On the Mahalanobis Distance Classification Criterion for Multidimensional Normal Distributions

Many existing engineering works model the statistical characteristics of the entities under study as normal distributions. These models are eventually used for decision making, requiring in practice the definition of the classification region corresponding to the desired confidence level. Surprisingly enough, however, a great amount of computer vision works using multidimensional normal models leave unspecified or fail to establish correct confidence regions due to misconceptions on the features of Gaussian functions or to wrong analogies with the unidimensional case. The resulting regions incur in deviations that can be unacceptable in high-dimensional models. Here we provide a comprehensive derivation of the optimal confidence regions for multivariate normal distributions of arbitrary dimensionality. To this end, firstly we derive the condition for region optimality of general continuous multidimensional distributions, and then we apply it to the widespread case of the normal probability density function. The obtained results are used to analyze the confidence error incurred by previous works related to vision research, showing that deviations caused by wrong regions may turn into unacceptable as dimensionality increases. To support the theoretical analysis, a quantitative example in the context of moving object detection by means of background modeling is given.

MMonCa: A flexible and powerful new Kinetic Monte Carlo simulator

Kinetic Monte Carlo (KMC) is a widely used technique to simulate the evolution of radiation damage inside solids. Despite de fact that this technique was developed several decades ago, there is not an established and easy to access simulating tool for researchers interested in this field, unlike in the case of molecular dynamics or density functional theory calculations. In fact, scientists must develop their own tools or use unmaintained ones in order to perform these types of simulations. To fulfil this need, we have developed MMonCa, the Modular Monte Carlo simulator. MMonCa has been developed using professional C++ programming techniques and has been built on top of an interpreted language to allow having a powerful yet flexible, robust but customizable and easy to access modern simulator. Both non lattice and Lattice KMC modules have been developed. We will present in this conference, for the first time, the MMonCa simulator. Along with other (more detailed) contributions in this meeting, the versatility of MMonCa to study a number of problems in different materials (particularly, Fe and W) subject to a wide range of conditions will be shown. Regarding KMC simulations, we have studied neutron-generated cascade evolution in Fe (as a model material). Starting with a Frenkel pair distribution we have followed the defect evolution up to 450 K. Comparison with previous simulations and experiments shows excellent agreement. Furthermore, we have studied a more complex system (He-irradiated W:C) using a previous parametrization [1]. He-irradiation at 4 K followed by isochronal annealing steps up to 500 K has been simulated with MMonCa. The He energy was 400 eV or 3 keV. In the first case, no damage is associated to the He implantation, whereas in the second one, a significant Frenkel pair concentration (evolving into complex clusters) is associated to the He ions. We have been able to explain He desorption both in the absence and in the presence of Frenkel pairs and we have also applied MMonCa to high He doses and fluxes at elevated temperatures. He migration and trapping dominate the kinetics of He desorption. These processes will be discussed and compared to experimental results. [1] C.S. Becquart et al. J. Nucl. Mater. 403 (2010) 75

On the complexity of radiation models for PV energy production calculation

Several authors have analysed the changes of the probability density function of the solar radiation with different time resolutions. Some others have approached to study the significance of these changes when produced energy calculations are attempted. We have undertaken different transformations to four Spanish databases in order to clarify the interrelationship between radiation models and produced energy estimations. Our contribution is straightforward: the complexity of a solar radiation model needed for yearly energy calculations, is very low. Twelve values of monthly mean of solar radiation are enough to estimate energy with errors below 3%. Time resolutions better than hourly samples do not improve significantly the result of energy estimations.

Nonparametric generalized belief propagation based on pseudo-junction tree for cooperative localization in wireless networks

Non-parametric belief propagation (NBP) is a well-known message passing method for cooperative localization in wireless networks. However, due to the over-counting problem in the networks with loops, NBP’s convergence is not guaranteed, and its estimates are typically less accurate. One solution for this problem is non-parametric generalized belief propagation based on junction tree. However, this method is intractable in large-scale networks due to the high-complexity of the junction tree formation, and the high-dimensionality of the particles. Therefore, in this article, we propose the non-parametric generalized belief propagation based on pseudo-junction tree (NGBP-PJT). The main difference comparing with the standard method is the formation of pseudo-junction tree, which represents the approximated junction tree based on thin graph. In addition, in order to decrease the number of high-dimensional particles, we use more informative importance density function, and reduce the dimensionality of the messages. As by-product, we also propose NBP based on thin graph (NBP-TG), a cheaper variant of NBP, which runs on the same graph as NGBP-PJT. According to our simulation and experimental results, NGBP-PJT method outperforms NBP and NBP-TG in terms of accuracy, computational, and communication cost in reasonably sized networks.

