Noise reduction of fast, repetitive GC/MS measurements using principal component analysis (PCA)

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Noise reduction of fast, repetitive GC/MS measurements using principal component analysis (PCA)"

Transcription

1 Analytica Chimica Acta 401 (1999) Noise reduction of fast, repetitive GC/MS measurements using principal component analysis (PCA) M. Statheropoulos a,, A. Pappa a, P. Karamertzanis a, H.L.C. Meuzelaar b a Department of Chemical Engineering, Sector 1, National Technical University of Athens (NTUA), 9 Iroon Polytechniou Street, , Athens, Greece b Center for Micro Analysis and Reaction Chemistry, University of Utah, Salt Lake City, USA Received 9 March 1999; received in revised form 3 June 1999; accepted 9 June 1999 Abstract Principal component analysis (PCA) was applied to the noise reduction of low ppb level benzene, toluene, ethyl benzene, xylene (BTEX) type gas chromatography/mass spectrometry (GC/MS) measurements (i.e. BTEX) with a fast, repetitive GC/MS system. The first three principal components (PCs) accounting for approximately 60 80% of the total variance in the original data could be attributed to chemical components, whilst the remaining PCs were found to be due to noise. Reconstruction of the data from the first three PCs resulted in noise reduction with improved signal fidelity. The results of PCA were comparable with those achieved by a Fourier transform method Elsevier Science B.V. All rights reserved. Keywords: Noise reduction; Principal component analysis (PCA); Roving gas chromatography/mass spectrometry (GC/MS) 1. Introduction A roving gas chromatography/mass spectrometry (GC/MS) system, using a zero-emission electric vehicle and equipped with a differential GPC has been used for monitoring and mapping low ppb concentration level benzene, toluene, ethyl benzene, xylene (BTEX) type VOCs in the direct neighborhood of a gas station [1 3]. Concentrations of VOCs in ambient air are usually very low, and in some cases, can be masked by various sources of noise. Thus, the evaluation of low intensity Corresponding author. Tel.: ; fax: address: (M. Statheropoulos) signals can be greatly facilitated by subtraction of the noise. Noise reduction can be achieved by various smoothing or filtering techniques. A number of reduction techniques are known, such as the Gaussian filtering, the Savitzky Golay filter, polynomial filter and the Fourier transforms methods [4 6]. Lee et al. [7] evaluated Principal component analysis (PCA) as a digital filter to improve the overall quality of GC/MS data on a test mixture of low molecular weight solvents. A marked increase in the signal-to-noise ratio (i.e. by a factor of from 2 to 100) was achieved. The study of the effectiveness of PCA in the noise reduction of low level outdoors BTEX measurements by fast, repetitive GC/MS was the primary target of the present work. PCA examines the degree of correlation between variables, while noise is presumed to control /99/$ see front matter 1999 Elsevier Science B.V. All rights reserved. PII: S (99)

2 36 M. Statheropoulos et al. / Analytica Chimica Acta 401 (1999) random, i.e. non-correlated, signal fluctuations. PCA is used to determine the underlying intrinsic dimensionality of the data. On removing the least significant PCs attributed to the noise and reconstructing the original data set, one expects reduced noise. The results of PCA on noise reduction are compared to those of a fast Fourier transform (FFT) method. It should be mentioned that there are ambiguities in the literature about the definition of noise and as to how it is measured. These ambiguities can be critical when the S/N ratio has to be determined [8]. Our noise estimations were based on N peak-to-peak. 2. Theoretical Multivariate data analysis (MDA) is an established set of techniques for examining the relationships among multiple variables [9]. The term multiple refers to many variables and/or linear combinations of variables. PCA is an MDA technique, which is used whenever it is necessary to form new variables which are linear combinations of the original variables. These components are orthogonal (i.e. not correlated) to each other. The new variables that are formed are referred to as Principal components (PCs). The PCs are extracted so that the first PC accounts for the maximum variance of the data. The second PC accounts for the maximum of the residual variance and so on. Generally, only a handful of PCs is needed to account for the maximum of the variance of the original data set, and for this reason, PCA is generally known as a data reduction technique. In PCA, the square dispersion matrix V is given as follows: V = [ 1 c 1 ] D T D where D is the original or modified data set with size c n, (objects variables). Well-behaved dispersion matrices can often be produced by pretreatment of the original data. Frequently used known pretreatments include mean centering and standardization. For the square matrix V, the eigenvalues and eigenvectors are calculated. The results of PCA are given as the matrices S (scores matrix) and L (loadings matrix). The S matrix is a c f matrix (objects PCs), where f is the number of the first significant PCs and L is an f n matrix (PCs variables). By post multiplying S with L, the mean centered data matrix R is calculated: R = SL R is a c n matrix. To obtain the complete reconstructed matrix of the original data, D rec, the pretreatment of the data, has to be taken into account. Noise reduction is based on reconstruction of the data using a limited number of PCs, which accounts for the maximum variance of the original data and can be attributed to components other than the white noise chemical components. On the other hand, by using only those PCs that are attributed to noise, the noise matrix N is constructed. 3. Experimental 3.1. Roving GC/MS system The fast mobile (roving) GC/MS system used [2] has an Enviroprobe (Femtoscan Corporation type) inlet system and a Hewlett-Packard MSD type mass analyzer. Single ion monitoring (SIM) was used for recording the mass peaks at m/z 78 (benzene), 91 (toluene) and 106 (xylene or ethyl benzene). The pulsed air sampling duration of the Enviroprobe inlet was 400 ms, and the sampling frequency was one sample per 15 s PCA Twenty four repetitive measurements (sampling points) consisting of 74 scans, each with a sampling frequency of 15 s (that corresponds to 1776 scans over a time period of 6 min) for the mass peaks at m/z 78, 91 and 106, were used as raw data. The size of the raw data matrix D was 24 74: 24 objects (SIM profile corresponds to 24 sampling points) and 74 variables (measurement points within each SIM profile). Three such matrices (D) were produced for each mass peak recorded. Two-dimensional contour plots (pseudo-3d plots) were constructed for the mass peaks at m/z 78, 91 and 106 in order to better visualize the measurements data. The X-axis represents the number of scans during the

3 M. Statheropoulos et al. / Analytica Chimica Acta 401 (1999) Fig. 1. Contour plots of raw data for mass peaks at m/z 78 (a), 91 (b) and 106 (c). A stripe can be attributed to air peak, B to benzene, C to toluene and D to isomers of xylene and/or ethyl benzene.

4 38 M. Statheropoulos et al. / Analytica Chimica Acta 401 (1999) Fig. 2. Reconstructed contour plots and the subtracted noise plot obtained through PCA for mass peaks at m/z 78 (a), 91 (b) and 106 (c). A stripe can be attributed to air peak, B to benzene, C to toluene and D to isomers of xylene and/or ethyl benzene.

