Novel sustainable carbon dot as dual replacements for emulsion stabilizers and Photoinitiators in macroporous polymerized high internal phase emulsion fabrication.

Biocatalytic hydrogen-bonded organic frameworks: Design and biomedical applications.

Artificial intelligence-driven non-targeted screening: Applications and prospects in environmental and food sciences

This work aimed at the use and understanding the impact of education in solving the growing environmental pollution and radiation exposure, which are both attributed to natural phenomena and human activities. It's a case study of two different universities in Libya namely; Omar Al-Mukhtar University, of Natural Resources and Environmental Sciences and Qubba Branch, University of Derna, Libya that are willing to utilize their knowledge in mitigating and combating environmental pollution. The total population of students studying environmental science and environmental education in these universities is 425, whereby, 402 students responded to the questionnaire used in the current study. This questionnaire comprises of four sections; socio-demographic section, knowledge, concern, willingness and behavior. Whereby; knowledge/environmental education was considered as the dependent variable while the other variables are considered as the independent variables. Descriptive statistics of the data using graphical representation of the obtained results demonstrates that 82.2% of the students respond with 5 and above (on a scale of 1 to 10), indicating that they know the major environmental pollution. Also, 45% of the students respond with 9 and 10 in demonstrating that they have knowledge on the major causes of environmental pollution. Furthermore, 72.2% of the responders responds with 6 and above to indicate that they know the major solutions for environmental pollution and based on this answers, interpretable artificial intelligence was used to determine the impacts of the independent variables on the targets. Overall, the performance results demonstrated that GPR-BO-M2 showed the highest performance among all the combinations used in modelling stage with R2-values = 0.951/0.937, RMSE = 0.684/0.651, MSE = 0.467/0.424 and MAE = 0.263/0.232. Hence, the results obtained in this work can be utilized by students, educationist, policy makers and experts in understanding and mitigating environmental pollution.

Stakeholder is a contested term that has spawned a multitude of ad hoc definitions. The ambiguity of these definitions has oftentimes impeded transdisciplinary research in environmental governance and conservation science because it hampers effective communication and operationalization of the stakeholder concept. We devised a project-configurable definition of stakeholder that integrates 2 stakeholder typologies: the holder types of Schmitter (e.g., knowledge, right, space, and interest holders) and the salience model (power, legitimacy, urgency, and proximity) of Mitchell etal. From a conceptual perspective, we synthesized role-based and salience-based views of stakeholder to the following definition: a stakeholder is someone who takes on one or several different roles relating to an issue for whom that issue has a certain baseline level of priority. Building on this definition, we produced a 6-step conceptual stakeholder identification workflow. The workflow combines expert discussion, structured stakeholder scoring, and iterative validation to narrow an initial actor universe to a transparent and defensible stakeholder set. We applied the method to a hypothetical peatland rewetting project in Central Europe to showcase how network boundaries and salience thresholds can be refined in order to move from an initially large set of actors to a documented and manageable set of stakeholders. Our definition of stakeholder and the identification workflow aim to offer scientists, managers, and policy makers a transparent tool for selecting, ranking, and justifying the actors who most urgently need to be at the table.

Abstract This study presents the first large-scale bibliometric analysis of academic research applying Geographic Information Systems (GIS) to explore the relationship between climate change and immovable cultural heritage. Drawing on 82 English-language publications indexed in the Web of Science Core Collection (1994–2024), the study maps the field’s evolution over the past three decades. Results show a steady increase in publications and citations, reflecting the growing importance of GIS as a methodological bridge linking environmental sciences, geosciences, and heritage management. Research has primarily focused on climate risk assessment (CRA), particularly hazard, exposure, and vulnerability mapping, while studies addressing adaptation planning or governance remain limited. The prominence of environmental and geoscientific disciplines underscores strong technical foundations, yet collaboration across social and policy domains remains fragmented. The relatively modest use of AI-based modelling and remote sensing also points to untapped potential for technological innovation. Overall, the findings indicate a rapidly expanding but still consolidating research landscape and highlight the need for greater interdisciplinarity, interoperable data infrastructures, and integrative approaches to support evidence-based heritage management and climate adaptation.

Biomimicking has inspired several designers, architects, and engineers. Mimicking nature's elegant designs, which are produced through a thorough and elaborate process of natural selection, is a familiar concept in human civilization. [1]. Plants dominate the earth, and all biodiversity depends on them [2]. Humans are no exception, as we depend heavily on plants for our livelihood, food, industry, and innovation. Nanotechnology, an emerging field of the 21st century, has also drawn inspiration from plants for the development of new-age nanosensors. Advanced research in nanosensing technology holds a promising future in various fields, including medicine, agriculture, ecology, environmental science, robotics, and photonics. This article addresses cutting-edge nanosensing technology inspired by plants. It also has the potential to lead to a sustainable future. This study explores the following areas. (1) Key concepts of bioinspired nanosensing technology (2) Emerging plant-inspired nanosensing technologies in various fields (3) Concerns and ethical issues.

