8,842 research outputs found
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
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