5 M. Statheropoulos et al. / Analytica Chimica Acta 401 (1999) Fig. 3. Ninth and 14th SIM profiles after reconstruction by PCA for mass peak signals at m/z 78 (a), 91 (b) and 106 (c). Less intense line corresponds to the raw data. chromatographic analysis time (15 s) of each measurement, the Y-axis the SIM profile number, and the third dimension was a gray scale related to the intensity of the respective signals (abundance in arbitrary units). The pretreatment method of mean centering was used for running the PCA analysis, using PONTOS, an in-house developed multivariate data analysis software package for spectroscopic data [10].

6 40 M. Statheropoulos et al. / Analytica Chimica Acta 401 (1999) Fig. 4. Frequency spectrum obtained by FFT for the mass peak signals at m/z 78. The first value is not included FFT analysis In FFT analysis, a conversion of the signal from the time domain to the frequency domain occurs. Consequently, the entire data set of roving GC/MS measurements results in a vector for each mass peak. Under Fourier transformation [11], this produces 1776 different magnitude coefficients ( frequency spectrum ). By rejecting the frequencies related to noise, increased signal-to-noise ratios are obtained, resulting in a smoother spectrum. MATLAB software, version 4.2 of Mathworks, was used for the Fourier transform. 4. Results and discussion In Fig. 1, the contour plots of the mass peaks at m/z 78 (a), 91 (b) and 106 (c) are presented. Furthermore, in Fig. 1a, two dark colour stripes (A and B) appear at 1.5 s (scan 9) and 3 s (scan 15), respectively, whereas in Fig. 1b, two dark colour stripes (A and C) are clearly present at 1.5 s (scan 9) and 5.5 s (scan 27), respectively. In addition, a less intense colour stripe (D) is present at 10.5 s (scan 50). It seems that the less intense stripe presented at 10.5 s in Fig. 1c can be attributed to D. By close examination of the mass spectra of the individual compounds in Fig. 1a c, stripes B, C and D can be attributed to benzene, toluene and the various isomers of xylene and/or ethyl benzene, respectively. Finally, the dark colour stripe (A) at 1.5 s present in all Fig. 1a c can be attributed to the air peak. It should be mentioned that the level of noise expressed as light colours is considered significant. This becomes especially important in the case of stripe D (xylene isomers or ethyl benzene, low S/N ratio) PCA results PCA resulted in 24 PCs. Using the screen plot criterion [12], three PCs were selected for describing the dimensionality of data. The first three PCs accounted for 59% (m/z 78), 70% (m/z 91) and 76% (m/z 106) of the total variance, respectively. In Fig. 2, the contour plots of reconstructed data using the first three PCs, as well as the extracted noise of mass peaks at m/z 78 (a), 91 (b) and 106 (c) are presented. It should be noted that the same pattern for noise is produced when (a) either the data are reconstructed using the least significant PCs (PC 4 PC 24 )or when (b) the reconstructed matrix D rec (reconstructed through the first three PCs) is subtracted from the original data matrix D. This provides a useful check of the mathematical procedures used. It appears that, by this method, a significant amount of noise is subtracted, whilst the fidelity of the signal is retained. This is shown in Fig. 3, which presents the reconstructed plots by PCA of the ninth (object 9) and 14th (object 14) SIM profiles (mass peak at m/z 78 Fig. 3a, m/z 91 Fig. 3b and m/z 106

7 M. Statheropoulos et al. / Analytica Chimica Acta 401 (1999) Fig. 5. Reconstructed contour plot and subtracted noise through FFT for the mass peak signals at m/z 78. Fig. 3c). An average increase in the S/N ratio (by 130%) was observed for all the data. In addition, stripe D is more clearly shown in the reconstructed plots. Finally, a remarkable volume data reduction is obtained by PCA. For the reconstruction of the initial data after PCA, the scores matrix S (24 3) and the loading matrix L (3 74) are necessary. That corresponds to (24 3) + (74 3)=98 3 values, whereas the initial data volume is values. Taking into account that the data are mean centering, the reconstructed matrix R = SL must be corrected by adding the mean of each column of the original data D to the R matrix, resulting in the final reconstructed matrix

8 42 M. Statheropoulos et al. / Analytica Chimica Acta 401 (1999) Fig. 6. Ninth SIM profile of mass peak signals at m/z 78 for raw data and after noise reduction by PCA and FFT. D rec. Thus, 74 more values (the number of columns of matrix D) are needed. Therefore, the % reduction data volume achieved by PCA is [ ] (24 74) (98 3) = 80% FFT results Fig. 4 presents the magnitudes of the frequencies of the data for mass peak at m/z 78 (frequency spectrum), resulting from FFT. A periodicity of 24 is obvious, as well as the expected symmetry around the central frequency of 889. Thus, peaks appear at 24-base frequencies i.e. 24, 48, 72. This is due to the signal formation, which has a periodicity 1776/24 = 74, in agreement with the roving GC/MS measurements. Assuming that the noise is completely random (white noise with a flat spectrum), retention of only the frequencies 24K, 24+/ 1, 24+/ 2 (Fig. 5) can bring about signal reconstruction. For comparison, the results of noise reduction using both techniques on the ninth SIM profile of the mass peak at m/z 78 are presented in Fig. 6. In conclusion, it seems that both techniques are capable of subtracting comparable amounts of noise while retaining and enhancing the signal profile. Nonetheless, PCA seems to give slightly better results with regard to overall spectrum quality after noise reduction. It should be emphasized that PCA subtracts random peaks that are not correlated (white noise), while the FFT used cannot subtracts the types of noise that have the same frequency of signals. 5. Conclusions PCA has proved to be an efficient tool for the noise reduction of roving CG/MS measurements. PCA extracts the white noise and increases the S/N ratio (an average increase by 130%). Besides, PCA has a remarkable capability of achieving a high degree of data compression (80%), which is important when data transfer by telemetry is needed. PCA results were comparable to those of an FFT method used in this work. References [1] A. Pappa, M. Statheropoulos, D. Theodossiou, H.L.C. Meuzelaar, Mathematical filtering of noise on roving GC/MS measurements, in: Poster Presentation at Field Screening Europe, September 30 October , Karlsruhe, Germany.

