Hasil untuk "Environmental Science"

Anjan Mukherjee, Ajoy Kanti Das, Nandini Gupta et al.

<p>This study introduces a novel framework, Generalized Interval-Valued Neutrosophic Rough Soft Sets (GIVNRS sets), designed to improve handling uncertainty, imprecision, and vagueness in complex decision-making scenarios. By integrating soft, rough, and generalized interval-valued neutrosophic set theories, the framework offers a robust methodology for addressing indeterminacy and incomplete data. The theoretical foundation of GIVNRS sets is built upon fundamental operations, including intersection, union, complement, and novel aggregation union operators tailored for multi-criteria decision-making (MCDM) applications. The practical applicability of the framework is demonstrated through a water quality assessment, where it successfully classifies river segments based on key water quality parameters such as pH, Dissolved Oxygen (DO), and Biochemical Oxygen Demand (BOD). The case study results show that the pollution scores for the river segments were computed, classifying the segments such as &ldquo;Good,&rdquo; &ldquo;Moderate,&rdquo; and &ldquo;Poor,&rdquo; with corresponding pollution levels. These findings highlight the framework&rsquo;s ability to manage incomplete and inconsistent data, providing a reliable and comprehensive water quality evaluation. Compared to traditional models, the GIVNRS set approach offers enhanced flexibility, stability, and adaptability. This study not only contributes to the theoretical development of neutrosophic, soft, and rough set theories but also establishes GIVNRS sets as a powerful tool for water quality decision-making. Future research will explore further advancements in the application and computational efficiency of this framework.</p>

Abdul Khair, Bambang Widjanarko Otok, Noraida Noraida et al.

Tanah Bumbu Regency has the highest rate of malaria in South Kalimantan Province. Due to the non-linear fluctuations in malaria cases by ethnicity, a hybrid model combining Autoregressive Integrated Moving Average (MARS ARIMA) and Multivariate Adaptive Regression Splines was proposed for time series forecasting. The purpose of this study is to use the MARS ARIMA hybrid model to predict malaria cases by ethnicity in Tanah Bumbu Regency. The findings demonstrate that the best inputs for MARS modeling are significant lags found using ACF and PACF. The hybrid MARS ARIMA model performs better than standalone ARIMA or MARS models, according to predictions. Key findings show that the number of patients over 35 during the preceding two periods influences increases in malaria cases for the Banjar ethnic group. Cases exceeding 13 in two prior periods and 19 in one prior period are associated with increases for the Javanese group. Cases of more than two or fewer than two in the preceding two periods and more than eleven in one preceding period have an impact on increases among the Bugis. Prior cases below 26 have an impact on Banjar case declines, whereas prior cases below 13 and above 3 have a significant impact on Javanese case declines. This study demonstrates how well the MARS ARIMA hybrid model predicts malaria cases according to ethnicity.

James B. Garvin, Connor J. Anderson, Katherine A. Melocik et al.

At least one large-body (diameter > 1.1 km) hypervelocity cratering event occurred during ~ 0.8-0.90 Ma (Zhamanshin, Kazakhstan) in the Middle Pleistocene Transition period. Analysis designed to reduce uncertainty in the dimensions of the Zhamanshin structure employing high resolution topography demonstrated that it likely generated a ~ 26.5 km diameter multi-ring crater. This is at least two times larger than the current best estimates. Using a range of accepted impactor sizes, velocities, compositions, and angles of impact, such impacts typically yield kinetic energies of impact over 240,000 Megatons (TNT). Explosive energetic events of this magnitude (e.g., Yellowstone Caldera) at other times (K-Pg) have created global environmental effects. The factor of two discrepancy in the dimensions of Zhamanshin increases the kinetic energy yield by factors of 7-10, with significantly larger environmental consequences. This justifies examination of rapid climate transitions linked to biological consequences, including those related to environmental perturbations, at ~0.9 Ma.

