Structural transition in interdependent networks with regular interconnections

Networks are often made up of several layers that exhibit diverse degrees of interdependencies. A multilayer interdependent network consists of a set of graphs $G$ that are interconnected through a weighted interconnection matrix $B$, where the weight of each inter-graph link is a non-negative real number $p$. Various dynamical processes, such as synchronization, cascading failures in power grids, and diffusion processes, are described by the Laplacian matrix $Q$ characterizing the whole system. For the case in which the multilayer graph is a multiplex, where the number of nodes in each layer is the same and the interconnection matrix $B=pI$, being $I$ the identity matrix, it has been shown that there exists a structural transition at some critical coupling, $p^*$. This transition is such that dynamical processes are separated into two regimes: if $p > p^*$, the network acts as a whole; whereas when $p<p^*$, the network operates as if the graphs encoding the layers were isolated. In this paper, we extend and generalize the structural transition threshold $p^*$ to a regular interconnection matrix $B$ (constant row and column sum). Specifically, we provide upper and lower bounds for the transition threshold $p^*$ in interdependent networks with a regular interconnection matrix $B$ and derive the exact transition threshold for special scenarios using the formalism of quotient graphs. Additionally, we discuss the physical meaning of the transition threshold $p^*$ in terms of the minimum cut and show, through a counter-example, that the structural transition does not always exist. Our results are one step forward on the characterization of more realistic multilayer networks and might be relevant for systems that deviate from the topological constrains imposed by multiplex networks.Comment: 13 pages, APS format. Submitted for publicatio

A network approach for power grid robustness against cascading failures

Cascading failures are one of the main reasons for blackouts in electrical power grids. Stable power supply requires a robust design of the power grid topology. Currently, the impact of the grid structure on the grid robustness is mainly assessed by purely topological metrics, that fail to capture the fundamental properties of the electrical power grids such as power flow allocation according to Kirchhoff's laws. This paper deploys the effective graph resistance as a metric to relate the topology of a grid to its robustness against cascading failures. Specifically, the effective graph resistance is deployed as a metric for network expansions (by means of transmission line additions) of an existing power grid. Four strategies based on network properties are investigated to optimize the effective graph resistance, accordingly to improve the robustness, of a given power grid at a low computational complexity. Experimental results suggest the existence of Braess's paradox in power grids: bringing an additional line into the system occasionally results in decrease of the grid robustness. This paper further investigates the impact of the topology on the Braess's paradox, and identifies specific sub-structures whose existence results in Braess's paradox. Careful assessment of the design and expansion choices of grid topologies incorporating the insights provided by this paper optimizes the robustness of a power grid, while avoiding the Braess's paradox in the system.Comment: 7 pages, 13 figures conferenc

A Topological Investigation of Phase Transitions of Cascading Failures in Power Grids

Cascading failures are one of the main reasons for blackouts in electric power transmission grids. The economic cost of such failures is in the order of tens of billion dollars annually. The loading level of power system is a key aspect to determine the amount of the damage caused by cascading failures. Existing studies show that the blackout size exhibits phase transitions as the loading level increases. This paper investigates the impact of the topology of a power grid on phase transitions in its robustness. Three spectral graph metrics are considered: spectral radius, effective graph resistance and algebraic connectivity. Experimental results from a model of cascading failures in power grids on the IEEE power systems demonstrate the applicability of these metrics to design/optimize a power grid topology for an enhanced phase transition behavior of the system

SARS-CoV2 (COVID-19) infection: is fetal surgery in times of national disasters reasonable?

Even though the global COVID‐19 pandemic may affect how medical care is delivered in general, most countries try to maintain steady access for women to routine pregnancy care, including fetal anomaly screening. This means that, also during this pandemic, fetal anomalies will be detected, and that discussions regarding invasive genetic testing and possibly fetal therapy will need to take place. For patients, concerns about Severe Acute Respiratory Syndrome‐Corona Virus 2 will add to the anxiety caused by the diagnosis of a serious fetal anomaly. Yet, also for fetal medicine teams the situation gets more complex as they must weigh up the risks and benefits to the fetus as well as the mother, while managing a changing evidence base and logistic challenges in their healthcare system

Epidemic processes in complex networks

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.Comment: 62 pages, 15 figures, final versio

República: Año III Número 387 - (14/11/33)