9 M. Statheropoulos et al. / Analytica Chimica Acta 401 (1999) [2] W. McClennen, C. Vaughn, P. Cole, S.A. Sheya, D. Wager, H.L.C. Meuzelaar, N.S. Arnold, Roving CG/MS: mapping gradients in time and space, in: Proceedings of the Specialist Workshop On Field-Portable Chromatography and Spectrometry, June 3 5, 1996, Snowbird, Utah. [3] S. Arnold, W.H. McClennen, H.L.C. Meuzelaar, Anal. Chem. 63 (1991) 299. [4] X.Y. Sun, H. Singh, B. Millier, C.H. Warren, W.A. Aue, J. Chromatogr. A 687 (1994) [5] B. Barak, Anal. Chem. 67 (1995) [6] R.E. Synovec, E.S. Yeung, Anal. Chem. 58 (1986) [7] T.A. Lee, L.M. Headley, J.K. Hardy, Anal. Chem. 63 (1991) 357. [8] P. Foley, J.G. Dorsey, Chromatographia 18 (1984) 503. [9] J.F. Hair, R.E. Anderson, R.L. Tatham, Multivariate Data Analysis, 2nd ed., Macmillan, New York, [10] M. Statheropoulos, H.L.C. Meuzelaar, N. Vassiliadis, Multivariate Data Analysis Techniques for Spectroscopic Data: the PONTOS Case, (software ver. 1.2 and manual), Center for Microanalysis and Reaction Chemistry, The University of Utah, [11] J.G. Proakis, D.G. Manolakis, Introduction to Digital Signal Processing, MacMillan, New York, [12] I.T. Jolliffe, Principal Component Analysis, Springer, New York, 1986.

Alignment and Preprocessing for Data Analysis

Alignment and Preprocessing for Data Analysis Alignment and Preprocessing for Data Analysis Preprocessing tools for chromatography Basics of alignment GC FID (D) data and issues PCA F Ratios GC MS (D) data and issues PCA F Ratios PARAFAC Piecewise

More information

AppNote 6/2003. Analysis of Flavors using a Mass Spectral Based Chemical Sensor KEYWORDS ABSTRACT

AppNote 6/2003. Analysis of Flavors using a Mass Spectral Based Chemical Sensor KEYWORDS ABSTRACT AppNote 6/2003 Analysis of Flavors using a Mass Spectral Based Chemical Sensor Vanessa R. Kinton Gerstel, Inc., 701 Digital Drive, Suite J, Linthicum, MD 21090, USA Kevin L. Goodner USDA, Citrus & Subtropical

More information

The Determination of Low Levels of Benzene, Toluene, Ethylbenzene, Xylenes and Styrene in Olive Oil Using a Turbomatrix HS and a Clarus SQ 8 GC/MS

The Determination of Low Levels of Benzene, Toluene, Ethylbenzene, Xylenes and Styrene in Olive Oil Using a Turbomatrix HS and a Clarus SQ 8 GC/MS application Note Gas Chromatography/ Mass Spectrometry Author A. Tipler, Senior Scientist PerkinElmer, Inc. Shelton, CT 06484 USA The Determination of Low Levels of Benzene, Toluene, Ethylbenzene, Xylenes

More information

Signal, Noise, and Detection Limits in Mass Spectrometry

Signal, Noise, and Detection Limits in Mass Spectrometry Signal, Noise, and Detection Limits in Mass Spectrometry Technical Note Chemical Analysis Group Authors Greg Wells, Harry Prest, and Charles William Russ IV, Agilent Technologies, Inc. 2850 Centerville

More information

# LCMS-35 esquire series. Application of LC/APCI Ion Trap Tandem Mass Spectrometry for the Multiresidue Analysis of Pesticides in Water

# LCMS-35 esquire series. Application of LC/APCI Ion Trap Tandem Mass Spectrometry for the Multiresidue Analysis of Pesticides in Water Application Notes # LCMS-35 esquire series Application of LC/APCI Ion Trap Tandem Mass Spectrometry for the Multiresidue Analysis of Pesticides in Water An LC-APCI-MS/MS method using an ion trap system

More information

Pesticide Analysis by Mass Spectrometry

Pesticide Analysis by Mass Spectrometry Pesticide Analysis by Mass Spectrometry Purpose: The purpose of this assignment is to introduce concepts of mass spectrometry (MS) as they pertain to the qualitative and quantitative analysis of organochlorine

More information

AMD Analysis & Technology AG

AMD Analysis & Technology AG AMD Analysis & Technology AG Application Note 120419 Author: Karl-Heinz Maurer APCI-MS Trace Analysis of volatile organic compounds in ambient air A) Introduction Trace analysis of volatile organic compounds

More information

Review Jeopardy. Blue vs. Orange. Review Jeopardy

Review Jeopardy. Blue vs. Orange. Review Jeopardy Review Jeopardy Blue vs. Orange Review Jeopardy Jeopardy Round Lectures 0-3 Jeopardy Round $200 How could I measure how far apart (i.e. how different) two observations, y 1 and y 2, are from each other?

More information

The First Quantitative Analysis of Alkylated PAH and PASH by GCxGC/MS and its Implications on Weathering Studies

The First Quantitative Analysis of Alkylated PAH and PASH by GCxGC/MS and its Implications on Weathering Studies The First Quantitative Analysis of Alkylated PAH and PASH by GCxGC/MS and its Implications on Weathering Studies INEF Penn State Conference 2013 Albert Robbat, Jr. and Patrick Antle Tufts University, Chemistry

More information

Convolution. 1D Formula: 2D Formula: Example on the web: http://www.jhu.edu/~signals/convolve/

Convolution. 1D Formula: 2D Formula: Example on the web: http://www.jhu.edu/~signals/convolve/ Basic Filters (7) Convolution/correlation/Linear filtering Gaussian filters Smoothing and noise reduction First derivatives of Gaussian Second derivative of Gaussian: Laplacian Oriented Gaussian filters

More information

Chemistry 321, Experiment 8: Quantitation of caffeine from a beverage using gas chromatography

Chemistry 321, Experiment 8: Quantitation of caffeine from a beverage using gas chromatography Chemistry 321, Experiment 8: Quantitation of caffeine from a beverage using gas chromatography INTRODUCTION The analysis of soft drinks for caffeine was able to be performed using UV-Vis. The complex sample

More information

Expectations for GC-MS Lab

Expectations for GC-MS Lab Expectations for GC-MS Lab Since this is the first year for GC-MS to be used in Dr. Lamp s CHEM 322, the lab experiment is somewhat unstructured. As you move through the two weeks, I expect that you will

More information

Quantitative & Qualitative HPLC

Quantitative & Qualitative HPLC Quantitative & Qualitative HPLC i Wherever you see this symbol, it is important to access the on-line course as there is interactive material that cannot be fully shown in this reference manual. Contents

More information

Signal to Noise Instrumental Excel Assignment

Signal to Noise Instrumental Excel Assignment Signal to Noise Instrumental Excel Assignment Instrumental methods, as all techniques involved in physical measurements, are limited by both the precision and accuracy. The precision and accuracy of a

More information

Enhancing GCMS analysis of trace compounds using a new dynamic baseline compensation algorithm to reduce background interference

