text:
Why Ezekiel Elliott Is Gonna Play Out This Season
Suspension on, suspension off, suspension on, suspension off - that's been the crazy timeline in a domestic violence disciplinary process that has rocked football and our court system. Being that Ezekiel Elliott's guilt or innocence is not being judged in a case that's become about whether the NFL's arbitration process is fair, football fans, and especially those fantasy fans all appear to just wanna know two things, 1. is Zeke playing? 2. How long? The stars have aligned for Zeke in this crazy legal process. He miraculously got his suspension put on hold with an "injunction" (legal term for hold - see ya learned something) after his legal team filed in Texas before the arbitration process was even finished. The court of appeals fixed that by vacating that hold because it decided the team filed too early and suspension was back on. As Zeke's legal team scrambled to get another hold in a NY court, it just happened to be a bye week - lucky for Zeke cause it bought them time to file motion papers and about 111 exhibits (thousands of pages) in a NY court. Just so happens that the Judge assigned to the NY case was on vacation and the stand in Judge felt uncomfortable stepping on the other Judge's toes and making a full ruling on the NFLPA's request to put the suspension on hold. So, what did he do? He granted Zeke a temporary restraining order, putting suspension on hold for two weeks until the vacationing Judge returns (presumably all relaxed and tan). There will be a hearing on October 30th where the assigned Judge (a she named Kat - the Honorable) will decide whether to extend that hold until the case is heard and decided. If she says yes then it pretty much means he will play out the rest of this season. Why? Because there will be a discovery process, hearings, motions, potential trial and testimony which can take months and if not, then the NFLPA will easily use legal maneuvers to delay this through end of season. If you came to this site to get my expert opinion, here it is: there's no need to wait until October 30th to find out if he's gonna get that permanent injunction- he will. This means he will definitely play out this season. How do I know? Because the subbing Judge paved the way for that very result in two ways. First, the Judge who issued the temporary hold wrote in his opinion that Zeke met the standard for a temporary restraining order and then said that the standard is exactly the same for a permanent hold. The standard is quite simply the Judge asking himself this: If I don't put a hold on this suspension, will Zeke suffer irreparable harm (harm that can't be fixed through monetary compensation) and if I do grant the hold, will the NFL suffer irreparable harm? The Judge decided that Zeke would be harmed if he didn't stop the suspension because it would allow discipline before the court could decide if the NFL's arbitration process was fair. Judge said, the case hasn't been heard and there were sufficient and significant questions about the fairness of the League's arbitration process. If you've been following this case you know why, 1. there's evidence that league executives tried to hide its lead investigator's conclusion that Zeke shouldn't be suspended, 2. Zeke couldn't cross-examine his own accuser because she wasn't required to testify and 3. Neither was league commissioner Roger Goodell. So the Judge is saying, there's a legit case here and it needs to be heard by a court of law. The Judge decided Zeke would be harmed because he could never get the games back that he missed. He would miss out on individual achievements, team achievements, rushing yards (which could impact his title as League's leading rusher) and maybe even qualifying for the ProBowl. Further, the team would suffer as a result of him not playing. On the flip side, the Judge felt the NFL would not be harmed if he put a hold on Zeke's suspension because he could be suspended again at a future date if NFLPA loses the case. The NFL made a big mistake early in the process in Texas when it tried to appease a Judge (Amos Mazzant) and agreed to let Zeke play in the Giants game until the Judge issued a ruling. Well that concession sent a message that him playing while the court process played out wasn't a big deal to the NFL. Furthermore, he has been playing since the beginning of the season and the NFL hasn't been harmed. The NFL claimed it's harmed on the public perception front because it can't enforce its domestic violence policy, but the Judge didn't buy into that argument since it can be enforced with a future suspension. Next, and this is big...The Judge said in his opinion (as a wink wink to the other Judge) that the standard for a temporary restraining order is the same as a permanent injunction (which is true). Meaning this Judge is basically saying to the returning Judge, something like this, "well, if it were me I would grant it long term cause I already decided he met the standard." Judges like to respect each other, especially ones that are colleagues in the same courthouse. So the vacationing Judge will likely grant the permanent injunction. Even more important, the stand-in Judge put another layer of protection for Zeke by citing the Brady case as precedent for the fact that NY district courts recognize that athletes who miss games will suffer irreparable harm because they basically can never get back that opportunity to achieve in that game and it affects their entire career and legacy. It's not a loss that money can fix. This means he's saying to the returning Judge and even the appellate Judges, something like this, "listen, this is an established standard here...an athlete who has games on the line shouldn't be suspended until the case is heard when there's a there there." This takes the case beyond Zeke and means any future player who wants to challenge a league arbitration in NY can now more easily get a permanent injunction until the case is heard and decided, so long as there's a legitimate challenge to the arbitration process itself. No more preemptive suspensions by the NFL when a league decision is challenged in a court of law. Now suspensions should only take hold after the case is heard and if the NFL wins because the court decides the arbitration process complied with the CBA. This puts a big magnifying glass on the league and its arbitration process and provides a nice check on its arbitrators to make sure the process is legit or face a lengthy court review and a stop on the suspension. Finally, if you're wondering, what if the vacationing judge grants the permanent hold but then the NFL appeals like it did in Texas... I would tell you don't worry. In Texas, the court only overturned the hold because the NFLPA filed too early, before the NFL arbitrator issued his final decision. Here, if the NY court finds there is irreparable harm, a appeals court would rarely overturn it. It's clear that Zeke has a lot to lose if he's suspended and NFL's arguments on them being harmed are weak. Plus courts rarely overturn injunctions - the standard is usually that the lower court "abused its discretion" and trust me when I tell you we don't have that here. An appeals court also wouldn't want to interfere with precedent since Brady II justified irreparable harm showing on the same reasoning that Zeke got his. Put simply, NFL lucked out and had the Texas injunction overturned on a technicality, and that's not what we would have if the court gives him the permanent injunction on Oct. 30. Lastly, there are some questions about what if Zeke settles and accepts a shortened suspension? I can tell you that from the outset I was told by sources close to the case that he will not accept even one game and he wants to clear his name. Now there are rumors that there are settlement talks, and I'm hearing from my sources that those rumors are not in the least bit true. Odds are: Zeke plays this season and you can take that to the bank.


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text:
Q: Hibernate Query Language - right outer join So I have an object A
And an object B
A is related to B via A.x.y.id = B.p.id
I am joining on a bunch of other things for A
So the query looks like:
"select distinct(item), otherItem from A item, B otherThing ");
        "left join item.unrelatedThing unrelatedThing "
        "... a few more left joins, for a where clause that isn't important"
        " right outer join otherThing.p p with p.id = A.x.y.id");
The problem is this right outer only gets 3 items, when there are 15 items. If I make it a left join, it gets 15 items, but the B it returns is wholly unmatched to the A.

redpajama_set_name: RedPajamaStackExchange


text:
\section{Introduction}

The largest structures identified in galaxy redshift surveys are
located at distances comparable to the maximum distance at which
structures can be effectively distinguished.  In the CfA redshift
survey beyond the Great Wall not much structure is recognizable at all
(\citealt{geller89}). In the {\it Sloan Digital Sky Survey}
(SDSS)\footnote{http://www.sdss.org/}
the large galaxy filaments are discernible up to roughly $
500$\,Mpc, and the most prominent feature is the Sloan Great Wall
(\citealt{gott05}), found at a distance of $\sim 300$\,Mpc.

Larger structures could potentially be isolated in the quasar part
of the SDSS. Recently \citet{clowes12} report a group of $73$
quasars that span redshifts $1.17 - 1.37$. A total length of this
twisted filament exceeds $1200$\,Mpc. Although \citet{park12} have shown
that the largest structures found in the galaxy distribution are
consistent with the canonical $\Lambda$CDM model, it is plausible
that the quasar alignment could be discordant with this model.

It appears that the question of the large structures could be
addressed using the X-ray surveys.
Most of extragalactic X-ray sources are asociated with various
types of active galactic nuclei (AGN). Because of strong cosmic
evolution and a wide luminosity function, the AGN observed in
the selected flux range are
distributed within a very wide range of redshifts. Equivalently,
the observed source flux is only weakly correlated with the source
distance. Roughly $90$\% of the X-ray background in the
$0.5-2$\,keV energy band is generated by sources brighter than
$3\cdot 10^{-16}$\,erg\,s$^{-1}$cm$^{-2}$ (e.g.
\citealt{moretti03,lehmer12}). A majority of these sources are located at
cosmological distances: $80$\% in the redshift range $0.3 -
2.2$ (\citealt{soltan08}). The comoving radial
distance\footnote{Assuming
``737'' $\Lambda$CDM cosmology, i.e.
$H_o = 70$\,km\,s$^{-1}$\,Mpc$^{-1}$,
$\Omega_m = 0.3$, and $\Omega_\Lambda = 0.7$.}
between
redshifts $0.3$ and $2.2$ exceeds $4200$\,Mpc, thus sources
detected in a moderately deep {\em Chandra}\ observation are tracers
of the matter distribution on Gpc scales. One can hardly
expect fluctuations on this scale, but the present
analysis would be capable also of detecting variations on smaller scales,
although with decreasing sensitivity.

