Theoretical and lidar studies of the density response of the mesospheric sodium layer to gravity wave perturbations

The density response of atmospheric layers to gravity waves is developed in two forms, an exact solution and a perturbation series solution. The degree of nonlinearity in the layer density response is described by the series solution whereas the exact solution gives insight into the nature of the responses. Density perturbation in an atmospheric layer are shown to be substantially greater than the atmospheric density perturbation associated with the propagation of a gravity wave. Because of the density gradients present in atmospheric layers, interesting effects were observed such as a phase reversal in the linear layer response which occurs near the layer peak. Once the layer response is understood, the sodium layer can be used as a tracer of atmospheric wave motions. A two dimensional digital signal processing technique was developed. Both spatial and temporal filtering are utilized to enhance the resolution by decreasing shot noise by more han 10 dB. Many of the features associated with a layer density response to gravity waves were observed in high resolution density profiles of the mesospheric sodium layer. These include nonlinearities as well as the phase reversal in the linear layer response

Operating manual for the RRL 8 channel data logger

A data collection device which takes measurements from external sensors at user specified time intervals is described. Three sensor ports are dedicated to temperature, air pressure, and dew point. Five general purpose sensor ports are provided. The user specifies when the measurements are recorded as well as when the information is read or stored in a minicomputer or a paper tape

Unveiling Su Aurigae in the near Infrared: New high spatial resolution results using Adaptive Optics

We present here new results on circumstellar nebulosity around SU Aurigae, a T-Tauri star of about 2 solar mass and 5 Myrs old at 152 pc in the J, H and K bands using high resolution adaptive optics imaging (0\farcs30) with the Penn state IR Imaging Spectrograph (PIRIS) at the 100 inch Mt. Wilson telescope. A comparison with HST STIS optical (0.2 to 1.1 micron) images shows that the orientation of the circumstellar nebulosity in the near-IR extends from PAs 210 to 270 degrees in H and K bands and up to 300 degrees in the J band. We call the circumstellar nebulosity seen between 210 to 270 degrees as 'IR nebulosity'. We find that the IR nebulosity (which extends up to 3.5 arcsecs in J band and 2.5 arcsecs in the K band) is due to scattered light from the central star. The IR nebulosity is either a cavity formed by the stellar outflows or part of the circumstellar disk. We present a schematic 3-dimensional geometrical model of the disk and jet of SU Aur based on STIS and our near-IR observations. According to this model the IR nebulosity is a part of the circumstellar disk seen at high inclination angles. The extension of the IR nebulosity is consistent with estimates of the disk diameter of 50 to 400 AU in radius, from earlier mm, K band interferometric observations and SED fittings.Comment: Accepted for publications in the Astronomical Journal, to appear in the May issue of the Journa

Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder

Pharmacogenomic tests used to guide clinical treatment for major depressive disorder (MDD) must be thoroughly validated. One important assessment of validity is the ability to predict medication blood levels, which reflect altered metabolism. Historically, the metabolic impact of individual genes has been evaluated; however, we now know that multiple genes are often involved in medication metabolism. Here, we evaluated the ability of individual pharmacokinetic genes (CYP2C19, CYP2D6, CYP3A4) and a combinatorial pharmacogenomic test (GeneSight Psychotropic(R); weighted assessment of all three genes) to predict citalopram/escitalopram blood levels in patients with MDD. Patients from the Genomics Used to Improve DEpression Decisions (GUIDED) trial who were taking citalopram/escitalopram at screening and had available blood level data were included (N=191). In multivariate analysis of the individual genes and combinatorial pharmacogenomic test separately (adjusted for age, smoking status), the F statistic for the combinatorial pharmacogenomic test was 1.7 to 2.9-times higher than the individual genes, showing that it explained more variance in citalopram/escitalopram blood levels. In multivariate analysis of the individual genes and combinatorial pharmacogenomic test together, only the combinatorial pharmacogenomic test remained significant. Overall, this demonstrates that the combinatorial pharmacogenomic test was a superior predictor of citalopram/escitalopram blood levels compared to individual genes

