Science.gov

Sample records for metodo quimiometrico simca

  1. APPLICATION OF SIMCA (SOFT INDEPENDENT MODELING OF CLASS ANALOGY) PATTERN RECOGNITION TO AIR POLLUTANT ANALYTICAL DATA

    EPA Science Inventory

    The SIMCA 3B computer program is a modular, graphics oriented pattern recognition package which can be run on a microcomputer with limited memory, e.g. an Osborne 1 with 64K memory. Principal component analysis is used to classify data with this program. The SIMCA program was use...

  2. COMPARISON OF SIMCA PATTERN RECOGNITION & LIBRARY SEARCH IDENTIFICATION OF HAZARDOUS COMPOUNDS FROM MASS SPECTRA

    EPA Science Inventory

    SIMCA pattern recognition methods have been applied to mass spectral data from a target list of hazardous chemicals. cheme has been proposed for classification and identification of five classes of compounds including aromatics, chlorocarbons, bromocarbons, hydrocarbons, and poly...

  3. COMPARISON OF SIMCA PATTERN RECOGNITION AND LIBRARY SEARCH IDENTIFICATION OF HAZARDOUS COMPOUNDS FROM MASS SPECTRA

    EPA Science Inventory

    SIMCA pattern recognition methods have been applied to mass spectral data from a target list of hazardous chemicals. cheme has been proposed for classification and identification of five classes of compounds including aromatics, chlorocarbons, bromocarbons, hydrocarbons, and poly...

  4. [Research on the Source Identification of Mine Water Inrush Based on LIF Technology and SIMCA Algorithm].

    PubMed

    Yan, Peng-cheng; Zhou, Meng-ran; Liu, Qi-meng; Zhang, Kai-yuan; He, Chen-yang

    2016-01-01

    Rapid source identification of mine water inrush is of great significance for early warning and prevention in mine water hazard. According to the problem that traditional chemical methods to identify source takes a long time, put forward a method for rapid source identification of mine water inrush with laser induced fluorescence (LIF) technology and soft independent modeling of class analogy (SIMCA) algorithm. Laser induced fluorescence technology has the characteristics of fast analysis, high sensitivity and so on. With the laser assisted, fluorescence spectrums can be collected real-time by the fluorescence spectrometer. According to the fluorescence spectrums, the type of water samples can be identified. If the database is completed, it takes a few seconds for coal mine water source identification, so it is of great significance for early warning and post-disaster relief in coal mine water disaster. The experiment uses 405 nm laser emission laser into the 5 kinds of water inrush samples and get 100 groups of fluorescence spectrum, and then put all fluorescence spectrums into preprocessing. Use 15 group spectrums of each water inrush samples, a total of 75 group spectrums, as the prediction set, the rest of 25 groups spectrums as the test set. Using principal component analysis (PCA) to modeling the 5 kinds of water samples respectively, and then classify the water samples with SIMCA on the basis of the PCA model. It was found that the fluorescence spectrum are obvious different of different water inrush samples. The fluorescence spectrums after preprocessing of Gaussian-Filter, under the condition of the principal component number is 2 and the significant level α = 5%, the accuracy of prediction set and testing set are all 100% with the SIMCA to classify the water inrush samples. PMID:27228775

  5. [Research on spectra recognition method for cabbages and weeds based on PCA and SIMCA].

    PubMed

    Zu, Qin; Deng, Wei; Wang, Xiu; Zhao, Chun-Jiang

    2013-10-01

    In order to improve the accuracy and efficiency of weed identification, the difference of spectral reflectance was employed to distinguish between crops and weeds. Firstly, the different combinations of Savitzky-Golay (SG) convolutional derivation and multiplicative scattering correction (MSC) method were applied to preprocess the raw spectral data. Then the clustering analysis of various types of plants was completed by using principal component analysis (PCA) method, and the feature wavelengths which were sensitive for classifying various types of plants were extracted according to the corresponding loading plots of the optimal principal components in PCA results. Finally, setting the feature wavelengths as the input variables, the soft independent modeling of class analogy (SIMCA) classification method was used to identify the various types of plants. The experimental results of classifying cabbages and weeds showed that on the basis of the optimal pretreatment by a synthetic application of MSC and SG convolutional derivation with SG's parameters set as 1rd order derivation, 3th degree polynomial and 51 smoothing points, 23 feature wavelengths were extracted in accordance with the top three principal components in PCA results. When SIMCA method was used for classification while the previously selected 23 feature wavelengths were set as the input variables, the classification rates of the modeling set and the prediction set were respectively up to 98.6% and 100%. PMID:24409729

  6. Identification of primary tumors of brain metastases by SIMCA classification of IR spectroscopic images.

    PubMed

    Krafft, Christoph; Shapoval, Larysa; Sobottka, Stephan B; Geiger, Kathrin D; Schackert, Gabriele; Salzer, Reiner

    2006-07-01

    Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the origin of brain metastases. IR spectroscopic images of 4 by 4 mm2 tissue areas were recorded in transmission mode by a FTIR imaging spectrometer coupled to a focal plane array detector. Unsupervised cluster analysis revealed variances within each cryosection. Selected clusters of five IR images with known diagnoses trained a supervised classification model based on the algorithm soft independent modeling of class analogies (SIMCA). This model was applied to distinguish normal brain tissue from brain metastases and to identify the primary tumor of brain metastases in 15 independent IR images. All specimens were assigned to the correct tissue class. This proof-of-concept study demonstrates that IR spectroscopy can complement established methods such as histopathology or immunohistochemistry for diagnosis. PMID:16787638

  7. CLASSIFICATION OF BINARY MASS SPECTRA OF TOXIC COMPOUNDS WITH AN INDUCTIVE EXPERT SYSTEM AND COMPARISON WITH SIMCA CLASS MODELING (JOURNAL VERSION)

    EPA Science Inventory

    The performance of an inexpensive, inductive rule-building expert system, 1ST CLASS, using the ID3 algorithm was compared to that of SIMCA class modeling in classifying the binary mass spectra of 78 toxic and related compounds. The compressed mass spectra consisted of 17 masses c...

  8. Trials and tribulations of 'omics data analysis: assessing quality of SIMCA-based multivariate models using examples from pulmonary medicine.

    PubMed

    Wheelock, Åsa M; Wheelock, Craig E

    2013-11-01

    Respiratory diseases are multifactorial heterogeneous diseases that have proved recalcitrant to understanding using focused molecular techniques. This trend has led to the rise of 'omics approaches (e.g., transcriptomics, proteomics) and subsequent acquisition of large-scale datasets consisting of multiple variables. In 'omics technology-based investigations, discrepancies between the number of variables analyzed (e.g., mRNA, proteins, metabolites) and the number of study subjects constitutes a major statistical challenge. The application of traditional univariate statistical methods (e.g., t-test) to these "short-and-wide" datasets may result in high numbers of false positives, while the predominant approach of p-value correction to account for these high false positive rates (e.g., FDR, Bonferroni) are associated with significant losses in statistical power. In other words, the benefit in decreased false positives must be counterbalanced with a concomitant loss in true positives. As an alternative, multivariate statistical analysis (MVA) is increasingly being employed to cope with 'omics-based data structures. When properly applied, MVA approaches can be powerful tools for integration and interpretation of complex 'omics-based datasets towards the goal of identifying biomarkers and/or subphenotypes. However, MVA methods are also prone to over-interpretation and misuse. A common software used in biomedical research to perform MVA-based analyses is the SIMCA package, which includes multiple MVA methods. In this opinion piece, we propose guidelines for minimum reporting standards for a SIMCA-based workflow, in terms of data preprocessing (e.g., normalization, scaling) and model statistics (number of components, R2, Q2, and CV-ANOVA p-value). Examples of these applications in recent COPD and asthma studies are provided. It is expected that readers will gain an increased understanding of the power and utility of MVA methods for applications in biomedical research

  9. GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA)

    PubMed Central

    2011-01-01

    Background The goal of metabolomics analyses is a comprehensive and systematic understanding of all metabolites in biological samples. Many useful platforms have been developed to achieve this goal. Gas chromatography coupled to mass spectrometry (GC/MS) is a well-established analytical method in metabolomics study, and 200 to 500 peaks are routinely observed with one biological sample. However, only ~100 metabolites can be identified, and the remaining peaks are left as "unknowns". Result We present an algorithm that acquires more extensive metabolite information. Pearson's product-moment correlation coefficient and the Soft Independent Modeling of Class Analogy (SIMCA) method were combined to automatically identify and annotate unknown peaks, which tend to be missed in routine studies that employ manual processing. Conclusions Our data mining system can offer a wealth of metabolite information quickly and easily, and it provides new insights, particularly into food quality evaluation and prediction. PMID:21542920

  10. Estudio numerico y experimental del proceso de soldeo MIG sobre la aleacion 6063--T5 utilizando el metodo de Taguchi

    NASA Astrophysics Data System (ADS)

    Meseguer Valdenebro, Jose Luis

    improvement on mechanical properties in aluminum metal joint. Los procesos de soldadura por arco electrico representan unas de las tecnicas mas utilizadas en los procesos de fabricacion de componentes mecanicos en la industria moderna. Los procesos de soldeo por arco se han adaptado a las necesidades actuales, haciendose un modo de fabricacion flexible y versatil. Los resultados obtenidos numericamente en el proceso de soldadura son validados experimentalmente. Los principales metodos numericos mas empleados en la actualidad son tres, metodo por diferencias finitas, metodos por elementos finitos y metodo por volumenes finitos. El metodo numerico mas empleado para el modelado de uniones soldadas, es el metodo por elementos finitos, debido a que presenta una buena adaptacion a las condiciones geometricas y de contorno ademas de que existe una diversidad de programas comerciales que utilizan el metodo por elementos finitos como base de calculo. Este trabajo de investigacion presenta un estudio experimental de una union soldada mediante el proceso MIG de la aleacion de aluminio 6063-T5. El metodo numerico se valida experimentalmente aplicando el metodo de los elementos finitos con el programa de calculo ANSYS. Los resultados experimentales obtenidos son: las curvas de enfriamiento, el tiempo critico de enfriamiento t4/3, geometria del cordon, microdurezas obtenidas en la union soldada, zona afectada termicamente y metal base, dilucion del proceso, areas criticas intersecadas entre las curvas de enfriamiento y la curva TTP. Los resultados numericos son: las curvas del ciclo termico, que representan tanto el calentamiento hasta alcanzar la temperatura maxima y un posterior enfriamiento. Se calculan el tiempo critico de enfriamiento t4/3, el rendimiento termico y se representa la geometria del cordon obtenida experimentalmente. La zona afectada termicamente se obtiene diferenciando las zonas que se encuentran a diferentes temperaturas, las areas criticas intersecadas entre las

  11. Estudio numerico y experimental del proceso de soldeo MIG sobre la aleacion 6063--T5 utilizando el metodo de Taguchi

    NASA Astrophysics Data System (ADS)

    Meseguer Valdenebro, Jose Luis

    improvement on mechanical properties in aluminum metal joint. Los procesos de soldadura por arco electrico representan unas de las tecnicas mas utilizadas en los procesos de fabricacion de componentes mecanicos en la industria moderna. Los procesos de soldeo por arco se han adaptado a las necesidades actuales, haciendose un modo de fabricacion flexible y versatil. Los resultados obtenidos numericamente en el proceso de soldadura son validados experimentalmente. Los principales metodos numericos mas empleados en la actualidad son tres, metodo por diferencias finitas, metodos por elementos finitos y metodo por volumenes finitos. El metodo numerico mas empleado para el modelado de uniones soldadas, es el metodo por elementos finitos, debido a que presenta una buena adaptacion a las condiciones geometricas y de contorno ademas de que existe una diversidad de programas comerciales que utilizan el metodo por elementos finitos como base de calculo. Este trabajo de investigacion presenta un estudio experimental de una union soldada mediante el proceso MIG de la aleacion de aluminio 6063-T5. El metodo numerico se valida experimentalmente aplicando el metodo de los elementos finitos con el programa de calculo ANSYS. Los resultados experimentales obtenidos son: las curvas de enfriamiento, el tiempo critico de enfriamiento t4/3, geometria del cordon, microdurezas obtenidas en la union soldada, zona afectada termicamente y metal base, dilucion del proceso, areas criticas intersecadas entre las curvas de enfriamiento y la curva TTP. Los resultados numericos son: las curvas del ciclo termico, que representan tanto el calentamiento hasta alcanzar la temperatura maxima y un posterior enfriamiento. Se calculan el tiempo critico de enfriamiento t4/3, el rendimiento termico y se representa la geometria del cordon obtenida experimentalmente. La zona afectada termicamente se obtiene diferenciando las zonas que se encuentran a diferentes temperaturas, las areas criticas intersecadas entre las

  12. Atlas de aves: Un metodo para documentar distribucion y seguir poblaciones

    USGS Publications Warehouse

    Robbins, C.S.; Dowell, B.A.; Dawson, D.K.

    1988-01-01

    Los Atlas de Aves son proyectos nacionales o regionalies para trazar en mapas la distribucion en reproduccion de cada especie de ave. Ese procedimiento se esta usando en Europa, Australia, Nueva Zelanda, Norteamerica, y partes de Africa. El tama?o de los cuadrados varia de medio grado de latitud y Iongitud hasta 5 x 5 km. El trabajo de campo de cada proyecto exige aproxlmadamente cinco a?os, pero los aficionados pueden llevar a cabo la mayor parte del trabajo. Es posible almacenar los resultados en un computador personal. Hay muchos beneficios: (I) se presenta la distribucion corriente de las aves de la nacion, del estado, o de la Iocalidad; (2) se desarrolla nueva informacion especialmente sobre especies raras o en peligro; (3) se descubren areas que tienen una avlfauna sobresaliente o habitats raros y ayuda a su proteccion, (4) se documentan cambios de dlstribucion; (5) se pueden usar para documentar cambios de poblacion, especialmente en los tropicos donde otros metodos son mas dificiles de usar porque hay muchas especies y no hay muchos observadores calificados en la identificacion de sonidos de las aves; (6) son proyectos buenos de investigacion para estudiantes graduados; (7) los turistas y los jefes de excursiones de historia natural pueden contribuir con muchas informaciones

  13. The Montessori System of Education: An Examination of Characteristic Features Set Forth in Il Metodo Della Pedagogica Scientifica. Bulletin, 1912, No. 17. Whole Number 489

    ERIC Educational Resources Information Center

    Smith, Anna Tolman

    1912-01-01

    The publication of "Il metodo della pedagogica scientifica," by Dr. Maria Montessori, docent in the University of Rome, giving a full account of the inception and development of the system of education of which she is the author and the simultaneous translation of the work into English and German are events so unusual as to challenge attention.…

  14. SIMCA T 1.0: A SAS Computer Program for Simulating Computer Adaptive Testing

    ERIC Educational Resources Information Center

    Raiche, Gilles; Blais, Jean-Guy

    2006-01-01

    Monte Carlo methodologies are frequently applied to study the sampling distribution of the estimated proficiency level in adaptive testing. These methods eliminate real situational constraints. However, these Monte Carlo methodologies are not currently supported by the available software programs, and when these programs are available, their…

  15. DETERMINATION OF CHEMICAL CLASSES FROM MASS SPECTRA OF TOXIC ORGANIC COMPOUNDS BY SIMCA PATTERN RECOGNITION AND INFORMATION THEORY

    EPA Science Inventory

    The low resolution mass spectra of a set of 78 toxic volatile organic compounds were examined for information concerning chemical classes. These compounds were predominately chloro- and/or bromoaromatics, -alkanes, or -alkenes, which are routinely sought at trace levels in ambien...

  16. Selection of Haploid Maize Kernels from Hybrid Kernels for Plant Breeding Using Near-Infrared Spectroscopy and SIMCA Analysis

    SciTech Connect

    Jones, Roger W.; Reinot, Tonu; Frei, Ursula K.; Tseng, Yichia; Lübberstedt, Thomas; McClelland, John F.

    2012-04-01

    Samples of haploid and hybrid seed from three different maize donor genotypes after maternal haploid induction were used to test the capability of automated near-infrared transmission spectroscopy to individually differentiate haploid from hybrid seeds. Using a two-step chemometric analysis in which the seeds were first classified according to genotype and then the haploid or hybrid status was determined proved to be the most successful approach. This approach allowed 11 of 13 haploid and 25 of 25 hybrid kernels to be correctly identified from a mixture that included seeds of all the genotypes.

  17. El Metodo Llamado Proyecto (The Project Approach). ERIC Digest.

    ERIC Educational Resources Information Center

    Katz, Lilian G.

    A project is an in-depth investigation of a topic worth learning more about, usually undertaken by a group of children within a class. The goal of a project is to learn more about a topic rather than to find answers to questions posed by a teacher. Project work is complementary to the systematic parts of a curriculum. Whereas systematic…

  18. Ensenanza de la Astronomia a Traves de Metodos no Tradicionales

    NASA Astrophysics Data System (ADS)

    Tignanelli, H. L.

    1990-11-01

    REUMEN: Se presentan los aspects pri nc ipales de a ense? anza de la astronor:. a para -; s. En esta cc .unicaci #n, 5 ha especial mfasis em Ia descripci':"n de las caracteristicas y las posibi lidades peda gicas de los no tradicionales de aprendiZaje. E' : In the following the principal aspects of teaching of astrono ..y for children) are oresented. In this paper, special emphasis has been given to desc rib the characteristics and pedagogical possibilities of the non traditional methods of learning. : TEACHING

  19. Problemi e di Fisica e Astronomia ed il metodo di Gerberto docente

    NASA Astrophysics Data System (ADS)

    Sigismondi, Costantino

    2015-04-01

    Teaching Physics and Astronomy to pupils of 14-19 years old requires nowadays a continuous upgrade of knowledge as well as a capacity of selecting topics. The art of presenting arguments made Gerbert the teacher Rogatus a Pluribus in the end of X century and it is still actual; the proposed series of problems wants to link everyday experiences with the mathematical models of the phenomena, to allow the prediction and explanation of the experimental data. These problems of Physics and Astronomy are “observation oriented”, as the method of Gerbert was to start from the experience to get the theory, and not viceversa. Physics is much more than an “applied Algebra”. In the dispute of Ravenna (980) between Gerbert and Otric from Magdeburg, the primacy of Physics with respect to Mathematics was discussed. In the Italian secondary technical schools there are laboratory activities, while there is nothing similar for Lyceums and for the Astronomy teaching which is limited to a series of notions to be learned without any kind of observation; considered too difficult in polluted skyes.

  20. La pronunciacion espanola y los metodos de investigacion. (Spanish Pronunciation and Methods of Investigation.)

    ERIC Educational Resources Information Center

    Torreblanca, Maximo

    1988-01-01

    Discusses the validity of studies of Spanish pronunciation in terms of research methods employed. Topics include data collection in the laboratory vs. in a natural setting; recorded vs. non-recorded data; quality of the recording; aural analysis vs. spectrographic analysis; and transcriber reliability. Suggestions for improving data collection are…

  1. Espectroscopia infravermelha para a determinacao de carbono do solo: Perspectiva de um metodo economicamente viavel e ambientalmente seguro

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Kyoto Protocol is an agreement among many of the world’s nations to, among other things, reduce atmospheric carbon dioxide concentrations in order to reduce global warming. One potential method to do so is to sequester carbon in soils. This has had the effect of stimulating the establishment of ...

  2. Modelos para la Unificacion de Conceptos, Metodos y Procedimientos Administrativos (Guidelines for Uniform Administrative Concepts, Methods, and Procedures).

    ERIC Educational Resources Information Center

    Serrano, Jorge A., Ed.

    These documents, discussed and approved during the first meeting of the university administrators affiliated with the Federation of Private Universities of Central America and Panama (FUPAC), seek to establish uniform administrative concepts, methods, and procedures, particularly with respect to budgetary matters. The documents define relevant…

  3. Las historias de la narrativa hispanoamericana: Criterios, metodos y ausencias. (Histories of the Latin-American Narrative: Criteria, Methods, and Absences).

    ERIC Educational Resources Information Center

    Zavalo, Lauro

    This paper explains that materials on the teaching of Latin-American literature are sparse, even though most researchers in the field will dedicate much of their time to teaching. The paper adds that, in scholarly journals, little attention is given to teaching literature, and the topic is also absent from most academic congresses. The paper then…

  4. "Mastery Learning" Como Metodo Psicoeducativo para Ninos con Problemas Especificos de Aprendizaje. ("Mastery Learning" as a Psychoeducational Method for Children with Specific Learning Problems.)

    ERIC Educational Resources Information Center

    Coya, Liliam de Barbosa; Perez-Coffie, Jorge

    1982-01-01

    "Mastery Learning" was compared with the "conventional" method of teaching reading skills to Puerto Rican children with specific learning disabilities. The "Mastery Learning" group showed significant gains in the cognitive and affective domains. Results suggested Mastery Learning is a more effective method of teaching reading skills to children…

  5. Metodo de Archivar las Observaciones del Comportamiento del Nino, Como Guia para Entenderlo Mejor (Methods of Recording Observations of Children's Behavior, A Guide for Better Understanding)

    ERIC Educational Resources Information Center

    Stamp, Isla M.

    1971-01-01

    Copies of the Behaviour Study Technique described in this article may be obtained in English from the Australian Council for Educational Research, Frederick St., Hawthorn, Victoria, Australia 3122. (RY)

  6. Lengua nacional: Fichas de trabajo 1. Metodo de lectura y escritura (National Language: Workbook 1. A Method of Reading and Writing).

    ERIC Educational Resources Information Center

    Peniche Leger, Maria Elena, Ed.

    This consumable, graded workbook can be used for exercises, tests, and individualized learning. Each level contains 30 units divided into four groups of exercises: reading analysis, grammar, composition, and spelling. Ten general tests are also included. For the accompanying reader, see FL 004 047. (Author/SK)

  7. Metodo y Proceso de la Investigacion Participativa en la Capacitacion Rural (The Method and Process of Participatory Research in Rural Leadership Training). Cuadernos del CREFAL 19.

    ERIC Educational Resources Information Center

    de Schutter, Anton

    In participatory research, education and learner participation are directly connected. The document analyzes the role of a participatory research method in the basic education of rural adults. The different phases of the Participant Research method are presented, along with a profound analysis of both research and participation. The claim is that…

  8. Rapid discrimination of Chinese red ginseng and Korean ginseng using an electronic nose coupled with chemometrics.

    PubMed

    Li, Shan; Li, Xiang-ri; Wang, Gang-li; Nie, Li-xing; Yang, Yao-jun; Wu, Hao-zhong; Wei, Feng; Zhang, Ji; Tian, Jin-gai; Lin, Rui-chao

    2012-11-01

    Red ginseng is a precious and widely used traditional Chinese medicine. At present, Chinese red ginseng and Korean ginseng are both commonly found on the market. To rapidly and nondestructively discriminate between Chinese red ginseng and Korean ginseng, an electronic nose coupled with chemometrics was developed. Different red ginseng samples, including Chinese red ginseng (n=30) and Korean ginseng (South Korean red ginseng and North Korean red ginseng n=26), were collected. The metal oxide sensors on an electronic nose were used to measure the red ginseng samples. Multivariate statistical analyses, including principal component analysis (PCA), discriminant factorial analysis (DFA) and soft independent modeling of class analogy (SIMCA), were employed. All of the samples were analyzed by PCA. Most of the samples were used to set up DFA and SIMCA models, and then the remaining samples (Nos. 9, 10, 17, 18, 29, 30, 34, 43, 44, 50, and 51) were projected onto the DFA and SIMCA models in the form of black dots to validate the models. The results indicated that Chinese red ginseng and Korean ginseng were successfully discriminated using the electronic nose coupled with PCA, DFA and SIMCA. The checking scores of the DFA and SIMCA models were 100. The samples projected onto the DFA and SIMCA models were all correctly discriminated. The DFA and SIMCA models were robust. Electronic nose technology is a rapid, accurate, sensitive and nondestructive method to discriminate between Chinese red ginseng and Korean ginseng. PMID:22742921

  9. Rapid and undamaged analysis of crude and processed Radix Scrophulariae by Fourier transform infrared spectroscopy coupled with soft independent modeling of class analogy

    PubMed Central

    Zhu, Huiping; Cao, Gang; Cai, Hao; Cai, Baochang; Hu, Jue

    2014-01-01

    Objective: The main objective of this work is to determine the feasibility of identification of crude and processed Radix Scrophulariae using the Fourier transform infrared spectroscopy couple with soft independent modeling of class analogy (FT-IR-SIMCA). Materials and Methods: A total of 50 different crude Radix Scrophulariae was used to product processed ones. The spectra were acquired by FT-IR spectroscopy using a diffuse reflectance fiber optic probe. For the multivariate analysis, SIMCA was used. Results showed that FT-IR-SIMCA was useful to discriminate the processed Radix Scrophulariae samples from crude samples. These samples could be successfully classified by SIMCA. Results: In all cases, the recognition and rejection rates were 97.8% and 100%, respectively. When testing with the blind sample that was picked out from the chosen samples, the accuracy was up to 90%. Conclusion: It means that the methodology is capable of accurately separating processed Radix Scrophulariae from crude samples. PMID:25210313

  10. Estudio comparativo de los metodos analitico-sintetico y global en el aprendizaje de la lectura (Comparative Study of the Analytical-Synthetical (Phonics) and Global (Sight) Reading Methods).

    ERIC Educational Resources Information Center

    Carbonell de Grompone, Maria A.; And Others

    An investigation into the phonics and sight methods of reading instruction being taught in Uruguay schools seeks valid predictions in support of each approach. The study, written in Spanish, examines the progressive reading habits and abilities of 12 first-grade classes. Teachers assigned to teach each method uniformly had equivalent training and…

  11. Positive Prevention: Successful Approaches To Preventing Youthful Drug and Alcohol Use [and] La Prevencion Positiva: Metodos que han tenido exito en la prevencion del uso de drogas y alcohol entre la juventud.

    ERIC Educational Resources Information Center

    American Association of School Administrators, Arlington, VA.

    The United States has the highest rate of youthful drug abuse of any industrialized country in the world. There is a growing awareness that drug and alcohol use are closely connected to other problems such as teenage suicide, adolescent pregnancy, traffic fatalities, juvenile delinquency, poor school performance, runaways, and dropouts. Youthful…

  12. Identification, classification, and discrimination of agave syrups from natural sweeteners by infrared spectroscopy and HPAEC-PAD.

    PubMed

    Mellado-Mojica, Erika; López, Mercedes G

    2015-01-15

    Agave syrups are gaining popularity as new natural sweeteners. Identification, classification and discrimination by infrared spectroscopy coupled to chemometrics (NIR-MIR-SIMCA-PCA) and HPAEC-PAD of agave syrups from natural sweeteners were achieved. MIR-SIMCA-PCA allowed us to classify the natural sweeteners according to their natural source. Natural syrups exhibited differences in the MIR spectra region 1500-900 cm(-1). The agave syrups displayed strong absorption in the MIR spectra region 1061-1,063 cm(-1), in agreement with their high fructose content. Additionally, MIR-SIMCA-PCA allowed us to differentiate among syrups from different Agave species (Agavetequilana and Agavesalmiana). Thin-layer chromatography and HPAEC-PAD revealed glucose, fructose, and sucrose as the principal carbohydrates in all of the syrups. Oligosaccharide profiles showed that A. tequilana syrups are mainly composed of fructose (>60%) and fructooligosaccharides, while A. salmiana syrups contain more sucrose (28-32%). We conclude that MIR-SIMCA-PCA and HPAEC-PAD can be used to unequivocally identify and classified agave syrups. PMID:25148997

  13. Comparison of classification methods used for analysis of complex biological gas mixtures by means of laser spectroscopy

    NASA Astrophysics Data System (ADS)

    Kistenev, Y. V.; Shapovalov, A. V.; Vrazhnov, D. A.; Nikolaev, V. V.; Nikiforova, O. Y.

    2015-11-01

    The results of comparison of quality of two classificators - SVM (support vector machine) and SIMCA (soft independent modelling of class analogies) on model data contained profiles of absorbtion specra of exhalted air are presented. It is shown, that SVM classification results can be improved by preprocessing if input data with principal component analysis method.