In the deepest {\em Chandra}\ exposures of $2$\,Ms CDF-N\
\citep{alexander03} and $4$\,Ms  CDF-S\ \hspace{-6pt}
\footnote{http://cxc.harvard.edu/cdo/cdfs.html.}
\citep{xue11}, several
hundred sources are detected. This allows the source distribution to be
investigated along the line of sight, provided the redshifts of
objects are known. However, to investigate large-scale matter
distribution, a transverse dimension of the survey should have a
comparable size to the radial one. In the present paper we explore
the possibility of analyzing the giant structures in the observable
Universe using a large number of the {\em Chandra}\ medium depth observations
scattered over the whole sky. Although a single pointing represents
a pencil-like cut through space, a set of several hundred pointings
to some extent act as a uniform all-sky survey.  The main objective
was to select all the pointings suitable for source detection from
the {\em Chandra}\ Data Archive, and then to construct an efficient
method of counting the sources in all the fields in a homogeneous way.
A number of sources in each field was used to estimate the amplitude
of the source counts, $N(S)$, at a fixed flux range around
$10^{-15}$\,erg\,s$^{-1}$cm$^{-2}$. A power law parametrization
of the $N(S)$
relationship was applied. Statistical characteristics of the
$N(S)$ amplitude variations are examined. Results, albeit
preliminary, demonstrate the strong and weak points of the method.
The volume of the archived {\em Chandra}\ observations is still too
small for a comprehensive study. Nevertheless, the presently
available data reveal the potential advantage of X-ray source counts
in investigations of the large-scale matter distribution.

The organization of the paper is as follows. In the next section,
selection and preparation of the observational data extracted from
the {\em Chandra}\ archives is described. Section~\ref{counts} gives
procedures for estimating the amplitude of the number source counts,
$N(S)$. We apply two independent methods to determine the
counts in two separate flux levels. Results of these
calculations, as well as statistical and (possible) systematic
errors are discussed in Sect.~\ref{correlations}. In
Sect.~\ref{variance} we concentrate on the question of
counts fluctuations
that allowed us to estimate the amplitude of the cosmic variance.
The main conclusions are summarized in Sect.~\ref{discussion}.

\section{Selection of observational material \label{selection}}

\begin{figure}
\resizebox{\hsize}{!}{\includegraphics{polar_N_n.ps}}

\caption{The distribution of $190$ pointings in the northern
galactic hemisphere. Two circles represent galactic latitudes  $b
= 30^\circ$ and $b = 60^\circ$. Each observation covers a circle
of $15$\,arcmin in diameter.  Labels close to some points in the
map denote the actual number of pointings in the area.  Symbol
sizes are not to scale, and even in the crowded areas, the
pointings do not necessarily overlap.}

\label{polar_n}
\end{figure}

Although the total number of the CXO observations now exceeds
$10000$, only a small fraction of pointings is suitable for the
present project. The
number of pointings in ACIS-I configuration longer than
$30$\,ks was equal to $963$ (as for 2012-10-02). Of these $599$ were
located at $|b| > 25$\,deg. Since we are mostly interested in the
fields at high galactic latitudes, without the dominating extended
source, the list of usable data was reduced substantially. In
this step we rejected the pointings at: M87, M33, LMC, SMC, many
Abell clusters (but not all), and the NGC galaxies.
Additionally,  it is desirable to have pointings scattered over the
large area rather than superimposed one onto another or closely
packed. Unfortunately, to some degree the pointings in the CXO
Archive have been accumulated under the opposite criteria.
The archive contains many observations
of nearby galaxies and clusters of galaxies, as well as a large
number of local sources close to the Galactic plane. Also, several
pointings cover the same area (e.g. {\em Chandra}\ Deep
Fields).

The {\em Chandra}\ Data Archive has been searched for all the ACIS-I
observations at high galactic latitudes with the exposure time
above $30$\,ks. Originally, a selection limit of $|b| > 30^\circ$
has been applied for both hemispheres. Then, only having a few
adequate pointings, we searched for more  observations in a
belt of $25^\circ < b < 30^\circ$ in the southern galactic
hemisphere. Eventually, within this extension just few pointings
satisfied all the selection criteria and were included
in the final set of data.

All the ``interesting''
observations were handled through the standard data processing
pipelines at the {\em Chandra}\ X-ray Center\footnote{See the
{\it Chandra Interactive Analysis of Observations} (CIAO) at
http://asc.harvard.edu/ciao.}. Each observation was carefully
inspected for its usefulness for the present investigation.
In particular,
pointings with an xtended source filling substantial fraction
of the field were removed. If the
extended source occupied a relatively small fraction of the field
of view, a section with the source was cut off, and the remaining
data unaffected by the extended emission were used.  Fields
with extremely strong point sources were treated in a similar
way; i.e., only areas affected by linear smearing generated during a
readout were removed.  All the exposures were examined for the
presence of the background flares and only ``good time intervals''
(GTI) were used. Because of a severe deterioration in the image
quality with the increasing off-axis angle, the search for sources was
limited to the circular area of $7.5$\,arcmin radius centered on
chips $0-3$.

\begin{figure}
\resizebox{\hsize}{!}{\includegraphics{polar_S_n.ps}}
\caption{Same as Fig~\ref{polar_n} for $112$ pointings in the
southern galactic hemisphere. A few pointings within
$-30^\circ < b < -28^\circ$ have been included to improve
statistics.}
\label{polar_s}
\end{figure}

Restrictive criteria of the field selection led to elimination
of $~\sim 96$\% of pointings in the CXO Archive. The almost
$400$ observations that remain constitute a sample that is still
numerous enough to make the data processing a painful and
time-consuming operation. Since we are more interested in observations
covering many different directions rather than a single spot in the
sky, we removed some CDF-S\ and CDF-N\ pointings from our sample.
However, we intentionally left several dozen observations in these
areas to facilitate the error analysis (see below). Eventually,
more than $300$ individual pointings were qualified for the
analysis. Their spatial distribution is highly nonrandom.
Concentrations on various angular scales, as well as a strong
asymmetry between galactic hemispheres is present.

The sky distribution of all the pointings is presented in the polar
equal area projection in Figs.~\ref{polar_n} and \ref{polar_s} for
the northern and southern galactic hemispheres (NGH and SGH, respectively).
Numerals close to some dots denote the numbers of pointings concentrated
in the marked areas. In the NGH, $190$ pointings were selected
for further processing, and $112$ in the SGH.  Symbols in
figures strongly exceed the actual extent in size of the individual
observation. Thus, in some cases where several pointings are
represented by a single dot, the pointings do not always overlap. A
detailed discussion of the statistical properties of the selected
material is presented in Sect.~\ref{correlations}.

The data in a ``canonical'' soft energy band of $0.5-2$\,keV
were used. For various reasons, both the exposure time and
sensitivity are highly variable functions of the position within the
field of view. To reduce the effects of sensitivity variations, low
sensitivity areas have been delineated using the {\em Chandra}\
effective exposure map\footnote{An exposure map is generated in a
standard data processing. It is a position-dependent product of
the effective area of the mirror/detector combination and the
effective exposure time [in cm$^2$\,s].}. For each observation, the
maximum amplitude of the exposure map was determined. Pixels with
the exposure map below $75$\% of this maximum value have not
been used.  Although this constraint reduces the original area of
$7.5$\,arcmin circle by roughly $13$\%, it secures for our purpose
an acceptable uniformity of the exposure (\citealt{soltan11}).

\section{`Bright' and `faint' source counts\label{counts}}

Two independent methods have been applied to estimate the number of
discrete point-like sources in a single observation. The first one
was based on a standard procedure of finding prominent
concentrations of counts within a detection cell. Sources isolated
in this way are labeled here as `bright'. A second method, described
in \citet{soltan11}, estimates number of the `faint' sources.
It calibrates deviations of the photon distribution
from the Poissonian one using the nearest neighbor statistics. It
is not able to isolate individual sources, but provides statistical
information on the population of sources generating small numbers of
photons.

To count `bright' sources in a single observation, a circular cell was
slid over the entire investigated area.  The cell size was set to
enclose $85$\% of counts generated by a point source. The radius of the
detection cell varied as a function of the off axis angle according to
the shape of the {\em Chandra}\ point spread function (PSF). All the
information on the PSF shape required in the procedure of `bright'
source selection as well as for the `faint' source assessment, was
obtained from {\it mkpsfmap} - a standard tool of the {\em Chandra}\
data processing. The search for `bright' sources was performed
in the same manner for all the pointings.  The iterative procedure was
applied. Using the sliding window technique, the strongest
concentration of photons was localized, and it was recognized as the
brightest source in the field of view.  Then, the area surrounding
this source was extracted from the data, and the search for the second
brightest source was performed in the same way. The procedure was
repeated for the consecutive sources until the number of counts
selected as the next source dropped below the threshold adopted
individually for each observation. The threshold counts were selected
at a level high enough to prevent random fluctuation of counts
to be approved as a real source. It was assumed in this step that the
background counts were distributed randomly over the field of view.
The search for sources was terminated when the probability of
random accumulation of counts exceed $10^{-6}$.  Owing to strong
variations in the PSF width, the minimum counts recognized as a
point-like source varies over the field of view, typically between
$4$ and $8$. This range varied a little between observations because
of different levels of the background counts.

Our data span a wide range of exposure times, from $30$\,ks
through more than $170$\,ks. Because of that the pointings differ
in the source detection threshold and in the number of detected
sources. To use the observed number of sources as the estimator
of the source counts per unit solid angle, which is independent of
the exposure time, one needs to adopt an analytic model for the
counts and to relate the observed number of sources in the
individual field to the parameter(s) of the model.

