Sustainability

BackgroundThe relationship between aesthetic appreciation and environmental values remains a critical yet under-researched area in environmental psychology. Although the Two-Major Environmental Values (2-MEV) model--encompassing preservation and utilization dimensions--serves as a standard framework for assessing environmental attitudes, the integration of aesthetic perception within this structure has largely remained unexplored. This study investigates the conceptual linkages across a diverse international sample to determine whether aesthetic appreciation functions independently of a traditional environmental value framework. Methods and FindingsWe conducted a large-scale, cross-sectional survey involving 11,800 pre- and in-service teachers across 34 countries. Participants environmental values were evaluated using the 2-MEV scale, while their aesthetic appreciation of nature and the built environment was assessed using Osgoods semantic differential technique. Employing principal component analysis, hierarchical exploratory factor analysis (EFA), analysis of variance (ANOVA), and within-class analysis (WCA), we accounted for cross-national variations and evaluated response consistency. The results demonstrate that aesthetic appreciation comprises two distinct dimensions-- focusing separately on nature and the built environment--that operate independently of traditional preservation and utilization values, showing only weak correlations. Furthermore, while the overarching psychological structure remains consistent globally, our findings reveal significant cross-national variations in respondent scores, particularly concerning utilization-related values. ConclusionsThese findings establish that aesthetic appreciation constitutes a distinct psychological construct separate from conventional environmental value frameworks. The observed cross-cultural variability underscores the necessity of accounting for national and cultural contexts when designing environmental education programs. By leveraging a robust, comprehensive global dataset, this study provides a vital empirical foundation for integrating aesthetic and value-based dimensions into future environmental research and educational policy.

Investigating Changes Detection in Land Use and Land Cover Analysis of Opencast Singareni Coal Mine Area Using Remote Sensing and GIS Techniques was the focus of the current investigation. Change Detection Analysis for Land Use Land Cover over a decade frequency (2005-2015) of cultivated soils surrounding OpenCast Coal Mine areas namely Ramakrishnapur, Srirampur and Medipalli of Telangana State.AWiFS data of IRS Resoursesat Satellite images of 2005 and 2015 were taken for the detection of temporal variation in Land use/ Land cover due to open cast coal mining.The ability of remote sensing techniques to produce precise spatiotemporal statistics of LULC and its changes in the typical coal mining region has been demonstrated, in open cast coal mining per year was the highest at Ramakrishnapur (@ 300 ha / year) followed by Srirampur (@ 150 ha / year) and Medipalli (@ 100 ha / year).At Ramakrishnapur with the onset of mining there was considerable decrease in agricultural land, shallow water bodies and deciduous forests i.e., conversion of these land uses to mining was evident. Whereas, at other two mining sites (Srirampur and Medipalli) conversion of scrubland followed by shallow water bodies, agriculture lands and deciduous forests into mining area was detected. However, the built-up land at all three-mining site was from cultivated lands and at Medipalli and Srirampur it was also contributed from scrubland. On the whole impact of open cast mining on deep water bodies was not detected. If the mining and surrounding regions continued and appropriate use of the land and water resources at hand, careful long-term planning is of utmost importance.

Currently, a significant proportion of young people are discouraged by the teaching of botany and, consequently, show little interest in preserving local biodiversity. On the other hand, with the recurrent use of digital technologies (DTs), young people have shown significant interest in virtual devices. Our project's tested the hypothesis whether plants awareness disparity in public school students was overcome through active teaching and learning. Thus, the objective was to investigate the use of active methodology in a non-formal teaching environment (e.g., sensory garden, SG) in order to stimulate learning in plant organography based on its evaluation using digital games. Our proposal was investigated at the Lagoa do Sino campus (Buri/SP, Brazil) in partnership with the Public School System of the Municipality of Campina do Monte Alegre/SP, Brazil. Furthermore, students were divided into two teams, which applied qualitative methodologies, such as that one of these (Team A) had face-to-face contact with the SG, using the Problem-Based Learning (PBL) methodology, digital game and survey. Team B, on the other hand, will only have contact with the game. After collecting the data, we verified statistically significant differences between the teams using the Wilcoxon test and based on the latent traits evaluated. Given this, the literature points out that discouraging students influences their learning and, consequently, their education. In addition, our considerations are based on the latent trait knowledge of botany and, thus, we reject our null hypothesis and accept our alternative hypothesis. On the other hand, based on the latent trait of plant perception, we cannot affirm the acceptance or rejection of the hypotheses. It is worth noting that future studies should have a larger number of participants than this research in order to better evaluate what is intended.