Enhancing GCMS analysis of trace compounds using a new dynamic baseline compensation algorithm to reduce background interference Enhancing GCMS analysis of trace compounds using a new dynamic baseline compensation algorithm to reduce background interference Abstract The advantages of mass spectrometry (MS) in combination with gas

More information

Application Note FTMS-55 Laser/Desorption Ionization FT-ICR Mass Spectrometry as a Tool for Statistical Analysis of Crude Oils

Application Note FTMS-55 Laser/Desorption Ionization FT-ICR Mass Spectrometry as a Tool for Statistical Analysis of Crude Oils Application Note FTMS-55 Laser/Desorption Ionization FT-ICR Mass Spectrometry as a Tool for Statistical Analysis of Crude Oils Introduction Crude oil is an extremely complex mixture of hydrocarbons and

More information

Background Information

Background Information 1 Gas Chromatography/Mass Spectroscopy (GC/MS/MS) Background Information Instructions for the Operation of the Varian CP-3800 Gas Chromatograph/ Varian Saturn 2200 GC/MS/MS See the Cary Eclipse Software

More information

Integrated Data Mining Strategy for Effective Metabolomic Data Analysis

Integrated Data Mining Strategy for Effective Metabolomic Data Analysis The First International Symposium on Optimization and Systems Biology (OSB 07) Beijing, China, August 8 10, 2007 Copyright 2007 ORSC & APORC pp. 45 51 Integrated Data Mining Strategy for Effective Metabolomic

More information

EEG COHERENCE AND PHASE DELAYS: COMPARISONS BETWEEN SINGLE REFERENCE, AVERAGE REFERENCE AND CURRENT SOURCE DENSITY

EEG COHERENCE AND PHASE DELAYS: COMPARISONS BETWEEN SINGLE REFERENCE, AVERAGE REFERENCE AND CURRENT SOURCE DENSITY Version 1, June 13, 2004 Rough Draft form We apologize while we prepare the manuscript for publication but the data are valid and the conclusions are fundamental EEG COHERENCE AND PHASE DELAYS: COMPARISONS

More information

Chemical Analysis of Chardonnay Wines: Identification and Analysis of Important Aroma Compounds

Chemical Analysis of Chardonnay Wines: Identification and Analysis of Important Aroma Compounds Chemical Analysis of Chardonnay Wines: Identification and Analysis of Important Aroma Compounds ABSTRACT Chardonnay wines from leading world producers were selected for analysis and comparison of volatile

More information

MarkerView Software 1.2.1 for Metabolomic and Biomarker Profiling Analysis

MarkerView Software 1.2.1 for Metabolomic and Biomarker Profiling Analysis MarkerView Software 1.2.1 for Metabolomic and Biomarker Profiling Analysis Overview MarkerView software is a novel program designed for metabolomics applications and biomarker profiling workflows 1. Using

More information

Detailed simulation of mass spectra for quadrupole mass spectrometer systems

Detailed simulation of mass spectra for quadrupole mass spectrometer systems Detailed simulation of mass spectra for quadrupole mass spectrometer systems J. R. Gibson, a) S. Taylor, and J. H. Leck Department of Electrical Engineering and Electronics, The University of Liverpool,

More information

Component Ordering in Independent Component Analysis Based on Data Power

Component Ordering in Independent Component Analysis Based on Data Power Component Ordering in Independent Component Analysis Based on Data Power Anne Hendrikse Raymond Veldhuis University of Twente University of Twente Fac. EEMCS, Signals and Systems Group Fac. EEMCS, Signals

More information

EM Clustering Approach for Multi-Dimensional Analysis of Big Data Set

EM Clustering Approach for Multi-Dimensional Analysis of Big Data Set EM Clustering Approach for Multi-Dimensional Analysis of Big Data Set Amhmed A. Bhih School of Electrical and Electronic Engineering Princy Johnson School of Electrical and Electronic Engineering Martin

More information

Simulation of high- and low-resolution mass spectra for assessment of calibration methods

Simulation of high- and low-resolution mass spectra for assessment of calibration methods RAPID COMMUNICATIONS IN MASS SPECTROMETRY Rapid Commun. Mass Spectrom. 27; 21: 35 313 Published online in Wiley InterScience (www.interscience.wiley.com).2846 Simulation of high- and low-resolution mass

More information

Overview. Triple quadrupole (MS/MS) systems provide in comparison to single quadrupole (MS) systems: Introduction

Overview. Triple quadrupole (MS/MS) systems provide in comparison to single quadrupole (MS) systems: Introduction Advantages of Using Triple Quadrupole over Single Quadrupole Mass Spectrometry to Quantify and Identify the Presence of Pesticides in Water and Soil Samples André Schreiber AB SCIEX Concord, Ontario (Canada)

More information

HIGH RESOLUTION MOBILITY SPECTROMETER A NEW FIELD ANALYTICAL TECHNIQUE

HIGH RESOLUTION MOBILITY SPECTROMETER A NEW FIELD ANALYTICAL TECHNIQUE Aerosol Instrumentation HIGH RESOLUTION MOBILITY SPECTROMETER A NEW FIELD ANALYTICAL TECHNIQUE Ion Mobility Spectrometry (IMS) is an emerging technique in field analysis. IONER has developed a new concept

More information

Daniel M. Mueller, Katharina M. Rentsch Institut für Klinische Chemie, Universitätsspital Zürich, CH-8091 Zürich, Schweiz

Daniel M. Mueller, Katharina M. Rentsch Institut für Klinische Chemie, Universitätsspital Zürich, CH-8091 Zürich, Schweiz Toxichem Krimtech 211;78(Special Issue):324 Online extraction LC-MS n method for the detection of drugs in urine, serum and heparinized plasma Daniel M. Mueller, Katharina M. Rentsch Institut für Klinische

More information

Setting up a Quantitative Analysis MS ChemStation

Setting up a Quantitative Analysis MS ChemStation Setting up a Quantitative Analysis MS ChemStation Getting Ready 1. Use the tutorial section "Quant Reports" on the MSD Reference Collection CD-ROM that came with your ChemStation software. 2. Know what

More information

Principal Component Analysis

Principal Component Analysis Principal Component Analysis ERS70D George Fernandez INTRODUCTION Analysis of multivariate data plays a key role in data analysis. Multivariate data consists of many different attributes or variables recorded

More information

Identification of unknown organic compounds based on comparison of electron ionization mass spectra

Identification of unknown organic compounds based on comparison of electron ionization mass spectra Identification of unknown organic compounds based on comparison of electron ionization mass spectra Andrey S. Samokhin Igor A. Revelsky Chemistry Department Lomonosov Moscow State University Identification

More information

Analysing chromatographic data using data mining to monitor petroleum content in water

Analysing chromatographic data using data mining to monitor petroleum content in water Analysing chromatographic data using data mining to monitor petroleum content in water Geoffrey Holmes, Dale Fletcher, Peter Reutemann and Eibe Frank Computer Science Department, University of Waikato,

More information

Detection of Adulterant Seed Oils in Extra Virgin Olive Oils by LC-MS and Principal Components Analysis

Detection of Adulterant Seed Oils in Extra Virgin Olive Oils by LC-MS and Principal Components Analysis Detection of Adulterant Seed Oils in Extra Virgin Olive Oils by LC-MS and Principal Components Analysis Nadia Pace AB SCIEX Concord, Ontario (Canada) Overview Various oils were analyzed using LC-MS/MS

More information

Comparison of BTEXS in Olive Oils by Static and Dynamic HT3 Headspace

Comparison of BTEXS in Olive Oils by Static and Dynamic HT3 Headspace Comparison of BTEXS in Olive Oils by Static and Dynamic HT3 Headspace Application Note Abstract The health benefits of consumption of olive oils as part of a healthy diet reaches back to the mid 1950 s.

