Results 111 to 120 of about 108,341 (245)

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

ChatCFD: A Large Language Model‐Driven Agent for End‐to‐End Computational Fluid Dynamics Automation with Structured Knowledge and Reasoning

Advanced Intelligent Discovery, EarlyView.
Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan, Kang Hu, Zhuowen Wu, Jiangyang Ge, Jiawei Miao, Yuzhi Zhang, He Sun, Weizong Wang, Tianhan Zhang   +8 more
wiley   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Insights from Financial Economics to Value Healthcare Investments that Reduce System-Level Risks: Example of Disease Elimination and Eradication. [PDF]

Appl Health Econ Health Policy
Rao M, Freeman M, Thijssen J, Bland S, Sculpher M, Claxton K, Revill P.   +6 more
europepmc   +1 more source

Discounting and Consumption Over an Uncertain Horizon: Draw-Down Plans for Family Trusts [PDF]

Individuals, endowments and trusts face uncertain lifetimes. When the planning horizon of an entity is stochastic and Pareto distributed, hyperbolic discounting and time-varying consumption rates are optimal. We derive expressions for the optimal rate of
Stephen Satchell, Susan Thorp
core  

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Modeling and Characterization of a Self‐Sensing Soft Hydraulic Muscle

Advanced Intelligent Systems, EarlyView.
This article presents the self‐sensing soft hydraulic muscle (SSHM), a novel soft actuator capable of simultaneously sensing force and length without external sensors. A comprehensive model accurately predicts SSHM behavior, validated experimentally with minimal errors. Using propylene glycol enhances durability and reduces hysteresis.
Nhu An Phan, Phuong Linh Dao, Duc Tu Vu, The Doan Le, Sy Trung Ngo, Minh Tri Phan, T. Thang Vo‐Doan, Ke Wu, Mai Thanh Thai   +8 more
wiley   +1 more source

Economic Burden of COVID-19 Hospitalization in Almaty, Kazakhstan. [PDF]

Clinicoecon Outcomes Res
Akhmetzhan A, Abikulova A, Mamyrkul M, Medeulova A, Nassyrova NB, Faizullina K.   +5 more
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Temporary carbon dioxide removals to offset methane emissions. [PDF]

Nat Clim Chang
Venmans F, Rickels W, Groom B.
europepmc   +1 more source