Oxygen exposures at NASA's Neutral Buoyancy Lab: a 20-year experience.

Astronauts training for extravehicular activity (EVA) operations can spend many hours submerged underwater in a pressurized suit, called an extravehicular mobility unit (EMU), exposed to pressures exceeding 2 atmospheres absolute (ATA). To minimize the risk of decompression sickness (DCS) a 46% nitrox mixture is used. This limits the nitrogen partial pressure, decreasing the risk of DCS. The trade-off with using a 46% nitrox mixture is the increased potential for oxygen toxicity, which can lead to severe neurologic symptoms including seizures. Suited runs, which typically expose astronauts of 0.9-1.1 ATA for longer than six hours, routinely exceed the recommendation for central nervous system oxygen toxicity limits (CNSOTL) published by the National Oceanic and Atmospheric Administration (NOAA). Fortunately, in over 50,000 hours of suited training dives spanning 20 years of EVA training operations at NASA's Neutral Buoyancy Laboratory (NBL) there has never been an occurrence of oxygen toxicity. This lends support to anecdotal sentiment among certain members of the hyperbaric community that the NOAA CNSOTL recommendations might be overly conservative, at least for the oxygen pressure and time regime in which NBL operates. The NOAA CNSOTL recommendations are the result of expert consensus with a focus on safety and do not necessarily reflect rigorous experimental evidence. The data from the NBL suited dive operations provide a foundation of evidence that can help inform the expert discussion on dive-related neurologic oxygen toxicity performance and overnight recovery in young, healthy males.

Characterizing the relationship between flow-mediated vasodilation and radial artery tonometry in peripheral artery disease.

BACKGROUND: Arterial stiffness, measured by the augmentation index (AIX) from radial artery tonometry, and endothelial dysfunction, measured by brachial-artery flow-mediated vasodilation (FMD), have each been associated with increased risk of cardiovascular events. However, their interrelationship in peripheral artery disease (PAD) patients is poorly understood. MATERIALS AND METHODS: In a cross-sectional analysis of 123 vascular surgery outpatients, the association between FMD and AIX was examined in controls with atherosclerotic risk factors (n = 32) and patients with PAD (n = 91). PAD was defined as claudication symptoms with an ankle-brachial index of <0.9 or a history of revascularization for symptomatic PAD. Controls had an ankle-brachial index ≥0.9 and no history of atherosclerotic vascular disease. RESULTS: Compared to controls, patients with PAD had lower FMD (6.3 ± 3.8 versus 8.4 ± 3.7, P = 0.008), while central AIX normalized to 75 beats per minute (25.5 ± 9.0 versus 19.3 ± 8.6, P = 0.001) and peripheral AIX (91.3 ± 14.5 versus 81.3 ± 11.4, P = 0.001) were higher. FMD was not significantly correlated with either central or peripheral AIX (central AIX: P = 0.58; peripheral AIX: P = 0.89) across the entire cohort, or in either the patients with PAD (central AIX: P = 0.48; peripheral AIX: P = 0.23) or controls (central AIX: P = 0.43; peripheral AIX: P = 0.92). In a multivariate model including FMD, higher AIX remained independently associated with PAD. CONCLUSIONS: In an analysis of vascular surgery outpatients, no correlation between FMD and AIX was detected. Larger prospective studies are needed to determine whether the inclusion of both parameters improves predictive models for the early identification and potential risk stratification of PAD patients.

A statistical clustering approach to discriminating perfusion from conduit vessel signal contributions in a pulmonary ASL MR image.

The measurement of pulmonary perfusion (blood delivered to the capillary bed within a voxel) using arterial spin labeling (ASL) magnetic resonance imaging is often complicated by signal artifacts from conduit vessels that carry blood destined for voxels at a distant location in the lung. One approach to dealing with conduit vessel contributions involves the application of an absolute threshold on the ASL signal. While useful for identifying a subset of the most dominant high signal conduit image features, signal thresholding cannot discriminate between perfusion and conduit vessel contributions at intermediate and low signal. As an alternative, this article discusses a data-driven statistical approach based on statistical clustering for characterizing and discriminating between capillary perfusion and conduit vessel contributions over the full signal spectrum. An ASL flow image is constructed from the difference between a pair of tagged magnetic resonance images. However, when viewed as a bivariate projection that treats the image pair as independent measures (rather than the univariate quantity that results from the subtraction of the two images), the signal associated with capillary perfusion contributions is observed to cluster independently of the signal associated with conduit vessel contributions. Analyzing the observed clusters using a Gaussian mixture model makes it possible to discriminate between conduit vessel and capillary-perfusion-dominated signal contributions over the full signal spectrum of the ASL image. As a demonstration of feasibility, this study compares the proposed clustering approach with the standard absolute signal threshold strategy in a small number of test images.