Extensive green roofs are an important component of urban green infrastructure. However, harsh rooftop conditions, including shallow substrates, high temperatures and limited water availability, considerably restrict plant selection. Although extensive green roofs are traditionally dominated by succulent species, increasing attention has been directed towards annual plants because of their rapid establishment, developmental plasticity and potential contribution to vegetation diversity. This review aimed to identify annual plant species introduced on extensive green roofs and to characterize the functional traits most frequently associated with their establishment under rooftop conditions. In addition, the review examined the geographical distribution and methodological characteristics of existing studies and identified species with potential for application under temperate climatic conditions. A total of 22 studies published between 2015 and 2025 were analyzed, comprising 100 annual species representing 29 plant families. The reviewed studies showed a clear geographical bias towards Mediterranean and arid regions, whereas temperate climates were considerably underrepresented. Among species occurring in Central Europe, ruderal life strategies, drought avoidance, efficient dispersal mechanisms, low plant height and prolonged flowering were the most frequently observed functional characteristics, while seed mass and specific leaf area (SLA) exhibited substantial interspecific variation. These findings suggest that functional traits, rather than taxonomic affiliation alone, provide a useful framework for selecting annual species for extensive green roofs. The review also highlights the need for long-term studies conducted under temperate climatic conditions to improve evidence-based plant selection and support the development of resilient and multifunctional green roof vegetation.

Cancer prevalence is distributed unevenly across regions and caused by the interaction of multiple risk factors. Previous studies focused on the use of global modeling techniques to predict cancer at the county level that overlooks important spatial differences. This study aims to develop geographically weighted machine learning models to predict cancer prevalence at the census tract level in the United States and identify local determinants of cancer burden. First, a scoping review was conducted to find a list of measurable drivers of cancer in the United States. Using this list, the data of these variables for 84415 census tracts were obtained from the Center for Disease Control and Prevention PLACES dataset and other publicly accessible resources. Then, several predictive models, including Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR), as well as Random Forest, XGBoost, and Deep Neural Network and their geographically weighted counterparts, were developed and compared using the Coefficient of Determination, Root Mean Square Error, and Absolute Error. Results presented that geographically weighted models outperformed other methods, and geographically weighted XGBoost achieved the strongest and most consistent overall performance with pseudo-R2 ranging between 0.89 and 0.98. Feature importance analysis of this model illustrated that most important cancer drivers changed location by location. Aged people, racial composition, preventative behaviors, and metabolic conditions such as diabetes, hypertension, and high cholesterol were determined as influential predictors, although their relative importance varied across regions. These findings revealed the value of localized models at a small geographic scale to identify regional cancer risk patterns and help the allocation of proper resources to hotspot areas. Keywords: Cancer prevalence, Census tracts, geographically weighted machine learning models, Deep neural network, XGBoost, Random Forest, Ordinary Least Squares, risk factor, determinant

