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Economy & Politics›
Monthly consumer price index (CPIH) in the United Kingdom 2017-2021
Published by D. Clark, Sep 29, 2021
In July 2021, the CPIH index in the United Kingdom reached 111.4, indicating a large increase in prices since November 2017. Between November 2017 and September 2020, the CPIH has been steadily increasing, peaking in the most recent period recorded.
Monthly consumer price index (CPIH) in the United Kingdom (UK) from November 2017 to July 2021
CPIH Index (2015=100)
November 2017 to July 2021
CPIH is an additional measure of the Consumer Price index which includes owner occupiers' housing costs (OOH).
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CPIH inflation rate in the UK 1989-2022
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Core inflation rate of the UK 1989-2022
Consumer Price Index in the UK 1988-2022
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CPIH in the UK 1988-2022
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PPI in the UK 2010-2022
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CPI inflation rate for food and non-alcoholic beverages in the UK 1989-2022
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British adults reporting a cost of living increase 2021-2023
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Meat consumer price index (CPI) monthly in the United Kingdom (UK) 2016-2022
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Office for National Statistics (UK). (August 18, 2021). Monthly consumer price index (CPIH) in the United Kingdom (UK) from November 2017 to July 2021 [Graph]. In Statista. Retrieved February 01, 2023, from https://www.statista.com/statistics/284786/united-kingdom-uk-monthly-consumer-price-index-cpih/
Office for National Statistics (UK). "Monthly consumer price index (CPIH) in the United Kingdom (UK) from November 2017 to July 2021." Chart. August 18, 2021. Statista. Accessed February 01, 2023. https://www.statista.com/statistics/284786/united-kingdom-uk-monthly-consumer-price-index-cpih/
Office for National Statistics (UK). (2021). Monthly consumer price index (CPIH) in the United Kingdom (UK) from November 2017 to July 2021. Statista. Statista Inc.. Accessed: February 01, 2023. https://www.statista.com/statistics/284786/united-kingdom-uk-monthly-consumer-price-index-cpih/
Office for National Statistics (UK). "Monthly Consumer Price Index (Cpih) in The United Kingdom (Uk) from November 2017 to July 2021." Statista, Statista Inc., 18 Aug 2021, https://www.statista.com/statistics/284786/united-kingdom-uk-monthly-consumer-price-index-cpih/
Office for National Statistics (UK), Monthly consumer price index (CPIH) in the United Kingdom (UK) from November 2017 to July 2021 Statista, https://www.statista.com/statistics/284786/united-kingdom-uk-monthly-consumer-price-index-cpih/ (last visited February 01, 2023)
Monthly consumer price index (CPIH) in the United Kingdom (UK) from November 2017 to July 2021 [Graph], Office for National Statistics (UK), August 18, 2021. [Online]. Available: https://www.statista.com/statistics/284786/united-kingdom-uk-monthly-consumer-price-index-cpih/


text:
\section{Introduction}
\label{intro}

Inhomogeneous systems present a number of features that make them
intrinsically more complicated than bulk systems. The fact that the
equilibrium state of the system depends on the position causes a
number of physical quantities to be likewise dependent on the position
(such as the molecular number density), or even ill-defined (such as
the pressure tensor).  This also applies to dynamical properties ---
the most important one of these, (self-)diffusion, is complicated by
the fact that tracer molecules cannot be followed at will for any
given length of time, since they will enter and abandon zones that
have different dynamical properties.

It is therefore not possible in general to obtain
a value for the diffusion coefficient $D$ by the
well known Einstein relation for the
mean standard deviation (MSD) of the displacements
\begin{equation}
\label{eq:einstein1905}
\left<r^2\right> \xrightarrow[t\rightarrow\infty]{} 6 D t.
\end{equation}
The direct application of such a formalism to an inhomogeneous
fluid would result in an average result containing contributions
from the bulk phases and the interfaces. Indeed, $D$ can be
expected to have different values at different parts of the
system. (The same problem would arise of course
in the other main approach to $D$: by means of the Green-Kubo
formula involving the velocity autocorrelation function.)

This is true in particular for the best-known
inhomogeneous fluid system: the liquid-vapor interface.  In this
case, a liquid phase and its vapor are separated by an interfacial
region which, on average, is flat. The spacial dependence is therefore
limited in this case to one Cartesian coordinate, which we will take
as $z$.  For example, the mean density profile, $\rho(z)$, is obtained
from simulation by defining slab in the $z$ direction (``binning''),
and collecting occupation statistics for each of the slabs. This way,
a profile is obtained that shows two plateaus at constant values
corresponding to the liquid and vapor densities, and a typically
monotonic interfacial variation between them. Theoretical approaches,
from the pioneering van der Waals theory to the most recent density
functional approximations, may be used to directly obtain $\rho(z)$,
which depends only on the temperature, $T$, and on the molecular
interactions.  The density profiles may be much more structured in
other, apparently more complex, systems like a dense fluid against a
planar wall potential, but the apparent simplicity of the liquid-vapor
interface hides a much deeper difficulty.\cite{CWT,Evans} The
fluctuations of a free liquid surface have \emph{capillary wave} (CW)
modes with very low frequencies, and hence low excitation energies for
long wavelengths.  In the absence of any external potential, the
thermodynamic limit of a macroscopic free liquid surface becomes
undetermined, and the interface would be fully delocalized by the long
wavelength CWs. The Earth gravity field, which would be fully
irrelevant for the thermodynamic properties of one-phase systems up to
the scale of meters, becomes crucial to stabilize the liquid surface,
damping the CW fluctuations for wavelengths larger than millimeters,
and amplitudes larger than about one molecular diameter.  Still, the
mean density profile under Earth gravity conditions would be smoother
than the one observed with typical computer simulations, which employ
transverse box sizes in the range of $10-30$ molecular diameters (the
interfacial width can be estimated to be about twice as large in the
first case\cite{MolThCap}).  Within that limited range for the
transverse size the inclusion of the Earth gravity would be
irrelevant, but it is already possible to observe the dependence of
$\rho(z)$ with the transverse size of the simulation box.%
\cite{toxvaerd_1995,Sides_1999}

The CW fluctuations are a severe nuisance for the study of the
molecular diffusion at the liquid surface, since the molecular
kinetics, relevant for any physicochemical process at the surface, is
mixed with large collective fluctuations for the instantaneous
position of the surface, which give a smooth and size dependent
$\rho(z)$. The simplest estimations of surface diffusion properties
consider the molecules within thin slabs placed in the region with
inhomogeneous values of $\rho(z)$,\cite{townsend_1991,senapati_2002}
in some cases separating diffusion in parallel and perpendicular
components: Refs.~%
\onlinecite{meyer_1988,benjamin_1992,michael_1998,buhn_2004} that deal with
liquid-liquid interfaces, Refs.~%
\onlinecite{liu,chanda_2005,chanda_2005_2,chanda_2006,%
paul_2005,paul_2005_2,paul_2005_3,liu_2005,liu_2005,%
gonzalez_2006,clavero_2007} on liquid-vapor interfaces, and
Refs.~%
\onlinecite{lee_1994,lee_1994,martins_2004,bhide_2005,sega_2005,pal_2005,%
marti_2006,hijkoop_2007,thomas_2007}
on liquids (typically, water) adsorbed on, or confined in, different
substrates.
Another approach is to consider some operational definition of the
outmost liquid molecules and track their dynamics for a limited time.%
\cite{Taylor_1996,taylor_2003} Such procedures can only
yield a coarse distinction between bulk and surface properties, given
the obvious arbitrariness in the choice of parameters such as the
surface slab width, the definition of outmost molecules, the
complications associated with the diffusing molecules leaving and
entering the different domains, and the blurring effect of the
area-dependent CW fluctuations.

Classical \emph{capillary wave theory} (CWT)\cite{CWT} gives a
framework to interprete the effects of the CW fluctuations, and
provides an accurate extrapolation of the $\rho(z)$ profile obtained
in typical computer simulations to larger sampling sizes, including
the effects of weak gravity fields.  However, only over the last
decade has CWT become a practical tool to extract the \emph{intrinsic}
molecular properties of a liquid surface, from the broad distributions
produced by the CW fluctuations. The theory assumes that an
\emph{intrinsic surface} (IS) may be defined, to describe the
instantaneous boundary between the two coexisting phases, so that the
molecular distribution referred to that surface would give an
intrinsic density profile sharper that $\rho(z)$ and, more
importantly, independent of the transverse sampling size.  Over the
last decade, the increasing resolution in X-ray reflectivity data
allowed the deconvolution of the Gaussian CW distribution out of the
surface structure factor, and hence to obtain experimental results for
the intrinsic profile in cold liquid metal surfaces, with a clear
atomic layering structure.\cite{Persham}  Similar results were
obtained in computer simulations of simple fluid models,%
\cite{ourlayering,ourlayering2} whenever the frustration of the
freezing allowed to explore low temperatures, $T/T_\mathrm{c} < 0.2$,
relative to the critical one. As in experiments, the deconvolution is
possible because even $\rho(z)$ presents some layering at these low
temperatures.
These results indicate that the typical smooth shape of $\rho(z)$ in a
LV interface results from the convolution of the Gaussian CW
fluctuations with a strongly layered intrinsic profile, such that it
should be possible to identify, with reasonable confidence, the
\emph{outmost molecular layer} of the liquid phase.  More recently,
that concept led to the development of \emph{intrinsic sampling
method} in computer simulations,%
\cite{Chacon_Tarazona_PhysRevLett,Chacon_Tarazona_PhysRevB,IS} based
on the operational definition of the CWT intrinsic surface as a
geometrical locus for that first molecular layer, so that the
intrinsic profile, and other molecular intrinsic properties of the
liquid surface,\cite{ISM_aplications,ISM_aplications2} may be
extracted with accuracy and high resolution, without the CW blurring
observed in $\rho(z)$.  The intrinsic profile calculated with such
methods represent a direct, quantitative link between the generic
framework of the CWT and the computer simulations of liquid
surfaces. The result is a deeper structural understanding of the
surface: the capillary wave fluctuations, which cause an
area-dependent broadening of the mean profile $\rho(z)$, are absent in
the intrinsic one. These two profiles are, in general, remarkably
different: between the plateaus corresponding to the liquid and vapor
densities the intrinsic one is far from monotonic, showing a marked
layering. In fact, it much more resembles the pair correlation
function or the density profiles close to a hard wall.

