Results 151 to 160 of about 2,418,141 (314)

De novo Genome Assembly and Annotation of 12 Fungi Associated with Fruit Tree Decline Syndrome in ON, Canada. [PDF]

Sci Data
Sulman M, Ilyukhin E, Villanueva O, Nguyen HDT, Ali S, Ellouze W.   +5 more
europepmc   +1 more source

Genomic reconstruction and directed interventions in a multidrug-resistant Shigellosis outbreak in Seattle, WA, USA: a genomic surveillance study. [PDF]

Lancet Infect Dis, 2023
Tansarli GS, Long DR, Waalkes A, Bourassa LA, Libby SJ, Penewit K, Almazan J, Matsumoto J, Bryson-Cahn C, Rietberg K, Dell BM, Hatley NV, Salipante SJ, Fang FC.   +13 more
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Dissemination and Implementation of a Telehealth-Enabled Program for Providing Infectious Disease Expertise in Rural Settings. [PDF]

Open Forum Infect Dis
Jump RLP, Bej TA, Vivo A, Wilson BM, Kowal C, Song S, Abdelrahim S, Wilson G, Milner A, Nguyen A, Rodriguez KL, Beyer N, Michaels Z, Amundson C, Bajema KL, Beck A, Burnham JP, Crnich CJ, Drekonja DM, Epstein L, Ewers T, Livorsi DJ, Narayan M, Perez F, Pfeiffer CD, Sabzwari RW, Salti AM, Tate D, Walkner T, Webster AS, Evans CT.   +30 more
europepmc   +1 more source

Magnificent Manifestation: The Symbolic Architecture of A.G. Rizzoli [PDF]

, 1997
Hernandez, Jo Farb
core   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source

Basal ganglia output (entopeduncular nucleus) coding of contextual kinematics and reward in the freely moving mouse. [PDF]

Elife
Verma Rodriguez AK, Ramírez-Jarquin JO, Rossi-Pool R, Tecuapetla F.   +3 more
europepmc   +1 more source

Surface Roughness Prediction in Ultra-Precision Milling: An Extreme Learning Machine Method with Data Fusion. [PDF]

Micromachines (Basel), 2023
Shang S, Wang C, Liang X, Cheung CF, Zheng P.   +4 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Exploring social, cultural and environmental factors that influence attitudes to exercise among people with Parkinson's disease: A qualitative study. [PDF]

J Health Psychol
Baron F, Bogosian A.
europepmc   +1 more source