The effects of solid rocket motor effluents on selected surfaces and solid particle size, distribution, and composition for simulated shuttle booster separation motors

A series of three tests was conducted using solid rocket propellants to determine the effects a solid rocket plume would have on thermal protective surfaces (TPS). The surfaces tested were those which are baselined for the shuttle vehicle. The propellants used were to simulate the separation solid rocket motors (SSRM) that separate the solid rocket boosters (SRB) from the shuttle launch vehicle. Data cover: (1) the optical effects of the plume environment on spacecraft related surfaces, and (2) the solid particle size, distribution, and composition at TPS sample locations

Consistent Testing for an Implication of Supermodular Dominance

Supermodularity, or complementarity, is a popular concept in economics which can characterize many objective functions, including utility, social welfare, and production functions. Further, supermodular dominance captures a preference for greater interdependence among inputs of those functions, and it can be applied to examine which input set would produce higher expected utility, social welfare, or production. However, contrary to the profuse literature on supermodularity, to the best of our knowledge, there is no existing work on either testing or empirical analysis for supermodular dominance. In this paper, we propose a consistent test for a useful implication of supermodular dominance and suggest a correlation dominance testing for Gaussian random variables as a special case. The test is based on a novel bootstrap critical value, which has potentially enhanced power performance by exploiting the information on the contact set on which the null hypothesis is binding. We also conduct Monte Carlo simulations to explore the finite sample performance of our tests. We then apply our test to analyze two economic questions. We first investigate whether the interdependence of stock returns among major firms has increased after the COVID-19, and find evidence supporting this conjecture. We also compare the interdependence of patent citations depending on distance, where greater interdependence can imply greater expected social welfare effect. The results suggest that, in most cases, between-state citations seem to have greater interdependence than within-state citations, implying that lively interaction between firms across states might engender greater expected social welfare than knowledge spillover within a geographically confined area

Identification and characterization of a novel extracellular matrix protein nephronectin that is associated with integrin alpha8beta1 in the embryonic kidney.

The epithelial-mesenchymal interactions required for kidney organogenesis are disrupted in mice lacking the integrin alpha8beta1. None of this integrin's known ligands, however, appears to account for this phenotype. To identify a more relevant ligand, a soluble integrin alpha8beta1 heterodimer fused to alkaline phosphatase (AP) has been used to probe blots and cDNA libraries. In newborn mouse kidney extracts, alpha8beta1-AP detects a novel ligand of 70-90 kD. This protein, named nephronectin, is an extracellular matrix protein with five EGF-like repeats, a mucin region containing a RGD sequence, and a COOH-terminal MAM domain. Integrin alpha8beta1 and several additional RGD-binding integrins bind nephronectin. Nephronectin mRNA is expressed in the ureteric bud epithelium, whereas alpha8beta1 is expressed in the metanephric mesenchyme. Nephronectin is localized in the extracellular matrix in the same distribution as the ligand detected by alpha8beta1-AP and forms a complex with alpha8beta1 in vivo. Thus, these results strongly suggest that nephronectin is a relevant ligand mediating alpha8beta1 function in the kidney. Nephronectin is expressed at numerous sites outside the kidney, so it may also have wider roles in development. The approaches used here should be generally useful for characterizing the interactions of novel extracellular matrix proteins identified through genomic sequencing projects

Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series

We propose two semiparametric model averaging schemes for nonlinear dynamic time series regression models with a very large number of covariates including exogenous regressors and autoregressive lags. Our objective is to obtain more accurate estimates and forecasts of time series by using a large number of conditioning variables in a nonparametric way. In the first scheme, we introduce a Kernel Sure Independence Screening (KSIS) technique to screen out the regressors whose marginal regression (or auto-regression) functions do not make a significant contribution to estimating the joint multivariate regression function; we then propose a semiparametric penalized method of Model Averaging MArginal Regression (MAMAR) for the regressors and auto-regressors that survive the screening procedure, to further select the regressors that have significant effects on estimating the multivariate regression function and predicting the future values of the response variable. In the second scheme, we impose an approximate factor modelling structure on the ultra-high dimensional exogenous regressors and use the principal component analysis to estimate the latent common factors; we then apply the penalized MAMAR method to select the estimated common factors and the lags of the response variable that are significant. In each of the two schemes, we construct the optimal combination of the significant marginal regression and auto-regression functions. Asymptotic properties for these two schemes are derived under some regularity conditions. Numerical studies including both simulation and an empirical application to forecasting inflation are given to illustrate the proposed methodolog

