text:
\section{Introduction}
X-ray spectra of BHXRBs show evidence for a two-phase structure to the accretion flow, an optically thick, geometrically thin accretion disc \citep{Shakura1973} giving rise to a blackbody component in the X-ray spectrum, and a hot optically-thin component, modelled as a power law. The relative strengths of these two components define the appearance of different `states' (e.g. \citealt{Homan2001}).  In the hard state, which we focus on in this paper, the power-law emission dominates the total luminosity.  It has been suggested that the power-law is produced by an inner, optically-thin Advection Dominated Accretion Flow (ADAF) (e.g. \citealt{Esin1997}), which replaces the inner optically thick disc at low accretion rates, and extends down to the Innermost Stable Circular Orbit (ISCO). This implies that the optically thick disc is truncated at some transition radius. Alternatively, the optically thick and optically thin components may co-exist over some range of radii, e.g. if the thin disc is sandwiched by a hot flow or corona \citep{Witt1997,Churazov2001}.  The corona may in turn evaporate the innermost regions of the disc at low accretion rates (e.g. \citealt{Meyer-Hofmeister2003,Mayer2007}), so that the optically thin flow is radially separated from the optically thick disc as for the ADAF model. It has also been suggested \citep{Malzac2007} that a cold thin accretion disc extends close to the black hole in the hard-state. In this model, most of the accretion power is transported away from the disc to power a strong outflowing corona and jet. Since the ADAF and corona perform similar roles in that they upscatter soft photons to produce the observed power-law, we shall henceforth refer to both components interchangeably as the corona, without necessarily favouring either picture.

In the hard state, the variability of the power-law continuum offers further clues to the structure of the accretion flow.  Studies of the timing properties of hard state BHXRBs show that the frequencies of broad Lorentzian features in their Power-Spectral Density functions (PSDs) correlate with the strength of the reflection features as well as the steepness of the power law continuum \citep{Revnivtsev2001,Gilfanov1999}. These correlations can naturally be explained if the Lorentzian frequencies correspond to a characteristic timescale at the disc truncation radius, e.g. the viscous time-scale, so that as the truncation radius increases the Lorentzian frequency decreases, with disc reflection and Compton cooling of the optically thin hot flow by disc photons decreasing accordingly.  In this picture, the truncation radius of the thin disc acts to generate the signals of the lowest-frequency Lorentzian in the PSD, while the highest-frequency Lorentzians may be generated at the innermost radius of the hot inner coronal flow, i.e., at the ISCO \citep{Done2007}.

Regardless of whether the corona is radially or vertically separated from the thin disc, photons upscattered by the corona should interact with the disc. This interaction gives rise to reflection features in the X-ray spectrum, including fluorescent iron line emission and a reflection continuum due to Compton scattering off the disc material. An often-neglected consideration is that a significant fraction of the photons interacting with the disc are absorbed and the disc heated in a process known as thermal reprocessing. Provided that the disc subtends at least a moderate solid angle as seen by the corona, this effect should be particularly significant in the hard state, where the coronal power law continuum dominates the total luminosity. When the power-law luminosity impinging on the disc is high compared to the disc luminosity due to internal heating, then a significant fraction of the disc blackbody emission should be reprocessed and will therefore track variations of the power law continuum.

The anticipated correlated variations of the blackbody and power-law emission can be studied using variability spectra, e.g. the rms spectrum, which show only the variable components of the spectrum \citep{Vaughan2003}.  If the geometry is such that the observed power-law produces reprocessed blackbody emission by X-ray heating the disc, then both power-law and blackbody components should appear together in the variability spectra.  Furthermore, by selecting different time ranges covered by these variability spectra (i.e., analogous to the method of Fourier-resolved spectrosopy, \citealt{Revnivtsev1999}), it is possible to determine whether the low-frequency part of the PSD has a different origin to the high-frequency part in terms of the contributions of blackbody and power-law components.  If the optically thick disc does drive the low-frequency Lorentzian, we predict that the blackbody component should be stronger in the corresponding variability spectrum.

In this work, we examine the variability spectra of two hard state black hole X-ray binaries, SWIFT J1753.5-0127 and GX 339-4, which have good {\it XMM-Newton} data for studying simultaneous variations of disc and power-law.
Previous analyses of time-averaged spectra for these {\it XMM-Newton} observations have shown the existence of the expected blackbody components, together with relativistically broadened reflection features, which have been used to argue that the disc is truncated at significantly smaller radii than previously thought, perhaps only a few gravitational radii \citep{Miller2006a,Miller2006b}. However, see \citealt{Gierlinski2008,Hiemstra2009,Done2007} for arguments in favour of disc truncation at larger radii. In the following Section, we describe the observations and data reduction. In Section~\ref{anres} we show the soft and hard-band PSDs obtained from the data, and present a technique to produce a type of rms spectrum, the `covariance spectrum' which we use to identify the variable spectral components for each hard state source.  In particular we show that, although both power-law and disc blackbody emission are correlated, as expected from thermal reprocessing, the disc is relatively more variable than the power-law on longer time-scales (corresponding to the low-frequency Lorentzian), contrary to what we would expect from simple reprocessing models.  In Section~\ref{discuss} we discuss the interpretation of our results and present further analysis to suggest that the low-frequency Lorentzian corresponds to fluctuations intrinsic to the disc.  A summary of our conclusions is given in Section~\ref{conc}.

\section{Observations and Data Reduction}
\label{obsred}
SWIFT J1753.5-0127 was observed during revolution 1152 for 42 ks by \textit{XMM-Newton} EPIC-pn on 2006 March 24 in \textit{pn-timing} mode using the medium optical filter. The events list was screened using the perl script \textsc{xmmclean}\footnote{http://lheawww.gsfc.nasa.gov/$\sim$kaa/xselect/xmmclean} to select only events with FLAG=0 and PATTERN $\leq$ 4. Examination of light curves showed no evidence for background flaring. Using SAS Version 7.0, \textsc{evselect} was used to extract the mean spectrum, following the procedure of \citet{Miller2006b}, using event positions between 20 and 56 in RAWX and using the full RAWY range. The SAS tasks \textsc{arfgen} and \textsc{rmfgen} were used to generate the Ancillary Response File (ARF) and Redistribution Matrix File (RMF).

GX 339-4 was observed by \textit{XMM-Newton} on 2004 March 16 during revolutions 782 and 783, again in \textit{pn-timing} mode using the medium optical filter. The SAS command \textsc{evselect} was used to filter the events on TIME to avoid background flaring, producing a total combined exposure of 127~ks. Data reduction was very similar to that for SWIFT J1753.5-0127, using SAS version 7.0, but care was taken to avoid pile-up. Successive columns from the centre of the image were excised in RAWX and spectra extracted until no discernable difference in spectral shape could be identified between successive selections on RAWX, implying that pile-up is no longer significant. The EPIC-pn data was deemed free of pile-up using extraction regions in RAWX from columns 30 to 36 and 40 to 46 (i.e., columns 37 to 39 inclusive were excised).  Background spectra were selected in RAWX from columns 10 to 18 over the full RAWY range. To generate an appropriate ARF for the data made in this way, it was necessary to use \textsc{arfgen} to generate an ARF for the full region in RAWX from columns 30 to 46 and generate a second ARF from the spectrum of the excluded region (RAWX columns 37 to 39) and then subtract the latter from the former using the command \textsc{addarf}\footnote{http://xmm.vilspa.esa.es/external/xmm\_user\_support\\/documentation/sas\_usg/USG/node63.html}.

For both sources, the \textsc{ftool} \textsc{grppha} was used to scale the background spectra and to ensure that a minimum of 20 counts were in each bin for $\chi^2$ fitting. The EPIC-pn covers the energy range from 0.2-10~keV, but the EPIC Calibration Status Document\footnote{http://xmm2.esac.esa.int/external/xmm\_sw\_cal/calib/index.shtml} recommends restricting the fit to energies greater than 0.5~keV. To be conservative, our EPIC-pn spectral fits were restricted to the range 0.7 to 10.0 keV.

We extracted data from \textit{RXTE} observations which were contemporaneous with the \textit{XMM-Newton} observations. We used the high time and spectral-resolution PCA Event mode data to extract mean spectra and make rms and covariance spectra using the same time binning as the EPIC-pn data (see Section~\ref{method}). Throughout this work we use \textit{RXTE} PCA data in the 3-25 keV range, and fit these together with the corresponding EPIC-pn spectra, tying all fit parameters together but allowing \textit{RXTE} spectral fits to be offset by a constant factor with respect to the simultaneous EPIC-pn fits, to allow for the difference in flux calibration between the PCA and EPIC-pn instruments, and also for the fact that slight flux differences may result from the fact that the {\it RXTE} observations covered shorter intervals than the {\it XMM-Newton} data.  A 1~per cent systematic error was assumed in all spectral fits to account for uncertainties in instrumental response and cross-calibration. The signal to noise of \textit{RXTE} HEXTE data was not sufficient to perform the covariance analysis we describe in section 3.2.

