Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method
- Autores
- Schenone, Agustina Violeta; Gomes, Adriano de Araújo; Culzoni, Maria Julia; Campiglia, Andres D.; Araújo, Mário Cesar Ugulino de; Goicoechea, Hector Casimiro
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- A new residual modeling algorithm for nonbilinear data is presented, namely unfolded partial least squares with interference modeling of non bilinear data by multivariate curve resolution by alternating least squares (U-PLS/IMNB/MCR-ALS). Nonbilinearity represents a challenging data structure problem to achieve analyte quantitation from second-order data in the presence of uncalibrated components. Total synchronous fluorescence spectroscopy (TSFS) generates matrices which constitute a typical example of this kind of data. Although the nonbilinear profile of the interferent can be achieved by modeling TSFS data with unfolded partial least squares with residual bilinearization (U-PLS/RBL), an extremely large number of RBL factors has to be considered. Simulated data show that the new model can conveniently handle the studied analytical problem with better performance than PARAFAC, U-PLS/RBL and MCR-ALS, the latter modeling the unfolded data. Besides, one example involving TSFS real matrices illustrates the ability of the new method to handle experimental data, which consists in the determination of ciprofloxacin in the presence of norfloxacin as interferent in water samples.
Fil: Schenone, Agustina Violeta. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Gomes, Adriano de Araújo. Universidade Federal da Paraíba; Brasil
Fil: Culzoni, Maria Julia. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Campiglia, Andres D.. University Of Central Florida. Department Of Chemistry; Estados Unidos
Fil: Araújo, Mário Cesar Ugulino de. Universidade Federal da Paraíba; Brasil
Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina - Materia
-
Second-Order Advantage
Synchronous Fluorescence
Residual Modeling
Ciprofloxacin - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/17630
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oai:ri.conicet.gov.ar:11336/17630 |
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spelling |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares methodSchenone, Agustina VioletaGomes, Adriano de AraújoCulzoni, Maria JuliaCampiglia, Andres D.Araújo, Mário Cesar Ugulino deGoicoechea, Hector CasimiroSecond-Order AdvantageSynchronous FluorescenceResidual ModelingCiprofloxacinhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1A new residual modeling algorithm for nonbilinear data is presented, namely unfolded partial least squares with interference modeling of non bilinear data by multivariate curve resolution by alternating least squares (U-PLS/IMNB/MCR-ALS). Nonbilinearity represents a challenging data structure problem to achieve analyte quantitation from second-order data in the presence of uncalibrated components. Total synchronous fluorescence spectroscopy (TSFS) generates matrices which constitute a typical example of this kind of data. Although the nonbilinear profile of the interferent can be achieved by modeling TSFS data with unfolded partial least squares with residual bilinearization (U-PLS/RBL), an extremely large number of RBL factors has to be considered. Simulated data show that the new model can conveniently handle the studied analytical problem with better performance than PARAFAC, U-PLS/RBL and MCR-ALS, the latter modeling the unfolded data. Besides, one example involving TSFS real matrices illustrates the ability of the new method to handle experimental data, which consists in the determination of ciprofloxacin in the presence of norfloxacin as interferent in water samples.Fil: Schenone, Agustina Violeta. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Gomes, Adriano de Araújo. Universidade Federal da Paraíba; BrasilFil: Culzoni, Maria Julia. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Campiglia, Andres D.. University Of Central Florida. Department Of Chemistry; Estados UnidosFil: Araújo, Mário Cesar Ugulino de. Universidade Federal da Paraíba; BrasilFil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaElsevier2015-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/17630Schenone, Agustina Violeta; Gomes, Adriano de Araújo; Culzoni, Maria Julia; Campiglia, Andres D.; Araújo, Mário Cesar Ugulino de; et al.; Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method; Elsevier; Analytica Chimica Acta; 859; 1-2015; 20-280003-2670enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.aca.2014.12.014info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0003267014014159info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:54:09Zoai:ri.conicet.gov.ar:11336/17630instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:54:09.419CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method |
title |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method |
spellingShingle |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method Schenone, Agustina Violeta Second-Order Advantage Synchronous Fluorescence Residual Modeling Ciprofloxacin |