  14. Origin assessment of EV olive oils by esterified sterols analysis.

    PubMed

    Giacalone, Rosa; Giuliano, Salvatore; Gulotta, Eleonora; Monfreda, Maria; Presti, Giovanni

    2015-12-01

    In this study extra virgin olive oils of Italian and non-Italian origin (from Spain, Tunisia and blends of EU origin) were differentiated by GC-FID analysis of sterols and esterified sterols followed by chemometric tools. PCA allowed to highlight the high significance of esterified sterols to characterise extra virgin olive oils in relation to their origin. SIMCA provided a sensitivity and specificity of 94.39% and 91.59% respectively; furthermore, an external set of 54 extra virgin olive oils bearing a designation of Italian origin on the labelling was tested by SIMCA. Prediction results were also compared with organoleptic assessment. Finally, the poor correlation found between ethylesters and esterified sterols allowed to hazard the guess, worthy of further investigations, that esterified sterols may prove to be promising in studies of geographical discrimination: indeed they appear to be independent of those factors causing the formation of ethyl esters and related to olive oil production. PMID:26041193

  15. Validation of multivariate screening methodology. Case study: detection of food fraud.

    PubMed

    López, M Isabel; Colomer, Núria; Ruisánchez, Itziar; Callao, M Pilar

    2014-05-27

    Multivariate screening methods are increasingly being implemented but there is no worldwide harmonized criterion for their validation. This study contributes to establish protocols for validating these methodologies. We propose the following strategy: (1) Establish the multivariate classification model and use receiver operating characteristic (ROC) curves to optimize the significance level (α) for setting the model's boundaries. (2) Evaluate the performance parameter from the contingency table results and performance characteristic curves (PCC curves). The adulteration of hazelnut paste with almond paste and chickpea flour has been used as a case study. Samples were analyzed by infrared (IR) spectroscopy and the multivariate classification technique used was soft independent modeling of class analogies (SIMCA). The ROC study showed that the optimal α value for setting the SIMCA boundaries was 0.03 in both cases. The sensitivity value was 93%, specificity 100% for almond and 98% for chickpea, and efficiency 97% for almond and 93% for chickpea. PMID:24832991

  16. Rapid detection of authenticity and adulteration of walnut oil by FTIR and fluorescence spectroscopy: a comparative study.

    PubMed

    Li, Bingning; Wang, Haixia; Zhao, Qiaojiao; Ouyang, Jie; Wu, Yanwen

    2015-08-15

    Fourier transform infrared (FTIR) and fluorescence spectroscopy combined with soft independent modeling of class analogies (SIMCA) and partial least square (PLS) were used to detect the authenticity of walnut oil and adulteration amount of soybean oil in walnut oil. A SIMCA model of FTIR spectra could differentiate walnut oil and other oils into separate categories; the classification limit of soybean oil in walnut oil was 10%. Fluorescence spectroscopy could differentiate oil composition by the peak position and intensity of emission spectrum without multivariate analysis. The classification limit of soybean oil adulterated in walnut oil by fluorescence spectroscopy was below 5%. The deviation of the prediction model for fluorescence spectra was lower than that for FTIR spectra. Fluorescence spectroscopy was more applicable than FTIR in the adulteration detection of walnut oil, both from the determination limit and prediction deviation. PMID:25794716

  17. Discrimination and classification techniques applied on Mallotus and Phyllanthus high performance liquid chromatography fingerprints.

    PubMed

    Viaene, J; Goodarzi, M; Dejaegher, B; Tistaert, C; Hoang Le Tuan, A; Nguyen Hoai, N; Chau Van, M; Quetin-Leclercq, J; Vander Heyden, Y

    2015-06-01

    Mallotus and Phyllanthus genera, both containing several species commonly used as traditional medicines around the world, are the subjects of this discrimination and classification study. The objective of this study was to compare different discrimination and classification techniques to distinguish the two genera (Mallotus and Phyllanthus) on the one hand, and the six species (Mallotus apelta, Mallotus paniculatus, Phyllanthus emblica, Phyllanthus reticulatus, Phyllanthus urinaria L. and Phyllanthus amarus), on the other. Fingerprints of 36 samples from the 6 species were developed using reversed-phase high-performance liquid chromatography with ultraviolet detection (RP-HPLC-UV). After fingerprint data pretreatment, first an exploratory data analysis was performed using Principal Component Analysis (PCA), revealing two outlying samples, which were excluded from the calibration set used to develop the discrimination and classification models. Models were built by means of Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Classification and Regression Trees (CART) and Soft Independent Modeling of Class Analogy (SIMCA). Application of the models on the total data set (outliers included) confirmed a possible labeling issue for the outliers. LDA, QDA and CART, independently of the pretreatment, or SIMCA after "normalization and column centering (N_CC)" or after "Standard Normal Variate transformation and column centering (SNV_CC)" were found best to discriminate the two genera, while LDA after column centering (CC), N_CC or SNV_CC; QDA after SNV_CC; and SIMCA after N_CC or after SNV_CC best distinguished between the 6 species. As classification technique, SIMCA after N_CC or after SNV_CC results in the best overall sensitivity and specificity. PMID:26002209

  18. ATR-FTIR spectroscopy and chemometrics: An interesting tool to discriminate and characterize counterfeit medicines.

    PubMed

    Custers, D; Cauwenbergh, T; Bothy, J L; Courselle, P; De Beer, J O; Apers, S; Deconinck, E

    2015-08-10

    Counterfeit medicines pose a huge threat to public health worldwide. High amounts of counterfeit pharmaceuticals enter the European market and therefore detection of these products is essential. Attenuated Total Reflection Fourier-Transform infrared spectroscopy (ATR-FTIR) might be useful for the screening of counterfeit medicines since it is easy to use and little sample preparation is required. Furthermore, this approach might be helpful to customs to obtain a first evaluation of suspected samples. This study proposes a combination of ATR-FTIR and chemometrics to discriminate and classify counterfeit medicines. A sample set, containing 209 samples in total, was analyzed using ATR-FTIR and the obtained spectra were used as fingerprints in the chemometric data-analysis which included Principal Component Analysis (PCA), k-Nearest Neighbours (k-NN), Classification and Regression Trees (CART) and Soft Independent Modelling of Class Analogy (SIMCA). First it was verified whether the mentioned techniques are capable to distinguish samples containing different active pharmaceutical ingredients (APIs). PCA showed a clear tendency of discrimination based on the API present; k-NN, CART and SIMCA were capable to create suitable prediction models based on the presence of different APIs. However k-NN performs the least while SIMCA performs the best. Secondly, it was tested whether these three models could be expanded to discriminate between genuine and counterfeit samples as well. k-NN was not able to make the desired discrimination and therefore it was not useful. CART performed better but also this model was less suited. SIMCA, on the other hand, resulted in a model with a 100% correct discrimination between genuine and counterfeit drugs. This study shows that chemometric analysis of ATR-FTIR fingerprints is a valuable tool to discriminate genuine from counterfeit samples and to classify counterfeit medicines. PMID:25476739

  19. Classification of Brazilian and foreign gasolines adulterated with alcohol using infrared spectroscopy.

    PubMed

    da Silva, Neirivaldo C; Pimentel, Maria Fernanda; Honorato, Ricardo S; Talhavini, Marcio; Maldaner, Adriano O; Honorato, Fernanda A

    2015-08-01

    The smuggling of products across the border regions of many countries is a practice to be fought. Brazilian authorities are increasingly worried about the illicit trade of fuels along the frontiers of the country. In order to confirm this as a crime, the Federal Police must have a means of identifying the origin of the fuel. This work describes the development of a rapid and nondestructive methodology to classify gasoline as to its origin (Brazil, Venezuela and Peru), using infrared spectroscopy and multivariate classification. Partial Least Squares Discriminant Analysis (PLS-DA) and Soft Independent Modeling Class Analogy (SIMCA) models were built. Direct standardization (DS) was employed aiming to standardize the spectra obtained in different laboratories of the border units of the Federal Police. Two approaches were considered in this work: (1) local and (2) global classification models. When using Approach 1, the PLS-DA achieved 100% correct classification, and the deviation of the predicted values for the secondary instrument considerably decreased after performing DS. In this case, SIMCA models were not efficient in the classification, even after standardization. Using a global model (Approach 2), both PLS-DA and SIMCA techniques were effective after performing DS. Considering that real situations may involve questioned samples from other nations (such as Peru), the SIMCA method developed according to Approach 2 is a more adequate, since the sample will be classified neither as Brazil nor Venezuelan. This methodology could be applied to other forensic problems involving the chemical classification of a product, provided that a specific modeling is performed. PMID:26042439

  20. Analysis of Flavonoid in Medicinal Plant Extract Using Infrared Spectroscopy and Chemometrics.

    PubMed

    Wulandari, Lestyo; Retnaningtyas, Yuni; Nuri; Lukman, Hilmia

    2016-01-01

    Infrared (IR) spectroscopy combined with chemometrics has been developed for simple analysis of flavonoid in the medicinal plant extract. Flavonoid was extracted from medicinal plant leaves by ultrasonication and maceration. IR spectra of selected medicinal plant extract were correlated with flavonoid content using chemometrics. The chemometric method used for calibration analysis was Partial Last Square (PLS) and the methods used for classification analysis were Linear Discriminant Analysis (LDA), Soft Independent Modelling of Class Analogies (SIMCA), and Support Vector Machines (SVM). In this study, the calibration of NIR model that showed best calibration with R (2) and RMSEC value was 0.9916499 and 2.1521897, respectively, while the accuracy of all classification models (LDA, SIMCA, and SVM) was 100%. R (2) and RMSEC of calibration of FTIR model were 0.8653689 and 8.8958149, respectively, while the accuracy of LDA, SIMCA, and SVM was 86.0%, 91.2%, and 77.3%, respectively. PLS and LDA of NIR models were further used to predict unknown flavonoid content in commercial samples. Using these models, the significance of flavonoid content that has been measured by NIR and UV-Vis spectrophotometry was evaluated with paired samples t-test. The flavonoid content that has been measured with both methods gave no significant difference. PMID:27529051

  1. Multivariate class modeling techniques applied to multielement analysis for the verification of the geographical origin of chili pepper.

    PubMed

    Naccarato, Attilio; Furia, Emilia; Sindona, Giovanni; Tagarelli, Antonio

    2016-09-01

    Four class-modeling techniques (soft independent modeling of class analogy (SIMCA), unequal dispersed classes (UNEQ), potential functions (PF), and multivariate range modeling (MRM)) were applied to multielement distribution to build chemometric models able to authenticate chili pepper samples grown in Calabria respect to those grown outside of Calabria. The multivariate techniques were applied by considering both all the variables (32 elements, Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Fe, Ga, La, Li, Mg, Mn, Na, Nd, Ni, Pb, Pr, Rb, Sc, Se, Sr, Tl, Tm, V, Y, Yb, Zn) and variables selected by means of stepwise linear discriminant analysis (S-LDA). In the first case, satisfactory and comparable results in terms of CV efficiency are obtained with the use of SIMCA and MRM (82.3 and 83.2% respectively), whereas MRM performs better than SIMCA in terms of forced model efficiency (96.5%). The selection of variables by S-LDA permitted to build models characterized, in general, by a higher efficiency. MRM provided again the best results for CV efficiency (87.7% with an effective balance of sensitivity and specificity) as well as forced model efficiency (96.5%). PMID:27041319

  2. Analysis of Flavonoid in Medicinal Plant Extract Using Infrared Spectroscopy and Chemometrics

    PubMed Central

    Retnaningtyas, Yuni; Nuri; Lukman, Hilmia

    2016-01-01

    Infrared (IR) spectroscopy combined with chemometrics has been developed for simple analysis of flavonoid in the medicinal plant extract. Flavonoid was extracted from medicinal plant leaves by ultrasonication and maceration. IR spectra of selected medicinal plant extract were correlated with flavonoid content using chemometrics. The chemometric method used for calibration analysis was Partial Last Square (PLS) and the methods used for classification analysis were Linear Discriminant Analysis (LDA), Soft Independent Modelling of Class Analogies (SIMCA), and Support Vector Machines (SVM). In this study, the calibration of NIR model that showed best calibration with R2 and RMSEC value was 0.9916499 and 2.1521897, respectively, while the accuracy of all classification models (LDA, SIMCA, and SVM) was 100%. R2 and RMSEC of calibration of FTIR model were 0.8653689 and 8.8958149, respectively, while the accuracy of LDA, SIMCA, and SVM was 86.0%, 91.2%, and 77.3%, respectively. PLS and LDA of NIR models were further used to predict unknown flavonoid content in commercial samples. Using these models, the significance of flavonoid content that has been measured by NIR and UV-Vis spectrophotometry was evaluated with paired samples t-test. The flavonoid content that has been measured with both methods gave no significant difference. PMID:27529051

  3. Comparability of higher order structure in proteins: chemometric analysis of second-derivative amide I Fourier transform infrared spectra.

    PubMed

    Stockdale, Gregory; Murphy, Brian M; D'Antonio, Jennifer; Manning, Mark Cornell; Al-Azzam, Wasfi

    2015-01-01

    Comparing higher order structure (HOS) in therapeutic proteins is a significant challenge. Previously, we showed that changes in solution conditions produced detectable changes in the second-derivative amide I Fourier transform infrared (FTIR) spectra for a variety of model proteins. Those comparisons utilized vector-based approaches, such as spectral overlap and spectral correlation coefficients to quantify differences between spectra. In this study, chemometric analyses of the same data were performed, to classify samples into different groups based on the solution conditions received. The solution conditions were composed of various combinations of temperature, pH, and salt types. At first, principal component analysis (PCA) was used to visually demonstrate that FTIR spectra respond to changes in solution conditions, which, presumably indicates variations in HOS. This observed when samples from the same solution condition form clusters within a PCA score plot. The second approach, called soft independent modeling of class analogy (SIMCA), was conducted to account for the within-class experimental error for the lysozyme spectra. The DModX values, indicative of the distance of each spectra to their respective class models, was found to be a more sensitive quantitative indicator of changes in HOS, when compared with the modified area of overlap algorithm. The SIMCA approach provides a metric to determine whether new observations do, or do not belong to a particular class or group. Thus, SIMCA is the recommended approach when multiple samples from each condition are available. PMID:25382804

  4. Screening Brazilian commercial gasoline quality by hydrogen nuclear magnetic resonance spectroscopic fingerprintings and pattern-recognition multivariate chemometric analysis.

    PubMed

    Flumignan, Danilo Luiz; Boralle, Nivaldo; de Oliveira, José Eduardo

    2010-06-30

    The identification of gasoline adulteration by organic solvents is not an easy task, because compounds that constitute the solvents are already in gasoline composition. In this work, the combination of Hydrogen Nuclear Magnetic Resonance ((1)H NMR) spectroscopic fingerprintings with pattern-recognition multivariate Soft Independent Modeling of Class Analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a Monitoring Program for Quality Control of Automotive Fuels. SIMCA was performed on spectroscopic fingerprints to classify the quality of representative commercial gasoline samples selected by Hierarchical Cluster Analysis (HCA) and collected over a 6-month period from different gas stations in the São Paulo state, Brazil. Following optimized the (1)H NMR-SIMCA algorithm, it was possible to correctly classify 92.0% of commercial gasoline samples, which is considered acceptable. The chemometric method is recommended for routine applications in Quality-Control Monitoring Programs, since its measurements are fast and can be easily automated. Also, police laboratories could employ this method for rapid screening analysis to discourage adulteration practices. PMID:20685442

  5. Discrimination of planting area of white peach based near-infrared spectra and chemometrics methods

    NASA Astrophysics Data System (ADS)

    Fu, Xiaping; Ying, Yibin; Zhou, Ying; Xu, Huirong; Xie, Lijuan; Jiang, Xuesong

    2007-09-01

    White peach is a famous peach variety for its super-quality and high economic benefit. It is originally planted in Yuandong Villiage, Jinhua County, Zhejiang province. By now, it has been planted in many other places in southeast of China. However, peaches from different planting areas have dissimilar quality and taste, which result in different selling price. The objective of this research was to discriminate peaches from different planting areas by using near-infrared (NIR) spectra and chemometrics methods. Diffuse reflectance spectra were collected by a fiber spectrometer in the range of 800-2500 nm. Discriminant analysis (DA), soft independent modeling of class analogy (SIMCA), and discriminant partial least square regression (DPLS) methods were employed to classify the peaches from three planting areas 'Jinhua', 'Wuyi', and 'Yongkang' of Zhejiang province. 360 samples were used in this study, 120 samples per planting area. The classifying correctness were above 92% for both DA and SIMCA mdoels. And the result of DPLS model was slightly better. By using DPLS method, two 'Jinhua' peaches, three 'Wuyi' peaches, and three 'Yongkang' peaches were misclassified, the accruacy was above 95%. The results of this study indicate that the three chemometrics methods DA, SIMCA, and DPLS are effective for discriminating peaches from different planting areas based on NIR spectroscopy.

  6. Chemometric and Statistical Analyses of ToF-SIMS Spectra of Increasingly Complex Biological Samples

    SciTech Connect

    Berman, E S; Wu, L; Fortson, S L; Nelson, D O; Kulp, K S; Wu, K J

    2007-10-24

    Characterizing and classifying molecular variation within biological samples is critical for determining fundamental mechanisms of biological processes that will lead to new insights including improved disease understanding. Towards these ends, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to examine increasingly complex samples of biological relevance, including monosaccharide isomers, pure proteins, complex protein mixtures, and mouse embryo tissues. The complex mass spectral data sets produced were analyzed using five common statistical and chemometric multivariate analysis techniques: principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), soft independent modeling of class analogy (SIMCA), and decision tree analysis by recursive partitioning. PCA was found to be a valuable first step in multivariate analysis, providing insight both into the relative groupings of samples and into the molecular basis for those groupings. For the monosaccharides, pure proteins and protein mixture samples, all of LDA, PLSDA, and SIMCA were found to produce excellent classification given a sufficient number of compound variables calculated. For the mouse embryo tissues, however, SIMCA did not produce as accurate a classification. The decision tree analysis was found to be the least successful for all the data sets, providing neither as accurate a classification nor chemical insight for any of the tested samples. Based on these results we conclude that as the complexity of the sample increases, so must the sophistication of the multivariate technique used to classify the samples. PCA is a preferred first step for understanding ToF-SIMS data that can be followed by either LDA or PLSDA for effective classification analysis. This study demonstrates the strength of ToF-SIMS combined with multivariate statistical and chemometric techniques to classify increasingly complex biological samples

  7. Supervised pattern recognition procedures for discrimination of whiskeys from gas chromatography/mass spectrometry congener analysis.

    PubMed

    González-Arjona, Domingo; López-Pérez, Germán; González-Gallero, Víctor; González, A Gustavo

    2006-03-22

    The volatile congener analysis of 52 commercialized whiskeys (24 samples of single malt Scotch whiskey, 18 samples of bourbon whiskey, and 10 samples of Irish whiskey) was carried out by gas chromatography/mass spectrometry after liquid-liquid extraction with dichloromethane. Pattern recognition procedures were applied for discrimination of different whiskey categories. Multivariate data analysis includes linear discriminant analysis (LDA), k nearest neighbors (KNN), soft independent modeling of class analogy (SIMCA), procrustes discriminant analysis (PDA), and artificial neural networks techniques involving multilayer perceptrons (MLP) and probabilistic neural networks (PNN). Classification rules were validated by considering the number of false positives (FPs) and false negatives (FNs) of each class associated to the prediction set. Artificial neural networks led to the best results because of their intrinsic nonlinear features. Both techniques, MLP and PNN, gave zero FPs and zero FNs for all of the categories. KNN is a nonparametric method that also provides zero FPs and FNs for every class but only when selecting K = 3 neighbors. PDA produced good results also (zero FPs and FNs always) but only by selecting nine principal components for class modeling. LDA shows a lesser classification performance, because of the building of linear frontiers between classes that does not apply in many real situations. LDA led to one FP for bourbons and one FN for scotches. The worse results were obtained with SIMCA, which gave a higher number of FPs (five for both scotches and bourbons) and FNs (six for scotchs and two for bourbons). The possible cause of these findings is the strong influence of class inhomogeneities on the SIMCA performance. It is remarkable that in any case, all of the methodologies lead to zero FPs and FNs for the Irish whiskeys. PMID:16536565

  8. Differentiation of opium and poppy straw using capillary electrophoresis and pattern recognition techniques.

    PubMed

    Reid, Raymond G; Durham, David G; Boyle, Susanne P; Low, Ann S; Wangboonskul, Jinda

    2007-12-12

    Opium samples from four different locations and poppy straw from different plant varieties have been assayed using micellar capillary electrophoresis incorporating a sweeping technique. Individual alkaloids (morphine, codeine, papaverine, noscapine, thebaine, oripavine, reticuline and narceine) were quantitatively determined in the different samples by a validated capillary electrophoresis method. Unsupervised pattern recognition of the opium samples and the poppy straw samples using hierarchical cluster analysis (HCA) and principal component analysis (PCA), showed distinct clusters. Supervised pattern recognition using soft independent modelling of class analogy (SIMCA) was performed to show individual groupings and allow unknown samples to be classified according to the models built using the CZE assay results. PMID:18022406

  9. Study of cluster analysis used in explosives classification with laser-induced breakdown spectroscopy

    NASA Astrophysics Data System (ADS)

    Wang, Q. Q.; He, L. A.; Zhao, Y.; Peng, Z.; Liu, L.

    2016-06-01

    Supervised learning methods (such as partial least squares regression-discriminant analysis, SIMCA, etc) are widely used in explosives recognition. The correct classification rate may be lowered if a sample or substrate is not included in the training dataset. Unsupervised learning methods (such as hierarchical clustering analysis, K-means, etc) have the potential to solve this problem. In this paper we analyzed results of using as input variables the intensities of seven lines and then five intensity ratios of the seven lines. It was demonstrated that unsupervised learning methods had the ability to achieve a better classification result.

  10. Fast discrimination of traditional Chinese medicine according to geographical origins with FTIR spectroscopy and advanced pattern recognition techniques

    NASA Astrophysics Data System (ADS)

    Li, Ning; Wang, Yan; Xu, Kexin

    2006-08-01

    Combined with Fourier transform infrared (FTIR) spectroscopy and three kinds of pattern recognition techniques, 53 traditional Chinese medicine danshen samples were rapidly discriminated according to geographical origins. The results showed that it was feasible to discriminate using FTIR spectroscopy ascertained by principal component analysis (PCA). An effective model was built by employing the Soft Independent Modeling of Class Analogy (SIMCA) and PCA, and 82% of the samples were discriminated correctly. Through use of the artificial neural network (ANN)-based back propagation (BP) network, the origins of danshen were completely classified.

  11. Classification of edible oils and modeling of their physico-chemical properties by chemometric methods using mid-IR spectroscopy

    NASA Astrophysics Data System (ADS)

    Luna, Aderval S.; da Silva, Arnaldo P.; Ferré, Joan; Boqué, Ricard

    This research work describes two studies for the classification and characterization of edible oils and its quality parameters through Fourier transform mid infrared spectroscopy (FT-mid-IR) together with chemometric methods. The discrimination of canola, sunflower, corn and soybean oils was investigated using SVM-DA, SIMCA and PLS-DA. Using FT-mid-IR, DPLS was able to classify 100% of the samples from the validation set, but SIMCA and SVM-DA were not. The quality parameters: refraction index and relative density of edible oils were obtained from reference methods. Prediction models for FT-mid-IR spectra were calculated for these quality parameters using partial least squares (PLS) and support vector machines (SVM). Several preprocessing alternatives (first derivative, multiplicative scatter correction, mean centering, and standard normal variate) were investigated. The best result for the refraction index was achieved with SVM as well as for the relative density except when the preprocessing combination of mean centering and first derivative was used. For both of quality parameters, the best results obtained for the figures of merit expressed by the root mean square error of cross validation (RMSECV) and prediction (RMSEP) were equal to 0.0001.

  12. Toward the characterization of biological toxins using field-based FT-IR spectroscopic instrumentation

    NASA Astrophysics Data System (ADS)

    Schiering, David W.; Walton, Robert B.; Brown, Christopher W.; Norman, Mark L.; Brewer, Joseph; Scott, James

    2004-12-01

    IR spectroscopy is a broadly applicable technique for the identification of covalent materials. Recent advances in instrumentation have made Fourier Transform infrared (FT-IR) spectroscopy available for field characterization of suspect materials. Presently, this instrumentation is broadly deployed and used for the identification of potential chemical hazards. This discussion concerns work towards expanding the analytical utility of field-based FT-IR spectrometry in the characterization of biological threats. Two classes of materials were studied: biologically produced chemical toxins which were non-peptide in nature and peptide toxin. The IR spectroscopic identification of aflatoxin-B1, trichothecene T2 mycotoxin, and strychnine was evaluated using the approach of spectral searching against large libraries of materials. For pure components, the IR method discriminated the above toxins at better than the 99% confidence level. The ability to identify non-peptide toxins in mixtures was also evaluated using a "spectral stripping" search approach. For the mixtures evaluated, this method was able to identify the mixture components from ca. 32K spectral library entries. Castor bean extract containing ricin was used as a representative peptide toxin. Due to similarity in protein spectra, a SIMCA pattern recognition methodology was evaluated for classifying peptide toxins. In addition to castor bean extract the method was validated using bovine serum albumin and myoglobin as simulants. The SIMCA approach was successful in correctly classifying these samples at the 95% confidence level.

  13. A novel acoustic sensor approach to classify seeds based on sound absorption spectra.

    PubMed

    Gasso-Tortajada, Vicent; Ward, Alastair J; Mansur, Hasib; Brøchner, Torben; Sørensen, Claus G; Green, Ole

    2010-01-01

    A non-destructive and novel in situ acoustic sensor approach based on the sound absorption spectra was developed for identifying and classifying different seed types. The absorption coefficient spectra were determined by using the impedance tube measurement method. Subsequently, a multivariate statistical analysis, i.e., principal component analysis (PCA), was performed as a way to generate a classification of the seeds based on the soft independent modelling of class analogy (SIMCA) method. The results show that the sound absorption coefficient spectra of different seed types present characteristic patterns which are highly dependent on seed size and shape. In general, seed particle size and sphericity were inversely related with the absorption coefficient. PCA presented reliable grouping capabilities within the diverse seed types, since the 95% of the total spectral variance was described by the first two principal components. Furthermore, the SIMCA classification model based on the absorption spectra achieved optimal results as 100% of the evaluation samples were correctly classified. This study contains the initial structuring of an innovative method that will present new possibilities in agriculture and industry for classifying and determining physical properties of seeds and other materials. PMID:22163455

  14. Authentication of fattening diet of Iberian pigs according to their volatile compounds profile from raw subcutaneous fat.

    PubMed

    Narváez-Rivas, M; Pablos, F; Jurado, J M; León-Camacho, M

    2011-02-01

    The composition of volatile components of subcutaneous fat from Iberian pig has been studied. Purge and trap gas chromatography-mass spectrometry has been used. The composition of the volatile fraction of subcutaneous fat has been used for authentication purposes of different types of Iberian pig fat. Three types of this product have been considered, montanera, extensive cebo and intensive cebo. With classification purposes, several pattern recognition techniques have been applied. In order to find out possible tendencies in the sample distribution as well as the discriminant power of the variables, principal component analysis was applied as visualisation technique. Linear discriminant analysis (LDA) and soft independent modelling by class analogy (SIMCA) were used to obtain suitable classification models. LDA and SIMCA allowed the differentiation of three fattening diets by using the contents in 2,2,4,6,6-pentamethyl-heptane, m-xylene, 2,4-dimethyl-heptane, 6-methyl-tridecane, 1-methoxy-2-propanol, isopropyl alcohol, o-xylene, 3-ethyl-2,2-dimethyl-oxirane, 2,6-dimethyl-undecane, 3-methyl-3-pentanol and limonene. PMID:21072505

  15. Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariate chemometric analysis.

