A Tool for Integer Homology Computation: Lambda-At Model

In this paper, we formalize the notion of lambda-AT-model (where $\lambda$ is a non-null integer) for a given chain complex, which allows the computation of homological information in the integer domain avoiding using the Smith Normal Form of the boundary matrices. We present an algorithm for computing such a model, obtaining Betti numbers, the prime numbers p involved in the invariant factors of the torsion subgroup of homology, the amount of invariant factors that are a power of p and a set of representative cycles of generators of homology mod p, for each p. Moreover, we establish the minimum valid lambda for such a construction, what cuts down the computational costs related to the torsion subgroup. The tools described here are useful to determine topological information of nD structured objects such as simplicial, cubical or simploidal complexes and are applicable to extract such an information from digital pictures.Comment: Journal Image and Vision Computing, Volume 27 Issue 7, June, 200

A Cross-National Comparison E-government Success Measures: A Theory-Based Empirical Research

The continuing rapid convergence of government and e-technologies presents new opportunities for research to investigate the ways citizens interact with e-government. The literature in the area is, however, still in its infancy with little or no theoretically grounded empirical research conducted in the area. The present research investigates citizen experience with e-government in the United States and Spain by utilizing difference tests. Results of the difference tests show that the Spanish e-government citizens put more emphasis on information quality in terms of relevance, reliability, timeliness, clarity, conciseness, and currency. Results of the difference tests also show that for the system usage construct, e-government citizens on both side of the Atlantic agree that their e-government should provide superior user training, facilitate use of extranets to communicate with governmental agencies, allow automated transmitting and processing of data, and allow real time monitoring of citizen request for information in an e-government integrated with governmental agencies environment

Neural-network-based curve fitting using totally positive rational bases

This paper proposes a method for learning the process of curve fitting through a general class of totally positive rational bases. The approximation is achieved by finding suitable weights and control points to fit the given set of data points using a neural network and a training algorithm, called AdaMax algorithm, which is a first-order gradient-based stochastic optimization. The neural network presented in this paper is novel and based on a recent generalization of rational curves which inherit geometric properties and algorithms of the traditional rational Bézier curves. The neural network has been applied to different kinds of datasets and it has been compared with the traditional least-squares method to test its performance. The obtained results show that our method can generate a satisfactory approximation

Multiscale analysis of morphology and mechanics in tail tendon from the ZDSD rat model of type 2 diabetes

Type 2 diabetes (T2D) impacts multiple organ systems including the circulatory, renal, nervous and musculoskeletal systems. In collagen-based tissues, one mechanism that may be responsible for detrimental mechanical impacts of T2D is the formation of advanced glycation end products (AGEs) leading to increased collagen stiffness and decreased toughness, resulting in brittle tissue behavior. The purpose of this study was to investigate tendon mechanical properties from normal and diabetic rats at two distinct length scales, testing the hypothesis that increased stiffness and strength and decreased toughness at the fiber level would be associated with alterations in nanoscale morphology and mechanics. Individual fascicles from female Zucker diabetic Sprague-Dawley (ZDSD) rats had no differences in fascicle-level mechanical properties but had increased material-level strength and stiffness versus control rats (CD). At the nanoscale, collagen fibril D-spacing was shifted towards higher spacing values in diabetic ZDSD fibrils. The distribution of nanoscale modulus values was also shifted to higher values. Material-level strength and stiffness from whole fiber tests were increased in ZDSD tails. Correlations between nanoscale and microscale properties indicate a direct positive relationship between the two length scales, most notably in the relationship between nanoscale and microscale modulus. These findings indicate that diabetes-induced changes in material strength and modulus were driven by alterations at the nanoscale

Analysis of CMB maps with 2D wavelets

We consider the 2D wavelet transform with two scales to study sky maps of temperature anisotropies in the cosmic microwave background radiation (CMB). We apply this technique to simulated maps of small sky patches of size 12.8 \times 12.8 square degrees and 1.5' \times 1.5' pixels. The relation to the standard approach, based on the cl's is established through the introduction of the scalogram. We consider temperature fluctuations derived from standard, open and flat-Lambda CDM models. We analyze CMB anisotropies maps plus uncorrelated Gaussian noise (uniform and non-uniform) at idfferent S/N levels. We explore in detail the denoising of such maps and compare the results with other techniques already proposed in the literature. Wavelet methods provide a good reconstruction of the image and power spectrum. Moreover, they are faster than previously proposed methods.Comment: latex file 7 pages + 5 postscript files + 1 gif file; accepted for publication in A&A

The Nuclear and Circum-nuclear Stellar Population in Seyfert 2 Galaxies: Implications for the Starburst-AGN Connection