Massively parallelizable list-mode reconstruction using a Monte Carlo-based elliptical Gaussian model

Purpose: A fully three-dimensional (3D) massively parallelizable list-mode ordered-subsets expectation-maximization (LM-OSEM) reconstruction algorithm has been developed for high-resolution PET cameras. System response probabilities are calculated online from a set of parameters derived from Monte Carlo simulations. The shape of a system response for a given line of response (LOR) has been shown to be asymmetrical around the LOR. This work has been focused on the development of efficient region-search techniques to sample the system response probabilities, which are suitable for asymmetric kernel models, including elliptical Gaussian models that allow for high accuracy and high parallelization efficiency. The novel region-search scheme using variable kernel models is applied in the proposed PET reconstruction algorithm. Methods: A novel region-search technique has been used to sample the probability density function in correspondence with a small dynamic subset of the field of view that constitutes the region of response (ROR). The ROR is identified around the LOR by searching for any voxel within a dynamically calculated contour. The contour condition is currently defined as a fixed threshold over the posterior probability, and arbitrary kernel models can be applied using a numerical approach. The processing of the LORs is distributed in batches among the available computing devices, then, individual LORs are processed within different processing units. In this way, both multicore and multiple many-core processing units can be efficiently exploited. Tests have been conducted with probability models that take into account the noncolinearity, positron range, and crystal penetration effects, that produced tubes of response with varying elliptical sections whose axes were a function of the crystal's thickness and angle of incidence of the given LOR. The algorithm treats the probability model as a 3D scalar field defined within a reference system aligned with the ideal LOR. Results: This new technique provides superior image quality in terms of signal-to-noise ratio as compared with the histogram-mode method based on precomputed system matrices available for a commercial small animal scanner. Reconstruction times can be kept low with the use of multicore, many-core architectures, including multiple graphic processing units. Conclusions: A highly parallelizable LM reconstruction method has been proposed based on Monte Carlo simulations and new parallelization techniques aimed at improving the reconstruction speed and the image signal-to-noise of a given OSEM algorithm. The method has been validated using simulated and real phantoms. A special advantage of the new method is the possibility of defining dynamically the cut-off threshold over the calculated probabilities thus allowing for a direct control on the trade-off between speed and quality during the reconstruction.

Optical absorption analysis of quaternary molybdate- and tungstate-ordered double perovskites

Quaternary-ordered double perovskite A2MM’O6 (M=Mo,W) semiconductors are a group of materials with a variety of photocatalytic and optoelectronic applications. An analysis focused on the optoelectronic properties is carried out using first-principles density-functional theory with several U orbital-dependent one-electron potentials applied to different orbital subspaces. The structural non-equivalence of the atoms resulting from the symmetry has been taken in account. In order to analyze optical absorption in these materials deeply, the absorption coefficients have been split into inter- and intra-non-equivalent species contributions. The results indicate that the effect of the A and M’ atoms on the optical properties are minimal whereas the largest contribution comes from the non-equivalent O atoms to M transitions.

