Results 51 to 60 of about 2,638,357 (294)
Advancing Human Skin Equivalents: The Crucial Role of Neurovascular Integration
Advanced Healthcare Materials, EarlyView.This review discusses the importance of integrating vascular and peripheral nerve systems into human skin equivalents (HSEs) to better recapitulate native skin physiology. Recent advances in vascularized, innervated, and neurovascularized HSEs are highlighted, together with emerging bioengineering strategies, current challenges, and future ...
Hao Wu +4 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Journal of New Theory, 2022 The sensitivity of the least-squares estimation in a regression model is impacted by multicollinearity and autocorrelation problems. To deal with the multicollinearity, Ridge, Liu, and Ridge-type biased estimators have been presented in the statistical ...
Tuğba Söküt Açar
doaj +1 more source
Advanced Materials, EarlyView.Membrane‐bound multimodal transducers enable longitudinal ultrasound‐guided photoacoustic monitoring and in situ thermal control of CAR T cells in heterogeneous solid tumors. Imaging correlates T cell trafficking with tumor response, distinguishing responders from nonresponders.
Myeongsoo Kim +14 more
wiley +1 more source
Advanced Materials, EarlyView.Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh +5 more
wiley +1 more source
A Poisson Ridge Regression Estimator [PDF]
The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML). The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson ridge regression
Shukur, Ghazi, Månsson, Kristofer
core +1 more source
Modified One-Parameter Liu Estimator for the Linear Regression Model
Modelling and Simulation in Engineering, 2020 Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper proposes a modified Liu estimator to solve the multicollinearity problem for the linear regression model.
Adewale F. Lukman +3 more
doaj +1 more source
Scientific African, 2022 The multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by lots of authors.
Issam Dawoud +2 more
doaj +1 more source
Life‐Like Ferrous Oxide Microspheres from Kombucha
Advanced Materials Interfaces, EarlyView.Kombucha bacterial cellulose, sodium alginate, and ferrous nitrate self‐assemble into membrane‐enclosed iron oxide microspheres. These microspheres bud daughter vesicles, sustain 24‐h electrochemical oscillations, and filter theta‐band signals.
Panagiotis Mougkogiannis +2 more
wiley +1 more source
The efficiency of modified jackknife and ridge type regression estimators: a comparison [PDF]
Surveys in Mathematics and its Applications, 2008 A common problem in multiple regression models is multicollinearity, which produces undesirable effects on the least squares estimator. To circumvent this problem, two well known estimation procedures are often suggested in the literature.
Sharad Damodar Gore +2 more
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