Intentional islanding of a power system can be an emergency response for isolating failures that might propagate and lead to major disturbances. Some of the islanding techniques suggested previously ...do not consider the power flow model; others are designed to minimize load shedding only within the islands. Often these techniques are computationally expensive. We aim to find approaches to partition power grids into islands to minimize the load shedding not only in the region where the failures start, but also in the topological complement of the region. We propose a new constraint programming formulation for optimal islanding in power grid networks. This technique works efficiently for small networks but becomes expensive as size increases. To address the scalability problem, we propose two grid partitioning methods based on modularity, properly modified to take into account the power flow model. They are modifications of the Fast Greedy algorithm and the Bloom algorithm, and are polynomial in running time. We tested these methods on the available IEEE test systems. The Bloom type method is faster than the Fast Greedy type, and can potentially provide results in networks with thousands of nodes. Our methods provide solutions which retain at least 40–50% of the system load. Overall, our methods efficiently balance load shedding and scalability.
•We present intentional islanding as a mitigation strategy for cascading in power grid.•An optimal islanding technique is presented.•Since the optimization is not scalable two methods from network theory are proposed.•All methods minimize load shedding in island and complement.
Telecommunication networks, as well as other network types, are critical infrastructures where any service disruption has a notable impact on individuals. Hence, studying network dynamics under ...failures or attacks is of paramount importance. In this paper, we assess the robustness of networks with respect to the spread of Susceptible-Infected-Susceptible (SIS) epidemics, using the N-Intertwined Mean-Field Approximation (NIMFA). A classical robustness metric is the NIMFA epidemic threshold, which is inversely proportional to the largest eigenvalue of the adjacency matrix, also called the spectral radius. Besides the NIMFA epidemic threshold, the viral conductance has been proposed as a measure incorporating the average fraction of infected nodes in the steady state for all possible effective infection rates. In general, the viral conductance provides more information about the network’s behavior with respect to virus spreading, however, the full picture is not always necessary. The aim of this paper is to understand when the spectral radius is adequate for reflecting robustness. By analyzing the relationship between spectral radius and viral conductance in several graph classes, we show that the two metrics are highly correlated. We thus conclude that the spectral radius is sufficient to compare the robustness of networks belonging to the same class.
Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required ...for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.
In epidemic modeling, the Susceptible-Alert-Infected-Susceptible (SAIS) model extends the SIS (Susceptible-Infected-Susceptible) model. In the SAIS model, “alert” individuals observe the health ...status of neighbors in their contact network, and as a result, they may adopt a set of cautious behaviors to reduce their infection rate. This alertness, when incorporated in the mathematical model, increases the range of effective/relative infection rates for which initial infections die out. Built upon the SAIS model, this work investigates how information dissemination further increases this range. Information dissemination is realized through an additional network (e.g., an online social network) sharing the contact network nodes (individuals) with different links. These “information links” provide the health status of one individual to all the individuals she is connected to in the information dissemination network. We propose an optimal information dissemination strategy with an index in quadratic form relative to the information dissemination network adjacency matrix and the dominant eigenvector of the contact network. Numerical tools to exactly solve steady state infection probabilities and influential thresholds are developed, providing an evaluative baseline for our information dissemination strategy. We show that monitoring the health status of a small but “central” subgroup of individuals and circulating their incidence information optimally enhances the resilience of the society against infectious diseases. Extensive numerical simulations on a survey–based contact network for a rural community in Kansas support these findings.
Background
Bone metastases are a frequent complication of advanced oncologic disease. Pain associated to bone metastasis is a major cause of morbidity in cancer patients, especially in elderly.
Aims
...The aim of this multicentric retrospective observational study is to evaluate the efficacy of different schedules of radiation therapy in elderly patients in terms of pain relief.
Methods
206 patients over the age of 60 were enrolled in 1 year time for a multicentre retrospective observational study. Patients were treated with palliative purposes for painful bone metastases.
Results
Pain intensity difference (PID) was found in 72% of patients. Reported PID was statistically significant for
p
< 0.01. Pain intensity measured by a point numeric rating scale was statistically significant reduced for
p
< 0.05 by one-fraction regimen compared to other two regimens.
Discussion
In recent years, numerous studies have evaluated the most appropriate regimen of fractionation in individual cases, despite this, a consensus about the best schedule is still debated.
Conclusions
On our analysis, single-fractionation scheme (8 Gy) confirmed to be statistical significant effective in providing pain reduction due to bone metastases. Radiation therapy provides significant pain relief of symptomatic bone metastases, but appropriate radiotherapy scheduled is needed in order to get significant response to treatment. Multidisciplinary approach is warranted to value the balance between the therapeutic objectives and the patient quality of life.