P. L. Rosendahl, J. Schneider, G. Bobillier et al.

<p>Understanding crack phenomena in the snowpack and their role in avalanche formation is imperative for hazard prediction and mitigation. Many studies have explored how structural properties of snow contribute to the initial instability of the snowpack, focusing particularly on failure initiation within weak snow layers and the onset of crack propagation. This work addresses the subsequent stage, the effect of slab touchdown after weak-layer failure in mixed-mode loading (compressive anticrack (mode I) and shear (mode II) loading). Our results demonstrate that slab touchdown reduces the energy release rate, which can lead to crack arrest even under static conditions. This challenges the idea that only the dynamic properties of snow layers and spatial snowpack variations govern arrest, emphasizing instead the crucial role of mechanical interactions between the slab, weak layer, and base layer. By integrating these findings into the broader context of snowpack stability analysis, we contribute to a more nuanced understanding of avalanche initiation mechanisms. The analysis is provided in a comprehensive open-source model (<span class="uri">https://github.com/2phi/weac</span>, last access: 11 June 2025).</p>

Bian He, Xinyu He, Yimin Liu et al.

Abstract The influence of the thermodynamic forcing of the Tibetan Plateau (TP) on the Asian summer monsoon remains controversial because the role of elevated heating across the TP remains unclear at multiple time scales. At the extended-range scale, the boundary forcing is more important than the initial field in the forecast process. In this study, we investigated the role of subdaily thermodynamic forcing across the TP in generating 30-day predictions of precipitation in East Asia by conducting a series of hindcast experiments. The surface potential vorticity forcing was used to identify typical years when the TP forcings were extremely strong or weak. The results indicated that the subdaily thermal forcing of the TP was very important for improving the East Asian precipitation forecast accuracy, especially for predictions longer than 14 days in June 2022, when diffusion heating is very strong and can develop over the TP. In such a case, the corrected TP heating could not only correct for low-level water vapor transport but also modular uplevel circulation, which could propagate downstream, thus favoring the correct prediction of precipitation over East Asia. However, in the other cases, the individual influences of thermal perturbations across the TP are not the only important factors. These findings reveal ways to improve the extended-range forecast skill over East Asia.

Su Wang, Mengrui Pan, Yao Dong et al.

The WASP-47 system is notable as the first known system hosting both inner and outer low-mass planetary companions around a hot Jupiter, with an ultra-short-period (USP) planet as the innermost planetary companion. The formation of such a unique configuration poses challenges to the lonely hot Jupiter formation model. Hot Jupiters in multiple planetary systems may have a similar formation process with warm Jupiter systems, which are more commonly found with companions. This implies that the WASP-47 system could bridge our understanding of both hot and warm Jupiter formation. In this work, we propose a possible formation scenario for the WASP-47 system based on its orbital configuration. The mean motion resonance trapping, giant planet perturbations, and tidal effects caused by the central star are key factors in the formation of USP planets in multiple planetary systems with hot Jupiters. Whether a planet can become a USP planet or a short-period super-Earth planet depends on the competition between eccentricity excitation by nearby giant planet perturbations and the eccentricity damping due to tidal effects. The ${Q}_{p}^{{\prime} }$ value of the innermost planet is essential for the final planetary configuration. Our results suggest that a ${Q}_{p}^{{\prime} }$ in the range of [1, 10] is favorable for the formation of the WASP-47 system. Based on the formation scenario, we estimate an occurrence rate of 8.4% ± 2.4% for USP planets in systems similar to WASP-47.

Mijung Kim, Nimrah Ahmed, Kadriye Akdemir et al.

Abstract Students’ reasoning and decision making on complex socioscientific issues are critical for developing scientific literacy for 21st century citizenship. By incorporating a scenario-based approach, this study aims to understand the complexity of students’ decision making on environmental issues: forests and land use. To help students grasp the context of these issues, we developed scenarios reflecting their experiences and understanding of forests within local communities. Through scenario-based surveys, students in Grade 5–6 science classrooms were encouraged to explore diverse stakeholders’ perspectives and articulate their decisions regarding the scenarios. Additionally, students in focus groups participated in semi-structured discussions and interviews. The data collected from the surveys and students’ dialogues were thematically analyzed. The study found that students prioritized environmental concerns, demonstrated skepticism toward politicians’ perspectives, and emphasized righteousness in their decision making. These findings suggest that a holistic approach is essential to engage students’ diverse perspectives in socioscientific and environmental problem solving. However, this also highlights the ongoing challenge of disciplinary boundaries within school curricula and pedagogical practices in science classrooms.

