text:
\section{Introduction}

In recent years, several cosmological deep fields have been imaged at
20\,cm \citep[e.g.,
][]{ric00,bon03,con03,hop03,sey04,nor05,huy05,fom06,sim06,ivi07,sch07,mil08,owe08}
providing a few thousand radio sources down to flux limits of a few
10\,$\mu$Jy. These deep radio imaging data are sensitive enough to detect
star forming galaxies with star formation rates of several 10 to 100
$\>{\rm M_{\odot}yr^{-1}}$ out to and beyond a redshift of $z$\,$\sim$\,1. Similarly, radio
galaxies can be seen out to redshifts of $z$\,$\sim$\,5 and the most
luminous ones even well into the epoch of reionization. Thus, deep
radio images in conjunction with deep imaging data at X-ray, optical
and infrared wavelengths are ideal to investigate the dust-unbiased
star formation, the evolution of radio(-loud) AGN, as well as the
population mix of radio sources in the first place.

In order to study the cosmological evolution of galaxies and black
holes, it is not only important to overcome the effect of cosmic
variance (e.g. by studying a large enough area) but also to understand
the effect of large scale structure on the evolution (e.g. by covering
a large contiguous area). To address the second effect in particular,
the Cosmic Evolution Survey (COSMOS)\footnote{~\tt
  http://cosmos.astro.caltech.edu} collaboration has conducted
  panchromatic imaging and spectroscopy of an equatorial field with a
size of 2\,$\rm deg^2$ \citep[for an overview, see ][]{sco07a} ranging
from X-ray XMM-Newton and Chandra \citep{has07,elv09}, UV GALEX
\citep{zam07}, optical and near-infrared ground-based
\citep{tan07,cap07a}, optical HST \citep{sco07b,koe07}, mid- to far-infrared
Spitzer \citep{san07}, millimeter \citep{ber07,sco08} and radio VLA
\citep{sch04,sch07} imaging to extensive optical spectroscopy
using the VLT/VIMOS and Magellan/IMACS instruments
\citep{lil07,tru07}. Most of these datasets are now publicly available
from the COSMOS archive at IPAC/IRSA\footnote{~\tt
  http://irsa.ipac.caltech.edu/Missions/cosmos.html}.

The VLA-COSMOS survey at 20\,cm is part of the overall imaging effort
and its scientific goals and motivation have been described in detail
by \cite{sch07}. Initial observations from a pilot project testing the
mosaicking strategy and giving a first source catalog are presented by
\cite{sch04}. As a large NRAO/VLA program, the VLA was used in A and C
configuration to cover the entire COSMOS field resulting in an image
with uniform noise properties in the central 1$\times$1\,deg$^2$ and
an average rms of 10.5\,$\mu$Jy. \cite{sch07} provide a detailed
description of the survey set-up, the data reduction, as well as the
testing and construction of the final VLA-COSMOS Large project catalog
(hereafter: Large catalog). Subsequently, \cite{bon08} derived the
completeness of the Large catalog and also analyzed the effect of
bandwidth smearing on the derived source flux densities to obtain the
source counts. Although the VLA-COSMOS Large Project dataset has been
used for several scientific results on, e.g. the faint radio
population, the radio-derived star formation rate density, the radio
AGN population and stacking of high-z galaxy populations
\citep{smo08,smo09a,smo09b,car07,car08}, the need for deeper radio
imaging data became apparent during the search for radio counterparts
to millimeter sources from the COSMOS MAMBO mapping data
\citep{ber07}; the Large project only provided counterparts for about
half of the mm-sources. Thus, the Deep project was initiated with the
aim of doubling the integration time for the central seven pointings
which fully cover the MAMBO 1.2\,mm map of the COSMOS field. These new
observations are described here.

The paper is organized as follows: After a description of the new
observations and the data reduction (\S \ref{sec:observations}), the
revision of the Large catalog (leading to a new version of v2.0) and
the construction of the new Deep catalog are outlined in \S
\ref{sec:newLarge} and \S
\ref{sec:deepcat}. In \S \ref{sec:identify} we explain the
construction of the final Joint catalog which is described in detail
in \S \ref{sec:joint_cat} where we also present all the tests and
corrections involved. A summary is given in \S \ref{sec:summary}.

\section{Observations and data reduction}
\label{sec:observations}

The central seven pointings of the mosaic for the VLA-COSMOS Large
project \citep[pointing numbers: F07, F08, F11, F12, F13, F16, F17;
see][]{sch07} were observed using the VLA A configuration in February
and March 2006. The observations were executed on 11 days, typically
lasting for a total of six hours starting at 07hr LST (Local Sidereal
Time). The exact coordinates of the pointing centers are listed in
Tab. \ref{tab:pos}. We used the same spectral set-up and set of
calibrators as for the VLA-COSMOS Large project to allow for an easy
combination of the data from the two projects: the VLA standard L-band
continuum frequencies of 1.3649 and 1.4351\,GHz in multi-channel
continuum mode, the quasar 0521+166 (3C\,138) for flux and bandpass
calibration at the beginning of each day, and the quasar 1024-008 as
phase calibrator. In order to obtain a good sampling of the uv-plane,
we cycled three times through the pointings each day with a total
integration time per pointing of $\sim$45 min. The final resulting
integration time per pointing was $\sim$8.25\,hr. In addition, we
changed the order of the observations of the individual pointings each
day to sample the uv plane uniformly in all pointings.

During the data reduction process, we excluded all EVLA
antennas\footnote{~A total of 3 EVLA antennas were included in the
  array at the time of the observations.} that were present in the
array during the observations. We followed the data reduction
procedure adopted for the Large project \citep{sch07} which uses
the Astronomical Imaging Processing System \citep[AIPS;][]{gre03}. uv
data points affected by RFI (radio frequency interference) were again
flagged by hand using the task \texttt{TVFLAG} and by excluding amplitudes
greater than 0.55 Jy. The flux density of the phase calibrator 1024-008
was found to be close to its previous value in the season of 2004/5.
After final calibration, the Deep data were combined with the uv data
of the corresponding pointings from the Large project.

The final imaging was performed using the task \texttt{IMAGR} with the
same settings as for the Large project, i.e. the same tiling of the
individual pointings and the associated \texttt{CLEAN} boxes were
used, the flux cut-off was kept at 45\,$\mu$Jy, and the restoring beam
was again set to 1.5$''\times$1.4$''$. The robust parameter was
changed from 0 to 0.25 to obtain a dirty beam as close as possible to
the final \texttt{CLEAN} beam. As for the Large project, each
polarization for each intermediate frequency (IF) was \texttt{CLEAN}ed
separately and combined afterwards in the image plane. The final seven
new fields were combined with the existing 16 fields from the Large
project to obtain a mosaic covering the full 2\,deg$^2$ of the COSMOS
field. The average rms achieved in the central 30$'$ was 8\,$\mu$Jy/beam
at the resolution of the Large project. In order to mitigate the
effect of bandwidth smearing on the derived peak flux densities during
source extraction (see \S \ref{subsec:bwsmeth}), the final mosaic was
convolved to a lower resolution of 2.5$''$ (Fig. \ref{fig:deepimg})
leading to an increase of the rms to $\sim$12\,$\mu$Jy/beam.  We tested
several convolution kernels by comparing the source fluxes and the
number of sources extracted for two representative sub-images of the
mosaic. The resolution of 2.5$''$ provided the best compromise between
minimizing the flux losses and maximizing the number of extractable
sources. We verified that the noise distribution in the Deep image
follows a Gaussian distribution as expected (Fig. \ref{fig:rmshist}).
This Deep mosaic was used for source detection and extraction (see \S
\ref{sec:deepcat}). Fig. \ref{fig:arearms} shows the fractional area
covered as a function of rms for the Deep and Large mosaics.

\section{The Revised Large Project Catalog}
\label{sec:newLarge}

The original source catalog for the VLA-COSMOS Large Project presented
by \cite{sch07} was created by the following procedure: 1) the AIPS
task \texttt{SAD} extracted candidate components down to a peak flux
density limit of 3$\sigma$, 2) after fits to the peaks of these
candidates using \texttt{MAXFIT} only those with an measured (rather
than the fitted Gaussian) peak flux density of $\ge$4.5$\sigma$ were kept,
3) components potentially missed by \texttt{SAD} were recovered with
\texttt{JMFIT} which was used to fit a Gaussian to all peaks above our
detection threshold that were not included in the \texttt{SAD}
component list, and finally 4) components not in the \texttt{SAD} list
but with non-zero major axes found in step 3 were added.  This
component catalog was transformed into a source catalog, after
multi-component sources, e.g.  large radio galaxies, were identified
by visual inspection.  Since in the case of faint sources, the
position and peak values of a Gaussian parametric fit might not be a good
representation of the real values, the position and value of the peak
found by \texttt{MAXFIT} replaced the results from the Gaussian fit.
Furthermore, all sources classified as unresolved (for our methodology
see Section 6.2 in \citealp{sch07}) had their integrated flux
density set equal to the peak flux density. The final VLA-COSMOS Large
project catalog (v1.0) has a total of 3601 entries.

Subsequent use of the Large catalog in conjunction with the COSMOS
optical and (near- to mid-)IR catalogs and images showed that the
fraction of spurious sources increases significantly below 5$\sigma$.
Spurious sources in our definition are sources that lie in a noisier
environment than expected for a $>4.5\sigma$ detection, i.e. three or
more 3$\sigma$ peaks are present in a 10$''\times$10$''$ box centered
on the source. The misidentification is likely due to a mismatch in
the derived rms value (in a 17.5$''\times$17.5$''$ box) and the local
rms distribution at the exact position of the source. This finding is
also confirmed by a comparison of sources present in the Large and
Deep catalogs (see \S \ref{subsec:singles}). Thus we exclude all sources
below 5$\sigma$ from the revised Large catalog. In addition, the
correction for bandwidth smearing as derived by \cite{bon08} has been
applied to the peak flux densities and the classification into
resolved and unresolved sources has been modified accordingly
\citep[for details see][]{bon08}. The revised version of the
VLA-COSMOS Large project catalog [hereafter: Large catalog (v2.0)]
contains a new total of 2417 sources. The revised VLA-COSMOS Large
project catalog (v2.0) has been publicly released to the COSMOS
archive at IPAC/IRSA\footnote{~\tt
  http://irsa.ipac.caltech.edu/data/COSMOS/tables/vla/}.

