A program for generating empirical spectrum classification schemes

Programs are described which derive a set of compound classification tests from data specifying a required classification hierarchy and example low resolution mass spectra. The generated tests are expressed in terms of conventional operations such as searching for a molecular ion and checking for fragment ions. These tests can be used in a laboratory computer to give real-time classification of spectra collected by gas chromatography mass spectrometry.     

Evaluation of classification results with the disjoint classification program SOLOMON

Practical application of pattern recognition techniques is often limited because of the way in which variables are selected and the need for supplementation of missing data. The software package comprising the MICA transformation technique and the SOLOMON classification program is extended to include an algorithm for estimating and supplementing missing data. The performance of this package is compared with that of known classification techniques on simulated data sets. The supplementation algorithm is tested with a data set for hyperlipoproteinemia patients.     

A program for evaluation of NAA spectra

A program for qualitative and quantitative analysis of spectra obtained by comparative NAA method is described. It includes peak search, calculation of essential peak parameters, isotope identification and estimation of concentrations and/or detection limits of nuclides, corrected for cooling time and decay during measurement. Corrections for blank samples and peak interference are performed as well. Uncertainties estimation of final results are performed according to the error propagation law. The program is aimed to help an experienced user to calculate the results of analysis but the possibility for automatic mode for routine analysis is provided as well.Supported by International Atomic Energy Agency through the research contract 7268/RB.     

Preliminary evaluation of laser-induced breakdown spectroscopy for tissue classification

Laser-induced breakdown spectroscopy (LIBS) is an on-line, real-time technology that can produce immediate information about the elemental contents of tissue samples. We have previously shown that LIBS may be used to distinguish cancerous from non-cancerous tissue. In this work, we study LIBS spectra produced from chicken brain, lung, spleen, liver, kidney and skeletal muscle. Different data processing techniques were used to study if the information contained in these LIBS spectra is able to differentiate between different types of tissue samples and then identify unknown tissues. We have demonstrated a clear distinguishing between each of the known tissue types with only 21 selected analyte lines from each observed LIBS spectrum. We found that in order to produce an analytical model to work well with new sample we need to have representative training data to cover a wide range of spectral variation due to experimental or environmental changes.     

A program for evaluation of gamma-spectra (ANA)

A program (ANA) for evaluation of -spectra is reported. The program is based on a nonlinear least-squares procedure which uses a composite algorithm called KATOK. The program includes spectrum visualization, energy and FWHM calibration, automatic peak search with data preparation, possibility for manual data preparation and utilities.     

The sca program : an easy way for the conformational evaluation of polycyclic molecules

The present version of the SCA (Systematic Conformational Analysis) program analyzes polycyclic derivatives containing five-, six and seven membered rings and derives a restricted number of best candidates for further energy minimization. The program requires an IBM PC, XT, AT or compatible equipped with a mouse, an enhanced graphics adaptor and an EGA monitor. Molecules are entered as two-dimensional structural diagrams. The program will then select the most representative geometries among all possible basic conformations together with an approximate conformational energy. Conformations so obtained may be viewed three-dimensionally. Alternatively, input files may be created for direct further molecular mechanics treatment. The latter link makes it possible to perform energy minimizations on structurally complex and flexible molecules in the reassuring confidence that all best candidates were considered.     

Reference materials for the radionuclide program – performance evaluation samples

 The U.S. Food and Drug Administration's (FDA) Radionuclides in Food Program was reinstituted in 1973, expanded in 1975 and again in 1990, to its present status. The need for reference materials for radionuclides in food samples was recognized as early as 1962. There were no available reference materials for these types of samples at that time. The materials developed to assure that the results being obtained were acceptable were primarily milk, water and food. The radionuclides of interest were iodine-131, cesium-137 and other short-lived radionuclides found in fission products. These were first issued through the then Health, Education and Welfare Department's Analytical Quality Control Program and, later, in 1970 through the Environmental Protection Agency (EPA). In November 1998, the EPA discontinued this program. The FDA is proposing to reinstitute part of this program, as a primary laboratory, traceable to the National Institute of Technology (NIST) and included in this, the FDA proposes to supply the States and/or their contractors with low-level standards and with milk- and water intercomparison samples. It will also use these results where possible as collaborative studies to validate some of the more recent methods adopted by the American Society for Testing and Materials (ASTM), American Public Health Association (APHA) and Association of Official Analytical Chemists International (AOAC, Int'l.) The FDA will also supply low-level standards to compliment these programs as did the EPA. It is expected that these samples will serve as performance evaluation samples for the States programs.     

