Sobre la Singularidad de la literatura

Análisis crítico de la obra La Singularidad de la Literatura de Derek Attridge

Bivariate second--order linear partial differential equations and orthogonal polynomial solutions

In this paper we construct the main algebraic and differential properties and the weight functions of orthogonal polynomial solutions of bivariate second--order linear partial differential equations, which are admissible potentially self--adjoint and of hypergeometric type. General formulae for all these properties are obtained explicitly in terms of the polynomial coefficients of the partial differential equation, using vector matrix notation. Moreover, Rodrigues representations for the polynomial eigensolutions and for their partial derivatives of any order are given. Finally, as illustration, these results are applied to specific Appell and Koornwinder orthogonal polynomials, solutions of the same partial differential equation.Comment: 27 page

Anàlisi comparativa de la traducció del "slang" en tres capítols de la sèrie "The Fresh Prince of Bel Air"

Treball Final de Grau en Traducció i Interpretació. Codi: TI0983. Curs acadèmic 2015-2016A aquest treball, es realitza una anàlisi comparativa de la traducció del slang dels tres primers capítols de la sèrie The Fresh Prince of Bel Air. S’han analitzat tant la versió original en anglès com la versió doblada en espanyol i les tècniques de traducció utilitzades. A més de les tècniques de traducció, també s’ha estudiat quina és la funció que s’acompleix en la traducció. Tot açò s’ha comentat segons els resultats obtinguts. Per a la realització d’aquesta anàlisi s’ha utilitzat la taula proposada per Tamayo (2010) però adaptada a les característiques d’aquest treball. A més a més, es defineix el terme slang i s’expliquen les seues característiques i les dificultats que té la traducció d’aquesta varietat lingüística. Per últim, s’extrauen les conclusions de l’estudi i la seua relació amb el grau i amb una visió futura per a la professió

Understanding the perceptual spectrum of commercial perfumes as a basis for a standard sensory wheel of fragrances

