14 research outputs found

    Modeling Resilience in Electrical Distribution Networks

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    Electrical distribution networks deliver a fundamental service to citizens. However, they are still highly vulnerable to natural hazards as well as to cyberattacks; therefore, additional commitment and investments are needed to foster their resilience. Toward that, this paper presents and proposes the use of a complex simulation model, called reconfiguration simulator (RecSIM), enabling to evaluate the effectiveness of resilience enhancement strategies for electric distribution networks and the required resources to implement them. The focus is, in particular, on one specific attribute of resilience, namely, the readiness, i.e., the promptness and efficiency to recover the service functionality after a crisis event by managing and deploying the available resources rapidly and effectively. RecSIM allows estimating how and to what extent technological, topological, and management issues might improve electrical distribution networks’ functionality after the occurrence of accidental faults, accounting for interdependency issues and reconfiguration possibilities. The viability of implementing RecSIM on a real and large urban network is showcased in the paper with reference to the study case of the electrical distribution network (EDN) of Rome city

    Cascades in interdependent flow networks

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    In this manuscript, we investigate the abrupt breakdown behavior of coupled distribution grids under load growth. This scenario mimics the ever-increasing customer demand and the foreseen introduction of energy hubs interconnecting the different energy vectors. We extend an analytical model of cascading behavior due to line overloads to the case of interdependent networks and find evidence of first order transitions due to the long-range nature of the flows. Our results indicate that the foreseen increase in the couplings between the grids has two competing effects: on the one hand, it increases the safety region where grids can operate without withstanding systemic failures; on the other hand, it increases the possibility of a joint systems’ failure

    Assortativity Decreases the Robustness of Interdependent Networks

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    It was recently recognized that interdependencies among different networks can play a crucial role in triggering cascading failures and hence system-wide disasters. A recent model shows how pairs of interdependent networks can exhibit an abrupt percolation transition as failures accumulate. We report on the effects of topology on failure propagation for a model system consisting of two interdependent networks. We find that the internal node correlations in each of the two interdependent networks significantly changes the critical density of failures that triggers the total disruption of the two-network system. Specifically, we find that the assortativity (i.e. the likelihood of nodes with similar degree to be connected) within a single network decreases the robustness of the entire system. The results of this study on the influence of assortativity may provide insights into ways of improving the robustness of network architecture, and thus enhances the level of protection of critical infrastructures

    Off-label long acting injectable antipsychotics in real-world clinical practice: a cross-sectional analysis of prescriptive patterns from the STAR Network DEPOT study

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    Introduction Information on the off-label use of Long-Acting Injectable (LAI) antipsychotics in the real world is lacking. In this study, we aimed to identify the sociodemographic and clinical features of patients treated with on- vs off-label LAIs and predictors of off-label First- or Second-Generation Antipsychotic (FGA vs. SGA) LAI choice in everyday clinical practice. Method In a naturalistic national cohort of 449 patients who initiated LAI treatment in the STAR Network Depot Study, two groups were identified based on off- or on-label prescriptions. A multivariate logistic regression analysis was used to test several clinically relevant variables and identify those associated with the choice of FGA vs SGA prescription in the off-label group. Results SGA LAIs were more commonly prescribed in everyday practice, without significant differences in their on- and off-label use. Approximately 1 in 4 patients received an off-label prescription. In the off-label group, the most frequent diagnoses were bipolar disorder (67.5%) or any personality disorder (23.7%). FGA vs SGA LAI choice was significantly associated with BPRS thought disorder (OR = 1.22, CI95% 1.04 to 1.43, p = 0.015) and hostility/suspiciousness (OR = 0.83, CI95% 0.71 to 0.97, p = 0.017) dimensions. The likelihood of receiving an SGA LAI grew steadily with the increase of the BPRS thought disturbance score. Conversely, a preference towards prescribing an FGA was observed with higher scores at the BPRS hostility/suspiciousness subscale. Conclusion Our study is the first to identify predictors of FGA vs SGA choice in patients treated with off-label LAI antipsychotics. Demographic characteristics, i.e. age, sex, and substance/alcohol use co-morbidities did not appear to influence the choice towards FGAs or SGAs. Despite a lack of evidence, clinicians tend to favour FGA over SGA LAIs in bipolar or personality disorder patients with relevant hostility. Further research is needed to evaluate treatment adherence and clinical effectiveness of these prescriptive patterns

    Effect of the interconnected network structure on the epidemic threshold

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    Most real-world networks are not isolated. In order to function fully, they are interconnected with other networks, and this interconnection influences their dynamic processes. For example, when the spread of a disease involves two species, the dynamics of the spread within each species (the contact network) differs from that of the spread between the two species (the interconnected network). We model two generic interconnected networks using two adjacency matrices, A and B, in which A is a 2N×2N matrix that depicts the connectivity within each of two networks of size N, and B a 2N×2N matrix that depicts the interconnections between the two. Using an N-intertwined mean-field approximation, we determine that a critical susceptible-infected-susceptible (SIS) epidemic threshold in two interconnected networks is 1/?1(A+?B), where the infection rate is ? within each of the two individual networks and ?? in the interconnected links between the two networks and ?1(A+?B) is the largest eigenvalue of the matrix A+?B. In order to determine how the epidemic threshold is dependent upon the structure of interconnected networks, we analytically derive ?1(A+?B) using a perturbation approximation for small and large ?, the lower and upper bound for any ? as a function of the adjacency matrix of the two individual networks, and the interconnections between the two and their largest eigenvalues and eigenvectors. We verify these approximation and boundary values for ?1(A+?B) using numerical simulations, and determine how component network features affect ?1(A+?B). We note that, given two isolated networks G1 and G2 with principal eigenvectors x and y, respectively, ?1(A+?B) tends to be higher when nodes i and j with a higher eigenvector component product xiyj are interconnected. This finding suggests essential insights into ways of designing interconnected networks to be robust against epidemics.Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc

    Disease-specific and general health-related quality of life in newly diagnosed prostate cancer patients: The Pros-IT CNR study

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    BACKGROUND: The National Research Council (CNR) prostate cancer monitoring project in Italy (Pros-IT CNR) is an observational, prospective, ongoing, multicentre study aiming to monitor a sample of Italian males diagnosed as new cases of prostate cancer. The present study aims to present data on the quality of life at time prostate cancer is diagnosed. METHODS: One thousand seven hundred five patients were enrolled. Quality of life is evaluated at the time cancer was diagnosed and at subsequent assessments via the Italian version of the University of California Los Angeles-Prostate Cancer Index (UCLA-PCI) and the Short Form Health Survey (SF-12). RESULTS: At diagnosis, lower scores on the physical component of the SF-12 were associated to older ages, obesity and the presence of 3+ moderate/severe comorbidities. Lower scores on the mental component were associated to younger ages, the presence of 3+ moderate/severe comorbidities and a T-score higher than one. Urinary and bowel functions according to UCLA-PCI were generally good. Almost 5% of the sample reported using at least one safety pad daily to control urinary loss; less than 3% reported moderate/severe problems attributable to bowel functions, and sexual function was a moderate/severe problem for 26.7%. Diabetes, 3+ moderate/severe comorbidities, T2 or T3-T4 categories and a Gleason score of eight or more were significantly associated with lower sexual function scores at diagnosis. CONCLUSIONS: Data collected by the Pros-IT CNR study have clarified the baseline status of newly diagnosed prostate cancer patients. A comprehensive assessment of quality of life will allow to objectively evaluate outcomes of different profile of care
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