    PubMed

    Myakalwar, Ashwin Kumar; Sreedhar, S; Barman, Ishan; Dingari, Narahara Chari; Venugopal Rao, S; Prem Kiran, P; Tewari, Surya P; Manoj Kumar, G

    2011-12-15

    We report the effectiveness of laser-induced breakdown spectroscopy (LIBS) in probing the content of pharmaceutical tablets and also investigate its feasibility for routine classification. This method is particularly beneficial in applications where its exquisite chemical specificity and suitability for remote and on site characterization significantly improves the speed and accuracy of quality control and assurance process. Our experiments reveal that in addition to the presence of carbon, hydrogen, nitrogen and oxygen, which can be primarily attributed to the active pharmaceutical ingredients, specific inorganic atoms were also present in all the tablets. Initial attempts at classification by a ratiometric approach using oxygen (∼777 nm) to nitrogen (742.36 nm, 744.23 nm and 746.83 nm) compositional values yielded an optimal value at 746.83 nm with the least relative standard deviation but nevertheless failed to provide an acceptable classification. To overcome this bottleneck in the detection process, two chemometric algorithms, i.e. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA), were implemented to exploit the multivariate nature of the LIBS data demonstrating that LIBS has the potential to differentiate and discriminate among pharmaceutical tablets. We report excellent prospective classification accuracy using supervised classification via the SIMCA algorithm, demonstrating its potential for future applications in process analytical technology, especially for fast on-line process control monitoring applications in the pharmaceutical industry. PMID:22099648

  16. Rapid detection of Listeria monocytogenes in milk using confocal micro-Raman spectroscopy and chemometric analysis.

    PubMed

    Wang, Junping; Xie, Xinfang; Feng, Jinsong; Chen, Jessica C; Du, Xin-jun; Luo, Jiangzhao; Lu, Xiaonan; Wang, Shuo

    2015-07-01

    Listeria monocytogenes is a facultatively anaerobic, Gram-positive, rod-shape foodborne bacterium causing invasive infection, listeriosis, in susceptible populations. Rapid and high-throughput detection of this pathogen in dairy products is critical as milk and other dairy products have been implicated as food vehicles in several outbreaks. Here we evaluated confocal micro-Raman spectroscopy (785 nm laser) coupled with chemometric analysis to distinguish six closely related Listeria species, including L. monocytogenes, in both liquid media and milk. Raman spectra of different Listeria species and other bacteria (i.e., Staphylococcus aureus, Salmonella enterica and Escherichia coli) were collected to create two independent databases for detection in media and milk, respectively. Unsupervised chemometric models including principal component analysis and hierarchical cluster analysis were applied to differentiate L. monocytogenes from Listeria and other bacteria. To further evaluate the performance and reliability of unsupervised chemometric analyses, supervised chemometrics were performed, including two discriminant analyses (DA) and soft independent modeling of class analogies (SIMCA). By analyzing Raman spectra via two DA-based chemometric models, average identification accuracies of 97.78% and 98.33% for L. monocytogenes in media, and 95.28% and 96.11% in milk were obtained, respectively. SIMCA analysis also resulted in satisfied average classification accuracies (over 93% in both media and milk). This Raman spectroscopic-based detection of L. monocytogenes in media and milk can be finished within a few hours and requires no extensive sample preparation. PMID:25863337

  17. Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

    PubMed Central

    Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

    2013-01-01

    The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

  18. Rice Seed Cultivar Identification Using Near-Infrared Hyperspectral Imaging and Multivariate Data Analysis

    PubMed Central

    Kong, Wenwen; Zhang, Chu; Liu, Fei; Nie, Pengcheng; He, Yong

    2013-01-01

    A near-infrared (NIR) hyperspectral imaging system was developed in this study. NIR hyperspectral imaging combined with multivariate data analysis was applied to identify rice seed cultivars. Spectral data was exacted from hyperspectral images. Along with Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA), K-Nearest Neighbor Algorithm (KNN) and Support Vector Machine (SVM), a novel machine learning algorithm called Random Forest (RF) was applied in this study. Spectra from 1,039 nm to 1,612 nm were used as full spectra to build classification models. PLS-DA and KNN models obtained over 80% classification accuracy, and SIMCA, SVM and RF models obtained 100% classification accuracy in both the calibration and prediction set. Twelve optimal wavelengths were selected by weighted regression coefficients of the PLS-DA model. Based on optimal wavelengths, PLS-DA, KNN, SVM and RF models were built. All optimal wavelengths-based models (except PLS-DA) produced classification rates over 80%. The performances of full spectra-based models were better than optimal wavelengths-based models. The overall results indicated that hyperspectral imaging could be used for rice seed cultivar identification, and RF is an effective classification technique. PMID:23857260

  19. Headspace-programmed temperature vaporizer-mass spectrometry and pattern recognition techniques for the analysis of volatiles in saliva samples.

    PubMed

    Pérez Antón, Ana; Del Nogal Sánchez, Miguel; Crisolino Pozas, Ángel Pedro; Pérez Pavón, José Luis; Moreno Cordero, Bernardo

    2016-11-01

    A rapid method for the analysis of volatiles in saliva samples is proposed. The method is based on direct coupling of three components: a headspace sampler (HS), a programmable temperature vaporizer (PTV) and a quadrupole mass spectrometer (qMS). Several applications in the biomedical field have been proposed with electronic noses based on different sensors. However, few contributions have been developed using a mass spectrometry-based electronic nose in this field up to date. Samples of 23 patients with some type of cancer and 32 healthy volunteers were analyzed with HS-PTV-MS and the profile signals obtained were subjected to pattern recognition techniques with the aim of studying the possibilities of the methodology to differentiate patients with cancer from healthy controls. An initial inspection of the contained information in the data by means of principal components analysis (PCA) revealed a complex situation were an overlapped distribution of samples in the score plot was visualized instead of two groups of separated samples. Models using K-nearest neighbors (KNN) and Soft Independent Modeling of Class Analogy (SIMCA) showed poor discrimination, specially using SIMCA where a small distance between classes was obtained and no satisfactory results in the classification of the external validation samples were achieved. Good results were obtained when Mahalanobis discriminant analysis (DA) and support vector machines (SVM) were used obtaining 2 (false positives) and 0 samples misclassified in the external validation set, respectively. No false negatives were found using these techniques. PMID:27591583

  20. Probability of identification: adulteration of American Ginseng with Asian Ginseng.

    PubMed

    Harnly, James; Chen, Pei; Harrington, Peter De B

    2013-01-01

    The AOAC INTERNATIONAL guidelines for validation of botanical identification methods were applied to the detection of Asian Ginseng [Panax ginseng (PG)] as an adulterant for American Ginseng [P. quinquefolius (PQ)] using spectral fingerprints obtained by flow injection mass spectrometry (FIMS). Samples of 100% PQ and 100% PG were physically mixed to provide 90, 80, and 50% PQ. The multivariate FIMS fingerprint data were analyzed using soft independent modeling of class analogy (SIMCA) based on 100% PQ. The Q statistic, a measure of the degree of non-fit of the test samples with the calibration model, was used as the analytical parameter. FIMS was able to discriminate between 100% PQ and 100% PG, and between 100% PQ and 90, 80, and 50% PQ. The probability of identification (POI) curve was estimated based on the SD of 90% PQ. A digital model of adulteration, obtained by mathematically summing the experimentally acquired spectra of 100% PQ and 100% PG in the desired ratios, agreed well with the physical data and provided an easy and more accurate method for constructing the POI curve. Two chemometric modeling methods, SIMCA and fuzzy optimal associative memories, and two classification methods, partial least squares-discriminant analysis and fuzzy rule-building expert systems, were applied to the data. The modeling methods correctly identified the adulterated samples; the classification methods did not. PMID:24645502

  1. Evaluation and optimization of the robustness of a multivariate analysis methodology for identification of alloys by laser induced breakdown spectroscopy

    NASA Astrophysics Data System (ADS)

    Vors, Evelyne; Tchepidjian, Krikor; Sirven, Jean-Baptiste

    2016-03-01

    In this study, laser induced breakdown spectroscopy (LIBS) with chemometrics was used for classification and identification of alloys, with a particular focus on the issue of the model robustness. A supervised classification model, Soft Independent Modeling of Class Analogy (SIMCA) was calculated with calibration spectra of 13 representative materials. These measurements were reproduced, with the same samples and using the same LIBS instrument, on two different dates (seven and eight months after the calibration measurements): during this period, instrumental variations occurred and the robustness of sample classification was assessed by the prediction error rate. Then, the optimization of SIMCA model parameters, including spectral preprocessing and wavelength selection, was performed using a full factorial experimental design, and a prediction error rate of 0% with a robustness of 100% was achieved for this period extending until eight months after the model calibration. The study was completed two and a half years later by a test of the robustness of the previously optimized model, carried out with an additional series of measurements on test samples with the same LIBS instrument. The predictive ability of the model on spectra acquired more than two years after validation remained good.

  2. A Novel Acoustic Sensor Approach to Classify Seeds Based on Sound Absorption Spectra

    PubMed Central

    Gasso-Tortajada, Vicent; Ward, Alastair J.; Mansur, Hasib; Brøchner, Torben; Sørensen, Claus G.; Green, Ole

    2010-01-01

    A non-destructive and novel in situ acoustic sensor approach based on the sound absorption spectra was developed for identifying and classifying different seed types. The absorption coefficient spectra were determined by using the impedance tube measurement method. Subsequently, a multivariate statistical analysis, i.e., principal component analysis (PCA), was performed as a way to generate a classification of the seeds based on the soft independent modelling of class analogy (SIMCA) method. The results show that the sound absorption coefficient spectra of different seed types present characteristic patterns which are highly dependent on seed size and shape. In general, seed particle size and sphericity were inversely related with the absorption coefficient. PCA presented reliable grouping capabilities within the diverse seed types, since the 95% of the total spectral variance was described by the first two principal components. Furthermore, the SIMCA classification model based on the absorption spectra achieved optimal results as 100% of the evaluation samples were correctly classified. This study contains the initial structuring of an innovative method that will present new possibilities in agriculture and industry for classifying and determining physical properties of seeds and other materials. PMID:22163455

  3. Fast discrimination of danshen from different geographical areas by NIR spectroscopy and advanced cluster analysis method

    NASA Astrophysics Data System (ADS)

    Li, Ning; Wang, Yan; Xu, Kexin

    2006-09-01

    Near infrared (NIR) diffuse reflection spectroscopy has been an effective way to perform quantitative analysis without the requirement of sample pretreatnient. In this paper, NIR Fourier transform infrared (FTIR) spectroscopy has been introduced to probe spectral features of traditional Chinese medicine Danshen. Infrared fingerprint spectra of Danshen can be established. Influence of differentiation of spectrum is also discussed. After pretreatment and derivation on the spectral data, methods of principal analysis (PCA), soft independent modeling of class analogy (SIMCA) and Artificial Neural Network (ANN) are combined to sort the geographical origins of 53 samples by local modeling. The result show that, as a basis of the other two methods, PCA is a more efficient one for identifying the geographical origins of Danshen. Combining SIMCA with PCA, an effective model is built to analyze the data after normalization and differentiation, the correct identification rate reaches above 90%. Then 36 samples are chosen as training set while other 17 samples being verifying set. Using ANN-based Back Propagation method, after proper training of BP network, the origins of Danshen are completely classified. Therefore, combined with advanced mathematical analysis, NIR diffuse spectroscopy can be a novel and rapid way to accurately evaluate the origin of Chinese medicine, and also to accelerate the modernization process of Chinese drugs.

  4. Digital image-based classification of biodiesel.

    PubMed

    Costa, Gean Bezerra; Fernandes, David Douglas Sousa; Almeida, Valber Elias; Araújo, Thomas Souto Policarpo; Melo, Jessica Priscila; Diniz, Paulo Henrique Gonçalves Dias; Véras, Germano

    2015-07-01

    This work proposes a simple, rapid, inexpensive, and non-destructive methodology based on digital images and pattern recognition techniques for classification of biodiesel according to oil type (cottonseed, sunflower, corn, or soybean). For this, differing color histograms in RGB (extracted from digital images), HSI, Grayscale channels, and their combinations were used as analytical information, which was then statistically evaluated using Soft Independent Modeling by Class Analogy (SIMCA), Partial Least Squares Discriminant Analysis (PLS-DA), and variable selection using the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA). Despite good performances by the SIMCA and PLS-DA classification models, SPA-LDA provided better results (up to 95% for all approaches) in terms of accuracy, sensitivity, and specificity for both the training and test sets. The variables selected Successive Projections Algorithm clearly contained the information necessary for biodiesel type classification. This is important since a product may exhibit different properties, depending on the feedstock used. Such variations directly influence the quality, and consequently the price. Moreover, intrinsic advantages such as quick analysis, requiring no reagents, and a noteworthy reduction (the avoidance of chemical characterization) of waste generation, all contribute towards the primary objective of green chemistry. PMID:25882407

  5. Characterization of the Authenticity of Pasta di Gragnano Protected Geographical Indication Through Flavor Component Analysis by Gas Chromatography-Mass Spectrometry and Chemometric Tools.

    PubMed

    Giannetti, Vanessa; Boccacci Mariani, Maurizio; Mannino, Paola

    2016-09-01

    An authentication study based on headspace solid-phase microextraction/GC-MS was performed with a set of 60 samples representative of traditional "Pasta di Gragnano protected geographical indication (PGI)" and the most common Italian pasta brands. Multivariate chemometric tools were used to classify the samples based on the chemical information provided from 20 target flavor compounds, including Maillard reaction and lipid oxidation products. Pattern recognition by principal component analysis and linear discriminant analysis showed a natural grouping of samples according to the drying process adopted for their production (i.e., the traditional Cirillo method versus a high-temperature approach). Subsequently, soft independent modeling by class analogy (SIMCA) and unequal dispersed classes (UNEQ) were used to build class models at 95% confidence and 100% sensitivity levels (forced models) for predictive classification purposes. The good performance obtained from the models in terms of cross-validation efficiency (SIMCA, 57.01%; UNEQ, 86.60%; 100% for both forced models) highlighted that targeted analysis of flavor profiles could be used to assess the authenticity of Pasta di Gragnano PGI samples. Hence, the proposed method may help to protect Pasta di Gragnano PGI from label frauds by verifying whether samples comply with statements concerning drying process conditions as stated in the product specification. PMID:27619656

  6. Chromatographic impurity fingerprinting of genuine and counterfeit Cialis® as a means to compare the discriminating ability of PDA and MS detection.

    PubMed

    Custers, D; Krakowska, B; De Beer, J O; Courselle, P; Daszykowski, M; Apers, S; Deconinck, E

    2016-01-01

    Public health is threatened worldwide by counterfeit medicines. Their quality, safety and efficacy cannot be guaranteed since no quality control is performed during and/or after the manufacturing process. Characterization of these products is a very important topic. During this study a High Performance Liquid Chromatography-Photodiode Array (HPLC-PDA) and a High Performance Liquid Chromatography - Mass Spectrometry (HPLC-MS) method were developed to analyse both genuine and counterfeit samples of Cialis®. The obtained PDA and MS fingerprints were explored and modelled using unsupervised Principal Component Analysis (PCA) and supervised Partial Least Squares and its discriminant variant (PLS, PLS-DA) as well the classification methods including Soft Independent Modelling of Class Analogy (SIMCA) and the k Nearest Neighbour classifier (kNN). Both MS1 and MS2 data and data measured at 254 nm and 270 nm were used with the aim to test the potential complementarity of PDA and MS detection. First, it was checked if both groups of fingerprints can support differentiation between genuine and counterfeit medicines. Then, it was verified if the obtained multivariate models could be improved by combining information present in MS and PDA fingerprints. Survey of the models obtained for the 254 nm data, 270 nm data and 254_270 nm data combination showed that a tendency of discrimination could be observed with PLS. For the 270 nm data and 254_270 nm data combination a perfect discrimination between genuine and counterfeit medicines is obtained with PLS-DA and SIMCA. This shows that 270 nm alone performs equally well compared to 254_270 nm. For the MS1 and MS1_MS2 data perfect models were obtained using PLS-DA and kNN, indicating that the MS2 data do not provide any extra useful information to acquire the aimed distinction. When combining MS1 and 270 nm perfect models were gained by PLS-DA and SIMCA, which is very similar to the results obtained for PDA alone. These results show

  7. Modeling excitation-emission fluorescence matrices with pattern recognition algorithms for classification of Argentine white wines according grape variety.

    PubMed

    Azcarate, Silvana M; de Araújo Gomes, Adriano; Alcaraz, Mirta R; Ugulino de Araújo, Mário C; Camiña, José M; Goicoechea, Héctor C

    2015-10-01

    This paper reports the modeling of excitation-emission matrices for classification of Argentinean white wines according to the grape variety employing chemometric tools for pattern recognition. The discriminative power of the data was first investigated using Principal Component Analysis (PCA) and Parallel Factor Analysis (PARAFAC). The score plots showed strong overlapping between classes. A forty-one samples set was partitioned into training and test sets by the Kennard-Stone algorithm. The algorithms evaluated were SIMCA, N- and U-PLS-DA and SPA-LDA. The fit of the implemented models was assessed by mean of accuracy, sensitivity and specificity. These models were then used to assign the type of grape of the wines corresponding to the twenty samples test set. The best results were obtained for U-PLS-DA and SPA-LDA with 76% and 80% accuracy. PMID:25872447

  8. Application of multivariate statistical methods to the analysis of ancient Turkish potsherds

    SciTech Connect

    Martin, R.C.

    1986-01-01

    Three hundred ancient Turkish potsherds were analyzed by instrumental neutron activation analysis, and the resulting data analyzed by several techniques of multivariate statistical analysis, some only recently developed. The programs AGCLUS, MASLOC, and SIMCA were sequentially employed to characterize and group the samples by type of pottery and site of excavation. Comparison of the statistical analyses by each method provided archaeological insight into the site/type relationships of the samples and ultimately evidence relevant to the commercial relations between the ancient communities and specialization of pottery production over time. The techniques used for statistical analysis were found to be of significant potential utility in the future analysis of other archaeometric data sets. 25 refs., 33 figs.

  9. Analysis of peptide-protein binding using amino acid descriptors: prediction and experimental verification for human histocompatibility complex HLA-A0201.

    PubMed

    Guan, Pingping; Doytchinova, Irini A; Walshe, Valerie A; Borrow, Persephone; Flower, Darren R

    2005-11-17

    Amino acid descriptors are often used in quantitative structure-activity relationship (QSAR) analysis of proteins and peptides. In the present study, descriptors were used to characterize peptides binding to the human MHC allele HLA-A0201. Two sets of amino acid descriptors were chosen: 93 descriptors taken from the amino acid descriptor database AAindex and the z descriptors defined by Wold and Sandberg. Variable selection techniques (SIMCA, genetic algorithm, and GOLPE) were applied to remove redundant descriptors. Our results indicate that QSAR models generated using five z descriptors had the highest predictivity and explained variance (q2 between 0.6 and 0.7 and r2 between 0.6 and 0.9). Further to the QSAR analysis, 15 peptides were synthesized and tested using a T2 stabilization assay. All peptides bound to HLA-A0201 well, and four peptides were identified as high-affinity binders. PMID:16279801

  10. [Quality characteristic comparison of Schisandrae Chinensis Fructus from different place].

    PubMed

    Zhou, Yong-fena; Wang, Jia-bo; Zhang, Dina-kun; Tan, Pena; Zhang, Hai-zhu; Li, Bao-cai; Xiao, Xiao-he

    2015-08-01

    The contents of schisandrol A, schisandrol B, schisantherin A, schisandrin A , schisandrin B, schisandrin C in Schisandrae Chinensis Fructus (SCF) were determined simultaneously by HPLC. Collect 100-seed weight, color, pulp content, longitude and latitude of SCF of different batches were collected. SIMCA-P and SPSS were applied to make PLS-DA analysis of 24 batches of SCF and correlation analysis of relevant parameters. According to the 13 parameters, SCF from three different places of origin could be distinguished effectively. It was found that the content of chemical component of SCF increased with latitude and longitude first, and then decrease. The results provide some theoretical basis for study of SCF genuineness and traditional method of identifying just from experience. PMID:26790284

  11. Application of hand-held and portable infrared spectrometers in bovine milk analysis.

    PubMed

    Santos, Poliana M; Pereira-Filho, Edenir R; Rodriguez-Saona, Luis E

    2013-02-13

    A simple and fast method for the detection and quantification of milk adulteration was developed using portable and hand-held infrared (IR) spectrometers. Milk samples were purchased from local supermarkets (Columbus, OH, USA) and spiked with tap water, whey, hydrogen peroxide, synthetic urine, urea, and synthetic milk in different concentrations. Spectral data were collected using mid-infrared (MIR) and near-infrared (NIR) spectrometers. Soft independent modeling of class analogy (SIMCA) classification models exhibited tight and well-separated clusters allowing the discrimination of control from adulterated milk samples. Partial least-squares regression (PLSR) was used to estimate adulteration levels, and results showed high coefficients of determination (R(2)) and low standard errors of prediction (SEP). Classification and quantification models indicated that the tested MIR systems were superior to NIR systems in monitoring milk adulteration. This method can be potentially used as an alternative to traditional methods due to their simplicity, sensitivity, low energy cost, and portability. PMID:23339381

  12. Nontargeted detection of adulteration of skim milk powder with foreign proteins using UHPLC-UV.

    PubMed

    Jablonski, Joseph E; Moore, Jeffrey C; Harnly, James M

    2014-06-01

    Chromatographic profiles of skim milk powder (SMP) and mixtures of SMP with soy (SPI), pea (PPI), brown rice (BRP), and hydrolyzed wheat protein (HWPI) isolates were obtained by ultrahigh-performance liquid chromatography (UHPLC) with 215 nm detection. Two data analysis approaches were compared for their utility to classify samples as authentic or adulterated. The t test approach evaluated data points exceeding the 99% confidence limit of the mean authentic SMP chromatogram and used data points from the entire chromatogram. The other approach used the multivariate Q statistic from a SIMCA model of authentic samples to determine adulteration and used a selected retention window to obtain best classifications. Q-Statistic and t test correctly classified adulteration of SMP with SPI at the 1% and 3% levels, respectively, while minimizing false classifications of authentic SMP. Detection of SMP adulterated with PPI, BRP, and HWPI was possible at higher adulteration levels. PMID:24811490

  13. Multivariate analysis of remote LIBS spectra using partial least squares, principal component analysis, and related techniques

    SciTech Connect

    Clegg, Samuel M; Barefield, James E; Wiens, Roger C; Sklute, Elizabeth; Dyare, Melinda D

    2008-01-01

    Quantitative analysis with LIBS traditionally employs calibration curves that are complicated by the chemical matrix effects. These chemical matrix effects influence the LIBS plasma and the ratio of elemental composition to elemental emission line intensity. Consequently, LIBS calibration typically requires a priori knowledge of the unknown, in order for a series of calibration standards similar to the unknown to be employed. In this paper, three new Multivariate Analysis (MV A) techniques are employed to analyze the LIBS spectra of 18 disparate igneous and highly-metamorphosed rock samples. Partial Least Squares (PLS) analysis is used to generate a calibration model from which unknown samples can be analyzed. Principal Components Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA) are employed to generate a model and predict the rock type of the samples. These MV A techniques appear to exploit the matrix effects associated with the chemistries of these 18 samples.

  14. Carcinogenic classification of polycyclic aromatic hydrocarbons through theoretical descriptors

    NASA Astrophysics Data System (ADS)

    Troche, Karla S.; Braga, Scheila F.; Coluci, Vitor R.; Galvão, Douglas S.

    Polycyclic aromatic hydrocarbons (PAHs) constitute an important family of molecules capable of inducing chemical carcinogenesis. In this work we report a comparative structure-activity relationship (SAR) study for 81 PAHs using different methodologies. The recently developed electronic indices methodology (EIM) with quantum descriptors obtained from different semiempirical methods (AM1, PM3, and PM5) was contrasted against more standard pattern recognition methods (PRMs), principal component analysis (PCA), hierarchical cluster analysis (HCA), Kth nearest neighbor (KNN), soft independent modeling of class analogies (SIMCA), and neural networks (NN). Our results show that PRMs validate the statistical value of electronic parameters derived from EIM analysis and their ability to identify active compounds. EIM outperformed more standard SAR methodologies and does not appear to be significantly Hamiltonian-dependent.

  15. Data-fusion for multiplatform characterization of an Italian craft beer aimed at its authentication.

    PubMed

    Biancolillo, Alessandra; Bucci, Remo; Magrì, Antonio L; Magrì, Andrea D; Marini, Federico

    2014-04-11

    Five different instrumental techniques: thermogravimetry, mid-infrared, near-infrared, ultra-violet and visible spectroscopies, have been used to characterize a high quality beer (Reale) from an Italian craft brewery (Birra del Borgo) and to differentiate it from other competing and lower quality products. Chemometric classification models were built on the separate blocks using soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) obtaining good predictive ability on an external test set (75% or higher depending on the technique). The use of data fusion strategies - in particular, the mid-level one - to integrate the data from the different platforms allowed the correct classification of all the training and validation samples. PMID:24745734

  16. Differentiation of Body Fluid Stains on Fabrics Using External Reflection Fourier Transform Infrared Spectroscopy (FT-IR) and Chemometrics.

    PubMed

    Zapata, Félix; de la Ossa, Ma Ángeles Fernández; García-Ruiz, Carmen

    2016-04-01

    Body fluids are evidence of great forensic interest due to the DNA extracted from them, which allows genetic identification of people. This study focuses on the discrimination among semen, vaginal fluid, and urine stains (main fluids in sexual crimes) placed on different colored cotton fabrics by external reflection Fourier transform infrared spectroscopy (FT-IR) combined with chemometrics. Semen-vaginal fluid mixtures and potential false positive substances commonly found in daily life such as soaps, milk, juices, and lotions were also studied. Results demonstrated that the IR spectral signature obtained for each body fluid allowed its identification and the correct classification of unknown stains by means of principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). Interestingly, results proved that these IR spectra did not show any bands due to the color of the fabric and no substance of those present in daily life which were analyzed, provided a false positive. PMID:26896150

  17. Circum-Arctic petroleum systems identified using decision-tree chemometrics

    USGS Publications Warehouse

    Peters, K.E.; Ramos, L.S.; Zumberge, J.E.; Valin, Z.C.; Scotese, C.R.; Gautier, D.L.

    2007-01-01

    Source- and age-related biomarker and isotopic data were measured for more than 1000 crude oil samples from wells and seeps collected above approximately 55??N latitude. A unique, multitiered chemometric (multivariate statistical) decision tree was created that allowed automated classification of 31 genetically distinct circumArctic oil families based on a training set of 622 oil samples. The method, which we call decision-tree chemometrics, uses principal components analysis and multiple tiers of K-nearest neighbor and SIMCA (soft independent modeling of class analogy) models to classify and assign confidence limits for newly acquired oil samples and source rock extracts. Geochemical data for each oil sample were also used to infer the age, lithology, organic matter input, depositional environment, and identity of its source rock. These results demonstrate the value of large petroleum databases where all samples were analyzed using the same procedures and instrumentation. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

  18. Differentiation of Aurantii Fructus Immaturus from Poniciri Trifoliatae Fructus Immaturus using Flow- injection Mass spectrometric (FIMS) Metabolic Fingerprinting Method Combined with Chemometrics

    PubMed Central

    Zhao, Yang; Chang, Yuan-Shiun; Chen, Pei

    2015-01-01

    A flow-injection mass spectrometric metabolic fingerprinting method in combination with chemometrics was used to differentiate Aurantii Fructus Immaturus from its counterfeit Poniciri Trifoliatae Fructus Immaturus. Flow-injection mass spectrometric (FIMS) fingerprints of 9 Aurantii Fructus Immaturus samples and 12 Poniciri Trifoliatae Fructus Immaturus samples were acquired and analyzed using principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). The authentic herbs were differentiated from their counterfeits easily. Eight characteristic components which were responsible for the difference between the samples were tentatively identified. Furthermore, three out of the eight components, naringin, hesperidin, and neohesperidin, were quantified. The results are useful to help identify the authenticity of Aurantii Fructus Immaturus. PMID:25622204

  19. Authentication of Tunisian virgin olive oils by chemometric analysis of fatty acid compositions and NIR spectra. Comparison with Maghrebian and French virgin olive oils.

    PubMed

    Laroussi-Mezghani, S; Vanloot, P; Molinet, J; Dupuy, N; Hammami, M; Grati-Kamoun, N; Artaud, J

    2015-04-15

    Six Tunisian virgin olive oil (VOO) varieties, Chemlali Sfax, Chetoui, Chemchali, Oueslati, Zarrazi and Zalmati, were characterised by two analytical methods. The gas chromatography allowed the determination of 14 fatty acids and squalene amounts. With fatty acids of each variety, a characteristic "morphotypes" for each oil variety was established. Chemlali Sfax and Zalmati showed strong similarities. Gas chromatography of fatty acid methyl esters (FAME) and near infrared (NIR) spectra of oils, associated to chemometric treatment, allowed the study of the inter-varietal variability and the verification of the variety origins of some Tunisian commercial VOOs. The specificity of Tunisian VOOs was evaluated by comparing the samples to Algerian, Moroccan and French Protected Designation of Origin VOOs. Classification in varietal origins by SIMCA used the FAME compositions and NIR spectra of the most represented varieties (Chemlali Sfax, Chetoui and Oueslati) showed a high potential to authenticate the varietal origin of Tunisian VOOs. PMID:25466003

  20. [The Classification of Wheat Varieties Based on Near Infrared Hyperspectral Imaging and Information Fusion].

    PubMed

    Dong, Gao; Guo, Jiani; Wang, Cheng; Chen, Zi-long; Zheng, Ling; Zhu, Da-zhou

    2015-12-01

    Hyperspectral imaging technology has great potential in the identification of crop varieties because it contains both image information and spectral information for the object. But so far most studies only used the spectral information, the image information has not been effectively utilized. In this study, hyperspectral images of single seed of three types including strong gluten wheat, medium gluten wheat, and weak gluten wheat were collected by near infrared hyperspectra imager, 12 morphological characteristics such as length, width, rectangularity, circularity and eccentricity were extracted, the average spectra of endosperm and embryo were acquired by the mask which was created by image segmentation. Partial least squares discriminant analysis (PLADA) and least squares support vector machine (LSSVM) were used to construct the classification model with image information, results showed that the binary classification accuracy between strong gluten wheat and weak gluten wheat could achieve 98%, for strong gluten wheat and medium gluten wheat, it was only 74.22%, which indicated that hyperspectral images could reflect the differences of varieties, but the accuracy might be poor when recognizing the varieties just by image information. Soft independent modeling of class analogy (SIMCA), PLSDA and LSSVM were used to established the classification model with spectral information, the classification effect of endosperm is slightly better than the embryo, it demonstrated that the grain shape could influence the classification accuracy. Then, we fused the spectral and image information, SIMCA, PLSDA and LSSVM were used to established the identification model, the fusion model showed better performance than the individual image model and spectral model, the classification accuracy which used the PLSDA raise from 96.67% to 98.89%, it showed that digging the morphological and spectral characteristics of the hyperspectral image could effectively improve the classification

  1. Physical profiling and IR spectroscopy: simple and effective methods to discriminate between genuine and counterfeit samples of Viagra® and Cialis®.

