The purpose of this scoping review was to compile reported outcomes in relation to service-learning in veterinary medicine and identify underrepresented areas that warrant further initiative to support a more intentional model of community partnership. The Bramer et al method was utilized in this scoping review across 3 bibliographic databases to obtain a comprehensive literature search, yielding 715 eligible publications for screening. The screening process was charted with the use of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. All citations were initially double-screened, with conflicts resolved by a third reviewer; in the final stages, fulltext screening was conducted by 2 reviewers. Only models of veterinary service-learning publications were included in the review, excluding all those in which education of veterinary students was not the primary population. Results yielded 36 studies for review that all documented student-centered outcomes, with only 12 mentioning community partners. Six core themes were noted across the studies evaluated, including skill building, shaping of career motivations and identity, mentorship as a support structure, and development of empathy and social justice orientation. While community engagement models in veterinary medicine are mutually beneficial by design, with clear benefits to experiential learning, there has been a lack of exploration past an internal institutionalized focus with limited representation of community perspective. A clearer understanding of community outcomes in service-learning programs is critical in supporting an equitable program design that offers a more meaningful and ethical clinical practice model while, in parallel, meeting the needs of the populations they aim to serve.

The prefrontal cortex (PFC) has been extensively investigated in relation to higher-order cognition, emotional regulation, and behavioural control, particularly within clinically oriented studies addressing psychiatric symptoms, self-regulation, and intervention outcomes. Although a growing body of literature has examined prefrontal function assessment and intervention, the thematic organization and structural interconnections within this clinically focused literature have not been sufficiently clarified. Mapping these conceptual relationships may help identify dominant research concentrations and underrepresented areas within the retrieved literature. A total of 1,301 peer-reviewed articles published between January 2014 and December 2024 were retrieved from Web of Science, PubMed, and Embase. After keyword extraction and standardization, the top 52 high-frequency terms were analyzed using NetMiner 4.0. Network indices including density, inclusiveness, and average path length were calculated, together with degree and betweenness centrality. Cohesive subgroup analysis was additionally performed to identify thematic clusters within the keyword network. The keyword network demonstrated a density of 0.408, inclusiveness of 1.0, and an average distance of 1.621, indicating a highly connected structure without isolated nodes. Central hubs included Cognition, Depressive disorders, Randomized controlled trial, Cognitive behavioural therapy, and Psychotherapy, which emerged as the principal structural hubs, suggesting that the retrieved literature was strongly concentrated on standardized cognitive assessment and clinically applied intervention frameworks. Mobile health, E-health intervention, and Chronic illness group also showed substantial structural influence. Cohesive subgroup analysis identified seven differentiated thematic clusters spanning cognitive rehabilitation, emotional regulation, psychotherapy, digital self-management, mindfulness-based executive support, stress resilience, and neurocognitive motivation. The retrieved literature analyzed in this study exhibited a strongly interconnected thematic structure centered on clinically oriented assessment and intervention domains. Because direct neuroimaging and neurophysiological modalities were comparatively less represented in the retrieved dataset, the present findings should be interpreted as a structural mapping of clinically weighted prefrontal function research rather than a comprehensive representation of the entire methodological landscape. Nevertheless, this network-based analysis provides a systematic overview of current thematic concentrations and offers a useful foundation for future comparative and longitudinal investigations. Not applicable.

ABSTRACT Over the past three decades, scholarship on radio and audio media has evolved in tandem with transformations in production technologies, distribution platforms, and listening practices. Early radio studies focused on broadcasting systems, regulation, and programming, while recent work increasingly engages digital audio platforms, podcasting, and creator-driven sound cultures. Yet limited attention has been given to how these shifts appear within the publication record of journals dedicated to radio and audio media. This study presents a retrospective bibliometric and content analysis of 570 articles published between 1997 and 2025, encompassing the Journal of Radio Studies (1997–2007) and the Journal of Radio & Audio Media (2008–2025). Using the journal archive as corpus, the study examines publication trends, topical emphases, methodological approaches, and patterns of authorship and geographic representation. By mapping these dynamics across nearly three decades, it highlights continuity and change in the field while identifying underrepresented areas and future research opportunities.

