Data-driven Localization and Estimation of Disturbance in the Interconnected Power System

Identifying the location of a disturbance and its magnitude is an important component for stable operation of power systems. We study the problem of localizing and estimating a disturbance in the interconnected power system. We take a model-free approach to this problem by using frequency data from generators. Specifically, we develop a logistic regression based method for localization and a linear regression based method for estimation of the magnitude of disturbance. Our model-free approach does not require the knowledge of system parameters such as inertia constants and topology, and is shown to achieve highly accurate localization and estimation performance even in the presence of measurement noise and missing data

Maximizing Reliability in WDM Networks Through Lightpath Routing

We study the reliability maximization problem in wavelength division multiplexing (WDM) networks with random link failures. Reliability in these networks is defined as the probability that the logical network is connected, and it is determined by the underlying lightpath routing, network topologies, and the link failure probability. By introducing the notion of lexicographical ordering for lightpath routings, we characterize precise optimization criteria for maximum reliability in the low failure probability regime. Based on the optimization criteria, we develop lightpath routing algorithms that maximize the reliability, and logical topology augmentation algorithms for further improving reliability. We also study the reliability maximization problem in the high failure probability regime.National Science Foundation (U.S.) (Grant CNS-0830961)National Science Foundation (U.S.) (Grant CNS-1017800)United States. Defense Threat Reduction Agency (Grant HDTRA1-07-1-0004)United States. Defense Threat Reduction Agency (Grant HDTRA-09-1-0050

Maximizing Reliability in WDM Networks through Lightpath Routing

We study the reliability maximization problem in WDM networks with random link failures. Reliability in these networks is defined as the probability that the logical network is connected, and it is determined by the underlying lightpath routing and the link failure probability. We show that in general the optimal lightpath routing depends on the link failure probability, and characterize the properties of lightpath routings that maximize the reliability in different failure probability regimes. In particular, we show that in the low failure probability regime, maximizing the “cross-layer” min cut of the (layered) network maximizes reliability, whereas in the high failure probability regime, minimizing the spanning tree of the network maximizes reliability. Motivated by these results, we develop lightpath routing algorithms for reliability maximization.National Science Foundation (U.S.) (Grant CNS-0830961)National Science Foundation (U.S.) (Grant CNS-1017800)United States. Defense Threat Reduction Agency (Grant HDTRA1-07-1-0004)United States. Defense Threat Reduction Agency (Grant HDTRA-09-1-0050

Chronic rhinosinusitis with nasal polyps in older adults : clinical presentation, pathophysiology, and comorbidity

Purpose of Review Chronic rhinosinusitis and nasal polyps (CRSwNP) is a common condition that significantly affects patients' life. This work aims to provide an up-to-date overview of CRSwNP in older adults, focusing on its aging-related clinical presentations, pathophysiology, and comorbidity associations including asthma. Recent Findings Recent large population-based studies using nasal endoscopy have shown that CRSwNP is a mostly late-onset disease. Age-related changes in physiologic functions, including nasal epithelial barrier dysfunction, may underlie the incidence and different clinical presentations of CRSwNP in older adults. However, there is still a paucity of evidence on the effect of aging on phenotypes and endotypes of CRSwNP. Meanwhile, late-onset asthma is a major comorbid condition in patients with CRSwNP; they frequently present with type 2 inflammatory signatures that are refractory to conventional treatments when they are comorbid. However, as they are more commonly non-atopic, causative factors other than classical atopic sensitization, such as Staphylococcus aureus specific IgE sensitization, are suggested to drive the type 2 inflammation. There are additional comorbidity associations in older patients with CRSwNP, including those with chronic otitis media and head and neck malignancy. Age is a major determinant for the incidence and clinical presentations of CRSwNP. Given the heterogeneity in phenotypes and endotypes, longitudinal investigations are warranted to elucidate the effects of aging on CRSwNP

Survivable paths in multilayer networks

We consider the problem of protection in multilayer networks. In single-layer networks, a pair of disjoint paths can be used to provide protection for a source-destination pair. However, this approach cannot be directly applied to layered networks where disjoint paths may not always exist. In this paper, we take a new approach which is based on finding a set of paths that may not be disjoint but together will survive any single physical link failure. We consider the problem of finding the minimum number of survivable paths. In particular, we focus on two versions of this problem: one where the length of a path is restricted, and the other where the number of paths sharing a fiber is restricted. We prove that in general, finding the minimum survivable path set is NP-hard, whereas both of the restricted versions of the problem can be solved in polynomial time. We formulate the problems as Integer Linear Programs (ILPs), and use these formulations to develop heuristics and approximation algorithms.National Science Foundation (U.S.) (NSF grant CNS-0830961)National Science Foundation (U.S.) (NSF grant CNS-1017800)United States. Defense Threat Reduction Agency (grant HDTRA-09-1-005)United States. Defense Threat Reduction Agency (grant HDTRA1-07-1-0004

A robust optimization approach to backup network design with random failures

This paper presents a scheme in which a dedicated backup network is designed to provide protection from random link failures. Upon a link failure in the primary network, traffic is rerouted through a preplanned path in the backup network. We introduce a novel approach for dealing with random link failures, in which probabilistic survivability guarantees are provided to limit capacity over-provisioning. We show that the optimal backup routing strategy in this respect depends on the reliability of the primary network. Specifically, as primary links become less likely to fail, the optimal backup networks employ more resource sharing amongst backup paths. We apply results from the field of robust optimization to formulate an ILP for the design and capacity provisioning of these backup networks. We then propose a simulated annealing heuristic to solve this problem for largescale networks, and present simulation results that verify our analysis and approach.National Science Foundation (U.S.) (grant CNS-0626781)National Science Foundation (U.S.) (grant CNS-0830961)United States. Defense Threat Reduction Agency (grant HDTRA1-07-1-0004)United States. Defense Threat Reduction Agency (grant HDTRA-09-1-005

Mycotoxin production of Alternaria strains isolated from Korean barley grains determined by LC-MS/MS

Twenty-four Alternaria strains were isolated from barley grain samples. These strains were screened for the production of mycotoxins on rice medium using thin layer chromatography. All 24 strains produced at least one of the five mycotoxins (ALT, AOH, ATX-I, AME, and TeA). Three representative strains, namely EML-BLDF1-4, EML-BLDF1-14, and EML-BLDF1-18, were further analyzed using a new LC–MS/MS-based mycotoxin quantification method. This method was used to detect and quantify Alternaria mycotoxins. We used positive ion electrospray mass spectrometry with multiple reaction mode (MRM) for the simultaneous quantification of various Alternaria mycotoxins produced by these strains. Five Alternaria toxins (ALT, ATX-I, AOH, AME, and TeA) were detected and quantified. Sample preparation included methanol extraction, concentration, and injection into LC–MS/MS. Limit of detection ranged from 0.13 to 4 μg/mL and limit of quantification ranged from 0.25 to 8 μg/mL