Results 181 to 190 of about 39,778,138 (282)

Exploring the hidden before the end: A phenomenological analysis of forgiveness at the end of life among spiritual caregivers. [PDF]

Palliat Med
Rossy Parés C, van Poecke N, Fernández-Capo M, Crespo I, Scherer-Rath M, van Laarhoven HWM.   +5 more
europepmc   +1 more source

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

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Evaluate the status and associated factors of Gəˀəz manuscripts heritage preservation: The case of Qäranǝyo mädḫane ˁaläm church, northwest Ethiopia. [PDF]

PLoS One
Yenesew SA.
europepmc   +1 more source

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Advanced Intelligent Discovery, EarlyView.
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula, Lynnicia N. Massenburg, Spenser R. Brown, Amber N. Bible, Chanda R. Harris, Lance X. Zhang, Kiara Parker, Scott T. Retterer, Jennifer L. Morrell‐Falvey, Rama K. Vasudevan, Alexis N. Williams   +10 more
wiley   +1 more source

Fluorescent Hydrogel‐Based Strain Sensor With Machine Learning‐Augmented Performance

Advanced Intelligent Discovery, EarlyView.
Fluorescent hydrogel strain sensor based on carbon quantum dots enabling optical readout of deformation through strain‐dependent emission changes, coupled with Random Forest analysis to capture nonlinear fluorescence‐concentration relationships and identify optimal sensing conditions. Hydrogels are ideal matrices for bio‐integrated wearable sensors due
Tailai Chen, Tianlong Liu, Chao Lu, Rimsha Malik, Jin Zhang   +4 more
wiley   +1 more source

Baptist church and empowerment of women and girls with disabilities in Mhondoro-Ngezi. [PDF]

Afr J Disabil
Mugoni G, Sipeyiye M.
europepmc   +1 more source

Accelerating the Discovery of Proton Conducting Electrolytes via Machine Learning‐Enabled Literature Mining

Advanced Intelligent Discovery, EarlyView.
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin, Seongho Lee, Seulchan Kim, Ho‐Il Ji, Joonhee Kang   +4 more
wiley   +1 more source

Dating ancient manuscripts using radiocarbon and AI-based writing style analysis. [PDF]

PLoS One
Popović M, Dhali MA, Schomaker L, van der Plicht J, Lund Rasmussen K, La Nasa J, Degano I, Perla Colombini M, Tigchelaar E.   +8 more
europepmc   +1 more source

Multiscale and Multi‐Timestep Switching of Multiple Machine Learning Force Fields for Artificial Intelligence‐Driven Materials Simulations

Advanced Intelligent Discovery, EarlyView.
Deep Potential model switching accelerates molecular dynamics by using a faster 4 Å model for most timesteps and periodically applying a high‐accuracy 6 Å model. Validation on solid TiO2 and liquid PEG shows preserved RDF correlations and stable NPT behavior, while NVE energy‐drift analyses identify cases requiring additional validation.
Ryuya Kanda, Megumu Yamazaki, Yuta Yoshimoto, Shintaro Izumi, Atsuki Inoue, Hiroshi Kawaguchi, Yasufumi Sakai   +6 more
wiley   +1 more source