The impacts of electronic word of mouth in social media on consumers` purchase intentions

The influence of Electronic Word of Mouth (eWOM) on consumers` purchase intentions has been known for a long time. However, eWOM has gained a new dimension with the advent of social media. Before this new phenomenon, people were able to talk with anonymous people on the Internet. Social media enable people to talk with friends and acquaintances, on the Internet. This new way of eWOM might be more powerful in terms of triggering purchase intention. This study discusses the electronic word of mouth within the context of social media. Particularly, this study examines the influence of eWOM in social media on consumers` purchase intentions. The research consists of two phases. First, survey will be conducted to understand the effect of eWOM in social media on purchase intention. Then interviews will be made to reveal that how eWOM in social media affects consumers` purchase intentions. The results should contribute to both researchers and practitioners

Characteristics and classification of A-type supergiants in the Small Magellanic Cloud

We address the relationship between spectral type and physical properties for A-type supergiants in the SMC. We first construct a self-consistent classification scheme for A supergiants, employing the calcium K to H epsilon line ratio as a temperature-sequence discriminant. Following the precepts of the `MK process', the same morphological criteria are applied to Galactic and SMC spectra with the understanding there may not be a correspondence in physical properties between spectral counterparts in different environments. We then discuss the temperature scale, concluding that A supergiants in the SMC are systematically cooler than their Galactic counterparts at the same spectral type, by up to ~10%. Considering the relative line strengths of H gamma and the CH G-band we extend our study to F and early G-type supergiants, for which similar effects are found. We note the implications for analyses of extragalactic luminous supergiants, for the flux-weighted gravity-luminosity relationship and for population synthesis studies in unresolved stellar systems.Comment: 14 pages, 14 figures, accepted by MNRAS; minor section removed prior to final publicatio

Condensation for a fixed number of independent random variables

A family of m independent identically distributed random variables indexed by a chemical potential \phi\in[0,\gamma] represents piles of particles. As \phi increases to \gamma, the mean number of particles per site converges to a maximal density \rho_c<\infty. The distribution of particles conditioned on the total number of particles equal to n does not depend on \phi (canonical ensemble). For fixed m, as n goes to infinity the canonical ensemble measure behave as follows: removing the site with the maximal number of particles, the distribution of particles in the remaining sites converges to the grand canonical measure with density \rho_c; the remaining particles concentrate (condensate) on a single site.Comment: 6 page

Programming with simulated neurons: a first design pattern

An investigation has been carried out with regard to programming a form of deterministic logic based entirely in terms of biologically plausible neurons. To this end, a prototype has been successfully developed that incorporates a neuron version of the classic state design pattern. This neuron version is based on a novel programming technique, which models logical states as persistently active cell assemblies. These are populations of intra-connected neurons that have been triggered to continually fire until programmatically suppressed, thus enabling a neural form of state-transition logic. These neural-state cell assemblies have been developed using a specialist neuron simulation software library that is commonly employed by neuroscientists and is the adopted software protocol for the hardware platforms currently being developed for the Human Brain Project. An underlying inspiration of the work is to look forward to the possibility of a programming paradigm based entirely on biologically plausible neurons. It is envisaged that such a neural programming paradigm would benefit from established techniques, and that the neural cell assembly state pattern that has been developed and described in this report is a next step in that direction. In addition, a new graphical notation has been formulated in order to visualise the prototype. Whilst not a primary focus of the research to date, this visualisation notation may prove beneficial to the computational neuroscience community who work with similar neuron simulation software as that employed for the prototype presented here

PlaNeural: spiking neural networks that plan

PlaNeural is a spike-based neural network that has the ability to plan. The network is a spreading activation network implemented with Cell Assemblies; this combination has built a dynamic network of nodes that is able to interact with an environment and respond appropriately. PlaNeural uses Cell Assemblies to make decisions and plan - there is no pre-determined code managing the decision process that leads to planning. PlaNeural is the planning component of a virtual robot in a virtual environment. This paper describes PlaNeural's behaviour in two virtual environments, programmed independently of it; actions are completed in a closed-loop. PlaNeural was programmed in PyNN, executed with Nest and on a neuromorphic platform, SpiNNaker. PlaNeural has been tested on two environments and results show a successful performance; in both cases PlaNeural takes appropriate actions to fulfil user selected goals based on environmental changes