More information

Mehtap Ergüven Abstract of Ph.D. Dissertation for the degree of PhD of Engineering in Informatics

Mehtap Ergüven Abstract of Ph.D. Dissertation for the degree of PhD of Engineering in Informatics INTERNATIONAL BLACK SEA UNIVERSITY COMPUTER TECHNOLOGIES AND ENGINEERING FACULTY ELABORATION OF AN ALGORITHM OF DETECTING TESTS DIMENSIONALITY Mehtap Ergüven Abstract of Ph.D. Dissertation for the degree

More information

Analysis of Organophosphorus Pesticides in Milk Using SPME and GC-MS/MS. No. GCMS-1603. No. SSI-GCMS-1603. Shilpi Chopra, Ph.D.

Analysis of Organophosphorus Pesticides in Milk Using SPME and GC-MS/MS. No. GCMS-1603. No. SSI-GCMS-1603. Shilpi Chopra, Ph.D. Gas Chromatograph Mass Spectrometer No. GCMS-1603 Analysis of Organophosphorus Pesticides in Milk Using SPME and GC-MS/MS Shilpi Chopra, Ph.D. Introduction Organophosphorus (OP) pesticides are a class

More information

Nonlinear Iterative Partial Least Squares Method

Nonlinear Iterative Partial Least Squares Method Numerical Methods for Determining Principal Component Analysis Abstract Factors Béchu, S., Richard-Plouet, M., Fernandez, V., Walton, J., and Fairley, N. (2016) Developments in numerical treatments for

More information

Monitoring Volatile Organic Compounds in Beer Production Using the Clarus SQ 8 GC/MS and TurboMatrix Headspace Trap Systems

Monitoring Volatile Organic Compounds in Beer Production Using the Clarus SQ 8 GC/MS and TurboMatrix Headspace Trap Systems application Note Gas Chromatography/ Mass Spectrometry Authors Lee Marotta Sr. Field Application Scientist Andrew Tipler Senior Scientist PerkinElmer, Inc. Shelton, CT 06484 USA Monitoring Volatile Organic

More information

Software Approaches for Structure Information Acquisition and Training of Chemistry Students

Software Approaches for Structure Information Acquisition and Training of Chemistry Students Software Approaches for Structure Information Acquisition and Training of Chemistry Students Nikolay T. Kochev, Plamen N. Penchev, Atanas T. Terziyski, George N. Andreev Department of Analytical Chemistry,

More information

Determination of N-cyclohexyl-diazeniumdioxide (HDO) containing compounds in treated wood using GC-MS

Determination of N-cyclohexyl-diazeniumdioxide (HDO) containing compounds in treated wood using GC-MS Application Note No. 051 Determination of N-cyclohexyl-diazeniumdioxide (HDO) containing compounds in treated wood using GC-MS by P Jüngel ¹), J Wittenzellner ²) and E Melcher ¹) ¹) Federal Research Centre

More information

The Unshifted Atom-A Simpler Method of Deriving Vibrational Modes of Molecular Symmetries

The Unshifted Atom-A Simpler Method of Deriving Vibrational Modes of Molecular Symmetries Est. 1984 ORIENTAL JOURNAL OF CHEMISTRY An International Open Free Access, Peer Reviewed Research Journal www.orientjchem.org ISSN: 0970-020 X CODEN: OJCHEG 2012, Vol. 28, No. (1): Pg. 189-202 The Unshifted

More information

Introduction to Principal Components and FactorAnalysis

Introduction to Principal Components and FactorAnalysis Introduction to Principal Components and FactorAnalysis Multivariate Analysis often starts out with data involving a substantial number of correlated variables. Principal Component Analysis (PCA) is a

More information

Principal Component Analysis Application to images

Principal Component Analysis Application to images Principal Component Analysis Application to images Václav Hlaváč Czech Technical University in Prague Faculty of Electrical Engineering, Department of Cybernetics Center for Machine Perception http://cmp.felk.cvut.cz/

More information

1. The standardised parameters are given below. Remember to use the population rather than sample standard deviation.

1. The standardised parameters are given below. Remember to use the population rather than sample standard deviation. Kapitel 5 5.1. 1. The standardised parameters are given below. Remember to use the population rather than sample standard deviation. The graph of cross-validated error versus component number is presented

More information

Face Recognition using Principle Component Analysis

Face Recognition using Principle Component Analysis Face Recognition using Principle Component Analysis Kyungnam Kim Department of Computer Science University of Maryland, College Park MD 20742, USA Summary This is the summary of the basic idea about PCA

More information

Suggested solutions for Chapter 3

Suggested solutions for Chapter 3 s for Chapter PRBLEM Assuming that the molecular ion is the base peak (00% abundance) what peaks would appear in the mass spectrum of each of these molecules: (a) C5Br (b) C60 (c) C64Br In cases (a) and

More information

VALIDATION OF ANALYTICAL PROCEDURES: TEXT AND METHODOLOGY Q2(R1)

VALIDATION OF ANALYTICAL PROCEDURES: TEXT AND METHODOLOGY Q2(R1) INTERNATIONAL CONFERENCE ON HARMONISATION OF TECHNICAL REQUIREMENTS FOR REGISTRATION OF PHARMACEUTICALS FOR HUMAN USE ICH HARMONISED TRIPARTITE GUIDELINE VALIDATION OF ANALYTICAL PROCEDURES: TEXT AND METHODOLOGY

More information

New UV curing systems for automotive applications

New UV curing systems for automotive applications Progress in Organic Coatings 40 (2000) 93 97 New UV curing systems for automotive applications K. Maag a,, W. Lenhard b, Helmut Löffles b a Ciba Specialty Chemicals Inc., Schwarzwaldallee 215, CH-4002

More information

Fast Continuous Online Analysis of VOCs in Ambient Air using Agilent 5975T LTM GC/MSD and Markes TD

