Velocity shear, turbulent saturation, and steep plasma gradients in the scrape-off layer of inner-wall limited tokamaks

The narrow power decay-length ($\lambda_q$), recently found in the scrape-off layer (SOL) of inner-wall limited (IWL) discharges in tokamaks, is studied using 3D, flux-driven, global two-fluid turbulence simulations. The formation of the steep plasma profiles measured is found to arise due to radially sheared $\vec{E}\times\vec{B}$ poloidal flows. A complex interaction between sheared flows and outflowing plasma currents regulates the turbulent saturation, determining the transport levels. We quantify the effects of sheared flows, obtaining theoretical estimates in agreement with our non-linear simulations. Analytical calculations suggest that the IWL $\lambda_q$ is roughly equal to the turbulent correlation length.Comment: 5 pages, 5 figure

Politicians at work. The private returns and social costs of political connections

We quantify the private returns and social costs of political connections exploiting a unique longitudinal dataset that combines matched employer-employee data for a representative sample of Italian firms with administrative archives on the universe of individuals appointed in local governments over the period 1985-97. According to our results, the revenue premium granted by political connections amounts to 5% on average, it is obtained through changes in domestic sales but not in exports, and it is not related to improvements in firm productivity. The connection premium is positive for upstream producers for the public administration only, and larger (up to 25%) in areas characterized by high public expenditure and high levels of corruption. These findings suggest that the gains in market power derive from public demand shifts towards politically connected firms. We estimate such shifts reduce the provision of public goods by approximately 20%.political connections, social welfare, productivity, employer-employee data

A Dynamic Clustering and Resource Allocation Algorithm for Downlink CoMP Systems with Multiple Antenna UEs

Coordinated multi-point (CoMP) schemes have been widely studied in the recent years to tackle the inter-cell interference. In practice, latency and throughput constraints on the backhaul allow the organization of only small clusters of base stations (BSs) where joint processing (JP) can be implemented. In this work we focus on downlink CoMP-JP with multiple antenna user equipments (UEs) and propose a novel dynamic clustering algorithm. The additional degrees of freedom at the UE can be used to suppress the residual interference by using an interference rejection combiner (IRC) and allow a multistream transmission. In our proposal we first define a set of candidate clusters depending on long-term channel conditions. Then, in each time block, we develop a resource allocation scheme by jointly optimizing transmitter and receiver where: a) within each candidate cluster a weighted sum rate is estimated and then b) a set of clusters is scheduled in order to maximize the system weighted sum rate. Numerical results show that much higher rates are achieved when UEs are equipped with multiple antennas. Moreover, as this performance improvement is mainly due to the IRC, the gain achieved by the proposed approach with respect to the non-cooperative scheme decreases by increasing the number of UE antennas.Comment: 27 pages, 8 figure

Quasi-deterministic dynamics, memory effects, and lack of self-averaging in the relaxation of quenched ferromagnets

We discuss the interplay between the degree of dynamical stochasticity, memory persistence and violation of the self-averaging property in the aging kinetics of quenched ferromagnets. We show that, in general, the longest possible memory effects, which correspond to the slowest possible temporal decay of the correlation function, are accompanied by the largest possible violation of self-averaging and a quasi-deterministic descent into the ergodic components. This phenomenon is observed in different systems, such as the Ising model with long-range interactions, including mean-field, and the short-range random field Ising model.Comment: Introduction strongly revised, changed figures. Accepted for publication as a Rapid Communication in Physical Review

Event-based Access to Historical Italian War Memoirs

The progressive digitization of historical archives provides new, often domain specific, textual resources that report on facts and events which have happened in the past; among these, memoirs are a very common type of primary source. In this paper, we present an approach for extracting information from Italian historical war memoirs and turning it into structured knowledge. This is based on the semantic notions of events, participants and roles. We evaluate quantitatively each of the key-steps of our approach and provide a graph-based representation of the extracted knowledge, which allows to move between a Close and a Distant Reading of the collection.Comment: 23 pages, 6 figure

FDI Determination and Corporate Tax Competition in a Volatile World

This paper investigates the role of economic and political volatility in the process of corporate tax-rate determination. The article is based on a theoretical framework that allows for the ability of multinational firms to choose the optimal timing of foreign investment and to shift profits by transfer pricing, and provides an empirical analysis on a large panel data set of countries over the 1983-2003 period. First, a reduced-form dynamic equation of corporate tax rate determination is estimated by the generalised method of moments (GMM), where a country’s top statutory corporate tax rate depends on a number of measures of economic and political volatility. The fundamental testable prediction derived from the theoretical model is that increased volatility should reduce a country’s corporate tax rate. Our results support the hypothesis that economic volatility is associated with lower top statutory corporate tax rates, while our measures of political volatility have no significant impact on corporate taxation policy. In order to identify the channels through which volatility works, we also estimate a structural model allowing for simultaneous determination of the corporate tax rate and the inflow of FDI to a particular country. The estimates of the structural model show that economic volatility affects the corporate tax setting process through their impact on FDI inflow.foreign direct investment, tax competition, volatility

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a `basin' of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.Comment: submitted to Scientific Repor