Crank-Nicholson method for rate equations in powder random lasers

3rd International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE 2014)

Kapital sozialaren garrantzia familia enpresetan

[EU]Kapital sozialaren ikuspegian oinarriturik eta kotizatu gabeko 172 familiaenpresa espainiarren lagin bat erabiliz, barne hartuz enpresan kudeaketa-funtzioak betetzen dituzten pertsona elkarrizketatu bi eta guztira 344 galdetegi izanik, uste dugu kapital sozial familiarrak bitartekari gisa balio duela kapital sozial ez-familiarraren eta enpresaren jardueraren artean. Gainera, gure emaitzek kapital sozialaren ulermena familia-enpresatik haratago hedatzen dute, erakundeek talde sozial nagusi baten presentzia ezaugarritzat duten testuinguru batean.

Types of embedded ties in buyer-supplier relationships and their combined effects on innovation performance

[EN] Purpose of the paper - This research analyzes the impact of three types of embedded ties, namely, specialized complementary resources, idiosyncratic investments, and knowledge sharing, on the innovation capacity of the firms. We also study the particularities of the Machine-Tool industry. Theoretical background – Our evaluation of the embedded buyer-supplier ties is based on the potential sources of relational rents proposed by Dyer and Sing (1998). We also draw on Uzzi and Lancaster (2003), Noordhoff et al. (2011), among others, to discuss the positive and negative aspects of embedded ties. Design/Methodology/Approach ‐ Using data from a survey of 202 European machine-tool firms acting as buyers and sellers, we propose and evaluate a Structural Equation model. Findings ‐ Only knowledge-sharing routines exert a significant positive effect on product innovation performance. Neither an increase in the idiosyncratic investments nor in complementary resources and capabilities enhance innovation performance. Also, knowledge-sharing routines mediate in the effect from idiosyncratic investments on innovation performance. Research Limitations. ‐ The machine tool industry has unique characteristics that make this generalization difficult. Also, there is considerable difficulty associated with testing more deeply the interrelations among these embedded ties in the long run. It is plausible to understand that these interrelations operate within a gradual process. Originality/Value/Contribution of Paper ‐ This research contributes to a better understanding of the role of embedded ties on innovativeness. To the best of our knowledge, there is no previous international empirical research analyzing the mediation effects among specialized complementary resources, idiosyncratic investments and knowledge sharing, and their effects on the innovation capacity of firms.

Cyclical Features of Uzawa-Lucas Endogenous Growth Model

This paper analyzes the cyclical properties of a generalized version of Uzawa-Lucas endogenous growth model. We study the dynamic features of different cyclical components of this model characterized by a variety of decomposition methods. The decomposition methods considered can be classified in two groups. On the one hand, we consider three statistical filters: the Hodrick-Prescott filter, the Baxter-King filter and Gonzalo-Granger decomposition. On the other hand, we use four model-based decomposition methods. The latter decomposition procedures share the property that the cyclical components obtained by these methods preserve the log-linear approximation of the Euler-equation restrictions imposed by the agent’s intertemporal optimization problem. The paper shows that both model dynamics and model performance substantially vary across decomposition methods. A parallel exercise is carried out with a standard real business cycle model. The results should help researchers to better understand the performance of Uzawa-Lucas model in relation to standard business cycle models under alternative definitions of the business cycle.

An Estimated New-Keynesian Model with Unemployment as Excess Supply of Labor

Wage stickiness is incorporated to a New-Keynesian model with variable capital to drive endogenous unemployment uctuations de ned as the log di¤erence between aggregate labor supply and aggregate labor demand. We estimated such model using Bayesian econometric techniques and quarterly U.S. data. The second-moment statistics of the unemployment rate in the model give a good t to those observed in U.S. data. Our results also show that wage-push shocks, demand shifts and monetary policy shocks are the three major determinants of unemployment fl uctuations. Compared to an estimated New-Keynesian model without unemployment (Smets and Wouters, 2007): wage stickiness is higher, labor supply elasticity is lower, the slope of the New-Keynesian Phillips curve is flatter, and the importance of technology innovations on output variability increases.

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.

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.