Entrevista con Manuel Villegas sobre 'El error de Prometeo. Psico(pato)logía del desarrollo moral'

Entrevista con Manuel Villegas

Desenvolupament d'un sistema de transferència de software per una placa entrenadora

El departament d’electrònica i telecomunicacions de la Universitat de Vic ha dissenyat un conjunt de plaques entrenadores amb finalitat educativa. Perquè els alumnes puguin utilitzar aquestes plaques com a eina d’estudi, és necessari disposar d’un sistema de gravació econòmic i còmode. La major part dels programadors, en aquest cas, no compleixen amb aquests requeriments. L’objectiu d’aquest projecte és dissenyar un sistema de programació que utilitzi la comunicació sèrie i que no requereixi d'un hardware ni software específics. D’aquesta manera, obtenim una placa autònoma i un programador gratuït, de muntatge ràpid i simple d’utilitzar. El sistema de gravació dissenyat s’ha dividit en tres blocs. Per una banda, un programa que anomenem “programador” encarregat de transferir codi de programa des de l’ordinador al microcontrolador de la placa entrenadora. Per altra banda, un programa anomenat “bootloader”, situat al microcontrolador, permet rebre aquest codi de programa i emmagatzemar-lo a les direccions de memòria de programa corresponents. Com a tercer bloc, s’implementa un protocol de comunicació i un sistema de control d’errors per tal d’assegurar una correcta comunicació entre el “programador” i el “bootloader”. Els objectius d’aquest projecte s’han complert i per les proves realitzades, el sistema de programació ha funcionat correctament.

Memoria de la elaboración de subtítulos para "Babel", primer capítulo de la serie documental Fry's Planet Word

Este trabajo pretende identificar algunas de las habilidades que un traductor audiovisual debe desarrollar, desde un punto de vista práctico, para ejercer la profesión, haciendo hincapié en el dominio del software específico para subtituladores. Esta memoria describe el proceso de ensayo y error llevado a cabo durante la elaboración de los subtítulos de un documental e identifica algunas de las dificultades con las que podemos encontrarnos al realizar un encargo de este tipo si trabajamos con programas de licencia gratuita, además de intentar aportar las soluciones correspondientes.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.