    PubMed

    Custers, Deborah; Vandemoortele, Suzanne; Bothy, Jean-Luc; De Beer, Jacques O; Courselle, Patricia; Apers, Sandra; Deconinck, Eric

    2016-03-01

    Counterfeit medicines are a global threat to public health. High amounts enter the European market, enforcing the need for simple techniques to help customs detect these pharmaceuticals. This study focused on physical profiling and IR spectroscopy to obtain a prime discrimination between genuine and illegal Viagra® and Cialis® medicines. Five post-tableting characteristics were explored: colour, mass, long length, short length, and thickness. Hypothesis testing showed that most illegal samples (between 60 and 100%) significantly differ from the genuine medicines, in particular for mass and long length. Classification and Regression Trees (CART) analysis resulted in a good discrimination between genuine and illegal medicines (98.93% correct classification rate for Viagra®, 99.42% for Cialis®). Moreover, CART confirmed the observation that mass and long length are the key physical characteristics which determine the observed discrimination. IR analysis was performed on tablets without blister and on tablets in intact blister. These data were analyzed using Soft Independent Modelling of Class Analogy (SIMCA) and Partial Least Squares - Discriminant Analysis (PLS-DA). Supervised techniques needed to be applied since Principal Component Analysis (PCA) was not able to generate the desired discrimination. Our study shows that a perfect discrimination between genuine and illegal medicines can be made by both SIMCA and PLS-DA without removing the tablets from the blister. This approach has the advantage of keeping the blister intact. Our study demonstrates that these user friendly techniques are reliable methods to aid customs to obtain a prime distinction between genuine and illegal samples on the spot. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26033891

  2. Incorporation of support vector machines in the LIBS toolbox for sensitive and robust classification amidst unexpected sample and system variability

    PubMed Central

    ChariDingari, Narahara; Barman, Ishan; Myakalwar, Ashwin Kumar; Tewari, Surya P.; Kumar, G. Manoj

    2012-01-01

    Despite the intrinsic elemental analysis capability and lack of sample preparation requirements, laser-induced breakdown spectroscopy (LIBS) has not been extensively used for real world applications, e.g. quality assurance and process monitoring. Specifically, variability in sample, system and experimental parameters in LIBS studies present a substantive hurdle for robust classification, even when standard multivariate chemometric techniques are used for analysis. Considering pharmaceutical sample investigation as an example, we propose the use of support vector machines (SVM) as a non-linear classification method over conventional linear techniques such as soft independent modeling of class analogy (SIMCA) and partial least-squares discriminant analysis (PLS-DA) for discrimination based on LIBS measurements. Using over-the-counter pharmaceutical samples, we demonstrate that application of SVM enables statistically significant improvements in prospective classification accuracy (sensitivity), due to its ability to address variability in LIBS sample ablation and plasma self-absorption behavior. Furthermore, our results reveal that SVM provides nearly 10% improvement in correct allocation rate and a concomitant reduction in misclassification rates of 75% (cf. PLS-DA) and 80% (cf. SIMCA)-when measurements from samples not included in the training set are incorporated in the test data – highlighting its robustness. While further studies on a wider matrix of sample types performed using different LIBS systems is needed to fully characterize the capability of SVM to provide superior predictions, we anticipate that the improved sensitivity and robustness observed here will facilitate application of the proposed LIBS-SVM toolbox for screening drugs and detecting counterfeit samples as well as in related areas of forensic and biological sample analysis. PMID:22292496

  3. Classification of diesel pool refinery streams through near infrared spectroscopy and support vector machines using C-SVC and ν-SVC

    NASA Astrophysics Data System (ADS)

    Alves, Julio Cesar L.; Henriques, Claudete B.; Poppi, Ronei J.

    2014-01-01

    The use of near infrared (NIR) spectroscopy combined with chemometric methods have been widely used in petroleum and petrochemical industry and provides suitable methods for process control and quality control. The algorithm support vector machines (SVM) has demonstrated to be a powerful chemometric tool for development of classification models due to its ability to nonlinear modeling and with high generalization capability and these characteristics can be especially important for treating near infrared (NIR) spectroscopy data of complex mixtures such as petroleum refinery streams. In this work, a study on the performance of the support vector machines algorithm for classification was carried out, using C-SVC and ν-SVC, applied to near infrared (NIR) spectroscopy data of different types of streams that make up the diesel pool in a petroleum refinery: light gas oil, heavy gas oil, hydrotreated diesel, kerosene, heavy naphtha and external diesel. In addition to these six streams, the diesel final blend produced in the refinery was added to complete the data set. C-SVC and ν-SVC classification models with 2, 4, 6 and 7 classes were developed for comparison between its results and also for comparison with the soft independent modeling of class analogy (SIMCA) models results. It is demonstrated the superior performance of SVC models especially using ν-SVC for development of classification models for 6 and 7 classes leading to an improvement of sensitivity on validation sample sets of 24% and 15%, respectively, when compared to SIMCA models, providing better identification of chemical compositions of different diesel pool refinery streams.

  4. Detection of organic residues on food processing equipment surfaces by spectral imaging method

    NASA Astrophysics Data System (ADS)

    Qin, Jianwei; Jun, Won; Kim, Moon S.; Chao, Kaunglin

    2010-04-01

    Organic residues on equipment surfaces in poultry processing plants can generate cross contamination and increase the risk of unsafe food for consumers. This research was aimed to investigate the potential of LED-induced fluorescence imaging technique for rapid inspection of organic residues on poultry processing equipment surfaces. High-power blue LEDs with a spectral output at 410 nm were used as the excitation source for a line-scanning hyperspectral imaging system. Common chicken residue samples including fat, blood, and feces from ceca, colon, duodenum, and small intestine were prepared on stainless steel sheets. Fluorescence emission images were acquired from 120 samples (20 for each type of residue) in the wavelength range of 500-700 nm. LED-induced fluorescence characteristics of the tested samples were determined. PCA (principal component analysis) was performed to analyze fluorescence spectral data. Two SIMCA (soft independent modeling of class analogy) models were developed to differentiate organic residues and stainless steel samples. Classification accuracies using 2-class ('stainless steel' and 'organic residue') and 4-class ('stainless steel', 'fat', 'blood', and 'feces') SIMCA models were 100% and 97.5%, respectively. An optimal single-band and a band-pair that are promising for rapid residue detection were identified by correlation analysis. The single-band approach using the selected wavelength of 666 nm could generate false negative errors for chicken blood inspection. Two-band ratio images using 503 and 666 nm (F503/F666) have great potential for detecting various chicken residues on stainless steel surfaces. This wavelength pair can be adopted for developing a LED-based hand-held fluorescence imaging device for inspecting poultry processing equipment surfaces.

  5. Evaluation of different grades of ginseng using Fourier-transform infrared and two-dimensional infrared correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Zhang, Yan-ling; Chen, Jian-bo; Lei, Yu; Zhou, Qun; Sun, Su-qin; Noda, Isao

    2010-06-01

    Ginseng is one of the most widely used herbal medicines which have many kinds of pharmaceutical values. The discrimination of grades of ginseng includes the cultivation types and the growth years herein. To evaluate the different grades of ginseng, the fibrous roots and rhizome roots of ginseng were analyzed by Fourier-transform infrared and two-dimensional infrared correlation spectroscopy in this paper. The fibrous root and rhizome root of ginseng have different content of starch, calcium oxalate and other components. For the fibrous roots of ginseng, mountain cultivation ginseng (MCG), garden cultivation ginseng (GCG) and transplanted cultivation ginseng (TCG) have clear difference in the infrared spectra and second derivative spectra in the range of 1800-400 cm -1, and clearer difference was observed in the range of 1045-1160 and 1410-1730 cm -1 in 2D synchronous correlation spectra. Three kinds of ginseng can be clustered very well by using SIMCA analysis on the basis of PCA as well. For the rhizome roots, the content of calcium oxalate and starch change with growth years in the IR spectra, and some useful procedure can be obtained by the analysis of 2D IR synchronous spectra in the range of 1050-1415 cm -1. Also, ginsengs cultivated in different growth years were clustered perfectly by using SIMCA analysis. The results suggested that different grades of ginseng can be well recognized using the mid-infrared spectroscopy assisted by 2D IR correlation spectroscopy, which provide the macro-fingerprint characteristics of ginseng in different parts and supplied a rapid, effective approach for the evaluation of the quality of ginseng.

  6. Classification of diesel pool refinery streams through near infrared spectroscopy and support vector machines using C-SVC and ν-SVC.

    PubMed

    Alves, Julio Cesar L; Henriques, Claudete B; Poppi, Ronei J

    2014-01-01

    The use of near infrared (NIR) spectroscopy combined with chemometric methods have been widely used in petroleum and petrochemical industry and provides suitable methods for process control and quality control. The algorithm support vector machines (SVM) has demonstrated to be a powerful chemometric tool for development of classification models due to its ability to nonlinear modeling and with high generalization capability and these characteristics can be especially important for treating near infrared (NIR) spectroscopy data of complex mixtures such as petroleum refinery streams. In this work, a study on the performance of the support vector machines algorithm for classification was carried out, using C-SVC and ν-SVC, applied to near infrared (NIR) spectroscopy data of different types of streams that make up the diesel pool in a petroleum refinery: light gas oil, heavy gas oil, hydrotreated diesel, kerosene, heavy naphtha and external diesel. In addition to these six streams, the diesel final blend produced in the refinery was added to complete the data set. C-SVC and ν-SVC classification models with 2, 4, 6 and 7 classes were developed for comparison between its results and also for comparison with the soft independent modeling of class analogy (SIMCA) models results. It is demonstrated the superior performance of SVC models especially using ν-SVC for development of classification models for 6 and 7 classes leading to an improvement of sensitivity on validation sample sets of 24% and 15%, respectively, when compared to SIMCA models, providing better identification of chemical compositions of different diesel pool refinery streams. PMID:24012979

  7. Modos de produccion cientifica: Culturas y metodologias de investigacion en la Universidad de Cadiz

    NASA Astrophysics Data System (ADS)

    Gonzalez Ramos, Ana M.

    2004-12-01

    Este trabajo de investigacion supone un modelo teorico de caracter aplicado, que proporciona la oportunidad de evaluar la produccion cientifica de los investigadores. Se encuadra dentro de la tradiccion de la estadistica aplicada y la sociologia del conocimiento. Atiende especialmente a dos conjuntos de temas de interes, por una parte, las caracteristicas principales que determinan el nivel y tipo de produccion academica producida por las unidades de investigacion y por los propios investigadores; por otra, la utilizacion que se hace de los metodos y tecnicas de investigacion puesto que de ello tambien depende el modo de produccion cientifica. Los puntos novedosos de esta tesis son: la medicion cuantitativa del objeto de estudio, la suma de los productos y las condiciones externas a la produccion del conocimiento mas otros elementos internos como las caracteristicas de los investigadores y la metodologia utilizada para desarrollar sus trabajos; y, finalmente, el uso de las nuevas tecnologias. El aprovechamiento de los recursos estadisticos y las fuentes de informacion secundarias se complementan con el diseno propio de una encuesta donde se implementa las caracteristicas descritas en un capitulo anterior sobre los metodos cientificos mas idoneos descritos en los principales manuales y articulos cientificos desde distintas disciplinas de conocimiento. Dicha encuesta ha sido desarrollada como un programa propio y en base a los mas innovadores usos de la tecnologia en la metodologia de encuestas.

  8. Short communication: Effect of storage temperature on the solubility of milk protein concentrate 80 (MPC80) treated with NaCl or KCl.

    PubMed

    Sikand, V; Tong, P S; Walker, J; Wang, T; Rodriguez-Saona, L E

    2016-03-01

    A previous study in our laboratory showed that addition of 150 mM NaCl or KCl into diafiltration water improved the solubility of freshly made milk protein concentrate 80 (MPC80). In the present study, the objectives were (1) to evaluate the solubility of NaCl- or KCl-treated MPC80 samples kept at varying temperatures and then stored for extensive periods at room temperature (21°C ± 1°C); and (2) to determine if MPC80 samples stored at different temperatures and protein conformation can be grouped or categorized together. Freshly manufactured MPC80 samples were untreated (control), processed with NaCl, or processed with KCl. One set of sample bags was stored at 4°C; second and third sets of bags were kept at 25°C and 55°C for 1 mo (31d) and then transferred to room temperature (21°C ± 1°C) storage conditions for 1 yr (365d). Samples were tested for nitrogen solubility index (NSI) and for protein changes by Fourier-transform infrared (FTIR) spectroscopy. Analysis of variance results for NSI showed 2 significantly different groupings of MPC80 samples. The more soluble group contained samples treated with NaCl or KCl and stored at either 4°C or 25°C. These samples had mean NSI >97.5%. The less soluble groups contained all control samples, regardless of storage temperature, and NaCl- or KCl-treated samples stored at 55°C. These samples had mean NSI from 39.5 to 58%. Within each of these groups (more soluble and less soluble), no significant differences in solubility were detected. Pattern recognition analysis by soft independent modeling of class analogy (SIMCA) was used to assess protein changes during storage by monitoring the amide I and amide II (1,700(-1) to 1,300cm(-1)) regions. Dominant bands were observed at 1,385cm(-1) for control, 1,551cm(-1) for KCl-treated samples, and 1,694cm(-1) for NaCl-treated samples. Moreover, SIMCA clustered the MPC80 samples stored at 4°C separately from samples stored at 25°C and 55°C. This study demonstrates that (1

  9. Choice and validation of a near infrared spectroscopic application for the identity control of starting materials. practical experience with the EU draft Note for Guidance on the use of near infrared spectroscopy by the pharmaceutical industry and the data to be forwarded in part II of the dossier for a marketing authorization.

    PubMed

    Vredenbregt, M J; Caspers, P W J; Hoogerbrugge, R; Barends, D M

    2003-11-01

    Recently the CPMP/CVMP sent out for consultation the draft Note for Guidance (dNfG) on the use of near infrared spectroscopy (NIRS) by the pharmaceutical industry and the data to be forwarded in part II of the dossier for a marketing authorization. We explored the practicability of this dNfG with respect to the verification of the correct identity of starting materials in a generic tablet-manufacturing site. Within the boundaries of the dNfG, a release procedure was developed for 12 substances containing structurally related compounds and substances differing only in particle size. For the method development literature data were also taken into consideration. Good results were obtained with wavelength correlation (WC), applied on raw spectra or second derivative spectra both without smoothing. The defined threshold of 0.98 for raw spectra differentiated between all molecular structures. Both methods were found to be robust over a period of 1 year. For the differentiation between the different particle sizes a subsequent second chemometric technique had to be used. Soft independent modelling of class analogy (SIMCA) with a probability level of 0.01 proved suitable. Internal and external validation I according to the dNfG showed no incorrect rejections or false acceptances. External validation II according to the dNfG was carried out with 95 potentially interfering substances from which 46 were tested experimentally. Macrogol 400 was not distinguished from macrogol 300. For the complete verification of the identity of macrogol 300 test A of the European Pharmacopoeia is needed in addition to the NIRS application. A release procedure developed with WC applied on raw spectra and SIMCA as a second method, which is different from the preferred method of the dNfG, was tested in practice with good results. We conclude that the dNfG has good practicability and that deviations from the preferred methods of the dNfG can also give good differentiation. PMID:14602194

  10. Quality control method to measure predator evasion in wild and mass-reared Mediterranean fruit flies (Diptera: Tephritidae)

    SciTech Connect

    Hendrichs, M.; Wornoayporn, V.; Hendrichs, J.

    2007-03-15

    varias razones, incluyendo perdidas debidas a diferentes tipos de depredadores. Estudios anteriores conducidos en el campo, y en jaulas de campo, han confirmado que las cepas de machos de laboratorio tienen menos capacidad de evadir depredadores que los machos silvestres. Estos estudios involucran, sin embargo, una considerable cantidad de manipulacion y observacion de depredadores, por lo que no son adecuados para ser usados como medidas rutinarias en los programas de cria masiva. Aqui describimos un metodo sencillo de control de calidad usando aspiradores para medir agilidad en la mosca del Mediterraneo y mostramos que este parametro esta relacionado a la capacidad de la moscas a evadir a depredadores. Aunque aun es necesario refinar la estandarizacion de este metodo para permitir la comparacion entre cepas, los resultados confirman la importancia de tener un metodo rutinario para medir la capacidad de evasion de depredadores en cepas de cria de laboratorio de la mosca del Mediterraneo. Ademas de medir este parametro de control de calidad de los machos esteriles, el metodo descrito podria tambien ser usado para la seleccion sistematica de cepas con una mayor capacidad de evasion de depredadores. (author)

  11. [Historical evolution of inguinal hernia treatment].

    PubMed

    Rodríguez-Ortega, M Fernando; Cárdenas-Martínez, Guadalupe; López-Castañeda, Hugo

    2003-01-01

    Hernia (know breuk in Dutch, rompure in French, keal in Greek and rupture in English) has plagued humans throughout recorded history and descriptions of hernia reduction date back to the Ebers papyrus in Egypt. In medicine it is difficult to find historical periods, but we found two eras of uneven time: pre-technique and technique. The first was distinguished by a blend of empiricism and magic, and the second for greater comprehension of the human body; however much of modern surgical techniques result from contributions of early surgeons. Nonetheless, it was not until the late 19th century that hernia surgeon Eduardo Bassini published his work Nuovo Metodo per la Cura Radiacale dell"Ernia Inguinale (in 1889). Among the most notable contemporany classic hernia repairs are the Bassini, Halsted, Shouldice, and Tension-free repair techniques. PMID:14617414

  12. L'eliosismologia: onde sismiche per studiare l'interno del Sole

    NASA Astrophysics Data System (ADS)

    Di Mauro, M. P.

    2014-12-01

    Negli ultimi cinquanta anni siamo stati testimoni di una straordinaria rivoluzione della conoscenza e comprensione della nostra stella grazie alla nascita dell'Eliosismologia, lo studio delle oscillazioni solari. Analogamente a ciò che accade nella Terra durante i terremoti, anche l'interno del Sole è pervaso continuamente da onde sismiche che provocano piccole oscillazioni, ovvero deformazioni della fotosfera. Le oscillazioni sono la manifestazione di diversi processi che avvengono all'interno della struttura del Sole e le frequenze sismiche dei modi osservati e misurati sulla superficie sono legate direttamente ai parametri fisici degli strati interni attraversati dalle onde sismiche. Lo studio delle oscillazioni rappresenta, quindi, l'unico metodo diretto per studiare la struttura e la dinamica interna del Sole. In questo articolo verranno illustrate le caratteristiche generali delle oscillazioni solari e verranno presentati i risultati importanti e i progressi notevoli raggiunti grazie all'Eliosismologia.

  13. Quarry identification of historical building materials by means of laser induced breakdown spectroscopy, X-ray fluorescence and chemometric analysis

    NASA Astrophysics Data System (ADS)

    Colao, F.; Fantoni, R.; Ortiz, P.; Vazquez, M. A.; Martin, J. M.; Ortiz, R.; Idris, N.

    2010-08-01

    To characterize historical building materials according to the geographic origin of the quarries from which they have been mined, the relative content of major and trace elements were determined by means of Laser Induced Breakdown Spectroscopy (LIBS) and X-ray Fluorescence (XRF) techniques. 48 different specimens were studied and the entire samples' set was divided in two different groups: the first, used as reference set, was composed by samples mined from eight different quarries located in Seville province; the second group was composed by specimens of unknown provenance collected in several historical buildings and churches in the city of Seville. Data reduction and analysis on laser induced breakdown spectroscopy and X-ray fluorescence measurements was performed using multivariate statistical approach, namely the Linear Discriminant Analysis (LDA), Principal Component Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). A clear separation among reference sample materials mined from different quarries was observed in Principal Components (PC) score plots, then a supervised soft independent modeling of class analogy classification was trained and run, aiming to assess the provenance of unknown samples according to their elemental content. The obtained results were compared with the provenance assignments made on the basis of petrographical description. This work gives experimental evidence that laser induced breakdown spectroscopy measurements on a relatively small set of elements is a fast and effective method for the purpose of origin identification.

  14. Sequential (step-by-step) detection, identification and quantitation of extra virgin olive oil adulteration by chemometric treatment of chromatographic profiles.

    PubMed

    Capote, F Priego; Jiménez, J Ruiz; de Castro, M D Luque

    2007-08-01

    An analytical method for the sequential detection, identification and quantitation of extra virgin olive oil adulteration with four edible vegetable oils--sunflower, corn, peanut and coconut oils--is proposed. The only data required for this method are the results obtained from an analysis of the lipid fraction by gas chromatography-mass spectrometry. A total number of 566 samples (pure oils and samples of adulterated olive oil) were used to develop the chemometric models, which were designed to accomplish, step-by-step, the three aims of the method: to detect whether an olive oil sample is adulterated, to identify the type of adulterant used in the fraud, and to determine how much aldulterant is in the sample. Qualitative analysis was carried out via two chemometric approaches--soft independent modelling of class analogy (SIMCA) and K nearest neighbours (KNN)--both approaches exhibited prediction abilities that were always higher than 91% for adulterant detection and 88% for type of adulterant identification. Quantitative analysis was based on partial least squares regression (PLSR), which yielded R2 values of >0.90 for calibration and validation sets and thus made it possible to determine adulteration with excellent precision according to the Shenk criteria. PMID:17611742

  15. Classification of dopamine, serotonin, and dual antagonists by decision trees.

    PubMed

    Kim, Hye-Jung; Choo, Hyunah; Cho, Yong Seo; Koh, Hun Yeong; No, Kyoung Tai; Pae, Ae Nim

    2006-04-15

    Dopamine antagonists (DA), serotonin antagonists (SA), and serotonin-dopamine dual antagonists (Dual) are being used as antipsychotics. A lot of dopamine and serotonin antagonists reveal non-selective binding affinity against these two receptors because the antagonists share structurally common features originated from conserved residues of binding site of the aminergic receptor family. Therefore, classification of dopamine and serotonin antagonists into their own receptors can be useful in the designing of selective antagonist for individual therapy of antipsychotic disorders. Data set containing 1135 dopamine antagonists (D2, D3, and D4), 1251 serotonin antagonists (5-HT1A, 5-HT2A, and 5-HT2C), and 386 serotonin-dopamine dual antagonists was collected from the MDDR database. Cerius2 descriptors were employed to develop a classification model for the 2772 compounds with antipsychotic activity. LDA (linear discriminant analysis), SIMCA (soft independent modeling of class analogy), RP (recursive partitioning), and ANN (artificial neural network) algorithms successfully classified the active class of each compound at the average 73.6% and predicted at the average 69.8%. The decision trees from RP, the best model, were generated to identify and interpret those descriptors that discriminate the active classes more easily. These classification models could be used as a virtual screening tool to predict the active class of new candidates. PMID:16387502

  16. Use of ATR-FTIR spectroscopy coupled with chemometrics for the authentication of avocado oil in ternary mixtures with sunflower and soybean oils.

    PubMed

    Jiménez-Sotelo, Paola; Hernández-Martínez, Maylet; Osorio-Revilla, Guillermo; Meza-Márquez, Ofelia Gabriela; García-Ochoa, Felipe; Gallardo-Velázquez, Tzayhrí

    2016-07-01

    Avocado oil is a high-value and nutraceutical oil whose authentication is very important since the addition of low-cost oils could lower its beneficial properties. Mid-FTIR spectroscopy combined with chemometrics was used to detect and quantify adulteration of avocado oil with sunflower and soybean oils in a ternary mixture. Thirty-seven laboratory-prepared adulterated samples and 20 pure avocado oil samples were evaluated. The adulterated oil amount ranged from 2% to 50% (w/w) in avocado oil. A soft independent modelling class analogy (SIMCA) model was developed to discriminate between pure and adulterated samples. The model showed recognition and rejection rate of 100% and proper classification in external validation. A partial least square (PLS) algorithm was used to estimate the percentage of adulteration. The PLS model showed values of R(2) > 0.9961, standard errors of calibration (SEC) in the range of 0.3963-0.7881, standard errors of prediction (SEP estimated) between 0.6483 and 0.9707, and good prediction performances in external validation. The results showed that mid-FTIR spectroscopy could be an accurate and reliable technique for qualitative and quantitative analysis of avocado oil in ternary mixtures. PMID:27314226

  17. Classification of structurally related commercial contrast media by near infrared spectroscopy.

    PubMed

    Yip, Wai Lam; Soosainather, Tom Collin; Dyrstad, Knut; Sande, Sverre Arne

    2014-03-01

    Near infrared spectroscopy (NIRS) is a non-destructive measurement technique with broad application in pharmaceutical industry. Correct identification of pharmaceutical ingredients is an important task for quality control. Failure in this step can result in several adverse consequences, varied from economic loss to negative impact on patient safety. We have compared different methods in classification of a set of commercially available structurally related contrast media, Iodixanol (Visipaque(®)), Iohexol (Omnipaque(®)), Caldiamide Sodium and Gadodiamide (Omniscan(®)), by using NIR spectroscopy. The performance of classification models developed by soft independent modelling of class analogy (SIMCA), partial least squares discriminant analysis (PLS-DA) and Main and Interactions of Individual Principal Components Regression (MIPCR) were compared. Different variable selection methods were applied to optimize the classification models. Models developed by backward variable elimination partial least squares regression (BVE-PLS) and MIPCR were found to be most effective for classification of the set of contrast media. Below 1.5% of samples from the independent test set were not recognized by the BVE-PLS and MIPCR models, compared to up to 15% when models developed by other techniques were applied. PMID:24374816

  18. Multivariate screening in food adulteration: untargeted versus targeted modelling.

    PubMed

    López, M Isabel; Trullols, Esther; Callao, M Pilar; Ruisánchez, Itziar

    2014-03-15

    Two multivariate screening strategies (untargeted and targeted modelling) have been developed to compare their ability to detect food fraud. As a case study, possible adulteration of hazelnut paste is considered. Two different adulterants were studied, almond paste and chickpea flour. The models were developed from near-infrared (NIR) data coupled with soft independent modelling of class analogy (SIMCA) as a classification technique. Regarding the untargeted strategy, only unadulterated samples were modelled, obtaining 96.3% of correct classification. The prediction of adulterated samples gave errors between 5.5% and 2%. Regarding targeted modelling, two classes were modelled: Class 1 (unadulterated samples) and Class 2 (almond adulterated samples). Samples adulterated with chickpea were predicted to prove its ability to deal with non-modelled adulterants. The results show that samples adulterated with almond were mainly classified in their own class (90.9%) and samples with chickpea were classified in Class 2 (67.3%) or not in any class (30.9%), but no one only as unadulterated. PMID:24206702

  19. Combining information from headspace mass spectrometry and visible spectroscopy in the classification of the Ligurian olive oils.

    PubMed

    Casale, Monica; Armanino, Carla; Casolino, Chiara; Forina, Michele

    2007-04-18

    An electronic nose and an UV-Vis spectrophotometer, in combination with multivariate analysis, have been used to verify the geographical origin of extra virgin olive oils. Forty-six oil samples from three different areas of Liguria were included in this analysis. Initially, the data obtained from the two instruments were analysed separately. Then, the potential of the synergy between these two technologies for testing food authenticity and quality was investigated. Application of Linear Discriminant Analysis, after feature selection, was sufficient to differentiate the three geographical denominations of Liguria ("Riviera dei Fiori", "Riviera del Ponente Savonese" and "Riviera di Levante"), obtaining 100% success in classification and close to 100% in prediction. The models built using SIMCA as a class-modelling tool, were not so effective, but confirmed that the results improve using the synergy between different analytical techniques. This paper shows that objective instrumental data related to two important organoleptic features such as oil colour and aroma, supply complementary information. PMID:17397658

  20. Classification of commercial wines from the Canary Islands (Spain) by chemometric techniques using metallic contents.

