Sistemas de detección y extracción semiautomática de siglas: estado de la cuestión

Informe de investigación realizado a partir de una estancia en el Équipe de Recherche en Syntaxe et Sémantique de la Université de Toulouse-Le Mirail, Francia, entre julio y setiembre de 2006. En la actualidad existen diversos diccionarios de siglas en línea. Entre ellos sobresalen Acronym Finder, Abbreviations.com y Acronyma; todos ellos dedicados mayoritariamente a las siglas inglesas. Al igual que los diccionarios en papel, este tipo de diccionarios presenta problemas de desactualización por la gran cantidad de siglas que se crean a diario. Por ejemplo, en 2001, un estudio de Pustejovsky et al. mostraba que en los abstracts de Medline aparecían mensualmente cerca de 12.000 nuevas siglas. El mecanismo de actualización empleado por estos recursos es la remisión de nuevas siglas por parte de los usuarios. Sin embargo, esta técnica tiene la desventaja de que la edición de la información es muy lenta y costosa. Un ejemplo de ello es el caso de Abbreviations.com que en octubre de 2006 tenía alrededor de 100.000 siglas pendientes de edición e incorporación definitiva. Como solución a este tipo de problema, se plantea el diseño de sistemas de detección y extracción automática de siglas a partir de corpus. El proceso de detección comporta dos pasos; el primero, consiste en la identificación de las siglas dentro de un corpus y, el segundo, la desambiguación, es decir, la selección de la forma desarrollada apropiada de una sigla en un contexto dado. En la actualidad, los sistemas de detección de siglas emplean métodos basados en patrones, estadística, aprendizaje máquina, o combinaciones de ellos. En este estudio se analizan los principales sistemas de detección y desambiguación de siglas y los métodos que emplean. Cada uno se evalúa desde el punto de vista del rendimiento, medido en términos de precisión (porcentaje de siglas correctas con respecto al número total de siglas extraídas por el sistema) y exhaustividad (porcentaje de siglas correctas identificadas por el sistema con respecto al número total de siglas existente en el corpus). Como resultado, se presentan los criterios para el diseño de un futuro sistema de detección de siglas en español.

Ly49E-dependent inhibition of natural killer cells by urokinase plasminogen activator.

The Ly49 natural killer (NK)-cell receptor family comprises both activating and inhibitory members, which recognize major histocompatibility complex (MHC) class I or MHC class I-related molecules and are involved in target recognition. As previously shown, the Ly49E receptor fails to bind to a variety of soluble or cell-bound MHC class I molecules, indicating that its ligand is not an MHC class I molecule. Using BWZ.36 reporter cells, we demonstrate triggering of Ly49E by the completely distinct, non-MHC-related protein urokinase plasminogen activator (uPA). uPA is known to be secreted by a variety of cells, including epithelial and hematopoietic cells, and levels are up-regulated during tissue remodeling, infections, and tumorigenesis. Here we show that addition of uPA to Ly49E-positive adult and fetal NK cells inhibits interferon-gamma secretion and reduces their cytotoxic potential, respectively. These uPA-mediated effects are Ly49E-dependent, as they are reversed by addition of anti-Ly49E monoclonal antibody and by down-regulation of Ly49E expression using RNA interference. Our results suggest that uPA, besides its established role in fibrinolysis, tissue remodeling, and tumor metastasis, could be involved in NK cell-mediated immune surveillance and tumor escape.

Steps in the formation of neurites and synapses studied in cultured leech neurons

Leech neurons in culture have provided novel insights into the steps in the formation of neurite outgrowth patterns, target recognition and synapse formation. Identified adult neurons from the central nervous system of the leech can be removed individually and plated in culture under well-controlled conditions, where they retain their characteristic physiological properties, grow neurites and form specific chemical or electrical synapses. Different identified neurons develop distinctive outgrowth patterns that depend on their identities and on the molecular composition of the substrate. On native substrates, the patterns displayed by these neurons reproduce characteristics from the adult or the developing neurons. In addition, the substrate may induce selective directed growth between pairs of neurons that normally make contact in the ganglion. Upon contact, pairs of cultured leech neurons form chemical or electrical synapses, or both types depending on the neuronal identities. Anterograde and retrograde signals during membrane contact and synapse formation modify the distribution of synaptic terminals, calcium currents, and responses to 5-hydroxytryptamine.

