Integrity and Efficiency in the EU: The Case Against the European Economic Constitution. CES Working Paper, no. 130, 2006

The European Constitutional Treaty (ECT) was presented by its drafters as an explicit constitution for the European Union (EU 25). A possible explanation for its rejection by the French and Dutch citizens in the course of spring 2005 is that it did not sufficiently amend the implicit constitution of the EU 25, the European Union Treaty (EUT), which was truly the object of voters’ aversion. Assuming this to be true, there should be a thorough debate on the relevance and viability of the de facto current constitution of the European Union. In this paper, we engage in this debate by identifying what is essentially wrong with the economic provisions of the EUT, which we designate as the “European economic constitution.” Using a constitutional political economy approach, we first attempt to demonstrate that both what we define as the “principle of integrity” and the “principle of efficiency” of collective action appear to be violated by the European economic constitution. This occurs, respectively, because its provisions are not neutral, nor revisable, and because they do not sufficiently allow for the possibility of cooperative collective decision (leading to convergence in welfare) in a more than ever numerous and heterogeneous EU. Our essential argument in this respect regards the implications of the structurally different economic performances and incentives of small and large countries under the European economic constitution. Finally, since the present European trade-off between “integrity” and “efficiency” appears sub-optimal, we present two original ways of achieving potentially better ones in the EU, through a “Great compromise” or “Economic constitution(s),” expressing a preference for the latter

Guaranteed Control of Sampled Switched Systems using Semi-Lagrangian Schemes and One-Sided Lipschitz Constants

In this paper, we propose a new method for ensuring formally that a controlled trajectory stay inside a given safety set S for a given duration T. Using a finite gridding X of S, we first synthesize, for a subset of initial nodes x of X , an admissible control for which the Euler-based approximate trajectories lie in S at t $\in$ [0,T]. We then give sufficient conditions which ensure that the exact trajectories, under the same control, also lie in S for t $\in$ [0,T], when starting at initial points 'close' to nodes x. The statement of such conditions relies on results giving estimates of the deviation of Euler-based approximate trajectories, using one-sided Lipschitz constants. We illustrate the interest of the method on several examples, including a stochastic one

Brief Announcement: Memory Lower Bounds for Self-Stabilization

In the context of self-stabilization, a silent algorithm guarantees that the communication registers (a.k.a register) of every node do not change once the algorithm has stabilized. At the end of the 90\u27s, Dolev et al. [Acta Inf. \u2799] showed that, for finding the centers of a graph, for electing a leader, or for constructing a spanning tree, every silent deterministic algorithm must use a memory of Omega(log n) bits per register in n-node networks. Similarly, Korman et al. [Dist. Comp. \u2707] proved, using the notion of proof-labeling-scheme, that, for constructing a minimum-weight spanning tree (MST), every silent algorithm must use a memory of Omega(log^2n) bits per register. It follows that requiring the algorithm to be silent has a cost in terms of memory space, while, in the context of self-stabilization, where every node constantly checks the states of its neighbors, the silence property can be of limited practical interest. In fact, it is known that relaxing this requirement results in algorithms with smaller space-complexity. In this paper, we are aiming at measuring how much gain in terms of memory can be expected by using arbitrary deterministic self-stabilizing algorithms, not necessarily silent. To our knowledge, the only known lower bound on the memory requirement for deterministic general algorithms, also established at the end of the 90\u27s, is due to Beauquier et al. [PODC \u2799] who proved that registers of constant size are not sufficient for leader election algorithms. We improve this result by establishing the lower bound Omega(log log n) bits per register for deterministic self-stabilizing algorithms solving (Delta+1)-coloring, leader election or constructing a spanning tree in networks of maximum degree Delta

Country size and strategic aspects of structural reforms in the EU. NERO meeting, OECD, Paris, June 12, 2006.

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Chemical analysis of a single basic cell of porous anodic aluminium oxide templates

We prepared anodic aluminium oxide (AAO) templates with “honeycomb” geometry, i.e. hexagonally ordered circular pores. The structures were extensively studied and characterized by EPMA coupled with FEG-SEM and FEG-TEM coupled with EDX at meso and nanoscopic scales, in other words, at the scale of a single basic cell making up the highly ordered porous anodic film. The analyses allowed the identification of the chemical compounds present and the evaluation of their levels in the different parts of each cell. Of note was the absence of phosphates inside the “skeleton” and their high content in the “internal part”. Various models of porous anodic film growth are discussed on the basis of the results, contributing to a better understanding of AAO template preparation and selfnanostructuring phenomena

Memory lower bounds for deterministic self-stabilization

In the context of self-stabilization, a \emph{silent} algorithm guarantees that the register of every node does not change once the algorithm has stabilized. At the end of the 90's, Dolev et al. [Acta Inf. '99] showed that, for finding the centers of a graph, for electing a leader, or for constructing a spanning tree, every silent algorithm must use a memory of $\Omega(\log n)$ bits per register in $n$-node networks. Similarly, Korman et al. [Dist. Comp. '07] proved, using the notion of proof-labeling-scheme, that, for constructing a minimum-weight spanning trees (MST), every silent algorithm must use a memory of $\Omega(\log^2n)$ bits per register. It follows that requiring the algorithm to be silent has a cost in terms of memory space, while, in the context of self-stabilization, where every node constantly checks the states of its neighbors, the silence property can be of limited practical interest. In fact, it is known that relaxing this requirement results in algorithms with smaller space-complexity. In this paper, we are aiming at measuring how much gain in terms of memory can be expected by using arbitrary self-stabilizing algorithms, not necessarily silent. To our knowledge, the only known lower bound on the memory requirement for general algorithms, also established at the end of the 90's, is due to Beauquier et al.~[PODC '99] who proved that registers of constant size are not sufficient for leader election algorithms. We improve this result by establishing a tight lower bound of $\Theta(\log \Delta+\log \log n)$ bits per register for self-stabilizing algorithms solving $(\Delta+1)$-coloring or constructing a spanning tree in networks of maximum degree~$\Delta$. The lower bound $\Omega(\log \log n)$ bits per register also holds for leader election