Comprehensive Perspective Research Articles

Waste, the real villain: a comprehensive analysis and prospective perspective on food loss and waste in China

IntroductionOne of the best ways to ensure food security is to reduce Food Loss and Waste (FLW). However, China still confronts numerous obstacles in food loss and waste study because of the intricate industrial chain, the wide range of accounting standards, and a lack of data, among other reasons.MethodsUsing the literature analysis method, 119 literatures were collected and analyzed to examine the current status of FLW in China at various stages after food production and throughout the life cycle from the perspectives of time series and research areas.ResultsThe study indicates that the rates of FLW in China have been higher than 20% in recent years and are still increasing. Among them, the highest FLW rates were found in the harvesting stage (3–6%), storage stage (8–10%) and consumption stage (10–17%). In addition, FLW results in a huge waste of resource endowments.DiscussionThe environment and resources are profoundly affected by these substantial food losses and wastes, leading to unnecessary depletion of resources. As China’s focus on food loss and waste intensifies, an increasing number of academics are expected to delve into this area, exploring dimensions such as ecological footprint assessment, innovative uses for food waste, and gathering primary data.

Multi-Dimensional Assessment, Regional Differences, and Influencing Factors of Agricultural Water Pollution from the Perspective of Grey Water Footprint in Zhejiang Province, China

The implementation of differentiated governance for agricultural water pollution (AWP) plays a significant role in alleviating the pressure on agricultural water resources. However, research that comprehensively assesses AWP and its influencing factors from a multidimensional perspective remains relatively limited. This study utilized the grey water footprint (GWF) model to quantify the agricultural grey water footprint (AGWF), agricultural grey water footprint efficiency (AGWFE), agricultural grey water footprint intensity (AGWFI), and agricultural water pollution level (AWPL) in Zhejiang from 2010 to 2020. Subsequently, we applied the standard deviational ellipse (SDE), the kernel density estimation (KDE), and the Dagum Gini coefficient to delve into the dynamic evolution and regional disparities of these indicators. Ultimately, we leveraged both the random forest model and the panel regression model to identify and examine the key factors shaping AGWF-related indicators. The results show that: (1) From 2010 to 2020, in Zhejiang, both AGWF and AGWFI exhibit a trend of first increasing and then decreasing, peaking in 2012. In contrast, AGWFE has consistently increased over the years, reaching an increase of 54.56 CNY/m3 by 2020. Meanwhile, despite fluctuations, AWPL in Zhejiang shows an overall gradual decline. (2) The centroids of relevant indicators for AWP in Zhejiang are primarily located in Jinhua (for AGWF and AGWFI), Shaoxing (for AWPL), and in the area where AGWFE converge. (3) Compared to 2010, the regional disparities in AGWF and AWPL have shrunk significantly in 2020, whereas the regional differences in AGWFE and AGWFI have increased to some extent. In most years, the regional disparities in AGWF, AGWFI, and AWPL are more pronounced in Northeastern Zhejiang compared to the southwestern part. (4) The influencing factors of AGWF, AGWFE, and AGWFI exhibit significant regional heterogeneity. In Northeastern Zhejiang, the primary factors influencing them are technological innovation, resource endowment, and crop-cultivation methods. Conversely, in the southwestern region, the primary factors exerting the same influence are the application intensities of fertilizers, pesticides, and agricultural film application. The primary drivers of AWPL in Zhejiang are grain yield, water resource availability, and crop-planting structure. Notably, these factors do not exhibit regional heterogeneity. The paper proposes AWP control policies from both a comprehensive and multi-dimensional perspective.

