Results 51 to 60 of about 25,940 (257)

Sparse dimensionality reduction approaches in Mendelian randomisation with highly correlated exposures

eLife, 2023
Multivariable Mendelian randomisation (MVMR) is an instrumental variable technique that generalises the MR framework for multiple exposures. Framed as a regression problem, it is subject to the pitfall of multicollinearity.
Vasileios Karageorgiou, Dipender Gill, Jack Bowden, Verena Zuber   +3 more
doaj   +1 more source

Exact and Approximation Algorithms for Sparse PCA

CoRR, 2020
49 pages, 1 ...
Yongchun Li, Weijun Xie 0001
openaire   +2 more sources

Sparse PCA for High-Dimensional Data With Outliers [PDF]

Technometrics, 2016
A new sparse PCA algorithm is presented, which is robust against outliers. The approach is based on the ROBPCA algorithm that generates robust but nonsparse loadings. The construction of the new ROSPCA method is detailed, as well as a selection criterion for the sparsity parameter.
Hubert, Mia, Reynkens, Tom, Schmitt, Eric, Verdonck, Tim   +3 more
openaire   +1 more source

Tuning Mechanoreceptor Signaling Enhances the Adjuvant Effect of Biomaterial Vaccines

Advanced Functional Materials, EarlyView.
Matrix stiffness serves as an independent immunological signal in biomaterial vaccines. Stiffer microporous hydrogel vaccines enhance dendritic cell maturation and migration to draining lymph nodes, promote T follicular helper cell expansion through Yap/Taz signaling, and increase antigen‐specific antibody production.
Lily Shang, Daniel P. Mayer, Prabhat K. Purbey, Yingzi Liu, Kindra Kelly‐Scumpia, Clara Kang, Natalie Tsubamoto, Dhriti Bolangadi, Iqra Arshad, Charisse Ng, Maksim V. Plikus, Dino Di Carlo, Jason S. Weinstein, Philip O. Scumpia   +13 more
wiley   +1 more source

Image Super-Resolution Via Wavelet Feature Extraction and Sparse Representation [PDF]

Radioengineering, 2018
This paper proposes a novel Super-Resolution (SR) technique based on wavelet feature extraction and sparse representation. First, the Low-Resolution (LR) image is interpolated employing the Lanczos operation. Then, the image is decomposed into sub-bands (
V. Alvarez-Ramos, V. Ponomaryov, S. Sadovnychiy   +2 more
doaj  

High‐Throughput Digital Decoding of Vascular Heterogeneity in Patient‐Specific Tumor Microenvironments

Advanced Healthcare Materials, EarlyView.
ABSTRACT Quantitative characterization of vascular heterogeneity in complex microphysiological systems (MPS), particularly within patient‐derived tumor microenvironments, remains a major challenge for scalable disease modeling and therapeutic evaluation.
Jungseub Lee, Wooju Park, Sujin Hyung, Sangmin Jung, Kyungho Lee, Junseok Jeon, Noo Li Jeon, Jeeyun Lee, Hye Ryoun Jang, Jihoon Ko   +9 more
wiley   +1 more source

Multifunctional Catechol‐Functionalized Cellulose Hydrogels for the Minimally Invasive Treatment of Acute Optic Nerve Injuries

Advanced Healthcare Materials, EarlyView.
Catechol‐functionalized cellulose hydrogels are developed as injectable, bioadhesive platforms for retinal neuroprotection. The hydrogels exhibit tunable rheological and mechanical properties, strong tissue adhesion, and sustained antioxidative activity.
Kai‐Hsiang Chang, Yi‐Ke Lin, Wei‐Li Chen, Ta‐Ching Chen, Jiashing Yu   +4 more
wiley   +1 more source

Rational Polynomial Coefficient Estimation via Adaptive Sparse PCA-Based Method

Remote Sensing
The Rational Function Model (RFM) is composed of numerous highly correlated Rational Polynomial Coefficients (RPCs), establishing a mathematical relationship between two-dimensional images and three-dimensional spatial coordinates.
Tianyu Yan, Yingqian Wang, Pu Wang
doaj   +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

Machine Learning for Green Solvents: Assessment, Selection and Substitution

Advanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta, Janhavi Nistane, Abhishek Sose, Harikrishna Sahu, Rampi Ramprasad   +4 more
wiley   +1 more source