A Preliminary Discussion of the Kinematics of BHB and RR Lyrae Stars near the North Galactic Pole

The radial velocity dispersion of 67 RR Lyrae variable and blue horizontal branch (BHB) stars that are more than 4 kpc above the galactic plane at the North Galactic Pole is 110 km/sec and shows no trend with Z (the height above the galactic plane). Nine stars with Z < 4 kpc show a smaller velocity dispersion (40 +/-9 km/sec) as is to be expected if they mostly belong to a population with a flatter distribution. Both RR Lyrae stars and BHB stars show evidence of stream motion; the most significant is in fields RR2 and RR3 where 24 stars in the range 4.0 < Z < 11.0 kpc have a mean radial velocity of -59 +/- 16 km/sec. Three halo stars in field RR 2 appear to be part of a moving group with a common radial velocity of -90 km/sec. The streaming phenomenon therefore occurs over a range of spatial scales. The BHB and RR Lyrae stars in our sample both have a similar range of metallicity (-1.2 < [Fe/H] < -2.2). Proper motions of BHB stars in fields SA 57 (NGP) and the Anticenter field (RR 7) (both of which lie close to the meridional plane of the Galaxy) show that the stars that have Z 4 kpc have a Galactic V motion that is < -200 km/sec and which is characteristic of the halo. Thus the stars that have a flatter distribution are really halo stars and not members of the metal-weak thick-disk.Comment: Accepted for publication in the March 1996 AJ. 15 pages, AASTeX V4.0 latex format (including figures), 2 eps figures, 2 separate AASTeX V4.0 latex table

Exploratory analysis using machine learning to predict for chest wall pain in patients with stage I non-small-cell lung cancer treated with stereotactic body radiation therapy.

Background and purposeChest wall toxicity is observed after stereotactic body radiation therapy (SBRT) for peripherally located lung tumors. We utilize machine learning algorithms to identify toxicity predictors to develop dose-volume constraints.Materials and methodsTwenty-five patient, tumor, and dosimetric features were recorded for 197 consecutive patients with Stage I NSCLC treated with SBRT, 11 of whom (5.6%) developed CTCAEv4 grade ≥2 chest wall pain. Decision tree modeling was used to determine chest wall syndrome (CWS) thresholds for individual features. Significant features were determined using independent multivariate methods. These methods incorporate out-of-bag estimation using Random forests (RF) and bootstrapping (100 iterations) using decision trees.ResultsUnivariate analysis identified rib dose to 1&nbsp;cc&nbsp;&lt;&nbsp;4000&nbsp;cGy (P&nbsp;=&nbsp;0.01), chest wall dose to 30&nbsp;cc&nbsp;&lt;&nbsp;1900&nbsp;cGy (P&nbsp;=&nbsp;0.035), rib Dmax&nbsp;&lt;&nbsp;5100&nbsp;cGy (P&nbsp;=&nbsp;0.05) and lung dose to 1000&nbsp;cc&nbsp;&lt;&nbsp;70&nbsp;cGy (P&nbsp;=&nbsp;0.039) to be statistically significant thresholds for avoiding CWS. Subsequent multivariate analysis confirmed the importance of rib dose to 1&nbsp;cc, chest wall dose to 30&nbsp;cc, and rib Dmax. Using learning-curve experiments, the dataset proved to be self-consistent and provides a realistic model for CWS analysis.ConclusionsUsing machine learning algorithms in this first of its kind study, we identify robust features and cutoffs predictive for the rare clinical event of CWS. Additional data in planned subsequent multicenter studies will help increase the accuracy of multivariate analysis

The Relationship Between Galaxies and Low Redshift Weak Lyman alpha Absorbers in the Directions of H1821+643 and PG1116+215

To study the nature of low z Lya absorbers in the spectra of QSOs, we have obtained high signal-to-noise UV spectra of H 1821+643 (z = 0.297) and PG 1116+215 (z = 0.177) with the GHRS on the HST. The spectra have minimum S/N of 70-100 and 3 sigma limiting equivalent widths of 50-75 mA. We detect 26 Lya lines with Wr > 50 mA toward H1821+643 and 13 toward PG1116+215, which implies a density of 102+/-16 lines per unit redshift. The two-point correlation function shows marginal evidence of clustering on ~500 km/s scales, but only if the weakest lines are excluded. We have also used the WIYN Observatory to measure galaxy redshifts in the ~1 degree fields centered on each QSO. We find 17 galaxy-absorber pairs within projected distances of 1 Mpc with velocity separations of 350 km/s or less. Monte Carlo simulations show that if the Lya lines are randomly distributed, the probability of observing this many close pairs is 3.6e-5. We find that all galaxies with projected distances of 600 kpc or less have associated Lya absorbers within 1000 km/s, and the majority of these galaxies have absorbers within 350 km/s. We also find that the Lya equivalent width is anticorrelated with the projected distance of the nearest galaxy out to at least 600 kpc, but this should be interpreted cautiously because there are potential selection biases. Statistical tests using the entire sample also indicate that the absorbers are not randomly distributed. We discuss the nature of the Lya absorbers in light of the new data.Comment: Accepted for publication in ApJ. 17 pages plus 11 tables and 17 figure

