Optoelectronic Properties of InAlN/GaN Distributed Bragg Reflector Heterostructure Examined by Valence

High-resolution monochromated electron energy loss spectroscopy (EELS) at subnanometric spatial resolution and <200 meV energy resolution has been used to assess the valence band properties of a distributed Bragg reflector multilayer heterostructure composed of InAlN lattice matched to GaN. This work thoroughly presents the collection of methods and computational tools put together for this task. Among these are zero-loss-peak subtraction and nonlinear fitting tools, and theoretical modeling of the electron scattering distribution. EELS analysis allows retrieval of a great amount of information: indium concentration in the InAlN layers is monitored through the local plasmon energy position and calculated using a bowing parameter version of Vegard Law. Also a dielectric characterization of the InAlN and GaN layers has been performed through Kramers-Kronig analysis of the Valence-EELS data, allowing band gap energy to be measured and an insight on the polytypism of the GaN layers.

FocusDET, a new toolbox for SISCOM analysis. Evaluation of the registration accuracy using monte carlo simulation

Subtraction of Ictal SPECT Co-registered to MRI (SISCOM) is an imaging technique used to localize the epileptogenic focus in patients with intractable partial epilepsy. The aim of this study was to determine the accuracy of registration algorithms involved in SISCOM analysis using FocusDET, a new user-friendly application. To this end, Monte Carlo simulation was employed to generate realistic SPECT studies. Simulated sinograms were reconstructed by using the Filtered BackProjection (FBP) algorithm and an Ordered Subsets Expectation Maximization (OSEM) reconstruction method that included compensation for all degradations. Registration errors in SPECT-SPECT and SPECT-MRI registration were evaluated by comparing the theoretical and actual transforms. Patient studies with well-localized epilepsy were also included in the registration assessment. Global registration errors including SPECT-SPECT and SPECT-MRI registration errors were less than 1.2 mm on average, exceeding the voxel size (3.32 mm) of SPECT studies in no case. Although images reconstructed using OSEM led to lower registration errors than images reconstructed with FBP, differences after using OSEM or FBP in reconstruction were less than 0.2 mm on average. This indicates that correction for degradations does not play a major role in the SISCOM process, thereby facilitating the application of the methodology in centers where OSEM is not implemented with correction of all degradations. These findings together with those obtained by clinicians from patients via MRI, interictal and ictal SPECT and video-EEG, show that FocusDET is a robust application for performing SISCOM analysis in clinical practice.

Foreground segmentation in depth imagery using depth and spatial dynamic models for video surveillance applications

Low-cost systems that can obtain a high-quality foreground segmentation almostindependently of the existing illumination conditions for indoor environments are verydesirable, especially for security and surveillance applications. In this paper, a novelforeground segmentation algorithm that uses only a Kinect depth sensor is proposedto satisfy the aforementioned system characteristics. This is achieved by combininga mixture of Gaussians-based background subtraction algorithm with a new Bayesiannetwork that robustly predicts the foreground/background regions between consecutivetime steps. The Bayesian network explicitly exploits the intrinsic characteristics ofthe depth data by means of two dynamic models that estimate the spatial and depthevolution of the foreground/background regions. The most remarkable contribution is thedepth-based dynamic model that predicts the changes in the foreground depth distributionbetween consecutive time steps. This is a key difference with regard to visible imagery,where the color/gray distribution of the foreground is typically assumed to be constant.Experiments carried out on two different depth-based databases demonstrate that theproposed combination of algorithms is able to obtain a more accurate segmentation of theforeground/background than other state-of-the art approaches.

Background foreground segmentation with RGB-D Kinect data: An efficient combination of classifiers

Low cost RGB-D cameras such as the Microsoft’s Kinect or the Asus’s Xtion Pro are completely changing the computer vision world, as they are being successfully used in several applications and research areas. Depth data are particularly attractive and suitable for applications based on moving objects detection through foreground/background segmentation approaches; the RGB-D applications proposed in literature employ, in general, state of the art foreground/background segmentation techniques based on the depth information without taking into account the color information. The novel approach that we propose is based on a combination of classifiers that allows improving background subtraction accuracy with respect to state of the art algorithms by jointly considering color and depth data. In particular, the combination of classifiers is based on a weighted average that allows to adaptively modifying the support of each classifier in the ensemble by considering foreground detections in the previous frames and the depth and color edges. In this way, it is possible to reduce false detections due to critical issues that can not be tackled by the individual classifiers such as: shadows and illumination changes, color and depth camouflage, moved background objects and noisy depth measurements. Moreover, we propose, for the best of the author’s knowledge, the first publicly available RGB-D benchmark dataset with hand-labeled ground truth of several challenging scenarios to test background/foreground segmentation algorithms.

