International sport federations in the world city network

In this article, we analyze the transnational urban geographies produced by international sport federations (ISFs) through their global, regional, and national headquarter locations. Data on the global urban presence of 35 major ISFs are examined through connectivity analysis and principal component analysis. The connectivity analysis reveals the relative dominance of cities in Europe and Pacific Asia, whereby Seoul, Tokyo, Kuala Lumpur, Cairo, and Lausanne stand out. The principal component analysis reveals the main subnetworks produced through ISF location decisions, which includes inter alia a "winter sports subnetwork" centered on Ankara, Belgrade, Helsinki, and Stockholm; an "Olympic subnetwork" centered on Lausanne; and a decentered subnetwork with truly "global sports."

Using Collective Intelligence to Route Internet Traffic

A COllective INtelligence (COIN) is a set of interacting reinforcement learning (RL) algorithms designed in an automated fashion so that their collective behavior optimizes a global utility function. We summarize the theory of COINs, then present experiments using that theory to design COINs to control internet traffic routing. These experiments indicate that COINs outperform all previously investigated RL-based, shortest path routing algorithms.Comment: 7 page

Increasing Awareness of Pharmacologic Interventions for Smoking Cessation

Smoking is a large cause of morbidity and mortality in the healthcare system. Many patients are interested in quitting smoking but have not found an effective strategy that works for them. There have been times when patients have been receptive to a discussion regarding medication assisted cessation but ultimately were not prescribed any medications from their provider. Despite the fact that it has been proven that pharmacotherapy increases the chances of smoking cessation. The goal of this community health project is to create a change within the healthcare system by providing evidenced based recommendations regarding pharmacologic treatment in smoking cessation for both providers and patients to ultimately decrease the burden of smoking within this community

Evaluating a three-dimensional panel of point forecasts : the Bank of England survey of external forecasters

This article provides a first analysis of the forecasts of inflation and GDP growth obtained from the Bank of England's Survey of External Forecasters, considering both the survey average forecasts published in the quarterly Inflation Report, and the individual survey responses, recently made available by the Bank. These comprise a conventional incomplete panel dataset, with an additional dimension arising from the collection of forecasts at several horizons; both point forecasts and density forecasts are collected. The inflation forecasts show good performance in tests of unbiasedness and efficiency, albeit over a relatively calm period for the UK economy, and there is considerable individual heterogeneity. For GDP growth, inaccurate real-time data and their subsequent revisions are seen to cause serious difficulties for forecast construction and evaluation, although the forecasts are again unbiased. There is evidence that some forecasters have asymmetric loss functions

On Expected Value Strong Controllability

The Probabilistic Simple Temporal Network (PSTN) generalizes Simple Temporal Networks with Uncertainty (STNUs) by introducing probability distributions over the timing of uncontrollable timepoints. PSTNs are controllable if there is a strategy to execute the controllable timepoints while bounding the risk of violating any constraint to a small value. If this risk bound can't be satisfied, PSTNs are not considered controllable. We introduce the Expected Value Probabilistic SimpleTemporal Network (EPSTN), which extends PSTNs by including a benefit to the satisfaction of temporal constraints. We study the problem of Expected Value Strong Controllability (EvSC) of EPSTNs, which seeks a schedule maximizing the expected value of satisfied constraints. We solve the EvSC problem by extending a previously developed linear program, combined with search over constraints to violate at execution time. We describe conditions under which the solution to this linear program is the maximum expected value schedule. We then show how to search for constraints to discard, using the linear program at the core of the search. While the general problem is shown to be exponential, we conclude by providing several methods to bound the complexity of search

VERITAS Observations of the Coma Cluster of Galaxies

Clusters of galaxies are one of the few prominent classes of objects predicted to emit gamma rays not yet detected by satellites like EGRET or ground-based Imaging Atmospheric Cherenkov Telescopes (IACTs). The detection of Very High Energy (VHE, E > 100 GeV) gamma rays from galaxy clusters would provide insight into the morphology of non-thermal particles and fields in clusters. VERITAS, an array of four 12-meter diameter IACTs, is ideally situated to observe the massive Coma cluster, one of the best cluster candidates in the Northern Hemisphere. This contribution details the results of VERITAS observations of the Coma cluster of galaxies during the 2007-2008 observing season.Comment: Submitted to Proceedings of "4th Heidelberg International Symposium on High Energy Gamma-Ray Astronomy 2008