Fast Continuous Online Analysis of VOCs in Ambient Air using Agilent 5975T LTM GC/MSD and Markes TD Fast Continuous Online Analysis of VOCs in Ambient Air using Agilent 5975T LTM GC/MSD and Markes TD Application Note Environmental Author Xiaohua Li Agilent Technologies (Shanghai) Co., Ltd. 412 Ying Lun

More information

Non-negative Matrix Factorization (NMF) in Semi-supervised Learning Reducing Dimension and Maintaining Meaning

Non-negative Matrix Factorization (NMF) in Semi-supervised Learning Reducing Dimension and Maintaining Meaning Non-negative Matrix Factorization (NMF) in Semi-supervised Learning Reducing Dimension and Maintaining Meaning SAMSI 10 May 2013 Outline Introduction to NMF Applications Motivations NMF as a middle step

More information

A Study on the Variability of Fresh Diesel from Service Station in Kota Bharu Using GC-MS and PCA

A Study on the Variability of Fresh Diesel from Service Station in Kota Bharu Using GC-MS and PCA A Study on the Variability of Fresh Diesel from Service Station in Kota Bharu Using GC-MS and PCA Muhammad Suffian Azah, Ahmad Fahmi Lim Abdullah a a Forensic Science Programme, School of Health Sciences,

More information

Automated Stellar Classification for Large Surveys with EKF and RBF Neural Networks

Automated Stellar Classification for Large Surveys with EKF and RBF Neural Networks Chin. J. Astron. Astrophys. Vol. 5 (2005), No. 2, 203 210 (http:/www.chjaa.org) Chinese Journal of Astronomy and Astrophysics Automated Stellar Classification for Large Surveys with EKF and RBF Neural

More information

Application Note # LCMS-81 Introducing New Proteomics Acquisiton Strategies with the compact Towards the Universal Proteomics Acquisition Method

Application Note # LCMS-81 Introducing New Proteomics Acquisiton Strategies with the compact Towards the Universal Proteomics Acquisition Method Application Note # LCMS-81 Introducing New Proteomics Acquisiton Strategies with the compact Towards the Universal Proteomics Acquisition Method Introduction During the last decade, the complexity of samples

More information

THREE DIMENSIONAL REPRESENTATION OF AMINO ACID CHARAC- TERISTICS

THREE DIMENSIONAL REPRESENTATION OF AMINO ACID CHARAC- TERISTICS THREE DIMENSIONAL REPRESENTATION OF AMINO ACID CHARAC- TERISTICS O.U. Sezerman 1, R. Islamaj 2, E. Alpaydin 2 1 Laborotory of Computational Biology, Sabancı University, Istanbul, Turkey. 2 Computer Engineering

More information

CROP CLASSIFICATION WITH HYPERSPECTRAL DATA OF THE HYMAP SENSOR USING DIFFERENT FEATURE EXTRACTION TECHNIQUES

CROP CLASSIFICATION WITH HYPERSPECTRAL DATA OF THE HYMAP SENSOR USING DIFFERENT FEATURE EXTRACTION TECHNIQUES Proceedings of the 2 nd Workshop of the EARSeL SIG on Land Use and Land Cover CROP CLASSIFICATION WITH HYPERSPECTRAL DATA OF THE HYMAP SENSOR USING DIFFERENT FEATURE EXTRACTION TECHNIQUES Sebastian Mader

More information

GUIDELINES ON THE USE OF MASS SPECTROMETRY (MS) FOR IDENTIFICATION, CONFIRMATION AND QUANTITATIVE DETERMINATION OF RESIDUES CAC/GL 56-2005

GUIDELINES ON THE USE OF MASS SPECTROMETRY (MS) FOR IDENTIFICATION, CONFIRMATION AND QUANTITATIVE DETERMINATION OF RESIDUES CAC/GL 56-2005 CAC/GL 56-2005 Page 1 of 6 GUIDELINES ON THE USE OF MASS SPECTROMETRY (MS) FOR IDENTIFICATION, CONFIRMATION AND QUANTITATIVE DETERMINATION OF RESIDUES CAC/GL 56-2005 CONFIRMATORY TESTS When analyses are

More information

Step-by-Step Analytical Methods Validation and Protocol in the Quality System Compliance Industry

Step-by-Step Analytical Methods Validation and Protocol in the Quality System Compliance Industry Step-by-Step Analytical Methods Validation and Protocol in the Quality System Compliance Industry BY GHULAM A. SHABIR Introduction Methods Validation: Establishing documented evidence that provides a high

More information

MUSICAL INSTRUMENT FAMILY CLASSIFICATION

MUSICAL INSTRUMENT FAMILY CLASSIFICATION MUSICAL INSTRUMENT FAMILY CLASSIFICATION Ricardo A. Garcia Media Lab, Massachusetts Institute of Technology 0 Ames Street Room E5-40, Cambridge, MA 039 USA PH: 67-53-0 FAX: 67-58-664 e-mail: rago @ media.

More information

(3)

(3) 1. Organic compounds are often identified by using more than one analytical technique. Some of these techniques were used to identify the compounds in the following reactions. C 3 H 7 Br C 3 H 8 O C 3

More information

Development of Headspace Gas Chromatography-Mass Spectrometry for Determination of Residual Monomer in Polymer Latex

Development of Headspace Gas Chromatography-Mass Spectrometry for Determination of Residual Monomer in Polymer Latex Journal of Metals, Materials and Minerals, Vol.20 No.3 pp.145-149, 2010 Development of Headspace Gas Chromatography-Mass Spectrometry for Determination of Residual Monomer in Polymer Latex Nopparat THAWEEWATTHANANON

More information

Mass Spectrometry Signal Calibration for Protein Quantitation

Mass Spectrometry Signal Calibration for Protein Quantitation Cambridge Isotope Laboratories, Inc. www.isotope.com Proteomics Mass Spectrometry Signal Calibration for Protein Quantitation Michael J. MacCoss, PhD Associate Professor of Genome Sciences University of

More information

Partial Least Squares (PLS) Regression.

