text:
\section{INTRODUCTION}

Because of its expected simplicity, the distribution and kinematics of
gas in the direction perpendicular to the plane of the disk of the
galaxy should have much to tell us about the forces acting on it and
its state of equilibrium. Considering the most obvious force, gravity,
and recalling that the scale height of molecular gas is much smaller
than that of stars, we expect a Gaussian distribution in z
$\rho(z)=\rho_0 \exp (-z^2/2 \sigma_z^2)$ (Spitzer 1942), if the
velocity dispersion $\sigma_v$ of the gas is constant. The Gaussian
scale height is then $\sigma_z^2=\sigma_v^2/4 \pi G \rho_0$, where
$\rho_0$ is the mid-plane mass density of the disk.

Knowing the scale height and the velocity dispersion in the vertical
direction one can estimate $\rho_0$, the mid-plane mass density of the
disk.  Studies using stellar populations (F dwarfs and K giants) as
test particles to probe the potential give estimates of both the local
disk mass density $\rho_0$ and the integral surface mass density
$\Sigma_0$ (Bahcall et al. 1992, Bahcall 1984a, Bahcall 1984b, Bahcall
1984c, Bienaym\'e et al. 1987, Kuijken \& Gilmore 1989a, Kuijken \&
Gilmore 1989b, Kuijken \& Gilmore 1989c, Kuijken \& Gilmore 1991a,
Kuijken \& Gilmore 1991b, Kuijken 1991).  In a complimentary approach
we can hope to probe the potential at different galactocentric
distances with gas (clouds) since gas emission from the whole disk can
be observed. Since the gas disk is much thinner than the stellar disk,
its vertical distribution probes only the midplane mass density. A
similar study has been carried out for HI by Celnik et. al (1979) and
Merrifield (1992).

The kinematic information about molecular clouds, especially their
velocity dispersion is important for determining their dynamics, with
each other as in collisions (influencing cloud formation/destruction,
star formation); and with the stars, increasing the velocity
dispersions of stars (Spitzer \& Schwarzschild 1951). The variation of
velocity dispersion with Galactic radius may give clues to the sources
of random kinetic energy to the clouds (Gammie et al. 1991),
star/cloud formation as a function of galactic radius etc.

Since the molecular gas forms a cold, thin layer in the disk, it may
be possible to look for signatures of disequilibrium in departures
from Gaussianity of the distribution. These departures may be due to
violent events stirring up the gas (for example supernovae), short
lifetimes of molecular clouds, infalling gas etc. or because of more
than one isothermal population with different values of velocity
dispersion $\sigma_v$.

The large scale distribution of molecular gas has been mapped using
the Massachusetts-Stony Brook galactic plane survey of $^{12}CO$ in
the plane by Sanders et al. 1986, Clemens et al. 1986; and the
Columbia survey by Cohen et al. 1986, Bronfman et al. 1989, Dame et
al. 1987. We use data from the Bell Labs $^{12}CO$ survey (Knapp et
al. 1985), consisting of strip maps in latitude because we need good
latitude coverage and sacrifice close sampling in longitude. The
details of the survey and the data as they relate to the present
analysis are presented in section 2.1.

The scale height of the molecular gas has been previously estimated by
Clemens et al. (1988) to be about 65 pc at $R=0.95 R_0$ and by Sanders
et al. (1984), Bronfman (1988), to be about 60 pc. Different surveys
thus give very consistent values of the scale height.

The same cannot be said for the velocity dispersion $\sigma_v$ of the
clouds.  The values of $\sigma_v$ found by different groups are
inconsistent by a factor of two, if not more. The velocity dispersion
for local (distance from the sun $< 3{\rm\,kpc}$ ) clouds has been estimated
with the additional input of their distances and the Galactic rotation
curve by Stark (1984) and Stark and Brand (1989), to be $7.8
^{+0.6}_{-0.5} \ {\rm\,km\,s^{-1}}$.  Blitz et al. (1984) find $\sigma_v=5.7\pm 1.2
\ {\rm\,km\,s^{-1}}$ for high latitude (hence local) clouds.  Liszt and Burton
(1983) estimate a single value of $\sigma_v=4.2 {\rm\,km\,s^{-1}}$ for the inner
galaxy by measuring the dispersion of what they call `jitter', which
is the difference between the terminal velocity of HI and that of
$^{13}CO$. Clemens (1985) estimates a similar value by fitting a
Gaussian to the tangent point emission. To get rid of emission coming
from galactic radii smaller than the tangent point radius (sub-tangent
point emission) the fit is restricted to $\pm \sigma_z$ since the
emission from nearby gas extends to higher latitudes. The present
paper takes a new approach to modeling the tangent point emission by
fitting simultaneously the terminal velocity, velocity dispersion and
the scale height to the observations. We do not try to isolate the
tangent point emission but take into account emission from the
sub-tangent point gas. The modeling procedure is described in sections
2.2 and 2.3.

We use this model to get the best fit values of the aforementioned
parameters for each longitude observed. As expected the main source of
uncertainty in the parameters is due to the clumpiness of the
molecular gas distribution. To estimate these uncertainties in the
parameters measured, we carry out Monte Carlo simulations of the cloud
distribution in the galaxy, using the known radial distribution of gas
and standard cloud properties. The details of the simulations are
discussed in section 2.5.

In section 3 we present the best fit parameters, and try to interpret
their variation across the inner galaxy. The errors and systematic
shifts in these parameters are estimated from the Monte Carlo
simulations. We also estimate the midplane mass density of the disk.

Section 4 contains a discussion of different values, methods and the
definitions of the parameters characterizing the galactic distribution
as estimated by previous studies; and how consistent various
determinations are, particularly with respect to velocity dispersion
estimates. The assumptions behind this study and various caveats are
also touched upon. The conclusions of this paper are summarized in
section 5.

Appendix A contains contour maps of CO emission as a function of
latitude and velocity, for several different longitudes. Contours of
emission according to the best fitting models are superposed.

The value of the circular velocity at the Sun $\Theta_0$ is taken to
be $220 {\rm\,km\,s^{-1}}$, and the assumed distance to the galactic center  is $8.5
{\rm\,kpc}$.

