The North American Chapter of the International Chemometrics Society

The North American Chapter of the International Chemometrics Society Newsletter # ICS D.L Massart, President Free University of Brussels Institute of Pharmacy Laarbeeklaan 103 B-1090 Brussels, Belgium W Wegscheider, Secretary Institute for Analyt-, Micro- & Radiochemistry Graz University of Technology Technikerstrasse A-8010 Graz, Austria Wegscheider @ rech.tu-graz.ada.at S.D Brown, Course Accreditation Departmentof Chemistry and Biochemistry University of Delaware Newark, DE 19716, USA sdb@brahms.UDel.edu B Vandeginste, Chemometric Abstracts Unilever Research Laboratory PO Box 114 S130 AC Vlaardingen, The Netherlands NAmICS D.B Dahlberg, President Department of Chemistry Lebanon Valley College Annville, PA 17003 Dahlberg@acad.LVC.edu Barry M Wise, President-Elect 4154 Laurel Drive, West Richland, WA 99352 bm_wise@pnl.gov D.M Schnur, Secretary Monsanto Company- U3E 800 N Lindbergh Boulevard St Louis, MO 63167 DMSchn@BB1T.Monsanto.com Illman and Blackburn, Editors-In-Chief Deborah L Illman 4715 N.E 100th, Seattle, WA 98125 illman@netcom.com Marlana B Blackburn Chemistry Department, Box 4076 College of St Catherine St Paul MN 55105-1794 mbblackburn@alex.stkate.edu P.D Wentzell, Treasurer - Canada Department of Chemistry Dalhousie University Halifax, Nova Scotia B3H 4J3 Wentzell@AC.DAL.ca Charles H Lockmueller, Treasurer USA Department of Chemistry Duke University Durham, NC 27708-0346 clochmul@chem.duke.edu NAmICS July 1994 Software Reviews Take a spin with Pirouette Review of Infometrix product Pirouette v 1.2 by Marlana Blackburn The developers of Pirouette aim high; they seek to design a powerful, yet user-friendly software tool that can tackle the most frequent types of chemometric investigations Infometrix achieves this ambitious goal by judiciously selecting techniques and then carefully implementing them Much thought has gone into the development of this high quality 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, Seasholtz waxes philosophic,  Happy Birthday NAmICS, NAmICS Newsletter #9 September 1994 Education,  Letters,  Vendor Information on ListServe, 10 Calendar, 12  Chemometrics On-Line Conference, 13 Software Reviews: Piroutte, cont Pirouette's menudriven 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 MB of memory and 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, 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 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 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 _ 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? 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 833 Seattle, WA 98121 phone: 206-441-4696 fax: 206-441-0841 internet: infomtrx@halcyo n.com _ S i g n e d , E d d i e a n d a L a ti n S q u a r e s 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.] A rose by any other name… Mary Beth Seasholtz, mseasholtz@dow.com, (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 ~ (~ indicates truncation) Solving for x via the normal equations gives calibration problem then was c T x ~T ~ 1~T ~ xˆ ( T T) T c For prediction, the unknown measurement must first be converted to scores by r T P  ~t , un un giving T ~T~ 1~T cˆ un ~tun xˆ run ( T T) T c (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: ~~ ~ T pseudoinverse The calibration equation now reads c = Rb, and bˆ  R  c , where R   V S U c pseudoinverse Prediction is simply T ˆ T ~~ ~ T cˆ un run b run VS U c (2) Equation (2) sure looks different from (1)! Well, recall T could be calculated from an eigenvector problem of RRT T ~ ~~ ~~  ~~ T … in fact T = US and P = V Making these substitutions into (1) give cˆ un run V(( US )( US )) ( US ) c 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? by Bruce R Kowalski Endowed Professor of Chemistry University 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 (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 Outliers 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 Q: How many IBM types does it take to change a light bulb? A: 100 Ten to 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 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 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 Ordering details: by Judith Barnsby BARNSBYJ@rsc.org Window on Chemometrics