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The study aims to present an insight into the research landscape of Library and Information Science (LIS) by India using a bibliometric visualization tool. The study analyses the research growth and trends, highly cited articles, productive publication titles, institutional and country collaboration.

The data were downloaded from the Web of Science Core Collection for a period of 20 years and analysed through VOSviewer, a data visualization software.

The results indicate that the overall annual contributions are increasing, although with uneven and slow growth from 2001 to 2014. However, the highest contributions and impact is witnessed over the past few years. All the top 10 cited papers are related to the area of information processing and management. The visualization technique made it clear that the area of research has made a transition from traditional concepts of library and information to novel ones involving big data, machine learning, altmetrics, etc. Also, the Indian Institute of Technology System, the Council of Scientific and Industrial Research and the Indian Institute of Management System have made the highest contributions. Furthermore, India shares maximum collaborations with the USA, followed by England and China.

The findings of this study would help readers to gain understanding about the contribution of India for the development of the LIS. It would also help researchers to identify the hotspots and left out areas of research in the Indian context that require further investigation, thus would help in policy decisions and future research. Furthermore, researchers will be sensitized about the network visualizations that can also help them to get connected with the peers. The study can also help the journals to recognize the trending topics, which will provide the researchers with the opportunities to work on the same. Funding agencies can also be benefitted by the findings of the current study as they will be informed about the research areas which need to be funded.

There are not many research studies that highlight the research trends in the area of LIS from India and visualize the collaboration among institutions and countries. The study tries to showcase the research trends and collaborative frameworks in the field of LIS in terms of network visualization.

This paper seeks to revisit the interrelationship among tourists’ perceived value of the destination, tourist satisfaction and destination loyalty in the heritage tourism site of Hoi An. In addition, the moderating role of tourists’ perceived crowding, which has become remarkably common at the site, in such a triangle relationship will also be explored. In other words, this study aims to validate an extended model of perceived value – tourist satisfaction – destination loyalty – perceived crowding.

The study collects data from 403 tourists who visited Hoi An during peak season through an online questionnaire. The data were later analysed using AMOS and Warp partial least squares.

The results validate the significant and positive correlation among perceived value, customer satisfaction and destination loyalty. Also, perceived crowding was confirmed to affect the relationship among these three variables negatively. In terms of academic contributions, this paper empirically proved that low levels of tourist satisfaction and destination loyalty among tourists who highly value their visiting experience at World Heritage Sites (WHS) can be caused by perceived crowding.

So far, current literature has investigated the direct (either positive or negative) relationship between perceived crowding and post-visit behaviours of tourists (Nie et al., 2022; Papadopoulou, Ribeiro, & Prayag, 2023; Stemmer, Gjerald, & Øgaard, 2022). Broadening this area of research, the authors of this paper used the social interference theory and the stimulus-overload theory to explain the low level of tourist satisfaction and destination loyalty among tourists who highly value their visiting experience at WHS.

This study aims to provide a new method for precisely sizing photovoltaic (PV) arrays for standalone, direct pumping PV Water Pumping (PVWP) systems for irrigation purposes.

The method uses historical weather data and considers daily variability in regional temperatures and rainfall, crop evapotranspiration rates and seasonality effects, all within a nonparametric bootstrapping approach to synthetically generate daily rainfall and crop irrigation needs. These needs define the required daily supply of pumped water to achieve a user-specified level of reliability, which provides the input to an intuitive approach for PV array sizing. An economic comparison of the costs for the PVWP versus a comparably powered diesel generator system is provided.

Pumping 22.8646 m³/day of water would meet the pasture crop irrigation needs on a one-acre (4046.78 m²) tract of land in South Florida, with 99.9% reliability. Given the specified assumptions, an 8.4834 m² PV array, having a peak power of 1.1877 (kW), could provide the 1.2347 (kWh/day) of hydraulic energy needed to supply this volume over a total head of 20 meters. The PVWP system is the low-cost option when diesel prices are above $0.90/liter and total installed PV array costs are fixed at $2.00/Watt peak power or total installed PV array costs are below $1.50/Watt peak power and diesel prices are fixed at $0.65/liter.