A power law is the obvious choice for the source number counts
per unit solid angle (hereafter per $1$\,sq.\,deg):
\begin{equation}
\frac{dN(S)}{dS} = N_o\, S^a\,,
\label{dNdS}
\end{equation}
with two a priori free parameters, normalization amplitude $N_o$,
and the slope $a$.
However, the limited number of sources, as well as a narrow dynamic
range of fluxes populated by sources in a single pointing, prohibits
any attempts to measure the slope $a$.  Also the data on the
source counts available in the literature for a couple of deep
fields do not provide information on the potential field-to-field
slope variations. In those few cases where the dynamic range
within a single field allows tracking changes of the slope, it
appears that the slope is constant below
$\sim 10^{-14}\,{\rm erg\,s^{-1}\,cm^{-2}}$ down to at least
$10^{-16}\,{\rm erg\,s^{-1}\,cm^{-2}}$
(e.g. \citealt{georgakakis08}).
Therefore, in the present investigation only the normalization is
fitted for each field separately, while a single, universal value
of the slope is assumed.

A several-step procedure was applied to find the best estimate of
$N_o$ using the observed number sources. Because the each
enhancements of counts within the detection cell is considered a
`source', one should
carefully evaluate a contribution of the background counts and
apply the adequate statistical correction. Let $n_s(k)$ be
the number of detected `sources' containing $k$ counts, where
$k\, =\, k_{\rm s}\, +\, k_{\rm b}$
is a sum of the genuine
X-ray photons emitted by a source, $k_{\rm s}$, and the background
counts, $k_{\rm b}$. $N_o$ is related to $n_s(k)$ in the
following way:
\begin{equation}
n_s(k) = A \sum_{k_{\rm b}=0}^{k}\,
       \left[\, {\rm P}_{\rm bkg}(k_{\rm b})\,
       \int dS\,N_o\, S^a\:
       {\rm P}(k_{\rm s}\,|\,S)\, \right]\,,
\label{ns1}
\end{equation}
where $A$ is the solid angle of the observation (in sq.\,deg),
${\rm P}_{\rm bkg}(k_{\rm b})$ denotes  the probability that
$k_{\rm b}$ background counts would be found in the detection cell,
and ${\rm P}(k_{\rm s}\,|\,S)$ is the probability that a source of
flux $S$ generates $k_{\rm s}$ photons (it is elaborated below).
The probability
of finding $k_{\rm b}$ counts within the detection cell is
given by the Poissonian distribution:
\begin{equation}
{\rm P}_{\rm bkg}(k_{\rm b}) =
         \frac{e^{-\lambda}\,\lambda^{k_{\rm b}}}{k_{\rm b}\!}\,,
\label{poisson}
\end{equation}
where $\lambda$ is the expected number of random counts within
the detection cell. For clarity, in formulae \ref{ns1} and
\ref{poisson}, a fixed detection cell radius and $\lambda$ have
been assumed. In the actual calculations, the right-hand side
of Eq.~\ref{ns1} was integrated over the solid angle $A$.

The sum over the background counts $k_{\rm b}$ in Eq.~\ref{ns1}
generally includes the $k_{\rm s} = 0$ and {1} components.
However, the minimum value of $k$ was set to warrant
${\rm P}_{\rm bkg}(k_{\rm b}=k) < 10^{-6}$, and
those components of the sum are effectively negligible.

It is convenient to use the instrumental count in each
observation as a flux unit. The flux $s$ in ACIS counts
is related to $S$ in physical units by a conversion factor
$\eta$\,: $s=S/\eta$,
with $\eta$ in ${\rm erg\,s^{-1}\,cm^{-2}\,count^{-1}}$
is obtained from the exposure map. The source counts using
the new flux unit are represented by
\begin{equation}
\frac{dn(s)}{ds} = n_o\, s^{\,a}\,,
\label{dnds}
\end{equation}
where
\begin{equation}
 n_o = A\, N_o\,\eta^{\,a+1}\,,
\label{n0}
\end{equation}
and the probability ${\rm P}(k_{\rm s}\,|\,S)$ takes the form:
\begin{equation}
{\rm P}(k_{\rm s}\,|\,s) =
 \frac{e^{-s}\,s^{k_{\rm s}}}{k_{\rm s}\!}\,.
\label{poiss_cnt}
\end{equation}

Equations~\ref{dNdS} and \ref{dnds} with a fixed slope
do not describe the actual counts over the entire flux range.
Substantial fraction of sources is found above the
count slope brake
$S_{\rm b} \approx 8\cdot 10^{-15}\,{\rm erg\,s^{-1}\,cm^{-2}}$
($S_{\rm b}$ is not very accurately determined, see
\citealt{georgakakis08}). Above $S_{\rm b}$ the differential
slope is close to $a_{\rm b} = -2.5$. Incorporating the broken
power law into Eq.~\ref{ns1} and using the instrumental
counts $s$, we finally get
\begin{equation}
\begin{multlined}
n_s(k) = n_o\: A\;\times \\
\times\;\sum_{k_{\rm b}=0}^{k-2}\,
       \left[\, {\rm P}_{\rm bkg}(k_{\rm b})\,
       \frac{\gamma(k_{\rm s}\!+a\!+\!1,s_{\rm b}) +
       s_{\rm b}^{a-a_1}\,\Gamma(k_{\rm s}\!+\!a_{\rm b}\!+\!1,s_{\rm b})}
       {\Gamma(k_{\rm s})}\,\right]\,,
\end{multlined}
\label{ns2}
\end{equation}
where $\gamma(\alpha,x)$ and $\Gamma(\alpha,x)$ are
the lower and upper incomplete gamma functions, respectively.

Equation~\ref{ns2} summed over $k$ gives the expected total number
of `bright' sources. To evaluate $n_o$, the number of actually
detected `bright' sources has been substituted on the left-hand
side of Eq.~\ref{ns2}. Then, the amplitude $N_o$ was obtained using
Eq.~\ref{n0}. Calculating the conversion factor, variations of
soft energy absorption by the cold gas in the Galaxy
were taken into account.
We assumed that the intrinsic source spectra are represented by
a power law with the photon spectral index $\Gamma = -1.4$.
The detected fluxes were corrected for the galactic absorption
using the appropriate $N_H$ data.
We used the NASA HEASARC tool\footnote
{http://heasarc.gsfc.nasa.gov/cgi-bin/Tools/w3nh/w3nh.pl}
based on \citet{kalberla05}.
The lowest $N_H$ in the sample is $6\cdot 10^{19}$,
and highest is $1.6\cdot 10^{22}\,{\rm cm}^-2$.
For the $0.5-2$\,keV energy band and the assumed spectrum,
this $N_H$ range introduces variations of the average photon energy
between $1.022$ and $1.154$, and a reduction of detected counts by
a factor $0.984$ through $0.695$.
The statistical properties of the $N_o$ distribution
in our sample are discussed in the next section in conjunction
with the analogous distribution obtained for `faint' sources.

The population of sources below the formal source detection
threshold, labeled as `faint', is investigated using a
statistical approach. Here only the basics of the method are
presented. All the details and potential applications were
discussed in a separate paper (\citealt{soltan11}).

After the removal of all the `bright' sources, the remaining counts
are a mix of the non-X-ray events, truly diffuse X-ray background,
and counts generated by a population of faint sources. Only this last
constituent is responsible for fluctuations of the count
distribution characteristic for point sources. One can express the
total number of events, $n_t$, within the investigated area
in the following form:

\begin{equation}
n_t\, =\, n_1 + n_2 + ... + n_{k_{\rm max}}\,,
\label{nt}
\end{equation}
where $n_1$ represents counts that are distributed randomly, $n_2$ -
counts produced by sources contributing exactly two counts each
(`2-photon sources'),
$n_3$ - counts by `3-photon sources', and so on up to
$n_{k_{\rm max}}$ - counts due to the brightest sources left
in the field (i.e., the brightest among the `faint' ones).

Counts distributed randomly constitute a composite
collection of events that also includes the
weakest discrete sources contributing single photons.
Photons coming from sources producing $2\le k \le k_{\rm max}$
counts create local enhancement of a unique shape determined
by the telescope PSF.
Statistical characteristics of these variations are efficiently
quantified using the nearest neighbor
statistics (NNST) of the count distribution. The probability that
a randomly chosen event has no neighbors within a distance $r$, is
\begin{equation}
P(r) = p_1\, P(r\,|\,1)\, +\, p_2\, P(r\,|\,2)\, + ... +
        p_{k_{\rm max}} P(r\,|\,k_{\rm max})\,,
\label{pr}
\end{equation}
where $p_1$ is a probability that this event is not related to any
source generating two or more counts, $p_k$ for $k = 2, ...,
k_{\rm max}$ is the probability that this event is produced by
the $k$-photon source,
and $P(r\,|\,k)$ is the conditional probability that there are
no other counts within $r$ provided the selected event belongs
to the $k$-photon source. Under the reasonable assumptions, for
$k\ge 2$
\begin{equation}
P(r\,|\,k) = P(r\,|\,1)\cdot {\cal P}(r\,|\,k)\,,
\label{prk}
\end{equation}
where ${\cal P}(r\,|\,k)$ is the probability that within $r$
there are no other counts from the same source. This quantity
is uniquely defined by the PSF. Taking $n_k = k\cdot n_s(k)$ and
$p_k = n_k/n_t$ and combining Eqs.~\ref{pr}, \ref{prk}, \ref{nt},
and \ref{dnds} we get
\begin{equation}
\frac{n_o}{n_t}\, P(r\,|\,1)\,
     \sum_{k=2}^{k_{\rm max}}\, \frac{\Gamma(k+a+1)}{\Gamma(k)}\,
     [1 - {\cal P}(r\,|\,k)]\, =\, P(r\,|\,1) - P(r)\,.
\label{nnst}
\end{equation}

In the relevant flux range the source counts are adequately
represented by a single power law. Since the maximum number of
photons, $k_{\rm max}$, is defined by the threshold for the `bright'
sources, the actual value of $k_{\rm max}$ is a function of a
position within the field of view; in most of the pointings
$3\le k_{\rm max}\le 7$.

