Analytic Scattering and Refraction Models for Exoplanet Transit Spectra

Observations of exoplanet transit spectra are essential to understanding the physics and chemistry of distant worlds. The effects of opacity sources and many physical processes combine to set the shape of a transit spectrum. Two such key processes - refraction and cloud and/or haze forward scattering - have seen substantial recent study. However, models of these processes are typically complex, which prevents their incorporation into observational analyses and standard transit spectrum tools. In this work, we develop analytic expressions that allow for the efficient parameterization of forward scattering and refraction effects in transit spectra. We derive an effective slant optical depth that includes a correction for forward scattered light, and present an analytic form of this correction. We validate our correction against a full-physics transit spectrum model that includes scattering, and we explore the extent to which the omission of forward scattering effects may bias models. Also, we verify a common analytic expression for the location of a refractive boundary, which we express in terms of the maximum pressure probed in a transit spectrum. This expression is designed to be easily incorporated into existing tools, and we discuss how the detection of a refractive boundary could help indicate the background atmospheric composition by constraining the bulk refractivity of the atmosphere. Finally, we show that opacity from Rayleigh scattering and collision induced absorption will outweigh the effects of refraction for Jupiter-like atmospheres whose equilibrium temperatures are above 400-500 K.Comment: ApJ accepted; submitted Feb. 7, 201

Is Growing Livestock Inventories a Sustainable Initiative Given Phosphorus Crop Removal Regulations?

As environmental regulations continue to tighten and shift from nitrogen to phosphorus-based application standards for manure, phosphorus removal will become increasingly important for any state considering a livestock growth initiative. A framework was developed that can determine a state’s phosphorus removal capacity based upon production of livestock and crops and varying phosphorus removal standards. The state level results indicate that Indiana, along with Arizona, Illinois, Iowa, Kansas, and Texas, are well positioned to undertake a livestock growth initiative given that each state has excess phosphorous removal capacity.Agribusiness, Livestock Production/Industries,

Inversion of spinning sound fields

A method is presented for the reconstruction of rotating monopole source distributions using acoustic pressures measured on a sideline parallel to the source axis. The method requires no \textit{a priori} assumptions about the source other than that its strength at the frequency of interest vary sinusoidally in azimuth on the source disc so that the radiated acoustic field is composed of a single circumferential mode. When multiple azimuthal modes are present, the acoustic field can be decomposed into azimuthal modes and the method applied to each mode in sequence. The method proceeds in two stages, first finding an intermediate line source derived from the source distribution and then inverting this line source to find the radial variation of source strength. A far-field form of the radiation integrals is derived, showing that the far field pressure is a band-limited Fourier transform of the line source, establishing a limit on the quality of source reconstruction which can be achieved using far-field measurements. The method is applied to simulated data representing wind-tunnel testing of a ducted rotor system (tip Mach number~0.74) and to control of noise from an automotive cooling fan (tip Mach number~0.14), studies which have appeared in the literature of source identification.Comment: Revised version of paper submitted to JASA; five more figures; expanded content with more discussion of error behaviour and relation to Nearfield Acoustical Holograph

The Utility of Participatory Family Diagramming in Qualitative Research: Multidisciplinary Applications and Practical Advice

Graphic elicitation and diagramming are useful for qualitative researchers. Diagrams of families have been used in clinical, education, and other applied settings as tools for description and analysis of family relationships since the 1950s. Despite the potential utility of family diagrams to qualitative researchers who seek to understand and theorize the complexities of family structures and relationships, participatory family diagramming, where diagrams of family relationships are co-created by researcher(s) and participant(s) and used as a foundation for interviewing, has largely remained an untapped resource. We describe how we used participatory family diagrams as design elements of multidisciplinary qualitative interview study projects and highlight the benefits of this practice. Our experiences demonstrate how participatory family diagramming enhances rapport with research participants, improves rigor, and aids in analysis of qualitative interview data. We offer practical suggestions for how to incorporate participatory family diagramming as a methodological tool into cross-disciplinary qualitative interview research

Advanced Biofuel Production in Louisiana Sugar Mills: an Application of Real Options Analysis

In order to more fully study the risks and uncertainty involved in cellulosic ethanol production, we examine a simulated plant in South Louisiana using Real Options Analysisreal options, risk, uncertainty, cellulosic ethanol, energy cane, sorghum, bagasse, simulation, Agribusiness, Agricultural Finance, Production Economics, Resource /Energy Economics and Policy, Risk and Uncertainty, q42, q14, q16, d81, g31,

Using Simulated Farm Case Studies to Teach Financial and Risk Management Concepts

