Harvesting for disseminating, open archives and role of academic libraries

The Scholarly communication system is in a critical stage, due to a number of factors.The Open Access movement is perhaps the most interesting response that the scientific community has tried to give to this problem. The paper examines strengths and weaknesses of the Open Access strategy in general and, more specifically, of the Open Archives Initiative, discussing experiences, criticisms and barriers. All authors that have faced the problems of implementing an OAI compliant e-print server agree that technical and practical problems are not the most difficult to overcome and that the real problem is the change in cultural attitude required. In this scenario the university library is possibly the standard bearer for the advent and implementation of e-prints archives and Open Archives services. To ensure the successful implementation of this service the Library has a number of distinct roles to play

Some Effects of Transaction Taxes Under Different Microstructures

We show that the effectiveness of transaction taxes depends on the market microstructure. Within our model, heterogeneous traders use a blend of technical and fundamental trading strategies to determine their orders. In addition, they may turn inactive if the profitability of trading decreases. We find that in a continuous double auction market the imposition of a transaction tax is not likely to stabilize financial markets since a reduction in market liquidity amplifies the average price impact of a given order. In a dealership market, however, abundant liquidity is provided by specialists and thus a transaction tax may reduce volatility by crowding out speculative orders.transaction tax; Tobin tax; microstructures; agent-based models; liquidity

Optimal Dimension of Transition Probability Matrices for Markov Chain Bootstrapping

� While the large portion of the literature on Markov chain (possibly of order higher than one) bootstrap methods has focused on the correct estimation of the transition probabilities, little or no attention has been devoted to the problem of estimating the dimension of the transition probability matrix. Indeed, it is usual to assume that the Markov chain has a one-step memory property and that the state space could not to be clustered, and coincides with the distinct observed values. In this paper we question the opportunity of such a standard approach. In particular we advance a method to jointly estimate the order of the Markov chain and identify a suitable clustering of the states. Indeed in several real life applications the "memory" of many processes extends well over the last observation; in those cases a correct representation of past trajectories requires a significantly richer set than the state space. On the contrary it can sometimes happen that some distinct values do not correspond to really "different states of a process; this is a common conclusion whenever, for example, a process assuming two distinct values in t is not affected in its distribution in t+1. Such a situation would suggest to reduce the dimension of the transition probability matrix. Our methods are based on solving two optimization problems. More specifically we consider two competing objectives that a researcher will in general pursue when dealing with bootstrapping: preserving the similarity between the observed and the bootstrap series and reducing the probabilities of getting a perfect replication of the original sample. A brief axiomatic discussion is developed to define the desirable properties for such optimal criteria. Two numerical examples are presented to illustrate the method. �order of Markov chains,similarity of time series,transition probability matrices,multiplicity of time series,partition of states of Markov chains,Markov chains,bootstrap methods

Harvesting for disseminating, open archives and role of academic libraries

The Scholarly communication system is in a critical stage, due to a number of factors.The Open Access movement is perhaps the most interesting response that the scientific community has tried to give to this problem. The paper examines strengths and weaknesses of the Open Access strategy in general and, more specifically, of the Open Archives Initiative, discussing experiences, criticisms and barriers. All authors that have faced the problems of implementing an OAI compliant e-print server agree that technical and practical problems are not the most difficult to overcome and that the real problem is the change in cultural attitude required. In this scenario the university library is possibly the standard bearer for the advent and implementation of e-prints archives and Open Archives services. To ensure the successful implementation of this service the Library has a number of distinct roles to play

Thermal Fluid-Dynamic Study for the Thermal Control of the New Alice Central Detectors. Studio termo fluido-dinamico per il controllo termico dei nuovi rivelatori centrali del progetto Alice

The Inner Tracking System Detector of the ALICE experiment at CERN laboratory will be replaced in 2020 with a new Detector. The new electronic components will have a high in terms of dissipated heat. This thesis work has been developed at CERN in Geneva in close contact with the group responsible for the cooling of the Detector. The aim of the thermal fluid dynamic study devised is to deliver to the group a reliable and accurate description od the air flow inside the New Inner Tracking Systemope

Relevant states and memory in Markov chain bootstrapping and simulation

Markov chain theory is proving to be a powerful approach to bootstrap and simulate highly nonlinear time series. In this work, we provide a method to estimate the memory of a Markov chain (i.e. its order) and to identify its relevant states. In particular, the choice of memory lags and the aggregation of irrelevant states are obtained by looking for regularities in the transition probabilities. Our approach is based on an optimization model. More specifically, we consider two competing objectives that a researcher will in general pursue when dealing with bootstrapping and simulation: preserving the “structural” similarity between the original and the resampled series, and assuring a controlled diversification of the latter. A discussion based on information theory is developed to define the desirable properties for such optimal criteria. Two numerical tests are developed to verify the effectiveness of the proposed method

Approximating Markov Chains for Bootstrapping and Simulation

In this work we develop a bootstrap method based on the theory of Markov chains. The method moves from the two competing objectives that a researcher pursues when performing a bootstrap procedure: (i) to preserve the structural similarity -in statistical sense- between the original and the bootstrapped sample; (ii) to assure a diversification of the latter with respect to the former. The original sample is assumed to be driven by a Markov chain. The approach we follow is to implement an optimization problem to estimate the memory of a Markov chain (i.e. its order) and to identify its relevant states. The basic ingredients of the model are the transition probabilities, whose distance is measured through a suitably defined functional. We apply the method to the series of electricity prices in Spain. A comparison with the Variable Length Markov Chain bootstrap, which is a well established bootstrap method, shows the superiority of our proposal in reproducing the dependence among data