Thermoplastics for aircraft interiors

The goal for this contract is the development of processes and techniques for molding thermally stable, fire retardant, low smoke emitting polymeric materials. Outlined in this presentation are: (1) the typical molding types; (2) a program schedule; (3) physical properties of molding types with the test methods to be used; (4) general properties of injection molding materials; and (5) preliminary materials selection

Learning curves for Gaussian process regression: Approximations and bounds

We consider the problem of calculating learning curves (i.e., average generalization performance) of Gaussian processes used for regression. On the basis of a simple expression for the generalization error, in terms of the eigenvalue decomposition of the covariance function, we derive a number of approximation schemes. We identify where these become exact, and compare with existing bounds on learning curves; the new approximations, which can be used for any input space dimension, generally get substantially closer to the truth. We also study possible improvements to our approximations. Finally, we use a simple exactly solvable learning scenario to show that there are limits of principle on the quality of approximations and bounds expressible solely in terms of the eigenvalue spectrum of the covariance function.Comment: 25 pages, 10 figure

A generalized Fellner-Schall method for smoothing parameter estimation with application to Tweedie location, scale and shape models

We consider the estimation of smoothing parameters and variance components in models with a regular log likelihood subject to quadratic penalization of the model coefficients, via a generalization of the method of Fellner (1986) and Schall (1991). In particular: (i) we generalize the original method to the case of penalties that are linear in several smoothing parameters, thereby covering the important cases of tensor product and adaptive smoothers; (ii) we show why the method's steps increase the restricted marginal likelihood of the model, that it tends to converge faster than the EM algorithm, or obvious accelerations of this, and investigate its relation to Newton optimization; (iii) we generalize the method to any Fisher regular likelihood. The method represents a considerable simplification over existing methods of estimating smoothing parameters in the context of regular likelihoods, without sacrificing generality: for example, it is only necessary to compute with the same first and second derivatives of the log-likelihood required for coefficient estimation, and not with the third or fourth order derivatives required by alternative approaches. Examples are provided which would have been impossible or impractical with pre-existing Fellner-Schall methods, along with an example of a Tweedie location, scale and shape model which would be a challenge for alternative methods

Source distribution analysis of magnetic microscopy maps of geological samples

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 52-53).Superconducting quantum interference devices (SQUID) are currently the most sensitive magnetometers for geological samples. Standard SQUID magnetometers are able to directly estimate the net moment of a sample, while SQUID microscopes require complex inversion of maps of the magnetic field above the sample. In order to extract magnetization information from SQUID microscope measurements, it is customary to model the sample as a distribution of magnetic dipoles. The calculations required for this operation in the space domain typically involve a pseudo inversion which becomes problematic due to the large amount of data, measurement noise, inherent loss of information in computational discretization, and ambiguity in determining an optimized "best" solution. To ameliorate these problems, we have implemented several regularization techniques and constraints. Using synthetic, computationally generated measurements, our investigation demonstrates that Tikhonov regularization with a high pass filter matrix performs better than unregularized least square methods, truncated singular value decomposition, and Tikhonov regularization using an identity matrix (minimum norm). Our study also gives insight regarding the benefit and cost of setting various constraints. Our findings are then tested on real measurements of a sample of shocked basalt and a test sample comprised of a section of a refrigerator magnet.by Joseph B. Silverman.S.B

The Effects of Negative Legacies on the Adjustment of Parentally Bereaved Children and Adolescents

This is a report of a qualitative analysis of a sample of bereaved families in which one parent died and in which children scored in the clinical range on the Child Behavior Check List. The purpose of this analysis was to learn more about the lives of these children. They were considered to be at risk of developing emotional and behavioral problems associated with the death. We discovered that many of these “high risk” children had a continuing bond with the deceased that was primarily negative and troubling for them in contrast to a comparison group of children not at risk from the same study. Five types of legacies, not mutually exclusive, were identified: health related, role related, personal qualities, legacy of blame, and an emotional legacy. Coping behavior on the part of the surviving parent seemed to make a difference in whether or not a legacy was experienced as negative

SOCIAL CONNECTEDNESS, COMMUNITY PARTICIPATION, AND HEALTH

Persons with disabilities (PWD) experience social, economic, and environmental disadvantages which have contributed to marginalization, health disparities, and challenges with community participation. Various forms of social closeness appear to serve as protective factors against physical and mental health for the non-disabled population, but it is unclear whether social connectedness is associated with community participation and health for PWD. This within-subjects, correlational design study used survey and Ecological Momentary Assessment (EMA) data from a sample of persons with mobility impairments (MI) to determine the direct and indirect effect of social connectedness and participation on health, the barriers and facilitators to participation that contribute to social connectedness, and whether social connectedness explains well-being during socializing experiences. Results indicated that social connectedness predicted health related outcomes and mediated the relationship between measures of community participation and mental health. Social connectedness can be best predicted by examining one\u27s sense of community integration and the severity of personal and environmental barriers. Finally, the effect of socializing on in-the-moment and later-day well-being does not seem to be significantly affected by social connectedness. Limitations and future directions are discussed

Chiasma

Newspaper reporting on events at the Boston University School of Medicine in the 1960s