Computing the Component-Labeling and the Adjacency Tree of a Binary Digital Image in Near Logarithmic-Time

Connected component labeling (CCL) of binary images is one of the fundamental operations in real time applications. The adjacency tree (AdjT) of the connected components offers a region-based representation where each node represents a region which is surrounded by another region of the opposite color. In this paper, a fully parallel algorithm for computing the CCL and AdjT of a binary digital image is described and implemented, without the need of using any geometric information. The time complexity order for an image of m × n pixels under the assumption that a processing element exists for each pixel is near O(log(m+ n)). Results for a multicore processor show a very good scalability until the so-called memory bandwidth bottleneck is reached. The inherent parallelism of our approach points to the direction that even better results will be obtained in other less classical computing architectures.Ministerio de Economía y Competitividad MTM2016-81030-PMinisterio de Economía y Competitividad TEC2012-37868-C04-0

Generating Second Order (Co)homological Information within AT-Model Context

In this paper we design a new family of relations between (co)homology classes, working with coefficients in a field and starting from an AT-model (Algebraic Topological Model) AT(C) of a finite cell complex C These relations are induced by elementary relations of type “to be in the (co)boundary of” between cells. This high-order connectivity information is embedded into a graph-based representation model, called Second Order AT-Region-Incidence Graph (or AT-RIG) of C. This graph, having as nodes the different homology classes of C, is in turn, computed from two generalized abstract cell complexes, called primal and dual AT-segmentations of C. The respective cells of these two complexes are connected regions (set of cells) of the original cell complex C, which are specified by the integral operator of AT(C). In this work in progress, we successfully use this model (a) in experiments for discriminating topologically different 3D digital objects, having the same Euler characteristic and (b) in designing a parallel algorithm for computing potentially significant (co)homological information of 3D digital objects.Ministerio de Economía y Competitividad MTM2016-81030-PMinisterio de Economía y Competitividad TEC2012-37868-C04-0

Homological Region Adjacency Tree for a 3D Binary Digital Image via HSF Model

Given a 3D binary digital image I, we define and compute an edge-weighted tree, called Homological Region Tree (or Hom-Tree, for short). It coincides, as unweighted graph, with the classical Region Adjacency Tree of black 6-connected components (CCs) and white 26- connected components of I. In addition, we define the weight of an edge (R, S) as the number of tunnels that the CCs R and S “share”. The Hom-Tree structure is still an isotopic invariant of I. Thus, it provides information about how the different homology groups interact between them, while preserving the duality of black and white CCs. An experimentation with a set of synthetic images showing different shapes and different complexity of connected component nesting is performed for numerically validating the method.Ministerio de Economía y Competitividad MTM2016-81030-

Lysosome biogenesis/scattering increases host cell susceptibility to invasion by Trypanosoma cruzi metacyclic forms and resistance to tissue culture trypomastigotes

A fundamental question to be clarified concerning the host cell invasion by Trypanosoma cruzi is whether the insect-borne and mammalian-stage parasites use similar mechanisms for invasion. To address that question, we analysed the cell invasion capacity of metacyclic trypomastigotes (MT) and tissue culture trypomastigotes (TCT) under diverse conditions. Incubation of parasites for 1h with HeLa cells in nutrient-deprived medium, a condition that triggered lysosome biogenesis and scattering, increased MT invasion and reduced TCT entry into cells. Sucrose-induced lysosome biogenesis increased HeLa cell susceptibility to MT and resistance to TCT. Treatment of cells with rapamycin, which inhibits mammalian target of rapamycin (mTOR), induced perinuclear lysosome accumulation and reduced MT invasion while augmenting TCT invasion. Metacylic trypomastigotes, but not TCT, induced mTOR dephosphorylation and the nuclear translocation of transcription factor EB (TFEB), a mTOR-associated lysosome biogenesis regulator. Lysosome biogenesis/scattering was stimulated upon HeLa cell interaction with MT but not with TCT. Recently, internalized MT, but not TCT, were surrounded by colocalized lysosome marker LAMP2 and mTOR. The recombinant gp82 protein, the MT-specific surface molecule that mediates invasion, induced mTOR dephosphorylation, nuclear TFEB translocation and lysosome biogenesis/scattering. Taken together, our data clearly indicate that MT invasion is mainly lysosome-dependent, whereas TCT entry is predominantly lysosome-independent.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Univ Fed Sao Paulo, Escola Paulista Med, Dept Microbiol Imunol & Parasitol, R Pedro de Toledo 669-6 Andar, BR-04039032 Sao Paulo, SP, BrazilInst Cochin, INSERM U1016, Dept Infect Immun & Inflammat, Paris, FranceUniv Fed Sao Paulo, Escola Paulista Med, Dept Microbiol Imunol & Parasitol, R Pedro de Toledo 669-6 Andar, BR-04039032 Sao Paulo, SP, BrazilFAPESP: 11/51475-3CNPq: 300578/2010-5Web of Scienc

Energy Demand Forecasting Using Deep Learning: Applications for the French Grid

This paper investigates the use of deep learning techniques in order to perform energy demand forecasting. To this end, the authors propose a mixed architecture consisting of a convolutional neural network (CNN) coupled with an artificial neural network (ANN), with the main objective of taking advantage of the virtues of both structures: the regression capabilities of the artificial neural network and the feature extraction capacities of the convolutional neural network. The proposed structure was trained and then used in a real setting to provide a French energy demand forecast using Action de Recherche Petite Echelle Grande Echelle (ARPEGE) forecasting weather data. The results show that this approach outperforms the reference Réseau de Transport d’Electricité (RTE, French transmission system operator) subscription-based service. Additionally, the proposed solution obtains the highest performance score when compared with other alternatives, including Autoregressive Integrated Moving Average (ARIMA) and traditional ANN models. This opens up the possibility of achieving high-accuracy forecasting using widely accessible deep learning techniques through open-source machine learning platforms