Karthikeyan K, Philip Wu, Xin Tang et al.

The Science Consultant Agent is a web-based Artificial Intelligence (AI) tool that helps practitioners select and implement the most effective modeling strategy for AI-based solutions. It operates through four core components: Questionnaire, Smart Fill, Research-Guided Recommendation, and Prototype Builder. By combining structured questionnaires, literature-backed solution recommendations, and prototype generation, the Science Consultant Agent accelerates development for everyone from Product Managers and Software Developers to Researchers. The full pipeline is illustrated in Figure 1.

Sam Kirkham

A fundamental challenge in the cognitive sciences is discovering the dynamics that govern behaviour. Take the example of spoken language, which is characterised by a highly variable and complex set of physical movements that map onto the small set of cognitive units that comprise language. What are the fundamental dynamical principles behind the movements that structure speech production? In this study, we discover models in the form of symbolic equations that govern articulatory gestures during speech. A sparse symbolic regression algorithm is used to discover models from kinematic data on the tongue and lips. We explore these candidate models using analytical techniques and numerical simulations, and find that a second-order linear model achieves high levels of accuracy, but a nonlinear force is required to properly model articulatory dynamics in approximately one third of cases. This supports the proposal that an autonomous, nonlinear, second-order differential equation is a viable dynamical law for articulatory gestures in speech. We conclude by identifying future opportunities and obstacles in data-driven model discovery and outline prospects for discovering the dynamical principles that govern language, brain and behaviour.

Bernie Boscoe, Shawn Johnson, Andrea Osbon et al.

Camera traps have long been used by wildlife researchers to monitor and study animal behavior, population dynamics, habitat use, and species diversity in a non-invasive and efficient manner. While data collection from the field has increased with new tools and capabilities, methods to develop, process, and manage the data, especially the adoption of ML/AI tools, remain challenging. These challenges include the sheer volume of data generated, the need for accurate labeling and annotation, variability in environmental conditions affecting data quality, and the integration of ML/AI tools into existing workflows that often require domain-specific customization and computational resources. This paper provides a guide to a low-resource pipeline to process camera trap data on-premise, incorporating ML/AI capabilities tailored for small research groups with limited resources and computational expertise. By focusing on practical solutions, the pipeline offers accessible approaches for data transmission, inference, and evaluation, enabling researchers to discover meaningful insights from their ever-increasing camera trap datasets.

Sanjana Paul

This paper introduces the Environmental Justice in Technology (EJIT) Principles, a framework to help reorient technological development toward social and ecological justice and collective flourishing. In response to prevailing models of technological innovation that prioritize speed, scale, and profit while neglecting systemic injustice, the EJIT principles offer an alternative: a set of guiding values that foreground interdependence, repair, and community self-determination. Drawing inspiration from the 1991 principles of environmental justice, this framework extends their commitments into the technological domain, treating environmental justice not as a peripheral concern but as a necessary foundation for building equitable and regenerative futures. We situate the EJIT principles within the broader landscape of environmental justice, design justice, and post-growth computing, proposing them as a values infrastructure for resisting extractive defaults and envisioning technological systems that operate in reciprocity with people and the planet. In doing so, this article aims to support collective efforts to transform not only what technologies we build, but how, why, and for whom.

Oscar Estrella, Hernan Luis Castillo Garcia, Fernando Javier Rengel Jimenez et al.