PURPOSE OF REVIEW: The purpose of this study was to investigate the association of 26 inflammatory biomarkers (acute phase proteins, cytokines, chemokines) and renal markers with coronary lipid core burden index (LCBI) assessed by near-infrared spectroscopy (NIRS) imaging, as well as the association of these biomarkers with long-term cardiovascular outcome. RECENT FINDINGS: NIRS-derived LCBI has recently been shown to be an independent predictor of major adverse cardiac events (MACE). However, studies on the association between circulating biomarkers and NIRS-derived characteristics have not yet been performed. Between 2008 and 2011, 581 patients underwent diagnostic coronary angiography or percutaneous coronary intervention for stable angina pectoris or acute coronary syndrome (ACS). NIRS of a non-culprit vessel was performed in a subset of 203 patients. In multivariable analyses, TNF-alpha tended to be associated with higher LCBI (beta 0.088 ln (pg/ml) increase per unit LCBI; 95% CI 0.000-0.177, p = 0.05) after adjustment for clinical characteristics. However, this association did not persist after Bonferroni correction (statistical threshold 0.0019). Major adverse cardiac events (MACE) were registered in 581 patients during a median follow-up time of 4.7 years (IQR: [4.2-5.6] years). After adjustment for clinical characteristics and Bonferroni correction, IL-8 (HR 1.60; 95% CI [1.18-2.17] per ln (pg/ml), p = 0.002) was borderline associated with MACE and significantly associated with all-cause mortality or ACS (HR 1.75; 95% CI [1.24-2.48] per ln (pg/ml), p = 0.0015). In conclusion, we found that IL-8 was independently associated with clinical outcome, but altogether, the multiplex panel we investigated here did not render a useful blood biomarker of high LCBI

Outcome predictors for maternal red blood cell alloimmunisation with anti-K and anti-D managed with intrauterine blood transfusion

Red blood cell (RBC) alloimmunisation with anti-D and anti-K comprise the majority of cases of fetal haemolytic disease requiring intrauterine red cell transfusion (IUT). Few studies have investigated which haematological parameters can predict adverse fetal or neonatal outcomes. The aim of the present study was to identify predictors of adverse outcome, including preterm birth, intrauterine fetal demise (IUFD), neonatal death (NND) and/or neonatal transfusion. We reviewed the records of all pregnancies alloimmunised with anti-K and anti-D, requiring IUT over 27 years at a quaternary fetal centre. We reviewed data for 128 pregnancies in 116 women undergoing 425 IUTs. The median gestational age (GA) at first IUT was significantly earlier for anti-K than for anti-D (24·3 vs. 28·7 weeks, P = 0·004). Women with anti-K required more IUTs than women with anti-D (3·84 vs. 3·12 mean IUTs, P = 0·036) and the fetal haemoglobin (Hb) at first IUT was significantly lower (51.0 vs. 70.5 g/l, P = 0·001). The mean estimated daily decrease in Hb did not differ between the two groups. A greater number of IUTs and a slower daily decrease in Hb (g/l/day) between first and second IUTs were predictive of a longer period in utero. Earlier GA at first IUT and a shorter interval from the first IUT until delivery predicted IUFD/NND. Earlier GA and lower Hb at first IUT significantly predicted need for phototherapy and/or blood product use in the neonate. In the anti-K group, a greater number of IUTs was required in women with a higher titre. Furthermore, the higher the titre, the earlier the GA at which an IUT was required in both groups. The rate of fall in fetal Hb between IUTs decreased, as the number of transfusions increased. Our present study identified pregnancies at considerable risk of an unfavourable outcome with anti-D and anti-K RBC alloimmunisation. Identifying such patients can guide pregnancy management, facilitates patient counselling, and can optimise resource use. Prospective studies can also incorporate these characteristics, in addition to laboratory markers, to further identify and improve the outcomes of these pregnancies

Multi-Layer Cyber-Physical Security and Resilience for Smart Grid

The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision theory as a tool to model the interactions among system components and the interaction between attackers and the system. We discuss game-theoretic applications and challenges in the design of cross-layer robust and resilient controller, secure network routing protocol at the data communication and networking layers, and the challenges of the information security at the management layer of the grid. The chapter will discuss the future directions of using game-theoretic tools in addressing multi-layer security issues in the smart grid.Comment: 16 page