[EN] Given the enormous number of perfumes available on the market, it is of interest to guide consumers in their purchase of a new fragrance. One approach is to project the multidimensional perceptual space of scents on a two-dimensional sensory map based on meaningful dimensions. One of the pioneering studies on this issue mapped 94 commercial perfumes according to two axes. Such an odor map is discussed here in detail by applying Principal Component Analysis to the numeric odor description of 176 fragrances. Quantitative odor profiles were obtained from Fragrantica's website and three fragrances guides published by Haarmann & Reimer, Michael Edwards, and the French Society of Perfumers. A sensory map was obtained that reflected the similarities and dissimilarities between those odor descriptors most commonly used in perfumery. This representation was consistent with other related plots that have been previously reported. One dimension discriminated between fragrances targeted at men versus women. An orthogonal factor distinguished perfumes for daytime versus nighttime wear. These ratings, as well as seasonal preferences, could be estimated based on the main odor character attributes applied to describe the scent. The results provide a scientific basis for the comprehensive classification of commercial perfumes compiled by Edwards according to his famous "Fragrance Wheel".Zarzo Castelló, M. (2020). Understanding the perceptual spectrum of commercial perfumes as a basis for a standard sensory wheel of fragrances. Cosmetics. 7(3):1-21. https://doi.org/10.3390/cosmetics7010003S12173Eurofragrance 2011: Feminine Fragrances Genealogyhttp://www.eurofragance.com/docs/26_2011_fem_geneology_eurofragance.jpgOlfactive Families of Fragrances According to the French Society of Perfumershttps://www.parfumeurs-createurs.org/fr/filiere-parfum/les-familles-olfactives-102Osmoz Website for Olfactory Exploration of Men’s and Women’s Commercial Fragranceshttp://www.osmoz.com/perfumes/searchChastrette, M., Laumer, J.-Y. de S., & Sauvegrain, P. (1991). Analysis of a system of description of odors by means of four different multivariate statistical methods. Chemical Senses, 16(1), 81-93. doi:10.1093/chemse/16.1.81Milotic, D. (2003). The impact of fragrance on consumer choice. Journal of Consumer Behaviour, 3(2), 179-191. doi:10.1002/cb.131Cadoret, M., Lê, S., & Pagès, J. (2009). A Factorial Approach for Sorting Task data (FAST). Food Quality and Preference, 20(6), 410-417. doi:10.1016/j.foodqual.2009.02.010Veramendi, M., Herencia, P., & Ares, G. (2013). Perfume Odor Categorization: To What Extent Trained Assessors and Consumers Agree? Journal of Sensory Studies, 28(1), 76-89. doi:10.1111/joss.12025Kostov, B., Bécue-Bertaut, M., & Husson, F. (2014). An original methodology for the analysis and interpretation of word-count based methods: Multiple factor analysis for contingency tables complemented by consensual words. Food Quality and Preference, 32, 35-40. doi:10.1016/j.foodqual.2013.06.009Teixeira, M. A., Rodríguez, O., & Rodrigues, A. E. (2010). Perfumery Radar: A Predictive Tool for Perfume Family Classification. Industrial & Engineering Chemistry Research, 49(22), 11764-11777. doi:10.1021/ie101161vTeixeira, M. A., Barrault, L., Rodríguez, O., Carvalho, C. C., & Rodrigues, A. E. (2014). Perfumery Radar 2.0: A Step toward Fragrance Design and Classification. Industrial & Engineering Chemistry Research, 53(21), 8890-8912. doi:10.1021/ie403968wNotes on Scent. Cabinethttp://cabinetmagazine.org/issues/32/jasper_wagner.phpZarzo, M. (2012). What is a Fresh Scent in Perfumery? Perceptual Freshness is Correlated with Substantivity. Sensors, 13(1), 463-483. doi:10.3390/s130100463Zarzo, M., & Stanton, D. T. (2009). Understanding the underlying dimensions in perfumers’ odor perception space as a basis for developing meaningful odor maps. Attention, Perception & Psychophysics, 71(2), 225-247. doi:10.3758/app.71.2.225Zarzo, M. (2015). Underlying dimensions in the descriptive space of perfumery odors: Part II. Food Quality and Preference, 43, 79-87. doi:10.1016/j.foodqual.2015.02.018HARPER, R. (1975). SOME CHEMICALS REPRESENTING PARTICULAR ODOUR QUALITIES. Chemical Senses, 1(3), 353-357. doi:10.1093/chemse/1.3.353Fenko, A., Schifferstein, H. N. J., Huang, T.-C., & Hekkert, P. (2009). What makes products fresh: The smell or the colour? Food Quality and Preference, 20(5), 372-379. doi:10.1016/j.foodqual.2009.02.007Yokoyama, K., & Ebisawa, F. (1993). Detection and evaluation of fragrances by human reactions using a chemical sensor based on adsorbate detection. Analytical Chemistry, 65(6), 673-677. doi:10.1021/ac00054a004Higuchi, T., Shoji, K., & Hatayama, T. (2004). Multidimensional scaling of fragrances: A comparison between the verbal and non-verbal methods of classifying fragrances1. Japanese Psychological Research, 46(1), 10-19. doi:10.1111/j.1468-5884.2004.00232.xLindqvist, A. (2012). Perfume Preferences and How They Are Related to Commercial Gender Classifications of Fragrances. Chemosensory Perception, 5(2), 197-204. doi:10.1007/s12078-012-9119-

Multivariate analysis of olfactory profiles for 140 perfumes as a basis to derive a sensory wheel for the classification of feminine fragrances