The respiratory system constitutes the primary interface between the human body and the external environment, demonstrating particular vulnerability to chemical toxicants through diverse exposure routes. Current regulatory frameworks face significant limitations in respiratory toxicity assessment, relying predominantly on expensive and low-throughput animal testing methods while lacking systematic premarket evaluation protocols. To address these challenges, we developed GFEnet, an innovative multimodal deep learning (DL) framework that synergistically integrates molecular graph features, structural fingerprints, and electron-level properties for comprehensive cross-scale respiratory toxicity prediction. The model was rigorously trained and evaluated across three toxicological dimensions, including in vivo mammalian respiratory toxicity, in vitro A549 cell cytotoxicity, and ACE2 gene regulation activity. GFEnet demonstrated exceptional predictive capability, achieving outstanding AUC values of 0.986, 0.965, and 0.919 on the respective test sets, substantially outperforming conventional machine learning algorithms and single-modality DL architectures. Systematic ablation studies confirmed the critical contribution of each feature modality to the model's predictive power. When applied to screen compounds from substances of very high concern and air pollutant databases, GFEnet identified fluorene-9-bisphenol and Michler's ketone as high-priority risk candidates exhibiting consistent toxicity across all evaluation end points. Subsequent in vivo validation using mouse models confirmed these predictions, demonstrating that both compounds induce significant pulmonary function impairment and histopathological damage. This study establishes GFEnet as a robust high-throughput screening platform for the early identification of respiratory toxicants, effectively bridging computational toxicology with environmental health protection and regulatory science.

Long-read sequencing (LRS) has transformed life science research by introducing third-generation sequencing (TGS) platforms applicable across various research fields, including environmental sciences. In the past decade, LRS platforms have been utilized to extensively study algal systems by improving genomic approaches such as metabarcoding, chromosome-level genome and pangenome assemblies, as well as providing new insights into algae-associated microbiomes and host-symbiont interactions. This review aims to discuss recent advancements in LRS in algal research. To achieve this aim, a systematic review was conducted according to the PRISMA 2020 guidelines and across three electronic databases (Web of Science, Scopus, and Google Scholar), with additional citation searching for relevant studies in four key algal research areas: metabarcoding, genomics, pangenomics, and host-symbionts interactions. Following the inclusion and exclusion criteria, only 51 studies were selected for this review. Throughout the review, we summarize the challenges of short-read sequencing (SRS) and discuss how LRS platforms address these challenges in algal studies. Furthermore, we discuss the future of LRS and explore how artificial intelligence (AI) can advance research on algal biology and ecology.

Education is considered the cornerstone of ideology and culture in society. In the context of the sub-continent, the presence of the traditional Madrasah system and the modern contemporary system of education is a unique phenomenon of pedagogical duality. The research article seeks to provide a qualitative, theoretical, and comparative analysis of the pedagogical strategies employed in both systems of education to highlight their strengths and weaknesses. The Madrasah system is based on Islamic philosophy, which is teacher-centered and places a strong emphasis on moral-spiritual training, character building, and textual knowledge through pedagogical strategies such as question answering, memorization, and oral explanation. The contemporary system is based on Western constructs of experiential learning theory and constructivism, which is student-centered and places a strong emphasis on critical thinking skills and the use of modern technology to meet the demands of a global scientific environment. This research article is based on a narrative research approach and is an analysis of the theoretical literature on the subject. The research is based on the works of prominent scholars such as Halstead, Dewey, Bruner, along with international frameworks such as UNESCO. The research concludes that although the Madrasah system is highly effective in value-based education and Islamic.

Contamination of agricultural water poses significant health risks that are often underrecognized in clinical practice. This review synthesizes peer-reviewed literature from biomedical and environmental sciences. It examines the pathways by which nitrates and zoonotic pathogens contaminate rural drinking water and delineates the resulting spectrum of acute and chronic health risks relevant to primary care. Agricultural practices are a primary source of nitrates and pathogens (e.g., Escherichia coli, Cryptosporidium, Giardia) in rural water supplies. Nitrate nitrogen exposure is linked not only to acute infant methemoglobinemia but also to chronic conditions like colorectal and thyroid cancers and adverse birth outcomes. These risks are observed at concentrations below the current United States Environmental Protection Agency regulatory limit of 10 mg L−1 NO3−–N. Pathogen exposure leads to acute gastrointestinal illness and can trigger long-term sequelae, including irritable bowel syndrome. Agricultural communities are uniquely vulnerable because they rely heavily on unregulated private wells, which are more prone to contamination than public systems. Evidence suggests a substantial and often underrecognized burden of waterborne disease in agricultural communities. The findings highlight a critical need for clinical vigilance regarding low-level nitrate nitrogen exposure and long-term post-infectious syndromes. By identifying these patterns, family physicians serve as essential sentinels for both individual patient safety and community public health.

