Supersonic Flow of Chemically Reacting Gas-Particle Mixtures. Volume 2: RAMP - A Computer Code for Analysis of Chemically Reacting Gas-Particle Flows

A computer program written in conjunction with the numerical solution of the flow of chemically reacting gas-particle mixtures was documented. The solution to the set of governing equations was obtained by utilizing the method of characteristics. The equations cast in characteristic form were shown to be formally the same for ideal, frozen, chemical equilibrium and chemical non-equilibrium reacting gas mixtures. The characteristic directions for the gas-particle system are found to be the conventional gas Mach lines, the gas streamlines and the particle streamlines. The basic mesh construction for the flow solution is along streamlines and normals to the streamlines for axisymmetric or two-dimensional flow. The analysis gives detailed information of the supersonic flow and provides for a continuous solution of the nozzle and exhaust plume flow fields. Boundary conditions for the flow solution are either the nozzle wall or the exhaust plume boundary

Supersonic flow of chemically reacting gas-particle mixtures. Volume 1: A theoretical analysis and development of the numerical solution

A numerical solution for chemically reacting supersonic gas-particle flows in rocket nozzles and exhaust plumes was described. The gas-particle flow solution is fully coupled in that the effects of particle drag and heat transfer between the gas and particle phases are treated. Gas and particles exchange momentum via the drag exerted on the gas by the particles. Energy is exchanged between the phases via heat transfer (convection and/or radiation). Thermochemistry calculations (chemical equilibrium, frozen or chemical kinetics) were shown to be uncoupled from the flow solution and, as such, can be solved separately. The solution to the set of governing equations is obtained by utilizing the method of characteristics. The equations cast in characteristic form are shown to be formally the same for ideal, frozen, chemical equilibrium and chemical non-equilibrium reacting gas mixtures. The particle distribution is represented in the numerical solution by a finite distribution of particle sizes

A Combined Geometric Morphometric and Discrete Element Modeling Approach for Hip Cartilage Contact Mechanics.

Finite element analysis (FEA) provides the current reference standard for numerical simulation of hip cartilage contact mechanics. Unfortunately, the development of subject-specific FEA models is a laborious process. Owed to its simplicity, Discrete Element Analysis (DEA) provides an attractive alternative to FEA. Advancements in computational morphometrics, specifically statistical shape modeling (SSM), provide the opportunity to predict cartilage anatomy without image segmentation, which could be integrated with DEA to provide an efficient platform to predict cartilage contact stresses in large populations. The objective of this study was, first, to validate linear and non-linear DEA against a previously validated FEA model and, second, to present and evaluate the applicability of a novel population-averaged cartilage geometry prediction method against previously used methods to estimate cartilage anatomy. The population-averaged method is based on average cartilage thickness maps and therefore allows for a more accurate and individualized cartilage geometry estimation when combined with SSM. The root mean squared error of the population-averaged cartilage geometry predicted by SSM as compared to the manually segmented cartilage geometry was 0.31 ± 0.08 mm. Identical boundary and loading conditions were applied to the DEA and FEA models. Predicted DEA stress distribution patterns and magnitude of peak stresses were in better agreement with FEA for the novel cartilage anatomy prediction method as compared to commonly used parametric methods based on the estimation of acetabular and femoral head radius. Still, contact stress was overestimated and contact area was underestimated for all cartilage anatomy prediction methods. Linear and non-linear DEA methods differed mainly in peak stress results with the non-linear definition being more sensitive to detection of high peak stresses. In conclusion, DEA in combination with the novel population-averaged cartilage anatomy prediction method provided accurate predictions while offering an efficient platform to conduct population-wide analyses of hip contact mechanics

MCAO near-IR photometry of the Globular Cluster NGC 6388: MAD observations in crowded fields

Deep photometry of crowded fields, such as Galactic Globular Clusters, is severely limited by the actual resolution of ground-based telescopes. On the other hand, the Hubble Space Telescope does not provide the near-infrared (NIR) filters needed to allow large color baselines. In this work we aim at demonstrating how ground based observations can reach the required resolution when using Multi-Conjugated Adaptive Optic (MCAO) devices in the NIR, such as the experimental infrared camera (MAD) available on the VLT. This is particularly important since these corrections are planned to be available on all ground--based telescopes in the near future. We do this by combining the infrared photometry obtained by MAD/VLT with ACS/HST optical photometry of our scientific target, the bulge globular cluster NGC 6388, in which we imaged two fields. In particular, we constructed color-magnitude diagrams with an extremely wide color baseline in order to investigate the presence of multiple stellar populations in this cluster. From the analysis of the external field, observed with better seeing conditions, we derived the deepest optical-NIR CMD of NGC 6388 to date. The high-precision photometry reveals that two distinct sub-giant branches are clearly present in this cluster. We also use the CMD from the central region to estimate the distance ((m-M)=15.33) and the reddening (E(B-V)=0.38) for this cluster. We estimate the age to be ~11.5+/- 1.5 Gyr. The large relative-age error reflects the bimodal distribution of the SGB stars. This study clearly demonstrates how MCAO correction in the NIR bands implemented on ground based telescopes can complement the high-resolution optical data from HST.Comment: 9 pages, 10 figures. Accepted for publication on A. &

Combination of Statistical Shape Modeling and Statistical Parametric Mapping to Quantify Cartilage Contact Mechanics in Hip Dysplasia

