Aplodontid, sciurid, castorid, zapodid and geomyoid rodents of the Rodent Hill locality, Cypress Hills formation, southwest Saskatchewan

The Rodent Hill Locality is a fossil-bearing site that is part of the Cypress Hills Formation, and is located roughly 15 km northwest of the town of Eastend, Saskatchewan. A number of fossil mammal and other vertebrate taxa are present at Rodent Hill; the primary objective of this project was to identify the fossil rodents of the families Sciuridae, Aplodontidae, Castoridae, Heliscomyidae, Heteromyidae, Florentiamyidae and Zapodidae. These taxa were correlated with rodents from other North American faunas to establish the age of the Rodent Hill Locality. The species Haplomys cf. H. liolophus, Dakotallomys cf. D. pelycomyoides, Kirkomys milleri, Proheteromys nebraskensis, Agnotocastor cf. A. praetereadens, and possibly Cedromus cf. C. wilsoni support the Whitneyan age designation of the Rodent Hill Locality. Taxa that are described from Rodent Hill that are better known from earlier-age sites include Heliscomys vetus and H. hatcheri, Ecclesimus sp. and Oligotheriomys sp. Taxa that are younger than Whitneyan but have been recovered at Rodent Hill include Parallomys sp., Plesiosminthus sp., Protospermophilus sp., and Nototamias sp. Two new species in the genus Sciurion, and one new species in the genus Pseudallomys are described, and a new species of Heliscomys is identified but not formally named. The rodents from the Rodent Hill Locality support the Whitneyan age assignment of the site. This is based on the presence of Whitneyan taxa, and the in situ co-occurrence of older and younger taxa within the site

Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences

With the rapid proliferation of smart mobile devices, users now take millions of photos every day. These include large numbers of clothing and accessory images. We would like to answer questions like `What outfit goes well with this pair of shoes?' To answer these types of questions, one has to go beyond learning visual similarity and learn a visual notion of compatibility across categories. In this paper, we propose a novel learning framework to help answer these types of questions. The main idea of this framework is to learn a feature transformation from images of items into a latent space that expresses compatibility. For the feature transformation, we use a Siamese Convolutional Neural Network (CNN) architecture, where training examples are pairs of items that are either compatible or incompatible. We model compatibility based on co-occurrence in large-scale user behavior data; in particular co-purchase data from Amazon.com. To learn cross-category fit, we introduce a strategic method to sample training data, where pairs of items are heterogeneous dyads, i.e., the two elements of a pair belong to different high-level categories. While this approach is applicable to a wide variety of settings, we focus on the representative problem of learning compatible clothing style. Our results indicate that the proposed framework is capable of learning semantic information about visual style and is able to generate outfits of clothes, with items from different categories, that go well together.Comment: ICCV 201

"Rho"ing a Cellular Boat with Rearward Membrane Flow.

The physicist Edward Purcell wrote in 1977 about mechanisms that cells could use to propel themselves in a low Reynolds number environment. Reporting in Developmental Cell, O'Neill et al. (2018) provide direct evidence for one of these mechanisms by optogenetically driving the migration of cells suspended in liquid through RhoA activation

Relationship between Hawking Radiation and Gravitational Anomalies

We show that in order to avoid a breakdown of general covariance at the quantum level the total flux in each outgoing partial wave of a quantum field in a black hole background must be equal to that of a (1+1)-dimensional blackbody at the Hawking temperature.Comment: 5 pages, 1 figure; v2: typo corrected, reference added; v3: comment added, minor editorial changes to agree with published versio

Material Recognition in the Wild with the Materials in Context Database

Recognizing materials in real-world images is a challenging task. Real-world materials have rich surface texture, geometry, lighting conditions, and clutter, which combine to make the problem particularly difficult. In this paper, we introduce a new, large-scale, open dataset of materials in the wild, the Materials in Context Database (MINC), and combine this dataset with deep learning to achieve material recognition and segmentation of images in the wild. MINC is an order of magnitude larger than previous material databases, while being more diverse and well-sampled across its 23 categories. Using MINC, we train convolutional neural networks (CNNs) for two tasks: classifying materials from patches, and simultaneous material recognition and segmentation in full images. For patch-based classification on MINC we found that the best performing CNN architectures can achieve 85.2% mean class accuracy. We convert these trained CNN classifiers into an efficient fully convolutional framework combined with a fully connected conditional random field (CRF) to predict the material at every pixel in an image, achieving 73.1% mean class accuracy. Our experiments demonstrate that having a large, well-sampled dataset such as MINC is crucial for real-world material recognition and segmentation.Comment: CVPR 2015. Sean Bell and Paul Upchurch contributed equall

Shock Vorticity Generation from Accelerated Ion Streaming in the Precursor of Ultrarelativistic Gamma-Ray Burst External Shocks

We investigate the interaction of nonthermal ions (protons and nuclei) accelerated in an ultrarelativistic blastwave with the pre-existing magnetic field of the medium into which the blastwave propagates. While particle acceleration processes such as diffusive shock acceleration can accelerate ions and electrons, the accelerated electrons suffer larger radiative losses. Under certain conditions, the ions can attain higher energies and reach farther ahead of the shock than the electrons, and so the nonthermal particles can be partially charge-separated. To compensate for the charge separation, the upstream plasma develops a return current, which, as it flows across the magnetic field, drives transverse acceleration of the upstream plasma and a growth of density contrast in the shock upstream. If the density contrast is strong by the time the fluid is shocked, vorticity is generated at the shock transition. The resulting turbulence can amplify the post-shock magnetic field to the levels inferred from gamma-ray burst afterglow spectra and light curves. Therefore, since the upstream inhomogeneities are induced by the ions accelerated in the shock, they are generic even if the blastwave propagates into a medium of uniform density. We speculate about the global structure of the shock precursor, and delineate several distinct physical regimes that are classified by an increasing distance from the shock and, correspondingly, a decreasing density of nonthermal particles that reach that distance.Comment: 8 pages, no figure