namics newsletter # 9 - cornell university · web viewinternational chemometrics society newsletter...
TRANSCRIPT
The North American Chapter of theInternational Chemometrics Society
Newsletter # 8 NAmICS July 1994
ICS
D.L. Massart, PresidentFree University of BrusselsInstitute of PharmacyLaarbeeklaan 103B-1090 Brussels, Belgium
W. Wegscheider, SecretaryInstitute for Analyt-, Micro- & RadiochemistryGraz University of TechnologyTechnikerstrasse 4A-8010 Graz, AustriaWegscheider @ rech.tu-graz.ada.at
S.D. Brown, Course AccreditationDepartmentof Chemistry and BiochemistryUniversity of DelawareNewark, DE 19716, [email protected]
B. Vandeginste, Chemometric AbstractsUnilever Research LaboratoryPO Box 114S130 AC Vlaardingen, The Netherlands
NAmICS
D.B. Dahlberg, PresidentDepartment of ChemistryLebanon Valley College Annville, PA [email protected]
Barry M. Wise, President-Elect4154 Laurel Drive,West Richland, WA [email protected]
D.M. Schnur, SecretaryMonsanto Company- U3E800 N. Lindbergh BoulevardSt. Louis, MO [email protected]
Illman and Blackburn, Editors-In-Chief
Deborah L. Illman4715 N.E. 100th, Seattle, WA [email protected]
Marlana B. BlackburnChemistry Department, Box 4076College of St. CatherineSt. Paul MN [email protected]
P.D. Wentzell, Treasurer - CanadaDepartment of ChemistryDalhousie UniversityHalifax, Nova Scotia B3H [email protected]
Charles H. Lockmueller, Treasurer - USADepartment of ChemistryDuke University
Durham, NC [email protected]
NAmICS Newsletter #9 September 1994
Software Reviews
Take a spin with Pirouette
Review of Infometrix product Pirouette v 1.2byMarlana Blackburn
The developers of Pirouette aim high; they seek to design a power-ful, yet user-friendly soft-ware tool that can tackle the most frequent types of chemometric investi-gations. Infometrix achieves this ambitious goal by judiciously se-lecting techniques and then carefully implement-ing them. Much thought has gone into the devel-opment of this high qual-ity product and it shows.
Pirouette's three modules each contain two algorithms. The exploration module implements hierarchical clustering and principal component analysis; the classification module offers K-nearest neighbors and SIMCA; the calibration module contains PLS and PCR routines. The underlying chemometric theory is solid. Necessary options are available and pertinent diagnostics calculated. Several types of preprocessing and many different
transformations are furnished. Prediction based on previously developed classification or calibration models is straight-forward.
[continued next page]____________________________________________________
From the Editor's Desk
It's a pleasure to bring you the eighth edition of the newsletter of the North American Chapter of the International Chemometrics Society. Dave Duewer and Dora Schnur roped me into, er, ah, asked me to guest-edit this issue. It's the one you've all been waiting for, yes, the Election Issue! There's quite a line-up of candidates waiting for you to cast your vote, so don't delay in returning your ballot (p. 20). All opinions expressed herein are solely those of contributing individuals; their institutions bear none of the blame.
Deborah Illman, Guest Editor
In this issue:
Candidate's Statements, 18 Ballot, 20 Miss Prim, 3Seasholtz waxes philosophic, 4 Happy Birthday NAmICS, 5Education, 8 Letters, 9 Vendor Information on List-Serve, 10Calendar, 12 Chemometrics On-Line Conference, 13
2
NAmICS Newsletter #9 September 1994
Software Reviews: Piroutte, cont.
Pirouette's menu-driven interface is uncluttered and intuitively organized. A rudimentary spreadsheet holds the data. Generating and managing data subsets is easy and efficient. One of Pirouette's several strengths is its clever graphic environment. The screen is divided into four windows containing "objects" (i.e., either raw data or computed results) selected by the user. For example, it is possible simultaneously to view eigenvalues, scores, and loadings in a PCA exploration. Changing the format of results is as easy as clicking on a toolbar button. Scores, for instance, can be displayed as a text table, a 2D scatterplot, a lineplot, or a 3D scatterplot. Windows can be zoomed to full screen or resized. The toolbar also provides the means to spin 3D plots, magnify 2D plots, and identify points in plots.
Pirouette provides what it calls "array plots" for certain objects. Consider a SIMCA model containing three classes. The scores window will contain three miniature score plots; each can be successively zoomed to fill the quadrant by double-clicking. These miniatures can be surprisingly informative. Other miniatures (called multiplots) of raw data show up to 231 pairwise variable plots (i.e., 22 variables worth); linear correlations are immediately visible even in the reduced form. This variety of data views and the advantageous use of color facilitate the tedious, yet necessary, process of examining a large data set.
The installation procedure is automatic. In a few cases, some customization of config.sys and autoexec.bat might be necessary but these matters are spelled out in the manual. The program accesses at most 16 MB of memory and requires at minimum a 386 computer with 4 MB of memory and 5 MB of hard disk space with an EGA or VGA adapter and mouse. A math co- processor is strongly recommended, as is more memory. I ran Pirouette on a 386sx (20 MHz, 4 MB, math co-processor) and a 486dx (66 MHz, 16 MB); the times given below correspond to the flashier hardware unless explicitly noted. The program's worksheet can hold up to 8000 samples or variables with the limit of the combination being determined by the available memory.
Extracting 10 principal components from a 75 sample/66 variable data set took less than 15 sec.
Pirouette employs data linking in two imaginative ways. First, in SIMCA, PCR, PLS, the number of model factors is linked to related objects (plots of modeling power, residuals, predictions, and leverage, etc). Thus, with a plot of eigenvalues v. number of factors in one window and up to three linked objects in other windows, clicking on the desired number of factors in the eigenvalue plot triggers an immediate update of the results in the remaining windows. The other type of data linking allows a user to select a subset of samples or variables in one view of the data and see those selections highlighted in another view.
This greatly simplifies the inspection and/or deletion of outliers. They can be highlighted in the residuals plot using a rubberband box, examined in the prediction plot, and then, with a single keystroke, excluded to form a new subset. This feature, coupled with the program's computational speed, makes it realistic to investigate and compare many subsets. For example, for my 75x66 data matrix, I could delete a few variables, re-run PCA, and compare the eigenvalue plots in less than 20 sec.
Besides its own data format, Pirouette supports ASCII and WKS formats for both input and output. I had no problem getting data into the program. I occasionally exported data in WKS format, loaded the file into a spreadsheet program, sorted the data, and so forth, and then re-read the file back into Pirouette. Bundled with Pirouette is MasterKey, a utility which translates data files produced by a variety of commercial instruments into Pirouette, ASCII, and WKS formats. To export only certain results, the user can choose to save the contents of an active window. This is handy for transferring results to a plotting package or a report generating program. Pirouette's flexibility in this important area of data handling is laudable.
Software Reviews: Piroutte, cont.
The Pirouette manual is outstanding. Besides THOROUGHLY documenting every feature of the program and presenting tutorials on each technique, it also discusses the theory behind the methods and
3
NAmICS Newsletter #9 September 1994
algorithms in a readable and informative style. The well-organized text includes many explanatory figures, a detailed index, and several excellent appendices.
