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Mid-field wireless power transfer (WPT) offers a compelling solution for delivering power to miniature implantable medical devices deep within the human body. Despite its potential, the current power delivery levels remain constrained, and the design of a compact source structure to focus the transmitter field on such implants presents significant challenges. In this paper, a novel miniaturized transmitter antenna operating at 1.71 GHz is proposed. Leveraging the antenna proximity-coupled feeding technique, we achieve optimal current distribution for efficient power transfer. Additionally, a receiver integrated within the human body is proposed, comprising a slotted ground and a meandering slotted radiating element. This receiver is excited via a coaxial feedline with a truncated ground. Our findings demonstrate wireless power transfer of −23 dB (0.501%) at a distance of 30 mm between the transmitter and receiver, alongside a peak gain of −20 dB with an impedance bandwidth of 39.61%. These results highlight promising advancements in enhancing energy transfer efficiency for deep-implant applications. [ABSTRACT FROM AUTHOR]

Background: The emergence of the artificial intelligence chatbot ChatGPT in November 2022 has garnered substantial attention across diverse disciplines. Despite widespread adoption in various sectors, the exploration of its application in libraries, especially within the medical domain, remains limited. Aims/Objectives: Many areas of interest remain unexplored like ChatGPT in medical libraries and this review aims to synthesise what is currently known about it to identify gaps and stimulate further research. Methods: Employing Cooper's integrative review method, this study involves a comprehensive analysis of existing literature on ChatGPT and its potential implementations within library contexts. Results: A systematic literature search across various databases yielded 166 papers, with 30 excluded for irrelevance. After abstract reviews and methodological assessments, 136 articles were selected. Critical Appraisal Skills Programme qualitative checklist further narrowed down to 29 papers, forming the basis for the present study. The literature analysis reveals diverse applications of ChatGPT in medical libraries, including aiding users in finding relevant medical information, answering queries, providing recommendations and facilitating access to resources. Potential challenges and ethical considerations associated with ChatGPT in this context are also highlighted. Conclusion: Positioned as a review, our study elucidates the applications of ChatGPT in medical libraries and discusses relevant considerations. The integration of ChatGPT into medical library services holds promise for enhancing information retrieval and user experience, benefiting library users and the broader medical community. [ABSTRACT FROM AUTHOR]

Background and Aim: Foot-and-mouth disease (FMD) is an infectious disease of cloven-hoofed animals, including buffalo, cattle, sheep, goats, and pigs, causing major economic losses to the local farmers and, overall, to the national economy of the country. This study aimed to detect FMDV serotypes in year-round FMD outbreaks, hematological and biochemical changes, and oxidative stress in FMDV-infected cattle and buffaloes in the district of Quetta, Balochistan, Pakistan, and the socioeconomic impact of FMD outbreaks on farmers. Materials and Methods: We conducted a cross-sectional study in the district of Quetta, Balochistan, Pakistan, where FMD virus (FMDV) serotypes were detected by enzyme-linked immunosorbent assay (ELISA). Hematological, biochemical, and oxidative analyses were performed by analyzing the blood of FMDV-infected and non-infected animals. Information on the associated risk factors was obtained through a structured questionnaire by interviewing farmers in each FMD-affected farm. Results: Thirty-four out of 38 farms (89%, 95% confidence interval [CI]: 75%-97%) were positive for FMD by ELISA. Higher FMD infection was detected in farms with a herd size of <50 animals (50%, 17/34), followed by >100 animals (32%, 11/34) and 51-100 animals (18%, 6/34). Fifty-seven percent (114/200, 95% CI: 50%-64%) of animals were positive for FMD. Of these, 61% (69/114) were cattle and 39% (45/114) were buffalo. FMD positivity was higher in females (86%, 98/114) than in males (14%, 16/114) and higher in animals older than 2 years of age (52%, 59/114). On average, farmers lose U.S. dollars 3000 annually due to FMD outbreaks. Animals infected with FMDV had significantly (p ≤ 0.05) white blood cell counts and significantly (p ≤ 0.05) lower hemoglobin and total protein concentrations in buffalo and cattle, whereas infected cattle showed significantly (p ≤ 0.05) lower albumin levels. Globulin levels were lower in buffaloes infected. Alanine aminotransferase levels were lower in infected cattle (p ≤ 0.05). Creatinine levels were higher in infected buffalo (p ≤ 0.05). Urea and phosphorus concentrations were higher in FMDV-infected cattle and buffalo (p ≤ 0.05). Calcium levels were lower in infected cattle and buffalo (p ≤ 0.05). Catalase enzyme activity in infected cattle and buffaloes was significantly lower (p < 0.05). Lipid peroxidation was significantly higher in FMDV-infected cattle and buffalo (p ≤ 0.05). Conclusion: This study confirmed serotype O circulation among cattle and buffalo in year-long FMD outbreaks in the Quetta District of Balochistan. Blood analysis identified a parameter deviated from the normal level due to FMDV infection. In addition, the outbreak of FMD has a significant negative economic impact on livestock farmers. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the research and citation impact of open access (OA) journals versus non-OA journals being published in the spectrum of library and information science (LIS) across the world and to further ascertain whether OA journals have greater citation counts than subscription-based journals in LIS discipline. Design/methodology/approach: A total of 116 LIS journals (58 OA and 58 non-OA) were chosen from Scimago website. After selecting the journals, Publish or Perish software program was used to retrieve the publications and their corresponding academic citations by using International Standard Serial Number of journals from Google Scholar for the period of 2011–2018. The non-parametric Mann–Whitney U-test was applied on various research and citation indicators, namely, citation count, citations per author, citations per paper; g-index, h-index, hI norm and hI annual through SPSS. Findings: Findings of the study demonstrate that non-OA journals in LIS have a significant citation advantage over OA journals. Moreover, Mann–Whitney U-test analysis rejected all the eight null hypotheses and reveals that non-OA journals in LIS discipline have greater citation counts, citations per author, citations per paper; g-index, h-index, hI norm and hI annual than OA journals. Originality/value: To the best of the authors' knowledge, this is the first study that embarks upon a whole-scale investigation of citation impact of OA and non-OA journals in LIS, which has implications for both research and practice. This study would serve as a reference guide to all involved in scholarly communication activities including academic communities, librarians, research funders, publishers and policymakers for publishing research work, grant funding, designing policies and subscriptions. [ABSTRACT FROM AUTHOR]

