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.

An anorexic lipid mediator regulated by feeding

Abstract: Oleylethanolamide (OEA) is a natural analogue of the endogenous cannabinoid anandamide. Like anandamide, OEA is produced in cells in a stimulus-dependent manner and is rapidly eliminated by enzymatic hydrolysis, suggesting a function in cellular signalling. However, OEA does not activate cannabinoid receptors and its biological functions are still unknown. Here we show that, in rats, food deprivation markedly reduces OEA biosynthesis in the small intestine. Administration of OEA causes a potent and persistent decrease in food intake and gain in body mass. This anorexic effect is behaviourally selective and is associated with the discrete activation of brain regions (the paraventricular hypothalamic nucleus and the nucleus of the solitary tract) involved in the control of satiety. OEA does not affect food intake when injected into the brain ventricles, and its anorexic actions are prevented when peripheral sensory fibres are removed by treatment with capsaicin. These results indicate that OEA is a lipid mediator involved in the peripheral regulation of feeding.

Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning

Abstract: Deep neural networks and machine-learning algorithms are pervasively used in several applications, ranging from computer vision to computer security. In most of these applications, the learning algorithm has to face intelligent and adaptive attackers who can carefully manipulate data to purposely subvert the learning process. As these algorithms have not been originally designed under such premises, they have been shown to be vulnerable to well-crafted, sophisticated attacks, including training-time poisoning and test-time evasion attacks (also known as adversarial examples). The problem of countering these threats and learning secure classifiers in adversarial settings has thus become the subject of an emerging, relevant research field known as adversarial machine learning. The purposes of this tutorial are: (a) to introduce the fundamentals of adversarial machine learning to the security community; (b) to illustrate the design cycle of a learning-based pattern recognition system for adversarial tasks; (c) to present novel techniques that have been recently proposed to assess performance of pattern classifiers and deep learning algorithms under attack, evaluate their vulnerabilities, and implement defense strategies that make learning algorithms more robust to attacks; and (d) to show some applications of adversarial machine learning to pattern recognition tasks like object recognition in images, biometric identity recognition, spam and malware detection.

Elliptic Flow of Charged Particles in Pb-Pb Collisions at root s(NN)=2.76 TeV

Abstract: We report the first measurement of charged particle elliptic flow in Pb-Pb collisions at root s(NN) p = 2.76 TeV with the ALICE detector at the CERN Large Hadron Collider. The measurement is performed in the central pseudorapidity region (vertical bar eta vertical bar < 0.8) and transverse momentum range 0.2 < p(t) < 5.0 GeV/c. The elliptic flow signal v(2), measured using the 4-particle correlation method, averaged over transverse momentum and pseudorapidity is 0.087 +/- 0.002(stat) +/- 0.003(syst) in the 40%-50% centrality class. The differential elliptic flow v(2)(p(t)) reaches a maximum of 0.2 near p(t) = 3 GeV/c. Compared to RHIC Au-Au collisions at root s(NN) = 200 GeV, the elliptic flow increases by about 30%. Some hydrodynamic model predictions which include viscous corrections are in agreement with the observed increase.

European clinical guidelines for hyperkinetic disorder-first upgrade

Abstract: BACKGROUND: The validity of clinical guidelines changes over time, because new evidence-based knowledge and experience develop OBJECTIVE: Hence, the European clinical guidelines on hyperkinetic disorder from 1998 had to be evaluated and modified METHOD: Discussions at the European Network for Hyperkinetic Disorders (EUNETHYDIS) and iterative critique of each clinical analysis Guided by evidence-based information and based on evaluation (rather than metaanalysis) of the scientific evidence a group of child psychiatrists and psychologists from several European countries updated the guidelines of 1998 When reliable information is lacking the group gives a clinical consensus when it could be found among themselves RESULTS: The group presents here a set of recommendations for the conceptualization and management of hyperkinetic disorder and attention deficit/hyperactivity disorder (ADHD) CONCLUSION: A general scheme for practice in Europe could be provided, on behalf of the European Society for Child and Adolescent Psychiatry (ESCAP)