In-plane effects on segmented-mirror control

Extremely large optical telescopes are being designed with primary mirrors composed of hundreds of segments. The “out-of-plane” piston, tip, and tilt degrees of freedom of each segment are actively controlled using feedback from relative height measurements between neighboring segments. The “in-plane” segment translations and clocking (rotation) are not actively controlled; however, in-plane motions affect the active control problem in several important ways, and thus need to be considered. We extend earlier analyses by constructing the “full” interaction matrix that relates the height, gap, and shear motion at sensor locations to all six degrees of freedom of segment motion, and use this to consider three effects. First, in-plane segment clocking results in height discontinuities between neighboring segments that can lead to a global control system response. Second, knowledge of the in-plane motion is required both to compensate for this effect and to compensate for sensor installation errors, and thus, we next consider the estimation of in-plane motion and the associated noise propagation characteristics. In-plane motion can be accurately estimated using measurements of the gap between segments, but with one unobservable mode in which every segment clocks by an equal amount. Finally, we examine whether in-plane measurements (gap and/or shear) can be used to estimate out-of-plane segment motion; these measurements can improve the noise multiplier for the “focus-mode” of the segmented-mirror array, which involves pure dihedral angle changes between segments and is not observable with only height measurements

Resolving the delta Andromedae spectroscopic binary with direct imaging

We present a direct image of the innermost companion to the red giant delta Andromedae using the Stellar Double Coronagraph at the Palomar Observatory. We use a Markov chain Monte Carlo based algorithm to simultaneously reduce the data and perform astrometry and photometry of the companion. We determine that the companion is most likely a main-sequence K-type star and is certainly not the previously hypothesized white dwarf.Comment: ApJ, accepted. 10 pages, 3 figure

AS-777-14 Resolution on Proposal to Establish the Strawberry Sustainability Research and Education Center

That the Academic Senate endorses the establishment of the Strawberry Sustainability Research Education Center

Surprisingly Little O VI Emission Arises in the Local Bubble

This paper reports the first study of the O VI resonance line emission (1032, 1038 Angstroms) originating in the Local Bubble (or Local Hot Bubble) surrounding the solar neighborhood. In spite of the fact that O VI absorption within the Local Bubble has been observed, no resonance line emission was detected during our 230 ksec Far Ultraviolet Spectroscopic Explorer observation toward a ``shadowing'' filament in the southern Galactic hemisphere. As a result, tight 2 sigma upper limits are set on the intensities in the 1032 and 1038 Angstrom emission lines: 500 and 530 photons cm^{-2} s^{-1} sr^{-1}, respectively. These values place strict constraints on models and simulations. They suggest that the O VI-bearing plasma and the X-ray emissive plasma reside in distinct regions of the Local Bubble and are not mixed in a single plasma, whether in equilibrium with T ~ 10^6 K or highly overionized with T ~ 4 to 6 x 10^4 K. If the line of sight intersects multiple cool clouds within the Local Bubble, then the results also suggest that hot/cool transition zones differ from those in current simulations. With these intensity upper limits, we establish limits on the electron density, thermal pressure, pathlength, and cooling timescale of the O VI-bearing plasma in the Local Bubble. Furthermore, the intensity of O VI resonance line doublet photons originating in the Galactic thick disk and halo is determined (3500 to 4300 photons cm^{-2} s^{-1} sr^{-1}), and the electron density, thermal pressure, pathlength, and cooling timescale of its O VI-bearing plasma are calculated. The pressure in the Galactic halo's O VI-bearing plasma (3100 to 3800 K cm^{-3}) agrees with model predictions for the total pressure in the thick disk/lower halo. We also report the results of searches for other emission lines.Comment: accepted by ApJ, scheduled for May 2003, replacement astro-ph submission corrects typos and grammatical errors in original versio

Semi-supervised Analysis of Human fMRI Data

Kernel Canonical Correlation Analysis (KCCA) is a general technique for subspace learning that incorporates principal components analysis (PCA) and Fisher linear discriminant analysis (LDA) as special cases. By finding directions that maximize correlation, CCA learns representations tied more closely to underlying process generating the the data and can ignore high-variance noise directions. However, for data where acquisition in a given modality is expensive or otherwise limited, CCA may suffer from small sample effects. We propose to use semisupervised Laplacian regularization to utilize data that are present in only one modality. This approach is able to find highly correlated directions that also lie along the data manifold, resulting in a more robust estimate of correlated subspaces. Functional magnetic resonance imaging (fMRI) acquired data are naturally amenable to subspace techniques as data are well aligned. fMRI data of the human brain are a particularly interesting candidate. In this study we implemented various supervised and semi-supervised versions of CCA on human fMRI data, with regression to single and multivariate labels (corresponding to video content subjects viewed during the image acquisition). In each variate condition, the semi-supervised variants of CCA performed better than the supervised variants, including a supervised variant with Laplacian regularization. We additionally analyze the weights learned by the regression in order to infer brain regions that are important to different types of visual processing