1,136 research outputs found
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-
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