Genomic Analysis of the Only Blind Cichlid Reveals Extensive Inactivation in Eye and Pigment Formation Genes

Trait loss represents an intriguing evolutionary problem, particularly when it occurs across independent lineages. Fishes in light-poor environments often evolve “troglomorphic” traits, including reduction or loss of both pigment and eyes. Here, we investigate the genomic basis of trait loss in a blind and depigmented African cichlid, Lamprologus lethops, and explore evolutionary forces (selection and drift) that may have contributed to these losses. This species, the only known blind cichlid, is endemic to the lower Congo River. Available evidence suggests that it inhabits deep, low-light habitats. Using genome sequencing, we show that genes related to eye formation and pigmentation, as well as other traits associated with troglomorphism, accumulated inactivating mutations rapidly after speciation. A number of the genes affected in L. lethops are also implicated in troglomorphic phenotypes in Mexican cavefish (Astyanax mexicanus) and other species. Analysis of heterozygosity patterns across the genome indicates that L. lethops underwent a significant population bottleneck roughly 1 Ma, after which effective population sizes remained low. Branch-length tests on a subset of genes with inactivating mutations show little evidence of directional selection; however, low overall heterozygosity may reduce statistical power to detect such signals. Overall, genome-wide patterns suggest that accelerated genetic drift from a severe bottleneck, perhaps aided by directional selection for the loss of physiologically expensive traits, caused inactivating mutations to fix rapidly in this species

A 3DGRAPE/AL: The Ames/Langley technology upgrade

This paper describes a new three-dimensional structured multiple-block volume grid generator called 3DGRAPE/AL. It is a significantly improved version of the previously-released and widely-distributed program 3DGRAPE, with many of the improvements taken from the grid-generator program 3DMAGGS. It generates volume grids by iteratively solving the Poisson Equations in three-dimensions. The right-hand-side terms are designed so that user-specified grid cell heights and user-specified grid cell skewness near boundary surfaces result automatically, with little user intervention. Versatility was a high priority in this code's development, and as a result it can generate grids in almost any three-dimensional physical domain. Improvements include added kinds of forcing functions, improved control of cell skewness, improved initial conditions, convergence acceleration, the ability to take as input the output from GRIDGEN, and a simple but powerful graphical user interface (GUI)

Clearing algorithms and network centrality

I show that the solution of a standard clearing model commonly used in contagion analyses for financial systems can be expressed as a specific form of a generalized Katz centrality measure under conditions that correspond to a system-wide shock. This result provides a formal explanation for earlier empirical results which showed that Katz-type centrality measures are closely related to contagiousness. It also allows assessing the assumptions that one is making when using such centrality measures as systemic risk indicators. I conclude that these assumptions should be considered too strong and that, from a theoretical perspective, clearing models should be given preference over centrality measures in systemic risk analyses

Aerodynamic Analysis of Simulated Heat Shield Recession for the Orion Command Module

The aerodynamic effects of the recession of the ablative thermal protection system for the Orion Command Module of the Crew Exploration Vehicle are important for the vehicle guidance. At the present time, the aerodynamic effects of recession being handled within the Orion aerodynamic database indirectly with an additional safety factor placed on the uncertainty bounds. This study is an initial attempt to quantify the effects for a particular set of recessed geometry shapes, in order to provide more rigorous analysis for managing recession effects within the aerodynamic database. The aerodynamic forces and moments for the baseline and recessed geometries were computed at several trajectory points using multiple CFD codes, both viscous and inviscid. The resulting aerodynamics for the baseline and recessed geometries were compared. The forces (lift, drag) show negligible differences between baseline and recessed geometries. Generally, the moments show a difference between baseline and recessed geometries that correlates with the maximum amount of recession of the geometry. The difference between the pitching moments for the baseline and recessed geometries increases as Mach number decreases (and the recession is greater), and reach a value of -0.0026 for the lowest Mach number. The change in trim angle of attack increases from approx. 0.5deg at M = 28.7 to approx. 1.3deg at M = 6, and is consistent with a previous analysis with a lower fidelity engineering tool. This correlation of the present results with the engineering tool results supports the continued use of the engineering tool for future work. The present analysis suggests there does not need to be an uncertainty due to recession in the Orion aerodynamic database for the force quantities. The magnitude of the change in pitching moment due to recession is large enough to warrant inclusion in the aerodynamic database. An increment in the uncertainty for pitching moment could be calculated from these results and included in the development of the aerodynamic database uncertainty for pitching moment

Macrostate Data Clustering

We develop an effective nonhierarchical data clustering method using an analogy to the dynamic coarse graining of a stochastic system. Analyzing the eigensystem of an interitem transition matrix identifies fuzzy clusters corresponding to the metastable macroscopic states (macrostates) of a diffusive system. A "minimum uncertainty criterion" determines the linear transformation from eigenvectors to cluster-defining window functions. Eigenspectrum gap and cluster certainty conditions identify the proper number of clusters. The physically motivated fuzzy representation and associated uncertainty analysis distinguishes macrostate clustering from spectral partitioning methods. Macrostate data clustering solves a variety of test cases that challenge other methods.Comment: keywords: cluster analysis, clustering, pattern recognition, spectral graph theory, dynamic eigenvectors, machine learning, macrostates, classificatio

Computational Aeroheating Predictions for X-34

Radiative equilibrium surface temperatures, heating rates, streamlines, surface pressures, and flow-field features as predicted by the Langley Aerothermodynamic Upwind Relaxation Algorithm (Laura) are presented for the X-34 Technology Demonstrator. Results for two trajectory points corresponding to entry peak heating and two control surface deflections are discussed. This data is also discussed in context of Thermal Protection System (TPS) design issues. The work presented in this report is part of a larger effort to define the X-34 aerothermal environment, including the application of engineering codes and wind-tunnel studies