El desarrollo exportador de las pymes industriales españolas participantes en un consorcio de exportación: un estudio de caso

[ES] Pese a los recientes esfuerzos realizados para dinamizarlos desde los organismos públicos competentes españoles, aún son relativamente pocos los consorcios de exportación realmente exitosos en España frente a los que ni llegan a constituirse o apenas sobreviven un tiempo. Por otra parte, también son escasos los estudios nacionales existentes en esta área. Este trabajo se centra en el análisis de las fases del proceso del desarrollo exportador de algunas pymes industriales españolas que participan en un consorcio de exportación, así como en los factores que influyen en la elección y funcionamiento de este mecanismo institucional colaborativo potencialmente eficaz para penetrar con mayor éxito en los mercados exteriores.

Orientación estratégica, innovación y resultados en PYMES de nueva creación: el rol del marketing

[ES] A pesar del importante papel de las PYMES de nueva creación en el desarrollo económico, no tenemos constancia de trabajos que hayan abordado de manera simultánea el estudio de la relación entre tres orientaciones estratégicas clave como son la orientación emprendedora (OE), la orientación al mercado (OM) y la orientación al aprendizaje (OA) con la innovación y con el éxito de las PYMES de nueva creación. Los trabajos existentes en la actualidad son de carácter parcial, ya que se limitan a estudiar los efectos de sólo algunas de estas tres orientaciones estratégicas en los resultados de dichas empresas (Li y Atuahene-Gima, 2001; Renko et al., 2009).

Using network mesures to test evolved NK-landscapes

In this paper we empirically investigate which are the structural characteristics that can help to predict the complexity of NK-landscape instances for estimation of distribution algorithms. To this end, we evolve instances that maximize the estimation of distribution algorithm complexity in terms of its success rate. Similarly, instances that minimize the algorithm complexity are evolved. We then identify network measures, computed from the structures of the NK-landscape instances, that have a statistically significant difference between the set of easy and hard instances. The features identified are consistently significant for different values of N and K.

Data analysis advances in marine science for fisheries management : supervised classification application

169 p. : il. col.

A review of travel time estimation and forecasting for advanced traveler information systems

Providing on line travel time information to commuters has become an important issue for Advanced Traveler Information Systems and Route Guidance Systems in the past years, due to the increasing traffic volume and congestion in the road networks. Travel time is one of the most useful traffic variables because it is more intuitive than other traffic variables such as flow, occupancy or density, and is useful for travelers in decision making. The aim of this paper is to present a global view of the literature on the modeling of travel time, introducing crucial concepts and giving a thorough classification of the existing tech- niques. Most of the attention will focus on travel time estimation and travel time prediction, which are generally not presented together. The main goals of these models, the study areas and methodologies used to carry out these tasks will be further explored and categorized.

Clasificadores supervisados para predecir la abstinencia a 12 meses en fumadores tratados con vareniclina

Tesis leida dentro del Master de "Ingeniería Computacional y Sistemas Inteligentes"

New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination

Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.

Kv7 Channels Can Function without Constitutive Calmodulin Tethering

9 p.

Pamplona, toda ella un castillo, y más que ciudad, ciudadela. Construcción de la imagen de una ciudad, 1876-1941

[ES] Un estudio de Pamplona (España) como una de las ciudades decimonónicas europeas resueltas a resistirse al modelo de gran urbe universal despersonalizada y anómica. Comparación con Vitoria, inmersa en ese proceso.

El impacto de las nuevas tecnologías: producción cultural, profesionalización, etc.

Ponencia leída en el Foro de Comunicaciones IkasArt II (BEC Barakaldo, 2010.06.18)

Increased opioid dependence in a mouse model of panic disorder

[EN] Panic disorder is a highly prevalent neuropsychiatric disorder that shows co-occurrence with substance abuse. Here, we demonstrate that TrkC, the high-affinity receptor for neurotrophin-3, is a key molecule involved in panic disorder and opiate dependence, using a transgenic mouse model (TgNTRK3). Constitutive TrkC overexpression in TgNTRK3 mice dramatically alters spontaneous firing rates of locus coeruleus (LC) neurons and the response of the noradrenergic system to chronic opiate exposure, possibly related to the altered regulation of neurotrophic peptides observed. Notably, TgNTRK3 LC neurons showed an increased firing rate in saline-treated conditions and profound abnormalities in their response to met5-enkephalin. Behaviorally, chronic morphine administration induced a significantly increased withdrawal syndrome in TgNTRK3 mice. In conclusion, we show here that the NT-3/TrkC system is an important regulator of neuronal firing in LC and could contribute to the adaptations of the noradrenergic system in response to chronic opiate exposure. Moreover, our results indicate that TrkC is involved in the molecular and cellular changes in noradrenergic neurons underlying both panic attacks and opiate dependence and support a functional endogenous opioid deficit in panic disorder patients.

The Linear Ordering Problem Revisited

The Linear Ordering Problem is a popular combinatorial optimisation problem which has been extensively addressed in the literature. However, in spite of its popularity, little is known about the characteristics of this problem. This paper studies a procedure to extract static information from an instance of the problem, and proposes a method to incorporate the obtained knowledge in order to improve the performance of local search-based algorithms. The procedure introduced identifies the positions where the indexes cannot generate local optima for the insert neighbourhood, and thus global optima solutions. This information is then used to propose a restricted insert neighbourhood that discards the insert operations which move indexes to positions where optimal solutions are not generated. In order to measure the efficiency of the proposed restricted insert neighbourhood system, two state-of-the-art algorithms for the LOP that include local search procedures have been modified. Conducted experiments confirm that the restricted versions of the algorithms outperform the classical designs systematically. The statistical test included in the experimentation reports significant differences in all the cases, which validates the efficiency of our proposal.

Sampling and learning the Mallows and Generalized Mallows models under the Cayley distance

[EN]The Mallows and Generalized Mallows models are compact yet powerful and natural ways of representing a probability distribution over the space of permutations. In this paper we deal with the problems of sampling and learning (estimating) such distributions when the metric on permutations is the Cayley distance. We propose new methods for both operations, whose performance is shown through several experiments. We also introduce novel procedures to count and randomly generate permutations at a given Cayley distance both with and without certain structural restrictions. An application in the field of biology is given to motivate the interest of this model.

Sampling and learning the Mallows and Weighted Mallows models under the Hamming distance

[EN]In this paper we deal with distributions over permutation spaces. The Mallows model is the mode l in use. The associated distance for permutations is the Hamming distance.