    PubMed

    Frías, Sergio; Conde, José E; Rodríguez-Bencomo, Juan J; García-Montelongo, Francisco; Pérez-Trujillo, Juan P

    2003-02-01

    Eleven elements, K, Na, Ca, Mg, Fe, Cu, Zn, Mn, Sr, Li and Rb, were determined in dry and sweet wines bearing the denominations of origin of El Hierro, La Palma and Lanzarote islands (Canary Islands, Spain). Analyses were performed by flame atomic absorption spectrophotometry, with the exceptions of lithium and rubidium for which flame atomic emission spectrophotometry was used. Sweet wines from La Palma were elaborated as naturally sweet with over-ripe grapes and significant differences were found in all the analysed elements with the exceptions of sodium, iron and rubidium with regard to dry wines from the same island. Contrarily, sweet wines from Lanzarote elaborated with grapes in a similar ripening state to dry wines did not present significant differences between them with the exception of strontium, the content of which was greater in dry wines. Among the three islands, significant differences in mean content were found with the exceptions of iron and copper. Cluster analysis and principal component analysis show differences in wines according to the island of origin and the ripening state of the grapes. Linear discriminant analysis using rubidium, sodium, manganese and strontium, the four most discriminant elements, gave 100% recognition ability and 95.6% prediction ability. The sensitivity and specificity obtained using soft independent modelling of class analogy (SIMCA) as a modelling multivariate technique were both 100% for El Hierro and Lanzarote, and 100 and 95%, respectively, for La Palma. The modelling and discriminant capacities of the different metals were also studied. PMID:18968916

  1. Metabolomics analysis in rats after administration of Datura stramonium

    PubMed Central

    Zhang, Meiling; Bao, Shihui; Lin, Feiou; Lin, Yingying; Zhang, Lijing; Xu, Mengzhi; Huang, Xueli; Wen, Congcong; Hu, Lufeng; Lin, Guanyang

    2015-01-01

    This study aimed to evaluate the effect of Datura stramonium on rats by examining the differences in urine and serum metabolites between Datura stramonium groups and control group. SIMCA-P+12.0.1.0 software was used for partial least-squares discriminant analysis (PLS-DA) to screen for the differential metabolites. Fifteen metabolites in urine including malonic acid, pentanedioic acid, D-xylose, D-ribose, xylulose, azelaic acid, threitol, glycine, butanoic acid, D-mannose, D-gluconic acid, galactonic acid, myo-inositol, octadecanoic acid, pseudouridine and ten metabolites in serum including alanine, butanedioic acid, L-methionine, propanedioic acid, hexadecanoic acid, D-fructose, tetradecanoic acid, D-glucose, D-galactose, oleic acid were selected as the characteristic metabolites. The PLS-DA scores plot indicated that serum and urine metabolites have a variety of changes among low dose group, high dose group and control group. These metabolites were related with amino metabolism, lipid metabolism and energy metabolism. The result reflected the relationship between metabolites in rat fluid and Datura stramonium spectra. Potential differences in metabolites and metabolic pathway analysis showed that the establishment of urine and serum metabolomics methods for further evaluating drug has great significance. PMID:26885052

  2. Using UV-Vis spectroscopy for simultaneous geographical and varietal classification of tea infusions simulating a home-made tea cup.

    PubMed

    Diniz, Paulo Henrique Gonçalves Dias; Barbosa, Mayara Ferreira; de Melo Milanez, Karla Danielle Tavares; Pistonesi, Marcelo Fabián; de Araújo, Mário César Ugulino

    2016-02-01

    In this work we proposed a method to verify the differentiating characteristics of simple tea infusions prepared in boiling water alone (simulating a home-made tea cup), which represents the final product as ingested by the consumers. For this purpose we used UV-Vis spectroscopy and variable selection through the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA) for simultaneous classification of the teas according to their variety and geographic origin. For comparison, KNN, CART, SIMCA, PLS-DA and PCA-LDA were also used. SPA-LDA and PCA-LDA provided significantly better results for tea classification of the five studied classes (Argentinean green tea; Brazilian green tea; Argentinean black tea; Brazilian black tea; and Sri Lankan black tea). The proposed methodology provides a simpler, faster and more affordable classification of simple tea infusions, and can be used as an alternative approach to traditional tea quality evaluation as made by skilful tasters, which is evidently partial and cannot assess geographic origins. PMID:26304362

  3. Near-infrared spectroscopy (NIRS) and chemometric analysis of Malaysian and UK paracetamol tablets: a spectral database study.

    PubMed

    Said, Mazlina M; Gibbons, Simon; Moffat, Anthony C; Zloh, Mire

    2011-08-30

    The influx of medicines from different sources into healthcare systems of developing countries presents a challenge to monitor their origin and quality. The absence of a repository of reference samples or spectra prevents the analysis of tablets by direct comparison. A set of paracetamol tablets purchased in Malaysian pharmacies were compared to a similar set of sample purchased in the UK using near-infrared spectroscopy (NIRS). Additional samples of products containing ibuprofen or paracetamol in combination with other actives were added to the study as negative controls. NIR spectra of the samples were acquired and compared by using multivariate modeling and classification algorithms (PCA/SIMCA) and stored in a spectral database. All analysed paracetamol samples contained the purported active ingredient with only 1 out of 20 batches excluded from the 95% confidence interval, while the negative controls were clearly classified as outliers of the set. Although the substandard products were not detected in the purchased sample set, our results indicated variability in the quality of the Malaysian tablets. A database of spectra was created and search methods were evaluated for correct identification of tablets. The approach presented here can be further developed as a method for identifying substandard pharmaceutical products. PMID:21645600

  4. Detection of UV-induced cyclobutane pyrimidine dimers by near-infrared spectroscopy and aquaphotomics

    PubMed Central

    Goto, Noriko; Bazar, Gyorgy; Kovacs, Zoltan; Kunisada, Makoto; Morita, Hiroyuki; Kizaki, Seiichiro; Sugiyama, Hiroshi; Tsenkova, Roumiana; Nishigori, Chikako

    2015-01-01

    Ultraviolet (UV) radiation causes cellular DNA damage, among which cyclobutane pyrimidine dimers (CPDs) are responsible for a variety of genetic mutations. Although several approaches have been developed for detection of CPDs, conventional methods require time-consuming steps. Aquaphotomics, a new approach based on near-infrared spectroscopy (NIRS) and multivariate analysis that determines interactions between water and other components of the solution, has become an effective method for qualitative and quantitative parameters measurement in the solutions. NIR spectral patterns of UVC-irradiated and nonirradiated DNA solutions were evaluated using aquaphotomics for detection of UV-induced CPDs. Groups of UV-irradiated and nonirradiated DNA samples were classified (87.5% accuracy) by soft independent modeling of class analogy (SIMCA). A precise regression model calculated from NIR water spectral patterns based on UVC doses (r Val = 0.9457) and the concentration of cis-syn cyclobutane thymine dimers (cis-syn T<>Ts; r Val = 0.9993) was developed using partial least squares regression (PLSR), while taking advantage of water spectral patterns, particularly around 1400–1500 nm. Our results suggested that, in contrast to DNA, the formation of cis-syn T<>Ts increased the strongly hydrogen bonded water. Additionally, NIRS could qualitatively and quantitatively detect cis-syn T<>Ts in isolated DNA aqueous solutions upon UVC exposure. PMID:26133899

  5. Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil

    NASA Astrophysics Data System (ADS)

    Yu, Ke-Qiang; Zhao, Yan-Ru; Liu, Fei; He, Yong

    2016-06-01

    The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil.

  6. Rapid detection and quantification of milk adulteration using infrared microspectroscopy and chemometrics analysis.

    PubMed

    Santos, P M; Pereira-Filho, E R; Rodriguez-Saona, L E

    2013-05-01

    The application of attenuated total reflectance mid-infrared microspectroscopy (MIR-microspectroscopy) was evaluated as a rapid method for detection and quantification of milk adulteration. Milk samples were purchased from local grocery stores (Columbus, OH, USA) and spiked at different concentrations of whey, hydrogen peroxide, synthetic urine, urea and synthetic milk. Samples were place on a 192-well microarray slide, air-dried and spectra were collected by using MIR-microspectroscopy. Pattern recognition analysis by Soft Independent Modeling of Class Analogy (SIMCA) showed tight and well-separated clusters allowing discrimination of control samples from adulterated milk. Partial Least Squares Regression (PLSR) showed standard error of prediction (SEP) ~2.33, 0.06, 0.41, 0.30 and 0.014 g/L for estimation of levels of adulteration with whey, synthetic milk, synthetic urine, urea and hydrogen peroxide, respectively. Results showed that MIR-microspectroscopy can provide an alternative methodology to the dairy industry for screening potential fraudulent practice for economic adulteration of cow's milk. PMID:23265450

  7. N-Glycan profile analysis of transferrin using a microfluidic compact disc and MALDI-MS.

    PubMed

    Quaranta, Alessandro; Sroka-Bartnicka, Anna; Tengstrand, Erik; Thorsén, Gunnar

    2016-07-01

    It has been known for a long time that diseases can be associated with changes to the glycosylation of specific proteins. This has been shown for cancer, immunological disorders, and neurodegenerative diseases. The possibility of using the glycosylation patterns of proteins as biomarkers for disease would be a great asset for clinical research or diagnosis. There is at present a lack of rapid, automated, and cost-efficient analytical techniques for the determination of the glycosylation of specific serum proteins. We have developed a method for determining the glycosylation pattern of proteins based on the affinity capture of a specific serum protein, the enzymatic release of the N-linked glycans, and the analysis of the glycan pattern using MALDI-MS. All sample preparation is performed in a disposable centrifugal microfluidic disc. The sample preparation is miniaturized, requiring only 1 μL of sample per determination, and automated with the possibility of processing 54 samples in parallel in 3.5 h. We have developed a method for the glycosylation pattern analysis of transferrin. The method has been tested on serum samples from chronic alcohol abusers and a control group. Also, a SIMCA model was created and evaluated to discriminate between the two groups. PMID:27137515

  8. Characterization and authentication of a novel vegetable source of omega-3 fatty acids, sacha inchi (Plukenetia volubilis L.) oil.

    PubMed

    Maurer, Natalie E; Hatta-Sakoda, Beatriz; Pascual-Chagman, Gloria; Rodriguez-Saona, Luis E

    2012-09-15

    Consumption of omega-3 fatty acids (ω-3's), whether from fish oils, flax or supplements, can protect against cardiovascular disease. Finding plant-based sources of the essential ω-3's could provide a sustainable, renewable and inexpensive source of ω-3's, compared to fish oils. Our objective was to develop a rapid test to characterize and detect adulteration in sacha inchi oils, a Peruvian seed containing higher levels of ω-3's in comparison to other oleaginous seeds. A temperature-controlled ZnSe ATR mid-infrared benchtop and diamond ATR mid-infrared portable handheld spectrometers were used to characterize sacha inchi oil and evaluate its oxidative stability compared to commercial oils. A soft independent model of class analogy (SIMCA) and partial least squares regression (PLSR) analyzed the spectral data. Fatty acid profiles showed that sacha inchi oil (44% linolenic acid) had levels of PUFA similar to those of flax oils. PLSR showed good correlation coefficients (R(2)>0.9) between reference tests and spectra from infrared devices, allowing for rapid determination of fatty acid composition and prediction of oxidative stability. Oils formed distinct clusters, allowing the evaluation of commercial sacha inchi oils from Peruvian markets and showed some prevalence of adulteration. Determining oil adulteration and quality parameters, by using the ATR-MIR portable handheld spectrometer, allowed for portability and ease-of-use, making it a great alternative to traditional testing methods. PMID:23107745

  9. Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil.

    PubMed

    Yu, Ke-Qiang; Zhao, Yan-Ru; Liu, Fei; He, Yong

    2016-01-01

    The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil. PMID:27279284

  10. The Verification of the Usefulness of Electronic Nose Based on Ultra-Fast Gas Chromatography and Four Different Chemometric Methods for Rapid Analysis of Spirit Beverages

    PubMed Central

    Śliwińska, Magdalena; Namieśnik, Jacek; Wardencki, Waldemar; Dymerski, Tomasz

    2016-01-01

    Spirit beverages are a diverse group of foodstuffs. They are very often counterfeited which cause the appearance of low quality products or wrongly labelled products on the market. It is important to find a proper quality control and botanical origin method enabling the same time preliminary check of the composition of investigated samples, which was the main goal of this work. For this purpose, the usefulness of electronic nose based on ultra-fast gas chromatography (fast GC e-nose) was verified. A set of 24 samples of raw spirits, 33 samples of vodkas, and 8 samples of whisky were analysed by fast GC e-nose. Four data analysis methods were used. The PCA was applied for the visualization of dataset, observation of the variation inside groups of samples, and selection of variables for the other three statistical methods. The SQC method was utilized to compare the quality of the samples. Both the DFA and SIMCA data analysis methods were used for discrimination of vodka, whisky, and spirits samples. The fast GC e-nose combined with four statistical methods can be used for rapid discrimination of raw spirits, vodkas, and whisky and in the same for preliminary determination of the composition of investigated samples. PMID:27446633

  11. Metabolite changes during the life history of Porphyra haitanensis.

    PubMed

    Wang, X; Zhao, P; Luo, Q; Yan, X; Xu, J; Chen, J; Chen, H

    2015-05-01

    Plant metabolomics is essentially the comprehensive analysis of complex metabolites of plant extracts. Metabolic fingerprinting is an important part of plant metabolomics research. In this study, metabolic fingerprinting of different stages of the life history of the red alga Porphyra haitanensis was performed. The stages included conchocelis filaments, sporangial branchlets, conchosporangia, discharged conchospores and conchosporangial branchlets after conchospore discharge. Metabolite extracts were analysed with ultra-performance liquid chromatography coupled with electrospray ionisation quadrupole-time of flight mass spectrometry. Analyses profiles were subjected to principal components analysis and orthogonal projection to latent structures discriminant analysis using the SIMCA-P software for biomarker selection and identification. Based on the MS/MS spectra and data from the literature, potential biomarkers, mainly of phosphatidylcholine and lysophosphatidylcholine, were identified. Identification of these biomarkers suggested that plasma membrane phospholipids underwent major changes during the life history of P. haitanensis. The levels of phosphatidylcholine and lysophosphatidylcholine increased in sporangial branchlets and decreased in discharged conchospores. Moreover, levels of sphingaine (d18:0) decreased in sporangial branchlets and increased in discharged conchospores, which indicates that membrane lipids were increasingly synthesised as energy storage in sporangial branchlets, while energy was consumed in sporangial branchlets to discharged conchospores. A metabolomic study of different growth phases of P. haitanensis will enhance our understanding of its physiology and ecology. PMID:25284486

  12. A candidate serum biomarker for bladder pain syndrome/interstitial cystitis†‡

    PubMed Central

    Rubio-Diaz, Daniel E.; Pozza, Megan E.; Dimitrakov, Jordan; Gilleran, Jason P.; Giusti, M. Monica; Stella, Judith L.; Rodriguez-Saona, Luis E.; Buffington, C. A. Tony

    2013-01-01

    Reliable diagnostic markers for Bladder Pain Syndrome/Interstitial Cystitis (IC) currently are not available. This study evaluated the feasibility of diagnosing IC in humans and domestic cats from the spectra of dried serum films (DSFs) using infrared microspectroscopy. Spectra were obtained from films from 29 humans and 34 domestic cats to create classification models using Soft Independent Modeling by Class Analogy (SIMCA). Ultrafiltration of serum improved discrimination capability. The classification models for both species successfully classified spectra based on condition (healthy/sick), and a different set of masked spectra correctly predicted the condition of 100% of the subjects. Classification required information from the 1500–1800 cm–1 spectral region to discriminate between subjects with IC, other disorders, and healthy subjects. Analysis of cat samples using liquid chromatography–mass spectroscopy revealed differences in the concentration of tryptophan and its metabolites between healthy and affected cats. These results demonstrate the potential utility of infrared microspectroscopy to diagnose IC in both humans and cats. PMID:19475139

  13. Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil

    PubMed Central

    Yu, Ke-Qiang; Zhao, Yan-Ru; Liu, Fei; He, Yong

    2016-01-01

    The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil. PMID:27279284

  14. Chemical composition analysis and authentication of whisky.

    PubMed

    Wiśniewska, Paulina; Dymerski, Tomasz; Wardencki, Waldemar; Namieśnik, Jacek

    2015-08-30

    Whisky (whiskey) is one of the most popular spirit-based drinks made from malted or saccharified grains, which should mature for at least 3 years in wooden barrels. High popularity of products usually causes a potential risk of adulteration. Thus authenticity assessment is one of the key elements of food product marketing. Authentication of whisky is based on comparing the composition of this alcohol with other spirit drinks. The present review summarizes all information about the comparison of whisky and other alcoholic beverages, the identification of type of whisky or the assessment of its quality and finally the authentication of whisky. The article also presents the various techniques used for analyzing whisky, such as gas and liquid chromatography with different types of detectors (FID, AED, UV-Vis), electronic nose, atomic absorption spectroscopy and mass spectrometry. In some cases the application of chemometric methods is also described, namely PCA, DFA, LDA, ANOVA, SIMCA, PNN, k-NN and CA, as well as preparation techniques such SPME or SPE. PMID:25315338

  15. Statistical Classification of Soft Solder Alloys by Laser-Induced Breakdown Spectroscopy: Review of Methods

    NASA Astrophysics Data System (ADS)

    Zdunek, R.; Nowak, M.; Pliński, E.

    2016-02-01

    This paper reviews machine-learning methods that are nowadays the most frequently used for the supervised classification of spectral signals in laser-induced breakdown spectroscopy (LIBS). We analyze and compare various statistical classification methods, such as linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), partial least-squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), support vector machine (SVM), naive Bayes method, probabilistic neural networks (PNN), and K-nearest neighbor (KNN) method. The theoretical considerations are supported with experiments conducted for real soft-solder-alloy spectra obtained using LIBS. We consider two decision problems: binary and multiclass classification. The former is used to distinguish overheated soft solders from their normal versions. The latter aims to assign a testing sample to a given group of materials. The measurements are obtained for several laser-energy values, projection masks, and numbers of laser shots. Using cross-validation, we evaluate the above classification methods in terms of their usefulness in solving both classification problems.

  16. [Using liquid chromatography-mass spectrometry based metabolomics to discriminate between cold pressed rice bran oils produced from two different cultivars of Oryza sativa L. ssp. indica in Thailand].

    PubMed

    Charoonratana, Tossaton; Songsak, Thanapat; Sakunpak, Apirak; Pathompak, Pathamaporn; Charoenchai, Laksana

    2015-09-01

    A newly developed liquid chromatography-mass spectrometry (LC-MS) method for the analysis of cold pressed rice bran oil (RBO) was established and used to discriminate between RBOs produced from two different cultivars of major Thai fragrant rice species. The cold pressed RBO was prepared using the screw compression method. The LC-MS data were preprocessed with MZmine 2.10 program before evaluating with principal component analysis using SIMCA 13 software. The LC-MS method was able to detect and quantify several kinds of valuable constituents such as fatty acids, vitamin E, and γ-oryzanol. The chromatographic condition was feasible; short time for analysis and simple method were achieved. From score plot and loading plot of principle component analysis (PCA) , two rice cultivar samples were clearly separated, and it was revealed that Khao-Hom-Pathum was more suitable than Khao-Hom-Mali for cold pressed RBO production since it contained high total γ-oryzanol and less saturated free fatty acids. As with the fixed price of all the rice brans, this information can be used in order to, if possible, preserve the price of rice brans from different cultivars. PMID:26753285

  17. Using color histograms and SPA-LDA to classify bacteria.

    PubMed

    de Almeida, Valber Elias; da Costa, Gean Bezerra; de Sousa Fernandes, David Douglas; Gonçalves Dias Diniz, Paulo Henrique; Brandão, Deysiane; de Medeiros, Ana Claudia Dantas; Véras, Germano

    2014-09-01

    In this work, a new approach is proposed to verify the differentiating characteristics of five bacteria (Escherichia coli, Enterococcus faecalis, Streptococcus salivarius, Streptococcus oralis, and Staphylococcus aureus) by using digital images obtained with a simple webcam and variable selection by the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA). In this sense, color histograms in the red-green-blue (RGB), hue-saturation-value (HSV), and grayscale channels and their combinations were used as input data, and statistically evaluated by using different multivariate classifiers (Soft Independent Modeling by Class Analogy (SIMCA), Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA), Partial Least Squares Discriminant Analysis (PLS-DA) and Successive Projections Algorithm-Linear Discriminant Analysis (SPA-LDA)). The bacteria strains were cultivated in a nutritive blood agar base layer for 24 h by following the Brazilian Pharmacopoeia, maintaining the status of cell growth and the nature of nutrient solutions under the same conditions. The best result in classification was obtained by using RGB and SPA-LDA, which reached 94 and 100 % of classification accuracy in the training and test sets, respectively. This result is extremely positive from the viewpoint of routine clinical analyses, because it avoids bacterial identification based on phenotypic identification of the causative organism using Gram staining, culture, and biochemical proofs. Therefore, the proposed method presents inherent advantages, promoting a simpler, faster, and low-cost alternative for bacterial identification. PMID:25023972

  18. Chemical data as markers of the geographical origins of sugarcane spirits.

    PubMed

    Serafim, F A T; Pereira-Filho, Edenir R; Franco, D W

    2016-04-01

    In an attempt to classify sugarcane spirits according to their geographic region of origin, chemical data for 24 analytes were evaluated in 50 cachaças produced using a similar procedure in selected regions of Brazil: São Paulo - SP (15), Minas Gerais - MG (11), Rio de Janeiro - RJ (11), Paraiba -PB (9), and Ceará - CE (4). Multivariate analysis was applied to the analytical results, and the predictive abilities of different classification methods were evaluated. Principal component analysis identified five groups, and chemical similarities were observed between MG and SP samples and between RJ and PB samples. CE samples presented a distinct chemical profile. Among the samples, partial linear square discriminant analysis (PLS-DA) classified 50.2% of the samples correctly, K-nearest neighbor (KNN) 86%, and soft independent modeling of class analogy (SIMCA) 56.2%. Therefore, in this proof of concept demonstration, the proposed approach based on chemical data satisfactorily predicted the cachaças' geographic origins. PMID:26593483

  19. The Verification of the Usefulness of Electronic Nose Based on Ultra-Fast Gas Chromatography and Four Different Chemometric Methods for Rapid Analysis of Spirit Beverages.

    PubMed

    Wiśniewska, Paulina; Śliwińska, Magdalena; Namieśnik, Jacek; Wardencki, Waldemar; Dymerski, Tomasz

    2016-01-01

    Spirit beverages are a diverse group of foodstuffs. They are very often counterfeited which cause the appearance of low quality products or wrongly labelled products on the market. It is important to find a proper quality control and botanical origin method enabling the same time preliminary check of the composition of investigated samples, which was the main goal of this work. For this purpose, the usefulness of electronic nose based on ultra-fast gas chromatography (fast GC e-nose) was verified. A set of 24 samples of raw spirits, 33 samples of vodkas, and 8 samples of whisky were analysed by fast GC e-nose. Four data analysis methods were used. The PCA was applied for the visualization of dataset, observation of the variation inside groups of samples, and selection of variables for the other three statistical methods. The SQC method was utilized to compare the quality of the samples. Both the DFA and SIMCA data analysis methods were used for discrimination of vodka, whisky, and spirits samples. The fast GC e-nose combined with four statistical methods can be used for rapid discrimination of raw spirits, vodkas, and whisky and in the same for preliminary determination of the composition of investigated samples. PMID:27446633

  20. Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics.

    PubMed

    Bajoub, Aadil; Medina-Rodríguez, Santiago; Gómez-Romero, María; Ajal, El Amine; Bagur-González, María Gracia; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

    2017-01-15

    High Performance Liquid Chromatography (HPLC) with diode array (DAD) and fluorescence (FLD) detection was used to acquire the fingerprints of the phenolic fraction of monovarietal extra-virgin olive oils (extra-VOOs) collected over three consecutive crop seasons (2011/2012-2013/2014). The chromatographic fingerprints of 140 extra-VOO samples processed from olive fruits of seven olive varieties, were recorded and statistically treated for varietal authentication purposes. First, DAD and FLD chromatographic-fingerprint datasets were separately processed and, subsequently, were joined using "Low-level" and "Mid-Level" data fusion methods. After the preliminary examination by principal component analysis (PCA), three supervised pattern recognition techniques, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogies (SIMCA) and K-Nearest Neighbors (k-NN) were applied to the four chromatographic-fingerprinting matrices. The classification models built were very sensitive and selective, showing considerably good recognition and prediction abilities. The combination "chromatographic dataset+chemometric technique" allowing the most accurate classification for each monovarietal extra-VOO was highlighted. PMID:27542473

  1. A NIR spectroscopy-based efficient approach to detect fraudulent additions within mixtures of dried porcini mushrooms.

    PubMed

    Casale, Monica; Bagnasco, Lucia; Zotti, Mirca; Di Piazza, Simone; Sitta, Nicola; Oliveri, Paolo

    2016-11-01

    Boletus edulis and allied species (BEAS), known as "porcini mushrooms", represent almost the totality of wild mushrooms placed on the Italian market, both fresh and dehydrated. Furthermore, considerable amounts of these dried fungi are imported from China. The presence of Tylopilus spp. and other extraneous species (i.e., species edible but not belonging to BEAS) within dried porcini mushrooms - mainly from those imported from China and sold in Italy - may represent an evaluable problem from a commercial point of view. The purpose of the present study is to evaluate near-infrared spectroscopy (NIRS) as a rapid and effective alternative to classical methods for identifying extraneous species within dried porcini batches and detecting related commercial frauds. To this goal, 80 dried fungi including BEAS, Tylopilus spp., and Boletus violaceofuscus were analysed by NIRS. For each sample, 3 different parts of the pileus (pileipellis, flesh and hymenium) were analysed and a low-level strategy for data fusion, consisting of combining the signals obtained by the different parts before data processing, was applied. Then, NIR spectra were used to develop reliable and efficient class-models using a novel method, partial least squares density modelling (PLS-DM), and the two most commonly used class-modelling techniques, UNEQ and SIMCA. The results showed that NIR spectroscopy coupled with chemometric class-modelling technique can be suggested as an effective analytical strategy to check the authenticity of dried BEAS mushrooms. PMID:27591669

  2. Improved detection of highly energetic materials traces on surfaces by standoff laser-induced thermal emission incorporating neural networks

    NASA Astrophysics Data System (ADS)

    Figueroa-Navedo, Amanda; Galán-Freyle, Nataly Y.; Pacheco-Londoño, Leonardo C.; Hernández-Rivera, Samuel P.

    2013-05-01

    Terrorists conceal highly energetic materials (HEM) as Improvised Explosive Devices (IED) in various types of materials such as PVC, wood, Teflon, aluminum, acrylic, carton and rubber to disguise them from detection equipment used by military and security agency personnel. Infrared emissions (IREs) of substrates, with and without HEM, were measured to generate models for detection and discrimination. Multivariable analysis techniques such as principal component analysis (PCA), soft independent modeling by class analogy (SIMCA), partial least squares-discriminant analysis (PLS-DA), support vector machine (SVM) and neural networks (NN) were employed to generate models, in which the emission of IR light from heated samples was stimulated using a CO2 laser giving rise to laser induced thermal emission (LITE) of HEMs. Traces of a specific target threat chemical explosive: PETN in surface concentrations of 10 to 300 ug/cm2 were studied on the surfaces mentioned. Custom built experimental setup used a CO2 laser as a heating source positioned with a telescope, where a minimal loss in reflective optics was reported, for the Mid-IR at a distance of 4 m and 32 scans at 10 s. SVM-DA resulted in the best statistical technique for a discrimination performance of 97%. PLS-DA accurately predicted over 94% and NN 88%.

  3. Elastoplasticidad anisotropa de metales en grandes deformaciones

    NASA Astrophysics Data System (ADS)

    Caminero Torija, Miguel Angel

    El objetivo de este trabajo es el desarrollo de modelos y algoritmos numericos que simulen el comportamiento del material bajo estas condiciones en el contexto de programas de elementos finitos, dando como resultado predicciones mas precisas de los procesos de conformado y deformacion plastica en general. Para lograr este objetivo se han desarrollado diversas tareas destinadas a mejorar las predicciones en tres aspectos fundamentales. El primer aspecto consiste en la mejora de la descripcion del endurecimiento cinematico anisotropo en pequenas deformaciones, lo cual se ha realizado a traves de modelos y algoritmos implicitos de superficies multiples. Ha sido estudiada la consistencia de este tipo de modelos tanto si estan basados en una regla implicita similar a la de Mroz o en la regla de Prager. Ademas se han simulado los ensayos de Lamba y Sidebottom, obteniendo, en contra de la creencia general, muy buenas predicciones con la regla de Prager. Dichos modelos podrian ser extendidos de forma relativamente facil para considerar grandes deformaciones a traves de procedimientos en deformaciones logaritmicas, similares a los desarrollados en esta tesis y detallados a continuacion. El segundo aspecto consiste en la descripcion de la anisotropia elastoplastica inicial. Esto se ha conseguido mediante el desarrollo de modelos y algoritmos para plasticidad anisotropa en grandes deformaciones, bien ignorando la posible anisotropia elastica, bien considerandola simultaneamente con la anisotropia plastica. Para ello ha sido necesario desarrollar primero un nuevo algoritmo de elastoplasticidad anisotropa en pequenas deformaciones consistentemente linealizado y sin despreciar ningun termino, de tal forma que se conserve la convergencia cuadratica de los metodos de Newton. Este algoritmo en pequenas deformaciones ha servido para realizar la correccion plastica de dos algoritmos en grandes deformaciones. El primero de estos algoritmos es una variacion del clasico algoritmo de

  4. Identification of frozen salt solutions combining LIBS and multivariate analysis methods

    NASA Astrophysics Data System (ADS)

    Schröder, S.; Pavlov, S.; Jessberger, E.; Hübers, H.

