Flight Test of Orthogonal Square Wave Inputs for Hybrid-Wing-Body Parameter Estimation

As part of an effort to improve emissions, noise, and performance of next generation aircraft, it is expected that future aircraft will use distributed, multi-objective control effectors in a closed-loop flight control system. Correlation challenges associated with parameter estimation will arise with this expected aircraft configuration. The research presented in this paper focuses on addressing the correlation problem with an appropriate input design technique in order to determine individual control surface effectiveness. This technique was validated through flight-testing an 8.5-percent-scale hybrid-wing-body aircraft demonstrator at the NASA Dryden Flight Research Center (Edwards, California). An input design technique that uses mutually orthogonal square wave inputs for de-correlation of control surfaces is proposed. Flight-test results are compared with prior flight-test results for a different maneuver style

Paternal Psychosocial Characteristics and Corporal Punishment of their 3-Year Old Children

This study uses data from 2,309 biological fathers who participated in the Fragile Families and Child Wellbeing Study (FFCWS) to examine associations between psychosocial characteristics and levels of corporal punishment (CP) toward their 3-year old children over the past month. Results indicate that 61% of the fathers reported no CP over the past month, 23% reported using CP once or twice, and 16% reported using CP a few times in the past month or more. In multivariate models controlling for important socio-demographic factors as well as characteristics of the child, fathers’ parenting stress, major depression, alcohol use, and drug use were significantly associated with greater use of CP, whereas involvement with the child and generalized anxiety order were not. Girls were less likely to be the recipient of CP than boys, and child externalizing behavior problems but not internalizing behavior problems were associated with more CP.Fragile families, childbearing, nonmarital childbearing, fartherhood, fathers, corporal punishment, behavior problems, stress, depression

Vacuum Stability of Standard Model^{++}

The latest results of the ATLAS and CMS experiments point to a preferred narrow Higgs mass range (m_h \simeq 124 - 126 GeV) in which the effective potential of the Standard Model (SM) develops a vacuum instability at a scale 10^{9} -10^{11} GeV, with the precise scale depending on the precise value of the top quark mass and the strong coupling constant. Motivated by this experimental situation, we present here a detailed investigation about the stability of the SM^{++} vacuum, which is characterized by a simple extension of the SM obtained by adding to the scalar sector a complex SU(2) singlet that has the quantum numbers of the right-handed neutrino, H", and to the gauge sector an U(1) that is broken by the vacuum expectation value of H". We derive the complete set of renormalization group equations at one loop. We then pursue a numerical study of the system to determine the triviality and vacuum stability bounds, using a scan of 10^4 random set of points to fix the initial conditions. We show that, if there is no mixing in the scalar sector, the top Yukawa coupling drives the quartic Higgs coupling to negative values in the ultraviolet and, as for the SM, the effective potential develops an instability below the Planck scale. However, for a mixing angle -0.35 \alt \alpha \alt -0.02 or 0.01 \alt \alpha \alt 0.35, with the new scalar mass in the range 500 GeV \alt m_{h"} \alt 8 TeV, the SM^{++} ground state can be absolutely stable up to the Planck scale. These results are largely independent of TeV-scale free parameters in the model: the mass of the non-anomalous U(1) gauge boson and its branching fractions.Comment: 17 revtex pages, 8 figures; to be published in JHE

Reusing Data and Metadata to Create New Metadata Through Machine-Learning & Other Programmatic Methods

Recent improvements in natural language processing (NLP) enable metadata to be created programmatically from reused original metadata or even the dataset itself. Transfer-learning applied to NLP has greatly improved performance and reduced training data requirements. In this talk, well compare machine-generated metadata to human-generated metadata and discuss characteristics of metadata and data archives that affect suitability for machine-learning reuse of metadata. Where as human-generated metadata is often populated once, populated from the perspective of data supplier, populated by many individuals with different words for the same thing, and limited in length, machine-generated metadata can be updated any number of times, generated from the perspective of any user, constrained to a standardized set of terms that can be evolved over time, and be any length required. Machine-learning generated metadata offers benefits but also additional needs in terms of version control, process transparency, human-computer interaction, and IT requirements. As a successful example, well discuss how a dataset of abstracts and associated human-tagged keywords from a standardized list of several thousand keywords were used to create a machine-learning model that predicted keyword metadata for open-source code projects on code.nasa.gov. Well also discuss a less successful example from data.nasa.gov to show how data archive architecture and characteristics of initial metadata can be strong controls on how easy it is to leverage programmatic methods to reuse metadata to create additional metadata

Neighborhood Race and Nearby Race Affects Neighborhood Changes in Relative Status and Stability: Testing an Ecological Extension of the Neighborhood Projection Thesis