Active teaching methodologies have been widely used to promote meaningful learning and student autonomy. In this context, quantitative approaches can help assess how students organize and integrate knowledge throughout the learning process. Among these approaches, semantic co-occurrence networks stand out, as they are capable of identifying relationships between words and revealing the conceptual structure of textual productions. The objective of this study was to investigate whether semantic network analyses can characterize differences in students conceptual organization in Microbiology during their participation in the active teaching methodology "Adopt a Bacterium." To this end, a case study was conducted in the Bacteriology course at the Institute of Biomedical Sciences of the University of Sao Paulo, analyzing the textual productions of two groups of students in the years 2024 and 2025 during their study of the bacterial genus Bacillus. The texts were evaluated using semantic co-occurrence networks, taking into account metrics of structure and conceptual integration. The results showed that both groups covered the microbiological content outlined in the course, though with different thematic focuses and approaches to integrating the concepts. Although both years featured modular structures (a statistical mode of 9 subgraphs), in 2025 the network exhibited greater discursive robustness (2 to 4 times more words with high Betweenness centrality) than in 2024. It is concluded that semantic network analysis allows for the characterization of differences in conceptual organization among students using active learning methodologies, serving as a complementary tool for assessing meaningful learning in Microbiology.

The health and wellbeing of living organisms and the environment are irrevocably interconnected. Animals constantly shape the environments in which they live, and environmental factors, in turn, shape the minds and behaviours of animals. The emerging discipline of environmental neuroscience studies this reciprocal interaction and offers a unique opportunity to integrate sustainability into undergraduate training. Here, we present and evaluate Forging Sustainable Research, an interdisciplinary undergraduate course that integrates teaching of neuroscience, biology, psychology, environmental science, and sustainable development. Students explore how research in these fields can be interlinked 24 and re-oriented towards addressing emerging environmental challenges. In parallel, students learn how to measure and mitigate the environmental impact of research activities. Student feedback suggests that the course is effective at raising awareness and understanding of sustainability in research, while also enhancing student perception of their own ability to promote positive change. As climate and ecosystem change impact all sectors, sustainability awareness in academic and professional spaces is increasingly sought after. Students in the course therefore receive training in transferable skills relevant for diverse career paths. In the long term, this course may serve as model for direct integration of sustainability training into undergraduate curricula in the natural sciences.

Small-scale fisheries provide essential coastal livelihoods in developing regions, yet they often confront severe institutional voids within fragile-state contexts. Adopting a social-ecological systems framework, this study addresses three sequential objectives: characterizing the contemporary institutional and demographic status of fishery cooperatives across the five South-Central Federal Member States in comparison to their late-1980s historical peak; ranking the socio-economic, infrastructural, regulatory, and environmental impediments to cooperative efficacy; and evaluating the contributions of these cooperatives to sustainable fisheries development. This investigation analyzes how fishery cooperatives act as institutional intermediaries to bolster economic resilience within the Somali coastal economy--a sector central to the National Transformation Plan, despite persistent regulatory fragmentation. Through semi-structured qualitative interviews with key informants--analyzed via reflexive thematic analysis and chi-square testing of age-cohort structure--the study finds that illegal, unreported, and unregulated fishing and inadequate post-harvest infrastructure are the principal constraints, whereas training, education, and community collaboration constitute the primary contributions. The results characterize these cooperatives as hybrid institutions that compensate for limited central-state capacity in remote coastal settlements while serving as intermediaries for the Federal Ministry of Fisheries and Blue Economy where co-management mandates are implemented. By extending the actor-community dimension of the SES framework to include age-cohort structure, this research demonstrates that clan-based reciprocal arrangements can serve as functional substitutes for Ostroms first design principle in contexts of persistent fragility. The study recommends multi-stakeholder partnerships to advance targeted capacity-building, financial literacy, and technological integration, and suggests future research into the post-harvest and retail sectors to examine the role of women in the Somali blue economy.