El presente trabajo de investigación refiere a la “Prospección geológica para calizas en el sector Zambi, ubicado en la parroquia Zambi, cantón Catamayo, provincia de Loja”, abarcando una extensión de 40 hectáreas consideradas como prioritarias y necesarias para la investigación, en la búsqueda inicial de zonas de acumulación de carbonatos de calcio, determinando sus propiedades tanto físicas como químicas que presentan estos depósitos y analizar su posible aplicación en actividades industriales. Una vez obtenida la información bibliográfica mediante trabajo de oficina, se realizó la primera visita al polígono de estudio, posterior a ello se desarrolló el levantamiento fotogramétrico por percepción remota a escala 1:1000, curvas principales cada 5 metros y curvas secundarias cada 1 metro, el mismo que se utilizó de base para realizar el levantamiento geológico a la misma escala, mediante descripción de afloramientos y calicatas en donde se evidenció tres tipos de litologías correspondientes a calizas, lutitas y cuarcitas. Una vez identificadas las rocas, se tomó muestras en diferentes puntos del área de estudio y se realizó ensayos físicos como el cálculo de peso específico, peso aparente y porosidad; ensayos químicos correspondientes a difracción de rayos X, fluorescencia de rayos X y pureza de carbonatos. Estos análisis determinaron el porcentaje de CaCo3 que existe en las calizas, siendo este compuesto el de mayor importancia con un valor promedio de 77,56% CaCo3 clasificándola como una caliza impura margosa; así mismo se identificó elementos como el AlO, SIO, PO, S, KO, CaO y FeO, los cuales según sus porcentajes de concentración en las muestras, permitieron conocer el uso industrial de las calizas con el cálculo del índice hidráulico, obteniendo como resultado que su aprovechamiento es para matriz de cemento portland. Se argumenta que esta roca está relacionada directamente con la industria cementera o industria de la construcción.

Tatsushi NISHI, Hidefumi KURAKADO, Ziang LIU

The workforce scheduling problem for cell production lines has been recognized as one of the significant issues in manufacturing systems. In most of previous studies, complex workers’ operations in a cell such as traveling times of multi-skilled operators in another cell to their workplaces, have not been considered in the workforce optimization model. In this paper, we consider the simultaneous optimization of the product input sequence and workforce assignment scheduling problem for multi-stage multi-item cell production lines. The problem is formulated as a resource-constrained project scheduling problem (RCPSP). We propose an RCPSP formulation of the scheduling problem for multi-product cell production lines where the traveling time of operators and products are considered. The exact solution of the RCPSP formulation is derived by using a general-purpose solver, Gurobi. The validity of the RCPSP model is verified by comparing it with a genetic algorithm (GA) using a commercial simulation software (Siemens Plant Simulation). Experimental results show that the derived exact solution of RCPSP is better than that of the solutions derived by the GA algorithm in the Siemens Plant Simulation.

Tiago B. Ramos, Maria C. Gonçalves, Martinus Th. vanGenuchten

Abstract Soil salinization poses a significant threat to agricultural production in Portugal. Collaborative research spanning three decades with the U.S. Salinity Laboratory in Riverside, California, has been instrumental in advancing our understanding of this issue. This study provides a concise overview of the causes of soil salinization in Portugal, focusing on ongoing efforts to comprehensively address this challenge. Key advancements highlighted in this study encompass the meticulous characterization of soil hydraulic and solute transport parameters, the application of cutting‐edge modeling tools for water flow and solute transport in diverse agricultural systems, and the utilization of innovative proximal and remote sensing methods for mapping soil salinity. Noteworthy results and practical implications of these advancements underscore their relevance in real‐world scenarios. While celebrating these achievements, the study emphasizes the current nature of the ongoing research, highlighting the dynamic landscape of soil salinization. The study underscores the imperative need for further advancements to effectively cope with soil salinization, especially in anticipation of the intensification of agricultural practices and the looming impacts of climate change. This comprehensive overview not only encapsulates past achievements but also sets the stage for future research endeavors in mitigating the pervasive effects of soil salinization on agricultural sustainability in Portugal.

Hugo Sant'Anna

This paper examines the labor market impacts of the 2015 Mariana Dam disaster in Brazil. It contrasts two theoretical models: an urban spatial equilibrium model and a factor of production model, with diverging perspectives on environmental influences on labor outcomes. Utilizing rich national administrative and spatial data, the study reveals that the unusual environmental alteration, with minimal human capital loss, primarily affected outcomes via the factor of production channel. Nevertheless, spatial equilibrium dynamics are discernible within certain market segments. This research contributes to the growing literature on environmental changes and its economic consequences.

Yanyu Dai, Fan Lu, Benqing Ruan et al.