\section{METHOD}

\subsection{Data}

The observations analyzed here were made using the 7 meter
antenna at Bell Laboratories. The data and details of the
survey and the instruments are presented by Knapp et al. (1985).
Here we summarize the information necessary for the present analysis.

The survey consists of 38 strip maps (in latitude) of
the $^{12}CO(1\rightarrow 0)$ line emission. The maps are sampled at
intervals of $\Delta b= 2 \arcmin$ with a half-power beamwidth
of $100 \arcsec$. The latitude coverage is $\simeq
\pm 2\deg$, varying slightly from one line of sight to another.
The latitude extent is more than adequate for studying the tangent
point emission (except possibly for $ l \geq 60\deg$), extending
more than three scale heights both above and below the centers of
distribution in more than half the lines of sight.

The strip maps were taken at longitudes between $4\deg$ and $90\deg$,
spaced at equal intervals of $\Delta \sin l=0.025$. The velocity
resolution is $0.65 {\rm\,km\,s^{-1}}$. The rms noise is typically 0.3 K but varies
slightly in each latitude strip.  Linear baselines were removed from
individual spectra.  Exceptions to this treatment are few and are
listed by Knapp et al. (1985).

We are able to analyze 22 of the 38 observed lines of sight. The
low longitude ($ 4\deg < l <17\deg$) maps were unusable due to the
lack of emission at (or reasonably near) the expected tangent point
velocities. The high longitude ($l > 61\deg$) maps were unusable
because their tangent point emission is at low velocities and is
contaminated by emission in reference positions; and because the
latitude extent of the maps is not adequate for this (almost) local
emission.

\subsection{Tangent points}

Assuming a circularly symmetric model of the galaxy, we can obtain
distances to the emission at extreme velocities in the first and
fourth quadrants. At each galactic longitude $l$, extreme velocity
emission comes from the tangent point at a galactocentric distance of
$R=R_0 \sin l$ (Figure 1). The tangent points are at a distance $d=R_0
\cos l$ from the sun.  Thus the observed angular extent $b$ gives
 the height $z=R_0 \cos l \tan b$. In the first quadrant the velocity
of the gas at radius R is given by
\begin{eqnarray}
V(R)= \frac{\Theta \sin l}{R/R_0} - \Theta_0 \sin l
\end{eqnarray}
where $\Theta$ is the circular velocity at $R$. At the tangent points
equation (1) reduces to $V_T=\Theta - \Theta_0 \sin l $.

{}From the observed $b$ extent and the terminal (extreme) velocities one
could calculate the scale height and the rotation velocity. The
velocity profiles however do not have a sharp cutoff due to the
velocity dispersion of the gas. Ideally the emission from the tangent
point T(b,v) is a bivariate Gaussian in altitude and velocity; but
emission from nearby radii is not well separated in velocity because of
the velocity dispersion of the gas.

\subsection{The velocity dispersion}

The finite velocity dispersion has two main effects that the present
analysis needs to take into account. First it makes the
velocity-to-distance conversion fuzzy, so it is difficult to separate
emission from $R$ (at the tangent point) and that from
$R^\prime (R^\prime=R+\Delta R)$, where $\Delta R$ depends on the
velocity dispersion. For cold gas (zero velocity dispersion) a
difference in velocity $\Delta V_T=7 {\rm\,km\,s^{-1}}$ would correspond to
$\Delta R \simeq 270/\sin(l) {\rm\,pc}$ near the tangent point. Expecting
velocity dispersions of this size, it is meaningful to calculate
parameters like the scale height, rotation velocity and the velocity
dispersion, averaged over intervals $\Delta R$ of a few hundred
parsecs.

At the same time we must take into account the fact that the emission
at velocity V comes from R, and from the annulus between R and
($R+\Delta R$), so that T(b,v) is no longer a simple bivariate
Gaussian.  Celnik et al.(1979) derived the expression for the expected
line shape near terminal velocity. In this section we calculate the
2-dimensional (in latitude and velocity) profile of emission from near
the tangent point, i.e.  between $R$ and $R+\Delta R$, taking the
scale height, rotation velocity and velocity dispersion to be constant
over $\Delta R $. We expect the additional information in the apparent
latitude-extent as a function of velocity to yield more constraints on
the positions of the emitting regions.

Consider emission seen at velocities close to the terminal velocity;
($\Delta V \ll \Theta$)

\begin{equation}
V(R^{\prime})=V_T-\Delta V=\Theta-\Theta_0 \sin l-\Delta V
\end{equation}
giving
\begin{equation}
 \frac{R ^{\prime}}{R_0}=\frac{\Theta \sin l}{\Theta - \Delta V}
\end{equation}
An observer's line of sight intersects the annulus at radius
$R^{\prime}$ at two points (figure 1). The distances to the points of
intersection, $r_1$ and $r_2$ are given by
\begin{eqnarray}
r_{\scriptstyle 1 \atop \scriptstyle 2}=R_0 \cos l\mp
R^{\prime}\sqrt{1-\frac{\sin^2 l}{(R^{\prime}/R_0)^2}} \nonumber \\ & & \\
\Rightarrow r_{\scriptstyle 1 \atop \scriptstyle 2}
=R_0 \cos l \mp R_0 \sin l \sqrt{\frac{\Theta ^2}{(\Theta -\Delta V)^2}- 1}
\end{eqnarray}

For the same scale height, gas at the subtangent points will have
smaller and larger latitude extent than the tangent point gas,
corresponding to the far and the near part of the annulus at
$R^{\prime}$ $$\sigma_{z \scriptstyle 1 \atop \scriptstyle 2}(V)=\frac
{\cos l}{\cos l\,\mp \,\sin l\sqrt{2 \Delta V/\Theta}} \sigma_z(V_T)$$

Finally we must take into account velocity crowding effects. The
optical depth per velocity interval is determined by the line of sight distance
per unit velocity interval.