The aim of our work here is to explore the application of the
intrinsic sampling method to the analysis of the molecular diffusion
at liquid surfaces. We may track down and analyze the movements of the
\emph{surface molecules}, i.e. those that define the IS. Thus we may
obtain, with great accuracy, dynamical information on molecules that
are ``at'' the interface, without the arbitrarity in the choice of a
surface slab, and making it possible to separate the molecular
diffusion on the surface from the fluctuations on the local position
of the surface.  The reader is referred to the previous references for
a complete description of the method, its variations, and their
results. The only relevant aspect here is that for each instantaneous
configuration of the system, this method selects a set of
\emph{surface molecules}, i.e. those identified as belonging to the
\emph{\it outmost liquid layer}, and called the IS \emph{pivots} in
the above references.  Within the intrinsic disorder of a liquid
surface we cannot expect that such molecular layer would have a sharp
definition --- it should indeed be regarded as a soft but robust
concept: changes in the set of parameters used for the operational IS
definition would produce small changes in the set of molecules which
are identifyed as belonging to the surface, but (at least for
$T/T_\mathrm{c}<0.8$) there is a clear optimal choice within rather
narrow windows for all parameters that must be fine tuned, as
commented at the end of the next section. In particular, the
two-dimensional density of the first liquid layer, i.e. the number of
surface molecules per unit area, is fairly well defined and provides
useful information on the molecular structure of a liquid surface,
which is blurred in the usual description in terms of $\rho(z)$.
\cite{our_new}

We begin with a section on methodology, Section \ref{methodology}, on
both the simulation details and the way the IS is calculated.  We then
consider diffusion in Section \ref{diffusion}, divided in three
subsections that go from the best known case, bulk diffusion, through
diffusion parallel to the interface, to the more involved case of
diffusion perpendicular to it.  We further analyze our results in
Section \ref{discussion}, where we consider
systems at other temperatures and other transverse
areas. We conclude with some remarks in \ref{conclusions}.

\section{methodology}
\label{methodology}

We consider the standard Lennard-Jones fluid,
in which molecules interact through a pairwise
potential of the form
\begin{equation}
\label{eq:LJ}
u(r)=
\epsilon
\left\{
  \left(
  \frac{\sigma}{r}
  \right)^{12}
-
  \left(
     \frac{\sigma}{r}
  \right)^6
-
  \left(
     \frac{\sigma}{r_\mathrm{c}}
  \right)^{12}
+
  \left(
     \frac{\sigma}{r_\mathrm{c}}
  \right)^6
\right\},
\end{equation}
 with interactions truncated at a cutoff radius of
$r_\mathrm{c}=3.02\sigma$.

In order to obtain dynamical information, molecular
dynamics (MD) simulations are performed,
using the software package \textsc{dl\_poly}.\cite{dlpoly}
The systems consists of a thick slab of liquid surrounded
by vapor. We therefore obtain two LV interfaces.
Since the two are independent (if the liquid is thick enough),
the properties measured in both should be averaged in order
to improve the accuracy, but for the sake of clarity we will
just present results obtained in one of the LV interfaces.

Our systems consist of $2592$ molecules, generally
(unless otherwise indicated)
at a temperature of
$k_\mathrm{B}T=0.678\epsilon$, which is our
estimate for the triple point temperature of the LJ fluid
(at this cutoff, see Ref.~\onlinecite{Matsy_de_Pablo} for
a discussion of the effect of truncation on this temperature).
The simulation cell is a square box of dimensions
$L \times L \times L_z$,
with (unless otherwise indicated)
$L=10.46\sigma$ and $L_z=90 \sigma$.
Periodic boundary
conditions are employed in all three directions.
The time step is set at a reduced value
of $dt=4.56\times 10^{-3} \sigma \sqrt{m/\epsilon}$.
The systems starts from either a crystalline configuration or a system
at other temperature and are equilibrated for $10^6$ time steps in the
$NVT$ ensemble (with a Nose-Hoover thermostat with a
time constant $10 dt$).

After this period, configurations are obtained
in the $NVE$ ensemble, in order to eliminate any
possible spurious effects of the thermostat on the
dynamics (in any case, we have checked these effects are
typically negligible). For the results
presented here, $50000$ configurations are
analyzed. We have found that only one configuration
out of ten needs to be analyzed, since the dynamics
is still slow for a time step of $10 dt$.
The analysis of the MSD is carried out in the standard
way; more sophisticated treatments aimed at reducing computer
storage\cite{understanding} are not needed in this case.

For each of these configurations, an IS analysis is carried out, as
described in Ref.~\onlinecite{IS}, requiring two operational parameters.
One of them, $n_\mathrm{s}$, has a very clear physical significance:
the two-dimensional density of the IS, i.e. the number of
\emph{surface molecules} to be selected per unit area.  Here we set
$n_\mathrm{s} \approx 0.8 \sigma^{-2}$, with a twofold motivation; on
one hand, this value had already been identified as the most physical
one from close inspection of the intrinsic profile for the LJ
fluid.\cite{IS}  On the other, the same set of simulations described
here can be used to independently obtain a value for this parameter,
confirming this value as the best one from a kinetic analysis (see
Ref.~\onlinecite{our_new} for details on this procedure).  The other
parameter, $q_\mathrm{u}$, fixes the maximum wave number to be used in
the Fourier representation of the IS. This mathematical surface
associated to each molecular configuration within the intrinsic
sampling method will not appear explicitly this article, but still it
is essential for the self-consistent procedure used to select the IS
molecules.  We have combined here a basis of $12$ planar waves for
each $x$ and $y$ direction, which with the transverse box size $L =
10.46 \sigma$ means a value of $q_\mathrm{u}=1.15 \times 2\pi/\sigma$,
within the optimal range of choices as explained in the above
references.

\begin{figure}
\includegraphics[width=8cm]{diff2}
\caption{\label{fig:diff2}
Mean fraction of molecules
which remain at the intrinsic surface for, at least, a time $t$,
$N_\mathrm{s}(t)/N_\mathrm{s}(0)$,
\textit{versus} reduced time $t$,
(units of $\sigma \sqrt{m/\epsilon}$).
Dotted line: linear regression of the
exponential decay at later times, shown to
intercept $t=0$ at about $0.8$.}
\end{figure}

In each analyzed configuration we select a number of surface
molecules, $N_\mathrm{s}=n_\mathrm{s} L^2$ (typically $88$ is our
optimal choice here) which self-consistently define the IS.  The
averages of the surface self-diffusion properties require us to follow
the individual history of each of these molecules, i.e. to identify
their permanence, exit, and possible reentrance in the IS list. All
the reported surface diffusion properties are associated to the
movement of molecules that stay continuously in the list of IS
molecules, and this requirement sets a clear limitation on the
avaliable sampling times. In Figure~\ref{fig:diff2}, $N_\mathrm{s}(t)$
represents the mean number of molecules which remain at the IS for, at
least, a time $t$; the exponential decay $N_\mathrm{s}(t) \sim
\exp(-t/\tau)$, with a typical decay time, or \emph{residence time} of
$\tau \approx 4.3 \sigma \sqrt{m/\epsilon}$ (at
$k_\mathrm{B}T=0.678\epsilon$), which we also list in
Table~\ref{table:diff1}.  This treatment mirrors the classical
definition of the bulk \textit{residence time} as the exponential
decay time for the process by which neighboring molecules drift apart.%
\cite{Impey_1983} It is also useful to keep in mind that for the case
of Argon with the usual LJ parameters $\epsilon/k_\mathrm{B}=119.8 K$
and $\sigma \approx 0.3405$nm one unit of reduced time corresponds to
$2.15$ picoseconds.  Thus, the decay time would be approximately
$9.2$ps for Argon.

This short value for the residence time implies that the sampling size
would rapidly decrease (and the statistical noise increase) for large
$t/\tau$.  The extrapolation to $t=0$ of this exponential decay at
longer times indicates that about $80\%$ of the molecules at the IS
will leave it at the constant rate of $1/\tau$, associated to the long
time exponential decay, while the remaining $20\%$ of the molecules
get out of the IS much faster, sometimes to undergo a rapid
reentrance. These molecules may be regarded as those which are only
marginally associated to the outmost liquid layer, e.g. those which
may be interpreted either as a local intrusion of the IS towards the
bulk liquid, or alternatively as a local extrusion of the next-outmost
layer towards the surface. The disordered structure of the liquid
makes the existence of such ambiguities unavoidable, and different
recipes to identify the IS from the molecular positions could make
different assignments to those molecules to be in, or out of, the list
of surface molecules. That is what makes the concept of the outmost
liquid layer a soft one, but at the same time a rather robust one,
since any reasonable choice of the tunable parameters would agree in
the selection of the large majority of the surface molecules. For the
diffusion properties analyzed here there is a further advantage, since
the relevant information to get the effective surface diffusion
coefficients comes from the sampling of molecular displacements at
the longest possible times, which automatically selects the properties
of those molecules with long permanence at the surface, representing
the outmost liquid layer with any sensible choice for the parameters
in the IS definition. The only practical inconvenience of the rapid
turnover of some surface molecules is that the time interval between
analyzed configurations, $\Delta t$, has to be short enough to make
sure that the estimation of $N_\mathrm{s}(t)$ is not affected by
further reduction --- in practice that is achieved, at
$k_\mathrm{B}T=0.678\epsilon$, with $\Delta t=10dt$, when only about
two and a half surface molecules are changed on average between
consecutive configurations.\cite{our_new}

\begin{figure}
\includegraphics[width=8cm]{rhos}
\caption{\label{fig:rhos}
Mean density profile,
$\rho(z)$ (solid line),
density profile of surface molecules,
$\rho_\mathrm{s}(z)$ (dotted line), and
density profile of old surface molecules,
$n_0 P_\mathrm{o}(z)$
(dashed line). The profiles are given in
reduced units of $\sigma^{-3}$.}
\end{figure}

The mean profile of the whole system, $\rho(z)$, and that restricted
to the surface molecules, $\rho_\mathrm{s}(z)$, are presented in
Figure~\ref{fig:rhos}, the later having a typical Gaussian shape which
represents the fluctuations of the IS, and which becomes wider with
increasing temperature and transverse sizes of the simulation
box. Notice that despite the mean profile character of
$\rho_\mathrm{s}(z)$, all the selected surface molecules lie exactly
on the instantaneous IS, we may therefore use them to follow exactly
the self-diffusion of the molecules at the outmost liquid layer,
without the coarsening effect of the CW fluctuations if we were
selecting the molecules within a fixed surface slab. Moreover, we may
keep track of the mean profiles for surface molecules which have
continuous permanence in the IS list for more than a time $t$, thus
defining a distribution $\rho_\mathrm{s}(z,t)$, whose integral over
$z$ is directly linked to the number of surface molecules older
than~$t$,
\begin{equation}
N_\mathrm{s}(t)= L^2 \int dz \rho_\mathrm{s}(z,t).
\end{equation}
We may expect that any diffusion property sampled for relatively large times would correspond to
molecules distributed as
\begin{equation}
\label{eq:factorizes}
\rho_\mathrm{s}(z,t)=n_0 P_\mathrm{o}(z) \exp(-t/\tau),
\end{equation}
where the time dependences factorizes into the same exponential decay
as $N_\mathrm{s}(t)$, and we define a $z$-distribution of \emph{old}
surface molecules, $P_\mathrm{o}(z)$, which is normalized to unity. The
prefactor has been discussed above to be $n_0\approx 0.8
n_\mathrm{s}$, i.e. representing about $80\%$ of the surface
molecules.  This is indeed the case, and in Figure~\ref{fig:rhos} we
compare the mean profile of the whole set of surface molecules,
$\rho_\mathrm{s}(z) \equiv \rho_\mathrm{s}(z,0)$, and the distribution
of old surface molecules normalized to $n_0$, i.e., $n_0 \
P_\mathrm{o}(z)$. The distribution of old surface molecules is
narrower, and asymmetric with respect to the whole one, and that may
be interpreted in terms of the rate at with molecules are incorporated
to, or deleted from, the list of surface molecules, as a function of
their position $z$.