    2012-12-01

    considerably complicates differentiation between salts with the same type of cation. The focus in this study was on the capability of different multivariate analysis (MVA) techniques applied to LIBS data to discriminate between salts with cations of the same kind in frozen salt solutions. With principal components analysis (PCA) the data were analyzed with the aim of separating the LIBS spectra into groups and revealing the most important lines in the spectra for discrimination and identification of the type of salt. PCA performance is improved by selecting the most relevant lines with emphasis on the sulfur and chlorine lines and additionally averaging the spectra before analysis. A subsequent local PCA can improve the discrimination ability for a sulfate and a chloride with the same type of cation. Soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) were performed. While SIMCA worked well for the pressed salt samples, its application to the spectra of the frozen salt solutions was not successful. A PLS-DA of the LIBS spectra of salts with the same cation is capable of distinguishing sulfate, chloride, and perchlorate. The results of this work demonstrate that LIBS is a suitable analytical technique for the investigation and identification of salts and frozen salt solutions under Martian atmospheric conditions.

  5. Correlating multispectral imaging and compositional data from the Mars Exploration Rovers and implications for Mars Science Laboratory

    USGS Publications Warehouse

    Anderson, Ryan B.; Bell, James F., III

    2013-01-01

    In an effort to infer compositional information about distant targets based on multispectral imaging data, we investigated methods of relating Mars Exploration Rover (MER) Pancam multispectral remote sensing observations to in situ alpha particle X-ray spectrometer (APXS)-derived elemental abundances and Mössbauer (MB)-derived abundances of Fe-bearing phases at the MER field sites in Gusev crater and Meridiani Planum. The majority of the partial correlation coefficients between these data sets were not statistically significant. Restricting the targets to those that were abraded by the rock abrasion tool (RAT) led to improved Pearson’s correlations, most notably between the red–blue ratio (673 nm/434 nm) and Fe3+-bearing phases, but partial correlations were not statistically significant. Partial Least Squares (PLS) calculations relating Pancam 11-color visible to near-IR (VNIR; ∼400–1000 nm) “spectra” to APXS and Mössbauer element or mineral abundances showed generally poor performance, although the presence of compositional outliers led to improved PLS results for data from Meridiani. When the Meridiani PLS model for pyroxene was tested by predicting the pyroxene content of Gusev targets, the results were poor, indicating that the PLS models for Meridiani are not applicable to data from other sites. Soft Independent Modeling of Class Analogy (SIMCA) classification of Gusev crater data showed mixed results. Of the 24 Gusev test regions of interest (ROIs) with known classes, 11 had >30% of the pixels in the ROI classified correctly, while others were mis-classified or unclassified. k-Means clustering of APXS and Mössbauer data was used to assign Meridiani targets to compositional classes. The clustering-derived classes corresponded to meaningful geologic and/or color unit differences, and SIMCA classification using these classes was somewhat successful, with >30% of pixels correctly classified in 9 of the 11 ROIs with known classes. This work shows

  6. Invertebrate fauna associated with Torpedograss, Panicum repens (Cyperales: Poaceae), in Lake Okeechobee, Florida, and prospects for biological control

    SciTech Connect

    Cuda, J.P.; Dunford, J.C.; Leavengood, J.M. Jr.

    2007-03-15

    Torpedograss, Panicum repens L., is an adventive, rhizomatous grass species that has become an invasive weed of terrestrial, wetland, and aquatic environments in tropical and subtropical regions worldwide. Until recently, strategies for controlling torpedograss in the USA have focused almost exclusively on mechanical and chemical methods, either alone or in combination, with varied results. A survey of the arthropods and nematodes currently associated with the plant in Lake Okeechobee, Florida, was conducted as part of a feasibility study to determine whether torpedograss is an appropriate target for a classical biological control program. Overall, approximately 4,000 arthropods and 400 nematode specimens were collected. Sweep, clipped vegetation, and soil core samples were dominated by representatives of the arthropod orders Hemiptera, Hymenoptera, Diptera, and Acari. Lesion nematodes of the genus Pratylenchus were commonly associated with the roots of torpedograss. None of the organisms collected were torpedograss specialists. Although classical biological control of torpedograss is feasible based on the extent of the infestation, economic losses, resistance to conventional controls, and the report of a potentially host specific natural enemy in India, the botanical position of this grass weed will require a formal risk assessment before proceeding with a classical biological control program. (author) [Spanish] La conota, Panicum repens L., es una especie foranea de pasto que produce rizomas que ha convertido en ser una maleza invasora de ambientes terrestres, pantanosos y acuaticos en regiones tropicales y subtropicales en todo el mundo. Hasta hace un tiempo reciente, las estrategias para controlar conota en los EEUU eran enfocadas casi exclusivamente en los metodos mecanicos y quimicos, solos o en combinacion, con resultados variables. Un muestreo de los artropodos y nematodos asociados corrientemente con esta planta en el Lago de Okeechobee, Florida, fue

  7. Sexual selection on multivariate phenotypes in Anastrepha Fraterculus (Diptera: Tephritidae) from Argentina

    SciTech Connect

    Sciurano, R.; Rodriguero, M.; Gomez Cendra, P.; Vilardi, J.; Segura, D.; Cladera, J.L.; Allinghi, Armando

    2007-03-15

    Despite the interest in applying environmentally friendly control methods such as sterile insect technique (SIT) against Anastrepha fraterculus (Wiedemann) (Diptera: Tephritidae), information about its biology, taxonomy, and behavior is still insufficient. To increase this information, the present study aims to evaluate the performance of wild flies under field cage conditions through the study of sexual competitiveness among males (sexual selection). A wild population from Horco Molle, Tucuman, Argentina was sampled. Mature virgin males and females were released into outdoor field cages to compete for mating. Morphometric analyses were applied to determine the relationship between the multivariate phenotype and copulatory success. Successful and unsuccessful males were measured for 8 traits: head width (HW), face width (FW), eye length (EL), thorax length (THL), wing length (WL), wing width (WW), femur length (FL), and tibia length (TIL). Combinations of different multivariate statistical methods and graphical analyses were used to evaluate sexual selection on male phenotype. The results indicated that wing width and thorax length would be the most probable targets of sexual selection. They describe a non-linear association between expected fitness and each of these 2 traits. This non-linear relation suggests that observed selection could maintain the diversity related to body size. (author) [Spanish] A pesar del interes por la aplicacion de metodos de control de bajo impacto ambiental sobre Anastrepha fraterculus (Diptera: Tephritidae), como la Tecnica del Insecto Esteril (TIE), no existe aun informacion suficiente sobre su biologia, taxonomia y comportamiento. Este trabajo tiene como objetivo evaluar el desempeno de moscas en jaulas de campo a traves del estudio de la competitividad sexual entre machos salvajes (seleccion sexual). Para ello, se muestreo una poblacion de Horco Molle, Tucuman (Argentina). En jaulas de campo se liberaron machos y hembras adultos

  8. La problematica de la demarcacion entre ciencia y pseudociencia y sus implicaciones en la educacion cientifica

    NASA Astrophysics Data System (ADS)

    Jimenez Tolentino, Dinorah

    2011-12-01

    En la sociedad prevalece una tendencia generalizada hacia la inclusion de creencias y practicas pseudocientificas. Esta investigacion responde a la necesidad de analizar como la proliferacion de las pseudociencias afecta la vision que tienen los estudiantes universitarios sobre las ciencias naturales. A tales efectos, la investigadora describe las concepciones epistemologicas que tienen los estudiantes sobre las ciencias y las pseudociencias e identifica los criterios de demarcacion, entre un area y otra, que se derivan de estas concepciones. De igual modo, esta identifica las creencias y practicas pseudocientificas de mayor arraigo entre los estudiantes, destacando, a su vez, la razon de ser de las mismas. Por ultimo, la investigadora analiza las implicaciones educativas de la problematica de la demarcacion entre ciencia y pseudociencia. La investigacion es de naturaleza mixta, enmarcada en los paradigmas empirico- analitico y cualitativo. El proceso investigativo se llevo a cabo mediante la administracion del cuestionario Criterios para la demarcacion entre ciencia y pseudociencia. La parte cualitativa estuvo enmarcada en el diseno de estudio de caso, recopilando informacion mediante entrevistas semiestructuradas en dos grupos focales. La poblacion de estudio estuvo constituida por estudiantes universitarios del nivel subgraduado de la Universidad Central de Bayamon. Los resultados del estudio reflejaron las concepciones erroneas de los estudiantes sobre la naturaleza de las ciencias y las pseudociencias. Con respecto a la demarcacion entre ciencia y pseudociencia, el criterio imperante entre los universitarios es el de la verificabilidad, considerando la aplicacion del metodo cientifico como el metodo para demostrar la veracidad de las teorias cientificas. Las creencias y practicas pseudocientificas no son muy frecuentes entre los universitarios. Estos atribuyen las mismas a la prevalencia de elementos supersticiosos y al engano a que es sometida la poblacion

  9. La implantacion del enfoque constructivista en el aula de ciencia: Estudio de caso multiple

    NASA Astrophysics Data System (ADS)

    Arroyo Betancourt, Luz I.

    participantes basado en lo que estas manifestaron en su practica didactica. Dos maestras coinciden en una vision constructivista social de la construccion del conocimiento, del aprendizaje y de los metodos didacticos. La otra manifesto una vision constructivista piagetiana en el aprendizaje, los metodos didacticos y en la construccion del conocimiento. Se espera que este trabajo, ademas de promover los estudios de caso sobre el enfoque constructivista de ensenanza en el contexto puertorriqueno, sirva para que los maestros, que estan transformando su enfoque educativo de uno tradicional a uno constructivista, tengan una vision mas clara de la implantacion de este enfoque. Se espera ademas que sirva para que el Departamento de Educacion y sus programas de adiestramiento y readiestramiento en servicio, asi como las universidades y sus programas de preparacion de maestros, tomen en cuenta los resultados y recomendaciones de este estudio al revisar sus programas.

  10. Implementacion de modulos constructivistas que atiendan "misconceptions" y lagunas conceptuales en temas de la fisica en estudiantes universitarios

    NASA Astrophysics Data System (ADS)

    Santacruz Sarmiento, Neida M.

    Este estudio se enfoco en los "misconception" y lagunas conceptuales en temas fundamentales de Fisica como son Equilibrio Termodinamico y Estatica de fluidos. En primer lugar se trabajo con la identificacion de "misconceptions" y lagunas conceptuales y se analizo en detalle la forma en que los estudiantes construyen sus propias teorias de fenomenos relacionados con los temas. Debido a la complejidad en la que los estudiantes asimilan los conceptos fisicos, se utilizo el metodo de investigacion mixto de tipo secuencial explicativo en dos etapas, una cuantitativa y otra cualitativa. La primera etapa comprendio cuatro fases: (1) Aplicacion de una prueba diagnostica para identificar el conocimiento previo y lagunas conceptuales. (2) Identificacion de "misconceptions" y lagunas del concepto a partir del conocimiento previo. (3) Implementacion de la intervencion por medio de modulos en el topico de Equilibrio Termodinamico y Estatica de Fluidos. (4) Y la realizacion de la pos prueba para analizar el impacto y la efectividad de la intervencion constructivista. En la segunda etapa se utilizo el metodo de investigacion cualitativo, por medio de una entrevista semiestructurada que partio de la elaboracion de un mapa conceptual y se finalizo con un analisis de datos conjuntamente. El desarrollo de este estudio permitio encontrar "misconceptions" y lagunas conceptuales a partir del conocimiento previo de los estudiantes participantes en los temas trabajados, que fueron atendidos en el desarrollo de las distintas actividades inquisitivas que se presentaron en el modulo constructivista. Se encontro marcadas diferencias entre la pre y pos prueba en los temas, esto se debio al requerimiento de habilidades abstractas para el tema de Estatica de Fluidos y al desarrollo intuitivo para el tema de Equilibrio Termodinamico, teniendo mejores respuestas en el segundo. Los participantes demostraron una marcada evolucion y/o cambio en sus estructuras de pensamiento, las pruebas estadisticas

  11. Investigating Antibacterial Effects of Garlic (Allium sativum) Concentrate and Garlic-Derived Organosulfur Compounds on Campylobacter jejuni by Using Fourier Transform Infrared Spectroscopy, Raman Spectroscopy, and Electron Microscopy ▿ †

    PubMed Central

    Lu, Xiaonan; Rasco, Barbara A.; Jabal, Jamie M. F.; Aston, D. Eric; Lin, Mengshi; Konkel, Michael E.

    2011-01-01

    Fourier transform infrared (FT-IR) spectroscopy and Raman spectroscopy were used to study the cell injury and inactivation of Campylobacter jejuni from exposure to antioxidants from garlic. C. jejuni was treated with various concentrations of garlic concentrate and garlic-derived organosulfur compounds in growth media and saline at 4, 22, and 35°C. The antimicrobial activities of the diallyl sulfides increased with the number of sulfur atoms (diallyl sulfide < diallyl disulfide < diallyl trisulfide). FT-IR spectroscopy confirmed that organosulfur compounds are responsible for the substantial antimicrobial activity of garlic, much greater than those of garlic phenolic compounds, as indicated by changes in the spectral features of proteins, lipids, and polysaccharides in the bacterial cell membranes. Confocal Raman microscopy (532-nm-gold-particle substrate) and Raman mapping of a single bacterium confirmed the intracellular uptake of sulfur and phenolic components. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were employed to verify cell damage. Principal-component analysis (PCA), discriminant function analysis (DFA), and soft independent modeling of class analogs (SIMCA) were performed, and results were cross validated to differentiate bacteria based upon the degree of cell injury. Partial least-squares regression (PLSR) was employed to quantify and predict actual numbers of healthy and injured bacterial cells remaining following treatment. PLSR-based loading plots were investigated to further verify the changes in the cell membrane of C. jejuni treated with organosulfur compounds. We demonstrated that bacterial injury and inactivation could be accurately investigated by complementary infrared and Raman spectroscopies using a chemical-based, “whole-organism fingerprint” with the aid of chemometrics and electron microscopy. PMID:21642409

  12. Lipidomics study of plasma phospholipid metabolism in early type 2 diabetes rats with ancient prescription Huang-Qi-San intervention by UPLC/Q-TOF-MS and correlation coefficient.

    PubMed

    Wu, Xia; Zhu, Jian-Cheng; Zhang, Yu; Li, Wei-Min; Rong, Xiang-Lu; Feng, Yi-Fan

    2016-08-25

    Potential impact of lipid research has been increasingly realized both in disease treatment and prevention. An effective metabolomics approach based on ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF-MS) along with multivariate statistic analysis has been applied for investigating the dynamic change of plasma phospholipids compositions in early type 2 diabetic rats after the treatment of an ancient prescription of Chinese Medicine Huang-Qi-San. The exported UPLC/Q-TOF-MS data of plasma samples were subjected to SIMCA-P and processed by bioMark, mixOmics, Rcomdr packages with R software. A clear score plots of plasma sample groups, including normal control group (NC), model group (MC), positive medicine control group (Flu) and Huang-Qi-San group (HQS), were achieved by principal-components analysis (PCA), partial least-squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Biomarkers were screened out using student T test, principal component regression (PCR), partial least-squares regression (PLS) and important variable method (variable influence on projection, VIP). Structures of metabolites were identified and metabolic pathways were deduced by correlation coefficient. The relationship between compounds was explained by the correlation coefficient diagram, and the metabolic differences between similar compounds were illustrated. Based on KEGG database, the biological significances of identified biomarkers were described. The correlation coefficient was firstly applied to identify the structure and deduce the metabolic pathways of phospholipids metabolites, and the study provided a new methodological cue for further understanding the molecular mechanisms of metabolites in the process of regulating Huang-Qi-San for treating early type 2 diabetes. PMID:27369808

  13. Evaluation of quality control strategies in Scutellaria herbal medicines.

    PubMed

    Boyle, Susanne P; Doolan, Paul J; Andrews, Clare E; Reid, Raymond G

    2011-04-01

    The statutory regulation of herbal medicines is under review within the United Kingdom (UK) and by 2011 all herbal medicines will require either a Product Licence or a Traditional Herbal Registration. The species Scutellaria baicalensis has been shown to possess anti-inflammatory, anti-viral and anti-tumor properties and is one of the most widely used Chinese herbal extracts in Eastern and Western medicines. The bioactivity of this herbal medicine is due to the radical scavenging activities of the flavone components of which there are more than 60. This research has characterised 5 key flavones in 18 extracts of Scutellaria using a combination of HPLC with DAD and MS detection. Employing an internal standard approach, the validated HPLC method afforded good sensitivity and excellent assay precision. Assays for the ferric reducing antioxidant power (FRAP) and total phenol determinations enabled determination of the antioxidant coefficient (PAC) of each Scutellaria extract. The potential usefulness of employing multivariate statistical analysis using a combination of the key parameters collected namely, FRAP activity, total phenol content, levels of 5 flavone biomarkers and the PAC as a means of quality evaluation of the Scutellaria herbal extracts was investigated. The PAC value was predicted by soft independent modelling of class analogy (SIMCA) as being the most discriminatory parameter and applying this ranking the herbal extracts were grouped into 3 clusters. The second most influential parameter in determining the clustering of the samples was the level of baicalin in each extract. It is proposed that the PAC value alone or in combination with a chromatographic fingerprint of key biomarkers [e.g. baicalin or (baicalin+baicalein)] may be useful indicators to adopt for the quality control of S. baicalensis. PMID:21163602

  14. Detection of counterfeit Viagra® by Raman microspectroscopy imaging and multivariate analysis.

    PubMed

    Sacré, Pierre-Yves; Deconinck, Eric; Saerens, Lien; De Beer, Thomas; Courselle, Patricia; Vancauwenberghe, Roy; Chiap, Patrice; Crommen, Jacques; De Beer, Jacques O

    2011-09-10

    During the past years, pharmaceutical counterfeiting was mainly a problem of developing countries with weak enforcement and inspection programs. However, Europe and North America are more and more confronted with the counterfeiting problem. During this study, 26 counterfeits and imitations of Viagra® tablets and 8 genuine tablets of Viagra® were analysed by Raman microspectroscopy imaging. After unfolding the data, three maps are combined per sample and a first PCA is realised on these data. Then, the first principal components of each sample are assembled. The exploratory and classification analysis are performed on that matrix. PCA was applied as exploratory analysis tool on different spectral ranges to detect counterfeit medicines based on the full spectra (200-1800 cm⁻¹), the presence of lactose (830-880 cm⁻¹) and the spatial distribution of sildenafil (1200-1290 cm⁻¹) inside the tablet. After the exploratory analysis, three different classification algorithms were applied on the full spectra dataset: linear discriminant analysis, k-nearest neighbour and soft independent modelling of class analogy. PCA analysis of the 830-880 cm⁻¹ spectral region discriminated genuine samples while the multivariate analysis of the spectral region between 1200 cm⁻¹ and 1290 cm⁻¹ returns no satisfactory results. A good discrimination of genuine samples was obtained with multivariate analysis of the full spectra region (200-1800 cm⁻¹). Application of the k-NN and SIMCA algorithm returned 100% correct classification during both internal and external validation. PMID:21715121

  15. Comparison of Mouse Urinary Metabolic Profiles after Exposure to the Inflammatory Stressors γ Radiation and Lipopolysaccharide

    PubMed Central

    Laiakis, Evagelia C.; Hyduke, Daniel R.; Fornace, Albert J.

    2012-01-01

    Metabolomics on easily accessible biofluids has the potential to provide rapid identification and distinction between stressors and inflammatory states. In the event of a radiological event, individuals with underlying medical conditions could present with similar symptoms to radiation poisoning, prominently nausea, diarrhea, vomiting and fever. Metabolomics of radiation exposure in mice has provided valuable biomarkers, and in this study we aimed to identify biomarkers of lipopolysaccharide (LPS) exposure to compare and contrast with ionizing radiation. LPS treatment leads to a severe inflammatory response and a cytokine storm, events similar to radiation exposure, and LPS exposure can recapitulate many of the responses seen in sepsis. Urine from control mice, LPS-treated mice, and mice irradiated with 3, 8 and 15 Gy of γ rays was analyzed by LCMS, and markers were extracted using SIMCA-P+ and Random Forests. Markers were validated through tandem mass spectrometry against pure chemicals. Five metabolites, cytosine, cortisol, adenine, O-propanoylcarnitine and isethionic acid, showed increased excretion at 24 h after LPS treatment (P < 0.0001, 0.0393, 0.0393, <0.0001 and 0.0004, respectively). Of these, cytosine, adenine and O-propanoylcarnitine showed specificity to LPS treatment when compared to radiation. On the other hand, increased excretion of cortisol after LPS and radiation treatments indicated a rapid systemic response to inflammatory agents. Isethionic acid excretion, however, showed elevated levels not only after LPS treatment but also after a very high dose of radiation (15 Gy), while additional metabolites showed responsiveness to radiation but not LPS. Metabolomics therefore has the potential to distinguish between different inflammatory responses based on differential ion signatures. It can also provide quick and reliable assessment of medical conditions in a mass casualty radiological scenario and aid in effective triaging. PMID:22128784

  16. Gasoline classification using near infrared (NIR) spectroscopy data: comparison of multivariate techniques.

    PubMed

    Balabin, Roman M; Safieva, Ravilya Z; Lomakina, Ekaterina I

    2010-06-25

    Near infrared (NIR) spectroscopy is a non-destructive (vibrational spectroscopy based) measurement technique for many multicomponent chemical systems, including products of petroleum (crude oil) refining and petrochemicals, food products (tea, fruits, e.g., apples, milk, wine, spirits, meat, bread, cheese, etc.), pharmaceuticals (drugs, tablets, bioreactor monitoring, etc.), and combustion products. In this paper we have compared the abilities of nine different multivariate classification methods: linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), regularized discriminant analysis (RDA), soft independent modeling of class analogy (SIMCA), partial least squares (PLS) classification, K-nearest neighbor (KNN), support vector machines (SVM), probabilistic neural network (PNN), and multilayer perceptron (ANN-MLP) - for gasoline classification. Three sets of near infrared (NIR) spectra (450, 415, and 345 spectra) were used for classification of gasolines into 3, 6, and 3 classes, respectively, according to their source (refinery or process) and type. The 14,000-8000 cm(-1) NIR spectral region was chosen. In all cases NIR spectroscopy was found to be effective for gasoline classification purposes, when compared with nuclear magnetic resonance (NMR) spectroscopy or gas chromatography (GC). KNN, SVM, and PNN techniques for classification were found to be among the most effective ones. Artificial neural network (ANN-MLP) approach based on principal component analysis (PCA), which was believed to be efficient, has shown much worse results. We hope that the results obtained in this study will help both further chemometric (multivariate data analysis) investigations and investigations in the sphere of applied vibrational (infrared/IR, near-IR, and Raman) spectroscopy of sophisticated multicomponent systems. PMID:20541639

  17. A preliminary MTD-PLS study for androgen receptor binding of steroid compounds

    NASA Astrophysics Data System (ADS)

    Bora, Alina; Seclaman, E.; Kurunczi, L.; Funar-Timofei, Simona

    The relative binding affinities (RBA) of a series of 30 steroids for Human Androgen Receptor (AR) were used to initiate a MTD-PLS study. The 3D structures of all the compounds were obtained through geometry optimization in the framework of AM1 semiempirical quantum chemical method. The MTD hypermolecule (HM) was constructed, superposing these structures on the AR-bonded dihydrotestosterone (DHT) skeleton obtained from PDB (AR complex, ID 1I37). The parameters characterizing the HM vertices were collected using: AM1 charges, XlogP fragmental values, calculated fragmental polarizabilities (from refractivities), volumes, and H-bond parameters (Raevsky's thermodynamic originated scale). The resulted QSAR data matrix was submitted to PCA (Principal Component Analysis) and PLS (Projections in Latent Structures) procedure (SIMCA P 9.0); five compounds were selected as test set, and the remaining 25 molecules were used as training set. In the PLS procedure supplementary chemical information was introduced, i.e. the steric effect was always considered detrimental, and the hydrophobic and van der Waals interactions were imposed to be beneficial. The initial PLS model using the entire training set has the following characteristics: R2Y = 0.584, Q2 = 0.344. Based on distances to the model criterions (DMODX and DMODY), five compounds were eliminated and the obtained final model had the following characteristics: R2Y D 0.891, Q2 D 0.591. For this the external predictivity on the test set was unsatisfactory. A tentative explanation for these behaviors is the weak information content of the input QSAR matrix for the present series comparatively with other successful MTD-PLS modeling published elsewhere.

  18. Testing of complementarity of PDA and MS detectors using chromatographic fingerprinting of genuine and counterfeit samples containing sildenafil citrate.

    PubMed

    Custers, Deborah; Krakowska, Barbara; De Beer, Jacques O; Courselle, Patricia; Daszykowski, Michal; Apers, Sandra; Deconinck, Eric

    2016-02-01

    Counterfeit medicines are a global threat to public health. High amounts enter the European market, which is why characterization of these products is a very important issue. In this study, a high-performance liquid chromatography-photodiode array (HPLC-PDA) and high-performance liquid chromatography-mass spectrometry (HPLC-MS) method were developed for the analysis of genuine Viagra®, generic products of Viagra®, and counterfeit samples in order to obtain different types of fingerprints. These data were included in the chemometric data analysis, aiming to test whether PDA and MS are complementary detection techniques. The MS data comprise both MS1 and MS2 fingerprints; the PDA data consist of fingerprints measured at three different wavelengths, i.e., 254, 270, and 290 nm, and all possible combinations of these wavelengths. First, it was verified if both groups of fingerprints can discriminate between genuine, generic, and counterfeit medicines separately; next, it was studied if the obtained results could be ameliorated by combining both fingerprint types. This data analysis showed that MS1 does not provide suitable classification models since several genuines and generics are classified as counterfeits and vice versa. However, when analyzing the MS1_MS2 data in combination with partial least squares-discriminant analysis (PLS-DA), a perfect discrimination was obtained. When only using data measured at 254 nm, good classification models can be obtained by k nearest neighbors (kNN) and soft independent modelling of class analogy (SIMCA), which might be interesting for the characterization of counterfeit drugs in developing countries. However, in general, the combination of PDA and MS data (254 nm_MS1) is preferred due to less classification errors between the genuines/generics and counterfeits compared to PDA and MS data separately. PMID:26753972

  19. Investigation of chlorinated aromatic compounds in the environment: Methods development and data interpretation

    SciTech Connect

    Ding, Wanghsien.

    1989-01-01

    Detection of low levels of chlorinated benzene compounds (CLBZ) and polychlorinated biphenyls (PCBs) in soil samples has been investigated with respect to potential sources in an industrial area of western New York state. The extract obtained by steam distillation was used directly with minimal additional cleanup steps for high resolution gas chromatography/mass spectrometry (HRGC/MS) and high resolution gas chromatography with electron capture detection (HRGC/ECD) analysis. The Nielson-Kryger steam distillation technique was used to extract CLBZ compounds and PCB congeners from soil samples. The recoveries of the CLBZ compounds in soil samples were monitored by comparison of the response for the {sup 13}C-labelled analogues in each isomeric group. The mean recoveries from field samples ranged from 63% to 76%. The recoveries of PCB congeners were measured using four air-dried subsurface soils which were spiked with Aroclors standard mixture. The mean recoveries of most PCB congeners ranged from 80% to 99%. Using HRGC/MS in the selected ion monitoring mode (SIM), a detection limit below 10 pg/g (10 pptr, parts per trillion) of the CLBZ compounds was achieved. For GC/ECD, an Apiezon L-coated glass capillary column was used to determine PCB congeners at background levels. More than 69 PCB congeners were separated on this column. The detection limit for an individual congener was about 0.01 ng/g. Application of SIMCA (SImple Modeling by Chemical Analogy) pattern recognition and multiple discriminant analysis showed that the pattern of CLBZ compounds in soil samples collected near Love Canal was similar to the patterns from the other areas in the Niagara Falls area. The highest concentrations of CLBZ compounds were detected in the area which is near and downwind from an industrial center with many potential sources of airborne emissions.

