Detecting highly overlapping community structure by greedy clique expansion

In complex networks it is common for each node to belong to several communities, implying a highly overlapping community structure. Recent advances in benchmarking indicate that existing community assignment algorithms that are capable of detecting overlapping communities perform well only when the extent of community overlap is kept to modest levels. To overcome this limitation, we introduce a new community assignment algorithm called Greedy Clique Expansion (GCE). The algorithm identifies distinct cliques as seeds and expands these seeds by greedily optimizing a local fitness function. We perform extensive benchmarks on synthetic data to demonstrate that GCE's good performance is robust across diverse graph topologies. Significantly, GCE is the only algorithm to perform well on these synthetic graphs, in which every node belongs to multiple communities. Furthermore, when put to the task of identifying functional modules in protein interaction data, and college dorm assignments in Facebook friendship data, we find that GCE performs competitively.Comment: 10 pages, 7 Figures. Implementation source and binaries available at http://sites.google.com/site/greedycliqueexpansion

Expression of Glutathione-S-Transferase MU 1 (GSTM1) and Glutathione-S-Transferase Theta 1 (GSTT1) in Patients with Aplastic Anemia and Myelodysplastic Syndromes

Aplastic Anemia is a disorder of the hematopoietic bone marrow stem cells that is frequently associated with drug or chemical exposures. Reduced ability to detoxify drugs or chemicals may result in an increased risk of disease. Glutathione S-transferases are Phase II enzymes, which help detoxify xenobiotics. Many patients who have developed aplastic anemia and myelodysplastic syndrome have the null genotype for GSTMI and/or GSTTI. For patients with GSTMI and GSTTI positive genotypes, non-expression of these enzymes may cause an increased risk in developing aplastic anemia or myelodysplastic syndrome. To test whether genotype positive patients have GSTMI or GSTTI null phenotypes, reverse transcription polymerase chain reactions were performed on patients with aplastic anemia or myelodysplastic syndrome that were genotypically positive for GSTMI and/or GSTTI. In GSTMI genotype positive patients, 11.1% showed no detectable gene expression. In 38 patients, genotype GSTTI positive, 15.g% showed no detectable gene expression. In 15 patients whose genotype was GSTMI positive and GSTTI positive, 6.7% had no detectable gene expression for either GSTMI and GSTTI, 13.3% had no gene expression for GSTTI and 0.0% had no gene expression for GSTMI (20.0% without expression total). Patients who develop aplastic anemia and myelodysplastic syndrome may have higher levels of non-expression of the Glutathione S-transferases and may be a factor in these diseases development

Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations

We construct a new framework for accelerating Markov chain Monte Carlo in posterior sampling problems where standard methods are limited by the computational cost of the likelihood, or of numerical models embedded therein. Our approach introduces local approximations of these models into the Metropolis-Hastings kernel, borrowing ideas from deterministic approximation theory, optimization, and experimental design. Previous efforts at integrating approximate models into inference typically sacrifice either the sampler's exactness or efficiency; our work seeks to address these limitations by exploiting useful convergence characteristics of local approximations. We prove the ergodicity of our approximate Markov chain, showing that it samples asymptotically from the \emph{exact} posterior distribution of interest. We describe variations of the algorithm that employ either local polynomial approximations or local Gaussian process regressors. Our theoretical results reinforce the key observation underlying this paper: when the likelihood has some \emph{local} regularity, the number of model evaluations per MCMC step can be greatly reduced without biasing the Monte Carlo average. Numerical experiments demonstrate multiple order-of-magnitude reductions in the number of forward model evaluations used in representative ODE and PDE inference problems, with both synthetic and real data.Comment: A major update of the theory and example

System Would Predictively Preempt Traffic Lights for Emergency Vehicles

Two electronic communication-and-control systems have been proposed as means of modifying the switching of traffic lights to give priority to emergency vehicles. Both systems would utilize the inductive loops already installed in the streets of many municipalities to detect vehicles for timing the switching of traffic lights. The proposed systems could be used alone or to augment other automated emergency traffic-light preemption systems that are already present in some municipalities, including systems that recognize flashing lights or siren sounds or that utilize information on the positions of emergency vehicles derived from the Global Positioning System (GPS). Systems that detect flashing lights and siren sounds are limited in range, cannot "see" or "hear" well around corners, and are highly vulnerable to noise. GPS-based systems are effective in rural areas and small cities, but are often ineffective in large cities because of frequent occultation of GPS satellite signals by large structures. In contrast, the proposed traffic-loop forward prediction system would be relatively invulnerable to noise, would not be subject to significant range limitations, and would function well in large cities -- even in such places as underneath bridges and in tunnels, where GPS-based systems do not work. One proposed system has been characterized as "car-active" because each participating emergency vehicle would be equipped with a computer and a radio transceiver that would communicate with stationary transceivers at the traffic loops. The other proposed system has been characterized as "car-passive" because a passive radio transponder would be installed on the underside of a participating vehicle

