Hasil untuk "Environmental sciences"

Guram Mikaberidze, Beso Mikaberidze, Dane Taylor

Network science has traditionally examined how structure determines dynamics. Here we invert this paradigm: we ask how functional dynamics and resource constraints shape network architecture. We introduce GradNet, an AI-enabled optimization framework that treats network topology as a continuously differentiable object. This allows designing networks that optimize arbitrary dynamical objectives, from synchronization to communication capacity, under realistic constraints. Applying this framework across diverse systems reveals that canonical network features emerge spontaneously from constrained optimization rather than requiring explicit imposition. Optimizing Kuramoto oscillator synchronization under fixed coupling budgets produces sparse, bipartite, frequency-disassortative architectures that eliminate classical synchronization thresholds. Minimizing social tension in opinion dynamics reproduces the empirically observed factional split in Zachary's karate club network. Maximizing entanglement distribution in spatial quantum networks under distance-dependent costs recovers minimum spanning tree architectures. These results demonstrate that optimization acts as both an engineering tool for network design, scalable to networks exceeding $10^5$ nodes, and a scientific probe revealing fundamental structure-function relationships. By recasting network architecture as the solution to constrained optimization problems, this variational perspective offers a unified framework connecting network analysis, design, and inference across physical, biological, and technological systems.

Richard Pan, Katherine A. Suess, Danilo Marchesini et al.

Environmental quenching -- where interactions with other galaxies and/or the intra-cluster medium (ICM) suppress star formation in low-mass galaxies -- has been well-established as the primary driver behind the formation of the red sequence for low-mass galaxies within clusters at low redshift ($z<1$). However, it remains unclear whether these mechanisms are active at higher-redshifts in proto-cluster environments that are not yet fully virialized. In large part, this regime has remained unexplored due to observational limitations; however, JWST has recently opened a new window into the role of environmental quenching on low-mass (log(M$_{\star}$/M$_{\odot}$$<$9.0) galaxies at cosmic noon ($2 < z < 3$). Here, we leverage the deep imaging and R$\sim$15 spectrophotometry enabled by the 20 band JWST/NIRCam data from the UNCOVER and MegaScience programs to examine environmental quenching in a newly discovered $z\approx2.58$ proto-cluster. We compare the star formation histories (SFHs) of 19 low-mass quiescent galaxies in the proto-cluster to a matched sample of 18 in the field, and find no significant differences. This similarity extends to galaxy sizes and quenched fractions, which also show no significant differences between the two environments across the full stellar mass range (8.5$<$log(M$_{\star}$/M$_{\odot}$$\leq$11.0). This indicates that the proto-cluster has not yet accelerated quenching relative to the field and is consistent with expectations that $z>2$ proto-clusters have yet to virialize and develop a dense enough environment required to efficiently quench low-mass galaxies.

Zongrong Li, Haiyang Li, Yifan Yang et al.

Wildfires in urbanized regions, particularly within the wildland-urban interface, have significantly intensified in frequency and severity, driven by rapid urban expansion and climate change. This study aims to provide a comprehensive, fine-grained evaluation of the recent 2025 Los Angeles wildfire's impacts, through a multi-source, tri-environmental framework in the social, built and natural environmental dimensions. This study employed a spatiotemporal wildfire impact assessment method based on daily satellite fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS), infrastructure data from OpenStreetMap, and high-resolution dasymetric population modeling to capture the dynamic progression of wildfire events in two distinct Los Angeles County regions, Eaton and Palisades, which occurred in January 2025. The modelling result estimated that the total direct economic losses reached approximately 4.86 billion USD with the highest single-day losses recorded on January 8 in both districts. Population exposure reached a daily maximum of 4,342 residents in Eaton and 3,926 residents in Palisades. Our modelling results highlight early, severe ecological and infrastructural damage in Palisades, as well as delayed, intense social and economic disruptions in Eaton. This tri-environmental framework underscores the necessity for tailored, equitable wildfire management strategies, enabling more effective emergency responses, targeted urban planning, and community resilience enhancement. Our study contributes a highly replicable tri-environmental framework for evaluating the natural, built and social environmental costs of natural disasters, which can be applied to future risk profiling, hazard mitigation, and environmental management in the era of climate change.

