Reverse Engineering of Computer-Based Navy Systems

The financial pressure to meet the need for change in computer-based systems through evolution rather than through revolution has spawned the discipline of reengineering. One driving factor of reengineering is that it is increasingly becoming the case that enhanced requirements placed on computer-based systems are overstressing the processing resources of the systems. Thus, the distribution of processing load over highly parallel and distributed hardware architectures has become part of the reengineering process for computer-based Navy systems. This paper presents an intermediate representation (IR) for capturing features of computer-based systems to enable reengineering for concurrency. A novel feature of the IR is that it incorporates the mission critical software architecture, a view that enables information to be captured at five levels of granularity: the element/program level, the task level, the module/class/package level, the method/procedure level, and the statement/instruction level. An approach to reverse engineering is presented, in which the IR is captured, and is analyzed to identify potential concurrency. Thus, the paper defines concurrency metrics to guide the reengineering tasks of identifying, enhancing, and assessing concurrency, and for performing partitioning and assignment. Concurrency metrics are defined at several tiers of the mission critical software architecture. In addition to contributing an approach to reverse engineering for computer-based systems, the paper also discusses a reverse engineering analysis toolset that constructs and displays the IR and the concurrency metrics for Ada programs. Additionally, the paper contains a discussion of the context of our reengineering efforts within the United States Navy, by describing two reengineering projects focused on sussystems of the AEGIS Weapon System

Galaxy Zoo: CANDELS barred discs and bar fractions

The formation of bars in disc galaxies is a tracer of the dynamical maturity of the population. Previous studies have found that the incidence of bars in discs decreases from the local Universe to z ~ 1, and by z > 1 simulations predict that bar features in dynamically mature discs should be extremely rare. Here, we report the discovery of strong barred structures in massive disc galaxies at z ~ 1.5 in deep rest-frame optical images from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey. From within a sample of 876 disc galaxies identified by visual classification in Galaxy Zoo, we identify 123 barred galaxies. Selecting a subsample within the same region of the evolving galaxy luminosity function (brighter than L*), we find that the bar fraction across the redshift range 0.5 ≤ z ≤ 2 (fbar = 10.7+6.3 -3.5 per cent after correcting for incompleteness) does not significantly evolve.We discuss the implications of this discovery in the context of existing simulations and our current understanding of the way disc galaxies have evolved over the last 11 billion yearsPeer reviewedFinal Accepted Versio

Using imputation to provide harmonized longitudinal measures of cognition across AIBL and ADNI

To improve understanding of Alzheimer’s disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer\u27s Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p \u3c 0.001) for clinical classification to measured data in the other dataset. Further, the increased power of the overall harmonised dataset was demonstrated by observing a significant association between CVLT-II test scores (imputed for ADNI) with PET Amyloid-β in MCI APOE-ε4 homozygotes in the imputed data (N = 65) but not for the original AIBL dataset (N = 11). These results suggest that MissForest can provide a practical solution for data harmonization using imputation across studies to improve power for more nuanced analyses

Pharmacokinetic modeling of R and S-Methadone and their metabolites to study the effects of various covariates in post-operative children

Methadone is a synthetic opioid used as an analgesic and for the treatment of opioid abuse disorder. The analgesic dose in the pediatric population is not well-defined. The pharmacokinetics (PKs) of methadone is highly variable due to the variability in alpha-1 acid glycoprotein (AAG) and genotypic differences in drug-metabolizing enzymes. Additionally, the R and S enantiomers of methadone have unique PK and pharmacodynamic properties. This study aims to describe the PKs of R and S methadone and its metabolite 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP) in pediatric surgical patients and to identify sources of inter- and intra-individual variability. Children aged 8-17.9 years undergoing orthopedic surgeries received intravenous methadone 0.1 mg/kg intra-operatively followed by oral methadone 0.1 mg/kg postoperatively every 12 h. Pharmacokinetics of R and S methadone and EDDP were determined using liquid chromatography tandem mass spectrometry assays and the data were modeled using nonlinear mixed-effects modeling in NONMEM. R and S methadone PKs were well-described by two-compartment disposition models with first-order absorption and elimination. EDDP metabolites were described by one compartment disposition models with first order elimination. Clearance of both R and S methadone were allometrically scaled by bodyweight. CYP2B6 phenotype was a determinant of the clearance of both the enantiomers in an additive gene model. The intronic CYP3A4 single-nucleotide polymorphism (SNP) rs2246709 was associated with decreased clearance of R and S methadone. Concentrations of AAG and the SNP of AAG rs17650 independently increased the volume of distribution of both the enantiomers. The knowledge of these important covariates will aid in the optimal dosing of methadone in children

The ACS Fornax Cluster Survey. VI. The Nuclei of Early-Type Galaxies in the Fornax Cluster

The Advanced Camera for Surveys (ACS) Fornax Cluster Survey is a Hubble Space Telescope program to image 43 early-type galaxies in the Fornax cluster, using the F475W and F850LP bandpasses of the ACS. We employ both 1D and 2D techniques to characterize the properties of the stellar nuclei in these galaxies, defined as the central "luminosity excesses" relative to a Sersic model fitted to the underlying host. We find 72+/-13% of our sample (31 galaxies) to be nucleated, with only three of the nuclei offset by more than 0.5" from their galaxy photocenter, and with the majority of nuclei having colors bluer than their hosts. The nuclei are observed to be larger, and brighter, than typical Fornax globular clusters, and to follow different structural scaling relations. A comparison of our results to those from the ACS Virgo Cluster Survey reveals striking similarities in the properties of the nuclei belonging to these different environments. We briefly review a variety of proposed formation models and conclude that, for the low-mass galaxies in our sample, the most important mechanism for nucleus growth is probably infall of star clusters through dynamical friction, while for higher mass galaxies, gas accretion triggered by mergers, accretions and tidal torques is likely to dominate, with the relative importance of these two processes varying smoothly as a function of galaxy mass. Some intermediate-mass galaxies in our sample show a complexity in their inner structure that may be the signature of "hybrid nuclei" that arose through parallel formation channels.Comment: 34 pages, 27 figures, accepted for publication in ApJ

The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III

The Sloan Digital Sky Survey (SDSS) started a new phase in August 2008, with new instrumentation and new surveys focused on Galactic structure and chemical evolution, measurements of the baryon oscillation feature in the clustering of galaxies and the quasar Ly alpha forest, and a radial velocity search for planets around ~8000 stars. This paper describes the first data release of SDSS-III (and the eighth counting from the beginning of the SDSS). The release includes five-band imaging of roughly 5200 deg^2 in the Southern Galactic Cap, bringing the total footprint of the SDSS imaging to 14,555 deg^2, or over a third of the Celestial Sphere. All the imaging data have been reprocessed with an improved sky-subtraction algorithm and a final, self-consistent photometric recalibration and flat-field determination. This release also includes all data from the second phase of the Sloan Extension for Galactic Understanding and Evolution (SEGUE-2), consisting of spectroscopy of approximately 118,000 stars at both high and low Galactic latitudes. All the more than half a million stellar spectra obtained with the SDSS spectrograph have been reprocessed through an improved stellar parameters pipeline, which has better determination of metallicity for high metallicity stars.Comment: Astrophysical Journal Supplements, in press (minor updates from submitted version