Partial Least Squares (PLS) Regression. Partial Least Squares (PLS) Regression. Hervé Abdi 1 The University of Texas at Dallas Introduction Pls regression is a recent technique that generalizes and combines features from principal component

More information

Method development for analysis of formaldehyde in foodsimulant. melamine-ware by GC-MS and LC-MS/MS. Internal Technical Report

Method development for analysis of formaldehyde in foodsimulant. melamine-ware by GC-MS and LC-MS/MS. Internal Technical Report of melamine-ware by GC-MS and LC-MS/MS Page 1 of 15 Method development for analysis of formaldehyde in foodsimulant extracts of melamine-ware by GC-MS and LC-MS/MS December 2012 Contact Point: Chris Hopley

More information

Authenticity Assessment of Fruit Juices using LC-MS/MS and Metabolomic Data Processing

Authenticity Assessment of Fruit Juices using LC-MS/MS and Metabolomic Data Processing Authenticity Assessment of Fruit Juices using LC-MS/MS and Metabolomic Data Processing Lukas Vaclavik 1, Ondrej Lacina 1, André Schreiber 2, and Jana Hajslova 1 1 Institute of Chemical Technology, Prague

More information

Guidance for Industry

Guidance for Industry Guidance for Industry Q2B Validation of Analytical Procedures: Methodology November 1996 ICH Guidance for Industry Q2B Validation of Analytical Procedures: Methodology Additional copies are available from:

More information

Accurate Mass Screening Workflows for the Analysis of Novel Psychoactive Substances

Accurate Mass Screening Workflows for the Analysis of Novel Psychoactive Substances Accurate Mass Screening Workflows for the Analysis of Novel Psychoactive Substances TripleTOF 5600 + LC/MS/MS System with MasterView Software Adrian M. Taylor AB Sciex Concord, Ontario (Canada) Overview

More information

Principal Components Analysis (PCA)

Principal Components Analysis (PCA) Principal Components Analysis (PCA) Janette Walde janette.walde@uibk.ac.at Department of Statistics University of Innsbruck Outline I Introduction Idea of PCA Principle of the Method Decomposing an Association

More information

Aiping Lu. Key Laboratory of System Biology Chinese Academic Society APLV@sibs.ac.cn

Aiping Lu. Key Laboratory of System Biology Chinese Academic Society APLV@sibs.ac.cn Aiping Lu Key Laboratory of System Biology Chinese Academic Society APLV@sibs.ac.cn Proteome and Proteomics PROTEin complement expressed by genome Marc Wilkins Electrophoresis. 1995. 16(7):1090-4. proteomics

More information

Computer Vision: Filtering

Computer Vision: Filtering Computer Vision: Filtering Raquel Urtasun TTI Chicago Jan 10, 2013 Raquel Urtasun (TTI-C) Computer Vision Jan 10, 2013 1 / 82 Today s lecture... Image formation Image Filtering Raquel Urtasun (TTI-C) Computer

More information

Random Vectors and the Variance Covariance Matrix

Random Vectors and the Variance Covariance Matrix Random Vectors and the Variance Covariance Matrix Definition 1. A random vector X is a vector (X 1, X 2,..., X p ) of jointly distributed random variables. As is customary in linear algebra, we will write

More information

Discrete Fourier Series & Discrete Fourier Transform Chapter Intended Learning Outcomes

Discrete Fourier Series & Discrete Fourier Transform Chapter Intended Learning Outcomes Discrete Fourier Series & Discrete Fourier Transform Chapter Intended Learning Outcomes (i) Understanding the relationships between the transform, discrete-time Fourier transform (DTFT), discrete Fourier

More information

Analysis of Liquid Samples on the Agilent GC-MS

Analysis of Liquid Samples on the Agilent GC-MS Analysis of Liquid Samples on the Agilent GC-MS I. Sample Preparation A. Solvent selection. 1. Boiling point. Low boiling solvents (i.e. b.p. < 30 o C) may be problematic. High boiling solvents (b.p. >

More information

MATRICES AND LINEAR ALGEBRA

MATRICES AND LINEAR ALGEBRA MATRICES AND LINEAR ALGEBRA Linear Algebra Matrix manipulation is the original essence of Matlab; hence the name MATrix LABoratory. In this section we will cover the basics of linear algebra, the ways

More information

Analysis of Phthalate Esters in Children's Toys Using GC-MS

Analysis of Phthalate Esters in Children's Toys Using GC-MS C146-E152 Analysis of Phthalate Esters in Children's Toys Using GC-MS GC/MS Technical Report No.4 Yuki Sakamoto, Katsuhiro Nakagawa, Haruhiko Miyagawa Abstract As of February 29, the US Consumer Product

More information

Detecting Network Anomalies. Anant Shah

Detecting Network Anomalies. Anant Shah Detecting Network Anomalies using Traffic Modeling Anant Shah Anomaly Detection Anomalies are deviations from established behavior In most cases anomalies are indications of problems The science of extracting

More information

CHE334 Identification of an Unknown Compound By NMR/IR/MS

CHE334 Identification of an Unknown Compound By NMR/IR/MS CHE334 Identification of an Unknown Compound By NMR/IR/MS Purpose The object of this experiment is to determine the structure of an unknown compound using IR, 1 H-NMR, 13 C-NMR and Mass spectroscopy. Infrared

More information

Curve Fitting. Next: Numerical Differentiation and Integration Up: Numerical Analysis for Chemical Previous: Optimization.

Curve Fitting. Next: Numerical Differentiation and Integration Up: Numerical Analysis for Chemical Previous: Optimization. Next: Numerical Differentiation and Integration Up: Numerical Analysis for Chemical Previous: Optimization Subsections Least-Squares Regression Linear Regression General Linear Least-Squares Nonlinear

More information

Notes for STA 437/1005 Methods for Multivariate Data

Notes for STA 437/1005 Methods for Multivariate Data Notes for STA 437/1005 Methods for Multivariate Data Radford M. Neal, 26 November 2010 Random Vectors Notation: Let X be a random vector with p elements, so that X = [X 1,..., X p ], where denotes transpose.

More information

Using the Singular Value Decomposition

Using the Singular Value Decomposition Using the Singular Value Decomposition Emmett J. Ientilucci Chester F. Carlson Center for Imaging Science Rochester Institute of Technology emmett@cis.rit.edu May 9, 003 Abstract This report introduces

More information

ECE438 - Laboratory 9: Speech Processing (Week 2)

ECE438 - Laboratory 9: Speech Processing (Week 2) Purdue University: ECE438 - Digital Signal Processing with Applications 1 ECE438 - Laboratory 9: Speech Processing (Week 2) October 6, 2010 1 Introduction This is the second part of a two week experiment.

More information

MassHunter for Agilent GC/MS & GC/MS/MS

MassHunter for Agilent GC/MS & GC/MS/MS MassHunter for Agilent GC/MS & GC/MS/MS Next Generation Data Analysis Software Presented by : Terry Harper GC/MS Product Specialist 1 Outline of Topics Topic 1: Introduction to MassHunter Topic 2: Data

More information

GC METHODS FOR QUANTITATIVE DETERMINATION OF BENZENE IN GASOLINE

GC METHODS FOR QUANTITATIVE DETERMINATION OF BENZENE IN GASOLINE ACTA CHROMATOGRAPHICA, NO. 13, 2003 GC METHODS FOR QUANTITATIVE DETERMINATION OF BENZENE IN GASOLINE A. Pavlova and R. Ivanova Refining and Petrochemistry Institute, Analytical Department, Lukoil-Neftochim-Bourgas

More information

Modelling, Extraction and Description of Intrinsic Cues of High Resolution Satellite Images: Independent Component Analysis based approaches

Modelling, Extraction and Description of Intrinsic Cues of High Resolution Satellite Images: Independent Component Analysis based approaches Modelling, Extraction and Description of Intrinsic Cues of High Resolution Satellite Images: Independent Component Analysis based approaches PhD Thesis by Payam Birjandi Director: Prof. Mihai Datcu Problematic

More information

Uncertainty Estimates in XPS

Uncertainty Estimates in XPS Uncertainty Estimates in XPS Limit of Detection When acquiring XPS data a number of variables determine the quality of a spectrum in terms of signal-to-noise. Examples of variables are: 1. X-ray flux 2.

