Abstract This study aims to assess the attention that communication platforms on the internet give to research outputs in the field of biochemistry education. To that end, academic papers in this area that received mentions on digital platforms such as Twitter and Wikipedia, news out-lets and policy documents were identified by a search performed through Altmetric Explorer. In total, nearly six hundred articles with at least one mention on online media were identified from the 1970s to the present. The analysis studies the trend over time regarding the annual number of papers with mentions as well as the Altmetric Attention Score achieved by the papers. The connection between the number of mentions that research papers in the area of biochemistry education received on online media and the citations achieved in scholarly articles is also examined. The results allow identifying the journals that receive more attention from online media as well as the principal digital platforms utilized to disseminate mentions related to research activity in this area. The conclusions suggest that analyzing the attention that online media pays to research outputs in the field of biochemistry education may contribute to appraising scientific production in the area.

Introduction:It is estimated that large language models (LLMs), including ChatGPT, are already widely used in academic paper writing. This study examined whether certain words and phrases reported as frequently used by LLMs have increased in medical literature, comparing their trends with common academic expressions.Methods:A structured literature review identified 135 potentially AI-influenced terms from 15 studies documenting LLM vocabulary patterns. For comparison, 84 common academic phrases in medical research served as controls. PubMed records from 2000 to 2024 were analyzed to track the frequency of these terms. Usage trends were normalized using a modified Z-score transformation.Results:Of the 135 potentially AI-influenced terms, 103 showed meaningful increases (modified Z-score ≥3.5) in 2024. Terms with the highest increases included “delve,” “underscore,” “primarily,” “meticulous,” and “boast.” The linear mixed-effects model revealed significantly higher usage of potentially AI-influenced terms compared to controls (β = 0.655, p < 0.001). Notably, these terms began increasing in 2020, preceding ChatGPT’s 2022 release, with marked acceleration in 2023–2024.Discussion:Certain words and phrases have become more common in medical literature since ChatGPT’s introduction. However, the use of these terms tended to increase before 2022, indicating the possibility that the emergence of LLMs amplified existing trends rather than creating entirely new patterns. By understanding which terms are overused by AI, medical educators and researchers can promote better editing of AI-assisted drafts and maintain diverse vocabulary across scientific writing.

Speaking is a key skill that helps kids grow socially and academically in elementary school. This study looks into good ways to teach speaking, finds common problems, and suggests new solutions to help students improve their speaking skills. The study uses library research to gather information from many academic papers. It finds that methods like acting out roles, telling stories, and using interactive media help students speak better by making them more involved, confident, and clear when sharing their ideas. For example, storytelling helps students tell stories in a clear way, and role-playing helps them feel more connected and speak more smoothly by acting out real-life situations. But there are some problems, like students not being confident enough, using their own local language instead of standard English, and not using a wide range of media. To fix these, the study suggests new ideas, like using picture boards and digital tools, which have helped students speak more fluently and take part more in class discussions. These results add to the conversation about how well people can communicate and give teachers real ideas for teaching speaking in a way that’s fun and includes everyone. By focusing on communication and putting students first, this research shows how important it is to use methods that are based on real-life situations and encourage active participation in speaking at the elementary level.

Purpose Gender differences persist in the labor market across both academic and nonacademic contexts. These differences remain a prominent focus of scholarly inquiry within academia. Analyzing gender differences in academic output among university faculty is crucial for advancing the scientific community. This study aimed to investigate gender differences in research output among academics in North America. Design/methodology/approach Data were obtained from the Web of Science database, including all publications by university faculty between 2013 and 2022. This study was grounded in the perspectives of human capital and institutional resources. Correlation analysis, regression modeling and intergroup difference tests were conducted to explore gender differences in research output among faculty in Library and Information Science (LIS). Findings Of the 12 hypotheses proposed, 8 hypotheses received support, whereas four hypotheses did not. The results indicated that the male faculty in LIS produced more academic papers than their female counterparts. The number of faculty members gradually declined with the increase in the total number of papers, with a more pronounced decrease among female academics. Female faculty exhibited lower levels of human capital and institutional resources than their male counterparts. The deficiency in these areas was identified as a pivotal influencing factor contributing to the lower research output of female faculty, with professional title and disciplinary quality serving as key contributors to gender differences. Furthermore, gender moderated the effect of human capital on research output, whereas no significant gender-based differences were observed in returns on institutional resources. Originality/value Unlike previous studies on gender and research output, this study primarily investigated the relationship between gender and research output among faculty in North American universities. It revealed substantial gender gaps in both the quantity and quality of research, thereby highlighting the influential role of human capital and institutional resources. The impact of human capital varied significantly by gender.

