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Gas-insulated switchgear (GIS) stands as a pivotal component in power systems, susceptible to partial discharge occurrences. Nevertheless, manual inspection proves labor-intensive, exhibits a low defect detection rate. Conventional inspection robots face limitations, unable to perform live line measurements or adapt effectively to diverse environmental conditions. This paper aims to introduce a novel solution: the GIS ultrasonic partial discharge detection robot (GBOT), designed to assume the role of substation personnel in inspection tasks.

GBOT is a mobile manipulator system divided into three subsystems: autonomous location and navigation, vision-guided and force-controlled manipulator and data detection and analysis. These subsystems collaborate, incorporating simultaneous localization and mapping, path planning, target recognition and signal processing, admittance control. This paper also introduces a path planning method designed to adapt to the substation environment. In addition, a flexible end effector is designed for full contact between the probe and the device.

The robot fulfills the requirements for substation GIS inspections. It can conduct efficient and low-cost path planning with narrow passages in the constructed substation map, realizes a sufficiently stable detection contact and perform high defect detection rate.

The robot mitigates the labor intensity of grid maintenance personnel, enhances inspection efficiency and safety and advances the intelligence and digitization of power equipment maintenance and monitoring. This research also provides valuable insights for the broader application of mobile manipulators in diverse fields.

The robot is a mobile manipulator system used in GIS detection, offering a viable alternative to grid personnel for equipment inspections. Comparing with the previous robotic systems, this system can work in live electrical detection, demonstrating robust environmental adaptability and superior efficiency.

Social engineering is crucial in today’s digital landscape. As technology advances, malicious individuals exploit human judgment and trust. This study explores how age, education and occupation affect individuals’ awareness, skills and perceptions of social engineering.

A quantitative research approach was used to survey a diverse demographic of Egyptian society. The survey was conducted in February 2023, and the participants were sourced from various Egyptian social media pages covering different topics. The collected data was analyzed using descriptive and inferential statistics, including independent samples t-test and ANOVA, to compare awareness and skills across different groups.

The study revealed that younger individuals and those with higher education tend to research social engineering more frequently. Males display a higher level of awareness but score lower in terms of social and psychological consequences as well as types of attacks when compared to females. The type of attack cannot be predicted based on age. Higher education is linked to greater awareness and ability to defend against attacks. Different occupations have varying levels of awareness, skills, and psychosocial consequences. The study emphasizes the importance of increasing awareness, education and implementing cybersecurity measures.

This study’s originality lies in its focus on diverse Egyptian demographics, innovative recruitment via social media, comprehensive exploration of variables, statistical rigor, practical insights for cybersecurity education and diversity in educational and occupational backgrounds.

The focus of this study was to evaluate the relationship between research publications in the pesticide field, a country’s gross domestic product (GDP) and GDP per capita. The study aims to analyze pesticide use in association with a country’s population and research publications. The purpose of this study is to uncover the country’s contribution to pesticide research and assess the financial resources allocated to it as a percentage of their GDP by exploring these factors.

The Web of Science database was used to retrieve data for the period of 2001–2020. The use of scientometric indicators allowed for the analysis of the collaborative patterns and active performance of countries in pesticide research. Socio-economic analysis was used to determine the contribution of countries toward pesticide research.

This study demonstrated a strong association (0.952%) between a country’s GDP and its research publications in the field of pesticide research. Countries, such as Denmark, Belgium and Australia, have benefited from global collaboration, which has enhanced their research efforts. Despite ranking lower in pesticide utilization, India focused on pesticide research, as indicated by its high publication/GDP per capita ratio (0.26).

Research on pesticides directly impacts agricultural practices, which, in turn, influence the economic production of the agricultural sector. Changes in pesticide usage can have inference for crop yields, food price and, eventually, the GDP. Comparative analysis can assist in evaluating the efficiency of regulatory policies in balancing ecological concerns with economic interests. Changes in regulations may impact both pesticide usage and economic outcomes.

This research focuses on the role of facilities management (FM) elements which are people who represent the household, and process, place and technology as the FM elements. The findings of this research include a list of suggestions to improve SSI implementation based on the FM elements. A waste separation behaviour model was established based on the findings, which was then further validated by experts in related fields.

This paper explains how the process, place and technology elements of FM moderate and influence waste separation behaviour among households. A conceptual framework is proposed, grounded on the theory of planned behaviour (TPB), and a questionnaire survey was conducted to collect primary data from 900 eligible respondents among the residents of high-rise residential units in Malaysia’s capital city, Kuala Lumpur. SmartPLS software was used to analyse the structural equation model (SEM) of the conceptual framework developed to test the moderator’s effects.

The findings show that the process, place and technology moderators significantly and positively affected the relationship between perceived behavioural control and waste separation behaviour. Process and technology moderators significantly and positively affect the relationship between moral norms and waste separation behaviour among households. This research focuses on the role of FM elements which are people who represent the household and process, place and technology as the FM elements. The findings of this research include a list of suggestions to improve Separation at Source Initiative (SSI) implementation based on the FM elements. A waste separation behaviour model was established based on the findings, which was then further validated by experts in related fields.

This study implements the case of categorical moderator type and multiple constructs toward the relationships of formative indicators and contributes to knowledge regarding the analysis of moderator variables and structural equation modelling.

Grounded on the distributed theory and the social exchange theory, the current study investigates the determinants that positively influence job performance among educators within the realm of higher education in India. It particularly assesses the impact of perceived academic leadership on performance and explores the mediating and moderating effects of organizational citizenship behavior and informal institutional leadership.

Employing a descriptive research design, this study encompasses a broad cross-section of faculty members from various higher educational institutions across India. Data were gathered from 826 educators using a snowball sampling technique, with questionnaires administered online. Each variable was measured using prevalidated scales.

The findings from the moderated mediation model indicate a significant indirect relationship between perceived academic leadership and job performance, which is mediated by organizational citizenship behavior. Furthermore, informal institutional leadership demonstrates significant conditional indirect effects, enhancing the link between academic leadership and job performance up to a threshold, beyond which its influence diminishes.

This study pioneers the exploration of academic dynamics beyond mere titles and ranks in the Indian educational sector. It delineates both the direct and indirect roles these dynamics play in enhancing faculty performance, providing a novel insight into the complexities of academic leadership.

This study aims to investigate the efficacy of Ag@GO/Na₂SiO₃ nanocomposite in eliminating As from aqueous solutions. Employing response surface methodology, the research systematically examines the adsorption process.

Various experimental parameters including sample pH, contact time, As concentration and adsorbent dosage are optimized to enhance the As removal process.

Under optimized conditions, the initial As concentration, contact time, pH and adsorbent dosage are determined to be 32 ppm, 50 mins, 6.5 and 0.4 grams, respectively. While the projected removal of As stands at 97.6% under these conditions, practical application achieves a 93% removal rate. Pareto analysis identifies the order of significance among factors as follows: adsorbent dosage > contact time > pH > As concentration.

This study highlights the potential Ag@GO/Na₂SiO₃ as a promising adsorbent for efficiently removing industrial As from aqueous solutions, and it is likely to have a good sufficiency in the filtration of water and wastewater treatment plans to remove some chemical pollution, including paints and heavy metals.

The simplicity of the nanocomposite preparation method without the need for advanced equipment and the cheapness of the raw materials and its potential ability to remove As are the prominent advantages of this research.

Predictive digital twin technology, which amalgamates digital twins (DT), the internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation and predictive purposes, has demonstrated its effectiveness across a wide array of industries. Nonetheless, there is a conspicuous lack of comprehensive research in the built environment domain. This study endeavours to fill this void by exploring and analysing the capabilities of individual technologies to better understand and develop successful integration use cases.

This study uses a mixed literature review approach, which involves using bibliometric techniques as well as thematic and critical assessments of 137 relevant academic papers. Three separate lists were created using the Scopus database, covering AI and IoT, as well as DT, since AI and IoT are crucial in creating predictive DT. Clear criteria were applied to create the three lists, including limiting the results to only Q1 journals and English publications from 2019 to 2023, in order to include the most recent and highest quality publications. The collected data for the three technologies was analysed using the bibliometric package in R Studio.

Findings reveal asymmetric attention to various components of the predictive digital twin’s system. There is a relatively greater body of research on IoT and DT, representing 43 and 47%, respectively. In contrast, direct research on the use of AI for net-zero solutions constitutes only 10%. Similarly, the findings underscore the necessity of integrating these three technologies to develop predictive digital twin solutions for carbon emission prediction.

The results indicate that there is a clear need for more case studies investigating the use of large-scale IoT networks to collect carbon data from buildings and construction sites. Furthermore, the development of advanced and precise AI models is imperative for predicting the production of renewable energy sources and the demand for housing.

This paper makes a significant contribution to the field by providing a strong theoretical foundation. It also serves as a catalyst for future research within this domain. For practitioners and policymakers, this paper offers a reliable point of reference.