Quantitative differentiation of climate and human activities on runoff is important for water resources management and future water resources trend prediction. In recent years, runoff in the middle reaches of the Yellow River (MRYR) has decreased dramatically. Many studies have analyzed the causes of runoff reduction, but there is still a lack of understanding of the spatial differences in runoff contributions and their causes. Therefore, this study quantitatively distinguishes the contributions of climate and human activities to runoff changes in nine sub-basins of the MRYR based on the Budyko framework and analyses the differences in the contributions of different basins and their causes. The results show that the runoff in the nine sub-basins decreases significantly and the precipitation increases from northwest to southeast. The contribution of human activities to runoff is greater than that of climate change, especially in the Huangfuchuan (HF) River and Kuye (KY) River basins, where the contribution of human activities to runoff exceeds 90%. The greater impact of human activities in HF River and KY River is due to the significantly higher water use growth rate and normalized vegetation index trends than in other areas. HIGHLIGHTS Spatial differences in the causes of runoff variation in nine small watersheds in the middle reaches of the Yellow River were analyzed.; The influence of NDVI and human water extraction cannot be ignored.;

Anahita Seifi, Najmeh Razmkhah

Artificial intelligence is the science of empowering machines to perform actions similar to human activities. In other words, artificial intelligence is considered a science and a set of computer technologies designed to think, reason and imitate human behavior.Artificial intelligence is considered a new technology that has influenced various aspects of human life, from the economy to health and employment.Activists in the field of artificial intelligence always talk about the capabilities of this technology. According to them, the development and expansion of artificial intelligence is a great tool to deal with human problems and dilemmas. For example,  the increase in temperature, decrease in biodiversity, deforestation, floods, droughts, air pollution, and garbage accumulation are all among the environmental problems that have plagued humanity, problems that require immediate and effective solutions. For this purpose, resorting to artificial intelligence and its capabilities in environmental care has been proposed as one of the scientific and technical solutions to deal with these environmental challenges.The capabilities of artificial intelligence in agricultural management, measuring the amount of greenhouse gases, managing and monitoring the optimization of energy consumption, recycling waste, and strengthening and optimizing the public transportation system are all among the potential capabilities of artificial intelligence in the protection of the environment.But on the other hand, the process of designing, producing, supplying, and resorting to artificial intelligence has been associated with various challenges such as high energy consumption, extensive use of rare metals, and destruction of mineral resources, as well as increasing waste production and environmental pollution. These problems have caused serious doubts about the capabilities of this technology considering the growing trend to resort to artificial intelligence. This has led to environmental activists raising the question of whether this technology will provide a toolbox for a sustainable future for humans.Concerns regarding the performance of artificial intelligence and the widespread global support for this technology on the other hand prompted the world community to respond to these doubts, by regularizing the processes of research, development, production, and supply of artificial intelligence.One of these attempts is preparing the First Draft of the Recommendation on the Ethics of Artificial Intelligence in September 2020 By the United Nations Educational, Scientific and Cultural Organization (UNESCO).This draft, which was prepared in the form of 8 sections with the efforts of UNESCO international experts, with the aim of creating an international framework in the field of ethical and legal issues related to artificial intelligence systems, is approved at the 41st annual meeting of UNESCO, which was held in November 2021, with the votes of 193 member countries of this organization as the first international document that specifically considers the ethical norms and human rights of artificial intelligence..This document will not be binding but it is significant because it will be the first international document that specifically considers the ethical norms and human rights of artificial intelligence.The drafters of this recommendation talked about four human values which the 1st is respecting, encouraging and ensuring the basic principles of human rights, the second is , protecting the environment,  the third is protecting biodiversity and the fourth, is  living in peace and reconciliation.This draft demanded all the activists in the field of artificial intelligence to participate in the activities and adhere to principles such as proportionality, safety, fairness, responsibility, and accountability.But when looking at the draft text it seems that in some cases it contains ambiguities and defects, especially environmental discussions.These defects lead to several questions such as: “Has UNESCO's ethical draft been able to address the challenges in the environment sector, to provide effective regulations and solutions?” and “Considering the important and ever-increasing role of private companies active in the production and supply of artificial intelligence systems, have the authors of the draft been able to act successfully regarding attributing responsibility, methods of compensation for environmental damages, and commitment to observe the precautionary principle?” This article aims at working on these subjects, questions, and ambiguities with an analytical-descriptive method.