Current work tests an ecological extension of Ellen’s (2000a) neighborhood projection thesis which explains individual-level moving behavior in response to neighborhood racial composition. It posits that residents anticipate future erosions in local services and amenities based on current and expected future racial composition. The ecological extension tested here anticipates declines in relative neighborhood status and neighborhood residential stability where the population is more predominantly African American initially, or becomes more African American over a decade, or is initially surrounded by more predominantly African American neighborhoods. All three of these race effects have generated mixed results in earlier studies. Looking at a decade of change (1990 to 2000) for two mid-Atlantic central cities (Baltimore (MD) and Philadelphia (PA)), results in both cities confirmed that relative status was more likely to decline if adjoining neighborhoods were more predominantly African American initially, or if the neighborhood was becoming more predominantly African American during the period. The impacts of racial composition on stability changes were neither uniform across cities nor uniformly adverse. At least for neighborhood changes in status, results support the proposed extension of Ellen’s model to the neighborhood level, and underscored the spatial externalities arising from nearby populations of color

Status and Distribution of the Gapped Ringed Crayfish, Orconectes neglectus chaenodactylus, in Arkansas

Orconectes neglectus chaenodactylus, the gapped ringed crayfish, is an uncommon and poorly-known, stream-dwelling crayfish that is endemic to the central White River basin of Arkansas and Missouri. This study surveyed a semi-random selection of stream sites in the Arkansas portion of this range in order to characterize the crayfish communities and evaluate the status of O. n. chaenodactylus in Arkansas. Collections of a total of 1,107 individual crayfish specimens were made at 45 sites, including 497 O. n. chaenodactylus from 21 sites. Orconectes punctimanus was the crayfish species most commonly associated with O. n. chaenodactylus, occurring at 71% of sites occupied by O. n. chaenodactylus. Orconectes n. chaenodactylus was found in streams not significantly different from the median characteristics of streams sampled in the study. It is our opinion that O. n. chaenodactylus is uncommon in Arkansas, and of only moderate concern due to its limited distribution in the state

Dynamic Chemical Shift Imaging for Image-Guided Thermal Therapy

Magnetic resonance temperature imaging (MRTI) is recognized as a noninvasive means to provide temperature imaging for guidance in thermal therapies. The most common method of estimating temperature changes in the body using MR is by measuring the water proton resonant frequency (PRF) shift. Calculation of the complex phase difference (CPD) is the method of choice for measuring the PRF indirectly since it facilitates temperature mapping with high spatiotemporal resolution. Chemical shift imaging (CSI) techniques can provide the PRF directly with high sensitivity to temperature changes while minimizing artifacts commonly seen in CPD techniques. However, CSI techniques are currently limited by poor spatiotemporal resolution. This research intends to develop and validate a CSI-based MRTI technique with intentional spectral undersampling which allows relaxed parameters to improve spatiotemporal resolution. An algorithm based on autoregressive moving average (ARMA) modeling is developed and validated to help overcome limitations of Fourier-based analysis allowing highly accurate and precise PRF estimates. From the determined acquisition parameters and ARMA modeling, robust maps of temperature using the k-means algorithm are generated and validated in laser treatments in ex vivo tissue. The use of non-PRF based measurements provided by the technique is also investigated to aid in the validation of thermal damage predicted by an Arrhenius rate dose model

Multi-Axis Identifiability Using Single-Surface Parameter Estimation Maneuvers on the X-48B Blended Wing Body

The problem of parameter estimation on hybrid-wing-body type aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aero- dynamic control effectors that act in coplanar motion. This fact adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of system inputs must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, asymmetric, single-surface maneuvers are used to excite multiple axes of aircraft motion simultaneously. Time history reconstructions of the moment coefficients computed by the solved regression models are then compared to each other in order to assess relative model accuracy. The reduced flight-test time required for inner surface parameter estimation using multi-axis methods was found to come at the cost of slightly reduced accuracy and statistical confidence for linear regression methods. Since the multi-axis maneuvers captured parameter estimates similar to both longitudinal and lateral-directional maneuvers combined, the number of test points required for the inner, aileron-like surfaces could in theory have been reduced by 50%. While trends were similar, however, individual parameters as estimated by a multi-axis model were typically different by an average absolute difference of roughly 15-20%, with decreased statistical significance, than those estimated by a single-axis model. The multi-axis model exhibited an increase in overall fit error of roughly 1-5% for the linear regression estimates with respect to the single-axis model, when applied to flight data designed for each, respectively

Lateral-Directional Parameter Estimation on the X-48B Aircraft Using an Abstracted, Multi-Objective Effector Model

The problem of parameter estimation on hybrid-wing-body aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aerodynamic control effectors that act in coplanar motion. This adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of flight and simulation data must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, time-decorrelation techniques are applied to a model structure selected through stepwise regression for simulated and flight-generated lateral-directional parameter estimation data. A virtual effector model that uses mathematical abstractions to describe the multi-axis effects of clamshell surfaces is developed and applied. Comparisons are made between time history reconstructions and observed data in order to assess the accuracy of the regression model. The Cram r-Rao lower bounds of the estimated parameters are used to assess the uncertainty of the regression model relative to alternative models. Stepwise regression was found to be a useful technique for lateral-directional model design for hybrid-wing-body aircraft, as suggested by available flight data. Based on the results of this study, linear regression parameter estimation methods using abstracted effectors are expected to perform well for hybrid-wing-body aircraft properly equipped for the task