The BTC40 Survey for Quasars at 4.8 < z < 6

The BTC40 Survey for high-redshift quasars is a multicolor search using images obtained with the Big Throughput Camera (BTC) on the CTIO 4-m telescope in V, I, and z filters to search for quasars at redshifts of 4.8 < z < 6. The survey covers 40 sq. deg. in B, V, & I and 36 sq. deg. in z. Limiting magnitudes (3 sigma) reach to V = 24.6, I = 22.9 and z = 22.9. We used the (V-I) vs. (I-z) two-color diagram to select high-redshift quasar candidates from the objects classified as point sources in the imaging data. Follow-up spectroscopy with the AAT and CTIO 4-m telescopes of candidates having I < 21.5 has yielded two quasars with redshifts of z = 4.6 and z = 4.8 as well as four emission line galaxies with z = 0.6. Fainter candidates have been identified down to I = 22 for future spectroscopy on 8-m class telescopes.Comment: 27 pages, 8 figures; Accepted for publication in the Astronomical Journa

Building more accurate decision trees with the additive tree.

The expansion of machine learning to high-stakes application domains such as medicine, finance, and criminal justice, where making informed decisions requires clear understanding of the model, has increased the interest in interpretable machine learning. The widely used Classification and Regression Trees (CART) have played a major role in health sciences, due to their simple and intuitive explanation of predictions. Ensemble methods like gradient boosting can improve the accuracy of decision trees, but at the expense of the interpretability of the generated model. Additive models, such as those produced by gradient boosting, and full interaction models, such as CART, have been investigated largely in isolation. We show that these models exist along a spectrum, revealing previously unseen connections between these approaches. This paper introduces a rigorous formalization for the additive tree, an empirically validated learning technique for creating a single decision tree, and shows that this method can produce models equivalent to CART or gradient boosted stumps at the extremes by varying a single parameter. Although the additive tree is designed primarily to provide both the model interpretability and predictive performance needed for high-stakes applications like medicine, it also can produce decision trees represented by hybrid models between CART and boosted stumps that can outperform either of these approaches

A toolkit of mechanism and context independent widgets

Most human-computer interfaces are designed to run on a static platform (e.g. a workstation with a monitor) in a static environment (e.g. an office). However, with mobile devices becoming ubiquitous and capable of running applications similar to those found on static devices, it is no longer valid to design static interfaces. This paper describes a user-interface architecture which allows interactors to be flexible about the way they are presented. This flexibility is defined by the different input and output mechanisms used. An interactor may use different mechanisms depending upon their suitability in the current context, user preference and the resources available for presentation using that mechanism

Expert-Augmented Machine Learning

Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications

Quasar Candidates in the Hubble Deep Field

We focus on the search for unresolved faint quasars and AGN in the crude combine images using a multicolor imaging analysis that has proven very successful in recent years. Quasar selection was carried out both in multicolor space and in "profile space," defined as the multi-parameter space formed by the radial profiles of the objects in the different images. By combining the dither frames available for each filter, we were able to obtain well-sampled radial profiles of the objects and measure their deviation from that of a stellar source. We also generated synthetic quasar spectra in the range 1.0 < z < 5.5 and computed expected quasar colors. We determined that the data are 90% complete for point sources at 26.2, 28.0, 27.8, 26.8 in the F300W, F450W, F606W and F814W filters, respectively. We find 41 compact objects in the HDF: 8 pointlike objects with colors consistent with quasars or stars, 18 stars, and 15 slightly resolved objects, 12 of which have colors consistent with quasars or stars. We estimate the upper limit of unresolved and slightly resolved quasars/AGNs with V < 27.0 and z < 3.5 to be 20 objects (16,200 per deg^2). We find good agreement among authors on the number of stars and the lack of quasar candidates with z > 3.5. We find more quasar candidates than previous work because of our more extensive modeling and use of all of the available color information. (abridged)Comment: We have clarified our discussion and conclusions, added some references and removed the appendix, which is now available from the first author. 37 pages including 10 embedded postscript figures and 6 tables. To appear in the Feb. 99 issue of A

The Indo-U.S. Library of Coude Feed Stellar Spectra

We have obtained spectra for 1273 stars using the 0.9m Coud\'e Feed telescope at Kitt Peak National Observatory. This telescope feeds the coud\'e spectrograph of the 2.1m telescope. The spectra have been obtained with the #5 camera of the coud\'e spectrograph and a Loral 3K X 1K CCD. Two gratings have been used to provide spectral coverage from 3460 \AA to 9464 \AA, at a resolution of $\sim$1\AA FWHM and at an original dispersion of 0.44 \AA/pixel. For 885 stars we have complete spectra over the entire 3460 \AA to 9464 \AA wavelength region (neglecting small gaps of $<$ 50 \AA), and partial spectral coverage for the remaining stars. The 1273 stars have been selected to provide broad coverage of the atmospheric parameters T$_{eff}$, log g, and [Fe/H], as well as spectral type. The goal of the project is to provide a comprehensive library of stellar spectra for use in the automated classification of stellar and galaxy spectra and in galaxy population synthesis. In this paper we discuss the characteristics of the spectral library, viz., details of the observations, data reduction procedures, and selection of stars. We also present a few illustrations of the quality and information available in the spectra. The first version of the complete spectral library is now publicly available from the National Optical Astronomy Observatory (NOAO) via FTP and HTTP.Comment: 18 pages, 6 figures, 4 table