Abstract In real-world applications, there is a fundamental problem: the data most critical to predict interesting events, anomalies, and high-stakes outliers are the rarest, while less interesting data is abundant. Although deep learning is deployed specifically for these difficult prediction tasks, data-driven models inevitably fail in underrepresented areas. This discrepancy between the empirical data- and the desired evaluation distribution is equivalent to a target distribution shift. The research field, termed Deep Imbalanced Regression (DIR), has emerged explicitly to address this challenge, which is particularly acute for continuous targets where most conventional classification-based methods are ill-suited. In this paper, we present the first comprehensive review of the DIR landscape, organized around a novel two-axis taxonomy that disentangles challenges along a Data Axis (target distribution shift, continuity, and density) and a Deep-Learning Axis (shared capacity, biased updates, and manifold distortion), where the latter captures a cascading failure mechanism through which deep models systematically neglect underrepresented targets. Within this framework, we systematically categorize and analyze 19 state-of-the-art methods spanning architectural, algorithm-level, and representation learning approaches, and empirically re-evaluate twelve of them with publicly available implementations under controlled, identical conditions. To stress-test generalization across the full target range, we introduce three novel targeted evaluation protocols, Balanced Extrapolation , Bimodal Interpolation , and Blind-Spot Isolation , that expose failure modes hidden by standard benchmarks ( https://github.com/noah-puetz/deconstructing_deep_imbalanced_regression ). Our study underscores the significant impact of imbalance on regression accuracy, offering a conceptual framework and practical benchmarks to catalyze further development of systems capable of capturing the rare as reliably as the common.

Freshwater fish biodiversity is undergoing a rapid decline worldwide due to habitat fragmentation, climate change, invasive species, overexploitation and pollution. Yet, for many regions, including biodiversity-rich but underrepresented areas such as Türkiye, large-scale assessments of species diversity and distribution remain limited. Environmental DNA (eDNA) metabarcoding offers a powerful, non-invasive and scalable tool for biodiversity assessment, capable of detecting both common and cryptic taxa. Here, we present the first nationwide, basin-scale eDNA metabarcoding survey of freshwater fishes across Türkiye's major river systems, spanning a transect of more than 6000 km and encompassing 29 sampling sites across seven principal basins. Triplicate water samples were analysed using high-throughput sequencing of the mitochondrial 12S ribosomal RNA (rRNA) gene, generating 351,392 high-quality reads (after filtration) and detecting 52 fish species, including native, invasive and several taxa previously unrecorded in their respective basins. The Eastern Mediterranean basin exhibited the highest species richness (28 species) and diversity (H' = 2.35; 1 - D = 0.88), whereas beta-diversity analyses revealed marked spatial structuring among basins (Jaccard similarity 0.17-0.58) and a clear biogeographic separation in principal co-ordinates analysis (PCoA) ordination. Importantly, eDNA metabarcoding uncovered cryptic and low-abundance taxa not detected by conventional surveys, demonstrating its complementary value and sensitivity. By providing the first comprehensive molecular baseline of Turkish freshwater ichthyofauna, this study illustrates the potential of large-scale eDNA approaches to transform biodiversity monitoring, inform conservation strategies and support management decisions in freshwater ecosystems facing accelerating environmental change.