Since we select a fixed number of surface molecules in each
configuration, the loss of molecules from the IS layer, either towards
the liquid or the vapor sides, is always compensated by the
incorporation of new ones, and the time reversal symmetry of the MD
guarantees that the inflow and outflow of surface molecules at a given
value of $z$ are identical. We denote by $\nu_\mathrm{io}(z)$ that
input/output rate per molecule, which may be directly sampled along
our simulations and are presented in Figure~\ref{fig:distros},
together with $P_\mathrm{o}(z)$, for ease of comparison. The results
are fairly well compatible with rates being independent of the
previous permanence time of the molecule at the IS, so that
\begin{equation}
\frac{d}{dt}N_\mathrm{s}(t)= - L^2 \int dz \rho_\mathrm{s}(z,t) \nu_\mathrm{io}(z),
\end{equation}
which for large $t$ implies
\begin{equation}
\label{eq:piv_t}
\frac{1}{\tau}=-\frac{1}{N_\mathrm{s}(t)}\frac{d N_\mathrm{s}(t)}{dt}= \int dz P_\mathrm{o}(z) \nu_\mathrm{io}(z).
\end{equation}

\begin{figure}
\includegraphics[width=8cm]{P_i}
\caption{\label{fig:distros}
Distribution of the input/output rate
per molecule, $\nu_\mathrm{io}(z)$, normalized to the
proper value set by Equation~\ref{eq:piv_t}
(hence, reduced in units of inverse time, $\sqrt{\epsilon/m}/\sigma$).
(solid line), together with $P_\mathrm{o}(z)$
in reduced units of $\sigma^{-1}$, normalized to unity (dashed line).}
\end{figure}

The shape of $\nu_\mathrm{io}(z)$ is clearly composed of two
contributions: a large peak corresponding to the exit/entrance of
surface molecules to/from the bulk liquid, an a much smaller one
corresponding to the exit/entrance of surface molecules to/from the
bulk vapor.  In the following section we show how to extract the
surface diffusion coefficients from the information from the observed
displacements of the surface molecules, and the information on their
turnover distributions contained in $P_\mathrm{o}(z)$ and
$\nu_\mathrm{io}(z)$.

\section{Diffusion in the bulk, and at the intrinsic surface}
\label{diffusion}

We discuss diffusion for the particular choice of
temperature  $k_\mathrm{B}T=0.678\epsilon$, in three
different cases: bulk diffusion, diffusion parallel
to the interface, and diffusion perpendicular to it.

\begin{figure}
\includegraphics[width=8cm]{diff1}
\caption{\label{fig:diff1}
Square root of the mean standard deviation of displacements for
different subset of molecules \textit{versus} time, in reduced units:
$\sigma$ for the square root of MSDs and $\sigma \sqrt{m/\epsilon}$
for time.  Solid lines: $x$, $y$, and $z$ components in the bulk
liquid (hardly distinguishable), long-dashed lines: $x$ and $y$
components for the intrinsic surface (hardly distinguishable),
short-dashed line: $z$ component for the intrinsic surface. Dotted
lines: prediction from the Maxwellian velocity distribution,
Eq.~(\ref{eq:Maxwell}), and fits to Einsteinian diffusion equations,
Eq.~(\ref{eq:einstein_xyz}), with two values of the self diffusion
coefficient, one corresponding to the bulk liquid, the other
to the intrinsic surface.}
\end{figure}

\subsection{Diffusion in the bulk}
\label{bulk}

In Figure~\ref{fig:diff1} we plot the square root of the MSD for the
$x$, $y$, and $z$ components of the displacement
versus time for the bulk liquid phase.
At short times all curves tend to the same line,
with a slope of $2$. This is the ballistic regime: times
so short that collisions can be neglected.
In this case the Maxwellian distribution for velocities
directly provides a value for the MSD
\begin{equation}
\label{eq:Maxwell}
\left< x^2 \right> = \frac{k_\mathrm{B}T}{m} t^2 ,
\end{equation}
which is the dotted line in the graph.

At longer times a diffusive regime is reached,
with the Einstein relation for each of the
three Cartesian coordinates because of isotropy:
\begin{equation}
\label{eq:einstein_xyz}
\left<x^2\right> \rightarrow 2 D t; \qquad
\left<y^2\right> \rightarrow 2 D t; \qquad
\left<z^2\right> \rightarrow 2 D t.
\end{equation}

We indeed find no difference between the three components of the bulk.
From linear interpolation of this line in the $\log$-$\log$ graph one
reads $D_\mathrm{b}=0.034\sigma\sqrt{\epsilon/m}$, in good agreement
with previous data,\cite{meier,liu} see Table~\ref{table:diff1}.

The time for the crossover between the ballistic and the diffusive
regimes can be estimated from the crossing of the two linear
regression lines. In this case this is $t_\mathrm{c} \approx 0.099
\sigma \sqrt{m/\epsilon}$.
The corresponding mean displacement in each
direction would be $\Delta x_\mathrm{c}\approx 0.081\sigma$ if
read from the intercept of the lines, or $\approx 0.074\sigma$
from the MSD curves at $t_\mathrm{c}$. We
also list these numbers in Table~\ref{table:diff2}, where
we will also include results for other temperatures that
will be discussed in the next Section.
Since the density is $\rho_\mathrm{liq} =0.83 \sigma^{-3}$,
assuming a local coordination close to the FCC packing,
the typical intermolecular distance would be
$d=(\sqrt{2}/\rho)^{1/3} \approx 1.2\sigma$, and
collisions would take place with typical displacements
around $\Delta x \approx d-\sigma_0$, where $\sigma_0$ is
the minimum of the LJ potential, $2^{1/6}\sigma$.
This prediction yields $\Delta x \approx 0.072\sigma$,
consistent with the values found.

\newcolumntype{C}{>{$}c<{$}}

\begin{table}
\begin{tabular}{|c|c||C|C||C|C|C|C|C|}
\hline
 model& source & T^* &  \rho_\mathrm{liq}^*  & \tau^* & D_\mathrm{b}^* &  D_\|^*  &  D_\perp^* \\
\hline
 SA   & this work         & 0.212    & 1.17 & 13.2      & 0.020  & 0.038       & 0.04  \\
\hline
      & this work         &0.678   & 0.83 & 4.3         & 0.034  & 0.13         & 0.10  \\
 LJ   & Liu et al.\cite{liu} %
                          & 0.75^+ & 0.83 & \mathrm{-}  & 0.037  & 0.15         & 0.075 \\
      & Meier et al.\cite{meier} &0.678^* & 0.83 & \mathrm{-}  & 0.033  & \mathrm{-}   &  \mathrm{-} \\
\hline
 LJ   & this work         &0.848    & 0.74 & 2.27       & 0.082  & 0.20        & 0.16  \\
      & Meier et al.\cite{meier} &0.848^*  & 0.74 & \mathrm{-} & 0.078  & \mathrm{-}  & \mathrm{-}\\
\hline
\end{tabular}
\caption{\label{table:diff1}
Table of results, in reduced units.  Listed: type of model (SA: soft
alkali model of Ref.~\onlinecite{ourlayering}), source of the data quoted
((bulk values have been interpolated from data of Meier et al,
Ref.~\onlinecite{meier}), reduced temperature $T^* = k_\mathrm{B} T /
\epsilon $, reduced density of the liquid phase $\rho_\mathrm{liq}^*=
\rho_\mathrm{liq} \sigma^3 $, reduced residence time $\tau^*=\tau
\sqrt{\epsilon/m}/\sigma$, and reduced diffusion coefficients $D^*=D
\sqrt{m/\epsilon}/\sigma $: for the bulk ($ D_\mathrm{b}^*$), parallel
to the liquid-vapor interface ($D_\|^*$), and perpendicular to it
($D_\perp^*$).}
\end{table}

\subsection{Diffusion parallel to the interface}
\label{parallel}

Turning to the molecules at the interface, i.e. those selected as
\emph{surface molecules} by the intrinsic sampling method, their MDS,
along the three Cartesian coordinates also plotted in
Figure~\ref{fig:diff1}.  The ballistic regime at short times is the
same for all three components, and the same as for the bulk; but at
longer times the curves are very different from the bulk, the $x$ and
$y$, parallel, components remaining indistinguishable, the $z$
component differing. We focus on the parallel diffusion in this
section, for which we could expect the first two relations of
Eq. (\ref{eq:einstein_xyz}) to hold, but with a different value of the
diffusion coefficient:
\begin{equation}
\label{eq:einstein_xy}
\left<x^2\right> \rightarrow 2 D_\| t; \qquad
\left<y^2\right> \rightarrow 2 D_\| t.
\end{equation}
At long times, the MSD for the parallel components of our surface
molecules show this expected linear growth with $t$ limit, and we find
$D_{\|} = 0.13 \sigma\sqrt{\epsilon/m}$, Therefore, the parallel
diffusion coefficient is almost four times larger than the bulk one.
This remarkable difference, with similar factors, had already been
reported in works on water,\cite{townsend_1991,Taylor_1996,liu}
ethanol,\cite{taylor_2003} dimethyl sulfoxide,\cite{senapati_2002}
and liquid-liquid interfaces in LJ mixtures\cite{meyer_1988,buhn_2004}
(although not all of these works discriminate different components of
the diffusion coefficient) --- we should remark that, on the other
hand, very little change has been obtained for liquid-liquid
interfaces in mixtures of water and other polar liquids.%
\cite{benjamin_1992,michael_1998} Two works consider the liquid-vapor
interface of the LJ fluid: a value of $D_\| =0.13
\sigma\sqrt{\epsilon/m} $, at a similar temperature of
$k_\mathrm{B}T=0.75\epsilon$, is reported in Ref.~\onlinecite{liu} (also
included in Table~\ref{table:diff1} ), in good agreement with our
result. On the other hand, Ref.~\onlinecite{gonzalez_2006} find only a
twofold increase over the bulk diffusion coefficient, even if their
choice of temperature is again very close,
$k_\mathrm{B}T=0.75\epsilon$.

The time for the crossover between the ballistic and the diffusive
regimes is $t_\mathrm{c} \approx 0.38 \sigma\sqrt{m/\epsilon}$. The
corresponding mean displacement in each is either $\Delta
x_\mathrm{c}\approx 0.32\sigma$ (from the intercept of the lines), or
$\approx 0.23\sigma$ (from the MSD curves).  This means that the same
approximate increase with respect to the bulk by a factor of about three
applies to the characteristic time between collisions,
the characteristic length between collisions,
and the diffusion coefficient (this is of course consistent with
$\left<x^2\right> \propto D t$).

