Results 201 to 210 of about 183,993 (251)

Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD sample. [PDF]

Netw Neurosci
Nakua H, Yu JC, Abdi H, Hawco C, Voineskos A, Hill S, Lai MC, Wheeler AL, McIntosh AR, Ameis SH.   +9 more
europepmc   +1 more source

Cyclic Mechanical Loading of Cardiomyocytes via Pressure‐Driven Non‐Planar Membrane Deformation in a Bioreactor System

Advanced Science, EarlyView.
In this research article, Mansoor and coworkers present a novel device that applies controlled mechanical stimuli to cardiomyocytes using pressure‐driven membrane deformation. By exposing cells to physiologically and pathologically relevant loading conditions, the platform reproduces distinct structural, functional and molecular responses associated ...
Haris Mansoor, Gabrielle Juul, Jil Patel, Heran Pradhan, Gram Hepner, Jackson Jewell, Mark Bardin, Ryan Slusser, Abigail Glezer, Leda Klouda, Melikhan Tanyeri, Anita Saraf   +11 more
wiley   +1 more source

Sustainable Fabrication of Tailored Bone Substitutes: From High‐Throughput Scaffold Manufacturing, Scaled‐Up HMSC Expansion to Dynamic Cultivation in a Perfusion Bioreactor

Advanced Science, EarlyView.
ABSTRACT The demand for off‐the‐shelf biocompatible bone substitutes has driven the development of numerous independent in vitro technologies to generate products resembling physiological tissues. Due to technical challenges and overly simplified cultivation approaches/niches, the end‐products are often uniformly shaped and inferior to native bone ...
Franziska Braun, Anna Paříková, Sandra Rother, Martin Kantor, Salman Muhammad Ilyas, Ricardo Bernhardt, Pavel Ndjawa Yomi, Jaromír Havlica, Revathi Appali, Benjamin Kruppke, Poh Soo Lee   +10 more
wiley   +1 more source

Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing

Advanced Science, EarlyView.
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale, Marie Celine Lefevre, Alessio Carmignani, Maria Cristina Ceccarelli, Matteo Battaglini, Attilio Marino, Gianni Ciofani   +6 more
wiley   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source

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A Survey on Canonical Correlation Analysis

IEEE Transactions on Knowledge and Data Engineering, 2021
In recent years, the advances in data collection and statistical analysis promotes canonical correlation analysis (CCA) available for more advanced research. CCA is the main technique for two-set data dimensionality reduction such that the correlation between the pairwise variables in the common subspace is mutually maximized.
Xinghao Yang, Wei Liu, Dacheng Tao
exaly   +2 more sources

Parametric Canonical Correlation Analysis

2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), 2019
Generally, suppose a wave is a linear combination of multiple basis(Not necessarily a sine or cosine waves, it could also be a wavelet, etc.), different types of waves may be similar on some basis, but vary greatly on a certain basis. To address this problem, we introduce a PCCA-based feature extraction method that extends canonical correlation ...
Shangyu Chen, Shuo Wang 0012, Richard O. Sinnott   +2 more
openaire   +1 more source

Canonical random correlation analysis

Proceedings of the 2010 ACM Symposium on Applied Computing, 2010
Canonical correlation analysis (CCA) is one of the most well-known methods to extract features from multi-view data and has attracted much attention in recent years. However, classical CCA is unsupervised and does not take class label information into account.
Jianchun Zhang, Daoqiang Zhang
openaire   +1 more source