Results 231 to 240 of about 269,153 (284)

A Bertrand model with Brownian motion and behavioral errors. [PDF]

Sci Rep
Gao B, Gao X, He S.
europepmc   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Traditional and Emerging Lipid Markers for Cardiovascular Risk Assessment in Young vs Older Adults.

JAMA Netw Open
Tang R, An J, Bellows BK, Moran AE, Allen NB, Wilkins JT, Xanthakis V, Tsai MY, Shah NS, Reynolds K, Zhang Y.   +10 more
europepmc   +1 more source

Accuracy of Point-of-Care Transdermal GFR Methodology. [PDF]

Kidney Int Rep
Dorshow RB, Friedemann J, Ross-Jones J, Johnson JR, Vitale L, Riley IR, Debreczeny MP, Harr J, Trelford LP, Goldstein SL.   +9 more
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Classical and quantum approaches to probabilistic modeling of fire occurrence in anthracite grade coal. [PDF]

Sci Rep
Thakur AK, Garg RD, Jain K, Kumar D.
europepmc   +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

Bifurcation and computational analysis of anthracnose virus spread in plants with splashing-rain under hypersensitive response. [PDF]

Sci Prog
Faiz K, Ahmad A, Dehingia K, Farman M, Sattar S, Bayram M.   +5 more
europepmc   +1 more source

Advanced machine learning models for predicting unconfined compressive strength from point load strength index of rock samples from Chennai and Bangalore. [PDF]

Sci Rep
Kochukrishnan S, Krishnamurthy P, Prasad CV, Navaneethan M.   +3 more
europepmc   +1 more source