Equation~\ref{nnst} allows us to determine $n_o$, provided the
relevant probability distributions are known. One can estimate the
probability $P(r)$ for each observation by measuring the distance to
the nearest neighbor for each photon in the field. Similarly,
$P(r\,|\,1)$ is given by the distribution of distances of the
randomly distributed points to the nearest photon.
The PSF related probability distributions, ${\cal P}(r\,|\,k)$,
were determined using the CIAO tool {\it mkpsfmap}. The distribution
of photons produced by a large number of sources were generated by
means of the Monte Carlo method, and the relevant probabilities
were determined as a function of position and number of photons.

The efficiency of the NNST method depends strongly on the PSF width,
and in the present investigation it provides interesting results
only for small off-axis angles. Because statistical uncertainties
increase rapidly at larger distances from the optical axis, we limited
the NNST calculation to the central region of $5$\, arcmin diameter.

The best estimate of $n_o$ was determined in the following way.  All
the probability distributions were calculated for several
(usually more than $20$) distances $r$, which uniformly covered the
domains of distributions $P(r\,|\,1)$ and $P(r)$.  Then, the
cumulative probability distributions in Eq.~\ref{nnst} were
replaced by the corresponding probability densities; e.g.,
$\Delta P(r) = P(r) - P(r + \Delta r)$ for the consecutive
distances $r$.
In all the calculations, $\Delta r = 0.246$\,arcsec ($\equiv 1/2$ of
the instrumental pixel) was used. Thus, a set of independent
equations covering all the observed separations was
constructed, and the best fit value of $n_o$ was determined using
the least square method. Finally, the count amplitude $N_o$ was
obtained using Eq.~\ref{n0} as for the 'bright' sources.

\section{Count correlations \label{correlations}}

The amplitudes of the number source counts determined for `bright'
and `faint' sources (hereafter denoted $N_o[b]$ and $N_o[f]$,
respectively) define the number source counts over adjoining, but
different flux levels. Therefore, the median flux of `bright' and
`faint' sources in each observation is not widely separated, and the
$N_o[b]$ and $N_o[f]$ averaged over the sky should be similar.
Nevertheless, one can expect systematic differences between both
estimates, if the count slope adapted in the calculations, $a$, did
not match the slope actually observed in the data. The differential
slope between $10^{-16}$ and $10^{-14}$\,erg\,s$^{-1}$cm$^{-2}$ in
the deep {\em Chandra}\ fields is well fitted with the slope of $-1.58$
(\citealt{georgakakis08,soltan11}). Using $a = - 1.58$ in the present
calculations, the average amplitude of the `faint' source counts is
larger by $\sim\!5$\% then that for the 'bright' sources. Both
amplitudes are practically identical for $a = 1.60$.  To preserve
internal consistency of the investigation, the latter slope was
used in subsequent calculations. Although this is steeper by
$0.02$ than the best fit by \citet{georgakakis08}, it stays within
their $1\sigma$ limits. One should note that the present
investigation is not suitable for assessing the count slope either within
the individual field or the average over the sky.  This is because
most systematic errors involved in the estimates of the number of
`bright' sources are independent of the errors affecting the
`faint' source assessment. The source counts amplitudes, $N_o[b]$
and $N_o[f]$ are functionally dependent on the slope $a$.
Therefore, a unique slope is required to balance both amplitudes. In
fact, modification of the slope by just $0.02$ demonstrates that the
systematics do not play a significant role in the analysis. One
should also stress that all the conclusions of the paper are not
affected by a selection of the particular value of the slope.

An apparent consistency of the average $N_o[b]$ and $N_o[f]$
estimates does not exclude local inhomogeneities of the source
distribution in the individual pointing.  One should note that the
amplitudes $N_o$ for `bright' and `faint' sources are obtained on
using the disconnected classes of sources; i.e., none source was
qualified as `bright' and 'faint' at the same time. Thus, for the
random source distribution, the source counts should be
uncorrelated.

\begin{figure}
\resizebox{\hsize}{!}{\includegraphics{nob_nof_n.ps}}
\caption{Amplitudes $N_o$ of the source number counts for flux $S$
in $10^{-15}$\,erg\,s$^{-1}$cm$^{-2}$ (see Eq.~\ref{dNdS}) for
the `bright' and `faint' sources in the sample of $302$ pointings;
$293$ pointings with the rms uncertainty of $N_o[b]$
smaller than $160$ per sq.\,deg are shown with dots, $9$ pointings
with larger rms - with crosses.}
\label{nobnof}
\end{figure}

Apart from the systematic errors, the $N_o[b]$ and $N_o[f]$
amplitudes are subject to large statistical uncertainties that
generate substantial scatter.  The average number of `bright'
sources per field ${\overline n_s} = 46.0$. Thus, the Poissonian
scatter alone introduces $\sim\!15$\% rms fluctuations to the
present estimate of $N_o[b]$. In reality, still larger variations
of $N_o[b]$ are expected due to  cosmic variance (source
clustering). The $N_o$
estimates for the `faint' sources are afflicted by even larger
errors, because the estimate of the count amplitudes is derived
indirectly. Two factors contribute most to the final
uncertainties. First, the amplitude estimate is proportional to the
difference between two probability distributions (see
Eq.~\ref{nnst}), and both distributions are subject to substantial
statistical scatter. Second, the `faint' sources' contribution to
the total events is small, typically $2 - 6$\%, while all the
remaining counts are distributed randomly. Therefore the net
signal, represented by the right-hand side in Eq.~\ref{nnst}, is
also very modest in comparison to the noise that is dominated by
the random scatter of the $P(r\,|\,1)$ distribution.

In Fig.~\ref{nobnof} the `bright' and `faint' source amplitudes $N_o$
as defined in Eq.~\ref{dNdS}\footnote{In the calculations broken
power law and Eq.~\ref{ns2} have been used.}, where $S$ is in
$10^{-15}$\,erg\,s$^{-1}$\,cm$^{-2}$, are plotted for the full sample
of $302$ pointings. The rms scatter of $N_o[b]$ is slightly
larger than what is expected from the Poissonian fluctuations of the
`bright' source numbers (see below for the detailed discussion),
while the amplitude of the $N_o[f]$ variations is much higher, and
it is clearly dominated by the statistical noise.
The rms for 'faint' sources amounts to $44$\% of the average
amplitude of $N_o[f]$. Despite the scatter, the correlation of the
`bright' and `faint' amplitudes is statistically significant. The
correlation coefficient for $302$ data points $\rho = 0.2003$.  The
non-directional probability that the data are drawn from the
uncorrelated population amounts to $0.00046$ (or $0.00023$ for
the directional case).  To minimize statistical noise, the
uncertainties of the individual $N_o$ estimates are carefully examined
(see below). Due to a wide range of exposure times in the processed
observations, these uncertainties strongly differ.
In order to check the influence of the poor quality estimates on the
subsequent statistical analysis, pointings with the largest
uncertainties of $N_o[b]$ have been identified. A removal of
pointings that suffer from the highest uncertainties does not
strengthen the $[b] - [f]$ correlation greatly. Nevertheless,
if nine pointings with $\sigma_{\rm o}(N_o[b]) > 160$ per sq.\,deg
are eliminated, the correlation coefficients in the sample of
$293$ pointings rises to $\rho = 0.2205$. The corresponding
directional probability for the uncorrelated general population
in this case drops to $7\cdot 10^{-5}$.

Although the $N_o[f]$ estimates are strongly affected by the
statistical noise at the level of the photon distribution within
the each pointing, the correlation between $N_o[f]$ and
$N_o[b]$ in the whole sample favors the calculations of a single
amplitude $N_o$ derived jointly from the `bright' and
`faint' sources.  To combine the $N_o[b]$ and $N_o[f]$
estimates into a single `best' estimate of the source number counts
amplitude for each pointing, an adequate error estimate and data
weighting for each measurement are essential. The errors for the
`bright` source counts were calculated using the Poissonian
noise, since this effect dominates. In the first step it was
assumed that the underlying population of sources is the same for
all the pointings; i.\,e., the cosmic variance effects were
neglected. Next, the expected number of the observed
`bright' sources was determined for each pointing separately,
taking the exposure time into account. Finally, the Poissonian
distribution around the expected number of sources was used to
compute the corresponding dispersion $\sigma_{\rm o}(N_o[b])$
individually for each pointing. The rms uncertainties are
contained between $64$ and $182$ per sq.deg with the average in
the whole sample of $112$ per sq.\,deg. The rms scatter of $N_o[b]$
amounts to $127$, which exceeds the Poissonian estimate almost by
$14$\%.

The $N_o[f]$ uncertainties result from a complex combination of the
Poisson-like fluctuations of the number of faint sources,
contribution of background counts, and a stochastic character of
the photon distribution on angular scales comparable to the width
of the PSF. In effect, the variance of $N_o[f]$ cannot be easily
derived from theoretical considerations, but instead it is
estimated directly from the observed distribution. It was evident
that the cosmic variance contributed marginally to the observed
$N_o[f]$ scatter. Also, no clear correlation of the variance with
the exposure time (or the total number of events) was found.
Therefore, equal uncertainties were assigned to all the
observations. As an error of the individual $N_o[f]$ estimate,
$\sigma_{\rm o}(N_o[f])$, the
rms scatter in the whole sample had been assumed: $\sigma(N_o[f]) =
337$ per sq.\,deg.

Our final best estimate of $N_{oi}$ of the $i$-th observations
is a weighted mean of $N_o[b]_i$ and $N_o[f]_i$:
\begin{equation}
N_{oi} = \alpha_i\cdot N_o[b]_i + \beta\cdot N_o[f]_i\,,
\label{weighted_n_o}
\end{equation}
with weights $\alpha_i$ and $\beta$ inversely proportional to the
squares of the corresponding rms uncertainties. The resulting
uncertainties of $N_o$, $\sigma_{\rm o}(N_o)$, are spread between
$63$ and $161$ per sq.\,deg.

The drastic unevenness  of the pointing distribution in the
celestial sphere presents a problem for our statistical analysis.
Estimates of the average count amplitude, as well as the count
correlation between different pointings, should take into account
fact that a large number of pointings cover the same sky area.
Obviously, the source counts based on pointings that cover the
overlapping areas of the sky are related. For the detached
(nonoverlapping) observations, the correlations would indicate
structures in the source distribution on the corresponding angular
scale. Since our sample contains a large number of overlapping
pointings, the spurious count correlations are also present at
larger angular scales than the field of view of a single pointing.
This is because the overlapping observations are dominated by a few
groups centered on {\em Chandra}\ deep fields. Some wide angular bins
that happen to include the separation between these fields contain
pairs predominantly drawn from those heavily observed areas. To
account for this bias, we assign weights to all the pointings.  As a
result of the application of weights, cosmic signals from all the
directions covered by the present observations contribute uniformly
to the investigated correlations. The weight of the $i$-th pointing
is defined by the formula

\begin{equation}
w_i\; =\, \Omega_i\; /\int_{\Omega_i} m_{\rm pnt}\,d\omega\,,
\label{weights}
\end{equation}
where $\Omega_i$ denotes the solid angle of the observation, and
$m_{\rm pnt}$ is the number of pointings that cover the area
$d\omega$. Thus, for all the detached pointings, $w = 1$ since
$m_{\rm pnt} = 1$ within the entire field of view, while for the
coinciding pointings, the weights are reduced proportionally to the
overlapped area and the number of the involved pointings. Unless
otherwise stated, these weights are applied in the calculations
below.

The average number counts amplitude $\overline{N}_o = 743$ per
sq.\,deg. with the rms scatter $\sigma(N_o) = 125$ per sq.\,deg.
The flux limits that define `bright' and `faint' sources depend on
the exposure time, but the flux separating both source classes is
always close to $10^{-15}$\,erg\,s$^{-1}$\,cm$^{-2}$. Therefore the
present $\overline{N}_o$ estimate characterizes the source counts
just around this flux level.

To compare the present result with the source number counts based on
several deep {\em Chandra}\ fields, we adopt the count parametrization by
\citet{georgakakis08}. Their data converted to the units used here
give $dN/dS = 574$ per sq.\,deg at
$S=10^{-15}$\,erg\,s$^{-1}$\,cm$^{-2}$; i.e., our figure is $29$\%
higher. Although this difference could partially be attributed to
various systematic effects inherent in the present calculations, one
should note that our amplitude is the average of a large number of
pointings distributed over the whole sky, while the {\em Chandra}\ Deep
Fields only cover a few selected areas. Applying the present method to the
selection of $47$ observations in the CDF-S\, we get the average
amplitude $N_o = 641 \pm 8$, per sq.\,deg, which exceeds the
\citet{georgakakis08} result by $12$\%. The uncertainty of the
average is based on the rms scatter of $56$ per sq.\,deg in those
$47$ pointings. Although all these data are localized at CDF-S, the
fields cover slightly different areas. Therefore variations of $N_o$
not only represent the statistical noise generated by our
procedures, but also include small contribution from the actual
fluctuations in the number of sources.

In the CDF-N\ the present calculations give $dN/dS = 797 \pm
17$ per sq.\,deg. This amplitude differs from the CDF-S\ one by
$24$\% and it is consistent with results by \citet{tozzi01} for
CDF-S, and CDF-N\ by \citet{brandt01}.

\begin{figure}
\resizebox{\hsize}{!}{\includegraphics{pair_rms_normslim.ps}}
\caption{The distribution of the `pair rms', i.e. rms difference
between the counts amplitudes in pairs of observations as a function
of the pair separation. Results obtained with and without weights
are shown with full and open circles, respectively (see text for
detailed explanation). The dotted line separates the overlapping
pointings from the detached ones. The lowest separation bin contains
pairs closer than $0.1$\,arcmin.}
\label{pair_rms}
\end{figure}

To assess the uncertainties proper to the method, and cleared of
the contribution generated by the cosmic variance, all $302$
observations (including overlapping)  have been used in the
following way. For all the possible pointing pairs, a difference
between amplitudes $N_o$ was obtained: $\Delta_{ij}=N_o(i)-N_o(j)$,
for $i, j = 1, ...,\, 302$, and $i\ne j$. The pairs were divided in
several bins according to the pair angular separation Then, for the
each separation bin the rms of $\Delta_{ij}$ was calculated:

\begin{equation}
\sigma_p^2 = \frac{1}{N_{ij}}\,
             \frac{1}{2}\sum_{i\ne j} \Delta_{ij}^2\,,
\label{sigma_p}
\end{equation}
where $N_{ij}$ denotes the number of pointing pairs in the given
separation bin, and `2' in the denominator is introduced to
normalize $\sigma_p$ to the rms of $N_o$. For perfectly overlapping
pointings, the `pair rms' $\sigma_p$ represents the scatter
intrinsic to the method, while for widely separated fields,
$\sigma_p$ is a quadratic sum of two components: noise produced
by Poissonian scatter of the source counts detected in each pointing
and the cosmic variance. If the observations partially overlap,
intermediate amplitudes of $\sigma_p$ are expected.  In
Fig.~\ref{pair_rms} the distribution of $\sigma_p$ for several bins
is shown. The abscissa positions give the average pair separation in
the bin.
One sigma error bars for detached pairs were calculated using the
bootstrap Monte Carlo method. A large number ($10000$) of simulated
sets of observations were generated.  In the simulated data the
original sky coordinates were used, while the amplitudes $N_o$
were drawn at random from the observed $N_o$ distribution. Then,
using Eq.~\ref{sigma_p} the pair rms $\sigma_p$ were calculated
for each simulated data set. The rms scatter of the $\sigma_p$ was
taken as the uncertainty of the actually observed signal.

Weights are superfluous for almost completely overlapping pointings,
since the rms mainly represents  the method errors, while weights adequately
measure the contribution due to the cosmic signal for the detached pairs.
To calculate the pair rms in that latter case  we use the formula:
\begin{equation}
\sigma_p^2 = \frac{1}{2}\left.\sum_{i\ne j} w_i\, w_j\, \Delta_{ij}^2
             \;\middle/\,\sum_{i\ne j} w_i\, w_j\right..
\label{wgt_sigma_p}
\end{equation}

At the smallest separations, the amplitude $\sigma_p = 41.6$\,per
sq.\,deg, and for the `bright' sources $\sigma_p[b] = 37.5$\,per
sq.\,deg.  A substantial decline in the pair rms for overlapping
pointings clearly indicates that the observed fluctuations are
dominated by the actual variations of the cosmic signal while
shortcomings of all the procedures and approximations engaged in the
calculations do not play a significant role. One should also note
that the rms scatter attributed here to the present method does not
affect the Poissonian character of the distribution of the number of
sources detected in a single observation. Thus, it is legitimate to
assume that the statistical properties of the $N_o$ distribution in
the sample are described by the cosmic variance and the Poissonian
scatter.

\section{Cosmic variance}
\label{variance}

No obvious variations of the pair rms is present for the
nonoverlapping pointings averaged over all the data. It indicates
that any potential, strong fluctuations of the counts amplitude have
angular scales that typically do not exceed a size of the individual
pointing. However, on smaller angular scales, fluctuations
exceeding the Poisson noise are present in our sample.

Assuming that the cosmic variance and the Poissonian noise add
in squares to produce the observed scatter of $N_o[b]$, the rms of
the cosmic variance $\sigma_{\rm CV} \approx 60$, or $8.1$\% of
the average $N_o[b]$ signal. This figure represents the mean
variance within a circle of $15$\,arcmin diameter. One should expect
that the cosmic variance amplitude also depends on the source
redshifts.  However, over a wide range of X-ray fluxes, the average
source redshift depends very weakly on the flux threshold (e.g.
\citealt{soltan08}). Thus, even for a wide span of exposure times,
the redshift distributions in the sample are statistically similar,
and the $\sigma_{\rm CV}$ amplitude is representative of all
our data.

The statistically significant correlation between the `bright' and
`faint' source counts also affirms the role of the cosmic variance.
The correlation alters the rms fluctuations of the combined counts
amplitude $N_o$. To test this effect on the distribution of $N_{o}$,
we generated a large number of simulated sets of count amplitudes
using Eq.~\ref{weighted_n_o}. In the simulated data we connected the
actual `bright' source amplitude of the $i$-th observation,
$N_o[b]_i$, with the $N_o[f]$ randomly drawn from the sample.  It
was found that the rms fluctuations of the $N_o$ in the simulated
data are in $99$\% cases smaller than the fluctuations in the real
data, which confirms the $N_o[b] - N_o[f]$ correlation revealed using
the Pearson test.