[EN] In order to guide consumers in their purchase of a new fragrance, one approach is to visualize the spectrum of men's or women's fragrances on a two-dimensional plot. One of such sensory maps available is the Hexagon of Fragrance Families. It displays 91 women's perfumes inside a polygon, so that each side accounts for a different olfactory class. In order to discuss this chart, odor profiles were obtained for these fragrances and additional feminine ones (140 in total, launched from 1912 to 1990). An olfactory dataset was arranged by coding numerically the descriptions obtained from Fragrantica and Osmoz websites, as well as from a perfume guide. By applying principal component analysis, a sensory map was obtained that properly reflected the similarities between odor descriptors. Such representation was equivalent to the map of feminine fragrances called Givaudan Analogies, comprised of five major categories. Based on the results, a modified version of the Hexagon based on 14 categories was proposed. The first principal component explained preference for daytime versus nighttime wear, and regression models were fitted in order to estimate such preferences according to the odor profiles. The second component basically discriminated floral versus chypre (mossy-woody) fragrances. Results provide a fundamental basis to develop standard sensory maps of women's fragrances.Zarzo Castelló, M. (2020). Multivariate analysis of olfactory profiles for 140 perfumes as a basis to derive a sensory wheel for the classification of feminine fragrances. Cosmetics. 7(11):1-20. https://doi.org/10.3390/cosmetics7010011S120711Kaeppler, K., & Mueller, F. (2013). Odor Classification: A Review of Factors Influencing Perception-Based Odor Arrangements. Chemical Senses, 38(3), 189-209. doi:10.1093/chemse/bjs141Osmoz Website for Olfactory Exploration of Men’s and Women’s Commercial Fragrances http://www.osmoz.com/perfumes/searchFragrantica Online Encyclopedia of Perfume https://www.fragrantica.com/search/Eurofragrance 2011: Feminine Fragrances Genealogy. Barcelona, Spain http://www.eurofragance.com/docs/26_2011_fem_geneology_eurofragance.jpgWorld of Perfumes; Caravan Fragancias SL: Zaragoza, Spain https://www.caravanfragancias.es/content/7-mundo-del-perfumeZarzo, M., & Stanton, D. T. (2009). Understanding the underlying dimensions in perfumers’ odor perception space as a basis for developing meaningful odor maps. Attention, Perception & Psychophysics, 71(2), 225-247. doi:10.3758/app.71.2.225Zarzo, M. (2015). Underlying dimensions in the descriptive space of perfumery odors: Part II. Food Quality and Preference, 43, 79-87. doi:10.1016/j.foodqual.2015.02.018Teixeira, M. A., Barrault, L., Rodríguez, O., Carvalho, C. C., & Rodrigues, A. E. (2014). Perfumery Radar 2.0: A Step toward Fragrance Design and Classification. Industrial & Engineering Chemistry Research, 53(21), 8890-8912. doi:10.1021/ie403968wCadoret, M., Lê, S., & Pagès, J. (2009). A Factorial Approach for Sorting Task data (FAST). Food Quality and Preference, 20(6), 410-417. doi:10.1016/j.foodqual.2009.02.010Kostov, B., Bécue-Bertaut, M., & Husson, F. (2014). An original methodology for the analysis and interpretation of word-count based methods: Multiple factor analysis for contingency tables complemented by consensual words. Food Quality and Preference, 32, 35-40. doi:10.1016/j.foodqual.2013.06.009Veramendi, M., Herencia, P., & Ares, G. (2013). Perfume Odor Categorization: To What Extent Trained Assessors and Consumers Agree? Journal of Sensory Studies, 28(1), 76-89. doi:10.1111/joss.12025Zarzo, M. (2019). Understanding the Perceptual Spectrum of Commercial Perfumes as a Basis for a Standard Sensory Wheel of Fragrances. Cosmetics, 7(1), 3. doi:10.3390/cosmetics7010003Olfactive Families of Fragrances according to the French Society of Perfumers https://www.parfumeurs-createurs.org/fr/filiere-parfum/les-familles-olfactives-102Chastrette, M., Elmouaffek, A., & Sauvegrain, P. (1988). A multidimensional statistical study of similarities between 74 notes used in perfumery. Chemical Senses, 13(2), 295-305. doi:10.1093/chemse/13.2.295Boelens, H. (1983). Structure—activity relationships in chemoreception by human olfaction. Trends in Pharmacological Sciences, 4, 421-426. doi:10.1016/0165-6147(83)90475-3Fenko, A., Schifferstein, H. N. J., Huang, T.-C., & Hekkert, P. (2009). What makes products fresh: The smell or the colour? Food Quality and Preference, 20(5), 372-379. doi:10.1016/j.foodqual.2009.02.007Zarzo, M. (2012). What is a Fresh Scent in Perfumery? Perceptual Freshness is Correlated with Substantivity. Sensors, 13(1), 463-483. doi:10.3390/s130100463HARPER, R. (1975). SOME CHEMICALS REPRESENTING PARTICULAR ODOUR QUALITIES. Chemical Senses, 1(3), 353-357. doi:10.1093/chemse/1.3.353Fragancias del Mundo, SL. Murcia, Spain http://fragrancesoftheworld.esMilotic, D. (2003). The impact of fragrance on consumer choice. Journal of Consumer Behaviour, 3(2), 179-191. doi:10.1002/cb.131Lindqvist, A. (2012). Perfume Preferences and How They Are Related to Commercial Gender Classifications of Fragrances. Chemosensory Perception, 5(2), 197-204. doi:10.1007/s12078-012-9119-7Yokoyama, K., & Ebisawa, F. (1993). Detection and evaluation of fragrances by human reactions using a chemical sensor based on adsorbate detection. Analytical Chemistry, 65(6), 673-677. doi:10.1021/ac00054a00