The one area where I am critical of Pirouette is its printing capabilities. For the record, I have used (or tried to use) the following printers: HP PaintJet (color), HP LaserJetII, Apple LaserWriterIINT, and two other postscript printers whose names appear in Pirouette's Printer Setup menu. The LaserJetII performed properly. The PaintJet was occasionally flaky. I never succeeded in getting output from any postscript device. All printing takes place in the foreground. Given the complexity of the images being printed, it is not surprising that the process is rather slow on aging hardware; it took my 386sx about 2 min/page for the LaserJetII. (I can't give a time for the 486dx because only postscript printers were available on that system.)
It is also distressing that offline devices are not recognized as such. For those working in a postscript environment, the otherwise fine performance of the software is compromised by printing difficulties. The program offers the option of printing to a file or saving TIFF images, which is a fast way around printing out of Pirouette. It took less than 15 sec for the 486 .tif file-write. Perhaps Windows users imagine saving TIFFs, switching into a Windows program that recognizes the format, printing via the Print Manager, and switching back to Pirouette. Good idea except for the switching part. Pirouette CAN run inside Windows (but only in standard mode and some applications don't like this) but it cannot task switch. Infometrix is aware of the postscript printing problems and is taking steps to address them. A Windows version of the program is due by the end of the year. Its release should make both the print speed and printer driver issues moot. I found the staff at Infometrix EXTREMELY responsive and knowledgeable. My phone calls and email messages were dealt with in a timely and professional fashion.
Overall, Pirouette is a very impressive product. It IS expensive (list $4000 with a 40% discount for academic users) but let's face it, good tools are never
cheap! A free, almost fully functional demo is available so interested parties can investigate the program for themselves. Since Infometrix will customize a demo containing your own data, this is a no-risk way to get a real feel for Pirouette and see how it works with your system.
For further information:Infometrix, Inc.2200 Sixth Avenue, Suite 833Seattle, WA 98121phone: 206-441-4696fax: 206-441-0841internet: [email protected]
__________________________________________
Ask Miss Prim
Dear Miss Prim,
My name is Eddie an my nayburhood is gonna becum a enterprise zone. I wanna start a kemmometrics kumpany wit my pals on da street. What shud we do?
Signed,
Eddie an da Latin Squares
Gentle (sic) Reader:
Perhaps you should look into a more lucrative business like statistical consulting. There are already gangs of unemployed chemometricians roaming the country looking for jobs. In fact, there is an international crisis, with svante or eighty such gangs throughout the world. These people are mean (not average), sum are squared, and many are in analysis. Do a target transformation on your goals.
[Questions for Miss Prim (Clare Gerlach) may be sent in care of the Editor-in-Chief.]
4
A rose by any other name…
Mary Beth Seasholtz, [email protected], (517)636-3646
The field of chemometrics is fortunate enough to have progressed to the point where there are multiple generations of ideas. As a graduate student in 1989 eager to learn the tools of the trade, I was confronted with two sets of ‘generations’ of equations describing PCR (and who knows how many for PLS, but that is another story!). This newsletter seemed a good place to present a few lines which demonstrate the equivalence of the two approaches, and to touch on the historical context which led to the move. Please forgive the omission to the multitude of appropriate references – Deborah only gave me one page.
The older of the two approaches begins with assuming R = TPT where T has orthogonal columns and P has orthonormal columns. In the mid 1960’s when chemometrics was born, there were a few methods available for calculating T and P. One was the not so well behaved NIPALS algorithm. Alternatively, T could be obtained by solving for the eigenvalues and eigenvectors of RRT (a square symmetric matrix), and then P could be estimated given R and T. The symmetric eigenvalue problem was studied for many years; the most famous book on the subject was published in 1965 by J.H. Wilkinson (The Algebraic Eigenvalue Problem). However, computational algorithms were not in high demand as computers of the 60’s certainly were not what they are today. The calibration problem then was (~ indicates truncation). Solving for x via the normal equations gives
. For prediction, the unknown measurement must first be converted to scores by , giving
(1)
In 1969 Gene Golub made the singular value decomposition (svd) an algorithmic reality. It was long known that an arbitrary matrix could be written as the product of three matrices, R = USVT, where U = eigenvectors of RRT, V = eigenvectors of RTR and RRT (they are the same). But, until Gene and his coworkers came on the scene there was not a direct calculation (you had to go through the covariance matrices as described above). With the advent of the widespread availability of the svd (and other useful code) through facilities like LINPACK, EISPACK, Numerical Recipes and Matlab, the PCR story has since evolved and a new word is being used: pseudoinverse. The calibration equation now reads c = Rb, and , where pseudoinverse. Prediction is simply
(2)
Equation (2) sure looks different from (1)! Well, recall T could be calculated from an eigenvector problem of RRT … in fact T = US and P = V. Making these substitutions into (1) give which is equation (2), after reduction using standard linear algebra rules.
As can be seen, it was because of some relatively new technology in the area of numerical linear algebra which gave rise to the new look for PCR. In addition to all the other things that keep us busy, I think we must be as diligent as we can to continue to bring into chemometrics new developments from disciplines such as applied mathematics, statistics and numerical analysis.
See what too much tequila can do?
byBruce R. KowalskiEndowed Professor of ChemistryUniversity of Washington
June 10, 1994
Happy 20th Birthday to the Chemometrics Society! It was on June 10, 1974 that the Laboratory for Chemometrics met with Svante Wold in Seattle over some great Mexican food and too much tequila and formed the Society. Our focus was on improving communication between chemists, statisticians and mathematicians. We also wanted all chemists to be about 10% chemometricians to insure that experiments would be designed optimally and all information would be extracted from chemical measurements. Well, the Mexican restaurant is no longer in business but the Society and field of chemometrics is alive and doing very well.
I was reading Chemometrics Society Newsletter Number 1 (I have a complete set) published in January, 1976, and it reported 101 members worldwide with half of them owning the program ARTHUR which some of you may remember. The newsletter announced that the second FACSS meeting had an attendance of 200 at the "Chemometrics in Analytical Chemistry" session with papers from Wold, Deming, Horlick, Duewer and Kowalski. Also announced was the "Chemometrics: Theory and Applications" session at the Summer 1976 ACS meeting in San Francisco that later produced the first book on chemometrics. The newsletter ended with comments, requests and suggestions from Richard Cramer, Ken Loach and Harold Martens. So much for ancient history.
Two journals, thousands of papers and reviews and dozens of books later we find ourselves today with rich areas of application, powerful chemometrics tools and essentially infinite computer power. We are very busy scientists. Also, scientists, statisticians, and mathematicians and even chemical engineers have discovered chemometrics and the race is on. What will our science be like in the next century, the year 2000?
Allow me to make a few predictions. You can use leave-one-out cross-validation to estimate the PRESS, SEP or RHSCV if you choose. First and foremost we should all see the necessity to have chemometrics permeate the formal education of all chemists, not only with graduate level courses, training courses and workshops but also at the beginning levels of chemical education. The old "scientific method" that relies on a lot of theory and few definite measurements must die. It should be replaced with equal amounts of theory, experimentation, measurements and simulation and emphasize the multivariate nature of the world around us. There is no place for univariate thinking in our multivariate, dynamic world.
