551 research outputs found
Irreversibility in response to forces acting on graphene sheets
The amount of rippling in graphene sheets is related to the interactions with
the substrate or with the suspending structure. Here, we report on an
irreversibility in the response to forces that act on suspended graphene
sheets. This may explain why one always observes a ripple structure on
suspended graphene. We show that a compression-relaxation mechanism produces
static ripples on graphene sheets and determine a peculiar temperature ,
such that for the free-energy of the rippled graphene is smaller than
that of roughened graphene. We also show that depends on the structural
parameters and increases with increasing sample size.Comment: 4 pages, 4 Figure
Uncertainty in the Fluctuations of the Price of Stocks
We report on a study of the Tehran Price Index (TEPIX) from 2001 to 2006 as
an emerging market that has been affected by several political crises during
the recent years, and analyze the non-Gaussian probability density function
(PDF) of the log returns of the stocks' prices. We show that while the average
of the index did not fall very much over the time period of the study, its
day-to-day fluctuations strongly increased due to the crises. Using an approach
based on multiplicative processes with a detrending procedure, we study the
scale-dependence of the non-Gaussian PDFs, and show that the temporal
dependence of their tails indicates a gradual and systematic increase in the
probability of the appearance of large increments in the returns on approaching
distinct critical time scales over which the TEPIX has exhibited maximum
uncertainty.Comment: 5 pages, 5 figures. Accepted to appear in IJMP
Precursors of extreme increments
We investigate precursors and predictability of extreme increments in a time
series. The events we are focusing on consist in large increments within
successive time steps. We are especially interested in understanding how the
quality of the predictions depends on the strategy to choose precursors, on the
size of the event and on the correlation strength. We study the prediction of
extreme increments analytically in an AR(1) process, and numerically in wind
speed recordings and long-range correlated ARMA data. We evaluate the success
of predictions via receiver operator characteristics (ROC-curves). Furthermore,
we observe an increase of the quality of predictions with increasing event size
and with decreasing correlation in all examples. Both effects can be understood
by using the likelihood ratio as a summary index for smooth ROC-curves
Strained graphene: tight-binding and density functional calculations
We determine the band structure of graphene under strain using density
functional calculations. The ab-initio band strucure is then used to extract
the best fit to the tight-binding hopping parameters used in a recent
microscopic model of strained graphene. It is found that the hopping parameters
may increase or decrease upon increasing strain, depending on the orientation
of the applied stress. The fitted values are compared with an available
parametrization for the dependence of the orbital overlap on the distance
separating the two carbon atoms. It is also found that strain does not induce a
gap in graphene, at least for deformations up to 10%
Localization of elastic waves in heterogeneous media with off-diagonal disorder and long-range correlations
Using the Martin-Siggia-Rose method, we study propagation of acoustic waves
in strongly heterogeneous media which are characterized by a broad distribution
of the elastic constants. Gaussian-white distributed elastic constants, as well
as those with long-range correlations with non-decaying power-law correlation
functions, are considered. The study is motivated in part by a recent discovery
that the elastic moduli of rock at large length scales may be characterized by
long-range power-law correlation functions. Depending on the disorder, the
renormalization group (RG) flows exhibit a transition to localized regime in
{\it any} dimension. We have numerically checked the RG results using the
transfer-matrix method and direct numerical simulations for one- and
two-dimensional systems, respectively.Comment: 5 pages, 4 figures, to appear in Phys. Rev. Let
Forecasting for Social Good
Forecasting plays a critical role in the development of organisational
business strategies. Despite a considerable body of research in the area of
forecasting, the focus has largely been on the financial and economic outcomes
of the forecasting process as opposed to societal benefits. Our motivation in
this study is to promote the latter, with a view to using the forecasting
process to advance social and environmental objectives such as equality, social
justice and sustainability. We refer to such forecasting practices as
Forecasting for Social Good (FSG) where the benefits to society and the
environment take precedence over economic and financial outcomes. We
conceptualise FSG and discuss its scope and boundaries in the context of the
"Doughnut theory". We present some key attributes that qualify a forecasting
process as FSG: it is concerned with a real problem, it is focused on advancing
social and environmental goals and prioritises these over conventional measures
of economic success, and it has a broad societal impact. We also position FSG
in the wider literature on forecasting and social good practices. We propose an
FSG maturity framework as the means to engage academics and practitioners with
research in this area. Finally, we highlight that FSG: (i) cannot be distilled
to a prescriptive set of guidelines, (ii) is scalable, and (iii) has the
potential to make significant contributions to advancing social objectives.Comment: 28 pages, 6 figure
Adsorption of alkanes, alkenes and their mixtures in single-walled carbon nanotubes and bundles
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