A new methodology for Bayesian history matching using parallel interacting Markov chain Monte Carlo

This paper presents an innovative application of a new class of parallel interacting Markov chains Monte Carlo to solve the Bayesian history matching (BHM) problem. BHM consists of sampling a posterior distribution given by the Bayesian theorem. Markov chain Monte Carlo (MCMC) is well suited for sampling, in principle, any type of distribution; however the number of iteration required by the traditional single-chain MCMC can be prohibitive in BHM applications. Furthermore, history matching is typically a highly nonlinear inverse problem, which leads in very complex posterior distributions, characterized by many separated modes. Therefore, single chain can be trapped into a local mode. Parallel interacting chains is an interesting way to overcome this problem, as shown in this paper. In addition, we presented new approaches to define starting points for the parallel chains. For validation purposes, the proposed methodology is firstly applied in a simple but challenging cross section reservoir model with many modes in the posterior distribution. Afterwards, the application to a realistic case integrated to geostatistical modelling is also presented. The results showed that the combination of parallel interacting chain with the capabilities of distributed computing commonly available nowadays is very promising to solve the BHM problem.     

The unanticipated difficult airway with recommendations for management

PURPOSE: To review the current literature and generate recommendations on the role of newer technology in the management of the unanticipated difficult airway. METHODS: A literature search using key words and filters of English language and English abstracted publications from 1990-96 contained in the Medline, Current Contents and Biological Abstracts databases was carried out. The literature was reviewed and condensed and a series of evidence-based recommendations were evolved. CONCLUSIONS: The unanticipated difficult airway occurs with a low but consistent incidence in anaesthesia practice. Difficult direct laryngoscopy occurs in 1.5-8.5% of general anaesthetics and difficult intubation occurs with a similar incidence. Failed intubation occurs in 0.13-0.3% general anaesthetics. Current techniques for predicting difficulty with laryngoscopy and intubation are sensitive, non-specific and have a low positive predictive value. Assessment techniques which utilize multiple characteristics to derive a risk factor tend to be more accurate predictors. Devices such as the laryngeal mask, lighted stylet and rigid fibreoptic laryngoscopes, in the setting of unanticipated difficult airway, are effective in establishing a patient airway, may reduce morbidity and are occasionally lifesaving. Evidence supports their use in this setting as either alternatives to facemask and bag ventilation, when it is inadequate to support oxygenation, or to the direct laryngoscope, when tracheal intubation has failed. Specifically, the laryngeal mask and Combitube have proved to be effective in establishing and maintaining a patent airway in "cannot ventilate" situations. The lighted stylet and Bullard (rigid) fibreoptic scope are effective in many instances where the direct laryngoscope has failed to facilitate tracheal intubation. The data also support integration of these devices into strategies to manage difficult airway as the new standard of care. Training programmes should ensure graduate physicians are trained in the use of these alternatives. Continuing medical education courses should allow physicians in practice the opportunity to train with these alternative devices.     

Differences between completers and early dropouts from 2 HIV intervention trials: a health belief approach to understanding prevention program attrition

OBJECTIVES: The purpose of this study was to identify factors predicting program attrition among participants in human immunodeficiency virus (HIV) risk reduction trials. METHODS: Participants were gay/bisexual men and severely mentally ill adults recruited to take part in HIV risk reduction small-group interventions. Program completers were compared with participants who were assessed at baseline but then failed to attend any sessions. The health belief model provided a framework for selection of possible predictors of program attrition. RESULTS: Younger age was associated with early dropout in both samples. Other predictors among gay/bisexual men included involvement in an exclusive sexual relationship, minority ethnicity, injection drug use, and higher perceived severity of AIDS. Severely mentally ill dropouts were less knowledgeable about safer sex methods and more likely to hold positive outcome expectancies for condom use. CONCLUSIONS: Evaluation of intervention effectiveness among vulnerable population segments is threatened if there is selective attrition. Better methods are needed to attract and maintain participation in HIV prevention programs. Alternatively, wider application of "intention to treat" analysis of intervention outcomes is recommended to minimize selection bias due to program dropout.     