Brain tissue segmentation using q-entropy in multiple sclerosis magnetic resonance images

The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.

Un outil d’évaluation neurocognitive des interactions humain-machine

De plus en plus de recherches sur les Interactions Humain-Machine (IHM) tentent d’effectuer des analyses fines de l’interaction afin de faire ressortir ce qui influence les comportements des utilisateurs. Tant au niveau de l’évaluation de la performance que de l’expérience des utilisateurs, on note qu’une attention particulière est maintenant portée aux réactions émotionnelles et cognitives lors de l’interaction. Les approches qualitatives standards sont limitées, car elles se fondent sur l’observation et des entrevues après l’interaction, limitant ainsi la précision du diagnostic. L’expérience utilisateur et les réactions émotionnelles étant de nature hautement dynamique et contextualisée, les approches d’évaluation doivent l’être de même afin de permettre un diagnostic précis de l’interaction. Cette thèse présente une approche d’évaluation quantitative et dynamique qui permet de contextualiser les réactions des utilisateurs afin d’en identifier les antécédents dans l’interaction avec un système. Pour ce faire, ce travail s’articule autour de trois axes. 1) La reconnaissance automatique des buts et de la structure de tâches de l’utilisateur, à l’aide de mesures oculométriques et d’activité dans l’environnement par apprentissage machine. 2) L’inférence de construits psychologiques (activation, valence émotionnelle et charge cognitive) via l’analyse des signaux physiologiques. 3) Le diagnostic de l‘interaction reposant sur le couplage dynamique des deux précédentes opérations. Les idées et le développement de notre approche sont illustrés par leur application dans deux contextes expérimentaux : le commerce électronique et l’apprentissage par simulation. Nous présentons aussi l’outil informatique complet qui a été implémenté afin de permettre à des professionnels en évaluation (ex. : ergonomes, concepteurs de jeux, formateurs) d’utiliser l’approche proposée pour l’évaluation d’IHM. Celui-ci est conçu de manière à faciliter la triangulation des appareils de mesure impliqués dans ce travail et à s’intégrer aux méthodes classiques d’évaluation de l’interaction (ex. : questionnaires et codage des observations).

Aircraft down-range profiles formed from simulated and compact-range radar backscatter

Compact-range radar backscatter measurements are taken of aircraft scale models. In addition, computer software is used to predict the RCS of the aircraft. Synthetic down-range profiles formed from the two sources of backscatter data are compared and visualized in an innovative manner. Similar discrimination rates between the two aircraft are obtained on data from both source

Speaker identification using models for phonemes

Motivation for Speaker recognition work is presented in the first part of the thesis. An exhaustive survey of past work in this field is also presented. A low cost system not including complex computation has been chosen for implementation. Towards achieving this a PC based system is designed and developed. A front end analog to digital convertor (12 bit) is built and interfaced to a PC. Software to control the ADC and to perform various analytical functions including feature vector evaluation is developed. It is shown that a fixed set of phrases incorporating evenly balanced phonemes is aptly suited for the speaker recognition work at hand. A set of phrases are chosen for recognition. Two new methods are adopted for the feature evaluation. Some new measurements involving a symmetry check method for pitch period detection and ACE‘ are used as featured. Arguments are provided to show the need for a new model for speech production. Starting from heuristic, a knowledge based (KB) speech production model is presented. In this model, a KB provides impulses to a voice producing mechanism and constant correction is applied via a feedback path. It is this correction that differs from speaker to speaker. Methods of defining measurable parameters for use as features are described. Algorithms for speaker recognition are developed and implemented. Two methods are presented. The first is based on the model postulated. Here the entropy on the utterance of a phoneme is evaluated. The transitions of voiced regions are used as speaker dependent features. The second method presented uses features found in other works, but evaluated differently. A knock—out scheme is used to provide the weightage values for the selection of features. Results of implementation are presented which show on an average of 80% recognition. It is also shown that if there are long gaps between sessions, the performance deteriorates and is speaker dependent. Cross recognition percentages are also presented and this in the worst case rises to 30% while the best case is 0%. Suggestions for further work are given in the concluding chapter.

