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The purpose of this study is to map trends in literature about digital school leadership over the last decades. Combining bibliometric and automatic content analyses, we map and analyze a sample of 350 documents, retrieved in Web of Science (WoS), Scopus and Education Resources Information Center (ERIC) including titles and abstracts. The software VosViewer and Leximancer are used for analyses. Our sample is divided reflecting an early phase of digitalization in school (1992–2009), a phase of an increasing digitalization in school (2010–2020) and a phase of digitalization related to the Covid-19 pandemic (2021–2023). In general, the research literature on digital school leadership can be characterized as an emerging, fragmented, and inter-disciplinary field. Most literature is published after 2010 with an increase in publications after 2019, resulting in a peak in 2021. The literature is characterized by some influential highly connected authors revealing some changing thematic patterns over time. Further, findings highlight that when research on digital school leadership draws from various disciplines, this also indicates a need for a holistic and multifaceted approach. Scholars from different disciplines contribute to an updated understanding of digital school leadership. This interdisciplinary collaboration thus enriches the discourse, as it demonstrates how various perspectives may add new insights into the conceptualization of digital school leadership.

 

 

Background: Inflammatory cytokines such as Interleukin 1β(IL1β), IL6,Tumor Necrosis Factor-α (TNF-α) can inhibit osteoblast differentiation and induce osteoblast apoptosis. PANoptosis, a newly identified type of programmed cell death (PCD), may be influenced by long noncoding RNA (lncRNAs) which play important roles in regulating inflammation. However, the potential role of lncRNAs in inflammation and PANoptosis during osteogenic differentiation remains unclear. This study aimed to investigate the regulatory functions of lncRNAs in inflammation and apoptosis during osteogenic differentiation. Methods and results: High-throughput sequencing was used to identify differentially expressed genes involved in osteoblast differentiation under inflammatory conditions. Two lncRNAs associated with inflammation and PANoptosis during osteogenic differentiation were identified from sequencing data and Gene Expression Omnibus (GEO) databases. Their functionalities were analyzed using diverse bioinformatics methodologies, resulting in the construction of the lncRNA-miRNA-mRNA network. Among these, lncRNA (MIR17HG) showed a high correlation with PANoptosis. Bibliometric methods were employed to collect literature data on PANoptosis, and its components were inferred. PCR and Western Blotting experiments confirmed that lncRNA MIR17HG is related to PANoptosis in osteoblasts during inflammation. Conclusions: Our data suggest that TNF-α-induced inhibition of osteogenic differentiation and PANoptosis in MC3T3-E1 osteoblasts is associated with MIR17HG. These findings highlight the critical role of MIR17HG in the interplay between inflammation, PANoptosis, and osteogenic differentiation, suggesting potential therapeutic targets for conditions involving impaired bone formation and inflammatory responses.

 

 

Mastitis, an important disease in dairy cows, causes significant losses in herd profitability. Accurate diagnosis is crucial for adequate control. Studies using artificial intelligence (AI) models to classify, identify, predict, and diagnose mastitis show promise in improving mastitis control. This bibliometric review aimed to evaluate AI and bovine mastitis terms in the most relevant Scopus-indexed papers from 2011 to 2021. Sixty-two documents were analyzed, revealing key terms, prominent researchers, relevant publications, main themes, and keyword clusters. “Mastitis” and “machine learning” were the most cited terms, with an increasing trend from 2018 to 2021. Other terms, such as “sensors” and “mastitis detection”, also emerged. The United States was the most cited country and presented the largest collaboration network. Publications on mastitis and AI models notably increased from 2016 to 2021, indicating growing interest. However, few studies utilized AI for bovine mastitis detection, primarily employing artificial neural network models. This suggests a clear potential for further research in this area.

 

 

Sustainability principles are becoming an integral part of all aspects of business operations, including human resource management (HRM). Despite extensive research in the field of sustainability, there is a lack of focus on sustainable practices in the recruitment process. This article aims to identify opportunities for sustainable HRM with a focus on the recruitment of new employees in a company. The authors defined three research questions using the PICO method and subsequently applied PRISMA, bibliometric analysis, and content analysis methods to address them. The result is a proposal for a sustainable recruitment model, illustrated using the Milky Way Map framework. The model highlights the key areas of recruitment that need to be considered to achieve sustainable management of the recruitment process. The research emphasizes the importance of implementing a sustainable approach to recruitment. Information systems/information technology (IS/IT) plays a crucial role in optimizing recruitment processes and reducing negative environmental, social, and economic impacts. The implementation of the proposed model can bring benefits such as more efficient talent management, cost reduction, and enhanced sustainability.

