Generic object classification for autonomous robots

Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.

Prevalence and persistence of gymnodimines in clams from the Gulf of Gabes (Tunisia) studied by mouse bioassay and LC-MS/MS

In this work we studied the toxicity in clams from the Gulf of Gabes, Tunisia (Southern Mediterranean). Samples from two stations (M2 and S6) were collected monthly from January 2009 to September 2010, and analyzed by the official control method of mousse bioassay (MBA) for lipophilic toxins. All samples were also analyzed with the LC-MS/MS method for the determination of lipophilic toxins, namely: okadaic acid group, pectenotoxins, yessotoxins and azaspiracids, spirolides and gymnodimines (GYMs). The results showed prevalence of GYMs since it was the only toxin group identified in these samples with a maximum of 2,136 μg GYM -A kg-1 (February 2009 at M2). Furthermore, GYMs showed persistence in the area, with only one blank sample below the limit of detection. Interestingly, this blank sample was found in June 2009 after an important toxic episode which supports the recent findings regarding the high detoxification capability of clams, much faster than that reported for oysters. In comparison, good agreement was found among MBA, the LD50 value of 80-100 μg kg-1 reported for GYM- A, and quantitative results provided by LC-MS/MS. On the contrary to that previously reported for Tunisian clams, we unambiguously identified and quantified by LC-MS/MS the isomers GYM- B/C in most samples. Phytoplankton identification and enumeration of Karenia selliformis usually showed higher densities at site M2 than S6 as expected bearing in mind toxin results, although additional results would be required to improve the correlation between K. selliformis densities and quantitative results of toxins. The prevalence and persistence of GYMs in this area at high levels strongly encourages the evaluation of the chronic toxic effects of GYMs. This is especially important taking into account that relatively large quantities of GYMs can be released into the market due to the replacement of the official control method from mouse bioassay to the LC-MS/MS for lipophilic toxins (Regulation (EU) No 15/2011), and the lack of Regulation for this group of toxins.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

Mophological analysis of the human vasculature from medical imaging. Application to cerebral and coranary arteries

In this project, we have investigated new ways of modelling and analysis of human vasculature from Medical images. The research was divided in two main areas: cerebral vasculature analysis and coronary arteries modeling. Regarding cerebral vasculature analysis, we have studed cerebral aneurysms, internal carotid and the Circle of Willis (CoW). Aneurysms are abnormal vessel enlargements that can rupture causing important cerebral damages or death. The understanding of this pathology, together with its virtual treatment, and image diagnosis and prognosis, includes identification and detailed measurement of the aneurysms. In this context, we have proposed two automatic aneurysm isolation method, to separate the abnormal part of the vessel from the healthy part, to homogenize and speed-up the processing pipeline usually employed to study this pathology, [Cardenes2011TMI, arrabide2011MedPhys]. The results obtained from both methods have been also compared and validatied in [Cardenes2012MBEC]. A second important task here the analysis of the internal carotid [Bogunovic2011Media] and the automatic labelling of the CoW, Bogunovic2011MICCAI, Bogunovic2012TMI]. The second area of research covers the study of coronary arteries, specially coronary bifurcations because there is where the formation of atherosclerotic plaque is more common, and where the intervention is more challenging. Therefore, we proposed a novel modelling method from Computed Tomography Angiography (CTA) images, combined with Conventional Coronary Angiography (CCA), to obtain realistic vascular models of coronary bifurcations, presented in [Cardenes2011MICCAI], and fully validated including phantom experiments in [Cardene2013MedPhys]. The realistic models obtained from this method are being used to simulate stenting procedures, and to investigate the hemodynamic variables in coronary bifurcations in the works submitted in [Morlachi2012, Chiastra2012]. Additionally, another preliminary work has been done to reconstruct the coronary tree from rotational angiography, and published in [Cardenes2012ISBI].

SelenoDB 1.0 : a database of selenoprotein genes, proteins and SECIS elements

Selenoproteins are a diverse group of proteinsusually misidentified and misannotated in sequencedatabases. The presence of an in-frame UGA (stop)codon in the coding sequence of selenoproteingenes precludes their identification and correctannotation. The in-frame UGA codons are recodedto cotranslationally incorporate selenocysteine,a rare selenium-containing amino acid. The developmentof ad hoc experimental and, more recently,computational approaches have allowed the efficientidentification and characterization of theselenoproteomes of a growing number of species.Today, dozens of selenoprotein families have beendescribed and more are being discovered in recentlysequenced species, but the correct genomic annotationis not available for the majority of thesegenes. SelenoDB is a long-term project that aims toprovide, through the collaborative effort of experimentaland computational researchers, automaticand manually curated annotations of selenoproteingenes, proteins and SECIS elements. Version 1.0 ofthe database includes an initial set of eukaryoticgenomic annotations, with special emphasis on thehuman selenoproteome, for immediate inspectionby selenium researchers or incorporation into moregeneral databases. SelenoDB is freely available athttp://www.selenodb.org.