Identifikasi Profil Budaya Organisasi yang Mendukung Implementasi Sistem Penjaminan Mutu Perguruan Tinggi

: This research was aimed to evaluate the implementation of the Internal Quality Assurance System of the Higher Education (SPMI-PT) of Manado State Polytechnic based on the ISO 9001 Quality Management System (QMS), to identify the organizational culture profile of Manado State Polytechnic, and to examine the relationship between the implementation of ISO 9001 and the culture profile of the institution. Questionnaireswere used in order to achieve the research aims.The study found that the implementation of the eight ISO 9001 principles had not achieved the maximum level of effectiveness, and Clan culture dominated the profile of the organizational culture of Manado State Polytechnic.The research also found that: Clan culture was significantly correlated with the quality principles of Leadership, People Involvement, Process Approach, Factual Approach to Decision Making, and Mutually Beneficial Supplier Relationships;Market culture was significantly correlated with the quality principle of Customer Focus while Hierarchy culture wassignificantly correlated with the quality principles of Systems Approach to Management,and Continual Improvement. The findings are the basis for the institution to be able to develop a strong organizational culture as a driver in implementing the SPMI-PT effectively and sustainably

Characterization of a 5-eV neutral atomic oxygen beam facility

An experimental effort to characterize an existing 5-eV neutral atomic oxygen beam facility being developed at Princeton Plasma Physics Laboratory is described. This characterization effort includes atomic oxygen flux and flux distribution measurements using a catalytic probe, energy determination using a commercially designed quadrupole mass spectrometer (QMS), and the exposure of oxygen-sensitive materials in this beam facility. Also, comparisons were drawn between the reaction efficiencies of materials exposed in plasma ashers, and the reaction efficiencies previously estimated from space flight experiments. The results of this study show that the beam facility is capable of producing a directional beam of neutral atomic oxygen atoms with the needed flux and energy to simulate low Earth orbit (LEO) conditions for real time accelerated testing. The flux distribution in this facility is uniform to +/- 6 percent of the peak flux over a beam diameter of 6 cm

Paper Session III-B - A Combined Probabilistic and Expert System Approach for Assigning Repair Start-Times at the NASA Shuttle Logistics Depot

The NASA Shuttle Logistics Depot (NSLD) is tasked with the responsibility for repair and manufacture of Line Replaceable Unit (LRU) hardware and components to support the Space Shuttle Orbiter. Due to shrinking budgets, cost effective repair of LRUs becomes a primary objective. To achieve this objective, it is imperative that resources can be assigned to those LRUs which have the greatest expectation of being needed as a spare. Forecasting the times at which spares are needed requires consideration of many significant factors including, for example, failure rate, flight rate, spares availability, and desired level of support, among others. This paper summarizes the results of the research and development work that has been accomplished in producing an automated system for assisting in the assignment of effective repair start-times for LRUs at the NSLD. This system, called the Repair Start-time Assignment System (RSAS), combines probabilistic modeling and expert system technology to generate an expected future need date. The result is a mathematically calculated value that has been adjusted heuristically to produce a date for beginning the repair that has significantly greater confidence (in the sense that a desired probability of support is assured) than dates produced using other techniques. Since an important output of RSAS is the longest repair turn-around time that will ensure a desired probability of support, RSAS has the potential for being applied to operations at any repair depot where spares are on-hand and repair start-times are of interest. In addition, RSAS incorporates tenants of Just-In-Time (JIT) techniques in the connotation that the latest repair start-time (i.e., the latest time at which repair resources must be committed) may be calculated for every failed unit. This could aid in reducing the spares inventory for certain items, without significantly increasing the risk of unsatisfied demand

A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables

This paper studies the estimation of large dynamic covariance matrices with multiple conditioning variables. We introduce an easy-to-implement semiparametric method to estimate each entry of the covariance matrix via model averaging marginal regression, and then apply a shrinkage technique to obtain the dynamic covariance matrix estimation. Under some regularity conditions, we derive the asymptotic properties for the proposed estimators including the uniform consistency with general convergence rates. We further consider extending our methodology to deal with the scenarios: (i) the number of conditioning variables is divergent as the sample size increases, and (ii) the large covariance matrix is conditionally sparse relative to contemporaneous market factors. We provide a simulation study that illustrates the finite-sample performance of the developed methodology. We also provide an application to financial portfolio choice from daily stock returns