A Hybrid Architecture for Recognising Speech Signals in Malayalam

Speech is the primary, most prominent and convenient means of communication in audible language. Through speech, people can express their thoughts, feelings or perceptions by the articulation of words. Human speech is a complex signal which is non stationary in nature. It consists of immensely rich information about the words spoken, accent, attitude of the speaker, expression, intention, sex, emotion as well as style. The main objective of Automatic Speech Recognition (ASR) is to identify whatever people speak by means of computer algorithms. This enables people to communicate with a computer in a natural spoken language. Automatic recognition of speech by machines has been one of the most exciting, significant and challenging areas of research in the field of signal processing over the past five to six decades. Despite the developments and intensive research done in this area, the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level. The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam.

Characterization of DnmA, the Dnmt2 homolog in Dictyostelium discoideum

Eukaryotic DNA m5C methyltransferases (MTases) play a major role in many epigenetic regulatory processes like genomic imprinting, X-chromosome inactivation, silencing of transposons and gene expression. Members of the two DNA m5C MTase families, Dnmt1 and Dnmt3, are relatively well studied and many details of their biological functions, biochemical properties as well as interaction partners are known. In contrast, the biological functions of the highly conserved Dnmt2 family, which appear to have non-canonical dual substrate specificity, remain enigmatic despite the efforts of many researchers. The genome of the social amoeba Dictyostelium encodes Dnmt2-homolog, the DnmA, as the only DNA m5C MTase which allowed us to study Dnmt2 function in this organism without interference by the other enzymes. The dnmA gene can be easily disrupted but the knock-out clones did not show obvious phenotypes under normal lab conditions, suggesting that the function of DnmA is not vital for the organism. It appears that the dnmA gene has a low expression profile during vegetative growth and is only 5-fold upregulated during development. Fluorescence microscopy indicated that DnmA-GFP fusions were distributed between both the nucleus and cytoplasm with some enrichment in nuclei. Interestingly, the experiments showed specific dynamics of DnmA-GFP distribution during the cell cycle. The proteins colocalized with DNA in the interphase and were mainly removed from nuclei during mitosis. DnmA functions as an active DNA m5C MTase in vivo and is responsible for weak but detectable DNA methylation of several regions in the Dictyostelium genome. Nevertheless, gel retardation assays showed only slightly higher affinity of the enzyme to dsDNA compared to ssDNA and no specificity towards various sequence contexts, although weak but detectable specificity towards AT-rich sequences was observed. This could be due to intrinsic curvature of such sequences. Furthermore, DnmA did not show denaturant-resistant covalent complexes with dsDNA in vitro, although it could form covalent adducts with ssDNA. Low binding and methyltransfer activity in vitro suggest the necessity of additional factor in DnmA function. Nevertheless, no candidates could be identified in affinity purification experiments with different tagged DnmA fusions. In this respect, it should be noted that tagged DnmA fusion preparations from Dictyostelium showed somewhat higher activity in both covalent adduct formation and methylation assays than DnmA expressed in E.coli. Thus, the presence of co-purified factors cannot be excluded. The low efficiency of complex formation by the recombinant enzyme and the failure to define interacting proteins that could be required for DNA methylation in vivo, brought up the assumption that post-translational modifications could influence target recognition and enzymatic activity. Indeed, sites of phosphorylation, methylation and acetylation were identified within the target recognition domain (TRD) of DnmA by mass spectrometry. For phosphorylation, the combination of MS data and bioinformatic analysis revealed that some of the sites could well be targets for specific kinases in vivo. Preliminary 3D modeling of DnmA protein based on homology with hDNMT2 allowed us to show that several identified phosphorylation sites located on the surface of the molecule, where they would be available for kinases. The presence of modifications almost solely within the TRD domain of DnmA could potentially modulate the mode of its interaction with the target nucleic acids. DnmA was able to form denaturant-resistant covalent intermediates with several Dictyostelium tRNAs, using as a target C38 in the anticodon loop. The formation of complexes not always correlated with the data from methylation assays, and seemed to be dependent on both sequence and structure of the tRNA substrate. The pattern, previously suggested by the Helm group for optimal methyltransferase activity of hDNMT2, appeared to contribute significantly in the formation of covalent adducts but was not the only feature of the substrate required for DnmA and hDNMT2 functions. Both enzymes required Mg2+ to form covalent complexes, which indicated that the specific structure of the target tRNA was indispensable. The dynamics of covalent adduct accumulation was different for DnmA and different tRNAs. Interestingly, the profiles of covalent adduct accumulation for different tRNAs were somewhat similar for DnmA and hDNMT2 enzymes. According to the proposed catalytic mechanism for DNA m5C MTases, the observed denaturant-resistant complexes corresponded to covalent enamine intermediates. The apparent discrepancies in the data from covalent complex formation and methylation assays may be interpreted by the possibility of alternative pathways of the catalytic mechanism, leading not to methylation but to exchange or demethylation reactions. The reversibility of enamine intermediate formation should also be considered. Curiously, native gel retardation assays showed no or little difference in binding affinities of DnmA to different RNA substrates and thus the absence of specificity in the initial enzyme binding. The meaning of the tRNA methylation as well as identification of novel RNA substrates in vivo should be the aim of further experiments.