\begin{equation}
\frac{dr}{dv}=\frac{R_0 \Theta^2 \sin l}{{(\Theta_0 \sin l+ V(R ^{\prime}))}^3}
{\left ({ \frac{\Theta^2}{(\Theta_0 \sin l+V(R^{\prime}))^2}-1}\right)}^{-1/2}
\end{equation}

Thus the emission in the velocity interval $\Delta V$ (corresponding to
$\Delta R = \Theta_0/R_0 \sin(l)$) near the terminal
velocity, keeping parameters, $\sigma_v$, $\sigma_z$ fixed over the
velocity interval is

\begin{equation}
T(v,z)=A\sum_{1,2}\int{\frac{1}{2 \pi \sigma_V \sigma_z(V)}
\exp{\left(-\frac{(v-V)^2}{2 \sigma_V^2}-\frac{(z-z_0(V))^2}{2 \sigma_z(V)^2}
\right)}\frac{dr}{dV} dV}.
\end{equation}

\subsection{Fitting}

The model profile is calculated (eqn. 7) as a function of latitude $b$
and velocity $V$ for each longitude and a least-squares fit is made to
the data to determine the best fit parameters, namely the amplitude A,
the centroid in the vertical direction $z_0$, the vertical scale
height $\sigma_z$, the terminal velocity $V_T$ and the velocity
dispersion $\sigma_v$.

  The fitting is done by least squares minimization using the downhill
simplex routine, `amoeba' (Press et al. 1993). Contour maps of
emission as a function of latitude b and velocity V and superposed
best-fit models are given in Appendix A (Figure 12) and Figures 2 and
3a .

The velocity range over which the fit is made is determined by the
width of the extreme velocity feature. For each line of sight the
spectra at all latitudes are summed to form a composite spectrum. The
peak at the highest velocity is identified as the terminal velocity
feature. The lower velocity at which the emission drops to
half-maximum is defined as $V_{\rm half}$. We fit the emission seen at
velocities greater than $V_{\rm half}$.

To see how sensitive the parameters obtained are to a change in the
velocity range over which the fitting is done, we do the fitting for
different values of $V_{\rm half}$ for one of the longitudes $l=39$.
Figure 3a shows the various values of $V_{\rm half}$ in
relation to the terminal velocity feature.  The best fit parameters
for each of the fits is plotted against $V_{\rm half}$ in figure 3b. We
see that the parameters are fairly insensitive to the velocity range
over which the model is fit.

\subsection {Error estimation}

The above analysis holds true for a diffuse medium. For molecular
clouds we might interpret $T(b,V)$ as a smoothed probability of
finding molecular clouds at galactic latitude $b$ and velocity
$V$. The molecular gas is distributed as clouds and cloud complexes,
which sample this probability. The main uncertainty in deriving the
parameters of the models is the shot noise due to the small number of
clouds and the clumpiness of the clouds. From figures 2, 3 and 12, it
is clear that the models do not trace the detailed structure of the
gas.

If we ignore the clumpiness of the molecular gas layer and treat the
emission as if it were from a smoothly distributed medium, the
$\chi^2$ per degree of freedom is typically found to be a few
(2-19). The $\chi^2$ per degree of freedom, or reduced $\chi^2$ is
calculated by the relation
\begin{equation}
\chi^2=\frac{1}{N}\Sigma \left( \frac{T(b,V)-T_{model}}{T_{photon}}\right) ^2
\end{equation}
where $T_{photon}$ is the photon noise, and N the number of degrees of
freedom. Since the main source of noise is the clumpiness of the
medium, which is greater than the instrumental noise, we do not expect
the $\chi^2 $ to be 1. On the other hand we use the relation $\chi^2
=1 $ to estimate `realistic' noise `$T_{real}$' of the emission and
then proceed to calculate the confidence intervals on the parameters
using the rescaled noise.

While setting the $\chi^2 =1 $, we have lost information on the
goodness of fit of the models. Also `$T_{real}$' is not necessarily
normally distributed, an assumption made while estimating confidence
levels on the distribution parameters. So we carry out Monte-Carlo
simulations of the cloud population in the galaxy. This also useful
for detecting systematic errors, to the extent that we understand and
can simulate the cloud population.

If we assume the clouds to be ballistic particles, it is the locations
and velocities of the clouds that follow the distribution derived in
the last section. Clearly a large number of optically thin entities
would mimic a smooth distribution. The velocity crowding (dr/dv
$\rightarrow \infty$) at the tangent points somewhat justifies the
assumption that there is a large number of clouds. Velocity intervals
of few ${\rm\,km\,s^{-1}}$ near the terminal velocity correspond to a ${\rm\,kpc}$ or so
of distance $r$ traversed along the line-of-sight. We would expect
$\sim 40$ clouds in the velocity interval of $7 {\rm\,km\,s^{-1}} $ near the
terminal velocity (at longitude $l=35\deg$). As for `transparency',
molecular clouds show optically thick clumps and filaments with a
typical surface filling fraction of $30\%$ (e.g. Bally et
al. 1987). Thus the approximation that we are counting the number of
clouds/clumps, and that little emission from clouds is shadowed, is
perhaps not entirely unjustified.

To test the limitations of this approximation, and to get an estimate
of the confidence levels on the parameters, we simulate the cloud
population in the Galaxy, taking the total mass of the molecular gas
in the galaxy to be $2 \times 10^9 {\,M_\odot}$, and the proportionality
constant $X=\frac{N(H_2)}{I(CO)} {\rm \ to \ be \ } 3 \times 10^{20} cm^{-2}
K^{-1}$.

