Metastability and instability in holographic gauge theories

We review and extend previous results regarding the stability and thermodynamics of Anti-de Sitter (AdS) spacetime at finite temperature. Using a combination of analytic and numerical techniques, we compute the energy, temperature, and entropy of perfect fluid stars in asymptotically AdS spacetimes. We find that at sufficiently high temperature (in the canonical ensemble) or energy (in the microcanonical ensemble) these configurations develop dynamical instabilities, which presumably lead to the formation of a black hole. We extend our analysis to the case of $AdS \times S$ compactifications stabilized by flux (such as those that arise in supergravity and string theory), and find that the inclusion of the sphere does not substantially alter these results. We then map out the phase structure of these theories in the canonical and microcanonical ensembles, paying attention to inequivalence of these ensembles for global anti-de Sitter space. With a certain scaling limit, the critical temperature can be parametrically lower than the string temperature, so that supergravity is a good description at the instability point. We comment on the implications of this for the unitarity of black holes.Comment: 39 pages, 13 figure

Analyzing synchronized clusters in neuron networks

The presence of synchronized clusters in neuron networks is a hallmark of information transmission and processing. Common approaches to study cluster synchronization in networks of coupled oscillators ground on simplifying assumptions, which often neglect key biological features of neuron networks. Here we propose a general framework to study presence and stability of synchronous clusters in more realistic models of neuron networks, characterized by the presence of delays, different kinds of neurons and synapses. Application of this framework to two examples with different size and features (the directed network of the macaque cerebral cortex and the swim central pattern generator of a mollusc) provides an interpretation key to explain known functional mechanisms emerging from the combination of anatomy and neuron dynamics. The cluster synchronization analysis is carried out also by changing parameters and studying bifurcations. Despite some modeling simplifications in one of the examples, the obtained results are in good agreement with previously reported biological data

Blade loss transient dynamics analysis, volume 2. Task 2: Theoretical and analytical development. Task 3: Experimental verification

The component element method was used to develop a transient dynamic analysis computer program which is essentially based on modal synthesis combined with a central, finite difference, numerical integration scheme. The methodology leads to a modular or building-block technique that is amenable to computer programming. To verify the analytical method, turbine engine transient response analysis (TETRA), was applied to two blade-out test vehicles that had been previously instrumented and tested. Comparison of the time dependent test data with those predicted by TETRA led to recommendations for refinement or extension of the analytical method to improve its accuracy and overcome its shortcomings. The development of working equations, their discretization, numerical solution scheme, the modular concept of engine modelling, the program logical structure and some illustrated results are discussed. The blade-loss test vehicles (rig full engine), the type of measured data, and the engine structural model are described

Co-design of a controller and its digital implementation: the MOBY-DIC2 toolbox for embedded model predictive control

Several software tools are available in the literature for the design and embedded implementation of linear model predictive control (MPC), both in its implicit and explicit (either exact or approximate) forms. Most of them generate C code for easy implementation on a microcontroller, and the others can convert the C code into hardware description language code for implementation on a field programmable gate array (FPGA). However, a unified tool allowing one to generate efficient embedded MPC for an FPGA, starting from the definition of the plant and its constraints, was still missing. The MOBY-DIC2 toolbox described in this brief bridges this gap. To illustrate its functionalities, the tool is exploited to embed the controller and observer for a real buck power converter in an FPGA. This implementation achieves a latency of about 30 µs with the implicit controller and 240 μs with the approximate explicit controller

Maxwell-Chern-Simons Theory With Boundary

The Maxwell-Chern-Simons (MCS) theory with planar boundary is considered. The boundary is introduced according to Symanzik's basic principles of locality and separability. A method of investigation is proposed, which, avoiding the straight computation of correlators, is appealing for situations where the computation of propagators, modified by the boundary, becomes quite complex. For MCS theory, the outcome is that a unique solution exists, in the form of chiral conserved currents, satisfying a Kac-Moody algebra, whose central charge does not depend on the Maxwell term.Comment: 30 page

The Butterfly Fauna Of The Italian Maritime Alps:Results Of The «Edit» Project

Bonelli, Simona, Barbero, Francesca, Casacci, Luca Pietro, Cerrato, Cristiana, Balletto, Emilio (2015): The butterfly fauna of the Italian Maritime Alps: results of the EDIT project. Zoosystema 37 (1): 139-167, DOI: 10.5252/z2015n1a6, URL: http://dx.doi.org/10.5252/z2015n1a

Accurate and Fast Simulation of Channel Noise in Conductance-Based Model Neurons by Diffusion Approximation

Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically detailed model neurons calls for the availability of fast numerical methods. In fact, exact techniques employ the microscopic simulation of the random opening and closing of individual ion channels, usually based on Markov models, whose computational loads are prohibitive for next generation massive computer models of the brain. In this work, we operatively define a procedure for translating any Markov model describing voltage- or ligand-gated membrane ion-conductances into an effective stochastic version, whose computer simulation is efficient, without compromising accuracy. Our approximation is based on an improved Langevin-like approach, which employs stochastic differential equations and no Montecarlo methods. As opposed to an earlier proposal recently debated in the literature, our approximation reproduces accurately the statistical properties of the exact microscopic simulations, under a variety of conditions, from spontaneous to evoked response features. In addition, our method is not restricted to the Hodgkin-Huxley sodium and potassium currents and is general for a variety of voltage- and ligand-gated ion currents. As a by-product, the analysis of the properties emerging in exact Markov schemes by standard probability calculus enables us for the first time to analytically identify the sources of inaccuracy of the previous proposal, while providing solid ground for its modification and improvement we present here