The rapid expansion of electronic waste (e-waste) has emerged as a critical global sustainability challenge, with low- and middle-income countries (LMICs) bearing a disproportionate share of its environmental and health burdens. Large volumes of discarded electronics are processed through informal and weakly regulated systems that rely on manual dismantling, open burning, and crude material recovery, leading to widespread contamination of air, soil, water, and food systems. These environmental releases generate chronic exposure pathways that contribute to neurological, respiratory, reproductive, and developmental health risks, particularly among informal workers, women, and children. Using a narrative and conceptual review approach, this article synthesizes evidence across environmental science, public health, and circular economy literature to examine contamination pathways, human health impacts, and institutional constraints associated with e-waste management in LMICs. Building on this synthesis, we advance a health-embedded circular economy framework that integrates exposure reduction, equity, and governance into circular e-waste interventions. Our analysis demonstrates that circular strategies focused solely on material recovery are insufficient and may reproduce existing inequities if health protection is not treated as a core performance metric. Embedding public health considerations, social inclusion, and global responsibility into circular e-waste systems is essential for achieving sustainable and just transitions. Aligning e-waste governance with planetary health principles and the Sustainable Development Goals offers a pragmatic pathway to reduce environmental contamination, safeguard vulnerable populations, and transform e-waste from a public health liability into an opportunity for inclusive development in LMICs.

ABSTRACT This paper describes the theoretical principles underpinning the pedagogical affordances of experiential learning through digital games, such as Minecraft, in order to engage primary school children in climate change challenges. It discusses the instructional value of an online interactive game for exploring possible climate change scenarios based on real-world data. The paper describes the instructional design of a series of school-based workshops, targeting students’ understanding of complex environmental systems and the interconnectedness of human actions and climate outcomes. The proposed design defines the expected learning outcomes of a game-based learning approach to sustainability, including problem-solving, collaboration, and climate literacy, as well as climate action skills. Participatory approaches through iterative cycles of collaboration and feedback were used in the co-construction of the instructional design. Stakeholders included children, teachers and teacher educators who collaborated with the research team of interdisciplinary voices relevant to climate change education, such as educationalists, environmental scientists, computer scientists, architects and urban planners. The instructional design aims to highlight novel ways of utilising digital technologies to foster local, actionable, tangible and engaging actions among children. In doing so, it provides a blueprint for educators interested in engaged digital pedagogies for teaching and learning about climate change.

This study conducts a comprehensive bibliometric analysis of scholarly research on green economy and sustainable finance from 2014 to 2024. Drawing upon a dataset of 692 peer-reviewed publications indexed in Scopus and analysed using the Bibliometrix R package, the study maps the field’s intellectual landscape, thematic development, and collaborative networks. The findings reveal a consistent increase in scientific output, with a pronounced surge in publications after 2018. This growth trend aligns with global policy milestones such as the Paris Agreement, the European Union [EU] Sustainable Finance Action Plan, and the proliferation of Environmental, Social, and Governance [ESG] integration and green bonds. China emerges as the most productive country, while institutions such as Jiangsu University, the Southwestern University of Finance and Economics, and the Lebanese American University lead in publication volume and collaboration intensity. Keyword co-occurrence and thematic mapping identify dominant themes related to green finance, environmental sustainability, ESG frameworks, and renewable energy, alongside emerging topics like climate risk disclosure and transition finance. Conceptual and co-word network analyses further reveal the interdisciplinary integration of finance, economics, policy, and environmental science. The study also demonstrates the growing decentralization of institutional influence and the rise of both North–South and South–South collaborations. These findings offer valuable insights into the evolving structure of research in sustainable finance and inform future academic inquiry and policy development.