Biologische Funktionsanalyse und Identifizierung neuer Substrate der Methyltransferase Dnmt2

Obwohl die DNA Methyltransferase 2 (Dnmt2) hoch konserviert ist und zu der am weitesten verbreiteten eukaryotischen MTase-Familie gehört, ist ihre biologische Funktion nach wie vor unklar. Nachdem lange Zeit keine DNA Methylierungsaktivität nachgewiesen werden konnte, wurde vor einigen Jahren über geringe Mengen an 5-Methylcytosin (5mC) in Retroelementen der “Dnmt2-only”-Organismen D. melanogaster, D. discoideum und E. histolytica berichtet (Kunert et al. 2003; Fisher et al. 2004; Kuhlmann et al. 2005; Phalke et al. 2009). Als kurze Zeit später robuste Methylierung der tRNAAsp durch humane Dnmt2 gezeigt wurde (Goll et al. 2006), wurde zunächst eine Dualspezifität des Enzyms vorgeschlagen (Jeltsch et al. 2006). Neuere Daten zum 5mC-Status verschiedener „Dnmt2-only“-Organismen bilden Anlass für kontroverse Diskussionen über Ausmaß und Bedeutung der DNA Methyltransferaseaktivität von Dnmt2 (Schaefer et al. 2010a; Krauss et al. 2011). Die vorliegende Arbeit konzentriert sich auf die Identifizierung neuer RNA Substrate des Dnmt2-Homologs DnmA aus D. discoideum sowie die biologische Bedeutung der tRNA-Methylierung durch Dnmt2. Wie in anderen Organismen beschrieben, fungiert auch DnmA als tRNAAsp(GUC) MTase in vitro und in vivo. Zusätzlich konnte in vitro tRNAGlu(UUC) als neues Substrat der Dnmt2-Homologe aus D. discoideum und dem Menschen identifiziert werden. In einem Kooperationsprojekt wurde außerdem auch tRNAAsp-Methylierungsaktivität für das Dnmt2-Homolog aus S. pombe (Pmt1) nachgewiesen. Crosslink-RNA-Immunopräzipitationen (RNA-CLIP) mit anschließender Next-Generation-Sequenzierung der mit DnmA assoziierten RNAs zeigen, dass DnmA mit tRNA Fragmenten interagiert, die sich vom Anticodonloop bis in den T-loop erstrecken. Neben der tRNAAsp(GUC) und tRNAGlu(UUC/CUC) sind Fragmente der tRNAGly(GCC) verstärkt angereichert. Inwiefern diese Fragmente eine biologische Funktion haben oder spezifische Degradationsprodukte darstellen, ist noch ungeklärt. Interessanterweise sind von einigen tRNAs wenige Sequenzen von antisense-Fragmenten in den RNA-CLIP Daten zu finden, die etwas kürzer, jedoch exakt komplementär zu den genannten sense-Fragmenten sind. Besonders stark sind diese Fragmente der tRNAGlu(UUC) vertreten. In einem weiteren RNA-CLIP Experiment wurden U-snRNAs, snoRNA und intergenische Sequenzen mit DnmA angereichert. Bei nachfolgenden in vitro Methylierungsstudien konnte ausschließlich die U2-snRNA als potentielles Nicht-tRNA-Substrat der hDnmt2 und DnmA identifiziert werden. Da tRNA Modifikationen im Anticodonloop die Codonerkennung beeinflussen können, wurde ein System etabliert um die Translationseffizienz eines GFP-Reportergens in Wildtyp- und dnmAKO-Zellen zu messen. In D. discoideum wird das Aspartat-Codon GAU ca. zehnmal häufiger genutzt als das GAC Codon, allerdings ist nur eine tRNAAsp(GUC) im Genom der Amöbe kodiert. Aus diesem Grund wurde zusätzlich die Frage