Funding and publishing scientific research has become increasingly competitive, highlighting a growing need for clear and accurate scientific communication. Scientific editors are professionals who help ensure that grant proposals and research manuscripts meet the standards of funding agencies and peer-reviewed journals while effectively communicating research significance to diverse audiences. However, detailed information characterizing the scientific editing profession is scarce. While some organizations have conducted salary surveys, to our knowledge, no comprehensive survey of the scientific editing field has been conducted. Here, we report findings from a 2024 comprehensive survey of 132 scientific editors. We collected data on demographics and education, career experience and current employment, skills and types of editing, and outcomes and satisfaction. Our data reveal that scientific editors have homogenous demographic characteristics but considerable variability in job titles, employment mechanisms, and career pathways. As the responsibilities of many scientific editors, including supporting proposal development, applying best practices in grantsmanship, and identifying strategies to enhance competitiveness for research funding, overlap with those of research development professionals, our findings provide considerations for further incorporating or defining the role of scientific editors within research development offices. Our results also suggest avenues for scientific editors to start or advance their careers. We anticipate that our results will serve as a foundation for discussions on the future directions of the scientific editing profession as well as areas for future research and professional development.

Heavy metal contamination in soil systems is an escalating global crisis, yet over 55% of urban agriculture literature focuses on high-tech indoor vertical farming, leaving vulnerable open-field tropical urban agriculture (UPA) severely under-researched. This study addresses this knowledge gap by evaluating the chemical mechanics of heavy metal translocation within highly acidic Xanthic Ferralsols in Fendall, Liberia, serving as a global proxy for tropical agro-ecosystem risks. Using a randomized complete block design, topsoil (0-20 cm) from five cultivated and five uncultivated sites (n = 10) and corresponding tissues of cabbage (Brassica oleracea), lettuce (Lactuca sativa), and sweet potato greens (Ipomoea batatas) were screened via handheld X-ray fluorescence spectrometry. Results revealed a compelling geochemical paradox: uncultivated soils demonstrated significantly higher geogenic background metal concentrations across all elements (p < 0.05). Systemic Nickel (Ni) above the World Health Organization (WHO) thresholds was recorded on both land-use histories. While plant tissues accumulation of Copper (Cu) and Zinc (Zn) remained within safe parameters, Lead (Pb) concentrations across all crops profoundly exceeded food safety standards, averaging 1.53 mg/kg, which is over 5 times above the WHO limit (0.30 mg/kg). Risk screening highlighted high soil-to-plant transfer factors (TF =>1) for Ni and Zn in plant tissue, in the order of cabbage > sweet potato greens > lettuce. These findings provide transferable insights into how high soil acidity accelerates toxic metal mobilization, offering a scalable framework for crop-specific exclusion policies and real-time field screening in tropical municipalities. AbstractRapid urban agricultural expansion in Montserrado County, Liberia, relies heavily on highly weathered acidic Xanthic Ferralsols. While these soils support crop growth, they present a hidden geogenic risk of heavy metal translocation to the human food chain. This study evaluated the concentrations of Copper (Cu), Nickel (Ni), Lead (Pb), and Zinc (Zn) in the soils and edible tissues of cabbage (Brassica oleracea), lettuce (Lactuca sativa), and sweet potato greens (Ipomoea batatas) in Fendall. The uncultivated soils exhibited a geochemical paradox, showing significantly higher total metal concentrations than cultivated plots. However, low soil pH (4.0-6.0) highly mobilized these geogenic metals, driving rapid plant uptake. While tissue concentrations of Cu, Ni, and Zn remained within safe physiological ranges, Lead (Pb) concentrations in all three crops reached an alarming mean of 1.53 mg/kg, exceeding the World Health Organization (WHO) permissible safety limit of 0.30 mg/kg by more than 5-fold. The soil-to-plant Transfer Factors (TF) for Lead ranged from 0.51 to 0.81, highlighting significant bioavailable translocation despite the lack of visible crop phytotoxicity. These results demonstrate that passive geogenic metal uptake poses a silent public health threat. Immediate agronomic interventions, including systematic liming and crop-exclusion frameworks, are urgently required to safeguard urban food security in Monrovia. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/740606v1_ufig1.gif" ALT="Figure 1"> View larger version (111K): org.highwire.dtl.DTLVardef@1171648org.highwire.dtl.DTLVardef@b7f56eorg.highwire.dtl.DTLVardef@15227e6org.highwire.dtl.DTLVardef@b996bf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background: Stress research in nursing education has largely focused on distress, stressors, and negative outcomes, although challenging experiences may also support motivation, confidence, learning, and growth when appraised positively. Objective: To develop and evaluate the psychometric properties of the Nursing Student Positive Stress Scale (NSPSS). Design: A methodological instrument development and psychometric evaluation study. Methods: The NSPSS was developed using a deductive, theory-driven approach informed by the transactional theory of stress and coping and positive psychology perspectives. Content validity was assessed by an international nursing expert panel. Psychometric evaluation used national survey data from nursing students in New Zealand. Of 539 responses, 507 were analysed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted using separate subsamples. Internal consistency was assessed using Cronbach's alpha and McDonald's omega, and convergent validity through correlation with Perceived Stress Scale-10 scores. Results: Content validity was strong (I-CVI = .88-1.00; S-CVI/Ave = .975; S-CVI/UA = .800). EFA identified a dominant factor explaining 41.38% of variance (loadings = .528-.735). CFA supported a two-context Academic and Clinical Positive Stress model with correlated residuals between five parallel item pairs, chi-square(29) = 60.49, CFI = .970, TLI = .954, RMSEA = .063, SRMR = .065. Internal consistency was good (alpha = .839; omega = .843). NSPSS scores correlated negatively with PSS-10 scores (r = -.298, p < .001). Conclusion: The NSPSS demonstrated strong content validity, preliminary evidence of structural and convergent validity, and good internal consistency reliability for assessing positive stress appraisal among nursing students. Further validation in independent samples is warranted.

