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This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to match natural cloud shapes. This model is intended to run quickly, and it can run in about 700 ms per cloud type. This model generates clouds that appear to match large-scale satellite imagery, and it reproduces natural small-scale shapes. This should enable future versions of ASSET to generate scenarios where the same scene is consistently viewed from both GEO and LEO satellites from multiple perspectives. [ABSTRACT FROM AUTHOR]

The design and initial experimental results from an event-based, rotating-polarizer, imaging polarimeter are presented. The speed of division-of-time imaging systems is traditionally constrained by the frame rate of the focal plane sensor and the need to sample several polarization angles during rotation. The asynchronous event reporting of event-based cameras (EBCs) frees these constraints but introduces challenges. The Stokes vectors used to describe polarization are based on irradiance, but EBCs are inherently change-detection systems that struggle to estimate irradiance. Two methods of estimating the polarization state without first recovering irradiance images are presented and compared. The DAVIS 346 sensor enables simultaneous recording of events with conventional frame-based images, enabling direct comparison of event-based polarization estimates to traditional techniques. [ABSTRACT FROM AUTHOR]

Discusses the contributions of Wellcome Trust in genetics research. Investment in the human genome project; Investment in the emerging technologies in functional genomics; Development of an integrated approach to support genetics and post-genomics research.

ABSTRACT In this study, we consider three different machine‐learning methods—a three‐hidden‐layer neural network, support vector regression, and Gaussian process regression—and compare how well they can learn from a synthetic data set for proton acceleration in the Target Normal Sheath Acceleration regime. The synthetic data set was generated from a previously published theoretical model by Fuchs et al. 2005 that we modified. Once trained, these machine‐learning methods can assist with efforts to maximize the peak proton energy, or with the more general problem of configuring the laser system to produce a proton energy spectrum with desired characteristics. In our study, we focus on both the accuracy of the machine‐learning methods and the performance on one GPU including memory consumption. Although it is arguably the least sophisticated machine‐learning model we considered, support vector regression performed very well in our tests. [ABSTRACT FROM AUTHOR]

Although co-payments and deductibles are means of keeping health expenditures low, they have also been cited as barriers that inhibit patients from accessing necessary healthcare. We aimed to evaluate Rhode Island residents' experiences with cost-related access challenges within the state's healthcare system. We conducted a cross-sectional survey of resident experiences with healthcare in Rhode Island. Our survey instrument was composed of the RAND Corporation "Short-Form Patient Satisfaction Questionnaire (PSQ-18)", questions developed by the Rhode Island Office of the Health Insurance Commissioner, and ranking of health priorities based on prior community assessments conducted by the Rhode Island Department of Health. Data were collected at venues across the state as part of the Rhode Island Department of Health 2015 Statewide Health Inventory. From July to August 2015, 404 surveys were completed. We found that 40% of respondents had a co-pay of $20-$50, while 35.7% of respondents had a deductible of greater than $500. Further, one-third of respondents delayed receiving care due to financial barriers. This decision resulted in a worsening condition or hospital visit for nearly half of those respondents. Co-pays and deductibles pose challenges to Rhode Islanders accessing health care. Cost-related barriers to healthcare access should continue to be addressed, especially in the context of preventive care services, which are now being built into health insurance premiums through the Patient Protection and Affordable Care Act. [ABSTRACT FROM AUTHOR]

Sintering of metal nanowire (NW) networks on transparent polymers is an emerging approach for fabricating transparent conductive electrodes used in multiple devices. Pulsed light sintering is a scalable sintering process in which large-area, broad-spectrum xenon lamp light causes rapid NW fusion to increase network conductivity, while embedding the NWs in the polymer to increase mechanical robustness. This paper develops a multiphysical approach for predicting evolution of conductivity, NW fusion and nanoscale temperature gradients on the substrate during pulsed light sintering of silver NWs on polycarbonate. Model predictions are successfully validated against experimentally measured temperature and electrical resistance evolution. New insight is obtained into the diameter-dependent kinetics of NW fusion and nanoscale temperature gradients on the substrate, which are difficult to obtain experimentally. These observations also lead to the understanding that NW embedding in intense pulsed light sintering (IPL) can occur below the glass transition temperature of the polymer, and to a new differential thermal expansion-based mechanism of NW embedding during IPL. These insights, and the developed model, create a framework for physics-guided choice of NWs, substrate and process parameters to control conductivity and prevent substrate damage during the process.