Finite element models can predict subject-specific chondrolabral stresses and help to elucidate the effect of under-coverage and incongruency of the hip joint in patients with dysplasia. However, complex stress patterns are difficult to generalize and evaluate statistically. With an established correspondence across shapes from statistical shape modeling (SSM), statistical parametric mapping (SPM) allows for evaluation of local variability while preserving model subject-specificity. Herein, we evaluated the combined application of SSM and SPM to compare cartilage contact stress between control subjects and patients with dysplasia. Previously published hip joint contact stresses were mapped onto chondrolabral surface meshes and incorporated into an SSM. Principal component analysis (PCA) quantified shape variation. Contact stress values from heel-strike of stair ascent (AH), stair descent (DH), and level walking (WH) and mid-stance of level walking (WM) were evaluated. Using SPM, regions of significant contact stress variation were identified based on test statistics from general linear statistical models and corrected for multiple comparisons using Gaussian random fields. Shape differences of the femoral and acetabular cartilage with labrum were captured by two and one PCA mode, respectively. Contact stress differences were observed in anterosuperior regions of the femoral cartilage for AH and DH and of the acetabular cartilage for DH and WM (Figure 1). The SPM identified regions of varied contact stresses were small and likely would have been diluted through averaging or region-splitting using traditional analysis methods. The combined application of SSM and SPM provides a method to generalize and statistically-compare subject-specific mechanics and joint morphology

Wide-Field InfraRed Survey Telescope (WFIRST) Final Report

In December 2010, NASA created a Science Definition Team (SDT) for WFIRST, the Wide Field Infra-Red Survey Telescope, recommended by the Astro 2010 Decadal Survey as the highest priority for a large space mission. The SDT was chartered to work with the WFIRST Project Office at GSFC and the Program Office at JPL to produce a Design Reference Mission (DRM) for WFIRST. Part of the original charge was to produce an interim design reference mission by mid-2011. That document was delivered to NASA and widely circulated within the astronomical community. In late 2011 the Astrophysics Division augmented its original charge, asking for two design reference missions. The first of these, DRM1, was to be a finalized version of the interim DRM, reducing overall mission costs where possible. The second of these, DRM2, was to identify and eliminate capabilities that overlapped with those of NASA's James Webb Space Telescope (henceforth JWST), ESA's Euclid mission, and the NSF's ground-based Large Synoptic Survey Telescope (henceforth LSST), and again to reduce overall mission cost, while staying faithful to NWNH. This report presents both DRM1 and DRM2.Comment: 102 pages, 57 figures, 17 table

Application of Statistical Shape Modeling to Predict Clinical Metric of Femoral Head Coverage in Patients with Developmental Dysplasia

Developmental dysplasia of the hip (DDH) is described as under-coverage of the femoral head by the acetabulum, resulting in mechanical instability. Though DDH is often diagnosed using plain film radiographs, these images cannot adequately capture 3D joint coverage. Herein, we applied a 3D statistical shape model (SSM) to the femur and hemi-pelvis of patients with DDH to objectively measure shape variation and evaluated whether SSM outputs could predict measurements of joint coverage. The femur and hemi-pelvis were semi-automatically segmented from CT images (83 hips from 47 females with DDH). Surfaces of each hip were reconstructed from segmentations, aligned, and input into a multi-domain SSM (shapeworks.sci.utah.edu). Correspondence particles were automatically placed over the bone surfaces and a subset on the femoral head and acetabulum were isolated for a joint-specific model. Modes of shape variation were determined with principal component analysis (PCA). A sparse model of PCA modes predicting coverage was determined using linear regression with Lasso regularization. Coverage measurements ranged from 27.3% to 39.4%. Eight and 13 modes were selected for the full bone and joint-specific models, respectively. These modes represented 6.1% and 39.6% of the overall shape variation for full bone and joint-specific models with mean prediction errors of 0.9% and 0.6% coverage, respectively (Figure 1). Selected modes represented the depth of the acetabulum and oblateness of the femoral head, aligning well with the clinical description of DDH. In addition, the full bone model captured morphological and pose-related differences potentially related to altered muscle paths or differences in femoral torsion

A dual role for prediction error in associative learning

Confronted with a rich sensory environment, the brain must learn statistical regularities across sensory domains to construct causal models of the world. Here, we used functional magnetic resonance imaging and dynamic causal modeling (DCM) to furnish neurophysiological evidence that statistical associations are learnt, even when task-irrelevant. Subjects performed an audio-visual target-detection task while being exposed to distractor stimuli. Unknown to them, auditory distractors predicted the presence or absence of subsequent visual distractors. We modeled incidental learning of these associations using a Rescorla--Wagner (RW) model. Activity in primary visual cortex and putamen reflected learning-dependent surprise: these areas responded progressively more to unpredicted, and progressively less to predicted visual stimuli. Critically, this prediction-error response was observed even when the absence of a visual stimulus was surprising. We investigated the underlying mechanism by embedding the RW model into a DCM to show that auditory to visual connectivity changed significantly over time as a function of prediction error. Thus, consistent with predictive coding models of perception, associative learning is mediated by prediction-error dependent changes in connectivity. These results posit a dual role for prediction-error in encoding surprise and driving associative plasticity

A look at the other 90 per cent: Investigating British Sign Language vocabulary knowledge in deaf children from different language learning backgrounds

In this study we present new data on deaf children's receptive and expressive vocabulary knowledge in British Sign Language (BSL) from a sample consisting of children with deaf parents, children with hearing parents, and children with additional needs. Their performance on three BSL vocabulary tasks was compared with (previously reported findings from) a sample of deaf fluent signers. We use these data to assess the effects of some key demographic/ child variables on deaf signing children's vocabulary and discuss findings in the relation to the meaning of 'normative' data and samples for this heterogeneous population. Findings show no effect of the presence of additional disabilities on participants' scores for any of the three tasks. As expected, chronological age is the most significant factor in performance on all vocabulary tasks while the number of deaf relatives only becomes statistically significant for the form recall task. This study contributes to the field of sign language assessment by seeking to identify key variables in heterogeneity and how these variables affect signed vocabulary acquisition with the long-term objective of informing intervention