Measuring the effect of ambient noise directionality and split-beam processing on the convergence of the cross-correlation function.

Measurements of ambient noise have been used to infer information about the ocean acoustic environment. In recent years the correlation of ambient noise has been shown to give estimates of the travel time of acoustic paths between the sensors recording the noise. A number of issues affect the results of the noise correlation. This paper presents the results of noise correlation of the two horizontally separated arrays of sensors in the 2010 ambient noise experiment. Using the experimental data, the effects on the convergence of the noise correlation are examined with respect to the size and shape of the arrays, the length of time used, and the directionality of the noise field.

Using Fisher information to quantify uncertainty in environmental parameters estimated from correlated ambient noise.

Efforts to characterize environmental parameters from ambient noise must contend with uncertainty introduced by stochastic fluctuations of the noise itself. This Letter calculates the Fisher information and Cramer-Rao bound of an unbiased correlated ambient noise parameter estimate. As an illustration, lower bounds on the error covariance of medium speed and attenuation parameters are obtained for a two-dimensional isotropic ambient noise scenario. The results demonstrate that an optimal sensor separation exists for obtaining the minimum error and the predictions are validated using simulated parameter inversions. The influences of record length, bandwidth, signal-to-noise, and spatial resolution are discussed.

A model for spatial coherence from directive ambient noise in attenuating, dispersive media.

As a complement to experimental efforts in seismics and acoustics to infer geo-acoustic properties of the propagation environment from the second order statistics of ambient noise measurements, a set of exact, explicit, closed form expressions for the cross-spectral density and spatial coherence of diffuse random wave fields is presented. Taken together, the expressions are well suited for modeling broadband, diffuse wave coherence in realistic scenarios involving directive, ambient noise from local (i.e., volume) and distant (i.e., plane wave) source features in an open, dispersive, attenuating medium.

A model for the spatial coherence of arbitrarily directive noise in the depth-stratified ocean.

Though referred to as noise, the ambient ocean soundscape carries valuable information about the physical ocean environment. To study this information, Kuperman and Ingenito introduced a model for spatial coherence in a depth stratified ocean arising from the vertically directive diffuse acoustic noise produced by bubbles distributed throughout the surface. Here the model is adapted to incorporate horizontal directivity as well, making it possible to include additional noise contributions from directive features such as storms, biologics, shipping, and wave breaking. As an analytic approach, the model can serve as a computationally light complement to existing methods.

Spatial coherence and cross correlation of three-dimensional ambient noise fields in the ocean.

Ambient acoustic noise fields in the ocean are generally three dimensional in that they exhibit vertical and horizontal directivity. A model of spatially homogeneous noise is introduced in which the directionality is treated as separable, that is, the overall directionality of the field is the product of the individual directivities in the horizontal and vertical. A uni-modal von Mises circular distribution from directional statistics is taken to represent the noise in the horizontal, whilst the vertical component is consistent with a surface distribution of vertical dipoles. An analysis of the coherence and cross correlation of the noise at two horizontally aligned sensors is developed. The coherence function involves a single integral over finite limits, whilst the cross-correlation function, derived on the assumption that the noise has been pre-whitened, is given by an integral with limits that depend on the correlation delay time. Although the cross-correlation function does not exhibit delta functions that could be identified with the Green's function for propagation between the two sensors in the field, it does drop abruptly to zero at numerical time delays equal to the travel time between the sensors. Hence the noise could be used to recover the sound speed in the medium.

Estimation of modal group velocities with a single receiver for geoacoustic inversion in shallow water.

Due to the expense associated with at-sea sensor deployments, a challenge in underwater acoustics has been to develop methods requiring a minimal number of sensors. This paper introduces an adaptive time-frequency signal processing method designed for application to a single source-receiver sensor pair. The method involves the application of conjugate time-frequency warping transforms to improve the SNR and resolution of the time-frequency distribution (TFD) of the measured field. Such refined knowledge of the TFD facilitates efforts to extract tomographic information about the propagation medium. Here the method is applied to the case of modal propagation in a shallow ocean range independent environment to extract a refined TFD. Given knowledge of the source-receiver separation, the refined TFD is used to extract the frequency dependent group velocities of the individual modal components. The extracted group velocities are then incorporated into a computationally light tomographic inversion method. Simulated and experimental results are discussed.