Temperature sensitivity of the oxygenation reaction of stripped haemolysates from the freshwater fishes Labeo capensis and Ciarias gariepinus

The oxygen binding properties of haemoglobin solutions of the mudfish Labeo capensis and the catfish Clarias gariepinus, stripped by gel filtration chromatography and buffered at 23°C in 0,05 M Hepes (pH 7,48), were determined at 8°C, 15°C and 23°C. The P50 values obtained for L. capensis at these respective temperatures were 0,89 (pH 7,63); 1,29 (pH 7,52) and 3,02 (pH 7,49) and those for C. gariepinus haemoglobin were 2,47 (pH 7,61 ); 3,34 (pH 7,53) and 6,30 (pH 7,49). The lower oxygen affinity of C. gariepinus haemoglobin may be related to the obligatory air breathing of C. gariepinus by means of a branchial organ which is absent in the mudfish. The purified hemolysate from C. gariepinus also displayed higher haem-haem co-operativity (n) at all three experimental temperatures compared to L. capensis. The heat of oxygenation (ΔH) between 8°C (pH 7,63) and 23°C (pH 7,49) calculated for L. capensis haemoglobin (−56,3 kJ.mol1) exceeded that of C. gariepinus (−43,1 kJ.mol1)

Semi-supervised clustering on heterogeneous information networks

Postprin

The Localization Transition of the Two-Dimensional Lorentz Model

We investigate the dynamics of a single tracer particle performing Brownian motion in a two-dimensional course of randomly distributed hard obstacles. At a certain critical obstacle density, the motion of the tracer becomes anomalous over many decades in time, which is rationalized in terms of an underlying percolation transition of the void space. In the vicinity of this critical density the dynamics follows the anomalous one up to a crossover time scale where the motion becomes either diffusive or localized. We analyze the scaling behavior of the time-dependent diffusion coefficient D(t) including corrections to scaling. Away from the critical density, D(t) exhibits universal hydrodynamic long-time tails both in the diffusive as well as in the localized phase.Comment: 13 pages, 7 figures

Unsupervised classemes

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-33885-4_41Proceedings of Information Fusion in Computer Vision for Concept Recognition at the ECCV 2012In this paper we present a new model of semantic features that, unlike previously presented methods, does not rely on the presence of a labeled training data base, as the creation of the feature extraction function is done in an unsupervised manner. We test these features on an unsupervised classification (clustering) task, and show that they outperform primitive (low-level) features, and that have performance comparable to that of supervised semantic features, which are much more expensive to determine relying on the presence of a labeled training set to train the feature extraction function

The response function of a sphere in a viscoelastic two-fluid medium

In order to address basic questions of importance to microrheology, we study the dynamics of a rigid sphere embedded in a model viscoelastic medium consisting of an elastic network permeated by a viscous fluid. We calculate the complete response of a single bead in this medium to an external force and compare the result to the commonly-accepted, generalized Stokes-Einstein relation (GSER). We find that our response function is well approximated by the GSER only within a particular frequency range determined by the material parameters of both the bead and the network. We then discuss the relevance of this result to recent experiments. Finally we discuss the approximations made in our solution of the response function by comparing our results to the exact solution for the response function of a bead in a viscous (Newtonian) fluid.Comment: 12 pages, 2 figure

Phase Transitions of Hard Disks in External Periodic Potentials: A Monte Carlo Study

The nature of freezing and melting transitions for a system of hard disks in a spatially periodic external potential is studied using extensive Monte Carlo simulations. Detailed finite size scaling analysis of various thermodynamic quantities like the order parameter, its cumulants etc. are used to map the phase diagram of the system for various values of the density and the amplitude of the external potential. We find clear indication of a re-entrant liquid phase over a significant region of the parameter space. Our simulations therefore show that the system of hard disks behaves in a fashion similar to charge stabilized colloids which are known to undergo an initial freezing, followed by a re-melting transition as the amplitude of the imposed, modulating field produced by crossed laser beams is steadily increased. Detailed analysis of our data shows several features consistent with a recent dislocation unbinding theory of laser induced melting.Comment: 36 pages, 16 figure

Detector Description and Performance for the First Coincidence Observations between LIGO and GEO

For 17 days in August and September 2002, the LIGO and GEO interferometer gravitational wave detectors were operated in coincidence to produce their first data for scientific analysis. Although the detectors were still far from their design sensitivity levels, the data can be used to place better upper limits on the flux of gravitational waves incident on the earth than previous direct measurements. This paper describes the instruments and the data in some detail, as a companion to analysis papers based on the first data.Comment: 41 pages, 9 figures 17 Sept 03: author list amended, minor editorial change

Deep Learning of Representations: Looking Forward

Deep learning research aims at discovering learning algorithms that discover multiple levels of distributed representations, with higher levels representing more abstract concepts. Although the study of deep learning has already led to impressive theoretical results, learning algorithms and breakthrough experiments, several challenges lie ahead. This paper proposes to examine some of these challenges, centering on the questions of scaling deep learning algorithms to much larger models and datasets, reducing optimization difficulties due to ill-conditioning or local minima, designing more efficient and powerful inference and sampling procedures, and learning to disentangle the factors of variation underlying the observed data. It also proposes a few forward-looking research directions aimed at overcoming these challenges

Analysis of LIGO data for gravitational waves from binary neutron stars

We report on a search for gravitational waves from coalescing compact binary systems in the Milky Way and the Magellanic Clouds. The analysis uses data taken by two of the three LIGO interferometers during the first LIGO science run and illustrates a method of setting upper limits on inspiral event rates using interferometer data. The analysis pipeline is described with particular attention to data selection and coincidence between the two interferometers. We establish an observational upper limit of $\mathcal{R}<$1.7 \times 10^{2}$per year per Milky Way Equivalent Galaxy (MWEG), with 90coalescence rate of binary systems in which each component has a mass in the range 1--3$M_\odot$.Comment: 17 pages, 9 figure