Cave plan repository: A standardized dataset for morphometric and geological analyses in speleology.

Proximity and positionality: Situating knowledge through the experiences of quantitative air quality data collectors working in participants' homes.

Advancing nonclinical blood pressure assessment: Current practices and future directions in drug development.

Development of a Mesh-type model for Canis familiaris and Monte Carlo simulations of radiation dosimetry parameters.

Why environmental scientists need ethics training more than ever before

Structural diversity and functional versatility of bacterial lactate dehydrogenases: Guideline for designing robust industrial enzyme.

Design and characterization of a novel vehicle-mounted dual-reactor smog chamber for controlled and real-world atmospheric process simulations.

Tracking the current situation and key paths of phosphogypsum harmlessness.

Closing Water Security Gaps in the United States: The Role of Environmental Engineers and Scientists.

The rapid and accurate identification of gas molecules in liquids is of critical importance for environmental science, biomedical research, and industrial process control. However, traditional techniques, such as gas chromatography-mass spectrometry, electrochemical sensors, and optical methods, often require complex sample pretreatment, can detect only a single gas, and frequently depend on specific indicators, limiting their real-time monitoring capability and the general applicability in gas detection. Here, we extend the concept of triboelectric spectroscopy (TES) to the in situ chemical analysis of gas molecules in liquids. This approach relies on the unique charge transfer patterns generated when a liquid droplet containing a specific dissolved gas molecules slides across an insulating surface. Based on TES, we have successfully identified six types of common gas molecules, including CO2, NH3, CH4, Ar, N2, and O2, with an identification accuracy of 96% and a detection limit of 0.02 mmol L-1. Furthermore, we demonstrate the practical utility of TES in complex biological matrices by efficiently detecting CO2 in plasma with a detection limit in the millimolar range. The measured TES peak charge transfer and total charge transfer exhibited strong linear correlations with CO2 concentration, with R2 values of 0.923 and 0.996, respectively, confirming a strong linear dependence and reliable predictability.

Research on pulmonary diseases and environmental factors has expanded rapidly, yet the field remains fragmented across exposure categories, disease outcomes and disciplinary boundaries, and its overall knowledge structure has not been systematically characterized.Data Sources: We conducted a bibliometric and knowledge-mapping study using 505 articles from the Web of Science Core Collection (WOSCC) and 489 records from PubMed, all retrieved on May 14, 2025.Study Selections: WOSCC was used to analyse publication trends, disciplinary structure, collaboration networks, thematic hotspots, co-citation patterns and funding profiles, whereas PubMed was used to assess country- and region-level productivity and international collaboration. Results: Publication output increased markedly after 2012 and remained consistently active from 2020 to 2024, while records indexed in 2025 were treated as partial-year data. The field was shaped primarily by Environmental Sciences, Public, Environmental and Occupational Health, and Toxicology, with relatively sparse collaboration networks and output concentrated in a limited number of authors, institutions and countries. Thematic analyses showed a clear evolution from broad exposure-disease associations towards more differentiated research on particulate matter, air quality, susceptibility, prevention and biological mechanisms. In particular, oxidative stress emerged as a key mechanistic hub linking environmental exposures with pulmonary injury and adverse respiratory outcomes. The intellectual base of the field was anchored in particulate pollution, inhalational exposure events and pulmonary function assessment. Research on pulmonary diseases and environmental factors has developed into a stable but still fragmented interdisciplinary domain, with current trends indicating a shift from descriptive association studies towards mechanism-oriented and prevention-relevant research.

The article deals with the creation and implementation of the Digital Analytical Platform of the Federal State Statistics Service (Rosstat DAP) as the core of the National Data Management System in the context of the digitalization of the economics. The authors have revealed and systematized the problems of the national statistics: fragmented data, high bur den on small and medium-sized businesses, lack of efficiency and evidence of information. The analysis of the normative evolution is used to formulate priorities of the development of statistics up to 2023: the transition to predictive analytics, ensuring trust in data, integration of sources based on the “one-stop shop” principle, personalization of services, staff development, international harmonization, transparency. The authors have described functional components of DAP: sample constructor, interactive visualization, statistical and network analysis, machine learning-based forecasting, application programming interface. It has been shown that the platform ensures the interaction of the state, business, science and society in a single digital environment on the principles of interdepartmental automation using the System of Inter departmental Electronic Interaction (SIEI), Unifi ed Identification and Authentication System (ESIA) and the Gostech platform. The results will be useful for the government authorities, large business and small and medium-sized enterprises, researchers and teachers.

