Critical exponents of Nikolaevskii turbulence

We study the spatial power spectra of Nikolaevskii turbulence in one-dimensional space. First, we show that the energy distribution in wavenumber space is extensive in nature. Then, we demonstrate that, when varying a particular parameter, the spectrum becomes qualitatively indistinguishable from that of Kuramoto-Sivashinsky turbulence. Next, we derive the critical exponents of turbulent fluctuations. Finally, we argue that in some previous studies, parameter values for which this type of turbulence does not appear were mistakenly considered, and we resolve inconsistencies obtained in previous studies.Comment: 9 pages, 6 figure

Engineering Entanglement: The Fast-Approach Phase Gate

Optimal-control techniques and a fast-approach scheme are used to implement a collisional control phase gate in a model of cold atoms in an optical lattice, significantly reducing the gate time as compared to adiabatic evolution while maintaining high fidelity. New objective functionals are given for which optimal paths are obtained for evolution that yields a control-phase gate up to single-atom Rabi shifts. Furthermore, the fast-approach procedure is used to design a path to significantly increase the fidelity of non-adiabatic transport in a recent experiment. Also, the entanglement power of phase gates is quantified.Comment: 7 pages, 4 figures. Phys. Rev. A (in press

Swarm-Oscillators

Nonlinear coupling between inter- and intra-element dynamics appears as a collective behaviour of elements. The elements in this paper denote symptoms such as a bacterium having an internal network of genes and proteins, a reactive droplet, a neuron in networks, etc. In order to elucidate the capability of such systems, a simple and reasonable model is derived. This model exhibits the rich patterns of systems such as cell membrane, cell fusion, cell growing, cell division, firework, branch, and clustered clusters (self-organized hierarchical structure, modular network). This model is extremely simple yet powerful; therefore, it is expected to impact several disciplines.Comment: 9 pages, 4 figure

Results Visualization in the XBrain XML Interface to a Relational Database

The University of Washington's XBrain application is used to dynamically export relational data over the web in XML format, as a prelude to data exchange. We describe additional tools to aid the human user in visualizing the dynamically generated XML results returned by the web application

Establishing the Relative Merits of Interior and Spoke-Type Permanent-Magnet Machines With Ferrite or NdFeB Through Systematic Design Optimization

In this paper, a multiobjective design optimization method combining design-of-experiments techniques and differential-evolution algorithms is presented. The method was implemented and utilized in order to provide practical engineering insights for the optimal design of interior and spoke-type permanent-magnet machines. Two combinations with 12 slots and 8 poles and 12 slots and 10 poles, respectively, have been studied in conjunction with rare-earth neodymium-iron-boron (NdFeB) and ferrites. As part of the optimization process, a computationally efficient finite-element electromagnetic analysis was employed for estimating the performance of thousands of candidate designs. Three optimization objectives were concurrently considered for minimum total material cost, power losses, and torque ripple, respectively. Independent variables were considered for both the stator and rotor geometries. A discussion based on a systematic comparison is included, showing, among other things and despite common misconception, that comparable cost versus loss Paretos can be achieved with any of the rotor topologies studied

Sentiment Recognition in Egocentric Photostreams

Lifelogging is a process of collecting rich source of information about daily life of people. In this paper, we introduce the problem of sentiment analysis in egocentric events focusing on the moments that compose the images recalling positive, neutral or negative feelings to the observer. We propose a method for the classification of the sentiments in egocentric pictures based on global and semantic image features extracted by Convolutional Neural Networks. We carried out experiments on an egocentric dataset, which we organized in 3 classes on the basis of the sentiment that is recalled to the user (positive, negative or neutral)