Origin and genetic differentiation of Three Mexican Native Groups (Purépechas, Triquis and Mayas): contribution of CODIS-STRs to the history of human populations of Mesoamerica

BACKGROUND: CODIS-STRs in Native Mexican groups have rarely been analysed for human identification and anthropological purposes. AIM:To analyse the genetic relationships and population structure among three Native Mexican groups from Mesoamerica.SUBJECTS AND METHODS: 531 unrelated Native individuals from Mexico were PCR-typed for 15 and 9 autosomal STRs (Identifiler™ and Profiler™ kits, respectively), including five population samples: Purépechas (Mountain, Valley and Lake), Triquis and Yucatec Mayas. Previously published STR data were included in the analyses. RESULTS:Allele frequencies and statistical parameters of forensic importance were estimated by population. The majority of Native groups were not differentiated pairwise, excepting Triquis and Purépechas, which was attributable to their relative geographic and cultural isolation. Although Mayas, Triquis and Purépechas-Mountain presented the highest number of private alleles, suggesting recurrent gene flow, the elevated differentiation of Triquis indicates a different origin of this gene flow. Interestingly, Huastecos and Mayas were not differentiated, which is in agreement with the archaeological hypothesis that Huastecos represent an ancestral Maya group. Interpopulation variability was greater in Natives than in Mestizos, both significant.CONCLUSION: Although results suggest that European admixture has increased the similarity between Native Mexican groups, the differentiation and inconsistent clustering by language or geography stresses the importance of serial founder effect and/or genetic drift in showing their present genetic relationships.

Mining and exploiting domain-specific corpora in the PANACEA platform

The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform that automates the stages involved in the acquisition,production, updating and maintenance of the large language resources required by, among others, MT systems. The development of a Corpus Acquisition Component (CAC) for extracting monolingual and bilingual data from the web is one of the most innovative building blocks of PANACEA. The CAC, which is the first stage in the PANACEA pipeline for building Language Resources, adopts an efficient and distributed methodology to crawl for web documents with rich textual content in specific languages and predefined domains. The CAC includes modules that can acquire parallel data from sites with in-domain content available in more than one language. In order to extrinsically evaluate the CAC methodology, we have conducted several experiments that used crawled parallel corpora for the identification and extraction of parallel sentences using sentence alignment. The corpora were then successfully used for domain adaptation of Machine Translation Systems.

Back to square one: Identification issues in DSGE models

We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. We show that observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t-statistics and may induce investigators to select false models. We examine whether different objective functions affect identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to detect identification failures and apply them to a state-of-the-art model.

Emerging functions of myelin associated proteins during development neuronal plasticity and and neurpdegeneration.

Adult mammalian central nervous system (CNS) axons have a limited regrowth capacity following injury. Myelin-associated inhibitors (MAIs) limit axonal outgrowth and their blockage improves the regeneration of damaged fiber tracts. Three of these proteins, Nogo-A, MAG and OMgp, share two common neuronal receptors: NgR1, together with its co-receptors (p75(NTR), TROY and Lingo-1), and the recently described paired immunoglobulin-like receptor B (PirB). These proteins impair neuronal regeneration by limiting axonal sprouting. Some of the elements involved in the myelin inhibitory pathways may still be unknown, but the discovery that blocking both PirB and NgR1 activities leads to near-complete release from myelin inhibition, sheds light on one of the most competitive and intense fields of neuroregeneration study during in recent decades. In parallel with the identification and characterization of the roles and functions of these inhibitory molecules in axonal regeneration, data gathered in the field strongly suggest that most of these proteins have roles other than axonal growth inhibition. The discovery of a new group of interacting partners for myelin-associated receptors and ligands, as well as functional studies within or outside the CNS environment, highlights the potential new physiological roles for these proteins in processes such as development, neuronal homeostasis, plasticity and neurodegeneration.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.