Purpose This study conducts a comprehensive bibliometric analysis to map the global research landscape on posttraumatic growth (PTG) in the context of cancer. While PTG has gained increasing scholarly attention as a positive psychological adaptation to trauma, no systematic evaluation has yet examined its research trajectory, key contributors, thematic evolution and knowledge gaps in the spectrum of cancer. This study aims to address this gap by identifying research trends, influential contributors, research hotspots and gaps, offering valuable insights to guide future investigations in the field. Design/methodology/approach A bibliometric approach was used using the Web of Science Core Collection (WOSCC) database. A total of 1,387 articles published between 1996 and 2023 were retrieved through a targeted search strategy. The statistical analysis was performed using the Bibliometrix open-source package of the R language environment. Findings The findings reveal a substantial growth in research related to PTG and cancer, with an annual growth rate of 11.49% over the past 28 years. The United States of America (USA) leads in research output, followed by China, Canada and Australia. Prominent contributors to the field include Richard G. Tedeschi, Crystal L. Park and Lawrence G. Calhoun. Psycho-Oncology stands out as the leading journal for disseminating research on PTG in the context of cancer. Keyword analysis further highlights key research hotspots, emerging trends and potential gaps in the evolving research landscape of PTG in cancer. Research limitations/implications The findings highlight the growing recognition of PTG as an essential aspect of cancer survivorship and psychosocial oncology. By identifying influential studies and under researched areas, this study offers a roadmap for researchers, policymakers and health-care practitioners to advance patient-centred care. Future research should prioritise interdisciplinary approaches and under-represented areas to deepen the understanding of PTG and its implications for cancer patients’ psychological well-being. Originality/value This study presents the first bibliometric analysis dedicated to mapping the global research landscape of PTG in cancer, offering a novel synthesis of its intellectual structure and developmental trajectory.

This paper introduces the Violence Perception Index (VPI), a novel methodology for quantifying violence-related discourse through geolocated YouTube comments. Utilizing the YouTube API and natural language processing techniques, the VPI measures public references to violence across 1.2 million unique geolocated videos in Mexico (2020–2024), extracting 14.8 million comments from over 500,000 videos with user engagement. This approach provides spatiotemporally granular data on violence-related discourse, which we treat as a proxy for violence perceptions, extending beyond traditional event-based datasets by capturing not only documented violence but also rumors, fears, and community discourse about violence, dimensions that influence community behavior and social stability independently of official records. Violence scores are constructed using a weighted Spanish-language dictionary developed through semantic network expansion from violence-related seed terms. The dictionary-based scoring approach demonstrates moderate-to-substantial agreement with large language model classifications across 700 stratified comments (75-81% agreement), validating the method’s capacity to systematically identify violence-related discourse at scale while maintaining computational efficiency for processing millions of comments. The VPI is benchmarked against established violence indicators including ACLED fatalities and official municipal homicide statistics through panel regression specifications incorporating comprehensive spatial and temporal fixed effects. Analysis reveals systematic geographic heterogeneity: the VPI correlates strongly with ACLED data in high-population areas but exhibits stronger correlation with official homicide records in low-population contexts. Rather than constituting a methodological limitation, this pattern demonstrates the VPI’s enhanced sensitivity in marginalized and remote regions where news-based datasets suffer from systematic reporting bias. The methodology is immediately scalable across languages and geographies, providing complementary intelligence for conflict monitoring, early warning systems, and policy interventions in precisely those underrepresented areas where traditional event-based monitoring systems provide incomplete coverage.

Urology has historically led surgical innovation with the early adoption of endoscopy, minimally invasive surgery, and neurostimulation devices. However, the current trajectory of innovation across urologic subspecialties remains undefined. Our objective was to characterize trends in US Food and Drug Administration device approvals in urology from 1990 to 2023 and assess regulatory, market, and subspecialty factors associated with device development activity. US Food and Drug Administration databases were queried for all devices approved through the Gastroenterology-Urology Device Panel between 1990 and 2023. Devices were categorized by subspecialty, regulatory pathway, device class, and company experience. Descriptive statistics and comparative analyses assessed approval trends, processing times, and market entry dynamics. Of 7860 devices approved by the Gastroenterology-Urology Panel, 4300 (54.7%) were urologic. Device approvals peaked in 1994 and then declined 76% between 1994 and 2023. Endourology accounted for 50.6% of devices but experienced a 60.7% decline in growth. Urogynecology and reconstructive pelvic surgery and neurourology demonstrated significant growth (833.3% and 650.0%, respectively), albeit from a low baseline. Most devices were class II (94.0%) and approved through the 510(k) pathway (98.7%). Approval times varied by device class (P < .001) and were shorter for companies with prior regulatory experience (P < .001). Urologic device regulatory approvals have declined since the 1990s in traditionally dominant subspecialties. While growth is emerging in underrepresented areas such as urogynecology and reconstructive pelvic surgery and neurourology, prolonged approval timelines within these subspecialties may impede progress. Regulatory reform and industry support may help revitalize innovation in urologic technology.