  20. Application of class-modelling techniques to infrared spectra for analysis of pork adulteration in beef jerkys.

    PubMed

    Kuswandi, Bambang; Putri, Fitra Karima; Gani, Agus Abdul; Ahmad, Musa

    2015-12-01

    The use of chemometrics to analyse infrared spectra to predict pork adulteration in the beef jerky (dendeng) was explored. In the first step, the analysis of pork in the beef jerky formulation was conducted by blending the beef jerky with pork at 5-80 % levels. Then, they were powdered and classified into training set and test set. The second step, the spectra of the two sets was recorded by Fourier Transform Infrared (FTIR) spectroscopy using atenuated total reflection (ATR) cell on the basis of spectral data at frequency region 4000-700 cm(-1). The spectra was categorised into four data sets, i.e. (a) spectra in the whole region as data set 1; (b) spectra in the fingerprint region (1500-600 cm(-1)) as data set 2; (c) spectra in the whole region with treatment as data set 3; and (d) spectra in the fingerprint region with treatment as data set 4. The third step, the chemometric analysis were employed using three class-modelling techniques (i.e. LDA, SIMCA, and SVM) toward the data sets. Finally, the best result of the models towards the data sets on the adulteration analysis of the samples were selected and the best model was compared with the ELISA method. From the chemometric results, the LDA model on the data set 1 was found to be the best model, since it could classify and predict 100 % accuracy of the sample tested. The LDA model was applied toward the real samples of the beef jerky marketed in Jember, and the results showed that the LDA model developed was in good agreement with the ELISA method. PMID:26604341

  1. [FTIR and classification study on the powdered milk with different assist material].

    PubMed

    Zhou, Jing; Sun, Su-Qin; Li, Yong-Jun; Zhou, Qun

    2009-01-01

    The near infrared spectrum atlases of milk powders mingled with different adjuvant are the object for cluster analysis. Drawing assistance from the disparity in infrared fingerprint atlas that change according to the contents of chemical constituent, and making mingled component models, the milk powders mingled with different adjuvant were taken for a rapid sorting test using SIMCA clustering analytical method. In the experiment, two hundred fifty sorts of milk powders in the markets from different manufacturers were scanned by near infrared ray, and were tested with reproducibility determination. It was found difficult to extract fingerprint characters just from the external appearance of the near infrared spectrum atlases from milk powders mingled with different adjuvant, and it is needed to adopt pattern recognition technique to determine intelligently. One hundred sixty atlases were drawn out randomly for cluster analysis, and unknown samples were pretested. Results showed that the milk powders mingled with different adjuvant can be identified by near infrared spectrum analysis associated with cluster analysis methods, notwithstanding the similar near infrared spectrum atlases of different sample were difficult to identify directly. No overlapping phenomenon was found among milk powders mingled with different adjuvant, and they did not interfere with each other. The results from clustering spectra between samples were satisfactory, and the correct ratios of blind detections were over 90%. In addition, the correct ratios of this method may be elevated remarkably with sufficient number of samples, increasing training set sample quantity and sampling representation, and strengthening the standard degree of manipulation. It is concluded that the designed model to determine milk powders mingled with different adjuvant is rational, and the determination capability is fine. PMID:19385217

  2. Occurrence of non-ortho-, mono-ortho- and di-ortho- substituted PCB congeners in different organs and tissues of polecats (Mustela putorius L. ) from the Netherlands

    SciTech Connect

    Leonards, P.E.G.; Hattum, B. Van; Cofino, W.P. . Inst. for Environmental Studies); Brinkman, U.A. . Dept. of Analytical Chemistry)

    1994-01-01

    The presence and concentrations of non-ortho-, mono-ortho-, and di-ortho--substituted PCB congeners in the pole-cat (n = 7), were investigated. PCBs were extracted with a Soxhlet apparatus. After cleanup the non-ortho-substituted PCB congeners were separated from the other PCBs by HPLC. Determinations were accomplished with GC-ECD or GC-MSD. Patterns of PCBs were examined in different organs and tissues: liver, kidney, muscle, anal gland secretion, mesenteric fat, and subcutaneous fat. Using a multivariate statistical method for data analysis (SIMCA), a significant difference of PCB patterns between anal gland secretion and the other organs and tissues was revealed. Lesser concentrations of congeners with seven and eight chlorine atoms in anal gland secretion were mainly responsible for this phenomenon. A more or less organ- and tissue-specific PCB pattern was observed in all animals. PCB patterns were not dependent on prey choice, which ranged from terrestrial (small rodents) to aquatic (amphibians). This finding implies that PCB patterns in the pole-cat seem to be controlled by metabolic processes rather than diet factors. The total concentration of PCBs in polecats varies widely, two orders of magnitude, from 1 to 3,700 [mu]g/g lipid. In some animals, PCBs exceeded the experimentally determined reproduction effect concentrations of mink and ferrets. Using the toxic equivalent approach, it was observed that planar PCB 126 accounts for 63 to 98% of the toxic equivalents. The results showed that juvenile animals contain greater PCB levels than adult males and females, which might be related to an increased elimination of PCBs in adult animals due to anal gland secretion. High concentrations of PCBs were observed in such secretion. A preliminary model for concentration of PCBs in polecats including this effect is proposed.

  3. Evaluation of old landfills--a thermoanalytical and spectroscopic approach.

    PubMed

    Smidt, Ena; Böhm, Katharina; Tintner, Johannes

    2011-02-01

    Abandoned landfills and dumps, where untreated waste materials were deposited in the past, are a main anthropogenic source of relevant gaseous emissions. The determination of stability is a crucial target in the context of landfill risk assessment. FTIR spectroscopy and simultaneous thermal analysis in association with multivariate statistical methods were applied to landfill materials in order to get information on the kind of waste and its reactivity. The spectral and thermal patterns are fingerprints of the material. Industrial waste and the material from a 5-year-old reactor landfill were distinguished from the defined classes of mechanically-biologically treated ("MBT") waste and 30 to 40-year-old stable landfills containing municipal solid waste and construction waste ("LF") by a classification model based on soft independent modeling of class analogy (SIMCA). Degradation experiments were carried out with the fresh material originating from one MBT plant that was subjected to aerobic and anaerobic conditions in lab-scale reactors. These samples were compared to samples of one reactor landfill and to the landfill fraction from the MBT plant to demonstrate the efficiency of the biological pretreatment before final disposal. Prediction models that are based on spectral or thermal characteristics and the corresponding reference analyses were calculated by means of a partial least squares regression (PLS-R). The developed models of the biological oxygen demand (BOD) and the dissolved organic carbon (DOC) were based on spectral data, the models of the total organic carbon (TOC) and total nitrogen (TN) were based on thermal data (heat flow profiles and mass spectra of combustion gases). Preliminary results are discussed. The enthalpy of the materials decreases with progressing mineralization, whereas the enthalpy of the remaining organic matter increases. The ratio of the enthalpies was used as an indicator of stability. Selected samples comprising old landfills, a

  4. Prediction of blood-brain barrier permeation of α-adrenergic and imidazoline receptor ligands using PAMPA technique and quantitative-structure permeability relationship analysis.

    PubMed

    Vucicevic, Jelica; Nikolic, Katarina; Dobričić, Vladimir; Agbaba, Danica

    2015-02-20

    Imidazoline receptor ligands are a numerous family of biologically active compounds known to produce central hypotensive effect by interaction with both α2-adrenoreceptors (α2-AR) and imidazoline receptors (IRs). Recent hypotheses connect those ligands with several neurological disorders. Therefore some IRs ligands are examined as novel centrally acting antihypertensives and drug candidates for treatment of various neurological diseases. Effective Blood-Brain Barrier (BBB) permeability (P(e)) of 18 IRs/α-ARs ligands and 22 Central Nervous System (CNS) drugs was experimentally determined using Parallel Artificial Membrane Permeability Assay (PAMPA) and studied by the Quantitative-Structure-Permeability Relationship (QSPR) methodology. The dominant molecules/cations species of compounds have been calculated at pH = 7.4. The analyzed ligands were optimized using Density Functional Theory (B3LYP/6-31G(d,p)) included in ChemBio3D Ultra 13.0 program and molecule descriptors for optimized compounds were calculated using ChemBio3D Ultra 13.0, Dragon 6.0 and ADMET predictor 6.5 software. Effective permeability of compounds was used as dependent variable (Y), while calculated molecular parametres were used as independent variables (X) in the QSPR study. SIMCA P+ 12.0 was used for Partial Least Square (PLS) analysis, while the stepwise Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) modeling were performed using STASTICA Neural Networks 4.0. Predictive potential of the formed models was confirmed by Leave-One-Out Cross- and external-validation and the most reliable models were selected. The descriptors that are important for model building are identified as well as their influence on BBB permeability. Results of the QSPR studies could be used as time and cost efficient screening tools for evaluation of BBB permeation of novel α-adrenergic/imidazoline receptor ligands, as promising drug candidates for treatment of hypertension or neurological diseases

  5. Dynamic analysis of phospholipid metabolism of mouse macrophages treated with common non-steroidal anti-inflammatory drugs.

    PubMed

    Peng, Haibo; Wu, Xia; Zhao, Lifang; Feng, Yifan

    2016-01-01

    Through studying the changes of the total phospholipid components in mouse macrophages under the inflammatory status and the drug intervention status, we found the targets of non-steroidal anti-inflammatory drugs on phospholipids, thus providing the basis for the targets of in vitro anti-inflammatory effects of non-steroidal anti-inflammatory drugs. After RAW264.7 cells were pretreated with common non-steroidal anti-inflammatory drugs (aspirin and ibuprofen) and, respectively, stimulated with KLA for various periods (0.5, 4, 12, 16, and 24 h), the phospholipids were extracted. The dynamic changes of phospholipids in cells under various stimulations were analyzed with UPLC-Q-TOF-MS technique. Through the statistical analysis of Simca-P, we explored the potential targets of non-steroidal anti-inflammatory drugs on phospholipids. Through the dynamic analysis of phospholipids, we found two biomarkers (PC(17:1/18:1), PA(18:0/18:4)) which might be in vitro intervention inflammatory response targets of non-steroidal anti-inflammatory drugs. The analysis results show that in anti-inflammatory effects, non-steroidal anti-inflammatory drugs can inhibit COX, induce the cellular fatty acid desaturation and the changes of phospholipid components, stimulate free fatty acids, activate calcium ion channels of endoplasmic reticulum, and promote cell endocytosis, thus controlling inflammation and activating cells. Non-steroidal anti-inflammatory drugs can promote endocytosis, alter cell inflammatory response, and activate the process cells, thus realizing the anti-inflammatory effects. PMID:26441061

  6. [Optimization of processing technology for xanthii fructus by UPLC fingerprint technique and contents of toxicity ingredient].

    PubMed

    Han, Yan-Quan; Hong, Yan; Xia, Lun-Zhu; Gao, Jia-Rong; Wang, Yong-Zhong; Sun, Yan-Hua; Yi, Jin-Hai

    2014-04-01

    The experiment's aim was to optimize the processing technology of Xanthii Fructus which through comparing the difference of UPLC fingerprint and contents of toxicity ingredient in water extract of 16 batches of processed sample. The determination condition of UPLC chromatographic and contents of toxicity ingredient were as follows. UPLC chromatographic: ACQUITY BEH C18 column (2.1 mm x 100 mm, 1.7 microm) eluted with the mobile phases of acetonitrile and 0.1% phosphoric acidwater in gradient mode, the flow rate was 0.25 mL x min(-1) and the detection wavelength was set at 327 nm. Contents of toxicity ingredient: Agilent TC-C18 column (4.6 mm x 250 mm, 5 microm), mobile phase was methanol-0.01 mol x L(-1) sodium dihydrogen phosphate (35: 65), flow rate was 1.0 mL x min(-1), and detection wavelength was 203 nm. The chromatographic fingerprints 16 batches of samples were analyzed in using the similarity evaluation system of chromatographic, fingerprint of traditional Chinese medicine, SPSS16.0 and SIMCA13.0 software, respectively. The similarity degrees of the 16 batches samples were more than 0.97, all the samples were classified into four categories, and the PCA showed that the peak area of chlorogenic acid, 3,5-dicaffeoylquinic acid and caffeic acid were significantly effect index in fingerprint of processed Xanthii Fructus sample. The outcome of determination showed that the toxicity ingredient contents of all samples reduced significantly after processing. This method can be used in optimizing the processing technology of Xanthii Fructus. PMID:25011263

  7. Žemės paviršiaus lūžio linijos padėties nustatymas lokaliai pritaikant plokštumas

    NASA Astrophysics Data System (ADS)

    Stankevičius, Žilvinas

    2010-01-01

    Straipsnyje pristatomas sukurtas LIDAR skenuotų ta\\vskų apdorojimo metodas. Ta\\vskų klasifikavimo metodas pagrįstas ta\\vskų atrinkimu artimoje gretimybėje ir lokalios plokštumos pritaikymu. Lokaliai plokštumai pritaikyti skaičiuojamos tikrinių vektorių reikšmės, taikomas Jacobi iteracijų metodas. Sukurtoji preliminari šlaito viršaus ir apačios linija tikslinama pritaikant lokalias plokštumas kairėje ir dešinėje kiekvieno segmento pusėje. Pagal aprašytą algoritmą sukurtos kompiuterinės programos. Testinėje teritorijoje išbandytas siūlomo metodo patikimumas. Lyginant rezultatus su tradiciniais kartogafavimo metodais toje pačioje teritorijoje gautais duomenimis, parinktos tinkamos algoritmo parametrų reikšmės. Eksperimento rezultatai patvirtino, kad sudarius šį algoritmą galima pasiekti M 1:1000 ir smulkesnių mastelių planų kokybę.

  8. Fusarium inhibition by wild populations of the medicinal plant Salvia africana-lutea L. linked to metabolomic profiling

    PubMed Central

    2014-01-01

    Background Salvia africana-lutea L., an important medicinal sage used in the Western Cape (South Africa), can be termed a ‘broad-spectrum remedy’ suggesting the presence of a multiplicity of bioactive metabolites. This study aimed at assessing wild S. africana-lutea populations for chemotypic variation and anti-Fusarium properties. Methods Samples were collected from four wild growing population sites (Yzerfontein, Silwerstroomstrand, Koeberg and Brackenfell) and one garden growing location in Stellenbosch. Their antifungal activities against Fusarium verticillioides (strains: MRC 826 and MRC 8267) and F. proliferatum (strains: MRC 6908 and MRC 7140) that are aggressive mycotoxigenic phytopathogens were compared using an in vitro microdilution assay. To correlate antifungal activity to chemical profiles, three techniques viz. Gas chromatography-mass spectrometry (GC-MS); Liquid chromatography-mass spectrometry (LC-MS) and 1H Nuclear Magnetic Resonance (NMR) were employed. Principal Component Analysis (PCA) was applied to the NMR data. The partial least squares-discriminant analysis (PLS-DA) was used to integrate LC-MS and NMR data sets. All statistics were performed with the SIMCA-P + 12.0 software. Results The dichloromethane:methanol (1:1; v/v) extracts of the plant species collected from Stellenbosch demonstrated the strongest inhibition of F. verticillioides and F. proliferatum with minimum inhibitory concentration (MIC) values of 0.031 mg ml-1 and 0.063 mg ml-1 respectively. GC-MS showed four compounds which were unique to the Stellenbosch extracts. By integrating LC-MS and 1H NMR analyses, large chemotype differences leading to samples grouping by site when a multivariate analysis was performed, suggested strong plant-environment interactions as factors influencing metabolite composition. Signals distinguishing the Stellenbosch profile were in the aromatic part of the 1H NMR spectra. Conclusions This study shows the potential of chemotypes of

  9. [Identification of varieties of black bean using ground based hyperspectral imaging].

    PubMed

    Zhang, Chu; Liu, Fei; Zhang, Hai-Liang; Kong, Wen-Wen; He, Yong

    2014-03-01

    In the present study, hyperspectral imaging combined with chemometrics was successfully proposed to identify different varieties of black bean. The varieties of black bean were defined based on the three different colors of the bean core. The hy-perspectral images in the spectral range of 380-1,030 nm of black bean were acquired using the developed hyperspectral imaging system, and the reflectance spectra were extracted from the region of interest (ROD) in the images. The average spectrum of a ROI of the sample in the images was used to represent the spectrum of the sample and build classification models. In total, 180 spectra of 180 samples were extracted. The wavelengths from 440 to 943 nm were used for analysis after the removal of the spec- tral region with absolute noises, and 440-943 nm spectra were preprocessed by multiplicative scatter correction (MSC). Five classification methods, including partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), K-nearest neighbor algorithm (KNN), support vector machine (SVM) and extreme learning machine (ELM), were used to build discriminant models using the preprocessed full spectra, the feature information extracted by principal component analysis (PCA) and the feature information extracted by wavelet transform (WT) from the preprocessed spectra, respectively. Among all the classification models using the preprocessed full spectra, ELM models obtained the best performance; among all the classification models using the feature information extracted from the preprocessed spectra by PCA, ELM model also obtained the best classification accuracy; and among all the classification models using the feature information extracted from the preprocessed spectra by WT, ELM models obtained the best classification performance with 100% accuracy in both the calibration set and the prediction set. Among all classification models, WT-ELM model obtained the best classification accuracy

  10. Aging of target lipid parameters in fingermark residue using GC/MS: Effects of influence factors and perspectives for dating purposes.

    PubMed

    Girod, Aline; Spyratou, Alexandra; Holmes, David; Weyermann, Céline

    2016-05-01

    (SIMCA) based on PCA classes, univariate exponential linear regression and PLSR. Furthermore, a probabilistic approach using the calculation of likelihood ratios (LR) through the construction of a Bayesian network was also tested. While the age of all test fingermarks were correctly evaluated when the storage conditions were known, the results were not significant when these conditions were unknown. Thus, this model clearly highlighted the impact of storage conditions on correct age evaluation. This research showed that reproducible aging modelling could be obtained based on fingermark residue exposed to influence factors, as well as promising age estimations. However, the proposed models are still not applicable in practice. Further studies should be conducted concerning the impact of influence factors (in particular, storage conditions) in order to precisely evaluate in which conditions significant evaluations could be obtained. Furthermore, these models should be properly validated before any application in real caseworks could be envisaged. PMID:27162015

  11. Pattern recognition analysis and classification modeling of selenium-producing areas

    USGS Publications Warehouse

    Naftz, D.L.

    1996-01-01

    Established chemometric and geochemical techniques were applied to water quality data from 23 National Irrigation Water Quality Program (NIWQP) study areas in the Western United States. These techniques were applied to the NIWQP data set to identify common geochemical processes responsible for mobilization of selenium and to develop a classification model that uses major-ion concentrations to identify areas that contain elevated selenium concentrations in water that could pose a hazard to water fowl. Pattern recognition modeling of the simple-salt data computed with the SNORM geochemical program indicate three principal components that explain 95% of the total variance. A three-dimensional plot of PC 1, 2 and 3 scores shows three distinct clusters that correspond to distinct hydrochemical facies denoted as facies 1, 2 and 3. Facies 1 samples are distinguished by water samples without the CaCO3 simple salt and elevated concentrations of NaCl, CaSO4, MgSO4 and Na2SO4 simple salts relative to water samples in facies 2 and 3. Water samples in facies 2 are distinguished from facies 1 by the absence of the MgSO4 simple salt and the presence of the CaCO3 simple salt. Water samples in facies 3 are similar to samples in facies 2, with the absence of both MgSO4 and CaSO4 simple salts. Water samples in facies 1 have the largest selenium concentration (10 ??gl-1), compared to a median concentration of 2.0 ??gl-1 and less than 1.0 ??gl-1 for samples in facies 2 and 3. A classification model using the soft independent modeling by class analogy (SIMCA) algorithm was constructed with data from the NIWQP study areas. The classification model was successful in identifying water samples with a selenium concentration that is hazardous to some species of water-fowl from a test data set comprised of 2,060 water samples from throughout Utah and Wyoming. Application of chemometric and geochemical techniques during data synthesis analysis of multivariate environmental databases from other

  12. Chemical composition of the major components of PM in different sites at the Metropolitan Region of Chile

    NASA Astrophysics Data System (ADS)

    Reyes, F.; Castillo, M. A.; Rubio, M.; Gramsch, E.; Vasquez, Y.; Oyola, P.

    2013-05-01

    Santiago, Chile's capital is one of most polluted megacity (5.5 million of people) of the world. Currently, PM2.5 annual concentration is over 2.2 times the Chilean standard (20 μg/m3). Continuous measurements of non-refractory PM1.0 (sulfate, nitrate, chloride, ammonium and organics aerosols), black carbon, and PM2,5 mass concentration were determined using Aerosol Chemical Speciation Monitor (ACSM, Aerodyne Research, Inc), absorption coefficient monitor (SIMCA, Santiago University) and dustrack monitor (TSI Inc) in order to know the temporal variability of the major components of PM. The measurements were carried out at kerbside, urban background, industrial and mixed residential/industrial locations during year 2012 and -2013. Meteorological data (Relative Humidity, temperature, wind speed, wind direction and precipitations) were obtained from the air quality network operated by the environmental authority. The results show strong correlation with the metropolitan region major sources. Multiple regression analysis indicates that precipitations have a strong impact on PM1.0 soluble components; relative humidity has effects only on chloride, sulfate and black carbon. Chloride concentration decrease when temperature is increasing. The perceptual contribution of each component is similar among all sites. All sites shows that OA (Organics Aerosol) as the major constituent of PM1.0 (>50%), followed of nitrates (>13%). Sulfate could be used to differentiate the industrial site; due to there is a strong impact of SO2 emission. Combustion sources direct impact can be seen at BC contribution at industrial and kerbside site. Also, the OA/BC ratio shows slow value at kerbside (3.05) and industrial (3.26) site, and higher at urban background site (4.15). Aged organics aerosols are majority found at all sites (f43/f44 plot), indicating that regional background is strong in all results. These results will be compared with size distribution measurements available from previous

  13. [Analysis and Discrimination of the Medicinal Plants Swertia Davidi Franch Based on Infrared Spectroscopy].

    PubMed

    Di, Zhun; Zhao, Yan-li; Zuo, Zhi-tian; Long, Hua; Zhang, Xue; Wang, Yuan-zhong; Li, Li

    2016-02-01

    Fourier-transform infrared spectroscopy combined with partial least squares discriminate analysis (PLS-DA) and hierarchical cluster analysis (HCA) were used to rapidly discriminate the Swertia davidi Franch which collected from different origins. The original infrared spectra data of different parts of all the 70 samples which collected from four different regions were preprocessed by automatic calibration, automatic smoothing, the first derivative and the,second derivative. Then the processed data were imported into OMNIC 8.2 and the absorption peaks were compared; PLS-DA was performed by SIMCA-P⁺ 10.0 and the effect of discrimination of different origins was compared by 3D score plot of the first three principal components; the infrared spectral data were imported into SPSS 19. 0 for HCA to compare classification results of different parts by the dendrogram. The results showed that: (1) There were differences among the spectra of the roots of different origins in the spectral peaks in 1,739, 1,647, 1,614, 1,503, 1,271, 1,243, 1,072 cm⁻¹. The spectra of the stems of different origins showed differentiation in the wavelength in 1 503, 1 270, 1 246 cm⁻¹; (2) The characteristic peaks of different parts of the same origin were different; (3) PLS-DA indicated that the data which were processed by automatic correction, automatic smoothing and second derivative have showed the best classification. In addition, the discrimination of roots which collected from different origins could be the best; (4) Tree diagram of HCA showed that the accuracy rate of cluster in roots, stems and leaves were 83%, 56%, and 70%, respectively. In conclusion: FTIR combined with PLS-DA and HCA can rapidly and accurately differentiate S. davidi that collected from different origins, the origin discrimination effect of different parts was clearly different that the classification of roots is the best, the second derivative could enhance the specificity of the samples, the classification

  14. Rapid discrimination of extracts of Chinese propolis and poplar buds by FT-IR and 2D IR correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Wu, Yan-Wen; Sun, Su-Qin; Zhao, Jing; Li, Yi; Zhou, Qun

    2008-07-01

    The extract of Chinese propolis (ECP) has recently been adulterated with that of poplar buds (EPB), because most of ECP is derived from the poplar plant, and ECP and EPB have almost identical chemical compositions. It is very difficult to differentiate them by using the chromatographic methods such as high performance liquid chromatography (HPLC) and gas chromatography (GC). Therefore, how to effectively discriminate these two mixtures is a problem to be solved urgently. In this paper, a rapid method for discriminating ECP and EPB was established by the Fourier transform infrared (FT-IR) spectra combined with the two-dimensional infrared correlation (2D IR) analysis. Forty-three ECP and five EPB samples collected from different areas of China were analyzed by the FT-IR spectroscopy. All the ECP and EPB samples tested show similar IR spectral profiles. The significant differences between ECP and EPB appear in the region of 3000-2800 cm -1 of the spectra. Based on such differences, the two species were successfully classified with the soft independent modeling of class analogy (SIMCA) pattern recognition technique. Furthermore, these differences were well validated by a series of temperature-dependent dynamic FT-IR spectra and the corresponding 2D IR plots. The results indicate that the differences in these two natural products are caused by the amounts of long-chain alkyl compounds (including long-chain alkanes, long-chain alkyl esters and long chain alkyl alcohols) in them, rather than the flavonoid compounds, generally recognized as the bioactive substances of propolis. There are much more long-chain alkyl compounds in ECP than those in EPB, and the carbon atoms of the compounds in ECP remain in an order Z-shaped array, but those in EPB are disorder. It suggests that FT-IR and 2D IR spectroscopy can provide a valuable method for the rapid differentiation of similar natural products, ECP and EPB. The IR spectra could directly reflect the integrated chemical

  15. Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

    NASA Astrophysics Data System (ADS)

    Anderson, Ryan B.; Bell, James F., III; Wiens, Roger C.; Morris, Richard V.; Clegg, Samuel M.

    2012-04-01

    We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO2 at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by ~ 3 wt.%. The statistical significance of these improvements was ~ 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and specifically fabricated

  16. Investigaccion-accion en la sala de clases sobre las creencias de la cultura de la ciencia de un grupo de estudiantes universitarios y su relacion reciproca con el aprendizaje de las ciencias biologicas

    NASA Astrophysics Data System (ADS)

    Cordova-Santiago, Lizzette Astrid

    La investigacion---accion que se llevo a cabo en la sala de clases tenia como punto de partida las creencias de la cultura de la ciencia de un grupo de estudiantes universitarios para luego examinar sus implicaciones en el proceso de aprendizaje de las Ciencias Biologicas. ¿Que se supone que hagan las creencias en relacion con el aprendizaje? ¿En que consiste incorporar este aspecto a la practica educativa universitaria? Utilizando el modelo de Kemmis y McTaggart (1987) la investigacion-accion se planteo como un proceso dinamico en cuatro momentos en espiral constituidos por la planificacion, la accion, la observacion y la reflexion. Cada una de las fases tuvo una intencion retrospectiva y prospectiva formando una espiral de autorreflexion del conocimiento y la accion. Se llevaron a cabo audio grabaciones en clases y analisis de documentos. Ademas, la profesora-investigadora hizo un portafolio para reflexionar sobre las creencias de la cultura de la ciencia que tienen los estudiantes y las creencias del aprendizaje que tiene la profesora y sobre como la comprension de estos elementos ayudo a mejorar su practica educativa a traves del tiempo. Los resultados obtenidos apuntan a que las creencias de la cultura de la ciencia que tiene el grupo de estudiantes son diversas. Ellos si creen que la ciencia tiene una cultura la cual describieron como: complicada y desconocida que evoluciona constantemente, que es un conjunto de metodos, que es altamente tecnologica, que resuelve problemas de salud, ayuda a interpretar la realidad del mundo que los rodea y su origen y que existen unas intersecciones entre la ciencia y el poder. Sobre las creencias del proceso de aprendizaje de la profesora-investigadora, estas senalan que el modelaje de actores, la vision de la academia que tiene ella asi como la participacion y negociacion entre todos los involucrados en el proceso educativo, son factores que inciden en el proceso de aprendizaje.

  17. Procesamiento Digital de Imagenes del Cometa Halley

    NASA Astrophysics Data System (ADS)

    Ferrin, L.; Fuenmayor, F.; Naranjo, O.; Bulka, P.; Mendoza, C.

    1987-05-01

    Se reportan observaciones fotográficas del cometa Halley, obtenidas con los telescopios Schmidt de 1-m del CIDA, y de 35 cms de la ULA. Se hicieron exposiciones desde 2 segundos a 30 minutos y se utilizaron emulsiones IIa-O, 103a-F, y 103a-D, guladas manualmente 0 automaticámente. Las imágenes fueron digitalizadas con el microdensitómetro PDS, y procesadas con el sistema HACIENDA del CCIBM. Se experimentó con la Transformada de Fourier en dos dimensiones, y con la aplicación de filtros de paso alto y bajo. Se encontró que el metodo de "autocorrelación" es el mejor para separar "la vegetación" de "la montaña". Se aplicaron diversas técnicas a fin de cubrir ambos extremos: a) enfatizar detalles débiles en la cola, y b) penetrar en las regiones más intensas de la coma. Se lograron ambos objetivos. Detalles en la cola permitieron determinar velocidades de propagación de unos 50 a 90 kms/ seg. Se pudieron detectar no menos de tres perturbaciones en "Y", y una en 5? Co de Cisne). Se cree que las primeras están asociadas a eventos de desconexión. Se puede separar la cola de gas de la de polvo. Las fotos de color permiten enfatizar diferentes regiones espectrales con mayor claridad aún. El "balance" del color puede ser hecho con la computadora.

  18. Introduccion a la hidraulica de aguas subterraneas : un texto programado para auto-ensenanza

    USGS Publications Warehouse

    Bennett, Gordon D.