Next, chemometrics will no longer be just a collection of our data analysis methods. The tools of chemometrics will spawn new measurement theories that will guide chemists in all areas of research. To this end a young chemometrician, Karl Booksh, and I offer a special report in the August issue of ANALYTICAL CHEMISTRY titled "Theory of Analytical Chemistry." I invite you to read this paper and incorporate it in your research and education activities. I also encourage you to expand this theory and move it into areas of chemistry beyond chemical analysis.
Finally, the tools of chemometrics will move from mathematics and software to firmware so as to be transparent to the user and very easy to use and hard to abuse. Our current software, while a great improvement over ARTHUR and SIMCA, is still too difficult to use. The younger generation of chemists have good backgrounds in linear algebra and have little difficulty with multivariate methods. However, the older generation that will be with us into the next century doesn’t understand our methods and therefore prefer to separate one peak from all the rest or correlate one molecular property at a time to molecular activity thereby missing the most important part of nature, covariance. We must accept the responsibility to make it easy for all chemists to incorporate multivariate methods into their work. Use this as an analogy. We are all expert users of TVs, VCRs, cellular phones and the like, but how many of us are truly familiar with the complex subsystems of these devices. To really be of use, our methods must be integrated into instruments and experiments to the point of being transparent.
I'll stop here. Many of you have your own vision of the future of chemometrics that I for one would surely love to hear. Perhaps you can use the newsletter as your vehicle to share your thoughts with the rest of us and thereby continue a twenty year tradition.
Outliers
Q: How many Californians does it take to change a light bulb?
A: Six. One to turn the bulb, one for support, and four to relate to the experience.
Q: How many Oregonians does it take to screw in a light bulb?
A: Five. One to change the bulb and four more to chase off the Californians who have come up to relate to the experience.
Q: How many Seattlites does it take to screw in a light bulb?
A: Two. One to change the bulb and one to hold both lattes.
Q: How many Zen masters does it take to screw in a light bulb?
A: A tree in a golden forest.
Q: How many surrealists does it take to change a light bulb?
A: Two: one to hold the giraffe, and the other to fill the bathtub with brightly colored machine tools.
Q: How many IBM types does it take to change a light bulb?
A: 100. Ten to do it and 90 to write document number GC7500439-0003 Multitasking Incandescent Source System Facility of which 10% of the pages state only “This page intentionally left blank.”
Q: How many Vulcans does it take to change a light bulb?
A: Approximately 1.00000000000000000000000
Q: How many existentialists does it take to screw in a light bulb?
A: Two: One to screw it in and one to observe how the light bulb itself symbolizes a single incandescent beacon of subjective reality in a netherworld of endless absurdity reaching out toward a maudlin cosmos of nothingness.
Open a Window on Chemometrics
byJudith [email protected]
Window on Chemometrics is a new monthly publication reporting on the latest work in the computer handling of analytical data. It covers the science of chemometrics and its applications in spectroscopy, chromatography, and other analytical techniques.
Produced by scanning the international scientific literature, including the major chemometrics and analytical chemistry publications, Window on Chemometrics gives reports of developments in the following key areas:
General Techniques & StatisticsCalibration & ValidationComputer Programs, Expert Systems and
ApplicationsSpectrometryChromatographyOther Analytical Techniques
Each report gives title, detailed abstract and bibliographic details.
A sample abstract:
Theory of medium-rank second-order calibration with restricted-Tucker models.
Smilde, A.K.; Wang, Y.D.; Kowalski, B.R.
J. Chemom., Jan-Feb 1994, 8(1), 21-36
Second order analytical instruments or instrumental methods (i.e. those that give a response matrix when analyzing a pure analyte) have the advantage of the ability to analyze mixtures which contain unknown interferences. However, this advantage can be lost, if a suitable calibration method is not used. A medium-rank second-order calibration method is proposed (full details given), based on least-squares restricted Tucker models. With this method the second-order advantage is retained.
Ordering details:
Window on Chemometrics ISSN 0966-908612 issues per year1994 subscription prices:US $162.00Canada L95.00 (+GST)EC & Rest of World L90.00
Please order from:
The Royal Society of ChemistryTurpin Distribution Services LtdBlackhorse RoadLetchworth, Herts SG6 1HNUK.
Tel: +44 (0)462 672555Fax: +44 (0)462 480947.
For further details and a sample copy of Window on Chemometrics, please contact:
Judith BarnsbyThe Royal Society of ChemistryThomas Graham HouseScience Park, Milton RoadCambridge CB4 4WFUK.
Tel: +44 (0)223 420066(Toll free in US: 1-800-473-9234)Fax: +44 (0)223 423429E-mail: [email protected].
Education
Chemometrics is for undergraduates, too
by Nick C. Thanasoulias
[Thanasoulias writes to us from the Chemistry Department at the University of Ioannina, Greece--Ed.]
Many colleagues, who teach in higher education institutions, keep wondering whether undergraduate students should be presented with chemometrics or not. Common questions involve the student's background in mathematics, knowledge of computers and ability to catch the idea behind the calculations that chemometrics requires. One common argument is that chemometrics is needed only if you plan to do research. So why not stick to the old familiar Gaussian least squares?
However, the fact is that everyday we are more and more confronted with the problem of agreement between results of different laboratories. Most industrial processes require pilot experiments which can be performed only by means of applying statistical and mathematical techniques to chemical problems. Quality control, especially in the clinical laboratory, is another major application of chemometrics.
It is more than certain that chemometrics can not be ignored. In my opinion it should be taught in the undergraduate level and students should become familiar with as many statistical techniques as possible.
In the University of Ioannina, Greece, chemometrics is taught during the last semester of the fourth year. Since students are able to choose their classes during that semester, chemometrics teaching can be modified according to the number of students attending the class. It usually consists of two modules: one theoretical and one experimental. The theoretical part includes some six to ten hours of classroom teaching and the chapters covered include: fundamentals of statistics, significance testing, analysis of variance, experimental errors, simple and multiple linear regression, factorial design and cumulative sum techniques.
The second module consists of a series of experimental classes which are designed so that they resemble a "miniature" thesis preparation. Each student is asked to apply to a real chemical problem some of the theoretical principles learned so far. The outline is as follows:
Definition of the chemical problem;
Literature study related to the chosen chemical problem (usually covers the last 2-5 years and students are asked to concentrate on review papers);
A normality test is applied to a set of repeated measurements in order for the student to decide whether to use parametric or non-parametric techniques. We usually take care that parametric statistics can be applied since students are not familiar with non-parametric methods and algorithms;
Classic one-at-a-time factor-change experiments are performed, in which change in an appropriately chosen variable (the response) as a function of one factor is followed while the other factors are kept constant. The choice of the factors and response relies on previous knowledge (usually from the literature study) and care is taken not to include more than one factor which may not have a significant effect on the response. The results are treated with the usual regression techniques;
One-way ANOVA tests are carried out for each factor in turn for the student to get an idea of how significant the effect of each factor may be;
Up to four factors are selected in a complete factorial design (five, if the measurements are very easy to perform). The factors are chosen in two levels and all the trials, consisting of all the possible combinations, are carried out twice for an estimation of the effects and the residual variance;
Finally, the student presents a report that follows closely the principles of scientific paper writing and is asked to make conclusions such as the suitability of the system for analytical purposes (limit of detection, limit of determination, sensitivitiy) and to propose ways of maximizing system response.