With the additional input of the size-linewidth-mass distribution,
\begin{equation}
\left(\frac{M}{100 {\,M_\odot}}\right)=\left( \frac{\Delta v}{0.36 {\rm\,km\,s^{-1}}} \right)
^4=\left( \frac {R} {{\rm\,pc}} \right)^2
\end{equation}
and the mass spectrum of the clouds (Solomon \& Rivolo 1989)
\begin{equation}
\frac{dn(M)}{dM} \propto M^{-1.5}
\end{equation}
we can perform Monte-Carlo simulations of the cloud distribution in
the galaxy. The upper and lower cutoffs for the cloud mass are taken to
be $10^6 {\,M_\odot}$ and $10^3 {\,M_\odot}$ respectively. The cloud centers are
distributed in $(R,\theta,z)$. The radial distribution of the gas is
taken from earlier galactic surveys, which closely sample in longitude
(Sanders et al. 1986, Dame et al. 1987). The azimuthal distribution
at a particular radius is taken to be uniform.  In the z-direction the
clouds centers follow a Gaussian distribution with mean $z= 0 {\rm\,pc}$,
and scale height $\sigma_z=50 {\rm\,pc}$. The cloud-cloud velocity
dispersion is taken to be $\sigma_v=7 {\rm\,km\,s^{-1}}$. The clouds themselves are
represented as Gaussians in z and v, with the aforementioned
size-linewidth relationship between $\sigma_z({\rm cloud})$ and
$\sigma_v({\rm cloud})$.

The clouds are then `observed' with a beam of FWHM $100\arcsec$ for 9
longitudes spanning the latitude range of the survey. The simulated
data sets have the same latitude and velocity coverage as the survey
and were modeled in the same fashion. Cloud-cloud shadowing near the
terminal velocity is considerable ($\simeq 7$ for mid-longitudes) and
is handled by scaling down the contribution from the shadowed region
of a cloud by $f=(1-0.3)^{n}$ where n is the number of clouds between
that cloud and the sun. Detailed modeling of the beam shape, cloud
sizes, radiative transfer etc. has not been carried out. A more
complicated model is perhaps not justified in view of the severe
blending of the features at the tangent point.

\section{RESULTS}

\subsection {Results of the simulations}

Examples of contour maps (in b-v) derived from the Monte-Carlo
simulations are shown in Figure 4 for longitudes $l=22.02\deg$,
$l=50.8\deg$ and $l=35.1\deg$ and the best fit models. At l=$35.1
\deg$ the terminal velocity regions are severely crowded with
typically 40 clouds in the region we are trying to fit. The
cloud-cloud shadowing goes up to 7, i.e. we might be looking `through'
up to 7 clouds near the tangent point velocities.

The parameters resulting from fitting the models to the simulations of
9 longitudes are shown in Table II and figure 5. All the longitudes
simulated have identical input distribution parameters, to test for
systematic errors as the velocity crowding changes with longitude. The
parameters measured agree well with the input parameters, with the
exception of the scale height $\sigma_z$, which is measured to be
higher than the input. It is reassuring that the $\chi^2$ per degree
of freedom for the simulated models is found to vary between 6 and 13,
similar to the values for the observations (2-19). The velocity
dispersion $\sigma_v$ has an uncertainty of $\pm 3{\rm\,km\,s^{-1}}$, while the
error bars obtained from leastsquare fitting and scaled up noise
correspond to $\pm 3.5{\rm\,km\,s^{-1}}$. The error-bars for $\sigma_z$ from
Monte-Carlo simulations are larger than the ones from the leastsquare
analysis. There are no systematic trends in the estimates of the
parameters with longitude.

The scale height of the gas is expected to be higher than the scale
height of the cloud centers, since $\sigma_{\rm centers}$ and
$\sigma_{\rm cloud}$ add in quadrature to give the scale height of the
gas. We repeat the simulations with clouds of different sizes at
l=$35.1 \deg$ , and the measured scale height of the gas does go down
with the size of the clouds. The values of $\sigma_z$ however are
still slightly higher than expected if the $\sigma_{\rm centers}$ and
$\sigma_{\rm cloud}$ add in quadrature. This is because of
crowding/shadowing which tends to flatten the
z-distribution. Simulations with no shadowing (i.e. transparent
clouds) and all of the mass in $10^4 {\,M_\odot}$ and $10^3 {\,M_\odot}$ clouds
reproduce the expected scale height of the gas (cf Table III). For the
standard mass-spectrum of the clouds in $10^6
{\,M_\odot}$ to $10^3 {\,M_\odot}$ clouds the contribution to scale height defined
by $\sigma_z^2({\rm cloud})= \sigma_z^2({\rm measured})-\sigma_z^2
({\rm centers})= 56 {\rm\,pc}$. Only one longitude in the Knapp et
al. survey shows a scale height larger than $55 {\rm\,pc}$ (table I), making
it difficult to accommodate the size spectrum used for the simulations.

The scale heights estimated for the Monte-Carlo simulations depend on
other properties like the density profiles of the clouds. Using clouds
with a sharp cutoff in emission at the cloud boundaries as seen in
local clouds ( e.g. Blitz \& Thaddeus 1980), the measured scale height
is lower than estimated for clouds with Gaussian density profiles
(table II). Simulations of emission at l=$35.1 \deg$ were done with
different values of scale height $\sigma_z({\rm centers})= 2, 10, 20,
30 {\rm \ and \ } 40 {\rm\,pc}$, and a size spectrum of $10^3-10^6
{\,M_\odot}$. The contribution of the cloud size to the scale height
$\sigma_z^2({\rm cloud})$ is constant $\simeq 42 \pm 2.7 {\rm\,pc}$ (figure
6). The scale height of molecular gas at the tangent points is
observed to be $ < 40 {\rm\,pc}$ along many lines of sight. If the resulting
scale height of the simulated data sets were not sensitive to cloud
properties we would conclude that this analysis favors small clouds.

Since the molecular gas is clumped, we wish to investigate the effect
of having no gas at the tangent points. It has been shown by Shane \&
Beiger-Smith (1966) that tangent points with little or no gas show a
low, broad-shouldered profile (also see figure 7). For the
distribution of clouds a lower profile may be taken to mean that
statistically there will be fewer clouds at the extreme
velocities. Since we allow the fitting program to choose the velocity
dispersion $\sigma_v$ and the terminal velocity $V_T$, missing tangent
point gas will lead to a lower value of $V_T$ and a higher value of
$\sigma_v$. The other possibility is that the fitting routine will get
confused by the small number of clouds and fit a single cloud giving a
small $\sigma_v$. The scatter in the parameters is found to be fairly
large for the simulations with no gas at the tangent points, as
expected from a smaller number of clouds (figure 8). Thus the very
high ($11 {\rm\,km\,s^{-1}}$) as well as the very low (2 ${\rm\,km\,s^{-1}}$) values of
$\sigma_v$ measured from the data are not believable.