ISSN 0966-9086 12 issues per year 1994 subscription prices: US $162.00 Canada L95.00 (+GST) EC & Rest of World L90.00 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 & Statistics Calibration & Validation Computer Programs, Expert Systems and Applications Spectrometry Chromatography Other 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 Please order from: The Royal Society of Chemistry Turpin Distribution Services Ltd Blackhorse Road Letchworth, Herts SG6 1HN UK Tel: +44 (0)462 672555 Fax: +44 (0)462 480947 For further details and a sample copy of Window on Chemometrics, please contact: Judith Barnsby The Royal Society of Chemistry Thomas Graham House Science Park, Milton Road Cambridge CB4 4WF UK Tel: +44 (0)223 420066 (Toll free in US: 1-800-473-9234) Fax: +44 (0)223 423429 E-mail: barnsbyj@rsc.org Chemometrics is for undergraduates, too 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: by Nick C Thanasoulias Definition of the chemical problem; [Thanasoulias writes to us from the Chemistry Department at the University of Ioannina, Greece Ed.] Literature study related to the chosen chemical problem (usually covers the last 2-5 years and students are asked to concentrate on review papers); Education 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 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 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 between QSAR 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 Information 301-496-5022; 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 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 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 Chemistry Lebanon Valley College Annville, PA 17003-0501 office: (717)867-6143 fax: (717)867-6124 E-Mail: Dahlberg@ACAD.LVC.EDU Chemometrics Software Upgrade PLS_Toolbox Version 1.4 For Use with MATLAB* Now Available Submitted 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 test data sets The PLS_Toolbox can be obtained on 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 hesitate to contact me Barry M Wise, Ph.D 4154 Laurel Drive West Richland WA 99352 E-mail: 73633.2451@compuserve.com Fax: (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 5.5 is 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 94065 415-598-9860 FAX 415-595-2321 CAMO S/A Olav Tryggvasons gt 24 N-7011 Trondheim Norway Telephone: +47 7351 4966 FAX: +47 7351 4257 _ _ Calendar of Events International Chemometrics Research Meeting July 3-7, 1994, Veldhoven, The Netherlands Secretariat: Laboratory for Analytical Chemistry Faculty of Science Catholic University of Nijmegen Towrnooiveld 6525 ED Nijmegen The Netherlands Telephone: +31 80 653173/92 FAX: +31 80 652653 10th European Symposium on Structure-Activity Relationships; QSAR and Molecular Modelling Sept 4-9, 1994, Barcelona, Spain Secretariat: Department of Medical Informatics Institut Municipal d'Investigacion Medica C/ Doctor Aiguader, 80 E-08003 Barcelona, Spain FAX:+ 34 2213237 E-mail: QSAR10@IMIM.ES 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 Laboratory 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 Wise email: BM_Wise@PNL.gov 5th International Conference on Statistical Methods forthe Environmetnal Sciences and 4th General Meeting of the International Environmetrics Society August 12-15, 1994, Burlington, Ontario, Canada Contact: A.H El-Shaarawi National Water Research Institute P.O Box 5050 Burlington, Ontario L7R 4A6 Canada Telephone: +1 905 3364584 FAX: +1 905 3364989 Email: U101@CS.CCIW.CA _ _ Chemometrics On-line Conference 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 Chair, InCINC'94 On-line Conference Program Session Chemometrics and Education Chair: Bruce Wilson bewilson@EMNGW1.EMN.COM COMPUTATIONAL ANALYTICAL CHEMISTRY AND ITS INTRODUCTION IN UNDERGRADUATE CURRICULA C.H Lochmueller, Charles E Reese Department of Chemistry, Duke University, Durham, NC CHEMOMETRIC TUTORIALS WHY AND HOW? Jerry Workman Perkin Elmer Corp FIVE YEARS OF TEACHING THE ART OF CHEMOMETRICS TO UNDERGRADUATE STUDENTS, D.B.Dahlberg Department of Chemistry, Lebanon Valley College, Annville, PA - Session Chemometrics: Philosophy, History and Directions Chair: Aloke Phatak alokep@SYD.DMS.CSIRO.AU CHEMOMETRICS: WHAT DO WE MEAN WITH IT, AND WHAT DO WE WANT FROM IT? Svante Wold Institute of Chemistry, Umeå