Piel artificial : metamorfosis arquitectónica del cuerpo a través de la superficie

El cuerpo, como conjunto organizado de partes que configuran el organismo, es una entidad metamórfica. El ser humano procura dar continuidad a esta condición mutante que le caracteriza, mediante diversas acciones de carácter arquitectónico. A partir de la observación de los procesos naturales, el individuo se autodefine artificialmente, transformando su realidad innata en una versión distorsionada de sí misma. Por adición, sustracción o modificación, la piel como última capa natural, se convierte en lienzo de manipulación plástica primordial para asegurar la existencia y controlar la identidad, individual y colectiva. La evolución experimental de estas intervenciones primarias, permite suplantar la piel natural por una reinterpretación construida; una piel exenta y desmontable con la que proyectar un yo diferente provisionalmente. El uso constante de esta prótesis removible e intercambiable, provoca que el cuerpo desnudo se transforme en un cuerpo vestido, en un entorno social en el que la desnudez deja de ser el estado natural del ser humano. La piel artificial se construye mediante una gran diversidad de procesos proyectuales, siendo la transformación de la superficie bidimensional en envolvente tridimensional el más utilizado a lo largo de la existencia de la vestimenta. El plano, concebido como principal formato de revestimiento humano, se adapta a su irregularidad topográfica por modelado, perforación, fragmentación, trazado, parametrización e interacción, transformándose en una envolvente cada vez más compleja y perfecta. Su diseño implica la consideración de variables como la dimensión y la escala, la función y la forma, la estructura, el material y la construcción, la técnica y los instrumentos. La vestimenta es una arquitectura habitacional individual, un límite corporal que relaciona el espacio entre el exterior e el interior, lo ajeno y lo propio, el tú y el yo; un filtro concreto y abstracto simultáneamente; una interfaz en donde el vestido es el continente y el cuerpo su contenido. ABSTRACT The body as a whole, organized of parts that make up the organism, is a metamorphic entity. The human being seeks to give continuity to this mutant condition which characterizes him through various actions of architectural character. From the observation of the natural processes, the individual defines itself artificially, transforming its innate reality into a distorted version of itself. By addition, subtraction or modification, the skin, as the last natural layer, becomes canvas of primary plastic handling in order to ensure the existence and to control the identity, both individual and collective. The experimental evolution of these primary interventions allows to impersonate the natural skin by a constructed reinterpretation; a free and detachable skin together with which to be able to project, temporarily, a different “I”. The constant use of this removable and interchangeable prosthesis causes the naked body to be transformed into a dressed body, in a social setting in which the nudity is no longer the natural state of the human being. The artificial skin is constructed by a variety of projectual processes; the most used throughout the existence of the outfit is transforming the two-dimensional surface into a three-dimensional covering. The plan, conceived as the main human lining format, adapts to its topographic irregularity by modeling, drilling, fragmentation, outline, parameters and interaction, thus becoming a type of increasingly more complex and perfect covering. Its design implies the consideration of different variables such as the dimension and the scale, the function and the shape, the structure, the material and the construction, the technique and the instruments. The clothing is an individual residential architecture, a body boundary which relates the space between outside and inside, between the external and the self, between “you” and “I”; at the same time a specific and abstract filter; an interface where the dress is the container and the body its content.