\subsection{Distribution parameters}

So far we have derived the general functional form of T(b,V) and the
shape of the emission contours. We also see that the derived
parameters are robust to small changes in the fitting procedure, and
the derived uncertainties in the parameters are comparable to those
from the simulations. All the data and the best fit models are shown
in Appendix A, figure 12.

Figures 9 and 10, and table 1 show the distribution parameters $V_T,
\sigma_v, \sigma_z, z_0$ for all the longitudes. At low longitudes
(l=$17 \deg, 19 \deg$) $\sigma_v$ and $\sigma_z$ are found to have low
values but with larger error-bars, due to the relatively small amount
of CO at those radii.

The midplane position $z_0$ as derived from the fitting shows a smooth
undulation (figure 10). The scale height increases with radius R; also
the errors in $\sigma_z$ increase, mainly due to the coverage in
latitude translating to a smaller coverage for the nearby gas at
higher longitudes. A linear fit gives a gradient in scale height of
$5.5 {\rm\,pc} {\rm\,kpc}^ {-1}$.

The terminal velocity closely matches the terminal velocity curve for
HI (Gunn et al. 1979), pointing to the similarity of the HI
and CO distribution and kinematics. This also reassures us that the
tangent points are not substantially devoid of molecular gas, since HI
has been shown to be present at tangent points by the absence of
low broad-shouldered profiles (Shane and Beiger-Smith 1966).

The values of the velocity dispersion found for different lines of
sight range from $\sim 2 {\rm\,km\,s^{-1}}$ to $11 {\rm\,km\,s^{-1}}$. There is however a
trend for the $\sigma_v$ to increase at higher longitudes, i.e. with
increase in galactocentric radius. A straight line fit through the
$\sigma_v$ values shows an increase from 3.8 ${\rm\,km\,s^{-1}}$ at 2.5 ${\rm\,kpc}$ to
7.1 ${\rm\,km\,s^{-1}}$ at 7.5 ${\rm\,kpc}$.

\subsection{Midplane mass density of the disk}
Considering the condition for vertical equilibrium of the clouds in
the galactic disk, in the simplest case of a single isothermal
population of clouds, the vertical component of the gravitational force
is balanced by the pressure due to turbulent motions of the gas
$P_z=\rho_z \sigma_v^2$. The thickness of the molecular gas layer
being much less than that of the mass, the vertical component of the
force $ K_z= -4 \pi G \rho_0 z$ ($\rho_0 $ is the midplane mass
density) and the distribution of gas is a Gaussian with scale height
$\sigma_z$.  The midplane mass density of the disk is then given by

\begin{equation}
\rho_0 =\frac {\sigma_v^2}{4 \pi G \sigma_z^2}
\end{equation}

With the additional assumption of isotropy of velocity dispersion of
clouds, we can estimate $\rho_0$ from the scale height and the
velocity dispersion (Knapp 1988).

Figure 11 shows the midplane mass density of the disk computed from
equation 10 and the best fit parameters $\sigma_V$ and $\sigma_z$ for
different longitudes. We fit an exponential disk $\rho=\rho_c
\exp(-R/R_c)$, yielding a scale length $R_c$ = $5  {\rm\,pc}$ and
midplane mass density at the center of the disk $\rho_0(0)=1.1
{\,M_\odot} {\rm\,pc}^{-3}$. From these two values we get the midplane mass
density at sun $\rho_0(R_0) \simeq 0.2 {\,M_\odot} {\rm\,pc}^{-3}$.  The scale
lengths of $3.2 {\rm\,kpc}$ and $10.1 {\rm\,kpc}$ and central densities of
$\rho_0(0)=0.5 {\,M_\odot} {\rm\,pc}^{-3}$ and $0.07 {\,M_\odot} {\rm\,pc}^{-3}$ lie within
$66\%$ confidence limits, leading to an uncertainty of a factor $\sim
2.5$ in the value of $\rho_0(R_0)$.

The simulations however show that the parameters determined have
systematic errors. The scale height of the gas is measured to be
systematically higher than the scale height of the cloud centers. If
we knew the sizes of the molecular clouds reliably we could compensate
for that. Liszt and Burton (1981) favor a smaller (5-10 pc) typical
cloud size by comparing the morphology of the l-v diagrams of
simulations with observed data. If most of the mass of the molecular
is in small clouds the corrections to the scale height are
small. Shadowing of one cloud by another flattens the distribution and
leads to a further overestimate of the scale height. This effect
should be smaller for higher longitudes (less crowding/shadowing); so
we probably are overestimating the scale length $R_c$. Apart from these
effects seen in  the simulations, we may expect the velocity dispersion
measured to have a non-random component from streaming motions as we
are measuring the horizontal velocity dispersion. Further discussion
of this effect is postponed to the next section.

\section{DISCUSSION}
For a consistent analysis of the vertical equilibrium in the disk, we
must measure the scale heights and the velocity dispersion of the {\it
same} population. In the current analysis we do just that for the
molecular gas seen at the tangent points. The tangent point emission is
modeled in two dimensions, so the scale height and the velocity
dispersion are fit simultaneously, along with the other two free
parameters of the model, the rotation velocity and the centroid of the
z-distribution. One might worry about correlated errors in the
determination of the four quantities, for example a lower terminal
velocity estimation may lead to a higher measurement of the velocity
dispersion. While we don't know the real parameters we can estimate
the local dips and peaks in the parameters as compared to the values
smoothed over large radii. The fluctuations in different parameters do
not seem to be correlated (figures 9 and 10). Moreover the best-fit
parameters of the Monte-Carlo simulations, where we do know the actual
(i.e. input) parameters, do not show correlated errors.

