Phase transition in the scalar noise model of collective motion in three dimensions

We consider disorder-order phase transitions in the three-dimensional version of the scalar noise model (SNM) of flocking. Our results are analogous to those found for the two-dimensional case. For small velocity (v <= 0.1) a continuous, second-order phase transition is observable, with the diffusion of nearby particles being isotropic. By increasing the particle velocities the phase transition changes to first order, and the diffusion becomes anisotropic. The first-order transition in the latter case is probably caused by the interplay between anisotropic diffusion and periodic boundary conditions, leading to a boundary condition dependent symmetry breaking of the solutions.Comment: 7 pages, 6 figures; submitted to EPJ on 17 of April, 200

On LL-close Sperner systems

For a set $L$ of positive integers, a set system $\mathcal{F} \subseteq 2^{[n]}$ is said to be $L$-close Sperner, if for any pair $F,G$ of distinct sets in $\mathcal{F}$ the skew distance $sd(F,G)=\min\{|F\setminus G|,|G\setminus F|\}$ belongs to $L$. We reprove an extremal result of Boros, Gurvich, and Milani\v c on the maximum size of $L$-close Sperner set systems for $L=\{1\}$ and generalize to $|L|=1$ and obtain slightly weaker bounds for arbitrary $L$. We also consider the problem when $L$ might include 0 and reprove a theorem of Frankl, F\"uredi, and Pach on the size of largest set systems with all skew distances belonging to $L=\{0,1\}$

Dependent Double Branching Annihilating Random Walk

Double (or parity conserving) branching annihilating random walk, introduced by Sudbury in '90, is a one-dimensional non-attractive particle system in which positive and negative particles perform nearest neighbor hopping, produce two offsprings to neighboring lattice points and annihilate when they meet. Given an odd number of initial particles, positive recurrence as seen from the leftmost particle position was first proved by Belitsky, Ferrari, Menshikov and Popov in '01 and, subsequently in a much more general setup, in the article by Sturm and Swart (Tightness of voter model interfaces) in '08. These results assume that jump rates of the various moves do not depend on the configuration of the particles not involved in these moves. The present article deals with the case when the jump rates are affected by the locations of several particles in the system. Motivation for such models comes from non-attractive interacting particle systems with particle conservation. Under suitable assumptions we establish the existence of the process, and prove that the one-particle state is positive recurrent. We achieve this by arguments similar to those appeared in the previous article by Sturm and Swart. We also extend our results to some cases of long range jumps, when branching can also occur to non-neighboring sites. We outline and discuss several particular examples of models where our results apply.Comment: 35 pages, 7 figure

Intelligent Assisting Tools for Endodontic Treatment

The integration of image processing in novel systems bids fair to significantly improve the endodontic practice in the near future. Also, the attempt to automatically locate and classify the root canals may result in significantly decreased chair time for both the patient and the practitioner. We focus on the shapes of human root canals and their automatic classification, methods for automatic processing, and center line identification of tooth root canal as defined previously. We introduce some micro-computed tomography image analysis methods possible for clinical implementation of cone beam computed tomography image analysis in endodontics and limitations of novel techniques. In this chapter, we present our results of segmentation and root canal identification of cone beam computed tomography images

Faster than FAST: GPU-Accelerated Frontend for High-Speed VIO

The recent introduction of powerful embedded graphics processing units (GPUs) has allowed for unforeseen improvements in real-time computer vision applications. It has enabled algorithms to run onboard, well above the standard video rates, yielding not only higher information processing capability, but also reduced latency. This work focuses on the applicability of efficient low-level, GPU hardware-specific instructions to improve on existing computer vision algorithms in the field of visual-inertial odometry (VIO). While most steps of a VIO pipeline work on visual features, they rely on image data for detection and tracking, of which both steps are well suited for parallelization. Especially non-maxima suppression and the subsequent feature selection are prominent contributors to the overall image processing latency. Our work first revisits the problem of non-maxima suppression for feature detection specifically on GPUs, and proposes a solution that selects local response maxima, imposes spatial feature distribution, and extracts features simultaneously. Our second contribution introduces an enhanced FAST feature detector that applies the aforementioned non-maxima suppression method. Finally, we compare our method to other state-of-the-art CPU and GPU implementations, where we always outperform all of them in feature tracking and detection, resulting in over 1000fps throughput on an embedded Jetson TX2 platform. Additionally, we demonstrate our work integrated in a VIO pipeline achieving a metric state estimation at ~200fps.Comment: IEEE International Conference on Intelligent Robots and Systems (IROS), 2020. Open-source implementation available at https://github.com/uzh-rpg/vili