As shown in Figure~\ref{fig:diff1}, the crossover from the ballistic
to the diffusive behavior is quite different for the bulk and the
surface molecules. The MSD in the bulk converges to the diffusive
regime from above, i.e. after leaving the rapid ballistic regime,
there is a time interval in which the relative growth of the MSD is
slower than in the asymptotic diffusive regime. On the contrary, the
parallel diffusion of the surface molecules shows a much smoother
interpolation between the two limiting regimes, which may be
interpreted as a signature of the stronger disorder in the correlation
structure at the surface, causing a wider time distribution for
molecular rearrangement leading to the diffusive regime.  The MSD is
always below the asymptotic diffusion, and with very little difference
between the normal ($z$), and transverse ($x,y$) directions up to $t
\sim 0.4 \sigma\sqrt{m/\epsilon}$, and displacements $\sim 0.2 \sigma
$, which are approximately half way between the ballistic prediction
and the observed results for bulk for the same $t$.  These values are
also listed in Table~\ref{table:diff2}, under the heading of
``split.''

The surface molecules reach the diffusive regime only for typical
displacements larger than one molecular diameter $\sigma$, which
require a time similar to the residence time. If we compute the time
needed to diffuse to a displacement of $\sigma$ we find $t_\sigma =
4.2 \sigma \sqrt{m/\epsilon}$, a value very close to that of $\tau$
($4.3$ in reduced units).  This means that only about one third of the
molecules at the surface ($\approx 0.8\times e^{-1}$) remain in it
before diffusing a transverse distance similar to their diameter.  We
have to bear in mind the exponential decay for the number of molecules
which remain at the surface after a time $t$ --- e.g. a molecule would
likely move a distance $2 \sigma$ on the surface in a time $t \approx
4 \tau$, while in the bulk it would need typical times $10$ times
larger to diffuse the same distance. However, less than two percent of
the surface molecules ($\approx 0.8\times e^{-4}$) would remain as
such for $t=4 \tau$ and longer times, so that the large value of
$D_\|$ has limited relevance for the actual surface kinetics. The
turnover process of molecules from the surface to the bulk phases, and
its reverse, would be at least as relevant as the diffusion on the
surface. Therefore, it is most important to analyze that turnover
process, beyond its simple description in terms of the typical time
$\tau$. In the next subsection we show how the intrinsic sampling
method may also give an effective diffusion coefficient for the
movement of the surface molecules in the $z$ direction, in their
wandering which will eventually take them out of the surface.

\subsection{Diffusion perpendicular to the surface}
\label{perpendicular}

The naive relation
\begin{equation}
\label{eq:einstein_z}
\left<z^2\right> \rightarrow 2 D_\perp t
\end{equation}
is bound to fail if we restrict the averaging to the molecules at the
surface --- these are limited in space to the region about which the
IS fluctuates (both in position and in time).  The MSD for the $z$
coordinate will therefore tend to a constant value equal to the
squared width of the surface molecules density profile.  An
intermediate diffusive regime between ballistic behavior and this
final plateau may appear sometimes, but there is no reason to expect
this in general. Indeed, this is not the case in the situation
considered here, as is obvious from the dashed line in
Figure~\ref{fig:diff1}.

We show how to go beyond this naive prediction in a
series of steps. First, Einstein's equation is more
general than Eq.~(\ref{eq:einstein_z}): this would be
the second moment of a probability distribution:
\begin{equation}
P(z,t)=\frac{1}{\sqrt{4\pi D_\perp t}} \exp
   \left[ - \frac{z^2}{4 D_\perp t} \right].
\end{equation}
This, of course, is the solution to the
diffusion equation
\begin{equation}
\frac{\partial P(z,t)}{\partial t}=
D_\perp \frac{\partial^2 P(z,t)}{\partial z^2},
\end{equation}
with an initial Dirac delta function distribution: $ P(z,t=0)=
\delta(z) $, and vanishing values of $P$ and its flux for
large $\pm z$. In our MD simulations that $P(z,t)$ would correspond to
selecting molecules which at the time $t=0$ were within a very thin slab
in the $z$ direction, and which in terms of their displacement $z$,
would diffuse to have a probability distribution $P(z,t)$ after a time $t$.

The same experiment could be done selecting the molecules on the
intrinsic surface at time $t=0$, and following their $z$ displacement
with $t$, but that would soon mix the surface and bulk diffusion as
commented in the introduction. Alternatively, we may represent in
$P(z,t)$ only the $z$ position of those molecules which have been
continuously at the IS from $t=0$.  That probability distribution
would not expand indefinitely, as required by the constant value of
the MSD for the $z$ component at long times in Figure~\ref{fig:diff1}.
That effect can be ascribed to an external potential $U(z)$ that
constrains surface molecules to a particular location in space.  Indeed, this
potential should be identified with a potential of mean force (PMF):
the mean-field description of the action of all other molecules on the
one diffusing on the surface.  Our diffusion equation would now be a
Smoluchowski equation:
\begin{equation}
\frac{\partial P(z,t)}{\partial t}=
D_\perp     \frac{\partial}{\partial z}
   \left[
    \frac{\partial P(z,t)}{\partial z}+
    \frac{1}{k_\mathrm{B} T}
         P(z,t) \frac{\partial U(z)}{\partial z}
  \right].
\end{equation}
(application of Smoluchowski equations to diffusion in non homogeneous
media can also be found in Refs.~\onlinecite{hijkoop_2007,liu}).  The
solution to this equation in the steady state would be an
\emph{equilibrium} distribution
\begin{equation}
P_\mathrm{eq}(z) \equiv
P(z,t\rightarrow\infty) \propto
 \exp
   \left[ - \frac{U(z)}{k_\mathrm{B} T} \right].
\end{equation}

A final ingredient comes from the fact that molecules
are continously leaving the IS,
a fact which may be incorporated through a loss
term in the Smoluchowski equation:
\begin{equation}
\label{eq:smoluloss}
\frac{\partial P(z,t)}{\partial t}=
D_\perp  \frac{\partial}{\partial z}
  \left[
    \frac{\partial P(z,t)}{\partial z}+
    \frac{1}{k_\mathrm{B} T}
         P(z,t) \frac{\partial U(z)}{\partial z}
  \right] -
                \nu_\mathrm{io}(z) P(z,t),
\end{equation}
where we have to plug the input/output frequency at each $z$ position, $\nu_\mathrm{io}(z)$,
discussed above and shown in Figure~\ref{fig:distros}.
The function $P(z,t)$ solving this equation would not keep its normalization,
since its $z$ integral will decay with time, as the probability that an
initially selected surface molecule would remain at the surface at time $t$.

For very long times we expect that, independently of the way we
initially select them, the remaining surface molecules will factorize
as in Equation (\ref{eq:factorizes}): $P(z,t) \sim \exp(-t/\tau)
P_\mathrm{o}(z)$, in terms of the probability distribution for the $z$
coordinates of old surface molecules, in Figure~\ref{fig:rhos}, and
decaying with the typical time $\tau$, so that (\ref{eq:smoluloss})
becomes
\begin{equation}
\label{eq:smoluloss2}
D_\perp \frac{d}{dz}
 \left[
    \frac{d P_\mathrm{o}(z)}{dz} +
    \frac{P_\mathrm{o}(z)}{k_\mathrm{B} T} \frac{U(z)}{dz} +
 \right]
-\left[
\nu_\mathrm{io}(z) P_\mathrm{o}(z)-\frac{1}{\tau}
 \right] P_\mathrm{o}=0,
\end{equation}
which, for a given $D_\perp$ could be used to get the
effective potential of mean force which is
compatible with forms of $P_\mathrm{o}(z)$ and $\nu_\mathrm{io}(z)$
obtained from our MD simulations, and related to the turnover
time $\tau$ through (\ref{eq:piv_t}).
The
potential of mean force could be easily obtained by integration of
Equation (\ref{eq:smoluloss2}):
\begin{equation}
\frac{1}{k_\mathrm{B} T}
\frac{dU(z)}{dz} =
-\frac{d (\log P_\mathrm{o})}{dz}+
 \frac{1}{ D_\perp }
   \int_{-\infty}^z dz'
       \left[
          \nu_\mathrm{io}(z') -
            \frac{1}{\tau}
       \right] P_\mathrm{o}(z').
\end{equation}
Thus, the only unknown in Equation (\ref{eq:smoluloss}) is the
parameter $D_\perp$, which is required both to get $U(z)$ and to set
the scale in the time variation of $P(z,t)$. If we integrate that
equation from the equilibrium probability distribution for all the
surface molecules, it would evolve in time towards the exponentially
decaying distribution of old surface molecules, and we could get
$D_\perp$ through the comparison of the actual evolution of $P(z,t)$
with the solution of the generalized Smoluchowski equation. A better
estimation of $D_\perp$ may be obtained if we start with a narrower
probability distribution $P(z,0)$, representing the surface molecules
which are initially within a thin slab around a given $z_0$. The
evolution of this probability distribution shows a first stage of
broadening, dominated by the diffusion so that $\left<(z-z_0)^2\right>
\rightarrow 2 D_\perp t$. In the later stage, the confining effects of
$U(z)$, and the losses regulated by $\nu_\mathrm{io}$ will saturate
the MDS and lead to the mature distribution $P(z,t) \sim \exp(-t/\tau)
P_\mathrm{o}(z)$, with a prefactor which would depend on the value of
$ D_\perp$.  The description of both the early and late stages with
the same effective diffusion coefficient, which should also be fairly
independent of the initial $z_0$ position of the chosen surface
molecules, is a strong requirement to confirm the validity of the
whole scheme, and hence the relevance of the best fitting value of
$D_\perp$ as a true normal surface diffusion coefficient.

In Figure \ref{fig:drift} we show results for the time evolution of a
peak initially at $z_0=-\sigma$ from the maximum of $P_\mathrm{o}(z)$
(its negative sign meaning toward the vapor side), with an initial
width of $0.2\sigma$.  The whole evolution of the $P(z,t)$ can be
traced, but we will just focus on its main features: its mean
position, its MSD, and its decay (normalization).  We try to fit these
three curves with the numerical solution of Eq.~(\ref{eq:smoluloss}),
and we obtain a very good agreement fitting a perpendicular diffusion
coefficient $D_\perp = (0.10\pm0.01)\sigma\sqrt{\epsilon/m}$ that is
comparable to, but smaller than the parallel one. Of course, the
exponential decay of $N(t)$ reproduces the previous value of
$\tau=4.26\sigma\sqrt{m/\epsilon}$ (see dotted line in
Fig.~\ref{fig:drift}). We have checked that our results are largely
independent of the initial position $z_0$, except for peaks very close
to the liquid phase. Indeed, the procedure seems to fail somewhat on
this side, presumably due to the more involved nature of the process
close to the liquid, with ``interstitial'' molecules, fluctuating
rapidly (ballistically) from being considered as belonging or not to
the IS. Those are again the expected limitations of any attempt to
locate the \emph{outmost liquid layer}, and we should be ready to
accept some degree of ``softness'' in that concept. Nevertheless, the
whole procedure provides a fairly well defined value of the normal
surface diffusion, with a value between those of the bulk and the
tangential surface diffusion, and close to the later.

