Detectors and Concepts for sub-100 ps timing with gaseous detectors

We give a short compendium of the main ongoing detectors and concepts capable of performing accurate sub-100 ps timing at high particle fluxes and on large areas, through technologies based on gaseous media. We briefly discuss the state-of-the-art, technological limitations and prospects, and a new bizarre idea

Effective pore size and radius of capture for K+ ions in K-channels

Indexación: Web of Science; Scopus.Reconciling protein functional data with crystal structure is arduous because rare conformations or crystallization artifacts occur. Here we present a tool to validate the dimensions of open pore structures of potassium-selective ion channels. We used freely available algorithms to calculate the molecular contour of the pore to determine the effective internal pore radius (r(E)) in several K-channel crystal structurss. r(E) was operationally defined as the radius of the biggest sphere able to enter the pore from the cytosolic side. We obtained consistent r(E) estimates for MthK and Kv1.2/2.1 structures, with r(E) = 5.3-5.9 angstrom and r(E) = 4.5-5.2 angstrom, respectively. We compared these structural estimates with functional assessments of the internal mouth radii of capture (r(C)) for two electrophysiological counterparts, the large conductance calcium activated K-channel (r(C) = 2.2 angstrom) and the Shaker K-v-channel (r(C) = 0.8 angstrom), for MthK and Kv1.2/2.1 structures, respectively. Calculating the difference between r(E) and r(C), produced consistent size radii of 3.1-3.7 angstrom and 3.6-4.4 angstrom for hydrated K+ ions. These hydrated K+ estimates harmonize with others obtained with diverse experimental and theoretical methods. Thus, these findings validate MthK and the Kv1.2/2.1 structures as templates for open BK and Kv-channels, respectively.http://recursosbiblioteca.unab.cl:2226/articles/srep1989

Cup products on polyhedral approximations of 3D digital images

Let I be a 3D digital image, and let Q(I) be the associated cubical complex. In this paper we show how to simplify the combinatorial structure of Q(I) and obtain a homeomorphic cellular complex P(I) with fewer cells. We introduce formulas for a diagonal approximation on a general polygon and use it to compute cup products on the cohomology H *(P(I)). The cup product encodes important geometrical information not captured by the cohomology groups. Consequently, the ring structure of H *(P(I)) is a finer topological invariant. The algorithm proposed here can be applied to compute cup products on any polyhedral approximation of an object embedded in 3-space

Connectivity forests for homological analysis of digital volumes

In this paper, we provide a graph-based representation of the homology (information related to the different “holes” the object has) of a binary digital volume. We analyze the digital volume AT-model representation [8] from this point of view and the cellular version of the AT-model [5] is precisely described here as three forests (connectivity forests), from which, for instance, we can straightforwardly determine representative curves of “tunnels” and “holes”, classify cycles in the complex, computing higher (co)homology operations,... Depending of the order in which we gradually construct these trees, tools so important in Computer Vision and Digital Image Processing as Reeb graphs and topological skeletons appear as results of pruning these graphs

Using membrane computing for obtaining homology groups of binary 2D digital images

Membrane Computing is a new paradigm inspired from cellular communication. Until now, P systems have been used in research areas like modeling chemical process, several ecosystems, etc. In this paper, we apply P systems to Computational Topology within the context of the Digital Image. We work with a variant of P systems called tissue-like P systems to calculate in a general maximally parallel manner the homology groups of 2D images. In fact, homology computation for binary pixel-based 2D digital images can be reduced to connected component labeling of white and black regions. Finally, we use a software called Tissue Simulator to show with some examples how these systems wor

Homological tree-based strategies for image analysis

Homological characteristics of digital objects can be obtained in a straightforward manner computing an algebraic map φ over a finite cell complex K (with coefficients in the finite field F2={0,1}) which represents the digital object [9]. Computable homological information includes the Euler characteristic, homology generators and representative cycles, higher (co)homology operations, etc. This algebraic map φ is described in combinatorial terms using a mixed three-level forest. Different strategies changing only two parameters of this algorithm for computing φ are presented. Each one of those strategies gives rise to different maps, although all of them provides the same homological information for K. For example, tree-based structures useful in image analysis like topological skeletons and pyramids can be obtained as subgraphs of this forest

Incremental-Decremental Algorithm for Computing AT-Models and Persistent Homology

In this paper, we establish a correspondence between the incremental algorithm for computing AT-models [8,9] and the one for computing persistent homology [6,14,15]. We also present a decremental algorithm for computing AT-models that allows to extend the persistence computation to a wider setting. Finally, we show how to combine incremental and decremental techniques for persistent homology computation

Human gait identification using persistent homology

This paper shows an image/video application using topological invariants for human gait recognition. Using a background subtraction approach, a stack of silhouettes is extracted from a subsequence and glued through their gravity centers, forming a 3D digital image I. From this 3D representation, the border simplicial complex ∂ K(I) is obtained. We order the triangles of ∂ K(I) obtaining a sequence of subcomplexes of ∂ K(I). The corresponding filtration F captures relations among the parts of the human body when walking. Finally, a topological gait signature is extracted from the persistence barcode according to F. In this work we obtain 98.5% correct classification rates on CASIA-B database