Japan’s 2D Trauma Culture: Defining Crisis Cinema in Post-3/11 Japan

This paper labors to expound the link between the socially mediated “trauma process,” or the creation of collective trauma through social discourse, and the proposed moniker of “crisis cinema” that has often been deployed by media scholars with no clear parameters. This paper, then, endeavors to evince the trauma process’ relevance to crises and disasters, explicitly define a paradigm by which crisis cinema can be understood, and subsequently utilized by a larger patronage, and showcase the pair’s reliance on one another. This is approached through the locus of the March 11, 2011 Fukushima Daiichi nuclear disaster and a selection of Japanese films that followed therein

Block representations and spectral properties of constant sum matrices

An equivalent representation of constant sum matrices in terms of block-structured matrices is given in this paper. This provides an easy way of constructing all constant sum matrices, including those with further symmetry properties. The block representation gives a convenient description of the dihedral equivalence of such matrices. It is also shown how it can be used to study their spectral properties, giving explicit formulae for eigenvalues and eigenvectors in special situations, as well as for quasi-inverses when these exist

Industry-Based Competitive Strategies for Ohio: Managing Three Portfolios

Deloitte Consulting, LLP, Cleveland State University, OSA Strategy. Political and business leaders have recognized a need to chart a new economic course for Ohio’s future. This study represents a step toward determining effective uses for limited development dollars in the state and filling in Ohio’s economic development strategy. This statewide industry study has been designed to provide economic development officials with insight, analysis, and strategic tools to help businesses compete more efficiently in an increasingly global marketplace

The Turbulent Warm Ionized Medium: Emission Measure Distribution and MHD Simulations

We present an analysis of the distribution of H-alpha emission measures for the warm ionized medium (WIM) of the Galaxy using data from the Wisconsin H-Alpha Mapper (WHAM) Northern Sky Survey. Our sample is restricted to Galactic latitudes |b| > 10. We removed sightlines intersecting nineteen high-latititude classical H II regions, leaving only sightlines that sample the diffuse WIM. The distribution of EM sin |b| for the full sample is poorly characterized by a single normal distribution, but is extraordinarily well fit by a lognormal distribution, with = 0.146 +/- 0.001 and standard deviation 0.190 +/- 0.001. drops from 0.260 +/- 0.002 at Galactic latitude 10<|b|<30 to 0.038 +/- 0.002 at Galactic latitude 60<|b|<90. The distribution may widen slightly at low Galactic latitude. We compare the observed EM distribution function to the predictions of three-dimensional magnetohydrodynamic simulations of isothermal turbulence within a non-stratified interstellar medium. We find that the distribution of EM sin |b| is well described by models of mildy supersonic turbulence with a sonic Mach number of ~1.4-2.4. The distribution is weakly sensitive to the magnetic field strength. The model also successfully predicts the distribution of dispersion measures of pulsars and H-alpha line profiles. In the best fitting model, the turbulent WIM occupies a vertical path length of 400-500 pc within the 1.0-1.8 kpc scale height of the layer. The WIM gas has a lognormal distribution of densities with a most probable electron density n_{pk} = 0.03 cm^{-3}. We also discuss the implications of these results for interpreting the filling factor, the power requirement, and the magnetic field of the WIM.Comment: 16 pages, 13 figures, ApJ in press. Replacement reflects version accepted for publicatio

Rapid Quantification of Biofouling With an Inexpensive, Underwater Camera and Image Analysis

To reduce the transport of potentially invasive species on ships\u27 submerged surfaces, rapid-and accurate-estimates of biofouling are needed so shipowners and regulators can effectively assess and manage biofouling. This pilot study developed a model approach for that task. First, photographic images were collected in situ with a submersible, inexpensive pocket camera. These images were used to develop image processing algorithms and train machine learning models to classify images containing natural assemblages of fouling organisms. All of the algorithms and models were implemented in a widely available software package (MATLAB©). Initially, an unsupervised clustering model was used, and three types of fouling were delineated. Using a supervised classification approach, however, seven types of fouling could be identified. In this manner, fouling was successfully quantified over time on experimental panels immersed in seawater. This work provides a model for the easy, quick, and cost-effective classification of biofouling

OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics

The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added

Qualification of a Null Lens Using Image-Based Phase Retrieval

In measuring the figure error of an aspheric optic using a null lens, the wavefront contribution from the null lens must be independently and accurately characterized in order to isolate the optical performance of the aspheric optic alone. Various techniques can be used to characterize such a null lens, including interferometry, profilometry and image-based methods. Only image-based methods, such as phase retrieval, can measure the null-lens wavefront in situ - in single-pass, and at the same conjugates and in the same alignment state in which the null lens will ultimately be used - with no additional optical components. Due to the intended purpose of a Dull lens (e.g., to null a large aspheric wavefront with a near-equal-but-opposite spherical wavefront), characterizing a null-lens wavefront presents several challenges to image-based phase retrieval: Large wavefront slopes and high-dynamic-range data decrease the capture range of phase-retrieval algorithms, increase the requirements on the fidelity of the forward model of the optical system, and make it difficult to extract diagnostic information (e.g., the system F/#) from the image data. In this paper, we present a study of these effects on phase-retrieval algorithms in the context of a null lens used in component development for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. Approaches for mitigation are also discussed

Radiolytic Gas-Driven Cryovolcanism in the Outer Solar System

Water ices in surface crusts of Europa, Enceladus, Saturn's main rings, and Kuiper Belt Objects can become heavily oxidized from radiolytic chemical alteration of near-surface water ice by space environment irradiation. Oxidant accumulations and gas production are manifested in part through observed H2O2 on Europa. tentatively also on Enceladus, and found elsewhere in gaseous or condensed phases at moons and rings of Jupiter and Saturn. On subsequent chemical contact in sub-surface environments with significant concentrations of primordially abundant reductants such as NH3 and CH4, oxidants of radiolytic origin can react exothermically to power gas-driven cryovolcanism. The gas-piston effect enormously amplifies the mass flow output in the case of gas formation at basal thermal margins of incompressible fluid reservoirs. Surface irradiation, H2O2 production, NH3 oxidation, and resultant heat, gas, and gas-driven mass flow rates are computed in the fluid reservoir case for selected bodies. At Enceladus the oxidant power inputs are comparable to limits on nonthermal kinetic power for the south polar plumes. Total heat output and plume gas abundance may be accounted for at Enceladus if plume activity is cyclic in high and low "Old Faithful" phases, so that oxidants can accumulate during low activity phases. Interior upwelling of primordially abundant NH3 and CH4 hydrates is assumed to resupply the reductant fuels. Much lower irradiation fluxes on Kuiper Belt Objects require correspondingly larger times for accumulation of oxidants to produce comparable resurfacing, but brightness and surface composition of some objects suggest that such activity may be ongoing

System and Method for Null-Lens Wavefront Sensing

A method of measuring aberrations in a null-lens including assembly and alignment aberrations. The null-lens may be used for measuring aberrations in an aspheric optic with the null-lens. Light propagates from the aspheric optic location through the null-lens, while sweeping a detector through the null-lens focal plane. Image data being is collected at locations about said focal plane. Light is simulated propagating to the collection locations for each collected image. Null-lens aberrations may extracted, e.g., applying image-based wavefront-sensing to collected images and simulation results. The null-lens aberrations improve accuracy in measuring aspheric optic aberrations

Consequences of climate change on food-energy-water systems in arid regions without agricultural adaptation, analyzed using FEWCalc and DSSAT

Effects of a changing climate on agricultural system productivity are poorly understood, and likely to be met with as yet undefined agricultural adaptations by farmers and associated business and governmental entities. The continued vitality of agricultural systems depends on economic conditions that support farmers’ livelihoods. Exploring the long-term effects of adaptations requires modeling agricultural and economic conditions to engage stakeholders upon whom the burden of any adaptation will rest. Here, we use a new freeware model FEWCalc (Food-Energy-Water Calculator) to project farm incomes based on climate, crop selection, irrigation practices, water availability, and economic adaptation of adding renewable energy production. Thus, FEWCalc addresses United Nations Global Sustainability Goals No Hunger and Affordable and Clean Energy. Here, future climate scenario impacts on crop production and farm incomes are simulated when current agricultural practices continue so that no agricultural adaptations are enabled. The model Decision Support System for Agrotechnology Transfer (DSSAT) with added arid-region dynamics is used to simulate agricultural dynamics. Demonstrations at a site in the midwest USA with 2008–2017 historical data and two 2018–2098 RCP climate scenarios provide an initial quantification of increased agricultural challenges under climate change, such as reduced crop yields and increased financial losses. Results show how this finding is largely driven by increasing temperatures and changed distribution of precipitation throughout the year. Without effective technological advances and operational and policy changes, the simulations show how rural areas could increasingly depend economically on local renewable energy, while agricultural production from arid regions declines by 50% or more