Remarkably, there is only one work, to our knowledge, that discusses
normal diffusion in a liquid-vapor interface, Ref.~\onlinecite{liu}. They
report a value (also included in Table~\ref{table:diff1} ) that is
lower than ours, and closer to the bulk value. This is presumably due
to their use of slabs, by which some of slower bulk diffusion is mixed
with the normal diffusion. The remaining works all discuss
liquid-liquid interfaces, providing very similar values for both
diffusion coefficients at the interface,\cite{meyer_1988,buhn_2004} or
lower values for the normal coefficient%
\cite{benjamin_1992,michael_1998} (even lower, in fact, than the bulk
values). It is our feeling that this discrepancy stems mainly from the
saturation of the curve corresponding to normal diffusion that has
been discussed (short dashed curve in Figure \ref{fig:diff1}): if a
diffusion is computed for times shorter than the split time, a similar
value for both coefficients will be found; but for longer times, an
(effective) lower normal coefficient will be obtained.

\begin{figure}
\includegraphics[width=8cm]{drift}
\caption{\label{fig:drift}
Diffusion of a narrow peak, comparing
simulation results (solid lines) and predictions from
Eq.~(\ref{eq:smoluloss}) (dashed lines). Upper left: mean position
(first moment of the distributions), in units of $\sigma$, lower left:
MSD (second moment of the distributions), in units of $\sigma^2$,
right: fraction of surviving molecules
$N_\mathrm{s}(t)/N_\mathrm{s}(0)$ (normalization of the
distributions).  Dotted line in the later: rescaling of the dashed
line to demonstrate we obtain the proper residence time.  All graphs are
\textit{versus} reduced time $t$ (units of $\sigma
\sqrt{m/\epsilon}$).}
\end{figure}

\begin{table}
\begin{tabular}{|c|C|C||C|C|C|C|C|C|C|C|C|}
\hline
 & & & \multicolumn{3}{c|}{bulk} & \multicolumn{3}{c|}{IS} &
  \multicolumn{2}{c|}{split} &  \sigma
 \\ \cline{4-12}
 model & T^* &  \tau^* &
  t_\mathrm{c} & \Delta x_\mathrm{c} \mathrm{(1)}  & \Delta x_\mathrm{c} \mathrm{(2)} &
  t_\mathrm{c} & \Delta x_\mathrm{c} \mathrm{(1)} & \Delta x_\mathrm{c}  \mathrm{(2)} &
  t_\mathrm{s} & \Delta x_\mathrm{s} &
  t_\sigma \\

\hline
SA & 0.212  & 13.2 & 0.19 & 0.087  & 0.078 & 0.36 & 0.16 & 0.14 & 0.8 & 0.2 & 13.2 \\
\hline
LJ & 0.678  & 4.3  & 0.099 & 0.081 & 0.074 & 0.38 & 0.32 & 0.23 & 0.4 & 0.2 & 4.2 \\
\hline
LJ & 0.848  & 2.27 & 0.19  & 0.18  & 0.14  &  0.47 & 0.43 & 0.32 & 0.3 & 0.2 & 2.9 \\
\hline
\end{tabular}
\caption{\label{table:diff2}
Table of relevant times and lengths for diffusion
at different temperatures, in reduced units:
$\sqrt{m/\epsilon}\sigma$ for time, $\sigma$
for lengths, $\epsilon/k_\mathrm{B}$
for temperature.
Listed: model type,
temperature, residence time (these first two
columns appear also in Table~\ref{table:diff1}),
crossover time and displacements for the bulk,
crossover time and displacements for the intrinsic surface,
split time and displacement,
time to cover a length of $\sigma$.
For the crossovers, two displacements are listed, one
from the intersection of the limiting lines, another
from the curves themselves. Details in the main text.}
\end{table}

\section{Discussion}
\label{discussion}

In order to support our main claims, we have performed simulations at
other temperatures. We would like to consider temperatures higher and
lower than the one considered. Hence, we have collected results for
the LJ liquid-vapor interface at a temperature $25\%$ higher,
$k_\mathrm{B}T=0.848\epsilon$.
It is not possible in principle to lower the temperature below the
triple point of LJ --- hence, in order to observe the influence of a
sizable drop in temperature, we have considered the soft alkali (SA)
potential of Ref.~\onlinecite{Chacon_Tarazona_PhysRevLett}.  The
parameters in this model have a similar meaning to the ones in the LJ:
$\sigma$ is the distance at which the potential vanishes and
$\epsilon$ is related to the volume integral of the intermolecular
potential function. Thus, the estimated critical temperature for this
model is $k_\mathrm{B}T_\mathrm{c}\approx 1.43\epsilon$, similar to
the one of the LJ fluid ($k_\mathrm{B}T_\mathrm{c}\approx
1.33\epsilon$).  This is a potential engineered to result in a very
low triple point temperature of $k_\mathrm{B}T_\mathrm{t}\approx
0.15\epsilon$.  We have considered a temperature of $k_\mathrm{B}T=
0.212\epsilon$.  The lateral size is $L=9.025\sigma$, and the number
of components employed in the IS Fourier analysis is $8$.  In
addition, the optimum value of the surface density is, for this model
$n_\mathrm{s}=0.7\sigma^{-2}$.  The curves showing the square root of
the MSD as a function of time, for the two temperatures, are given in
Figure \ref{fig:otherTs}.

The results for the residence time and for the diffusion coefficients
are included in Table~\ref{table:diff1}.  We see that with increasing
temperature decay diffusion becomes faster and residence times
shorter, as is to be expected. The ratio $D_\|/D_\mathrm{b}$ is about
$2.4$ for the higher temperature (LJ fluid), since the increase in
$D_\|$ is less drastic than that in $D_\mathrm{b}$. For the lower
temperature (SA fluid) this ratio is about $2$: in this case the
reduction in $D_\|$ turns out to be more drastic than that in
$D_\mathrm{b}$.  This is probably due to the fluid phase being already
very dense, while the molecules at the surface still have the option
of hopping along it --- surface diffusion is therefore reduced due to
the prevalence of energetic attraction (exerted mainly from the bulk
liquid) over entropy at lower temperatures.

\begin{figure}
\includegraphics[width=8cm]{diffTs}
\caption{\label{fig:otherTs}
Same as Figure~\ref{fig:diff1} for a lower temperature of
$k_\mathrm{B} T = 0.212\epsilon$, for the SA model (left), and a
higher one of $k_\mathrm{B} T = 0.848\epsilon$ for the same model, the
LJ fluid (right).  Solid lines: $x$, $y$, and $z$ components in the
bulk liquid (hardly distinguishable), long-dashed lines: $x$ and $y$
components for the intrinsic surface (hardly distinguishable, except
at the longest times due to statistical noise), short-dashed line: $z$
component for the intrinsic surface. Dotted lines: prediction from the
Maxwellian velocity distribution, Eq.~(\ref{eq:Maxwell}), and fits to
Einsteinian diffusion equations, Eq.~(\ref{eq:einstein_xyz}).}
\end{figure}

We have also repeated the analysis of typical times and lengths for
the curves in Figure \ref{fig:otherTs}, and collected this information
in Table~\ref{table:diff2}.  The most obvious correlation is between
the time needed to diffuse a length of $\sigma$, $t_\sigma$ and the
residence time. In all three cases, these two quantities are nearly
equal. This corresponds to a natural assumption of a certain isotropy
in the diffusion process: by the time a molecule at the IS has
displaced a length of one molecular diameter, it is likely that the
molecule has also left the IS (which is of course consistent with the
IS being of molecular width). In other words, the product of $D_\|$
and $\tau$ should be nearly constant, which indeed is true, providing
a typical length of $\sqrt{D_\|\tau}\approx 0.7\sigma$ in all three
cases.

There seems to be some agreement in the split length, the approximate
displacement beyond which the parallel and perpendicular diffusion
curves split, with a value around $0.2\sigma$ in all cases.  Other
correlations are seen to be model-dependent. For example, the trend
for typical bulk crossover times and lengths differs in the SA model
due to its shallower potential well. Indeed, the argument given above
in terms of a local coordination close to the FCC packing is still
valid for the higher temperature, yielding a value of $\Delta x
\approx d-\sigma_0 = 0.12\sigma $ (to compare against $0.14\sigma$),
but fails for the SA model, with a value of $d$ that is below the
appropriate $\sigma_0\approx 1.5\sigma$.

In addition to varying the temperature, it is natural to explore the
dependence of diffusion with the interfacial area. On one hand, the CW
framework leads us to think that there could be a change of $D_\perp$
with the area. On the other hand, if this quantity is a true intrinsic
property of the surface, it should be area-independent.
In order to explore this possibility, we have scaled the lateral
length of our simulation box, $L$, by factors of $1/2$, $2/3$, $3/2$,
and $2$ (i.e., the area going from $1/4$ to $4$ times the original).
For the last two cases, we have increased the number of molecules to
$8000$ and $15625$, respectively (otherwise, the liquid film would
have been too thin); we have also enlarged the cell in the $z$
direction, with $L_z=200$ for the smallest area in order to
accommodate a thicker liquid slab.  In order to keep the same
resolution in the IS Fourier treatment, the $12$ functions for the
original area will now be $6$, $8$, $18$, and $24$, respectively.

