DeepPicar: A Low-cost Deep Neural Network-based Autonomous Car

We present DeepPicar, a low-cost deep neural network based autonomous car platform. DeepPicar is a small scale replication of a real self-driving car called DAVE-2 by NVIDIA. DAVE-2 uses a deep convolutional neural network (CNN), which takes images from a front-facing camera as input and produces car steering angles as output. DeepPicar uses the same network architecture---9 layers, 27 million connections and 250K parameters---and can drive itself in real-time using a web camera and a Raspberry Pi 3 quad-core platform. Using DeepPicar, we analyze the Pi 3's computing capabilities to support end-to-end deep learning based real-time control of autonomous vehicles. We also systematically compare other contemporary embedded computing platforms using the DeepPicar's CNN-based real-time control workload. We find that all tested platforms, including the Pi 3, are capable of supporting the CNN-based real-time control, from 20 Hz up to 100 Hz, depending on hardware platform. However, we find that shared resource contention remains an important issue that must be considered in applying CNN models on shared memory based embedded computing platforms; we observe up to 11.6X execution time increase in the CNN based control loop due to shared resource contention. To protect the CNN workload, we also evaluate state-of-the-art cache partitioning and memory bandwidth throttling techniques on the Pi 3. We find that cache partitioning is ineffective, while memory bandwidth throttling is an effective solution.Comment: To be published as a conference paper at RTCSA 201

HST/FOS spectra of PG 1351+64: An intrinsic absorber at low redshift

A 1 A resolution spectra of the nearby (z = 0.08797) Seyfert galaxy PG 1351+64 taken with the Faint Object Spectrograph (FOS) onboard the Hubble Space Telescope is presented. Spectral coverage runs from 1200-3200 A in the observed frame and includes emission and absorption features due to Ly-alpha, N 5, Si 4, C 4, and Mg 2. Three distinct intrinsic absorption systems in Ly-alpha, N 5, Si 4, and C 4, and tentatively in Mg 2, at velocities of 900 km/s, 1630 km/s, and 2900 km/s (plus or minus 100 km/s) relative to the emission-line redshift of the QSO were detected. The maximum relative velocity of these absorbers is less than 5000 km/s and therefore does not meet Weymann, Carswell, & Smith's criteria for Broad-Absorption-Line (BAL) QSO's at high-z. However, the absorptions are almost certainly intrinsic to the QSO given the low redshift of this object. In addition, PG 1351+64 is marginally radio-quiet, as are all BALQSO's, based on recent estimates of the radio-loud/radio-quiet dividing line. The narrow velocity width, less than 500 km/s, and low outflow velocities of the absorption systems are more similar to so called 'associated absorbers' seen at high-z in radio-loud quasars, but whose absorptions are thought to arise in clouds much farther from the nucleus (greater than 1 kpc) than are BAL clouds (1-10 pc). Despite the qualitative resemblance to the associated absorbers, the absorption systems in PG 1351+64 appear to be the low-luminosity analogs of BALQSO absorption troughs. The lower observed outflow velocities in PG 1351+64 are due to the much lower luminosity of the nuclear source in comparison to the high-z, high-luminosity BALQSO's. In addition, 'satellite' emission lines displaced 4000-5000 km/s blueward and redward of the Mg 2 emission were discovered

NUMERIC BREAST PHANTOM GENERATION FROM MAGNETIC RESONANCE DATA FOR MICROWAVE IMAGING APPLICATIONS

INTRODUCTION New methods for microwave imaging are currently being explored for breast cancer detection and monitoring. The potential advantages of microwave imaging over current modalities have motivated a number of studies into imaging the internal structures of breast tissue using microwaves (see [1] and references therein). The exploration of such techniques requires models for electromagnetic simulations that are both realistic and anatomically representative of real breast tissue[2] . We have developed a new 3D-model generation tool to translate Magnetic Resonance (MR) images into breast phantoms.  These phantoms are suited to the simulations used to test prototype microwave imaging systems. This new technique attempts to improve on manual segmentation by introducing a number of robust, semi-automated segmentation algorithms for generating patient-specific numeric breast phantoms unlike similar model generation techniques previously used [2]. The limited number of microwave-appropriate models motivated that development of a robust tool that could represent the complex internal structures of breast tissues. METHODS The new programs utilized a number of image segmentation techniques, able to handle a wide range of MR image types and varying breast compositions, to produce a voxel-based surface mesh, which is readily transportable to electromagnetic simulation software. A custom multi-modal phantom was constructed using graphite-doped rubber following previously developed phantom construction techniques [3] and scanned in an MR machine in order to validate the new 3D modelling program’s ability to accurately reconstruct complex structures. The phantom served as ground truth to quantify the reconstruction accuracy. RESULTS The program constructed complex meshes from MR data representing the internal fibroglandular tissue structures (see Figure 1a). The generated meshes included major structures accurately represented with varying levels of complexity according to the user parameters (see figure 1b).  In addition to this, the program was able to reconstruct the custom phantom with minimal error providing a ground-truth validation of the segmentation technique. DISCUSSION AND CONCLUSIONS The newly developed program for breast phantom generation provides a useful tool for generating numeric models that are critical to the future investigation of microwave imaging techniques, generating patient specific models catered to microwave imaging.

