Ubiquity of optical activity in planar metamaterial scatterers

Recently it was discovered that periodic lattices of metamaterial scatterers show optical activity, even if the scatterers or lattice show no 2D or 3D chirality, if the illumination breaks symmetry. In this Letter we demonstrate that such `pseudo-chirality' is intrinsic to any single planar metamaterial scatterer and in fact has a well-defined value at a universal bound. We argue that in any circuit model, a nonzero electric and magnetic polarizability derived from a single resonance automatically imply strong bianisotropy, i.e., magneto-electric cross polarizability at the universal bound set by energy conservation. We confirm our claim by extracting polarizability tensors and cross sections for handed excitation from transmission measurements on near-infrared split ring arrays, and electrodynamic simulations for diverse metamaterial scatterers.Comment: 5 pages, 4 figure

Kernel Bounds for Structural Parameterizations of Pathwidth

Assuming the AND-distillation conjecture, the Pathwidth problem of determining whether a given graph G has pathwidth at most k admits no polynomial kernelization with respect to k. The present work studies the existence of polynomial kernels for Pathwidth with respect to other, structural, parameters. Our main result is that, unless NP is in coNP/poly, Pathwidth admits no polynomial kernelization even when parameterized by the vertex deletion distance to a clique, by giving a cross-composition from Cutwidth. The cross-composition works also for Treewidth, improving over previous lower bounds by the present authors. For Pathwidth, our result rules out polynomial kernels with respect to the distance to various classes of polynomial-time solvable inputs, like interval or cluster graphs. This leads to the question whether there are nontrivial structural parameters for which Pathwidth does admit a polynomial kernelization. To answer this, we give a collection of graph reduction rules that are safe for Pathwidth. We analyze the success of these results and obtain polynomial kernelizations with respect to the following parameters: the size of a vertex cover of the graph, the vertex deletion distance to a graph where each connected component is a star, and the vertex deletion distance to a graph where each connected component has at most c vertices.Comment: This paper contains the proofs omitted from the extended abstract published in the proceedings of Algorithm Theory - SWAT 2012 - 13th Scandinavian Symposium and Workshops, Helsinki, Finland, July 4-6, 201

The melting performance of single screw extruders

A number of recent screw designs is analyzed for melting performance, using a simple analytical approach based on Tadmor's original work. The melting length for a screw with constant depth channel is used as reference. An ideal compression screw will have a melting length of one-half the melting length of the reference screw. The Maillefer melt separation principle is discussed. The Maillefer screw melts in 2/3 of the length of the reference screw. Screws by Barr, by Dray and Lawrence and by Kim are shown to approach the ideal compression screw. A new design screw, using ideal compression and multiple channels and having a very large screw pitch, is shown to be a considerably more efficient melting device than any of the other, screws discussed

Radio-frequency transparent demodulation for broadband hybrid wireless-optical links

A novel demodulation technique which is transparent to radio-frequency (RF) carrier frequency is presented and experimentally demonstrated for multigigabit wireless signals. The presented demodulation technique employs optical single-sideband filtering, coherent detection, and baseband digital signal processing. Multigigabit wireless signal demodulation of 1.25-Gbaud quadrature phase-shift-keying modulated data at 40- and 35-GHz RF carrier frequency is experimentally demonstrated using the proposed demodulation scheme

Advances in Learning Bayesian Networks of Bounded Treewidth

This work presents novel algorithms for learning Bayesian network structures with bounded treewidth. Both exact and approximate methods are developed. The exact method combines mixed-integer linear programming formulations for structure learning and treewidth computation. The approximate method consists in uniformly sampling $k$-trees (maximal graphs of treewidth $k$), and subsequently selecting, exactly or approximately, the best structure whose moral graph is a subgraph of that $k$-tree. Some properties of these methods are discussed and proven. The approaches are empirically compared to each other and to a state-of-the-art method for learning bounded treewidth structures on a collection of public data sets with up to 100 variables. The experiments show that our exact algorithm outperforms the state of the art, and that the approximate approach is fairly accurate.Comment: 23 pages, 2 figures, 3 table

