Results 151 to 160 of about 640,924 (242)

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Exploring relationships between college students' social networks, social support, and mental health during the COVID-19 pandemic. [PDF]

PLOS Ment Health
Broda MD, Wang TW, Hui J, Ross E, McGinnis HA, Chan DM, Tomlinson CA, Luce C.   +7 more
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

Stability analysis of discrete delta fractional models under summation multipoint constraints for robust engineering systems. [PDF]

Sci Rep
Mohammed PO, Al-Sarairah E, Baleanu D, Yousif MA, Arab M.   +4 more
europepmc   +1 more source

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

Advanced Intelligent Discovery, EarlyView.
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh, Raiyan Siddique, Sarah S. Sharif, Yaser Mike Banad   +3 more
wiley   +1 more source

Editorial: Complexity Characteristics of Natural Language. [PDF]

Entropy (Basel)
Drożdż S, Kwapień J, Stanisz T.
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Quantifying transcript complexity via the condition number of gene-specific random matrix. [PDF]

Brief Bioinform
Zhang B, Guo Y, Liu G, Zou M.
europepmc   +1 more source

Robot‐Assisted Measurement of the Critical Micelle Concentration

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The study introduces (SIMO) smart integrator for manual operations, a robotic platform for precise, repeatable determination of (CMC) critical micelle concentration in surfactants. SIMO reduces standard deviation by 80% compared to manual methods. Surfactant, dye, and diluent selection, robotic protocols, and data handling are detailed.
Vincenzo Scamarcio, Gadi Slor, Josie Hughes, Francesco Stellacci   +3 more
wiley   +1 more source

An adaptive hybrid quadrature scheme: Combining Simpson's rule and Gaussian quadrature for enhanced numerical integration. [PDF]

PLoS One
Asgedom AA, Kefela YY.
europepmc   +1 more source