Matlab version r2009a

Manufactured by MathWorks

Sourced in United States

MATLAB R2009a is a numerical computing environment and programming language. It provides a platform for algorithm development, data visualization, and numerical computation. The software can be used for a wide range of applications, including signal processing, image analysis, and control system design. MATLAB R2009a includes a suite of mathematical, engineering, and scientific functions that can be used to solve complex problems.

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Lab products found in correlation

Simca p 11, by Sartorius (1 mentions) Sieve 2, by Thermo Fisher Scientific (1 mentions) Xcalibur 2.1 workstation, by Thermo Fisher Scientific (1 mentions) Pmod version 3, by PMOD Technologies (1 mentions) Paravision version 5, by Bruker (1 mentions) Avance 2, by Bruker (1 mentions)

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MATLAB (20315 citations) MATLAB R2009a (32 citations)

3 protocols using matlab version r2009a

Quantifying Liquid Phase Content in Samples

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The liquid phase (referred to water and lipid molecules) content, X, was determined by analyzing the Free Induction Decay (FID) signal after 90° RF pulses of 2.9 μs. The measurement was repeated 160 times with a relaxation delay of 1 s (RD) between two following scans, in order to assure complete relaxation of the FID signal. RD was determined using the following relation (1):
The interpolation of the experimental curves of the FID was achieved through a non-linear based fitting on the least squares method using the Marquardt algorithm, implemented in SigmaPlot scientific software (version 9, Systat Software Inc., San Jose, CA, USA).
The FID due to the protein and water protons network and water and lipid protons envelope was analyzed by applying two relaxation processes: a Gaussian-type relaxation process related to ‘solid’ polymer protons and a Lorentzian relaxation process related to ‘liquid phase’ protons according to the expfit algorithm [38 (link)] carried out in MatLab version R2009a (The Mathworks Inc., Natick, MA, USA).

Gianferri R., Sciubba F., Durazzo A., Gabrielli P., Lombardi-Boccia G., Giorgi F., Santini A., Engel P., Di Cocco M.E., Delfini M, & Lucarini M. (2023). Time Domain NMR Approach in the Chemical and Physical Characterization of Hazelnuts (Corylus avellana L.). Foods, 12(10), 1950.

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Multivariate Analysis of UHPLC-MS Data

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All of the data were subjected to principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to interpret the interrelationships between the samples. With respect to PLS-DA, samples were divided into a calibration set for modeling and a validation set for the established model evaluation. The prediction set consisted of samples that were not used for the calibration set.
The very high quantities of acquired UHPLC-LTQ-Orbitrap MS raw data were processed with an Xcalibur 2.1 workstation (Thermo Scientific, Germany). The normalization was accomplished using Sieve 2.1 software (Thermo Scientific, USA), which was specifically used to perform background subtraction, component detection and peak alignment. SIMCA-P+ 11.5 (Umetrics, Sweden) and Unscrambler 7.0 (CAMO, Norway) software were utilized to carry out the spectral pre-processing. PCA and PLS were conducted using Matlab version R2009a (The MathWorks, Inc., USA) with Statistical Toolbox and in-house functions. The iToolbox utilized to run synergy interval partial least squares (siPLS) analysis algorithms was downloaded from http://www.models.kvl.dk/ for the NIR wavelength selection.

Shengyun D., Yuqi W., Fei W., Xiaodan M, & Jiayu Z. (2019). A proposed protocol based on integrative metabonomics analysis for the rapid detection and mechanistic understanding of sulfur fumigation of Chinese herbal medicines. RSC Advances, 9(53), 31150-31161.

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In vivo and ex vivo MR imaging protocol

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In vivo MR imaging scans were performed using a horizontalbore, 7 T small-animal MR tomograph with a maximum gradient strength of 290 mT/m (ClinScan; Bruker BioSpin MR imaging). T 2weighted images (referred to as tse3DT 2 in the following sections) were used for PET image fusion and region-of-interest definitions using PMOD, version 3.2, image view and fusion tools (PMOD Technologies). Sequence details for all MR imaging sequences are detailed in the Supplemental Methods. rCBF measurements were conducted with single-slice pulsed ASL using a flow-sensitive alternating inversion recovery true fast imaging with steady-state precession approach (21) . ASL MR imaging data were analyzed using a simplified version of the Bloch equation (Supplemental Methods) and Matlab, version R2009a (The MathWorks), with an in-house-programmed routine.
Ex vivo microscopic MR imaging scans were performed at the Centre for Advanced Imaging, Brisbane, Australia, on a vertical-bore smallanimal MR scanner operating at 16.4 T (Avance II; Bruker BioSpin) using a Micro 2.5 gradient system, a 15 mm SAW volume coil, and ParaVision, version 5.1. T 2 *-weighted (referred to as highres-3DT 2 *) images at high resolution were used for MR imaging-based amyloid plaque quantification.

Maier F.C., Keller M.D., Bukala D., Bender B., Mannheim J.G., Brereton I.M., Galloway G.J, & Pichler B.J. (2015). Quantification of β-Amyloidosis and rCBF with Dedicated PET, 7 T MR Imaging, and High-Resolution Microscopic MR Imaging at 16.4 T in APP23 Mice. Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 56(10).

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