EFFECT OF PUBLIC PRIVATE PARTNERSHIP FINANCING STRUCTURE ON COMPLETION OF GEOTHERMAL ENERGY DEVELOPMENT PROJECTS IN KENYA

Objective: To determine the effect of Public Private Partnership (PPP) financing structure on the completion of geothermal energy development projects in Kenya. Theoretical Framework: The study used agency and public choice theories to analyze the dynamics between PPP financing structure and completion of geothermal energy development projects. Methodology: A cross-sectional census survey in Kenya surveyed 48 geothermal energy development projects, collecting quantitative data through structured questionnaires and qualitative insights from industry regulators, financiers, and practitioners. A combination of descriptive, correlation, and linear regression statistical models were applied. Multiple diagnostics tests and data triangulation were performed. Results and Discussion: The study results provide strong statistical evidence depicting a positive relationship between PPP financing structure and the completion of geothermal energy development projects in Kenya. The findings suggest that as the level of PPP involvement increases, so does the likelihood of faster project completion. The study also reveals that a balanced PPP financing structure has a substantial effect on the completion of geothermal energy development projects. The analysis demonstrates that a hybrid PPP financing structure comprising recommended proportions of private and government equity, commercial and concessional loans, hybrid finance, and grants significantly affects project completion outcomes. Research Implications: The study emphasizes the significance of a structured PPP financing model, comprising private and government equity, concessional and commercial loans, hybrid finance, and mixed grants, in mitigating inherent PPP risks for enhanced project completion outcomes. In addition, effective government support measures and robust delivery capability of developers jointly influence the two variables in a significant manner. Originality/Value: This study uniquely analyzes the influence of PPP financing structure on the completion of geothermal energy development projects in Kenya, integrating quantitative and qualitative data for a comprehensive perspective, thus offering essential insights for stakeholders.

Unveiling the roadblocks: exploring substance use disorder treatment policies in Iran through a qualitative lens

Abstract Background Different countries, including Iran, have implemented various policies to address substance use disorder. This study aims to describe the policies related to substance use disorder treatment and identify challenges related to these policies in Iran since the beginning of the Iranian Revolution in 1979. Methods This qualitative study utilized document analysis and interviews with policymakers and implementers. We reviewed a total of 22 documents related to substance use disorder treatment and harm reduction. The results from document analysis complemented and validated the interview data. The research population comprised policymakers and implementers, including individuals directly involved in formulating and implementing substance use disorder treatment policies. Purposive sampling was employed, with a snowball strategy utilized to maximize diversity. Data saturation was achieved after conducting 32 semi-structured interviews. Conventional content analysis was used for data analysis. Results In general, the policy landscape for substance use disorder treatment in the Islamic Republic of Iran can be divided into two periods: the “Moral Model” era (1979–1993) and the “Disease Model” era (1993–present). Challenges within the content of substance use disorder treatment policies in Iran encompass the lack of law revisions, existence of contradictions in laws and nature of disease, the absence of evidence-based policymaking, and an inadequate comprehensive perspective on the phenomenon of substance use disorder. Conclusions The presence of multiple authorities with different perspectives on substance use disorder and its treatment, coupled with the application of personal preferences in policymaking and the absence of evidence-based policymaking, have contributed to weaknesses in decision-making and policy formulation. The true philosophy of Disease Model appears not to have been fully grasped by health policymakers in Iran, as all Disease Model policies have been pursued with an emphasis on abstinence and quitting. Iran and other nations facing similar challenges should place more reliance on evidence-based approaches and shift away from the “Moral Model” paradigm to develop more effective substance use disorder treatment policies.

High Entropy Ceramics for Electromagnetic Functional Materials

AbstractMicrowave absorbing materials play an increasingly important role in modern electronic warfare technology for enhancing electromagnetic compatibility and suppressing electromagnetic interference. High‐entropy ceramics (HECs) possess extraordinary physical and chemical properties, and more importantly, the high tunability of multi‐component HECs has brought new opportunities to microwave absorbing materials. Rich crystallographic distortions and multi‐component occupancies enable HECs to have highly efficient microwave absorption properties, excellent mechanical properties, and thermal stability. Therefore, the structural advantages of HECs are integrated from comprehensive perspectives, emphasizing on the role of dielectric and magnetic properties in the absorption phenomenon. Strategies are proposed to improve the microwave absorption capacity of HECs, including composition optimization, microstructure engineering, and post‐treatment technology. Finally, the problems and obstacles associated with high‐entropy materials (HEMs) research are discussed. The innovative design concepts of high‐entropy microwave absorbing ceramics are highlighted.

