Results 81 to 90 of about 82,972,811 (208)

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu, Pan Zhang, Shangqian Wu, Hao Sun, Minwei Li, Sophia Tsoka, Zizhang Sheng, Lei Deng   +7 more
wiley   +1 more source

Numerical approximation of Volterra integral equations with highly oscillatory kernels

Results in Applied Mathematics
The Volterra integral equations (VIEs) with oscillatory kernels arise in several applied problems and need to be treated with a computational method have multiple characteristics. In the literature (Zaheer-ud-Din et al., 2022; Li et al., 2012), the Levin
Suliman Khan
doaj   +1 more source

An efficient sparse regularity concept [PDF]

, 2009
Let A be a 0/1 matrix of size m×n, and let p be the density of A (i.e., the number of ones divided by m · n). We show that A can be approximated in the cut norm within ε · mnp by a sum of cut matrices (of rank 1), where the number of summands is ...
Cooper, Colin, Amin Coja-Oghlan (5364851), Alan Frieze, Alan Frieze (3880564), Colin Cooper, Coja-Oghlan, Amin, Frieze, Alan, Colin Cooper (5364674), Amin Coja-Oghlan   +8 more
core   +1 more source

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

Adapting the interior point method for the solution of linear programs on high performance computers [PDF]

, 1991
In this paper we describe a unified algorithmic framework for the interior point method (IPM) of solving Linear Programs (LPs) which allows us to adapt it over a range of high performance computer architectures. We set out the reasons as to why IPM makes
Levkovitz, R, Mitra, G, Anderson, J
core   +3 more sources

CONTEST : a Controllable Test Matrix Toolbox for MATLAB [PDF]

, 2009
Large, sparse networks that describe complex interactions are a common feature across a number of disciplines, giving rise to many challenging matrix computational tasks.
Alan Taylor, Higham, Desmond J., EPSRC Grants (Funder), Taylor, Alan, Desmond J. Higham, , EPSRC Grants (Funder), Higham, D.J.   +6 more
core   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Generalized power method for sparse principal component analysis [PDF]

In this paper we develop a new approach to sparse principal component analysis (sparse PCA). We propose two single-unit and two block optimization formulations of the sparse PCA problem, aimed at extracting a single sparse dominant principal component of
Journée, Michel, Nesterov, Yurii, Richtarik, Peter, Sepulchre, Rodolphe   +3 more
core  

Charting Endocrine Progenitors Across Species and Organs

Advanced Science, EarlyView.
Endocrine progenitors give rise to the hormone‐producing cells of the pancreas and intestine. Using single‐cell multiomics and proteomics, this study compares these progenitors across species, systems, and organs, mapping the conserved and species‐specific gene regulatory networks that guide their formation.
Changying Jing, Michael Sterr, Özüm Sehnaz Caliskan, Lama Saber, Nicole Katarina Rogers, Samuel Ogden, Kei Kozawa, Christos Karampelias, Jessica Jaki, Aimée Bastidas‐Ponce, Falk Janos Farkas, Oliver Czarnecki, Osvaldo Rodrigues Pereira, Perla Cota, Valerie Vandenbempt, Diego Balboa, Anika Böttcher, Natalie Krahmer, Mohammad Lotfollahi, Julie B. Sneddon, Heiko Lickert, Mostafa Bakhti   +21 more
wiley   +1 more source

Interpretable STAP Algorithm Based on Deep Convolutional Neural Network

Leida xuebao
In practical settings, the efficacy of Space-Time Adaptive Processing (STAP) algorithms relies on acquiring sufficient Independent Identically Distributed (IID) samples.
Zhipeng LIAO, Keqing DUAN, Jinjun HE, Zizhou QIU, Yongliang WANG   +4 more
doaj   +1 more source