Level Set Segmentation with Shape and Appearance Models Using Affine Moment Descriptors

We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images.

Image sub-segmentation by PFCM and Artificial Neural Networks to detect pore space in 2D and 3D CT soil images

The image by Computed Tomography is a non-invasive alternative for observing soil structures, mainly pore space. The pore space correspond in soil data to empty or free space in the sense that no material is present there but only fluids, the fluid transport depend of pore spaces in soil, for this reason is important identify the regions that correspond to pore zones. In this paper we present a methodology in order to detect pore space and solid soil based on the synergy of the image processing, pattern recognition and artificial intelligence. The mathematical morphology is an image processing technique used for the purpose of image enhancement. In order to find pixels groups with a similar gray level intensity, or more or less homogeneous groups, a novel image sub-segmentation based on a Possibilistic Fuzzy c-Means (PFCM) clustering algorithm was used. The Artificial Neural Networks (ANNs) are very efficient for demanding large scale and generic pattern recognition applications for this reason finally a classifier based on artificial neural network is applied in order to classify soil images in two classes, pore space and solid soil respectively.

Microcalcifications Detection using PFCM and ANN

This work presents a method to detect Microcalcifications in Regions of Interest from digitized mammograms. The method is based mainly on the combination of Image Processing, Pattern Recognition and Artificial Intelligence. The Top-Hat transform is a technique based on mathematical morphology operations that, in this work is used to perform contrast enhancement of microcalcifications in the region of interest. In order to find more or less homogeneous regions in the image, we apply a novel image sub-segmentation technique based on Possibilistic Fuzzy c-Means clustering algorithm. From the original region of interest we extract two window-based features, Mean and Deviation Standard, which will be used in a classifier based on a Artificial Neural Network in order to identify microcalcifications. Our results show that the proposed method is a good alternative in the stage of microcalcifications detection, because this stage is an important part of the early Breast Cancer detection

Localization and activity detection Based on the fusion of environment And inertial sensors = Localización y detección de actividad Basadas en integración de sensores y dispositivos inerciales

Los sensores inerciales (acelerómetros y giróscopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarización. Hoy en día todos los smartphones contienen como mínimo un acelerómetro y un magnetómetro, siendo complementados en losmás modernos por giróscopos y barómetros. Esto, unido a la proliferación de los smartphones ha hecho viable el diseño de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estarán contenidos en tejidos inteligentes) o los integrados en su móvil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitación o la oferta de información referente al sitio turístico que se está visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detección de actividad y la mejora de la precisión de servicios de localización para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos móviles de última generación (luz y proximidad, acelerómetro, giróscopo y magnetómetro). Las actividades objetivo son conocidas como ‘atómicas’ (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades más complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificación sencillos que puedan ser integrados en un móvil como el Naïve Bayes, Tablas y Árboles de Decisión. Además, se pretende igualmente detectar la posición en la que el usuario lleva el móvil, no sólo con el objetivo de utilizar esa información para elegir un clasificador entrenado sólo con datos recogidos en la posición correspondiente (estrategia que mejora los resultados de estimación de la actividad), sino también para la generación de un evento que puede producir la ejecución de una acción. Finalmente, el trabajo incluye un análisis de las prestaciones de la clasificación variando el tipo de parámetros y el número de sensores usados y teniendo en cuenta no sólo la precisión de la clasificación sino también la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ción proveniente de un acelerómetro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario está haciendo junto con la estimación aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detección de máximos y mínimos usando ventanas temporales y umbrales sin requerir información específica del usuario. El ámbito de seguimiento de peatones en interiores es interesante por la falta de un estándar de localización en este tipo de entornos. Se ha diseñado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la información medida por un acelerómetro colocado en el pie del usuario con medidas de posición. Se han aplicado también diferentes técnicas de corrección de errores como las de velocidad cero que se basan en la detección de los instantes en los que el pie está apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulación basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicación de monitorización de actividad que proporciona al usuario información sobre el nivel de actividad que realiza durante un período de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo hábitos saludables. Se han desarrollado dos versiones de esta aplicación. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi móvil adquiriendo los datos de un acelerómetro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicación utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el diseño de una aplicación para la creación automática de un diario de viaje a partir de la detección de eventos importantes. Esta aplicación toma como entrada la información procedente de la estimación de actividad y de localización además de información almacenada en bases de datos abiertas (fotos, información sobre sitios) e información sobre sensores reales y virtuales (agenda, cámara, etc.) del móvil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ‘atomic’ activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Naïve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ‘Activity Monitor’ whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ‘Travel Logbook’ has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.

Multiprotocol Android Application for Smart Control and Monitoring in Buildings

This paper presents a multiprotocol mobile application for building automation which supports and enables the integration of the most representative control technologies such as KNX, LonWorks and X-10. The application includes a real-time monitoring service. Finally, advanced control functionalities based on gestures recognition and predefined scenes have been implemented. This application has been developed and tested in the Energy Efficiency Research Facility located at CeDInt-UPM, where electrical loads, blinds and HVAC and lighting systems can be controlled.

