Results 151 to 160 of about 52,512 (299)

Design Optimization of Soft Fabric Pneumatic Actuators

Advanced Intelligent Systems, EarlyView.
This study presents a systematic optimization framework for elongating and bending fabric‐based soft pneumatic actuators. After a preliminary design‐space reduction, the framework minimizes energy consumption under mechanical performance constraints by integrating validated finite element modeling with statistical surrogate models. Optimal designs were
Grigorios M. Chatziathanasiou, Konstantina Tsintzira, Panagiotis Polygerinos   +2 more
wiley   +1 more source

Regional Neuroanatomic Effects on Brain Age Inferred Using Magnetic Resonance Imaging and Ridge Regression. [PDF]

J Gerontol A Biol Sci Med Sci, 2023
Massett RJ, Maher AS, Imms PE, Amgalan A, Chaudhari NN, Chowdhury NF, Irimia A, Alzheimer’s Disease Neuroimaging Initiative.   +7 more
europepmc   +1 more source

Cooptimized Sensing and Sole Mechanics Enable Embodied‐Intelligence Design of User‐Specific Smart Footwear

Advanced Intelligent Systems, EarlyView.
An embodied codesign framework for smart footwear is presented, jointly tuning lattice mechanics and sensing for personalized plantar pressure monitoring. By integrating pneumatic sensing within 3D‐printed lattice soles, the system achieves accurate real‐time centre‐of‐pressure tracking with reduced sensor count and energy demand, demonstrating how ...
Fengyu Zhong, Marco Pontin, Amy Zavatsky, Perla Maiolino   +3 more
wiley   +1 more source

Ridge Regression for Functional Form Identification of Continuous Predictors of Clinical Outcomes in Glomerular Disease. [PDF]

Glomerular Dis, 2023
Rubin J, Mariani L, Smith A, Zee J.
europepmc   +1 more source

Automatic Kernel Regression Modelling using Combined Leave-One-Out Test Score and Regularised Orthogonal Least Squares

, 2004
This paper introduces an automatic robust nonlinear identification algorithm using the leave-one-out test score also known as the PRESS (Predicted REsidual Sums of Squares) statistic and regularised orthogonal least squares.
Sharkey, P. M., Hong, X., Sharkey, P.M., Chen, S.   +3 more
core  

High‐elevation endemic plants predicted to lose habitat from changing climate in Washington State

American Journal of Botany, EarlyView.
Abstract Premise High‐elevation plants face unique challenges from potential climate change impacts that will likely require upslope migration into increasingly smaller suitable habitat. This situation is particularly acute for endemic species that by definition occupy small geographic ranges.
Nicholas L. Gjording, Erik W. Ertsgaard, David E. Giblin, Iris H. Dimpsey, Owen B. Bard   +4 more
wiley   +1 more source

The NFDA-Nonsmooth Feasible Directions Algorithm applied to construction of Pareto Fronts of Ridge and Lasso Regressions

Trends in Computational and Applied Mathematics
Ridge and Lasso regressions are types of linear regression, a machine learning tool for dealing with data. Based on multiobjective optimization theory, we transform Ridge and Lasso regression into bi-objective optimization problems. The Pareto fronts of
W. P. Freire
doaj   +1 more source

Ridge Regression and Ill-Conditioning

, 2014
Hoerl and Kennard (1970) suggested the ridge regression estimator as an alternative to the Ordinary Least Squares (OLS) estimator in the presence of multicollinearity.
Iguernane, Mohamed, Ghadban Khalaf, Khalaf, Ghadban, Mohamed Iguernane   +3 more
core   +1 more source

Real‐World Evaluation of Talquetamab for the Treatment of Relapsed/Refractory Multiple Myeloma (RRMM): An International Myeloma Working Group Immunotherapy Registry Real‐World Analysis

American Journal of Hematology, EarlyView.
ABSTRACT Talquetamab is a GPRC5D × CD3 bispecific antibody approved for relapsed/refractory multiple myeloma (RRMM). This is the first real‐world study to comprehensively report muco‐cutaneous toxicities, infections, and efficacy of talquetamab in 151 patients across five countries with the longest follow‐up reported enabling better efficacy and ...
Murali Janakiram, Carlyn R. Tan, Hira Mian, Chiung‐Yu Huang, Rakesh Popat, Joaquín Martínez‐Lopez, Efsthathios Kastritis, Wee‐Joo Chng, Prashant Kapoor, Mrugakshi Dave, Susan Bal, Laurent Garderet, Andre De Menezes Silva Corraes, Christine Riedhammer, Torsten Steinbrunn, Magdalene Corona, Chandramouli Nagarajan, Hermann Einsele, Tom Martin, Amrita Krishnan, Yi Lin, Nadine Abdullah, Niels Abildgaard, Ingerid Abrahamsen, Melissa Alsina, Kenneth Anderson, Hervé Avet‐Loiseau, Ashraf Badros, Nizar Jacques Bahlis, Susan Bal, Rahul Banerjee, Dina Ben‐Yehuda, Jesús G. Berdeja, Michele Cavo, Ajai Chari, Wen‐Ming Chen, Marta Chesi, Wee‐Joo Chng, Yael Cohen, Adam Cohen, Gordon Cook, Luciano Costa, Andrew Cowan, Carlos Fernández de Larrea, Benjamin Derman, Juan Du, Hermann Einsele, Gösta Gahrton, Francesca Gay, Sergio A. Giralt, Simon Harrison, J Jean‐Luc Harousseau, Joy Ho, Doris Hansen, Maung Myo Htut, Andrzej J. Jakubowiak, Murali Janakiram, Prashant Kapoor, Efstathios Kastritis, Jonathan Kaufman, Kihyun Kim, Amrita Krishnan, Shaji Kumar, Chara Kyriakou, Xavier Leleu, Yi Lin, Sagar Lonial, Matthew frigault, Johan L. Lund, Elias Mai, Angelo Maiolino, Elias Mai, Angelo Maiolino, Sireesha Asoori Maringanti, Thomas Martin, Joaquin Martinez‐Lopez, María‐Victoria Mateos, Giampaolo Merlini, Hira Mian, Joseph Mikhael, Monique Minnema, Philippe Moreau, Gareth Morgan, Nikhil Munshi, Omar Nadeem, Chandramouli Nagarajan, Ajay Nooka, Michael O'Dwyer, Rimke Oostvogel, Alberto Orfao, Paula Rodriguez Otero, Darren Pan, Krina Patel, Rashesh Popat, Noemí Puig   +94 more
wiley   +1 more source

Hierarchical Ridge Regression for Incorporating Prior Information in Genomic Studies. [PDF]

J Data Sci, 2022
Kawaguchi ES, Li S, Weaver GM, Lewinger JP.   +3 more
europepmc   +1 more source