Background: Neuroanatomy poses a significant challenge for Psychology students due to its spatial and conceptual complexity. Educational approaches that enhance the relevance and visualization of neuroanatomical content may improve students learning experiences. This study implemented a tractography-based activity focused on the virtual dissection of the arcuate fasciculus, a major white matter pathway, in undergraduate Psychology students and examined the relationships between perceived learning and students perceptions of utility, difficulty and handling, and organizational aspects of the activity. Methods: First-year undergraduate Psychology students participated in a two-session tractography-based activity combining instruction on white matter anatomy and diffusion tractography with a hands-on virtual dissection of the arcuate fasciculus using research-grade software routinely employed in neuroscience research. Following the activity, students completed an anonymous questionnaire assessing perceived learning, utility, difficulty and handling, and organizational aspects of the activity. Pearson correlations, multiple regression analyses, and relative importance analyses were performed. Results: Sixty-eight students completed the questionnaire. Students reported generally positive perceptions of the activity across the evaluated dimensions, with perceived learning receiving the highest mean score (M = 3.44, SD = .85). Perceived utility showed the strongest association with perceived learning (r = .64, p < .001). The regression model explained 41% of the variance in perceived learning (R2 = .41, adjusted R2 = .38, p < .001). Perceived utility was the only significant predictor in the model ({beta} = .59, p = .001), accounting for 67.9% of the explained variance. Conclusions: The findings support the feasibility of integrating authentic neuroimaging tools into undergraduate neuroanatomy teaching. Students who perceived the activity as more useful also reported higher perceived learning outcomes, with perceived utility emerging as the strongest predictor of perceived learning. In contrast, perceived difficulty and handling, and organizational aspects did not make significant independent contributions. These results suggest that students perceptions of educational relevance may play an important role in technology-enhanced STEM learning experiences.

