text:
\section{Introduction}
\label{introduction}
\setcounter{footnote}{0}

In spite of the successes of the $\Lambda \rm CDM$ cosmological model \citep[i.e.][]{springel_05}, a major discrepancy remains between the predicted number density of
dark matter halos and the observed number density of galaxies
in the low-mass regime ($L<L_*$) \citep[i.e.][]{guo_10, papastergis_12, moster_10, moster_13, behroozi_13}.
This behavior is usually explained by supernova(SN)-driven outflows \citep{dekel_86} which expel baryons from the galactic disk.
Indeed, these galactic outflows are observed in almost every star-forming galaxy (SFG) \citep[][for a review]{VeilleuxS_05a} and are likely to enrich the inter-galactic
medium \citep[e.g.][]{dekel_86, aguirre_01, oppenheimer_06}.

The physical mechanisms for driving  galactic winds are complex and the cold gas
could be accelerated by  thermal energy injection \citep{springel_03},
by momentum injection from radiation pressure \citep[e.g.][]{murray_05},
by  cosmic ray pressure \citep[e.g.][]{booth_13, salem_14}
or by a combination of these mechanisms \citep[e.g.][]{hopkins_15}
The wide range physical scales that describe SN explosions from Astronomical Unit (AU) to tens of kiloparsecs (kpc), are beyond
the capabilities of cosmological simulations.

Hence, in most of these simulations, outflows are usually implemented with sub-grid prescriptions
\citep[e.g.][]{schaye_10, oppenheimer_10,Vogelsberger_14a}.
A popular sub-grid recipe is to let the loading factor $\eta$, i.e. the ratio between the outflow rate $\dot M_{\rm out}$
and the star-formation rate (SFR), be a function of galaxy (halo) mass or circular velocity $V_c$ \citep{oppenheimer_10}
such as $\eta\propto V_c^{-1}$ for momentum-driven winds and $\eta\propto V_c^{-2}$ for energy-driven winds.
An alternative way to implement the collective effect of SN explosions is the (stochastic) implementation
of thermal feedback, where galactic winds develop without imposing any input outflow velocity nor mass loading factor
such as in the EAGLE simulations \citep[e.g.][]{schaye_15},
 the FIRE simulations \citep{hopkins_14, muratov_15},
and  the multi-phase scheme of \citet{barai_15}.

Given the high impact of SN feedback on galaxy formation and the
wide range of mass loading factors used in numerical simulations \citep[see the compilations in][]{zahid_14, torrey_14,schroetter_15},
observational constraints are of  paramount importance.
Unfortunately, our knowledge on the loading factor or the mass outflow rate $\dot M_{\rm out}$
is incomplete despite of the many efforts  made in the past decades \citep[i.e.][]{heckman_96, heckman_00, martin_98, martin_99, rupke_05, rubin_10, martin_12}.
Indeed, estimates of the ejected mass flux $\dot M_{\rm out}$ using standard galaxy absorption lines
\citep[e.g.][]{heckman_90, heckman_00, pettini_02, martin_02, martin_05, martin_12, martin_13}
 are uncertain by orders of magnitude mainly due to the difficulty in constraining the location of the probed outflowing gas~\footnote{
Furthermore, outflow rates from these low-ionization metal lines also require uncertain ionization corrections \citep[e.g.][]{chisholm_16}.
}.
Indeed, the gas responsible for the blue shifted absorption lines in galaxies could be 0.1, 1 or 10 kpc away from the host.
Some recent studies have made serious attempts at determining the scaling of outflow rates with galaxy properties
 by setting the absorbing gas at a fixed distance \citep{ heckman_15, chisholm_15, wood_15}.

Background quasars can give us the minimum distance of the gas
from the impact parameter $b$ and thereby potentially yield more accurate outflow rates
\citep[][]{bouche_12, kacprzak_14, schroetter_15, muzahid_15}.
One difficulty is that it is rare for the LOS to a background quasar to pass near a star-forming galaxy.
Hence, one needs to devise strategies to build large samples of galaxy-quasar pairs.
Another difficulty is that background quasars can probe not only
the circum-galactic medium but also the outer regions of gaseous disks and the gas near other, undetected galaxies.

In order to obtain large samples of galaxy-quasar pairs, one can select quasars around galaxies or galaxies around quasars with absorption systems.
The former requires quasar follow-up observations, while the latter requires one to detect the associated galaxies.
In the era of large quasar catalogs from Sloan Digital Sky Survey (SDSS), we favor the absorption selection technique combined with integral field unit (IFU) observations.
Indeed, from \hbox{{\rm Mg}{\sc \,ii}}\ absorption$-$selected quasar spectra, because we know the host galaxy redshift without knowing its position, IFUs can detect galaxies at previously unknown impact parameters.
This kind of instrument also allows us to determine geometrical and kinematic properties of galaxies in the same observation.
So far, IFUs such as SINFONI allowed us to probe galaxies within 20 kpc from the quasar line of sight (at redshift around 1).
With the new VLT/MUSE instrument \citep{bacon_06, bacon_09}, one can now detect galaxies further away ($\sim$250 kpc away at $z=1$) thanks to its field of view
of $1 \times 1$ arcmin (compared to $8 \arcsec \times8 \arcsec$ for SINFONI).
The large wavelength coverage of MUSE (4800\AA\ to 9300\AA) allows us to target quasar fields with multiple \hbox{{\rm Mg}{\sc \,ii}}\ ($\lambda \lambda 2796, 2802$) absorption lines
having redshifts from 0.4 to 1.4 for [\hbox{{\rm O}{\sc \,ii}}]($\lambda \lambda 3727, 3729$) identification.
We complement the VLT/MUSE IFU observations (which have a resolution $R\sim 2000$ or 150 \hbox{${\rm km\,s}^{-1}$})
 with VLT/UVES follow-up high-resolution spectra of the quasars in order to study
 the line-of-sight kinematics with the resolution ($<10$ \hbox{${\rm km\,s}^{-1}$}) necessary for obtaining accurate constraints on outflow properties.

In this paper, we present the first results on galactic outflows from our MUSE survey.
In \S~\ref{MEGAFLOW} we present the survey, the MUSE$+$UVES  data and the data reduction.
\S~\ref{section:results_all} describes the sample results while \S~\ref{wind} presents our wind model as well as individual galaxy properties.
Conclusions are then discussed in \S~\ref{conclusion}.

We use the $\Lambda\rm CDM$ standard cosmological parameters: $H_0$=70~km~s$^{-1}$, $\Omega_{\Lambda}$=0.7 and $\Omega_{M}$=0.3.
\section{The MEGAFLOW survey}
\label{MEGAFLOW}

\subsection{Target selection strategy}
\label{target_selection}

Current samples of galaxy$-$quasar pairs for strong \hbox{{\rm Mg}{\sc \,ii}}\ absorbers, as in \citet{bouche_12, schroetter_15, muzahid_15} and \citet{bouche_16},
are made of a dozen pairs.
Here, we seek to increase the sample size by almost an order of magnitude
in order to allow for statistical analysis of the relation between the absorption properties (and ultimately wind properties such as outflow rates and loading factors) and the galaxy properties.
Thanks to the multiplexing capabilities of MUSE,
having a sample 80---100 pairs is now within reach using 20--25 quasar fields.

As in our previous surveys,  we first select background quasar spectra with \hbox{{\rm Mg}{\sc \,ii}}\ \hbox{$\lambda 2796$}\ absorption lines.
For our MusE GAs FLOw and Wind (MEGAFLOW) survey, our strategy consists in selecting multiple \hbox{{\rm Mg}{\sc \,ii}}\ absorbers (three, four or five) in quasar spectra
from the Zhu and M\'enard catalog\footnote{This catalog can be found at http://www.pha.jhu.edu/~gz323/Site/Download$\_$Absorber$\_$Catalog.html} \citep{zhu_13}
based on the SDSS survey \citep{ross_12, alam_15}.
These \hbox{{\rm Mg}{\sc \,ii}}\ absorptions should have redshifts between $0.4$ and $1.4$ such that the [\hbox{{\rm O}{\sc \,ii}}] $\lambda \lambda 3727, 3729$ galaxy emission lines fall into the MUSE wavelength range (4800\AA\ to 9300\AA).

To restrict the impact parameter range, we constrain the rest equivalent width (REW) of these absorptions $W_r^{\hbox{$\lambda 2796$}}$ to $W_r^{\hbox{$\lambda 2796$}}>$0.5~\AA\
because of the well-known anti-correlation between impact parameter and $W_r^{\hbox{$\lambda 2796$}}$ \citep{lanzetta_90, steidel_95, chen_10, kacprzak_11b, bordoloi_11, werk_13, nielsen_13}.
Also the largest $W_r^{\hbox{$\lambda 2796$}}$ tend to be associated with outflows \citep[e.g.][]{kacprzak_11b, lan_14}.
We define a strong absorber an absorber with $W_r^{\hbox{$\lambda 2796$}}>0.3 - 0.5$ \AA\ as in \citet{nestor_05}.
This limit of 0.5 \AA\ corresponds to $b \lesssim$100 kpc.
We also need to pay attention to where the galaxy emission lines will appear in the spectrum and try to avoid bright sky emission lines as much as possible.

The MEGAFLOW survey will consist of 20--25 quasar fields and the MUSE observations started in September 2014.
In October 2014, we obtained UVES observations on the first two fields
(Table~\ref{table:muse-obs})\footnote{as Director Discretionary Time (DDT) program 293.A-5038(A)}.
In this paper, we present the first results on these two fields towards SDSSJ213748$+$0012 and SDSSJ215200$+$0625, which
 have 4 \hbox{{\rm Mg}{\sc \,ii}}\ absorption systems each.

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

\subsubsection{MUSE observations}
\label{observations}
MUSE data were taken in September 2014  in visitor mode during the first   Guaranteed Time Observations (GTO) run
(program ID 0.94A-0211).
We first point the telescope towards a quasar and then we offset the first exposure by $\approx 4-5 \arcsec$ in Right Ascension (RA) and Declination (Dec).
This first offset is made to avoid the quasar flux to fall in the same pixels than the first pointing.
Each observation was composed of four exposures of $900$ seconds with a rotation of $90^\circ$ between every exposure as well as small dithering ($<1\arcsec$).
This observation strategy is used in order to minimize systematics.
From each MUSE observation, we obtain a combined cube of 317 $\times$ 316 spatial pixels (spaxels).
Each spaxel has $\sim3680$ spectral pixels ranging from 4750~\AA\ to 9350~\AA.
With a spectral sampling of 1.25~\AA$/$pixel, the average spectral resolution of the data is $\sim2.4$~\AA FWHM.
The spatial resolution for the two quasar fields is $\sim0.8\arcsec$ FWHM with spatial sampling of 0.2$\arcsec/$pixel at 7000~\AA.
The seeing constraint ($<0.9\arcsec$) is necessary if we want to derive galaxy parameters and detect them.
Indeed, galaxies at redshift $\sim1$ can be small in size ($<1.2\arcsec$) and we need the seeing to be smaller than the galaxy to better derive its parameters.

\begin{table*}
\centering
\caption{Summary of MUSE 094.A-0211(B) observations. \label{table:muse-obs}
}
\begin{tabular}{llcrc}
\hline
Field	 		          & $z_{\rm qso}$    &  PSF($\arcsec$)     &  T$_{\rm exp}$(s)  &  Date         \\
(1)   		                  &	(2)	     & (3)	           &  (4)               &  (5)          \\
\hline
J213748+0012                      &1.668             &0.8                  &3600                & 2014-09-23      \\
J215200+0625                      &2.409             &0.7                  &7200                & 2014-09-24      \\
\hline
\end{tabular}\\
\vspace*{0,1cm}
{
(1) Quasar name;
(2) Quasar emission redshift;
(3) FWHM of the seeing PSF (at $\approx$7000~\AA);
(4) Exposure time;
(5) Date of observations.
}\\
\end{table*}

\subsubsection{MUSE data reduction}
\label{MUSE_reduction}
The data are reduced using version $1.0$ of the MUSE data reduction software (DRS) pipeline\footnote{A short description of the pipeline is given in \citet[][]{weilbacher_14}.}.
We process bias, flat field calibrations and arc lamp exposures taken during the night of the observations.
Following calibration processing, raw science frames are bias subtracted and flat-fielded using master bias and master flat fields respectively.
The flat-fielding is renormalized in each slice to account for slight changes due to temperature variations
using a single flat field exposure taken hourly  before the science observation or when the instrument temperature changes
by more than 0.5$^{\circ}$ C.
An additional flat-field correction was performed using the twilight sky exposures taken at the beginning of each night  to correct for slight optical path differences between  sky and calibration unit.
Geometrical calibration and astrometric solution are then applied.
The wavelength solution is obtained from the arc lamps and calibrated in air. Wavelengths are also corrected for the heliocentric velocity.
The flux calibration is obtained from a spectrophotometric star observed for each night.