A comparison of simple agents implemented in simulated neurons

Neuromorphic embodied cell assembly agents that learn are one application being developed for the Human Brain Project (HBP). The HBP is building tools, available for all researchers, for building brain simulations. Existing simulated neural Cell Assembly agents are being translated to the platforms provided by the HBP; these agents run on neuromorphic chips in addition to von Neumann based computers. Whilst translation of the agents to the software technology demanded by the HBP platforms is relatively straightforward, porting to the neuromorphic chips is a non-trivial software engineering task. Versions of the simple agent, CABot1, have been developed in fatiguing leaky integrate and fire neurons, Izhikevich neurons and leaky integrate and fire neurons. These have been developed to run in Java, PyNN, NEST and Neuromorphic hardware. All variants are roughly equivalent. The agents view a picture, implement simple commands, and respond to a context sensitive directive involving the content of the picture. By running variants of these agents on different platforms, and with the different simulated neural models, implicit assumptions in these models can be revealed. Once these Cell Assembly agents have been translated and embodied in a virtual environment, they will be extended to learn more effectively. The use of neural hardware supports the real time simulation of many more neurons, providing a platform for exploration of more complex simulated neural systems

Adaptive high-order finite element solution of transient elastohydrodynamic lubrication problems

This article presents a new numerical method to solve transient line contact elastohydrodynamic lubrication (EHL) problems. A high-order discontinuous Galerkin (DG) finite element method is used for the spatial discretization, and the standard Crank-Nicolson method is employed to approximate the time derivative. An h-adaptivity method is used for grid adaptation with the time-stepping, and the penalty method is employed to handle the cavitation condition. The roughness model employed here is a simple indentation, which is located on the upper surface. Numerical results are presented comparing the DG method to standard finite difference (FD) techniques. It is shown that micro-EHL features are captured with far fewer degrees of freedom than when using low-order FD methods

Spacetime Supersymmetry in a nontrivial NS-NS Superstring Background

In this paper we consider superstring propagation in a nontrivial NS-NS background. We deform the world sheet stress tensor and supercurrent with an infinitesimal B_{\mu\nu} field. We construct the gauge-covariant super-Poincare generators in this background and show that the B_{\mu\nu} field spontaneously breaks spacetime supersymmetry. We find that the gauge-covariant spacetime momenta cease to commute with each other and with the spacetime supercharges. We construct a set of "magnetic" super-Poincare generators that are conserved for constant field strength H_{\mu\nu\lambda}, and show that these generators obey a "magnetic" extension of the ordinary supersymmetry algebra.Comment: 13 pages, Latex. Published versio

A two-state kinetic model for the unfolding of single molecules by mechanical force

We investigate the work dissipated during the irreversible unfolding of single molecules by mechanical force, using the simplest model necessary to represent experimental data. The model consists of two levels (folded and unfolded states) separated by an intermediate barrier. We compute the probability distribution for the dissipated work and give analytical expressions for the average and variance of the distribution. To first order, the amount of dissipated work is directly proportional to the rate of application of force (the loading rate), and to the relaxation time of the molecule. The model yields estimates for parameters that characterize the unfolding kinetics under force in agreement with those obtained in recent experimental results (Liphardt, J., et al. (2002) {\em Science}, {\bf 296} 1832-1835). We obtain a general equation for the minimum number of repeated experiments needed to obtain an equilibrium free energy, to within $k_BT$, from non-equilibrium experiments using the Jarzynski formula. The number of irreversible experiments grows exponentially with the ratio of the average dissipated work, \bar{\Wdis}, to $k_BT$.}Comment: PDF file, 5 page