Results 41 to 50 of about 26,456 (261)

A Synovium‐on‐Chip Platform to Study Multicellular Interactions in Arthritis

Advanced Healthcare Materials, EarlyView.
The Synovium‐on‐Chip comprises a thin microporous PDMS membrane to support co‐culture of fibroblast‐like synoviocytes (FLS), THP‐1‐derived macrophages, and endothelial cells, enabling real‐time analysis of synovial‐vascular interactions. FLS migration through the pores drives endothelial remodeling, while TNF‐α stimulation induces robust inflammatory ...
Laurens R. Spoelstra, Fleur R. Semmekrot, Nuno Araújo‐Gomes, Daniël Wijnperle, Monique M. A. Helsen, Martijn H.J. Van Den Bosch, Loes. I. Segerink, Séverine Le Gac, Marcel Karperien   +8 more
wiley   +1 more source

Effectiveness of Wavelet Denoising on Secondary Ion Mass Spectrometry Signals

East European Journal of Physics, 2023
Wavelet theory has already achieved huge success. For Secondary Ions Mass Spectrometry (SIMS) signals, denoising the secondary signal, which is altered by the measurement, is considered that an essential step prior to applying such a signal processing ...
Nadia Dahraoui, M'hamed Boulakroune, S. Khelfaoui, S. Kherroubi, Yamina Benkrima   +4 more
doaj   +1 more source

Mixture-model-based signal denoising [PDF]

Advances in Data Analysis and Classification, 2007
This paper proposes a new signal denoising methodology for dealing with asymmetrical noises. The adopted strategy is based on a regression model where the noise is supposed to be additive and distributed following a mixture of Gaussian densities. The parameters estimation is performed using a Generalized EM (GEM) algorithm.
Samé, Allou, Oukhellou, Latifa, Côme, Etienne, Aknin, Patrice   +3 more
openaire   +2 more sources

DNCNet: Deep Radar Signal Denoising and Recognition

IEEE Transactions on Aerospace and Electronic Systems, 2022
Deep learning with its rapid development and advancement has achieved unparalleled performance in many areas like computer vision as well as cognitive radio and signal recognition. However, the performance of most deep neural networks would suffer from degradation in the data mismatch scenario, e.g., the test dataset has a related but nonidentical ...
Mingyang Du, Ping Zhong, Xiaohao Cai, Daping Bi   +3 more
openaire   +3 more sources

Porous Hybrid Soft Actuators From Liquid Crystal Networks and Lyotropic Chromonic Liquid Crystal Templated Hydrogels

Advanced Materials, EarlyView.
The graphic illustrates the design of a hybrid bilayer composed of a liquid crystal hydrogel (LCH) and a liquid crystal network (LCN). The figure highlights the magnetic alignment of the chromonic hydrogel and the thermal‐responsive actuation of the LCN along with the LCH when both layers are aligned or misaligned, enabling programmable, light‐driven ...
Ramón Santiago Herrera Restrepo, Irving Hafed Tejedor García, Matthew Gene Scarfo, Negin Bouzari, Negar Rajabi, Olga Bantysh, Joel Torres‐Andrés, Christopher W. V. James, Maria Guix, Amirreza Aghakhani, Jordi Ignés‐Mullol, Salvador Pané, Josep Puigmartí‐Luis, Hamed Shahsavan   +13 more
wiley   +1 more source

From Signal to Safety: A Data-Driven Dual Denoising Model for Reliable Assessment of Blasting Vibration Impacts

Buildings
With the acceleration of urban renewal, directional blasting has become a common method for building demolition. Analyzing the time–frequency characteristics of blast-induced seismic waves allows for the assessment of risks to surrounding structures ...
Miao Sun, Jing Wu, Junkai Yang, Li Wu, Yani Lu, Hang Zhou   +5 more
doaj   +1 more source

Improved multi-wavelet denoising with neighboring coefficients of cutting force for application in the load spectrum of computer numerical control lathe

Advances in Mechanical Engineering, 2018
To obtain accurate computer numerical control lathe cutting force signals and improve the precision of load stress cycle statistic, an improved multi-wavelet denoising with neighboring coefficients method is proposed.
Jialong He, Zhaojun Yang, Chuanhai Chen, Guofa Li, Zhen Li, Yuhui Jia   +5 more
doaj   +1 more source

Soft Ionic and Electronic Triboelectric Nanogenerators: Toward Attachable and Implantable Biomedical Applications

Advanced Materials, EarlyView.
This review provides an overview of triboelectric nanogenerator (TENG)–based biomedical applications by classifying studies into electronic and ionic systems across attachable and implantable platforms. It summarizes key material choices, device structures, and working mechanisms that characterize current TENG‐based research, and outlines six future ...
Kyongtae Choi, Jimin Park, Won Jun Song, Soohwan An, Seonggyu Choe, Byeong‐Rak Keum, Min Young Kim, Dae Hee Hwang, Young‐Geun Park, Sung‐Won Kim, Sangyul Baik, Gwang‐Bum Im, Younghoon Lee   +12 more
wiley   +1 more source

A New Underwater Acoustic Signal Denoising Technique Based on CEEMDAN, Mutual Information, Permutation Entropy, and Wavelet Threshold Denoising

Entropy, 2018
Owing to the complexity of the ocean background noise, underwater acoustic signal denoising is one of the hotspot problems in the field of underwater acoustic signal processing.
Yuxing Li, Yaan Li, Xiao Chen, Jing Yu, Hong Yang, Long Wang   +5 more
doaj   +1 more source

Generative Models for Crystalline Materials

Advanced Materials, EarlyView.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source