This paper considers the problem of estimating multiple different traffic flows moving on the same physical support from aggregate measurement. This problem is relevant in the area of Internet ...traffic management, in particular for anomaly detections, but it also appears of interest in many other applicative areas. In this paper, two on-line procedures are proposed, characterized by the search of an optimal trade-off between the conflicting requirements of achieving good estimation accuracy and of keeping the measurement costs sufficiently low. The procedures have been tested and validated against real data with satisfactory results.
Various epidemics have arisen in rural locations through human-animal interaction, such as the H1N1 outbreak of 2009. To study the spreading of infectious diseases in rural regions, we have surveyed ...a rural county and its communities, and collected a dataset characterizing the rural population. From the respondents’ answers, we build a social (face-to-face) contact network. With this network, we explore the potential spread of epidemics through a Susceptible-Latent-Infected- Recovered (SLIR) disease model. We simulate an exact model of a stochastic SLIR Poisson process with disease parameters representing several infectious illnesses. To explore an array of potential diseases, we vary the infection rate across the spectrum of outbreaks and quantify the social network susceptibility through the whole spectrum. The extent to which social dynamics can control the spreading process is studied across this disease strength spectrum. We explore two models of a susceptible individual's dynamics in response to infections observed among the individuals in his neighborhood, namely preventive behavior adoption and social distancing. Through extensive simulations, our investigation reveals the potentially powerful impacts of social spontaneous responses in rural settings. We compare the strategies over the spectrum, and demonstrate that behavioral responses are most effective in the intermediate range of infection strengths.
The preemption policy currently in use in MPLS-enabled commercial routers selects LSPs for preemption based only on their priority and holding time. This can lead to waste of resources and excessive ...number of rerouting decisions. In this paper, a new preemption policy is proposed and complemented with an adaptive scheme that aims to minimize rerouting. The new policy combines the three main preemption optimization criteria: number of LSPs to be preempted, priority of the LSPs, and preempted bandwidth. Weights can be configured to stress the desired criteria. The new policy is complemented by an adaptive scheme that selects lower priority LSPs that can afford to have their rate reduced. The selected LSPs will fairly reduce their rate in order to accommodate the new high-priority LSP setup request. Performance comparisons of a nonpreemptive approach, a policy currently in use by commercial routers, and our policies are also investigated.
Managing the bandwidth allocated to a Label Switched Path in MPLS networks plays a major role for provisioning of Quality of Service and efficient use of resources. In doing so, two main contrasting ...factors have to be considered: not only the bandwidth should be adapted to the traffic profile but also the effort for bandwidth renegotiation associated with a variation of the allocated bandwidth should be kept at low levels. In this context, we formulate a problem of optimal LSP bandwidth reservation as the one of minimizing a convex combination of the difference between the assigned bandwidth and the estimated future traffic, and of a measure of the frequency of bandwidth variations. The contribution of this paper is to propose a new method to reserve optimally the bandwidth of an LSP, avoiding an excess of bandwidth renegotiations on the basis of prediction of future traffic, assuming a simple birth-and-death model to describe the traffic dynamics. Whenever the prediction is inaccurate due to unpredictable variations in the characteristics of real traffic, a suitable “emergency procedure” is proposed, which performs a new traffic prediction and a consequent modified bandwidth reservation. Numerical results are presented which show the effectiveness of the method and the achieved performance, both for simulated and real data traffic.
In power system reconfiguration, the status (ON/OFF) of switches are optimized such that maximum power is delivered to loads after the occurrence of a fault. The optimized reconfiguration is achieved ...by prioritizing power delivered to vital loads over semi-vital and nonvital loads. The formulation presented in this paper considers a new balanced hybrid (AC and DC) shipboard power system (SPS). Analysis of the nonconvex reconfiguration formulation is done by an appropriate nonconvex solver and by convex approximation. Unlike the nonconvex solution that is based on branch-and-bound methods, convex approximation significantly reduces complexity. It is shown that for the hybrid SPS reconfiguration problem, low complexity convex approximations are effective in finding optimal solutions. Cumulative distribution function (CDF) of the power delivered to loads is presented to showcase the system robustness against random fault scenarios. A combined objective of maximizing power delivery and minimizing the number of switching actions is included in the analysis. Tradeoff between power delivered and number of switching operations after reconfiguration has been discussed at steady state. A separate analysis is also included to observe the intermediate dynamic switch states while the reconfiguration is in progress to capture the trade-off more prominently.
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