Cellular polarity in aging: role of redox regulation and nutrition

Cellular polarity concerns the spatial asymmetric organization of cellular components and structures. Such organization is important not only for biological behavior at the individual cell level, but also for the 3D organization of tissues and organs in living organisms. Processes like cell migration and motility, asymmetric inheritance, and spatial organization of daughter cells in tissues are all dependent of cell polarity. Many of these processes are compromised during aging and cellular senescence. For example, permeability epithelium barriers are leakier during aging; elderly people have impaired vascular function and increased frequency of cancer, and asymmetrical inheritance is compromised in senescent cells, including stem cells. Here, we review the cellular regulation of polarity, as well as the signaling mechanisms and respective redox regulation of the pathways involved in defining cellular polarity. Emphasis will be put on the role of cytoskeleton and the AMP-activated protein kinase pathway. We also discuss how nutrients can affect polarity-dependent processes, both by direct exposure of the gastrointestinal epithelium to nutrients and by indirect effects elicited by the metabolism of nutrients, such as activation of antioxidant response and phase-II detoxification enzymes through the transcription factor nuclear factor (erythroid-derived 2)-like 2 (Nrf2). In summary, cellular polarity emerges as a key process whose redox deregulation is hypothesized to have a central role in aging and cellular senescence.PTDC/QUI/69466/2006PTDC/QUI-BIQ/104311/2008PTDC/BIA-PRO/101624/2008PEst-OE/QUI/UI0612/201

Estudio de la creatividad en la formación inicial del profesorado

Este estudio tiene como principal objetivo conocer y valorar el tratamiento e importancia que se le otorga a la creatividad en la formación inicial del profesorado en la Facultad de Educación de Segovia. Utilizamos una mezcla de métodos (cuantitativo y cualitativo) mediante el uso de cuestionarios, entrevistas e historias de vida. Con sus resultados extraemos una serie de conclusiones y reflexiones sobre el desarrollo de esta investigación, así como una serie de pautas de actuación para ayudar a desarrollar la creatividad en las aulas.Máster en Investigación en Ciencias Sociales. Educación, Comunicación Audiovisual, Economía y Empres

A parallel Homological Spanning Forest framework for 2D topological image analysis

In [14], a topologically consistent framework to support parallel topological analysis and recognition for2 D digital objects was introduced. Based on this theoretical work, we focus on the problem of findingefficient algorithmic solutions for topological interrogation of a 2 D digital object of interest D of a pre- segmented digital image I , using 4-adjacency between pixels of D . In order to maximize the degree ofparallelization of the topological processes, we use as many elementary unit processing as pixels theimage I has. The mathematical model underlying this framework is an appropriate extension of the clas- sical concept of abstract cell complex: a primal–dual abstract cell complex (pACC for short). This versatiledata structure encompasses the notion of Homological Spanning Forest fostered in [14,15]. Starting froma symmetric pACC associated with I , the modus operandi is to construct via combinatorial operationsanother asymmetric one presenting the maximal number of non-null primal elementary interactions be- tween the cells of D . The fundamental topological tools have been transformed so as to promote anefficient parallel implementation in any parallel-oriented architecture (GPUs, multi-threaded computers,SIMD kernels and so on). A software prototype modeling such a parallel framework is built.Ministerio de Educación y Ciencia TEC2012-37868-C04-02/0

Toward Parallel Computation of Dense Homotopy Skeletons for nD Digital Objects

An appropriate generalization of the classical notion of abstract cell complex, called primal-dual abstract cell complex (pACC for short) is the combinatorial notion used here for modeling and analyzing the topology of nD digital objects and images. Let D ⊂ I be a set of n-xels (ROI) and I be a n-dimensional digital image.We design a theoretical parallel algorithm for constructing a topologically meaningful asymmetric pACC HSF(D), called Homological Spanning Forest of D (HSF of D, for short) starting from a canonical symmetric pACC associated to I and based on the application of elementary homotopy operations to activate the pACC processing units. From this HSF-graph representation of D, it is possible to derive complete homology and homotopy information of it. The preprocessing procedure of computing HSF(I) is thoroughly discussed. In this way, a significant advance in understanding how the efficient HSF framework for parallel topological computation of 2D digital images developed in [2] can be generalized to higher dimension is made.Ministerio de Economía y Competitividad TEC2016-77785-PMinisterio de Economía y Competitividad MTM2016-81030-

Labeling Color 2D Digital Images in Theoretical Near Logarithmic Time

A design of a parallel algorithm for labeling color flat zones (precisely, 4-connected components) of a gray-level or color 2D digital image is given. The technique is based in the construction of a particular Homological Spanning Forest (HSF) structure for encoding topological information of any image.HSFis a pair of rooted trees connecting the image elements at inter-pixel level without redundancy. In order to achieve a correct color zone labeling, our proposal here is to correctly building a sub- HSF structure for each image connected component, modifying an initial HSF of the whole image. For validating the correctness of our algorithm, an implementation in OCTAVE/MATLAB is written and its results are checked. Several kinds of images are tested to compute the number of iterations in which the theoretical computing time differs from the logarithm of the width plus the height of an image. Finally, real images are to be computed faster than random images using our approach.Ministerio de Economía y Competitividad TEC2016-77785-PMinisterio de Economía y Competitividad MTM2016-81030-