Transverse Spin Diffusion in a Dilute Spin-Polarized Degenerate Fermi Gas

We re-examine the calculation of the transverse spin-diffusion coefficient in a dilute degenerate spin-polarized Fermi gas, for the case of s-wave scattering. The special feature of this limit is that the dependence of the spin diffusion coefficient on temperature and field can be calculated explicitly with no further approximations. This exact solution uncovers a novel intermediate behaviour between the high field spin-rotation dominated regime in which D H^–2 , D T^–2 , and the low-field isotropic, collision dominated regime with D = D T^–2 . In this intermediate regime, D_, T^–2 but D D. We emphasize that the low-field crossover cannot be described within the relaxation time approximation. We also present an analytical calculation of the self-energy in the s-wave approximation for a dilute spin-polarized Fermi gas, at zero temperature. This emphasizes the failure of the conventional Fermi-liquid phase space arguments for processes involving spin flips. We close by reviewing the evidence for the existence of the intermediate regime in experiments on weakly spin-polarized ³ He and ³ He– ⁴ He mixtures.     

Free-living inferential modeling of blood glucose level using only noninvasive inputs

The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements.     

Accuracy estimate and optimization techniques for SimRank computation

The measure of similarity between objects is a very useful tool in many areas of computer science, including information retrieval. SimRank is a simple and intuitive measure of this kind, based on a graph-theoretic model. SimRank is typically computed iteratively, in the spirit of PageRank. However, existing work on SimRank lacks accuracy estimation of iterative computation and has discouraging time complexity. In this paper, we present a technique to estimate the accuracy of computing SimRank iteratively. This technique provides a way to find out the number of iterations required to achieve a desired accuracy when computing SimRank. We also present optimization techniques that improve the computational complexity of the iterative algorithm from O(n ⁴) in the worst case to min(O(nl), O(n ³/ log₂ n)), with n denoting the number of objects, and l denoting the number object-to-object relationships. We also introduce a threshold sieving heuristic and its accuracy estimation that further improves the efficiency of the method. As a practical illustration of our techniques, we computed SimRank scores on a subset of English Wikipedia corpus, consisting of the complete set of articles and category links.     

Scaling the formation of slug bubbles in microfluidic flow-focusing devices

The present study aims at scaling the formation of slug bubbles in flow-focusing microfluidic devices using a high-speed digital camera and a micro particle image velocimetry (μ-PIV) system. Experiments were conducted in two different polymethyl methacrylate square microchannels of respectively 600 × 600 and 400 × 400 μm. N₂ bubbles were generated in glycerol–water mixtures with several concentrations of surfactant sodium dodecyl sulfate. The influence of gas and liquid flow rates, the viscosity of the liquid phase and the width of the microchannel on the bubble size were explored. The bubble size was correlated as a function of the width of the microchannel W _c, the ratio of the gas/liquid flow rates Q _g/Q _l and the liquid Reynolds number. During the pinch-off stage, the variation of the minimum width of the gaseous thread W _m with the remaining time could be scaled as _boxclose_boxclose ()^ - 0.15 (T - t)^1/3 . W_{\text{m}} \propto ({\frac{{Q_{\text{g}} }}{{Q_{\text{l}} }}})^{ - 0.15} (T - t)^{1/3} . The velocity fields in the liquid phase around the thread, determined by μ-PIV measurements, were obtained around a forming bubble to reveal the role of the liquid phase.     

Robot-Assisted Bridge Inspection

The Center for Robot-Assisted Search and Rescue (CRASAR®) deployed a customized AEOS man-portable unmanned surface vehicle and two commercially available underwater vehicles (the autonomous YSI EcoMapper and the tethered VideoRay) for inspection of the Rollover Pass bridge in the Bolivar peninsula of Texas in the aftermath of Hurricane Ike. A preliminary domain analysis with the vehicles identified key tasks in subsurface bridge inspection (mapping of the debris field and inspecting the bridge footings for scour), control challenges (navigation under loss of GPS, underwater obstacle avoidance, and stable positioning in high currents without GPS), possible improvements to human-robot interaction (having additional display units so that mission specialists can view and operate on imagery independently of the operator control unit, incorporating 2-way audio to allow operator and field personnel to communicate while launching or recovering the vehicle, and increased state sensing for reliability), and discussed the cooperative use of surface, underwater, and aerial vehicles. The article posits seven milestones in the development of a fully functional UMV for bridge inspection: standardize mission payloads, add health monitoring, improve teleoperation through better human-robot interaction, add 3D obstacle avoidance, improve station-keeping, handle large data sets, and support cooperative sensing.