\section[]{Analysis and Results}
\label{anres}
\subsection{Power-spectral densities}
Before describing the spectral analysis method and results, we first examine the timing properties of each source in soft and hard spectral bands using the power-spectral density function (PSD).  For each source, we used the EPIC-pn data to generate light curves with 1~ms time binning in two energy bands: 0.5-1~keV (soft) and 2-10~keV (hard).  Only complete segments of 131~s duration\footnote{Specifically, containing 131072 time bins.} were used to construct the PSDs, segments with gaps (which can be common at high count rates in timing mode) were skipped over. The resulting Poisson-noise-subtracted PSDs are shown in figure~\ref{psds}.  It is clear from the figure that the PSDs are significantly different in shape between the two bands.  In GX~339-4, the hard-band PSD shows two broad components, with the higher-frequency component appearing to be shifted to even higher frequencies in the hard band. In SWIFT~J1753.5-0127, soft and hard PSDs appear, within the noise, to overlap more closely at higher frequencies.  However, in both sources the soft band PSD shows relatively larger low-frequency power compared to the PSD components at frequencies above $\sim~0.2$~Hz.  This $\sim~20\%$ extra low-frequency power at lower X-ray energies may be associated with the soft excess emission, e.g. if the disc is varying more than the power-law on longer time-scales. Alternatively, there could be power-law spectral variability that applies only on longer time-scales and causes the soft band variability amplitude to be enhanced, i.e., due to steepening of the power-law spectral slope on longer time-scales.  To determine the origin of the extra low-frequency power in the soft band, we must carry out a spectral analysis of the variations on different time-scales, the methodology for which we describe in the next section.
\begin{figure*}
\centering
\includegraphics[width=60mm,angle=-90]{swiftpsd.ps}
\hspace{0.5cm}
\includegraphics[width=60mm,angle=-90]{gx339psd.ps}
\caption{Soft and hard band PSDs for SWIFT~J1753.5-0127 and GX~339-4.  The solid line denotes the 0.5-1~keV PSD, while the dotted line denotes the 2-10~keV PSD.  The Poisson noise component has been subtracted from all PSDs.}
\label{psds}
\end{figure*}

\subsection[]{Methodology: rms and covariance spectra}
\label{method}
When fitting models to X-ray spectra, it is typical to use mean X-ray spectra that only describe the time-averaged spectral shape of a source. Such fits say nothing about the way the different spectral components such as disc blackbody and power-law vary with respect to each other in time. By looking at the absolute amplitude of variations in count rate as a function of energy we can construct `variability spectra' which pick out only the time-varying components.  One technique is to construct Fourier-frequency resolved spectra, obtaining a PSD for each individual energy channel and integrating the PSD over a given Fourier-frequency range in order to measure the variance in that channel, which is used to obtain the rms and so construct the spectrum due to components which vary over that frequency range (e.g. \citealt{Revnivtsev1999}).  This approach is attractive in that it allows the user to pick out complex patterns of spectral variability where components have different time-scales of variation, as may be implied by the soft and hard band PSDs shown in figure~\ref{psds}.  Here we will consider only two time-scales of variability, corresponding roughly to the high and low-frequency parts of the PSD which show significant relative differences between the soft and hard bands.  To approximate the more complex Fourier-resolved approach we will measure over two time-scale ranges a variant of the `rms spectrum', which measures the absolute Root-Mean-Squared variability (rms) as a function of energy (e.g. see \citealt{Vaughan2003}).

Producing the rms spectrum involves allocating each photon event to a time and energy bin, dividing the light curve into segments consisting of $N$ time bins per segment and then working out the variance in each segment for each energy bin according to the following standard formula:
\begin{equation}
\sigma_{\rm xs}^2 = \frac{1}{N-1} \sum_{i=1}^N(X_i - \bar{X})^2 - \overline{\sigma_{\rm err}^2}
\end{equation}
where $X_i$ is the count rate in the $i^{\rm th}$ bin and $\bar{X}$ is the mean count rate in the segment. The expectation of Poisson noise variance, given by the average squared-error $\overline{\sigma_{\rm err}^2}$, is  subtracted, leaving the `excess variance', $\sigma_{\rm xs}^2$, in each segment. The excess variances can then be averaged over all of the segments of the light curve. The square root of the average excess variance plotted against energy forms the rms spectrum\footnote{This is absolute rms, since we are not normalising by the mean count rate.}.  By selecting the time bin size and the segment size, we can isolate different time-scales of variability, effectively replicating the Fourier resolved approach for the two time-scale ranges that we are interested in.  For this purpose, we choose two combinations of bin size and segment size.  To look at variations on shorter time-scales we choose 0.1~s time bins measured in segments of 4~s (i.e., 40 bins long), i.e., covering the frequency range 0.25-5~Hz\footnote{The upper frequency limit is set by the Nyquist frequency, $\nu_{\rm Nyq}=1/(2\Delta t)$ where $\Delta t$ is the time bin size.}.  For longer time-scale regions we use 2.7~s bins in segments of 270~s, i.e., covering the range 0.0037-0.185~Hz.  Note that these two frequency ranges do not overlap and also cover the two parts of both source PSDs which show distinct behaviour in soft and hard bands.

There is, however, a problem with the rms spectrum when signal to noise is low, e.g. at higher energies. It is possible for the expectation value of the Poisson variance term to be larger than the measured average variance term, producing negative average excess variances. If this is the case, it is not possible to calculate the rms at these energies and this introduces a bias towards the statistically higher-than-average realisations of rms values, which can still be recorded. In order to overcome these problems we have developed a technique called the `covariance spectrum'. The covariance is calculated according to the formula:
\begin{equation}
\sigma_{\rm cov}^2 = \frac{1}{N-1} \sum_{i=1}^N(X_i - \bar{X})(Y_i - \bar{Y})
\end{equation}
where $Y_i$ now refers to the light curve for a `reference band' running over some energy range where the variability signal-to-noise is large.  In this work, we use reference bands of 1--4 keV for EPIC-pn data and 3--5~keV for PCA data.  In other words, the covariance spectrum is to the rms spectrum what the cross-correlation function of a time series is to its auto-correlation function.  The covariance spectrum therefore does not suffer from the same problems as the rms spectrum, as no Poisson error term has to be subtracted, since uncorrelated noise tends to cancel out and any negative residuals do not affect the calculation. To remove the reference band component of the covariance, and produce a spectrum in count-rate units, we obtain the normalised covariance for each channel using:
\begin{equation}
\sigma_{\rm cov, norm} = \frac{\sigma_{\rm cov}^2}{\sqrt{\sigma_{\rm xs,y}^2}}
\end{equation}
where $\sigma_{\rm xs,y}^2$ is the excess variance of the reference band. Therefore, the only requirement for there being a valid, unbiased value of covariance at a given energy is that the reference excess variance is not negative. This is usually the case, since the reference band is chosen to include those energies with the largest absolute variability. When the covariance is being calculated for an energy channel inside the reference band, the channel of interest is removed from the reference band. The reasoning behind this is that if the channel of interest is duplicated in the reference band, the Poisson error contribution for that channel will not cancel and will contaminate the covariance. One can think of the covariance technique as applying a matched filter to the data, where the variations in the good signal-to-noise reference band pick out much weaker correlated variations in the energy channel of interest that are buried in noise. In this way the covariance spectrum picks out the components of the energy channel of interest that are correlated with those in the reference band.

It is important to note that the covariance spectrum only picks out the correlated variability component and is therefore a more appropriate measure than the rms spectrum in constraining the reprocessing of hard photons to soft photons, which will result in correlated variations. When the raw counts rms and covariance spectra are overlaid, as in figure~\ref{fig:covrms}, they match closely indicating that the reference band is well correlated with all other energies (the spectral `coherence' is high, e.g. see \citealt{Vaughan1997}). Another advantage of the matched filter aspect of the covariance spectrum is that it leads to smaller statistical errors than the rms spectrum. Specifically, the errors are given by:
\[
Err\left[\sigma_{\rm cov, norm}\right]=\sqrt{\frac{\sigma_{\rm xs,x}^2 \overline{\sigma_{\rm err,y}^2}+\sigma_{\rm xs,y}^2 \overline{\sigma_{\rm err,x}^2}+\overline{\sigma_{\rm err,x}^2}~\overline{\sigma_{\rm err,y}^2}}{NM\sigma_{\rm xs,y}^2}}
\]
where $M$ denotes the number of segments and subscripts x and y identify excess variances and Poisson variance terms for the channel of interest and reference band respectively.  This error equation can be derived simply from the Bartlett formula for the error on the zero-lag cross-correlation function, assuming that the source light curves have unity intrinsic coherence \citep{Bartlett1955,Box1976}. By comparison with equation B2 of \citealt{Vaughan2003}, using the relation:
\[
 \frac{\overline{\sigma_{\rm err,y}^2}}{\sigma_{\rm xs,y}^2} << \frac{\overline{\sigma_{\rm err,x}^2}}{\sigma_{\rm xs,x}^2}
\]
(which is true because the reference band has good signal to noise) it can be shown that the errors on the covariance are smaller than corresponding errors on the rms values.

Finally, we note that, since the covariance is analogous to the zero-lag cross-correlation function, it could be affected by intrinsic time lags in the data. Using measurements of the cross-spectral phase-lags between various energy bands, we have confirmed that the lags between hard and soft band variations are smaller than the time bin sizes used to make the long and short time-scale covariance spectra.  Thus, intrinsic time lags will have no effect on our results.
\begin{figure}
\centering
\includegraphics[width=84mm]{swiftj1753covrms.ps}
\caption{Overlaid covariance and rms spectra for EPIC-pn and PCA data for SWIFT J1753.5-0127. The large error bars in the EPIC-pn data indicate negative excess variances where no rms value could be determined.}
\label{fig:covrms}
\end{figure}

\subsection{SWIFT J1753.5-0127}
We first consider the covariance spectra of SWIFT~J1753.5-0127, and use {\sc xspec~v12}\footnote{http://heasarc.gsfc.nasa.gov/xanadu/xspec/} \citep{Arnaud1996} to fit the long and short-time-scale data together with the mean spectrum in order to identify the origin of the additional long-time-scale variability which can be seen in the soft band PSD.  The covariance spectra do not show sufficient signal-to-noise to detect the rather weak iron line present in the mean spectrum of this source \citep{Hiemstra2009,Reis2009}, so for simplicity we fit only a simple power-law and multicolour disc blackbody \textsc{diskbb}, together with neutral absorption. We fit the short and long-time-scale covariance and mean spectra simultaneously, tying the absorbing column density and renormalising constant for PCA data to be the same for the mean and covariance spectra. An F-test showed that the disk blackbody temperature does not change significantly between spectra, so that was also tied to be the same for all spectra.  The remaining parameters were allowed to be free between the covariance and mean spectra.  For those parameters that were free to vary, EPIC-pn and PCA values were tied together.  The $\chi^2$ of the final fit was 1802 for 1948 degrees of freedom (d.o.f.) and full fit parameters are listed in Table~\ref{tab:swift}.  The best-fitting unfolded spectra and the corresponding data/model ratios are shown in figure~\ref{fig:swifteeufspec}.