Background: As part of our social accountability mandate, the University of Ottawa Faculty of Medicine produced a sociodemographic picture of our region’s residents, including gender, race/ethnicity, language, and neighbourhood of residence, in order to contribute to a representative healthcare workforce that can address the specific needs of our underserved communities. Approach: For our 2023 medical school cohort, we obtained data from the Ontario Medical Student Applicant Service Survey which is a mandatory component for all Ontario medical school applications and includes questions pertaining to first language and nine other equity, diversity, and inclusion factors. We compared these data to regional demographic data held at the Ottawa Neighbourhood Study, and linked the postal codes of students to their location of residence during high school to map their geographic contexts of origin. We developed a dynamic dashboard, accessible to faculty, students, and the community. Results: Among the 183 students in the 2023 MD cohort, only 22.4% came from designated priority regions, with few from rural areas or First Nations communities. Analysis revealed an overrepresentation of students from higher socioeconomic neighbourhoods, with just 28.2% of Ottawa-based students from the most socioeconomically disadvantaged quintiles, compared to 51.2% from the most advantaged. Our cohort was more diverse than our community with respect to non-official first languages, second and third generation status, and non-White self-reported race, but had an inadequate representation of certain priority groups (e.g., Black and Indigenous students). We found overrepresentation of students with at least one parent completing each of the higher levels of education compared to adults in the region (e.g. bachelor’s degree (51.4% vs 25.0%)), and more with parents working in education (30.1% vs 16.5%) and health (15.8% vs 7.5%) than regional comparisons. In addition, compared to our region’s residents, far more students came from the highest earning households (32.8% vs 13.2%). Implications: These insights have important implications for our future regional health workforce. First, they have guided targeted outreach initiatives to high schools in underrepresented areas. Second, they have informed our new regional admissions mandate, which includes a target of at least 50% of our medical school cohort from our priority region, and goals for specific representation streams. Third, we are revising our curriculum to ensure that the cases students encounter in their training reflect the social and demographic profiles of students they will care for in clinical practice. This initiative offers a replicable model for other institutions aiming to strengthen their healthcare workforce by aligning admissions and curriculum with their social accountability mandates. By ensuring medical students are representative of diverse communities, the initiative supports a more equitable healthcare system and builds a workforce prepared to meet the needs of underserved populations.

This systematic literature review (SLR) examines the ways in which parental involvement enhances educational quality and school sustainability during the last ten years. A thorough search of six academic databases yielded 39 peer-reviewed publications using the PRISMA framework. Combining automated theme mapping with Leximancer and theoretical framework-informed manual coding, the analysis ensured both interpretative depth and computational breadth. The findings show that when parental involvement is expanded beyond standard communication to include co-governance, socioemotional support, and digital collaboration, it enhances student outcomes, institutional resilience, and inclusive practices. According to the data, which is framed within systemic and ecological perspectives, parental involvement improves schools’ ability to adapt to the varied demands of the community while also reinforcing academic accomplishment. However, enduring obstacles, such as socioeconomic disparity, cultural misalignments, and disjointed regulations, continue to restrict equitable participation, especially in environments with limited resources and a varied population. An intersectional viewpoint that is still under-represented in the literature is advanced by this review’s integration of the cultural, digital, and emotional aspects of parental participation. Cross-cultural studies in under-represented areas, as well as longitudinal and mixed-methods designs to investigate causal pathways, could be beneficial for future study. Strengthening family-school connections and advancing sustainable education systems will require special attention to equity-driven, context-responsive, and technology-enabled solutions.