We are measuring the scale height and the velocity dispersions for the
tangent point gas. The fact that we are sampling a portion of the
total gas in the inner galaxy may be of concern in that the parameters
may not be very representative. The velocity crowding at the tangent
points means that we are typically looking at $\simeq 1 {\rm\,kpc}$ of path
length. With the present analysis we fit the parameters to intervals
of a few hundred parsecs in Galactic radius, about $1 {\rm\,kpc} $ in the
line of sight distance. The typical number of clouds at tangent points
is 40 (at longitude $l=35 \deg$), so we are not finding the parameters
of just a single cloud unless the tangent point regions are severely
underpopulated.

\subsection {Tangent point analysis}

Since we expect the velocity dispersion to have values of few ${\rm\,km\,s^{-1}}$,
the tangent point emission has to be modeled more carefully than if we
were seeking to derive the rotation curve. Most of the analyses of the
tangent point gas have been done to determine the rotation curve of
the gas (atomic or molecular). In this paper we are concerned more
with the determination of velocity dispersion and the scale height of
the gas. In principle the velocity dispersion and scale height could
be estimated simply by looking at the gas at forbidden velocities,
i.e. $V > V_T$. This is not very practical however for the following
two reasons. The first has to do with the calculation of the terminal
velocity; most estimates involve assumptions about the value of the
velocity dispersion, or at least its constancy (Gunn et al. 1979), or
the size-linewidth relation of the constituent clouds (Clemens 1985,
Liszt et al. 1981).  It would be quite circular then to use such a
rotation curve to calculate velocity dispersions.  One could use the
rotation curve determined from HI data to determine the velocity
dispersions for molecular gas. The disadvantage in doing so is mainly
due to the clumped nature of molecular gas, which means we see only a
few clouds at forbidden velocities. For this reason the velocity
dispersion and scale heights found by this method are very sensitive
to the terminal velocity. Shane and Bieger-Smith (1966) and Burton and
Gordon (1978) subtract the equivalent width of the terminal velocity
feature, which overestimates the velocity dispersion, and
underestimates the terminal velocity. These methods give values of
terminal velocities accurate to a few ${\rm\,km\,s^{-1}}$ - about the value
expected for the velocity dispersion.

\subsection{Velocity dispersion}
Various methods have been used to estimate the velocity dispersion of
molecular gas. These are summarized by Stark \& Brand (1989). The
values of $\sigma_v$ found are also diverse, from 4.2 ${\rm\,km\,s^{-1}}$ to 7.8
${\rm\,km\,s^{-1}}$.  The situation is further complicated by the definition of
velocity dispersion, and its possible confusion with streaming
motions. As a working definition we assume that any motion that
averages out for a distance of $\Delta R=200-400{\rm\,pc}$ does not
contribute to the velocity dispersion. This is achieved by keeping the
parameters (for example rotation velocity $\Theta$) stiff over such
intervals in radius, while fitting the terminal velocity feature
(section 2.3). In treatments where the terminal velocity is allowed to
vary between longitudes quite close to one another ( e.g. figure 3 in
Burton \& Gordon (1978)) smoothing the rotation curve to $\Delta
R=200-400{\rm\,pc}$ and calculating the scatter of $V_T$ around the smoothed
value would be a method equivalent to ours.

Stark (1984) and Stark and Brand (1989) estimate the velocity
dispersion of a population of local clouds, at distances of up to $3
{\rm\,kpc}$ from the sun. They find a velocity dispersion
$\sigma_v=7.8 ^{+0.6}_{-0.5} {\rm\,km\,s^{-1}}$. Given that they do not distinguish
between streaming and random motions, and have an operational
definition similar to ours; their value of $\sigma_v$ found in the
solar neighborhood is consistent with our value.

The $\sigma_v$ determination likely to be most free of the vagaries of
the rotation curve and large scale motions is the velocity dispersion
derived for high latitude clouds by Blitz et. al. (1984) who find
$\sigma_v=5.7 \pm 1.2 {\rm\,km\,s^{-1}}$ for a sample of 28 clouds, after excluding
a `pathological cloud' with velocity $-24.6{\rm\,km\,s^{-1}}$. This is however a
measure of the velocity dispersion (mostly) in the vertical direction
which may be different from the line-of-sight velocity dispersion
estimated in this paper. Note that these are smaller clouds, and if
they have a velocity dispersion greater than the galactic plane GMCs
(Stark 1983) the vertical velocity dispersion value may be still
smaller than the velocity dispersion in the plane.

\subsection {Vertical distribution of the gas}

The vertical distribution of the gas is found in this study is
consistent with previous values. The scale height is found to
increase with radius. A linear fit gives a gradient in scale height of
$5.5 {\rm\,pc} {\rm\,kpc}^ {-1}$, and extrapolates to give a scale height $58
{\rm\,pc}$ at ${\,R_\odot}$.  Similar values are found by Dame and Thaddeus
(1985), Dame et. al.  (1987), Sanders et. al. (1984), Grabelsky
et. al. (1987), and Clemens et. al. (1988). We find from the Monte
Carlo simulations that the (cloud-cloud) scale height is overestimated
if the cloud sizes are comparable to the scale height, and because of
cloud-cloud shadowing at tangent points. The second effect is expected
to be smaller at tangent points seen at higher longitude. This
introduces an error in the gradient of the scale height with
radius. The first effect (cloud size) will lead to an incorrect
constant term in the scale height-radius relation. Extrapolating the
$\sigma_z$ to $R_0$ we may under or overestimate $\sigma_z(R_0)$
depending on which of these effects dominates. Local determinations of
the scale height at $R_0$ for clouds/HII regions (Fich \& Blitz 1984)
give a value of $88 {\rm\,pc}$. The distinction between the distribution of
cloud centers and the scale height of the gas may be best made for
local clouds.

The positions of the CO layer centroid, $z_0$, are also consistent
with the above mentioned studies. The centroid $z_0$ also shows a dip,
going as far as $ \simeq 50 {\rm\,pc}$ (comparable to $\sigma_z$) south of
the midplane. Simulations made with the distribution of gas centered
at z=0 do not show large deviations from z=0 (figure 5, table II).
This feature is not seen in the studies of the vertical distribution
of HI (Celnik et al. 1979). Unfortunately it is difficult to see the
azimuthal structure of this waviness, since we can only look at the
tangent points. At any rate this smooth variation argues against
massively incorrect velocity-to-distance transforms, since that would
disturb the smoothness of such a feature if it was there, and would
require a conspiracy to produce one if it were not.