On each individual exposure, we use the default configuration of the DRS recipe and with the sky removal method turned off.
This produces, for the $4$ individual exposures, a large table called the ``pixel-table''.
For each individual exposure, star positions were registered in order to have accurate relative astrometry as shifts can occur
between exposures due to the derotator wobble ($<0.3\arcsec$).
The ``pixel-tables'' were then combined into a single data cube using the previously calculated offsets.
The sky-subtraction was performed on this combined data cube with ZAP (Zurich Atmosphere Purge), an algorithm developed by \citet{soto_16b, soto_16a}.
ZAP operates by first subtracting a baseline sky level, found by calculating the median per spectral plane
and  then uses principal component analysis  and determines the minimal number of eigenspectra that can reconstruct the residual emission features in the data cube.
Absolute astrometry is obtained by matching the positions of point sources in the data cube
against the SDSS astrometry.

Finally, we cross$-$checked the flux calibration of these point sources against the SDSS magnitudes in the
$r$ and $i$ filter bands
(the central wavelengths are $\lambda_r=6165 \rm\AA$ and $\lambda_i=7481 \rm\AA$ for $r$ and $i$ filters respectively)
 whose bandpass are within the MUSE wavelength coverage.
Using the $r$ and $i$ images obtained from the MUSE data cube convolved with the SDSS filters,
we fitted a Moffat profile on each of the stars to calculate their total flux in
each filter and then compare them with the SDSS ones.
SDSS filters are design to be in AB magnitudes, but there are still corrections needed for some filters.
Given that for the $r$ and $i$ filters, the AB to SDSS magnitudes correction is negligible,
we can correct fluxes into AB magnitudes directly using the following relation:
\begin{equation}
 AB = -2.5\log_{10}(f) - 5\log_{10}(<\lambda>) - 2.406 \label{eq:abmag}
\end{equation}
where $f$ is the flux in erg\,s$^{-1}$\,cm$^{-2}$\,\AA$^{-1}$\ and $<\lambda>$ the filter central wavelength in \AA.

The comparison between MUSE and SDSS magnitudes is shown in Table~\ref{table:magnitudes}.
For both fields (J2137$+$0012 and J2152$+$0625), the agreement is around $1/10$th of a magnitude.
In addition, another data reduction was performed using CubeFix and CubeSharp (Cantalupo, in prep) in order to show cleaner images
of the fields in the Appendix (Fig~\ref{fig:J213748_field} and~\ref{fig:J215200_field}).

\begin{table*}[]
\centering
\caption{Magnitude differences between MUSE and SDSS for J213748+0012 and J215200+0625 fields.}
\label{table:magnitudes}
\begin{tabular}{lccccccc}
\hline
Field		&object	&Instrument	&RA		& DEC				& mag$_r$	&mag$_i$			&Difference \\
(1)		&(2)	&(3)		&(4)		&(5)				&(6)		&(7)				&(8)			\\
\hline
J213748$+$0012	&QSO	&MUSE		&21:37:48.41	&$+$00:12:20.49				&18.33		&18.19					&$-0.13$\\
		&	&SDSS		&21:37:48.44	&$+$00:12:20.00				&18.20		&18.05					&\\
		&Star	&MUSE		&21:37:47.65	&$+$00:12:21.29				&19.71		&19.55					&$-0.09$\\
		&	&SDSS		&21:37:47.65	&$+$00:12:20.89				&19.61		&19.46					&\\
\hline
J215200$+$0625	&QSO	&MUSE		&21:52:00.05	&$+$06:25:17.26				&19.42		&19.44					&$-0.07$\\
		&	&SDSS		&21:52:00.03	&$+$06:25:16.36				&19.42		&19.30					&\\
		&Star	&MUSE		&21:51:59.84	&$+$06:25:05.48				&16.71		&16.47					&$-0.17$\\
		&	&SDSS		&21:51:59.83	&$+$06:25:04.72				&16.53		&16.29					&\\
\end{tabular}\\
{
(1) Field;
(2) Object type;
(3) Instrument (MUSE or SDSS);
(4) Right Ascension (RA);
(5) Declination (DEC);
(6) Magnitude in $r$ filter (central wavelength $\lambda_r=6165 \rm\AA$);
(7) Magnitude in $i$ filter (central wavelength $\lambda_i=7481 \rm\AA$);
(8) Average difference SDSS$-$MUSE (mag).\\
}
\end{table*}

\subsubsection{UVES observation and reduction}
\label{section:uves}

The high resolution spectra for J213748+0012 and J215200+0625 were taken with
UVES mounted on the 8.2m
VLT at Paranal, Chile \citep{dekker_00}.
These two fields were observed in DDT time under the program 293.A-5038(A).
UVES is a cross-dispersed echelle spectrograph with two arms that are
functionally identical: one covers the wavelengths in the  range 3000-5000
\AA (Blue) and the other covers the range  4200-11000 \AA (Red). The
details of the observational campaigns are presented in Table \ref{table:uves-obs}.
The slit width of 1.2 arcsec and a CCD readout with 2x2 binning used for
all the observations resulted in a spectral resolution power R $\approx 38000$ dispersed on pixels of $\sim$1.3 \hbox{${\rm km\,s}^{-1}$}.
The settings were chosen in order to have a maximum of absorptions from host galaxies (from \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2586$ to \hbox{{\rm Mg}{\sc \,i}}\ $\lambda2852$).
The Common Pipeline Language (CPL version 6.3) of the UVES pipeline was
used to bias correct and flat field the exposures and then to extract
the wavelength and flux calibrated spectra. After the standard reduction, the custom
software  UVES popler\footnote{http$://$astronomy.swin.edu.au$/\sim$mmurphy$/$UVES$\_$popler$/$}
(version 0.66) was used to combine the extracted echelle orders into
single 1D spectra. The continuum was fitted with low-order polynomials.

\begin{table*}
\centering
\caption{Summary of UVES 293.A-5038(A) observations. \label{table:uves-obs}}
\begin{tabular}{llccc}
\hline
Target 		&setting $\lambda_c$ (nm)	&  T$_{\rm exp}$ (s)	&Date 		\\
\hline
J213748+0012	&390+580			&5970  			&2014-10-19	\\
J215200+0625	&390+580			&9015  			&2014-10-21,24 2014-11-18	\\
\hline
\end{tabular}

\vspace*{0,1cm}
\end{table*}

\section{MEGAFLOW sample first results}
\label{section:results_all}

\subsection{Galaxy detections}
\label{detection}

As we mentioned,  the two fields (SDSSJ213748$+$0012 and SDSSJ215200$+$0625)
 were selected to each have at least 3 absorbing systems with $W_r>0.5$~\AA\ (see Table~\ref{table:muse-det}).

In each MUSE field, we search for [\hbox{{\rm O}{\sc \,ii}}] $\lambda \lambda 3727, 3729$ emission lines corresponding to the \hbox{{\rm Mg}{\sc \,ii}}\ absorption redshifts seen in the quasar spectrum.
However, the MUSE field of view of $1\arcmin \times 1\arcmin$ allows us to search for other companions in the fields,
giving insight into the environment related to the host.
We allow the potential host galaxies to have a redshift difference within a velocity interval of $\approx 1000$~\hbox{${\rm km\,s}^{-1}$}\ with respect to the absorber redshift ($z_{\rm gal} = z_{\rm abs} \pm 0.01$ for a $z\approx1$ galaxy).
This velocity interval is set to prevent selection effects on surrounding gas velocities and thus not rejecting gas able to escape the gravitational well of the host galaxy in case of outflowing gas (more details on escape velocity in \S~\ref{outflow}).
In the case where there are multiple galaxy candidates for a single \hbox{{\rm Mg}{\sc \,ii}}\ line,
we select the galaxy with the smallest impact parameter from the quasar LOS.
Table~\ref{table:muse-det} shows the detection rates for each field.
For one of the undetected galaxies the expected emission line falls near a sky emission line at 7618 \AA\
(the $z\approx1.0437$ absorber in SDSSJ213748+0012) and the other line is too faint to be detected.
For the reader interested in all of the galaxies detected in these MUSE data,  we provide  in the appendix a catalog with all the galaxies
for which a redshift could be determined.

\begin{table}
\centering
\caption{Summary of MUSE galaxy detection. \label{table:muse-det}}
\begin{tabular}{lccccc}
\hline
Field name 		&$z_{\rm absorber}$		& $W_{r}^{\lambda2796}$ 	&$N_{\rm det}$ 	&$b$	\\
(1)			&(2)				&(3)				&(4)			&(5)	\\
\hline
J213748+0012		&0.8063				&0.724$\pm$0.09			&1			&88	\\
			&1.0437				&0.767$\pm$0.08			&0\footnote{Affected by OH emission line at 7618\AA.}			&$\cdots$	\\
			&1.1890				&0.308$\pm$0.06			&1			&63	\\
			&1.2144				&1.144$\pm$0.06			&3			&87, 212, 246	\\
J215200+0625		&1.0534				&0.522$\pm$0.14			&2			&45, 189	\\
			&1.1761				&0.526$\pm$0.15			&0			&$\cdots$	\\
			&1.3190				&1.347$\pm$0.12			&1			&34	\\
			&1.4309				&1.152$\pm$0.11			&4			&62, 78, 184, 211	\\
\hline
\end{tabular}\\
{
(1) Quasar field name;
(2) \hbox{{\rm Mg}{\sc \,ii}}\ absorption lines redshift;
(3) \hbox{{\rm Mg}{\sc \,ii}}\ ($\lambda2796$) REW (\AA);
(4) Number of detected galaxies near absorber redshift;
(5) Impact parameter(s) of the detected galaxy(ies) (kpc);
}
\vspace*{0,1cm}
\end{table}

We detect galaxies at redshifts of three of the four \hbox{{\rm Mg}{\sc \,ii}}\ absorbers for the SDSSJ213748$+$0012 quasar field (see Table~\ref{table:muse-det}).
For the \hbox{{\rm Mg}{\sc \,ii}}\ absorber at $z= 0.8063$, we  find one [\hbox{{\rm O}{\sc \,ii}}] emission-line galaxy at a distance $b$ of 88~kpc.
For the $z=1.1890$ \hbox{{\rm Mg}{\sc \,ii}}\ absorber, we also find one galaxy at an impact parameter of 63~kpc.
For the last $z=1.2144$ \hbox{{\rm Mg}{\sc \,ii}}\ absorber, we find three [\hbox{{\rm O}{\sc \,ii}}] emitters, at  impact parameters of 87, 212 and 246~kpc.
Given the large impact parameters of the latter two galaxies compared to the typical galaxy halo at these redshifts,
and given the large \hbox{{\rm Mg}{\sc \,ii}}\ REW of 1 \AA, we assume the galaxy with the smallest impact parameter to be the host galaxy.

For the SDSSJ215200$+$0625 field, we also detect galaxies at the redshifts of three out of the four \hbox{{\rm Mg}{\sc \,ii}}\ absorbers (see Table~\ref{table:muse-det}).
Two galaxies are identified for the first \hbox{{\rm Mg}{\sc \,ii}}\ absorber at $z=1.0534$, at impact parameters of 45 and 189~kpc.
The host of the second absorber at $z=1.1761$ is not detected in spite of the wavelength for the expected [\hbox{{\rm O}{\sc \,ii}}] line being clear of OH lines.
The third \hbox{{\rm Mg}{\sc \,ii}}\ absorption has a redshift of 1.3190 and has only one galaxy corresponding to that redshift at an impact parameter of 34~kpc.
The last \hbox{{\rm Mg}{\sc \,ii}}\ absorption is at $z=1.4309$ and we found 4 [\hbox{{\rm O}{\sc \,ii}}] emitters at that redshift,
which have impact parameters of 62, 78, 184 and 211~kpc (see Figure~\ref{fig:J2152G3}).
This might be indicative of a group environment.
Among, two have impact parameters very close to each other (62 and 78~kpc).
We choose to assume that the closest galaxy (at 62~kpc) should be responsible for the \hbox{{\rm Mg}{\sc \,ii}}\
absorption because it is the most massive and the brightest ($V_{\rm max} = 298$ \hbox{${\rm km\,s}^{-1}$} and 200 \hbox{${\rm km\,s}^{-1}$}, [\hbox{{\rm O}{\sc \,ii}}] fluxes being $5.05 \times 10^{-17}$erg\,s$^{-1}$\,cm$^{-2}$\ and $1.38 \times 10^{-17}$erg\,s$^{-1}$\,cm$^{-2}$ , respectively).

Using the propagated noise in the MUSE datacube, we can estimate flux (and surface brightness) limits on the expected [\hbox{{\rm O}{\sc \,ii}}] emission line for the non-detected host galaxies.
For the SDSSJ213748$+$0012 quasar field, at the first expected [\hbox{{\rm O}{\sc \,ii}}] wavelength ($\sim 6730 \AA$), with a noise of $2.3\times10^{-20}$ erg\,s$^{-1}$\,cm$^{-2}$\,\AA$^{-1}$ (1$\sigma$),
we estimate a surface brightness limit of $1.43\times10^{-18}$ erg\,s$^{-1}$\,cm$^{-2}$\,arcsec$^{-2}$ (1$\sigma$) for emission line objects (assuming a $\rm FWHM = 2.48$ \AA).
This corresponds to a flux limit of $1.04\times10^{-18}$ erg\,s$^{-1}$\,cm$^{-2}$ (1$\sigma$) for an unresolved emitter at 0.82$\arcsec$ seeing.
The flux limit is $\sqrt{2}$ times for the [\hbox{{\rm O}{\sc \,ii}}] doublet (assuming a resolved doublet), or $1.47\times10^{-18}$ erg\,s$^{-1}$\,cm$^{-2}$ (1$\sigma$),
which corresponds to a SFR of 0.13~\hbox{M$_{\odot}$\,yr$^{-1}$}\ at $z=1$, typical of our sample.
Surface brightness and flux limits are shown in Table~\ref{table:flux-limit}.