Desk-computer program for evaluation of complex equilibria from spectrophotometric data

The program MINISPEF is designed to run on a desk-computer with 16 kbytes of memory. It can calculate the optimum values of the overall stability constants and molar absorptivities of a maximum of 8 species with compositions M_qL_pH_r (r or q can be zero), or the mixed-ligand complexes formed in the system MA_N + MB_N (N = 2, 3 or 4), from spectrophotometric data. The program is based on the authors' program MINIPOT.     

A combined linear and nonlinear factor analysis program package for chemical data evaluation

An underlying variable factor analysis program (UVFA) is described. The theories of principal component analysis and nonlinear least-squares projection techniques are outlined and compared. Several applications from various chemical fields are presented which show that a complete analysis of the underlying structure and dimensionality of a chemical data set should always include these nonlinear projection techniques.     

Semidirect MP2 gradient evaluation on workstation computers: The MPGRAD program

A semidirect implementation of the closed-shell MP2 gradient for efficient use on workstation computers is presented. The approach is based on the algorithm proposed by Frisch and coworkers but includes several modifications to reduce disk storage requirements and exploits nonabelian point group symmetry. The performance of the resulting program MPGRAD (BIOSYM Corp., San Diego, CA) is demonstrated in applications to the molecules [AlSi(CH₃)₃]₄ and ferrocene. The largest calculation involved 492 basis functions and was carried out on IBM RS/6000 workstations with memory sizes of 32 and 128 Mb. The ratio of CPU to wallclock time exceeds 90% in all typical applications. © 1993 John Wiley & Sons, Inc.     

A computer program for a general case evaluation of the expanded uncertainty

The ISO Guide to the Expression of Uncertainty in Measurement provides a uniform method for the evaluation of combined standard uncertainty of a measurand whose expectation and standard deviation are stable over the measurement period. However, the method provided for the evaluation of the expanded uncertainty is not complete. Particularly, it does not include the case where the contributing components are correlated. Also, the probability distribution of the combined uncertainty must be close to a Normal distribution otherwise other methods must be used. The method presented here, which is implemented in a computer program, is based on a combination of the ISO guide method and Monte-Carlo simulation.The Monte-Carlo Simulation can obtain the data needed for the evaluation of the expanded and standard uncertainties directly from the measurement equation (that defines the measurand in terms of the contributing components) or from a spreadsheet-like format. Some sample results obtained by the computer program using both methods are compared and discussed.     

Discussion on classification and performance evaluation of diversified testing procedures

Accreditation and Quality Assurance - More and more testing procedures with different principles are being developed covering both quantitative and qualitative analyses. To ensure the reliability...     

Utilizing FTIR-ATR spectroscopy for classification and relative spectral similarity evaluation of different Colletotrichum coccodes isolates

Colletotrichum coccodes (C. coccodes) is a pathogenic fungus which causes anthracnose on tomatoes and black dot disease in potatoes. It is important to differentiate among these isolates and to detect the origin of newly discovered isolates, in order to treat the disease in its early stages. However, distinguishing between isolates using common biological methods is time-consuming, and not always available. We used Fourier Transform Infra-Red (FTIR)-Attenuated Total Reflectance (ATR) spectroscopy and advanced mathematical and statistical methods to distinguish between different isolates of C. coccodes. To our knowledge, this is the first time that FTIR-ATR spectroscopy was used, combined with multivariate analysis, to classify such a large number of 15 isolates belonging to the same species. We obtained a success rate of approximately 90% which was achieved using the region 800-1775 cm(-1). In addition we succeeded in determining the relative spectral similarity between different fungal isolates by developing a new algorithm. This method could be an important potential diagnostic tool in agricultural research, since it may outline the extent of the biological similarity between fungal isolates. Based on the PCA calculations, we grouped the fifteen isolates included in this study into four different degrees of similarity.     