Parallel Computer Vision Algorithms for Graphics Processing Units

La evolución de los teléfonos móviles inteligentes, dotados de cámaras digitales, está provocando una creciente demanda de aplicaciones cada vez más complejas que necesitan algoritmos de visión artificial en tiempo real; puesto que el tamaño de las señales de vídeo no hace sino aumentar y en cambio el rendimiento de los procesadores de un solo núcleo se ha estancado, los nuevos algoritmos que se diseñen para visión artificial han de ser paralelos para poder ejecutarse en múltiples procesadores y ser computacionalmente escalables. Una de las clases de procesadores más interesantes en la actualidad se encuentra en las tarjetas gráficas (GPU), que son dispositivos que ofrecen un alto grado de paralelismo, un excelente rendimiento numérico y una creciente versatilidad, lo que los hace interesantes para llevar a cabo computación científica. En esta tesis se exploran dos aplicaciones de visión artificial que revisten una gran complejidad computacional y no pueden ser ejecutadas en tiempo real empleando procesadores tradicionales. En cambio, como se demuestra en esta tesis, la paralelización de las distintas subtareas y su implementación sobre una GPU arrojan los resultados deseados de ejecución con tasas de refresco interactivas. Asimismo, se propone una técnica para la evaluación rápida de funciones de complejidad arbitraria especialmente indicada para su uso en una GPU. En primer lugar se estudia la aplicación de técnicas de síntesis de imágenes virtuales a partir de únicamente dos cámaras lejanas y no paralelas—en contraste con la configuración habitual en TV 3D de cámaras cercanas y paralelas—con información de color y profundidad. Empleando filtros de mediana modificados para la elaboración de un mapa de profundidad virtual y proyecciones inversas, se comprueba que estas técnicas son adecuadas para una libre elección del punto de vista. Además, se demuestra que la codificación de la información de profundidad con respecto a un sistema de referencia global es sumamente perjudicial y debería ser evitada. Por otro lado se propone un sistema de detección de objetos móviles basado en técnicas de estimación de densidad con funciones locales. Este tipo de técnicas es muy adecuada para el modelado de escenas complejas con fondos multimodales, pero ha recibido poco uso debido a su gran complejidad computacional. El sistema propuesto, implementado en tiempo real sobre una GPU, incluye propuestas para la estimación dinámica de los anchos de banda de las funciones locales, actualización selectiva del modelo de fondo, actualización de la posición de las muestras de referencia del modelo de primer plano empleando un filtro de partículas multirregión y selección automática de regiones de interés para reducir el coste computacional. Los resultados, evaluados sobre diversas bases de datos y comparados con otros algoritmos del estado del arte, demuestran la gran versatilidad y calidad de la propuesta. Finalmente se propone un método para la aproximación de funciones arbitrarias empleando funciones continuas lineales a tramos, especialmente indicada para su implementación en una GPU mediante el uso de las unidades de filtraje de texturas, normalmente no utilizadas para cómputo numérico. La propuesta incluye un riguroso análisis matemático del error cometido en la aproximación en función del número de muestras empleadas, así como un método para la obtención de una partición cuasióptima del dominio de la función para minimizar el error. ABSTRACT The evolution of smartphones, all equipped with digital cameras, is driving a growing demand for ever more complex applications that need to rely on real-time computer vision algorithms. However, video signals are only increasing in size, whereas the performance of single-core processors has somewhat stagnated in the past few years. Consequently, new computer vision algorithms will need to be parallel to run on multiple processors and be computationally scalable. One of the most promising classes of processors nowadays can be found in graphics processing units (GPU). These are devices offering a high parallelism degree, excellent numerical performance and increasing versatility, which makes them interesting to run scientific computations. In this thesis, we explore two computer vision applications with a high computational complexity that precludes them from running in real time on traditional uniprocessors. However, we show that by parallelizing subtasks and implementing them on a GPU, both applications attain their goals of running at interactive frame rates. In addition, we propose a technique for fast evaluation of arbitrarily complex functions, specially designed for GPU implementation. First, we explore the application of depth-image–based rendering techniques to the unusual configuration of two convergent, wide baseline cameras, in contrast to the usual configuration used in 3D TV, which are narrow baseline, parallel cameras. By using a backward mapping approach with a depth inpainting scheme based on median filters, we show that these techniques are adequate for free viewpoint video applications. In addition, we show that referring depth information to a global reference system is ill-advised and should be avoided. Then, we propose a background subtraction system based on kernel density estimation techniques. These techniques are very adequate for modelling complex scenes featuring multimodal backgrounds, but have not been so popular due to their huge computational and memory complexity. The proposed system, implemented in real time on a GPU, features novel proposals for dynamic kernel bandwidth estimation for the background model, selective update of the background model, update of the position of reference samples of the foreground model using a multi-region particle filter, and automatic selection of regions of interest to reduce computational cost. The results, evaluated on several databases and compared to other state-of-the-art algorithms, demonstrate the high quality and versatility of our proposal. Finally, we propose a general method for the approximation of arbitrarily complex functions using continuous piecewise linear functions, specially formulated for GPU implementation by leveraging their texture filtering units, normally unused for numerical computation. Our proposal features a rigorous mathematical analysis of the approximation error in function of the number of samples, as well as a method to obtain a suboptimal partition of the domain of the function to minimize approximation error.