\subsection {Mid-plane mass density of the disk}

The mid-plane mass density of the disk has been derived making
numerous assumptions. We assume that the molecular gas layer is in
equilibrium, at least on the larger scales. We also assume that there
is a single population of molecular clouds at least with respect to
their velocity dispersions. There may be more than one population of
molecular clouds with different velocity dispersions. The vertical
distribution of molecular gas in that case will not be a single
Gaussian but a sum of more than one Gaussian. One way to test these
assumptions is to see whether the vertical distribution is indeed
Gaussian. We show in a subsequent paper that there exists a population
of small clouds at high z. The tail of the distribution is the
inconsistent with a Gaussian distribution. Similar high tails have
been found for HI (Lockman 1984). Given the `noise' in the data due to
the small number of molecular clouds, we do not think a more
complicated model can be derived.

We also assume that the clouds are independent ballistic particles so
the number of clouds found in any region is a Poissonian
variable. Moreover it is assumed that the distribution of cloud
centers is dictated by the dynamics of the disk alone. In fact the
occurrence of a cloud in a region of space is not a Poissonian event
as the clouds are correlated in space and organized into cloud
complexes.

To examine the vertical equilibrium the value of the {\it vertical}
velocity dispersion should be known, something possible only for local
molecular clouds.  We are {\it always} measuring the {\it azimuthal}
velocity dispersion when we look at the tangent points. The gas being
a dissipational component we expect the velocity dispersion to be
isotropic. The assumption of the isotropy of the velocity dispersion
can be checked by comparing the $\sigma_v$ derived for high latitude
clouds (in part the vertical component), which is $5.7 \pm 1.2 {\rm\,km\,s^{-1}}$
(Blitz et al. 1984), with the value of the azimuthal component
(extrapolated value at the solar neighborhood), which we find to be
$\simeq 7.8 {\rm\,km\,s^{-1}} $. Within the errors this value is consistent with
the velocity dispersion for the high latitude clouds and also with the
expected shape of the velocity ellipsoid.

The values of the radial ($u$), azimuthal ($v$) and the vertical ($w$)
velocity dispersion of (late type) stars in the solar neighborhood are
related as: $u \simeq2w$, $v \simeq \sqrt 2w$ (Mihalas \& Binney
1981). Given the uncertainty in the estimated velocity dispersion we
cannot determine if the velocity ellipsoid of the gas has that shape,
even locally. Support for the isotropy of the velocity dispersions
comes from the shape of the velocity ellipsoid of early type
stars. The O and B stars show fairly isotropic velocity dispersions
(Mihalas \& Binney 1981, p 423);
$\langle{v^2}\rangle/\langle{u^2}\rangle \simeq 1$, although the
vertical component $\langle{w^2}\rangle$ is consistently but slightly
lower. These stars are young enough that they show mainly the
kinematics of the interstellar medium.

We would like to check the mass density profile estimated in this
study against previous measurements; two such check points are the
scale length on the exponential disk (of both  the light and mass
distribution), and the mass density in the solar neighborhood. Using
the values of velocity dispersion and the scale height extrapolated to
solar radius we get a $\rho_0(R_0)=0.34 {\,M_\odot} {\rm\,pc}^{-3}$; extrapolation
of the exponential profile fitted to individual $\rho_0(R)$ gives
$\rho_0(R_0)=0.2 {\,M_\odot} {\rm\,pc}^{-3}$ with a formal uncertainty of a factor
of 2.5. Using the local value of vertical velocity dispersion
$\sigma_v$ (Blitz et al. 1984) gives $\rho_0(R_0)=0.18 {\,M_\odot}
{\rm\,pc}^{-3}$. These results are consistent with the local mass density
determinations from stellar kinematics $\rho_0(R_0)=0.2$ (Bahcall et
al. 1992, Bahcall 1984a, Bahcall 1984b, Bahcall 1984c) and
$\rho_0(R_0)=0.1$ (Bienaym\'e et al. 1987, Kuijken
\& Gilmore 1989a, Kuijken \& Gilmore 1989b, Kuijken \& Gilmore 1989c,
Kuijken \& Gilmore 1991a, Kuijken \& Gilmore 1991b, Kuijken 1991). The
best fit exponential mass distribution gives a scale length $5 {\rm\,kpc} $,
again with an uncertainty of a factor of 2. The scale length of the
light in the galactic disk has been found to be 3.4${\rm\,kpc}$ (de
Vaucouleurs \& Pence 1978) and 5 ${\rm\,kpc}$ (van der Kruit 1987). Both the
scale length and the local $\rho_0(R_0)$ found in the present study
are consistent with the values of $5 {\rm\,kpc}$ and $0.1 {\,M_\odot} {\rm\,pc}^{-3}$
estimated by Merrifield (1992).

The systematic errors in this study as we know them are as
follows. The vertical velocity dispersion may be lower than the
azimuthal velocity dispersion used by a factor of $\sqrt 2$. This
would lower the mass density estimate from the one given here by a
factor of two. The scale height may be overestimated here because of
cloud size and also because of shadowing of clouds by one
another. This could raise the mass density estimate from the one
calculated here by a factor of at least 2.8. Also it may lead to an
overestimate of the scale length of the mass distribution since the
shadowing is lower at high longitudes. Given the systematic and
statistical errors none of the parameters of the mass distribution
mentioned in the last paragraph is favored over the other

\section{CONCLUSIONS}

In this work we have modeled the emission from molecular gas at the
tangent points in the first quadrant of the Galaxy and measured the
terminal velocity, the line of sight velocity dispersion, the scale
height and the deviation from the galactic plane. The modeling takes
into account emission from a large path along the line of sight to the
tangent point. The errors in the parameters are estimated by applying
the modeling technique to simulations of the galactic molecular cloud
population. We find

(1)The terminal velocities are in good agreement with the
terminal velocities from HI data, indicating that there is molecular
gas at most terminal points, and once again pointing to the similarity
of the kinematics of atomic and molecular gas.