Multivariate Analysis and Classification of 146 Odor Character Descriptors

[EN] Introduction: Smells can be described by assigning the words that come to mind when sniffing an odorous material. A great number of terms can be applied, but not all of them are independent, and it is possible to establish groups of words often applied together when describing a smell. Such classification of olfactory descriptors is of scientific interest in order to better understand the dimensionality and structure of human olfactory perception space. For this purpose, compilations of olfactory profiles contain valuable information that may lead to certain consensus in odor classification. Methods: One of the most comprehensive odor databases is the Dravnieks¿ Atlas, which contains quantitative olfactory profiles for 160 samples. For each one, a large panel rated the applicability of 146 odor character descriptors on a numeric scale. Results: By applying principal component analysis to this Atlas, 105 descriptors were reorganized in 24 classes, and 33 attributes were considered as odors intermediate of two or three categories. The similarities between classes were studied by means of a further multivariate analysis based on latent variables, which provides valuable information about the most salient dimensions of odor space. Conclusions: Consistent with other reported statistical analyses of olfactory databases, the perceptual space of odor character is multidimensional with about 20¿30 dimensions, and it is better described as a continuum spectrum rather than as a segmented space. Implications: Attempts to classify all possible odor descriptors in a restricted number of classes appear to be inappropriate. Instead, 24 categories of related terms are proposed here, regarding the rest as intermediate smells, assuming that olfactory classes are not independent and follow certain hierarchy according to particular underlying dimensions.Partial financial support was received from the Spanish Ministry or Education and Science under grant no. FU2004-1119.Zarzo Castelló, M. (2021). Multivariate Analysis and Classification of 146 Odor Character Descriptors. Chemosensory Perception. 14(2):79-101. https://doi.org/10.1007/s12078-021-09288-1S7910114

A sensory 3-D map of the odor description space derived from a comparison of numeric odor profile databases

Many authors have proposed different schemes of odor classification, which are useful to aid the complex task of describing smells. However, reaching a consensus on a particular classification seems difficult because our psychophysical space of odor description is a continuum and is not clustered into well-defined categories. An alternative approach is to describe the perceptual space of odors as a low-dimensional coordinate system. This idea was first proposed by Crocker and Henderson in 1927, who suggested using numeric profiles based on 4 dimensions: fragrant, acid, burnt, and caprylic. In the present work, the odor profiles of 144 aroma chemicals were compared by means of statistical regression with comparable numeric odor profiles obtained from 2 databases, enabling a plausible interpretation of the 4 dimensions. Based on the results and taking into account comparable 2D sensory maps of odor descriptors from the literature, a 3D sensory map (odor cube) has been drawn up to improve understanding of the similarities and dissimilarities of the odor descriptors most frequently used in fragrance chemistry.Zarzo Castelló, M. (2015). A sensory 3-D map of the odor description space derived from a comparison of numeric odor profile databases. Chemical Senses. 40(5):305-313. doi:10.1093/chemse/bjv012S30531340

Higher order hypergeometric Lauricella function and zero asymptotics of orthogonal polynomials

The asymptotic contracted measure of zeros of a large class of orthogonal polynomials is explicitly given in the form of a Lauricella function. The polynomials are defined by means of a three-term recurrence relation whose coefficients may be unbounded but vary regularly and have a different behaviour for even and odd indices. Subclasses of systems of orthogonal polynomials having their contracted measure of zeros of regular, uniform, Wigner, Weyl, Karamata and hypergeometric types are explicitly identified. Some illustrative examples are given

Hedonic Judgments of Chemical Compounds Are Correlated with Molecular Size

Different psychophysical works have reported that, when a wide range of odors is assessed, the hedonic dimension is the most salient. Hence, pleasantness is the most basic attribute of odor perception. Recent studies suggest that the molecular size of a given odorant is positively correlated with its hedonic character. This correlation was confirmed in the present study, but further basic molecular features affecting pleasantness were identified by means of multiple linear regression for the compounds contained in five chemical sets. For three of them, hedonic judgments are available in the literature. For a further two chemical sets, hedonic scores were estimated from odor character descriptions based on numerical profiles. Generally speaking, fairly similar equations were obtained for the prediction of hedonic judgments in the five chemical sets, with R2 values ranging from 0.46 to 0.71. The results suggest that larger molecules containing oxygen are more likely to be perceived as pleasant, while the opposite applies to carboxylic acids and sulfur compounds