Regional insect collections can be valuable resources when covering under-represented areas, unique time periods, or unique collectors. Houghton and Baraga County Michigan are two predominantly forested counties in the Upper Peninsula (UP) of Michigan. The main campus for Michigan Technological University is based in Houghton, MI with a forestry field campus in Baraga County that was acquired in 1954. The university has had forest entomology research in some capacity at least since the 1930’s with faculty, students, and members of the community preserving and submitting various specimens in the decades since then, making it a unique collection demographically. The collection was recently revamped with specimens formally sorted with all labels digitally transcribed and published in Ecdysis. The history of the collection and its present state is briefly described. The Michigan Technological University Insect Collection houses specimens from a relatively under-collected region of the state and has a number of contributions that are more than 50 years old, with new submissions now collated annually. Our hope is to make this collection more accessible and to support larger conservation efforts or researchers or educators to expand their knowledge of insect distributions and the UP’s natural history.

Accurate knowledge of the seafloor is fundamental for understanding marine geomorphology, ecosystem distribution, and sustainable use of ocean resources, yet knowledge distribution remains uneven across ocean basins. This study presents the first spatially explicit bibliometric analysis of seafloor-mapping research (i.e., bathymetric studies) in the Mediterranean Sea, synthesizing georeferenced studies from nearly 700 peer-reviewed publications (1966–2020). Using GIS-based mapping and a novel classification matrix combining research density and impact metrics, the study quantifies geographic disparities in data coverage and research contribution. Results highlight strong geographic imbalances in research effort, with high-output “Consolidated High-Impact Hubs” concentrated in limited regions, while extensive “Underrepresented Areas” persist elsewhere. Importantly, research impact does not consistently align with studies density: some low-output zones host high-impact research, whereas certain high-density areas show weaker alignment between volume and influence of research effort. These findings highlight both structural and methodological imbalances in seafloor mapping research and underscore the need for more geographically balanced and integrated bathymetric research efforts. The framework developed here provides a transferable approach to other regional seas for evaluating the spatial distribution and impact of seabed-mapping research in marine geosciences. It provides a quantitative baseline for directing future mapping initiatives, optimizing collaborative surveys, and improving the representativeness of seabed data across the Mediterranean Sea and its regional basins.

Neurocritical care is a rapidly evolving, multidisciplinary speciality. Understanding the research landscape is essential for identifying thematic priorities, gaps and patterns of collaboration that may influence evidence-based practice. This bibliometric analysis aimed to examine the conceptual and collaborative structures within global neurocritical care research between 2014 and 2024. Data were collected from the Scopus database, covering publications from 2014 to 2024. The search terms included 'neurocritical care' or 'neurological intensive care' or 'neuro ICU' or 'neurointensive care'. Bibliometric analysis was conducted using the Bibliometrix R package and VOSviewer. Conceptual structures were explored through co-occurrence mapping and thematic analysis. Social structures were examined through co-author analysis. A total of 2762 articles were retrieved from the Scopus database. Traumatic brain injury, seizure monitoring, stroke, paediatric neurocritical care and disorders of consciousness were among the themes identified as foundational in the field. In contrast, seizure, EEG and epilepsy emerged as motor themes based on their higher centrality and density values. Several clinically important areas, including intracranial pressure monitoring, ethics and palliative care, appeared to be less central within the neurocritical care research landscape. Social structure analysis indicated that high-income countries occupy more central positions in global neurocritical care research networks, while participation from low- and middle-income countries remains comparatively limited. While seizure-related research demonstrates strong thematic development, the broader integration of underrepresented areas, such as paediatric care, ethical decision-making and intracranial pressure monitoring, could contribute to more balanced scientific and clinical progress in neurocritical care. Nurses and multidisciplinary ICU teams should prioritise underrepresented but clinically important areas of neurocritical care. Targeted research, stronger collaboration and the use of advanced technologies in monitoring and decision-making can improve early risk detection, care planning and patient- and family-centred outcomes.