Automated Announcements of Approaching Emergency Vehicles

Street intersections that are equipped with traffic lights would also be equipped with means for generating audible announcements of approaching emergency vehicles, according to a proposal. The means to generate the announcements would be implemented in the intersection- based subsystems of emergency traffic-light-preemption systems like those described in the two immediately preceding articles and in "Systems Would Preempt Traffic Lights for Emergency Vehicles" (NPO-30573), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 36. Preempting traffic lights is not, by itself, sufficient to warn pedestrians at affected intersections that emergency vehicles are approaching. Automated visual displays that warn of approaching emergency vehicles can be helpful as a supplement to preemption of traffic lights, but experience teaches that for a variety of reasons, pedestrians often do not see such displays. Moreover, in noisy and crowded urban settings, the lights and sirens on emergency vehicles are often not noticed until a few seconds before the vehicles arrive. According to the proposal, the traffic-light preemption subsystem at each intersection would generate an audible announcement for example, emergency vehicle approaching, please clear intersection whenever a preemption was triggered. The subsystem would estimate the time of arrival of an approaching emergency vehicle by use of vehicle identity, position, and time data from one or more sources that could include units connected to traffic loops and/or transponders connected to diagnostic and navigation systems in participating emergency vehicles. The intersection-based subsystem would then start the announcement far enough in advance to enable pedestrians to leave the roadway before any emergency vehicles arrive

Intersection-Controller Software Module

An important part of the emergency-vehicle traffic-light-preemption system summarized in the preceding article is a software module executed by a microcontroller in each intersection controller. This module monitors the broadcasts from all nearby participating emergency vehicles and intersections. It gathers the broadcast data pertaining to the positions and velocities of the vehicles and the timing of traffic and pedestrian lights and processes the data into predictions of the future positions of the vehicles. Analyzing the predictions by a combination of proximity tests, map-matching techniques, and statistical calculations designed to minimize the adverse effects of uncertainties in vehicle positions and headings, the module decides whether to preempt and issues the appropriate commands to the traffic lights, pedestrian lights, and electronic warning signs at the intersection. The module also broadcasts its state to all nearby vehicles and intersections. The module is designed to mitigate the effects of missing data and of unpredictable delays in the system. It has been intensively tested and refined so that it fails to warn in very few cases and issues very few false warnings

Central-Monitor Software Module

One of the software modules of the emergency-vehicle traffic-light-preemption system of the two preceding articles performs numerous functions for the central monitoring subsystem. This module monitors the states of all units (vehicle transponders and intersection controllers): It provides real-time access to the phases of traffic and pedestrian lights, and maps the positions and states of all emergency vehicles. Most of this module is used for installation and configuration of units as they are added to the system. The module logs all activity in the system, thereby providing information that can be analyzed to minimize response times and optimize response strategies. The module can be used from any location within communication range of the system; with proper configuration, it can also be used via the Internet. It can be integrated into call-response centers, where it can be used for alerting emergency vehicles and managing their responses to specific incidents. A variety of utility subprograms provide access to any or all units for purposes of monitoring, testing, and modification. Included are "sniffer" utility subprograms that monitor incoming and outgoing data for accuracy and timeliness, and that quickly and autonomously shut off malfunctioning vehicle or intersection units

Intersection Monitor for Traffic-Light-Preemption System

The figure shows an intersection monitor that is a key subsystem of an emergency traffic-light-preemption system that could be any of the systems described in the three immediately preceding articles and in Systems Would Preempt Traffic Lights for Emergency Vehicles (NPO-30573), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 36. This unit is so named because it is installed at an intersection, where it monitors the phases (in the sense of timing) of the traffic lights. The mode of operation of this monitor is independent of the type of traffic-light-controller hardware or software in use at the intersection. Moreover, the design of the monitor is such that (1) the monitor does not, by itself, affect the operation of the traffic- light controller and (2) in the event of a failure of the monitor, the trafficlight controller continues to function normally (albeit without preemption). The monitor is installed in series with the traffic-light controller at an intersection. The control signals of interest are monitored by use of high-impedance taps on affected control lines. These taps are fully isolated and further protected by high-voltage diodes that prevent any voltages or short circuits that arise within the monitor from affecting the controller. The signals from the taps are processed digitally and cleaned up by use of high-speed logic gates, and the resulting data are passed on to other parts of the traffic-light-preemption intersection subsystem. The data are compared continuously with data from vehicles and used to calculate timing for reliable preemption of the traffic lights. The pedestrian crossing at the intersection is also monitored, and pedestrians are warned not to cross during preemption