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.

A subjective model for trustworthiness evaluation in the social Internet of Things

Abstract: The integration of social networking concepts into the Internet of Things (IoT) has led to the so called Social Internet of Things (SIoT) paradigm, according to which the objects are capable of establishing social relationships in an autonomous way with respect to their owners. The benefits are those of improving scalability in information/service discovery when the SIoT is made of huge numbers of heterogeneous nodes, similarly to what happens with social networks among humans. In this paper we focus on the problem of understanding how the information provided by the other members of the SIoT has to be processed so as to build a reliable system on the basis of the behavior of the objects. We define a subjective model for the management of trustworthiness which builds upon the solutions proposed for P2P networks. Each node computes the trustworthiness of its friends on the basis of its own experience and on the opinion of the common friends with the potential service providers. We employ a feedback system and we combine the credibility and centrality of the nodes to evaluate the trust level. Preliminary simulations show the benefits of the proposed model towards the isolation of almost any malicious node in the network.

Oxytocin injected into the ventral tegmental area induces penile erection and increases extracellular dopamine in the nucleus accumbens and paraventricular nucleus of the hypothalamus of male rats

Abstract: The neuropeptide oxytocin (20-100 ng), induces penile erection when injected unilaterally into the caudal but not rostral mesencephalic ventral tegmental area (VTA) of male Sprague-Dawley rats. Such pro-erectile effect started 30 min after treatment and was abolished by the prior injection of d(CH2)5Tyr(Me)(2)-Orn(8)-vasotocin (1 microg), an oxytocin receptor antagonist injected into the same caudal ventral tegmental area or of haloperidol (1 microg), a dopamine receptor antagonist, injected either into the nucleus accumbens shell (NAs) or into the paraventricular nucleus of the hypothalamus (PVN) ipsilateral to the injected ventral tegmental area. Penile erection was seen 15 min after the occurrence of, or concomitantly to, an increase in extracellular dopamine and its metabolite 3,4-dihydroxyphenylacetic acid (DOPAC) in the dialysate obtained from the nucleus accumbens or the paraventricular nucleus, which was also abolished by d(CH2)5Tyr(Me)(2)-Orn(8)-vasotocin (1 microg), injected into the ventral tegmental area before oxytocin. In the caudal ventral tegmental area oxytocin-containing axons/fibres (originating from the paraventricular nucleus) appeared to closely contact cell bodies of mesolimbic dopaminergic neurons retrogradely labelled with Fluorogold injected into the nucleus accumbens shell, suggesting that oxytocin effects are mediated by the activation of mesolimbic dopaminergic neurons, followed in turn by that of incerto-hypothalamic dopaminergic neurons impinging on oxytocinergic neurons mediating penile erection. As the stimulation of paraventricular dopamine receptors not only induces penile erection, but also increases mesolimbic dopamine neurotransmission by activating oxytocinergic neurons, these results provide further support for the existence of a neural circuit in which dopamine and oxytocin influence both the consummatory and motivational/rewarding aspects of sexual behaviour.

The Multiple Functions of Hemoglobin

Abstract: The aim of this review is to focus and discuss several parallel biological functions of hemoglobin besides its basic function of oxygen transport. In light of the information present in the literature the following possible physiological roles of hemoglobin are discussed: (1) hemoglobin as molecular heat transducer through its oxygenation-deoxygenation cycle, (2) hemoglobin as modulator of erythrocyte metabolism, (3) hemoglobin oxidation as an onset of erythrocyte senescence, (4) hemoglobin and its implication in genetic resistance to malaria, (5) enzymatic activities of hemoglobin and interactions with drugs, and (6) hemoglobin as source of physiological active catabolites.

The prevention of thalassemia.

Abstract: The thalassemias are among the most common inherited diseases worldwide, affecting individuals originating from the Mediterranean area, Middle East, Transcaucasia, Central Asia, Indian subcontinent, and Southeast Asia. As the diseases require long-term care, prevention of the homozygous state constitutes a major armament in the management. This article discusses the major prevention programs that are set up in many countries in Europe, Asia, and Australia, often drawing from the experience in Sardinia. These comprehensive programs involve carrier detections, molecular diagnostics, genetic counseling, and prenatal diagnosis. Variability of clinical severity can be attributable to interactions with α-thalassemia and mutations that increase fetal productions. Special methods that are currently quite expensive and not widely applicable are preimplantation and preconception diagnosis. The recent successful studies of fetal DNA in maternal plasma may allow future prenatal diagnosis that is noninvasive for the fetus.

Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection

Abstract: To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for malware detection. However, its security against well-crafted attacks has not only been recently questioned, but it has been shown that machine learning exhibits inherent vulnerabilities that can be exploited to evade detection at test time. In other words, machine learning itself can be the weakest link in a security system. In this paper, we rely upon a previously-proposed attack framework to categorize potential attack scenarios against learning-based malware detection tools, by modeling attackers with different skills and capabilities. We then define and implement a set of corresponding evasion attacks to thoroughly assess the security of Drebin, an Android malware detector. The main contribution of this work is the proposal of a simple and scalable secure-learning paradigm that mitigates the impact of evasion attacks, while only slightly worsening the detection rate in the absence of attack. We finally argue that our secure-learning approach can also be readily applied to other malware detection tasks.