Results 71 to 80 of about 66,013 (262)

Coagulative Granular Hydrogels with an Enzyme Catalyzed Fibrin Network for Endogenous Tissue Regeneration

Advanced Healthcare Materials, EarlyView.
Coagulative granular hydrogels are composed of packed thrombin‐functionalized microgels that catalyze the conversion of fibrinogen into a secondary fibrin network, filling the interstitial voids. This bio‐inspired approach stabilizes the biomaterial to match the robustness of bulk hydrogels without compromising injectability, mimicking the initial ...
Zhipeng Deng, Camila B. Tovani, Simona Bianco, Gianni Comandini, Aya Elghajiji, Mina Aleemardani, Roxana Moscalu, Jeremie Zappia, Bianca Fernandes, Olivia Annett, Chrissy L. Hammond, Jason Wong, Dave J. Adams, Fabrizio Scarpa, Michael R. Whitehouse, Annela M. Seddon, James P. K. Armstrong   +16 more
wiley   +1 more source

A Unified Feasible SQP Framework for sparse and non-negative sparse recovery

EURASIP Journal on Advances in Signal Processing
Sparse signal recovery is a central problem in many areas, including medical imaging, remote sensing, machine learning, and data science. In many practical settings, the underlying signal is inherently non-negative, due to the physical nature of the ...
Mohammad Saeid Alamdari, Masoud Fatemi
doaj   +1 more source

Space alternating variational estimation based sparse Bayesian learning for complex‐value sparse signal recovery using adaptive Laplace priors

IET Signal Processing, 2023
Due to its self‐regularising nature and its ability to quantify uncertainty, the Bayesian approach has achieved excellent recovery performance across a wide range of sparse signal recovery applications.
Zonglong Bai, Liming Shi, Jinwei Sun, Mads Græsbøll Christensen   +3 more
doaj   +1 more source

Sparse Recovery with Partial Support Knowledge [PDF]

, 2011
The goal of sparse recovery is to recover the (approximately) best k-sparse approximation x of an n-dimensional vector x from linear measurements Ax of x. We consider a variant of the problem which takes into account partial knowledge about the signal. In particular, we focus on the scenario where, after the measurements are taken, we are given a set S
Do Ba, Khanh, Indyk, Piotr
openaire   +3 more sources

Sparse Approximation and Recovery by Greedy Algorithms [PDF]

IEEE Transactions on Information Theory, 2014
We study sparse approximation by greedy algorithms. Our contribution is two-fold. First, we prove exact recovery with high probability of random $K$-sparse signals within $\lceil K(1+\e)\rceil$ iterations of the Orthogonal Matching Pursuit (OMP). This result shows that in a probabilistic sense the OMP is almost optimal for exact recovery.
Eugene D. Livshitz, Vladimir N. Temlyakov   +1 more
openaire   +2 more sources

A Long‐Lived Human Neurovascular PENTA Culture Model Captures Incomplete Vascular Repair and Glia‐Associated Signaling After Traumatic Brain Injury

Advanced Healthcare Materials, EarlyView.
A long‐lived, five‐cell‐type human neurovascular (PENTA) model recreates vascular disorganization and incomplete repair after traumatic brain injury (TBI). By integrating endothelial, glial, neuronal, and immune components within a 3D scaffold, the platform enables time‐resolved analysis of neurovascular remodeling and provides a human‐relevant system ...
Daniel S. Hinrichsen, Sunghyun Jun, Colleen M. Arrasmith, Charitha C. Anamala, Mitchell D. Thielen, Anapaula Garcia, Volha Liaudanskaya   +6 more
wiley   +1 more source

Enhanced Human Antigen‐Specific B Cell Responses Using In Vitro 3D Tonsil Cultures Containing Stromal Cells

Advanced Healthcare Materials, EarlyView.
We developed a fully human 3D tonsil cell culture system incorporating supportive stromal cells that better sustains and activates immune cells than conventional methods. The model generates stronger, more targeted antibody responses to viral antigens and vaccines, providing a physiologically relevant and entirely human platform for studying immune ...
Maaike V. J. Braham, Marlon de Gast, Liubov Babii, Sabine Kruijer, Theo M. Bestebroer, Mathilde Richard, Mathieu Claireaux, S. Marieke van Ham, Jelle de Wit, Cécile A. C. M. van Els, Anja ten Brinke, Marit J. van Gils   +11 more
wiley   +1 more source

Sparse ECG Denoising with Generalized Minimax Concave Penalty

Sensors, 2019
The electrocardiogram (ECG) is an important diagnostic tool for cardiovascular diseases. However, ECG signals are susceptible to noise, which may degenerate waveform and cause misdiagnosis.
Zhongyi Jin, Anming Dong, Minglei Shu, Yinglong Wang   +3 more
doaj   +1 more source

Universal discretization and sparse recovery

Journal of Approximation Theory
This excellent paper provides error bounds on approximations that are in the first place based on least-squares approximations. Least-squares approximations in the form of best approximations are basically defined by orthogonality of the error function to the space of approximations.
Feng Dai, Vladimir N. Temlyakov
openaire   +1 more source

Respiratory Organ‐on‐a‐Chip for Disease Modeling: From Architecture to Functional Integration

Advanced Healthcare Materials, EarlyView.
Respiratory organ‐on‐a‐chip (ROC) models capture key mechanical and cellular cues of the human respiratory system, enabling quantitative dissection of disease mechanisms. This review links ROC architectures to disease modeling, functional integration, and commercialization, and proposes a decision framework that aligns model complexity with mechanistic
Jinzhuo Hu, Yongjie Tang, Sidi Liu, Tao Xu, Qian Liu   +4 more
wiley   +1 more source