Robust thermal face recognition using region classifiers

This paper presents a robust approach for recognition of thermal face images based on decision level fusion of 34 different region classifiers. The region classifiers concentrate on local variations. They use singular value decomposition (SVD) for feature extraction. Fusion of decisions of the region classifier is done by using majority voting technique. The algorithm is tolerant against false exclusion of thermal information produced by the presence of inconsistent distribution of temperature statistics which generally make the identification process difficult. The algorithm is extensively evaluated on UGC-JU thermal face database, and Terravic facial infrared database and the recognition performance are found to be 95.83% and 100%, respectively. A comparative study has also been made with the existing works in the literature.

Human activity recognition by inertial signals obtained from a smartphone

Human Activity Recognition (HAR) is an emerging research field with the aim to identify the actions carried out by a person given a set of observations and the surrounding environment. The wide growth in this research field inside the scientific community is mainly explained by the high number of applications that are arising in the last years. A great part of the most promising applications are related to the healthcare field, where it is possible to track the mobility of patients with motor dysfunction as also the physical activity in patients with cardiovascular risk. Until a few years ago, by using distinct kind of sensors, a patient follow-up was possible. However, far from being a long-term solution and with the smartphone irruption, that monitoring can be achieved in a non-invasive way by using the embedded smartphone’s sensors. For these reasons this Final Degree Project arises with the main target to evaluate new feature extraction techniques in order to carry out an activity and user recognition, and also an activity segmentation. The recognition is done thanks to the inertial signals integration obtained by two widespread sensors in the greater part of smartphones: accelerometer and gyroscope. In particular, six different activities are evaluated walking, walking-upstairs, walking-downstairs, sitting, standing and lying. Furthermore, a segmentation task is carried out taking into account the activities performed by thirty users. This can be done by using Hidden Markov Models and also a set of tools tested satisfactory in speech recognition: HTK (Hidden Markov Model Toolkit).

Cladistic association analysis of Y chromosome effects on alcohol dependence and related personality traits

Association between Y chromosome haplotype variation and alcohol dependence and related personality traits was investigated in a large sample of psychiatrically diagnosed Finnish males. Haplotypes were constructed for 359 individuals using alleles at eight loci (seven microsatellite loci and a nucleotide substitution in the DYZ3 alphoid satellite locus). A cladogram linking the 102 observed haplotype configurations was constructed by using parsimony with a single-step mutation model. Then, a series of contingency tables nested according to the cladogram hierarchy were used to test for association between Y haplotype and alcohol dependence. Finally, using only alcohol-dependent subjects, we tested for association between Y haplotype and personality variables postulated to define subtypes of alcoholism—antisocial personality disorder, novelty seeking, harm avoidance, and reward dependence. Significant association with alcohol dependence was observed at three Y haplotype clades, with significance levels of P = 0.002, P = 0.020, and P = 0.010. Within alcohol-dependent subjects, no relationship was revealed between Y haplotype and antisocial personality disorder, novelty seeking, harm avoidance, or reward dependence. These results demonstrate, by using a fully objective association design, that differences among Y chromosomes contribute to variation in vulnerability to alcohol dependence. However, they do not demonstrate an association between Y haplotype and the personality variables thought to underlie the subtypes of alcoholism.

Ionophores and receptors using cation-π interactions: Collarenes

Cation-π interactions are important forces in molecular recognition by biological receptors, enzyme catalysis, and crystal engineering. We have harnessed these interactions in designing molecular systems with circular arrangement of benzene units that are capable of acting as ionophores and models for biological receptors. [n]Collarenes are promising candidates with high selectivity for a specific cation, depending on n, because of their structural rigidity and well-defined cavity size. The interaction energies of [n]collarenes with cations have been evaluated by using ab initio calculations. The selectivity of these [n]collarenes in aqueous solution was revealed by using statistical perturbation theory in conjunction with Monte Carlo and molecular dynamics simulations. It has been observed that in [n]collarenes the ratio of the interaction energies of a cation with it and the cation with the basic building unit (benzene) can be correlated to its ion selectivity. We find that collarenes are excellent and efficient ionophores that bind cations through cation-π interactions. [6]Collarene is found to be a selective host for Li+ and Mg2+, [8]collarene for K+ and Sr2+, and [10]collarene for Cs+ and Ba2+. This finding indicates that [10]collarene and [8]collarene could be used for effective separation of highly radioactive isotopes, 137Cs and 90Sr, which are major constituents of nuclear wastes. More interestingly, collarenes of larger cavity size can be useful in capturing organic cations. [12]Collarene exhibits a pronounced affinity for tetramethylammonium cation and acetylcholine, which implies that it could serve as a model for acetylcholinestrase. Thus, collarenes can prove to be novel and effective ionophores/model-receptors capable of heralding a new direction in molecular recognition and host-guest chemistry.