Energy quantization in solution-processed layers of indium oxide and their application in resonant tunneling diodes

\u3cp\u3eThe formation of quantized energy states in ultrathin layers of indium oxide (In\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e) grown via spin coating and thermally annealed at 200°C in air is studied. Optical absorption measurements reveal a characteristic widening of the optical band gap with reducing In\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e layer thickness from ≈43 to ≈3 nm in agreement with theoretical predictions for an infinite quantum well. Through sequential deposition of In\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e and gallium oxide (Ga\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e) layers, superlattice-like structures with controlled dimensionality and spatially varying conduction band characteristics are demonstrated. This simple method is then explored for the fabrication of functional double-barrier resonant tunneling diodes. Nanoscale current mapping analysis using conductive atomic force microscopy reveals that resonant tunneling is not uniform but localized in specific regions of the apparent device area. The latter observation is attributed to variation in the layer(s) thickness of the In\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e quantum well and/or the Ga\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e barrier layers. Despite the nonidealities, the tremendous potential of solution-processable oxide semiconductors for the development of quantum effect devices that have so far been demonstrated only via sophisticated growth techniques is demonstrated.\u3c/p\u3

Creating information delivery specifications using linked data

The use of Building Information Management (BIM) has become mainstream in many countries. Exchanging data in open standards like the Industry Foundation Classes (IFC) is seen as the only workable solution for collaboration. To define information needs for collaboration, many organizations are now documenting what kind of data they need for their purposes. Currently practitioners define their requirements often a) in a format that cannot be read by a computer; b) by creating their own definitions that are not shared. This paper proposes a bottom up solution for the definition of new building concepts a property. The authors have created a prototype implementation and will elaborate on the capturing of information specifications in the future

Resource Usage Analysis from a Different Perspective on MOOC Dropout

We present a novel learning analytics approach, for analyzing the usage of resources in MOOCs. Our target stakeholders are the course designers who aim to evaluate their learning materials. In order to gain insight into the way educational resources are used, we view dropout behaviour in an atypical manner: Instead of using it as an indicator of failure, we use it as a mean to compute other features. For this purpose, we developed a prototype, called RUAF, that can be applied to the data format provided by FutureLearn. As a proof of concept, we perform a study by applying this tool to the interaction data of learners from four MOOCs. We also study the quality of our computations, by comparing them to existing process mining approaches. We present results that highlight patterns showing how learners use resources. We also show examples of practical conclusions a course designer may benefit from.Comment: 30 pages, 40 figure

Variational principle for scale-free network motifs

For scale-free networks with degrees following a power law with an exponent $\tau\in(2,3)$, the structures of motifs (small subgraphs) are not yet well understood. We introduce a method designed to identify the dominant structure of any given motif as the solution of an optimization problem. The unique optimizer describes the degrees of the vertices that together span the most likely motif, resulting in explicit asymptotic formulas for the motif count and its fluctuations. We then classify all motifs into two categories: motifs with small and large fluctuations

Network-Assisted Resource Allocation with Quality and Conflict Constraints for V2V Communications

The 3rd Generation Partnership Project (3GPP) has recently established in Rel. 14 a network-assisted resource allocation scheme for vehicular broadcast communications. Such novel paradigm is known as vehicle--to--vehicle (V2V) \textit{mode-3} and consists in eNodeBs engaging only in the distribution of sidelink subchannels among vehicles in coverage. Thereupon, without further intervention of the former, vehicles will broadcast their respective signals directly to their counterparts. Because the allotment of subchannels takes place intermittently to reduce signaling, it must primarily be conflict-free in order not to jeopardize the reception of signals. We have identified four pivotal types of allocation requirements that must be guaranteed: one quality of service (QoS) requirement and three conflict conditions which must be precluded in order to preserve reception reliability. The underlying problem is formulated as a maximization of the system sum-capacity with four types of constraints that must be enforced. In addition, we propose a three-stage suboptimal approach that is cast as multiple independent knapsack problems (MIKPs). We compare the two approaches through simulations and show that the latter formulation can attain acceptable performance at lesser complexity