scholarly journals In-depth investigation on quantitative characterization of pyrolysis oil by 31P NMR

RSC Advances ◽  
2016 ◽  
Vol 6 (21) ◽  
pp. 17567-17573 ◽  
Author(s):  
Haoxi Ben ◽  
Jack R. Ferrell III
Keyword(s):  
Quantitative Data ◽  
31P Nmr ◽  
Time Dependent ◽  
Pyrolysis Oil ◽  
Quantitative Characterization

The investigation on time-dependent changes when using 31P NMR to analyze pyrolysis bio-oils has been accomplished and the proposed application of this method is essential to achieve reliable quantitative data.

Novel Experimental-Computational Method for Quantitative Applications in Electronic Packaging

2001 ◽  
Author(s):  
Cosme Furlong ◽  
Ryszard J. Pryputniewicz
Keyword(s):  
Electronic Packaging ◽  
Quantitative Data ◽  
Experimental Methods ◽  
Computational Method ◽  
Electronic Packages ◽  
Quantitative Characterization ◽  
Design And Optimization ◽  
Combined Use ◽  
Microelectronic Components

Abstract Rapid advances in microelectronics require design and optimization of components and packages, for new and ever more demanding applications, in relatively short periods of time while satisfying electrical, thermal, and mechanical specifications, as well as cost and manufacturability expectations. In addition, reliability and durability have to be taken into consideration. As a consequence, some of the most sophisticated analytical, computational, and experimental methods are being used for development, optimization, and quantitative characterization of electronic packages. In this paper, a novel experimental-computational method, based on combined use of recent advances in laser-based optics and computational modeling, is described and its application is demonstrated by case studies of microelectronic components subjected to electro-thermo-mechanical loads. Results of these studies show that this methodology provides an effective engineering tool for nondestructive testing (NDT) applications in electronic packaging and provides indispensable quantitative data for development, optimization, and applications in electronic packaging.

QUANTITATIVE CHARACTERIZATION OF THE COMPLEXITY OF MULTICHANNEL HUMAN EEGS

2005 ◽  
Vol 15 (05) ◽  
pp. 1737-1744 ◽  
Author(s):  
P. E. RAPP ◽  
C. J. CELLUCCI ◽  
T. A. A. WATANABE ◽  
A. M. ALBANO
Keyword(s):  
Standard Deviation ◽  
Principal Component ◽  
Algorithmic Complexity ◽  
Time Dependent ◽  
Quantitative Characterization ◽  
Complexity Measures ◽  
Eyes Closed ◽  
Multichannel Signals ◽  
Eyes Open

In this contribution, eleven different measures of the complexity of multichannel EEGs are described, and their effectiveness in discriminating between two behavioral conditions (eyes open resting versus eyes closed resting) is compared. Ten of the methods were variants of the algorithmic complexity and the covariance complexity. The eleventh measure was a multivariate complexity measure proposed by Tononi and Edelman. The most significant between-condition change was observed with Tononi–Edelman complexity which decreased in the eyes open condition. Of the algorithmic complexity measures tested, the binary Lempel–Ziv complexity and the binary Lempel–Ziv redundancy of the first principal component following mean normalization and normalization against the standard deviation gave the most significant between-group discrimination. A time-dependent generalization of the covariance complexity that can be applied to nonstationary multichannel signals is also described.

Quantitative characterization of phospholipids in milk fat via 31P NMR using a monophasic solvent mixture

Lipids ◽  
2003 ◽  
Vol 38 (5) ◽  
pp. 585-591 ◽  
Author(s):  
Sergio Murgia ◽  
Stefania Mele ◽  
Maura Monduzzi
Keyword(s):  
Milk Fat ◽  
31P Nmr ◽  
Solvent Mixture ◽  
Quantitative Characterization

scholarly journals Analysis of turnover dynamics of the submembranous actin cortex

2013 ◽  
Vol 24 (6) ◽  
pp. 757-767 ◽  
Author(s):  
Marco Fritzsche ◽  
Alexandre Lewalle ◽  
Tom Duke ◽  
Karsten Kruse ◽  
Guillaume Charras
Keyword(s):  
Quantitative Data ◽  
Living Cells ◽  
Cell Cortex ◽  
Turnover Rates ◽  
Quantitative Characterization ◽  
Actin Cortex ◽  
Associated Proteins ◽  
Myosin Motors ◽  
Slow Turnover

The cell cortex is a thin network of actin, myosin motors, and associated proteins that underlies the plasma membrane in most eukaryotic cells. It enables cells to resist extracellular stresses, perform mechanical work, and change shape. Cortical structural and mechanical properties depend strongly on the relative turnover rates of its constituents, but quantitative data on these rates remain elusive. Using photobleaching experiments, we analyzed the dynamics of three classes of proteins within the cortex of living cells: a scaffold protein (actin), a cross-linker (α-actinin), and a motor (myosin). We found that two filament subpopulations with very different turnover rates composed the actin cortex: one with fast turnover dynamics and polymerization resulting from addition of monomers to free barbed ends, and one with slow turnover dynamics with polymerization resulting from formin-mediated filament growth. Our data suggest that filaments in the second subpopulation are on average longer than those in the first and that cofilin-mediated severing of formin-capped filaments contributes to replenishing the filament subpopulation with free barbed ends. Furthermore, α-actinin and myosin minifilaments turned over significantly faster than F-actin. Surprisingly, only one-fourth of α-actinin dimers were bound to two actin filaments. Taken together, our results provide a quantitative characterization of essential mechanisms under­lying actin cortex homeostasis.

scholarly journals Метод количественного описания фиксированных гистологических образцов с помощью цифровой голографической микроскопии

2021 ◽  
Vol 47 (9) ◽  
pp. 18
Author(s):  
А.В. Белашов ◽  
А.А. Жихорева
Keyword(s):  
Quantitative Data ◽  
Digital Holographic Microscopy ◽  
Quantitative Characterization ◽  
Elastic Cartilage ◽  
Different Types ◽  
Phase Images ◽  
Automated Processing ◽  
Novel Method ◽  
Holographic Microscopy

A novel method for the quantitative characterization of fixed histological samples based on the statistical analysis of their phase images obtained using digital holographic microscopy is developed and presented. The proposed approach allows for fully automated processing of reconstructed phase images and obtaining quantitative data of morphological and optical characteristics of histological tissues structures. The method was validated on three histological samples of different types of tissues: ciliated columnar epithelium, elastic cartilage, and liver.

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