To interpret the fits to the covariance spectra, consider the case where the observed PSDs have identical shapes in both hard and soft bands (they may have different normalisations).  In this case, the ratio of soft to hard-band variability amplitudes measured over the same time-scale range will be identical for any given time-scale range.  Therefore, since (for high-coherence variations) the covariance spectrum quantifies variability amplitude as a function of energy, the shape of the covariance spectrum will be independent of time-scale.  On the other hand, if the soft band contains more long-time-scale variability relative to short-time-scale variability than the hard band, the long-time-scale covariance spectrum will appear {\it softer} than the short-time-scale covariance spectrum: lower energies show correspondingly greater variability on long time-scales and therefore larger fluxes in the covariance spectra.  Just such an effect is seen in the model fits to the covariance spectra: the long-time-scale covariance spectrum is softer than the short-time-scale covariance spectrum, because the disc blackbody normalisation is higher on long time-scales.  The power-law slope is remarkably similar on both long and short time-scales however.  Therefore the additional long-term variability in the soft-band PSD seems to result from {\it additional} variability of the disc blackbody, not any extra power-law variability (e.g. due to spectral pivoting).
\begin{table}
\centering
\caption{Fit parameters for mean and covariance spectra of SWIFT J1753.5-0127 for the model {\sc constant*phabs*(diskbb+powerlaw)}}
\begin{tabular}{l c c c}
\hline
Parameter & Mean & 2.7s-270s Cov & 0.1s-4s Cov \\
\hline
$C_{\rm PCA}$ & $1.222^{+0.006}_{-0.006}$ & tied to mean & tied to mean \\ [1ex]
$N_{\rm H}$ & $0.194^{+0.007}_{-0.006}$ & tied to mean & tied to mean \\[1ex]
$\Gamma$ & $1.625^{+0.005}_{-0.005}$ & $1.55\pm0.02$ & $1.55\pm0.03$ \\[1ex]
$A_{\rm pl}$ & $0.0731^{+0.0009}_{-0.0009}$ & $0.0118^{+0.0004}_{-0.0004}$ & $0.0128^{+0.0006}_{-0.0006}$ \\[1ex]
$kT_{\rm in}$ & $0.286^{+0.015}_{-0.014}$ & tied to mean & tied to mean \\[1ex]
$A_{\rm disc}$ & $320\pm25$ & $129\pm11$ & $75\pm20$ \\[1ex]
\hline
\end{tabular}
\begin{flushleft} From top to bottom, the parameters are: constant renormalising factor applied to model fit to PCA data; neutral absorbing column density ($10^{22}$~cm$^{-2}$); power-law photon index; power-law normalisation (photons cm$^{-2}$~s$^{-1}$~keV$^{-1}$ at 1 keV); disc blackbody inner radius temperature (keV); disc blackbody normalisation ($\left[r_{\rm in}/(D/10~{\rm kpc})\right]^{2}$ where $r_{\rm in}$ is the disc inner radius in km and $D$ is the distance in kpc).  All errors are 90~per cent confidence limits.  Since disc temperature and normalisation are highly correlated, the errors on blackbody normalisation are obtained while fixing temperature at the best-fitting value.
\end{flushleft}
\label{tab:swift}
\end{table}
\begin{figure}
\centering
\includegraphics[width=60mm,angle=-90]{swiftj1753eeufspec.ps}
\includegraphics[width=94mm]{swift_three_ratios.ps}
\caption{Top panel: Unfolded spectra for SWIFT~J1753.5-0127 showing the relative contributions of the disc blackbody and power law components in the mean spectrum and short and long-time-scale covariance spectra. Dotted lines indicate spectral components of the short time-scale covariance, dashed lines indicate those of the long time-scale covariance. Bottom panel: SWIFT~J1753.5-0127 data/model ratios for the best-fitting disc blackbody plus power-law model.}
\label{fig:swifteeufspec}
\end{figure}

We can show in a model-independent way that the blackbody component is the source of the additional long-term variability seen in the soft-band PSD, by measuring the `covariance ratio', i.e., plotting the ratio of long-time-scale to short time-scale covariance spectra.  By plotting the ratio, we remove most of the effects of the spectral response (except the smearing by the instrumental resolution) and can see more clearly the nature of any spectral differences.
The covariance ratio plot is shown in figure~\ref{fig:swiftcovratios}, and shows clearly that the excess in long-time-scale covariance arises abruptly below 2 keV, as expected if caused only by the disc emission, rather than being due to a gradual change across the whole spectrum which might be caused by differences in the power-law index. The interpretation of the short time-scale covariance spectrum is addressed later in section 4.4.
\begin{figure}
\centering
\includegraphics[width=84mm]{swiftj1753covratios.ps}
\caption{Covariance ratios for SWIFT~J1753.5-0127 showing the extra blackbody component which contributes on longer timescales.}
\label{fig:swiftcovratios}
\end{figure}

Having established that the reference band is well correlated with all other energies, the normalisations of the covariance spectral components, given in Table~\ref{tab:swift}, relative to those of the mean spectrum indicate the rms variability amplitude.  For example, dividing the disc blackbody covariance normalisations by that of the mean spectrum indicates fractional rms for the disc emission of 40~per cent and 23~per cent over long and short time-scale ranges respectively.  The power-law variability is more complicated to quantify, since the covariance spectra show significantly harder power-law slopes than the mean.  This result implies that the power-law fractional rms increases with energy.  The power-law normalisations imply that at 1~keV the fractional rms of the power-law is 16~per cent and 18~per cent over the long and short time-scale ranges respectively.

\subsection{GX 339-4}
We next produced mean, long and short time-scale covariance spectra for EPIC-pn timing mode and PCA observations of GX 339-4.
We carried out fits to the spectra using a model consisting of a narrow Gaussian emission line (width $\sigma=0.01$~keV) and power law (including the multiplicative model \textsc{hrefl} to account for the reflected continuum from a cold optically thick disk), smeared with the convolution model \textsc{kdblur} in order to account for relativistic broadening of the reflected emission from material orbiting a maximally spinning black hole (see \citealt{Reis2008} for evidence for a high black hole spin in GX~339-4).  A multicolour disc model \textsc{diskbb} was also included to account for the soft X-ray excess. Strictly speaking this component should also be smeared, but it is not appropriate to smear this model with \textsc{kdblur}, as the disc temperature is itself a function of radius.  Since in the \textsc{kdblur} model the disc innermost radius and iron line radial emissivity are somewhat degenerate, the emissivity index was fixed at -3 (i.e., disc-like). Also, the outer radius was fixed at 400~$R_{\rm G}$. The remaining parameters, except the black body normalisation, reflection covering fraction, photon index, power law normalisation and Gaussian normalisation were tied to be the same between the mean and both covariance spectra (we confirmed with F-tests that the tied parameters do not vary significantly between the spectra).  As with SWIFT~J1753.5-0127, the EPIC-pn and PCA parameters were tied together for the same spectra and a renormalising constant factor was included to allow for differences in EPIC-pn and PCA flux calibration. The final fit had a $\chi^2$ of 2489 for 2199 d.o.f. and a full list of model parameters is given in Table~\ref{tab:gx}.  The best-fitting unfolded spectra and data/model ratios can be seen in figure~\ref{fig:gx339eeufspec}.
\begin{figure}
\centering
\includegraphics[width=60mm,angle=-90]{gx339eeufspec.ps}
\includegraphics[width=94mm]{gx339_three_ratios.ps}
\caption{Top panel: Unfolded spectra fitted for GX~339-4 showing the relative contributions of the blackbody, power law (incorporating reflection continuum) and iron line components. Dotted lines indicate spectral components of the short time-scale covariance, dashed lines indicate those of the long time-scale covariance. Bottom panel: GX~339-4 data/model ratios for the best-fitting disc blackbody plus power-law and relativistically smeared reflection model.}
\label{fig:gx339eeufspec}
\end{figure}
\begin{table}
 \centering
  \caption{Fit parameters for mean and covariance spectra of GX 339-4 for the model {\sc constant * phabs * (diskbb+kdblur(hrefl * powerlaw+gaussian))}}
  \begin{tabular}{l c c c}
  \hline
   Parameter & Mean & 2.7s-270s Cov & 0.1s-4s Cov \\
   \hline
$C_{\rm PCA}$ & $1.296\pm0.003$ & tied to mean & tied to mean \\[1ex]
$N_{\rm H}$ & $0.574\pm0.006$ & tied to mean & tied to mean \\[1ex]
$\Gamma$ & $1.766\pm0.006$ & $1.896\pm0.010$ & $1.875\pm0.011$ \\[1ex]
$A_{\rm pl}$ & $0.266\pm0.002$ & $0.110\pm0.001$ & $0.107\pm0.001$ \\[1ex]
$kT_{\rm in}$ & $0.177\pm0.001$ & tied to mean & tied to mean \\[1ex]
$A_{\rm disc}/10^{4}$ & $8.20\pm0.65$ & $3.20\pm0.26$ &  $2.46\pm0.21$\\[1ex]
$R_{\rm in}$ & $4.08\pm0.16$ & tied to mean & tied to mean \\[1ex]
$\theta_{\rm inc}$ & $40.2\pm1.4$ & tied to mean & tied to mean \\[1ex]
$E_{\rm Fe}$ & $6.42\pm0.07$ & tied to mean & tied to mean \\[1ex]
$A_{\rm Fe}/10^{-3}$ & $1.17\pm0.07$ & $0.61\pm0.07$ & $0.58\pm0.09$ \\[1ex]
$CF$ & $0.91\pm0.04$ & $1.13\pm0.08$ & $1.16\pm0.09$ \\[1ex]
\hline
\end{tabular}
\begin{flushleft}
For the definitions of the parameters listed in the first six rows see Table~\ref{tab:swift}. The additional parameters shown are for the relativistically smeared reflection (from top to bottom): disc innermost radius (units of $R_{\rm G}$); disc inclination (fixed to be the same in both {\sc kdblur} and {\sc hrefl}); Gaussian line energy; Gaussian normalisation (photons~cm$^{-2}$~s$^{-1}$); covering fraction of the reflection (where 1.0 corresponds to $2\pi$ steradians).
\end{flushleft}
\label{tab:gx}
\end{table}

The fits to the covariance spectra for GX~339-4 show a similar pattern to that seen for SWIFT~J1753.5-0127, in that the long time-scale covariance spectrum is softer than the short time-scale covariance spectrum because of a significantly stronger disc blackbody component, while their power-law indices are very similar.  We can confirm this interpretation using a plot of the covariance ratio, which is shown in figure~\ref{fig:gxcovratios}, and shows a similar rise at low energies to that seen for SWIFT~J1753.5-0127, which underlines the interpretation that the disc blackbody component is the main contributor to the additional variability seen at low frequencies in the soft band in GX~339-4. The reader is referred to sections 4.1 and 4.4 for a consistent interpretation of the short time-scale covariance spectrum in GX~339-4 and SWIFT~J1753.5-0127. Note that the apparent emission feature around 2~keV is probably an instrumental effect, possibly related to mild pile-up in timing mode, since it disappears when larger regions of RAWX are excised from the data.  Due to the 1~per cent systematic included in the spectral fitting, this feature has no effect on the fit results.