Purpose This study aims to examine the relationship between servant leadership (SL) and employee engagement (EE) and highlight the role that different mediators and moderators play in influencing their relationship. This study provides a thorough understanding of the existing literature, synthesizing the results of 30 empirical articles published between 2014 and 2025 and identifying research gaps for further investigation. Design/methodology/approach Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, the review carefully performs a systematic screening and selection procedure to find the most pertinent research articles. Finally, 30 articles were identified examining the direct and indirect relationships between SL and EE, focusing on individual and contextual contexts. Findings The majority of the analyzed studies − 23 out of 30 − show a direct and significant correlation between SL and EE conducted across industries. Nonetheless, the research studies demonstrate a deep understanding of the indirect link between SL and EE by studying mediators such as organizational support, meaningfulness and job satisfaction. Additionally, various moderators, including autonomy and employee proactivity, were found to either enhance or impede the relationship between SL and EE. Some studies suggest that the effectiveness of SL in fostering EE is contingent upon contextual or individual factors, thus questioning the link between SL and EE. Originality/value This study represents the first systematic literature review of SL and EE, with the direct and indirect relationships between these two constructs. It highlights the need for further exploration in underrepresented areas such as cultural context, mixed-methods research and the long-term effects of SL on EE. The review enriches academic literature and provides actionable insights for scholars and practitioners seeking to enhance leadership effectiveness and EE.

Urban and rural areas worldwide face growing challenges from rapid population growth, climate change, and resource constraints. Governments are responding by adopting smart city and smart village initiatives that use technology to promote sustainable development. Yet, academic research on these topics differs markedly across countries due to distinct policy priorities, development needs, and research contexts. This study performs a comparative bibliometric analysis of smart city and smart village publications in Indonesia, Malaysia, and Japan, using Scopus-indexed data processed with VOSviewer. Results show Indonesia has effectively integrated both domains, with research evolving from a technology focus toward collaborative governance and sustainability. Japan, meanwhile, emphasizes systematic, infrastructure-driven smart city development, but its smart village studies remain disconnected from key rural issues like depopulation and aging populations. In Malaysia, smart village research predominantly centers on biomedical and public health themes rather than technology-based rural advancement, revealing a clear research gap. These findings can inform policymakers on research prioritization, guide funding toward underrepresented areas, and aid in creating balanced measurement frameworks that align global standards with local realities. Ultimately, although smart development concepts are global, their academic exploration and practical application must be adapted to each country’s unique context.

Abstract Agroforestry systems (AFSs) are often considered a means to reconcile agricultural production with biodiversity conservation, yet the alignment between scientific research and practice remains poorly understood. In Brazil, a country with widespread AFS adoption, we conducted a systematic review of 631 publications (1982–2019) and integrated them with national Agricultural Census data to map the landscape of AFS research and implementation. Our analysis shows that while scientific output has accelerated, research efforts are geographically concentrated in the Atlantic Forest and Amazon biomes, leaving other major ecosystems like the Cerrado and Caatinga under-represented. A marked discrepancy was observed in the Northeast region, which hosts two-thirds of Brazil's AFS establishments but receives disproportionately low research attention. While simple, production-oriented AFSs were more frequently studied, biodiverse systems, particularly those with very high species richness, showed a clear association with family farming and traditional knowledge. Furthermore, regression models indicated that AFS prevalence is negatively associated with market-oriented production (commercialization), a finding consistent with their role in food sovereignty. These results point to persistent regional imbalances in the research agenda and suggest the need to strengthen knowledge production in underrepresented areas to better reflect the range of AFS practices in the country.

Biodiversity-focused contributory science platforms generate massive quantities of opportunistic records for research, but data are spatially, temporally, and taxonomically biased. While research attempting to quantify these biases abounds, less is known about how varied user motivations and behavior shapes how data accrue. Here, we compare how different iNaturalist user groups prioritize where and when they sample in the southeastern United States. We categorized users by participation level and traveler status, and examined how these groups differentially sample across land cover categories, urban and rural areas, protected land, urban parks, low-income urban neighborhoods, and weekends versus weekdays. We found that highly active users prioritize sampling in biodiversity-rich locations, filling data gaps in natural green spaces and rural areas while perpetuating biases toward protected areas and parks within urban areas. In contrast, casual users tend to primarily incorporate sampling into their daily lives, filling gaps within urban neighborhoods and on non-protected land while perpetuating biases toward developed areas. Local iNaturalist users, especially casual users, were the most likely to sample in low-income census tracts compared with travelers and are important for gap-filling in these underrepresented areas. Understanding how participants with different motivations shape opportunistic biodiversity data can inform contributory project planning and downstream data use. Our results emphasize the importance of recruiting new participants, retaining current participants, and engaging locals in contributory science programs. Further efforts to derive insight from opportunistic biodiversity data may benefit from accounting for variation in motivations of participants and resulting heterogeneity in biases across space and time.

