Tax Decentralisation and local Government size

The aim of this paper is to re-examine the relationship between fiscal federalism and the size of local governments. Traditionally, the empirical studies have focused on the different accountability power of grants and local taxes, concluding that the former encourages the growth and the latter contributes to contain local public spending. Yet, the existing literature is more silent about the possibility that different types of tax autonomy may still have differential impacts on the expansion of the local public sector. The paper addresses this issue by introducing a new testable hypothesis - the “Tax Separation Hypothesis” (TSH) - according to which tax decentralisation organised on tax bases used only by local governments would favour most the containment of local public expenditures, while that organised on tax base sharing (i.e. piggybacking mechanisms) is not expected to have a significant impact on the local government size. Using an unbalanced panel data set of OECD countries, we adopt the novel approach of disentangling the impact of local taxes - on income, property, and goods and services - on the size of the local public sector. In particular, property taxes only - mostly based on a “tax separation” scheme - seem to have a negative impact on the size of local government. Instead, both income taxes and general taxes on goods and services – often shared with central governments – have uncertain impacts on the size of local governments (and more frequently positive). We conclude that tax decentralisation is a necessary condition to contain local public expenditures, yet it is not sufficient, as a tax separation scheme would in fact be required.Fiscal decentralisation; Tax sharing; Tax separation; Property taxes; Local government size.

Superbroadcasting of conjugate quantum variables

We consider the problem of broadcasting arbitrary states of radiation modes from N to M>N copies by a map that preserves the average value of the field and optimally reduces the total noise in conjugate variables. For N>=2 the broadcasting can be achieved perfectly, and for sufficiently noisy input states one can even purify the state while broadcasting--the so-called superbroadcasting. For purification (i.e. M<=N), the reduction of noise is independent of M. Similar results are proved for broadcasting with phase-conjugation. All the optimal maps can be implemented by linear optics and linear amplification.Comment: 7 pages, 1 eps figures. Accepted for publication on Europhysics Letter

Integral sliding modes generation via DRL-assisted Lyapunov-based control for robot manipulators

This paper proposes an enhanced version of the integral sliding mode (ISM) control, where a deep neural network (DNN) is first trained as a deep reinforcement learning (DRL) agent. Then, such a DNN is fine-tuned relying on a Lyapunov-based weight adaptation law, with the aim of compensating the lack of knowledge of the full dynamics in the case of robot manipulators. Specifically, a DRL agent is trained off-line on a reward depending on the sliding variable to estimate the unknown drift term of the robot dynamics. Such an estimate is then exploited to initialize and perform the fine tuning of the online adaptation mechanism based on the DNN. The proposal is theoretically analysed and assessed in simulation relying on the planar configuration of a Franka Emika Panda robot manipulator

Actuator fault diagnosis with neural network-integral sliding mode based unknown input observers

This paper proposes an integral sliding mode (ISM) based unknown input observer (UIO) which is able to perform fault diagnosis (FD) in condition of lack of knowledge of the plant model. In particular, a two-layer neural network (NN) is employed to estimate online the drift term of the system dynamics needed to compute the so-called integral sliding manifold. The weights of such a NN are updated online using adaptation laws directly derived from theoretical analysis, carried out in this paper. Finally, the proposal has been assessed in simulation relying on a benchmark model of a DC motor

Experimental detection of quantum channel capacities

We present an effcient experimental procedure that certifies non vanishing quantum capacities for qubit noisy channels. Our method is based on the use of a fixed bipartite entangled state, where the system qubit is sent to the channel input. A particular set of local measurements is performed at the channel output and the ancilla qubit mode, obtaining lower bounds to the quantum capacities for any unknown channel with no need of a quantum process tomography. The entangled qubits have a Bell state configuration and are encoded in photon polarization. The lower bounds are found by estimating the Shannon and von Neumann entropies at the output using an optimized basis, whose statistics is obtained by measuring only the three observables $\sigma_{x}\otimes\sigma_{x}$, $\sigma_{y}\otimes\sigma_{y}$ and $\sigma_{z}\otimes\sigma_{z}$.Comment: 5 pages and 3 figures in the principal article, and 4 pages in the supplementary materia

Generating qudits with d=3,4 encoded on two-photon states

We present an experimental method to engineer arbitrary pure states of qudits with d=3,4 using linear optics and a single nonlinear crystal.Comment: 4 pages, 1 eps figure. Minor changes. The title has been changed for publication on Physical Review

Design of a deep neural network-based integral sliding mode control for nonlinear systems under fully unknown dynamics

In this letter a novel deep neural network based integral sliding mode (DNN-ISM) control is proposed for controlling perturbed systems with fully unknown dynamics. In particular, two DNNs with an arbitrary number of hidden layers are exploited to estimate the unknown drift term and the control effectiveness matrix of the system, which are instrumental to design the ISM controller. The DNNs weights are adjusted according to adaptation laws derived directly from Lyapunov stability analysis, and the proposal is satisfactorily assessed in simulation relying on benchmark examples

Hallermann–Streiff syndrome with severe bilateral enophthalmos and radiological evidence of silent brain syndrome: a new congenital silent brain syndrome?

BACKGROUND: We present the first case of a congenital form of silent brain syndrome (SBS) in a young patient affected by Hallermann-Streiff syndrome (HSS) and the surgical management of the associated eyelid anomalies. METHODS: HSS signs were evaluated according to the Francois criteria. Orbital computed tomography (CT) and genetic analysis were performed. An upper eyelid retractor-free recession was performed. Follow-up visits were performed at day 1, weeks 1 and 3, and months 3, 6, 9 (for both eyes), and 12 (for left eye) after surgery. RESULTS: The patient exhibited six of the seven signs of HSS. Orbital CT showed bilateral enophthalmos and upward bowing of the orbital roof with air entrapment under the upper eyelid as previously described for SBS. Genetic analysis showed a 2q polymorphism. During follow-up, the cornea showed absence of epithelial damage and the upper eyelids were lowered symmetrically, with a regular contour. CONCLUSION: Our HSS patient shares features with SBS. We postulate that SBS could include more than one pattern, ie, an acquired form following ventriculoperitoneal shunting and this newly reported congenital form in our HSS patient in whom typical syndromic skull anomalies led to this condition. The surgical treatment has been effective in restoring an appropriate lid level, with good globe apposition and a good cosmetic result

Isotropic phase squeezing and the arrow of time

We prove that isotropic squeezing of the phase is equivalent to reversing the arrow of time.Comment: 8 pages. 2 eps figures. elsart styl