Results 101 to 110 of about 869,216 (289)
Elinvar Materials: Recent Progress and Challenges
Elinvar materials, exhibiting temperature‐invariant elastic modulus, are critical for precision instruments and emerging technologies. This article reviews recent progress in the field, with a focus on the anomalous thermoelastic behavior observed in key material systems.
Wenjie Li, Yang Ren
wiley +1 more source
Anomaly Detection of Hospital Claim Using Support Vector Regression
BPJS Kesehatan plays a crucial role in providing affordable access to healthcare services and reducing individual financial burdens. However, deficit issues can disrupt the sustainability of the program, making anomaly detection highly important to ...
Luthfia Nurma Hapsari, Nur Rokhman
doaj +1 more source
Lipid nanoparticles (LNPs) are optimized to co‐deliver Cas9‐encoding messenger RNA (mRNA), a single guide RNA (sgRNA) targeting the endogenous cystic fibrosis transmembrane conductance regulator (CFTR) gene, and homologous linear double‐stranded donor DNA (ldsDNA) templates encoding CFTR.
Ruth A. Foley +12 more
wiley +1 more source
Training Subset Selection for Support Vector Regression [PDF]
Cenru Liu, Jiahao Cen
doaj +1 more source
An adaptive sampling method for global sensitivity analysis based on least-squares support vector regression [PDF]
In the field of engineering, surrogate models are commonly used for approximating the behavior of a physical phenomenon in order to reduce the computational costs.
Bourinet, Jean-Marc +2 more
core
Substrate Stress Relaxation Regulates Cell‐Mediated Assembly of Extracellular Matrix
Silicone‐based viscoelastic substrates with tunable stress relaxation reveal how matrix mechanics regulates cellular mechanosensing and cell‐mediated matrix remodelling in the stiff regime. High stress relaxation promotes assembly of fibronectin fibril‐like structures, increased nuclear localization of YAP and formation of β1 integrin‐enriched ...
Jonah L. Voigt +2 more
wiley +1 more source
Using Support Vector Machine for Prediction Dynamic Voltage Collapse in an Actual Power System [PDF]
—This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines. Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation
Hussain, Aini +2 more
core
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim +14 more
wiley +1 more source
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source