Tariq Eldakruri, Edip Senyurek

Geothermal energy provides continuous low emission potential but is underused in Qatar because of high capital costs, drilling risks, and uncertainty in subsurface conditions. This study examines how automation can improve the techno economic and environmental feasibility of geothermal deployment through three pathways: Enhanced Geothermal Systems in the Dukhan Basin, repurposed oil and gas wells, and ground source heat pumps for district cooling. Using geological datasets and financial modeling, the analysis shows that full automation reduces capital expenditure by 12 to 14 percent and operating expenditure by 14 to 17 percent. The Levelized Cost of Energy decreases from 145 USD per MWh to 125 USD per MWh, and payback periods shorten by up to two years. Environmental results indicate that geothermal substitution can avoid between 4000 and 17600 tons of CO2 per year for each project. Automation also reduces uncertainty in investment outcomes based on Monte Carlo simulations. Overall, the results show that automation strengthens the economic viability of geothermal systems and supports their integration into Qatars long term energy diversification and decarbonization strategies.

Hyunwoo Yoo, Gail L. Rosen

Traditional machine learning models struggle to generalize in microbiome studies where only metadata is available, especially in small-sample settings or across studies with heterogeneous label formats. In this work, we explore the use of large language models (LLMs) to classify microbial samples into ontology categories such as EMPO 3 and related biological labels, as well as to predict pathogen contamination risk, specifically the presence of E. Coli, using environmental metadata alone. We evaluate LLMs such as ChatGPT-4o, Claude 3.7 Sonnet, Grok-3, and LLaMA 4 in zero-shot and few-shot settings, comparing their performance against traditional models like Random Forests across multiple real-world datasets. Our results show that LLMs not only outperform baselines in ontology classification, but also demonstrate strong predictive ability for contamination risk, generalizing across sites and metadata distributions. These findings suggest that LLMs can effectively reason over sparse, heterogeneous biological metadata and offer a promising metadata-only approach for environmental microbiology and biosurveillance applications.

Chiara De Luca, Elisa Donati

Queen bee presence is essential for the health and stability of honeybee colonies, yet current monitoring methods rely on manual inspections that are labor-intensive, disruptive, and impractical for large-scale beekeeping. While recent audio-based approaches have shown promise, they often require high power consumption, complex preprocessing, and are susceptible to ambient noise. To overcome these limitations, we propose a lightweight, multimodal system for queen detection based on environmental sensor fusion-specifically, temperature, humidity, and pressure differentials between the inside and outside of the hive. Our approach employs quantized decision tree inference on a commercial STM32 microcontroller, enabling real-time, low-power edge computing without compromising accuracy. We show that our system achieves over 99% queen detection accuracy using only environmental inputs, with audio features offering no significant performance gain. This work presents a scalable and sustainable solution for non-invasive hive monitoring, paving the way for autonomous, precision beekeeping using off-the-shelf, energy-efficient hardware.

Yuzhuo Li, Di Zhao, Tingrui Qiao et al.

Identifying individual animals within large wildlife populations is essential for effective wildlife monitoring and conservation efforts. Recent advancements in computer vision have shown promise in animal re-identification (Animal ReID) by leveraging data from camera traps. However, existing Animal ReID datasets rely exclusively on visual data, overlooking environmental metadata that ecologists have identified as highly correlated with animal behavior and identity, such as temperature and circadian rhythms. Moreover, the emergence of multimodal models capable of jointly processing visual and textual data presents new opportunities for Animal ReID, but existing datasets fail to leverage these models' text-processing capabilities, limiting their full potential. Additionally, to facilitate the use of metadata in existing ReID methods, we propose the Meta-Feature Adapter (MFA), a lightweight module that can be incorporated into existing vision-language model (VLM)-based Animal ReID methods, allowing ReID models to leverage both environmental metadata and visual information to improve ReID performance. Experiments on MetaWild show that combining baseline ReID models with MFA to incorporate metadata consistently improves performance compared to using visual information alone, validating the effectiveness of incorporating metadata in re-identification. We hope that our proposed dataset can inspire further exploration of multimodal approaches for Animal ReID.