So far, we have tried systems such as the oxidation of pyrogallol by various oxidants with chemiluminescence detection, the determination of gallic acid and tannins, the correlation of analytical methods for determination of glucomse content of foodstuffs, and the synthesis of zeolites and their ion-exchange capability, among others.__________________________________________
Letters to the Editor
Communication gap betweenQSAR and Physiologial Modelers--What to do?
Dear Editor,
… an increasing percentage of activities supported by public and private sector organizations are framed against the complexities associated with assessing and managing the many forms of risk as may be posed to humans and the environment by chemical, biological, and physical agents.
A "Workshop on Decision Support Methodologies for Human Health Risk Assessment of Toxic Substances" was held November last year. The focus of the Workshop was on the status, direction, and utility of models described as PBPKPD (Physiologically Based/ Pharmacokinetic / Pharmacodynamic means to model metabolic disposition of chemical substances) and similar discussions on efforts in QSAR (Quantitative Structure Activity Relationships).
The Workshop was funded by: Agency for Toxic Substances And Disease Registry (ATSDR), National Institute of Environmental Health Sciences (NIEHS), National Cancer Institute's (NCI) Division of Cancer Etiology (DCE), Environmental Protection Agency (EPA), Wright Patterson Air Force Base, Toxicology Division, and the National Library of Medicine (NLM).
I had two roles, one as a member of the Workshop's steering committee and as one of the wrap-up speakers. My presentation focused on the array of data and information resources needed to efficiently and effectively support the development, testing, application, and validation of means to model the effect of chemical, biological, and physical agents on biological systems. The resources generally useful
in organizational decision making are relevant to assessing and managing the many forms of risk.
What was distressing to me and others at the Workshop was the almost complete lack of communication between the PBPKPD and QSAR modelers--which raises the challenge as to what should be done to insure that understanding evolves of the inter-relationships of these models.
The steering committee will be maintained, and I will continue as a member. I would like to be able to use it as a platform to identify needs for data and information resources which so far have not been identified, and to use this platform to help prioritize forms of such resources to support scientific efforts.
Sidney Siegel, Ph.D.Chief, Office of Hazardous Substances Information301-496-5022; FAX. 301-480-3537
__________________________________________
Expert System Available
An expert system is now available, at no cost, which will determine chemical class, molecular weight and target compound identity from low resolution mass spectra. The target compounds are 75 volatile toxic and related compounds. Class and MW information is valid for compounds other than the target set. Description is provided in D.R. Scott, Anal. Chim.Acta, 285, 209-222 (1994), and in forthcoming paper by D.R. Scott in Chemometrics and Intell. Lab. Sys., accepted February 1994. For a copy of the program and instructions, send a 3.5 or 5.25-inch MS-DOS formatted diskette to D.R. Scott, AREAL, MD-77, U.S. EPA, Research Triangle Park, N.C. 27711, USA.
News from the President-Elect
Vendor information on List-Serve
Message to List-Serve Readers:
An important role of NAmICS is to provide a conduit for communication between those who create and/or apply chemometrics and those who provide the instrumentation and software to implement it. In the case of software we have attempted to do this through reviews in our newsletter.
Unfortunately this approach takes a great deal of time. I spent about 60 hours on the review that I wrote for the newsletter. Although I personally hope that others will offer reviews of software and instrumentation that they use, we have had little success in finding those willing to do so.
It has been suggested that we allow software and hardware companies an opportunity to present their products to our members. We, the officers of NAmICS, agree with this suggestion, but wish to avoid long sales pitches or monologues. Yet it would be helpful if the vendors provided the philosophy, scope, contents, references, prices, and purchasing procedures for their products. It will take some trial and error and feedback from the membership in order to define the line between useful information and annoying advertisements.
There is nothing to prevent any member of the list-server from posting an advertisement (other than the VERY real risk of alienating possible customers). For this reason, we suggest that presentations first be sent to me for initial screening and negotiated editing.
Our first attempt at providing information about a software package will follow this message. Please let me know what you think about its form and presentation. In making these comments please also remember that you signed
onto this list-serve in order to be kept current in the development and application of chemometrics.
Donald Dahlberg, Ph.D.Department of ChemistryLebanon Valley CollegeAnnville, PA 17003-0501office: (717)867-6143fax: (717)867-6124E-Mail: [email protected]
Chemometrics Software UpgradePLS_Toolbox Version 1.4For Use with MATLAB*
Now AvailableSubmitted by Barry M. Wise
***************************************
I am pleased to announce that the PLS_Toolbox Version 1.4 is now available. This upgrade of the PLS_Toolbox is the most extensive since it was first released in 1991. The toolbox is now completely compatible with MATLAB 4.x, and takes advantage of many of the new MATLAB features. In addition, I am now offering technical support for the PLS_Toobox through my home e-mail account and home FAX.
Many new functions have been added to the toolbox, and others have been improved considerably. Some examples are:
* Multivariate instrument standardization with additive background correction.
* Two and three dimensional scores and loadings plots with labelled points.
* Locally weighted regression with y-distance weighting.
* K-means statistical cluster analysis with dendrograms.
* Savitsky-Golay smoothing and derivatives.
Another major addition to the PLS_Toolbox is a general regression modelling routine, MODLMKER, that allows the user to access all the scaling functions, regression functions and cross validation methods from one routine. This function also produces plots of leverage versus studentized residuals for detection of calibration outliers. Model parameters, including date and time stamp, scaling vectors, final regression vectors and information on the method used to create the model are stored in single matrices. These single matrices can be used with new data and the MODLPRED function to make new (properly scaled) predictions. In addition, the models can be "read" by MODLRDER, a function that prints all information about a model's creation to the screen.
The entire contents of the PLS_Toobox Version 1.4 are listed below. The toolbox includes 53 functions, 16 demonstrations and 8 test data sets. The PLS_Toolbox can be obtained on 3 1/2 inch high- density diskettes for DOS or Macintosh. The disks are supplied with the 30+ page manual which outlines the use of all the functions. Please contact me at the e-mail address below concerning availability and pricing. Academic and bulk discounts are available. If you have comments or questions about the PLS_Toolbox, please do hesitate to contact me.
Barry M. Wise, Ph.D4154 Laurel DriveWest RichlandWA 99352
E-mail: [email protected]: (509)967-3973
% PLS_Toolbox Contents.% Version 1.4 22-May-94% Copyright (c) 1994 by Barry M. Wise%% Data Scaling and Preprocessing.% auto -Autoscales data.% mncn - Mean centers data.% scale - Scaling using specified means and std. devs.% rescale - Scales data back to original scaling.% delsamps - Deletes samples from data matrices.% savgol - Savitsky-Golay smoothing and derivatives.% ftest - Inverse F test statistic.% shuffle - Randomly re-orders matrix rows.%% Principal Components and Cluster Analysis.% pca - Principal components analysis.% pcapro - Applies existing PCA model to new data.% mdpca - PCA for matrices with missing data.% pltloads - Two and three dimensional loadings plots.% pltscrs - Two and three dimensional scores plots.% cluster - K-means cluster analysis with dendrograms.%% Principal Components Regression.% pcr1 - Principal components regression.% pcrcv - General cross-validation for PCR models.% pcrcv1 - Leave one out cross-validation for PCR models.% pcrcvblk - PCR cross-validation with contiguous data.% pcrcvrnd - PCR cross validation using random test sets.%% Partial Least Squares Regression.% pls - Partial least squares regression.% plsnipal - NIPALS algorithm for one PLS latent variable.% plspred - Predictions based on existing PLS model.% conpred - Converts PLS models to regression vectors.% conpred1 - Converts PLS models to single vector.% plscv - General cross-validation for PLS models.% plscv1 - Leave one out cross-validation for PLS models.% pcrcvblk - PLS cross validation using contiguous blocks.% pcrcvrnd - PLS cross validation using random test sets.%% Other Linear Regression Methods.% powerpls - Continuum regression by "powered" method.% ridge - Ridge regression by Hoerl-Kennard method.% ridgecv - Ridge regression by cross-validation.%% General Regression Modelling.% modlmker - Develops PCR, PLS and RR models.% modlrder - Displays information from MODLMKER.% modlpred - Predictions for MODLMKER models.%% Non-Linear Regression Methods.% polypls - PLS with polynomial inner-relationships.% polypred - New predictions with poly-PLS models.% spl_pls - PLS with spline inner-relationships.% splspred - New predictions with SPL_PLS.% splnfit - Spline fits to bivariate data.% splnpred - New predictions based on spline fits.% lwrpred - Predictions based on LWR model.% lwrxy - LWR predictions with y-distance weighting.