Toward Sustainable Utilization and Production of Tartaric Acid

AbstractGlobal efforts toward establishing a circular carbon economy have guided research interests towards exploring renewable technologies that can replace environmentally harmful fossil fuel‐based production routes. In this context, sugar‐based bio‐derived substrates have been identified as renewable molecules for future implementation in chemical industries. Tartaric acid, a special C4 bio‐compound with two hydroxyl and carboxylic groups in the structure, displays great potential for the food, polymer, and pharmaceutical industries due to its unique biological reactivity and performance‐enhancing properties. To this point, there has yet to be a comprehensive literature review and perspective on the applications and synthesis of tartaric acid. As such, we have conducted a detailed and thorough outlook and discussion in terms of biological activity, organic synthesis, catalysis, structural characterization and synthetic routes. Lastly, we provide a critical discussion on the applications and synthesis of tartaric acid to give our insights into developing sustainable chemical technologies for the future.

An analysis of the effects of aging society on global stock markets

PurposeThe primary purpose of this study is to explore the effects of demographic transition toward aging populations on the performance of stock market indices across various economic developments. The research aims to provide valuable insights into the life-cycle hypothesis on savings patterns, investment behavior and the potential reverberations on global financial markets.Design/methodology/approachThe study adopts a comprehensive global perspective, scrutinizing the effects of aging populations on stock market indices across developed, developing and transitional economies through the panel data analysis. Using annual data spanning the period from 1991 to 2020, encompassing a sample of 10 countries from each economic development level, the study employs the panel autoregressive distributed lag (ARDL) model with fixed effect estimation.FindingsThe findings unveil a statistically significant positive impact of the elderly population proportion on global stock market indices. However, the magnitude and contours of this impact exhibit considerable heterogeneity across different country groups. Specifically, the study finds that while the aging population significantly influences stock market performance in developed nations, its effect is overshadowed by other economic factors, such as consumer price indices and interest rates, in developing countries and economies in transition.Originality/valueThe originality and value of this study lie in its comprehensive global perspective, which encompasses a diverse array of economies at varying developmental stages. The research contributes to an understanding of the effects of demographic transitions on stock market performance on a global scale. The insights derived from this study hold significant implications for policymakers, financial institutions and investors seeking to navigate the challenges and opportunities posed by aging societies in an increasingly interconnected global economy. Additionally, the findings highlight the need for specific strategies and policies that account for the unique economic characteristics and developmental stages of different nations.

An Analysis of the Future Trends and Challenges of Autonomous Driving Technology

Abstract. Autonomous driving technology is one of the most groundbreaking innovations in the automotive industry in recent years. This article will explore the latest trends in autonomous driving, analyzing its historical development, current status, and future prospects, while also assessing its potential across different application scenarios. With the support of data and illustrations, this article aims to provide a comprehensive perspective to understand the development and challenges of this technology. As technology progresses, autonomous driving will significantly enhance traffic safety, efficiency, and convenience, ultimately leading the transportation industry into a new era. Although current autonomous driving systems still face challenges such as boundary identification and safety concerns, ongoing research and innovation across various fields will drive continuous improvements. In the future, autonomous driving is expected to become part of mainstream transportation, not only boosting traffic efficiency but also reducing the workload of drivers and lowering the incidence of traffic accidents. Plans for its widespread global adoption are already underway.