As shown in Figure~\ref{fig:distros2}, functions $P_\mathrm{o}(z)$ and
$\nu_\mathrm{io}(z)$ contract for smaller areas and stretch for
larger ones, as is to be expected from the general broadening due to
CWs.  (In order to obtain these curves, it is important that the
various properties of the IS should be computed by subtracting the $z$
value of the $q=0$ (constant) mode --- otherwise, bulk density
fluctuations produce a spurious broadening of the distributions at
smaller areas,\cite{Chacon_Tarazona_PhysRevLett} contrary to the
contraction that is found). Nevertheless, the repetition of the
analysis by means of the Smoluchowski Equation (\ref{eq:smoluloss}),
shows no measurable dependence of $D_\perp$
with the area within our $10\%$ error bar.  This supports the
identification of $D_\perp$ as a true intrinsic property of the
surface, and confirms the methods described. Indeed, simpler methods
based on dividing the system in slabs,\cite{buhn_2004, liu} or
selected ``outmost'' molecules\cite{Taylor_1996,taylor_2003} would
have resulted in a clear dependence of $D_\perp$ with the area.

\begin{figure}
\includegraphics[width=8cm]{P_i2}
\caption{\label{fig:distros2}
Comparison of the different distribution functions for different
lateral sizes.  Left: input/output rate per molecule,
$\nu_\mathrm{io}(z)$; right: density profile for old surface molecules,
$P_\mathrm{o}(z)$.  Solid lines: original lateral size $L=10.46\sigma$
(same curves as in Fig. \ref{fig:distros}); dashed line: lateral size
twice longer; dotted lines: lateral size twice shorter.  All functions
are normalized to unity.}
\end{figure}

\section{Conclusions and future work}
\label{conclusions}

We have described an application of the intrinsic sampling method to
the analysis of dynamical processes at the liquid-vapor interface.
The main conclusion is that a liquid surface is a region of enhanced
molecular mobility, with respect to that in the bulk liquid, but
without strong anisotropy.  The characterization of the normal
diffusion constant for the molecules at the outmost liquid layer
requires a much more elaborated method that for the transverse
component, but at the end of the day we get similar values for
$D_\perp$ and $D_\|$, both at high and low temperatures for the simple
liquid models studies in this article. This fact is consistent with
our results for the residence time, which governs turnover rate, i.e.,
the rate at which molecules enter and leave the intrinsic surface ---
a time that turns out to be comparable to the typical times for the
threshold of diffusion. Thus, the typical time required for a molecule
to travel a distance on the order of a molecular diameter is very
similar to its residence time as a surface molecule. Therefore, even if
diffusion coefficients can still be computed for molecules that stay
at the surface for times long enough, the turnover processes are
equally important when discussing the dynamical properties of the
interface. We have discussed two main features of these processes: the
overall residence time, and the input/output rate per molecule,
$\nu_\mathrm{io}(z)$, the spacial distribution function of the
turnover rate.

The particular details of interfacial dynamics will be, of course,
model-dependent. We next provide some relevant cases on which the
method describe here could be applied. References will be given to
previous works on these systems, but we would like to emphasize that
these works have employed the usual approach (by means of slabs),
therefore the present approach (by means of the IS) could shed new
light on the structure and dynamics of systems of considerable applied
interest.

The most important applications of this technique would now be
realistic models of complex fluids, such as the liquid-vapor interface
of water\cite{liu_2005,liu} In this case, the more orderly nature of
liquid phase, and the high surface tension, are likely to provide
additional stability for the molecules at the interface, thereby
leading to longer residence times and more surface molecules reaching
the diffusion regime. We have already started an effort to study this
system from the point of view presented in this article --- in
particular, the discrepancy in our value of the normal diffusion
coefficient for the LJ fluid with results of Ref.~\onlinecite{liu}
suggest that the corresponding values for water will likewise differ.
We also intend to employ this approach to clarify the controversy
surrounding normal diffusion in liquid-liquid interfaces.%
\cite{meyer_1988,benjamin_1992,michael_1998,buhn_2004}

Similar systems of interest include aqueous solutions%
\cite{paul_2005,paul_2005_2,paul_2005_3,chang_2006}
(the later is a useful review on ion solvation at liquid surfaces)
and surfactants at interfaces.%
\cite{chanda_2005,chanda_2005_2,chanda_2006,clavero_2007} Surfactants
will be usually located at the surface, and most will reach the
diffusive regime.  The relationship between structure and dynamics is
specially interesting in systems with strong profiling, such as liquid
metals,\cite{gonzalez_2006} confined water,%
\cite{martins_2004,sega_2005,marti_2006,hijkoop_2007,lee_1994} and
liquid-solid interfaces.\cite{thomas_2007} Similarly, diffusion in
amphiphilic bilayer structures, \cite{bhide_2005,sega_2005}
micelles,\cite{pal_2005} and microemulsions can be described in a
manner similar to the one presented here.

\section{Acknowledgments}

Financial support for this work has been provided by the Direcci\'on
General de Investigaci\'on, Ministerio de Ciencia y Tecnolog\'{\i}a of
Spain, under grants FIS2004-05035-C03, FIS2007-65869-C03, and
CTQ2005-00296/PPQ and Comunidad Aut\'onoma de Madrid under program
MOSSNOHO-CM (S-0505/Esp-0299).

\newpage

redpajama_set_name: RedPajamaArXiv


7News has obtained an unusual video. It is reportedly captured in this area - about 5 miles due north of Ladyville along the Belize District coastline.
As first reported in the Guardian newspaper, It shows 7 coffins along with skeletal remains in shallow waters in an area known as Little Rocky Point. Apparently, the property owner had gone for some water recreation when he came upon the disturbing sight.
When we called the Department of Archeology they say they are looking for the area but have not found it yet. They do plan to investigate it and determine the origins of the coffins.
The area is known to have significant historical sites - but we note that. We'll tell you when the Institute of Archeology does find out something.
This week the Guardian Newspaper was provided with video footage which shows as many as 7 coffins along with human remains in shallow waters off the coast in an area known as rocky point. Its an area due north of Ladyville and the discovery was made by someone who owns property there and had gone to swim there.
We contacted the Department of Archaeology and they are on an active mission to find the coffins as these form part of Belize's rich history. Archaeologist Jose Ramos told the Guardian that the entire area is dotted with significant historical sites but it is not aware of this most recent find.
Personnel from the department have been deployed to the area but so far have been unsuccessful at locating the coffins. They however say that the effort to locate them will not subside.
We will keep our readers informed.


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Our private tours are ideal for school groups, cruise guests, convention groups or anyone else simply looking for a private and custom experience. Please call or contact us using the form below with inquiries. Thank you.


text:
Hanging Upside Down, David Blaine Risks Health
The illusionist plans to spend three days and two nights upside down.
By DAN CHILDS<br>ABC News Medical Unit
September 19, 2008, 10:00 PM
Sept. 22, 2008 — -- For three days and two nights, illusionist David Blaine will enjoy an unusual view of New York City's Central Park -- one that can only be enjoyed from six stories in the air, while hanging upside down.
The magician's latest stunt, called the "Dive of Death," began 8:30 this morning as he was hoisted into position. The effort will reportedly culminate in Blaine dropping to the ground at 11 p.m. Wednesday.
Dr. Ronald Ruden, Blaine's physician, told ABCNews.com that when he first heard the name of the stunt, "It scared the crap out of me."
Considering the various health hazards Blaine may face as he hangs in the position for about 60 hours, Ruden's concern is warranted. He said the stunt will be all endurance -- no smoke and mirrors.
"How he does this I'm not 100 percent sure," Ruden said. "He seems to have the ability to use his mind to control his body to not experience pain and discomfort, as well as take away his basic drives to eat and sleep and defy his fear."
"We don't even know what the physiology of this is," he said with a laugh. "I hate that."
Blaine told "Good Morning America" today right before he was hoisted into the air that he always found images of Harry Houdini hanging upside down "compelling to look at."
Houdini dangled upside down wearing a straightjacket and tried to escape as quickly as possible, but Blaine's niche is testing his endurance.
"I always liked that idea of being upside down," Blaine said. "So I started experimenting on how long could somebody actually be put upside down. And there was no documentation of it. Nobody really had research on it. I invited doctors to kind of look and watch me as I was doing experiments. And although the dangers are high, I think there's a way to override that. "
Blaine said he has prepared for the challenges of the 2½-day hang by losing some weight, performing special exercises and practicing dangling upside down.
But there are certain health considerations that simple conditioning cannot address. During his ordeal, Blaine will not eat or sleep. He will urinate through a catheter. And doctors not involved with the stunt say there are definite risks involved with his attempt.
"He's practiced a lot, but I'm not sure how long he has done it," Ruden said. "I'm pretty certain that the longest he has done it so far is around six hours."
Blood Pressure a Major Concern for Blaine
In particular, Ruden and other physicians agreed that Blaine will face multitude of risks associated with the unusual increase in blood pressure that Blaine will experience.
"The heart is centered pretty close to the head, so it does not have to pump blood very high," Ruden said. "When you flip it around, though, the toes are four and a half feet from the heart. So the heart has to pump blood to a higher altitude than what it is used to."
This, in turn, means a higher blood pressure. With this risk come a number of possible problems -- not the least of which are stroke and possible blindness as the blood pressure in his eyes increases.
Blaine said doctors will be on hand during the stunt, checking for brain hemorrhaging and stroke and making sure his vision stays clear.
"Certainly, [the stunt] could potentially be very dangerous because the brain relies on gravity to allow blood to flow out of the skull," said Dr. Wendy Wright, assistant professor of neurology and neurosurgery at Emory University Hospital in Atlanta.
"Hanging upside down could cause blood to pool in the skull and pressure could build up inside the brain and eyes," Wright said. "This may result in congestion in the blood vessels causing stokes, or even rupturing of blood vessels causing bleeding. Seizures or death may also result."
The lower extremities have no such problem, of course; as long as we're up and about, our leg muscles do yeoman's work in squeezing the blood back to the heart.
"The lower extremities of man are endowed with constrictor mechanisms that protect the small arteries and capillaries from damage when we stand up," said Dr. Jay Cohn, professor of medicine at the University of Minnesota Medical School in Minneapolis.
"The brain does not have such constrictor mechanisms," he added. "Therefore, prolonged position with the head down may increase pressure in the small arteries and capillaries and lead to blood vessel rupture or blood leakage."
So as Blaine quite literally turns millions of years of evolution on its head, he will also be tempting injury and death. And any pre-existing health conditions could make the stunt even more risky.
"This could be worse if he has high blood pressure to start with," said Dr. Richard Smalling, director of interventional cardiovascular medicine at the Memorial Hermann Heart and Vascular Institute at the University of Texas Health Science Center in Houston.
"If he had any previously undiagnosed vascular abnormalities in his brain the risk would be magnified substantially. Hopefully these issues have already been investigated and he has been cleared medically."
Cardiovascular issues are only part of the picture. Wright said Blaine will also have to contend with a restricted ability to breathe, because his diaphragm will be upside down, with the weight of his intestines pushing upon it. And a lack of proper blood flow to his legs, if profound, may cause muscle tissue to die off as it is starved of oxygen.
And then there is the risk of plummeting to certain death.
"If you fall, there's nobody there to catch you," Ruden said. "You become street pizza."
Should Blaine survive the stunt, it will be the latest entry in an increasingly bizarre and death-defying resume.
"In the earlier part of his career he was buried alive, entombed in ice, he stood on top of a pole. All of this had the kind of flavor of death and resurrection."
"Some people think it's a death wish. I think it's the exact opposite -- a desire to live life at its fullest," Ruden said.
And Blaine is certainly not the first to try hanging upside down for extended periods of time. Indeed, an entire industry has been built around a practice called inversion therapy, in which people hang upside down for short periods of time, supposedly to remedy back pain and other ailments.
But while mostly harmless, this unconventional approach to health is not for everyone.
"[Inversion therapy] has its own side effects and adverse health risks, including headaches and bleeding into the retina," Wright said. "People with hypertension, glaucoma, heart disease or women who are pregnant should not try this. All others should check with their doctor before trying inversion therapy."
Still, Blaine is a man who has been buried alive and has spent days encased in a block of ice. In short, it is likely that he will have a few tricks up his sleeve -- or down it, as the case may be -- to avoid harming himself.
"As far as 'tricks,' I suppose this is the 'magic' part that he keeps closely guarded," Wright said. "Presumably, he would have practiced spending long periods of time in this position prior to doing it in public and is sure that his body can handle the changes."
But physicians emphasized that potential copycats should shy away from this stunt. And for Dr. Kenneth Mack, medical director of the Mayo Clinic Pediatric Center, in Rochester, Minn., the idea that even Blaine would attempt such a stunt was baffling.
"I guess with the economy being so bad, people are really turning their lives upside down looking for employment," he said.