%% Multivariate Instrument Standardization.% stdgen - Standardization transform generator.% stdsslct - Selects data subsets for standardization.%% Multivariate Statistical Process Control.% replace - Replaces variables based on PCA or PLS models.% plsrsgn - Generates a matrix of PLS models for MSPC.% plsrsgcv - Cross-validation for PLSRSGN models.%% Identification of Finite Impulse Response Models.% plspuls - Identifies FIR models by PLS for MISO systems.% fir2ss - Transforms FIR model to equiv. state space.% writein2 - Writes matrices for FIR model identification.% wrtpulse - Writes matrices w/ delays for identification.% autocor - Auto-correlation function for time series.% crosscor - Cross-correlation function for time series.%% PLS_Toolbox Demonstrations.% pcademo - Pricipal components analysis.% mddemo - PCA for missing data.% clstrdmo - Statistical cluster analysis and dendrograms.% plsdemo - Partial least squares regression and PCR.% ridgdemo - Ridge regression functions.% pwrdemo - Continuum regression by "power" method.% modldemo - PLS, PCR and RR with MODLMKER.% polydemo - PLS with polynomial inner relationship.% lwrdemo - Locally weighted regression functions.% splndemo - PLS with spline inner relationships.% stddemo - Multivariate instrument standardization.% sgdemo - Savitsky-Golay smoothing and derivatives.% ccordemo - Cross- and auto-correlation.% pulsdemo - Identification of FIR models with PLS.% rsgndemo - Collections of PLS models for MSPC.% rplcdemo - Failed sensors replacement for MSPC models.%% PLS_Toolbox Test Data Sets.% splndata - Synthetic data for spline demo.% nir_data - Near infrared spectra of pseudo gas samples.% pcadata - Liquid-fed ceramic melter data for pca demo.% ridgdata - Hald data set of cement samples.% repdata - Liquid-fed ceramic melter data for RPLCDEMO.% pol_data - Non-linear surge tank data for polypls demo.% pulsdata - Liquid-fed ceramic melter PULSDEMO data.% plsdata - Liquid-fed ceramic melter PLSDEMO data.
* MATLAB is a registered trademard of The MathWorks, Inc.
Unscramber version 5.5is announced
Unscrambler, which has brought you multivariate calibraton, classification, and prediction using PLS, PCA, PCR, and neural networds, now offers Simca classification and other updates such as "improved import from Lotus, Excel and JCAMP," according to a company announcement. The new version offers a "new data edit function for easy splitting of one matrix into several submatrices" and can "sort objects 40 to 200 times faster" now.
Unscrambler for Windows is scheduled for release in 1995, and the company, Computer-Aided Modelling A/S, says it plans to maintain features of the current DOS version: high performance, easy use, the capability of handling very large data sets, and a wide range of plots. It will comply with the GUI standard and have an object-oriented design.
For further information:CAMO USA,722 Port Walk Pl.Redwood Shores, CA 94065415-598-9860FAX 415-595-2321
CAMO S/AOlav Tryggvasons gt 24N-7011 TrondheimNorway
Telephone: +47 7351 4966FAX: +47 7351 4257__________________________________________
Calendar of Events
International Chemometrics Research MeetingJuly 3-7, 1994, Veldhoven, The NetherlandsSecretariat: Laboratory for Analytical ChemistryFaculty of ScienceCatholic University of NijmegenTowrnooiveld 16525 ED NijmegenThe NetherlandsTelephone: +31 80 653173/92FAX: +31 80 652653
10th European Symposium on Structure-Activity Relationships; QSAR and Molecular ModellingSept. 4-9, 1994, Barcelona, SpainSecretariat: Department of Medical InformaticsInstitut Municipal d'Investigacion MedicaC/ Doctor Aiguader, 80E-08003 Barcelona, SpainFAX:+ 34 3 2213237E-mail: [email protected]
5th International Conference on Statistical Methods forthe Environmetnal Sciences and 4th General Meeting of the International Environmetrics SocietyAugust 12-15, 1994, Burlington, Ontario, CanadaContact: A.H. El-ShaarawiNational Water Research InstituteP.O. Box 5050Burlington, Ontario L7R 4A6 CanadaTelephone: +1 905 3364584FAX: +1 905 3364989Email: [email protected]
__________________________________________
Chemometrics On-lineConference held this fall
The North American Chapter of the International Chemometrics Society and Elsevier are sponsoring the First International Chemometrics Internet Conference, to be held September 26 to November 18, 1994. Some 38 papers will be submitted electronically and downloaded over the network by conference participants. Discussion periods over the Internet will follow, according to organizer Barry M. Wise.
A total of ten sessions will be held; session chairs will moderate the discussion of the papers. And a special issue of Chemometrics and Intelligent Labora-tory Systems will be published with the conference papers and discussion summaries. Instructions for participants will be sent out in the newsletter at the end of August or by e-mail to those that send Barry a note expressing interest.
Barry M. Wiseemail: [email protected]
Chair, InCINC'94
On-line Conference Program
Session 1Chemometrics and EducationChair: Bruce [email protected]
COMPUTATIONAL ANALYTICAL CHEMISTRY AND ITS INTRODUCTION IN UNDERGRADUATE CURRICULAC.H. Lochmueller, Charles E. ReeseDepartment of Chemistry, Duke University, Durham, NC
CHEMOMETRIC TUTORIALS -- WHY AND HOW?Jerry WorkmanPerkin Elmer Corp.
FIVE YEARS OF TEACHING THE ART OF CHEMOMETRICS TO UNDERGRADUATE STUDENTS,D.B.DahlbergDepartment of Chemistry, Lebanon Valley College, Annville, PA
- - - - - - - - - - - - - - - - - - - - - - -
Session 2Chemometrics: Philosophy, History and DirectionsChair: Aloke [email protected]
CHEMOMETRICS: WHAT DO WE MEAN WITH IT, AND WHAT DO WE WANT FROM IT?Svante WoldInstitute of Chemistry, Umeå University, Umeå
WHAT IS CHEMOMETRICS?Tormod Naes, Tomas Isaksson, Harald MartensMATFORSK and Consensus Analysis, Norway.