We report the results of a spectroscopic investigation of a sample of 20 of the brightest type 2 Seyfert nuclei. Our goal is to search for the direct spectroscopic signature of massive stars, and thereby probe the role of circumnuclear starbursts in the Seyfert phenomenon. The method used is based on the detection of the higher order Balmer lines and HeI lines in absorption and the Wolf-Rayet feature at $\sim$4680 \AA in emission. These lines are strong indicators of the presence of young (a few Myrs) and intermediate-age (a few 100 Myrs) stellar populations. In over half the sample, we have detected HeI and/or strong stellar absorption features in the high-order (near-UV) Balmer series together with relatively weak lines from an old stellar population. In three others we detect a broad emission feature near 4680 \AA that is most plausibly ascribed to a population of Wolf-Rayet stars (the evolved descendants of the most massive stars). We therefore conclude that the blue and near-UV light of over half of the sample is dominated by young and/or intermediate age stars. The ``young'' Seyfert 2's have have larger far-IR luminosities, cooler mid/far-IR colors, and smaller [OIII]/H$\beta$ flux ratios than the ``old'' ones. These differences are consistent with a starburst playing a significant energetic role in the former class. We consider the possibility that there may be two distinct sub-classes of Seyfert 2 nuclei (``starbursts'' and ``hidden BLR''). However, the fact that hidden BLRs have been found in three of the ``young'' nuclei argues against this, and suggests that nuclear starbursts may be a more general part of the Seyfert phenomenon.Comment: To be published in ApJ, 546, Jan 10, 200

Electron Transport in Gaseous Detectors with a Python-based Monte Carlo Simulation Code

Understanding electron drift and diffusion in gases and gas mixtures is a topic of central importance for the development of modern particle detection instrumentation. The industry-standard MagBoltz code has become an invaluable tool during its 20 years of development, providing capability to solve for electron transport (`swarm') properties based on a growing encyclopedia of built-in collision cross sections. We have made a refactorization of this code from FORTRAN into Cython, and studied a range of gas mixtures of interest in high energy and nuclear physics. The results from the new open source PyBoltz package match the outputs from the original MagBoltz code, with comparable simulation speed. An extension to the capabilities of the original code is demonstrated, in implementation of a new Modified Effective Range Theory interface. We hope that the versatility afforded by the new Python code-base will encourage continued use and development of the MagBoltz tools by the particle physics community.Comment: Preprint submitted to Computer Physics Communication

Unifying phantom inflation with late-time acceleration: scalar phantom-non-phantom transition model and generalized holographic dark energy

The unifying approach to early-time and late-time universe based on phantom cosmology is proposed. We consider gravity-scalar system which contains usual potential and scalar coupling function in front of kinetic term. As a result, the possibility of phantom-non-phantom transition appears in such a way that universe could have effectively phantom equation of state at early time as well as at late time. In fact, the oscillating universe may have several phantom and non-phantom phases. As a second model we suggest generalized holographic dark energy where infrared cutoff is identified with combination of FRW parameters: Hubble constant, particle and future horizons, cosmological constant and universe life-time (if finite). Depending on the specific choice of the model the number of interesting effects occur: the possibility to solve the coincidence problem, crossing of phantom divide and unification of early-time inflationary and late-time accelerating phantom universe. The bound for holographic entropy which decreases in phantom era is also discussed.Comment: 13 pages, clarifications/refs added, to match with published versio

Chain Homotopies for Object Topological Representations

This paper presents a set of tools to compute topological information of simplicial complexes, tools that are applicable to extract topological information from digital pictures. A simplicial complex is encoded in a (non-unique) algebraic-topological format called AM-model. An AM-model for a given object K is determined by a concrete chain homotopy and it provides, in particular, integer (co)homology generators of K and representative (co)cycles of these generators. An algorithm for computing an AM-model and the cohomological invariant HB1 (derived from the rank of the cohomology ring) with integer coefficients for a finite simplicial complex in any dimension is designed here. A concept of generators which are "nicely" representative cycles is also presented. Moreover, we extend the definition of AM-models to 3D binary digital images and we design algorithms to update the AM-model information after voxel set operations (union, intersection, difference and inverse)

Charge Transfer Properties Through Graphene for Applications in Gaseous Detectors

Graphene is a single layer of carbon atoms arranged in a honeycomb lattice with remarkable mechanical and electrical properties. Regarded as the thinnest and narrowest conductive mesh, it has drastically different transmission behaviours when bombarded with electrons and ions in vacuum. This property, if confirmed in gas, may be a definitive solution for the ion back-flow problem in gaseous detectors. In order to ascertain this aspect, graphene layers of dimensions of about 2x2cm$^2$, grown on a copper substrate, are transferred onto a flat metal surface with holes, so that the graphene layer is freely suspended. The graphene and the support are installed into a gaseous detector equipped with a triple Gaseous Electron Multiplier (GEM), and the transparency properties to electrons and ions are studied in gas as a function of the electric fields. The techniques to produce the graphene samples are described, and we report on preliminary tests of graphene-coated GEMs.Comment: 4pages, 3figures, 13th Pisa Meeting on Advanced Detector