\section{Discussion\label{discussion}}

Variations of the source number counts were analyzed using the
{\em Chandra}\ observations distributed in both galactic hemispheres.
We applied two independent methods determining the source
counts in the two adjacent flux levels. Then, both amplitudes for
each pointing were reduced to the standard flux of
$10^{-15}$\,erg\,s$^{-1}$cm$^{-2}$.
The amplitudes represent separate species of sources. Thus,
for the Poissonian distribution of sources both amplitudes are
expected to be statistically uncorrelated.

The dominating contribution in the observed field-to-field
variations comes from the Poissonian noise induced by the relatively
small average number of sources per field. This effect seriously
confused a search for the potential correlations in the $N_o$
distribution on large angular scales. Scarce observational data,
particularly in the south galactic hemisphere, prevent us from
drawing conclusions at a high confidence level. The pointings are
distributed very inhomogeneously in the celestial sphere on the
large, as well as on small angular scales. Due to these deficiencies,
the picture emerging from the present investigation is ambiguous
to some extent.

On large angular scales, the fluctuations of the counts
amplitude averaged over the whole sample of $302$ observations do
not exhibit distinct irregularities that could be symptomatic for
the existence of the large angular scale structure of the XRB.
However, the statistically significant correlation between
`bright' and `faint' sources within individual pointings is clearly
visible, implying a nonrandom source distribution on adequately
small scales.  The present data are insufficient to measure
the angular range of these correlations precisely. A sharp rise of
$\sigma_p$ with increasing separation for the overlapping pointings
(between $3$ and $15$\,arcmin; see Fig.~\ref{pair_rms}) indicates
that the angular size of fluctuations is most likely smaller than
the extent of a single pointing. A substantially larger collection
of closely separated observations is needed to determine this
question.

Despite the apparent absence of large angular scale features in
the $\sigma_p$ distribution, some differences between the data in
both galactic hemispheres seem to be present. Unfortunately, the
available observational material is inhomogeneous, which makes the
comparison between N and S quite problematic. In particular, the
number of pointings in the northern and southern hemispheres are
$190$ and $112$, respectively. An asymmetry is even stronger in the
total area covered by the pointings: in the north it is twice as big
as in the south.

We notice that the fluctuations of $N_o[b]$ in the north are
noticeable larger than in the south. Since the average numbers of
detected `bright' sources per field in both areas are very similar,
the Poissonian contribution to the rms of $N_o[b]$ are also equal and
amount to $112$ per sq.\,deg. In effect, the whole difference is
attributed to the cosmic variance, which in the north exceeds $68$
per sq.deg, while in the south $\sigma_{\rm CV} = 41$ per sq.\,deg.
Also the $N_o[b] - N_o[f]$ correlations are substantially different
in both hemispheres.  In the north the correlation is statistically
significant at the confidence level of $99.98$\% (using the
directional probability), while the data in the south are consistent
with no correlation. It is complicated to interpret these
discrepancies. Although some statistical characteristics of count
amplitudes in both hemispheres look essentially different at first
glance, it is most likely that these ``unusual'' features are
artifacts that should be attributed to the specific properties of
this particular set of observations, rather than to the genuine
large-scale variations of the source distribution.

A large number of the new pointings would improve statistical
significance of the investigations. Unfortunately, one cannot expect
a rapid inflow of the new {\em Chandra}\ observations. Therefore, a more
promising way to proceed would be to search for the correlation
between the existing {\em Chandra}\ observations and the data in other
available X-ray surveys.  In particular, the relationship between
the counts amplitude determined here and the RASS maps should be
investigated.

\begin{acknowledgements}
We are grateful to the anonymous
referee for careful reading and for for remarks and propositions
for improving the paper that resulted in the substantial and -- in
some points -- essential changes in our work.
We thank all the people who created the {\em Chandra}\ Interactive
Analysis of Observations software for producing a user-friendly
environment.  This work has been partially supported by the Polish
NCN grant 2011/01/B/ST9/06023.
\end{acknowledgements}

redpajama_set_name: RedPajamaArXiv


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redpajama_set_name: RedPajamaCommonCrawl


text:
Q: How Do I Use an HTML5 Canvas as a WebGL Texture I want to:

*

*Set Uniform values for case i.

*Render compute shader for case i to an HTML5 <canvas> tag.

*Use the <canvas> contents (case i render output) as a texture in the next render pass.

*Repeat for all cases.

*Extract answers into JS from color data.

I'm trying to make a compute shader and need to carry a value per pixel (fragment) on each render pass. A simple example would be incrementing the blue value of a pixel on each render call.
I.e.
pass 1: b=1
pass 2: b=2
pass 2: b=3
etc.

*

*Is this kind of a shader loop even possible?

*Is there a better way to keep a'carry' texture in video memory for multipass processing (where uniform values must change between passes, unlike standard in-shader multipass processing)?

A: The short answer is you can't
You can't currently access the canvas as a texture. Some other solutions

*

*Copy the canvas to a texture
gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, gl.canvas);

Will copy the current contents of the canvas into a texture.

*Render to your own texture by attaching it to a framebuffer.
In this case you'd render to a texture that is set as an attachment to a framebuffer and then render that texture to the canvas (assuming you want to see the result and not just do math). There's an example here and here.


The 7 Habits of Highly Effective People tells us that we need to focus on important things before the urgent things. We are all waiting for that elusive, magical moment when we have more time, when things get easier, when today's crisis is over and done with. That is a fantasy that is never going to happen.
Today Michael Synk and I talk about brand promises, how to improve on them, and take on two client case studies to boot. Let's dive right in.
Business owners struggling to grow their client base are often missing key components for opening the "right door" to new business. On today's podcast episode, Caryn Copp, Chief Door Opener at Kopp Consulting, will shed some light into the secrets of "door opening.".
David Hassell is a serial entrepreneur and founder of 15Five, a SaaS company focused on helping managers and CEOs get effective insights from their people. On today's show, David and I discuss the dynamics of a top notch team.


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14 Tips Every Designer Would Want to Know When Were a Newbie
Internet marketingBy Jessica Venkat December 6, 2018
No ratings yet. Web design is one of the most requested professions now, in the Internet age. And if one hasn't studied it in a college or a university, it's not a big deal to take a course or even an online course to learn the basics of web design without having to leave the house.…
Apple is starting to sell its first iPhone XR case, and it's clear so you can show off your bright new phone – TechCrunch
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Apple's new iPhone XR comes in a half a dozen colors, including blue, yellow, red and coral. In fact, the colors are sufficiently fresh that it'd be kind of silly to buy a traditional phone case that would protect it but also hide if from plain view. It's for this reason that Apple just began…
250-page document dump is another nail in Facebook's coffin
Web technologyBy Jessica Venkat December 5, 2018
As part of its investigation of Facebook in the wake of the Cambridge Analytica scandal, the British government seized a huge cache of the company's internal documents. Despite Facebook's best efforts, those documents are now online. And the picture they paint is not pretty. You can peruse all of the roughly 250 pages on Parliament's website. While…
AI-Powered Online Automated Malware Analysis Platform
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Looking for an automated malware analysis software? Something like a 1-click solution that doesn't require any installation or configuration…a platform that can scale up your research time… technology that can provide data-driven explanations… well, your search is over! Israeli cybersecurity and malware researchers today at Black Hat conference launch a revolutionary machine learning and artificial…
How Blockchain Technology Can Impact the World
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Australia rushes its 'dangerous' anti-encryption bill into parliament, despite massive opposition – TechCrunch
Australia's controversial anti-encryption bill is one step closer to becoming law, after the two leading but sparring party political giants struck a deal to pass the legislation. The bill, in short, grants Australian police greater powers to issue "technical notices" — a nice way of forcing companies — even websites — operating in Australia to…
Bitcoin scammers steal identity of television host in New Zealand
A television host in New Zealand has denounced Bitcoin BTC scammers for impersonating him to fraudulently market a dodgy cryptocurrency business. In a sharp message, breakfast host Daniel Faitaua made it perfectly clear: he has never owned any Bitcoin, and any websites stating otherwise are absolutely false, local media reports. The fraudsters claimed Faitaua doubled his…
Free Open Source Vulnerability Management App for Developers
Developers around the world depend on open source components to build their software products. According to industry estimates, open source components account for 60-80% of the code base in modern applications. Collaboration on open source projects throughout the community produces stronger code, squashing the bugs and catching the vulnerabilities that impact the security of organizations…
8 Effective Ways to Optimize Your Website for Mobile Speed in 2019
No ratings yet. The loading time of a website affects users' behavior. It could either boost your conversions or make your target audience leave the site. A thorough speed optimization makes sense anyway because: 53% of people will abandon a website if it takes more than 3 seconds to load (according to Google research 2017);…
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Welcome back to the latest edition of politicians don't get technology! Our latest guest is Rudy Giuliani, former New York mayor and current cybersecurity adviser to President Trump. Rudy Giuliani doesn't understand Twitter or the internet. It's embarrassing enough that Giuliani inadvertently tweeted a link to a website criticizing Trump, but now he is doubling down on…
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Having attended boarding school since the age of seven, I've noticed that the boarding school experience is pretty universal. How many of these signs can you relate to?
1. You own way too many dresses and blazers.
Your wardrobe exclusively becomes a mesh of JCrew, Anthropologie, Ralph Lauren, and Vineyard Vines. Girls get new dresses for every parties and dinners; guys get blazers in every pastel color. Shirts without collars, untucked shirts, and unbelted pants are unimaginable and a serious fashion faux pas.
2. You have at least one embarrassing memory with your "advisor".
Each student has an advisor. Not a big deal. But when this advisor, who doubles as your English teacher (or even chaplain!), walks in on you changing, breaking co-ed, or dancing in the middle of the room? That's just uncomfortable.
3. Meet me at the "area of refuge" or some other sketchy place is just code word for "Let's hook up".
Hooking up in places like the black photo room, an empty classroom, or even out in the woods becomes so normal. Eventually an invitation to places like the area of refuge become a code name for hook-ups.
4. You can't live without Hunters, Uggs, North Face, Longchamp, and Tory Burch.
For each season and occasion, there is a right brand to be wearing or using. Hunters in all colors of the rainbow appear when the chance of precipitation exceeds 40%; Uggs in all shapes and sizes appear when the temperature drops below 50F.
5. When you're allowed Internet access past midnight, say goodbye to sleep!
Chances are that your boarding school didn't let you have Internet access whenever you wanted. In fact, the web shuts off at different times for each grade, but when that system malfunctions . . . you'll have no self-control until sunrise.
6. You can make your room look spotless in less than five minutes.
Whenever there are random room searches, you stuff your clothes under your covers and kick everything on the floor into your closet. Without actually cleaning, the room looks squeaky-clean in less than five minutes.
7. You don't ever lock your door.
You trust everyone in your dorm so much you never even think to lock your door. You don't even know where your key is until you need to turn it in at the end of school.
8. You hated it while you were there, but you miss it so much now.
You think you hate the food, you think you hate the dress code, and you think you hate everyone and everything there. By the time senior spring comes around, you're anxious to leave the damn place to go off to college, but the minute you leave, you start to realize how much you love it there. You refuse to let go of your boarding school friends. You remember only the best from it. You feel empty inside because your boarding school experience has truly made you the person you are.