Based on the ratio of component normalisations to those in the mean spectrum, the fractional rms values for the disc component are 39~per cent and 30~per cent over the long and short time-scale ranges respectively.  The corresponding power-law fractional rms values at 1~keV are 41~per cent and 40~per cent.  Using the same approach, we can also define a fractional rms for the iron line emission for long and short time-scales, at $\sim50$~per cent in each case.  Interestingly, the $\sim25$~per cent increase in iron line rms over that of the power-law emission (which drives the line variability) is comparable to the increase in reflection covering fraction from the mean to covariance spectra.  These results may imply the presence of an additional constant power-law component which dilutes the power-law fractional variability but does not contribute to reflection.  It is also interesting to note that the power-law component in the covariance spectra for GX~339-4 is softer than in the mean spectrum, i.e., the difference is in the opposite sense to that seen in SWIFT~J1753.5-0127.

\begin{figure}
\centering
\includegraphics[width=84mm]{gx339covratios.ps}
\caption{Covariance ratios for GX 339-4 showing the extra thermal component on longer timescales}
\label{fig:gxcovratios}
\end{figure}

\section{Discussion}
\label{discuss}
We have shown that disc blackbody emission contributes significantly to the X-ray variability spectra in the hard state of the black hole candidates SWIFT~J1753.5-0127 and GX~339-4, and moreover, that the disc emission is the origin of the additional soft band variability seen on longer time-scales in both sources, which manifests itself as an enhanced low-frequency component in the PSD.  In this section, we discuss the evidence for a connection between disc and power-law variability through X-ray reprocessing, and then consider two possible explanations for the enhanced disc variability on long time-scales, in terms of geometry changes or fluctuations intrinsic to the accretion disc.  Finally we will compare our results and interpretation to the wider picture of different accretion states.

\subsection{Power-law variability and evidence for thermal reprocessing}
The power-law emission clearly dominates the X-ray luminosity in both sources, as can be seen in figures~\ref{fig:swifteeufspec} and \ref{fig:gx339eeufspec}.  In this situation, if the disc sees a reasonable fraction of the power-law emission, we should expect that X-ray heating of the disc, i.e., thermal reprocessing of power-law emission, will produce a significant fraction of the observed disc luminosity.  In fact, the thermal reprocessed emission is directly related to the disc reflection component in the spectrum: if a fraction of incident power-law luminosity $f$ is reflected by the disc (both through Compton reflection and emission line fluorescence), then a fraction $1-f$ must be absorbed and will be reprocessed into thermal blackbody radiation.  The reflected fraction $f$ depends on disc ionisation state but simple exploration of the disc reflection models in {\sc xspec} shows that it is typically 30-40~per cent of the incident luminosity, so that around 60-70~per~cent of the incident luminosity is reprocessed into disc blackbody emission.  For typical iron K$\alpha$ line equivalent widths (around 1~keV with respect to the reflection continuum), we then expect the line flux to be of order 1~per cent of the thermally reprocessed flux.  We might reasonably assume that the blackbody component in the short time-scale covariance spectrum is produced by thermal reprocessing of the varying power-law, which also drives the line emission in the same spectrum. The unabsorbed disc flux is $\sim4.5\times 10^{-10}$~erg~cm$^{-2}$~s$^{-1}$, and the iron line flux is $\sim6\times10^{-12}$~erg~cm$^{-2}$~s$^{-1}$ which is 1.3~per cent of the reprocessed flux, i.e., consistent with a reprocessing origin for the thermal emission, at least on short time-scales.

In SWIFT~J1753.5-0127, the disc blackbody emission is considerably weaker than in GX~339-4, and correspondingly we would expect a relatively weak iron line, with a few tens of eV equivalent width, which is only just consistent with the lower-limits on line strengths reported by \citet{Hiemstra2009} and \citet{Reis2009}.  It is possible that the disc in SWIFT~J1753.5-0127 is substantially ionised (e.g. see \citealt{Reis2009}) which would enhance line emission relative to the absorbed (and hence thermally reprocessed) emission.

Since it is likely that there is substantial X-ray heating of the disc, one must interpret the observed blackbody normalisations in the mean spectra with caution\footnote{The absolute normalisation in the covariance spectra is a function of variability amplitude and cannot be interpreted in the same way as in the mean spectrum.}.  The disc emissivity may be more centrally concentrated than the theoretically expected $R^{-3}$ law, and so the normalisations indicate better the emitting surface area and cannot be simply translated to an inner radius.  Nonetheless, the inferred emitting areas are still relatively small, implying distance scales of tens to hundreds of km (assuming distances $>7$~kpc and 6-15~kpc for SWIFT~J1753.5-0127 and GX~339-4 respectively; \citealt{Zurita2008,Hynes2004}).  We also note here that although the need for disc blackbody emission to explain the spectrum of SWIFT~J1753.5-0127 has been questioned by \citet{Hiemstra2009}, the model-independent covariance ratio plots in figure~\ref{fig:swiftcovratios} show that a distinct soft component must be present in order to explain the difference in the shapes of the covariance spectra.

It is interesting to note that the power-law indices of the covariance spectra are different to those of the mean spectra, but in an opposite sense for each of the two sources considered here: compared to the mean spectrum SWIFT~J1753.5-0127 shows a harder power-law in the covariance spectra, while GX~339-4 shows a softer power-law.  The difference may be caused by flux-dependent spectral pivoting or steepening, so that as flux increases the spectrum gets softer in GX~339-4, increasing the covariance at soft energies relative to the mean, while the opposite effect occurs in SWIFT~J1753.5-0127 (it hardens as it gets brighter).  The difference in behaviour may be related to the source luminosity: if they lie at similar distances SWIFT~J1753.5-0127 is at least a factor 10 less luminous than GX~339-4, implying a significantly lower accretion rate.  Correlations between flux and spectral-hardness have been seen in BHXRB hard states, and interestingly the sign of the correlation appears to switch over from negative to positive at low luminosities, both on short time-scales \citep{Axelsson2008} and in the long-term global correlation \citep{Wu2008}.  The same switch in flux-hardness correlation could be related to the different power-law behaviour of SWIFT~J1753.5-0127 and GX~339 which we see here.

The same pattern appears on both long and short time-scales, which show almost identical power-law indices in their covariance spectra, so that the effect of the power-law spectral variability will be to change the normalisation of the PSD, but not the shape.  Since most of the power-law luminosity will be found at tens of keV (assuming a thermal cutoff at around 100~keV), spectral steepening with flux will cause the observed GX~339-4 0.5-10~keV variability amplitude to be enhanced compared to the true luminosity variations. Conversely, observed variations in SWIFT~J1753.5-0127 will be smaller than the total luminosity variations.  Therefore, the fractional luminosity variations for SWIFT~J1753.5-0127 and GX~339-4 may be similar, but GX~339-4 shows a significantly greater normalisation in the PSDs shown in figure~\ref{psds}.

\subsection{Variable coronal geometry}
We have seen that it is likely that reprocessing of the power-law drives at least some of the disc variability seen in hard state sources, and possibly all of it on time-scales $<1$~s. However, model-independent covariance ratio plots and spectral fitting show that the covariance spectra of both sources demonstrate increased disc blackbody variability with respect to the power law on longer timescales.   There are several possible explanations for this pattern, but the key thing that any successful model needs to achieve is an increase in disk variability on longer timescales without a concomitant rise in power law variability. Also, it is important to note that the additional disc variability must still be correlated with power-law variations, because the enhanced disc variations appear in the covariance spectrum, which is identical to the rms spectrum over the high signal-to-noise energy range covered by the disc (i.e., coherence is unity). If the disc variations were independent of the power-law they would cancel to some extent, since they would be uncorrelated with the power-law component, and covariance would be smaller than the rms.  Thus the blackbody variations map on to power-law variations but with larger amplitude.

One possibility is to change the geometry of the system on longer time-scales.  For example, a variable coronal scale height on longer timescales could lead to changes in the solid angle of disc heated by the power-law, thus increasing the disc blackbody variability amplitude relative to the power-law. Weaker correlated power-law variation could then be produced if scale-height correlates with power-law luminosity.  Alternatively, correlated power-law variations could be due to variable seed photon numbers from the disc due to the enhanced variable heating, but in either case the additional power-law variability must be of smaller amplitude than the observed blackbody variability.  Regardless of these model-dependent arguments, one can make a simple observational test of the variable-geometry model, by comparing the variability of reflection on long and short time-scales.

GX~339-4 shows significant reflection features in its covariance spectra, so any variation in coronal geometry should manifest itself as increased variability in the reflection components as the disk sees the varying power law.  However, the spectral fit parameters given in Table~\ref{tab:gx} indicate that there is little change in reflection amplitude between long and short time-scales, both in terms of reflection covering fraction and iron line equivalent width (e.g. ratio of line flux to power-law normalisation, which is meaningful because the power-law indices are so similar). To highlight this similarity in the covariance spectra, we show in figure~\ref{fig:gxrefl} the data/model ratios for the PCA spectra with the reflection components taken out of the fit.  The spectra demonstrate no significant change in the reflection continuum and associated iron line. This implies that if there is any change in geometry, it is small, and the increase in the thermal component of the variability spectra on longer timescales has a different origin.
\begin{figure}
\centering
\includegraphics[width=84mm]{gx339reflection.ps}
\caption{Data to model ratios of covariance spectra in GX 339-4 with reflection normalisations set to zero}
\label{fig:gxrefl}
\end{figure}

To place this result on a more rigorous statistical footing, we show in
figure~\ref{fig:contour} a contour plot of the best-fitting short and long-time-scale reflection covering fractions, which are obtained only from fits to the PCA data, which are most sensitive to the reflection continuum\footnote{As a result, the best-fitting covering fraction is significantly lower than observed in the joint fit with EPIC-pn, but since we are interested in the {\it relative} change in reflection between different time-scales, this does not affect our basic result.}. If variable geometry is the cause of the enhanced long-term blackbody variability, we would expect the covering fraction to show a similar enhancement in variability on long time-scales.  The dashed line in the figure shows the largest ratio of short-to-long-time-scale covering fraction which crosses the 99~per cent confidence contour, with a value of 0.81, placing a 99~per cent confidence upper limit of 23~per cent on any increase in the covering fraction on long time-scales compared to short time-scales (the 90~per cent confidence upper limit on any increase is 12~per cent). In contrast, the long-time-scale blackbody variability amplitude increases by 30~per cent compared to that on shorter time-scales, which cannot be explained by the permitted increase in variable reflection at greater than the 99~per cent confidence level.  Thus, in GX~339-4 at least, we can rule out long-time-scale changes in coronal geometry as a viable explanation for the enhanced blackbody variability amplitude. Note also that the same arguments apply to any other non-geometric arguments which seek to produce the extra long-term disc variability by varying the power-law contribution as seen by the disc, e.g through variable beaming of the power-law towards the disc. Due to the weakness of the iron line in SWIFT J1753.5-0127 it is not possible to place similar constraints on coronal geometry changes in this source, although by analogy we expect the same interpretation to apply.