This article aims to identify the factors prevalent among health science librarians toward vaccine hesitancy. With the development of COVID-19 vaccines in 2021, numerous efforts are being taken to vaccinate people to control the spread of coronavirus. Recent research has shown a high level of vaccine hesitancy among various groups in various fields but no study has been conducted to explore the factors responsible for vaccine hesitancy among library professionals. A cross-sectional online survey of Indian health science librarians was conducted. Data was collected through an online questionnaire designed on Google Forms and analyzed using MS-Excel. Descriptive statistics were used in the study. The majority of respondents (77%) showed a high level of vaccine hesitancy due to issues of safety, negative information, and confusion over vaccines. Measures to increase vaccination uptake and authentic sources with respect to COVID-19 vaccines have been discussed. [ABSTRACT FROM AUTHOR]

The study presents an overview of global research output on the Bacille Calmette-Guerin (BCG) vaccine from 1989–2021 using various scientometric indicators. The objective is to inform and present a comprehensive analysis of BCG vaccine research to health practitioners, researchers, and librarians that has not been explored from the perspective of scientometrics. Using a search strategy, data was collected from the Web of Science database and 2416 original articles were identified. Computed analysis of the literature was done through the software bibloshiny (a web interface for bibliometrix analysis) in the R statistical programming environment. The study examined the pattern of growth of research output, prolific authors, institutions, key journals, and countries involved in BCG vaccine research. Findings reveal an increase in research output on BCG vaccine from 2008 onwards. The highest number of articles 163 were published in 2016. Key journals, authors, and institutions working in the field of BCG vaccine research have been identified. A Sankey diagram has been used to depict the evolution of BCG vaccine research. This article reports the evolution of BCG vaccine research in terms of annual growth of publications, relevant authors, institutions, countries, and the evolution of author keywords and the growth of BCG vaccine research areas. [ABSTRACT FROM AUTHOR]

Cloud computing is an interdisciplinary field which has witnessed exponential growth in recent years and there is a need to consolidate the research efforts. This study used citation analysis method to identify most cited papers which have achieved the status of citation classics. It is the first study using Dimensions.ai database to identify classics in cloud computing literature. Using a search strategy data was extracted from Dimensions database from 2010 and 2020. Finally 96 papers were identified as citation classics which were cited with at least 400 citations. Data was finally analyzed through Biblioshiny package of R Studio. It was found that Future Generation Computer Systems, IEEE Communication Survey and Tutorials, IEEE Transaction on Parallel and Distributed Systems, Computer and IEEE Access are the key journals contributing to classics. Most papers were contributed from China and USA. R. Buyya is the prolific author who has contributed nine citation classics. [ABSTRACT FROM AUTHOR]