Two simulated farm case studies provide a means for teaching financial and risk management strategies to western Kentucky grain farmers. Aggregate financial data for 227 grain farms define the case studies, which illustrate how cost and debt affect cash flow and working capital over a 5-year period. Responding to the case studies, farmers were able to discuss these financial concepts in a group setting among competitor neighbors without revealing personal business information. The use of composite financial data engaged the farmers and allowed for improved discussion on risk management products and the potential to protect working capital over multiple years. Extension professionals can apply the methods described

The Martian daytime convective boundary layer: Results from radio occultation measurements and a mesoscale model

We investigate the behavior of the Martian daytime convective boundary layer (CBL) through a combination of data analysis and modeling. This study relies on two subsets of Mars Express radio occultation (RO) measurements that sounded the atmosphere in north- ern spring of successive Mars years. Only the first year of observations has been examined previously (Hinson et al., 2008); the second year provides complementary spatial coverage and greatly increases the total number of observations. Analysis of the RO profiles yields basic characteristics of the CBL, such as its depth D and the average potential temperature of the mixed layer θm. We also combine RO retrievals of surface pressure with surface tem- peratures from infrared sounding to characterize the surface forcing, expressing the result as a potential temperature θs. These observations are at local times in early afternoon for θs and late afternoon for θm and D, when each parameter is near its diurnal maximum. We use measurements at mid-to-low latitudes, which sample a wide range of θs (227–294 K), to determine the response of the lower atmosphere to spatial variations in surface forcing. The depth of the CBL ranges from less than 3 km in the midlatitude topographic basins to more than 9 km above elevated terrain in the tropics. The dependence of θm on θs is linear, with a characteristic slope of about 0.7 in both years. We gain further insight by performing a simulation with the Oregon State University Mars Mesoscale Model in a region centered on Isidis Planitia, which includes two potential landing sites for the Mars 2020 Rover. As expected from previous modeling of much smaller craters, the arc of steep to- pography along the western and southern margins of Isidis produces a distinctive, diurnally varying, mesoscale circulation. The simulation captures key features of the observations, such as the wide variations in θm and D — by 34 K and 9 km, respectively — that occur within this region. The model also accounts for peculiar features of RO profiles on the rim of Isidis, where the wind field strongly influences the depth and diurnal evolution of the CBL. Detailed comparisons with the observations validate the general performance of the model and confirm several aspects of the simulated wind field

Parallel Sparse Tensor Decomposition in Chapel

In big-data analytics, using tensor decomposition to extract patterns from large, sparse multivariate data is a popular technique. Many challenges exist for designing parallel, high performance tensor decomposition algorithms due to irregular data accesses and the growing size of tensors that are processed. There have been many efforts at implementing shared-memory algorithms for tensor decomposition, most of which have focused on the traditional C/C++ with OpenMP framework. However, Chapel is becoming an increasingly popular programing language due to its expressiveness and simplicity for writing scalable parallel programs. In this work, we port a state of the art C/OpenMP parallel sparse tensor decomposition tool, SPLATT, to Chapel. We present a performance study that investigates bottlenecks in our Chapel code and discusses approaches for improving its performance. Also, we discuss features in Chapel that would have been beneficial to our porting effort. We demonstrate that our Chapel code is competitive with the C/OpenMP code for both runtime and scalability, achieving 83%-96% performance of the original code and near linear scalability up to 32 cores.Comment: 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 5th Annual Chapel Implementers and Users Workshop (CHIUW 2018

An Empirical Evaluation of Allgatherv on Multi-GPU Systems

Applications for deep learning and big data analytics have compute and memory requirements that exceed the limits of a single GPU. However, effectively scaling out an application to multiple GPUs is challenging due to the complexities of communication between the GPUs, particularly for collective communication with irregular message sizes. In this work, we provide a performance evaluation of the Allgatherv routine on multi-GPU systems, focusing on GPU network topology and the communication library used. We present results from the OSU-micro benchmark as well as conduct a case study for sparse tensor factorization, one application that uses Allgatherv with highly irregular message sizes. We extend our existing tensor factorization tool to run on systems with different node counts and varying number of GPUs per node. We then evaluate the communication performance of our tool when using traditional MPI, CUDA-aware MVAPICH and NCCL across a suite of real-world data sets on three different systems: a 16-node cluster with one GPU per node, NVIDIA's DGX-1 with 8 GPUs and Cray's CS-Storm with 16 GPUs. Our results show that irregularity in the tensor data sets produce trends that contradict those in the OSU micro-benchmark, as well as trends that are absent from the benchmark.Comment: 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID