Infrared scanner Patent

Infrared scanning system for maintaining spacecraft orientation with earth referenc

Delamination growth in composite materials

The Double Cantilever Beam (DCB) and the End Notched Flexure (ENF) specimens are employed to characterize MODE I and MODE II interlaminar fracture resistance of graphite/epoxy (CYCOM 982) and graphite/PEEK (APC2) composites. Sizing of test specimen geometries to achieve crack growth in the linear elastic regime is presented. Data reduction schemes based upon beam theory are derived for the ENF specimen and include the effects of shear deformation and friction between crack surfaces on compliance, C, and strain energy release rate, G sub II. Finite element (FE) analyses of the ENF geometry including the contact problem with friction are presented to assess the accuracy of beam theory expressions for C and G sub II. Virtual crack closure techniques verify that the ENF specimen is a pure Mode II test. Beam theory expressions are shown to be conservative by 20 to 40 percent for typical unidirectional test specimen geometries. A FE parametric study investigating the influence of delamination length and depth, span, thickness and material properties on G sub II is presented. Mode I and II interlaminar fracture test results are presented. Important experimental parameters are isolated, such as precracking techniques, rate effects, and nonlinear load-deflection response. It is found that subcritical crack growth and inelastic materials behavior, responsible for the observed nonlinearities, are highly rate-dependent phenomena with high rates generally leading to linear elastic response

Delamination growth in composite materials

Research related to growth of an imbedded through-width delamination (ITWD) in a compression loaded composite structural element is presented. Composites with widely different interlaminar fracture resistance were examined, viz., graphite/epoxy (CYCOM 982) and graphite/PEEK (APC-2). The initial part of the program consisted of characterizing the material in tension, compression and shear mainly to obtain consistent material properties for analysis, but also as a check of the processing method developed for the thermoplastic APC-2 material. The characterization of the delamination growth in the ITWD specimen, which for the unidirectional case is essentially a mixed Mode 1 and 2 geometry, requires verified mixed-mode growth criteria for the two materials involved. For this purpose the main emphasis during this part of the investigation was on Mode 1 and 2 fracture specimens, namely the Double Cantilever Beam (DCB) and End Notched Flexure (ENF) specimens

Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Temperature Dependence of Radiation Induced Conductivity in Insulators

We report on measurements of Radiation Induced Conductivity (RIC) of thin film Low Density Polyethylene (LDPE) samples. RIC occurs when incident ionizing radiation deposits energy in a material and excites electrons into conduction states. RIC is calculated as the difference in sample conductivity under an incident flux and “dark current” conductivity under no incident radiation. The primary focus of this study is the temperature dependence of the steady state RIC over a wide range of absorbed dose rates, from cryogenic temperatures to well above room temperature. The measured RIC values are compared to theoretical predictions of dose rate and temperature dependence based on photoconductivity models developed for localized trap states in disordered semiconductors. We also investigated the variation of RIC as a function of material, applied electric field, and incident beam energy parameters

Regulatory control and the costs and benefits of biochemical noise

Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. How protein concentration fluctuations affect the growth rate of a population of cells, is, however, a wide open question. We present a mathematical model that makes it possible to quantify the effect of protein concentration fluctuations on the growth rate of a population of genetically identical cells. The model predicts that the population's growth rate depends on how the growth rate of a single cell varies with protein concentration, the variance of the protein concentration fluctuations, and the correlation time of these fluctuations. The model also predicts that when the average concentration of a protein is close to the value that maximizes the growth rate, fluctuations in its concentration always reduce the growth rate. However, when the average protein concentration deviates sufficiently from the optimal level, fluctuations can enhance the growth rate of the population, even when the growth rate of a cell depends linearly on the protein concentration. The model also shows that the ensemble or population average of a quantity, such as the average protein expression level or its variance, is in general not equal to its time average as obtained from tracing a single cell and its descendants. We apply our model to perform a cost-benefit analysis of gene regulatory control. Our analysis predicts that the optimal expression level of a gene regulatory protein is determined by the trade-off between the cost of synthesizing the regulatory protein and the benefit of minimizing the fluctuations in the expression of its target gene. We discuss possible experiments that could test our predictions.Comment: Revised manuscript;35 pages, 4 figures, REVTeX4; to appear in PLoS Computational Biolog

The Apache Point Observatory Galactic Evolution Experiment (APOGEE) Spectrographs

We describe the design and performance of the near-infrared (1.51--1.70 micron), fiber-fed, multi-object (300 fibers), high resolution (R = lambda/delta lambda ~ 22,500) spectrograph built for the Apache Point Observatory Galactic Evolution Experiment (APOGEE). APOGEE is a survey of ~ 10^5 red giant stars that systematically sampled all Milky Way populations (bulge, disk, and halo) to study the Galaxy's chemical and kinematical history. It was part of the Sloan Digital Sky Survey III (SDSS-III) from 2011 -- 2014 using the 2.5 m Sloan Foundation Telescope at Apache Point Observatory, New Mexico. The APOGEE-2 survey is now using the spectrograph as part of SDSS-IV, as well as a second spectrograph, a close copy of the first, operating at the 2.5 m du Pont Telescope at Las Campanas Observatory in Chile. Although several fiber-fed, multi-object, high resolution spectrographs have been built for visual wavelength spectroscopy, the APOGEE spectrograph is one of the first such instruments built for observations in the near-infrared. The instrument's successful development was enabled by several key innovations, including a "gang connector" to allow simultaneous connections of 300 fibers; hermetically sealed feedthroughs to allow fibers to pass through the cryostat wall continuously; the first cryogenically deployed mosaic volume phase holographic grating; and a large refractive camera that includes mono-crystalline silicon and fused silica elements with diameters as large as ~ 400 mm. This paper contains a comprehensive description of all aspects of the instrument including the fiber system, optics and opto-mechanics, detector arrays, mechanics and cryogenics, instrument control, calibration system, optical performance and stability, lessons learned, and design changes for the second instrument.Comment: 81 pages, 67 figures, PASP, accepte

Genetic determinants of cortical structure (thickness, surface area and volumes) among disease free adults in the CHARGE Consortium

Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging

Galaxy Collisions - Dawn of a New Era

The study of colliding galaxies has progressed rapidly in the last few years, driven by observations with powerful new ground and space-based instruments. These instruments have used for detailed studies of specific nearby systems, statistical studies of large samples of relatively nearby systems, and increasingly large samples of high redshift systems. Following a brief summary of the historical context, this review attempts to integrate these studies to address the following key issues. What role do collisions play in galaxy evolution, and how can recently discovered processes like downsizing resolve some apparently contradictory results of high redshift studies? What is the role of environment in galaxy collisions? How is star formation and nuclear activity orchestrated by the large scale dynamics, before and during merger? Are novel modes of star formation involved? What are we to make of the association of ultraluminous X-ray sources with colliding galaxies? To what do degree do mergers and feedback trigger long-term secular effects? How far can we push the archaeology of individual systems to determine the nature of precursor systems and the precise effect of the interaction? Tentative answers to many of these questions have been suggested, and the prospects for answering most of them in the next few decades are good.Comment: 44 pages, 9 figures, review article in press for Astrophysics Update Vol.