This paper presents a comparative analysis of the floristic composition and site characteristics of four peat bogs in Bucovina, Romania: Poiana Stampei, Romanesti, Saru Dornei, and Gaina-Lucina. The research was based on phytosociological releves on 25 msq plots and direct field phenological observations, on six field visits from May to August 2026. Vegetation was characterised using the Braun Blanquet method, and floristic similarity between sites was assessed with the Sorensen and Bray Curtis indices. All four plots shared a common core of taxa characteristic of peatland vegetation: Sphagnum spp., Carex rostrata, Drosera rotundifolia, Eriophorum vaginatum, and Vaccinium species. Species richness was 13 taxa at Poiana Stampei, Romanesti, and Saru Dornei, and 12 at Gaina-Lucina. Romanesti and Saru Dornei showed the highest floristic similarity (descriptive values, not statistically tested, given a single releve per site), while Gaina-Lucina differed most markedly, not through species richness, which was similar across sites, but through species identity and through the presence of Betula nana, a glacial relict absent from the other sites. The results provide a descriptive basis for future research on the floristic composition and conservation of these habitats.

PurposeDiscussions surrounding the biomedical faculty job market often focus on applicant competitiveness and external metrics such as number of publications and funding records. Consequently, there is typically less discussion about applicant readiness, the point at which applicants perceive themselves as prepared to enter the market. Since 2018 our group, the Faculty Job Market Collaboration (FJMC), has conducted annual end-of-cycle surveys of biomedical faculty job applicants, producing the largest longitudinal dataset on this process to date. MethodsWe employed a mixed-methods design examining faculty applicants in biological science fields in North America. Regression analyses were conducted on a longitudinal dataset of 729 respondents across multiple hiring cycles. To determine how applicants evaluated their own preparation, qualitative interviews were conducted with a separate cohort of biomedical postdoctoral applicants during the 2024-2026 job cycles. ResultsOur findings demonstrate that rather than depending on a single quantitative threshold, readiness is a multifaceted construct shaped by actionable and interpersonal drivers. Key factors influencing an applicants perceived readiness include taking agency to submit applications, receiving explicit support from a mentor, incorporating strategic use of artificial intelligence tools into application preparation, and their career stage. ConclusionBy distinguishing individual readiness from systemic assumptions of market competitiveness, this study highlights a blind spot in academic workforce development. Our results suggest that applicants can achieve readiness and successful outcomes through different combinations of support, strategy, and timing rather than a uniform metric profile. By integrating quantitative and qualitative data, our study provides an evidence-based framework for understanding applicant readiness and offers practical guidance to help trainees navigate the increasingly competitive academic job market. Teaser TextOur mixed-model analysis of the biomedical faculty job market is designed to help prospective faculty candidates assess their readiness to enter the job market. By integrating multiple indicators of academic productivity, funding success, and professional experience, our study provides evidence-based benchmarks that can guide applicants in evaluating their competitiveness and identifying areas for further development before pursuing faculty positions.

The global market concentrates extractive pressure on lands held by Indigenous peoples, including peoples living in isolation, for whom free, prior and informed consent cannot be obtained and protection must therefore rest on territorial instruments. Halmahera, Indonesia, holds some of the worlds largest lateritic nickel reserves beneath a lowland rainforest inhabited by the Hongana Manyawa, yet the trajectory of land use and cover change across the island has not been quantified. We characterised land use and cover change over the 17,437 km2 island between 2014 and 2024 using MapBiomas time series, and projected a business-as-usual scenario to 2054 with a stochastic cellular-automata model implemented in Dinamica EGO, calibrated with weights of evidence on eight variables describing mining and logging concessions, transport infrastructure, settlements and previous clearing. Forest covered 83.0% of the island in 2014 and 82.1% in 2024; under unchanged policy it falls to 73.7% by 2054, a net loss of 162 thousand ha, or 11.2% of the 2014 baseline, at gross rates of 47,000-51,000 ha per decade. Deforestation probability is highest within 500 m of previous clearing and declines with distance from settlements, cities and mining sites, while proximity to national parks carries a negative weight of evidence. The frontier is self-propagating and spatially predictable, and legally designated territory retains forest within it. Protecting the Hongana Manyawa consequently depends on excluding extractive licensing from the interior forest ahead of the frontier rather than behind it.

