Shifting network tomography toward a practical goal

Boolean Inference makes it possible to observe the congestion status of end-to-end paths and infer, from that, the congestion status of individual network links. In principle, this can be a powerful monitoring tool, in scenarios where we want to monitor a network without having direct access to its links. We consider one such real scenario: a Tier-1 ISP operator wants to monitor the congestion status of its peers. We show that, in this scenario, Boolean Inference cannot be solved with enough accuracy to be useful; we do not attribute this to the limitations of particular algorithms, but to the fundamental difficulty of the Inference problem. Instead, we argue that the "right" problem to solve, in this context, is compute the probability that each set of links is congested (as opposed to try to infer which particular links were congested when). Even though solving this problem yields less information than provided by Boolean Inference, we show that this information is more useful in practice, because it can be obtained accurately under weaker assumptions than typically required by Inference algorithms and more challenging network conditions (link correlations, non-stationary network dynamics, sparse topologies). © 2011 ACM

Implementation of the Five Qubit Error Correction Benchmark

The smallest quantum code that can correct all one-qubit errors is based on five qubits. We experimentally implemented the encoding, decoding and error-correction quantum networks using nuclear magnetic resonance on a five spin subsystem of labeled crotonic acid. The ability to correct each error was verified by tomography of the process. The use of error-correction for benchmarking quantum networks is discussed, and we infer that the fidelity achieved in our experiment is sufficient for preserving entanglement.Comment: 6 pages with figure

The Fault-Finding Capacity of the Cable Network When Measured Along Complete Paths

We look into whether or not it is possible to find the exact location of a broken node in a communication network by using the binary state (normal or failed) of each link in the chain. To find out where failures are in a group of nodes of interest, it is necessary to link the different states of the routes to the different failures at the nodes. Due to the large number of possible node failures that need to be listed, it may be hard to check this condition on large networks. The first important thing we've added is a set of criteria that are both enough and necessary for testing in polynomial time whether or not a set of nodes has a limited number of failures. As part of our requirements, we take into account not only the architecture of the network but also the positioning of the monitors. We look at three different types of probing methods. Each one is different depending on the nature of the measurement paths, which can be random, controlled but not cycle-free, or uncontrolled (depending on the default routing protocol). Our second contribution is an analysis of the greatest number of failures (anywhere in the network) for which failures within a particular node set can be uniquely localized and the largest node set within which failures can be uniquely localized under a given constraint on the overall number of failures in the network. Both of these results are based on the fact that failures can be uniquely localized only if there is a constraint on the overall number of failures. When translated into functions of a per-node attribute, the sufficient and necessary conditions that came before them make it possible for an efficient calculation of both measurements

The motivation and pleasure dimension of negative symptoms: neural substrates and behavioral outputs.

A range of emotional and motivation impairments have long been clinically documented in people with schizophrenia, and there has been a resurgence of interest in understanding the psychological and neural mechanisms of the so-called "negative symptoms" in schizophrenia, given their lack of treatment responsiveness and their role in constraining function and life satisfaction in this illness. Negative symptoms comprise two domains, with the first covering diminished motivation and pleasure across a range of life domains and the second covering diminished verbal and non-verbal expression and communicative output. In this review, we focus on four aspects of the motivation/pleasure domain, providing a brief review of the behavioral and neural underpinnings of this domain. First, we cover liking or in-the-moment pleasure: immediate responses to pleasurable stimuli. Second, we cover anticipatory pleasure or wanting, which involves prediction of a forthcoming enjoyable outcome (reward) and feeling pleasure in anticipation of that outcome. Third, we address motivation, which comprises effort computation, which involves figuring out how much effort is needed to achieve a desired outcome, planning, and behavioral response. Finally, we cover the maintenance emotional states and behavioral responses. Throughout, we consider the behavioral manifestations and brain representations of these four aspects of motivation/pleasure deficits in schizophrenia. We conclude with directions for future research as well as implications for treatment

Quantum metrology and its application in biology

Quantum metrology provides a route to overcome practical limits in sensing devices. It holds particular relevance to biology, where sensitivity and resolution constraints restrict applications both in fundamental biophysics and in medicine. Here, we review quantum metrology from this biological context, focusing on optical techniques due to their particular relevance for biological imaging, sensing, and stimulation. Our understanding of quantum mechanics has already enabled important applications in biology, including positron emission tomography (PET) with entangled photons, magnetic resonance imaging (MRI) using nuclear magnetic resonance, and bio-magnetic imaging with superconducting quantum interference devices (SQUIDs). In quantum metrology an even greater range of applications arise from the ability to not just understand, but to engineer, coherence and correlations at the quantum level. In the past few years, quite dramatic progress has been seen in applying these ideas into biological systems. Capabilities that have been demonstrated include enhanced sensitivity and resolution, immunity to imaging artifacts and technical noise, and characterization of the biological response to light at the single-photon level. New quantum measurement techniques offer even greater promise, raising the prospect for improved multi-photon microscopy and magnetic imaging, among many other possible applications. Realization of this potential will require cross-disciplinary input from researchers in both biology and quantum physics. In this review we seek to communicate the developments of quantum metrology in a way that is accessible to biologists and biophysicists, while providing sufficient detail to allow the interested reader to obtain a solid understanding of the field. We further seek to introduce quantum physicists to some of the central challenges of optical measurements in biological science.Comment: Submitted review article, comments and suggestions welcom

SRLG: To Finding the Packet Loss in Peer to Peer Network

We introduce the ideas of watching methods (MPs) and watching cycles (MCs) for distinctive localization of shared risk connected cluster (SRLG) failures in all-optical networks. An SRLG failure causes multiple links to interrupt at the same time due to the failure of a typical resource. MCs (MPs) begin and finish at identical (distinct) watching location(s).They are constructed such any SRLG failure leads to the failure of a unique combination of methods and cycles. We tend to derive necessary and ample conditions on the set of MCs and MPs required for localizing associate single SRLG failure in a capricious graph. We determine the minimum range of optical splitters that area unit needed to watch all SRLG failures within the network. Extensive simulations area unit won�t to demonstrate the effectiveness of the planned watching technique

Focal Spot, Spring/Summer 1985

https://digitalcommons.wustl.edu/focal_spot_archives/1040/thumbnail.jp

Attentional Set-Shifting Deficit in Parkinson’s Disease Is Associated with Prefrontal Dysfunction: An FDG-PET Study

The attentional set-shifting deficit that has been observed in Parkinson’s disease (PD) has long been considered neuropsychological evidence of the involvement of meso-prefrontal and prefrontal-striatal circuits in cognitive flexibility. However, recent studies have suggested that non-dopaminergic, posterior cortical pathologies may also contribute to this deficit. Although several neuroimaging studies have addressed this issue, the results of these studies were confounded by the use of tasks that required other cognitive processes in addition to set-shifting, such as rule learning and working memory. In this study, we attempted to identify the neural correlates of the attentional set-shifting deficit in PD using a compound letter task and 18F-fluoro-deoxy-glucose (FDG) positron emission tomography during rest. Shift cost, which is a measure of attentional set-shifting ability, was significantly correlated with hypometabolism in the right dorsolateral prefrontal cortex, including the putative human frontal eye field. Our results provide direct evidence that dysfunction in the dorsolateral prefrontal cortex makes a primary contribution to the attentional set-shifting deficit that has been observed in PD patients