The Strategic Adaptation of Party Organizations to New Information and Communication Technologies : A Study of Catalan and Spanish Parties

Aquest document se centra en els casos dels dos principals partits espanyols (PP i PSOE) i catalans (PSC i CDC) en el període immediatament després de les eleccions generals espanyoles de maig de 2008, quan aquests celebraren els seus congressos. En general, es poden distingir tres tipus d'actors: en primer lloc, els ciberactivistes que tracten d'obtenir el reconeixement formal de la seva activitat en els seus partits. Així com, els líders del partit que poden intentar promoure la presència del partit en el ciberespai, però que també poden romandre indecisos perquè no és clar l'impacte electoral a la xarxa del ciberactivisme. Finalment, alguns militants tradicionals (off-line) solen ser reticents al reconeixement del ciberactivisme perquè amenaça les recompenses previstes dins del partit. Aquest article mostra com els nostres partits varen respondre al desafiament del ciberactivisme i arriba a la conclusió que la seva situació electoral, mediada per la seva ideologia, estructura organitzativa i el tipus de militància, poden ajudar-nos a comprendre el grau diferent d'institucionalització en l'organització del partit.

Towards Direct Policy Search Reinforcement Learning for Robot Control

This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

CXCR4-activated astrocyte glutamate release via TNFalpha: amplification by microglia triggers neurotoxicity.

Astrocytes actively participate in synaptic integration by releasing transmitter (glutamate) via a calcium-regulated, exocytosis-like process. Here we show that this process follows activation of the receptor CXCR4 by the chemokine stromal cell-derived factor 1 (SDF-1). An extraordinary feature of the ensuing signaling cascade is the rapid extracellular release of tumor necrosis factor-alpha (TNFalpha). Autocrine/paracrine TNFalpha-dependent signaling leading to prostaglandin (PG) formation not only controls glutamate release and astrocyte communication, but also causes their derangement when activated microglia cooperate to dramatically enhance release of the cytokine in response to CXCR4 stimulation. We demonstrate that altered glial communication has direct neuropathological consequences and that agents interfering with CXCR4-dependent astrocyte-microglia signaling prevent neuronal apoptosis induced by the HIV-1 coat glycoprotein, gp120IIIB. Our results identify a new pathway for glia-glia and glia-neuron communication that is relevant to both normal brain function and neurodegenerative diseases.

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S-SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient.Location Two study areas in the Alps of Switzerland.Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways - summing binary predictions, summing random draws of binomial trials and summing predicted probabilities - to obtain a final species count.Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S-SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump-shaped pattern of SR observed along the elevational gradient. The S-SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S-SDM approaches the summed binomial trials based on predicted probabilities and summed predicted probabilities - do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S-SDM approaches fail to appropriately reproduce the observed hump-shaped patterns of SR along the elevational gradient.Main conclusions Macroecological approach and S-SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S-SDM by MEM predictions.