Mirza Akhi Khatun, Mangolika Bhattacharya, Ciarán Eising et al.

This research develops a new method to detect anomalies in time series data using Convolutional Neural Networks (CNNs) in healthcare-IoT. The proposed method creates a Distributed Denial of Service (DDoS) attack using an IoT network simulator, Cooja, which emulates environmental sensors such as temperature and humidity. CNNs detect anomalies in time series data, resulting in a 92\% accuracy in identifying possible attacks.

Zhichao Fang, Jonathan Dudek, Ed Noyons et al.

To reflect the extent to which science is cited in policy documents, this paper explores the presence of policy document citations for over 18 million Web of Science-indexed publications published between 2010 and 2019. Enabled by the policy document citation data provided by Overton, a searchable index of policy documents worldwide, the results show that there are 3.9% of publications in the dataset cited at least once by policy documents. Policy document citations present a citation delay towards newly published publications and show a stronger predominance to the document types of review and article. Based on the Overton database, publications in the field of Social Sciences and Humanities have the highest relative presence in policy document citations, followed by Life and Earth Sciences and Biomedical and Health Sciences. Our findings shed light not only on the impact of scientific knowledge on the policy-making process, but also on the particular focus of policy documents indexed by Overton on specific research areas.

Chenjiao Tan, Qian Cao, Yiwei Li et al.

The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision. This paper explores the capabilities of GPT-4V in the realms of geography, environmental science, agriculture, and urban planning by evaluating its performance across a variety of tasks. Data sources comprise satellite imagery, aerial photos, ground-level images, field images, and public datasets. The model is evaluated on a series of tasks including geo-localization, textual data extraction from maps, remote sensing image classification, visual question answering, crop type identification, disease/pest/weed recognition, chicken behavior analysis, agricultural object counting, urban planning knowledge question answering, and plan generation. The results indicate the potential of GPT-4V in geo-localization, land cover classification, visual question answering, and basic image understanding. However, there are limitations in several tasks requiring fine-grained recognition and precise counting. While zero-shot learning shows promise, performance varies across problem domains and image complexities. The work provides novel insights into GPT-4V's capabilities and limitations for real-world geospatial, environmental, agricultural, and urban planning challenges. Further research should focus on augmenting the model's knowledge and reasoning for specialized domains through expanded training. Overall, the analysis demonstrates foundational multimodal intelligence, highlighting the potential of multimodal foundation models (FMs) to advance interdisciplinary applications at the nexus of computer vision and language.

Adrian Kent

We propose dynamical collapse models in which the stochastic collapse terms affect only photons and/or gravitons. In principle, isolated systems comprising only massive particles could evolve unitarily indefinitely in such models. In practice, since photons and gravitons are ubiquitous and scatter from massive particles, dynamical collapses of the former will effectively induce collapses of the latter. In non-relativistic models in which particle number is conserved and interactions are modelled by classical potentials, massive systems can be modelled as collections of elementary massive particles bound by potentials, interacting with an environment of photons and gravitons. In this picture, although the photon and/or graviton collapse dynamics effectively localize massive systems, these collapses take the effective form of approximate measurements on the environment whose effect on the massive systems is indirect. We argue that these environmental collapse models, like standard mass-dependent spontaneous localisation models, may be consistent with quantum experiments on microscopic systems while predicting very rapid effective collapse of macroscopic massive systems, and hence a potential solution to the quantum measurement problem. However, the models considered here have different experimental signatures from standard mass-dependent spontaneous localisation models. For example, they predict no deviations from standard quantum interferometry for mesoscopic systems of massive particles isolated from a decohering environment, nor do they predict anomalous spontaneous emission of radiation from isolated matter of the type prediction by standard mass-dependent spontaneous localization models. New experiments and analyses are required to obtain empirical bounds on the decoherence rate in our models.

