Results 81 to 90 of about 1,788,984 (247)
The diamond norm plays an important role in quantum information and operator theory. Recently, it has also been proposed as a regularizer for low-rank matrix recovery.
Kliesch, Martin +3 more
core +1 more source
Cross-domain underwater object recognition is essential for intelligent visual monitoring in marine ranching, yet domain shift caused by varying water conditions and imaging devices severely degrades model performance.
Yun Zhang, Lei Song
doaj +1 more source
Comprehensive Prohibition of Nuclear Weapons - an Emerging International Norm?
There have been calls for the abolition of nuclear weapons from the day they were invented. Over the last fifteen years, some indications can be found that such calls have been getting louder, among them Barack Obama's famous 2009 speech in Prague.
Steffek, J. +3 more
core +1 more source
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
Rank aggregation via nuclear norm minimization
The process of rank aggregation is intimately intertwined with the structure of skew-symmetric matrices. We apply recent advances in the theory and algorithms of matrix completion to skew-symmetric matrices. This combination of ideas produces a new method for ranking a set of items.
David F. Gleich, Lek-Heng Lim
openaire +2 more sources
Combining osimertinib with the STING agonist ADU‐S100 activates innate and adaptive immunity to overcome the non‐inflamed microenvironment of Egfr‐mutant lung cancer. This combination increases NK and CD8+ T‐cell infiltration, associated with activation of the STING‐IRF3 pathway and local immunogenic cell death.
Jun Nishimura +19 more
wiley +1 more source
Alternating Direction Method of Multipliers for Generalized Low-Rank Tensor Recovery
Low-Rank Tensor Recovery (LRTR), the higher order generalization of Low-Rank Matrix Recovery (LRMR), is especially suitable for analyzing multi-linear data with gross corruptions, outliers and missing values, and it attracts broad attention in the fields
Jiarong Shi +3 more
doaj +1 more source
Pair‐wise comparison of the CellSearch and FETCH enrichment technologies for circulating tumor cells (CTCs) from metastatic breast, prostate, and small cell lung cancer patients shows an increased capture of CTCs using FETCH enrichment. The clinical implementation of circulating tumor cells (CTCs) as a predictive tool for therapy efficacy in the ...
Michiel Stevens +6 more
wiley +1 more source
Temporal associations in longitudinal nontargeted metabolomics data are generally ignored by common pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS ...
Zhaozhou Lin +3 more
doaj +1 more source
Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq +8 more
wiley +1 more source

