Results 171 to 180 of about 876,733 (274)

Mechanical Properties of Architected Polymer Lattice Materials: A Comparative Study of Additive Manufacturing and CAD Using FEM and µ‐CT

Advanced Functional Materials, EarlyView.
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker, Thierry Roland, Damien Favier, Antoine Egele, Michael Heymann, Cosima Stubenrauch   +5 more
wiley   +1 more source

The Utilization of Partial Least Squares for Simultaneous Feature Selection and Extraction

Revstat Statistical Journal
Several works concerning the utilization of Partial Least Squares as a supervised dimension reduction technique have been developed over the years in the field of chemometrics, among others, for regression purposes. However, Partial Least Squares can be
Elisavet Beki, Ntotsis Kimon
doaj  

Multi-marker discovery for mild cognitive impairment in metabolomics using machine learning with a global surrogate model via partial least squares. [PDF]

Metabolomics
Tatara Y, Yamamoto H, Terai K, Matsuta R, Kasai S, Tamada Y, Mikami T, Murashita K, Itoh K.   +8 more
europepmc   +1 more source

Implementation of Drug‐Induced Rhabdomyolysis and Acute Kidney Injury in Microphysiological System

Advanced Functional Materials, EarlyView.
A modular Muscle–Kidney proximal tubule‐on‐a‐chip integrates 3D skeletal muscle and renal proximal tubule tissues to model drug‐induced rhabdomyolysis and acute kidney injury. The coculture system enables dynamic tissue interaction, functional contraction monitoring, and quantification of nephrotoxicity, revealing drug side effect‐induced metabolic ...
Jaesang Kim, Zhuo Feng Lee, Gi‐Dong Sim, Sejoong Kim, Jessie S. Jeon   +4 more
wiley   +1 more source

Partial least squares multimodal analysis of brain network correlates of language deficits in aphasia. [PDF]

Brain Commun
Kristinsson S, den Ouden DB, Rorden C, Newman-Norlund R, Johnson L, Wilmskoetter J, Gleichgerrcht E, Hillis AE, Hickok G, Fridriksson J, Bonilha L.   +10 more
europepmc   +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

Partial least squares (PLS) regression and its application to coal analysis

Revista Técnica de la Facultad de Ingeniería
Los métodos instrumentales de análisis químico hacen uso de las relaciones entre la señal obtenida y una propiedad del sistema estudiado (generalmente, una concentración).
Carlos E Alciaturi, Marcos E Escobar, Carlos De La Cruz, Carlos Rincón   +3 more
doaj  

Lavender hydrosol analysis using UV spectroscopy data and partial least squares regression. [PDF]

MethodsX
Preiner S, Tarcsay BL, Pethő D, Miskolczi N.   +3 more
europepmc   +1 more source

Expanding Chemical Space of Nucleic Acid Nanoparticles for Tunable Antiviral‐Like Immunomodulatory Responses and Potent Adjuvant Activity

Advanced Functional Materials, EarlyView.
We introduce a nucleic acid nanoparticle (NANP) platform designed to be rrecognized by the human innate immune system in a regulated manner. By changing chemical composition while maintaining constant architectural parameters, we identify key determinants of immunorecognition enabling the rational design of NANPs with tunable immune activation profiles
Martin Panigaj, Hannah S. Newton, Jian Wang, Laxmi Pandey, Yelixza I. Avilla, Phong Nguyen, Morgan Chandler, Justin Halman, Yasmine Radwan, Stephanie Smith, Elijah Edmondson, Simone Difilippantonio, Chelsea Sanders, Bao Tran, Yongmei Zhao, Shaojun Xie, Edward Cedrone, Barry W. Neun, Meni Wanunu, Nikolay V. Dokholyan, Marina A. Dobrovolskaia, Kirill A. Afonin   +21 more
wiley   +1 more source

Predicting the Determinants of Colorectal Cancer Screening Behaviors Using Protection Motivation Theory: A Cross-Sectional Partial Least Squares Structural Equation Modeling Analysis. [PDF]

Health Sci Rep
Gholian-Aval M, Behrouzi B, Jamali J.
europepmc   +1 more source