\subsection{SFR determination}

We use the $L_{\hbox{{\rm O}{\sc \,ii}}}$ ($\lambda \lambda 3727, 3729$) luminosity to estimate the SFR as follows.
We use the \citet{kennicutt_98} calibration, which assumes a \citet{salpeter_55} Initial Mass Function (IMF):
\begin{equation}
 SFR (\rm{M_{\odot}~yr^{-1}})=(1.4\pm0.4)\times 10^{-41}~ L([\hbox{{\rm O}{\sc \,ii}}])_o(\rm {erg}~s^{-1}) \label{eq:sfr}
\end{equation}
Where $L([\hbox{{\rm O}{\sc \,ii}}])_o$ is the [\hbox{{\rm O}{\sc \,ii}}] observed luminosity.
Using a \citet{chabrier_03} IMF and assuming a mean flux attenuation of $A_V=1$, which is typical for $z=1$ galaxies \citep[e.g.][]{charlot_02}, gives the same results (within 10\%) as Equation~\ref{eq:sfr}.

Equation 4 in \citet[][hereafter K04]{kewley_04} uses also a Salpeter IMF but makes no assumption of reddening.
In their paper, they show that using the ``average'' attenuation correction of $0.3$ mag leads to underestimate the high SFR[\hbox{{\rm O}{\sc \,ii}}] ($>1$\hbox{M$_{\odot}$\,yr$^{-1}$}) and overestimate the low SFRs.
They provide a way of deriving the E(B-V) (Eq.16 and 18 of K04) color excess which leads to a more accurate mean attenuation, assuming that $A_V=3.1\times E(B-V)$.
We choose to use the following equations (Eq~\ref{eq:sfr_k04} and \ref{eq:sfr_k04_2} from K04) to derive our SFRs.

\begin{equation}
 SFR(\rm{M_{\odot}~yr^{-1}})=(6.58\pm1.65)\times 10^{-42}~ L([\hbox{{\rm O}{\sc \,ii}}])_i (\rm {erg}~s^{-1}) \label{eq:sfr_k04}
\end{equation}

\begin{equation}
 L([\hbox{{\rm O}{\sc \,ii}}])_i=3.11 \times 10^{-20}~ L([\hbox{{\rm O}{\sc \,ii}}])_o^{1.495} \label{eq:sfr_k04_2}
\end{equation}

\begin{table*}
\centering
\caption{Surface brightness and flux limits. \label{table:flux-limit}
}
\begin{tabular}{lcccccc}
\hline
Quasar field 	&$z_{\rm absorber}$			&LSF	&  Noise 		&PSF	&Surface brightness limit 	&[\hbox{{\rm O}{\sc \,ii}}] flux limit	\\
(1) 		&(2)			&  (3)					&(4)	&(5)			&(6)	&(7)					\\
\hline
J213748+0012G1	&0.8063								&2.48	&$2.3\times10^{-20}$	&0.82 	&$1.43\times10^{-18}$		&$1.47\times10^{-18}$	\\
J213748+0012	&1.0437								&2.37	&$3.7\times10^{-20}$	&0.78 	&$2.19\times10^{-18}$		&$2.14\times10^{-18}$	\\
J213748+0012G2	&1.1890								&2.57	&$2.4\times10^{-20}$	&0.75 	&$1.54\times10^{-18}$		&$1.45\times10^{-18}$	\\
J213748+0012G3	&1.2144								&2.43	&$2.4\times10^{-20}$	&0.76 	&$1.45\times10^{-18}$		&$1.39\times10^{-18}$	\\
J215200+0625G1	&1.0534								&2.28	&$2.1\times10^{-20}$	&0.67 	&$1.19\times10^{-18}$		&$1.01\times10^{-18}$	\\
J215200+0625	&1.1761								&2.60	&$1.7\times10^{-20}$	&0.66 	&$1.10\times10^{-18}$		&$9.14\times10^{-19}$	\\
\textbf{J215200+0625G2}	&1.3190								&2.41	&$3.6\times10^{-20}$	&0.66 	&$2.17\times10^{-18}$		&$1.79\times10^{-18}$	\\
J215200+0625G3	&1.4309								&2.60	&$2.1\times10^{-20}$	&0.66 	&$1.36\times10^{-18}$		&$1.13\times10^{-18}$	\\
\hline
\end{tabular}\\
{
(1) Quasar field name;
(2) \hbox{{\rm Mg}{\sc \,ii}}\ absorption line redshift;
(3) Line Spread Function FWHM (LSF) of the MUSE data (\AA);
(4) Data cube noise at the expected [\hbox{{\rm O}{\sc \,ii}}] wavelength (erg\,s$^{-1}$\,cm$^{-2}$\,\AA$^{-1}$) given at 1~$\sigma$;
(5) PSF of the data ($\arcsec$);
(6) Surface brightness limit (erg\,s$^{-1}$\,cm$^{-2}$\,arcsec$^{-2}$) given at 1~$\sigma$;
(7) [\hbox{{\rm O}{\sc \,ii}}] flux limit (erg\,s$^{-1}$\,cm$^{-2}$) given at 1~$\sigma$.\\
}
\end{table*}

\subsection{Galaxy morpho-kinematic properties}
\label{section:galaxy_properties}

Before classifying the galaxy$-$quasar pairs as favorable for gas outflows or inflows based on
the azimuthal angle $\alpha$ of the apparent quasar location with respect to the galaxy major axis,
we need to determine the galaxy's major axis position angle (PA)\footnote{The position angle (PA) of a galaxy is the angle between the galaxy major axis and the celestial north.}.

\begin{figure}[]
  \centering
  \includegraphics[width=4cm]{galaxy_feedback_alpha.pdf}
  \caption{Scheme representing the azimuthal angle:
  The galaxy is represented at the center in black, the red arrows represent the outflowing gas expelled from both side of the galaxy minor axis.
  The azimuthal angle $\alpha$ is represented by the blue angle between the galaxy major axis and the quasar LOS (in yellow).
}
  \label{fig:alpha}
\end{figure}

We determine the PAs from  the morpho-kinematic properties of each galaxy using two approaches.
First, we used the 2D fitting tool Camel\footnote{The source code can be found at https://bitbucket.org/bepinat/camel.git} on the [\hbox{{\rm O}{\sc \,ii}}] emission lines
to extract velocity and dispersion maps as in \citet{epinat_12} in order to establish whether the galaxy has a regular
velocity field compatible with a disk.
Second, we use the GalPaK$^{\rm 3D}$\ algorithm \citep{bouche_15} to derive simultaneously the morphological and kinematic properties of these galaxies
using the continuum subtracted sub-cubes extracted around the [\hbox{{\rm O}{\sc \,ii}}] emission lines.
GalPaK$^{\rm 3D}$\  uses a disk parametric model with 10 free parameters and a Monte-Carlo Markov Chain (MCMC) algorithm with non-traditional sampling laws in order to efficiently probe the parameter space. Because the algorithm   uses  a 3-dimensional kernel
 to convolve the model with the spatial point-spread function (PSF or seeing) and the instrument line spread function (LSF),
it returns the intrinsic (free of the PSF) galaxy properties (such as half-light radius, inclination, and maximum velocity).
Other parameters include the major-axis position angle, the galaxy flux, position, redshift and intrinsic velocity dispersion.
Results on the geometrical and kinematic properties of each galaxy are presented in Table~\ref{table:galpak}.

Figures~\ref{fig:J2137G1}$-$\ref{fig:J2152G3}
show GalPaK$^{\rm 3D}$\ reconstructed models as well as Camel velocity maps for the 6 galaxies in the two fields.
In Figure~\ref{fig:J2137G1} (SDSSJ213748+0012 field), the other emission sources are
the quasar and a star's residual continuum.
In these figures, the left panel corresponds to a narrow band image of 30 pixels (37.5 \AA) around the galaxy's [\hbox{{\rm O}{\sc \,ii}}] emission lines.
The background continuum has been subtracted so that we can only see the galaxy in emission.
In each of these Figures, we see the galaxy (inside the white rectangles) within 15$\arcsec$ of the quasar LOS (represented by a white cross).
In the two right columns of these Figures, [\hbox{{\rm O}{\sc \,ii}}] integrated flux and velocity maps are shown.
The top row corresponds to a 2$\times$2 (2 pixels FWHM) spatial Gaussian-smoothed flux map (left) and the Camel velocity map (right).
The bottom row shows the GalPaK$^{\rm 3D}$\ model flux (left) and the PSF-deconvolved velocity (right) maps.
We can see that in all cases, except in Figure~\ref{fig:J2137G2} for the dispersion-dominated SDSSJ213748+0012G2 galaxy,
 the model flux maps from GalPaK$^{\rm 3D}$\ is in a good agreement with the observed flux, and that GalPaK$^{\rm 3D}$\ and Camel velocity maps are consistent.
Table~\ref{table:galpak} lists the resulting parameters for each galaxy.

GalPaK$^{\rm 3D}$\ results are reliable if the central galaxy pixel has, at minimum, a Signal to Noise Ratio (SNR) pixel$^{-1}$ of 3 \citep{bouche_15}.
For each galaxy, we have SNR pixel$^{-1}$ of 11.0, 11.0, 4.5, 9.3, 4.2, 10.5 for SDSSJ213748+0012G1, G2, G3 and SDSSJ215200+0625G1,
G2, G3 respectively.
We checked that the parameters have converged for each galaxy as well as cross checked on raw data.

\subsection{Classification and notes on the individual cases}

To put constraints on galactic outflows, we first need to select galaxy$-$quasar pairs suitable for wind studies (wind pairs).
To do so, we measure the angle between the galaxy major axis and the apparent quasar location, which is
referred to as  the azimuthal angle $\alpha$ (see Figure~\ref{fig:alpha}).
Depending on this angle, the quasar LOS is likely to probe different phenomena around the galaxy.
If $55^\circ \leq \alpha \leq 90^\circ$, the quasar's position on the sky is roughly along the galaxy minor axis and is likely to cross the outflowing material of the
galaxy\footnote{the Bordoloi papers have the definition of azimuthal angle reversed, i.e. their minor axis correspond to an $\alpha$ angle $<45^\circ$.}
\citep[e.g.][]{bordoloi_11, bordoloi_14, kacprzak_12, kacprzak_14}.
If a pair has such an azimuthal angle, it will be classified as a wind-pair.
On the other hand, if the quasar is positioned along the galaxy major axis ($0^\circ \leq \alpha \leq 30^\circ$), the quasar LOS is likely to probe inflowing or circum-galactic gas.
With such configuration, we classify the pair as suitable for accretion studies (inflow pair).
In between, ($35^\circ \leq \alpha \leq 55^\circ$), we cannot distinguish between these two extreme cases.

In addition to the azimuthal angle, if a galaxy has a low inclination, classification  can be ambiguous given that the uncertainty on the position angle will be large.
Figure~\ref{fig:incl_vs_alpha} shows galaxy inclination as a function of quasar azimuthal angle.
From the 5 detected galaxies in the two quasar fields that are non-mergers, 2 are classified as inflow$-$pairs, one is an ambiguous case as its azimuthal angle is 47$^\circ$,
one is a face-on galaxy and
only 1 (\textbf{J215200+0625G2}) can be robustly classified as a wind-pair.

\subsubsection{SDSSJ213748+0012G1 galaxy}
The first detected galaxy (`G1') in the SDSSJ213748+0012 quasar field (Figure~\ref{fig:J2137G1}) has an impact parameter $b\approx 88$~kpc and corresponds to the $z_{\rm abs}\approx 0.8063$ \hbox{{\rm Mg}{\sc \,ii}}\
absorption lines with a REW $W_r^{\lambda2796}$ of $0.789$~\AA.
This J213748+0012G1 galaxy is inclined by $i\approx49\pm1.4^\circ$ and its derived maximum rotation velocity is $V_{\rm max}\approx127\pm5$~\hbox{${\rm km\,s}^{-1}$}.
With an [\hbox{{\rm O}{\sc \,ii}}] integrated flux of $8.7\times10^{-17}$erg\,s$^{-1}$\,cm$^{-2}$, its SFR is $\approx6.3\pm0.7$~\hbox{M$_{\odot}$\,yr$^{-1}$}.
In Figure~\ref{fig:J2137G1}, we can see that the morphology and the position angle is well reproduced by GalPaK$^{\rm 3D}$.
The azimuthal angle $\alpha$ with the quasar LOS is $\alpha=25$ deg, i.e. the LOS is aligned with the major-axis.

