3,515 research outputs found

    Exact Post Model Selection Inference for Marginal Screening

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    We develop a framework for post model selection inference, via marginal screening, in linear regression. At the core of this framework is a result that characterizes the exact distribution of linear functions of the response yy, conditional on the model being selected (``condition on selection" framework). This allows us to construct valid confidence intervals and hypothesis tests for regression coefficients that account for the selection procedure. In contrast to recent work in high-dimensional statistics, our results are exact (non-asymptotic) and require no eigenvalue-like assumptions on the design matrix XX. Furthermore, the computational cost of marginal regression, constructing confidence intervals and hypothesis testing is negligible compared to the cost of linear regression, thus making our methods particularly suitable for extremely large datasets. Although we focus on marginal screening to illustrate the applicability of the condition on selection framework, this framework is much more broadly applicable. We show how to apply the proposed framework to several other selection procedures including orthogonal matching pursuit, non-negative least squares, and marginal screening+Lasso

    An Anatomy of a Cartel: The National Industrial Recovery Act of 1933 and the Compliance Crisis of 1934

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    This paper explores the nature and causes of the cartel compliance crisis that befell the National Industrial Recovery Act (NIRA) one year after its passage in 1933. We employ a simple game-theoretic model of the NIRA's cartel enforcement mechanism to show that the compliance crisis can largely be explained by changes in expectations, rather than a change in enforcement policy. Specifically, firms initially overestimated the probability that defection would be met with sanction by the cartel's enabling body, the National Recovery Administration-including a consumer boycott resulting from loss of the patriotic Blue Eagle emblem-and complied with the industry cartel rules. As these expectations were correctly adjusted downward, cartel compliance was lost. We support this hypothesis empirically with industry-level panel data showing how output and wage rates varied according to consumer confidence in the Blue Eagle. The analysis provides insight about cartel performance more generally

    Determination of specific gravity of municipal solid waste

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    This investigation was conducted to evaluate experimental determination of specific gravity (Gs) of municipal solid waste (MSW). Water pycnometry, typically used for testing soils was adapted for testing MSW using a large flask with 2000 mL capacity and specimens with 100–350 g masses. Tests were conducted on manufactured waste samples prepared using US waste constituent components; fresh wastes obtained prior and subsequent to compaction at an MSW landfill; and wastes obtained from various depths at the same landfill. Factors that influence specific gravity were investigated including waste particle size, compaction, and combined decomposition and stress history. The measured average specific gravities were 1.377 and 1.530 for as-prepared/uncompacted and compacted manufactured wastes, respectively; 1.072 and 1.258 for uncompacted and compacted fresh wastes, respectively; and 2.201 for old wastes. The average organic content and degree of decomposition were 77.2% and 0%, respectively for fresh wastes and 22.8% and 88.3%, respectively for old wastes. The Gs increased with decreasing particle size, compaction, and increasing waste age. For fresh wastes, reductions in particle size and compaction caused occluded intraparticle pores to be exposed and waste particles to be deformed resulting in increases in specific gravity. For old wastes, the high Gs resulted from loss of biodegradable components that have low Gs as well as potential access to previously occluded pores and deformation of particles due to both degradation processes and applied mechanical stresses. The Gs was correlated to the degree of decomposition with a linear relationship. Unlike soils, the Gs for MSW was not unique, but varied in a landfill environment due both to physical/mechanical processes and biochemical processes. Specific gravity testing is recommended to be conducted not only using representative waste composition, but also using representative compaction, stress, and degradation states

    Development and Validation of a Computational Model for Predicting the Behavior of Plumes from Large Solid Rocket Motors

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    Exhaust plumes from large solid rocket motors fired at ATK's Promontory test site carry particulates to high altitudes and typically produce deposits that fall on regions downwind of the test area. As populations and communities near the test facility grow, ATK has become increasingly concerned about the impact of motor testing on those surrounding communities. To assess the potential impact of motor testing on the community and to identify feasible mitigation strategies, it is essential to have a tool capable of predicting plume behavior downrange of the test stand. A software package, called PlumeTracker, has been developed and validated at ATK for this purpose. The code is a point model that offers a time-dependent, physics-based description of plume transport and precipitation. The code can utilize either measured or forecasted weather data to generate plume predictions. Next-Generation Radar (NEXRAD) data and field observations from twenty-three historical motor test fires at Promontory were collected to test the predictive capability of PlumeTracker. Model predictions for plume trajectories and deposition fields were found to correlate well with the collected dataset

    High fidelity simulations of ion trajectories in miniature ion traps using the boundary-element method