This paper systematically reviewed research work on drivers of teamwork, which will reinforce construction work teams to enhance workers’ safety performance. This study adds to the existing but limited understanding of teamwork drivers on construction workers’ safety performance. This paper presents scholars and industry-based professionals with critical initiatives that have to be implemented in organisations to get positive results in safety while working in teams with an emphasis on systems drivers of teamwork on safety performance at the organisational level, which will help in providing information on the functioning of the teams and contribute towards improved safety performance of team workers.

This study aims to systematically examine the existing body of knowledge on drivers of teamwork by analysing 53 publications from the years 1997–2021. The Scopus search engine was used to conduct a systematic review and germane publications were collated.

According to the findings of the review, since 1997, there has been a burgeoning concern in the research of drivers of teamwork and its impact on workers’ safety performance. After performing a systematic review, 37 drivers of teamwork were identified. The top five drivers are effective communications, team workers’ relations, leadership, shared knowledge and information, and team training. Moreover, it was noted that the United States and Australia have been the international regions of focus for most of the research in the area of drivers of teamwork from the years 1997–2021. The 37 drivers of teamwork are distributed into six major socio-technical components: people drivers; culture drivers; metrics drivers; organisational and management practices and procedures drivers; infrastructure drivers and technology drivers.

The results reported present research scholars and professional practitioners with an overview of the drivers of teamwork that could be implemented in the construction industry to streamline potential implementations and improve safety performance of construction workers.

A list of teamwork drivers has been developed to ratify potential empirical research in the area of construction safety. The results would contribute to the existing but restricted understanding of drivers of teamwork in the construction industry.

This study aims to highlight the growth and development of Indo-German collaborative research over the past three decades. Moreover, this study encompasses an in-depth examination of funding acknowledgements to gain valuable insights into the financial support that underpins these collaborative endeavours. Together with this paper, the authors provide an openly accessible data set of Indo-German research papers for further and reproducible research activities (the “Indo-German Literature Dataset”).

The data were retrieved from the Web of Science (WoS) database from the year 1990 till the 30th of November 2022. A total of 36,999 records were retrieved against the used query. Acknowledged entities were extracted using a named entity recognition (NER) model specifically trained for this task. Interrelations between the extracted entities and scientific domains, lengths of acknowledgement texts, number of authors and affiliations, number of citations and gender of the first author, as well as collaboration patterns between Indian and German funders were examined.

The study reveals a consistent and increasing growth in the publication trend over the years. The study brings to light that Physics, Chemistry, Materials Science, Astronomy and Astrophysics and Engineering prominently dominate the Indo-German collaborative research. The USA, followed by England and France, are the most active collaborators in Indian and German research. Largely, research was funded by major German and Indian funding agencies, international corporations and German and American universities. Associations between the first author’s gender and acknowledged entity were observed. Additionally, relations between entity, entity type and scientific domain were discovered.

The study paves the way for enhanced collaboration, optimized resource utilization and societal advantages by offering a profound comprehension of the intricacies inherent in research partnerships between India and Germany. Implementation of the insights gleaned from this study holds the promise of cultivating a more resilient and influential collaborative research ecosystem between the two nations.

The study highlights a deeper understanding of the composition of the Indo-German collaborative research landscape of the past 30 years and its significance in advancing scientific knowledge and fostering international partnerships. Furthermore, the authors provide an open version of the original WoS data set. The Indo-German Literature Data set consists of 22,844 papers from OpenAlex and is available for related studies like literature studies and scientometrics.

Drawing on the ability-motivation-opportunity model, this study investigates how gender-inclusive human resource management practices and overall fairness perception promote the career progression of female employees via psychological empowerment.

Partial least structural equation modelling (PLS-SEM) was applied to two-waves data collected from 308 respondents from Pakistan to confirm hypotheses.

Findings suggest that gender-inclusive HRM practices substantially affect female employees' psychological empowerment and career progression. Psychological empowerment is a mediating mechanism that explains the effect of gender-inclusive HRM practices on female employees' career progression. Finally, overall fairness perception further amplifies the effect of gender-inclusive HRM practices on psychological empowerment and career progression.

The study provides evidence to policymakers that organizations may promote psychological empowerment and career progression of female employees by implementing gender-inclusive HRM practices and promoting overall fairness perception.

This study contributes to achieving the SDGs by examining the impact of gender-inclusive HRM practices and overall fairness perception on female employees' psychological empowerment and career progression. Specifically, it aligns with “Goal 5 - achieve gender equality and empower all women and girls” and “Goal 8 - promote sustained, inclusive, and sustainable economic growth, full and productive employment, and decent work for all”.