adressiert, inwiefern die DnmA-abhängige Methylierung dieser tRNA das „Wobbling“ beeinflusst. Dazu wurde dem Reportergen jeweils eine (GAU)5- und (GAC)5-Leadersequenz vorgeschaltet. Entgegen der Annahme wurde der (GAC)5-Leader in beiden Stämmen etwas effizienter translatiert. Insgesamt zeigte der dnmAKO-Stamm eine leicht erhöhte Translationseffizienz der Reportergene. Vergleichende Analysen zur Aufnahme von Fremd-DNA zeigten signifikant reduzierte Transformationseffizienzen mit einem integrierenden Plasmid in dnmAKO-Zellen. Ein weiterer dnmAKO-Stamm zeigte diesen Effekt jedoch nicht, wobei bei derselben Mutante eine deutlich reduzierte Aufnahme eines extrachromosomalen Plasmids zu verzeichnen war. Untersuchungen zum Einfluss von DnmA auf die Regulation des Retroelements skipper ergaben keinen Zusammenhang zwischen der Generierung kleiner RNAs und der erhöhten Transkription des Retrotransposons in dnmAKO-Zellen (Kuhlmann et al. 2005). Durch Kompensationsversuche sowie Experimente mit einer weiteren dnmAKO-Mutante konnte die Mobilisierung des Retrotransposons nicht eindeutig als DnmA-Funktion eingeordnet werden. In einem weiteren Projekt wurden die Bindung des m5C-bindenden Proteins EhMLBP aus E. histolytica an DNA mittels Rasterkraftmikroskopie abgebildet (Lavi et al. 2006). Neben vermutlich unspezifischen Endbindungsereignissen konnte eine bevorzugte Bindungsstelle des Proteins an LINE DNA (long intersperesed nuclear element) identifiziert werden. Möglicherweise fällt diese mit einem von zwei A/T-reichen Bereichen der LINE DNA zusammen, von denen vermutet wird, dass diese für die Bindung von EhMLBP an DNA von Bedeutung sind. Insgesamt bestätigen die Ergebnisse dieser Arbeit die tRNAAsp Methylierungsaktivität als konservierte Dnmt2-Funktion. Darüber hinaus erweitern sie das Substratspektrum der Dnmt2-Methyltransferasen im Bereich der tRNA. Außerdem wird erstmals ein potentielles Nicht-tRNA Substrat vorgeschlagen. Zusätzlich geben neu entdeckte Phänotypen Hinweise auf vielfältige zelluläre Dnmt2-Funktionen.

Fingerprint Segmentation

In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.

A low-cost 3D reconstruction system using a single-shot projection of a pattern matrix

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Anaerobic threshold estimation by statistical modelling.

Anaerobic threshold (AT) is usually estimated as a change point problem by visual analysis of the cardiorespiratory response to incremental dynamic exercise. In this study, two phase linear (TPL) models of the linear-linear and linear-quadratic type were used for the estimation of AT. The correlation coefficient between the classical and statistical approaches was 0.88, and 0.89 after outlier exclusion. The TPL models provide a simple method for estimating AT that can be easily implemented using a digital computer for the automatic pattern recognition of AT.

Análise discriminatória de alvos da paisagem urbana em imagens aéreas multiespectrais

Pós-graduação em Ciências Cartográficas - FCT