An evaluation of planarity of the spatial QRS loop by three dimensional vectorcardiography: its emergence and loss

Aims: To objectively characterize and mathematically justify the observation that vectorcardiographic QRS loops in normal individuals are more planar than those from patients with ST elevation myocardial infarction (STEMI). Methods: Vectorcardiograms (VCGs) were constructed from three simultaneously recorded quasi-orthogonal leads, I, aVF and V2 (sampled at 1000 samples/s). The planarity of these QRS loops was determined by fitting a surface to each loop. Goodness of fit was expressed in numerical terms. Results: 15 healthy individuals aged 35–65 years (73% male) and 15 patients aged 45–70 years (80% male) with diagnosed acute STEMI were recruited. The spatial-QRS loop was found to lie in a plane in normal controls. In STEMI patients, this planarity was lost. Calculation of goodness of fit supported these visual observations. Conclusions: The degree of planarity of the VCG loop can differentiate healthy individuals from patients with STEMI. This observation is compatible with our basic understanding of the electrophysiology of the human heart

Evaluation of CNN-based Single-Image Depth Estimation Methods

While an increasing interest in deep models for single-image depth estimation methods can be observed, established schemes for their evaluation are still limited. We propose a set of novel quality criteria, allowing for a more detailed analysis by focusing on specific characteristics of depth maps. In particular, we address the preservation of edges and planar regions, depth consistency, and absolute distance accuracy. In order to employ these metrics to evaluate and compare state-of-the-art single-image depth estimation approaches, we provide a new high-quality RGB-D dataset. We used a DSLR camera together with a laser scanner to acquire high-resolution images and highly accurate depth maps. Experimental results show the validity of our proposed evaluation protocol

Directed Placement for mVLSI Devices

Continuous-flow microfluidic devices based on integrated channel networks are becoming increasingly prevalent in research in the biological sciences. At present, these devices are physically laid out by hand by domain experts who understand both the underlying technology and the biological functions that will execute on fabricated devices. The lack of a design science that is specific to microfluidic technology creates a substantial barrier to entry. To address this concern, this article introduces Directed Placement, a physical design algorithm that leverages the natural "directedness" in most modern microfluidic designs: fluid enters at designated inputs, flows through a linear or tree-based network of channels and fluidic components, and exits the device at dedicated outputs. Directed placement creates physical layouts that share many principle similarities to those created by domain experts. Directed placement allows components to be placed closer to their neighbors compared to existing layout algorithms based on planar graph embedding or simulated annealing, leading to an average reduction in laid-out fluid channel length of 91% while improving area utilization by 8% on average. Directed placement is compatible with both passive and active microfluidic devices and is compatible with a variety of mainstream manufacturing technologies

Topology and Geometry of the CfA2 Redshift Survey

We analyse the redshift space topology and geometry of the nearby Universe by computing the Minkowski functionals of the Updated Zwicky Catalogue (UZC). The UZC contains the redshifts of almost 20,000 galaxies, is 96% complete to the limiting magnitude m_Zw=15.5 and includes the Center for Astrophysics (CfA) Redshift Survey (CfA2). From the UZC we can extract volume limited samples reaching a depth of 70 hMpc before sparse sampling dominates. We quantify the shape of the large-scale galaxy distribution by deriving measures of planarity and filamentarity from the Minkowski functionals. The nearby Universe shows a large degree of planarity and a small degree of filamentarity. This quantifies the sheet-like structure of the Great Wall which dominates the northern region (CfA2N) of the UZC. We compare these results with redshift space mock catalogues constructed from high resolution N-body simulations of two Cold Dark Matter models with either a decaying massive neutrino (tauCDM) or a non-zero cosmological constant (LambdaCDM). We use semi-analytic modelling to form and evolve galaxies in these dark matter-only simulations. We are thus able, for the first time, to compile redshift space mock catalogues which contain galaxies, along with their observable properties, rather than dark matter particles alone. In both models the large scale galaxy distribution is less coherent than the observed distribution, especially with regard to the large degree of planarity of the real survey. However, given the small volume of the region studied, this disagreement can still be a result of cosmic variance.Comment: 14 pages including 10 figures. Accepted for publication in Monthly Notice

