Cooperation and Competition of Metropolises in South Eastern Europe: Athens and Constantinople. Evolution and Perspective.

This study searches the cooperation and the competition among the metropolises in South East Europe. Especially, it focuses on the interaction between Athens and Constantinople. First, it outlines the contemporary regional network of cities of SE Europe. Secondly, it presents the location, the infrastructure and the investments of the private and the public sector in Athens and the Constantinople. Furthermore, there is a comparison made in each category between the two cities and there are pinpointed the opportunities of common actions. Ultimately, the conclusions of the study underline the potential created in SE Europe because of the interaction these metropolises. The study is useful due to the necessity to find out how the relationships of the two development poles in SE Europe, taking always into account the differences in culture between the two countries, affect important issues in planning as the Foreign Direct Investments, the urban governance and the networks between metropolises built by the cooperation and the competition.

Affordance of vibrational excitation for music composition and performance

Mechanical vibrations have typically been used in the performance domain within feedback systems to inform musicians of system states or as communication channels between performers. In this paper, we propose the addi- tional taxonomic category of vibrational excitation of mu- sical instruments for sound generation. To explore the va- riety of possibilities associated with this extended taxon- omy, we present the Oktopus, a multi-purpose wireless sys- tem capable of motorised vibrational excitation. The sys- tem can receive up to eight inputs and generates vibrations as outputs through eight motors that can be positioned ac- cordingly to produce a wide range of sounds from an ex- cited instrument. We demonstrate the usefulness of the proposed system and extended taxonomy through the de- velopment and performance of Live Mechanics, a compo- sition for piano and interactive electronics

Optimal experiment design in a filtering context with application to sampled network data

We examine the problem of optimal design in the context of filtering multiple random walks. Specifically, we define the steady state E-optimal design criterion and show that the underlying optimization problem leads to a second order cone program. The developed methodology is applied to tracking network flow volumes using sampled data, where the design variable corresponds to controlling the sampling rate. The optimal design is numerically compared to a myopic and a naive strategy. Finally, we relate our work to the general problem of steady state optimal design for state space models.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS283 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Discovering Graphical Granger Causality Using the Truncating Lasso Penalty

Components of biological systems interact with each other in order to carry out vital cell functions. Such information can be used to improve estimation and inference, and to obtain better insights into the underlying cellular mechanisms. Discovering regulatory interactions among genes is therefore an important problem in systems biology. Whole-genome expression data over time provides an opportunity to determine how the expression levels of genes are affected by changes in transcription levels of other genes, and can therefore be used to discover regulatory interactions among genes. In this paper, we propose a novel penalization method, called truncating lasso, for estimation of causal relationships from time-course gene expression data. The proposed penalty can correctly determine the order of the underlying time series, and improves the performance of the lasso-type estimators. Moreover, the resulting estimate provides information on the time lag between activation of transcription factors and their effects on regulated genes. We provide an efficient algorithm for estimation of model parameters, and show that the proposed method can consistently discover causal relationships in the large $p$, small $n$ setting. The performance of the proposed model is evaluated favorably in simulated, as well as real, data examples. The proposed truncating lasso method is implemented in the R-package grangerTlasso and is available at http://www.stat.lsa.umich.edu/~shojaie.Comment: 12 pages, 4 figures, 1 tabl