Purpose: The internship period is a critical stage for nursing students to develop professional values. This study aimed to investigate the current status of professional identity among nursing interns, analyze the effects of social support, perceived stress, psychological resilience, and career adaptability on professional identity, and explore the mediating role of career adaptability between social support and professional identity, so as to provide empirical evidence for enhancing professional identity and optimizing nursing talent training systems. Methods: Using convenience sampling, 407 nursing interns from a tertiary hospital in Quanzhou were selected as participants from May to July 2025. Data were collected using a general information questionnaire, the Social Support Scale, the Perceived Stress Scale, the Psychological Resilience Scale, the Professional Identity Questionnaire for Nursing Students, the Career Adaptability Scale, and the Questionnaire for Nurse Intention to Retention Employed. SPSS 26.0 was used for reliability analysis, descriptive analysis, independent samples t-test, one-way ANOVA, Pearson correlation analysis, and multiple linear regression analysis. The PROCESS macro was employed to test the mediating effect. Results: The total score of professional identity among nursing interns was (61.74{+/-}11.08), with 73.5% showing moderate professional identity. Parents' attitude toward nursing, reasons for choosing the profession, personal attitude toward the major, and employment intention showed statistically significant differences in professional identity scores (p<0.05). Pearson correlation analysis revealed that professional identity was significantly positively correlated with social support (r=0.474), psychological resilience (r=0.389), and career adaptability (r=0.609) (p<0.01), and significantly negatively correlated with perceived stress (r=-0.378) (p<0.01). Multiple linear regression analysis indicated that career adaptability ({beta}=0.309, p<0.001) and social support ({beta}=0.383, p<0.001) were significant positive predictors of professional identity, whereas reasons for choosing the profession ({beta}=-3.603, p=0.001) and employment intention ({beta}=-7.116, p<0.001) were significant negative predictors. The model explained 49.2% of the variance in professional identity. Mediation effect analysis showed that career adaptability played a partial mediating role between social support and professional identity, with a mediation effect value of 0.288 (95% CI: 0.221-0.363), accounting for 40.2% of the total effect. Conclusions: Nursing interns' professional identity is at a moderately high level. Social support and career adaptability are positive influencing factors. Career adaptability plays a partial mediating role between social support and professional identity; social support indirectly enhances professional identity by strengthening career adaptability.

The growing concerns due to plastic pollution in India have intensified the search for sustainable materials. Mycelium-based composites (MBCs) have emerged as bio-based alternatives for packaging and thermal insulation applications. India, the worlds largest producer of bananas, generates significant quantities of banana biomass (~200 tons per hectare per year), much of which remains underutilized. The banana peduncle, the stalk that supports the fruit bunch, is one such underutilized biomass. In this study, banana peduncle fibers were used as the main substrate with Pleurotus ostreatus for the fabrication of MBCs. Banana peduncle fibers were mixed with wood shavings (10-50 wt%) to enhance the dimensional stability and structural integrity of the composites. The properties of developed MBCs such as density, shrinkage, moisture absorption, water absorption, morphology, compressive properties, and thermal conductivity were studied. The 90% banana peduncle fibers-10% wood shavings formulation showed the highest radial mycelial growth rate (7 mm/day). MBCs consisting of 100% banana peduncle fibers had volumetric shrinkage of 36%, while the incorporation of 30-50% wood shavings reduced shrinkage by approximately 17%. Among the formulations, MBCs containing 30% wood shavings had the highest compressive strength (4.82 MPa) and compressive modulus (1.78 MPa), whereas MBCs containing 50% wood shavings had the highest recovery (59.6%). In contrast, MBCs fabricated using 100% banana peduncle fibers had the lowest thermal conductivity (0.04 W/m. K). These results demonstrate that banana peduncle fibers are a promising lignocellulosic substrate for the development of MBCs for sustainable packaging and thermal insulation.

