Results 111 to 120 of about 620,297 (279)

Distribution of Electrical Resistivity in Single Carbon Fiber Filaments and Its Correlation With Tensile Modulus

Advanced Engineering Materials, EarlyView.
A statistical framework is applied to quantify the distribution of electrical resistivity among individual filaments of two commercially available carbon fiber types. Correlations between filament resistivity, tensile modulus, and diameter are examined and complemented by TEM analysis to provide new insight into filament‐level variability relevant for ...
Nils Wieja, Daniel Sebastian Wolz, Philip Johannes Steinbild, Markus Löffler, Darius Pohl, Jan Wolf, Anja Winkler, Thomas Behnisch, Bernd Rellinghaus, Maik Gude   +9 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

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

Book Reviews

Austrian Journal of Statistics, 2016
Weak Convergence and Empirical Processes (A.W. van der Vaart, J.A. Wellner) Quasi-Likelihood and its Application. A General Approach to Parameter Estimation (C.C. Heyde) Wahrscheinlichkeitsrechnung und Statistik in Beispielen und Aufgaben (V. Nollau, L.
Klaus Pötzelberger, Werner G. Müller, Hans Kellerer, Mushtaq Hussain, Michael Schimek, Reinhold Hatzinger, Walter Katzenbeisser, Friedrich Leisch, Herwig Friedl, Franz Konecny, Klemens Fuchs, Alfred Franz, Wolfgang Wertz, Jürgen Pilz   +13 more
doaj   +1 more source

Maximum A Posteriori Covariance Estimation Using a Power Inverse Wishart Prior [PDF]

, 2012
The estimation of the covariance matrix is an initial step in many multivariate statistical methods such as principal components analysis and factor analysis, but in many practical applications the dimensionality of the sample space is large compared to ...
Nielsen, Søren Feodor, Sporring, Jon
core   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 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

Variable Selection and Inference for Multi-period Forecasting Problems [PDF]

This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models.
Allan Timmermann, Andreas Pick, M. Hashem Pesaran   +2 more
core  

4D Mapping of ZIF Biocomposites for High Protein Loading and Tunable Release Profiles

Advanced Functional Materials, EarlyView.
Systematic four‐dimensional mapping of zeolitic imidazolate framework biocomposites reveals how precursor ratios, total concentration, and washing define crystalline phase, protein loading, and release kinetics. This comprehensive study identifies conditions yielding record loading (∼85%) and precise phase–property correlations.
Michael R. Hafner, Francesco Carraro, Behnaz Abbasgholi‐NA, Simone Dal Zilio, Max Schmallegger, Helmar Wiltsche, Lingcong Ge, Michael R. Reithofer, Efwita Astria, Laura Villanova, Heinz Amenitsch, Christian Doonan, Paolo Falcaro   +12 more
wiley   +1 more source

Extensive Review of Materials for Next‐Generation Transparent Batteries and Their Design Strategies

Advanced Functional Materials, EarlyView.
Review explores emerging materials and design strategies for transparent batteries, examining electrodes, electrolytes, separators, and device architectures optimized for high electrochemical performance, mechanical flexibility, and optical transparency.
Atul Kumar Mishra, Shuvaraj Ghosh, Malkeshkumar Patel, Sourov Hossain, Ju‐Hyung Yun, Joondong Kim   +5 more
wiley   +1 more source