Carla Pedro Gomes

Land-use transitions and carbon emissions of aquaculture expansion in the Brazilian Amazon

Felipe Siqueira Pacheco, Sebastián Heilpern, Rafael Marques Almeida, Suresh A. Sethi et autres

Accounting for land-use change underlying food sector expansion is critical for conserving ecosystem integrity. This challenge is particularly acute in the Amazon, where the conversion of forests for food production is pronounced and has broad implications for global biodiversity and the cycling …

us, br (code pays fourni par la source)

Autonomous Materials Exploration Integrates Automated Phase Identification and AI Agents Enhanced by Human Guidance

Anonymous, Maximilian Amsler, Duncan R. Sutherland, Sebastian Ament et autres

Autonomous experimentation holds the potential to accelerate materials development by combining artificial intelligence (AI) with modular robotic platforms to explore extensive combinatorial chemical and processing spaces. Such self-driving laboratories can not only increase the throughput of repetitive experiments, but also incorporate human …

us (code pays fourni par la source)

FEAT: Free energy Estimators with Adaptive Transport *

Jiajun He, Yuanqi Du, Francisco Vargas, Yuanqing Wang et autres

Abstract We present Free energy Estimators with Adaptive Transport (FEAT), a novel framework for free energy estimation—a critical challenge across scientific domains. FEAT leverages learned transports implemented via stochastic interpolants and provides consistent, minimum-variance estimators based on escorted Jarzynski equality and controlled …

gb, us, fr (code pays fourni par la source)

AlphaNet: scaling up local-frame-based neural network interatomic potentials

Bangchen Yin, Jiaao Wang, Weitao Du, Pengbo Wang et autres

Molecular dynamics simulations demand an unprecedented combination of accuracy and scalability to tackle grand challenges in catalysis and materials design. To bridge this gap, we present AlphaNet, a local-frame-based equivariant model that simultaneously improves computational efficiency and predictive precision for interatomic interactions. …

cn, us, hk, il (code pays fourni par la source)

Expanding Connected Components from Alternative Terminals: Global Optimization for Freshwater Fishes Under the UN's 30x30 Conservation Goal

Yue Mao, Imanol Miqueleiz, Aaron Ferber, Marc Grimson et autres

Climate change and biodiversity loss are among humanity’s most pressing challenges. In 2022, under the auspices of the United Nations, over 190 countries reached a historic agreement to address the alarming loss of biodiversity and restore natural ecosystems. Target 3, often referred …

us (code pays fourni par la source)

Climate Change before International Courts

Carla Pedro Gomes, Heloísa Oliveira, Armando Rocha Trindade, Matteo Fermeglia

This book provides a comprehensive analysis of environmental law and climate change litigation within international courts, both substantively and procedurally. Climate change litigation is an area of continuous growth and complexity, particularly within international courts and bodies. This book uses a comparative …

Improving Multislice Electron Ptychography with a Generative Prior

Christian K. Belardi, Chia‐Hao Lee, Yingheng Wang, Justin Lovelace et autres

Multislice electron ptychography (MEP) is an inverse imaging technique that computationally reconstructs the highest-resolution images of atomic crystal structures from diffraction patterns. Available algorithms often solve this inverse problem iteratively but are both time consuming and produce suboptimal solutions due to their …

3D Ptychographic Inverse Imaging with Generative Diffusion Models

Chia‐Hao Lee, Christian K. Belardi, Yingheng Wang, Justin Lovelace et autres

Artificial intelligence and machine learning are poised to revolutionize electron microscopy, enabling advances in instrument automation, parameter optimization, image classification, and defect analysis [1-5]. These applications primarily leverage the predictive power of machine learning, focusing on tasks such as feature extraction and …

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Scientifically-Interpretable Reasoning Network (ScIReN): Discovering Hidden Relationships in the Carbon Cycle and Beyond

Joshua Poh-Onn Fan, Huiming Xu, Tao Feng, Md. Nasim et autres

Soils have potential to mitigate climate change by sequestering carbon from the atmosphere, but the soil carbon cycle remains poorly understood. Scientists have developed process-based models of the soil carbon cycle based on existing knowledge, but they contain numerous unknown parameters and …

Leveraging biodiversity to maximize nutrition and resilience of global fisheries

Sebastián Heilpern, Franz W. Simon, Suresh A. Sethi, Kathryn J. Fiorella et autres

us (code pays fourni par la source)

Probabilistic phase labeling and lattice refinement for autonomous materials research

Ming-Chiang Chang, Sebastian Ament, Maximilian Amsler, Duncan R. Sutherland et autres

X-ray diffraction (XRD) is a powerful method for determining a material’s crystal structure in high-throughput experimentation, and is widely being incorporated in artificially intelligent agents for autonomous scientific discovery. However, rapid, automated, and reliable analysis of XRD data at rates that match …

us (code pays fourni par la source)

Optimal transport for generating transition states in chemical reactions

Chenru Duan, Guan-Horng Liu, Yuanqi Du, Tianrong Chen et autres

Abstract Transition states (TSs) are transient structures that are key to understanding reaction mechanisms and designing catalysts but challenging to capture in experiments. Many optimization algorithms have been developed to search for TSs computationally. Yet, the cost of these algorithms driven by …

cn, us (code pays fourni par la source)