Person:
Rosales Conrado, Noelia

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First Name
Noelia
Last Name
Rosales Conrado
URI
https://hdl.handle.net/20.500.14352/76222
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Ciencias Químicas
Department
Química Analítica
Area
Química Analítica
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End date: 2017 × Start date: 2017 ×

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Now showing 1 - 3 of 3
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    Learning Principal Component Analysis by Using Data from Air Quality Networks
    (Journal of Chemical Education, 2017) Pérez Arribas, Luis Vicente; León González, María Eugenia; Rosales Conrado, Noelia
    With the final objective of using computational and chemometrics tools in the chemistry studies, this paper shows the methodology and interpretation of the Principal Component Analysis (PCA) using pollution data from different cities. This paper describes how students can obtain data on air quality and process such data for additional information related to the pollution sources, climate effects, and social aspects over pollution levels by using a powerful chemometrics tool such as principal component analysis (PCA). The paper could also be useful for students interested in environmental chemistry and pollution interpretation; this statistical method is a simple way to display visually as much as possible of the total variation of the data in a few dimensions, and it is an excellent tool for looking into the normal pollution patterns.
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    Project number: 81
    Página web del grupo bilingüe de la Facultad de Educación para la enseñanza de las ciencias: elaboración, explotación y juicio crítico de los estudiantes de cara a la internacionalización de la docencia
    (2017) Peña Martínez, Juan; Sánchez Gómez, Pedro; Rosales Conrado, Noelia; Fresno Galán, María; Acebrón Hernández, Ainhoa; Merino Catalina, Beatriz; Cabezas Martínez, Sara; Meléndez Pérez, Celia; Martínez Arevalo, Victoria; Lazaro Sánchez, Paula
    Elaboración de una página web con material didáctico de Ciencias para el grupo bilingüe de Educación, que además sirve para ofrecer información para estudiantes que pudieran estar interesados en formar parte del grupo, incluyendo estudiantes extranjeros.
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    Determination of ibuprofen enantiomers in breast milk using vortex-assisted matrix solid-phase dispersion and direct chiral liquid chromatography
    (Journaol of Chromatography A, 2017) León González, María Eugenia; Rosales Conrado, Noelia
    A mixture of B-cyclodextrin (B-CD) and primary and secondary amine (PSA) sorbents was employed for the extraction and quantification of ibuprofen enantiomers from human breast milk, combining a vortex-assisted matrix solid-phase dispersion method (MSPD) and direct chiral liquid chromatography (CLC) with ultraviolet detection (UV). The MSPD sample preparation procedure was optimized focusing on both the type and amount of dispersion/sorption sorbents and the nature of the elution solvent, in order to obtain acceptable recoveries and avoiding enantiomer conversion. These MSPD parameters were optimized with the aid of an experimental design approach. Hence, a factorial design was used for identification of the main variables affecting the extraction process of ibuprofen enantiomers. Under optimum selected conditions, MSPD combined with direct CLC-UV was successfully applied for ibuprofen enantiomeric determination in breast milk at enantiomer levels between 0.15 and 6.0 µg∙g-1. The proposed analytical method also provided good repeatability, with relative standard deviations of 6.4 % and 8.3 % for the intra-day and inter-day precision, respectively.