When considering Industrial Robots, one often envisions large-scale mechanical systems integrated within manufacturing facilities, specifically designed to transport objects across assembly lines, perform complex assembly tasks, and handle material manipulation with high precision. These robots are capable of performing repetitive and demanding operations, but if proper safety protocols are not implemented, they can pose serious safety hazards to human workers. While these perceptions are accurate, they do not fully capture the complexity and extensive scope of industrial robotics. This review, supported by an exhaustive analysis of numerous technical reviews, academic papers, and research studies conducted over multiple years, synthesizes these findings to provide a comprehensive and sophisticated understanding of industrial robotics. It covers the intricacies of engineering design, including kinematic and dynamic modeling, as well as the development of advanced algorithms and control systems that enable precise, real-time operations. Additionally, it highlights the critical role these robots play in boosting productivity, ensuring operational efficiency, and maintaining consistency in manufacturing processes. With recent advancements in artificial intelligence, new perspectives have emerged regarding control and modeling strategies, paving the way for the development of cognitive robots capable of autonomous decision-making and adaptive behavior, thus opening exciting prospects for the future of industrial automation.

Food-derived biostimulants support sustainable agriculture; however, the scale and heterogeneity of the field hinder their synthesis. We profiled 2005–2025 innovation by mining 2,586 PATENTSCOPE filings and Web of Science articles; texts were analyzed with KH Coder and topic models, with large language models assisting in interpretation. Patent activity surged after 2018, emphasizing plant growth promotion, yield stability, and abiotic stress tolerance (amino acids, seaweed extracts, polyphenols, humic substances, and microbial consortia). In parallel, academic papers have shifted from descriptive trials to mechanism-level work on drought/salinity responses, gene expression, and metabolomics. Together, these signals outline a translation path in which deployable biological inputs converge with mechanistic evidence. Our NLP pipeline distilled heterogeneous texts into actionable indicators, yielding a reproducible map from patent/literature trends to testable hypotheses for formulation, dose, and seed stage delivery.

The purpose of this Systematic Literature Review (SLR) is to explore the role of interactive educational games in increasing public awareness about climate change and the mitigation strategies that can be adopted. The review examines how educational games can enhance understanding of climate change by integrating narratives, simulations, and gamification. A systematic approach was used to collect and analyze 28 relevant academic papers, focusing on interactive games used to teach climate change. The methodology involved identifying studies from various databases, applying specific inclusion and exclusion criteria, and synthesizing findings from studies that explore the effectiveness of games in environmental education.The review found that interactive educational games, especially those utilizing augmented reality (AR), simulation, and narrative-based approaches, are effective tools for raising awareness about climate change. These games engage players by simulating real-world environmental challenges and offering mitigation solutions. However, the effectiveness varies depending on the audience's age, background, and technical skills. Challenges such as limited access to technology and differing levels of engagement across age groups were identified, but these can be addressed by using more accessible mobile platforms and gamified learning experiences. This SLR contributes to the understanding of how interactive games can be a valuable tool in climate change education. It highlights the potential of combining emerging technologies like AR and machine learning with traditional educational methods to create engaging and effective learning experiences. The paper provides insights into the current state of research on game-based climate change education.