ABSTRACT This curriculum-focused paper details the Critical Arts-Science-Advocacy Framework (CASAF), a three-part, multidisciplinary learning sequence for K-12 teacher education and geography education in the Anthropocene. Rooted in the author’s professional praxis from the 2023–2025 school years at a public university, CASAF emphasizes the need to move beyond the “green status quo” and “green business as usual” to take meaningful action for environmental teaching and learning. As environmental issues are not just a single-subject “science issue,” taking meaningful action for Earth justice requires a multidisciplinary approach that cultivates environmental science agency and uses arts-based educational research methods and pedagogy. In CASAF, students are guided through the following phases of the learning sequence: 1) Experiential learning and mapping emotional geographies; 2) Engaging in community science to explore campus biodiversity; 3) Zines for environmental storytelling and public pedagogy. This actionable framework will help prepare future environmental change agents and Earth justice practitioners.

Detection of N-nitrosamines (NA) in pharmaceuticals became a point of interest due to the mutagenic and carcinogenic potential of some compounds of this class, and their identification as nitrosated forms of marketed drugs, otherwise known as NA Drug Substance-Related Impurities (NDSRIs). The Ames test is used to assess the mutagenic potential of drug impurities, including NAs. Concerns over the sensitivity of the Ames test, as recommended in Organization for Economic Co-operation and Development Test Guideline 471, in predicting the rodent carcinogenic potential of NAs has prompted optimization of several test parameters used for detecting the mutagenicity of NAs (e.g. methods used for metabolic activation and the selection of tester strains). In order to discuss optimal Ames test conditions for the evaluation of NAs, including NDSRIs, the Office of New Drugs in the US Food and Drug Administration's Center for Drug Evaluation and Research and the Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee co-organized and co-sponsored a workshop entitled "Nitrosamines: Ames Data Review and Method Development Workshop". The workshop featured five sessions addressing charge questions pertinent to the Ames test conditions and performance through the presentation of data and panel discussions. This report outlines the key takeaway points from the workshop.

Purpose Extreme weather event exposure can be associated with a range of direct and indirect health and wellbeing impacts. There is a recognised need to improve the assessment of exposure to extreme weather, beyond mainstream epidemiology techniques and psychopathology, to include the subjective and individual experience of extreme weather events. In response, this study aims to outline the development and initial validation of a quantitative measure, the Rating Evaluation - Impacts of Extreme Weather (REvIEW), designed to assess the differential impacts of extreme weather events. Design/methodology/approach The REvIEW is a novel 29-item measure, developed in consultation with an advisory group consisting of multidisciplinary healthcare practitioners, academics and environmental scientists. An Australian mixed-method, cross-sectional study was conducted. The REvIEW assesses the extent of negative impacts from extreme weather events, with each item rated on a 6-point Likert scale. Findings The results supported the three domains of the REvIEW (livelihood, wellbeing and connection) and provide preliminary support for the use of this scale to quantitatively assess impacts from exposure to extreme weather events. Originality/value The REvIEW offers a novel approach to conceptualising and measuring the differential impacts of extreme weather event exposure, with the potential to inform multidisciplinary research and practice relating to understanding and responding to the impacts of extreme weather events.

Psychological and cultural determinants of intentions toward environmentally responsible behavior: A cross-cultural study in the tourism context.

