Large magnetic circular dichroism in resonant inelastic x-ray scattering at the Mn L-edge of Mn-Zn ferrite

We report resonant inelastic x-ray scattering (RIXS) excited by circularly polarized x-rays on Mn-Zn ferrite at the Mn L2,3-resonances. We demonstrate that crystal field excitations, as expected for localized systems, dominate the RIXS spectra and thus their dichroic asymmetry cannot be interpreted in terms of spin-resolved partial density of states, which has been the standard approach for RIXS dichroism. We observe large dichroic RIXS at the L2-resonance which we attribute to the absence of metallic core hole screening in the insulating Mn-ferrite. On the other hand, reduced L3-RIXS dichroism is interpreted as an effect of longer scattering time that enables spin-lattice core hole relaxation via magnons and phonons occurring on a femtosecond time scale.Comment: 7 pages, 2 figures, http://link.aps.org/doi/10.1103/PhysRevB.74.17240

Medium dependence of asphaltene agglomeration inhibitor efficiency

Applying chemical additives (molecule inhibitors or dispersants) is one of the common ways to control asphaltene agglomeration and precipitation. However, it is not clear why at some conditions the synthetic flocculation inhibitors as well as resins not only do not inhibit the asphaltene agglomeration,, they may also promote it, and why the increasing of the additive concentration may lead to the diminishing of their efficacy. To clarify this issue, in the present work we have performed a set of vapor preassure osmometry experiments investigating the asphaltene agglomeration inhibition by commercial and new inhibitor molecules in toluene and o-diclorobenzene. Monte Carlo computer modeling has been applied to interpret some unexpected trends of molar mass of the Puerto Ceiba asphaltene clusters at different concentrations of inhibitor, assuming that inhibitors efficiency is directly related to their adsorption on the surface of asphaltene or its complexes. It has been found that a self-assembly of inhibitor molecules, induced by relative lyophilic or lyophobic interactions, may be a reason of the inhibitor efficacy declining.Comment: 21 page

Analysing the behaviour of robot teams through relational sequential pattern mining

This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of the team members to work together to achieve a common goal in a cooperative manner. The aim is to define a systematic method to verify the effective collaboration among the members of a team and comparing the different multi-agent behaviours. Using external observations of a Multi-Agent System to analyse, model, recognize agent behaviour could be very useful to direct team actions. In particular, this report focuses on the challenge of autonomous unsupervised sequential learning of the team's behaviour from observations. Our approach allows to learn a symbolic sequence (a relational representation) to translate raw multi-agent, multi-variate observations of a dynamic, complex environment, into a set of sequential behaviours that are characteristic of the team in question, represented by a set of sequences expressed in first-order logic atoms. We propose to use a relational learning algorithm to mine meaningful frequent patterns among the relational sequences to characterise team behaviours. We compared the performance of two teams in the RoboCup four-legged league environment, that have a very different approach to the game. One uses a Case Based Reasoning approach, the other uses a pure reactive behaviour.Comment: 25 page

Identification of network modules by optimization of ratio association

We introduce a novel method for identifying the modular structures of a network based on the maximization of an objective function: the ratio association. This cost function arises when the communities detection problem is described in the probabilistic autoencoder frame. An analogy with kernel k-means methods allows to develop an efficient optimization algorithm, based on the deterministic annealing scheme. The performance of the proposed method is shown on a real data set and on simulated networks

Self-doping processes between planes and chains in the metal-to-superconductor transition of YBa2Cu3O6.9

The interplay between the quasi 1-dimensional CuO-chains and the 2-dimensional CuO2 planes of YBa2Cu3O6+x (YBCO) has been in focus for a long time. Although the CuO-chains are known to be important as charge reservoirs that enable superconductivity for a range of oxygen doping levels in YBCO, the understanding of the dynamics of its temperature-driven metal-superconductor transition (MST) remains a challenge. We present a combined study using x-ray absorption spectroscopy and resonant inelastic x-ray scattering (RIXS) revealing how a reconstruction of the apical O(4)-derived interplanar orbitals during the MST of optimally doped YBCO leads to substantial hole-transfer from the chains into the planes, i.e. self-doping. Our ionic model calculations show that localized divalent charge-transfer configurations are expected to be abundant in the chains of YBCO. While these indeed appear in the RIXS spectra from YBCO in the normal, metallic, state, they are largely suppressed in the superconducting state and, instead, signatures of Cu trivalent charge-transfer configurations in the planes become enhanced. In the quest for understanding the fundamental mechanism for high-Tc-superconductivity (HTSC) in perovskite cuprate materials, the observation of such an interplanar self-doping process in YBCO opens a unique novel channel for studying the dynamics of HTSC.Comment: 9 pages, 4 Figure

Digital Technology and Marketing Management Capability: Achieving Growth in SMEs

Purpose The purpose of this study is to evaluate the relationships between digital technology, tangible/intangible assets and marketing capabilities to gain more insight into the factors related to small- and medium-sized enterprises’ (SMEs’) growth in the UK. Based on the resource-advantage theory, this research addresses the question “to what extent does digital technology influence marketing capability which leads to companies’ growth?” Design/methodology/approach Data were gathered through 21 in-depth interviews with managers from different multinational organizations and six focus groups with employees. Findings The study identifies the two key components of digital technology as information quality and service convenience. In addition, the relationships between digital technology, tangible/intangible assets and marketing capabilities perform the significant role of facilitator of a company’s growth. Research limitations/implications The focus on UK SMEs limits the generalizability of the results. Further studies should be conducted in other sectors and country settings to examine the associations identified in the current study. Originality/value This study identifies the main impacts of digital technology on intellectual/physical assets. While managers and employees have specified that marketing capability is significant for organizations, there are a few other areas of concern with regard to consequences related to a company’s growth, competence and core competence, particularly in an SME’s setting. Keyword

A Non-Sequential Representation of Sequential Data for Churn Prediction

We investigate the length of event sequence giving best predictions when using a continuous HMM approach to churn prediction from sequential data. Motivated by observations that predictions based on only the few most recent events seem to be the most accurate, a non-sequential dataset is constructed from customer event histories by averaging features of the last few events. A simple K-nearest neighbor algorithm on this dataset is found to give significantly improved performance. It is quite intuitive to think that most people will react only to events in the fairly recent past. Events related to telecommunications occurring months or years ago are unlikely to have a large impact on a customer’s future behaviour, and these results bear this out. Methods that deal with sequential data also tend to be much more complex than those dealing with simple nontemporal data, giving an added benefit to expressing the recent information in a non-sequential manner

Suppressing breakers with polar oil films : using an epic sea rescue to model wave energy budgets

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geophysical Research Letters 44 (2017): 1414–1421, doi:10.1002/2016GL071505.Oil has been used to still stormy seas for centuries, but the mechanisms are poorly understood. Here we examine the processes by using quantitative information from a remarkable 1883 sea rescue where oil was used to reduce large breakers during a storm. Modeling of the oil film's extent and waves under the film suggests that large breakers were suppressed by a reduction of wind energy input. Modification of surface roughness by the film is hypothesized to alter the wind profile above the sea and the energy flow. The results are central to understanding air-sea momentum exchange, including its role in such processes as cyclone growth and storm surge, although they address only one aspect of the complex problem of wind interaction with the ocean surface.TFD was partially supported by ONR MURI grant N00014- 11-1-0701