Macaulay style formulas for sparse resultants

We present formulas for computing the resultant of sparse polyno- mials as a quotient of two determinants, the denominator being a minor of the numerator. These formulas extend the original formulation given by Macaulay for homogeneous polynomials.

Nutritional and insulin regulation of fatty acid synthetase and leptin gene expression through ADD1/SREBP1.

The ability to regulate specific genes of energy metabolism in response to fasting and feeding is an important adaptation allowing survival of intermittent food supplies. However, little is known about transcription factors involved in such responses in higher organisms. We show here that gene expression in adipose tissue for adipocyte determination differentiation dependent factor (ADD) 1/sterol regulatory element binding protein (SREBP) 1, a basic-helix-loop-helix protein that has a dual DNA-binding specificity, is reduced dramatically upon fasting and elevated upon refeeding; this parallels closely the regulation of two adipose cell genes that are crucial in energy homeostasis, fatty acid synthetase (FAS) and leptin. This elevation of ADD1/SREBP1, leptin, and FAS that is induced by feeding in vivo is mimicked by exposure of cultured adipocytes to insulin, the classic hormone of the fed state. We also show that the promoters for both leptin and FAS are transactivated by ADD1/SREBP1. A mutation in the basic domain of ADD1/SREBP1 that allows E-box binding but destroys sterol regulatory element-1 binding prevents leptin gene transactivation but has no effect on the increase in FAS promoter function. Molecular dissection of the FAS promoter shows that most if not all of this action of ADD1/SREBP1 is through an E-box motif at -64 to -59, contained with a sequence identified previously as the major insulin response element of this gene. These results indicate that ADD1/SREBP1 is a key transcription factor linking changes in nutritional status and insulin levels to the expression of certain genes that regulate systemic energy metabolism.

Transformation kernel density estimation of actuarial loss functions

[cat] Es presenta un estimador nucli transformat que és adequat per a distribucions de cua pesada. Utilitzant una transformació basada en la distribució de probabilitat Beta l’elecció del paràmetre de finestra és molt directa. Es presenta una aplicació a dades d’assegurances i es mostra com calcular el Valor en Risc.

Transformation kernel density estimation of actuarial loss functions

[cat] Es presenta un estimador nucli transformat que és adequat per a distribucions de cua pesada. Utilitzant una transformació basada en la distribució de probabilitat Beta l’elecció del paràmetre de finestra és molt directa. Es presenta una aplicació a dades d’assegurances i es mostra com calcular el Valor en Risc.

Majorization arrow in quantum-algorithm design

We apply majorization theory to study the quantum algorithms known so far and find that there is a majorization principle underlying the way they operate. Grover's algorithm is a neat instance of this principle where majorization works step by step until the optimal target state is found. Extensions of this situation are also found in algorithms based in quantum adiabatic evolution and the family of quantum phase-estimation algorithms, including Shor's algorithm. We state that in quantum algorithms the time arrow is a majorization arrow.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

DnaSP, DNA polymorphism analyses by the coalescent and other methods

DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (~5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. Availability: The software package, including complete documentation and examples, is freely available to academic users from: http://www.ub.es/dnasp

Reconfigurable Architecture To Estimate The Motion Of An Underwater Vehicle

This work proposes a parallel architecture for a motion estimation algorithm. It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great numbers of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. Due to its regular processing scheme, parallel implementation of correspondence problem can be an adequate approach to reduce the computation time. This work introduces parallel and real-time implementation of such low-level tasks to be carried out from the moment that the current image is acquired by the camera until the pairs of point-matchings are detected

El mapa y el territorio: una aproximación histórico-bibliográfica a la emergencia de las Humanidades Digitales en España

Este artículo consta de tres partes: en la primera me ocupo de algunas analogías y paralelismos históricos, tales como el libro y la imprenta, que han moldeado la reflexión en torno a la tecnología digital, al hipertexto y a la interactividad. En la segunda parte mi objetivo es trazar una panorámica ordenada cronológicamente sobre los principales proyectos de digitalización (bibliotecas, archivos, corpus y ediciones de obras literarias medievales y áureas) aparecidos en el ámbito académico hispánico desde 1986 hasta 2005; por supuesto, el recuento es incompleto pero aspira a ser representativo. Por último, la tercera parte se centra en cómo ha evolucionado la relación entre estudios literarios y la tecnología digital desde 2006 hasta la celebración del primer congreso oficial sobre Humanidades Digitales en 2013.

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

NoFeud : Privacitat per a xarxes socials

Aquest treball fi de carrera és un estudi-prototip d'un model de privacitat per a xarxes socials on els missatges són visibles només per a qui comparteix un cert nombre d'amics en comú, fent servir els algorismes RSA i la compartició de secrets de Shamir. Per realitzar el prototip s'ha creat un plugin de Google Chrome per a la part de client i per a la part de servidor un servei en NodeJS i l'emmagatzematge en una base de dades NoSQL mongoDB, que són tecnologies emergents dins del desenvolupament web; per tant, tot el codi ha estat escrit en JavaScript.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

An Adaptive Remeshing Procedure for Proximity Maneuvering Spacecraft Formations

We consider a methodology to optimally obtain reconfigurations of spacecraft formations. It is based on the discretization of the time interval in subintervals (called the mesh) and the obtainment of local solutions on them as a result of a variational method. Applied to a libration point orbit scenario, in this work we focus on how to find optimal meshes using an adaptive remeshing procedure and on the determination of the parameter that governs it