University of Cagliari

About: University of Cagliari is a education organization based out in Cagliari, Italy. It is known for research contribution in the topics: Population & Dopamine. The organization has 11029 authors who have published 29046 publications receiving 771023 citations. The organization is also known as: Università degli Studi di Cagliari & Universita degli Studi di Cagliari.

Endocannabinoids Mediate Presynaptic Inhibition of Glutamatergic Transmission in Rat Ventral Tegmental Area Dopamine Neurons through Activation of CB1 Receptors

Abstract: The endogenous cannabinoid system has been shown to play a crucial role in controlling neuronal excitability and synaptic transmission. In this study we investigated the effects of a cannabinoid receptor (CB-R) agonist WIN 55,212-2 (WIN) on excitatory synaptic transmission in the rat ventral tegmental area (VTA). Whole-cell patch clamp recordings were performed from VTA dopamine (DA) neurons in an in vitro slice preparation. WIN reduced both NMDA and AMPA EPSCs, as well as miniature EPSCs (mEPSCs), and increased the paired-pulse ratio, indicating a presynaptic locus of its action. We also found that WIN-induced effects were dose-dependent and mimicked by the CB1-R agonist HU210. Furthermore, two CB1-R antagonists, AM281 and SR141716A, blocked WIN-induced effects, suggesting that WIN modulates excitatory synaptic transmission via activation of CB1-Rs. Our additional finding that both AM281 and SR141716A per se increased NMDA EPSCs suggests that endogenous cannabinoids, released from depolarized postsynaptic neurons, might act retrogradely on presynaptic CB1-Rs to suppress glutamate release. Hence, we report that a type of synaptic modulation, previously termed depolarization-induced suppression of excitation (DSE), is present also in the VTA as a calcium-dependent phenomenon, blocked by both AM281 and SR141716A, and occluded by WIN. Importantly, DSE was partially blocked by the D2DA antagonist eticlopride and enhanced by the D2DA agonist quinpirole without changing the presynaptic cannabinoid sensitivity. These results indicate that the two pathways work in a cooperative manner to release endocannabinoids in the VTA, where they play a role as retrograde messengers for DSE via CB1-Rs.

A Survey of Petri Net Methods for Controlled Discrete EventSystems

Abstract: This paper surveys recent research on the application of Petri net models to the analysis and synthesis of controllers for discrete event systems. Petri nets have been used extensively in applications such as automated manufacturing, and there exists a large body of tools for qualitative and quantitative analysis of Petri nets. The goal of Petri net research in discrete event systems is to exploit the structural properties of Petri net models in computationally efficient algorithms for computing controls. We present an overview of the various models and problems formulated in the literature focusing on two particular models, the controlled Petri nets and the labeled nets. We describe two basic approaches for controller synthesis, based on state feedback and event feedback. We also discuss two efficient techniques for the on-line computation of the control law, namely the linear integer programming approach which takes advantage of the linear structure of the Petri net state transition equation, and path-based algorithms which take advantage of the graphical structure of Petri net models. Extensions to timed models are briefly described. The paper concludes with a discussion of directions for future research.

RAISE: a raw images dataset for digital image forensics

Abstract: Digital forensics is a relatively new research area which aims at authenticating digital media by detecting possible digital forgeries. Indeed, the ever increasing availability of multimedia data on the web, coupled with the great advances reached by computer graphical tools, makes the modification of an image and the creation of visually compelling forgeries an easy task for any user. This in turns creates the need of reliable tools to validate the trustworthiness of the represented information. In such a context, we present here RAISE, a large dataset of 8156 high-resolution raw images, depicting various subjects and scenarios, properly annotated and available together with accompanying metadata. Such a wide collection of untouched and diverse data is intended to become a powerful resource for, but not limited to, forensic researchers by providing a common benchmark for a fair comparison, testing and evaluation of existing and next generation forensic algorithms. In this paper we describe how RAISE has been collected and organized, discuss how digital image forensics and many other multimedia research areas may benefit of this new publicly available benchmark dataset and test a very recent forensic technique for JPEG compression detection.

Elastic properties of hydrogenated graphene

Abstract: There exist three conformers of hydrogenated graphene, referred to as chair-, boat-, or washboard-graphane. These systems have a perfect two-dimensional periodicity mapped onto the graphene scaffold but they are characterized by a $s{p}^{3}$ orbital hybridization, have different crystal symmetry, and otherwise behave upon loading. By first-principles calculations we determine their structural and phonon properties, as well as we establish their relative stability. Through continuum elasticity we define a simulation protocol addressed to measure by a computer experiment their linear and nonlinear elastic moduli and we actually compute them by first principles. We argue that all graphane conformers respond to any arbitrarily oriented extension with a much smaller lateral contraction than the one calculated for graphene. Furthermore, we provide evidence that boat-graphane has a small and negative Poisson ratio along the armchair and zigzag principal directions of the carbon honeycomb lattice (axially auxetic elastic behavior). Moreover, we show that chair-graphane admits both softening and hardening hyperelasticity, depending on the direction of applied load.