Results 151 to 160 of about 96,366 (253)

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

The role of cognitive function in predicting metabolic risk in schizophrenia: a multi-model comparison incorporating clinical features. [PDF]

Front Psychiatry
Li R, Ren X, Jiang T, Huo J, Ping J, Zhu S, Luo A.   +6 more
europepmc   +1 more source

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

Systemic Immune-Inflammation Markers Associate With Cervical Human Papillomavirus Infection in Asymptomatic Women. [PDF]

Open Forum Infect Dis
Cho MG, Chang Y, Ryu S.
europepmc   +1 more source

Hydration Behavior of Tricalcium Silicate in Seawater Relevant Salt Systems: A Hybrid Study with the Aid of Machine Learning

Advanced Intelligent Discovery, EarlyView.
The hydration behavior of C3S in seawater‐relevant solutions is studied based on experiments, boundary nucleation and growth (BNG) modeling, and machine learning. The main ions included in seawater modify hydration mechanisms, with MgCl2 showing the strongest acceleration effect at the same concentration.
Yanjie Sun, Chen Zhang, Ting Zhang, Mengze Hong, Peiliang Shen, Chi Sun Poon, Gang Li   +6 more
wiley   +1 more source

Calorie tracking and energy balance: links to body image-related factors and functional impairment in a fitness sample. [PDF]

Front Nutr
Slama FA, Halioua R, Claussen MC.
europepmc   +1 more source

Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

Advanced Intelligent Systems, EarlyView.
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov, Hanzhi Ma, Junbo Peng, Huifeng Dong, Jiangshan Zhuo, Mengke Shi, Lvting Wang, Shengchao Jiang, Ye Shi   +8 more
wiley   +1 more source

Auditory-conceptual associations in Peter and the Wolf and Carnival of the Animals: Evidence from 6- to 9-year-old children. [PDF]

Psychon Bull Rev
Di Stefano N, Ansani A, Focaroli V, Borsella R, Formenti G, Velardi A, Schiavio A, Spence C.   +7 more
europepmc   +1 more source

Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing

Advanced Intelligent Systems, EarlyView.
This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang, Hyeok Yun, Kyeongrae Cho, Seungjoon Eom, Soomin Kim, Seongsoo Jeong, Rockhyun Baek   +6 more
wiley   +1 more source

Mental health of palestinian undergraduates during the War on Gaza: a cross-sectional study on PTSD, CPTSD, and psychological distress. [PDF]

Sci Rep
Baker I, Zrineh A, Qadire MA, Ramadan M, Sneineh HA, Kateeb E, Khatib S.   +6 more
europepmc   +1 more source