This Perspective outlines the challenges addressed at the first Annual Parkinson's Disease (PD) Prevention Think Tank, held on November 20-21, 2025 in Gainesville, Florida at the Fixel Institute. Over the course of two days, attendees from a wide variety of disciplines, including movement disorders neurology, environmental sciences, agriculture, public policy, public health, patient advocate groups, and more, discussed the current state of primary prevention research in PD, examined the lessons learned from prevention research in other disorders, and identified necessary regulatory and policy actions for moving toward primary prevention of PD. Eight key components of primary prevention are identified (8 C's): accurately Count incidence and prevalence, Conduct longitudinal cohort studies, induce policy Change, Counsel on individual behavior change, Communicate clearly with the general public and with key stakeholders, form multi-centric Coalitions across neurodegenerative disorders, apply Cross-disciplinary approaches, and provide sustained financial Commitment to support ongoing prevention and mitigation efforts. These proceedings serve as an initial call-to-action for at-risk individuals, the clinicians who care for them, and for policymakers.

Remote sensing has rapidly advanced with the integration of deep learning, enabling more accurate and scalable detection of land use and land cover (LULC) changes, particularly with the increasing availability of Sentinel-1 and Sentinel-2 multispectral imagery. This review traces the evolution of classical machine learning approaches toward modern deep learning architectures, including Convolutional Neural Networks (CNNs), encoder-decoder models, Siamese and dual-stream networks, attention-based frameworks, and, more recently, Transformer-based models. Recent developments in Earth observation foundation models, trained on large-scale, multimodal datasets, have introduced new capabilities, including zero-shot inference, cross-sensor transferability, and improved generalization across diverse geographic regions. Despite these advances, significant challenges remain. The fusion of multimodal data, including optical, SAR, and ancillary sources, is complicated by differences in spatial, spectral, and temporal characteristics. Furthermore, domain adaptation, label noise, and limited geographic transferability continue to constrain the robustness of change detection pipelines. The quantification of uncertainty and model interpretability has also become increasingly important for operational applications in urban planning, agriculture, ecosystem monitoring, and disaster response. In addition, the growing computational and environmental costs of large-scale model pretraining underscore the need for more sustainable AI practices. Future research should therefore focus on advancing the Earth observation foundation and generative models, developing temporal AI methods for long-term sequence analysis, and promoting responsible, energy-efficient geospatial artificial intelligence. Integrating advances in remote sensing, machine learning, and environmental science will be essential for building practical, scalable, and reliable planetary monitoring systems.

Triclosan (TCS) is a common chemical antibacterial agent widely used in personal care and medical products. With its increasing application, TCS is continuously released into the environment, and its impacts on ecological systems and human health have garnered growing attention. In this study, research progress on triclosan was comprehensively reviewed through bibliometric methods. All relevant articles and reviews published between 2014 and 2024 were retrieved from the Web of Science Core Collection (WoSCC). Bibliometric analyses were conducted using VOSviewer, CiteSpace, and Bibliometrix software. The results revealed a total of 4,019 articles in the field of TCS research, involving 17,346 researchers from 435 institutions across 98 countries/regions, and were published in 891 journals. The annual output of TCS-related literature showed an increasing trend, with China and the UnitedStates publishing the largest number of articles. "Science of The Total Environment" was the most productive journal, publishing 316 articles, while "Environmental Science & Technology" received the highest number of citations (8,637 times). Current research focuses on the interactions between TCS and other environmental pollutants (e.g., microplastics and heavy metals), as well as its impacts on organismal health and removal/degradation mechanisms. These findings are expected to enhance the understanding of TCS research characteristics and provide guidance for future research directions.

Citizen science (CS) is increasingly used for research, environmental monitoring and policy input while enhancing participants' skills and well-being. However, it remains unevenly distributed globally, with limited presence in low- and middle-income countries, e.g. India, that are vulnerable to climate risks. This systematic review, following the PRISMA framework, identified 58 initiatives from academic and non-academic sources and analysed the scope and drivers of environmental and ecological CS projects in India. The findings reveal disparities in project diversity, geographic distribution and levels of participant engagement across the scientific process. Projects are concentrated in more affluent states and are predominantly biodiversity-focussed, with fewer addressing local socio-environmental concerns, highlighting the untapped potential of CS to address socio-environmental challenges in India. To scale its impact, we recommend strengthening linkages with government and academia, expanding thematic coverage and designing locally relevant projects with higher levels of public engagement aligned with policy needs.