Innovative Microgrid Services and Applications in Electric Grids: Enhancing Energy Management and Grid Integration

Currently, microgrids are a reliable solution for integrating distributed energy resources and managing demand on electricity grids, serving as a pathway towards a responsible energy transition. However, the evolving needs of the sector require specialized approaches to enhance grid flexibility and support the increasing penetration of renewable energy sources and their rising demand. This article explores and characterizes various advanced and innovative services offered by microgrids to improve the resilience, security, and reliability of electricity grids. It analyzes technical advances and novel control methodologies that demonstrate the potential for microgrids beyond mere energy provision. These include ancillary services, services aligned with demand response programs, and advanced asset management and energy resource optimization services. A global case study is conducted to provide a framework for the services that microgrids can provide. The case study validates the efficiency and reliability of electric grids with microgrids and addresses challenges related to their stability and resilience. This research provides a comprehensive perspective on the benefits of implementing microgrids and proposes new guidelines for the deployment of these systems in both urban and rural areas within the framework of energy communities in the Colombian electricity system, emphasizing the need for collaboration among stakeholders to ensure sustainable energy solutions.

Registered Report: Self-Control Beyond Inhibition—German Translation and Quality Assessment of the Self-Control Strategy Scale (SCSS)

Self-control is crucial for goal attainment and related to several beneficial outcomes, such as health and education. For a long time, it was predominantly understood in terms of inhibition, namely the ability to suppress immediate urges for the sake of long-term goals. Still, research on other self-control strategies has a longstanding tradition and recent research has moved towards a broader approach, integrating different strategies of self-control (e.g., reappraisal or pre-commitment) to gain a more comprehensive perspective on relevant processes in goal protection. The current study aimed to translate and validate the Self-Control Strategy Scale (SCSS, Katzir et al., 2021) to enable its application in German speaking populations while assuring high measurement quality. Across 5 studies (N = 3,400), we assessed the internal structure, reliability and convergent and discriminant validity. Additionally, the strategies’ relationship with several self-control outcomes (e.g., achievement, health behavior, or pro-environmental behavior) were tested. The assumed eight-factor structure was confirmed, internal consistency and retest reliability were sufficient for most subscales and the model was invariant between gender and age groups. Convergent and discriminant validity were overall adequate. Different associations emerged between strategies and outcomes, depending on the outcome domain. Thus, the SCSS appears to be a valid and reliable measure, which can be used in German. The results provide a good starting point for future research on the utility of self-control strategies in different domains.

Understanding society: a reflexive foresight matrix for navigating complexity and shaping the future

Purpose This paper introduces the foresight matrix, a conceptual framework for foresight analysis rooted in critical realism (CR) and complexity theory. It aims to address the need for a comprehensive theoretical perspective that embraces emergence and recognizes the interplay between different layers of reality. Informed by critical theory within futures studies, the study seeks to provide additional foresight theoretical perspectives in addressing contemporary societal challenges and collectively shaping desirable futures. Design/methodology/approach The proposed reflexive foresight matrix incorporates elements of CR, complexity theory and morphogenesis theory, providing an alternative conceptual framework for analyzing complex social challenges. It integrates the vertical layers – empirical, actual and real – and horizontal dimensions – structure, agency and culture. This matrix guides researchers through a systematic analysis of structural barriers, cultural influences and individual agency, offering a comprehensive tool for understanding the underlying mechanisms driving social change. Findings The reflexive foresight matrix dissects complex situations into structure, agency and culture dimensions, enabling a thorough understanding of societal dynamics by examining the interplay between these dimensions and their influence on individual and collective behaviors. This conceptual framework guides researchers through a systematic analysis of structural barriers, cultural influences and individual agency, uncovering the mechanisms driving social change. Through reflexive monitoring and temporal action analysis, it explores historical and contextual factors, informing future tendencies. Practical implications The reflexive foresight matrix provides a multidimensional lens for understanding social issues, prompting researchers to consider the interplay between structure, agency and culture across different layers of reality. By exploring historical and contextual factors, this framework enables an insight into diverse perspectives and their impact on future outlooks. Furthermore, the matrix facilitates critical inquiry into prevailing power dynamics and narratives, offering insights into societal injustices and inequalities. This critical examination empowers stakeholders to challenge dominant narratives and work toward more equitable and desirable futures. Social implications The proposed reflexive foresight matrix offers a comprehensive approach to analyzing complex social challenges, potentially impacting futures thinking and foresight practices. By integrating CR, complexity theory and morphogenesis theory, the framework fosters a deep understanding of the interplay between various factors influencing future tendencies. This comprehensive view of problems allows analysts to consider structural barriers, cultural influences and agency, thereby enhancing foresight efforts in addressing contemporary challenges. Originality/value The proposed reflexive foresight matrix contributes to futures thinking and foresight practices by offering a comprehensive approach to analyzing complex social challenges. By combining CR, complexity theory and morphogenesis theory, the framework fosters an insightful understanding of the interplay between various factors influencing future trajectories. Moreover, the integration of critical perspectives and reflexive methodologies into foresight practices underscores the importance of challenging dominant narratives, fostering inclusive decision-making processes and empowering individuals and communities to shape their futures.