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Pirates of the Caribbean: On Stranger Tides - Theatrical Review
PIRATES OF THE CARIBBEAN:
Sequels driven by success alone (quality not withstanding) are a mixed blessing at best. While it is always good to visit new places and experience new adventures with characters you have come to love, the legacy always begins to diminish little by little with each new installment. The new Pirates of the Caribbean movie is proof positive that sometimes a fresh start can breath some new life into a stale franchise but it isn't all perfect.
Theater: El Capitan - Hollywood
Time: 8:00 pm May 20, 2011
Loves: Pirates and swashbuckling adventures, Johnny Depp
Likes: Ian McShane, Geoffrey Rush
Neutral: Penelope Cruz, cash-in sequels
Hates: Movies that try to cram too much into 2 hours, characters that do things cause it is in the script
Likely: That we are going to get a 5th entry into the PotC world
I still remember that opening weekend back in 2003, when nobody knew who Captain Jack Sparrow was and a good chunk of the population still either never took notice or were just oblivious to the soon to be legendary Johnny Depp. Depp up to that point had based his career on playing odd ball characters (hence his numerous collaborations with director Tim Burton) and after watching The Curse of the Black Pearl I remember being blown away, not by how awesome the movie was or even his performance, but more about how much it DIDN'T suck. Just about everyone thought going in that there was no way in hell a movie based off a theme park ride could be any good. While the movie itself was a good bit of fun, it was Depp as the now infamous pirate Jack Sparrow that stole the show, which for any fan of his work prior to that films release was regarded as par for the course from the actor. The two sequels that followed predictably focused on the lovable whelp but were underwhelming at best (and a complete bore at worst). Now we have the fourth chapter in the continuing adventures of Captain Jack Sparrow, but has this pirate been out at sea for too long or has he finally found his sea legs once again?
We find the crafty Captain Jack Sparrow in London where he is putting together a crew to go after the mythical Fountain of Youth...or at least that is what everyone tells Jack he is there for. After a series of events (sloppily put together mind you) Jack finds himself aboard the dreaded pirate ship Queen Anne's Revenge which is captained by the pirate all other pirates fear, Blackbeard (Ian McShane). Blackbeard, along with his lively and sultry daughter Angelica (Penelope Cruz), are on a quest to find the fountain as well and need the expertise of Jack who says to have knowledge on its whereabouts. They aren't the only ones sailing for the prize as the Spanish armada and the now legitimate Captain of the English fleet, Barbossa (Geoffrey Rush), are also on the hunt for the fabled fountain. It is a race against time and the first one there is the one to claim the gift of eternal youth!
Jack is wondering why he is even in this movie.
This is an adventure movie at its most pure sense and much more than just a pirate movie. All the pretentious subplots and army of secondary characters that plagued the the prior sequels has been mercifully replaced by a fairly straightforward adventure and only a handful of new faces. Other than the poorly handled opening act of the film and a relentless need to push the narrative forward without ever taking a breath I believe this is the sequel that the first film deserved. The thing I loved most about that first film was the world that had been created in which pirates and the supernatural co-existed. And even though I tend to geek out when a movie is populated with mythological creatures regardless of the setting, there was just a bit too much of that type of nonsense going on in the two sequels for my taste. But this fourth entry has found a good footing and mixes the typical grungy trappings of the pirate world with the supernatural beautifully.
While the script writers are in desperate need to find a new angle for their villains (In all four films now the main villain has had a crew that could not be killed) and the territory covered here isn't all that original, I found the film to be much more enjoyable overall compared to the previous two films. I think a lot of that had to do with the execution, where instead of front loading the film with a sequence that never really amounted to anything beyond serving its own needs (The cannibals from the second film and the quest to save Jack in the third) we get a quick sequence of events that, while handled poorly, cut to the chase quite literally. By the half hour mark we already have all our main characters on task and on their way to find their prize. This new sense of direction helped give the film a bit more focus while also cutting away a lot of the fat that weighed down its predecessors but retaining the sense of fun that has always been present in all the films.
Angelica wonders why she wants a father so badly.
With this being more of an adventure as opposed to a quest, the characters involved in the chase are every bit as important as the chase itself and we get some much needed fresh faces to take this journey along with some old friends as well. Blackbeard is probably the biggest addition to the mix and other than some continuity issues concerning the films that came before this one (with him being such a big threat to the pirate community why had no one ever spoken of him before now?) I liked him as the main baddie. Ian McShane played the venerable pirate with an appropriate mix of shrewdness and villainy but on the flip side he also seemed to have very little in the realm of a personality to him. He never seemed to react to anything beyond a cold stare and a shrug of his shoulders. Although I did like that his powers came from a more practical source (if you consider voodoo practical that is) which added a little bit of that reality you need to ground the more outrageous happenings.
Penelope Cruz as Angelica was a welcome sight as well, although her character introduction was handled poorly and was given what amounted to one of the most pointless sword fights in the entire series. The actress didn't really have to do much other than be herself which some may see as a bad thing but I thought her personality lent itself well to the pirate world. While she never really seemed like much of a threat I did like that we finally got to have somewhat of a romantic interest for Captain Jack and her on screen chemistry with Johnny Depp was palpable (perhaps because this wasn't their first film together). The whole subplot of her being Blackbeard's daughter was a little underdeveloped though and didn't really add much of anything to the proceedings other than her being used as leverage from time to time for someone to get what they wanted. The other two new characters we get are more of the secondary nature with the priest Philip (Sam Claflin) and the mermaid Syrena (Astrid Berges_Frisbey). While clearly supposed to be stand-ins for the William Turner/Elizabeth Swan relationship present in the first three films they were unfortunately not given much screen time to make anything concerning them matter enough for us to care what happened to them one way or the other.
Barbossa wonders why he was brought back to life.
Of the returning characters we only get three or four if you count the horribly implemented cameo by Keith Richards as Jack's dad whose sudden appearance and disappearance felt completely forced. You also got the welcome presence of Mr. Gibbs (Kevin McNally) whom is not given a whole lot to do unfortunately. And what would a Pirates' sequel be without the crusty personality of Captain Barbossa. I still to this day do not agree with how they brought this character back from the dead (it wreaked of a studio trying to capitalize on a character's popularity) but at the very least we still get to see Geoffrey Rush chew the scenery as only he can. Even given my disdain for how the character of Barbossa has been handled I still found him to be a very welcome addition and probably one of the very few holdovers from the previous trilogy I would want.
Then there is the star of the show, the one guy everyone is showing up on opening weekend to see and probably the only thing anybody has ever clung on to through the entire series. But I have something to say about this person that will probably baffle and confound many of the POTC faithful, Captain Jack Sparrow is the least interesting character in On Stranger Tides. I know, it's very strange to hear that but it's true. He is still up to his same old tricks and Depp is most certainly on point but there is a very apparent problem with how this series is handling the character, he simply has nothing to him any more. In the first film it was funny and somewhat fresh to have him trying to reclaim his ship from those that stole it. In Dead Mans Chest he was manipulating anyone and everyone to save his life from a deal struck with Davy Jones. In At World's End he was just being used by everyone for their own needs as he struggled with the choice of becoming immortal or not. But in On Stranger Tides he once again wants his ship back (after losing it for the third time) and is looking for the fountain of youth which is never explained WHY he wants it. The filmmakers have taken the lazy route and just stuck him with the same old problems he had in the previous films (get his ship back, save his neck by being clever and act as looney as possible when the situation calls for it).
Blackbeard wonders why he can do magic.
Sure, you can surmise that he wants to be young forever but if so it is never mentioned, he just wants to find it for the sake of integrating him into the plot. And as for his "knowledge" on where it is located...well let's just say he isn't quite honest about that bit of information so his use to anybody in the film is fleeting at best. So let's take stock of what Captain Jack Sparrow's role in this new film is exactly. #1 He wants to find a place for no reason other than to find it. #2 He is taken captive to help find this place which he has absolutely no knowledge of. #3 During the journey all he does is spew out his witty comebacks as he stumbles about while doing nothing of any real consequence. The character Jack Sparrow has no real impact on anything other than being a glorified court jester that performs a task here and there that anybody could do. Without a doubt I think the way his character was handled here is a crime but it is something so subtle that most will be dazzled by Depp's performance regardless without ever truly realizing just how much of a throwaway character he is here. He is there for the fans plain and simple, it seemed as though there was a script that was finished before it had the Pirates of the Caribbean moniker attached to it and then they had to find places to add the captain in afterwards.
That's not to say he isn't any fun, Captain Jack Sparrow is just as crazy as he always has been and provides some great laughs over the course of the adventure, he just doesn't seem to be very necessary to move the plot along. Luckily the movie didn't have to rely on him this time around because despite Depp doing his best to steal the show it is the adventure itself that kept my interest from beginning to end. Jack Sparrow had little impact on my enjoyment of the film which is both a good and bad thing depending on your point of view. Most people are going into this just for that character alone where as I went into this hoping for a fun adventure flick. I got what I wanted out of it but I don't think the same can be said for the captain's fan base.
Jack contemplates ending it all.
So, about that adventuring I keep bringing up. The film is structured in a very familiar way that any fan of the genre will recognize and spares no time in getting right to the point. As Captain Jack says so himself, "It's not the destination, but the journey there that matters". That is the cornerstone to any good adventure and On Stranger Tides delivered a rollicking good time as we witness such sites as Blackbeard and his dark magic string his entire crew up by the wave of his sword, man-eating mermaids that lull their victims into a daze by singing to them just before ripping them apart and probably the most literal example of a ship in a bottle ever. The way events unfolded reminded me a lot of Indiana Jones and The Last Crusade as did it's finale (maybe it reminded of it a little too much in some cases) which was much more uneventful than any of the previous films in the series.
Everything leading up to the end was done well enough with only a few stumbling blocks on the way (the raid on the Spanish encampment and a scene with Jack being forced to jump off a cliff for instance) but the grand finale at the fountain of youth was all fairly predictable stuff. While the journey certainly does account for the majority of an adventure film the payoff itself has to be worthwhile as well to have made the journey worth it and I didn't find any of the climatic moments at their destination to be anything special unfortunately. I was unimpressed with the fountain itself and how it was used as a story device which in a way kind of made everything that came before it seem more shallow than it actually was.
Phillip and Syrena develop a relationship telepathically.
I must point out also that there were a large number of issues with how the film dealt with many of its characters motivations that didn't help much. Jack of course is up to his same lunacy as I mentioned earlier but other characters just didn't seem to have a point to anything they did or said. Blackbeard's reasoning for finding the fountain is because he fears a confrontation with a one legged man whom it is foretold will kill him...but that is never really explored or given any form of competent conclusion. Angelica seems to be going through a number of different issues but she also had the most perplexing character moments. Spoiler warning here...Why was she posing as Jack Sparrow at the beginning? Was she really working with Blackbeard or was she conning him? What are her true feelings for Jack? Why did Jack maroon her on that island at the end?
Barbossa's intentions were not made clear until half way through the movie but it still didn't make a whole lot of sense that he would sell himself to captain a ship flying British flags on the off chance he would come across the person responsible for destroying the Black Pearl. The biggest character motivation issue I had though was dealing with Phillip and Syrena. They become attracted to one another pretty fast (I guess that is what good looking people do) but given the blood thirsty nature of how all the other mermaids react towards humans it is never explained why she is different. While the subplot of them falling in love was handled in an adequate manner (although they really could have used some more time together) the real questionable moment happens when Syrena helps out a certain character that for all she knows could have been one of her captures and saves the day at the end. Oh and let's not forget the Spanish fleet and how little they had to do with anything, honestly their use here was confounding and even though they did do something at the end it started to feel as though the filmmakers were over stuffing their movie again with pointless characters and subplots. If the Spanish fleet had not been in the film it wouldn't have impacting anything at all.
Jack wonders how long until he ends up just like this guy.
If you haven't been able to tell yet I am kind of mixed on my reaction to the film at this moment. It definitely has its share of problems, probably the most out of the four films, but just on a basic pure entertainment scale I found it all to be a whole lot of fun. There are some great moments to be found here, the mermaid scene I would consider to be a highlight and the movie moves along at a good quick pace. Seeing Jack do his thing is always fun even if he doesn't have a whole lot to do. For every moment I found myself being impressed by one thing there was always something else that made me question my enjoyment. But I can't bring myself to completely endorse it nor condemn it. If ever there were a movie that gave me equal sides of conflicting emotions this would be it.
It is a good natured piece of entertainment though that will likely please most of everyone that watches it and most certainly fans of the franchise. But I would bet my left peg-leg that those same people will start to pick it apart well after viewing it and start to question if it was really as good as they thought while watching it. I would have to say that the franchise has found its sea legs but it just hasn't learned how to walk again just yet. When the inevitable sequel comes out I hope they get some better writers and trim that fat just a tad bit more. So there you have it, put on your best pirate formal wear and...
Tractor Tire Award of the Week - PotC: On Stranger Tides
Have you ever watched a trailer and had that one scene, that one shot that made you go "Wow, that was cool!"? Or maybe there w...


The rebuild of the Mohawks baseball team finally paid dividends in 2015. The boys had a tremendous season with a league record of 9 wins and 3 losses. The Mohawks fell to Vauxhall in the provincial tier 1 final. They also reached the final of the 2015 High School Baseball Tournament held in Medicine Hat. One of the other highlights of the 2015 year was beating the McCoy Colts for the first time in several years.
The 2016 team is now starting their winter weight program and will soon start winter training camp. The seniors on the Mohawks baseball team look forward to pursuing more wins this year while welcoming new recruits to the program. Come out in the spring and watch the Mohawks Baseball team bring baseball to life at Medicine Hat High School once again.
This year the goal is to have a Senior and JV Team at Medicine Hat High School. The goal of the JV Team is to help introduce baseball to students and to provide them with experience for the next year when they would hope to make the senior team. The JV Team will be made primarily of grade nines with the possible addition of some grade eights from Alexandra or Roy Wilson. The JV Team will be included in all of the practices and my goal is to have a total of six games including two intersquads. There will be no cuts made to the JV Team so if someone wants to play, they will always be welcome. However, should a ninth grade student be strong enough to play on the Senior Team, they will be placed on that team.


The Mastiff was bred to be a dog that participated in war. They are gentle giants but do not get them aroused. They make natural guard dogs and watch dogs and will protect the family with their life. Actually, just seeing a Mastiff will deter everyone but the dumbest crook.
They do not need a great deal of exercise and can be lazy. Even though they do not tend to roam they should be controlled at all times in public. They can do well with other dogs if they have been extensively socialized when very young. They love older, considerate children.
As a reminder, never leave a child unsupervised with a puppy or dog. *Approximate Adult Size. The approximate adult size (two years old or older) of the Mastiff is 27 to 31 inches to the withers (highest point of the shoulder) and 150 to 190 pounds.	*Special Health Considerations. Most dog breeds have certain inherited health problems associated with that specific breed and the Mastiff is no exception.
Be on the look out for Canine Hip Dysplasia (genetic based looseness in the hip joint that can lead to arthritis pain and lameness), eye disease and bloat (Gastric Dilation-Volvulus, the second leading killer of dogs, can kill within the hour, this space is too limited for a complete explanation but you should read up on this). Feeding more then once a day and avoiding exercise right after meals may help guard against bloat. This disease list is an informative guideline only. Other diseases may also be significant threats, please contact your veterinarian for a complete list. She should visit the veterinarian several times in the first year for shots, boosters and check up.
The Mastiff has a short haired, smooth coat. She should be brushed regularly. Brushing will help her maintain a clean and healthy coat and help you keep a closer eye on her health and strengthen your emotional bond with her. Her teeth should be brushed at least twice a week with toothpaste and toothbrush designed for dogs. Brushing removes the accumulation of plaque and tartar which can cause cavities (rarely) and periodontal disease. Dog periodontal disease can lead to pain, loss of teeth, bad breath and other serious disease.
*Life Span. The Mastiff can live between 5 and 10 years with proper nutrition, medical care and excellent living conditions. *History. The Mastiff comes from Great Britain where they were once used as hunting and war dogs.
They have a history going back over 4000 years. They were first registered by the American Kennel Association in 1885. Some Registries: *Mastiff Club of America *UKC United Kennel Club *NKC National Kennel Club *CKC Continental Kennel Club *APRI Americas Pet Registry Inc. *AKC American Kennel Club *FCI Federation Cynologique Internationale *NZKC New Zealand Kennel Club *KCGB = Kennel Club of Great Britain *ANKC = Australian National Kennel Club *ACR = American Canine Registry Litter Size: 2 to 5 Mastiff puppies Category: Working Terms To Describe: Powerful, massive, courage, good nature, dignified, docile, loyal, alert, protective, *SPECIAL GOOD POINTS Makes a good watch dog. Makes a good guard dog.
Easy to groom. Generally do not roam. Is not a barker. *SPECIAL BAD POINTS Some may bite in fear. Can be a bit slow to learn and difficult to train. Maydrool and slobber.
Tends to snore. *Other Names Known By: English Mastiff, Old English Mastiff, Bandog, Alaunt *Every dog is an individual so not everything in this information may be correct for your dog. This information is meant as a good faith guideline only.


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