Background: As of October 1, 2020, World Health Organization (WHO) reports that COVID-19 has spread in 216 countries or territories or areas which results into throwing billions of lives under lockdown as healthcare services struggle to cope. Therefore, timely access to healthcare information during COVID-19 crisis is mandatory to restrain its spread. Objectives: To comprehend the information needs and seeking behaviour of general public during COVID-19 outbreak in India. Methods: A national survey through an online questionnaire was conducted in India and 1310 respondents participated in the study through snowball sampling technique. Results: The most decisive information needs of majority of respondents were COVID-19 signs and symptoms, causes and treatments of illness, prevention and control of COVID-19. Conspicuously, news websites, dedicated websites of coronavirus and medical staff were the most preferred and trustworthy sources of information related to COVID-19. Furthermore, credibility or authenticity of information was identified as the major problem in seeking COVID-19 information. Conclusion: The study's findings provide insight into the spectrum of health information seeking among general public in India during COVID-19 outbreak. This study may be useful to social welfare and government health departments, hospitals, and health-information communicators engaged in public safety and well-being in India. [ABSTRACT FROM AUTHOR]

The aim of this research paper is to investigate the knowledge management strategies adopted by the libraries of central universities in India. Review of literature, reveals that codification and personalisation have been considered knowledge management strategies for sharing explicit and tacit knowledge within the library system. To determine the most used knowledge management strategies in libraries, 14 tools (seven each for codification and personalisation) were recognised from the literature review and taken for examination. A total of 116 library and information science professionals of 23 central universities spread across India were surveyed through a web-based questionnaire to explore the knowledge management strategies followed and data analyses were conducted by using SPSS version 22.0. The findings of the research show that both codification and personalisation have been used in libraries, though the balance of codification and personalisation was not in 80-20 ratio. Between codification and personalisation, codification was found to be the most useful strategy with collective mean difference, i.e., 0.312. This study has practical implications for those who are not fully aware of the prominence of knowledge management and how knowledge management strategies can be used to gain a competitive advantage. [ABSTRACT FROM AUTHOR]

Accurately predicting the Modulus of Resilience (MR) of subgrade soils, which exhibit non-linear stress–strain behaviors, is crucial for effective soil assessment. Traditional laboratory techniques for determining MR are often costly and time-consuming. This study explores the efficacy of Genetic Programming (GEP), Multi-Expression Programming (MEP), and Artificial Neural Networks (ANN) in forecasting MR using 2813 data records while considering six key parameters. Several Statistical assessments were utilized to evaluate model accuracy. The results indicate that the GEP model consistently outperforms MEP and ANN models, demonstrating the lowest error metrics and highest correlation indices (R2). During training, the GEP model achieved an R2 value of 0.996, surpassing the MEP (R2 = 0.97) and ANN (R2 = 0.95) models. Sensitivity and SHAP (SHapley Additive exPlanations) analysis were also performed to gain insights into input parameter significance. Sensitivity analysis revealed that confining stress (21.6%) and dry density (26.89%) are the most influential parameters in predicting MR. SHAP analysis corroborated these findings, highlighting the critical impact of these parameters on model predictions. This study underscores the reliability of GEP as a robust tool for precise MR prediction in subgrade soil applications, providing valuable insights into model performance and parameter significance across various machine-learning (ML) approaches. [ABSTRACT FROM AUTHOR]

Venezuelan equine encephalitis virus (VEEV) is an arbovirus that is associated with robust inflammation that contributes to neurodegenerative phenotypes. In addition to triggering central nervous system (CNS) inflammation, VEEV will also induce mitochondrial dysfunction, resulting in increased cellular apoptosis. In this study, we utilize the TC-83 strain of VEEV to determine the role of mitochondrial oxidative stress in mediating inflammation elicited by murine brain microglial cells. Using an in vitro model, we show that murine microglia are susceptible to TC-83 infection, and that these cells undergo mitochondrial stress as the result of infection. We also indicate that bystander microglia contribute more significantly to the overall inflammatory load than directly infected microglia. Use of a mitochondrial targeted antioxidant, mitoquinone mesylate, greatly reduced the pro-inflammatory cytokines released by both direct infected and bystander microglia. Our data suggest that release of interleukin-1β, a key instigator of neuroinflammation during VEEV infection, may be the direct result of accumulating mitochondrial stress. This data improves our understanding inflammation elicited by murine microglia and will aid in the development of more accurate in vitro and in vivo murine model of VEEV-induced neuroinflammation. [ABSTRACT FROM AUTHOR]