Building Disease Detection Algorithms with Very Small Numbers of Positive Samples

Although deep learning can provide promising results in medical image analysis, the lack of very large annotated datasets confines its full potential. Furthermore, limited positive samples also create unbalanced datasets which limit the true positive rates of trained models. As unbalanced datasets are mostly unavoidable, it is greatly beneficial if we can extract useful knowledge from negative samples to improve classification accuracy on limited positive samples. To this end, we propose a new strategy for building medical image analysis pipelines that target disease detection. We train a discriminative segmentation model only on normal images to provide a source of knowledge to be transferred to a disease detection classifier. We show that using the feature maps of a trained segmentation network, deviations from normal anatomy can be learned by a two-class classification network on an extremely unbalanced training dataset with as little as one positive for 17 negative samples. We demonstrate that even though the segmentation network is only trained on normal cardiac computed tomography images, the resulting feature maps can be used to detect pericardial effusion and cardiac septal defects with two-class convolutional classification networks

Advanced Techniques for Rehabilitation after Total Hip and Knee Arthroplasty: Henry Chase Marble, 1885–Unknown

This biographical sketch on Henry Chase Marble corresponds to the historic text, The Classic: Application of Curative Therapy in the Ward, available at DOI 10.1007/s11999-009-0790-1

Zone center phonons of the orthorhombic RMnO3 (R = Pr, Eu, Tb, Dy, Ho) perovskites

A short range force constant model (SRFCM) has been applied for the first time to investigate the phonons in RMnO3 (R = Pr, Eu, Tb, Dy, Ho) perovskites in their orthorhombic phase. The calculations with 17 stretching and bending force constants provide good agreement for the observed Raman frequencies. The infrared frequencies have been assigned for the first time. PACS Codes: 36.20.Ng, 33.20.Fb, 34.20.CfComment: 8 pages, 1 figur

Gamma, X-ray and neutron shielding properties of polymer concretes

We have studied the X-ray and gamma radiation shielding parameters such as mass attenuation coefficient, linear attenuation coefficient, half value layer, tenth value layer, effective atomic numbers, electron density, exposure buildup factors, relative dose, dose rate and specific gamma ray constant in some polymer based concretes such as sulfur polymer concrete, barium polymer concrete, calcium polymer concrete, flourine polymer concrete, chlorine polymer concrete and germanium polymer concrete. The neutron shielding properties such as coherent neutron scattering length, incoherent neutron scattering lengths, coherent neutron scattering cross section, incoherent neutron scattering cross sections, total neutron scattering cross section and neutron absorption cross sections in the polymer concretes have been studied. The shielding properties among the studied different polymer concretes have been compared. From the detail study, it is clear that barium polymer concrete is good absorber for X-ray, gamma radiation and neutron. The attenuation parameters for neutron are large for chlorine polymer concrete. Hence, we suggest barium polymer concrete and chlorine polymer concrete are the best shielding materials for X-ray, gamma and neutrons

Interacting invariants for Floquet phases of fermions in two dimensions

We construct a many-body quantized invariant that sharply distinguishes among two-dimensional nonequilibrium driven phases of interacting fermions. This is an interacting generalization of a band-structure Floquet quasienergy winding number and describes chiral pumping of quantum information along the edge. In particular, our invariant sharply distinguishes between a trivial and anomalous Floquet Anderson insulator in the interacting, many-body localized setting. It also applies more generally to models where only fermion parity is conserved, where it differentiates between trivial models and ones that pump Kitaev Majorana chains to the boundary, such as ones recently introduced in the context of emergent fermions arising from eigenstate Z2 topological order. We evaluate our invariant for the edge of such a system with eigenstate Z2 topological order, and show that it is necessarily nonzero when the Floquet unitary exchanges electric and magnetic excitations, proving a connection between bulk anyonic symmetry and edge chirality that was recently conjectured

Suppressing the Folding of Flowing Viscous Jets Using an Electric Field

In this work, we study the folding and unfolding of flowing viscous jets by imposing an electric field. We demonstrate that a folded viscous jet can be induced to unfold through jet widening in a sufficiently strong electric field. The folded jets unfold above a critical slenderness, which increases as the jet capillary number increases. Our systematic elucidation of the mechanisms behind the controlled folding has important implications on processes such as nozzle designs for industrial applications that rely on the manipulation of high-speed viscous jets, including liquid dispensing, printing, and food processing.published_or_final_versio

GiViP: A Visual Profiler for Distributed Graph Processing Systems

Analyzing large-scale graphs provides valuable insights in different application scenarios. While many graph processing systems working on top of distributed infrastructures have been proposed to deal with big graphs, the tasks of profiling and debugging their massive computations remain time consuming and error-prone. This paper presents GiViP, a visual profiler for distributed graph processing systems based on a Pregel-like computation model. GiViP captures the huge amount of messages exchanged throughout a computation and provides an interactive user interface for the visual analysis of the collected data. We show how to take advantage of GiViP to detect anomalies related to the computation and to the infrastructure, such as slow computing units and anomalous message patterns.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

Self-amplified photo-induced gap quenching in a correlated electron material.

Capturing the dynamic electronic band structure of a correlated material presents a powerful capability for uncovering the complex couplings between the electronic and structural degrees of freedom. When combined with ultrafast laser excitation, new phases of matter can result, since far-from-equilibrium excited states are instantaneously populated. Here, we elucidate a general relation between ultrafast non-equilibrium electron dynamics and the size of the characteristic energy gap in a correlated electron material. We show that carrier multiplication via impact ionization can be one of the most important processes in a gapped material, and that the speed of carrier multiplication critically depends on the size of the energy gap. In the case of the charge-density wave material 1T-TiSe2, our data indicate that carrier multiplication and gap dynamics mutually amplify each other, which explains-on a microscopic level-the extremely fast response of this material to ultrafast optical excitation

Chemotaxis When Bacteria Remember: Drift versus Diffusion

{\sl Escherichia coli} ({\sl E. coli}) bacteria govern their trajectories by switching between running and tumbling modes as a function of the nutrient concentration they experienced in the past. At short time one observes a drift of the bacterial population, while at long time one observes accumulation in high-nutrient regions. Recent work has viewed chemotaxis as a compromise between drift toward favorable regions and accumulation in favorable regions. A number of earlier studies assume that a bacterium resets its memory at tumbles -- a fact not borne out by experiment -- and make use of approximate coarse-grained descriptions. Here, we revisit the problem of chemotaxis without resorting to any memory resets. We find that when bacteria respond to the environment in a non-adaptive manner, chemotaxis is generally dominated by diffusion, whereas when bacteria respond in an adaptive manner, chemotaxis is dominated by a bias in the motion. In the adaptive case, favorable drift occurs together with favorable accumulation. We derive our results from detailed simulations and a variety of analytical arguments. In particular, we introduce a new coarse-grained description of chemotaxis as biased diffusion, and we discuss the way it departs from older coarse-grained descriptions.Comment: Revised version, journal reference adde