redpajama_set_name: RedPajamaCommonCrawl


President Trump has given conflicting signals in the past day about the fate of immigrants brought to the United States illegally as children.
After a dinner at the White House Thursday, Senate Minority Leader Chuck Schumer and House Minority Leader Nancy Pelosi said they were confident that a deal could be reached. Trump then said that a deal was "fairly close" but also that he wanted more out of the arrangement.
"We'll only do it if we get extreme security, not only surveillance but everything that goes with surveillance," he said Thursday. "If there's not a wall, we're doing nothing," he added, speaking of his campaign promise to build a new security wall along the U.S.-Mexico border.
The overnight confusion about the future of the 800,000 undocumented immigrants currently protected by the Deferred Action for Childhood Arrivals program, or DACA, mirrors Trump's conflicting statements since he became a presidential candidate in 2015.
At various times, Trump has promised to terminate the DACA program immediately and told so-called Dreamers that they have nothing to worry about.
Here's what President Trump has most recently said about DACA, and how it contrasts with his previous statements.
Two days after the Trump Administration announced its decision on DACA, the president tweeted that recipients of the program should remain calm. "For all of those (DACA) that are concerned about your status during the 6 month period, you have nothing to worry about – No action!" he wrote.
The tweet came just one day after the President struck a deal with Schumer and Pelosi to extend the debt ceiling for three months, and reportedly discussed his support for the DREAM Act — legislation that provides people who arrived in the U.S. as undocumented minors with their parents a pathway to citizenship— during the negotiations.
"I'd like to see something where we have good border security, and we have a great DACA transaction where everybody is happy and now they don't have to worry about it anymore because, obviously, as you know, before, it was not a legal deal," Trump said, referring to the fact that former President Obama had implemented the program via executive action.
He also retweeted a post from an account criticizing illegal immigration. "Make no mistake, we are going to put the interest of AMERICAN CITIZENS FIRST! The forgotten men & women will no longer be forgotten," the original tweet said.
Later that day, Trump released a written statement claiming that by implementing the program under executive action, President Obama was "violating the actions of our Republic" and Congress had to act in compliance with the legislative process. He also argued that DACA had "helped spur a humanitarian crisis," by providing incentives for unaccompanied minors from South America to cross the border, some of whom became gang members.
"We're going to show great heart. DACA is a very, very difficult subject for me. I will tell you. To me, it's one of the most difficult subjects I have," Trump said at a press conference in February.
"But you have some absolutely incredible kids — I would say mostly. They were brought here in such a way. It's a very — it's a very very tough subject. We are going to deal with DACA with heart. I have to deal with a lot of politicians, don't forget. And I have to convince them that what I'm saying is, is right. And I appreciate your understanding on that," Trump said.
"They shouldn't be very worried," Trump said in an ABC News interview in January when asked how his policies would affect the Dreamers.
"We will immediately terminate President Obama's two illegal executive amnesties, in which he defied federal law and the constitution to give amnesty to approximately 5 million illegal immigrants," Trump said at a campaign event in August 2016, promising to end DACA as well as Deferred Action for Parents of Americans and Lawful Permanent Residents.
That speech echoed the promise Trump made when he launched his presidential campaign on June 16, 2015. "I will immediately terminate President Obama's illegal executive order on immigration, immediately," he said at that time.


text:
Skrwilno – dawna gromada, czyli najmniejsza jednostka podziału terytorialnego Polskiej Rzeczypospolitej Ludowej w latach 1954–1972.

Gromady, z gromadzkimi radami narodowymi (GRN) jako organami władzy najniższego stopnia na wsi, funkcjonowały od reformy reorganizującej administrację wiejską przeprowadzonej jesienią 1954 do momentu ich zniesienia z dniem 1 stycznia 1973, tym samym wypierając organizację gminną w latach 1954–1972.

Gromadę Skrwilno z siedzibą GRN w Skrwilnie utworzono – jako jedną z 8759 gromad na obszarze Polski – w powiecie rypińskim w woj. bydgoskim, na mocy uchwały nr 24/10 WRN w Bydgoszczy z dnia 5 października 1954. W skład jednostki weszły obszary dotychczasowych gromad Skrwilno, Szczawno (bez miejscowości Obórki), Rak, Ruda, Szucie, Mościska i Baba ze zniesionej gminy Skrwilno w tymże powiecie. Dla gromady ustalono 23 członków gromadzkiej rady narodowej.

1 stycznia 1958 do gromady Skrwilno włączono wsie Czarnia Duża, Czarnia Mała, Otocznia i Zambrzyca ze znoszonej gromady Zambrzyca w powiecie sierpeckim w woj. warszawskim.

31 grudnia 1961 do gromady Skrwilno włączono wsie Borki, Skudzawy i Skudzawy Nowe ze zniesionej gromady Skudzawy w tymże powiecie.

1 stycznia 1972 do gromady Skrwilno włączono sołectwo Urszulewo ze zniesionej gromady Czumsk Duży w tymże powiecie, po czym gromadę Skrwilno połączono z gromadą Okalewo, tworząc z ich obszarów gromadę Skrwilno z siedzibą Gromadzkiej Rady Narodowej w Skrwilnie w tymże powiecie (de facto gromadę Okalewo zniesiono, włączając jej obszar do gromady Skrwilno).

Gromada przetrwała do końca 1972 roku, czyli do kolejnej reformy gminnej. 1 stycznia 1973 w powiecie rypińskim reaktywowano gminę Skrwilno.

Przypisy

Skrwilno

redpajama_set_name: RedPajamaWikipedia


Go take a look at this post at BLDGBLOG on Tatlin's Monument to the Third International. Be sure to stay for the essay that makes up the second half of the post. Absolutely excellent, this site. One of my favorites, and this post takes things to a new level.
The unbuilt status of Vladimir Tatlin's Monument to the 3rd International – or Tatlin's Tower – is both befuddling and possibly contentious. In other words, are we sure that Tatlin's Tower has not actually been built? Can this state of unconstruction be proven?
Perhaps Tatlin's Tower exists after all – but we've been looking in all the wrong places.


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easy inexpensive material to cover wood deck floor - Shanghai Seven Trust Industry Co.,ltd.
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text:
Miss Model of the World 2009, the 20th edition of Miss Model of the World beauty pageant, was held in Shenzhen, China, where 66 delegates around the world competed for the crown. Eméne Alexandra Nyame of France was crowned Miss Model of the World 2009 by overcoming titleholder Maria Lakimuk of Ukraine.

Results

Placements

Special awards
Miss Friendship -  - GanAwardstagoo Bayarkhuu

Miss Photogenic -  -  YAwardsuliya Galichenko

Best National Costume -  - Derya Limen,  - AwardsGantagoo Bayarkhuu,  - Wang Shan

Best in Evening Gown -  - LaAwardsn Huong Ngoc Nguyen

Best in Swimsuit -  - Sabina OvaAwardsriova

Best in Talent -  - Natalie Jean Sangster, Awards - Liisa Maria Löoke,  - Dragana Dujović

Best in Figure -  - EAwardsméne Alexandra Nyame

Best Skin -  - LinAwardsa Maria Gómez Espinosa

Best in Media Impression -  -  YAwardsuliya Galichenko

Miss Charity Ambassador -  - Bo Bo Wang

Remainder
ALBANIA - Krist Petraj ZicishtiAwards

BELGIUM - Emmely PolenAwards

BULGARIA - Nikol VasilevaAwards

CANADA - Jenna-Lee CreelmanAwards

CONGO - Munze BinuamanzaAwards

CRIMEA (Ukraine) - Yuliya ObukhovaAwards

CZECH REPUBLIC - Eliska PospislovaAwards

DENMARK - Cana BertelsenAwards

ESTONIA - Liisa Maria LöokeAwards

ETHIOPIA - Bewunetwa Abebe MekuriyaAwards

GEORGIA - Zina MstoyaniAwards

GERMANY - Nina RittinghausAwards

GHANA - Angela SurajiAwards

GREECE - Vasiliki EfthymiouAwards

HOLLAND - Doreth LangelaarAwards

ITALY - Elena PiccardoAwards

KAZAKHSTAN - Vera StarkovaAwards

KENYA - Ruth Nyambura KinuthiaAwards

KOREA - Kyoung-sil SonAwards

KOSOVO - Roberta GjokaAwards

LATVIA - Kristine SedmaleAwards

LITHUANIA - Vilmante SimanaviciuteAwards

MACEDONIA - Andjela BosheskaAwards

MARGARITA ISLAND (VEN) - Jéssica de Abreu RodríguezAwards

MEXICO - Maria Fernanda Maldonado CañasAwards

MOLDOVA - Irina NegaraAwards

NAMIBIA - Elizabeth ValomboleniAwards

NIGERIA - Ishola TayoAwards

NORWAY - Cathrine GulliksenAwards

PHILIPPINES - Jaysel Morelos ArrozalAwards

RUSSIA - Kristina AzarovaAwards

SOUTH AFRICA - Charlotte SmithAwards

SWEDEN - Madelene NordAwards

TAIWAN - Mi LeeAwards

UJRUGUAY - Camila Fernández CarvalhoAwards

U.S.A. - Lexie GuerreroAwards

Replaced
VENEZUELA - Aswan Yarbouh

References

External links
 Miss Model of the World Website

Miss Model of the World
2009 beauty pageants
2009 in China
Beauty pageants in China

