour vectors instead of conventional optical density measurements using a scanner in transmission mode. This allows extending the detection limit to excess of 40 Gy. • Gaf-EBT3 radiochromic films exposed to photons from 6 MV linac. • RGB colour histogram constructed using ImageJ program. • Cosine-distance (CD) calculated using RGB colour vectors. • Photon doses presented as a function of CD. [ABSTRACT FROM AUTHOR]

Background Patients with major depressive disorder have varying response rates to treatment. Multiple factors such as non-adherence, comorbidity, chronic stressors, and biological factors may be responsible for this variation. Inflammatory (pro and anti) markers have been well studied as a cause for depression, predisposing factors, and a consequence of depression. Among these, interleukins (ILs), interferons, C-reactive protein (CRP), and tumor necrosis factor-alpha (TNF-α) have been studied repeatedly. We conducted a pilot study to assess the levels of these inflammatory markers in patients with major depressive disorder. The specific objectives of this study were to compare and correlate changes in pro- and anti-inflammatory markers throughout different phases of depression, including pretreatment and posttreatment periods, and to evaluate the pattern of pro- and anti-inflammatory markers in patients who experienced remission or showed a positive response to treatment. Methodology This was a prospective, clinic-based, cohort study done for a period of one and a half years. Patients aged 18-65 years with depressive disorder per the International Classification of Diseases Tenth Edition and who scored more than 7 on the Hamilton Depression Rating Scale were included in this study. A total of 81 patients were recruited who were followed up till eight weeks after inclusion. A total of 31 patients completed the eight weeks of follow-up. Levels of IL-10 and TNF-α were assessed at baseline, two weeks, four weeks, and eight weeks of follow-up. Results This study tried to compare the levels of pro- and anti-inflammatory markers across pretreatment and various posttreatment phases of depression. Results showed that the levels of pro-inflammatory cytokine TNF-α increased from baseline till eight weeks of follow-up, and levels of IL-10 decreased from baseline till eight weeks of follow-up. However, these changes were not statistically significant. Conclusions This study supports the hypothesis that inflammatory markers can be trait markers of depression rather than the consequence or result., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Mandal et al.)