Results 71 to 80 of about 6,305 (217)
Reconstruction of Self-Sparse 2D NMR Spectra from Undersampled Data in the Indirect Dimension
Reducing the acquisition time for two-dimensional nuclear magnetic resonance (2D NMR) spectra is important. One way to achieve this goal is reducing the acquired data.
Zhong Chen +4 more
doaj +1 more source
In this paper, we consider convolutional neural networks operating on sparse inputs with an application to depth upsampling from sparse laser scan data. First, we show that traditional convolutional networks perform poorly when applied to sparse data even when the location of missing data is provided to the network. To overcome this problem, we propose
Jonas Uhrig +5 more
openaire +3 more sources
Sparsity driven ultrasound imaging [PDF]
An image formation framework for ultrasound imaging from synthetic transducer arrays based on sparsity-driven regularization functionals using single-frequency Fourier domain data is proposed. The framework involves the use of a physics-based forward model of the ultrasound observation process, the formulation of image formation as the solution of an ...
Tüysüzoğlu, Ahmet +4 more
openaire +6 more sources
Although too much iron in the brain promotes neurodegeneration, iron ion chelators have had mixed effects in clinical trials. This review explains why; some chelators do not render the iron redox‐inactive (e.g., L1) whereas others do (e.g., desferrioxamine).
Barry Halliwell
wiley +1 more source
Sonar automatic target recognition (ATR) systems suffer from complex acoustic scattering, background clutter, and waveguide effects that are ever-present in the ocean.
Andrew Christensen +2 more
doaj +1 more source
An epithelial GPR35 isoform supports tumor‐associated transcriptional and metabolic phenotypes
GPR35 generates two functionally distinct isoforms with previously unresolved roles. GPR35‐short mediates immune‐cell chemotaxis, while GPR35‐long is enriched in colorectal cancer epithelium, where it supports increased metabolism, proliferation, and tumor‐associated transcriptional programs.
Jørgen D. Rønneberg +14 more
wiley +1 more source
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs.
Varsha S. Lalapura +3 more
doaj +1 more source
Discerning protein pools by selective staining with self‐labeling tags
Cell surface proteins have an intra‐ and extracellular pool. Combining genetic fusion to self‐labeling tags that can be addressed with small molecule fluorophores allows separating these pools. We highlight recent developments and techniques for state‐of‐the‐art interrogation of cell surface proteins in the complex tissue setting.
Kati Fischermanns, Johannes Broichhagen
wiley +1 more source
Hijacking emergency granulopoiesis: Neutrophil ontogeny and reprogramming in cancer
Neutrophils are highly plastic innate immune cells; their functions in cancer extend beyond the tumour microenvironment. This Review summarises current understanding of neutrophil maturation and heterogeneity and highlights tumour‐induced granulopoiesis as a systemic programme that expands immature, immunosuppressive neutrophils via tumour‐derived ...
Gabriela Marinescu, Yi Feng
wiley +1 more source
Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary +1 more
wiley +1 more source