Aplicación de la teoría de redes complejas a procesos dinámicos en la sociedad

Podemos definir la sociedad como un sistema complejo que emerge de la cooperación y coordinación de billones de individuos y centenares de países. En este sentido no vivimos en una isla sino que estamos integrados en redes sociales que influyen en nuestro comportamiento. En esta tesis doctoral, presentamos un modelo analítico y una serie de estudios empíricos en los que analizamos distintos procesos sociales dinámicos desde una perspectiva de la teoría de redes complejas. En primer lugar, introducimos un modelo para explorar el impacto que las redes sociales en las que vivimos inmersos tienen en la actividad económica que transcurre sobre ellas, y mas concretamente en hasta qué punto la estructura de estas redes puede limitar la meritocracia de una sociedad. Como concepto contrario a meritocracia, en esta tesis, introducimos el término topocracia. Definimos un sistema como topocrático cuando la influencia o el poder y los ingresos de los individuos vienen principalmente determinados por la posición que ocupan en la red. Nuestro modelo es perfectamente meritocrático para redes completamente conectadas (todos los nodos están enlazados con el resto de nodos). Sin embargo nuestro modelo predice una transición hacia la topocracia a medida que disminuye la densidad de la red, siendo las redes poco densascomo las de la sociedad- topocráticas. En este modelo, los individuos por un lado producen y venden contenidos, pero por otro lado también distribuyen los contenidos producidos por otros individuos mediando entre comprador y vendedor. La producción y distribución de contenidos definen dos medios por los que los individuos reciben ingresos. El primero de ellos es meritocrático, ya que los individuos ingresan de acuerdo a lo que producen. Por el contrario el segundo es topocrático, ya que los individuos son compensados de acuerdo al número de cadenas mas cortas de la red que pasan a través de ellos. En esta tesis resolvemos el modelo computacional y analíticamente. Los resultados indican que un sistema es meritocrático solamente si la conectividad media de los individuos es mayor que una raíz del número de individuos que hay en el sistema. Por tanto, a la luz de nuestros resultados la estructura de la red social puede representar una limitación para la meritocracia de una sociedad. En la segunda parte de esta tesis se presentan una serie de estudios empíricos en los que se analizan datos extraídos de la red social Twitter para caracterizar y modelar el comportamiento humano. En particular, nos centramos en analizar conversaciones políticas, como las que tienen lugar durante campañas electorales. Nuestros resultados indican que la atención colectiva está distribuida de una forma muy heterogénea, con una minoría de cuentas extremadamente influyente. Además, la capacidad de los individuos para diseminar información en Twitter está limitada por la estructura y la posición que ocupan en la red de seguidores. Por tanto, de acuerdo a nuestras observaciones las redes sociales de Internet no posibilitan que la mayoría sea escuchada por la mayoría. De hecho, nuestros resultados implican que Twitter es topocrático, ya que únicamente una minoría de cuentas ubicadas en posiciones privilegiadas en la red de seguidores consiguen que sus mensajes se expandan por toda la red social. En conversaciones políticas, esta minoría de cuentas influyentes se compone principalmente de políticos y medios de comunicación. Los políticos son los mas mencionados ya que la gente les dirige y se refiere a ellos en sus tweets. Mientras que los medios de comunicación son las fuentes desde las que la gente propaga información. En un mundo en el que los datos personales quedan registrados y son cada día mas abundantes y precisos, los resultados del modelo presentado en esta tesis pueden ser usados para fomentar medidas que promuevan la meritocracia. Además, los resultados de los estudios empíricos sobre Twitter que se presentan en la segunda parte de esta tesis son de vital importancia para entender la nueva "sociedad digital" que emerge. En concreto hemos presentado resultados relevantes que caracterizan el comportamiento humano en Internet y que pueden ser usados para crear futuros modelos. Abstract Society can be defined as a complex system that emerges from the cooperation and coordination of billions of individuals and hundreds of countries. Thus, we do not live in social vacuum and the social networks in which we are embedded inevitably shapes our behavior. Here, we present an analytical model and several empirical studies in which we analyze dynamical social systems through a network science perspective. First, we introduce a model to explore how the structure of the social networks underlying society can limit the meritocracy of the economies. Conversely to meritocracy, in this work we introduce the term topocracy. We say that a system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Our model is perfectly meritocratic for fully connected networks but becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. Hence, in the light of our model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies. Next, we present several empirical studies that use data gathered from Twitter to analyze online human behavioral patterns. In particular, we focus on political conversations such as electoral campaigns. We found that the collective attention is highly heterogeneously distributed, as there is a minority of extremely influential accounts. In fact, the ability of individuals to propagate messages or ideas through the platform is constrained by the structure of the follower network underlying the social media and the position they occupy on it. Hence, although people have argued that social media can allow more voices to be heard, our results suggest that Twitter is highly topocratic, as only the minority of well positioned users are widely heard. This minority of influential accounts belong mostly to politicians and traditional media. Politicians tend to be the most mentioned, while media are the sources of information from which people propagate messages. We also propose a methodology to study and measure the emergence of political polarization from social interactions. To this end, we first propose a model to estimate opinions in which a minority of influential individuals propagate their opinions through a social network. The result of the model is an opinion probability density function. Next, we propose an index to quantify the extent to which the resulting distribution is polarized. Finally, we illustrate our methodology by applying it to Twitter data. In a world where personal data is increasingly available, the results of the analytical model introduced in this work can be used to enhance meritocracy and promote policies that help to build more meritocratic societies. Moreover, the results obtained in the latter part, where we have analyzed Twitter, are key to understand the new data-driven society that is emerging. In particular, we have presented relevant information that can be used to benchmark future models for online communication systems or can be used as empirical rules characterizing our online behavior.