\subsubsection{SDSSJ213748+0012G2 galaxy}
  The galaxy J213748+0012G2 (Figure~\ref{fig:J2137G2})
corresponding to the $z_{\rm abs}\approx1.1890$ \hbox{{\rm Mg}{\sc \,ii}}\ absorption lines with a REW $W_r^{\lambda2796}$ of 0.308~\AA\
in the J213748+0012 quasar spectrum,
has an impact parameter of $b\approx64$~kpc and a total [\hbox{{\rm O}{\sc \,ii}}] doublet flux of $1.47 \times 10^{-16}$ erg\,s$^{-1}$\,cm$^{-2}$.
From the [\hbox{{\rm O}{\sc \,ii}}] integrated flux we derive a SFR of $\approx41\pm8.0$~\hbox{M$_{\odot}$\,yr$^{-1}$}.
This galaxy has a large velocity dispersion $\sigma\approx114\pm2.3$~\hbox{${\rm km\,s}^{-1}$}, i.e. it is a dispersion dominated system with $V/\sigma\sim0.2$.
Furthermore,  the velocity field derived from the line fitting algorithm Camel does not agree with its morphology, i.e.
its morphological and kinematic main axes are strongly misaligned, by $\approx80^\circ$ (Figure~\ref{fig:J2137G2}).
This  is a strong indication for a merger, and therefore this galaxy will not be considered as a wind case
since the position angle of this galaxy is ambiguous.

\subsubsection{SDSSJ213748+0012G3 galaxy}
 The other galaxy (J213748+0012G3, Figure~\ref{fig:J2137G3}) from the J213748+0012 field corresponding to the \hbox{{\rm Mg}{\sc \,ii}}\ absorption lines at redshift $z_{\rm abs}\approx 1.2144$ and a REW
 $W_r^{\lambda2796}$ of 1.144\AA\
has an impact parameter $b$ of $\approx$ 87~kpc.
This galaxy has an inclination $i\approx40\pm5^\circ$, a maximum rotational velocity \hbox{$V_{\rm max}$} $\approx166\pm18$~\hbox{${\rm km\,s}^{-1}$}
and an [\hbox{{\rm O}{\sc \,ii}}] flux of $4.17 \times 10^{-17}$~erg\,s$^{-1}$\,cm$^{-2}$.
From this flux we derive a SFR of $\approx8.9\pm1.1$~\hbox{M$_{\odot}$\,yr$^{-1}$}.
Contrary to J213748+0012G2, the kinematic and morphological PAs agree well (Figure~\ref{fig:J2137G3}), hence the 3D GalPaK$^{\rm 3D}$\ model
accounts for the 3D emission of this galaxy.
In this case, the quasar LOS is at $\approx45^\circ$ from  the major axis of this galaxy, this pair is thus classified as ambiguous.

\subsubsection{SDSSJ215200+0625G1 galaxy}
 The first detected galaxy from the SDSSJ215200+0625 quasar field corresponds to the \hbox{{\rm Mg}{\sc \,ii}}\ absorption lines at redshift $z_{\rm abs}\sim1.0534$ with a REW $W_r^{\lambda2796}$ of 0.545~\AA.
This galaxy (J215200+0625G1) has an impact parameter $b\approx45$~kpc, a maximum rotational velocity $V_{\rm max}\approx 161\pm2$~\hbox{${\rm km\,s}^{-1}$}\ and an inclination $i\approx69\pm0.7^\circ$.
With an [\hbox{{\rm O}{\sc \,ii}}] integrated flux of $1.09\times 10^{-16}$ we derive a SFR of $\approx19.0\pm3.1$~\hbox{M$_{\odot}$\,yr$^{-1}$}.
For this galaxy, Figure~\ref{fig:J2152G1} shows a good agreement between GalPaK$^{\rm 3D}$\ and Camel flux and velocity maps.
We can clearly see that the quasar LOS is aligned with the major axis of this galaxy with $\alpha=4$ deg and is thus classified as an inflow-pair.

\textbf{\subsubsection{SDSSJ215200+0625G2 galaxy}}\footnote{In all the paper (text, Tables and Figures), the only wind-pair will appear in bold font to help the reader}
 The galaxy (\textbf{J215200+0625G2}) corresponding to the redshift $z_{\rm abs}\approx1.3190$ \hbox{{\rm Mg}{\sc \,ii}}\ absorption lines with a rest equivalent
width $W_r^{\lambda2796}$ of 1.424~\AA\ has an impact parameter $b\approx34$~kpc.
The derived galaxy redshift is 1.31845 with an inclination of $i\approx59\pm11^\circ$ and a maximum rotational velocity \hbox{$V_{\rm max}$}~$\approx130\pm29$~\hbox{${\rm km\,s}^{-1}$}.
With an [\hbox{{\rm O}{\sc \,ii}}] flux of $\approx 1.99 \times 10^{-17}$~erg\,s$^{-1}$\,cm$^{-2}$, we derive a SFR of $\approx4.6\pm0.4$~\hbox{M$_{\odot}$\,yr$^{-1}$}.
Even if this galaxy is faint, as seen in Figure~\ref{fig:J2152G2}, its GalPaK$^{\rm 3D}$-derived morphology and position angle are in good agreement with Camel maps.
The quasar LOS is aligned with the minor axis of this galaxy with $\alpha=88\pm5$ deg.

\subsubsection{SDSSJ215200+0625G3 galaxy}
\label{2152G3}
 The last galaxy (J215200+0625G3) in the J215200+0625 quasar field has an impact parameter $b\approx63$~kpc and corresponds to the \hbox{{\rm Mg}{\sc \,ii}}\ absorption lines at redshift $z_{\rm abs}\approx1.4309$
with $W_r^{\lambda2796}=1.152$~\AA.
The galaxy has an inclination of $i\approx13\pm4^\circ$, a maximum rotational velocity \hbox{$V_{\rm max}$}~$\approx298\pm40$~\hbox{${\rm km\,s}^{-1}$}\
and an [\hbox{{\rm O}{\sc \,ii}}] integrated flux of $\approx5.05 \times 10^{-17}$~erg\,s$^{-1}$\,cm$^{-2}$.
With this flux we derive a SFR of $\approx19\pm3.0$~\hbox{M$_{\odot}$\,yr$^{-1}$}.
Figure~\ref{fig:J2152G3} shows that the morphology is in agreement with Camel but the position angle derived for this galaxy is more uncertain due to the low inclination of this galaxy.
With an azimuthal angle of $\alpha=72\pm20$ deg and its low inclination, we cannot determine whether the quasar LOS is aligned with the minor or major axis of the galaxy.

\begin{figure*}[]
  \centering
  \includegraphics[width=18cm]{J2137_galpak_camel_z080.pdf}
  \caption{GalPaK and Camel results on galaxy J213748+0012G1.
  \textit{Left:} Narrow band image (30 pixels corresponding to 37.5 \AA) for [\hbox{{\rm O}{\sc \,ii}}] $\lambda3727, 3729$ at redshift $z=0.8069$.
  The quasar LOS is represented by the white cross and the galaxy is inside the white rectangle.
  The other spot on the right corresponds to continuum residuals from a star.
  \textit{Right:} from left to right: [\hbox{{\rm O}{\sc \,ii}}] doublet integrated flux and velocity maps.
The top row corresponds to a 2$\times$2 Gaussian smoothed flux map (the left panel) and Camel velocity map (top right).
The bottom row represents the GalPaK$^{\rm 3D}$\ model flux (left) and PSF-deconvolved velocity maps (right).
Color bars on the right show the velocities of the corresponding Velocity maps, in \hbox{${\rm km\,s}^{-1}$}.
This galaxy has a maximum SNR/pixel of $\approx$11.
}
  \label{fig:J2137G1}
\end{figure*}

\begin{figure*}[]
  \centering
  \includegraphics[width=18cm]{J2137_galpak_camel_z118.pdf}
  \caption{Same as Figure~\ref{fig:J2137G1} but for J213748+0012G2 at redshift $z=1.1893$.
  This galaxy has a maximum SNR/pixel of $\approx$11.
  For this galaxy, we can see that the velocity maps do not agree with each other.
  Because one part of the galaxy is not reproduced by our model and clearly has a flux component (top middle panel),
  this galaxy seems to be a merger and therefore the azimuthal angle of this pair is not reliable.
}
  \label{fig:J2137G2}
\end{figure*}

\begin{figure*}[]
  \centering
  \includegraphics[width=18cm]{J2137_galpak_camel_z121.pdf}
  \caption{Same as Figure~\ref{fig:J2137G1} but for J213748+0012G3 at redshift $z=1.2140$.
  This galaxy has a maximum SNR/pixel of 4.5.
  The spots located bottom right in the narrow band image corresponds to other galaxies.
  These galaxy have very low probability to be the host of the \hbox{{\rm Mg}{\sc \,ii}}\ absorption line in the quasar spectrum as they are located further away from the quasar LOS (212~kpc and 246~kpc).
}
  \label{fig:J2137G3}
\end{figure*}

\begin{figure*}[]
  \centering
  \includegraphics[width=18cm]{J2152_galpak_camel_z105.pdf}
  \caption{Same as Figure~\ref{fig:J2137G1} but for J215200+0625G1 at redshift $z=1.0534$.
  This galaxy has a maximum SNR/pixel of 9.3.
  The spot located top middle-right in the narrow band image corresponds to another galaxy.
  Like the one in Figure~\ref{fig:J2137G3}, this galaxy is less likely to be the host of the \hbox{{\rm Mg}{\sc \,ii}}\ absorption line in the quasar spectrum as it is located further away from the quasar LOS (189~kpc).
}
  \label{fig:J2152G1}
\end{figure*}

\begin{figure*}[]
  \centering
  \includegraphics[width=18cm]{J2152_galpak_camel_z131.pdf}
  \caption{Same as Figure~\ref{fig:J2137G1} but for \textbf{J215200+0625G2} at redshift $z=1.3184$.
  This galaxy has a maximum SNR/pixel of 4.2 and is thus difficult to see in the left image but can be seen in the smoothed [OII] flux image.
}
  \label{fig:J2152G2}
\end{figure*}

\begin{figure*}[]
  \centering
  \includegraphics[width=18cm]{J2152_galpak_camel_z143.pdf}
  \caption{Same as Figure~\ref{fig:J2137G1} but for J215200+0625G3 at redshift $z=1.4303$.
  Note that the emissions around the galaxy in the observed [\hbox{{\rm O}{\sc \,ii}}] flux panel is noise and not tidal tails.
  This galaxy has a maximum SNR/pixel of 10.5.
  Again, as in Figures~\ref{fig:J2137G3} and \ref{fig:J2152G1}, residual spots are galaxies further away from the quasar LOS and are thus less likely to be the host of the absorbing materials (78, 184 and 211~kpc).
  The 78~kpc away galaxy is close enough to be considered as an host galaxy but we choose to ignore it based on impact parameter argument.
}
  \label{fig:J2152G3}
\end{figure*}

\begin{table*}[]
\centering
\caption{Morpho-kinematics results on host galaxies. \label{table:galpak}
}
\begin{tabular}{lccclcllcll}
\hline
Galaxy 		&$z_{\rm abs}$		&$z_{\rm gal}$	&$b$	&SNR	&Size  		&$i$		&$V_{\rm max}$	&Flux			&$\alpha$	&Class	\\
(1) 		&(2)			&(3)	&(4)		&(5)	&(6)		&(7)		&(8)		&(9)			&(10)		&(11)	\\
\hline
J213748+0012G1	&0.8063		&0.80690$\pm$0.00001	&88.1$\pm$0.2	&11	&2.43$\pm$0.06	&49.6$\pm$1.4	&126.2$\pm$5	&$8.67\times10^{-17}$	&25$\pm1$	&Inflow	\\
J213748+0012G2	&1.1890		&1.18925$\pm$0.00001	&63.7$\pm$0.2	&11	&3.15$\pm$0.08	&55.6$\pm$0.8	&15.9$\pm$8	&$1.47\times10^{-16}$	& $\cdots$	& Merger	\\
J213748+0012G3	&1.2144		&1.21397$\pm$0.00003	&87.2$\pm$0.2	&4.5	&5.38$\pm$0.33	&40.4$\pm$5.0	&166.5$\pm$18	&$4.18\times10^{-17}$	&47$\pm2$	&Ambig.	\\
J215200+0625G1	&1.0534		&1.05335$\pm$0.00001	&45.4$\pm$0.2	&9.3	&5.52$\pm$0.09	&69.4$\pm$0.7	&161.4$\pm$2	&$1.09\times10^{-16}$	&4$\pm1$	&Inflow	\\
\textbf{J215200+0625G2}	&1.3190		&1.31843$\pm$0.00005	&34.0$\pm$0.2	&4.2	&3.06$\pm$0.51	&58.9$\pm$10.8	&130.6$\pm$29	&$1.99\times10^{-17}$	&88$\pm5$	&Wind	\\
J215200+0625G3	&1.4309		&1.43033$\pm$0.00004	&62.5$\pm$0.2	&10.5	&1.51$\pm$0.12	&13.3$\pm$3.4	&298.5$\pm$39	&$5.05\times10^{-17}$	&72$\pm20$	&Wind$/$Ambig.	\\
\hline
\end{tabular}\\
\vspace*{0,1cm}
{
(1) Quasar name;
(2) \hbox{{\rm Mg}{\sc \,ii}}\ absorption redshift;
(3) Galaxy redshift;
(4) Impact parameter (kpc);
(5) SNR per pixel;
(6) Galaxy half-light radius (kpc);
(7) Galaxy inclination (degrees);
(8) Galaxy maximum velocity (\hbox{${\rm km\,s}^{-1}$} );
(9) Integrated [\hbox{{\rm O}{\sc \,ii}}] flux of the galaxy (erg\,s$^{-1}$\,cm$^{-2}$);
(10) Azimuthal angle (degrees);
(11) Class (inflow-pair/wind-pair) based on $\alpha$ selection.
}
\end{table*}

\begin{figure}[]
  \centering
  \includegraphics[width=9cm]{incl_vs_alpha_MEGAFLOW.pdf}
  \caption{Galaxy inclinations as a function of azimuthal angle $\alpha$ for the 5 non-merger galaxies detected in the two fields J213748+0012 and J215200+0625.
  We note that only one galaxy is classified as a wind-pair.
  The dashed areas correspond to azimuthal angle ranges for which we classify pairs as inflow-pairs (blue and narrow dashes) or wind-pairs (green and wider dashes).
  These areas stop for face-on galaxies as uncertainty on position angles are too large and thus difficult to classify pairs.
  \label{fig:incl_vs_alpha}
}
\end{figure}