Integrative Learning Strategies for Enhancing Critical Thinking in Islamic Religious Education

This research employs a qualitative approach to explore integrative learning strategies aimed at enhancing critical thinking skills in Islamic Religious Education at the secondary school level in Padang, Indonesia. The study involved four teachers and 120 students from various classes to provide a comprehensive perspective. Given the increasing importance of critical thinking in education, especially in subjects that shape students' moral and ethical foundations, this research emphasizes the crucial role of developing these skills within Islamic Religious Education. Data were collected through direct classroom observations, in-depth interviews with teachers and students to capture their experiences and insights on the strategies used, and a detailed analysis of relevant teaching materials. The findings reveal that group discussions create a dynamic environment where students can exchange ideas, broaden perspectives, and develop critical arguments. Case study analyses enable students to connect religious concepts to real-life situations, reinforcing the practical significance of religious teachings. Problem-solving activities promote logical, systematic, and reflective thinking skills, especially when addressing complex moral and ethical dilemmas. The study also highlights that these strategies not only enhance students' critical thinking but also increase their active engagement in learning, deepen their understanding of religious teachings, and foster a reflective approach toward moral values. This research offers an in-depth understanding of the effectiveness of integrative learning strategies in Islamic Religious Education and underscores their relevance in preparing students to meet the demands of modern education, which prioritizes critical thinking skills.

Peroxisome proliferator-activated receptor agonists as an adjuvant for cancer therapy: A review

Cancer is now one of the leading diseases responsible for the highest mortality rates worldwide. Cancer treatment is extremely intricate and is often associated with less targeted effects and more side effects. In the last few years, two significant revolutions in cancer treatment have altered treatment paradigms: immuno-oncology and the pursuit of actionable changes in oncogene-driven cancers. Significant obstacles continue to exist in both areas of cancer treatment. Next-generation sequencing technologies for molecular prescreening in clinical research are advancing, but their widespread clinical use is hindered by challenges related to the clinical interpretation of large genomic data. Moreover, cancer mono-chemotherapy is associated with issues such as inadequate efficacy, drug resistance, and systemic toxicity. It is not possible to administer cytotoxic drugs limitlessly. Combination therapy was developed in response to this circumstance, with the expectation of achieving high therapeutic efficacy at lower dosages of medication. Peroxisome proliferator-activated receptors (PPARs) are a group of essential lipid sensors and metabolic pathway regulators. In addition, they possess the ability to modulate immunity, inflammation, and endothelial nitric oxide synthase activation. Alongside their well-established functions, new insights into the roles of PPAR agonists in cancer research are emerging. After reviewing current research, it is evident that PPAR modulators have significant potential for managing cancer. This review aims to consolidate the functions of PPAR ligands alongside other cancer therapies. We provide a comprehensive perspective on the applicability of PPAR ligands in cancer treatment as an adjuvant.