\begin{figure}
\centering
\includegraphics[width=60mm,angle=-90]{contourplot.ps}
\caption{GX 339-4 confidence contour plots for the permitted range of reflection covering fraction in simultaneous fits to the long and short-time-scale covariance spectra. The dotted line passes through the 99~per cent confidence contour, so its gradient defines an upper limit to the ratio of long to short-time-scale covering fraction. Also shown are the 90 and 68~per cent confidence level contours.}
\label{fig:contour}
\end{figure}

\subsection{Intrinsic disc variability}

Having established that variable coronal geometry cannot explain the extra blackbody variability on longer timescales, we are left to consider the possibility that the variations are intrinsic to the disc itself.  Perhaps the simplest possibility is that the fluctuations are due to accretion rate fluctuations in the disc which undergo viscous damping before they reach the corona.  Such damping is expected in thin discs (e.g. see \citealt{Churazov2001}), but will not be as significant in geometrically thick flows, which might correspond to the corona.  Therefore one can envisage that the long time-scale variability, e.g. corresponding to the low-frequency Lorentzian in the PSD, is generated in the thin disc, producing relatively large amplitude blackbody variations but being damped before reaching an inner coronal emitting region (perhaps inside the innermost radius of the thin disc). The correlated power-law variability could then arise either from the residual undamped variations in accretion rate which reach the corona, or be driven by seed photon variations from the disc.

If the inner radius of the disc were to fluctuate on long time-scales, then the varying disc area would also introduce extra blackbody variability. This model is in some sense analogous to that of changes in coronal scale height, since any change in disc area will vary the solid angle of disc seen by the corona which will cause an increase in reflection as well as correlated power-law variability driven by seed photon variations.  One could mitigate these effects if the coronal properties were linked to those of the disc inner-radius, e.g. as inner radius decreases, so does coronal scale-height.  This situation might be expected if the corona is formed by evaporation of the disc \citep{Meyer-Hofmeister2003}, so that condensation of the disc will drain and cool the coronal plasma, leading to a reduction in scale-height.

\subsection{Wider implications}
We have established that the hard-state variability on time-scales greater than seconds, corresponding to the low-frequency Lorentzian PSD component, is very probably produced by variations intrinsic to the accretion disc, perhaps in the form of propagating accretion rate fluctuations, as envisaged by \citet{Lyubarskii1997} to explain the broad shapes of observed PSDs.  These variations then manifest as weaker power-law variations, either through propagation of accretion fluctuations to the corona \citep{Churazov2001}, or through variations of seed photons from the disc, which are Compton upscattered in the corona.  On shorter time-scales, the blackbody variations are probably mostly produced by X-ray heating of the disc by the power-law, which is a required outcome of the X-ray reflection directly observed in these systems.  The exact split between direct emission from intrinsic disc variations and X-ray heating is difficult to judge, since some residual intrinsic variations may remain on short time-scales, and X-ray heating will also contribute on long time-scales.  But in the case of intrinsic disc accretion fluctuations, the variable X-ray heating is itself a product of those fluctuations, and so any intrinsic disc variations on long time-scales must be large, at least comparable to the fractional rms of blackbody emission, i.e., 40~per cent in both sources.

It is interesting to contrast the large intrinsic disc variability in these hard state sources with that in the soft states, where the disc emission dominates the bolometric luminosity.  The soft states are well-known for showing very weak, if any, variability \citep{Homan2001}, and the strongest variability which is seen, e.g. in Cyg~X-1, is associated with the power-law, with the disc being remarkably constant \citep{Churazov2001}.  Therefore it seems likely that hard state discs are inherently unstable compared to soft state discs.  This difference may represent just another observable distinction between hard and soft states, but it is interesting to speculate that it may play a more primary role in creating the other observed differences, such as a strong corona and jet formation in the hard state.  Certainly, it seems likely that intrinsic disc variability plays an important role in determining the PSD shape in the hard state. For instance, the low energy PSD of GRS~1915+105 in the $\chi$-class hard intermediate state \citep{Rodriguez2004} shows a low frequency component which disappears at higher energies, possibly indicating that this source is demonstrating intrinsic disc variability.

It is worth noting here that X-ray/optical  studies of AGN also show evidence for reprocessing on short time-scales and intrinsic disc variations on longer time-scales \citep{Uttley2003,Arevalo2008,Breedt2009}.  However these AGN are relatively luminous and radio-quiet and so are likely analogues of BHXRB soft states, perhaps indicating that disc-stability shows a mass-dependence, e.g. related to the transition between gas- and radiation-pressure dominated discs \citep{Maccarone2003}.

Our results strongly suggest that disc variations are responsible for the low-frequency component in the hard state PSD.  A number of authors have suggested that the low-frequency Lorentzian corresponds to the viscous time-scale of the inner, truncation radius of the thin disc (e.g. \citealt{Churazov2001,Done2007}), a view which is consistent with our results.  The higher-frequency PSD components may then be produced in the corona, which is likely to be geometrically thick so will show naturally shorter variability time-scales.  The viscous time-scale scales with scale-height ($H$) over radius ($R$) as $(H/R)^{2}$.  Assuming the ratio of disc scale-height to radius $H/R\sim \alpha \sim 0.1$ (where $\alpha$ is the viscosity parameter), the predicted inner disc radius corresponding to the observed low-frequency PSD peak around $\sim 0.05$~Hz is 15~R$_{\rm G}$ (see \citealt{Done2007}).  However, this radius may be even smaller for smaller $H/R$, which would make the disc truncation radius consistent with the results from fits to the iron line (this work, and \citealt{Reis2008,Reis2009}).  However, in the latter case the corona would need to be very compact, or seed photon variations from intrinsic disc variability would modulate the power-law with a similar amplitude to the disc.  In either case, assuming the disc is thin and that it varies on the viscous time-scale, its inner radius must be relatively small.  Such a picture is very different from earlier models for the hard state, where the disc is highly truncated and power-law emission is produced by a very extended corona or ADAF (e.g. \citealt{Esin1997}).

\section{Conclusions}
\label{conc}

Spectral fits to observations of BHXRB sources in the hard state show increasing evidence for both power law and black body components. In this work we have explored the hard-state variability of two sources with known soft excesses, SWIFT~J1753.5-0127 and GX~339-4. Our findings are summarised below.

\begin{enumerate}[1.]
\item We have introduced a new spectral analysis technique, the covariance spectrum, which measures the correlated variability in different energy bands. This technique overcomes the problems of low signal-to-noise and bias associated with the rms spectrum and has smaller statistical errors.

\item PSDs of the two sources demonstrate larger low-frequency power in the soft band.

\item The longer time-scale (2.7-270~s) covariance spectra of both sources are softer than the short time-scale (0.1-4~s) covariance spectra, due to additional disc variability, i.e., extra disc variability occurs on longer time-scales without a concomitant rise in power law variability on such timescales. However, the coherence of the rms and covariance spectra show clearly that disc variations are not independent of the power law variations.

\item The strength of reflection features that are detected in the short time-scale covariance spectra of GX~339-4 are consistent with the observed blackbody variations on those time-scales being driven by thermal reprocessing of the power-law emission absorbed by the disc.  However,
the reflection covering fraction and iron line equivalent width show little change between short and long time-scales, implying that additional reprocessing, due to coronal geometry change, is not responsible for the additional blackbody variability seen on longer time-scales.

\item The extra blackbody variability seen on longer time-scales appears to be intrinsic to the accretion disc itself, giving rise to the extra low-frequency power in the PSD. This represents the first clear evidence that the low-frequency Lorentzian component in hard state PSDs is produced by disc variability.  Models invoking damped mass accretion rate variations or oscillations in the disc truncation radius can satisfactorily explain the observed pattern of variability.

\item The implication of such variations occurring in a thin disc on viscous timescales, is that the disc truncation radius is $<20$~R$_{\rm G}$.

\end{enumerate}

This work highlights the importance of measuring spectral variability on a range of time-scales. Mean spectra, which describe the average properties of a source, provide no information on how different spectral components are related to one another as a function of time. By using the covariance spectra we have been able to disentangle the correlated spectral components in these two sources, identify thermal reprocessing as the mechanism by which variability is correlated in different bands, produce model-independent evidence for additional blackbody variability on longer time-scales and therefore associate intrinsic disc variability with the low frequency Lorentzian feature seen in hard-state PSDs.

\section*{Acknowledgments}
We would like to thank Beike Hiemstra and the anonymous referee for useful comments. We are grateful to Maria D\'{i}az Trigo for providing the GX 339-4 EPIC-pn events files and helpful advice.  TW is supported by an STFC postgraduate studentship grant, and PU is supported by an STFC Advanced Fellowship.  This research has made use of data obtained from the High Energy Astrophysics Science Archive Research Center (HEASARC), provided by NASA's Goddard Space Flight Center, and also made use of NASA's Astrophysics Data System.

redpajama_set_name: RedPajamaArXiv


Wait, you're only 5'4"? Are you sure?
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I seriously did a double take to make sure I read that right. You're an Amazon Shelby!
It happened again. Someone asked me if I was 5'7". How is this possible?