MIC-1, a novel macrophage inhibitory cytokine, is a divergent member of the TGF-β superfamily

Macrophages play a key role in both normal and pathological processes involving immune and inflammatory responses, to a large extent through their capacity to secrete a wide range of biologically active molecules. To identify some of these as yet not characterized molecules, we have used a subtraction cloning approach designed to identify genes expressed in association with macrophage activation. One of these genes, designated macrophage inhibitory cytokine 1 (MIC-1), encodes a protein that bears the structural characteristics of a transforming growth factor β (TGF-β) superfamily cytokine. Although it belongs to this superfamily, it has no strong homology to existing families, indicating that it is a divergent member that may represent the first of a new family within this grouping. Expression of MIC-1 mRNA in monocytoid cells is up-regulated by a variety of stimuli associated with activation, including interleukin 1β, tumor necrosis factor α (TNF-α), interleukin 2, and macrophage colony-stimulating factor but not interferon γ, or lipopolysaccharide (LPS). Its expression is also increased by TGF-β. Expression of MIC-1 in CHO cells results in the proteolytic cleavage of the propeptide and secretion of a cysteine-rich dimeric protein of Mr 25 kDa. Purified recombinant MIC-1 is able to inhibit lipopolysaccharide -induced macrophage TNF-α production, suggesting that MIC-1 acts in macrophages as an autocrine regulatory molecule. Its production in response to secreted proinflammatory cytokines and TGF-β may serve to limit the later phases of macrophage activation.

The cancer growth suppressor gene mda-7 selectively induces apoptosis in human breast cancer cells and inhibits tumor growth in nude mice

A differentiation induction subtraction hybridization strategy is being used to identify and clone genes involved in growth control and terminal differentiation in human cancer cells. This scheme identified melanoma differentiation associated gene-7 (mda-7), whose expression is up-regulated as a consequence of terminal differentiation in human melanoma cells. Forced expression of mda-7 is growth inhibitory toward diverse human tumor cells. The present studies elucidate the mechanism by which mda-7 selectively suppresses the growth of human breast cancer cells and the consequence of ectopic expression of mda-7 on human breast tumor formation in vivo in nude mice. Infection of wild-type, mutant, and null p53 human breast cancer cells with a recombinant type 5 adenovirus expressing mda-7, Ad.mda-7 S, inhibited growth and induced programmed cell death (apoptosis). Induction of apoptosis correlated with an increase in BAX protein, an established inducer of programmed cell death, and an increase in the ratio of BAX to BCL-2, an established inhibitor of apoptosis. Infection of breast carcinoma cells with Ad.mda-7 S before injection into nude mice inhibited tumor development. In contrast, ectopic expression of mda-7 did not significantly alter cell cycle kinetics, growth rate, or survival in normal human mammary epithelial cells. These data suggest that mda-7 induces its selective anticancer properties in human breast carcinoma cells by promoting apoptosis that occurs independent of p53 status. On the basis of its selective anticancer inhibitory activity and its direct antitumor effects, mda-7 may represent a new class of cancer suppressor genes that could prove useful for the targeted therapy of human cancer.