Additional contribution expected from Steve Brown
- - - - - - - - - - - - - - - - - - - - - - -
Session 3Data Rectification/ValidationChair: David [email protected]
COMBINED PROCESSING OF EXPERIMENTAL SERIES WITH SYSTEMATIC ERRORS – NON-LINEAR PHYSICO-CHEMICAL MODEL WITH LINEAR ERROR MODEL. APPLICATION TO VAPORIZATION THERMODYNAMICS OF KClE.B. RudnyiDepartment of Chemistry, Moscow State University, Moscow, Russia
THE APPLICATION OF NONLINEAR DYNAMIC DATA RECONCILIATION TO PLANT DATAKaren F. McBrayer, Thomas F. EdgarDepartment of Chemical Engineering, University of Texas, Austin, TX
DYNAMIC DATA RECTIFICATION USING THE EXTENDED KALMAN FILTER AND RECURRENT NEURAL NETWORKSThomas W. Karjala, David M. HimmelblauDepartment of Chemical Engineering, University of Texas, Austin, TX
- - - - - - - - - - - - - - - - - - - - - - -
Session 4Chemometrics in Dynamic SystemsChair: Ali [email protected]
A COMPARISON OF NEURAL NETWORKS, NON-LINEAR BIASED REGRESSION AND A GENETIC ALGORITHM FOR DYNAMIC MODEL IDENTIFICATIONBarry M. Wise, Bradley R. HoltPacific Northwest Laboratory, Richland, WA
APPLICATION OF EVOLVING FACTOR ANALYSIS IN THERMOCHROMATOGRAPHYMatti ElomaaDepartment of Polymer Chemistry, University of Helsinki, Meritullinkatu, FinlandCharles H. LochmuellerDepartment of Chemistry, Duke University, Durham, NCMihkel Kaljurand and Mihkel KoelDept. of Analytical Chemistry, Institute of Chemistry, Estonian Academy of Sciences, Tallinn, Estonia.
RESOLUTION OF SIMULTANEOUS, DYNAMIC THERMAL PROCESSES IN THERMOCHROMATOGRAPHY OF OIL SHALE BY FACTOR ANALYSISM.Koel, M.KaljurandInstitute of Chemistry, Academy of Sciences of the Estonian Republic, Tallinn, EstoniaC.H. Lochmueller, Martin MoebusDepartment of Chemistry, Duke, University, Durham, NC
NONLINEAR TIME SERIES MODELS FOR MULTIVARIABLE DYNAMIC PROCESSESXianchun Wu, Ali CinarDepartment of Chemical Engineering, Illinois Institute of Technology, Chicago, IL
- - - - - - - - - - - - - - - - - - - - - - -
Session 5Non-Linear Alternative to Neural NetworksChair: Lyle [email protected]
SMOOTHERS AND SPLINES FOR NONLINEARIZING PLS AND PCRIldiko E. FrankJerIl, Inc., 790 Esplanada, Stanford, CA
THE USE OF A NONPARAMETRIC METHOD FOR MODELING CAPACITY FACTORS IN RP-HPLCMargriet M.W.B. Hendriks, Pierre M.J. Coenegracht, Durk A. DoornbosResearch Group Chemometrics, University Center for Pharmacy, University of Groningen, Groningen
NONLINEAR PARTIAL LEAST SQUARES USING NEURAL NETWORKSE.C. Malthouse, R.S.H. Mah*, A.C. TamhaneNorthwestern University Department of Statistics,*Department of Chemical Engineering
CHEMICAL CLASSIFICATION OF MICROSENSOR ARRAY RESPONSES BY AN EMPIRICAL CLUSTERING TECHNIQUEG.C. Osbourn*, J.W. Bartholomew, G.C. Frye, A.J. RiccoSandia National Laboratories, Albuquerque, NM
A COMPARISON OF CLASSIFICATION IN ARTIFICIAL INTELLIGENCE, INDUCTION VERSUS NEURAL NETWORKS Mulholland, D.B. HibbertDepartment of Analytical Chemistry, University of New South Wales, PO Box 1, Kensington, NSW 2033, Australia.
- - - - - - - - - - - - - - - - - - - - - - -
Session 6Chemometrics in ChromatographyChair: Paul [email protected]
THE USE OF STATISTICAL TECHNIQUES TO INVESTIGATE THE AGEING PROCESS OF RP-HPLC STATIONARY PHASESAnnabel Bolck, Age K. Smilde, Chris Bruins, Durk A. DoornbosResearch Group Chemometrics, University Centre for Pharmacy, University of Groningen, Groningen.
CHEMOMETRIC ANALYSIS OF GAS CHROMATOGRAPHIC DATA OF OILS FROM EUCALYPTUS CAMALDULENSIS (RIVER RED GUM)Peter J. Dunlop and C.M. BignellDepartment of Chemistry, University of Adelaide, South AustraliaJ.F. JacksonDepartment of Viticulture, Oenology and Horticulture, University of Adelaide, South AustraliaR.B. InmanInstitute of Molecular Virology, University of Wisconsin, Madison, WID. Brynn HibbertSchool of Chemistry, University of New South Wales, Sydney, NSW
POWER SPECTRUM BASED ANALYSIS OF MULTICOMPONENT CHROMATOGRAMSAttila FelingerDepartment of Analytical Chemistry, University of Veszprem, Veszprem, HungaryMaria C. Pietrogrande and Francesco DondiDepartment of Chemistry University of Ferrara, Ferrara, Italy
PREDICTION OF REVERSED PHASE HPLC RETENTION BY PRINCIPAL COMPONENTS ANALYSIS AND TARGET TESTING.C.H. Lochmueller, C.E. Reese, Su-Hsiu HsuDepartment of Chemistry, Duke University, Durham, NC
- - - - - - - - - - - - - - - - - - - - - - -
Session 7General SessionChairs:Charles Lochmueller
[email protected] M. [email protected]
ON THE IDENTIFICATION OF THE NUMBER OF ABSORBING SPECIES AND THE NUMBER OF INDEPENDENT REACTIONS FROM SPECTRAL MEASUREMENTM. Amrhein, D. Bonvin, B. SrinivasanInstitut d'Automatique, Ecole Polytechnique Federale de Lausanne, SwitzerlandM. SchumacherLonza AG, Visp, Switzerland
MULTIRESPONSE STEEPEST ASCENT IN A DESIGN SPACE CONSISTING OF BOTH MIXTURE AND PROCESS VARIABLESC.A.A. Duineveld, P.M.J. CoenegrachtResearch Group Chemometrics, University Centre for Pharmacy, University of Groningen, Groningen
THE USE OF CHEMOMETRIC TECHNIQUES IN PROCESS ANALYTICAL METHOD DEVELOPMENT AND OPERATIONCharles E. MillerDuPont Packaging and Industrial Polymers Research, PO Box 1089, Orange, TX.
PARTIAL LEAST SQUARES AND COMPOSITIONAL DATA: PROBLEMS AND ALTERNATIVESJohn E. Hinkle and William S. RayensDepartment of Statistics, University of KentuckyLexington, KY
CHEMOMETRIC META-ANALYSIS: TRYING TO MAKE SENSE OF DATA FROM DIFFERENT TIMES AND PLACESDavid Lee Duewer, NIST
MODEL VALIDATION IN PRACTICE - AN OVERVIEW OF TECHNIQUES USED IN MULTIVARIATE DATA ANALYSISSuzanne Schoenkopf and Max Egebo@ CAMO as (Norway).