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text:
LIVE Khmer Morning News
Cambodia-China Joint Army Drill Kicks Off, As US Military Relations Cool
Aun Chhengpor
Cambodia's Deputy Prime Minister and Defence Minister Tea Banh (2nd R) inspects tanks inside the Army Institute after a graduation ceremony at Army Institute in Kampong Speu province March 12, 2015.
Hundreds of soldiers begin a 15-day joint exercise involving live-fire rocket launches, mock tank battles and anti-terrorism training, while Cambodia snubbed a planned U.S. joint exercise.
Hundreds of Cambodian and Chinese soldiers began a 15-day joint military exercise in central Cambodia this week, involving live-fire rocket launches from helicopters, mock tank battles, and anti-terrorism and emergency relief training. China will reportedly also donate tanks and armored personnel carriers on the occasion.
The unprecedented show of military cooperation - dubbed 'Golden Dragon' - is the latest sign that the long-ruling Cambodian People's Party (CPP) is relying on Beijing to shore up its iron-fisted control of the country through growing diplomatic, economic and military support, according to analysts.
They say increased Chinese military support will also aid the Cambodia Army's balance of power with its neighbors. But some warn that Cambodia's suspension of planned joint military exercises with the U.S. military last year signals Phnom Penh's growing divide with the United States and its regional allies, and other Asian countries that seek to counter China's aspirations for regional primacy.
Guaranteeing Internal Security
"Cambodia's decision to bandwagon with China is aimed at insulating itself from Western pressures to maintain a liberal multiparty-democracy and to respect human rights. Cambodia knows that if it hews to China's line there will be little or no interference in its domestic political affairs," said Carlyle Thayer, a Southeast Asia expert at the Australian Defense Force Academy.
"China provides the training and material assistance to the Royal Cambodian Armed Forces necessary for it to defend Cambodia's borders and, if called upon, to guarantee internal security," he said, adding that Prime Minister Hun Sen likely considers a Cambodian officer corps trained by China as more loyal to him than U.S.-trained officers.
In 2015, the CPP made some 80 senior army and police commanders members of the party's large Central Committee to ensure loyalty of the security forces ahead of the general elections in July, according to Human Rights Watch, and some commanders have openly threatened violence against the opposition. Hun Sen's two sons - who both received U.S. military officer training - have also been placed in top positions in the army.
Hun Manet, the premier's eldest son and a senior general in the army talks to journalists during a sports tournament of the Royal Cambodian Armed Forces, January 5, 2017. (Kann Vicheika/VOA Khmer)
Last year, the CPP closed the door on Cambodia's two-decade-long, faltering experiment with human-rights respecting, multi-party democracy supported by Western donors. In November, the opposition Cambodia National Rescue Party (CNRP) was dissolved and its leader jailed on treason charges, while a harsh crackdown on independent media and civil society was launched.
Critics say the CPP appears eager to avoid a repeat of the 2013 elections when it narrowly beat the CNRP in a disputed vote, which prompted opposition protests that were crushed by security forces.
Balancing Military Power with Neighbors
First conducted in 2016, the Cambodian-Chinese joint exercises will be held in Kompong Speu Province with the largest number of soldiers yet – 280 Cambodian and 190 Chinese soldiers. Up to 100 Chinese tanks and armored personnel carriers used in the drills will be gifted to Cambodia afterward, the CPP-affiliated newspaper The Khmer Times reported.
Cambodia's defense and internal security expense makes up around 16 percent of the national budget, at close to $973 million, and has risen with an annual 15 percent in the past three years, according to the Finance Ministry figures. In recent years, China has been the main source of arms - through sales or donations – while also training and funding the Cambodian military.
The continued provision of Chinese military support is likely to make Cambodia's army feel more secure in its dealings with its much more powerful neighbors Thailand and Vietnam, said Chheang Vannarith, a current research associate with the Singapore-based ISEAS–Yusof Ishak Institute, who has advised Cambodia's Ministry of Defense in the past.
Though neighborly relations are generally cordial, violent border disputes have erupted with Thailand over the border-hugging Preah Vihear Temple in 2008-2011. Vietnam has a complicated relationship with Cambodia, having invaded to oust the China-backed, Maoist Khmer Rouge regime in 1979 and to install a new communist party elite that continues to rule until today as the CPP.
Complicating Cambodia's Regional Relations
Experts said Cambodia's tightening embrace with China, expanded with growing military cooperation, effectively puts it on the side of Beijing on contentious regional political issues. This could have repercussions for its international relations, but that is a price Phnom Penh appears willing to pay.
"In Cambodia's view China's militarization of the South China Sea demonstrates that China will soon be the dominant military power in the region and all other countries will have to acknowledge this fact," said Thayer.
A Chinese army advisor (C) puts rank on Cambodian army graduates during a graduation ceremony at Army Institute in Kampong Speu province March 12, 2015.
Vietnam and several regional countries, including the Philippines and Malaysia, seek to counter China's territorial claims in the South China Sea. The U.S. and its close allies, such as Japan, are also attempting to contain Beijing's ambitions at greater regional control.
"In Cambodia's calculation, it is accruing favor in Beijing because of its support (in the South China Sea dispute). And Cambodia might one day have to call in a favor from China in the event of conflict with another country, either regional or extra-regional," said Thayer.
He added, however, that China's expanding "military diplomacy" was not limited to Cambodia, as "China has military ties will all ASEAN members that vary in scope and depth".
Chheang Vannarith said Vietnam wants to maintain its close historical ties with the Cambodian leadership and is likely concerned by China's growing influence on the CPP government.
Both countries, he said, seek "dominance" in Cambodia, adding that, "In Cambodia's foreign policy under the current ruling regime, there can't be any exclusion of either Vietnam or China."
Gen. Chhum Socheat, spokesman of the Cambodia's Defense Ministry, denied that Chinese military support further consolidates Beijing's influence in Cambodia and affects its foreign policy.
"The military aid from the People's Republic of China to the Royal Cambodian Armed Forces comes with no strings attached and no conditions. They assist us sincerely to strengthen and train the RCAF forces to higher capabilities in the tasks of national defense," he told VOA.
The Chinese Embassy in Phnom Penh did not reply to VOA's request for comment on the joint exercises by time of publication.
During a visit to Cambodia by Chinese Prime Minister Li Keqiang in January, a joint communiqué highlighted China's "willingness to provide necessary assistance to Cambodia in maintaining stability, realizing development and improving people's livelihood."
US Military Relations Sour
Relations with the U.S. Army, meanwhile, have soured as the Hun Sen government increasingly relies on Beijing's support and dissolved all democratic opposition.
Last year, Cambodia suspended the joint military exercise with the U.S. Army, Angkor Sentinel, which was due to have been held for the eighth year in a row, as well as a long-running U.S. Navy program that provided humanitarian assistance in the country. Cambodia said its forces were too busy to join the annual exercise.
Following Cambodia's wave of repression last year, Washington responded by ending several programs benefiting the government and the army.
The U.S. Embassy in Phnom Penh said in February that military-to-military support was being reduced as "senior leaders within the Cambodian military have made troubling statements about using violence in relation to elections." Though it added that cooperation continues for emergency relief preparedness, officer training and U.N. peace-keeping training.
An annual U.S. government report released this month, called the Worldwide Threat Assessment of the U.S. Intelligence Community, warned that Southeast Asian countries "will struggle to preserve foreign policy autonomy in the face of Chinese economic and diplomatic coercion."
FILE: Riot police block a street near the Supreme Court in Phnom Penh, Cambodia, Tuesday, Oct. 31, 2017. The Supreme Court on Tuesday uphold the lower court's decision to continue to detain opposition leader Kem Sokha who has been charged with treason, the latest in a series of moves to gain an advantage ahead of next year's general election. (AP Photo/Heng Sinith)
Pointing to the recent crackdown in Cambodia, it said, "Having alienated Western partners, Hun Sen will rely on Beijing's political and financial support, drawing Cambodia closer to China as a result."
Former CNRP leader Sam Rainsy claimed in an interview with The Australian newspaper last month that the U.S. and other countries seeking to contain China's aspirations at regional dominance should be worried by developments in Cambodia.
"China is securing more and more facilities, including military bases in Cambodia," said Rainsy, who is in self-imposed exile as he faces charges in Cambodia. "This will strategically affect Japan, Vietnam, Australia and India. Australia should feel concerned because this could disrupt the balance of power in the whole region."
Asked by VOA about the claims, Gen. Chum Socheat denied that China was securing military bases in Cambodia, saying, "Our constitution does not permit it."
Hun Sen Rejects Fears Over Alleged 'Chinese Mafia' Inroads in Coastal Province
US Tariffs Spark Fears of Trade Conflict in Asia
With CARI Act, US Senators Hope to Fight Chinese Influence in Cambodia
Analysts Concerned Over Chance of Further Sanctions After US Aid Cut
Cambodian Activists Plan to Protest Hun Sen's Visit to Australia

redpajama_set_name: RedPajamaCommonCrawl


text:
The rise and fall of the Sony empire
By Ray Walters on December 31, 2011 at 9:36 am
In 2001, Sony had become a massive conglomerate of largely unrelated divisions. While on paper owning a movie company along with a music production business looks like it makes sense, for Sony it was a different matter. By acquiring several different companies, it created corporate bloat at its finest. Politics and bureaucracy crippled communication and formed factions between the different areas of the company, stifling innovation. Case in point is the fact that Sony was working on its own MP3 version of the Walkman, and would have beat Apple to the punch, except for the fact that some of the different labs inside Sony that were working on development had never even met in person. What was once a focused, innovative brand had become a quagmire of corporate red tape and politics.
Currently, Sony's most profitable branch isn't its electronics division, but its financial side. Simply put, the company makes more money selling life insurance than it does electronics. While not entirely unusual, this fact is an indicator of the three elements that Sony once possessed and is now missing: vision, innovation, and brand focus.
To regain any semblance of its former glory, Sony will have to take some decisive actions:
Howard Stringer, Sony's CEO, will need to be replaced with someone who understands current and future market trends, and be able to cast vision for capitalizing on the ever-changing playing field that Sony is part of.
Take a hard look at the conglomerate that Sony has become and sell off those divisions that are neither profitable nor relevant to the vision mentioned above.
Bring the sexy back to the Walkman brand. Sony has taken what can arguably called the most famous brand name in the history of electronics and slapped it onto any device that is portable. This title should be reserved for a flagship device that seeks to change the way that users consume media like the Walkman did. It should not be the catch-all category that it is now.
Using the the flagship mentioned above, bring unity to the line of devices that allows a person to say "That's a Sony" when they see it. A good example is the NEX line of digital cameras that Sony offers. One look is all it takes for a camera savvy consumer to know that the device that someone is holding is a mirrorless NEX camera. The lineup of Sony devices should be a progression of mouthwatering must-haves for the technophile, not a listing of total "meh." The devices should build off each other in a way that not only makes sense but offers enhanced functionality for users.
Speaking of enhanced functionality, Sony will need to strengthen the PS3 as a media platform to deliver paid content to customers. For the first time since its release, PS3 sales are neck and neck with the Xbox 360. The PS3 has a better media experience out of the box than the 360 does, so why hasn't Sony been pushing that fact at every opportunity? Take care of the network hack issues, strengthen the choices of streaming content (which are already good to begin with) and enact an aggressive campaign to increase the residual income the device brings in. Having a Blu-ray player built into the system is great, but the format is going to eventually lose out to the ever increasing popularity of watching media online. If Sony wants to make even more of a splash, tie the new groundbreaking Walkman device into the PS3 in a way that is actually useful.
Watching the slow, painful decline that Sony has been experiencing over the past fifteen years has been akin to witnessing a loved gadget fade into obsolescence. As a former enthusiast for Sony products, I long for the days when buying a Trinitron television — even though it was more expensive than rest — guaranteed I was getting the best set on the market. For Sony to return to profitability it needs to find a visionary leader (it's not Howard Stringer, believe me) that will "unite the clans" of Sony, thus enabling innovation to once again rule the day in the company. Until this happens, the future of Sony is very much in doubt — but if all else fails, it could always start selling cheap car insurance like Geico.


