Enzymatic cleavage as a processing step in the maturation of Muc4/sialomucin complex

2006 ◽  
Vol 97 (6) ◽  
pp. 1267-1274 ◽  
Author(s):  
Pedro Soto ◽  
Jin Zhang ◽  
Kermit L. Carraway
Keyword(s):  
Enzymatic Cleavage ◽  
Processing Step ◽  
Sialomucin Complex

A Flying Gray Ball Multi-illuminant Image Dataset for Color Research

2020 ◽  
Vol 64 (5) ◽  
pp. 50411-1-50411-8
Author(s):  
Hoda Aghaei ◽  
Brian Funt
Keyword(s):  
Machine Vision ◽  
Spectral Reflectance ◽  
Color Constancy ◽  
Ground Truth ◽  
Practical Approach ◽  
Post Processing ◽  
Illumination Estimation ◽  
Processing Step ◽  
Image Dataset

Abstract For research in the field of illumination estimation and color constancy, there is a need for ground-truth measurement of the illumination color at many locations within multi-illuminant scenes. A practical approach to obtaining such ground-truth illumination data is presented here. The proposed method involves using a drone to carry a gray ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera. The captured images are then post-processed. In the post-processing step, machine vision techniques are used to detect the gray ball within each frame. The camera RGB of light reflected from the gray ball provides a measure of the illumination color at that location. In total, the dataset contains 30 scenes with 100 illumination measurements on average per scene. The dataset is available for download free of charge.

HYBRID CLASSIFICATION SCHEMES FOR HEART MURMUR DETECTION TO ASSIST PHONOCARDIOGRAM BASED SIGNAL ACQUISITION

2017 ◽  
Vol 13 (9) ◽  
pp. 6480-6488 ◽  
Author(s):  
A.D. Jeyarani ◽  
Reena Daphne ◽  
Solomon Roach
Keyword(s):  
Neural Network ◽  
Signal Acquisition ◽  
Heart Murmur ◽  
Classification Techniques ◽  
Classification Schemes ◽  
Neural Network Classification ◽  
Nonlinear Classification ◽  
Processing Step ◽  
System Characterization ◽  
Hybrid Classification

The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.

Self-Assembling Micelles Based on an Intrinsically Disordered Protein Domain

2018 ◽  
Author(s):  
Sarah Klass ◽  
Matthew J. Smith ◽  
Tahoe Fiala ◽  
Jessica Lee ◽  
Anthony Omole ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Fusion Proteins ◽  
Organic Molecules ◽  
Intrinsically Disordered Protein ◽  
Protein Domain ◽  
Enzymatic Cleavage ◽  
Intrinsically Disordered ◽  
Disordered Protein ◽  
Self Assembling ◽  
Protein Tag

Herein, we describe a new series of fusion proteins that have been developed to self-assemble spontaneously into stable micelles that are 27 nm in diameter after enzymatic cleavage of a solubilizing protein tag. The sequences of the proteins are based on a human intrinsically disordered protein, which has been appended with a hydrophobic segment. The micelles were found to form across a broad range of pH, ionic strength, and temperature conditions, with critical micelle concentration (CMC) values below 1 µM being observed in some cases. The reported micelles were found to solubilize hydrophobic metal complexes and organic molecules, suggesting their potential suitability for catalysis and drug delivery applications.

A Deep Learning based Arabic Script Recognition System: Benchmark on KHAT

2020 ◽  
Vol 17 (3) ◽  
pp. 299-305 ◽  
Author(s):  
Riaz Ahmad ◽  
Saeeda Naz ◽  
Muhammad Afzal ◽  
Sheikh Rashid ◽  
Marcus Liwicki ◽  
...  
Keyword(s):  
Deep Learning ◽  
Character Recognition ◽  
Data Augmentation ◽  
Short Term Memory ◽  
Recognition System ◽  
Learning Approach ◽  
Arabic Text ◽  
Data Set ◽  
Processing Step ◽  
Handwritten Arabic

This paper presents a deep learning benchmark on a complex dataset known as KFUPM Handwritten Arabic TexT (KHATT). The KHATT data-set consists of complex patterns of handwritten Arabic text-lines. This paper contributes mainly in three aspects i.e., (1) pre-processing, (2) deep learning based approach, and (3) data-augmentation. The pre-processing step includes pruning of white extra spaces plus de-skewing the skewed text-lines. We deploy a deep learning approach based on Multi-Dimensional Long Short-Term Memory (MDLSTM) networks and Connectionist Temporal Classification (CTC). The MDLSTM has the advantage of scanning the Arabic text-lines in all directions (horizontal and vertical) to cover dots, diacritics, strokes and fine inflammation. The data-augmentation with a deep learning approach proves to achieve better and promising improvement in results by gaining 80.02% Character Recognition (CR) over 75.08% as baseline.

An investigation of the enzymatic cleavage of κ-casein in non-coagulating milk

2020 ◽  
Vol 109 ◽  
pp. 104754
Author(s):  
Kajsa Nilsson ◽  
Ahmed Abdelghani ◽  
Stephen Burleigh ◽  
Lene Buhelt Johansen ◽  
Helena Lindmark-Månsson ◽  
...  
Keyword(s):  
Enzymatic Cleavage

Despeckling of Sar Images Using Shrinkage of Two-Dimensional Discrete Orthonormal S-Transform

2020 ◽  
pp. 2150023
Author(s):  
Priya R. Kamath ◽  
Kedarnath Senapati ◽  
P. Jidesh
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Relevant Information ◽  
Detection Algorithm ◽  
Two Dimensional ◽  
Sar Images ◽  
S Transform ◽  
Processing Step ◽  
Frequency Components ◽  
Shock Filter

Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated.

scholarly journals S-Alkylcysteinase: Enzymatic Cleavage of S-Methyl-l-cysteine and Its Sulfoxide

1963 ◽  
Vol 238 (4) ◽  
pp. 1441-1446
Author(s):  
Junichi Nomura ◽  
Yasutomi Nishizuka ◽  
Osamu Hayaishi
Keyword(s):  
Enzymatic Cleavage

scholarly journals ENZYMATIC CLEAVAGE OF THIOETHERS

1950 ◽  
Vol 186 (1) ◽  
pp. 287-296
Author(s):  
Francis. Binkley
Keyword(s):  
Enzymatic Cleavage
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