Tobias Lorey, Paul Ralph, Michael Felderer

As software engineering research becomes more concerned with the psychological, sociological and managerial aspects of software development, relevant theories from reference disciplines are increasingly important for understanding the field's core phenomena of interest. However, the degree to which software engineering research draws on relevant social sciences remains unclear. This study therefore investigates the use of social science theories in five influential software engineering journals over 13 years. It analyzes not only the extent of theory use but also what, how and where these theories are used. While 87 different theories are used, less than two percent of papers use a social science theory, most theories are used in only one paper, most social sciences are ignored, and the theories are rarely tested for applicability to software engineering contexts. Ignoring relevant social science theories may (1) undermine the community's ability to generate, elaborate and maintain a cumulative body of knowledge; and (2) lead to oversimplified models of software engineering phenomena. More attention to theory is needed for software engineering to mature as a scientific discipline.

Adrien Tavernier, Gabriel Pinto, Millarca Valenzuela et al.

In 2019 while launching a multidisciplinary research project aimed at developing the Puna de Atacama region as a natural laboratory, investigators within the University of Atacama (Chile) conducted a bibliographic search identifying previously studied geographical points of the region and of potential interest for planetary science and astrobiology research. This preliminary work highlighted a significant absence in foreign publications consideration of local institutional involvement. In light of this, a follow-up study was carried out to confirm or refute these first impressions, by comparing the search in two bibliographic databases: Web of Science and Scopus. The results show that almost 60% of the publications based directly on data from the Puna, the Altiplano or the Atacama Desert with objectives related to planetary science or astrobiology do not include any local institutional partner (Argentina, Bolivia, Chile and Peru). Indeed, and beyond the ethical questioning of international collaborations, Latin-American planetary science deserve a strategic structuring, networking, as well as a road map at a national and continental scale, not only to enhance research, development and innovation but also to protect an exceptional natural heritage sampling extreme environmental niches on Earth. Examples of successful international collaborations such as the field of meteorites, terrestrial analogues and space exploration in Chile or astrobiology in Mexico are given as illustrations and possible directions to follow in order to develop planetary sciences in South America.

Hechen Yang, Chen Li, Xin Zhao et al.

The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) is a microscopic image data set, including the original Environmental Microorganism images (EMs) and the corresponding object labeling files in ".XML" format file. The EMDS-7 data set consists of 41 types of EMs, which has a total of 2365 images and 13216 labeled objects. The EMDS-7 database mainly focuses on the object detection. In order to prove the effectiveness of EMDS-7, we select the most commonly used deep learning methods (Faster-RCNN, YOLOv3, YOLOv4, SSD and RetinaNet) and evaluation indices for testing and evaluation. EMDS-7 is freely published for non-commercial purpose at: https://figshare.com/articles/dataset/EMDS-7_DataSet/16869571

Moorad Alexanian

Both Albert Einstein and Erwin Schrödinger have defined what science is. Einstein includes not only physics, but also all natural sciences dealing with both organic and inorganic processes in his definition of science. According to Schrödinger, the present scientific worldview is based on the two basic attitudes of comprehensibility and objectivation. On the other hand, the notion of religion is quite equivocal and unless clearly defined will easily lead to all sorts of misunderstandings. Does science, as defined, encompass the whole of reality? More importantly, what is the whole of reality and how do we obtain data for it? The Christian worldview considers a human as body, mind, and spirit (soul), which is consistent with Cartesian ontology of only three elements: matter, mind, and God. Therefore, is it possible to give a precise definition of science showing that the conflicts are actually apparent and not real?