Solomon,a classification program based on a statistical multivariate disjoint model

An algorithm called SOLOMON is presented for classification of patterns in multi-dimensional space. This is achieved by constructing a statistical model based on multivariate analysis of the classes under study. The disjoint multivariate analysis is done by using multi-inductive component analysis which has many advantages compared to techniques such as principal components analysis. A weghting algorithm is described for optimum classification results.     

The ROBIA program for predicting organic reactivity

A program to predict organic reactions, ROBIA, has been developed. It achieves reaction prediction on the basis of coded rules and molecular modeling calculations, generating possible transition states, intermediates, and products given the starting material and reaction conditions. The program generates all possible reaction pathways, on the basis of the selected transformations within its database, and evaluates them selecting the most feasible ones. The program has been successfully tested against several examples.     

A program for the kinetic evaluation of thermoanalyttcal curves obtained by differential scanning calorimetry

The kinetic investigation of thermoanalytical curves of complex chemical reactions requires tedious calculation and large arrays for data processing. A computer program (BASIC) has been developed with which the intricate thermoanalytical curves can be resolved into individual signals and the signals evaluated kinetically according to several mathematical expressions. A computed simulation of the thermoanalytical curves using the parameters of bulk reation is carried out to verify the validity of the parameters. The method is suitable for determining the amount of isothermal conversion in dynamically observed curing reaction of epoxy resins.     

A computer program for automated data evaluation to support in vitro higher-throughput screening for drug metabolism and pharmacokinetics attributes

With the advances in analytical techniques, higher-throughput screening for drug metabolism and pharmacokinetics (DMPK) attributes has become an integral part of drug discovery. However, as the number of compounds increases, the volume of data that needs to be processed and evaluated increases exponentially. As a result, a major challenge for the analytical chemist is how to quickly process the vast amount of data so as to keep up with the throughput of the screening assay. We have developed a customized computer program for automated evaluation of the liquid chromatography/tandem mass spectrometric (LC/MS/MS) data generated from the in vitro DMPK screening assays. This program performs automatic data processing and quality control. It identifies analytical anomalies, such as low internal standard intensity and poor reproducibility of replicates. All analytical anomalies for individual compounds are summarized into an 'E-Log' in a color-coded format for reviewing. With the use of this program and other supporting software, data processing and evaluation for up to 100 compounds are accomplished in several minutes.     

Application of a new AMIQAS computer program for integrated quality control, method evaluation and proficiency testing

Summary The computer program AMI - Quality Assessment Scheme (AMIQAS) was designed to give easy statistical management of analytical data in relation to method evaluation, internal quality control and proficiency testing. The program is designed in accordance with the recommendation of the ISO 5725 guideline and other official recommendations. The program consists of a database, test for outliers, statistics and graphs for evaluation of an analytical method for chemical, biological and environmental analysis, different control charts to be used in day-to-day internal quality control (Shewhart charts and z-charts). Finally the program has facilities to perform proficiency testing (also called external quality control) and produce the relevant evaluation reports for the documentation of method performance and quality control of results of measurements. The present paper demonstrates the applicability of the AMIQAS program for integrated method evaluation, internal quality control and proficiency testing using the determination of the concentration of lead in human whole blood as the numerical example.     

The evaluation of probabilistic classification methods : Part 1. A monte carlo study with ALLOC

Probabilistic classification (i.e., classification of individuals into one of several groups by assigning probabilities of classification to each individual) is desirable when the main interest is in individuals rather than the whole group. The evaluation of probabilistic assignments is described in detail, including statistical features such as measures for the sharpness of the classification, the predictive ability and the reliability of the probability values. In a simulation study, the influence of the objects—variable ratio and the interclass distance on the results was examined for the training data themselves (resubstitution method), an independent test set, and a pseudo-independent test set created from the training set (leave-one-out method). The results indicate that the leave-one-method can often be used instead of an independent test set. In many cases, the assignments cited as probabilities are not probabilities at all, because the classification system is too over-confident.