    1987-01-01

    Este ' texto programado esta diseflado para ayudarle a comprender la teoria de la hidniulica de aguas subterraneas por medio de la auto-enseflanza. La instrucci6n programada es un enfoque a una materia, un metodo de aprender;que no elimina el esfuerzo mental del proceso de aprendizaje. Algunas secciones de este programa necesitan solamente ser leidas; otras tendrian que ser elaboradas con lapiz y papel. Algunas preguntas pueden ser contestadas directamente; otras requieren calculos. A medida que se avanza en el texto, tendra que consultar frecuentemente textos o referencias sobre matematicas, mecanica de fluidos e hidrologia. En cada una de las ocho partes del texto, inicie el programa de instrucci6n leyendo la Secci6n 1. Elija una respuesta a la pregunta al final de la secci6n y dirijase a la nueva secci6n indicada al lado de la respuesta escogida. Si su respuesta fue correcta, pase a la secci6n que contiene materia nueva y otra pregunta, y proceda tal como en la Secci6n 1. Si su respuesta no fue correcta, dirijase a la secci6n que contiene explicaciones adicionales sobre el tema anterior y que le indica volver a la pregunta inicial e intentar de nuevo. En este caso, valdra Ia pena repasar el material de la secci6n anterior. Continue de esta man era en el programa hasta que llegue a Ia secci6n que indica el final de la parte. Observe que aunque las secciones estan en orden numerico en cada una de las ocho partes, por lo general, usted no procedeni en secuencia numerica (Secci6n 1 ala Secci6n 2, etc.) de principia a fin.

  19. Sterile insect technique: A model for dose optimisation for improved sterile insect quality

    SciTech Connect

    Parker, A.

    2007-03-15

    The sterile insect technique (SIT) is an environment-friendly pest control technique with application in the area-wide integrated control of key pests, including the suppression or elimination of introduced populations and the exclusion of new introductions. Reproductive sterility is normally induced by ionizing radiation, a convenient and consistent method that maintains a reasonable degree of competitiveness in the released insects. The cost and effectiveness of a control program integrating the SIT depend on the balance between sterility and competitiveness, but it appears that current operational programs with an SIT component are not achieving an appropriate balance. In this paper we discuss optimization of the sterilization process and present a simple model and procedure for determining the optimum dose. (author) [Spanish] La tecnica de insecto esteril (TIE) es una tecnologia de control de plagas favorable para el medio ambiente con una aplicacion de un control integrado de plagas claves para toda la area, incluyendo la supresion o eliminacion de poblaciones introducidas y la exclusion de nuevas introducciones. La esterilidad reproductiva es normalmente inducida por radiacion ionizada, un metodo conveniente y consistente que mantiene un grado razonable para la capacidad de competencia en insectos liberados. El costo y la eficacia de un programa de control que incluye TIE dependen en tener un balance entre la esterilidad y la capacidad para competir, pero parece que los programas operacionales corrientes con TIS como un componente no estan logrando el tener un balance apropiado. En esta publicacion, nosotros discutimos la optimizacion del proceso de esterilizacion y presentamos un modelo y procedimiento sencillos para determinar la dosis optima. (author)

  20. Estimaciones de Prevalencia del VIH por Género y Grupo de Riesgo en Tijuana, México: 2006

    PubMed Central

    Iñiguez-Stevens, Esmeralda; Brouwer, Kimberly C.; Hogg, Robert S.; Patterson, Thomas L.; Lozada, Remedios; Magis-Rodriguez, Carlos; Elder, John P.; Viani, Rolando M.; Strathdee, Steffanie A.

    2010-01-01

    OBJETIVO Estimar la prevalencia del VIH en adultos de 15-49 años de edad en Tijuana, México - en la población general y en subgrupos de riesgo en el 2006. METODOS Se obtuvieron datos demográficos del censo Mexicano del 2005, y la prevalencia del VIH se obtuvo de la literatura. Se construyó un modelo de prevalencia del VIH para la población general y de acuerdo al género. El análisis de sensibilidad consistió en estimar errores estándar del promedio-ponderado de la prevalencia del VIH y tomar derivados parciales con respecto a cada parámetro. RESULTADOS La prevalencia del VIH es 0.54%(N = 4,347) (Rango: 0.22%–0.86%, (N = 1,750–6,944)). Esto sugiere que 0.85%(Rango: 0.39%–1.31%) de los hombres y 0.22%(Rango: 0.04%–0.40%) de las mujeres podrían ser VIH-positivos. Los hombres que tienen sexo con hombres (HSH), las trabajadoras sexuales usuarias de drogas inyectables (MTS-UDI), MTS-noUDI, mujeres UDI, y los hombres UDI contribuyeron las proporciones más elevadas de personas infectadas por el VIH. CONCLUSIONES El número de adultos VIH-positivos entre subgrupos de riesgo en la población de Tijuana es considerable, marcando la necesidad de enforcar las intervenciones de prevención en sus necesidades específicas. El presente modelo estima que hasta 1 en cada 116 adultos podrían ser VIH-positivos. PMID:19685824

  1. Pulsation, Mass Loss and the Upper Mass Limit

    NASA Astrophysics Data System (ADS)

    Klapp, J.; Corona-Galindo, M. G.

    1990-11-01

    RESUMEN. La existencia de estrellas con masas en exceso de 100 M0 ha sido cuestionada por mucho tiempo. Lfmites superiores para la masa de 100 M0 han sido obtenidos de teorfas de pulsaci6n y formaci6n estelar. En este trabajo nosotros primero investigamos la estabilidad radial de estrellas masivas utilizando la aproximaci6n clasica cuasiadiabatica de Ledoux, la aproximaci6n cuasiadiabatica de Castor y un calculo completamente no-adiabatico. Hemos encontrado que los tres metodos de calculo dan resultados similares siempre y cuando una pequefia regi6n de las capas externas de la estrella sea despreciada para la aproximaci6n clasica. La masa crftica para estabilidad de estrellas masivas ha sido encontrada en acuerdo a trabajos anteriores. Explicamos Ia discrepancia entre este y trabajos anteriores por uno de los autores. Discunmos calculos no-lineales y perdida de masa con respecto a) lfmite superior de masa. The existence of stars with masses in excess of 100 M0 has been questioned for a very long time. Upper mass limits of 100 Me have been obtained from pulsation and star formation theories. In this work we first investigate the radial stability of massive stars using the classical Ledoux's quasiadiabatic approximation. the Castor quasiadiabatic approximation and a fully nonadiabatic calculation. We have found that the three methods of calculation give similar results provided that a small region in outer layers of the star be neglected for the classical approximation. The critical mass for stability of massive stars is found to be in agreement with previous work. We explain the reason for the discrepancy between this and previous work by one of the authors. We discuss non-linear calculations and mass loss with regard to the upper mass limit. Key words: STARS-MASS FUNCTION - STARS-MASS LOSS - STARS-PULSATION

  2. Attenuation of Ultraviolet Radiation by Dust in Interstellar Clouds

    NASA Astrophysics Data System (ADS)

    Escalante, V.

    1994-07-01

    Se han obtenido soluciones de la ecuación de transporte para la dispersión coherente, no conservativa y anisotrópica para estimar la precisión de métodos aproximados, usados en modelos de nubes en que la luz es atenuada principalmente por el polvo. En los cálculos se ha aplicado el metodo de armónicos esféricos para distintos parámetros del polvo. Se ha explorado la posibilidad de descubrir cambios en las caracterísiticas del polvo mediante observaciones de regiones fotodisociadas. Se muestra que para altos valores del albedo de dispersión simple y del parametro de asimetria de Ia función de fase que son adecuados para el polvo galáctico, no es posible determinar variaciones de más de un factor de 2 en el cociente de gas a polvo. Solutions to the transfer equation for coherent, non-conservative, anisotropic scattering have been obtained in order to estimate the accuracy of approximate methods used in models of clouds where light is attenuated mostly by dust. In the calculations the spherical harmonic method has been applied for different grain parameters. The possibility of discovering changes of dust characteristics through observations of photodissociation regions has been considered. It is shown that for the high values of the single scattering albedo and the asymmetry parameter of the phase function for redistribution that appear to be appropriate for galactic dust, it is not possible to determine variations of more than a factor of 2 in the gas to dust ratio.

  3. Elastoplasticidad anisotropa de metales en grandes deformaciones

    NASA Astrophysics Data System (ADS)

    Caminero Torija, Miguel Angel

    El objetivo de este trabajo es el desarrollo de modelos y algoritmos numericos que simulen el comportamiento del material bajo estas condiciones en el contexto de programas de elementos finitos, dando como resultado predicciones mas precisas de los procesos de conformado y deformacion plastica en general. Para lograr este objetivo se han desarrollado diversas tareas destinadas a mejorar las predicciones en tres aspectos fundamentales. El primer aspecto consiste en la mejora de la descripcion del endurecimiento cinematico anisotropo en pequenas deformaciones, lo cual se ha realizado a traves de modelos y algoritmos implicitos de superficies multiples. Ha sido estudiada la consistencia de este tipo de modelos tanto si estan basados en una regla implicita similar a la de Mroz o en la regla de Prager. Ademas se han simulado los ensayos de Lamba y Sidebottom, obteniendo, en contra de la creencia general, muy buenas predicciones con la regla de Prager. Dichos modelos podrian ser extendidos de forma relativamente facil para considerar grandes deformaciones a traves de procedimientos en deformaciones logaritmicas, similares a los desarrollados en esta tesis y detallados a continuacion. El segundo aspecto consiste en la descripcion de la anisotropia elastoplastica inicial. Esto se ha conseguido mediante el desarrollo de modelos y algoritmos para plasticidad anisotropa en grandes deformaciones, bien ignorando la posible anisotropia elastica, bien considerandola simultaneamente con la anisotropia plastica. Para ello ha sido necesario desarrollar primero un nuevo algoritmo de elastoplasticidad anisotropa en pequenas deformaciones consistentemente linealizado y sin despreciar ningun termino, de tal forma que se conserve la convergencia cuadratica de los metodos de Newton. Este algoritmo en pequenas deformaciones ha servido para realizar la correccion plastica de dos algoritmos en grandes deformaciones. El primero de estos algoritmos es una variacion del clasico algoritmo de

  4. In-line solid state prediction during pharmaceutical hot-melt extrusion in a 12 mm twin screw extruder using Raman spectroscopy.

    PubMed

    Saerens, Lien; Ghanam, Dima; Raemdonck, Cedric; Francois, Kjell; Manz, Jürgen; Krüger, Rainer; Krüger, Susan; Vervaet, Chris; Remon, Jean Paul; De Beer, Thomas

    2014-08-01

    The aim of this research was to use Raman spectroscopy for the in-line monitoring of the solid state of materials during pharmaceutical hot-melt extrusion in the die head of a 12 mm (development scale) twin-screw extruder during formulation development. A full factorial (mixed) design was generated to determine the influence of variations in concentration of Celecoxib (CEL) in Eudragit® E PO, three different screw configurations and varying barrel temperature profiles on the solid state, 'melt temperature' and die pressure of continuously produced extrudates in real-time. Off-line XRD and DSC analysis were used to evaluate the suitability of Raman spectroscopy for solid state predictions. First, principal component analysis (PCA) was performed on all in-line collected Raman spectra from the experimental design. The resulting PC 1 versus PC 2 scores plot showed clustering according to solid state of the extrudates, and two classes, one class where crystalline CEL is still present and a second class where no crystalline CEL was detected, were found. Then, a soft independent modelling of class analogy (SIMCA) model was developed, by modelling these two classes separately by disjoint PCA models. These two separate PCA models were then used for the classification of new produced extrudates and allowed distinction between glassy solid solutions of CEL and crystalline dispersions of CEL. All extrudates were classified similarly by Raman spectroscopy, XRD and DSC measurements, with exception of the extrudates with a 30% CEL concentration extruded at 130 °C. The Raman spectra of these experiments showed bands which were sharper than the amorphous spectra, but broader than the crystalline spectra, indicating the presence of CEL that has dissolved into the matrix and CEL in its crystalline state. XRD and DSC measurements did not detect this. Modifications in the screw configuration did not affect the solid state and did not have an effect on the solid state prediction of

  5. CALL FOR PAPERS: Progress in Supersymmetric Quantum Mechanics

    NASA Astrophysics Data System (ADS)

    2003-12-01

    This is a call for contributions to a special issue of Journal of Physics A: Mathematical and General dedicated to the subject of Supersymmetric Quantum Mechanics as featured in the International Conference in Supersymmetric Quantum Mechanics (PSQM03), 15--19 July 2003, University of Valladolid, Spain (http://metodos.fam.cie.uva.es/~susy_qm_03/). Participants at that meeting, as well as other researchers working in this area or in related fields, are invited to submit a research paper to this issue. The Editorial Board has invited Irina Areféva, David J Fernández, Véronique Hussin, Javier Negro, Luis M Nieto and Boris F Samsonov to act as Guest Editors for the special issue. Their criteria for acceptance of contributions are as follows: bullet The subject of the paper should be in the general area covered by the PSQM03 conference. bullet Contributions will be refereed and processed according to the usual mechanisms of the journal. bullet Papers should present substantial new results (they should not be simply reviews of authors' own work that is already published elsewhere). The guidelines for the preparation of contributions are as follows: bullet DEADLINE for submission of contributions is 15 January 2004. This deadline will allow the special issue to appear in approximately September 2004. bullet There is a page limit of 15 pages per research contribution. Further advice on publishing your work in Journal of Physics A: Mathematical and General may be found at www.iop.org/Journals/jphysa. bullet Contributions to the special issue should if possible be submitted electronically at www.iop.org/Journals/jphysa or by e-mail to jphysa@iop.org, quoting `JPhysA special issue --- PSQM03'. Submissions should ideally be in either standard LaTeX form or Microsoft Word. Please see the web site for further information on electronic submissions. bullet Authors unable to submit by email may send hard copy contributions to: Journal of Physics A, Institute of Physics Publishing

  6. A protocol for storage and long-distance shipment of Mediterranean fruit fly (Diptera: Tephritidae) eggs. 1. Effect of temperature, embryo age , and storage time on survival and quality

    SciTech Connect

    Caceres, C.; Wornoayporn, V.; Islam, S.M.; Ahmad, S.

    2007-03-15

    The operational use of Mediterranean fruit fly (medfly) Ceratitis capitata (Wiedemann), genetic sexing strains in Sterile Insect Technique applications can be maximized by developing methods for effective shipment of eggs. This would enable a central production facility to maintain the relevant mother stocks and large colonies to supply eggs to satellite centers that would mass produce only males for irradiation and release. In order to achieve this, the survival of medfly embryos of different ages was assessed after storage at 5, 10, 15, 20, and 25 deg. C in water for different periods of time. Survival was affected by all 3 variables, i.e., embryo age, water temperature, and length of storage. Storage of embryos at any temperature for 120 h resulted in almost no survival. Controlling the age of the embryo at the time of the temperature treatment is crucial for the success of this procedure. Embryos collected between 0 to 12 h after oviposition and pre-incubated at 25 deg. C for 12 h provide a suitable 72 h window for shipment when maintained between 10 to 15 deg. C. Under these conditions, no significant reductions in survival during all the developmental stages were observed. (author) [Spanish] El uso operacional de cepas de la mosca del mediterraneo Ceratitis capitata (Wiedemann) en las cuales es posible separar los sexos a traves de mecanismos geneticos para su utilizacion en la Tecnica del Insecto Esteril (TIE), puede ser maximizado con el desarrollo de metodos efectivos para el envio y transporte de huevos. Esto permite que un laboratorio de produccion centralizada mantenga las respectivas colonias responsables por la produccion de huevos para este abastecer laboratorios satelites responsables por la produccion masiva de solamente machos para subsiguiente irradiacion y liberacion. Para ser posible esta alternativa fue evaluada la supervivencia de embriones de diferentes edades despues de su almacenamiento en agua a 5, 10, 15, 20 y 25 deg. C por diferentes

  7. DIABETES MELLITUS COMO FACTOR DE RIESGO DE DEMENCIA EN LA POBLACIÓN ADULTA MAYOR MEXICANA

    PubMed Central

    Silvia, Mejía-Arango; Clemente, y Zúñiga-Gil

    2012-01-01

    Introduccion La diabetes mellitus y las demencias constituyen dos problemas crecientes de salud entre la población adulta mayor del mundo y en particular de los paises en desarrollo. Hacen falta estudios longitudinales sobre el papel de la diabetes como factor de riesgo para demencia. Objetivo Determinar el riesgo de demencia en sujetos Mexicanos con diabetes mellitus tipo 2. Materiales y Metodos Los sujetos diabéticos libres de demencia pertenecientes al Estudio Nacional de Salud y Envejecimiento en México fueron evaluados a los dos años de la línea de base. Se estudió el papel de los factores sociodemográficos, de otras comorbilidades y del tipo de tratamiento en la conversión a demencia. Resultados Durante la línea de base 749 sujetos (13.8%) tuvieron diabetes. El riesgo de desarrollar demencia en estos individuos fue el doble (RR, 2.08 IC 95%, 1.59–2.73). Se encontró un riesgo mayor en individuos de 80 años y más (RR 2.44 IC 95%, 1.46–4.08), en los hombres (RR, 2.25 IC 95%, 1.46–3.49) y en sujetos con nivel educativo menor de 7 años. El estar bajo tratamiento con insulina incrementó el riesgo de demencia (RR, 2.83, IC 95%, 1.58–5.06). Las otras comorbilidades que aumentaron el riesgo de demencia en los pacientes diabéticos fueron la hipertensión (RR, 2.75, IC 95%, 1.86–4.06) y la depresión (RR, 3.78, 95% IC 2.37–6.04). Conclusión Los sujetos con diabetes mellitus tienen un riesgo mayor de desarrollar demencia, La baja escolaridad y otras comorbilidades altamente prevalentes en la población Mexicana contribuyen a la asociación diabetes-demencia. PMID:21948010

  8. Use of IPA to demonstrate loss of forest interior birds from isolated woodlots

    USGS Publications Warehouse

    Robbins, C.S.; Boone, D.D.

    1983-01-01

    'Empleo de indices puntuales de abundancia (IPA) para demostrar la perdida de aves forestales en bosques aislados'. En Maryland, E.U., se seleccionaron bloques boscosos de diferente superficie, divididos en seis clase de tamano (2,8-6 ha, 7-14, 20-30, 34-80, 105-1300, mayores de 4000 ha). En estas ?islas' forestales fue programado un conjunto de muestreos puntuales con estas caracteristicas: 1) Cada punto se visito tres veces. 2) En cada visita se hicieron cuatro censos consecutivos de 5 minutos de duracion, empleando diferentes simbolos para machos cantores, adultos no cantores, aves en vuelo y aves inmaduras. 3) Los conteos se hicieron en tres epocas: final de Mayo, mitad de Junio y final de Junio. 4) Se dividio el tiempo de censo en tres priodos horarios: 5,15-6,30 ; 6,30-8; 8-9,30 hrs. 5) Los puntos se agruparon en co juntos de 4 a 9, considerando que un conjunto es el nlimero que un observador puede cubrir por manana. 6) La vegetacion fue descrita exhaustivamente en cuanto composicion y fisionomla. El principal objetivo que se busca consiste en conocer los requisitos areales de ciertas especies de bosque muy sensibles a la fragmentacion del habitat. Puede observarse (Figura 1) que una serie de migrantes de largo alcance se asientan en relacion con el aumento de la superficie del rodal arbo1ado, sabre todo en macizos de 4.000 o mas hectareas. Sin embargo, las especies sedentarias (Fig. 2) tienen pauta de presencia irregular en funcion del area, forestal, con tendencia a presentarse menos en los bosques mas extensos, Dryocopus pileatus, por excepcion, reacciona negativamente al pequeno tamano de la parcela arbolado, prefiriendo bosques grandes. Parecida respuesta da tambien Sitta carolinensis. Aunque se sabe poco de las exigencias areales de las aves forestales americanas, el metodo de los IPA resulta muy adecuado para esta clase de investigacion de tanto interes en gestion ambiental, posibilitando colectar gran cantidad de datos comparables en un periodo de

  9. La preparacion en ciencia de los candidatos a maestros del nivel elemental primario segun la reforma de la educacion cientifica en Puerto Rico: Una propuesta de secuencia curricular

    NASA Astrophysics Data System (ADS)

    Rodriguez Plaza, Evelyn

    procesos de la ciencia y las destrezas de la investigacion cientifica. En los cursos de metodologia en la ensenanza de la ciencia se deben estudiar los modelos, los metodos, las estrategias y las tecnicas mas efectivas para la ensenanza y el aprendizaje de la ciencia, asi como las tecnicas de avaluacion.

  10. Nanoparticulas basadas en complejos de Fe(II) con transicion de espin: sintesis, caracterizacion y aplicaciones en electronica molecular

    NASA Astrophysics Data System (ADS)

    Monrabal Capilla, Maria

    Esta tesis doctoral esta organizada en 5 capitulos y esta destinada al estudio de sistemas de Fe (II) que presentan el fenomeno de la transicion de espin a escala nanometrica. El capitulo 1 contiene una introduccion general sobre materiales moleculares multifuncionales, destacando aquellos ejemplos mas importantes. Por otro lado, se explicara el fenomeno de la transicion de espin, tratando aspectos conceptuales, los antecedentes mas importantes y la situacion actual. En el capitulo 2 se describen los diferentes procesos existentes para la obtencion de diferentes tipos de nanoparticulas. Ademas, se presenta la sintesis y caracterizacion de nanoparticulas del polimero de coordinacion unidimensional [Fe(Htrz)2(trz)]BF4, obtenidas mediante el metodo de micelas inversas. Estas nanoparticulas, con una estrecha distribucion de tamanos centrada alrededor de los 11 nm, presentan una transicion de espin muy abrupta, con un ancho ciclo de histeresis termica de unos 40K. En el capitulo 3 se describe el proceso de modificacion del tamano de las nanoparticulas descritas en el capitulo anterior, llevado a cabo variando la proporcion de surfactante/H2O en el medio. Ademas, con el objetivo de modificar las propiedades magneticas de las nanoparticulas obtenidas en el capitulo 2, se lleva a cabo la sintesis de nanoparticulas de polimeros de la misma familia del [Fe(Htrz)2(trz)]BF4. En concreto se sintetizaron 3 nuevos tipos de nanoparticulas basadas en el polimero [Fe(Htrz)1-x(NH2trz)x](ClO4)2, siendo x = 0.05, 0.15 y 0.3, en cada caso. Estas nanoparticulas siguen presentando una estrecha distribucion de tamanos y una transicion de espin muy abrupta y con un ancho ciclo de histeresis. Ademas, se observa que este ciclo se desplaza a temperaturas mas proximas a la temperatura ambiente a medida que se aumenta el porcentaje de 4-amino-1, 2, 4- triazol en la muestra. Pero al mismo tiempo se produce una disminucion de la anchura de este ciclo. Por ultimo, en este capitulo se presenta la

  11. Pollen Forecast and Dispersion Modelling

    NASA Astrophysics Data System (ADS)

    Costantini, Monica; Di Giuseppe, Fabio; Medaglia, Carlo Maria; Travaglini, Alessandro; Tocci, Raffaella; Brighetti, M. Antonia; Petitta, Marcello

    2014-05-01

    The aim of this study is monitoring, mapping and forecast of pollen distribution for the city of Rome using in-situ measurements of 10 species of common allergenic pollens and measurements of PM10. The production of daily concentration maps, associated to a mobile phone app, are innovative compared to existing dedicated services to people who suffer from respiratory allergies. The dispersal pollen is one of the most well-known causes of allergic disease that is manifested by disorders of the respiratory functions. Allergies are the third leading cause of chronic disease and it is estimated that tens millions of people in Italy suffer from it. Recent works reveal that during the last few years there was a progressive increase of affected subjects, especially in urban areas. This situation may depend: on the ability to transport of pollutants, on the ability to react between pollutants and pollen and from a combination of other irritants, existing in densely populated and polluted urban areas. The methodology used to produce maps is based on in-situ measurements time series relative to 2012, obtained from networks of air quality and pollen stations in the metropolitan area of Rome. The monitoring station aerobiological of University of Rome "Tor Vergata" is located at the Department of Biology. The instrument used to pollen monitoring is a volumetric sampler type Hirst (Hirst 1952), Model 2000 VPPS Lanzoni; the data acquisition is carried out as reported in Standard UNI 11008:2004 - "Qualità dell'aria - Metodo di campionamento e conteggio dei granuli pollinici e delle spore fungine aerodisperse" - the protocol that describes the procedure for measuring of the concentration of pollen grains and fungal spores dispersed into the atmosphere, and reported in the "Manuale di gestione e qualità della R.I.M.A" (Travaglini et. al. 2009). All 10 allergenic pollen are monitored since 1996. At Tor Vergata university is also operating a meteorological station (SP2000, CAE

  12. Modelizacion, control e implementacion de un procesador energetico paralelo para aplicacion en sistemas multisalida

    NASA Astrophysics Data System (ADS)

    Ferreres Sabater, Agustin

    modelizacion, y aplicacion en convertidores PWM, esta aun por estudiar y valorar. El primer Capitulo consiste en una breve introduccion al problema de la regulacion cruzada y la impedancia cruzada para posteriormente describir las tecnicas de post-regulacion actualmente mas empleadas, con especial atencion al post-regulador con transformador controlado. El Capitulo segundo trata del estudio de las caracteristicas estaticas del postregulador con transformador controlado. Partiendo de los estudios disponibles sobre el postregulador se plantean mejoras en su modo de actuacion y se discuten tres alternativas diferentes para controlar el transformador. Las dos primeras consisten en emplear un convertidor auxiliar Boost en sus dos modos de funcionamiento, continuo y discontinuo. La tercera consiste en controlar el transformador con una tension PWM directamente, sin filtrado. Finalmente se comprueba experimentalmente, para el estado estacionario, el funcionamiento del post-regulador para cada uno de los tres metodos de control. El Capitulo tercero trata de la dinamica de la salida controlada con el post-regulador cuando este emplea un convertidor auxiliar tipo Boost. Mediante la tecnica de promediado de variables de estado se propone el modelo de pequena senal, tanto para el modo continuo como para el modo discontinuo de funcionamiento del convertidor auxiliar. Los resultados mas significativos de esta seccion son las expresiones analiticas de las impedancias cruzadas y de la impedancia de la salida post-regulada. Como complemento al modelo de pequena senal se plantea un modelo de gran senal implementado sobre el simulador Pspice. Con este nuevo modelo se reproducen los resultados obtenidos con el modelo de pequena senal y ademas es posible simular los transitorios en las tensiones de salida ante cambios de carga. La modelizacion del convertidor cuando el transformador se controla con una tension PWM sin filtrar es el objetivo del Capitulo 4. En las secciones siguientes del Capitulo

  13. Farmyard Manure and Fertilizer Effects on Seed Potato (Solanum tuberosum L.) Yield in Green House Production

    NASA Astrophysics Data System (ADS)

    László, M.

    2009-04-01

    radicular, deve estar exposta ao fósforo para suprir as necessidades das plantas. Ademais, há um determinado valor de concentração de fósforo, na solução do solo, acima da qual a taxa de absorção não é aumentada. Essas considerações suscitam a possibilidade de questionar se a aplicação de fósforo em sulcos seria a forma mais eficiente de usá-lo quando se pretende alcancar elevadas produções. Deve-se lembrar entretanto, que solos tropicais, ainda com baixos teores fósforo e alta capacidade de adsorção, seria necessária dose muito elevada de P, quando aplicada á lanço, em todo o terreno. Se a aplicação localizada do fósforo pode, em parte, ser explicada, a do nitrogênio e potássio não são facilmente justificadas sob o aspecto de eficiéncia de utilização. Pelo contrário, ela pode ser questionada, principalmente pelas suas caracteristicas de difusão, pelo efeito que altas concentração de amónio e cloreto podem ter sobre a pressão osmotica da solução do solo junto aos tubérculos plantados, pelo efeito negativo do cloreto sobre a absorção de fósforo e também sobre a capacidade produtiva das plantas. Portanto, existe a possibilidade de ocorrer toxidez de amónio e de cloreto ao se aplicar doses altas dos fertilizantes nos sulcos de plantios. Isto pode determinar uma menor eficiéncia no uso dos fertilizantes. Materiais e Metodos: Nos desenvolverémos os três experimentos (i.e.: 1., 2., 3.) para aumentár-se do produção e produtividade da batata (Solanum tuberosum L.) semente pré- básica no casa de vegetação com diferentes doságens do latossolo vermelho novo, do esterco de curral e do adubo fórmula 4N:14P:8K no Empresa Brasileira de Pesquisa Agropecuaria- Centro Nacional de Pesquisas de Hortaliças, da Brazília-DF no 1990. Caracteristicas agroquímicas do solo em faixa arado (dados estimados), e conteudos N, P2O5, K2O do esterco de curral e palha de arroz queimado (dados estimados): a., caracteristicas agroquímicas do solo