Program listing for the REEDM (Rocket Exhaust Effluent Diffusion Model) computer program

The program listing for the REEDM Computer Program is provided. A mathematical description of the atmospheric dispersion models, cloud-rise models, and other formulas used in the REEDM model; vehicle and source parameters, other pertinent physical properties of the rocket exhaust cloud and meteorological layering techniques; user's instructions for the REEDM computer program; and worked example problems are contained in NASA CR-3646

User's manual for the REEDM (Rocket Exhaust Effluent Diffusion Model) computer program

The REEDM computer program predicts concentrations, dosages, and depositions downwind from normal and abnormal launches of rocket vehicles at NASA's Kennedy Space Center. The atmospheric dispersion models, cloud-rise models, and other formulas used in the REEDM model are described mathematically Vehicle and source parameters, other pertinent physical properties of the rocket exhaust cloud, and meteorological layering techniques are presented as well as user's instructions for REEDM. Worked example problems are included

Super-resolution, Extremal Functions and the Condition Number of Vandermonde Matrices

Super-resolution is a fundamental task in imaging, where the goal is to extract fine-grained structure from coarse-grained measurements. Here we are interested in a popular mathematical abstraction of this problem that has been widely studied in the statistics, signal processing and machine learning communities. We exactly resolve the threshold at which noisy super-resolution is possible. In particular, we establish a sharp phase transition for the relationship between the cutoff frequency ($m$) and the separation ($\Delta$). If $m > 1/\Delta + 1$, our estimator converges to the true values at an inverse polynomial rate in terms of the magnitude of the noise. And when $m < (1-\epsilon) /\Delta$ no estimator can distinguish between a particular pair of $\Delta$-separated signals even if the magnitude of the noise is exponentially small. Our results involve making novel connections between {\em extremal functions} and the spectral properties of Vandermonde matrices. We establish a sharp phase transition for their condition number which in turn allows us to give the first noise tolerance bounds for the matrix pencil method. Moreover we show that our methods can be interpreted as giving preconditioners for Vandermonde matrices, and we use this observation to design faster algorithms for super-resolution. We believe that these ideas may have other applications in designing faster algorithms for other basic tasks in signal processing.Comment: 19 page

Case-control study to detect protective factors on pig farms with low Salmonella prevalence

The prevalence of Salmonella in UK pigs is amongst the highest in Europe, highlighting the risk to public health and the need to investigate on-farm controls. The objective of this study was to identify factors currently in operation on pig farms that had maintained a low Salmonella seroprevalence. For this purpose a case-control study was designed and pig farms with a low (\u3c10%) seroprevalence were compared against two randomly selected control farms, sharing the same geographical region and production type. A total of 11,452 samples, including pooled and individual floor faeces and environmental samples from pigs and their vicinity were tested and prevalence examined. In addition, detailed questionnaires were completed during the farm visits to collect descriptive data for risk factor analysis. It was shown that control farms had significantly higher prevalence compared to the case farms (19.4% and 4.3% for pooled and 6.7% and 0.1% for individual samples, respectively). The two risk factor analyses identified multiple variables associated with Salmonella prevalence including variables related to feed, effectiveness of cleaning and disinfection, biosecurity and batch production

A dependent nominal type theory

Nominal abstract syntax is an approach to representing names and binding pioneered by Gabbay and Pitts. So far nominal techniques have mostly been studied using classical logic or model theory, not type theory. Nominal extensions to simple, dependent and ML-like polymorphic languages have been studied, but decidability and normalization results have only been established for simple nominal type theories. We present a LF-style dependent type theory extended with name-abstraction types, prove soundness and decidability of beta-eta-equivalence checking, discuss adequacy and canonical forms via an example, and discuss extensions such as dependently-typed recursion and induction principles

Improving the condition number of estimated covariance matrices

High dimensional error covariance matrices and their inverses are used to weight the contribution of observation and background information in data assimilation procedures. As observation error covariance matrices are often obtained by sampling methods, estimates are often degenerate or ill-conditioned, making it impossible to invert an observation error covariance matrix without the use of techniques to reduce its condition number. In this paper we present new theory for two existing methods that can be used to ‘recondition’ any covariance matrix: ridge regression, and the minimum eigenvalue method. We compare these methods with multiplicative variance inflation, which cannot alter the condition number of a matrix, but is often used to account for neglected correlation information. We investigate the impact of reconditioning on variances and correlations of a general covariance matrix in both a theoretical and practical setting. Improved theoretical understanding provides guidance to users regarding method selection, and choice of target condition number. The new theory shows that, for the same target condition number, both methods increase variances compared to the original matrix, with larger increases for ridge regression than the minimum eigenvalue method. We prove that the ridge regression method strictly decreases the absolute value of off-diagonal correlations. Theoretical comparison of the impact of reconditioning and multiplicative variance inflation on the data assimilation objective function shows that variance inflation alters information across all scales uniformly, whereas reconditioning has a larger effect on scales corresponding to smaller eigenvalues. We then consider two examples: a general correlation function, and an observation error covariance matrix arising from interchannel correlations. The minimum eigenvalue method results in smaller overall changes to the correlation matrix than ridge regression, but can increase off-diagonal correlations. Data assimilation experiments reveal that reconditioning corrects spurious noise in the analysis but underestimates the true signal compared to multiplicative variance inflation

Alternative Markers of Performance in Simulation: Where We Are and Where We Need To Go

This article on alternative markers of performance in simulation is the product of a session held during the 2017 Academic Emergency Medicine Consensus Conference â Catalyzing System Change Through Health Care Simulation: Systems, Competency, and Outcomes.â There is a dearth of research on the use of performance markers other than checklists, holistic ratings, and behaviorally anchored rating scales in the simulation environment. Through literature review, group discussion, and consultation with experts prior to the conference, the working group defined five topics for discussion: 1) establishing a working definition for alternative markers of performance, 2) defining goals for using alternative performance markers, 3) implications for measurement when using alternative markers, identifying practical concerns related to the use of alternative performance markers, and 5) identifying potential for alternative markers of performance to validate simulation scenarios. Five research propositions also emerged and are summarized.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142535/1/acem13321_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142535/2/acem13321.pd

Spring 1971

Damage to the GOlf Course by James L. HOlmes (page 3) Editorial (7) Turf Bulletin\u27s Photo Quiz by Frederick G. Cheney (7) Pesticide Waste Disposal by R.G. Novak and O.H. Hammer (8) 1971 Turf Conference Program (12-13) Turf Management by A.J. Powell, Jr. (14) Homeowner\u27s Guide for Spring Lawn Care (16) The Role of Shade Trees in Urban Arboriculture by Malcolm A. McKenzie (17) Locating Cause of Pressure Loss in Power Sprayers (18) How Soil pH is Affected by the Fertilizers You Use by F.E. Hutchinson (20

Solving variational inequalities defined on a domain with infinitely many linear constraints

We study a variational inequality problem whose domain is defined by infinitely many linear inequalities. A discretization method and an analytic center based inexact cutting plane method are proposed. Under proper assumptions, the convergence results for both methods are given. We also provide numerical examples to illustrate the proposed method