 

 

In recent years, smart fisheries, as an emerging model for fishery development, have become a research hotspot in the fishery and aquaculture industries of many countries. Smart fisheries can be thought of as a system that combines techniques for raising, catching, or selling aquatic products to improve production and sustainable development. Smart fisheries are crucial to improving fishery and aquaculture management. In this study, a comprehensive analysis was conducted using bibliometric analysis, the results of which are presented through visual mapping and data charts. This study collected data from the China National Knowledge Infrastructure (CNKI) database and compared it with the WoS database. A total of 949 articles were retrieved on topics related to smart fisheries, including 579 articles from WoS and 370 articles from CNKI. The results present the visualization and analysis of annual publications, author collaboration maps, research collaboration institutions, keywords, etc. The development of smart fisheries in China is obviously different from that in foreign countries. China attaches great importance to technology and production, while foreign countries focus on environmental issues. Therefore, this study helps us to understand the current research status, research hotspots, and future development directions of smart fisheries, providing certain references for future management.

 

 

The integration of artificial intelligence (AI) into medical practice has become a critical focus in contemporary medical research. This bibliometric analysis examined the scope of AI utilization across the healthcare spectrum by analyzing a significant body of publications from the Scopus and PubMed databases. After removing duplicates and reviews, a total of 2061 articles were assessed using VOSviewer software (version 1.6.20). The results were organized into two main sections: influential factors and thematic directions of AI integration in healthcare. The first section highlights the most productive countries, authors, and institutions in terms of publications. The second section explores the keywords used in the relevant literature, and identifies the main thematic areas where AI has a significant impact in medical sector. The findings of this study aimed not only to assess AI’s current contributions to medicine in general but also to highlight specific technological advancements across medical departments, offering a comprehensive overview.

 

 

Landslide is a typical geological disaster distributed in most countries worldwide. Due to long-term natural weathering and human engineering disturbances, the instability of landslides is prone to occur. Once monitoring and disposal methods are implemented inappropriately, they can lead to landslide hazards, seriously threatening the safety of people’s lives and property. For a long time, extensive research on landslide monitoring has been conducted from various countries, providing crucial technical support for reducing the incidence and severity of landslide hazards. However, considering the complex geological conditions of actual landslides and the direct impact of internal and external factors such as rainfall, storms, and earthquakes, the early warning accuracy of landslide hazards is still relatively low. Therefore, based on advanced research achievements, it is significant to carry out research on the current status and development trends of landslide monitoring technology. Based on the Web of Science core database, this study quantitatively analyzes the advanced research achievements in global landslide monitoring in the past decade using bibliometric analysis. A systematic analysis of landslide monitoring technology development is conducted according to each study’s publication time, keywords, and countries. On this basis, a multi-dimensional monitoring system for landslides was proposed, which utilizes the complementary advantages of multi-dimensional monitoring technology to achieve all-round, high-precision, and real-time monitoring of landslides. Finally, taking the Xinpu landslide in the Three Gorges Region of China as an example, a multi-source and multi-field-monitoring experiment was conducted. The application of landslide multi-field-monitoring technology provides an essential reference for monitoring, early warning, as well as the scientific prevention and control of landslide hazard.

 

 

