Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Maria Anna Maggi

Showing results (1-10 of 41) with videos related to

Pageof 5
Sort By:
Food Chemistry|October 22, 2016
Investigation by response surface methodology of the combined effect of pH and composition of water-methanol mixtures on the stability of curcuminoidsAngelo Antonio D'Archivio, Maria Anna Maggi
Food Chemistry|October 22, 2016
Geographical identification of saffron (Crocus sativus L.) by linear discriminant analysis applied to the UV-visible spectra of aqueous extractsAngelo Antonio D'Archivio, Maria Anna Maggi
Molecules (Basel, Switzerland)|December 2, 2020
Saffron: Chemical Composition and Neuroprotective ActivityMaria Anna Maggi, Silvia Bisti, Cristiana Picco
Journal of Chromatography. A|June 19, 2014
Cross-column prediction of gas-chromatographic retention indices of saturated estersAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Analytical and Bioanalytical Chemistry|July 5, 2012
Quantitative structure/eluent-retention relationships in reversed-phase high-performance liquid chromatography based on the solvatochromic methodAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Journal of Separation Science|January 23, 2010
Multiple-column RP-HPLC retention modelling based on solvatochromic or theoretical solute descriptorsAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Analytica Chimica Acta|March 19, 2011
Multi-variable retention modelling in reversed-phase high-performance liquid chromatography based on the solvation method: a comparison between curvilinear and artificial neural network regressionAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Analytical and Bioanalytical Chemistry|November 15, 2014
Artificial neural network prediction of multilinear gradient retention in reversed-phase HPLC: comprehensive QSRR-based models combining categorical or structural solute descriptors and gradient profile parametersAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Journal of Pharmaceutical and Biomedical Analysis|March 14, 2015
Quantitative structure-retention relationships of cannabimimetic aminoalkilindole derivatives and their metabolitesAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Journal of Separation Science|May 17, 2014
Prediction of the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditionsAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Pageof 5

Showing results (1-10 of 41) with videos related to

Sort By:
Pageof 5
Food Chemistry|October 22, 2016
Investigation by response surface methodology of the combined effect of pH and composition of water-methanol mixtures on the stability of curcuminoidsAngelo Antonio D'Archivio, Maria Anna Maggi
Food Chemistry|October 22, 2016
Geographical identification of saffron (Crocus sativus L.) by linear discriminant analysis applied to the UV-visible spectra of aqueous extractsAngelo Antonio D'Archivio, Maria Anna Maggi
Molecules (Basel, Switzerland)|December 2, 2020
Saffron: Chemical Composition and Neuroprotective ActivityMaria Anna Maggi, Silvia Bisti, Cristiana Picco
Journal of Chromatography. A|June 19, 2014
Cross-column prediction of gas-chromatographic retention indices of saturated estersAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Analytical and Bioanalytical Chemistry|July 5, 2012
Quantitative structure/eluent-retention relationships in reversed-phase high-performance liquid chromatography based on the solvatochromic methodAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Journal of Separation Science|January 23, 2010
Multiple-column RP-HPLC retention modelling based on solvatochromic or theoretical solute descriptorsAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Analytica Chimica Acta|March 19, 2011
Multi-variable retention modelling in reversed-phase high-performance liquid chromatography based on the solvation method: a comparison between curvilinear and artificial neural network regressionAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Analytical and Bioanalytical Chemistry|November 15, 2014
Artificial neural network prediction of multilinear gradient retention in reversed-phase HPLC: comprehensive QSRR-based models combining categorical or structural solute descriptors and gradient profile parametersAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Journal of Pharmaceutical and Biomedical Analysis|March 14, 2015
Quantitative structure-retention relationships of cannabimimetic aminoalkilindole derivatives and their metabolitesAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Journal of Separation Science|May 17, 2014
Prediction of the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditionsAngelo Antonio D'Archivio, Maria Anna Maggi, Fabrizio Ruggieri
Pageof 5