Abstract Floating wetland islands (FWIs), traditionally applied for ecological restoration and water purification, are increasingly recognized for their multifunctional potential. Their ability to combine environmental remediation with food production positions FWIs as a promising nature-based solution (NbS) for advancing sustainable development. To identify research trends and knowledge gaps in this emerging field, a bibliometric analysis and systematic review of FWIs for crop production were performed using the Scopus database. A total of 83 publications were identified between 2000 and 2024, the majority being research articles (78.3%), with “Environmental Sciences” as the predominant subject area (35.8%). China emerged as the leading contributor, accounting for 71 publications (16.9%). Keyword co-occurrence analysis revealed three main thematic clusters: “agriculture,” “hydroponics,” and “wetlands,” reflecting the interdisciplinary nature of FWIs, which combine elements of hydroponic cultivation, ecological engineering, and water quality management. The review emphasizes the importance of plant selection and system design, not only to enhance nutrient retention but also to maximize biomass productivity, particularly when the goal is to obtain harvestable crops. From an economic perspective, FWIs show favorable viability: revenues from crop sales often surpass operational costs, though construction remains the most significant investment. Social acceptance tends to be high when commercial value is demonstrated; however, barriers such as limited technical training and concerns over food safety remain. Despite varied terminology, FWIs systems consistently demonstrate multifunctionality, offering solutions for both ecosystem restoration and sustainable crop production. Graphical Abstract

Background: Urbanization is rapidly transforming cities worldwide, with significant implications for local climates. This study explores the impact of urbanization on climate change in Bangalore and its surrounding areas through a biostatistical lens. Objectives: The objective is to analyze the influence of urbanization factors-particularly land use changes, population growth, infrastructure development, and vegetation cover-on temperature rise to better understand and address the urban heat island effect. Methods: Using regression and correlation analysis on data from surveys of urban planners, environmental scientists, and local officials, the study investigates how population growth, land use changes, infrastructure development, and vegetation cover influence temperature variations. Results: Results reveal a strong positive correlation between urbanization factors and increased temperatures, highlighting the urban heat island effect. Specifically, land use changes have the most significant impact on temperature rise, while population growth, infrastructure development, and vegetation cover show varying degrees of influence. Conclusion: The study concludes that sustainable urban growth strategies are crucial to mitigating local warming and enhancing climate resilience. These findings underscore the need for integrated urban planning approaches to address climate change effectively. Major Findings: Urbanization strongly drives Bangalore’s warming: Land-use change is the dominant predictor; population, infrastructure and vegetation also correlate. The regression explains 96.7% temperature variance, with an R² of 0.967. The findings of the study highlight green-space preservation and climate-sensitive planning.

Applications of machine learning-based quantitative structure activity relationship (ML-QSAR) models in environmental science.

A literature review on heavy metal pollution in aquatic environments: Assessment methods, ecotoxicological impacts, and health risk implications.

ABSTRACT Gain‐Probability (G‐P) analysis quantifies the probability that a randomly selected individual from one group scores higher or lower than an individual from another group, by varying magnitudes. While G‐P methods have been developed under normality and various skewed distributions, symmetric heavy‐tailed settings remain largely unexplored, despite their prevalence in finance, environmental science, and other applied domains. We extend the G‐P framework to the broad family of scale mixtures of normal (SMN) distributions, including the Student's t, slash, variance gamma (VG), and Pearson Type VII distributions. Analytical expressions for G‐P under SMN are derived for both independent and matched data, and parameter estimation is performed using the expectation maximisation (EM) algorithm. Simulation studies show that the proposed estimators are accurate, robust to heavy tails, and improve with sample size, with performance most sensitive to group separation and noise level. An application to daily returns of US and Chinese equity indices demonstrates how G‐P analysis captures distributional tail effects that are overlooked by traditional tests. The results support G‐P analysis under SMN as a practical, interpretable alternative to significance testing, enabling robust inference for symmetric heavy‐tailed data in diverse applied settings.

Climate anxiety research has emerged as a significant interdisciplinary scholarship linking mental health, environmental science, and social justice. Despite its growing prominence, no comprehensive bibliometric analysis has systematically mapped its intellectual structure and global dynamics. This study presents a bibliometric synthesis of 579 publications on climate anxiety indexed in Scopus and Web of Science from 2000 to 2024. Using Biblioshiny (the graphical interface for the R package "bibliometrix") and VOSviewer, we analyzed co-authorship, co-citation, and keyword co-occurrence networks to examine patterns in scientific production, thematic development, and institutional and geographic distribution. Citation trend analysis and keyword mapping traced thematic evolution across three phases: 2003-2015, 2016-2020, and 2021-2024. Results indicate exponential growth in climate anxiety research since 2019, with 242 publications in 2024 alone. The field is largely shaped by prominent scholars from the Global North and over the years thematic clusters have expanded from foundational constructs such as solastalgia and eco-anxiety to broader concerns including ecological grief, place attachment, and pro-environmental behavior. However, research remains geographically concentrated in high-income countries, with limited representation from climate-vulnerable regions, underscoring persistent epistemic disparities. Overall, the field demonstrates rapid development and growing interdisciplinary reach, yet continues to reflect inequities in global authorship and knowledge production. Advancing a more inclusive and context-sensitive climate anxiety scholarship requires centering Global South perspectives, decolonizing research agendas, and promoting equitable collaboration.