\subsection{Radial dependence of CGM}
\label{REW}

For each quasar spectrum, we measure the REW for the \hbox{{\rm Mg}{\sc \,ii}}\ absorption lines ($W_{r}^{\lambda 2796}$) in the UVES data and compare them with
the SDSS values $W_{r}^{\lambda 2796}$ (see Table~\ref{table:REW}).
We find that the results are consistent with each other.
We also calculate REWs of the \hbox{{\rm Mg}{\sc \,ii}}\ \hbox{$\lambda 2803$}, \hbox{{\rm Mg}{\sc \,i}}\ \hbox{$\lambda 2852$}, \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2586$ and \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2600$ in UVES quasar spectra.
Results are shown in Table~\ref{table:REW}.
Figures~\ref{fig:J213748_abs} and~\ref{fig:J215200_abs} show the UVES MgI\ \hbox{$\lambda 2852$}, \hbox{{\rm Mg}{\sc \,ii}}\ $\lambda \lambda 2796,2802$ and \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda \lambda 2586,2600$ absorption profiles
and label the measured REW of each profile for both quasar fields.

\begin{figure*}[h!]
  \centering
  \includegraphics[width=18cm]{J213748_UVES_absorptions.pdf}
  \caption{UVES \hbox{{\rm Mg}{\sc \,i}}\ \hbox{$\lambda 2852$}, \hbox{{\rm Mg}{\sc \,ii}}\ $\lambda \lambda 2796,2802$ and \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda \lambda 2586,2600$ absorption lines centered
  at host galaxy systemic velocity for the SDSSJ213748+0012 quasar spectrum.
  The left panel corresponds to absorption lines from the SDSSJ213748+0012G1 host galaxy (a).
  The middle panel to the SDSSJ213748+0012G2 host galaxy (b),
  and right panel to SDSSJ213748+0012G3 (c).
  Note that in the right column, the \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda 2586$ REW is calculated without the $\approx$200~\hbox{${\rm km\,s}^{-1}$}\ absorption component.}
  \label{fig:J213748_abs}
\end{figure*}

\begin{figure*}[h!]
  \centering
  \includegraphics[width=18cm]{J215200_UVES_absorptions.pdf}
  \caption{UVES \hbox{{\rm Mg}{\sc \,i}}\ \hbox{$\lambda 2852$}, \hbox{{\rm Mg}{\sc \,ii}}\ $\lambda \lambda 2796,2802$ and \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda \lambda 2586,2600$ absorption lines centered
  at host galaxy systemic velocity for the SDSSJ215200+0625 quasar spectrum.
  The left panel corresponds to absorption lines from the SDSSJ215200+0625G1 host galaxy (a).
  The middle panel to the \textbf{SDSSJ215200+0625G2} host galaxy (b),
  and right panel to SDSSJ215200+0625G3 (c).}
  \label{fig:J215200_abs}
\end{figure*}

One of the first deductions we can make from Figures~\ref{fig:J213748_abs} and~\ref{fig:J215200_abs} is that there is no clear difference (like different asymmetry behavior for instance) between what seems
to be outflowing material and circum-galactic or inflowing gas concerning the different absorption lines.

Figure~\ref{fig:rew_vs_b} shows the distribution of REW $W^{\lambda 2796}_{\rm r}$ for pairs
with an azimuthal angle $\alpha > 45^\circ$ as a function of impact parameter $b$ for this work
as well as \citet{kacprzak_11b, kacprzak_11} and \citet{schroetter_15}.
This Figure shows that for wind pairs, as mentioned in \citet{bouche_12}, we clearly see a tight correlation between $W^{\lambda 2796}_{\rm r}$ and $b$.
This $W^{\lambda 2796}_{\rm r} - b$ correlation goes approximatively as $b^{-1}$.
This figure shows that the anti-correlation between impact parameter $b$ and $W_r$ is again confirmed at $b<100$ kpc.
The scatter around the relation in Figure~\ref{fig:rew_vs_b} is $\approx0.3$ dex (delineated with the dotted lines).
The solid line traces the fiducial $1/b$ relation for mass-conserved bi-conical outflows \citep[see][]{bouche_12}.

\begin{table*}[h!]
\centering
\caption{UVES rest equivalent widths. \label{table:REW}
}
\begin{tabular}{lcccccccl}
\hline
Galaxy 		&$W_r^{\lambda \rm 2796}$(SDSS)	&$W_r^{\lambda \rm 2796}$	&$W_r^{\lambda \rm 2802}$	&$W_r^{\lambda \rm 2852}$	&$W_r^{\lambda \rm 2586}$	&$W_r^{\lambda \rm 2600}$	&$log(N_{\hbox{{\rm H}{\sc \,i}}})$	&Class	\\
(1) 		&(2)				&(3)				&(4)				&(5)				&(6)				&(7)				&(8)		&(9)\\
\hline
J213748+0012G1	&0.724$\pm$0.09			&0.789$\pm$0.02			&0.572$\pm$0.02			&0.145$\pm$0.02			&0.135$\pm$0.02			&0.309$\pm$0.02			&19.24		&Inflow	\\
J213748+0012G2	&0.308$\pm$0.06			&0.294$\pm$0.02			&0.155$\pm$0.02			&0.039$\pm$0.02			&$\cdots$			&0.058$\pm$0.02			&18.61		& Merger	\\
J213748+0012G3	&1.122$\pm$0.06			&1.132$\pm$0.02			&1.040$\pm$0.02			&0.223$\pm$0.02			&0.707$\pm$0.02			&0.947$\pm$0.02			&19.58		&Ambig.	\\
J215200+0625G1	&0.522$\pm$0.14			&0.545$\pm$0.02			&0.460$\pm$0.02			&0.116$\pm$0.02			&0.175$\pm$0.02			&0.271$\pm$0.02			&19.01		&Inflow	\\
\textbf{J215200+0625G2}	&1.347$\pm$0.12			&1.424$\pm$0.02			&1.065$\pm$0.02			&0.158$\pm$0.02			&0.322$\pm$0.02			&0.709$\pm$0.02			&19.71		&Wind	\\
J215200+0625G3	&1.152$\pm$0.11			&1.157$\pm$0.02			&$\cdots$			&$\cdots$			&0.122$\pm$0.02			&0.242$\pm$0.02			&19.59		& Wind$/$Ambig.	\\
\hline
\end{tabular}\\
\vspace*{0,1cm}
{
(1) Quasar name;
(2) SDSS \hbox{{\rm Mg}{\sc \,ii}}\ \hbox{$\lambda 2796$}\ rest equivalent width (\AA );
(3) UVES \hbox{{\rm Mg}{\sc \,ii}}\ \hbox{$\lambda 2796$}\ rest equivalent width (\AA );
(4) UVES \hbox{{\rm Mg}{\sc \,ii}}\ \hbox{$\lambda 2803$}\ rest equivalent width (\AA );
(5) UVES \hbox{{\rm Mg}{\sc \,i}}\ \hbox{$\lambda 2852$}\ rest equivalent width (\AA );
(6) UVES \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2586$ rest equivalent width (\AA );
(7) UVES \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2600$ rest equivalent width (\AA );
(8) Gas column density at the impact parameter (cm$^{-2}$);
(9) Class (inflow-pair/wind-pair) based on $\alpha$ selection.
}
\end{table*}

\begin{figure}[]
  \centering
  \includegraphics[width=8.0cm]{rew_vs_b_MEGAFLOW_with_scatter03.pdf}
  \caption{$W_r^{\lambda 2796}$ as a function of impact parameter $b$ for galaxy-quasar pairs classified as wind-pairs.
  The dashed blue lines show the 0.3 dex scatter.
  The horizontal dotted black lines represent the $W_r^{\lambda 2796}$=0.8~\AA\ and $W_r^{\lambda 2796}$=0.5~\AA\ selection limits.
  }
  \label{fig:rew_vs_b}
\end{figure}

\section{Wind model}
\label{wind}

In this section, we describe the wind modeling.
We create a cone having an opening angle corresponding to \hbox{$\theta_{\rm max}$}\footnote{\hbox{$\theta_{\rm max}$} is defined from the central axis,
and the cone subtends an area $\Sigma$ of $\pi \cdot \theta_{\rm max}^2$.}
and fill it randomly with particles representing cold gas clouds being pushed away by a hot medium or radiation pressure.
These particles are distributed such that their number goes like $1 / r^2$, where $r$ is the distance to the galaxy center.
The particle density is normalized arbitrarily to reproduce the optical depth of the absorption profiles.

Such entrained clouds are accelerated to their terminal velocity quickly in a few kpc or $<10$ kpc since the pressure from
 the hot medium or the radiation field scales as $1/r^2$. The range of impact parameters for the galaxy$-$quasar pair
in our sample is always larger than 30~kpc. Hence, we assume, for simplicity, that the particles have a constant radial velocity corresponding to \hbox{$V_{\rm out}$}.
In addition, a single LOS probes a rather small range of distances from the host galaxy such that a gradient in the outflow velocity would have no significant impact on our results.
So far, only in one LOS with an impact parameter less than 10 kpc in \citet{schroetter_15}, we required an accelerated wind profile.

We then orient the cone following the galaxy inclination and simulate the quasar LOS such that
the galaxy$-$quasar pair matches the geometrical configuration of the MUSE data.

The particle velocities are then projected along the simulated quasar LOS and the distribution of the projected velocities gives us a
simulated optical depth $\tau_{\rm v}$, which we turn into an absorption profile $\propto \exp(-\tau_{\rm v})$.
In order to facilitate comparison with the data, Poisson noise is added to the simulated absorption profile to simulate the instrumental noise.
This noise is chosen to have the same level as the data.

The model has two main free parameters, the wind speed \hbox{$V_{\rm out}$}\ and \hbox{$\theta_{\rm max}$}\ the wind opening angle.
These two parameters are independent for a given galaxy inclination as one can see from the following arguments (see also \citet{schroetter_15} for more details).
The outer edges of the absorption profile (reddest for a cone pointing away from the observer, bluest for a cone pointing towards the observer) depends directly on the wind velocity (Figure A-1 in \citet{schroetter_15}).
The inner edge (towards Vsys) of the absorption profile depends directly on the wind opening angle \hbox{$\theta_{\rm max}$}\ (Figure A-1 in \citet{schroetter_15}).
Note that the galaxy inclination impacts the absorption profiles similarly to the \hbox{$\theta_{\rm max}$}\ parameter but since the inclination is determined by our 3D fit with GalPaK$^{\rm 3D}$, there are no degeneracies.

In order to determine which model best reproduces the data, the best fit model is found by eye.
However, given that there are stochastic features in the simulated profiles,  we generate dozens of simulated profiles for a given set of parameters.
The errors on these parameters are given by the range of values allowed by the data.
We proceed as follow:
We first generate models changing only one parameter to fit one part of the absorption profile (outer part for \hbox{$V_{\rm out}$}\ or inner part for \hbox{$\theta_{\rm max}$}).
Then, we change only the other parameter (\hbox{$\theta_{\rm max}$}\ or \hbox{$V_{\rm out}$}) generating other models to fit the other part of the absorption.
We generate models with range of values of 10 to 500~\hbox{${\rm km\,s}^{-1}$}\ (with steps of 10~\hbox{${\rm km\,s}^{-1}$}) for \hbox{$V_{\rm out}$}\ and 20 to 50$^\circ$ (with steps of 5$^\circ$) for \hbox{$\theta_{\rm max}$}.
As mentioned before, these two parameters being independent, there is no degeneracy between generated models.
We use these parameters range to fit the data since outflows are likely to be collimated in a cone with an opening angle around 30$^\circ$
\citep[e.g.][]{chen_10, bouche_12, bordoloi_11, kacprzak_12, martin_12, bordoloi_14, rubin_14}

Examples on how the wind model behaves as we change the different parameters can be seen in the appendix of \citet{schroetter_15}.