Environmental concerns and the need to mitigate the effects of climate change have driven the adoption of renewable energy sources, such as offshore wind farms (OWFs), making it essential to assess their overlap with seabird habitats to estimate potential impacts. This study is the first to estimate the vulnerability of coastal and seabirds to OWFs at a national scale by integrating biological trait data from the literature, spatial occurrence records from citizen science platforms, and expert knowledge (elicited from 23 specialists) into established quantitative risk frameworks. Collision risk and susceptibility scores were calculated at the family and subfamily levels, as well as disturbance and displacement indices by species and susceptibility by state. The groups with the highest collision risk and susceptibility were Fregatidae (0.354; 0.486), Sulidae (0.199; 0.419), Sterninae (0.190; 0.384) and Diomedeidae (0.190; 0.416). The extreme risk for Fregatidae is driven by their specific flight characteristics, with impacts concentrated in the highly frequented southeast and northeast regions. Regarding disturbance and displacement, Limnodromus griseus exhibited the highest national score (MMA: 0.098), while Diomedea dabbenena had the highest global score (IUCN: 0.092), highlighting the critical need to integrate both regional and global conservation statuses. Spatially, the state exhibiting the highest overall vulnerability to OWF impacts was Rio Grande do Sul (23.78; 10.69), a critical hotspot characterized by high species richness and oceanographic productivity. These findings establish an indispensable national baseline for Marine Spatial Planning, reinforcing the need for targeted pre-installation assessments, the identification of sentinel species, and spatially differentiated management during environmental licensing processes.

The tidal wetlands of Louisiana comprise about 25% of those found throughout the conterminous United States yet estimates of wetland loss rates in the region between 1932 and 2016 have exceeded 60 km2 yr-1. To mitigate further degradation and wetland loss in the region, a globally unprecedented $50B, 50-year plan for coastal Louisiana is driving restoration efforts, and demand exists from multiple stakeholders for regularly updated, regional-scale, accurate land cover information. We used machine learning (random forests; RF) and cloud computing to develop a new Landsat-based, marsh vegetation community geospatial dataset. The dataset depicts wetland vegetation community types defined in a previous study at annual (1985-2025) time steps at 30-m resolution. An RF algorithm was used to integrate training samples with feature variables derived from Landsat imagery, and the resulting geospatial data product achieved an overall correct classification rate of 78%. The approach for development of the land cover dataset presented here has potential for application in other coastal wetland habitats throughout the world.

Abstract Unplanned Extubation is a frequent adverse event in Neonatal Intensive Care Units (NICUs), that is associated with increased morbidity, prolonged hospitalization and financial costs. Evidence suggests that unplanned extubation (UE) is preventable through the management of its risk factors. Many modifiable UE risk factors are directly related to nursing care, thus empowering nurses through education can improve neonatal safety outcomes. This study aimed to evaluate the effectiveness of a structured educational intervention in improving nurses knowledge and practices related to UE in NICUs. A quasi-experimental pretest-posttest study was conducted in two tertiary hospitals in northern Jordan. One hospital is university-affiliated and one is governmental hospital. Participating Nurses in the selected settings received a four-week multimodal educational intervention related to UE. The intervention comprised of face-face session, WhatsApp-based educational messages, educational videos and placement of a poster in the NICU. Knowledge and practices of 58 nurses were assessed at baseline, post intervention and one month later using a validated questionnaire and direct observation. A baseline rate of UE was also measured in both settings with rate of 5 events per 100 ventilator days in the university-affiliated compared to 32 events per 100 ventilator days in governmental hospital. Repeated-measures and mixed-design ANOVA revealed significant improvements in nurses knowledge in both settings with a large effect size (p{superscript 2} = .60). Also, the observed preventive practices scores also improved significantly and remained elevated at one-month follow-up (p{superscript 2} = .50). Older age was associated with lower baseline knowledge, though this was diminished post study intervention. Whereas no demographic variables were associated with practice scores. The high rates of UE highlight the need for quality improvement. Study findings suggest that UE-focused education is a feasible and cost-effective strategy for strengthening neonate nurses competencies regarding safer care for mechanically ventilated neonates in the NICUs.