It was such a nice way to end off 2012 by visiting the Haghani and Libman families to photograph mom, dad with their brand new addition. Both families were so great to work with and it is always so nice to meet and to be a part of a family's first ever professional photo session. Wishing both families all the best in 2013 and we can only imagine all the amazing changes and experiences that the new year will offer!


Denise Fenzi has competed in a wide range of dog sports – titling dogs in obedience (AKC and UKC), tracking (AKC and schutzhund), schutzhund (USA), mondioring (MRSA), herding (AKC), conformation (AKC), and agility (AKC). She is best known for her flashy and precise obedience work – as demonstrated by two AKC OTCH dogs and perfect scores in both schutzhund and mondio ringsport obedience.
While a successful competitor, Denise's real passion lies in training dogs and solving the problems that her own dogs and her student's dogs present. She is a recognized expert in developing drive, motivation, and focus in competition dogs, and is known internationally as an engaging speaker and an expert in no force training for sport dogs. She has consistently demonstrated the ability to train and compete with dogs using motivational methods in sports where compulsion is the norm.
In addition to training and speaking, Denise is a prolific writer. You can find her at www.denisefenzi.com where she maintains an active blog on all things related to dog training. She is also an active writer on facebook; follow her there to learn more about her range of interests in addition to dog training. Denise and Deb Jones have recently finished a four book series, "Dog Sports Skills" which has received widespread acclaim in the dog sports community. In addition, she has written numerous books on her own, including "Train the Dog in Front of You," "Beyond the Back Yard; Train Your Dog to Listen Anytime, Anywhere!" and, for the younger audience, "Blogger Dog, Brito!" Several of these books have won Maxwell awards for Best Training and Behavior book from the Dog Writers of America.
Denise thoughtfully and persistently works to break down the barriers that prevent people from obtaining a truly interactive and mutually enjoyable sport relationship with their dogs. Fenzi Academy is the culmination of her efforts as a forward step in providing progressive information to any trainer who wishes to learn.


Raccoon Aromatherapy Diffuser – Naptime Aromatherapy Co.
Curiosity and fun are written all over the face of our Raccoon Diffuser.
Diffuse 100% pure, therapeutic grade essential oils or from our expanding Naptime Aromatherapy line.


[Bug Report] [Silent Hill 2] GSdx Screenshots have wrong height.
Resolved: [Bug Report] [Silent Hill 2] GSdx Screenshots have wrong height.
I should mention that this isn't a major or severe bug, but it should still be reported I guess.
I was taking some screenshots using the GSdx screenshot function (F8 while in-game). But then after checking on them, I noticed the height was wrong.
Instead of having 1920x1080, it was saved at 1920x521.
Instead of having 2560x1440, it was saved at 2560x695.
When GSdx is set to Native Res, the height is correct, but this obviously results in bad quality.
I think this might be related to an old bug with the game in previous versions of GSdx/PCSX2 where the screen would only show half of it while playing. This was fixed in later revisions, but it seems there's still a remnant of it somewhere when taking screen captures.
Back when that bug was around, it only affected NTSC versions of the game. PAL versions were fine afaik.
- No HW hacks were used in GSdx.
- Manual Gamefix applied: Enable SW Mode when an FMV plays (Should have no impact on this bug, but I went ahead and tested it with this fix turned off too, and the result was the same).
Right now I'm just using Bandicam to take screenshots instead, as I know of no other alternative to get around this.
Windows PrintScreen function works with PCSX2. Just press Print Screen(if in full screen) or ALT-PRINTSCREEN(if windowed mode). Then go to paint or whatever and CTRL-V it in. Of course Bandicam prolly works better for you(since with it you don't gotta drop out of the game to paste your screenshot into a program), just thought I'd mention this.
Yep, Bandicam is the better alternative for me atm.
I prefer the GSdx screenshot function though, because it takes screenshots at whatever your internal res is at, even if you're not playing in Fullscreen or if your monitor doesn't actually support said resolution. Not sure how complicated it is to fix this though.. I know rama was pretty involved with the old bug in SH2 if I remember right, so maybe he can shed some light on this possibly being fixed in the future.
could you try reproducing this issue with CRC hacks disabled in HW hacks settings ?
Just saw this post. Tried it with CRC hacks disabled, same result.
This is not an error pcsx2/GSdx internal scaling works correctly.
Try this you lose then just two or four pixels.
But I do not understand why the system cuts (Cropping) the images before they are saved.
Here are two examples of how Biohazard 4 is scaled correctly under 4K.
Ryudo: Is the Issue still present on the latest development build ?
I checked out this issue with the PAL version and didn't manage to reproduce it. I tried a slightly newer dev build than the one in the OP from late 2014 and one of the latest 2016 dev builds , but all screenshots were saved at the height I selected in-game.


text:
Healthcare Industry News: ExtraCorporeal Circulation
Devices Group Purchasing
MAQUET Cardiovascular Awarded Three-Year Contract From Novation for Cardiopulmonary Products Used in Cardiac Surgery
WAYNE, N.J., Dec. 11 -- (Healthcare Sales & Marketing Network) -- MAQUET Cardiovascular LLC, a leading provider of cardiovascular technologies, announced today that it has signed a three-year contract with Novation, the industry's leading supply contracting company, to provide all of its cardiopulmonary (perfusion) products to the members of VHA Inc., University HealthSystem Consortium (UHC) and Provista. The agreement becomes effective on January 1, 2010, and runs through December 31, 2012. MAQUET Cardiovascular's cardiopulmonary products are used in on-pump cardiac surgery and include heart-lung machines, the QUADROX-i family of generators, the ROTAFLOW Centrifugal Pump, the MECC (Minimized ExtraCorporeal Circulation) System, the PLEGIOX Cardioplegia Heat Exchanger, standard or customized tubing packs and a full line of adult, pediatric and ECMO cannulae.
"This agreement represents an important milestone for MAQUET Cardiovascular as it is our first GPO contract for cardiopulmonary products in the United States and underscores the value of our products to surgeons and perfusionists," said Raoul Quintero, President of MAQUET Cardiovascular U.S. Sales LLC. "We are committed to supporting positive patient outcomes and are pleased that members will now have access to our full range of innovative perfusion products, as well as our surgical devices for beating heart cardiac surgery and our market-leading VASOVIEW Endoscopic Vessel Harvesting (EVH) Systems through two contracts we signed with Novation previously."
"Novation continues to provide members of VHA, UHC and Provista with the most advanced technology, best customer service and preferred pricing. We found that MAQUET Cardiovascular's cardiopulmonary product portfolio met the requirements of our rigorous contracting review process," said Scott Crandall, Senior Director, Contract Services Cardiology at Novation. "We are pleased that this is the third agreement we have signed this year with MAQUET Cardiovascular."
About Novation
Founded in 1998, Novation is the leading health care supply contracting company for more than 25,000 members of VHA Inc. and the University HealthSystem Consortium (UHC), two national health care alliances and nearly 15,000 members of Provista, LLC. Novation offers its customers contract development and management, supply chain data and measurement, and industry knowledge and advocacy. Based in Irving, Texas, Novation develops and manages competitive contracts with more than 500 suppliers. VHA, UHC and Provista members used Novation contracts to purchased nearly $35.7 billion in 2008.
About MAQUET Cardiovascular
MAQUET Cardiovascular is a leader in providing innovative products for cardiac surgery, vascular intervention and cardiac support to hospitals and clinics and the cardiac surgeons, interventional cardiologists, perfusionists and other healthcare professionals who care for patients with cardiovascular disease. MAQUET Cardiovascular is focused on providing clinicians with future-oriented technology that fits into their daily practice and that improves the therapeutic management of patients. MAQUET Cardiovascular continues to invest in the development of innovative technologies and solutions that advance clinical practice, improve patient outcomes and enhance quality of life.
MAQUET Cardiovascular was formed in 2003 when MAQUET combined its existing Cardiopulmonary business with Jostra's equipment and consumables for open heart surgery and Siemens Life Support Systems that GETINGE acquired in 2003. In 2008, it added the Cardiac Surgery and Vascular Interventions businesses that GETINGE acquired from Boston Scientific and Guidant in 2008. In 2009, it added the cardiac assist businesses that GETINGE acquired from Datascope. MAQUET Cardiovascular provides healthcare professionals with products in four business units: Cardiopulmonary (perfusion products), Cardiac Surgery (clampless beating heart and endoscopic vessel harvesting), Vascular Interventions (vascular surgery products), and Cardiac Assist (intra-aortic balloon counterpulsation therapy).
About MAQUET
The MAQUET Group is the global market leader for Medical Systems, focusing on the Operating Room (OR) and Intensive Care Unit (ICU). The integrated products of MAQUET are specially designed to deliver optimal clinical treatment and therapy concepts within acute care hospitals. MAQUET provides innovative medical solutions from three divisions:
Cardiovascular with products for cardiac assist (intra-aortic balloon counterpulsation therapy), coronary artery bypass surgery, aneurysm and vascular repair, peripheral interventions and ExtraCorporeal Circulation.
Critical Care for intensive care ventilators and anesthesia machines.
Surgical Workplaces for OR tables, lights and ceiling service units, prefabricated OR and ICU suites, as well as telemedicine for the OR integration.
MAQUET is a subsidiary of the publicly-listed Swedish GETINGE GROUP, a company with over $2.8 billion in revenues (2008 fiscal year) and 12,800 employees worldwide. In 2008 MAQUET itself generated pro-forma revenues (including the acquisition of Datascope Corp.) of over $1.4 billion. The company now has 5,000 employees in 35 international sales and service organizations, as well as a network of more than 200 sales representatives.
www.maquet.com
www.getingegroup.com
MAQUET - The Gold Standard.
Source: MAQUET Cardiovascular
Search: MAQUET Cardiovascular
Search: Novation
Search: perfusion
Search: cardiopulmonary