Stigma associated with schizophrenia has been well-documented in both society and healthcare settings. However, the use of stigmatizing language in research papers remains largely unexplored. This study examined how researchers refer to schizophrenia in peer-reviewed articles, aiming to characterize the descriptive terms used to refer to individuals with schizophrenia and assess the adoption of person-first language. We conducted an electronic search on PubMed using the MeSH term “schizophrenia” and randomly selected 500 articles. Descriptive terminology was categorized as neutral (e.g., “schizophrenia patients”), person-first (e.g., “person with schizophrenia”), or identity-first (e.g., “schizophrenic patient”). Reference terms were assessed based on their alignment with a person-first perspective. Of the 500 studies, 475 (95%) included at least one term referring to people affected by schizophrenia. Among them, 238 (50.1%) used identity-first terms, 228 (48%) used person-first terms, and 91 (18.2%) employed both. Over time, the use of identity-first terms decreased. The decline in identity-first terms over time suggests a positive impact of the person-first movement. Despite these encouraging findings, our data also indicate that there is still room for improvement in reducing the use of identity-first terms. We propose recommendations for researchers to promote less stigmatizing language.

This research illuminates the role and utilization of academic drafts (naskah akademik) in shaping regional laws (Perda) at the Medan City Government. This study seeks to ascertain the contribution of scholarly articles to enhancing the quality, legitimacy, and harmonization of regional law. Using a qualitative-descriptive approach and analysis of documents at the local level, such as local government reports, legal documents, and secondary data, this study finds that academic manuscripts serve as the scientific and legal basis for each step of the policy-making process. The results show that the Medan City Government, through cooperation with the DPRD and Kemenkumham, emphasizes manuscript hearings as a way to provide philosophical, sociological, and juridical justification for each bill. However, from the study, significant implementation bottlenecks have also been found, such as weak human resource capacity, weak institutional coordination, and insufficient public participation. This means that there is often duplication and delay in legal harmonization. For the successful implementation of regional legislation, governance needs to be promoted on the basis of preventive legal harmonization, capacity building, and participatory approaches. Therefore, academic papers should not just be perfunctory qualifications, but tools of knowledge-based governance based on evidence, legality, and the people.

Breast cancer is one of the most common and lethal heterogeneous cancers among women worldwide, posing a significant threat to female health. Cancer associated fibroblasts (CAFs) play a critical role in the initiation and progression of breast cancer, and their behavior within the tumor microenvironment profoundly influences disease development. Systematic research on the functions of CAFs in breast cancer remains relatively limited. This study employs bibliometric theories and methods to comprehensively analyze the existing knowledge framework of breast cancer CAFs research, thereby identifying and examining research hotspots and future trends in this field. This study retrieved literature related to CAFs in breast cancer from the Science Core Collection (WOSCC) database, covering publications from 2005 to 2025. After rigorous screening, 377 eligible academic papers were included as research subjects. Utilizing software tools such as VOSviewer, Pajek, Scimago Graphica, and CiteSpace, we conducted an in-depth analysis across multiple dimensions, including countries, research institutions, authors, journals, and keywords, to elucidate the knowledge structure of this field and identify research hotspots and developmental trends. The findings indicate a general upward trend in annual publications, with particularly rapid growth between 2022 and 2024. China, the United States, and Italy were the most prolific countries, demonstrating strong academic influence. Among institutions, the University of Calabria, Chongqing Medical University, and the University of Manchester contributed the most research output. Notable researchers, including Marcello Maggiolini, Michael P. Lisanti, and Manran Liu, stood out in terms of publication volume and collaborative engagement. Regarding journals, Cancers published the highest number of articles, while Nature Communications had the greatest impact, with a 2023 impact factor of 14.7. This study systematically reviews the origin, activation mechanisms, and heterogeneity of CAFs in breast cancer. The research reveals that CAFs can be activated through various cytokines and signaling pathways and exhibit significant heterogeneity across different breast cancer subtypes. CAFs secrete multiple factors involved in angiogenesis and extracellular matrix (ECM) remodeling, thereby promoting breast cancer cell metastasis and invasion. Additionally, CAFs may suppress the host's anti-tumor immune response. Current therapeutic strategies targeting CAFs primarily focus on disrupting intercellular communication, degrading the ECM, and overcoming drug resistance. Future research may concentrate on exploring the mechanisms by which immunotherapy regulates CAF activity and the potential of combination therapies. This study provides a comprehensive overview of the current status, hotspots, and cutting-edge advancements in breast cancer CAF research. Our study systematically examines research hotspots and trends in breast cancer CAF studies, establishing a solid literature-based foundation for defining future research directions and priorities. It highlights the significant potential and importance of targeting CAFs in the breast cancer stroma for therapeutic intervention and tumor progression inhibition. The findings are expected to offer scientific guidance for subsequent research and advance the development of breast cancer CAF studies. Although this study has certain limitations, it provides valuable references for future related research.