PEG-3, a nontransforming cancer progression gene, is a positive regulator of cancer aggressiveness and angiogenesis

Cancer is a progressive disease culminating in acquisition of metastatic potential by a subset of evolving tumor cells. Generation of an adequate blood supply in tumors by production of new blood vessels, angiogenesis, is a defining element in this process. Although extensively investigated, the precise molecular events underlying tumor development, cancer progression, and angiogenesis remain unclear. Subtraction hybridization identified a genetic element, progression elevated gene-3 (PEG-3), whose expression directly correlates with cancer progression and acquisition of oncogenic potential by transformed rodent cells. We presently demonstrate that forced expression of PEG-3 in tumorigenic rodent cells, and in human cancer cells, increases their oncogenic potential in nude mice as reflected by a shorter tumor latency time and the production of larger tumors with increased vascularization. Moreover, inhibiting endogenous PEG-3 expression in progressed rodent cancer cells by stable expression of an antisense expression vector extinguishes the progressed cancer phenotype. Cancer aggressiveness of PEG-3 expressing rodent cells correlates directly with increased RNA transcription, elevated mRNA levels, and augmented secretion of vascular endothelial growth factor (VEGF). Furthermore, transient ectopic expression of PEG-3 transcriptionally activates VEGF in transformed rodent and human cancer cells. Taken together these data demonstrate that PEG-3 is a positive regulator of cancer aggressiveness, a process regulated by augmented VEGF production. These studies also support an association between expression of a single nontransforming cancer progression-inducing gene, PEG-3, and the processes of cancer aggressiveness and angiogenesis. In these contexts, PEG-3 may represent an important target molecule for developing cancer therapeutics and inhibitors of angiogenesis.

Cerebral cortical hyperactivation in response to mental stress in patients with coronary artery disease

The central nervous system (CNS) effects of mental stress in patients with coronary artery disease (CAD) are unexplored. The present study used positron emission tomography (PET) to measure brain correlates of mental stress induced by an arithmetic serial subtraction task in CAD and healthy subjects. Mental stress resulted in hyperactivation in CAD patients compared with healthy subjects in several brain areas including the left parietal cortex [angular gyrus/parallel sulcus (area 39)], left anterior cingulate (area 32), right visual association cortex (area 18), left fusiform gyrus, and cerebellum. These same regions were activated within the CAD patient group during mental stress versus control conditions. In the group of healthy subjects, activation was significant only in the left inferior frontal gyrus during mental stress compared with counting control. Decreases in blood flow also were produced by mental stress in CAD versus healthy subjects in right thalamus (lateral dorsal, lateral posterior), right superior frontal gyrus (areas 32, 24, and 10), and right middle temporal gyrus (area 21) (in the region of the auditory association cortex). Of particular interest, a subgroup of CAD patients that developed painless myocardial ischemia during mental stress had hyperactivation in the left hippocampus and inferior parietal lobule (area 40), left middle (area 10) and superior frontal gyrus (area 8), temporal pole, and visual association cortex (area 18), and a concomitant decrease in activation observed in the anterior cingulate bilaterally, right middle and superior frontal gyri, and right visual association cortex (area 18) compared with CAD patients without myocardial ischemia. These findings demonstrate an exaggerated cerebral cortical response and exaggerated asymmetry to mental stress in individuals with CAD.

Effect of rabies virus infection on gene expression in mouse brain

A variety of molecular genetic approaches were used to study the effect of rabies virus (RV) infection on host gene expression in mouse brain. The down-regulation of gene expression was found to be a major effect of RV infection by using subtraction hybridization. However, a combination of techniques identified approximately 39 genes activated by infection. These included genes involved in regulation of cell metabolism, protein synthesis, synaptic activity, and cell growth and differentiation. Northern blot analysis to monitor temporal activation of several of these genes following infection revealed essentially two patterns of activation: (i) an early response with up-regulation beginning within 3 days after infection and correlating with transcription of RV nuclear protein; and (ii) a late response with enhanced expression occurring at days 6–7 after infection and associated with peak RV replication. The gene activation patterns and the known functions of their products suggest that a number of host genes may be involved in the replication and spread of RV in the brain.