Because the approach is not dependent on the shapes of the sampling distributions for regional climate factors and can be adapted to consider different types of crops, it is highly portable and applicable for precisely determining array sizes for standalone, direct pumping PVWP systems for irrigating diverse crop types in diverse regions.

Since the introduction of the outstanding web AI chat system, ChatGPT, it has caused a significant impact in both academia and the business world. Many studies have started to explore its potential applications in various fields. However, there is a lack of research from the perspective of user experience. To fill this theoretical gap and provide a theoretical basis for the operation and design of related services, this study plans to develop a set of evaluation scales for AI chat system user experience and explore the relationship between various factors and user satisfaction.

This study obtained 41 evaluation indicators through literature review and user research. Subsequently, these indicators were used as questionnaire items, combined with satisfaction metrics. A total of 515 questionnaires were distributed, and factor analysis and linear regression were employed to determine the specific elements influencing user experience and the user satisfaction model.

This study found that the factors influencing user experience are usefulness, accuracy, logical inference, interactivity, growth, anthropomorphism, convenience, credibility, ease of use, creativity, and security. Among these factors, only accuracy, anthropomorphism, creativity, and security indirectly influence satisfaction through usefulness, while the rest of the factors have a direct positive impact on user satisfaction.

This study provides constructive suggestions for the design and operation of related services and serves as a reference for future theoretical research in this area.

Because of the importance of having enough sleep in life and health, this study aims to determine the effect of vitamin D supplementation on sleep quality and pregnancy symptoms (primary outcomes) and side effects (secondary outcome).

In this triple-blind randomized controlled clinical trial, 88 pregnant women with gestational age of 8–10 weeks and serum vitamin D concentration less than 30 ng/ml were allocated into vitamin D (n = 44) and control (n = 44) groups by blocked randomization method. The vitamin D group received a 4,000 IU vitamin D pill, and the control group received a placebo pill daily for 18 weeks. Independent t-, Mann–Whitney U and ANCOVA tests were used to analyze the data.

The post-intervention mean (SD: standard deviation) of total sleep quality score in the vitamin D and placebo group were 1.94 (2.1) and 4.62 (1.71), respectively. According to the Mann–Whitney U test, this difference between the two groups was statistically significant (p < 0.001). The mean (SD) of pregnancy symptoms in the vitamin D and placebo groups was 23.95 (16.07) and 26.62 (13.84), respectively, and there was no significant difference between the two groups based on ANCOVA test (p = 0.56). Considerable side effects were not observed in any groups.

This study was conducted due to the contradictory results of the effect of vitamin D on sleep quality and the high prevalence of sleep disorders and pregnancy symptoms.

This cross-sectional online survey in Oman in April 2021 aimed to assess university students' resilience, stress levels and meaning during the COVID-19 pandemic and identify characteristic profiles.

A cross-sectional survey design was used to collect data from full-time students at one University in Oman. Outcomes included sociodemographic information, the brief resilience scale, the perceived stress scale-4 and the meaning in life questionnaire to explore the students' profiles.

A total of 964 students participated (response rate = 34.8%), of which 35% had low resilience scores. The average perceived stress, presence of meaning in life and search for meaning in life scores were 7.9 ± 2.3, 24.2 ± 6.9 and 24.9 ± 7.7, respectively. Cluster analysis identified three groups: low-risk and fewer impacts (cluster A, n = 503, 523%), moderate-risk and moderate impacts (cluster B, n = 160, 16.6%) and high-risk and more impacts (cluster C, n = 301, 31.2%). Cluster C students experienced more psychological problems and were at high risk during the pandemic.

The respondents' honesty is a possible error that could influence the results. Low response rates limit its generalizability, and cause-effect relationships among mental health outcomes cannot be discerned.

This study identified three distinct groups of students, each with different levels of severity in their health problems. There is an increased need for education and counseling to support students during this period, and university management should focus on implementing personal precautionary measures and providing high-tech, user-friendly platforms for students to enhance their learning.

These findings suggest that tailored strategies should be developed to address the unique psychological needs of each group. The study provides important information for university management to understand the pandemic's psychological impact on students and develop effective interventions to support their well-being.