University, Umeå WHAT IS CHEMOMETRICS? Tormod Naes, Tomas Isaksson, Harald Martens MATFORSK and Consensus Analysis, Norway Additional contribution expected from Steve Brown - Session Data Rectification/Validation Chair: David Himmelblau twk@axon.che.utexas.edu COMBINED PROCESSING OF EXPERIMENTAL SERIES WITH SYSTEMATIC ERRORS – NONLINEAR PHYSICO-CHEMICAL MODEL WITH LINEAR ERROR MODEL APPLICATION TO VAPORIZATION THERMODYNAMICS OF KCl E.B Rudnyi Department of Chemistry, Moscow State University, Moscow, Russia THE APPLICATION OF NONLINEAR DYNAMIC DATA RECONCILIATION TO PLANT DATA Karen F McBrayer, Thomas F Edgar Department of Chemical Engineering, University of Texas, Austin, TX DYNAMIC DATA RECTIFICATION USING THE EXTENDED KALMAN FILTER AND RECURRENT NEURAL NETWORKS Thomas W Karjala, David M Himmelblau Department of Chemical Engineering, University of Texas, Austin, TX - Session Chemometrics in Dynamic Systems Chair: Ali Cinar CHECINAR@MINNA.ACC.IIT.EDU A COMPARISON OF NEURAL NETWORKS, NON-LINEAR BIASED REGRESSION AND A GENETIC ALGORITHM FOR DYNAMIC MODEL IDENTIFICATION Barry M Wise, Bradley R Holt Pacific Northwest Laboratory, Richland, WA APPLICATION OF EVOLVING FACTOR ANALYSIS IN THERMOCHROMATOGRAPHY Matti Elomaa Department of Polymer Chemistry, University of Helsinki, Meritullinkatu, Finland Charles H Lochmueller Department of Chemistry, Duke University, Durham, NC Mihkel Kaljurand and Mihkel Koel Dept 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 ANALYSIS M.Koel, M.Kaljurand Institute of Chemistry, Academy of Sciences of the Estonian Republic, Tallinn, Estonia C.H Lochmueller, Martin Moebus Department of Chemistry, Duke, University, Durham, NC NONLINEAR TIME SERIES MODELS FOR MULTIVARIABLE DYNAMIC PROCESSES Xianchun Wu, Ali Cinar Department of Chemical Engineering, Illinois Institute of Technology, Chicago, IL - Session Non-Linear Alternative to Neural Networks Chair: Lyle Ungar Ungar@central.cis.upenn.edu SMOOTHERS AND SPLINES FOR NONLINEARIZING PLS AND PCR Ildiko E Frank JerIl, Inc., 790 Esplanada, Stanford, CA THE USE OF A NONPARAMETRIC METHOD FOR MODELING CAPACITY FACTORS IN RP-HPLC Margriet M.W.B Hendriks, Pierre M.J Coenegracht, Durk A Doornbos Research Group Chemometrics, University Center for Pharmacy, University of Groningen, Groningen NONLINEAR PARTIAL LEAST SQUARES USING NEURAL NETWORKS E.C Malthouse, R.S.H Mah*, A.C Tamhane Northwestern University Department of Statistics, *Department of Chemical Engineering CHEMICAL CLASSIFICATION OF MICROSENSOR ARRAY RESPONSES BY AN EMPIRICAL CLUSTERING TECHNIQUE G.C Osbourn*, J.W Bartholomew, G.C Frye, A.J Ricco Sandia National Laboratories, Albuquerque, NM A COMPARISON OF CLASSIFICATION IN ARTIFICIAL INTELLIGENCE, INDUCTION VERSUS NEURAL NETWORKS Mulholland, D.B Hibbert Department of Analytical Chemistry, University of New South Wales, PO Box 1, Kensington, NSW 2033, Australia - Session Chemometrics in Chromatography Chair: Paul Edwards edwardsp@vax.edinboro.edu THE USE OF STATISTICAL TECHNIQUES TO INVESTIGATE THE AGEING PROCESS OF RP-HPLC STATIONARY PHASES Annabel Bolck, Age K Smilde, Chris Bruins, Durk A Doornbos Research 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 Bignell Department of Chemistry, University of Adelaide, South Australia J.F Jackson Department of Viticulture, Oenology and Horticulture, University of Adelaide, South Australia R.B Inman Institute of Molecular Virology, University of Wisconsin, Madison, WI D Brynn Hibbert School of Chemistry, University of New South Wales, Sydney, NSW POWER SPECTRUM BASED ANALYSIS OF MULTICOMPONENT CHROMATOGRAMS Attila Felinger Department of Analytical Chemistry, University of Veszprem, Veszprem, Hungary Maria C Pietrogrande and Francesco Dondi Department 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 Hsu Department of Chemistry, Duke University, Durham, NC - Session General Session Chairs:Charles Lochmueller clochmul@chem.duke.edu Barry M Wise bm_wise@pnl.gov ON THE IDENTIFICATION OF THE NUMBER OF ABSORBING SPECIES AND THE NUMBER OF INDEPENDENT REACTIONS FROM SPECTRAL MEASUREMENT M Amrhein, D Bonvin, B Srinivasan Institut d'Automatique, Ecole Polytechnique Federale de Lausanne, Switzerland M Schumacher Lonza AG, Visp, Switzerland MULTIRESPONSE STEEPEST ASCENT IN A DESIGN SPACE CONSISTING OF BOTH MIXTURE AND PROCESS VARIABLES C.A.A Duineveld, P.M.J