AN IMPROVED SVD-BASED EFFICIENT NUMERICAL ALGORITHM FOR PERFORMING PARTIAL LEAST SQUARES (PLS)T.W. Wang, J. Batra, P. Sarma, A. Khettry, M. Berry*, M. HansenDepartment of Chemical Engineering, *Department of Computer Science, The University of Tennessee, Knoxville, TN
THE USE OF BOOTSTRAPPING TO ESTIMATE CONDITIONAL PROBABILITY FIELDS FOR SOURCE LOCATIONS OF AIRBORNE POLLUTANTSP.K. Hopke and Chong Le LiDepartments of Chemistry and Civil and Environmental Engineering, Clarkson University Potsdam, NYWilliam Ciszek and Sheldon LandsbergerDepartments of Computer Science and Nuclear Engineering, University of Illinois at Urbana-Champaign, Urbana, IL
- - - - - - - - - - - - - - - - - - - - - - -
Session 8QSAR/Chemometrics in Molecular ModellingChair: Dora [email protected]
APPLICATION OF COMPARITIVE MOLECULAR FIELD ANALYSIS TO CHOLINE ACETYLTRANSFERASE INHIBITORS.G.B.McGaughey, J.P.BowenComputational Center for Molecular Structure and Design, University of Georgia, Athens, GA
APPLICATIONS OF CHEMOMETRICS AND NEURAL NETWORKS TO DRUG FINGERPRINTINGWilliam J. Welsh, Wangkan Lin, Samuel Tersigni, and Radu DutaUniversity of Missouri-St. LouisJames Brower, Thomas Layloff, Walt ZielinskiFDA Division of Drug Analysis, St. Louis, MO
- - - - - - - - - - - - - - - - - - - - - - -
Session 9Detection of Process ShiftsChair: Jim [email protected]
DISTURBANCE DETECTION AND ISOLATION BY PRINCIPAL COMPONENT ANALYSISWenfu Ku, Robert H. Storer, Christos GeorgakisChemical Process Modeling and Control Research Center, Lehigh University, Bethlehem, PA
A NEW USE FOR THE GABRIEL BIPLOT: PROCESS MONITORING OF MULTIVARIATE OBSERVATIONSRoss Sparks, Aloke PhatakCSIRO Division of Mathematics and Statistics, Locked Bag 17, North Ryde, NSW
MULTIVARIATE STATISTICAL METHODS FOR MONITORING CONTINUOUS PROCESSES AND DISTURBANCE DIAGNOSISAnne Raich, Ali CinarDepartment of Chemical Engineering, Illinois Institute of Technology, Chicago, IL
- - - - - - - - - - - - - - - - - - - - - - -Session 10:Second Order Calibration and Three Way AnalysisChair: Age Smilde - [email protected]
MULTIVARIATE CURVE RESOLUTION APPLIED TO SECOND ORDER DATARoma TaulerDepartment of Analytical Chemistry, University of Barcelona, Diagonal 647, Barcelona
MULTI-WAY PARTIAL LEAST SQUARES IN MONITORING BATCH PROCESSESPaul Nomikos & John F. MacGregorDepartment of Chemical Engineering, McMaster University, Hamilton, Ontario
- - - - - - - - - - - - - - - - - - - - - - -
Outliers
Q: How many Californians does it take to change a light bulb?
A: Six. One to turn the bulb, one for support, and four to relate to the experience.
Q: How many big black monoliths does it take to change a light bulb?
A: Sorry, light bulbs are an evolutionary dead end.
Q: How many light bulbs does it take to change a light bulb?
A: One, if it knows its own Goedel number.
Q: How many programmers does it take to screw in a light bulb?
A: None. That's a hardware problem.
Q: How many bureaucrats does it take to screw in a light bulb?
A: Two. One to assure the everything possible is being done while the other screws the bulb into the water faucet.
Q: How many board meetings does it take to get a light bulb changed?
A: This topic was resumed from last week's discussion but is incomplete pending resolution of some action items. It will be continued next week.
Q: How many chemometricians does it take to change a light bulb?
A: None, that's an experimental problem.
Q: How many chemometricians does it take to screw in a light bulb?
A: Two. One to hold the light bulb, one to rotate the coordinate axes.
Q: How many chemometricians does it take to change a light bulb?
A: Eight (plus or minus one). One chemometrician to commission an experimentalist to collect a bunch of random measurements on the light bulb (size, shape, wattage, make, chemical composition of glass, filament type and shape), one to apply meaningless transformations to the data, called preprocessing, another to model the data, uncovering latent-maniacal tendencies related to the underlying physical processes governing light bulb operation, another to dispute the validity of that model, another to display the results by means of pictures with colored dots and lines, another to interpret the plots and ascertain if the bulb is indeed burned out (with 95% confidence) and one (lab manager) to direct the technician to change the bulb.
__________________________________________
Get Serious
If you are a user of PC multivariate statistical software who is tired of switching between Windows desktop and DOS statistics programs with clumsy interfaces and memory limitations, Dr. Rick Requejo of Pattern Recognition Associates says he has some news for you. SIRIUS for Windows is a new Windows version of the multivariate program for the pc computer from Pattern Recognition Systems in Norway. He tells us that principal component analysis, PCR, PLS, SIMCA, and all that alphabet gumbo is now combined with experimental design to provide "integrated data exploration, classification and calibration capabilities for the Windows environment."
For further information:Pattern Recognition AssociatesP.O.Box 9280The Woodlands, Texas 77387Phone: 409-690-0095FAX: 713-298-2259
And now: It's time for Elections! Here are the candidate's statements:
President-Elect
Candidates: Barry M.Wise(unopposed)
Dr. Barry M. Wise is a Senior Research Scientist in the Molecular Science Research Center at Battelle Pacific Northwest Laboratories He is currently Program Manager for the Materials and Interfaces Department. Barry graduated from the University of Washington Chemical Engineering Department in 1991, where he worked with Larry Ricker and Bruce Kowalski. He is an active researcher in chemometrics.
Current projects include using genetic algorithms for non-linear model structure selection and a priori prediction of optimal models in continuum regression. Dr. Wise has been quite active in NAmICS, including being a guest editor of the newsletter and prime organizer of InCINC'94, the First International Chemometrics InterNet Conference, to be held this fall. Barry is also Vice-Chair of this year's Gordon Conference on Statistics in Chemistry and Chemical Engineering.
Barry is committed to making NAmICS an active organization that acts as a focal point for exchange of information related to chemometrics. This includes the newsletter, sponsoring conferences, and using electronic communications for disscussion of issues in chemometrics.
Secretary
Candidates:Dora Schnur(unopposed)
I joined Monsanto's Agricultural Group in 1989 as a computational chemist and took over running the molecular modeling effort in 1992. Previously, I was a post-doctoral fellow with Phil Bowen at the University of North Carolina Laboratory for Molecular Modeling (1988-89) and received my Ph.D. in Organic Chemistry with Dave Dalton at Temple University (Philadephia) in 1989. My
research areas and interests are molecular mechanics force fields, 3D-QSAR and experimental design applied to organic synthesis. I am a charter member of N AmICS and was newletter editor-in-chief for 1992-94. My future NAmICS activities include QSAR session chair for INCINC. My avocations include singing semi-professional opera, particularly lyric-coloratura parts such as Violetta (Traviata) and various Mozart, Donizetti and French opera heroines. Having recently bought a house with a yard full of fruit trees, I am looking forward to indulging my hobby of jam-making this summer provided that my 10 month-old, 11-pound kitten doesn't knock down all the fruit while pretending to be a mountain lion hunting in the trees. My only known addictions are coffee, collecting opera CD's (particularly historic recordings) and collecting far more yarn and fabric for needlework and sewing projects than I can finish with my present lifestyle.
Editor-In-Chief
Candidates: Deborah L. Illman and Marlana Blackburn (joint ticket)(unopposed)
Deborah Illman is Associate Editor in the science and technology group of Chemical & Engineering News, a publication of the American Chemical Society with a circulation of about 150,000. Illman covers topics in analytical, environmental, and process chemistry, in addition to anchoring chemical education for the magazine.
Illman is former Associate Director of the Center for Process Analytical Chemistry (CPAC) at the University of Washington in Seattle, an organization she helped found in 1984. CPAC is a National Science Foundation Industry-University Cooeprative Research Center aimed at developing new sensors for on-line monitoring of chemical processes and in-situ environmental analysis. The center is funded by over 40 sponsors from the chemical industry and federal laboratories, and has successfully developed and transferred many technologies to sponsors, including an on-line near infrared spectrometer, software for multivariate data analysis, and various optical fiber-based sensing devices.
Illman received a bachelor's degree in chemistry
(1976) from the University of WAshington, and a doctorate in physical chemistry from the State University of Campinas, Brazil (1981). She returned to the University of Wsshington chemistry department in 1982 as postdoctoral research associate in the Laboratory for Chemometrics, where she also lectured in chemistry and coauthored a book on Chemometrics.
Marlana Blackburn was born, raised, and educated in the south. After graduating from the University of Florida with a BS in Chemistry, she spent a VERY boring year writing computer programs (in COBOL and RPG using punch cards!) for an insurance company. This experience drove her back to Gainesville and graduate school where she passed the next four years learning atomic spectroscopy in Jim Winefordner's group. Since receiving her PhD in 1978, she has held positions in several government research labs (e.g., at NBS, NIH, NRL). She came to chemometrics late and in a roundabout fashion. In 1987 after sitting in on a numerical analysis class at the University of Minnesota, she began to look for computational problems in analytical chemistry. For the last six years she has been Assistant Professor of Chemistry at Bloomsburg University in Pennsylvania. In the fall she will join the faculty of the College of St. Catherine in St. Paul, MN. One of her primary teaching goals is to incorporate fundamental chemometric principles into the undergraduate analytical chemistry curriculum.
Treasurer
Candidates: Charles Lochmueller(unopposed)
Charles H. Lochmueller (b. May 4, 1940 New York, NY) is Professor of Chemistry and of Biochemical Engineering at Duke University ( Asst. ('69-'74), Assoc.('75-79); Chair, Department of Chemistry (1982-87); Director of Graduate Studies in Biochemical Engineering ( '89- ); Director of the Center for Biochemical Engineering ('90-'93). He came to Duke after two years postdoctoral at Purdue University ('67-'69) with L.B. Rogers and graduate work (M.S. '65, Ph.D. '68) at Fordham University with Michael Cefola. A Fellow of the Royal Chemical Society and of the American Institute of Chemists, he has served as Chairman of the Analytical Division of the American Chemical
Society (1983-84). He is an elected member of the Committee of Revision, United States Pharmacopeial Convention (1985-90;'90-95). He was appointed by the National Research Council to serve on the Analytical Chemistry Panel which advises and evaluates the programs of the Center for Analytical Chemistry - National Bureau of Standards (now NIST) ('87-'90).
He is the Editor-in-Chief of the journal Isolation and Purification and serves/ed on the Editorial Boards of the Journal of Chemical Information and Computer Sciences, the Journal of Chromatographic Science, of Chemometrics, the Editorial Advisory Board for Chemically Modified Surfaces, the Advisory Boards of the Handbook of Trace Substances and of Critical Reviews in Analytical Chemistry and the Yearbook of Chromatography.
In more than 130 published papers, his interests have included such diverse areas as analytical robotics, and the application of chemometrics to retention prediction in RPLC, the analysis of low resolution spectra, and to studies of polymer and rubber pyrolysis and ignition and to proton-induced x-ray emission analysis, mass spectrometry and nuclear magnetic resonance. His main efforts are in the area of separation science, especially in the molecular basis for selectivity in chromatography
It's Election Time!Cast your vote for NAmICS officers by filling in
the very official ballot below and returning it by the deadline indicated to Dave Duewer, Building 222/ Chemistry, Room B-364, National Institute of Standards and Technology, Gaithersburg, Maryland 20899.
Official Ballotof the NAmICS
President-Elect:
Barry M. Wise
Other:________________________________
Secretary:
Dora Schnur
Other:________________________________
Editor-In-Chief:
Deborah Illman and Marlana Blackburn
Other:________________________________
Treasurer:
Charles Lochmueller
Other:________________________________
DEADLINE: JULY 31, 1994
Email your vote to…[email protected]
- or –SnailMail it to…
Dave Lee DuewerBuilding 222/ Chemistry, Room B-156National Institute of Standards and TechnologyGaithersburg, Maryland 20te to899
A PROCLAMATIONon the organization of the
North American Chapter of the International Chemometrics Society(revised from Newsletter #2)
Objective: NAmICS has been established to promote and disseminate knowledge and encourage development and application of chemometrics and allied subjects throughout North America.
Membership: Membership of NAmICS is open to all who are interested in chemometrics. Applications for membership are available from
David DuewerBuilding 222/Chemistry, Room B364National Institute of Standards and TechnologyGaithersburg, Maryland 20899
Official publications: A newsletter is published approximately three times a year.
Yearly dues: Members..........................................$10.00 USStudents and Postdoctoral Fellows.....$6.00 USCorporate.......................................$250.00 US
On majority vote of the elected officers, an individual’s dues may be paid with service to NAmICS or may be temporarily waived.
Unhand those wallets! While we expect you all are eager to financially support NAmICS, one of the first duties for our first set of elected officers was to get us officially chartered as a non-profit organization so that the IRS won’t pull our plug due to technical difficulties. We now have a tax number and dues will hopefully be collected with your 1995 membership.
The officers of NAmICS will have two year terms, with biannual elections held in the first quarter of even-numbered years. In the initial election, both a President and a President-Elect will be elected. In following elections, the President-Elect will become President at the time of issuance of the election ballots.
Elected Officiers TermPresident............................................................2 yearsPresident-Elect...................................................2 yearsExecutive Secretary............................................2 yearsTreasurer
United States and x-North America..............2 yearsCanada........................................................2 years
Editor-in-Chief of Newsletter.............................2 years
Additionally, the elected officers may create a Council on Chemometrics (size and duties as needed) to provide advice, guidance, and required labor. Members will be appointed to the Council by majority vote of the elected officers. They shall serve at the pleasure of the elected officers, for a maximum of five continuous years.
NAmICS Newsletter # 8
Original Guest Editor: Deborah IllmanEditor-in-Chief: Dora Schnur
This version has been re-formatted from not-quite-the-final-version original Word Perfect® files. In addition to my usual “minor typographical edits”, I’ve made changes to reflect the look and content of the distributed version.The original “Page 22” was the “NAmICS Application form”.
David L. Duewer, 18-Jan-2001