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    In this paper we present numerical modeling results for endcap and linear ion traps, used for experiments at the National Physical Laboratory in the UK and Innsbruck University respectively. The secular frequencies for Strontium-88 and Calcium-40 ions were calculated from ion trajectories, simulated using boundary-element and finite-difference numerical methods. The results were compared against experimental measurements. Both numerical methods showed high accuracy with boundary-element method being more accurate. Such simulations can be useful tools for designing new traps and trap arrays. They can also be used for obtaining precise trapping parameters for desired ion control when no analytical approach is possible as well as for investigating the ion heating rates due to thermal electronic noise.Comment: 6 pages, 5 figures, changes made to the text according to the editor's and referee's comment

    Synthesis and Properties of Bio-based 3D Printable Resins

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    A photopolymer resin is a monomer that, when introduced to light of a certain wavelength, starts to polymerize into a solid. This has become a growing part of the 3D printing industry. There have been many advancements in the field of 3D printing, however, a lot of these resins are not environmentally friendly and even harmful if not handled in the correct manner. Plant based resins are becoming more and more popular because of their biodegradability and for the possibility of using renewable resources. Glycerol is a plant-based compound that is produced in excess in industry. Glycerol obtained from bioethanol production as waste and can be used for value-added chemicals. Also, changing the wavelength of light required to polymerize means that researchers are trying to move away from using UV light because it is very harmful to human skin and can even damage a person’s vision. Also, UV light creates ozone as a by-product which can be harmful to the environment. This combination can have multiple real-world applications, not limited to 3D printing. It can possibly be used for gas separation and even polymer batteries. In this presentation, we converted glycerol based secondary alcohol into photopolymerizable resins. For preliminary studies, we varied the alkyl groups of the secondary alcohol containing ether and photopolymerized with different amounts of crosslinkers. We also used plant-based resin to get 3D printed polymers to see their properties. Finally, our synthesized resins mixed with commercial plant-based resins will be used to get 3D printed structures. Synthesis and characterization of these resins will be shown in the presentation

    QTL and Drought Effects on Leaf Physiology in Lowland Panicum virgatum

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    Switchgrass is a key component of plans to develop sustainable cellulosic ethanol production for bioenergy in the USA. We sought quantitative trait loci (QTL) for leaf structure and function, using the Albany full-sib mapping population, an F1 derived from lowland tetraploid parents. We also assessed both genotype × environment interactions (G×E) in response to drought and spatial trends within experimental plots, using the mapping population and check clones drawn from the parent cultivars. Phenotypes for leaf structure and physiological performance were determined under well-watered conditions in two consecutive years, and we applied drought to one of two replicates to test for G×E. Phenotypes for check clones varied with location in our plot and were impacted by drought, but there was limited evidence of G×E except in quantum yield (ΦPSII). Phenotypes of Albany were also influenced by plant location within our plot, and after correcting for experimental design factors and spatial effects, we detected QTL for leaf size, tissue density (LMA), and stomatal conductance (gs). Clear evidence of G×E was detected at a QTL for intrinsic water use efficiency (iWUE) that was expressed only under drought. Loci influencing physiological traits had small additive effects, showed complex patterns of heritability, and did not co-localize with QTL for morphological traits. These insights into the genetic architecture of leaf structure and function set the stage for consideration of leaf physiological phenotypes as a component of switchgrass improvement for bioenergy purposes

    Modeling and Correcting the Time-Dependent ACS PSF

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    The ability to accurately measure the shapes of faint objects in images taken with the Advanced Camera for Surveys (ACS) on the Hubble Space Telescope (HST) depends upon detailed knowledge of the Point Spread Function (PSF). We show that thermal fluctuations cause the PSF of the ACS Wide Field Camera (WFC) to vary over time. We describe a modified version of the TinyTim PSF modeling software to create artificial grids of stars across the ACS field of view at a range of telescope focus values. These models closely resemble the stars in real ACS images. Using 10 bright stars in a real image, we have been able to measure HST s apparent focus at the time of the exposure. TinyTim can then be used to model the PSF at any position on the ACS field of view. This obviates the need for images of dense stellar fields at different focus values, or interpolation between the few observed stars. We show that residual differences between our TinyTim models and real data are likely due to the effects of Charge Transfer Efficiency (CTE) degradation. Furthermore, we discuss stochastic noise that is added to the shape of point sources when distortion is removed, and we present MultiDrizzle parameters that are optimal for weak lensing science. Specifically, we find that reducing the MultiDrizzle output pixel scale and choosing a Gaussian kernel significantly stabilizes the resulting PSF after image combination, while still eliminating cosmic rays/bad pixels, and correcting the large geometric distortion in the ACS. We discuss future plans, which include more detailed study of the effects of CTE degradation on object shapes and releasing our TinyTim models to the astronomical community
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