Stability analysis of nonlinear power electronics systems utilizing periodicity and introducing auxiliary state vector

Variable-structure piecewise-linear nonlinear dynamic feedback systems emerge frequently in power electronics. This paper is concerned with the stability analysis of these systems. Although it applies the usual well-known and widely used approach, namely, the eigenvalues of the Jacobian matrix of the Poincare/spl acute/ map function belonging to a fixed point of the system to ascertain the stability, this paper offers two contributions for simplification as well that utilize the periodicity of the structure or configuration sequence and apply an alternative simpler and faster method for the determination of the Jacobian matrix. The new method works with differences of state variables rather than derivatives of the Poincare/spl acute/ map function (PMF) and offers geometric interpretations for each step. The determination of the derivates of PMF is not needed. A key element is the introduction of the so-called auxiliary state vector for preserving the switching instant belonging to the periodic steady-state unchanged even after the small deviations of the system orbit around the fixed point. In addition, the application of the method is illustrated on a resonant dc-dc buck converter

Implementing Risk Adjusted Capitation Payments with Health Care Reforms in Hung

Since the late nineties Hungarian governments have been considering the introduction of new health care arrangements by establishing organizations with devolved responsibilities for the management of health care. These organizations are typically financed through a weighted (risk adjusted) capitation system which is regarded as an adequate and optimal tool for resource allocation purposes. Through capitation one needs to handle large inequities in the Hungarian health care system and keep an eye on the incentives for efficiency. For the capitation formula a relatively broad choice of risk adjusters are available in the form of pharmacy- and diagnosis-based patient level utilization data (health-based adjusters) and area level socio-economic data (non health-based adjusters). The instant application of health-based adjusters has limitations because they reflect a distorted provider structure and offer perverse incentives; therefore a gradual shift from using non health-based adjusters to health-based adjusters is preferred. The early phase of the capitation system also implies a strong presence of risk sharing arrangements and other complementary policies. Given that promoting efficiency and equity are to be pursued, the capitation approach outlined in this paper should serve as a guide to future Hungarian health care system reforms. Journal of Economic Literature (JEL) code: I28, G28, G32, H5

Two body problem on two point homogeneous spaces, invariant differential operators and the mass center concept

We consider the two body problem with central interaction on two point homogeneous spaces from point of view of the invariant differential operators theory. The representation of the two particle Hamiltonian in terms of the radial differential operator and invariant operators on the symmetry group is found. The connection of different mass center definitions for these spaces to the obtained expression for Hamiltonian operator is studied.Comment: 26 pages, LaTeX, no figures, text improve

Measuring and filtering reactive inhibition is essential for assessing serial decision making and learning

Learning complex structures from stimuli requires extended exposure and often repeated observation of the same stimuli. Learning induces stimulus-dependent changes in specific performance measures. The same performance measures, however, can also be affected by processes that arise due to extended training (e.g. fatigue) but are otherwise independent from learning. Thus, a thorough assessment of the properties of learning can only be achieved by identifying and accounting for the effects of such processes. Reactive inhibition is a process that modulates behavioral performance measures on a wide range of time scales and often has opposite effects than learning. Here we develop a tool to disentangle the effects of reactive inhibition from learning in the context of an implicit learning task, the alternating serial reaction time task. Our method highlights that the magnitude of the effect of reactive inhibition on measured performance is larger than that of the acquisition of statistical structure from stimuli. We show that the effect of reactive inhibition can be identified not only in population measures but also at the level of performance of individuals, revealing varying degrees of contribution of reactive inhibition. Finally, we demonstrate that a higher proportion of behavioral variance can be explained by learning once the effects of reactive inhibition are eliminated. These results demonstrate that reactive inhibition has a fundamental effect on the behavioral performance that can be identified in individual participants and can be separated from other cognitive processes like learning