\subsection{The wind$-$pair case of \textbf{J215200+0625G2}}
\label{individual}

Figure~\ref{fig:J215200_abs}, middle column (b), shows the UVES \hbox{{\rm Mg}{\sc \,i}}\ \hbox{$\lambda 2852$}, \hbox{{\rm Mg}{\sc \,ii}}\ $\lambda \lambda 2796,2802$
and \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda \lambda 2586,2600$ absorption lines for this galaxy-quasar pair.
From this Figure, we can see that the \hbox{{\rm Mg}{\sc \,ii}}\ $\lambda \lambda 2796,2802$ absorption lines are saturated and thus the need to simulate the absorption from \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda 2586$ which is
the only non-saturated absorption lines in the presented transitions.

The bottom right panel of Figure~\ref{fig:J215200G2} shows the UVES \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2586$ absorption lines corresponding to the \textbf{J215200+0625G2} galaxy redshift of $z=1.3184$.
This absorption is the one we intend to fit in order to constrain outflow properties since other absorption lines like \hbox{{\rm Mg}{\sc \,ii}}\ are saturated (see panel (b) of Figure~\ref{fig:J215200_abs}).
In this profile, we can see a suppression of absorption around 80~\hbox{${\rm km\,s}^{-1}$}.
We first tried to fit this absorption with our wind model described in \S~\ref{wind} but failed to reproduce this gap, even with stochastic effects.
This lack of absorbing particles at these velocities shows that the outflowing cone must have a low density region inside it.

Given that the geometry of this galaxy-quasar system (with a galaxy inclination $i$ of 59$^\circ$) and that the quasar line of sight is crossing the outflowing cone near its middle ($\alpha=88^\circ$),
we thus developed a partially empty cone model in order to reproduce the absorption profile.

The principle is the same as the wind model described in \S~\ref{wind} except that we only fill the cone with particles from a certain opening angle $\theta_{\rm in}$ to \hbox{$\theta_{\rm max}$}.
The inner cone is thus empty.
This model should only work if the azimuthal angle $\alpha$ of a galaxy$-$quasar system is above $\sim80^\circ$, so the quasar LOS is crossing this empty region
and thus creating a gap of velocities in the simulated profile.

This empty inner cone could be the signature of a hotter gas filling the inner cone while the ionized gas traced by our low-ionization lines
would correspond to the walls of the outflowing cone in a manner similar to \citet{fox_15} for the MilkyWay and to \citet{veilleux_02} for NGC1482.

Figure~\ref{fig:J215200G2} illustrates the resulting wind modeling for this galaxy.
The first left column corresponds to the wind model representation.
The top left panel shows a [\hbox{{\rm O}{\sc \,ii}}] integrated flux, continuum subtracted, image with the orange cross showing the quasar LOS position.
The inclined circles represent the outflowing cone.
The bottom left panel represents a side view of the cone, the quasar LOS being represented by the dashed red line, the observer being on the left.
This representation allows us to see if the outflowing material is ejected toward or away from us, assuming our cone model is representative.
The red part of the cone represents the empty inner part.

On the middle column are represented the simulated profiles (top) and UVES spectrum around the absorption line \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2586$ (bottom).
The red part of the simulated profile is the profile without instrumental noise and the apparent noise is due to stochastic
effects from the Monte Carlo particle distribution.
The red simulated absorption profile does not change much for the UVES data as compare to the noise-added one.
We also present in Figure~\ref{fig:J215200G2}, top right panel, a similar simulated profile (with the same parameters) but without the empty inner cone model.
We clearly see on this Figure that we cannot reproduce the gap shown in the data without an empty region.

The bottom middle panel corresponds to UVES data.
It corresponds to the QSO spectrum absorption lines centered at the galaxy systemic velocity.
The element \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2586$ corresponding to the absorption lines is shown in the bottom middle column panel.

To reproduce the shape of this absorption profile and generate the simulated profile shown in the top middle panel of Figure~\ref{fig:J215200G2}, we adjust the outflow speed \hbox{$V_{\rm out}$}\ and the cone opening angle \hbox{$\theta_{\rm max}$}\
while keeping the geometrical parameters of the galaxy fixed as described in \S~\ref{wind}.

The best values for reproducing the UVES \hbox{{\rm Fe}{\sc \,ii}}\ $\lambda2586$ absorption profile are an outflow velocity \hbox{$V_{\rm out}$}\ of $150 \pm 10$~\hbox{${\rm km\,s}^{-1}$}\ and
a cone opening angle \hbox{$\theta_{\rm max}$}\ of $20\pm5^\circ$.
For this specific case, we derive an inner opening angle of the cone of $\theta_{\rm in} \approx 7^\circ$.

\label{J215200G2}
\begin{figure*}[h!]
  \centering
  \includegraphics[width=16cm]{J215200G2_UVES_v3.pdf}
  \caption{
  Representation of the cone model and quasar spectrum associated with the \textbf{J215200+0625G2} galaxy ($z=1.31845$).
  \textit{Top left: }the cone model seen in the sky plane (xy).
  This is a narrow band image centered around the galaxy [\hbox{{\rm O}{\sc \,ii}}] emission lines with the continuum subtracted.
  The dashed circle represents the inclined galaxy disk and the black and white inclined circles illustrate the gas outflow cone.
  The orange cross represents the position of the quasar LOS.
  \textit{Bottom left: }a side view of the cone where the z-axis corresponds to the quasar LOS direction with the observer to the left.
  The red part of the cone represents the empty inner cone.
  \textit{Middle: }Normalized flux for the \hbox{{\rm Fe}{\sc \,ii}}\ ($\lambda 2586$) absorption line observed with UVES (bottom) and the reconstructed profile (top).
  Note that this model does not reproduce the depth of the absorption line.
  In UVES simulated absorption profile, the red line corresponds to the simulated profile without any instrumental noise.
  This wind model uses a very low-density inner cone as described in \S~\ref{individual}.
  \textit{Right: }same as the top middle panel but with no empty inner cone model.
  This simulated profile has the same parameters as the empty inner cone one.
  We can clearly see that we cannot reproduce the gap in absorptions seen in the UVES absorption profile without the empty cone model.
  This outflow has a \hbox{$V_{\rm out}$}\ of 150$\pm$10~\hbox{${\rm km\,s}^{-1}$}, a cone opening angle \hbox{$\theta_{\rm max}$}\ of 20$\pm$5$^\circ$ and an inner opening angle $\theta_{in}$ of 7$\pm$2$^\circ$.}
  \label{fig:J215200G2}
\end{figure*}

\subsection{Outflow rates}
\label{outflow}
Having constrained the outflow velocity and cone opening angle for the wind-pair, we can now derive the ejected mass rate $\dot M_{\rm out}$ as well as the loading factor.

For our wind-pair, the equivalent width of the absorption lines only depends on \hbox{$\theta_{\rm max}$}\ and \hbox{$V_{\rm out}$}\ (see \S~\ref{wind}).
After testing several opening angles and outflow velocities, we fitted the width of the absorption profile created by gas outflowing from the galaxy.
The asymmetry of the profile depends on the system geometry.
To constrain the ejected mass rate probed by the quasar LOS, we use relation~\ref{eq:Mout} from \citet{bouche_12} and \citet{schroetter_15}:
\begin{eqnarray}
 \dot M_{\rm out} &\approx& \mu \cdot N_{\rm H}(b) \cdot b \cdot V_{\rm out} \cdot \frac{\pi}{2} \cdot \theta_{\rm max}\label{eq:Mout}\\
{\dot M_{\rm out} \over 0.5\/ \hbox{M$_{\odot}$\,yr$^{-1}$}\ }& \approx &{\mu \over 1.5} \cdot {N_{\rm H}(b)\over 10^{19} \rm cm^{-2}} \cdot {b\over 25 \rm kpc} \cdot {V_{\rm out} \over 200 \hbox{${\rm km\,s}^{-1}$}\ } \cdot {\theta_{\rm max} \over 30^{\circ}}\nonumber
\end{eqnarray}
$\mu$ being the mean atomic weight, $b$ the impact parameter, \hbox{$\theta_{\rm max}$}\ the cone opening angle\footnote{We remind the reader that \hbox{$\theta_{\rm max}$} is defined from the central axis,
and the cone subtends an area $\Sigma$ of $\pi \cdot \theta_{\rm max}^2$.}, \hbox{$V_{\rm out}$}\ the outflow velocity and $N_{\rm H}(b)$ is the gas column density
at the $b$ distance.

The only parameter which is yet to be constrained is the gas column density $N_{\rm H}(b)$.
To do that, we use the empirical relation~\ref{eq:menard} between the neutral gas column density
and the \hbox{{\rm Mg}{\sc \,ii}}\ \hbox{$\lambda 2796$}\ REW $W_r^{\lambda 2796}$ \citep{menard_09}:

\begin{equation}
 \log (N_{\rm HI}) (\hbox{cm}^{-2}) = \log [(3.06 \pm 0.55) \times 10^{19} \times (W_r^{\lambda 2796} )^{1.7 \pm 0.26}]\label{eq:menard}.
\end{equation}

To compute the errors, we assume a gaussian error distribution.
As described in \citet{schroetter_15}, for regions with \hbox{{\rm H}{\sc \,i}}\ column density above $\log(N_{\rm HI})=19.5$, the ionized gas contribution is negligible.
Also argued by \citet{jenkins_09}, if this column density is above this limit, one can use the correlation between \hbox{{\rm Mg}{\sc \,ii}}\ equivalent width and $N_{\rm HI}$ as a proxy for the $N_{\rm H}$ gas column density.
For the wind-pair \textbf{J215200+0625G2}, we have a gas column density of $\log (N_{\rm HI})\approx19.7\pm0.07$.

Another aspect of outflow properties is whether the outflowing gas is able to escape from the galaxy gravitational well.
To determine this, we derive the escape velocity $V_{\rm esc}$ for the \textbf{J215200+0625G2} galaxy.
The escape velocity for an isothermal sphere is defined by Eq.~\ref{eq:Vesc} \citep{VeilleuxS_05a}.
\begin{equation}
 V_{\rm esc}=V_{\rm max}\cdot\sqrt{2\left[1+\ln \left(\frac{R_{\rm vir}}{r}\right)\right]}\label{eq:Vesc}
\end{equation}
$V_{\rm max}$ being the maximum rotation velocity of the galaxy and $R_{\rm vir}$ its virial radius.
The virial radius of the galaxies can be define as $R_{\rm vir} \approx V_{\rm max}/10H(z)$ where $H(z)$ is the Hubble parameter at redshift $z$.
In Table~\ref{table:results}, we compare the outflow velocity with the escape velocity for the wind-pair.
This ratio $V_{\rm out}/V_{\rm esc}$ of 0.52 shows that
the outflowing material is not able to reach the escape velocity and will thus likely to fall back onto the galaxy, assuming we are tracing the gas going out of the galaxy.
One can ask whether we are already tracing the gas falling back onto the galaxy.
If this is the case, we should see another opposite component (with respect to the systemic velocity) in the absorption profile corresponding to the outflowing gas.

Table~\ref{table:results} also lists the estimated outflow rate.
The errors on the ejected mass rate $\dot M_{\rm out}$ are dominated by the ones on the gas column density $N_{\rm HI}$ and the SFR.

\begin{table*}[h]
\centering
\caption{Results for the galaxy \textbf{J215200+0625G2}.}
\label{table:results}
\begin{tabular}{lccccccccc}
\hline
Galaxy		&$b$ (kpc)	& log($N_{\rm H}(b)$)	& $V_{\rm max}$		& $V_{\rm out}$	&$\theta_{\rm max}$	&SFR		&$\dot M_{\rm out}$	&$\frac{V_{\rm out}}{V_{\rm esc}}$	&$\eta$	\\
(1)		&(2)		&(3)			&(4)			&(5)		&(6)			&(7)		&(8)			&(9)					&(10)	\\
\hline
\textbf{J215200+0625G2}	&34.0		&19.7$\pm$0.07		&$140.8 \pm 51$		&$150 \pm 10$	&20 $\pm$ 5.0		&4.6$\pm$0.4	&1.7 $^{+1.1}_{-0.8}$	&0.52					&0.75	\\
		&		&			&			&		&			&		&1.1 $^{+0.9}_{-0.6}$	&					&0.49	\\
\hline
\end{tabular}\\
{
(1) Galaxy name;
(2) Impact parameter (kpc);
(3) Gas column density at the impact parameter (cm$^{-2}$);
(4) Maximum rotational velocity of the galaxy (\hbox{${\rm km\,s}^{-1}$} );
(5) Wind velocity (\hbox{${\rm km\,s}^{-1}$} );
(6) Cone opening angle (degrees)
(7) Star Formation Rate (\hbox{M$_{\odot}$\,yr$^{-1}$});
(8) Ejected mass rate for one cone (\hbox{M$_{\odot}$\,yr$^{-1}$});
(9) Ejection velocity divided by escape velocity;
(10) Mass loading factor: ejected mass rate divided by star formation rate
(for both cones).
Values in the second row ($\dot M_{\rm out}=1.1^{+0.9}_{-0.6}$~\hbox{M$_{\odot}$\,yr$^{-1}$} and $\eta=0.49$) correspond to the empty inner cone model.
\\
}
\end{table*}

From the outflow rate, we compute the mass loading factor $\eta$ by comparing it to the SFR ($\eta=\dot M_{\rm out} / \rm SFR$).
For our \textbf{SDSSJ215200+0625G2} pair, we used the empty cone model to reproduce the absorption profile with an inner cone opening angle $\theta_{\rm in}$ of 7$^\circ$.
To be consistent with the other cases, we give two solutions for this galaxy$-$quasar pair: one with the filled cone and one with the inner cone subtracted.