SDSS DR7 superclusters. Morphology

We study the morphology of a set of superclusters drawn from the SDSS DR7. We calculate the luminosity density field to determine superclusters from a flux- limited sample of galaxies from SDSS DR7, and select superclusters with 300 and more galaxies for our study. The morphology of superclusters is described with the fourth Minkowski functional V3, the morphological signature (the curve in the shapefinder's K1-K2 plane) and the shape parameter (the ratio of the shapefinders K1/K2). We investigate the supercluster sample using multidimensional normal mixture modelling, and use Abell clusters to identify our superclusters with known superclusters and to study the large-scale distribution of superclusters. The superclusters in our sample form three chains of superclusters; one of them is the Sloan Great Wall. Most superclusters have filament-like overall shapes. Superclusters can be divided into two sets; more elongated superclusters are more luminous, richer, have larger diameters, and a more complex fine structure than less elongated superclusters. The fine structure of superclusters can be divided into four main morphological types: spiders, multispiders, filaments, and multibranching filaments. We present the 2D and 3D distribution of galaxies and rich groups, the fourth Minkowski functional, and the morphological signature for all superclusters. Widely different morphologies of superclusters show that their evolution has been dissimilar. A study of a larger sample of superclusters from observations and simulations is needed to understand the morphological variety of superclusters and the possible connection between the morphology of superclusters and their large-scale environment.Comment: Comments: 20 pages, 18 figures, accepted for publication in Astronomy and Astrophysic

Bend propagation in the flagella of migrating human sperm

A pre-requisite for sexual reproduction is successful unification of the male and female gametes; in externally-fertilising echinoderms the male gamete is brought into close proximity to the female gamete through chemotaxis, the associated signalling and flagellar beat changes being elegantly characterised in several species. In the human, sperm traverse a relatively high-viscosity mucus coating the tract surfaces, there being a tantalising possible role for chemotaxis. To understand human sperm migration and guidance, studies must therefore employ similar viscous in vitro environments. High frame rate digital imaging is used for the first time to characterise the flagellar movement of migrating sperm in low and high viscosities. While qualitative features have been reported previously, we show in precise spatial and temporal detail waveform evolution along the flagellum. In low viscosity the flagellum continuously moves out of the focal plane, compromising the measurement of true curvature, nonetheless the presence of torsion can be inferred. In high viscosities curvature can be accurately determined and we show how waves propagate at approximately constant speed. Progressing waves increase in curvature approximately linearly except for a sharper increase over a distance 20-27 m from the head/midpiece junction. Curvature modulation, likely influenced by the outer dense fibres, creates the characteristic waveforms of high viscosity swimming, with remarkably effective cell progression against greatly increased resistance, even in high viscosity liquids. Assessment of motility in physiological viscosities will be essential in future basic research, studies of chemotaxis and novel diagnostics

Morphology of Mock SDSS Catalogues

We measure the geometry, topology and morphology of the superclusters in mock SDSS catalogues prepared by Cole et al.(1998). The mock catalogues refer to $\tau$CDM and \LCDM {\em flat} cosmological models and are populated by galaxies so that these act as biased tracers of mass, conforming with the correlation function measured using APM catalogue. We compute the Minkowski Functionals (MFs) for the cosmic density fields using SURFGEN (Sheth et al.2003) and use the available 10 realizations of $\tau$CDM to study the effect of cosmic variance in estimation of MFs and Shapefinders, which we find to be extremely well constrained statistics. Although all the mock catalogues of galaxies have the same two-point correlation function and similar clustering amplitude, the global MFs due to $\tau$CDM show systematically lower amplitude compared to those due to \LCDM; an indirect, but detectable effect due to nonzero, higher order correlation functions. The characteristic thickness (T), breadth (B) and length (L) of the superclusters are measured using the available 10 realizations of $\tau$CDM. While T$\le$B and T, B$\in$[1,17] h$^{-1}$Mpc, we find the top 10 superclusters to be as long as 90 h$^{-1}$Mpc, with the longest superclusters identified at percolation to be rare objects with their length as large as 150 h$^{-1}$Mpc. The $\tau$CDM superclusters are found to be significantly longer than those in \LCDM. Thickness (T), breadth (B), planarity (P) and mass/volume$-$weighted planarity and filamentarity of the superclusters are found to be useful to compare the two models (abridged).Comment: 23 Pages, 12 Figures, MNRAS Style. Minor modifications to the text. New references adde