Abstract The severe impact of domestic cats on vertebrate biodiversity is unequivocal. However, cats are generalist predators that also hunt various invertebrate taxa, yet we are still far from understanding the impacts of these predators on arthropod populations. Here, we analysed records from social media to explore which arthropods are most preyed upon by domestic cats in urban environments. Using the search algorithms of two online platforms, iStock and TikTok , we analysed &gt;17,000 photos and videos, which yielded 550 records of predation events by domestic cats. We examined these images to identify the orders of arthropods most frequently preyed upon by cats. We compared our findings with data from a recent global synthesis of academic papers quantifying the diet of domestic cats. In total, we recorded 14 distinct arthropod orders killed by domestic cats. Orthoptera was the most frequently preyed upon order, accounting for 20.7% of the records. Hemiptera (14.5%) and Blattodea (14.4%) were also commonly observed. Our data show that domestic cats hunt a surprisingly diverse range of arthropods in urban settings. Overall, the data collected from social media showed similarities but also some differences compared to the general patterns found in the scientific literature on the diet of domestic cats. This finding emphasizes that these different data streams are not redundant; therefore, combining them can be an effective way to thoroughly document ecological interactions in urban environments. Social media serves as a powerful and rapidly growing source of biodiversity data for ecologists and conservation biologists. Our study presents new records of arthropod predation by cats and highlights the diversity of invertebrate prey killed by domestic cats in urban settings. Together, these findings offer new insights into the neglected impacts of cats on arthropod populations.

Purpose This paper presents an initial analysis of the USA’ 2025 tariff programme, announced under the second Trump administration. This study aims to conceptually evaluate the likely economic consequences of these measures, situate them within historical and theoretical trade policy frameworks and outline a forward-looking empirical research agenda. Design/methodology/approach The analysis draws on historical comparisons with the 2018–2019 trade war, economic theory and empirical literature on tariffs. It also incorporates early economic indicators from 2025 to examine impacts on prices, trade flows and investment. Findings The study finds that the 2025 tariffs are likely to increase inflationary pressures, disrupt global supply chains and challenge multilateral trade norms. The policy is evaluated as being driven more by political and strategic considerations than by economic optimisation. The authors highlight the importance of second-order effects and uncertainty, especially in firm-level and macroeconomic planning. Research limitations/implications As an early-stage assessment, the paper relies on projections and prior empirical evidence rather than post-implementation data. However, it identifies important research avenues on firm-level adjustment, inflation, global trade governance and geopolitical risk. Practical implications The paper offers research insights that can help policymakers evaluate the effectiveness and unintended costs of protectionist strategies. It also provides guidance for firms seeking to adapt to the strategic and operational risks introduced by tariff shocks and the resulting uncertainty. Originality/value To the best of the authors’ knowledge, this is one of the first academic papers to evaluate the 2025 US tariff measures in a comparative and theoretical context. It contributes a forward-looking research agenda grounded in trade theory and empirical analysis of past episodes.

