Hasil untuk "Environmental Science"

Renyi Zhang, A. Khalizov, Lin Wang et al.

L. Khot, S. Sankaran, J. Maja et al.

Zhong Lin Wang

The study presents the fundamental scientific understanding of electron transfer in contact electrification in solid–solid and liquid–solid cases and a newly revised model for the formation of electric double layer. The potential revolutionary impacts of triboelectric nanogenerators as energy sources and sensors are presented in the fields of health care, environmental science, wearable electronics, internet of things, human–machine interfacing, robotics, and artificial intelligence.

K. Suding

M. Jamshidian, E. Tehrany, Muhammad Imran et al.

W. Oberkampf, Christopher J. Roy

S. Kirksey, S. Helmreich

Anthropologists have been committed, at least since Franz Boas, to investigating relationships between nature and culture. At the dawn of the 21st century, this enduring interest was inflected with some new twists. An emergent cohort of “multispecies ethnographers” began to place a fresh emphasis on the subjectivity and agency of organisms whose lives are entangled with humans. Multispecies ethnography emerged at the intersection of three interdisciplinary strands of inquiry: environmental studies, science and technology studies (STS), and animal studies. Departing from classically ethnobiological subjects, useful plants and charismatic animals, multispecies ethnographers also brought understudied organisms—such as insects, fungi, and microbes—into anthropological conversations. Anthropologists gathered together at the Multispecies Salon, an art exhibit, where the boundaries of an emerging interdiscipline were probed amidst a collection of living organisms, artifacts from the biological sciences, and surprising biopolitical interventions.

N. Oreskes, E. Conway

J. Nichols, B. Williams

D. Foster, F. Swanson, J. Aber et al.

E. Oliver, M. Burrows, M. Donat et al.

This research was supported by the Australian Research Council grants CE170100023 and FT170100106, Natural Environment Research Council International Opportunity Fund NE/N00678X/1, National Sciences and Engineering Research Council of Canada Discovery Grant RGPIN-2018-05255, and Brian Mason (Impacts of an unprecedented marine heatwave). This project was partially supported through funding from the Earth Systems and Climate Change Hub of the Australian Government's National Environmental Science Program.

Yiping Cao, R. Mezzenga

Amyloid fibrils have traditionally been considered only as pathological aggregates in human neurodegenerative diseases, but it is increasingly becoming clear that the propensity to form amyloid fibrils is a generic property for all proteins, including food proteins. Differently from the pathological amyloid fibrils, those derived from food proteins can be used as advanced materials in biomedicine, tissue engineering, environmental science, nanotechnology, material science as well as in food science, owing to a combination of highly desirable feature such as extreme aspect ratios, outstanding stiffness and a broad availability of functional groups on their surfaces. In food science, protein fibrillization is progressively recognized as an appealing strategy to broaden and improve food protein functionality. This review article discusses the various classes of reported food protein amyloid fibrils and their formation conditions. It furthermore considers amyloid fibrils in a broad context, from their structural characterization to their forming mechanisms and ensued physical properties, emphasizing their applications in food-related fields. Finally, the biological fate and the potential toxicity mechanisms of food amyloid fibrils are discussed, and an experimental protocol for their health safety validation is proposed in the concluding part of the review.

M. S. Andersen

Jeffrey D Wolt

Transgenic modification of plants is a key enabling technology for developing sustainable biofeedstocks for biofuels production. Regulatory decisions and the wider acceptance and development of transgenic biofeedstock crops are considered from the context of science-based risk assessment. The risk assessment paradigm for transgenic biofeedstock crops is fundamentally no different from that of current generation transgenic crops, except that the focus of the assessment must consider the unique attributes of a given biofeedstock crop and its environmental release. For currently envisioned biofeedstock crops, particular emphasis in risk assessment will be given to characterization of altered metabolic profiles and their implications relative to non-target environmental effects and food safety; weediness and invasiveness when plants are modified for abiotic stress tolerance or are domesticated; and aggregate risk when plants are platforms for multi-product production. Robust risk assessments for transgenic biofeedstock crops are case-specific, initiated through problem formulation, and use tiered approaches for risk characterization.

Qinglin Yang, Yang He, Lukai Zhou et al.