Predicting Springtime Herbicide Exposure across Multiple scales in Pacific Coastal Drainages (Oregon, USA)

Identification of non-point sources of watershed pollution such as pesticide runoff is challenging due to spatial and temporal variation in landscape patterns of land use and environmental conditions. Regional case study monitoring investigations can document region-specific conditions and processes to inform managers about pesticide movement through watersheds. Additionally, modeling field-collected data within these contexts can be used to predict pesticide presence in un-sampled areas. During a 45 day period in the spring of 2019, we sampled sixteen coastal watersheds in Oregon, USA for current-use water-borne herbicides commonly used in forestland vegetation management. At 80 % of sampling locations, at least one of four commonly used herbicides was detected in integrative passive water samplers, with hexazinone and atrazine most commonly detected. In this study, we use total accumulation of detected compounds to compare relative detections with upstream management and environmental watershed variables using multiple linear regression. An additive effects model was developed using slope, herbicide activity notified during the sampling window, and recent clearcut harvest notifications to predict variation in total herbicide accumulation (R2 = 0.8914). The model was then applied to predict concentrations in un-sampled watersheds throughout the Oregon’s coastal region at three watershed scales using Hydrologic Unit Codes (HUCs) 8, 10, and 12. Regional differences in predicted values were visualized using choropleth maps. Subwatersheds (HUC12) were grouped by subbasin (HUC8) and base mean predicted values were compared to further quantify regional differences. Models predicted that south coast sites have higher than average herbicide concentrations, which aligned with field-collected data findings

FOOD SAFETY INNOVATION IN THE UNITED STATES: EVIDENCE FROM THE MEAT INDUSTRY

Recent industry innovations improving the safety of the Nation's meat supply range from new pathogen tests, high-tech equipment, and supply chain management systems, to new surveillance networks. Despite these and other improvements, the market incentives that motivate private firms to invest in innovation seem to be fairly weak. Results from an ERS survey of U.S. meat and poultry slaughter and processing plants and two case studies of innovation in the U.S. beef industry reveal that the industry has developed a number of mechanisms to overcome that weakness and to stimulate investment in food safety innovation. Industry experience suggests that government policy can increase food safety innovation by reducing informational asymmetries and strengthening the ability of innovating firms to appropriate the benefits of their investments.Food safety, innovation, meat, asymmetric information, Beef Steam Pasteurization System, Bacterial Pathogen Sampling and Testing Program, Food Consumption/Nutrition/Food Safety, Livestock Production/Industries,

Gene expression differs in susceptible and resistant amphibians exposed to Batrachochytrium dendrobatidis.

Chytridiomycosis, the disease caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd), has devastated global amphibian biodiversity. Nevertheless, some hosts avoid disease after Bd exposure even as others experience near-complete extirpation. It remains unclear whether the amphibian adaptive immune system plays a role in Bd defence. Here, we describe gene expression in two host species-one susceptible to chytridiomycosis and one resistant-following exposure to two Bd isolates that differ in virulence. Susceptible wood frogs (Rana sylvatica) had high infection loads and mortality when exposed to the more virulent Bd isolate but lower infection loads and no fatal disease when exposed to the less virulent isolate. Resistant American bullfrogs (R. catesbeiana) had high survival across treatments and rapidly cleared Bd infection or avoided infection entirely. We found widespread upregulation of adaptive immune genes and downregulation of important metabolic and cellular maintenance components in wood frogs after Bd exposure, whereas American bullfrogs showed little gene expression change and no evidence of an adaptive immune response. Wood frog responses suggest that adaptive immune defences may be ineffective against virulent Bd isolates that can cause rapid physiological dysfunction. By contrast, American bullfrogs exhibited robust resistance to Bd that is likely attributable, at least in part, to their continued upkeep of metabolic and skin integrity pathways as well as greater antimicrobial peptide expression compared to wood frogs, regardless of exposure. Greater understanding of these defences will ultimately help conservationists manage chytridiomycosis