Figure~\ref{fig:eta_vs_vmax} shows the loading factor $\eta$ as a function of halo mass and maximum rotational velocity \hbox{$V_{\rm max}$}\ for this work and previous similar studies \citep{bouche_12, kacprzak_14, schroetter_15}.
The derived loading factor for galaxy \textbf{SDSSJ215200+0625G2} follows the same trend as the others.
The red arrow shows the loading factor for the subtracted mass from the low-density inner cone.

\begin{figure*}[]
  \centering
  \includegraphics[width=14cm]{eta_vs_vmax_MEGAFLOW_with_new_model}
  \caption{Comparison of mass loading factors assumed by theoretical/empirical models (curves) with values derived from background quasar observations
  (dots and triangles) as a function of the maximum rotational velocity.
 The result from this work is represented by the red circle.
 The red arrow represents the loading factor of the \textbf{SDSSJ215200+0625G2} galaxy with the subtracted mass from the inner cone model.
 The cyan circles show the results for galaxies at $z\approx0.8$ from \citet{schroetter_15}.
 The green square shows the mass loading factor for a $z\approx0.2$ galaxy \citep{kacprzak_14}.
 The triangles show the results for $z\approx0.2$ galaxies from \citet{bouche_12}.
 The gray triangles show the galaxies with quasars located at $>$60kpc where the mass loading factor is less reliable due to the large travel time
 needed for the outflow to cross the quasar LOS (several 100 Myr) compared to the short time scale of the \hbox{{\rm H}$\alpha$}\ derived SFR ($\sim 10$Myr).
 The upper halo mass axis is scaled on $V_{\rm max}$ at redshift 0.8 from \citet{mo_02}.
  }
  \label{fig:eta_vs_vmax}
\end{figure*}

MUSE allows us to probe galaxies with an impact parameter larger than before with an IFU.
But, in Figure~\ref{fig:eta_vs_vmax}, we caution the reader that loading factor for galaxies with impact parameters larger than 60 kpc are less
reliable because of the time needed for the gas to travel from the galaxy to the quasar LOS ($\sim 400$ Myr at $\hbox{$V_{\rm out}$}\approx 150 \hbox{${\rm km\,s}^{-1}$}$ with $b=60$ kpc).
A major limitation for the comparison between data and models in Figure~\ref{fig:eta_vs_vmax},
is that $\eta$ in simulations are usually measured on a scale of a few kpc away from the galaxy, which is one order of magnitude lower than most of the observations (tens of kpc).

\section{Summary}
\label{conclusion}
We present results on 2 GTO VLT/MUSE fields in which we searched for galaxy-quasar pairs.
These fields were selected from the SDSS database where we searched for multiple \hbox{{\rm Mg}{\sc \,ii}}\ absorbers, with $z\approx 0.8 - 1.4$ and $W_r^{\lambda 2796}>0.5$\AA,
in the quasar spectra.
Out of 8 \hbox{{\rm Mg}{\sc \,ii}}\ absorptions in the quasar spectra of these two fields, we detect 6 redshift-corresponding SFGs.
For these 2 fields (J213748+1112 and J215200+0625) we also have high resolution spectra of the quasars from the VLT/UVES instrument.
In each of these two fields, we detected more than 40 emitters in the $1\arcmin \times 1\arcmin$ MUSE field of view (see the Appendix).
We focused on galaxies at MgII absorptions redshifts in the quasar spectra and for which the associated quasar LOS is aligned with their minor axis ($\alpha>55^\circ$)
and is thus likely to probe outflowing materials (wind$-$pairs).
Among the 6 detected SFGs, one is likely to be a wind-pair due to its orientation with respect to its relative quasar.

In summary, thanks to our new GTO VLT/MUSE and VLT/UVES data,
MUSE allows us to detect galaxies far away from their associated quasar ($\sim 100$~kpc) as compare to previous similar works \citep[i.e. ][]{bouche_12, kacprzak_14, schroetter_15}.
For the wind-pair \textbf{SDSSJ215200+0625G2}, we found that the outflow velocity \hbox{$V_{\rm out}$}\ is $\approx 150$~\hbox{${\rm km\,s}^{-1}$}.
The outflowing gas is likely to stay inside the gravitational well of the galaxy and the loading factor is $\eta\approx0.7$.
We showed a gap in velocities in the absorption profile which led to a low-density inner cone modeling.
At this point, we have outflowing constraints for one galaxy but we showed that MUSE is able to provide very good data and will play a fundamental role in this field.

MUSE allowed us to probe multiple galactic wind cases at the same time and enhance the number of cases with only two quasar fields.
We also have a case of low-density inner cone which opens discussions on geometrical properties of outflowing materials.
The MEGAFLOW sample is currently growing and successful in detecting galaxies in each quasar field ($\approx$84$\%$ detection).
Future work will be done with a lot more observation with MUSE$+$UVES, and in a short time, the MEGAFLOW sample should be large enough to produce statistical results on outflow properties.
\acknowledgments
\textit{Acknowledgments.} NB acknowledges support from a Career Integration Grant (CIG) (PCIG11-GA-2012-321702) within the 7th European Community Framework Program.
This work has been carried out thanks to the support of the ANR FOGHAR (ANR-13-BS05-0010-02), the OCEVU Labex (ANR-11-LABX-0060) and the A*MIDEX project (ANR-11-IDEX-0001-02)
funded by the ``Investissements d'Avenir" French government program managed by the ANR.
This work received financial support from the European Research Council under
the European Union's Seventh Framework Programme (FP7$/$2007-2013) $/$ ERC Grant agreement 278594-GasAroundGalaxies.

\clearpage

redpajama_set_name: RedPajamaArXiv


text:
Чекчинский сельсовет — упразднённая административно-территориальная единица, существовавшая на территории Московской губернии и Московской области до 1939 года.

Чекчинский сельсовет был образован в первые годы советской власти. По данным 1921 года он входил в состав Ошейкинской волости Волоколамского уезда Московской губернии.

По данным 1926 года в состав сельсовета входили 2 населённых пункта — Большое Чекчино и Малое Чекчино.

В 1929 году Чекчинский с/с был отнесён к Лотошинскому району Московского округа Московской области.

17 июля 1939 года Чекчинский с/с был упразднён, а его территория передана в Бреневский сельсовет.

Примечания

Упразднённые сельсоветы Лотошинского района

redpajama_set_name: RedPajamaWikipedia


Education History: Grew up in Australia, college and graduate school at Osaka University in Japan in behavioral physiology, graduate school at University of Florida in behavioral neuroscience and a Ph.D. from Florida State University in Neuroscience.
I work in a laboratory designing and conducting experiments using animal models (rats and mice). We collect the data and publish it in journals for people to read and go to conferences to talk to other scientists. I interact with students who are developing laboratory skills and give lectures to college students.
I am interested in behavior, what makes us eat certain things or move in certain ways? I'm also interested in biology and it's a way we can figure out HOW we have these different behaviors. I took classes that I was interested in and I followed people who worked in labs until I found something that I enjoyed a lot.
A day working in the laboratory involves taking care of the animals, running experiments, collecting data. Some days I spend in the office which involves reading about what else is going on in the science world, analyzing data that I've collected from the laboratory and writing about what we have found. Several times a year, I am able to go to different places in the US and the world to meet with other scientists and talk about what we have found in the laboratory and problems we have solving particular questions.
That my job is to think!
I work on questions about how biology influences behavior, for example, how do we taste something that's sweet and why do some people think sweet tastes good but some people hate it? These are questions that almost all of us have thought about and can relate to, yet there is a lot we don't understand.
What did you have to learn in order to do what you do?
I had to take classes about basic neuroscience, work in different laboratories to learn how to do experiments and learn from more established scientists about how to design experiments and collect data.
Do what you feel interests you the most! It doesn't matter if you think it's unusual or impractical or you don't know quite yet how you will get there.
STEM involves a wide range of topics and types of skills, many of which are still unexplored.


Before getting to the heart of the matter here are a few disclaimers.
My expertise in the field of water chemistry is limited to observing the results of, and in some cases repairing, the damage caused by the introduction of improperly treated water into a boiler. My expertise does not cover water chemistry itself. Therefore, this article complies and presents information from sources who have experience and expertise in the field of boiler water chemistry.
Any type of boiler made by any manufacturer will be damaged by the addition of water with improper chemistry.
In most cases, damage caused by improperly treated entering a boiler is gradual and cumulative. This slow damage impacts a plant's bottom line in the form of escalating fuel and steam system maintenance costs. Check the accompanying chart to see just how expensive a thin coating of scale inside a boiler can be.
Coleridge's quote pertains to this article because its focus is about unusable water. More specifically, water unusable in its current form. In the mariner's case he was adrift, surrounded by water yet dying of thirst. He couldn't just drink the water. He knew the dissolved salt in the water would kill him. For boilers, impurities in improperly treated water will, over a period of time, do the same. I've presented seminars on boilers and other machinery maintenance issues and invariably there is someone in the audience who claims they do not treat makeup water and have had no boiler problems. In some cases it's true; the reason is, fortunately the quality of the city water where they are located allows for non-treatment. However, this is a rare occurrence; water quality varies significantly even in close geographical areas so beware, even if the cleaner on the next block gets away with it doesn't mean you can.
Water is often referred to as the universal solvent and therein lies the problem. Water dissolves almost anything it contacts – emphasis on almost.Salt, sugar, acid, bases, many gasses, water doesn't care, it just dissolves and dissolves and keeps on rolling. Take a moment to think about that. What barbarian among us would confuse a glass of sparkling San Pellegrino or Perrier with a glass of common tap water, after all it's just H2O isn't it? The difference in taste is what's dissolved in the water. New water added to a boiler condensate return tank must be treated to remove or control the concentration levels of many of these solutes (a solute is something dissolved in a solvent like water). Look at the accompanying chart to understand the large effect a scale coating on boiler internals has on the increase in fuel consumption.
TAP, MAKEUP OR CITY WATER-Raw water used to make up for the water lost in using the steam generated by the boiler. This water contains most of the impurities which require treatment.
FEED WATER-Water contained in the return tank. A combination of fresh makeup water added to the tank and condensate returning to the return or condensate tank from the machinery.
BOILER WATER- Water contained inside the boiler, which will be converted to steam.
We will only be concerned with feed and boiler water from this point forward. There are maximum allowable quantities of dissolved impurities for both feed and boiler water and these will vary slightly with each boiler manufacturer.
This is a good place to break for this article, in the next issue we will delve into what's dissolved in the water and how to treat raw water to make it safe to use in a boiler.


text:
For questions about Joseph Stalin, the leader of the U.S.S.R. from 1922 to 1952 and a leading figure in the Bolshevik Revolution.
Joseph Stalin was one of the founding figures of the U.S.S.R. and its leader for much of its early history.
He was one of the leading figures in the Bolshevik Revolution, alongside Vladimir Lenin, Leon Trotsky, and others. After the revolution, he took the office of General Secretary of the Soviet Union's Communist Party, a position which he held until it was abolished in 1941, after which he took the title of Premier. He held the office until 1952, shortly before his death in 1953.
From his position as General Secretary, and later Premier, he effectively served as the dictator of the Soviet Union for nearly 30 years. He was a major figure in World War II.
SJuan76
Semaphore♦
sempaiscuba
Did Stalin kill all Soviet officers involved in the Winter War?
Why did Stalin keep the famine of 1932 a secret?
Why did Stalin and the Soviet leadership have Leon Trotsky assassinated?
How did the world react to Trotsky's assassination?
Is this anecdote about Stalin, Roosevelt and Churchill true?
soviet-union × 40
world-war-two × 11
communism × 10
20th-century × 7
russia × 5
trotskyism × 5
political-history × 4
hitler × 4
cold-war × 3
1930s × 3
assassination × 3
yugoslavia × 3
finland × 3
nazi-germany × 2
china × 2
israel × 2
russian-revolution × 2
churchill × 2
lenin × 2
europe × 1
economy × 1
religion × 1
science × 1
everyday-life × 1
international-relations × 1

redpajama_set_name: RedPajamaCommonCrawl


The Golden Jewels Ministry is our ministry to Seniors, and is led by Carol Fulkroad and Sheila Bowman.
This ministry meets periodically throughout the year for a variety of events focused on fellowship and getting to know one another. Of course, the term, "fun, food, and fellowship" is often used to describe their enjoyable events.


text:
Calendar conundrum
Suzanne Pollak
Members of the Howard County Jewish community were out in force at last Thursday's school board meeting that addressed a possible change in the public school system's calendar.
The change, concerning whether schools should remain open on Rosh Hashanah and Yom Kippur, presented two options. One maintains the current calendar, which closes schools on the High Holidays. The other opens schools on all days except for state-mandated holidays as a way to be "equitable" to all.
Christine O'Connor, who chairs the Howard County Board of Education, began the meeting, which had more than 100 attendees, saying the board had received an estimated 500 emails concerning the topic.
The first to testify were those who the change would affect most directly: students.
Leanna Feinleib, a senior at Howard High School, said the proposal is "forcing us to choose between our education and our religion. … I don't even understand why it's even being considered."
"The school system has presented no current [data] on the operational impact of keeping schools open on Rosh Hashanah and Yom Kippur from the perspective of Jewish students and teachers," said Jamie Kotler, a student at Atholton High School.
The numbers were the focus for many of those who spoke at the meeting. Many members of the community reminded the board that closing school on the High Holidays was due to a 1979 survey that concluded the absentee rate on those days — 12 percent in 1979 — would make it operationally impractical to open schools.
"Lacking current data, the report [from the board of education] states 'the only way to obtain absence data on those days would be to open school,'" said Beth Shalom Rabbi Susan Grossman, president of the Howard County Board of Rabbis, during her testimony. "It does not seem very responsible to open school without knowing beforehand if there will be sufficient staff and [substitute teachers] available to ensure a safe and sound educational environment."
Jeremy Goldman, an Ellicott City resident, is a parent of two children who testified at the meeting. He is in favor of the first option.
"My son, who is in fourth grade, asked me the same [question]," said Goldman when asked what prompted the board to consider this change. "I don't have an answer. The [board's] report says 'recognizing the changing demographic in Howard County' [but] no one knows what that means."
Michelle Ostroff, executive director of the Jewish Federation of Howard County, submitted several statistics to demonstrate the Jewish community has grown significantly since the 1979 survey. The statistics were taken from the 2010 Jewish community study of Howard County. It said in 2010, there were 17,500 Jews in the county; an 8 percent increase since 1999. It also said there were 7,500 Jewish households; a 15 percent increase since 1999.
"In order to make a data-driven decision, more work must be done. That work should include a survey of various cultural and religious communities regarding absences on all of our most important days," Ostroff told the board. "The Jewish Federation is fully committed to assisting in collecting data and partnering with other faith and cultural organizations as well as the Howard County [Education] Association and the Howard County Administrators Association to report what's needed to make an informed decision."
Not all testimony supported keeping schools closed during the High Holidays. Indian-American resident Dipak Srinivasan said he supports keeping the schools open, because "I think it's the only responsible thing to do." Srinivasan explained he, and his wife, are forced to take off of work on those days to watch their children. His children also must miss school on Indian holidays.
"We've gone along with this discriminatory practice for that long," Srinivasan said, referring to 1979.
Several people at the meeting spoke about the Lunar New Year, celebrated by the Chinese community. They requested the board move to professional development days to coincide with the Lunar New Year and believe supporting the board's first option would lead to this change.
The board also heard from one member of the community who is no stranger to the inner workings of the school system.
"I think the underlying issue behind the committee's premature recommendation [is] the desire to treat all faith groups equally and to honor and respect the diversity of belief and culture that makes Howard County such an amazing place to live," said Joshua Kaufman, former member and chairman of the Howard County Board of Education. "The committee's instinct is wonderful and I fully support it.
"However, making a change that will negatively impact the operations of the school system," Kaufman continued, "While making students and staff across the county feel less valued and included is the totally wrong way to do that."
Previous articleCongress targets terror funds
Next articleHoCo organizations fight Islamophobia through dialogue
Possible hate crime at Gaithersburg Giant
How to survive a hostage situation


text:
[ARCHIVED] Minor Decoy Operation
Reporting Deputy: Varon Potter
File # N/A
Palm Desert, Calif. – On June 24, 2022, Deputies from the City of Palm Desert Business District and Special Enforcement Teams, in conjunction with Agents from the California Department of Alcoholic Beverage Control, conducted a Minor Decoy Operation at multiple bars and restaurants throughout the City of Palm Desert. The Minor Decoy Program allows local law enforcement agencies to use persons under 20 years of age as decoys to purchase alcoholic beverages from licensed premises. During the operation, nine local bars and restaurants were and contacted and three servers were issued misdemeanor citations for violation of 25658(a) Business and Professions Code, Furnishing an Alcoholic Beverage to a Minor.
The Decoy Program has been recognized as an excellent method to attack the problems associated with the unlawful purchase and consumption of alcoholic beverages by people under the age of 21.
In 1994, the California Supreme Court ruled that the use of minor decoys was not entrapment and did not violate due process requirements. Since the Supreme Court ruling hundreds of law enforcement agencies have used the Decoy Program. When used on a regular basis, the percentage of licensees selling to minors drops dramatically.
Under a law passed by the state legislature in 1995, licensees face increased penalties for sales to minors. A first time sale may result in a fine or license suspension. A second sale to a minor within a three year period is an automatic license suspension. A third sale to a minor within a three year period may result in license revocation.
Other News in Palm Desert Station
Driving Under the Influence (DUI) Checkpoint
Assault on a peace Officer with a Firearm, Vehicle Pursuit, Domestic Violence, False Imprisonment
Driving Under the Influence Fatal Traffic Collision
Attempted Murder Suspect Apprehended
Driving Under the Influence Checkpoint
Armed Robbery Suspects Apprehended
Armed Robbery Suspect Apprehended
Know Your Limit Campaign
Winter Enforcement Mobilization


Some items in your iTunes library might be stored in other locations.
Select an item in iTunes and choose File > Get Info. The path to the file is shown at the bottom of the Summary pane (the Where section).
To reveal the file in Windows Explorer, select the song and choose File > Show in Explorer.
For best results, keep a copy of everything in your iTunes library in the iTunes folder.
The iTunes Library file is a database of your library's contents. If you move or delete this file, iTunes creates a new one the next time you open iTunes, but it doesn't contain playlists, song ratings, comments, and other information you created.
What are the iTunes library files?


text:
Glenn District 4 candidates differ on…
Glenn District 4 candidates differ on transportation, library issues
WILLOWS — Voters have a handful of candidates to choose from when it comes time to vote for who will fill the vacancy being left by retiring Glenn County Supervisor Denny Bungarz.
At a recent candidates" forum in Willows, Heather Baker, Jim Bettencourt, James "Jake" Jacobs, Mike Murray and Jim Yoder all answered questions submitted by audience members about a number of issues, including growth, transportation, library funding, jobs and economic development and, at the end, a casino.
One of the issues the candidates differed on is library funding. The libraries have taken cuts from the county budget in recent years. Last fall, the county formed an advisory committee comprised of representatives from the county, cities and libraries to examine funding and other issues.
Bettencourt said he feels library funding affects both cities and the county, but said "If we don"t have funding in the county coffers, it doesn"t matter what we think."
The real issue, he added, is how to bring more money into the county.
"Jobs need to be nurtured and developed," Bettencourt said. "We have to generate money somewhere."
Baker said if half the people using libraries live in the county and half live in the city, it"s reasonable the city and county should share the burden of helping the library.
Yoder said the library is one of the "hot topics," but didn"t lay blame on the supervisors.
"How do we fund it? Where does the money come from?" Yoder asked. "The Board of Supervisors makes hard decisions."
Yoder suggested the answer is to do as the Willows City Council did. The council dedicated city funds when the county money didn"t match up.
"What we need to do is redirect and look at different ways we can fund libraries and sustainable usage by youth and the elderly …" he said.
Murray said he doesn"t think the library of today is the same as the library of yesterday. He said with everything becoming computerized, "I think maybe our libraries should be geared to that more."
However, he said the county should fund the libraries "because it"s their responsibility — they should fund it to the max."
Jacobs said a library is a reservoir of knowledge. He said it"s obvious the library should be funded, and it should be a strong resource.
"Maybe we should do a better job marketing it," Jacobs said. "There are solutions, there are answers. We need to all work together to find that."
Transportation was another issue that brought out some differences when the panel was asked whether bus service is efficient.
Baker said the county needs to be accountable for how things are, and that the first problem is the bus goes to Butte County, "where people can take money from our county." She said there needs to be an audit of transportation.
But Yoder said the Glenn Ride is a viable mode of transportation for the community.
"I believe it is a worthwhile service … we need to make sure it stays viable and grows for the future," he said, adding, "With gas prices rising to nearly $10 a gallon, we"ll probably all be riding the bus."
Murray said he"s probably transportation"s biggest detractor and supporter.
"We made major mistakes when we started," he said. "We didn"t answer the right questions."
Murray also said that to use federal money, the commission has to meet certain federal requirements, such as finding out if transit needs are unmet.
"We can"t spend it on roads," he said. "We have to serve this portion of the population."
Jacobs said transportation was mandated in the 1980s when it was a subsidy for taxi service, and it worked well for a number of years.
But he said it takes money from transportation that would be used for roads.
"It needs to be monitored, with citizen involvement, to be fine-tuned," Jacobs said.
Bettencourt focused on the price of fuel, and the difficulties price increases will cause for those traveling to Butte College. He said buses will become an issue for young people. He would pursue working with college officials to come up with a solution to help develop a bus system for students.
There were other issues — and differences — in the candidates" closing statements.
Bettencourt talked about the decline in agriculture as the leading factor in the county"s economics, and said the unemployment rate is twice the state average.
"The unemployed, underpaid deserve job opportunities," he said. "Without jobs, we"re no more than a welfare county …"
Bettencourt said he wants to bring in private-sector jobs. He said social problems will not go away, but jobs will put money in people"s pockets. He supports the casino.
"Let"s talk about jobs," said Murray. One of his first jobs on a steering committee of the City Council was to bring Johns Manville to Willows. He said he helped create private-sector jobs "with a positive, proactive approach," citing Wal-Mart and Thunderhill Park as other examples.
But Yoder said although the panel talked about immediate issues, one thing it didn"t look at were issues that will affect citizens for decades.
"We should be looking at the long-term effect," Yoder said. "The decisions I make, I look at our children … we are going to graduate 150 seniors … what kind of opportunity do they have to remain in the county?"
Yoder said growth and jobs give opportunities. He mentioned the proposed casino and super Wal-Mart, which will provide jobs that other industries interested in the area are going to look at and say, "They have growth."
Yoder"s mention of the casino brought a response from Heather Baker.
"I was wondering when somebody was going to bring up the elephant in the room," Baker said. "It"s going to require so much research. I"m willing to do that research …"
Baker added that when you look at the need to grow, you also need to look at the effect in the long term, and added the casino is "a relatively new enterprise" that is being looked at as an advantage — for five years.
"We see dips in crime, then a rise," she said.
Baker said growth is imperative.
"Is it growth at any cost, or is it going to hurt us later?" she asked, adding the county shouldn"t "put all our economic eggs in one basket."
It was Jacobs who had the last word.
Jacobs said he likes the pace in Willows and is not anti-growth. But he said industry, a good medical facility, good schools, a quality work force, are all issues the Board of Supervisors might not have a lot of say in.
He said he"s seen the community better, and it can be better again.
"But by and large, I"m not looking to live in Chico," Jacobs said. "Jobs will come if it"s right for them. We need to provide the quality service government provides."
And on the casino, he said he has taken a position — he supports the voters.
"I"m going to wait for the voters to decide," Jacobs said. "I, for one, feel if the people decide the issue, the board will follow their wishes."
Willows Chamber of Commerce and the Elks Lodge sponsored the forum.
Staff writer Barbara Arrigoni can be reached at 896-7757 or barrigoni@chicoer.com.
Five individuals are competing to represent Willows on the Glenn County Board of Supervisors. Current Supervisor Denny Bungarz is retiring. The candidates are: Heather Baker, an interior designer; Jim Yoder, a former policeman turned private investigator who sits on the Willows City Council; Mike Murray, current Willows mayor and chairman of the Local Agency Formation Commission; James "Jake" Jacobs, a longtime sheriff"s deputy and current district fire chief; and Jim Bettencourt, a lifelong resident who battles the county"s substance abuse problem through the program, Not In Our Town.
Tracy police shoot, wound 17-year-old male
Shooters in central California killings of 6 still at large


This is a fashionable Yukata with stream and jag pattern, which is dyed.
A small fabric written in the name is sewed between collar and the center back seam.
Stains are tiny or slight.
It has slight discoloration and prominent stains inside collar.
They will not appear when you wear.
It has minor loose threads on sleeve seam.
It has relatively slight discoloration on the base.
It also has some other imperfections such as tiny stains and patinas.


text:
@implementation CPConfig

NSString *const kCPMinimumRequiredCocoaPodsBinaryVersion = @"0.17.0.rc2";

- (id)init
{
  self = [super init];
  if (self) {
    _launchPath = @"pod";
    _useShell = true;
    _reposDir = [NSHomeDirectory() stringByAppendingPathComponent:@".cocoapods"];
    _minimumSupportedCocoaPodsVersion  = kCPMinimumRequiredCocoaPodsBinaryVersion;
    _sourceAggregate = [[CPSourceAggregate alloc] initWithPath:_reposDir];
  }
  return self;
}

- (CPSource*)masterRepo {
  return [self.sourceAggregate sourceWithName:@"master"];
}

@end

redpajama_set_name: RedPajamaGithub