text:
The Food Judge
Food miscellanies
oldie-friendly
Home » ★★★★☆ » Park Chinois. Put on your dancing shoes.
Park Chinois. Put on your dancing shoes.
Posted by Nicky Richmond on December 9, 2015 in ★★★★☆, food, oldie-friendly | Leave a comment
"Park Chinois occupies a niche, and offers a balance to the current club culture. It brings about a rebirth of the Dinner Dance aesthetic, a modern interpretation underpinned by old school values." Website: Park Chinois
One of the more creative of our serial restaurateurs, Alan Yau has for this, his latest venture, chosen to target the much-moneyed Mayfair crowd and it looks like he's using old Shanghai as his reference point. In the dripping Golden Triangle bounded by 5 Hertford Street, The Arts Club and Novikov comes Park Chinois, doing a me too to the itinerant rich who frequent this particular part of Mayfair.
1930s Shanghai, the "wickedest city in the world" the Paris of the East, was a melting pot of ex-pat French, White Russians, Brits and Americans, famous for its opium dens, organised crime and cross-cultural cabaret lifestyle.
Much of Shanghai was a French Concession, governed and occupied by France until 1943. Maybe that's why this is called Park Chinois, in a nod to history. Certainly the French influence can be seen in the décor, though I'd say it's more bordello Rococo than Parisian elegance. There's a lot of gilt, red and cream, crushed silk, plump cushions, soft velvets and lush colourful fabrics, gorgeously rendered. It's a land of plenty and it's plenty full for a middling Sunday night in December.
Liveried footmen usher you in through the heavy doors to a plush, richly decorated hallway, where you are instantly overheated by a roaring coal fire. Through the red doors, above which a sign announces "on air", you enter a lost world, a world of many white-coated waiters and heavily made-up women in glittery clothing. I fail to notice, towards the rear, a stage of sorts, with spotlights and musical instruments, as I am whisked to the left hand side of the room where I have no choice but to sit side-by-side with C.
I am assuming that the table has been laid out thus because the space is too narrow for a waiter to get through. The tables in this section are circular and the wrong shape and size for side-to-side dining. One would, if one were not insistent upon moving, have to spend the meal contorting one's self towards one's partner and sitting on one's side bottom to reach the food whilst conducting a conversation face to face instead of cheek to cheek.
C has just had four back injections so doing the table-twist isn't on the cards. We move to Siberia, bottom right, next to a set of drums. I do not need to look at C's face although I am now able to see it full-on and I am thinking that perhaps the move was a mistake. Because I don't read reviews before I go to new restaurants, I have no idea that live performance is part of the deal. Tip: if you are seated next to the drums understand that you will not be having any conversation during the performance. Married, fine, date, not great.
Without this being any sort of surprise we are offered, in that time-honoured way of restaurants on the hard-sell, a glass of champagne. I bristle and go for a perfectly serviceable 125ml glass of Crozes Hermitage for £9.50 instead. They charge £5 for fizzy water.
We consider duck but see that it costs £75 and takes 45 minutes and is recommended to be eaten with caviar, ranging in price from £85 to £280 for a 50g serving. Mayfair = caviar and I am told that it is ordered by wealthy Chinese and that duck and caviar is a thing. Not in my world. To me it's gilding the lily; also I didn't think to take out a bank loan before I came out to dinner.
Instead, we go for an old faithful, salt and pepper squid, served with papaya (£18). It comes breaded, not in the traditional batter, the papaya matchsticks too thickly cut. All Thai'd up with lime leaf, the seasoning and spicing is good. Had they shredded and bashed the papaya, this would have been perfect.
Bang bang chicken, (£19) another classic dish, is not the usual cold shredded chicken and a dollop of sesame dressing on top, but instead is a salad of warm crisp chicken below a mixed salad and cubes of puffed rice. A little more sesame would not have gone amiss, but this was an interesting take on a classic dish and again good, if you forget about the classic version.
Wok-fried crispy chicken is a take on Peking duck – the skin of the whole chicken with a small layer of chicken meat beneath, finished to a deep red glaze and laid out on the plate like a lobster, Served with two dipping accompaniments, this is gorgeous but at £35, somewhat high on the oh my God scale of charging.
Not sure whether to order the Park Carbonara with Inaniwa udon, sea urchin, 65 degree organic egg and pancetta (£32) I'm glad we do as this turns out to be the best dish of the evening. Capturing the essence of your classic carbonara, but with a Japanese twist, the sea urchin gives it an umami hit, the soft noodles coated in creaminess, altogether a silken, unctuous, gooey, rich plate of joy.
Whole Dover sole (£42) was deep-fried, overpowered by the garlic and spring onion and slightly dry. Don't.
Also a disappointment was the spaghetti squash, morels, pumpkin and girolles, (£15) a gloopy unattractive dish, full of overcooked chunks of squash, tasting of little. The morels were without flavour. More work needed.
The desserts were much more than an afterthought and I very much hope that someone will want to help me work through the hot chocolate menu – the Anaesthetic Sensation, with its hit of Sichuan pepper looks particularly inviting.
The citrus and meringue concoction (£9.50) was intense to the border of too much but I liked it. The rum-soaked pineapple with liquorice ice-cream (£10:50) was so alcoholic it needed a warning. I'm not complaining, mind. Not a dessert for anyone in AA.
On our way out we asked about downstairs and the marvellous Maitre d' gave us a sneak peek. It's a stunning space, a proper dance hall, all glitz and glamour, with a private room to the side all decked out in red velvet; inviting and louche. I can't see myself popping in there after work though.
Alan Yau says that he wants to recreate the era of dinner dancing as a "balance to current club culture" but I'm not sure what he means by that. In his 'hood there is already The Arts Club and 5 Hertford Street, both of which (member-only) clubs have dancing and I think Mr Yau has his work cut out to fill this 15,000 sq ft space night after night. I worry that he may have overestimated the market for dinner-dance amongst the botox brigade.
I hope he does something more casual with the Automat premises, not yet open, so I can go and just eat the food which is mostly good and sometimes excellent. It's a big gamble, but then, that's true to the spirit of old Shanghai, is it not?
Salt and pepper squid Thai style
Not a lobster
Sad spaghetti squash
Entranced by the entrance
For Dancing Queens
← Sexy Fish. Wear your best trout pout. Taking a journey on the Darjeeling Express. Making a difference. →
Eccentric elegance. Sybaritic sustainability. Worton. February 28, 2020
Texture. Let it snow. February 7, 2020
Indian Accent. Halloween haven. November 1, 2018
She's not dead, she's just resting. September 22, 2018
Parsons. On the nose. January 16, 2018
Bouillon Bilk December 28, 2017
Under the influencer? Be honest. December 22, 2017
When in Rome. Or not, if you are me. November 20, 2017
Dad, food and me. August 9, 2017
Jikoni. Coming in from the cold. April 28, 2017
It's been a while. April 26, 2017
Weighing myself. December 3, 2016
And so it starts. Not a restaurant review. December 3, 2016
Burgundy, reloaded. September 14, 2016
What Nicky does next. September 11, 2016
Hedone. He done good. Very good. August 19, 2016
Blandford Comptoir. August 3, 2016
Sosharu. Atherton goes further east than the City. July 31, 2016
Bonhams. July 25, 2016
The Marksman. Right on target. July 7, 2016
Bacco. A mid-town Italian adventure. June 9, 2016
Loch Bay and other stories. The Isle of Skye. June 2, 2016
Six Portland Road. It's the real thing. May 28, 2016
Something for the weekend? The joy of Bristol's bistros. May 20, 2016
Coya. Peruvian/Japanese Roka-style mashup. May 13, 2016
A Jewel in The Crown at Burchetts Green. May 2, 2016
Pitt Cue. Sheer piggery. April 27, 2016
45 Jermyn Street. The Fountain Room gets a facelift. April 13, 2016
Ellory. Doesn't quite live up to the name. April 2, 2016
Noble Rot. An affair to remember. March 25, 2016


text:
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">

<title>Source code</title>
<link rel="stylesheet" type="text/css" href="../../../../../../../stylesheet.css" title="Style">

001
018
019package org.apache.hadoop.io.serializer.avro;
020
021import org.apache.hadoop.classification.InterfaceAudience;
022import org.apache.hadoop.classification.InterfaceStability;
023
024/**
025 * Tag interface for Avro 'reflect' serializable classes. Classes implementing
026 * this interface can be serialized/deserialized using
027 * {@link AvroReflectSerialization}.
028 */
029@InterfaceAudience.Public
030@InterfaceStability.Evolving
031public interface AvroReflectSerializable {
032
033}

redpajama_set_name: RedPajamaGithub


text:
Exit Completed: company sold its business/assets or its part of the business to a local partner and leaved the market
Exited Exit Completed
Nvidia is an American multinational technology company. It designs graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip units (SoCs) for the mobile computing and automotive market.
The Moscow laboratory of the company was one of the 4 largest data centers of the company, and it accounted for up to 70% of all games tested by the company. The office engineers take part in many global projects of the company, focusing on the development and development of the software component of solutions for the gaming and professional markets, including the AI market.
Nvidia had already suspended shipments to Russia but kept a presence there "to support our employees and their families," the company said in a statement Monday, 3 October 2022. Now it is "ceasing all activities" in the country, Nvidia said. Nvidia has officially left Russia, follows from its reporting for the third quarter of 2022. It has been working in Russia since 2003.
October 30, 2022 Nvidia has officially left Russia, follows from its reporting for the third quarter of 2022.
November 21, 2022 Nvidia has officially left Russia, follows from its reporting for the third quarter of 2022. It has been working in Russia since 2003.
July 01, 2022 Nvidia has stopped continuing to sell gaming software licenses in the Russian Federation - mass media
March 06, 2022 Nvidia stopped working in Russia
March 08, 2022 Nvidia suspends all sales to Russia, joining AMD and Intel
May 26, 2022 Nvidia CEO names 2 big challenges after disappointing guidance
March 05, 2022 NVIDIA Stops Sales In Russia According To Spokesperson