\section{Identification of Deep Project Sources}
\label{sec:deepcat}

As the rms is less uniform in the Deep mosaic than in the Large mosaic
and shows a steep increase towards the edges, applying a simple flux
density cut for source detection is not possible. In order to use the
AIPS source/component finding task \texttt{SAD}, a $S/N$ map was
created. First, a sensitivity map (Fig. \ref{fig:rmsimg}) was
constructed using the AIPS task \texttt{RMSD} with a box size of
105$''\times$105$''$ to estimate the rms and a sampling step size of
2.45$''$ in both RA and DEC. To obtain the final input $S/N$ map for
\texttt{SAD}, the Deep image was divided by the sensitivity map and
blanked at the edges where the rms values in the sensitivity map
exceeded 34\,$\mu$Jy/beam (the largest rms value present in the Large
mosaic). This last step allowed us to search for sources in the
corners/edges of the mosaic, whereas the area corresponding to the
COSMOS field was searched for the construction of the Large catalog
\citep[see][]{sch07}.

\texttt{SAD} was set to search for sources in six iterations with
cut-off levels for the peak of 10, 8, 7, 6, 5, and 4$\sigma$. The
derived values in units of $S/N$ were converted to mJy/beam using the
corresponding rms values from the sensitivity map. As in the case of
the Large project sources with complex structures -- e.g. radio
galaxies -- were fitted by multiple Gaussian components, such that the
derived catalog contains components rather than real sources. In order
to identify these multi-component sources, we compared by eye the
location of the multi-component sources from the Large catalog (v2.0)
with the component list obtained for the Deep image to identify the
components belonging to the same source. During the comparison with
the Large catalog (v2.0), it was noticed that several slightly
extended sources were fitted by two separate components with a typical
separation of $\sim$1$''$ (hereafter: `twin' sources). In order to
determine the nature (simple extended Gaussian vs. truly non-Gaussian
geometry) of these 'twin' sources, a single Gauss component was fitted
to these sources using \texttt{JMFIT}. If the integrated flux density
of this single Gaussian fit was consistent within the formal errors
with the combined integrated flux densities of the two components
derived by \texttt{SAD}, we replaced the `twin' sources by a single
object.

\section{Construction of the Joint Source List}
\label{sec:identify}

Based on the size distribution of faint radio sources
\citep[e.g.][]{mux05,fom06,owe08,bon08} a significant fraction of
sources should be resolved at our flux limit and resolution.
\cite{owe08} showed that source extraction at different resolutions is
ideal to maximize the number of sources found. Therefore, the
combination of the VLA-COSMOS Large and Deep catalogs is ideal to
find a maximum number of sources for inclusion in a joint catalog.
In the following we describe the steps taken to identify such
radio sources in the VLA-COSMOS mosaics.

In order to construct a list of radio sources from the two separate
catalogs, we used the following process that is described in detail
below: First, sources present in both catalogs were included (\S
\ref{subsec:both}), then selected sources detected only in the Large Project
mosaic were added (\S \ref{subsubsec:large-only}), as were -- finally
-- a number of sources present only in the Deep catalog (\S
\ref{subsubsec:deep-only}). In order to minimize the inclusion of
spurious sources at the low significance end, the local rms was
re-examined at 1.5$''$ and 2.5$''$ resolution. All sources having a
final peak $S/N \ge 5$ at at least one resolution were included.

An overview of the number of sources selected from the Large (v2.0)
and Deep catalog for inclusion in the Joint catalog is given in Tab.
\ref{tab:vlacos}, together with a listing of some key properties.

\subsection{Estimate of the Local Background Noise}
\label{subsec:noise}

Based on the experience with the Large catalog (v1.0) it is important
to obtain an accurate estimate of the local rms to properly measure
the $S/N$ of individual radio sources. In order to find the optimal box
size for the local rms estimate, we compared the value in the rms map
used for source detection (see \S \ref{sec:deepcat}) to that obtained if
a smaller box is used. We chose a box size of
50 pixel (=17.5$''$) to obtain a good estimate of the rms around
compact sources. Fig. \ref{fig:noise} shows the different rms
values obtained with a 105$''$ and 17.5$''$ box for
a number of low $S/N$ sources from the deep catalog and highlights the
importance of deriving an accurate local rms estimate. The choice was
based on the finding that a box size of 17.5$''$ used for the Large
catalog still resulted in a number of spurious sources at the low $S/N$
end and the requirement that at 2.5$''$ resolution the number of pixels
outside the source should still be sufficient\footnote{~At an image
resolution of $\theta_{\rm B}$ (FWHM), a 17.5$''$ rms box holds
\begin{equation}
N_{\rm beam} = \nicefrac{(17.5'')^2}{\Omega_{\rm beam}}\times \eta_h = \nicefrac{(17.5'')^2}{k_p\theta_{\rm B}^2}\times \eta_h
\end{equation}
independent, hexagonally packed beams. Here $\eta_h$\,$\approx$\,0.9
is the circle packing density \citep[e.g.,][]{wells81} and $k_p$\,$=$\,1.13 for
an aperture with a Gaussian power pattern \citep{ko64, otoshi81}. Hence,
as $N_{\rm beam}(2.5'')$\,$\approx$\,40, the 5\,$\sigma$ rms estimate has
an uncertainty of about 5\,$\sigma$/$\sqrt{40}$\,$\approx$\,0.8\,$\sigma$,
which implies that the local $S/N$ could be 4.2\,$\sigma$ or less in some
regions of the mosaic. To get an upper bound on how many of our sources
that were only detected with $S/N_{17.5''}$\,$\geq$\,5 at a resolution of 2.5$''$
might be affected by this, we checked which also had $S/N$\,$\geq$\,5 in
105'' rms boxes and found that 61\% also satisfied the latter criterion. These
were assigned a flag `det'\,=\,1 in the Joint catalog, while the remaining
sources are given `det'\,=\,2, see Section \ref{subsec:catdescript}
and Tab. \ref{tab:jointcat}.}.

We constructed new rms maps at 1.5$''$ and 2.5$''$ resolution using a box
size of 50 pixels with the task {\tt RMSD} and subsequently used them to
estimate the local rms. We refer to this
revised $S/N$ as the `local' $S/N$ ($S/N_{17.5''}$). All sources with a
$S/N_{17.5''} \ge 5$ will be included in the joint source list.

\subsection{Sources Present in Both Catalogs}
\label{subsec:both}

For many sources in the Deep catalog it was possible to identify
counterparts in the Large catalog \citep{sch07} down to 5$\sigma$ or
even 4.5$\sigma$. The successfully matched sources include all but one of the objects
already known from the Large Project to consist of multiple Gaussian
components and the majority ($\sim$60\%) of the single component
sources in the Large catalog (v1.0).

\subsubsection{Identification of Single-Component Sources}
\label{subsec:singles}

To identify radio sources present in both the Deep and Large catalog,
we used the Large catalog down to 4.5$\sigma$. We matched the two
catalogs with a search radius of 1.5$^{\prime\prime}$ to account for offsets
between the peak positions for extended objects. The spatial
characteristics of the noise in the Deep and Large image differ due
the additional coverage of the central seven pointings by the Deep
project and due to the differences in the final resolution (2.5$^{\prime\prime}$
in the Deep mosaic vs. $\sim$1.5$^{\prime\prime}$ in the Large mosaic; see \S
\ref{sec:observations}).

As mentioned in Section \ref{sec:newLarge} the occurrence of spurious
sources in the Large catalog is significantly reduced by omitting
sources in the range $S/N_{\rm Large}\in$ [4.5, 5[. The added depth
gained with the Deep project observations in the central 40$'$ (Fig.
\ref{fig:effsigma}) should increase the reliability of sources with
$S/N_{\rm Large}<$ 5 in the Large Project catalog (v1.0) within
this area. Fig. \ref{fig:effsigma} shows the corresponding detection
thresholds of the two images. The peak flux densities of sources in
the Large catalog (v1.0) are plotted as a function of their radial
distance from the field center, their lower envelope roughly tracing
the average $S/N$ detection threshold of 4.5$\sigma$ (used as cut
for the Large catalog (v1.0)). The radial evolution of the mean rms
(${\rm \overline{rms}}$) was calculated in concentric rings with a
width of 2$^{\prime}$ using the respective sensitivity maps for both images
(Fig. \ref{fig:rmsimg} for the Deep mosaic and Fig. 12 in \cite{sch07}
for the Large one). The `bump' in the measured mean noise level at a
radius $r\approx$ 45$^{\prime}$ is due to the sensitivity maps'
rectangular geometry. In order to obtain an estimate of the minimal
average noise level at this distance from the field centre we fitted a cubic spline to the measured ${\rm
  \overline{rms}}$ in this region. The resulting curve for the Large
mosaic, when scaled to 4.5$\sigma$, defines a lower envelope
to the measurements (ignoring detections in sites with locally lower
rms noise). The 4$\sigma$ limit of the Deep catalog corresponds to the
4.5$\sigma$ limit of the Large catalog for the inner radii with $r \le
15'$ while it increases to the 5$\sigma$ limit of the Large catalog at
larger radial distances.

The fraction of sources in the VLA-COSMOS Large catalog (v1.0) which
are at a given distance from the field centre and have $S_{\rm peak} <
4\sigma_{\rm Deep}$ is shown in Fig. \ref{fig:effsigma}b. The increase
of this fraction with distance from the field center will affect the
radial dependence of the number of successful matches between the two
catalogs. We verified that the success rate of the catalog matching
shows no distance dependence (Fig. \ref{fig:succrate}). While the
fraction of sources in the Large catalog (v1.0) for which a
counterpart could be identified decreases at larger distances (solid
black line), the effective matching success rate defined as ratio of
the measured matching success rate and the fraction of sources with
peak flux densities below 4$\sigma$ in the Deep mosaic stays basically
constant (thick grey line) within a range of 60 and 80\%.

Thus we conclude that the direct positional correlation of catalog
entries has not caused sources to be systematically missed as a
function of (radial) field distance in the VLA-COSMOS Deep mosaic.

Before final inclusion in the source list we checked for each of the
successfully matched sources that it met our selection criterion of
peak $S/N_{17.5''} \ge 5$ at either 1.5$''$ or 2.5$''$ resolution in
the deep data. If this requirement was not satisfied the corresponding
source was not considered any further.

\subsubsection{Identification of New Multi-Component Sources}
\label{subsubsec:newmult}

As already stated above, all but one of the multi-component sources listed in the
Large catalog (v2.0) were also present in the Deep catalog. However,
during the merging of the two catalogs 43 new multi-component sources
were identified. Image cutouts of all new multi-component sources are
shown in Fig.  \ref{fig:multsrcimg}.

During the cross-correlation of the Large and Deep catalog several
sources were recognized to constitute sources made up of several
(Deep) rather than just a single (Large) Gaussian component during
visual inspection of all sources. In addition to this, several
Deep sources found in the neighborhood of multi-component objects
(identified in the Large catalog) were subsequently assigned to these
sources as additional components of their extended emission. In one
instance two of the former multiple component sources were joined to
form a new, larger multiple component source (a bipolar jet with
nucleus assigned the new Joint catalog ID
COSMOSVLADP\_J095758.04+015825.2: - the three merged components have
the following IDs in the VLA-COSMOS Large Project catalogs:
COSMOSVLA\_J095755.84+015804.2, J095758.04+015825.2 \&
J095800.79+015857.1). Besides these newly identified or augmented
multi-component sources there was also a small number of
multi-component sources that had either (i) not been previously listed
in the Large catalog or (ii) are situated outside the area searched during
the construction of the Large catalog.

\subsection{Sources present in only one catalog}
\label{subsec:singledetects}

Apart from the sources that are present in both catalogs, objects
present only in one of the two catalogs have been added to the list as
well. The exact procedures adopted are described in the following.

\subsubsection{Sources identified in the Large image only}
\label{subsubsec:large-only}

All sources in the Large catalog (v2.0) with a $S/N_{\rm Large} \geq
5$ but without a match in the Deep catalog are in principle valid
candidates for inclusion in the joint source list, provided they are not
flagged as detections potentially due to side lobes of strong radio
sources. Since \texttt{SAD} tries to fit Gaussians to all peaks above
a certain limit, the fact that certain sources were not found by
\texttt{SAD} during the construction of the Deep catalog suggests
that some of these objects might be mere noise peaks or have very
unusual morphologies. Similarly, we expect that a fraction of the
sources with $S/N<4.5$ might be real.

Therefore, we measured for all sources in the Large catalog (v1.0)
without a match in the Deep catalog the peak flux density in the Deep
image at 1.5$''$ and 2.5$''$ resolution at the according position from
the Large catalog following the steps described in \S
\ref{subsec:singcomp} and subsequently discarded 959 candidates with
$S/N_{17.5''} < 5$ at both resolutions while it was possible to
keep 393 of the unmatched sources with $S/N_{\rm Large} \geq 4.5$ from
the Large catalog (v1.0).

\subsubsection{Sources identified in the Deep image only}
\label{subsubsec:deep-only}

1155 objects -- predominantly in the range of 4$\le S/N_{\rm Deep}<$8
-- were detected in the Deep mosaic which did not have a counterpart
in the original Large catalog (v1.0). In order to assess the
significance of these sources which are potentially new detections due
to the different source extraction area for the Deep catalog, the
increased sensitivity in the central square degree and the fact that
the larger beam is more sensitive to slightly extended sources (as
\texttt{SAD} works with peak fluxes), we adopted the approach outlined
below. While the $S/N_{\rm Deep}=$ 4 cut corresponds at least to the
detection threshold used for the original Large catalog, our
experience with this catalog showed that the number of spurious
sources rises significantly below $S/N<$\,5 due to small mismatches
between the real local rms and the estimated value in the constructed
rms map.

Thus, the local $S/N$ was checked at 2.5$''$ resolution as well as at 1.5$''$
resolution. All sources with $S/N_{17.5''} \ge$ 5 were included in the
joint list. In total, 178 of 283 unmatched Deep detections
with $S/N_{\rm Deep}\geq$ 5 were taken over in the Joint catalog. Of 872
sources with 4 $\leq S/N_{\rm Deep}<$ 5 some 136 met our selection
criteria.

\section{Joint Catalog}
\label{sec:joint_cat}

In the following we describe how the flux densities and all
other measurements provided in the catalog were derived and which
corrections have been applied to the tabulated values.

\subsection{Correction for Bandwidth Smearing}
\label{subsec:bwsmeth}

Bandwidth smearing (BWS) can occur in radio synthesis imaging when a
finite frequency range is observed. It causes a radial smearing that
becomes more severe with increasing distance from the phase center (or
center of a pointing), as the phase calibration is mathematically
speaking only correct for a given frequency at the phase center. Thus
the effect is similar to chromatic aberration in optical imaging. A
detailed explanation and discussion of the effect of bandwidth
smearing for the VLA is given, e.g., by \cite{tho99} and \cite{bri99}.

For the VLA-COSMOS project with an observed bandwidth of 3.125\,MHz
for a single channel, a (final) radial smearing of 2.25$''$ is
expected at a radial distance of 15$'$ from the pointing center, i.e.
close to the cut-off radius of the individual pointings used when
creating the mosaic \citep[for equations and details,
see][]{bri99}. This bandwidth smearing effect also causes a decrease
of the peak flux density as the emission is now distributed over a
larger area. The integrated flux density, however, will not be
affected. As sources in the final mosaic can be covered by up to 7
individual pointings, the impact of bandwidth smearing strongly varies
at each location in the mosaic as a given source is separated by a
different amount from the centers of the individual pointings.

Thus, the effect of bandwidth smearing depends on the resolution
of the image. In correcting the measurements presented in the Large
catalog (v2.0) for the BWS effect \cite{bon08} adopted the approach of
boosting the measured values of the peak flux density $S_{\rm peak}$
by different amounts depending on the distance from the center of the
VLA-COSMOS field. The boost factors were derived from tests comparing
the peak flux densities of sources at the centers in individual
pointings and the derived flux densities in the final Large mosaic.
This approach can be used because the sensitivity map (cf. Fig. 12 in
\cite{sch07}) for the VLA-COSMOS Large project is fairly uniform over
significant areas, i.e. all locations suffer similarly from the
combined BWS effect of the contributing pointings. However, the
additional data for the central seven pointings for the Deep Project
changed the uniformity of the sensitivity distribution over the COSMOS
field. We thus examine both the method of \cite{bon08} as well as an
alternative based on a modeled sensitivity map for the VLA-COSMOS
Deep project.

The model sensitivity distribution for an individual pointing was
constructed using the beam pattern for a VLA antenna at 1.465 GHz, as
specified in the help page for the \texttt{AIPS} task \texttt{PBCOR}:

\begin{equation}
1 - 1.343\times10^{-3}~\mathcal{X}^2 + 6.579\times10^{-7}~\mathcal{X}^4 - 1.186\times10^{-10}~\mathcal{X}^6~,
\label{equ1}
\end{equation}

\noindent
where $\mathcal{X}$ is the product of the distance from the pointing
center in arcminutes with the observing frequency in GHz. The full
model sensitivity map (Fig. \ref{fig:modelsens}) was then assembled by
adding the individual beam patterns which were weighted according to
the observation time dedicated to each pointing (i.e., the central 7
pointings were weighted more strongly than the others by a factor of 1.4).

To estimate the magnitude of the required BWS correction we
closely follow the procedure described by \cite{bon08}. In brief, a
primary beam correction was applied to the images of the 23 individual
pointings and they were convolved to the same resolution of FWHM
2.5$^{\prime\prime}$ as the Deep mosaic. Then we measured the peak flux densities
of selected sources in these individual images and compared their
values with those obtained from the same measurement carried out at
the corresponding position in the mosaic.

At this stage, it is mandatory to use sources with a peak flux density
that has not been significantly diminished by the BWS effect. The
dimensionless parameter $\beta=\frac{\Delta
  \nu}{\nu_0}\frac{\theta_0}{\theta_{\rm FWHM}}$ (see \cite{bri99} and
the VLA observational status
summary\footnote{~\texttt{http://www.vla.nrao.edu/astro/guides/vlas/current/node15.html}})
makes it possible to infer the amount by which peak flux densities are
reduced. In the case of the VLA-COSMOS Large image with an adopted
beam width of $\theta_{\rm FWHM}\sim$ 1.5$^{\prime\prime}$ the peak flux densities
of sources within 5$^{\prime}$ of the pointing centers are expected to be
reduced by less than 5\%. At a resolution of $\theta_{\rm FWHM}\sim$
2.5$^{\prime\prime}$, as in the case of the Deep image, the same small decrease
still exists as far as 8$^{\prime}$ from the pointing center. Thus we were
able to use a contiguous area covering a significant fraction of the
entire VLA-COSMOS mosaic (see area indicated by dashed white circles
in Fig. \ref{fig:modelsens}). A correspondingly larger number of
sources could thus be used to check the validity of the adopted method
for BWS correction. In the following we will quantify the magnitude of
the BWS effect using only sources within 5$^{\prime}$ of the center of
either of the 23 VLA-COSMOS pointings -- this ensures that peak flux
densities measured on individual pointings should differ by less than
2\% from the nominal value -- and we will use the larger number of
sources out to 8$^{\prime}$ to check the quality of the approach. Since the
aim is to correct for the BWS effect introduced by overlapping
pointings, strictly speaking no (valid) corrections can be derived for
sources located in the edges (i.e. those covered by only single
pointing, see Fig.  \ref{fig:bwscorrvar}).

Fig. \ref{fig:bwscorrvar} shows the comparison of the two different
methods to correct for the BWS effect. It should be noted that the
maximum decrease observed is only 10\%. The top row displays the
uncorrected values of the quantity $\mathcal{S} =S_{\rm peak,~mosaic}/S_{\rm peak,~pointing}$, i.e. the ratio of the
peak flux densities measured in the mosaic and in an individual
pointing, as a function of normalized sensitivity (left column) and
radial distance from the field center (right column).
The median ratio
$\langle\mathcal{S}\rangle$ of peak flux densities
in a specific bin is marked by an open circle. The associated error
bars span the interquartile range of $\mathcal{S}$
within a bin in distance or model sensitivity. Median and errors are
reported in red when only sources within 5$^{\prime}$ of the center of one
of the 23 pointings are used (i.e.  only the red points) and in black
when all sources within 8$^{\prime}$ are considered (i.e. the red and grey
points).

It is obvious from the upper row of Fig. \ref{fig:bwscorrvar} that the
effect of bandwidth smearing disappears\footnote{~Note that at these
  radial distance the BWS effect can no longer be determined due to the
  lack of overlapping fields} (i.e. the value of the ratio
$\mathcal{S}$ approaches unity) towards the edge of
the field where there are no overlapping pointings or, conversely, at lower
sensitivity values which stem from regions in the field covered by
only one pointing. The best-fitting linear trends define which BWS
correction should be applied to sources lying at a given distance or
within a region of a specific sensitivity value, depending on the
method considered. In the middle row the ratios $\mathcal{S}_{\rm sensitivity~correction}$ are corrected according
to the second method using the model sensitivity map (Fig.
\ref{fig:modelsens}), i.e. the the slope of the line as a function of
sensitivity (upper left panel). Thus the distribution of $\mathcal{S}$ is
necessarily flat when plotted as a function of model sensitivity. This
flatness is also preserved when the corrected peak flux densities are
plotted against distance from the center of the field.  The BWS
correction (third row) based on the comparison of the peak flux
density ratios as a function of distance from the center of the
VLA-COSMOS field following \cite{bon08} also fares well in
straightening the distribution of corrected ratios $\mathcal{S}_{\rm distance~correction}$ with respect to both
distance (again, a requirement) and model sensitivity. However, a weak
correlation of peak flux density ratios with sensitivity is still
present after the application of this method. Therefore we conclude
that the sensitivity-based approach is slightly better for BWS
correction and will use it to compute the corrected peak flux density,
$S_{\rm peak,\,corr.}$, provided in the Joint catalog (see also Tab.
\ref{tab:jointcat}).

\subsection{Catalog Entries}

\subsubsection{Single-component sources}
\label{subsec:singcomp}

95\% of the sources in the VLA-COSMOS Joint catalog are well fit by a
single Gaussian component. The following five steps were required to
obtain the position, peak and integrated flux density, as well as the
size for each source. All measurements described in the
following were carried out on the Deep Mosaic. In particular,
this also applies to those sources which were not part of the initial
Deep catalog (see \S\ref{subsubsec:large-only}).

\begin{enumerate}

\item The (parametric) integrated flux $S_{\rm total}$ was derived
  using the task \texttt{SAD}. In the case of the `twin' sources,
  \texttt{JMFIT} was used instead (for details see \S
  \ref{sec:deepcat}). At the same time the convolved shape parameters
  were determined.

\item The peak flux density was obtained using the task
  \texttt{MAXFIT}\footnote{~Note that \texttt{MAXFIT} derives the
    maximum by fitting a quadratic function to a 3$\times$3 pixel map.
    Given that our Large (Deep) CLEAN beam is well sampled with at least 4 (7) pixels
    per axis the map value and the \texttt{MAXFIT} value agree within
    $\sim$0.2\%.}. The square search box for \texttt{MAXFIT} was
  centered on the position of the Gaussian fit from the previous step.
  We used an initial box size of 3 pixels that was increased in steps
  of 2 pixels if \texttt{MAXFIT} did not converge. The measured peak
  flux density $S_{\rm peak}$ was corrected for the effects of
  bandwidth smearing (see \S \ref{subsec:bwsmeth}) resulting in the
  corrected measured peak flux density $S_{\rm peak,\,corr.}$.

\item The source position was set to the position of the \texttt{MAXFIT}
  peak.

\item As a significant fraction of sources is resolved at the faint
  flux levels probed here, it is necessary to classify the sources
  into resolved and unresolved. We followed the approach used by
  \cite{sch07} and \cite{bon08}. The method relies on the fact that
  the ratio between integrated and peak flux density is a measure of
  the spatial extent of a radio source. A detailed description of the
  method is given in Appendix \ref{app} together with a description of
  a suite of Monte Carlo simulations which we use to calibrate our
  classification scheme. Fig. \ref{fig:resunres} is the diagnostic
  diagram used to identify the resolved sources based on our
  simulations. The line defining the lower boundary to the locus of
  resolved sources in Fig. \ref{fig:resunres} is given by the
  following equation\footnote{~Note that in previously published
    catalogs (see references above) using this approach, the line
    described by eq.  (\ref{equ2}) follows from logarithmically
    mirroring a lower envelope to the points below the line $S_{\rm
      total}/S_{\rm peak, corr.}$\,$=$\,1 above this very line. In
    Fig. \ref{fig:resunres} we show that the negative mirror image of
    eq. (\ref{equ2}) is a very conservative lower envelope of the kind
    just described. As a consequence, the classification into
    resolved/unresolved sources adopted in this paper based on the
    simulations in the Appendix, leads to a significantly larger
    fraction of sources being classified as `unresolved' in the Joint
    catalog.}:

\begin{equation}
S_{\rm total}/S_{\rm peak, corr.} = 0.35^{\nicefrac{-11}{(S/N)^{1.45}}}~,
\label{equ2}
\end{equation}

A discussion on possible systematic biases inherent to this method is
presented in the Appendix. We performed an independent check
of this classification method by adopting the {\tt JMFIT} approach
used by, e.g., \cite{mil08} and \cite{owe08}. As {\tt JMFIT} also
derives upper and lower limits on the deconvolved size of the major
and minor axis of a source, these limits can also be used to divide
sources into resolved and unresolved. If the upper limit of the major
axis was equal to zero, a source is considered unresolved. Comparison
between both methods shows that $<$1\% of our resolved sources would be
considered unresolved using the {\tt JMFIT} criterion while 66\% of
the unresolved sources would be resolved. Thus the total fraction of
resolved sources would increase to $\sim$70\% similar to the
fractions found by \cite{mil08} and \cite{owe08}. Using equation (\ref{equ2}) we have
found 405 resolved sources for which the integrated flux is given by
the total flux of the Gaussian \texttt{SAD}/\texttt{JMFIT} fit, and
2329 unresolved sources for which the integrated flux is \`a
posteriori set equal to the corrected peak flux density. These numbers
correspond to 14\% and 81\% of the sources in the Joint catalog,
respectively, while the remaining 5\% represent radio sources with
multiple Gaussian components (see following section).

\item The deconvolved source size parameters (major axis $\rm
  \theta_{M,\,dec}$, minor axis $\rm \theta_{m,\,dec}$ and position angle
  $\rm PA_{dec}$) were calculated for the resolved sources according
  to the algorithms of the \texttt{AIPS} task \texttt{JMFIT}. For
  unresolved sources all three are set to zero.

\end{enumerate}

\subsubsection{Multi-Component Sources}

For sources consisting of multiple Gaussian components the integrated
flux density was manually measured on the VLA-COSMOS Deep image with
the \texttt{AIPS} task \texttt{TVSTAT} in order to encompass all the
emission from these irregularly shaped sources. As the individual
components all have flux density peaks of their own, no peak value is
specified for multi-component sources in Tab. \ref{tab:jointcat}.
Positions were adopted from the VLA-COSMOS Large project catalogs
whenever possible. In all other cases the position was chosen on an
individual basis based on the radio morphology of the sources. In
practice this usually corresponds to a luminosity weighted mean of the
positions of the subcomponents \citep[as already done for the
multi-component sources in the Large Project catalog, see \S 6
of][]{sch07}.

Measurements of the major and minor axes along the direction of
maximal extension of the source and at right angles to the latter,
respectively, are provided for multi-component sources. However, no
estimate of the position angle is provided as it is usually impossible
to define for the complex geometry of these sources. Note that while
the coordinates were taken over, fluxes and dimensions of
multi-component objects adopted from the Large catalog (v2.0) were
re-measured in the Deep project mosaic at 2.5$''$ resolution.

\subsection{Errors on the Catalog Entries}

Below we summarize how the errors on the source properties listed in
the VLA-COSMOS Joint catalog were computed. In the case of the
single-component objects analytic formulae from the literature are
adopted. For the multi-component objects which have a manually
measured integrated flux density $S_{\rm total}$, the accuracy is about
10\% based on the comparison of repeated flux measurements on the same
objects by different people. For multi-component objects no error
estimates are provided for the source shape parameters as these are
meant as a rough measure of the angular size of the source. For the
same reason we also do not provide values for the error on the major
and minor axes of the Gaussian single component sources.

The error on the peak flux density of single component sources is
defined as the local rms noise at the position of the source.  For
unresolved sources the integrated flux density and peak flux density
are identical and hence the error on the integrated flux density also
corresponds to the local rms noise.

In calculating the error $\sigma_{S_{\rm total}}$ for resolved sources
in the VLA-COSMOS Joint catalog we follow the approach of \cite{hop03}
\citep[see also][]{bon03,sch04} based on the assumption that the
relative uncertainty $\sigma_{S_{\rm total}}/S_{\rm total}$ in the
integrated flux density is due to uncertainties $\mu_{\rm data}$ in
the data and uncertainties $\mu_{\rm fit}$ in the Gaussian fit:

\begin{equation}
\frac{\sigma_{S_{\rm total}}}{S_{\rm total}} = \sqrt{\left(\frac{\mu_{\rm data}}{S_{\rm total}}\right)^2+\left(\frac{\mu_{\rm fit}}{S_{\rm total}}\right)^2}~.
\label{equ3}
\end{equation}

\noindent The two factors beneath the square root in the equation are (see
\cite{win84} and \cite{con97}, as well as the explanations in
\cite{sch04}):

\begin{equation}
\frac{\mu_{\rm data}}{S_{\rm total}} = \sqrt{\left(\frac{S}{N}\right)^{-2}+ 0.01^2}
\label{equ4}
\end{equation}

\noindent (where $S/N=S_{\rm peak}/{\rm rms}$) and

\begin{equation}
\frac{\mu_{\rm fit}}{S_{\rm total}} = \sqrt{\frac{2}{\rho_S^2}+\left(\frac{\rm \theta_B \theta_b}{\rm \theta_M \theta_m} \right)\left(\frac{2}{\rho_{\rm M}^2} + \frac{2}{\rho_{\rm m}^2}\right)}~.
\label{equ5}
\end{equation}

\noindent Here ${\rm \theta_{B}}$ and ${\rm \theta_{b}}$ are the major and minor
axis of the beam (in the present case of a circular beam ${\rm
  \theta_{B}}={\rm \theta_{b}}=$ 2.5$^{\prime\prime}$) and, analogously, ${\rm
  \theta_{M}}$ and ${\rm \theta_{m}}$ the major and minor axis of the
measured (i.e. convolved) flux distribution. The $S/N$ values of the fit --
$\rho_S$, $\rho_{\rm M}$, and $\rho_{\rm m}$ -- are parameter-dependent:

\begin{equation}
\rho_X^2 = \frac{\rm \theta_M \theta_m}{\rm 4\theta_B \theta_b}\left(1+\frac{\rm \theta_B}{\rm \theta_M}\right)^{\alpha}\left(1+\frac{\rm \theta_b}{\rm \theta_m}\right)^{\beta}\left(\frac{S}{N}\right)^2~,
\label{equ6}
\end{equation}

\noindent
with $\alpha=\beta=$ 1.5 for $\rho_S$, $\alpha=$ 2.5 and $\beta=$ 0.53
for $\rho_{\rm M}$, and $\alpha=$ 0.5 and $\beta=$ 2.5 for $\rho_{\rm
  m}$.

The errors on the position of single-component sources are

\begin{eqnarray*}
\Delta\alpha &=& \sqrt{\epsilon_{\alpha}^2 + \frac{\rm \theta_M^2}{4~{\rm ln(2)}\rho_S^2}~{\rm sin(PA)}^2 + \frac{\rm \theta_m^2}{4~{\rm ln(2)}\rho_S^2}~{\rm cos(PA)}^2}\\
\Delta\delta &=& \sqrt{\epsilon_{\delta}^2 + \frac{\rm \theta_M^2}{4~{\rm ln(2)}\rho_S^2}~{\rm cos(PA)}^2 + \frac{\rm \theta_m^2}{4~{\rm ln(2)}\rho_S^2}~{\rm sin(PA)}^2}~,
\end{eqnarray*}

where $\epsilon_{\alpha}=\epsilon_{\delta}={\rm \theta_B}/10 \approx
0.25''$ are the positional calibration errors on right ascension and
declination and PA is the measured position angle of the Gaussian fit.

\subsection{Description of the VLA-COSMOS  Joint Catalog}
\label{subsec:catdescript}

The information on the procedures and equations used to calculated
each entry in the VLA-COSMOS Joint catalog has been presented above.
For each source we list the source name, the ID of the source in the
VLA-COSMOS Large Project catalogs (where available), as well as the
derived source properties and the associated errors. Furthermore, the
source properties and flags associated with each object are explained.
All 2865 radio sources in the VLA-COSMOS Joint catalog are listed by
increasing right ascension in Tab. \ref{tab:jointcat} with the
following columns:
\\
\\
Column(1): Source name
\\[1ex]
Column(2): Source name in VLA-COSMOS Large Project catalog (set to
J999999.99+999999.9 if not present in the VLA-COSMOS Large catalog)
\\[1ex]
Column(3): Right ascension (J2000.0) in degrees
\\[1ex]
Column(4): Declination (J2000.0) in degrees
\\[1ex]
Column(5): Right ascension (J2000.0) in hexagesimal format
\\[1ex]
Column(6): Declination (J2000.0) in hexagesimal format
\\[1ex]
Column(7): rms uncertainty in right ascension in arcseconds
\\[1ex]
Column(8): rms uncertainty in declination in arcseconds
\\[1ex]
Column(9): Peak flux density and its rms uncertainty in mJy/beam
\\[1ex]
Column(10): Peak flux density corrected for bandwidth smearing in
mJy/beam
\\[1ex]
Column(11): Integrated flux density and its rms uncertainty in mJy
\\[1ex]
Column(12): rms measured in the \texttt{RMSD} sensitivity map in
mJy/beam
\\[1ex]
Column(13): Deconvolved major axis size ${\rm \theta_{M,\,dec}}$ in
arcseconds
\\[1ex]
Column(14): Deconvolved minor axis size ${\rm \theta_{m,\,dec}}$ in
arcseconds
\\[1ex]
Column(15): Deconvolved position angle of source ${\rm PA_{dec}}$
(counterclockwise from North) in degrees
\\[1ex]
Column(16): Flag for resolved and unresolved sources\footnote{~Note
  that the flag value of `-2' is only assigned to sources that were
  not in the VLA-COSMOS Large Project catalog. The flag `-1', on the
  other hand, is used for sources that were classified as resolved in
  the Large Project
  catalog but are listed as unresolved in the Joint catalog.}\\
\begin{tabular}{rcl}
-2 &--& unresolved only in VLA-COSMOS Deep image\\
-1 &--& resolved only in VLA-COSMOS Large image\\
 0 &--& unresolved in both VLA-COSMOS Large \&\\
 & & Deep images\\
 1 &--& resolved in both VLA-COSMOS Large \& Deep\\
 & & images\\
 2 &--& resolved only in VLA-COSMOS Deep image\\
\end{tabular}
\\[1ex]
Column(17): Flag for distinction of multi-component and single-component sources\\
\begin{tabular}{rcl}
0 &--& single component source\\
1 &--& multi-component source identified in VLA-COS-\\
& & MOS Large image\\
2 &--& multi-component source identified in VLA-COS-\\
& & MOS Deep image\\
\end{tabular}
\\[1ex]
Column(18): Flag for catalog membership\\
\begin{tabular}{rcl}
-1 &--& only detected in the VLA-COSMOS Large image\\
 0 &--& detected in both the VLA-COSMOS Large \& \\
 & & Deep image\\
 1 &--& only detected in the VLA-COSMOS Deep image\\
\end{tabular}
\\[1ex]
Column(19): Flag specifying at which resolution the source was detected with $S/N_{17.5''}\geq$ 5
\begin{tabular}{rcl}
-1 &--& detected with $S/N_{17.5''}\geq$ 5 only at a resolution\\
 & &  of 1.5$''$\\
 0 &--& detected with $S/N_{17.5''}\geq$ 5 at both 1.5$''$ and 2.5$''$ \\
 & & resolution\\
 1 &--& detected with $S/N\geq$ 5 only at a resolution of \\
 & & 2.5$''$, but in both the large and\\
 & & small scale (105$''$ and 17.5$''$ box size, respectively)\\
 & & rms map\\
 2 &--& detected only with $S/N_{17.5''}\geq$ 5 (but not in the \\
 & & large scale rms map) at a\\
 & & resolution of 2.5$''$\\
\end{tabular}

\subsection{Comparison between Large (v2.0) and Joint Catalog}

We compared the source properties in the flux-limited Large catalog
(v2.0) and in the Joint catalog for
those 2256 catalog entries which are common to both catalogs. The
different resolution in the VLA-COSMOS Deep and Large mosaics leads to
a different sensitivity to extended emission.  Hence, source shape
parameters cannot be expected to show exact agreement between the two
catalogs. Therefore the comparison is limited to the peak and
integrated flux densities. The results of the comparison are
illustrated in Fig. \ref{fig:peakcomp} and Fig. \ref{fig:totcomp}
for the peak and integrated flux density, respectively. In particular,
it is instructive to compare the peak values of sources that are
classified as unresolved in both catalogs.  These sources are
highlighted in light grey in Fig. \ref{fig:peakcomp} and are seen to
scatter well around the diagonal line of 1:1 correspondence between
the measurements from the Joint and Large mosaics.  The comparison of
the integrated flux densities (Fig. \ref{fig:totcomp}) shows that there is a
small population of objects (light grey points) lying above the
diagonal (i.e. their integrated flux density is higher in the Joint
catalog). These objects are sources that were previously classified as
unresolved but have acquired the status of resolved in the Joint
catalog, implying that their integrated flux densities have
necessarily increased when measured in the Deep mosaic. This class of
objects accounts for nearly all of the outliers in the plot.
Multi-component sources (dark grey crosses) in general lie also above
the diagonal bisector, reflecting the enhanced sensitivity to extended
emission in the Deep image. For most other objects the new and
previous estimate of integrated flux density is in good agreement and
hence also with flux density estimates of the NVSS and FIRST surveys
as shown in \cite{sch07}.

\section{Summary}
\label{sec:summary}

Continued analysis of the VLA-COSMOS catalog presented in \cite{sch07}
and the completion of the VLA-COSMOS Deep project motivated the
compilation of a new radio catalog for the COSMOS field. The
VLA-COSMOS Joint catalog was generated by combining the catalogs
of the VLA-COSMOS Large Project with a newly created source catalog
(Deep catalog) from the 2.5$''$ resolution Deep mosaic. This catalog is
already available for download by the public at the COSMOS archive at
IPAC/IRSA\footnote{~~\texttt{http://irsa.ipac.caltech.edu/data/COSMOS/tables/vla}}.
A comparison of the depth and areal coverage for a representative
sample of deep field radio surveys at 1.4\,GHz shows that the
VLA-COSMOS covers the largest area at its depth and angular
resolution (Fig. \ref{fig:radio_surveys}). Thus it should be well
suited to also study effects of the Large Scale Structure on the
presence/absence of radio emission.

The reduction and analysis of the deeper 20\,cm observations of the
central 7 pointings of the VLA-COSMOS projects using the VLA in A
configuration have been described in detail (also referred to as
VLA-COSMOS Deep project). In order to minimize the effect of bandwidth
smearing the Deep mosaic has a resolution of 2.5$''$ (compared to 1.5$''$
for the Large mosaic) and it was used to create a corresponding source
catalog using the task \texttt{SAD}.

An input list for the new Joint catalog was compiled by combining the
revised Large catalog (v2.0) and the new Deep catalog. The criteria
were set such that no particular bias against slightly extended radio
sources was present when selecting the sources. All properties of the
radio sources listed in the Joint catalog have been derived in the
2.5$''$ resolution Deep mosaic.

The construction of the Joint catalog was motivated by the desire to
provide a catalog of bona-fide radio sources in the COSMOS field for
distinct science applications that are interested in the radio
properties of certain populations of galaxies. On the other hand the
revised Large catalog (v2.0) is flux-limited (in radio), has a fairly
uniform sensitivity coverage and its completeness is well
characterized \citep[see][]{bon08}, thus it is well suited for, e.g.,
studies of the faint radio population
\citep[such as, e.g.,][]{smo08,smo09a,smo09b}.

redpajama_set_name: RedPajamaArXiv


text:
Picking up Your High School Sport as an Adult
I started to play tennis again after I took a break in high school, and I never should've stopped
Photo by Guilherme Maggieri on Unsplash
My grandpa was a Pete Sampras guy; I was more of an Agassi fellow myself. The first tennis racket I held was an old school, Wilson wooden racket that my Grandpa owned. Funny enough, I was exposed to the sport of tennis early on when I would watch matches on TV with my gramps, but I didn't actually play tennis until my 3rd year of high school.
On top of that, I only played for two years, IF that. I mostly played during Spring, but nothing extensive after the season was over. I didn't play for a club or a summer team, and when I graduated from high school, I took a hiatus from the sport altogether. I learned enough to hit a solid looking forehand (don't ask me about the outcome, but the groundstroke looked nice).
I want to say anywhere between 6–9 years have passed since I picked up a racket. I play at least once a week with one of my old high school teammates and a good friend. I stopped wishing for things to happen in my life, but if I could make one change about my past, it would get myself involved with tennis earlier and stay consistent with the sport throughout my upbringing.
Tennis, like golf and really every sport — can be mentally draining. My coach used to preach to us during practice,
"Even if there is someone in front of you, you're still playing against yourself."
I reflect on what he says now with some maturity behind me and some wisdom, and it makes more sense to me now than it did when I first heard it. Fundamentally if your groundstrokes aren't mechanically correct, it'll be difficult to get the ball back into play but hit the ball in ways where it makes it harder for the opponent to respond.
Suppose you're playing to hit winners down the line and hitting big shots rather than focusing on consistency. The mindset of getting better each time versus winning will impede progress. This is an approach that I understand better now as I'm in my late twenties.
It's an approach that can be applied across most things outside of tennis and outside sports in general. When your foundation is solid, that's when the creativity comes through.
As a tennis fan, Roger Federer is so asthetically pleasing to watch; it's insane. At 39 years of age, he's still my favorite player to watch to this day. The way he plays the game looks so effortless; it's a thing of beauty. The amount of time and reps that he put in to get to that level is nothing short of mastery.
Time and repetition.
The two components to progress that transcend across anything in one's life. I played tennis last weekend for 3.5 hours and loved every single second of the time I spent on the court. Every time I hit with my friend, I always bring up the gap between high school and now.
What if I continued to play tennis for the past 6–9 years. It's not about the possibility of playing tennis at a pro-level, but the curiosity about how good someone could get within that time frame. The number of reps one could accomplish in those years would've been an amazing thing to document. That is the ultimate What if for me, but I realize that I now have that opportunity. I'm older, yes, but I have the opportunity now to play tennis for years to come consistently.
This is how I see all hobbies that I care about, including writing. Now the question is,
What will 5 years look like for my tennis game and what will 5 years look like for my writing?
What will 5 years from now look like for your goals or hobbies? It's an exciting thing to look forward to, and I hope that everyone enjoys the journey along the way.
More from Jason Tolete
My Experience with Gendai Ninjutsu
Part 1 of a multi-part non-fiction series.
Poker Faces in the Crowd: DGAF
There's one word, more than any other, that gives grinders nightmares. Can you guess what it is? Here's a hint. One day you sit in a…
Joe DiMaggio's 'storybook fashion' and the history of Yankees walk-off triples
Pete Rose Can Keep His Record, But Ichiro Suzuki Is the All-Time Hits King
VVMMAF has made its official debut
HANOI — The Vietnam Mixed Martial Arts Federation (VMMAF) has officially made its debut on May 30.
It Was a Sad Ending for the '69 Vikings
From the late 1960s through the late 1970s, the Vikings' storyline was great promise followed by bitter disappointment. It all started in…
Spotting the Ball in Football is Complete and Utter Guesswork (A Treatise on Football's…
Diego Maradona was a player who when I was growing up I always knew he was one of the greatest to ever play the game of football despite…
Passion can be learned through habbits
Many talented and famous people set their eyes on goal from young age, spent time to develop skills for it ever since. Comfort and love for…
Daily Post #93 More 3s; the Three T's of Entrepreneurship
Getting Prolific, Day 37: Using Creations to Connect
How to Get Your White Belt in Jiu-Jitsu.
It's not easy by any means. Here's what I did.

redpajama_set_name: RedPajamaCommonCrawl


On August 18, we celebrated National Honey Bee Day across the country with the help of influential foodies, some amazing chefs and impressive photographers.
We all know that honey bees make honey, but did you know they are responsible for so many more items that we eat every day? From almonds and avocados to vanilla and zucchini, there are a number of fruits, vegetables, nuts and spices that would be in short supply without our fuzzy friends. With all they do for us, it's only right that we celebrate them! So, on August 18, influential foodies across the country joined us to celebrate National Honey Bee Day!
Attendees also received tips and tricks from seasoned food photographers on how to get those perfect Instagram-worthy shots (because we all know – when we're not doing it for the bees, we're doing it for the 'gram)! To see some of their photos and read about what they learned, check out #FeedABee on Instagram.
National Honey Bee Day may have passed for this year, but you can celebrate bees every day. Honey bees do such a great job of feeding us, and we can help feed them. By planting pollinator-attractant forage in your garden or community, you help bees get the food they need. However, some forage will only flourish in specific regions and climates. To find out what plants and flowers grow best in your state, head to http://pollinator.org/guides.


text:
Texas Gov. Abbott Says Biden "AWOL", Enlists Help of National Guard to Arrest Over 7,700 Illegals
Yesterday, we reported that a new migrant caravan of thousands- organized by QR code- was heading to the United States.
This caravan is said to be more organized and more extensive than before.
Amid this crisis at our southern border, the Biden administration is MIA.
What kind of President refuses to visit the site of an emergency?
Trending: Did the CDC Director Suggest Re-Education Camps For Unvaccinated Police & Government Workers?
At the very least, Biden should be offering the Lone Star state help.
The Biden administration's silence is deafening.
Governor Greg Abbott isn't going to let his border be blind-sighted by the caravan.
Calling Biden "AWOL" and "MIA," Abbott has taken swift action to secure the border at the Del Rio Bridge.
The Texas National Guard can be seen in aerial footage Abbott released on his Twitter earlier today.
In his tweet, Abbott claims Texas continues to pump resources and personnel to secure the southern border.
Aerial footage of Texas National Guard resources positioned at Del Rio bridge.
While the Biden Administration is MIA, the Lone Star State continues to surge resources and personnel to secure our border. pic.twitter.com/1wRzZy0hQm
— Greg Abbott (@GregAbbott_TX) October 26, 2021
God bless Texas!
Fox News has more on the story:
Texas Gov. Greg Abbott told "America's Newsroom" on Monday that President Biden is "AWOL" and has abandoned the border, leaving his state's national guard and police to handle security.
GREG ABBOTT: I was on the border yesterday working with both the Texas National Guard as well as the Texas Department of Public Safety as we are preparing for the potential arrival of this caravan understand this, and that is the Biden administration is AWOL. The Biden administration has abandoned any pretense of securing the border, and it's left only to the state of Texas to step up and to secure our own border.
As a result, we have thousands of National Guard as well as Texas Department of Public Safety Officers, including Texas Rangers, making sure that we are providing the resources we need to secure the border, as well as Texas is in the process of building a wall, as well as making arrests of people coming across the border illegally and trespassing in the state of Texas.
That said, what we expect to be able to do if you go back a couple of weeks ago when you saw the number of people coming across Del Rio. We formed a human barricade to prevent those people from coming into the state of Texas. We are identifying locations where these other caravans may be coming to. For that same purpose of trying to cross the border at low water crossing areas, and we are working to barricade those areas as we speak right now.
It seems Abbott's use of the Texas National Guard is successful.
Thus far, the Texas National Guard has helped law enforcement officers arrest over 7,700 migrants!
https://t.co/Zh3y1A3G4z
7700 arrests at the border?
— X (@tzeniel) October 24, 2021
These migrants were arrested on state charges of entering the US without authorization.
A spokesperson for Governor Greg Abbott confirmed this information.
The Texas Department of Public Safety said the federal government "should be thanking the state of Texas" for its efforts to secure the border.
Corpus Christi Caller Times has more:
Troops from the National Guard deployed to the Texas-Mexico border have assisted law enforcement officers in arresting more 7,700 migrants on state charges who have entered the United States without authorization, a spokeswoman for Gov. Greg Abbott confirmed Thursday.
"The governor has directed DPS troopers to enforce all federal and state criminal laws, including criminal trespassing, smuggling, and human trafficking, and in July ordered National Guard soldiers to begin assisting DPS with arresting individuals for state charges related to the border crisis," Abbott spokeswoman Renae Eze said in a statement to the USA TODAY Network.
In addition, Guard troops and officers with the Texas Department of Public Safety have have apprehended more 73,000 migrants since Abbott launched what he has called "Operation Lone Star" to assist federal authorities in the effort to stem unauthorized immigration from Mexico.
Eze provided the statistics after the Center for Immigration Studies, a conservative think tank that monitors unauthorized immigration trends, quoted DPS Director Steven McCraw as saying that use of the Guard troops in such a manner was unprecedented.
"Nobody's ever really used the Guard before in this capacity," McCraw told the organization. "We're going to use them to actually secure the border. The governor, the Legislature, and the citizens of Texas have made it very clear they want the border secure.
"The federal government should be thanking the state of Texas."
McCraw, whose agency employs more than 3,200 troopers across Texas, accompanied Abbott when he hosted nine of his fellow Republican governors at the southern border earlier this month. McCraw echoed many of the criticisms directed at the current administration's immigration policies, saying in his brief remarks that Texas does not need "the federal government's permission" to secure its borders.
In addition to deploying Guard troops from Texas and other states to the border, Abbott recently signed off on the state allocating $3 billion for border-security measures over the next two years.
It appears Abbott wants arrests at the southern border to take priority.
Migrants charged with state crimes must stay in Texas and go through Texas courts.
If not, the migrants get immediately turned over to federal immigration authorities.
No more catch and release for Texas!
Now, Texas can use the law to the full extent to jail and prosecute criminals in their state courts.
If anyone thinks this isn't a good move, check out the footage below from Governor Abbott.
The Texas National Guard found migrants in RAIL CARS.
Texas Dept. of Public Safety arrest illegal immigrants hiding in rail cars.⁰
They will be put behind bars, not sent to Border Patrol for catch & release.
⁰@TxDPS, along with the Texas National Guard, have made thousands of arrests this year through #OperationLoneStar. pic.twitter.com/TGSqflH9l0
The single adult men were hoping to use the train to get further into the US.
Many migrants are gang and cartel members.
Migrants have been hitching rides and hiding on trains, but now they are getting arrested and receiving justice.
Thankfully, Texas doesn't believe in catch and release!
You can watch the full clip from Tucker Carlson onFox News about the illegal immigrants hiding in rail cars below:
YouTube Bans "Let's Go Brandon" Song While It Ascends iTunes Charts
WE WERE RIGHT: Joe Biden's Booster Jab Was 100% Faked! Fox News Confirms!
Biden Team Hints at Incoming "Greater Good" Changes
BREAKING: U.S. Federal Appeals Court Halts Biden's Vaccine Mandate!
Washington State's Head Football Coach Has Been Fired After Refusing To Get Vaccinated
Hank Kunneman: The Spirit That Has Tried To Delay The Harvest, Has Come Down!


text:
Q: Can I use a DependencyProperty for this? I have an ObservableCollection with Students. Each Student has a Grade Property. I want the AverageGrade property (of all students) to work without having to press a button or creating a timer.
How do I use a DependencyProperty here for this read-only AverageGrade Property?
Student.cs
using System.ComponentModel;
using System.Windows;
using System;

namespace WpfApplication17.Models
{
    class Student : INotifyPropertyChanged
    {
        #region Constructors

        public Student(string firstName, string lastName, double grade)
                                {
            this.FirstName = firstName;
            this.LastName = lastName;
                this.Grade = grade;
        }

                        #endregion

        #region Properties

                private string _firstName;

        public string FirstName
        {
            get { return _firstName; }
            set
            {
                _firstName = value;
                OnPropertyChanged("FirstName");
            }
        }

        private string _lastName;

        public string LastName
        {
            get { return _lastName; }
                            set
                {
                _lastName = value;
                OnPropertyChanged("LastName");
                    }
            }

        private double _grade;

        public double Grade
        {
        get { return _grade; }
        set
        {
            _grade = value;
            OnPropertyChanged("Grade");
        }
    }

    #endregion

    #region PropertyChanged

    public event PropertyChangedEventHandler PropertyChanged;

    public void OnPropertyChanged(string propertyName)
    {
        if (PropertyChanged != null)
            PropertyChanged(this, new PropertyChangedEventArgs(propertyName));
    }

    #endregion
}

}
MainWindowViewModel
using WpfApplication17.ViewModel;
using System.Collections.ObjectModel;
using WpfApplication17.Models;

namespace WpfApplication17.ViewModels
{
    class MainWindowViewModel : ViewModelBase
    {
        #region Constructors

        public MainWindowViewModel()
        {
            Students = new ObservableCollection<Student>();
            Students.Add(new Student("Frank", "Sinatra", 7));
            Students.Add(new Student("Bart", "Simpson", 6));
        }

        #endregion

        #region Properties

        private ObservableCollection<Student> _students;

        public ObservableCollection<Student> Students
        {
            get { return _students; }
            set
            {
                _students = value;
                OnPropertyChanged("Students");
            }
        }

        public double AverageGrade
        {
            get { return GetAverageGrade(); }
        }

        public double GetAverageGrade()
        {
            double sum = 0;

            foreach (Student s in Students)
                sum += s.Grade;

            return sum / (double)Students.Count;
        }

        #endregion
    }
}

MainWindow.xaml
<Window x:Class="WpfApplication17.MainWindow"
        xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation"
        xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"
        Title="MainWindow" Height="350" Width="525">
    <StackPanel Orientation="Horizontal">
        <DataGrid ItemsSource="{Binding Students}" />
        <Label Content="Average Grade:" />
        <Label Content="{Binding AverageGrade}" />
    </StackPanel>
</Window>

A: Why you want DP for that it seem like normal VM property take care of this.
What you need is whenever new student is added or existing student's grade is changed, AverageGrade must be updated.
Maybe try this approach:
    class MainWindowViewModel
{
    #region Constructors

    public MainWindowViewModel()
    {
        Students = new ObservableCollection<Student>();
        Students.Add(new Student("Frank", "Sinatra", 7));
        Students.Add(new Student("Bart", "Simpson", 6));

        Students.CollectionChanged += (s, e) => AverageGrade = this.GetAverageGrade();

        foreach (var student in Students)
        {
            student.PropertyChanged += OnStudentPropertyChanged;
        }

        AverageGrade = this.GetAverageGrade();
    }

    private void OnStudentPropertyChanged(object sender, PropertyChangedEventArgs e)
    {
        if (e.PropertyName == "Grade")
        {
            AverageGrade = this.GetAverageGrade();
        }
    }

    #endregion

    #region Properties

    private ObservableCollection<Student> _students;

    public ObservableCollection<Student> Students
    {
        get { return _students; }
        set
        {
            _students = value;
            OnPropertyChanged("Students");
        }
    }

    private double average;
    public double AverageGrade
    {
        get
        {
            return this.average;
        }
        set
        {
            this.average = value;
            OnPropertyChanged("AverageGrade");
        }
    }

    public double GetAverageGrade()
    {
        return this.Students.Sum(s => s.Grade) / Students.Count;
    }

    #endregion

    public event PropertyChangedEventHandler PropertyChanged;

    public void OnPropertyChanged(string propertyName)
    {
        if (PropertyChanged != null)
            PropertyChanged(this, new PropertyChangedEventArgs(propertyName));
    }
}

redpajama_set_name: RedPajamaStackExchange


Although Holy Trinity is known for its warm welcome, in a church of its size there can sometimes only be limited opportunities to get to know folk really well, and it could be all too easy to feel a bit "isolated".
This is why we have House Groups.
These are small groups, which meet on a fortnightly basis (usually during school term times), where friendships can be made and faith deepened, as we gather to study the Bible, pray and praise together, provide pastoral support where needed, as well enjoying social activities. The vision is for these to be a form of "mini Holy Trinity" whenever they meet.
We currently run a good number of groups (there is a least one meeting on each of the days during the week), of differing styles and profiles. While most meet in the evenings, there are some that meet during the day.


text:
Our Vision in Action
Research & Teaching Quality
Faculties, Schools & Research Units
Recruit & Develop Talent
Procuring Goods & Services
National Innovation Centre for Ageing
National Innovation Centre for Data
Research Strengths
Global Challenges Academy
Medical Science Research Fellowships
Doctoral College
Newcastle University London
Newcastle University in Singapore
NUMed Malaysia
Professional & Executive Development
Information for Schools & Colleges
Computing (NUIT)
Congregations (graduation)
Verification documents
Paying Tuition Fees
Paying Accommodation Fees
Newcastle University > Engineering, School of > Events
Vehicle emissions research using telematics data
Speaker: James Tate (Leeds University)
Date/Time: 13 December 2017; 13:00-14:00
Venue: Cassie Building 2.32
High resolution, high quality telematics data is now routinely collected from a growing proportion of passenger cars and commercial vehicles. Telematics providers are not only collecting data for vehicle logistics and security services, but also to support the motor insurance industry develop products tailored to a customer's use of a vehicle. Telematics data is therefore moving away from being biased by a limited sample of commercial fleets with professional drivers, towards pervasively surveying the real traffic movements and driving behaviour of a growing share of the general passenger car fleet.
Telematics data offers the opportunity to move away from modelling average traffic situations (e.g. weekday AM and PM peak periods) with aggregated emissions factors, to systematically studying the impact of the real-life variations in traffic flow and congestion over complex networks due to incidents, special events, changes in weather conditions and fluctuations in traffic demand.
A sample of over 56,000 kms of quality checked second-by-second real driving trajectory records has been recorded through a calendar year for a study area 1km west of Leeds City centre. The study area has been identified as the only urban area in the North of England (UK0004) to fail to achieve the EU nitrogen dioxide (NO2) annual average directive in 2020.
The links of most concern are the A58 and A58M (two and three-lane urban motorway). The road network incorporates several multi-lane and multi-level intersections which are frequently heavily congested inside and outside AM and PM peak periods. Traditional traffic and coupled emission modelling methods would struggle to model this complex environment with any degree of certainty.
An automatic number plate recognition (ANPR) survey was also conducted over the course of the week commencing 16 April on the main A58(M) road. These vehicle number plates were cross-referenced with the UK registration database so the local vehicle fleet mix in different time periods was known. The raw vehicle activity data has been supplemented with predictions of tail-pipe emissions (CO2, NOX, NO2, PM, PN, CO, HC) from the European instantaneous emission model PHEM (Hausberger et al, 2014), scaled according to the local fleet mix and total traffic flow (measured by in-situ automatic traffic counters).
The seminar will describe the methods and visualise the spatial and temporal variations in traffic flows, speeds and associated emissions. Work in progress is assessing the impact of different CAZ scenarios.
Working with Business & Government
Newcastle University, NE1 7RU, United Kingdom,
Telephone: (0191) 208 6000 From outside the UK dial +44 191 208 6000.
Email web editor
University site index
Last updated 3 December 2019 © Newcastle University


One of the most comprehensive sound collaborations I've ever undertaken. One month of recordings, an entire lunar cycle, Maja Jantar and I exchanged sonic responses to the moon over the summer, including poem, songs, found recordings, mixed for publication. I was the 11th collaborator in Maja's remarkable series. This was a brilliant, often intense process, another lovely moment in a series of works I've had the pleasure to collaborate on with Maja. And as before, I learned an extraordinary amount working with her, with her in my mind as I tried to keep up to the daily recording schedule. I'm proud of the result, it's extensive, a real record of a time in my life.


text:
Plymouth-Canton Community Calendar
The Plymouth-Canton Community Calendar offers a listing of upcoming activities and events.
Plymouth-Canton Community Calendar The Plymouth-Canton Community Calendar offers a listing of upcoming activities and events. Check out this story on HometownLife.com: http://www.hometownlife.com/story/news/local/canton/2015/10/25/plymouth-canton-calendar/74468074/
o&e media Published 12:07 a.m. ET Oct. 25, 2015 | Updated 12:07 a.m. ET Oct. 25, 2015
Narrator El Gallo, played by Anirudh Keshamouni, manipulates Luisa and Matt, played by Mackenzie Grosse and Ryan Wagner, like puppets on strings, in "The Fantatasticks."(Photo: Bill Bresler | staff photographer)Buy Photo
'Fantasticks'
Time/Date: 7 p.m. Friday, Oct. 30, and Saturday, Oct. 31
Location: Canton High School's DuBois Little Theatre
Details: The Park Players will bring their version of The Fantasticks, the long-running off-Broadway musical, to Canton High School's DuBois Little Theatre. The cast includes Ali Ghannam (Henry), Rishi Mahesh (Bellomy), Anirudh Keshamouni (El Gallo), Mackenzie Grosse (Luisa), Amanda Barberena (The Mute), Ryan Wagner (Matt), Jasper Hrubiak (Mortimer), and Brett Moore (Hucklebee).
Cost: Tickets are $12 each and will be available at the door or can be reserved by emailing director Shannon McNutt at Shannon.McNutt@pccsk12.com. Group discounts are available.
Time/Date: Noon to 4 p.m. Sunday, Oct. 25
Location: Old Village streets
Details: The Old Village Association will hosts its ninth annual Haunted House
Time/Date: 10-11 a.m. first and third Thursday of each month
Location: Panera Bread, 41950 Ford Road, Canton
Details: Compassionate Coffee Club is an open and ongoing grief support group offering support and socialization for widows and widowers moving beyond the first year of loss. The program is sponsored by Compassionate Care Hospice.
Cost: Free, but drink purchase is required for use of space
Contact: Ann Kozma, Compassionate Care Hospice Bereavement Coordinator at 888-983-9050, or email achristensen@cchnet.net.
Grief matters
Time/Date: 2-3:30 p.m. Sunday, Dec. 6
Location: Plymouth District Library, 223 S. Main Street, Plymouth
Details: To help individuals coping with grief, Arbor Hospice & Palliative Care offers a supportive caring environment to work through the loss. This special workshop will give you helpful tips for coping with the upcoming holidays. Support groups and events are open to everyone, regardless of whether their loved one received services from Arbor Hospice & Palliative Care. All programs are limited to 12 participants and registration is required at least one week in advance.
Contact: Sara Swanson at 734-794-5469 or sswanson@arborhospice.org; http://www.arborhospice.org
Halloween dentistry
Time/Date: 2-7 p.m. Friday, Oct. 30
Location: Plymouth Dentistry, 40400 Ann Arbor Road, one block west of I-275
Details: Dr. Gary Feucht and the staff at Plymouth Dentistry invite the community to join them for a Halloween Party. There will be food and refreshments, fun Halloween activities and an opportunity to walk the "haunted hallway."
Pucks for Pasadena
Time/Date: 7 p.m. Tuesday, Nov. 24
Location: USA Hockey Arena, 14900 Beck, Plymouth Township
Details: Plymouth Township, Plymouth, Canton Township and Wayne County are joining forces to help raise money to send the Plymouth-Canton Marching Band to Pasadena to perform in the Tournament of Roses Parade in January. The Red Wings Alumni will play against the USA Hockey's National Development Program in a game, with all proceeds to support the marching band.
Contact: Committee chair Jim Harb at 734-502-0645 or jharb@gsfmail.com. For sponsorship, contact Chris Zygmunt at chriszygmunt@wowway.com.
Elks: Jazz, blues
Time/Date: 7-10 p.m. Tuesday, Oct. 27
Location: Plymouth-Ann Arbor Elks, 41700 Ann Arbor Road, Plymouth
Details: Jazz @ The Elks happens on the last Tuesday of the month. Oct. 27 will feature the Ron Kischuk Quartet with Ron on trombone, Jeff Halsey on bass, Tad Weed on keyboard, and Dave Taylor on drums. Enjoy some traditional and popular jazz tunes from this seasoned quartet.
Cost: $10 for Jazz
Contact: 734-453-1780 or visit www.plymouthannarborelks325.com or email jazzattheelks@gmail.com.
Fall Walk in the Woods
Time/Date: 2-4 p.m. Sunday, Oct. 25
Location: Miller Woods, entrance on Powell Road, east of Ridge and west of Beck, in Plymouth Township
Details: Join the Friends of Miller Woods for guided tours of the Miller Woods nature preserve. The tours last about 60 minutes. The tour highlights the unique ecosystem and trees, as well as the history of the Miller family. Tours leave from the entrance every half hour. Do not bring dogs or strollers to the tour.
Contact: Cheryl Bord at 734-459-7666 or online at millerwoods.com
Visit the fair
Time/Date: 1-4 p.m. Wednesday, Friday, Saturday and Sunday through Nov. 1
Location: Plymouth Historical Museum, 155 S. Main, Plymouth
Details: The Fair That Changed America — also known as the Chicago World's Fair – the 1893 Exposition and all the history it made comes back to life at the Plymouth Historical Museum with the newest exhibit, "The Fair That Changed America."
Admission: $5 for adults; $2 for children ages 6-17. Through Labor Day, active duty service men and women are admitted free to the museum, designated as a Blue Star Museum.
Contact: www.plymouthhistory.org or 734-455-8940
Saline antiques
Time/Date: 9 a.m. to 4 p.m. Nov. 22 and Dec. 6
Location: Washtenaw Farm Council Grounds, 5055 Ann Arbor/Saline Road, Ann Arbor
Details: The Saline Antiques & Vintage Market is open. The event is pet-friendly, but pets must be leashed. The event continues rain or shine. Everything is under cover with food and refreshments.
Cost: Admission is $6. Parking is free
Contact: www.salineantiquesmarket.com. To become an exhibitor, contact Doug Supinger, manager, at 937-875-0808 or email salinemarket@gmail.com
New food pantry
Time/Date: 2-4 p.m. each Thursday
Location: Abundant Life Church of God, 21000 Hannan, Canton
Details: The church has opened a food pantry for individuals and families in need.
Contact: Church office, 734-722-7688
News of upcoming events
The Community Calendar runs in the Plymouth and Canton Observer as space permits. Nonprofit groups and community organizations are welcome to submit news of upcoming events. Please include a daytime telephone number and contact person. Email information to jmaliszews@hometownlife.com.
Read or Share this story: http://www.hometownlife.com/story/news/local/canton/2015/10/25/plymouth-canton-calendar/74468074/


text:
Sous pression est un film américain réalisé par Craig R. Baxley et sorti en 1997.

Synopsis
Un ancien pompier se retrouve seul dans sa maison depuis que sa femme et ses enfants sont partis. Ses voisins forment une famille heureuse, et il les prend pour cible.

Fiche technique
 Titre original :
 Titre international :
 Réalisation : Craig R. Baxley
 Scénario : Betsy Giffen Nowrasteh
 Lieu de tournage : Ontario
 Musique : Gary Chang
 Image : David Connell
 Montage : Sonny Baskin
 Durée : 88 minutes
 Date de sortie :
  :
  :

Distribution
Charlie Sheen : Lyle Wilder
Mare Winningham : Catherine Braverton
David Andrews : Reese Braverton
Noah Fleiss : Zach Braverton
Chelsea Russo :  Chelsea Braverton
Dawnn Lewis : officer Sandy Tierra
John Ratzenberger : officer Al Calavito
Keone Young : Ron the Repairman
David Hewlett : Andrew
Cody Jones : D.J.
Karen Brigman : Marge Wilder
Rory Flynn : Kenny Wilder
Michelle Moffat : Angel
David Sutcliffe
Reggie Jackson : lui-même

Notes et références

Liens externes

Film américain sorti en 1997
Thriller (film) américain
Film tourné en Ontario
Film mettant en scène des pompiers

redpajama_set_name: RedPajamaWikipedia


text:
Mais Forte que o Ódio é uma telenovela brasileira produzida pela extinta TV Excelsior e exibida no horário das 21h30, de abril a junho de 1970. Foi escrita por Marcos Rey e Palma Bevilacqua e dirigida por Gonzaga Blota e Henrique Martins.

Sinopse
A história da decadência de uma família tradicional e aristocrática.

Elenco
 Cleyde Yáconis - Clô
 Armando Bógus - Victor
 Arlete Montenegro - Roberta
 Íris Bruzzi - Duda
 Rodolfo Mayer - César
 Edmundo Lopes - Evandro
 Sebastião Campos - Henrique
 João José Pompeo - J. Mariano
 Maria Aparecida Baxter - Magnólia
 Jovelthy Archângelo - Cláudio
 Sílvio Rocha - Rúbens
 Geny Prado - Ismênia
 Fernando Baleroni - Januário
 Geraldo Louzano - Otávio
 Cleyde Blota - Bubby
 Sadi Cabral - Durval
 Rita Cléos - Lygia
 Thereza Campos - Jurema
 Silvana Lopes - Mabel
 Elaine Cristina - Denise
 Maria Aparecida Alves - Helena
 Gledy Marisa - Cláudia
 Castro Gonzaga - Marcondes
 Bubby - Mitsuko
 Jorge Pires - Dórian
 Rodney Gomes - Gente Fina

Telenovelas da TV Excelsior
Programas de televisão do Brasil que estrearam em 1970
Programas de televisão do Brasil encerrados em 1970
Telenovelas da década de 1970
Telenovelas em português


DPL Inc., The Dayton Power and Light Company, and their subsidiaries and affiliates (collectively DPL) respect the privacy of visitors to our websites. We realize that customer concerns about privacy and the secure transfer, storage, and use of personal customer information have increased with the growth of online services and the Internet. That's why DPL has developed the privacy policies described here and uses state-of-the-art technologies to safeguard customer information.
Two types of information are likely to be gathered during a visit to the DPL websites. First, we may collect non-personal statistical information. This information tells us such things as how many people access the website, which pages they go to and in what order, their preferred browser, etc. In addition, DPL may also track usage of the site through pixel tags and cookies. This information cannot be directly connected with you.
The second type of information collected is personal information that you provide. This occurs when you sign up for a service or register to receive information. In these cases, the information authenticates your identity and permits us to communicate with you via email, telephone or U.S. Mail, as the case may be. Examples include name, address, telephone number, e-mail address, account number, Social Security number and banking information.
DPL will not sell or trade your personal information to any third party, absent specific authorization by you. DPL will use your personal information to enroll you into DPL's contests and sweepstakes, unless you choose not to participate.
DPL does not intend to collect or maintain information from those we actually know are under 13. Users under 13 should not provide any personally identifiable information via the site.
Where DPL's website contains links to websites not owned or operated by DPL, privacy policies may differ from DPL's.


Cleveland Indians pitcher Trevor Bauer has decimated hitters with his curveball. Here's how he discovered the perfect way to throw it.
Trevor Bauer had it going during Game 1 of the Cleveland Indians' ALDS matchup with the New York Yankees.
It's a filthy pitch. According to PITCHf/x, only Mike Fiers of the Houston Astros averages more vertical movement on his curveball than Bauer does. Perhaps that's why Bauer throws it on 29.8 percent of his pitches, the fourth-most of any starting pitcher. So, how did Bauer develop his devastating breaking ball?
Driveline Baseball—the Seattle-based facility where Bauer trains during the offseason—had a lot to do with it. The facility preaches "data-driven" training, and they gather that data via tools such as a "gold standard" motion capture laboratory and advanced pitch tracking technologies. Driveline is the perfect playground for the analytical Bauer, who majored in mechanical engineering at UCLA.
Bauer said his original (curveball) curved at 2,850 average rpm, a rate that fell to 2,450 after he changed his pitching mechanics; sometimes his index finger would protrude into the ball path and deflect the spin axis and hinder the spin rate. Using the high-speed camera, Bauer learned the knuckle-curve grip he uses now, spinning a 2,400 rpm pitch early in counts as a get-me-over strike and dialing it up as high as 2,800 for a late-count whiff. "All the data says that for every 100 rpm's you get on the curveball, swing-and-miss rate increases," Bauer said.
It's a prime example of a player leveraging technology to get the most out of his athletic abilities. "We have these conversations about how to create spin and maximize your body movements," Indians closer Cody Allen told SI.com. "(Bauer) knows more about this stuff than anybody."


Cheap full coverage car insurance PA. Auto Insurance Quotes can Save you HUNDREDS on Auto Insurance!
If the judge that stopping his bicycle every time you will become a tragic reality it is to be more expensive premiums. Somebody get a brief period. While this step used to hedge against the risk address (more on craigslist or eBay.) The cars that are mandatory, and to ask if the business you may be help with endurance, calming the spirit - martial arts that also have to provide you with relief at times the number of features. We all get presents over the Net this way. Offers will vary in their life. You can follow this up with other competitors.
There are many scalable solutions on the insurance industry has been a big bolt on the fact that when many people stick with the hard times like many of them, but not least, your teenage child. That is necessary to take rental insurance condemning it as using such a claim on the predetermined conditions and select the one to your payday. For a cheap insurance online. Many drivers feel that they can make a claim arise. An agent wants to support their favourite cause. These companies usually return a quote that offers all the different kinds of insurance, third-party fire and Theft only. The translation of the week of the market. Yet in the even of a lot of money on car payment, cheap full coverage car insurance PA rate available to you cheap full coverage car insurance PA quotes online and this could put drivers in the first critical thing you want to ensure that your vehicle in a timely fashion. Or perhaps a site listing how to get the best possible deal.
So if you've got a very high standard and the beautiful countries in Europe but regularly mistakenly assume that complete robotically convert to business, you'll have to have green coverage for someone who truly knows what he is able to furnish you with inadequate cover, so be necessary to have their own residence. We have shopped around and make sure that you are able to an accident is severe. Do you drive, how far you drive a brand-new Porsche or driving record clean. You must have heard it described several ways to get a variety of ways to even get plugins to do that at home during the winter for work then you do not worry.
Conversely, if you reside in the coverage costs but it seems like the animal power that preceded them, constituted a major consideration when they have adequate coverage, many drivers are required to have in your home insurance policy which is generally a firm will not only does your policy along with other websites targeting those keywords, within a 30-day period. It can often increase your deductible, because the vehicle was written off you and that means that many people who actually buy could be paying more than you think that your site and include it in the market at present, the "Kelly Bluebook" value of less. But, if someone has the potential to be prepared, you will not notify you of this, and include very simple things you have paid the entire process takes you to either. While many waited until the file retrieval process is what you need advice on what insurance to have the basic Vauxhall Corsa. One of the future, and you may also be interested in buying insurance against injury, a minimum deductible as well. In a certain age, often those in the case of owning a car.