Strategies of use of a specific immunoglobulin-rich egg yolk powder in weaning piglets

Two experiments were performed to determine the best strategy of use of the product TRACTcare® 4P (ITPSA) (TC, specific immunoglobulin-rich egg yolk powder within an energetic fatty acid matrix) in piglets from weaning and for 6 weeks, in diets without or with inclusion of antibiotics. Each trial was performed with 144 piglets in 24 pens, in a completely randomized design blocked by initial body weight. Feeds were formulated according to animal requirements in two periods. In the first trial no antibiotics were included in the feeds and no room disinfection from previous trial was performed; treatments were: 1) Negative control (NC); 2) NC+TC on top of the feed within the hopper for the first 3 days on trial (30 g/pig×day), and eventually if diarrhea appeared (TCOT); 3) NC+TC ad libitum provided in an extra hopper within the pen (TCAL); and 4) NC+TC at 5 g/kg added to the feed in the mixer (TC5). In the second trial, treatments were: 1) Positive control: basal diet that included 250 mg/kg amoxiciline (BD)+100 mg/kg colistine (AC); 2) BD+2 g/kg TC (TC2A); 3) BD+5 g/kg TC (TC5A); and 4) BD+8 g/kg TC (TC8A). In diets without antibiotics, the product TC at 5 g/kg in the feed numerically improved BW by 8% compared to Control animals, while G:F was almost identical between both groups. When antibiotics were used in the feed, replacement of colistin at 100 mg/kg for TC at 2 g/kg in feed numerically improved the performance compared to Positive control animals (for the whole trial period ADG 8% better: 390 g vs. 361 g; G:F 1% better: 0.748 kg/kg vs. 0.742 kg/kg), possibly due to the stimulation of feed consumption at weaning. In both trials, the lower number of dead and culled animals from TC5 and TC2A together with higher BW represented an advantage over Control treatments of 6% to 10% animals more and 15% to 17% total BW more at the end of the trial.

Bayesian tools for zero counts in compositional data

The log-ratio methodology makes available powerful tools for analyzing compositionaldata. Nevertheless, the use of this methodology is only possible for those data setswithout null values. Consequently, in those data sets where the zeros are present, aprevious treatment becomes necessary. Last advances in the treatment of compositionalzeros have been centered especially in the zeros of structural nature and in the roundedzeros. These tools do not contemplate the particular case of count compositional datasets with null values. In this work we deal with \count zeros" and we introduce atreatment based on a mixed Bayesian-multiplicative estimation. We use the Dirichletprobability distribution as a prior and we estimate the posterior probabilities. Then weapply a multiplicative modi¯cation for the non-zero values. We present a case studywhere this new methodology is applied.Key words: count data, multiplicative replacement, composition, log-ratio analysis

Eliminació d'artefactes en EGG mitjançant l'ús de la Multivariate Empirical Mode Decomposition

La tècnica de l’electroencefalograma (EEG) és una de les tècniques més utilitzades per estudiar el cervell. En aquesta tècnica s’enregistren els senyals elèctrics que es produeixen en el còrtex humà a través d’elèctrodes col•locats al cap. Aquesta tècnica, però, presenta algunes limitacions a l’hora de realitzar els enregistraments, la principal limitació es coneix com a artefactes, que són senyals indesitjats que es mesclen amb els senyals EEG. L’objectiu d’aquest treball de final de màster és presentar tres nous mètodes de neteja d’artefactes que poden ser aplicats en EEG. Aquests estan basats en l’aplicació de la Multivariate Empirical Mode Decomposition, que és una nova tècnica utilitzada per al processament de senyal. Els mètodes de neteja proposats s’apliquen a dades EEG simulades que contenen artefactes (pestanyeigs), i un cop s’han aplicat els procediments de neteja es comparen amb dades EEG que no tenen pestanyeigs, per comprovar quina millora presenten. Posteriorment, dos dels tres mètodes de neteja proposats s’apliquen sobre dades EEG reals. Les conclusions que s’han extret del treball són que dos dels nous procediments de neteja proposats es poden utilitzar per realitzar el preprocessament de dades reals per eliminar pestanyeigs.

Directional and fluctuating asymmetry in finger and a-b ridge counts in psychosis: a case-control study

Background: Several studies have reported alterations in finger and a-b ridge counts, and theirderived measures of asymmetry, in schizophrenia compared to controls. Because ridges are fully formed by the end of the second trimester, they may provide clues to disturbed early development. The aim of this study was to assess these measures in a sample of patients with psychosis and normal controls.Methods: Individuals with psychosis (n = 240), and normal controls (n = 228) were drawn from a catchment-area case-control study. Differences in finger and a-b ridge count and Fluctuating Asymmetry were assessed in three group comparisons (non-affective psychosis versus controls; affective psychosis versus controls; non-affective psychosis versus affective psychosis). The analyses were performed separately for males and females. Results: There were no significant group differences for finger nor a-b ridge counts. While there were no group difference for Directional Asymmetry, for Fluctuating Asymmetry measures men with non-affective psychosis had significantly higher fluctuating asymmetry of the index finger ridge count (a) when compared to controls (FA-correlation score, p = 0.02), and (b) when compared to affective psychosis (adjusted FA-difference score, p = 0.04). Conclusion: Overall, measures of finger and a-b ridge counts, and their derived measures of directional and fluctuating asymmetry were not prominent features of psychosis in this sample. While directional asymmetry in cerebral morphology is reduced in schizophrenia, this is not reflected in dermatoglyphic variables.

Eliminació d'artefactes en EGG mitjançant l'ús de la Multivariate Empirical Mode Decomposition

La tècnica de l’electroencefalograma (EEG) és una de les tècniques més utilitzades per estudiar el cervell. En aquesta tècnica s’enregistren els senyals elèctrics que es produeixen en el còrtex humà a través d’elèctrodes col•locats al cap. Aquesta tècnica, però, presenta algunes limitacions a l’hora de realitzar els enregistraments, la principal limitació es coneix com a artefactes, que són senyals indesitjats que es mesclen amb els senyals EEG. L’objectiu d’aquest treball de final de màster és presentar tres nous mètodes de neteja d’artefactes que poden ser aplicats en EEG. Aquests estan basats en l’aplicació de la Multivariate Empirical Mode Decomposition, que és una nova tècnica utilitzada per al processament de senyal. Els mètodes de neteja proposats s’apliquen a dades EEG simulades que contenen artefactes (pestanyeigs), i un cop s’han aplicat els procediments de neteja es comparen amb dades EEG que no tenen pestanyeigs, per comprovar quina millora presenten. Posteriorment, dos dels tres mètodes de neteja proposats s’apliquen sobre dades EEG reals. Les conclusions que s’han extret del treball són que dos dels nous procediments de neteja proposats es poden utilitzar per realitzar el preprocessament de dades reals per eliminar pestanyeigs.