Results 71 to 80 of about 43,727 (260)
Deterministic Compressed Sensing Matrices From Sequences With Optimal Correlation
Compressed sensing (CS) is a new method of data acquisition which aims at recovering higher dimensional sparse vectors from considerably smaller linear measurements. One of the key problems in CS is the construction of sensing matrices. In this paper, we
Zhi Gu +4 more
doaj +1 more source
Highly luminescent chiral manganese halide crystals are synthesized using chiral ligands, and they exhibit dissymmetry factors up to 1.4 × 10−2 and show X‐ray detection scintillation capability with a light yield of 43 380 photons/MeV and a low detection limit of 0.05198 µGyair·s−1.
Yue Han +9 more
wiley +1 more source
A nanofiber‐supported decellularized extracellular matrix (NaDE) membrane recreates key biochemical and mechanical features of native intestinal tissue. This platform enables the formation of a more physiologically relevant intestinal epithelium, enhancing stem cell maintenance and promoting diverse cell differentiation.
Jaeseung Youn +7 more
wiley +1 more source
Sparse kronecker pascal measurement matrices for compressive imaging
Background The construction of measurement matrix becomes a focus in compressed sensing (CS) theory. Although random matrices have been theoretically and practically shown to reconstruct signals, it is still necessary to study the more promising ...
Yilin Jiang +3 more
doaj +1 more source
A Novel Decellularized Fibrocartilage Graft Promotes Tympanic Membrane Repair
An off‐the‐shelf decellularized porcine meniscus fibrocartilage graft (MEND) is engineered for pediatric tympanoplasty. Featuring a microchannel architecture that promotes host cell invasion, MEND rapidly closes tympanic membrane perforations and fully remodels in vivo, outperforming fascia and matching cartilage grafts while avoiding donor‐site ...
Paul M. Gehret +6 more
wiley +1 more source
Logarithmically sparse symmetric matrices
AbstractA positive definite matrix is called logarithmically sparse if its matrix logarithm has many zero entries. Such matrices play a significant role in high-dimensional statistics and semidefinite optimization. In this paper, logarithmically sparse matrices are studied from the point of view of computational algebraic geometry: we present a formula
openaire +3 more sources
Storage Formats for Sparse Matrices in Java [PDF]
Many storage formats (or data structures) have been proposed to represent sparse matrices. This paper presents a performance evaluation in Java comparing eight of the most popular formats plus one recently proposed specifically for Java (by Gundersen and Steihaug [6] Java Sparse Array) using the matrix-vector multiplication operation. © Springer-Verlag
Mikel Luján +4 more
openaire +2 more sources
A 3D Human Neuron‐on‐Chip Platform to Monitor Neuronal Injury Responses
This study presents a novel 3D Neuron‐on‐Chip model that can maintain human PSC‐derived excitatory prefrontal cortex neurons in 3D hydrogels and can be used to monitor neuronal injury responses over time. Results show injury‐induced acute neuronal excitotoxicity, declining neuronal connectivity, and the activation of a neurodegenerative, SASP‐like ...
Ruiping Tang +16 more
wiley +1 more source
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 +9 more
wiley +1 more source
This review examines how cellular behavior is regulated by mechanical cues transmitted through soft biomaterials, from single‐cell mechanosensing to tissue‐level adaptation. It highlights why physiological relevance, rather than model complexity alone, is critical for translational mechanobiology and introduces a scoring framework linking material ...
Mathias Polz +9 more
wiley +1 more source