title_short |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method |
title_full |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method |
title_fullStr |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method |
title_full_unstemmed |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method |
title_sort |
Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method |
dc.creator.none.fl_str_mv |
Schenone, Agustina Violeta Gomes, Adriano de Araújo Culzoni, Maria Julia Campiglia, Andres D. Araújo, Mário Cesar Ugulino de Goicoechea, Hector Casimiro |
author |
Schenone, Agustina Violeta |
author_facet |
Schenone, Agustina Violeta Gomes, Adriano de Araújo Culzoni, Maria Julia Campiglia, Andres D. Araújo, Mário Cesar Ugulino de Goicoechea, Hector Casimiro |
author_role |
author |
author2 |
Gomes, Adriano de Araújo Culzoni, Maria Julia Campiglia, Andres D. Araújo, Mário Cesar Ugulino de Goicoechea, Hector Casimiro |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Second-Order Advantage Synchronous Fluorescence Residual Modeling Ciprofloxacin |
topic |
Second-Order Advantage Synchronous Fluorescence Residual Modeling Ciprofloxacin |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.4 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
A new residual modeling algorithm for nonbilinear data is presented, namely unfolded partial least squares with interference modeling of non bilinear data by multivariate curve resolution by alternating least squares (U-PLS/IMNB/MCR-ALS). Nonbilinearity represents a challenging data structure problem to achieve analyte quantitation from second-order data in the presence of uncalibrated components. Total synchronous fluorescence spectroscopy (TSFS) generates matrices which constitute a typical example of this kind of data. Although the nonbilinear profile of the interferent can be achieved by modeling TSFS data with unfolded partial least squares with residual bilinearization (U-PLS/RBL), an extremely large number of RBL factors has to be considered. Simulated data show that the new model can conveniently handle the studied analytical problem with better performance than PARAFAC, U-PLS/RBL and MCR-ALS, the latter modeling the unfolded data. Besides, one example involving TSFS real matrices illustrates the ability of the new method to handle experimental data, which consists in the determination of ciprofloxacin in the presence of norfloxacin as interferent in water samples. Fil: Schenone, Agustina Violeta. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina Fil: Gomes, Adriano de Araújo. Universidade Federal da Paraíba; Brasil Fil: Culzoni, Maria Julia. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina Fil: Campiglia, Andres D.. University Of Central Florida. Department Of Chemistry; Estados Unidos Fil: Araújo, Mário Cesar Ugulino de. Universidade Federal da Paraíba; Brasil Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina |
description |
A new residual modeling algorithm for nonbilinear data is presented, namely unfolded partial least squares with interference modeling of non bilinear data by multivariate curve resolution by alternating least squares (U-PLS/IMNB/MCR-ALS). Nonbilinearity represents a challenging data structure problem to achieve analyte quantitation from second-order data in the presence of uncalibrated components. Total synchronous fluorescence spectroscopy (TSFS) generates matrices which constitute a typical example of this kind of data. Although the nonbilinear profile of the interferent can be achieved by modeling TSFS data with unfolded partial least squares with residual bilinearization (U-PLS/RBL), an extremely large number of RBL factors has to be considered. Simulated data show that the new model can conveniently handle the studied analytical problem with better performance than PARAFAC, U-PLS/RBL and MCR-ALS, the latter modeling the unfolded data. Besides, one example involving TSFS real matrices illustrates the ability of the new method to handle experimental data, which consists in the determination of ciprofloxacin in the presence of norfloxacin as interferent in water samples. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/17630 Schenone, Agustina Violeta; Gomes, Adriano de Araújo; Culzoni, Maria Julia; Campiglia, Andres D.; Araújo, Mário Cesar Ugulino de; et al.; Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method; Elsevier; Analytica Chimica Acta; 859; 1-2015; 20-28 0003-2670 |
url |
http://hdl.handle.net/11336/17630 |
identifier_str_mv |
Schenone, Agustina Violeta; Gomes, Adriano de Araújo; Culzoni, Maria Julia; Campiglia, Andres D.; Araújo, Mário Cesar Ugulino de; et al.; Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method; Elsevier; Analytica Chimica Acta; 859; 1-2015; 20-28 0003-2670 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.aca.2014.12.014 info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0003267014014159 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1842269268060667904 |
score |
13.13397 |