Sketching space

In this paper, we present a sketch modelling system which we call Stilton. The program resembles a desktop VRML browser, allowing a user to navigate a three-dimensional model in a perspective projection, or panoramic photographs, which the program maps onto the scene as a `floor' and `walls'. We place an imaginary two-dimensional drawing plane in front of the user, and any geometric information that user sketches onto this plane may be reconstructed to form solid objects through an optimization process. We show how the system can be used to reconstruct geometry from panoramic images, or to add new objects to an existing model. While panoramic imaging can greatly assist with some aspects of site familiarization and qualitative assessment of a site, without the addition of some foreground geometry they offer only limited utility in a design context. Therefore, we suggest that the system may be of use in `just-in-time' CAD recovery of complex environments, such as shop floors, or construction sites, by recovering objects through sketched overlays, where other methods such as automatic line-retrieval may be impossible. The result of using the system in this manner is the `sketching of space' - sketching out a volume around the user - and once the geometry has been recovered, the designer is free to quickly sketch design ideas into the newly constructed context, or analyze the space around them. Although end-user trials have not, as yet, been undertaken we believe that this implementation may afford a user-interface that is both accessible and robust, and that the rapid growth of pen-computing devices will further stimulate activity in this area

The Anisotropic Distribution of Galactic Satellites

We present a study of the spatial distribution of subhalos in galactic dark matter halos using dissipationless cosmological simulations of the concordance LCDM model. We find that subhalos are distributed anisotropically and are preferentially located along the major axes of the triaxial mass distributions of their hosts. The Kolmogorov-Smirnov probability for drawing our simulated subhalo sample from an isotropic distribution is P_KS \simeq 1.5 \times 10^{-4}. An isotropic distribution of subhalos is thus not the correct null hypothesis for testing the CDM paradigm. The nearly planar distribution of observed Milky Way (MW) satellites is marginally consistent (probability \simeq 0.02) with being drawn randomly from the subhalo distribution in our simulations. Furthermore, if we select the subhalos likely to be luminous, we find a distribution that is consistent with the observed MW satellites. In fact, we show that subsamples of the subhalo population with a centrally-concentrated radial distribution, similar to that of the MW dwarfs, typically exhibit a comparable degree of planarity. We explore the origin of the observed subhalo anisotropy and conclude that it is likely due to (1) preferential accretion of subhalos along filaments, often closely aligned with the major axis of the host halo, and (2) evolution of satellite orbits within the prolate, triaxial potentials typical of CDM halos. Agreement between predictions and observations requires the major axis of the outer dark matter halo of the Milky Way to be nearly perpendicular to the disk. We discuss possible observational tests of such disk-halo alignment with current large galaxy surveys.Comment: 14 pages (including appendix), 9 figures. Accepted for Publication in ApJ. Minor changes to reflect referee's comment

Automated Classification of Airborne Laser Scanning Point Clouds

Making sense of the physical world has always been at the core of mapping. Up until recently, this has always dependent on using the human eye. Using airborne lasers, it has become possible to quickly "see" more of the world in many more dimensions. The resulting enormous point clouds serve as data sources for applications far beyond the original mapping purposes ranging from flooding protection and forestry to threat mitigation. In order to process these large quantities of data, novel methods are required. In this contribution, we develop models to automatically classify ground cover and soil types. Using the logic of machine learning, we critically review the advantages of supervised and unsupervised methods. Focusing on decision trees, we improve accuracy by including beam vector components and using a genetic algorithm. We find that our approach delivers consistently high quality classifications, surpassing classical methods