Georges Gras

Preprint of a paper to appear in "Communications in Advanced Mathematical Sciences". Let K be a real abelian extension of Q. Let p be a prime number, S the set of p-places of K and G\_K,S the Galois group of the maximal S-ramified pro-p-extension of K (i.e., unramified outside p and infinity). We revisit the problem of annihilation of the p-torsion group T\_K:=tor\_Z\_p(G\_K,S^ab) initiated by us and Oriat then systematized in our paper on the construction of p-adic L-functions in which we obtained a canonical ideal annihilator of T\_K in full generality (1978--1981). Afterwards (1992--2014) some annihilators, using cyclotomic units, were proposed by Solomon, Belliard--Nguyen Quang Do, Nguyen Quang Do--Nicolas, All, Belliard--Martin.In this text, we improve our original papers and show that, in general, the Solomon elements are not optimal and/or partly degenerated. We obtain, whatever K and p, an universal non-degenerated annihilator in terms of p-adic logarithms of cyclotomic numbers related to L\_p-functions at s=1 of its primitive characters of K (Theorem 9.4). Some computations are given with PARI programs; the case p=2 is analyzed and illustrated in degrees 2, 3, 4 to test a conjecture.

R. Foltz, G. Wilson, A. Muzzin et al.

Using a sample of 4 galaxy clusters at $1.35 < z < 1.65$ and 10 galaxy clusters at $0.85 < z < 1.35$, we measure the environmental quenching timescale, $t_Q$, corresponding to the time required after a galaxy is accreted by a cluster for it to fully cease star formation. Cluster members are selected by a photometric-redshift criterion, and categorized as star-forming, quiescent, or intermediate according to their dust-corrected rest-frame colors and magnitudes. We employ a "delayed-then-rapid" quenching model that relates a simulated cluster mass accretion rate to the observed numbers of each type of galaxy in the cluster to constrain $t_Q$. For galaxies of mass $M_* \gtrsim 10^{10.5}~ \mathrm{M}_\odot$, we find a quenching timescale of $t_Q=$ 1.24 Gyr in the $z\sim1.5$ cluster sample, and $t_Q=$ 1.50 Gyr at $z\sim1$. Using values drawn from the literature, we compare the redshift evolution of $t_Q$ to timescales predicted for different physical quenching mechanisms. We find $t_Q$ to depend on host halo mass such that quenching occurs over faster timescales in clusters relative to groups, suggesting that properties of the host halo are responsible for quenching high-mass galaxies. Between $z=0$ and $z=1.5$, we find that $t_Q$ evolves faster than the molecular gas depletion timescale and slower than an SFR-outflow timescale, but is consistent with the evolution of the dynamical time. This suggests that environmental quenching in these galaxies is driven by the motion of satellites relative to the cluster environment, although due to uncertainties in the atomic gas budget at high redshift, we cannot rule out quenching due to simple gas depletion.

Md. Arafat Hossain, John Canning, Sandra Ast et al.

A novel portable fluorometer combining the attributes of a smartphone with an easy fit, simple and compact sample chamber fabricated using 3D printing has been developed for pH measurements of environmental water in the field. The results were then compared directly with those obtained using conventional electrode based measurements.

Loet Leydesdorff, Jin Bihui

Methods developed for mapping the journal structures contained in aggregated journal-journal citations in the Science Citation Index are applied to the Chinese Science Citation Database of the Chinese Academy of Sciences. This database covers 991 journals, of which only 37 had originally English titles. Using factor-analytical and graph-analytical techniques we show that this data is dually structured. The main structure is the intellectual organization of the journals in journal groups (as in the international SCI), but the university-based journals provide an institutional layer that orients this structure towards practical ends (e.g., agriculture). The Chinese Science Citation Database exhibits the characteristics of Mode 2 in the production of scientific knowledge more than its western counterparts. The contexts of application lead to correlation (interfactorial complexity) among the components.

Bernhelm Booss-Bavnbek

We recall major findings of a systematic investigation of the mathematization of the individual sciences, conducted by the author in Bielefeld some 35 years ago under the direction of Klaus Krickeberg, and confront them with recent developments in physics, medicine, economics, and spectral geometry.