Consideration of tip speed limitations in preliminary analysis of minimum COE wind turbines

A relation between Cost Of Energy, COE, maximum allowed tip speed, and rated wind speed, is obtained for wind turbines with a given goal rated power. The wind regime is characterised by the corresponding parameters of the probability density function of wind speed. The non-dimensional characteristics of the rotor: number of blades, the blade radial distributions of local solidity, twist angle, and airfoil type, play the role of parameters in the mentioned relation. The COE is estimated using a cost model commonly used by the designers. This cost model requires basic design data such as the rotor radius and the ratio between the hub height and the rotor radius. Certain design options, DO, related to the technology of the power plant, tower and blades are also required as inputs. The function obtained for the COE can be explored to �nd those values of rotor radius that give rise to minimum cost of energy for a given wind regime as the tip speed limitation changes. The analysis reveals that iso-COE lines evolve parallel to iso-radius lines for large values of limit tip speed but that this is not the case for small values of the tip speed limits. It is concluded that, as the tip speed limit decreases, the optimum decision for keeping minimum COE values can be: a) reducing the rotor radius for places with high weibull scale parameter or b) increasing the rotor radius for places with low weibull scale parameter

Self-consistent relativistic band structure of the CH3NH3PbI3 perovskite

The electronic structure and properties of the orthorhombic phase of the CH 3 NH 3 PbI 3 perovskite are computed with density functional theory. The structure, optimized using a van der Waals functional, reproduces closely the unit cell volume. The experimental band gap is reproduced accurately by combining spin-orbit effects and a hybrid functional in which the fraction of exact exchange is tuned self-consistently to the optical dielectric constant. Including spin-orbit coupling strongly reduces the anisotropy of the effective mass tensor, predicting a low electron effective mass in all crystal directions. The computed binding energy of the unrelaxed exciton agrees with experimental data, and the values found imply a fast exciton dissociation at ambient temperature. Also polaron masses for the separated carriers are estimated. The values of all these parameters agree with recent indications that fast dynamics and large carrier diffusion lengths are key in the high photovoltaic efficiencies shown by these materials.

Analysis of SnS2 hyperdoped with V proposed as efficient absorber material

Intermediate-band materials can improve the photovoltaic efficiency of solar cells through the absorption of two subband-gap photons that allow extra electron-hole pair formations. Previous theoretical and experimental findings support the proposal that the layered SnS2 compound, with a band-gap of around 2 eV, is a candidate for an intermediate-band material when it is doped with a specific transition-metal. In this work we characterize vanadium doped SnS2 using density functional theory at the dilution level experimentally found and including a dispersion correction combined with the site-occupancy-disorder method. In order to analyze the electronic characteristics that depend on geometry, two SnS2 polytypes partially substituted with vanadium in symmetry-adapted non-equivalent configurations were studied. In addition the magnetic configurations of vanadium in a SnS2 2H-polytype and its comparison with a 4H-polytype were also characterized. We demonstrate that a narrow intermediate-band is formed, when these dopant atoms are located in different layers. Our theoretical predictions confirm the recent experimental findings in which a paramagnetic intermediate-band material in a SnS2 2H-polytype with 10% vanadium concentration is obtained.

Femtosecond observation of benzyne intermediates in a molecular beam: Bergman rearrangement in the isolated molecule

In this communication, we report our femtosecond real-time observation of the dynamics for the three didehydrobenzene molecules (p-, m-, and o-benzyne) generated from 1,4-, 1,3-, and 1,2-dibromobenzene, respectively, in a molecular beam, by using femtosecond time-resolved mass spectrometry. The time required for the first and the second C-Br bond breakage is less than 100 fs; the benzyne molecules are produced within 100 fs and then decay with a lifetime of 400 ps or more. Density functional theory and high-level ab initio calculations are also reported herein to elucidate the energetics along the reaction path. We discuss the dynamics and possible reaction mechanisms for the disappearance of benzyne intermediates. Our effort focuses on the isolated molecule dynamics of the three isomers on the femtosecond time scale.

Three-dimensional modeling of and ligand docking to vitamin D receptor ligand binding domain

The ligand binding domain of the human vitamin D receptor (VDR) was modeled based on the crystal structure of the retinoic acid receptor. The ligand binding pocket of our VDR model is spacious at the helix 11 site and confined at the β-turn site. The ligand 1α,25-dihydroxyvitamin D3 was assumed to be anchored in the ligand binding pocket with its side chain heading to helix 11 (site 2) and the A-ring toward the β-turn (site 1). Three residues forming hydrogen bonds with the functionally important 1α- and 25-hydroxyl groups of 1α,25-dihydroxyvitamin D3 were identified and confirmed by mutational analysis: the 1α-hydroxyl group is forming pincer-type hydrogen bonds with S237 and R274 and the 25-hydroxyl group is interacting with H397. Docking potential for various ligands to the VDR model was examined, and the results are in good agreement with our previous three-dimensional structure-function theory.

On the acidity and reactivity of HNO in aqueous solution and biological systems

The gas phase and aqueous thermochemistry and reactivity of nitroxyl (nitrosyl hydride, HNO) were elucidated with multiconfigurational self-consistent field and hybrid density functional theory calculations and continuum solvation methods. The pKa of HNO is predicted to be 7.2 ± 1.0, considerably different from the value of 4.7 reported from pulse radiolysis experiments. The ground-state triplet nature of NO− affects the rates of acid-base chemistry of the HNO/NO− couple. HNO is highly reactive toward dimerization and addition of soft nucleophiles but is predicted to undergo negligible hydration (Keq = 6.9 × 10−5). HNO is predicted to exist as a discrete species in solution and is a viable participant in the chemical biology of nitric oxide and derivatives.

The hard-soft acid-base principle in enzymatic catalysis: dual reactivity of phosphoenolpyruvate.

In this paper, the chemical reactivity of C3 of phosphoenolpyruvate (PEP) has been analyzed in terms of density functional theory quantified through quantum chemistry calculations. PEP is involved in a number of important enzymatic reactions, in which its C3 atom behaves like a base. In three different enzymatic reactions analyzed here, C3 sometimes behaves like a soft base and sometimes behaves like a hard base in terms of the hard-soft acid-base principle. This dual nature of C3 of PEP was found to be related to the conformational change of the molecule. This leads to a testable hypothesis: that PEP adopts particular conformations in the enzyme-substrate complexes of different PEP-using enzymes, and that the enzymes control the reactivity through controlling the dihedral angle between the carboxylate and the C==C double bond of PEP.

Estudo da cristalinidade de filmes finos de nitreto de índio e simulado pelo pacote de programas Wien2k

Neste trabalho, foi utilizado o método de deposição assistida por feixe de íons (IBAD na sigla em inglês) para produção de filmes finos de nitreto de índio em substratos de silício (111) e Safira-C. Variando as condições de deposição e utlilizando a técnica de difração de raios-X, investigou-se com o intuito de obter os parâmetros que resultam em filmes finos com melhor grau de cristalinidade. Os filmes produzidos a 380C apresentaram alta cristalinidade, superior àqueles a 250C. Temperaturas muito superiores a 380C não ocasionam a formação de filme cristalino de InN, como foi observado ao utilizar a temperatura de 480C; o mesmo se observa ao utilizar temperatura ambiente. Na temperatura considerada adequada ,de 380C, obteve-se que a utilização de Ra, ou seja, a razão de fluxo de partículas entre o nitrogênio e índio, em torno de 2,3 permite obter um melhor grau de cristalinização, o qual decresce conforme se diverge desse valor. A comparação entre difratogramas de amostras produzidas com e sem a evaporação prévia de titânio, o qual é possível observar um deslocamento dos picos do InN, indicam que o efeito Gettering permite a redução de impurezas no filme, principalmente de oxigênio. Utilizou-se a técnica de Retroespalhamento de Rutherford para obtenção da composição dos elementos e o perfil de profundidade. Notou-se uma forte mistura dos elementos do substrato de silício e safira com o nitreto de índio mesmo próximos a superfície. A presença indesejável de impurezas, principalmente o oxigênio, durante a deposição de filmes finos é praticamente inevitável. Desta forma, cálculos ab initio baseados na Teoria do Funcional da Densidade (DFT) foram realizados para investigar defeitos isolados e complexos de oxigênio no nitreto de índio e a sua influência nas propriedades óticas. Considerou-se diferentes concentrações de oxigênio (x=2,76, 8,32, 11,11 e 22,22%) aplicando-se o método PBEsolGGA e TB-mBJ para o tratamento da energia e potencial de troca e correlação. Obteve-se que é energeticamente favorável o oxigênio existir principalmente como defeito carregado e isolado. Os resultados utilizando a aproximação de TB-mBJ indicam um estreitamento do bandgap conforme a concentração de oxigênio aumenta. Entretanto, a alta contribuição do efeito de Moss-Burstein resulta num efetivo alargamento do band gap, gerando valores de band gap ótico maiores que no do bulk de nitreto de índio.