Background: Breast cancer (BC) remains the most commonly malignancy among women worldwide. Although early-stage BC typically presents with curative possibilities, advanced-stage disease, especially with metastasis, is significantly limited in terms of effective therapeutic interventions, thereby establishing it as the second leading cause of cancer-related deaths in women. Antibody–Drug Conjugates (ADCs) establish a groundbreaking class of anti-neoplastic agents characterized by high specificity and targeting precision. These agents have been significant in reshaping the therapeutic approach to breast cancer, especially those subtypes with overexpression of the Human Epidermal Growth Factor Receptor 2 (HER2). Comprising monoclonal antibodies, cytotoxic payloads, and conjugative linkers, ADCs function by specifically targeting antigens on cancer cells, thereby facilitating the intracellular delivery of the toxic payload. The present investigation endeavors to synthesize existing primary research outcomes through rigorous bibliometric and data analytical approaches, thereby elucidating the current research landscape, delineating research foci, and identifying potential avenues for future innovation. Methods: For bibliometric analysis, a comprehensive data set comprising 2181 entries related to ADCs in breast cancer was retrieved from the Web of Science Core Collection (WoSCC) spanning the years 1999 to 2023. This data was further filtered from the Science Citation Index Expanded (SCI-Expanded). Analysis software tools such as CiteSpace and VOSviewer were employed for multifaceted analyses such as trends of publications, contributions of countries, and burst analytics. In the dimension of clinical trials, we interrogated databases including ClinicalTrials.gov (https://www.clinicaltrials.gov) and the WHO International Clinical Trials Registry Platform (ICTRP) (https://trialsearch.who.int). A total of 239 clinical trials were initially sourced, among which, 175 were from ClinicalTrials.gov and 64 from ICTRP. After repetitive and correlation-based screening, 119 trials specifically addressing ADC therapeutic strategies in breast cancer were included. Analytical algorithms were executed using Microsoft-based software to evaluate treatment paradigms, emergent research themes, and progress. Results: Our investigations signify a growing trend of research on ADCs, with consistent advancements in scientific achievements. The analysis revealed that variables such as economic stratification of nations, healthcare investment paradigms, and disease incidence rates serve as significant determinants in shaping research output. Geographically, the United States emerged as the predominant contributor to the research corpus (36.56%), closely followed by China (21.33%). The underpinning of research accomplishments was found to be significantly bolstered by advancements in molecular biology, immunology, and genetic research. Moreover, the advent of nuclear magnetic resonance diagnostic modalities has contributed saliently to the diagnostic and therapeutic management of breast cancer. Conclusion: Our study provides a comprehensive overview of the ADC research landscape through rigorous bibliometric and clinical trial evaluations. At present, the ADC arena has witnessed the successful development and FDA approval of 14 distinct agents, substantially improving the clinical outcomes for a broad spectrum of oncological patients. Future research imperatives may include the exploration of ADCs targeting mutated oncoproteins, dual-specificity ADCs, combination payload strategies, peptide-drug conjugates (PDCs), and non-internalizing ADC modalities. With sustained academic and clinical focus, the ADC domain is poised for transformative advancements in targeted therapeutics across a variety of malignancies.

 

 

Currently, reverse logistics and sustainability are recognized as strategies to enhance the performance of supply chain processes and customer service and to reduce environmental impact, which is reflected in the planning of and reduction in costs throughout the production process. This article developed a bibliometric review that considered the growth of reverse logistics and sustainability from the perspective of different organizations, authors, thematic subareas, countries, journals, keywords, and volume of citations and publications. For this, a methodology was developed that consisted of reviewing previous research, obtaining the Scopus data set, applying the analysis with Microsoft Excel 365 and VOSviewer version 1.6.18 to determine the applications and trends of future research, and identifying the global impact in the last six years on organizations. The search equation with the application of filters resulted in 22,625 articles. The Sustainability Switzerland journal provided the most significant number of contributions in terms of publications, and the Journal of Cleaner Production stood out for its number of citations. Tseng, M.L. and Govindan, K. were the most active authors. China, the United States, and the United Kingdom were the most notable countries. Chinese Academy of Sciences and the Ministry of Education of the People’s Republic of China were the most influential institutions. The main findings were the recognition of the potential research lines and industry 4.0 technologies applied in supply chains and the development of sustainable processes with the fusion of reverse logistics, sustainability, and circular economy.

 

 

Climate change presents one of the most significant challenges facing the world in the 21st century. In 2019, the UK became the first major economy to pass laws to end its contribution to the world’s greenhouse gas emissions; parliament passed legislation requiring the UK government to achieve its carbon neutrality commitment by 2050. This will require all industries, including the housing sector, which currently contributes around 14% of the UK’s greenhouse gas emissions, to reduce their carbon emission contribution. One of the ways in which the housing sector plans to accomplish this is through delivering new zero carbon ready homes by 2050, at the latest. This study makes an innovative contribution to advancing the field of carbon neutral construction through its identification of the barriers to the UK in regards to their ability to deliver zero carbon homes (ZCH) and the provision of potential recommendations to overcome these barriers. To achieve this, a mixed-review method is used, combining a qualitative systematic analysis and a quantitative bibliometric approach. Several key barriers were identified and assigned to following key themes: legislative, socio-cultural, economic, financial, skills and knowledge, technical, industrial, environmental, and procurement factors. Legislative obstacles were found to be a primary barrier due to a lack of certainty, clarity, and clear definitions, as well as the removal and excess of government policies. Significantly, the findings reveal the under-researched impact of recent disruptive events, such as the COVID-19 pandemic, Brexit, and economic factors in the UK, opening up novel avenues for exploring their implications. Overall, this study advances industry understanding and highlights innovative directions necessary to propel the sector towards realizing the UK’s legally-binding 2050 net zero target through the development of zero carbon ready homes.