Short-range correlations in finite nuclear systems

Recent results concerning the use of the Correlated Basis Function to investigate the ground state properties of medium-heavy doubly magic nuclei with microscopic interactions are presented. The calculations have been done by considering a Short-Range Correlation between nucleons. The possibility of identifying effects produced by Short-Range Correlations in electromagnetically induced phenomena is discussed.Comment: 12 pages, 10 Postscript figures, Contribution to the International Workshop on Nuclear Theory, Rila Mountains, Bulgaria 10 to June 15, 200

Random Phase Approximation and neutrino-nucleus cross sections

The Random Phase Approximation theory is used to calculate the total cross sections of electron neutrinos on $^{12}$C nucleus. The role of the excitation of the discrete spectrum is discussed. A comparison with electron scattering and muon capture data is presented. The cross section of electron neutrinos coming from muon decay at rest is calculated.Comment: 6 pages, 5 eps figures, Presented at the XX Max Born Symposium, Wroclaw (Poland

Symmetry classification of quasi-linear PDE's containing arbitrary functions

We consider the problem of performing the preliminary "symmetry classification'' of a class of quasi-linear PDE's containing one or more arbitrary functions: we provide an easy condition involving these functions in order that nontrivial Lie point symmetries be admitted, and a "geometrical'' characterization of the relevant system of equations determining these symmetries. Two detailed examples will elucidate the idea and the procedure: the first one concerns a nonlinear Laplace-type equation, the second a generalization of an equation (the Grad-Schl\"uter-Shafranov equation) which is used in magnetohydrodynamics.Comment: 15 pages; to be published in Nonlinear Dynamic

Cognition, Incentives, and Public Governance:Laboratory Federalism from the Organizational Viewpoint

The Second Generation Theory (SGT) of fiscal federalism, which draws upon contemporary economic and industrial organization theory, hitherto focuses only on the negative benefits of public decentralization: the potentially superior ability to align perverse incentives vis-à-vis the centralized governance alternative. The SGT neglects the positive benefits of decentralization (mistake-ridden learning, flexibility, and option discovery), although the limitations of organization theory do not justify such neglect. By likening intergovernmental grants to incomplete contracts, this work shows that the SGT can include the laboratory nature of decentralization.Experimentation, incomplete contracts, intergovernmental grants, learning, Second Generation Theory of fiscal federalism.

Old and New Theories of Fiscal Federalism, Organizational Design Problems, and Tiebout

This work is a contribution to the Second Generation Theory (SGT) of fiscal federalism that studies fiscal federalism through contemporary economic and industrial organization theory. First, it establishes context by introducing the two classic motivations in support of federalism, namely, incentives and knowledge. Second, it succinctly discusses the incentive-based organizational approach of the SGT. Third, it shows that the Tiebout model already embeds an organizational approach, which instead rests on a knowledge motivation. The underlying theme is that the SGT should include both the incentive and knowledge motivations for fiscal decentralization.Economic organization, Incentives, Knowledge, Second Generation Theory of fiscal federalism.

Joint segmentation of color and depth data based on splitting and merging driven by surface fitting

This paper proposes a segmentation scheme based on the joint usage of color and depth data together with a 3D surface estimation scheme. Firstly a set of multi-dimensional vectors is built from color, geometry and surface orientation information. Normalized cuts spectral clustering is then applied in order to recursively segment the scene in two parts thus obtaining an over-segmentation. This procedure is followed by a recursive merging stage where close segments belonging to the same object are joined together. At each step of both procedures a NURBS model is fitted on the computed segments and the accuracy of the fitting is used as a measure of the plausibility that a segment represents a single surface or object. By comparing the accuracy to the one at the previous step, it is possible to determine if each splitting or merging operation leads to a better scene representation and consequently whether to perform it or not. Experimental results show how the proposed method provides an accurate and reliable segmentation