Unbalanced expression of the different subunits of elongation factor 1 in diabetic skeletal muscle

In studies using subtraction cloning to screen for alterations in mRNA expression in skeletal muscle from humans with Type 2 diabetes mellitus and control subjects, one of the most prominent differences was in the mRNA for elongation factor (EF)-1α. With Northern blot analysis, EF-1α expression was enhanced by 2- to 6-fold in both Types 1 and 2 human diabetics. In contrast, no changes in expression of EF-1β or -γ were noted. We observed similar results in animal models of Type 1 diabetes. EF-1α expression, but not EF-1β or -γ expression, was also enhanced in streptozotocin-induced diabetic rats, and this effect was reversed by insulin treatment. An increased level of EF-1α mRNA was also observed in nonobese diabetic mice. This unbalanced regulation of the expression of the different subunits of EF-1 may contribute to alterations not only in protein synthesis but also in other cellular events observed in the diabetic state.

Tumor metastasis suppressor nm23H1 regulates Rac1 GTPase by interaction with Tiam1

The putative tumor metastasis suppressor nm23H1 was originally identified in murine melanomas by subtraction cloning. It displays nucleoside diphosphate kinase activity and regulates cellular events, including growth and development. Recently nm23H1 has been reported to also act as a GTPase-activating protein of the Ras-related GTPase Rad. We attempted to determine whether nm23H1 also regulates Rho-family GTPases. Although we were unable to detect a direct association between nm23H1 and Rho-family GTPases, nm23H1 was shown to be associated with a Rac1-specific nucleotide exchange factor, Tiam1, by interaction with its amino-terminal region in extracts from the cells expressing exogenous Tiam1 and from native tissue. Overexpression of nm23H1 inhibited the Tiam1-induced production of GTP-bound Rac1 and activation of c-Jun kinase. On the other hand, forced overexpression of the wild type, but not the kinase-inactivated mutant of nm23H1, converted the GDP-bound forms of Rac1, Cdc42, and RhoA to their GTP-bound forms in vitro by its nucleoside diphosphate kinase activity, but nm23H1 alone apparently did not produce the GTP-bound form of these GTPases in vivo. These results suggest that nm23H1 negatively regulates Tiam1 and inhibits Rac1 activation in vivo. Moreover, adhesion-stimulated membrane ruffles of Rat1 fibroblasts were reduced by overexpression of nm23H1. Based on these observations, we concluded that we had identified a function of nm23H1 as a regulator of Rac1 and that it may be related to the effect of nm23H1 as a tumor metastasis suppressor.

Separating Growth from Elastic Deformation during Cell Enlargement1

Plants change size by deforming reversibly (elastically) whenever turgor pressure changes, and by growing. The elastic deformation is independent of growth because it occurs in nongrowing cells. Its occurrence with growth has prevented growth from being observed alone. We investigated whether the two processes could be separated in internode cells of Chara corallina Klien ex Willd., em R.D.W. by injecting or removing cell solution with a pressure probe to change turgor while the cell length was continuously measured. Cell size changed immediately when turgor changed, and growth rates appeared to be altered. Low temperature eliminated growth but did not alter the elastic effects. This allowed elastic deformation measured at low temperature to be subtracted from elongation at warm temperature in the same cell. After the subtraction, growth alone could be observed for the first time. Alterations in turgor caused growth to change rapidly to a new, steady rate with no evidence of rapid adjustments in wall properties. This turgor response, together with the marked sensitivity of growth to temperature, suggested that the growth rate was not controlled by inert polymer extension but rather by biochemical reactions that include a turgor-sensitive step.

Imaging neuroscience: Principles or maps?

This article reviews some recent trends in imaging neuroscience. A distinction is made between making maps of functional responses in the brain and discerning the rules or principles that underlie their organization. After considering developments in the characterization of brain imaging data, several examples are presented that highlight the context-sensitive nature of neuronal responses that we measure. These contexts can be endogenous and physiological, reflecting the fact that each cortical area, or neuronal population, expresses its dynamics in the context of interactions with other areas. Conversely, these contexts can be experimental or psychological and can have a profound effect on the regional effects elicited. In this review we consider experimental designs and analytic strategies that go beyond cognitive subtraction and speculate on how functional imaging can be used to address both the details and principles underlying functional integration and specialization in the brain.