Results 121 to 130 of about 621,525 (301)

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Suppression of information spreading in MEG source estimation using a functionally-structured Bayesian approach

NeuroImage
Magnetoencephalography (MEG) is a noninvasive method that can measure human brain activity with high temporal resolution. However, the spatial resolution of MEG is limited because MEG signals are recorded by sensors located outside the head. Although MEG
Kai Miyazaki, Shun Nirasawa, Naoki Ishibashi, Kazuaki Akamatsu, Okito Yamashita, Yoichi Miyawaki   +5 more
doaj   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

The Association between the Parents’ Knowledge of Carbohydrate Counting and the Glycaemic Control of the Children with Type 1 Diabetes

International Journal of Pediatrics, 2018
Background. Medical nutritional therapy is an important component of type 1 diabetes (T1D) care in children and carbohydrate counting is one such method.
Priyanga Ranasinghe, Vidarsha Rajini Senadeera, Rashmi Senarathna, Uththara Sapurnika, Vindhya Ramanayake, Ranil Jayawardena   +5 more
doaj   +1 more source

Multivariate generalized S-estimators. [PDF]

In this paper we introduce generalized S-estimators for the multivariate regression model. This class of estimators combines high robustness and high efficiency.
Croux, Christophe, Roelant, E., Van Aelst, S.   +2 more
core  

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Bayes Estimation for the Mean Matrix of the SSMESN Family of Matrix Variate Distributions

Austrian Journal of Statistics
In this paper, the problem of finding a Bayes estimation for the mean matrix of the scale and shape mixtures of matrix variate extended skew normal distributions is considered, and its applications in the multivariate linear regression and the stress ...
Amir Rezaei, Fatemeh Yousefzadeh
doaj   +1 more source

Mapping Nanoscale Protein‐Corona Kinetics of DoE‐Optimized Perfluorocarbon Encapsulated‐PLGA Nanoparticles by In Situ, Time‐Resolved Synchrotron SAXS

Advanced Healthcare Materials, EarlyView.
A two‐phase workflow (OFAT screening followed by central composite design) maps how processing variables tune PFCE‐PLGA nanoparticle size, dispersity, surface charge, loading, and 19F‐MRI signal. In situ, time‐resolved synchrotron SAXS tracks albumin‐corona growth on intact dispersions and reveals PFCE‐dependent adsorption pathways.
Joice Maria Joseph, Maria Rosa Gigliobianco, Cristina Minnelli, Paolo Moretti, Francesco Spinozzi, Giovanna Mobbili, Sara Pistolesi, Cristina Casadidio, Gabriella Teti, Roberta Censi, Stefano Antonio Gattone, Piera Di Martino   +11 more
wiley   +1 more source

Cholesky-based model averaging for covariance matrix estimation

Statistical Theory and Related Fields, 2017
Estimation of large covariance matrices is of great importance in multivariate analysis. The modified Cholesky decomposition is a commonly used technique in covariance matrix estimation given a specific order of variables.
Hao Zheng, Kam-Wah Tsui, Xiaoning Kang, Xinwei Deng   +3 more
doaj   +1 more source

Marginal Effects in Multivariate Probit and Kindred Discrete and Count Outcome Models, with Applications in Health Economics [PDF]

Estimation of marginal or partial effects of covariates x on various conditional parameters or functionals is often the main target of applied microeconometric analysis.
John Mullahy
core