it:Miss Model of the World


text:
Tag: bottom lounge
People's Temple, Radar Eyes and Outer Minds at the Bottom Lounge
Three bands that excel at trippy garage rock reminiscent of the 1960s played Feb. 6 in the Volcano Room, upstairs at the Bottom Lounge. The headliners, People's Temple, have a new album, Musical Garden, out on Chicago's consistently marvelous Hozac Records. The same label also just put out a new 7-inch by one of the other bands at this concert, Chicago's Radar Eyes. The night also featured another outstanding Chicago band, Outer Minds. It was a solid night of great songs, though it seemed to fizzle out at the end, when some technical difficulties resulted in People's Temple playing without drums for a couple of songs. Despite that anticlimactic ending, People's Temple had sounded great when they were jamming out at the start of their set.
Outer Minds
Radar Eyes
People's Temple
The Clean at the Bottom Lounge
The Clean came to Chicago for the first time in some years on Thursday (Sept. 30), playing at the Bottom Lounge. The New Zealand post-punk trio has been making music since 1978 (with some time off now and then along the way). This was the first time I'd ever seen them, and it was a pretty cool experience. When the band switched from guitar to keyboards, the artsier side of its music came out. But the final stretch was more poppy and melodic.
Guitarist David Kilgour left the stage rather abruptly at the end of the main set and then again at the end of the first encore, almost seeming to surprising his band mates, drummer Hamish Kilgour and bassist Robert Scott. It seemed that the band was calling it a night at that point and the Bottom Lounge turned on the house music. But the audience wasn't ready to leave, giving the Clean a loud and sustained round of applause, and finally the guys came back and played one of their best-known tunes, "Tally Ho!"
www.myspace.com/theclean
PHOTOS OF THE CLEAN
THE CLEAN'S SET LIST
The show started out with an energetic set by Chicago's Mannequin Men, including a whole bunch of new songs. A new album must be in the works — or should be, in any case. www.myspace.com/mannequinmen
PHOTOS OF MANNEQUIN MEN
Serena Maneesh and Depreciation Guild
Serena Maneesh plays March 31, 2010, at the Bottom Lounge in Chicago.
Serena Maneesh, a Norwegian band that plays the deliciously loud rock music known as "shoe gaze," hasn't toured the U.S. for a few years, but the group was back this week. The tour brought Serena Maneesh on Wednesday (March 31) to Chicago's Bottom Lounge. It was an event worthy of a big turnout, but alas, attendance looked a little sparse. Despite that, the group's front man, Emil Nikolaisen, made a gracious (and, I think, heartfelt) statement from the stage about how special it felt for him to play again in Chicago.
It was the last night that Nikolaisen's sister, the tall and very Nordic-looking bassist-singer Hilma, played with the band on this tour before heading back to Norway to take care of her children. Lucky for us that we got to see Serena Maneesh with Hilma in the lineup!
With a sound that resembles the churning yet melodic noise of My Bloody Valentine, Serena Maneesh has some songs that seem more like pop than psychedelic hard rock, especially when Hilma takes over on lead vocals. In concert, though, the band was all about the loud jams on Wednesday night. Emil drapes some sort of fringed shawl over himself and occasionally sets aside his guitar just so that he can cavort and twirl to the waves of noise. No actual "shoe-gazing" for this Norwegian rocker! It makes for an exciting spectacle, both for the ears and for the eyes, and Serena Maneesh delivered a strong set.
But no encore? What's up with that? The crowd clearly wanted more, but from what I hear, Serena Maneesh did not do encores at its recent New York shows, either.
www.myspace.com/serenamaneesh
www.serena-maneesh.com
Four bands played Wednesday, and the opening acts included Canyon playing instrumental hard rock reminiscent of Pelican. And sandwiched between all these bands was yet another bunch of noise-makers, Apteka, which played with impressive energy.
See my photos of Serena Maneesh, the Depreciation Guild, Apteka and Canyon.
Loney Dear returns
On Saturday night (Oct.10), as I was coming out of the play Fedra at Lookingglass, I decided on the spur of the moment to head over to the Bottom Lounge for a concert by Sweden's Loney Dear. I showed up in time to see most of the set by Asobi Seksu, which was properly loud and shoe-gazy… But then I was disappointed to see that a number of Asobi Seksu fans left before the set by headliner Loney Dear. This terrific Swedish band ended up playing to a fairly small crowd. Maybe the crowd wouldn't have looked so small if this show had been at a smaller venue like Schubas, where Loney Dear has played in the past, but the Bottom Lounge room tends to dwarf the audience. The Bottom Lounge vibe is OK for a rock show, but when the music's mellower or folkier (as it is with Loney Dear) the old-fashioned concert-hall vibe at a place like Schubas somehow seems more fitting.
Since the last time I saw Loney Dear, I've been listening more to the band's most recent CD, Dear John, which has a number of wonderfully subtle songs. I especially like the hushed, heartfelt track "Harm/Slow," and I was glad to hear the Bottom Lounge quiet down as Loney Dear main man Emil Svanängen sang "Harm" (I believe he sang only the first song in this two-song medley).
I didn't have my camera, so I can't offer any of my own photos from the Loney Dear show, but check out this cool set of images from Kirstie Shanley


text:
Ron E. Ainsworth
Ron@BousteadCo.com
Ron E. Ainsworth has been involved in Mergers & Acquisitions, Capital Markets, Finacial Restructuring, and Business Valuations for over thirty-five years. Mr. Ainsworth's career experience encompasses 400+ domestic and cross-border transactions totaling over $15 billion in value across an array of industries, including food services, healthcare, manufacturing, apparel, and technology.
As the CEO of Trenwith Securities, Inc., Mr. Ainsworth partnered with BDO, the world's fifth largest accounting firm and grew Trenwith's footprint to over 135 offices across 110 countries. Mr. Ainsworth ran Trenwith BDO for 10 years, during which he worked with his partners in Latin America, Canada, India, and China to develop an international M&A and Corporate Finance business. He served as Chairman while expanding Trenwith China presence with the development of a Wholly Owned Foreign Enterprise in Beijing, China. During this period the firm conducted hundreds of transactions with prominent Fortune 500 companies and established relationships with a variety of international capital providers. In 2008, Mr. Ainsworth sold his interest in Trenwith Securities, Inc. and pursued a variety of personal investment projects.
Ron currently resides as a Principal of Boustead & Company Limited. Boustead & Company Limited focuses on providing mergers & acquisitions and capital markets advisory to the middle market.
After selling Trenwith Securities, Inc. in 2008, Ron pursued various personal investments, detailed below:
In 2017, Mr. Ainsworth completed the acquisition of a minority interest in Gussing Renewable Energy America. Gussing Renewable Energy is a carbon recycling business headquartered in Vienna Austria and has power plants in Thailand, Japan, Austria, and the USA.
In 2015 Mr. Ainsworth with his partners acquired a minority interest in 3 Pam LLC. In his role as managing partner, Mr. Ainsworth led the recapitalization of 3 Pam LLC and negotiated an exclusive asset management agreement with the Bravo Fund, a $3.5 billion dollar distress debt fund managed by PIMCO. From 2015 – 2017, Mr. Ainsworth remained a shareholder and board member, where he provided guidance on a $ 3.0 billion dollar portfolio of defaulted mortgage pools.
Also in 2015, Mr. Ainsworth sold NuView Financial Service to Land Home Financial Services, the 42nd largest mortgage lender in the US.
In 2013, Mr. Ainsworth formed a partnership to acquire a controlling interest in Loan Leaders of America. One of the largest California mortgage lender since 1997.
Also in 2013, Mr. Ainsworth co-managed the acquisition and recapitalization of Informationlogix, a technology company that provides services to Bank of America, US Trust, and Merrill Lynch. Today Ainsworth still serves on the executive management committee and board director.
In 2010, Mr. Ainsworth was a co-founder of NuView Financial Services LLC. NuView purchased and serviced non-preforming mortgage debt from the major money center banks.


text:
Contributing
------------

Contributions are welcome, and they are greatly appreciated! Every little bit
helps, and credit will always be given.

You can contribute in many ways:

Types of Contributions
======================

Report Bugs
~~~~~~~~~~~

Report bugs at https://github.com/rockymeza/django-local-requests/issues.

If you are reporting a bug, please include:

-  Your operating system name and version.
-  Any details about your local setup that might be helpful in troubleshooting.
-  Detailed steps to reproduce the bug.

Fix Bugs or Implement Features
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Look through the GitHub issues for bugs reports or feature requests. Should you
find anything interesting, please feel free to submit a pull request for it.

Write Documentation
~~~~~~~~~~~~~~~~~~~

django-local-requests could always use more documentation, whether as
part of the official django-local-requests docs, in docstrings, or
even on the web in blog posts, articles, and such.

Submit Feedback
~~~~~~~~~~~~~~~

The best way to send feedback is to file an issue at https://github.com/rockymeza/django-local-requests/issues.

If you are proposing a feature:

-  Explain in detail how it would work.
-  Keep the scope as narrow as possible, to make it easier to implement.
-  Remember that this is a volunteer-driven project, and that contributions are
   welcome :)

Get Started!
============

Ready to contribute? Here's how to set up `django-local-requests` for local development.

1.  Fork the `django-local-requests` repo on GitHub.

2.  Clone your fork locally::

    $ git clone git@github.com:your_name_here/django-local-requests.git

3.  Install your local copy into a virtualenv. Assuming you have
    virtualenvwrapper installed, this is how you set up your fork for local
    development::

    $ mkvirtualenv local_requests
    $ cd django-local-requests/
    $ pip install -r requirements-dev.txt

4.  Create a branch for local development::

    $ git checkout -b name-of-your-bugfix-or-feature

    Now you can make your changes locally.

5.  When you're done making changes, check that your changes pass lint and the
    tests::

    $ make test
    $ make lint
    $ make test-all  # will test on different versions of Python and Django

6.  Commit your changes and push your branch to GitHub::

    $ git add .
    $ git commit -m "Your detailed description of your changes."
    $ git push origin name-of-your-bugfix-or-feature

7.  Submit a pull request through the GitHub website.

Pull Request Guidelines
=======================

Before you submit a pull request, check that it meets these guidelines:

1.  The pull request should include tests.

2.  If the pull request adds functionality, the docs should be updated.

3.  Add your change to the ``HISTORY.rst`` section for the next release.

4.  The pull request should work for all the versions of Python and Django that
    we need to support. Check https://travis-ci.org/rockymeza/django-local-requests/pull_requests
    and make sure that the tests pass for all supported Python and Django
    versions. You can also run ``make test-all`` to test on all the target
    versions.

redpajama_set_name: RedPajamaGithub


I think I'm making this post more as a warning. There's an organization called Check One Two who work to raise awareness for testicular cancer who've been rolling out a campaign a la the ALS Ice Bucket Challenge across social media. Sooooo, you know, if this happens to catch on there's a horrible chance you'll become susceptible to posts on your favorite websites of people grabbing their crotches and nominating their friends to do the same.
Celebs are already doing it!
The definition continues to say that particularly, my success in education denoted a form of "selling out" by betraying my culture. So doing well in school was bad for my black cred, or nah?


Surrey Business School welcomes international congress of researchers and policy makers to discuss a range of financial topics.
Financial experts from around the world gathered at the University of Surrey recently for Banking, Finance, Money and Institutions: The Post Crisis Era, a conference jointly organised by the Centre for Money, Banking and Institutions (CMBI) at Surrey Business School and the Centre for Research in Contemporary Finance at Fordham University in the United States.
In light of the ongoing problems in various economies and banking sectors across the globe, the conference provided a forum for paper presentations and discussions on a variety of topics, including the performance of banking and financial markets, financial stability and risk management, and the monetary, regulatory and institutional environment.
The conference, held on 2-3 November, featured guest speakers Anthony Saunders, the John M. Schiff Professor of Finance at the Stern School of Business, New York University, and Hans Degryse, Professor of Finance at the KU Leuven in Belgium and Tilburg University in the Netherlands.
For more information, visit the CMBI website.