This study explored the efficacy of chronotherapy combined with the Rational Emotive Behavior Therapy (REBT) for Generalized Anxiety Disorder. An experimental design was applied with the sample size of N=30 participants. The participants were selected from the province of Khyber Pakhtunkhwa (KPK) province. Generalized anxiety disorder-7 scale Urdu and DSM-5-TR was used to assess the participant’s symptoms of Generalized Anxiety disorder. Firstly, the pre and post-test was tested for the C-REBT (chronotherapy and REBT) and REBT. The results showed that both were significant difference in reducing the anxiety symptoms in pre and post assessment. Findings suggested that C-REBT (chronotherapy and REBT) therapy has significant effect in alleviating the anxiety symptoms as compared to using REBT alone. The study endorsed the multifaceted psychological intervention strategies. Moreover, the study promoted the ideology of better management of mental health issues disorders tailored as per the needs of individuals and promote better mental health services in the under-represented areas of Pakistan.

ABSTRACT This study investigates how practicum courses in Greek university programs for early childhood pre-service teachers integrate social sustainability within initial teacher education. We conducted a content analysis of nine Early Childhood Education curricula from universities across Greece, identifying seven categories related to social sustainability with an uneven representation. Our findings reveal a primary emphasis in these curricula on professional development and learning environments. Conversely, categories like social cohesion and justice, inclusion, information and communication technologies (ICTs), reflection and critical thinking, and inter/trans-disciplinarity were less consistently represented. This suggests that while Greek Early Childhood Education Departments prioritize the development of professional competencies and educational settings for social sustainability in practicum courses, a holistic approach of teacher preparation requires greater emphasis on fostering social cohesion and justice, inclusion, ICTs, reflection and critical thinking, and inter/trans-disciplinarity. Strengthening these underrepresented areas in the university curricula could significantly enhance early childhood pre-service teachers’ critical thinking skills, ultimately improving their capacity to promote social sustainability in early childhood education.

Commodities flow through trade networks across the world, with trajectories that can be effectively modelled using approaches similar to those used in human mobility studies. Yet, documenting these movements comprehensively is challenging due to data sparsity, cost, and privacy constraints. Origin-destination (OD) matrices provide a widely used framework for representing mobility, although they inherently omit locations not directly observed as either origins or destinations. This incompleteness creates gaps across different geographical scales, constraining our ability to characterise movement patterns in underrepresented areas. In this study, we introduce a vector-field-based method to address these persistent data challenges. By transforming OD data into continuous vector fields, we capture spatial flow patterns more comprehensively than traditional network approaches, while also enabling robust analysis of mobility directions. Our approach incorporates interpolation techniques that handle incomplete and sparse datasets effectively; when approximately 500 out of 853 areas are removed, 189 areas (36%) maintain degree deviations of less than 15 degrees, showing that the general direction of flow is preserved for over one-third of the impacted areas and enabling continuous spatial analysis. We apply this framework to cattle trade data from Minas Gerais, Brazil. Cattle movements are particularly significant as they directly impact disease transmission, including foot-and-mouth disease. Accurately modelling these flows supports effective disease surveillance and preparedness, with benefits for both animal health and economic stability. Our analysis reveals distinct spatial clusters of trade behaviour, temporal patterns in flow directions, and seasonally varying critical points likely associated with known periodicities in cattle trade driven by breeding cycles, slaughter schedules, and fluctuations in global demand. While previous vector-field studies focused on human mobility, our framework addresses the distinct challenges of commodity flows, where aggregated OD data, sparse observations, and lack of data are the norm. It enables inference in unobserved areas which is a critical capability for modelling scenarios such as disease spread. This approach enhances our capacity to infer flow patterns from incomplete datasets and advances understanding of large-scale commodity trade dynamics.