Results 41 to 50 of about 4,379,261 (288)

Structural and biochemical insights into the thermostable esterase Ta0887 from Thermoplasma acidophilum

FEBS Open Bio, EarlyView.
In this study, a novel esterase from the thermoacidophilic archaeon Thermoplasma acidophilum was biochemically and structurally characterized. Our results demonstrate that Ta0887 is a highly thermostable esterase that preferentially hydrolyzes p‐nitrophenyl hexanoate and possesses an α‐helical cap domain that likely contributes to its substrate ...
Alejandro Delgado‐Rey, Miriam Livier Llamas‐García, Gabriela M. Montero‐Morán, Leticia Santos, Samuel Lara‐González   +4 more
wiley   +1 more source

Local Feature Discriminant Projection [PDF]

, 2016
In this paper, we propose a novel subspace learning algorithm called Local Feature Discriminant Projection (LFDP) for supervised dimensionality reduction of local features.
Zhen, Xiantong, Shao, Ling, He, Xiaofei, Yu, Mengyang   +3 more
core   +1 more source

Characterization of the key membrane protein cytochrome Cyc2 from Ghiorsea bivora

FEBS Open Bio, EarlyView.
This study reports the first detailed biochemical analysis of Cyc2TAG1_1, a cytochrome protein involved in microbial iron oxidation. We produced and purified this enzyme in E. coli, then measured its iron‐oxidizing efficiency, and characterized its electrical and structural properties.
Josiane Azizi, Alain Dolla, Frauke Baymann, Celine Rommevaux, Latifa Elantak, Helene Gaussier, Matthieu Nouailler   +6 more
wiley   +1 more source

Comparison of dimensionality reduction techniques for the fault diagnosis of mono block centrifugal pump using vibration signals

Engineering Science and Technology, an International Journal, 2014
Bearing fault, Impeller fault, seal fault and cavitation are the main causes of breakdown in a mono block centrifugal pump and hence, the detection and diagnosis of these mechanical faults in a mono block centrifugal pump is very crucial for its reliable
N.R. Sakthivel, Binoy B. Nair, M. Elangovan, V. Sugumaran, S. Saravanmurugan   +4 more
doaj   +1 more source

Application of Linear and Nonlinear Dimensionality Reduction Methods

, 2012
Dimensionality reduction methods have proved to be important tools in exploratory analysis as well as confirmatory analysis for data mining in various fields of science and technology. Where ever applications involve reducing to fewer dimensions, feature
Sun, Mingui, Vinjamuri, Ramana, Wang, Wei, Mao, Zhi-Hong   +3 more
core   +1 more source

Gravity‐Dependent Modulation of Downbeat Nystagmus: Insights From Velocity‐Storage Dysfunction

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Downbeat nystagmus varies with head position, a phenomenon termed gravity‐dependent modulation. We aimed to clarify its mechanism using a velocity‐storage model. Methods In 10 patients with downbeat nystagmus due to cerebellar disorders, we recorded eye movements at different pitch‐ and roll‐axis head positions.
Ji‐Hyung Park, Eun‐Hyuk Choi, Jorge Otero‐Millan, David S. Zee, Jeong‐Yoon Choi, Ji‐Soo Kim   +5 more
wiley   +1 more source

Visualization of large-scale user association feature data based on a nonlinear dimensionality reduction method

Nonlinear Engineering
The prosperity of data science and the booming growth of the internet industry have made the analysis and processing of large-scale user-related feature data a particularly important issue in modern society.
Nong Linlin
doaj   +1 more source

A Clustering-Based Dimensionality Reduction Method Guided by POD Structures and Its Application to Convective Flow Problems

Algorithms
Proper orthogonal decomposition (POD) is a widely used linear dimensionality reduction technique, but it often fails to capture critical features in complex nonlinear flows.
Qingyang Yuan, Bo Zhang
doaj   +1 more source

Diffusion Basis Spectrum Imaging of Tissue Microstructure and Early Treatment in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Conventional MRI cannot resolve the coexisting pathological processes within multiple sclerosis tissue. Diffusion Basis Spectrum Imaging decomposes the diffusion signal into fiber, cell, and hindered ratios indexing axonal integrity, cellularity, and extracellular space, respectively.
Apisit Kaewsanit, Aime Luna, Bradley Judge, Nicole Shelley, Karl Friedrichsen, Jayashree Rajamanickam, Zhude Tu, Yong Wang, Tammie L. S. Benzinger, Qing Wang, Matthew R. Brier   +10 more
wiley   +1 more source

A tied-weight autoencoder for the linear dimensionality reduction of sample data

Scientific Reports
Dimensionality reduction is a method used in machine learning and data science to reduce the dimensions in a dataset. While linear methods are generally less effective at dimensionality reduction than nonlinear methods, they can provide a linear ...
Sunhee Kim, Sang-Ho Chu, Yong-Jin Park, Chang-Yong Lee   +3 more
doaj   +1 more source