Driven by the combined effects of global warming and the urban heat island (UHI) effect, building energy consumption has been rising steadily in recent years. The photovoltaic-cool roof (PVCR) system has emerged as an effective solution for urban energy conservation and carbon reduction. However, existing research on the energy-saving benefits of PVCR remains relatively limited, and none of these studies have considered the interaction between photovoltaic modules and high-reflectivity roofs (also called cool roof, CR). Therefore, field experiments were conducted to compare the thermal performance of the PVCR system against that of three conventional roof configurations, including photovoltaic roof (PVR), asphalt roof (AR), and CR. The results demonstrate that the PVCR system achieves a remarkable daytime cooling effect, with a maximum temperature reduction of 29 °C compared to the AR system, and maintains lower temperature fluctuations throughout the entire day. In addition, the findings reveal that the photovoltaic modules exhibit a lower average temperature when installed on the cool roof, with a temperature decrease of 0.15 °C relative to the asphalt roof. A numerical model incorporating the photothermal interaction between a high-reflectivity surface and PV modules was developed and validated with experimental data. The numerical model considers the interactions between the photovoltaic (PV) modules and the high reflectivity surface, including shortwave radiation reflection, longwave radiative exchange, and convective heat transfer. The sensitivity analysis indicates that a change in the spacing and height of the PV arrays from 0.3 m to 0.5 m increases the relative energy-saving efficiency of the system. The conclusions drawn in this paper can provide a reference for the application of the PVCR system in hot-summer and cold-winter areas.

Ekundayo A. ADESINA, Oluibukun G. AJAYI, Joseph O. ODUMOSU et al.

Traditional urban growth models often decouple land-use change from its climatic consequences, creating planning blind spots. This study introduces a globally transferable Dynamic Suitability-Weighted CA-Markov (DSW-CA-Markov) framework that, for the first time, integrates Land Surface Temperature (LST) trends as dynamic suitability factors within Cellular Automata transition rules, enabling bidirectional urban-thermal feedback simulation. We develop and validate this framework using multi-temporal Landsat data (2010, 2015, 2020) from Abuja, Nigeria, then project integrated urban-thermal patterns to 2030. Our primary innovation is a dynamic feedback mechanism where pixel-level LST change rates are embedded as evolving suitability factors within CA transition rules, moving beyond static suitability mapping or post-hoc thermal correlation. Results reveal a 157.29% built-up increase (2010-2020) with LST rises of 3.6 °C, and projected continued expansion with amplified UHI effects. The DSW-CA-Markov framework demonstrates superior capability in simulating coupled urban-thermal dynamics compared to conventional CA-Markov approaches (Kappa improvement: 0.08; thermal : 0.73 vs. 0.65). This study provides both a novel methodological template for climate-responsive urban modelling and crucial insights for sustainable planning in fast-growing cities globally.

Clark Barrett, Swarat Chaudhuri, Fabrizio Montesi et al.

We introduce CSLib, an open-source framework for proving computer-science-related theorems and writing formally verified code in the Lean proof assistant. CSLib aims to be for computer science what Lean's Mathlib is for mathematics. Mathlib has been tremendously impactful: it is a key reason for Lean's popularity within the mathematics research community, and it has also played a critical role in the training of AI systems for mathematical reasoning. However, the base of computer science knowledge in Lean is currently quite limited. CSLib will vastly enhance this knowledge base and provide infrastructure for using this knowledge in real-world verification projects. By doing so, CSLib will (1) enable the broad use of Lean in computer science education and research, and (2) facilitate the manual and AI-aided engineering of large-scale formally verified systems.