Sand and Dust Storm Risk Assessment in Arid Central Asia: Implications for the Environment, Society, and Agriculture

AbstractThis study aimed to assess sand and dust storm (SDS) risks in arid Central Asia during 2001–2021 from a multisectoral (environment, society, and agriculture) and comprehensive perspective on the Google Earth Engine (GEE) platform. The results show that the areas with moderate or greater SDS risk accounted for 18.75% of the total area of arid Central Asia. The high SDS risk areas are mainly concentrated in the oases around the desert and are most widely distributed in spring and summer. The SDS risk in the oasis area of southern Xinjiang increased significantly, while the SDS risk in the northeastern Aral Sea region and the Kazakh hilly region decreased significantly over the 21 years. Khwarazm of Uzbekistan, located in the Amu Darya River Delta, is the administrative district with the highest comprehensive risk of sandstorms, and the Balkan State of Turkmenistan and Kashi City and Zepu County in China are the administrative districts with the highest multisectoral risk of sandstorms. The results of this study provide a complete picture of SDS risks in the arid Central Asia region and will provide some guidance to policymakers and local authorities in SDS risk mitigation.

The Role of Yoga in Enhancing Decision Making: A Research Perspective

This research explores the impact of yoga on enhancing decision-making abilities from a comprehensive research perspective. “Yoga, an ancient practice encompassing physical postures, breathes control, and meditation”, has gained attention in contemporary psychology and neuroscience for its potential cognitive benefits. This research aspires to analyze relationship among “Yoga practice & decision-making processes”, examining how regular “yoga practice” may influence cognitive functions relevant to decision making. The implications of these findings for personal well-being, professional performance, and organizational effectiveness are discussed, emphasizing the importance of integrating yoga-based interventions into educational, clinical, and corporate settings. Finally, avenues for future research are proposed, including longitudinal studies to examine “long-term provoke of yoga practice” on decision making and randomized controlled trials to establish causal relationships. Overall, this research underscores the multifaceted benefits of yoga in enhancing cognitive functions and informs strategies for optimizing decision-making processes in diverse contexts.

A historical perspective on the insect central complex: Anatomy, development, and function

The central complex (CX), a remarkable brain region at the core of insect behaviors, has been the subject of extensive research for decades. In this review, we offer a comprehensive historical perspective on the anatomy, development, and function of the CX. The CX consists of discrete and highly structured neuropils found at the center of the brain, which are conserved across insects and arthropods. The developmental processes that shape the CX are themselves conserved across insects. In early research, the CX had been shown to receive visual information and control motor function. Using increasingly advanced methods throughout the years, it has become clear that the CX is involved in high-level behavioral control, such as in vector navigation and goal directed orientation. Its numerical simplicity presents a rare opportunity to study structure-function relationships in small brains, gain insights into evolutionary neurobiology, and develop novel neuromorphic technologies inspired by insect brains. Since the CX is a highly conserved brain region involved in the control of spatial tasks, it is uniquely suited to gain a detailed understanding of the computations required for these processes at the level of neural circuits.

Artificial Intelligence as Research Methods in Urban Design

This paper delves into the role of artificial intelligence (AI) in urban design, focusing on its capability to manage complex urban systems via paradigm classification and comparative analysis. It methodically explores how AI improves design generation, optimizes morphology, and simulates real-world scenarios, thereby enhancing design quality and efficiency throughout the urban design process. Furthermore, the study contributes to the development of comprehensive AI evaluation criteria, integrating both theoretical and practical perspectives to critically understand the advantages and limitations of AI in urban design applications.

Fundamental effects of array density and modulation frequency on image quality of diffuse optical tomography.

Diffuse optical tomography (DOT) provides three-dimensional image reconstruction of chromophore perturbations within a turbid volume. Two leading strategies to optimize DOT image quality include, (i) arrays of regular, interlacing, high-density (HD) grids of sources and detectors with closest spacing less than 15mm, or (ii) source modulated light of order ∼100MHz. However, the general principles for how these crucial design parameters of array density and modulation frequency may interact to provide an optimal system design have yet to be elucidated. Herein, we systematically evaluated how these design parameters effect image quality via multiple key metrics. Specifically, we simulated 32 system designs with realistic measurement noise and quantified localization error, spatial resolution, signal-to-noise, and localization depth of field for each of ∼85000 point spread functions in each model. We found that array density had a far stronger effect on image quality metrics than modulation frequency. Additionally, model fits for image quality metrics revealed that potential improvements diminish with regular arrays denser than 9mm closest spacing. Further, for a given array density, 300MHz source modulation provided the deepest reliable imaging compared to other frequencies. Our results indicate that both array density and modulation frequency affect the spatial sampling of tissue, which asymptotically saturates due to photon diffusivity within a turbid volume. In summary, our results provide comprehensive perspectives for optimizing future DOT system designs in applications from wearable functional brain imaging to breast tumor detection.

Immigrant Youth Adaptation and Risk Involvement: The Case of Immigrant Youth From France and the Former Soviet Union in Israel

Immigration is challenging for youth as it requires reorganization of their developmental system and can increase their vulnerability to risk factors. Adaptation processes may be affected further by the cultural context in which they take place. This study explored immigration and adaptation experiences among youth at risk, who had immigrated to Israel from France and from the Former Soviet Union (FSU), and the impact of these experiences on the youth’s involvement in risk behaviors. The 27 participants interviewed for this qualitative study were 11 immigrant youth from France, 10 from the FSU, and 6 practitioners who work with immigrant youth at risk. Data analysis indicates that immigration is a significant life event that affects all spheres of the youth’s lives: identity, relationships with parents and peers, and school integration. Based on the participants’ interviews, we conceptualized adaptation as a multilevel process, related to youth’s potential involvement in risk behaviors. Moreover, immigrant youth’s experiences on different levels are shaped by their culture of origin—a matrix in which their adaptation and risk behavior occur. The findings, derived from a comprehensive perspective of both the youth and the practitioners, have substantial implications for practice and policy to enhance immigrant youth’s constructive adaptation. Specifically, we emphasize the key role of pre- and post-migration preparation that targets immigrant youth and their parents, and Israeli education institutions that receive immigrants.

Unveiling and advancing grassland degradation research using a BERTopic modelling approach

Grassland degradation presents overwhelming challenges to biodiversity, ecosystem services, and the socio-economic sustainability of dependent communities. However, a comprehensive synthesis of global knowledge on the frontiers and key areas of grassland degradation research has <pg=>not been achieved due to the limitations of traditional scientometrics methods. The present synthesis of information employed BERTopic, an advanced natural language processing tool, to analyze the extensive ecological literature on grassland degradation. We compiled a dataset of 4,504 publications from the Web of Science core collection database and used it to evaluate the geographic distribution and temporal evolution of different grassland types and available knowledge on the subject. Our analysis identified key topics in the global grassland degradation research domain, including the effects of grassland degradation on ecosystem functions, grassland ecological restoration and biodiversity conservation, erosion processes and hydrological models in grasslands, and others. The BERTopic analysis significantly outperforms traditional methods in identifying complex and evolving topics in large datasets of literature. Compared to traditional scientometrics analysis, BERTopic provides a more comprehensive perspective on the research areas, revealing not only popular topics but also emerging research areas that traditional methods may overlook, although scientometrics offers more specificity and detail. Therefore, we argue for the simultaneous use of both approaches to achieve more systematic and comprehensive assessments of specific research areas. This study represents an emerging application of BERTopic algorithms in ecological research, particularly in the critical research focused on global grassland degradation. It also highlights the need for integrating advanced computational methods in ecological research in this era of data explosion. Tools like the BERTopic algorithm are essential for enhancing our understanding of complex environmental problems, and it marks an important stride towards more sophisticated, data-driven analysis in ecology.