Abstract Academic research on economic issues from a gender approach remains limited, and similarly, few studies and academic papers have addressed the issue of the social and solidarity economy (SSE) from this perspective. The main objective of this paper is to contribute to the academic gap by completing an academic review on the subject and by presenting a panel data analysis of the contribution of the SSE to the evolution of the employment rate in terms of gender in the counties of the Basque Autonomous Community (BAC). Using panel data analysis, this study examines the contribution of the SSE to employment rates by gender across Basque counties. Although a stronger presence of the SSE as a whole positively influences the employment rate of both men and women, a sector‐specific analysis reveals that only the manufacturing sector exhibits a positive relationship with male employment rates. Therefore, further research on the SSE sector from a gender perspective is needed—both to determine whether the observed differences between men and women persist in this field and to explore the underlying reasons. This is particularly relevant in a context where the principles of equality and equity should be inherent to the very nature of the SSE organizations.

Large language models (LLMs) such as GPT-4 are increasingly integrated into research, industry, and enterprise workflows, yet little is known about how input file formats shape their outputs. While prior work has shown that formats can influence response time, the effects on readability, complexity, and semantic stability remain underexplored. This study systematically evaluates GPT-4’s responses to 100 queries drawn from 50 academic papers, each tested across four formats, TXT, DOCX, PDF, and XML, yielding 400 question–answer pairs. We have assessed two aspects of the responses to the queries: first, efficiency quantified by response time and answer length, and second, linguistic style measured by readability indices, sentence length, word length, and lexical diversity where semantic similarity was considered to control for preservation of semantic context. Results show that readability and semantic content remain stable across formats, with no significant differences in Flesch–Kincaid or Dale–Chall scores, but response time is sensitive to document encoding, with XML consistently outperforming PDF, DOCX, and TXT in the initial experiments conducted in February 2025. Verbosity, rather than input size, emerged as the main driver of latency. However, follow-up replications conducted several months later (October 2025) under the updated Microsoft Copilot Studio (GPT-4) environment showed that these latency differences had largely converged, indicating that backend improvements, particularly in GPT-4o’s document-ingestion and parsing pipelines, have reduced the earlier disparities. These findings suggest that the file format matters and affects how fast the LLMs respond, although its influence may diminish as enterprise-level AI systems continue to evolve. Overall, the content and semantics of the responses are fairly similar and consistent across different file formats, demonstrating that LLMs can handle diverse encodings without compromising response quality. For large-scale applications, adopting structured formats such as XML or semantically tagged HTML can still yield measurable throughput gains in earlier system versions, whereas in more optimized environments, such differences may become minimal.

This academic paper provides a comprehensive analysis of mixed marriages and the legal status of children within the context of Indonesian International Private Law. The study meticulously explores the formal definition of a mixed marriage, establishing it as a legal union between individuals of different citizenships, thereby subject to intersecting national legal systems. The research delves into the specific regulatory framework governing Mixed Marriages in Indonesia, with a critical examination of Law No. 1 of 1974 on Marriage and its implementing regulations. A significant portion of the analysis is dedicated to the intricate legal aspects concerning the child's status in a mixed marriage. This encompasses a detailed discussion on the child's citizenship, governed by the principle of ius sanguinis under Law No. 12 of 2006 on Citizenship, which creates potential for dual citizenship and subsequent legal complexities. The paper further investigates the fundamental rights and obligations of the child, affirming that these must be upheld irrespective of parental nationality, including the inalienable right to a legal identity, parental care, and formal education. Concurrently, the research outlines the concomitant parental obligations in a mixed marriage, which are paramount and include the provision of nurture, guidance, and comprehensive protection for the child's well-being. The study concludes with a critical evaluation of the practical implementation of these mixed marriage law aspects in Indonesia, identifying discernible gaps between statutory provisions and their real-world application. It underscores persistent challenges in juridical practice and administrative consistency, ultimately highlighting the ongoing pursuit of complete legal certainty for binational families navigating the Indonesian legal landscape.