Coenegracht Research Group Chemometrics, University Centre for Pharmacy, University of Groningen, Groningen THE USE OF CHEMOMETRIC TECHNIQUES IN PROCESS ANALYTICAL METHOD DEVELOPMENT AND OPERATION Charles E Miller DuPont Packaging and Industrial Polymers Research, PO Box 1089, Orange, TX PARTIAL LEAST SQUARES AND COMPOSITIONAL DATA: PROBLEMS AND ALTERNATIVES John E Hinkle and William S Rayens Department of Statistics, University of Kentucky Lexington, KY CHEMOMETRIC META-ANALYSIS: TRYING TO MAKE SENSE OF DATA FROM DIFFERENT TIMES AND PLACES David Lee Duewer, NIST MODEL VALIDATION IN PRACTICE - AN OVERVIEW OF TECHNIQUES USED IN MULTIVARIATE DATA ANALYSIS Suzanne 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 Hansen Department 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 POLLUTANTS P.K Hopke and Chong Le Li Departments of Chemistry and Civil and Environmental Engineering, Clarkson University Potsdam, NY William Ciszek and Sheldon Landsberger Departments of Computer Science and Nuclear Engineering, University of Illinois at Urbana-Champaign, Urbana, IL - Session QSAR/Chemometrics in Molecular Modelling Chair: Dora Schnur dmschn@BB1T.MONSANTO.COM APPLICATION OF COMPARITIVE MOLECULAR FIELD ANALYSIS TO CHOLINE ACETYLTRANSFERASE INHIBITORS G.B.McGaughey, J.P.Bowen Computational Center for Molecular Structure and Design, University of Georgia, Athens, GA APPLICATIONS OF CHEMOMETRICS AND NEURAL NETWORKS TO DRUG FINGERPRINTING William J Welsh, Wangkan Lin, Samuel Tersigni, and Radu Duta University of Missouri-St Louis James Brower, Thomas Layloff, Walt Zielinski FDA Division of Drug Analysis, St Louis, MO - Session Detection of Process Shifts Chair: Jim Pollard pollard@shell.com DISTURBANCE DETECTION AND ISOLATION BY PRINCIPAL COMPONENT ANALYSIS Wenfu Ku, Robert H Storer, Christos Georgakis Chemical Process Modeling and Control Research Center, Lehigh University, Bethlehem, PA A NEW USE FOR THE GABRIEL BIPLOT: PROCESS MONITORING OF MULTIVARIATE OBSERVATIONS Ross Sparks, Aloke Phatak CSIRO Division of Mathematics and Statistics, Locked Bag 17, North Ryde, NSW MULTIVARIATE STATISTICAL METHODS FOR MONITORING CONTINUOUS PROCESSES AND DISTURBANCE DIAGNOSIS Anne Raich, Ali Cinar Department of Chemical Engineering, Illinois Institute of Technology, Chicago, IL - Session 10: Second Order Calibration and Three Way Analysis Chair: Age Smilde - asmilde@anal.chem.uva.nl MULTIVARIATE CURVE RESOLUTION APPLIED TO SECOND ORDER DATA Roma Tauler Department of Analytical Chemistry, University of Barcelona, Diagonal 647, Barcelona MULTI-WAY PARTIAL LEAST SQUARES IN MONITORING BATCH PROCESSES Paul Nomikos & John F MacGregor Department 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 Associates P.O.Box 9280 The Woodlands, Texas 77387 Phone: 409-690-0095 FAX: 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 Ballot of 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… DLDUEWER@enh.nist.gov - or – SnailMail it to… Dave Lee Duewer Building 222/ Chemistry, Room B-156 National Institute of Standards and Technology Gaithersburg, Maryland 20te to899 A PROCLAMATION on 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 Duewer Building 222/Chemistry, Room B364 National Institute of Standards and Technology Gaithersburg, Maryland 20899 Official publications: A newsletter is published approximately three times a year Yearly dues: Members $10.00 US Students and Postdoctoral Fellows $6.00 US Corporate $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 evennumbered 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 Term President years President-Elect years Executive Secretary years Treasurer United States and x-North America years Canada years Editor-in-Chief of Newsletter 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 # Original Guest Editor: Deborah Illman Editor-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 ... _ _ Chemometrics On-line Conference held this fall The North American Chapter of the International Chemometrics Society and Elsevier are sponsoring the First International Chemometrics. .. 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... National Institute of Standards and Technology Gaithersburg, Maryland 20te to899 A PROCLAMATION on the organization of the North American Chapter of the International Chemometrics Society (revised