Feeling entitled to more: Ostracism increases dishonest behavior

postprin

Rejecting another pains the self: The impact of perceived future rejection

The current investigation examined whether people would experience a higher level of pain after rejecting another person, especially for those high in evaluative concern, through increased perceptions of future rejection. Three experiments provide converging support to these predictions. After reliving a past rejecting experience (Experiments 1 and 2) and concurrently rejecting another person (Experiment 3), the source of rejection experienced a higher level of pain than participants in the control conditions. We also found that evaluative concern, either primed (Experiment 2) or measured (Experiment 3) moderated the above effect, such that this effect was only observed among participants high in evaluative concern, but not among those low in evaluative concern. Moreover, perceived future rejection mediated the moderating effect of evaluative concern and rejecting another person on the levels of pain that people experience (Experiment 3). These findings contribute to the literature by showing a mechanism explaining why rejecting another person pains the self and who are more susceptible to this influence.postprin

Glass transition in metallic glasses: A microscopic model of topological fluctuations in the bonding network

Understanding of the structure and dynamics of liquids and glasses at an atomistic level lags well behind that of crystalline materials, even though they are important in many fields. Metallic liquids and glasses provide an opportunity to make significant advances because of its relative simplicity. We propose a microscopic model based on the concept of topological fluctuations in the bonding network. The predicted glass transition temperature, Tg, shows excellent agreement with experimental observations in metallic glasses. To our knowledge this is the first model to predict the glass transition temperature quantitatively from measurable macroscopic variables

Glass transition in metallic glasses: A microscopic model of topological fluctuations in the bonding network

Understanding of the structure and dynamics of liquids and glasses at an atomistic level lags well behind that of crystalline materials, even though they are important in many fields. Metallic liquids and glasses provide an opportunity to make significant advances because of its relative simplicity. We propose a microscopic model based on the concept of topological fluctuations in the bonding network. The predicted glass transition temperature, Tg, shows excellent agreement with experimental observations in metallic glasses. To our knowledge this is the first model to predict the glass transition temperature quantitatively from measurable macroscopic variables

Kinetic pathways of multi-phase surfactant systems

The relaxation following a temperature quench of two-phase (lamellar and sponge phase) and three-phase (lamellar, sponge and micellar phase) samples, has been studied in an SDS/octanol/brine system. In the three-phase case we have observed samples that are initially mainly sponge phase with lamellar and micellar phase on the top and bottom respectively. Upon decreasing temperature most of the volume of the sponge phase is replaced by lamellar phase. During the equilibriation we have observed three regimes of behaviour within the sponge phase: (i) disruption in the sponge texture, then (ii) after the sponge phase homogenises there is a lamellar nucleation regime and finally (iii) a bizarre plume connects the lamellar phase with the micellar phase. The relaxation of the two-phase sample proceeds instead in two stages. First lamellar drops nucleate in the sponge phase forming a onion `gel' structure. Over time the lamellar structure compacts while equilibriating into a two phase lamellar/sponge phase sample. We offer possible explanatioins for some of these observations in the context of a general theory for phase kinetics in systems with one fast and one slow variable.Comment: 1 textfile, 20 figures (jpg), to appear in PR

How good are Global Newton methods? Part 2

Newton's method applied to certain problems with a discontinuous derivative operator is shown to be effective. A global Newton method in this setting is exhibited and its computational complexity is estimated. As an application a method is proposed to solve problems of linear inequalities (linear programming, phase 1). Using an example of the Klee-Minty type due to Blair, it was found that the simplex method (used in super-lindo) required over 2,000 iterations, while the method above required an average of 8 iterations (Newton steps) over 15 random starting values.Naval Surface Weapons Center, Dahlgren, VAhttp://archive.org/details/howgoodareglobal00goldO&MN Direct FundingApproved for public release; distribution is unlimited

Observation of optically addressable nonvolatile memory in VO₂ at room temperature

Vanadium dioxide (VO2) is a phase change material that can reversibly change between high and low resistivity states through electronic and structural phase transitions. Thus far, VO2 memory devices have essentially been volatile at room temperature, and nonvolatile memory has required non-ambient surroundings (e.g., elevated temperatures, electrolytes) and long write times. For the first time, here, the authors report the observation of optically addressable nonvolatile memory in VO2 at room temperature with a readout by voltage oscillations. The read and write times have to be kept shorter than about 150 µs. The writing of the memory and onset of the voltage oscillations have a minimum optical power threshold. Although the physical mechanisms underlying this memory effect require further investigations, this discovery illustrates the potential of VO2 for new computing devices and architectures, such as artificial neurons and oscillatory neural networks

Joint product numerical range and geometry of reduced density matrices

© 2016, Science China Press and Springer-Verlag Berlin Heidelberg. The reduced density matrices of a many-body quantum system form a convex set, whose three-dimensional projection Θ is convex in R3. The boundary ∂Θ of Θ may exhibit nontrivial geometry, in particular ruled surfaces. Two physical mechanisms are known for the origins of ruled surfaces: symmetry breaking and gapless. In this work, we study the emergence of ruled surfaces for systems with local Hamiltonians in infinite spatial dimension, where the reduced density matrices are known to be separable as a consequence of the quantum de Finetti’s theorem. This allows us to identify the reduced density matrix geometry with joint product numerical range Π of the Hamiltonian interaction terms. We focus on the case where the interaction terms have certain structures, such that a ruled surface emerges naturally when taking a convex hull of Π. We show that, a ruled surface on ∂Θ sitting in Π has a gapless origin, otherwise it has a symmetry breaking origin. As an example, we demonstrate that a famous ruled surface, known as the oloid, is a possible shape of Θ, with two boundary pieces of symmetry breaking origin separated by two gapless lines

Sequence-to-Sequence Imputation of Missing Sensor Data

Although the sequence-to-sequence (encoder-decoder) model is considered the state-of-the-art in deep learning sequence models, there is little research into using this model for recovering missing sensor data. The key challenge is that the missing sensor data problem typically comprises three sequences (a sequence of observed samples, followed by a sequence of missing samples, followed by another sequence of observed samples) whereas, the sequence-to-sequence model only considers two sequences (an input sequence and an output sequence). We address this problem by formulating a sequence-to-sequence in a novel way. A forward RNN encodes the data observed before the missing sequence and a backward RNN encodes the data observed after the missing sequence. A decoder decodes the two encoders in a novel way to predict the missing data. We demonstrate that this model produces the lowest errors in 12% more cases than the current state-of-the-art