In further education, barriers to scientific knowledge often arise due to limited competence in reading and comprehending complex academic literature. This study investigates the potential of generative artificial intelligence (AI) to scaffold reflective practice-based learning by assisting learners in overcoming these barriers by embedding generative AI within professional training. This research highlights a pathway for re-engaging adult learners with academic discourse, offering scalable solutions for lifelong learning in an era of rapid technological change. Specifically, we explore whether generative AI can enhance the accessibility of scientific literature, thereby supporting professional development through improved technological literacy. The research employed a mixed-methods approach, combining questionnaires and semi-structured interviews. The questionnaire assessed the learners perceived difficulty in engaging with academic papers. At the same time, the interviews delved into the effectiveness of generative AI assistance and its integration into their professional practice. Initial findings suggest that generative AI can act as a scaffolding mechanism, providing simplified translations and interpretations of complex texts. This support helps learners to understand and apply scientific content in their contexts. These results highlight the potential of generative AI in enhancing reflective practice-based learning by bridging gaps in scientific literacy, ultimately contributing to the future of practice-oriented education in an era shaped by disruptive technologies.

This study explains the relationship between law, legal science, and regulations in building a national legal system that is effective, fair, and responsive to societal needs. As a state based on the rule of law, Indonesia utilizes law as the basis for regulating all aspects of national and state life. Legal science plays a crucial role as a guide in the law-making process, from planning, drafting, deliberation, ratification, and evaluation. This study uses a normative juridical approach by studying various legal theories, such as the Stufenbau des Recht (The Law of Law) by Hans Kelsen and Hans Nawiasky, the theory of law as a tool for community development by Roscoe Pound, and the principles contained in Law Number 13 of 2022 concerning the Formation of Legislation. The results show that legal quality is highly dependent on the application of legal science principles, such as clarity of purpose, transparency, and public participation. However, challenges remain, such as poor coordination between institutions, low-quality academic papers, and minimal public participation in the legislative process. Therefore, the consistent application of legal science is essential to produce legal products that are consistent, non-contradictory, and capable of guaranteeing justice and legal certainty. In conclusion, collaboration between law, legal science, and legislation is key to creating a democratic national legal system based on Pancasila and the 1945 Constitution.

This is a commentary on the academic paper entitled “Intrinsic social media literacy: a public relations strategy addressing problematic social media use among teenagers globally.” PSMU is best defined as a non-substance-related disorder that results in the preoccupation

The purpose of this study is to investigate how character education is implemented at the junior high school (SMP) level by conducting a thorough literature review using the Scopus database. The approach is a review of the literature that involves examining academic papers over the past ten years that are relevant to character education in junior high schools. The findings of the study demonstrate the significance of character education in forming junior high school students' moral principles and personalities. The inclusion of character values in the curriculum, mentorship programs, extracurricular activities, and parental involvement are a few of the successful tactics that have been found. The primary obstacles encountered include variations in student backgrounds, scarce resources, and inconsistent implementation. This study also shows how crucial it is for communities, families, and schools to work together in a holistic manner in order for character education to be successful. In conclusion, a thorough and long-lasting strategy is needed for character education in junior high schools. For the purpose of creating successful character education programs at the junior high school level, researchers, educators, and policymakers can benefit greatly from the insights this study offers.

ABSTRACT Participatory mapping is a broad and diverse field of research and practice that involves non-expert mapmakers in gathering, documenting, and sharing data on spatially bounded issues, creating maps that reflect place-based knowledge. The field encompasses a range of approaches, from countermapping to Public Participation GIS (PPGIS), which differ in their influences, methods, applications, and goals. This diversity has contributed to a lack of consensus on what participatory mapping is, how it is used, and whether a universal methodology exists. Through a scoping literature review of academic papers with 'participatory mapping' in the title or abstract, we have constructed an intellectual history of the field, examining how it has been used, when, where, and for what purposes over time. We find that shifting understandings of participation, the influence of geospatial technologies, and the expansion of participatory mapping beyond geography have been central to its evolution. Our analysis identifies two distinct approaches to participatory mapping, differentiated by their aims of engagement, methodological orientation, emphasis on process or method, common areas of application, publication sources, and geographic contexts. This intellectual history enhances our understanding of participatory mapping research, tracing key trends, changes, and the future trajectory of the field.