The phosphorylation state of the FIGQY tyrosine of neurofascin determines ankyrin-binding activity and patterns of cell segregation

Cell–cell recognition and patterning of cell contacts have a critical role in mediating reversible assembly of a variety of transcellular complexes in the nervous system. This study provides evidence for regulation of cell interactions through modulation of ankyrin binding to neurofascin, a member of the L1CAM family of nervous system cell adhesion molecules. The phosphorylation state of the conserved FIGQY tyrosine in the cytoplasmic domain of neurofascin regulates ankyrin binding and governs neurofascin-dependent cell aggregation as well as cell sorting when neurofascin is expressed in neuroblastoma cells. These findings suggest a general mechanism for the patterning of cell contact based on external signals that regulate tyrosine phosphorylation of L1CAM members and modulate their binding to ankyrin.

Genetic Separation of FK506 Susceptibility and Drug Transport in the Yeast Pdr5 ATP-binding Cassette Multidrug Resistance Transporter

Overexpression of the yeast Pdr5 ATP-binding cassette transporter leads to pleiotropic drug resistance to a variety of structurally unrelated cytotoxic compounds. To identify Pdr5 residues involved in substrate recognition and/or drug transport, we used a combination of random in vitro mutagenesis and phenotypic screening to isolate novel mutant Pdr5 transporters with altered substrate specificity. A plasmid library containing randomly mutagenized PDR5 genes was transformed into appropriate drug-sensitive yeast cells followed by phenotypic selection of Pdr5 mutants. Selected mutant Pdr5 transporters were analyzed with respect to their expression levels, subcellular localization, drug resistance profiles to cycloheximide, rhodamines, antifungal azoles, steroids, and sensitivity to the inhibitor FK506. DNA sequencing of six PDR5 mutant genes identified amino acids important for substrate recognition, drug transport, and specific inhibition of the Pdr5 transporter. Mutations were found in each nucleotide-binding domain, the transmembrane domain 10, and, most surprisingly, even in predicted extracellular hydrophilic loops. At least some point mutations identified appear to influence folding of Pdr5, suggesting that the folded structure is a major substrate specificity determinant. Surprisingly, a S1360F exchange in transmembrane domain 10 not only caused limited substrate specificity, but also abolished Pdr5 susceptibility to inhibition by the immunosuppressant FK506. This is the first report of a mutation in a yeast ATP-binding cassette transporter that allows for the functional separation of substrate transport and inhibitor susceptibility.

Oncogenic mutation in the Kit receptor tyrosine kinase alters substrate specificity and induces degradation of the protein tyrosine phosphatase SHP-1

Activating mutations in the Kit receptor tyrosine kinase have been identified in both rodent and human mast cell leukemia. One activating Kit mutation substitutes a valine for aspartic acid at codon 816 (D816V) and is frequently observed in human mastocytosis. Mutation at the equivalent position in the murine c-kit gene, involving a substitution of tyrosine for aspartic acid (D814Y), has been described in the mouse mastocytoma cell line P815. We have investigated the mechanism of oncogenic activation by this mutation. Expression of this mutant Kit receptor tyrosine kinase in a mast cell line led to the selective tyrosine phosphorylation of a 130-kDa protein and the degradation, through the ubiquitin-dependent proteolytic pathway, of a 65-kDa phosphoprotein. The 65-kDa protein was identified as the src homology domain 2 (SH2)-containing protein tyrosine phosphatase SHP-1, a negative regulator of signaling by Kit and other hematopoietic receptors, and the protein product of the murine motheaten locus. This mutation also altered the sites of receptor autophosphorylation and peptide substrate selectivity. Thus, this mutation activates the oncogenic potential of Kit by a novel mechanism involving an alteration in Kit substrate recognition and the degradation of SHP-1, an attenuator of the Kit signaling pathway.

Structural code for DNA recognition revealed in crystal structures of papillomavirus E2-DNA targets

Transcriptional regulation in papillomaviruses depends on sequence-specific binding of the regulatory protein E2 to several sites in the viral genome. Crystal structures of bovine papillomavirus E2 DNA targets reveal a conformational variant of B-DNA characterized by a roll-induced writhe and helical repeat of 10.5 bp per turn. A comparison between the free and the protein-bound DNA demonstrates that the intrinsic structure of the DNA regions contacted directly by the protein and the deformability of the DNA region that is not contacted by the protein are critical for sequence-specific protein/DNA recognition and hence for gene-regulatory signals in the viral system. We show that the selection of dinucleotide or longer segments with appropriate conformational characteristics, when positioned at correct intervals along the DNA helix, can constitute a structural code for DNA recognition by regulatory proteins. This structural code facilitates the formation of a complementary protein–DNA interface that can be further specified by hydrogen bonds and nonpolar interactions between the protein amino acids and the DNA bases.

REBASE—restriction enzymes and methylases

REBASE contains comprehensive information about restriction enzymes, DNA methylases and related proteins such as nicking enzymes, specificity subunits and control proteins. It contains published and unpublished references, recognition and cleavage sites, isoschizomers, commercial availability, methy­lation sensitivity, crystal data and sequence data. Homing endonucleases are also included. Most recently, extensive information about the methy­lation sensitivity of restriction enzymes has been added and a new feature contains complete analyses of the putative restriction systems in the sequenced bacterial and archaeal genomes. The data is distributed via email, ftp (ftp.neb.com) and the Web (http://rebase.neb.com).