L. Al Dehailan, E. A. Martinez-Mier

IntroductionDevelopmental defects of enamel (DDE) encompass a spectrum of conditions that occur during tooth formation, including enamel fluorosis, molar–incisor hypomineralization (MIH), and other forms of enamel hypoplasia. It has been proposed that DDE are associated with nutritional deficiencies as well as environmental exposures during tooth development.ObjectiveThis scoping review summarized and analyzed the evidence on the association between dietary habits, environmental exposures, medical/health-related factors, demographic factors and biological factors and DDE aiming to provide a comprehensive overview of the available evidence in this area.MethodologyFollowing the Joanna Briggs Institute (JBI) framework using Population, Concept, and Context (PCC) to guide the development of the research question and eligibility. The population of interest were individuals from any age group or gender diagnosed with DDE. The eligibility concepts were factors that may contribute to DDE such as dietary and environmental exposures. The study selection followed the PRISMA guidelines. Studies published from January 1993 to December 2024 were identified through searches in Web of Science and PubMed.ResultsOur review included 125 studies from 1993 to 2024, mainly on fluorosis (105 studies), mostly cross-sectional, and conducted in Asia and North America. Fewer studies addressed MIH (5) and other non-fluorosis DDE (15), primarily in Europe, South America, and Asia, with most participants being children aged 6–12 years, and small sample sizes. The review evaluated DDE and its main subtypes, molar-incisor hypomineralization (MIH) and enamel fluorosis across conditions, overlapping risk factors were identified, such as excessive fluoride intake, vitamin D deficiency, early childhood illnesses, and exposure to environmental contaminants. Condition-specific patterns were also noted, fluorosis being primarily associated with high fluoride exposure and early weaning, whereas MIH was more frequently linked to vitamin D deficiency and early systemicConclusionThe findings highlight that enamel fluorosis, MIH, and other enamel hypoplasias are part of a shared continuum of DDE influenced by interrelated dietary, environmental, and biological factors. These findings suggest common developmental pathways leading to enamel disruption and emphasize the need for longitudinal and mechanistic studies to clarify causal relationships and inform preventive strategies.

Monika Czop, Joanna Wyczarska-Kokot, Joanna Kalka et al.

A municipal wastewater treatment plant is a complex system of technological devices and facilities designed to remove pollutants from wastewater. The operation of such plants generates a waste stream that can be classified into three types: screenings (code 19 08 01), sand trap contents (code 19 08 02), and stabilized municipal sewage sludge (code 19 08 05). Each generated waste must be managed in accordance with the applicable law. In the context of new business models within the closed-loop economy, wastewater treatment plants are viewed as a resource rich resource that can be used to reclamate degraded lands. The purpose of the study was to evaluate the physicochemical parameters of the waste, which could form the basis for the preparation of soil-forming material. The input material considered was excess digester sludge after the stabilization process, sand from the sand traps, and sand after cleaning the wastewater network. The tested sludge contained 35 % organic substances, 12 % organic carbon, 1.8 % total nitrogen, and 0.24 % potassium. The sand contained about 1 % organic matter, 1.8 % organic carbon, 0.5 % total nitrogen, and 0.02 % potassium. Sand and sludge were prepared in the following mixtures: 1:1, 1:2, 2:1. These mixtures were then assessed for their suitability in the reclamation of degraded areas.

Gavin L. Simpson

Nonlinear relationships between covariates and a response variable of interest are frequently encountered in animal science research. Within statistical models, these nonlinear effects have, traditionally, been handled using a range of approaches including transformation of the response, parametric nonlinear models based on theory or phenomenological grounds, or through fixed degree spline or polynomial terms. If it is desirable to learn the shape of these relationships then generalized additive models (GAMs) are an excellent alternative. GAMs extend the generalized linear model such that the linear predictor includes one or more smooth functions, parameterised using penalised splines. A wiggliness penalty on each function is used to avoid over fitting while estimating the parameters of the spline basis functions to maximise fit to the data. Modern GAMs include automatic smoothness selection methods to find an optimal balance between fit and complexity of the estimated functions. Because GAMs learn the shapes of functions from the data, the user can avoid forcing a particular model to their data. Here, I provide a brief description of GAMs and visually illustrate how they work. I then demonstrate the utility of GAMs on three example data sets of increasing complexity, to show i) how learning from data can produce a better fit to data than that of parametric models, ii) how hierarchical GAMs can be used to estimate growth data from multiple animals in a single model, and iii) how hierarchical GAMs can be used for formal statistical inference in a designed experiment. The examples are supported by R code that demonstrates how to fit each of the models considered, and reproduces the results of the statistical analyses reported here. Ultimately, I show that GAMs are a modern, flexible, and highly usable statistical model that is amenable to many research problems in animal science.