Non deterministic Repairable Fault Trees for computing optimal repair strategy

In this paper, the Non deterministic Repairable Fault Tree (NdRFT) formalism is proposed: it allows to model failure modes of complex systems as well as their repair processes. The originality of this formalism with respect to other Fault Tree extensions is that it allows to face repair strategies optimization problems: in an NdRFT model, the decision on whether to start or not a given repair action is non deterministic, so that all the possibilities are left open. The formalism is rather powerful allowing to specify which failure events are observable, whether local repair or global repair can be applied, and the resources needed to start a repair action. The optimal repair strategy can then be computed by solving an optimization problem on a Markov Decision Process (MDP) derived from the NdRFT. A software framework is proposed in order to perform in automatic way the derivation of an MDP from a NdRFT model, and to deal with the solution of the MDP

The Mean Drift: Tailoring the Mean Field Theory of Markov Processes for Real-World Applications

The statement of the mean field approximation theorem in the mean field theory of Markov processes particularly targets the behaviour of population processes with an unbounded number of agents. However, in most real-world engineering applications one faces the problem of analysing middle-sized systems in which the number of agents is bounded. In this paper we build on previous work in this area and introduce the mean drift. We present the concept of population processes and the conditions under which the approximation theorems apply, and then show how the mean drift is derived through a systematic application of the propagation of chaos. We then use the mean drift to construct a new set of ordinary differential equations which address the analysis of population processes with an arbitrary size

A computational approach based on the colored Petri net formalism for studying multiple sclerosis

Multiple Sclerosis (MS) is an immune-mediated inflammatory disease of the Central Nervous System (CNS) which damages the myelin sheath enveloping nerve cells thus causing severe physical disability in patients. Relapsing Remitting Multiple Sclerosis (RRMS) is one of the most common form of MS in adults and is characterized by a series of neurologic symptoms, followed by periods of remission. Recently, many treatments were proposed and studied to contrast the RRMS progression. Among these drugs, daclizumab (commercial name Zinbryta), an antibody tailored against the Interleukin-2 receptor of T cells, exhibited promising results, but its efficacy was accompanied by an increased frequency of serious adverse events. Manifested side effects consisted of infections, encephalitis, and liver damages. Therefore daclizumab has been withdrawn from the market worldwide. Another interesting case of RRMS regards its progression in pregnant women where a smaller incidence of relapses until the delivery has been observed

Increased prevalence of impulse control disorder symptoms in endocrine diseases treated with dopamine agonists: a cross-sectional study

INTRODUCTION: Impulse control disorders (ICDs) have been described as a side effect of dopamine agonists (DAs) in neurological as well as endocrine conditions. Few studies have evaluated the neuropsychological effect of DAs in hyperprolactinemic patients, and these have reported a relationship between DAs and ICDs. Our objective was to screen for ICD symptoms in individuals with DA-treated endocrine conditions. MATERIALS AND METHODS: A cross-sectional analysis was conducted on 132 patients with pituitary disorders treated with DAs (DA exposed), as well as 58 patients with pituitary disorders and no history of DA exposure (non-DA exposed). Participants responded to the full version of the Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s disease (QUIP). RESULTS: Compared with the non-DA-exposed group, a higher prevalence of DA-exposed patients tested positive for symptoms of any ICD or related behavior (52% vs. 31%, p < 0.01), any ICD (46% vs. 24%, p < 0.01), any related behavior (31% vs. 17%, p < 0.05), compulsive sexual behavior (27% vs. 14%, p < 0.04), and punding (20% vs. 7%, p < 0.02) by QUIP. On univariate analysis, DA treatment was associated with a two- to threefold increased risk of any ICD or related behavior [odds ratio (OR) 2.43] and any ICD (OR 2.70). In a multivariate analysis, independent risk factors for any ICD or related behavior were DA use (adjusted OR 2.22) and age (adjusted OR 6.76). Male gender was predictive of the risk of hypersexuality (adjusted OR 3.82). DISCUSSION: Despite the QUIP limitations, a clear sign of increased risk of ICDs emerges in individuals with DA-treated pituitary disorders. Our data contribute to the growing evidence of DA-induced ICDs in endocrine conditions

Multiple sclerosis disease: A computational approach for investigating its drug interactions

Multiple Sclerosis (MS) is a chronic and potentially highly disabling disease that can cause permanent damage and deterioration of the central nervous system. In Europe it is the leading cause of non-traumatic disabilities in young adults, since more than 700,000 EU people suffer from MS. Although recent studies on MS pathophysiology have been performed, providing interesting results, MS remains a challenging disease. In this context, thanks to recent advances in software and hardware technologies, computational models and computer simulations are becoming appealing research tools to support scientists in the study of such disease. Motivated by this consideration, we propose in this paper a new model to study the evolution of MS in silico, and the effects of the administration of the daclizumab drug, taking into account also spatiality and temporality of the involved phenomena. Moreover, we show how the intrinsic symmetries of the model we have developed can be exploited to drastically reduce the complexity of its analysis