The HIV positive selection mutation database

The HIV positive selection mutation database is a large-scale database available at that provides detailed selection pressure maps of HIV protease and reverse transcriptase, both of which are molecular targets of antiretroviral therapy. This database makes available for the first time a very large HIV sequence dataset (sequences from ∼50 000 clinical AIDS samples, generously contributed by Specialty Laboratories, Inc.), which makes possible high-resolution selection pressure mapping. It provides information about not only the selection pressure on individual sites but also how selection pressure at one site is affected by mutations on other sites. It also includes datasets from other public databases, namely the Stanford HIV database [S. Y. Rhee, M. J. Gonzales, R. Kantor, B. J. Betts, J. Ravela and R. W. Shafer (2003) Nucleic Acids Res., 31, 298–303]. Comparison between these datasets in the database enables cross-validation with independent datasets and also specific evaluation of the effect of drug treatment

Real-Time Data Driven Wildland Fire Modeling

We are developing a wildland fire model based on semi-empirical relations that estimate the rate of spread of a surface fire and post-frontal heat release, coupled with WRF, the Weather Research and Forecasting atmospheric model. A level set method identifies the fire front. Data are assimilated using both amplitude and position corrections using a morphing ensemble Kalman filter. We will use thermal images of a fire for observations that will be compared to synthetic image based on the model state.Comment: 8 pages, 4 figures. ICCS 0

Morphing Ensemble Kalman Filters

A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF) with the ideas of morphing and registration from image processing. This results in filters suitable for nonlinear problems whose solutions exhibit moving coherent features, such as thin interfaces in wildfire modeling. The ensemble members are represented as the composition of one common state with a spatial transformation, called registration mapping, plus a residual. A fully automatic registration method is used that requires only gridded data, so the features in the model state do not need to be identified by the user. The morphing EnKF operates on a transformed state consisting of the registration mapping and the residual. Essentially, the morphing EnKF uses intermediate states obtained by morphing instead of linear combinations of the states.Comment: 17 pages, 7 figures. Added DDDAS references to the introductio

A realtime observatory for laboratory simulation of planetary flows

Motivated by the large-scale circulation of the atmosphere and ocean, we develop a system that uses observations from a laboratory analog to constrain, in real time, a numerical simulation of the laboratory flow. This system provides a tool to rapidly prototype new methods for state and parameter estimation, and facilitates the study of prediction, predictability, and transport of geophysical fluids where observations or numerical simulations would not independently suffice. A computer vision system is used to extract measurements of the physical simulation. Observations are used to constrain the model-state of the MIT General Circulation Model in a probabilistic, ensemble based assimilation approach. Using a combination of parallelism, domain decomposition and an efficient scheme to select ensembles of model-states, we show that estimates that effectively track the fluid state can be produced. To the best of our knowledge this is the first such observatory for laboratory analogs of planetary circulation that functions in real time.National Science Foundation (U.S.) (CNS-0540259)National Science Foundation (U.S.) (grant CNS-0540248

Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time

Background: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford's HIVdb) to predict virological outcome at 12, 24, and 48 weeks. Methodology/Principal Findings: Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression, we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable viral load (<50 copies/ml) at 12 (8-16) weeks (2152 TCEs), 24 (16-32) weeks (2570 TCEs), and 48 (44-52) weeks (1083 TCEs). The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility score of the systems was slightly smaller for HIVdb, with 1.92±1.17, compared to Rega and ANRS, with 2.22±1.09 and 2.23±1.05, respectively. However, similar odds ratio's were found for the association between each-unit increase in genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5-1.7] for HIVdb, 1.7 [1.5-1.8] for ANRS, and 1.7 [1.9-1.6] for Rega. Odds ratio's increased over time, but remained comparable (odds ratio's ranging between 1.9-2.1 at 24 weeks and 1.9-2.

Tracking Object Motion Across Aspect Changes for Augmented Reality

Amodel registration system capable of tracking an object through distinct aspects in real-time is presented. The system integrates tracking, pose determination, and aspect graph indexing. The tracking combines steerable #lters with normalizedcrosscorrelation, compensates for rotation in 2D and is adaptive. Robust statistical methods are used in the pose estimation to detect and remove mismatches. The aspect graph is used to determine when features will disappear or become di#cult to track and to predict when and where new features will become trackable. The overall system is stable and is amenable to real-time performance.