Results 71 to 80 of about 141 (134)

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

A Language‐Guided Multimodal Foundation Model for Zero‐Shot and Multi‐Task Brain Signal Analysis

Advanced Intelligent Systems, EarlyView.
METIS aligns brain signals with natural‐language instructions to enable zero‐shot and multi‐task brain signal analysis. Pretrained on over 70 000 h of EEG and iEEG recordings, it generalizes across sleep stage classification, epilepsy detection, and neurological disorder diagnosis, providing a scalable foundation model for clinically meaningful brain ...
Mingzhi Chen, Yiyu Gui, Guibo Luo, Yuchao Yang   +3 more
wiley   +1 more source

Balancing Exploration and Exploitation Through a Sequential Hybrid of Roach Infestation and Mayfly Algorithms for Constrained Engineering Design Optimization

AI &Innovation, EarlyView.
ABSTRACT Maintaining an effective balance between exploration and exploitation is essential during optimization processes, from mathematical functions to more complex problems such as constrained engineering design optimization, particularly when addressing highly nonlinear issues with numerous local optima and strict feasibility requirements.
Enrique Lizárraga, Fevrier Valdez, Oscar Castillo, Patricia Melin   +3 more
wiley   +1 more source

Cortical Network Overconnectivity Relates to Sensory, Cognitive, and Social Dimensions in Young Children With Autism Spectrum Disorder

Autism Research, EarlyView.
ABSTRACT The heterogeneity in both the neurobiological mechanisms and the phenotypic presentations of autism spectrum disorder (ASD) poses a major challenge to clinical and translational research. Alterations in functional connectivity (FC) have been associated with ASD, yet it remains unclear whether and how divergent brain network properties may ...
Borja Rodríguez‐Herreros, Ahmad Mheich, Joana Maria Almeida Osório, Sonia Richetin, Vincent Junod, Lorène Arnold, Victoria Aeschbach, Lilia Nora Adamou, Katherina Gschwend, Laura Mendes, David Romascano, Paola Yu, Marine Jequier Gygax, Anne M. Maillard, Micah M. Murray, Mahmoud Hassan, Nadia Chabane   +16 more
wiley   +1 more source

Mitochondria‐endoplasmic reticulum organelle glue as maturation promoter for origination/dimensional dual‐cross cardiomyocytes

BMEMat, EarlyView.
Mitochondria‐endoplasmic reticulum contact sites (MERCS) are areas where the mitochondria and endoplasmic reticulum closely interact. In this study, we utilize synthetic organelle glues to artificially engineer MERCS for regulating cardiomyocyte development, through which the immature and chemo‐plasticity issues of undifferentiated cells are addressed.
Wei Tang, Hao Sun, Chenqi Duan, Jiajia Chang, Yuxing Wang, Ming Zhao, Huiyue Zhao, Shan Lu, Yang Yang, Da Huo   +9 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Geometry‐Based Neural‐Network Prediction of Electron Localization Function Topology in Dense Hydrogen

Chemistry – A European Journal, EarlyView.
We present a machine‐learning framework that predicts the electron localization function (ELF) of dense hydrogen directly from atomic geometry, bypassing explicit electronic‐structure calculations. Trained on ab initio data for fluid hydrogen across multiple pressures, the model achieves high accuracy and reveals pressure‐dependent nonlocal ...
Xiaoyu Wang, Miriam Marqués, Sergio Gómez, Francesc Serratosa, Eva Zurek, Julia Contreras‐García   +5 more
wiley   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

Comparative assessment of volume‐of‐fluid (VOF) multiphase solvers for viscoplastic flow over grooved patterned surfaces

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Accurately simulating multiphase flows at low capillary numbers remains challenging due to spurious currents and interface discretization errors. We present a systematic comparison of four volume‐of‐fluid (VOF) solvers within the OpenFOAM framework for pressure‐driven Poiseuille–Bingham flow over grooved surfaces: interFoam with classical ...
Amir Joulaei, Alice Villette, Seyed Mohammad Taghavi   +2 more
wiley   +1 more source