More information

Teaching notes: Time of flight mass spectrometry

Teaching notes: Time of flight mass spectrometry Teaching notes: Time of flight mass spectrometry These teaching notes relate to section 3.1.1.2 Mass numbers and isotopes of our AS and A-level Chemistry specifications (7404, 7405). This resource aims

More information

Automatic Facial Occlusion Detection and Removal

Automatic Facial Occlusion Detection and Removal Automatic Facial Occlusion Detection and Removal Naeem Ashfaq Chaudhry October 18, 2012 Master s Thesis in Computing Science, 30 credits Supervisor at CS-UmU: Niclas Börlin Examiner: Frank Drewes Umeå

More information

Technical Report. Automatic Identification and Semi-quantitative Analysis of Psychotropic Drugs in Serum Using GC/MS Forensic Toxicological Database

Technical Report. Automatic Identification and Semi-quantitative Analysis of Psychotropic Drugs in Serum Using GC/MS Forensic Toxicological Database C146-E175A Technical Report Automatic Identification and Semi-quantitative Analysis of Psychotropic Drugs in Serum Using GC/MS Forensic Toxicological Database Hitoshi Tsuchihashi 1 Abstract: A sample consisting

More information

Supervised Feature Selection & Unsupervised Dimensionality Reduction

Supervised Feature Selection & Unsupervised Dimensionality Reduction Supervised Feature Selection & Unsupervised Dimensionality Reduction Feature Subset Selection Supervised: class labels are given Select a subset of the problem features Why? Redundant features much or

More information

Quality Evaluation of Honey Using Multivariate Analysis

Quality Evaluation of Honey Using Multivariate Analysis Middle-East Journal of Scientific Research 3 (Sensing, Signal Processing and Security): 1-17, 015 ISSN 1990-933 IDOSI Publications, 015 DOI: 10.589/idosi.mejsr.015.3.ssps.6 Quality Evaluation of Honey

More information

A Semi-parametric Approach for Decomposition of Absorption Spectra in the Presence of Unknown Components

A Semi-parametric Approach for Decomposition of Absorption Spectra in the Presence of Unknown Components A Semi-parametric Approach for Decomposition of Absorption Spectra in the Presence of Unknown Components Payman Sadegh 1,2, Henrik Aalborg Nielsen 1, and Henrik Madsen 1 Abstract Decomposition of absorption

More information

ICH Topic Q 2 (R1) Validation of Analytical Procedures: Text and Methodology. Step 5

ICH Topic Q 2 (R1) Validation of Analytical Procedures: Text and Methodology. Step 5 European Medicines Agency June 1995 CPMP/ICH/381/95 ICH Topic Q 2 (R1) Validation of Analytical Procedures: Text and Methodology Step 5 NOTE FOR GUIDANCE ON VALIDATION OF ANALYTICAL PROCEDURES: TEXT AND

More information

UHPLC/MS: An Efficient Tool for Determination of Illicit Drugs

UHPLC/MS: An Efficient Tool for Determination of Illicit Drugs Application Note: 439 UHPLC/MS: An Efficient Tool for Determination of Illicit Drugs Guifeng Jiang, Thermo Fisher Scientific, San Jose, CA, USA Key Words Accela UHPLC System MSQ Plus MS Detector Drugs

More information

1 Example of Time Series Analysis by SSA 1

1 Example of Time Series Analysis by SSA 1 1 Example of Time Series Analysis by SSA 1 Let us illustrate the 'Caterpillar'-SSA technique [1] by the example of time series analysis. Consider the time series FORT (monthly volumes of fortied wine sales

More information

RAPID MARKER IDENTIFICATION AND CHARACTERISATION OF ESSENTIAL OILS USING A CHEMOMETRIC APROACH

RAPID MARKER IDENTIFICATION AND CHARACTERISATION OF ESSENTIAL OILS USING A CHEMOMETRIC APROACH RAPID MARKER IDENTIFICATION AND CHARACTERISATION OF ESSENTIAL OILS USING A CHEMOMETRIC APROACH Cristiana C. Leandro 1, Peter Hancock 1, Christian Soulier 2, Françoise Aime 2 1 Waters Corporation, Manchester,

More information

Introduction to Fourier Transform Infrared Spectrometry

Introduction to Fourier Transform Infrared Spectrometry Introduction to Fourier Transform Infrared Spectrometry What is FT-IR? I N T R O D U C T I O N FT-IR stands for Fourier Transform InfraRed, the preferred method of infrared spectroscopy. In infrared spectroscopy,

More information

Linear Algebra Review. Vectors

Linear Algebra Review. Vectors Linear Algebra Review By Tim K. Marks UCSD Borrows heavily from: Jana Kosecka kosecka@cs.gmu.edu http://cs.gmu.edu/~kosecka/cs682.html Virginia de Sa Cogsci 8F Linear Algebra review UCSD Vectors The length

More information

Strategies for Developing Optimal Synchronous SIM-Scan Acquisition Methods AutoSIM/Scan Setup and Rapid SIM. Technical Overview.

Strategies for Developing Optimal Synchronous SIM-Scan Acquisition Methods AutoSIM/Scan Setup and Rapid SIM. Technical Overview. Strategies for Developing Optimal Synchronous SIM-Scan Acquisition Methods AutoSIM/Scan Setup and Rapid SIM Technical Overview Introduction The 5975A and B series mass selective detectors (MSDs) provide

More information

EELE445 - Lab 2 Pulse Signals

EELE445 - Lab 2 Pulse Signals EELE445 - Lab 2 Pulse Signals PURPOSE The purpose of the lab is to examine the characteristics of some common pulsed waveforms in the time and frequency domain. The repetitive pulsed waveforms used are

More information

Department of Chemistry College of Science Sultan Qaboos University. Topics and Learning Outcomes

Department of Chemistry College of Science Sultan Qaboos University. Topics and Learning Outcomes Department of Chemistry College of Science Sultan Qaboos University Title : CHEM 3326 (Applied Spectroscopy) Credits : 3 Course Format : 2 lectures and 2 tutorials Course Text : Spectrometric Identification

More information