(2)The velocity dispersion of the molecular gas increases with radius
between R$=2.5 {\rm\,kpc}$ and $7.5 {\rm\,kpc}$. A straight line fit extrapolates
to give a local value of $7.8 {\rm\,km\,s^{-1}}$.

(3)The scale height also increases with the galactic radius. Again a
linear fit to the scale-height as a function of radius gives a local
value of $57 {\rm\,pc}$.

(4)The centroid of the a dip below the galactic plane with a maximum
excursion of $-51 {\rm\,pc}$ at $R/R_0 = 0.7$.

(5)The simulations of the distribution of molecular clouds with
`standard' properties show morphology similar to the data. Using these
simulations to estimate the errors in the parameters, we see that the
scale height of the gas is measured to be higher than the scale height
of the cloud centers, depending on the size of the clouds. This effect
cannot be corrected for without better knowledge of cloud properties.
The simulations also show that missing gas at the tangent points leads
to an overestimate of the velocity dispersion.

(6)The midplane mass density of the disk shows a decline with the
Galactic radius. An exponential disk model fitted to the data gives a
scale length of $5 {\rm\,kpc}$. The local midplane mass density obtained
from extrapolating this model is $\rho_0(R_0)=0.2 {\,M_\odot}
{\rm\,pc}^{-3}$. Both the scale length and the local mass density estimates
are uncertain to a factor of two at least.

\acknowledgements
It is a pleasure to thank G. R. Knapp for suggesting this problem and
for advice during all stages of this work. We would like to thank
J. Binney, R. Braun, W. B. Burton, C. Gammie and D. Spergel for
helpful discussions and R. H. Lupton for his very flexible graphics
package `SM'. We also thank the refree for comments. This work was
supported by NSF grant AST89-21700 to Princeton University.

\section{Appendix A}
This section shows the latitude-velocity maps of $^{12}CO (J: 1
\rightarrow 0)$ emission at different galactic longitudes from the
survey of Knapp et al. (1985) along with the best fit models for each
line of sight. The latitudes have been converted to the height above
the midplane at tangent points, according to the relation $z=b \ R_0 \
\cos l$, and the y axis is labeled as such. This conversion holds only
for the tangent point emission at extreme positive velocity.

redpajama_set_name: RedPajamaArXiv


text:
WHERE WE'VE BEEN: THE HISTORY OF THE DIOCESE
The Episcopal Church in Hawai'i began in 1862 when King Kamehameha IV and Queen Emma invited the Church of England to Hawai'i. The King and Queen supported the Church's establishment throughout the islands with gifts of land, and by founding the Cathedral of St. Andrew in Honolulu. Queen Emma also founded Queen's Hospital (now Queen's Medical Center) and St. Andrew's Priory School for Girls in Honolulu.
The last Queen of Hawai'i, Queen Lili'uokalani, depended upon the spiritual support of the Episcopal Church during and following the overthrow of her reign in 1893.
The Missionary District of Honolulu originally included the Hawaiian Islands, as well as Guam, Okinawa, Taiwan and Kwajalein. It became the Diocese of Hawai'i in 1969 and now consists solely of the State of Hawai'i.
The Diocese is made up of people who are native to Hawai'i and from everywhere else in the world who worship according to the Book of Common Prayer, 1979. Even though we are Episcopalians, our friends and other members of our families may worship as Roman Catholics, in a variety of Protestant faiths, as well as Buddhists, Shintoists, Mormons, Jews, Hindus and in traditional Hawaiian and other native ways. We hold our cultural and religious variety in respect.
Worship in the Diocese fits the heritage, language and experience of the parishioners. Congregations in the Diocese have formed based on various ethnic groups, such as Hawaiian, Chinese, Filipino, Japanese and Korean. The Eucharist is celebrated regularly in Hawaiian, complete with Hawaiian language hymns. The Diocese celebrates annually, King Kamehameha IV and Queen Emma Day —the Feast of the Holy Sovereigns —on November 28.
GRACE AND BEAUTY: 150 YEARS OF THE EPISCOPAL CHURCH IN HAWAI'I
In 2012, the Episcopal Church in Hawai'i celebrated its sesquicentennial. To mark this special occasion, a documentary about the history of the Church in Hawai'i was produced. Grace and Beauty: 150 Years of the Episcopal Church in Hawai'i is by Emmy Award Winning filmmaker Stephanie Castillo.
Celebrating 150 Years in Hawai'i: Beginning in September 2012, the Diocese of Hawai'i celebrated its sesquicentennial - 150th anniversary - with special events on all of the islands. The "main event" coincided with the Annual Meeting of Convention on November 9-11, 2012, and brought our Presiding Bishop, the Most Rev. Katharine Jefferts Schori to the islands. Also invited were the Diocese's former Bishops as well as dignitaries from our state, the country and the world. To view photos and read more about the Sesquicentennial, click HERE.
CELEBRATING OUR HOLY SOVEREIGNS:
PULAMA 2016 FEAST DAY
During November, churches around the Diocese will be planning special services for the Feast of the Holy Sovereigns, honoring King Kamehameha IV and Queen Emma. The feast day celebrates the King and Queen who brought the Anglican Church to Hawai'i, and left an enduring legacy of community service that continues to lift the human spirit, mind and body. The Rev. Moki Hino and Dixie Kaetsu produced this video entitled Pūlama, paying homage to our King and Queen.
This is a section of the beautiful stained glass window at The Cathedral of St. Andrew in Honolulu. It depicts the arrival of Thomas Nettleship Staley, received by King Kamehameha IV and Queen Emma. Staley was appointed the first Bishop of Hawai'i in 1862.

redpajama_set_name: RedPajamaCommonCrawl


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text:
Movie review: 'Captain Marvel' reaches back to hint at how a certain superhero group began
Mar 6, 2019 at 12:24 PM Mar 6, 2019 at 12:24 PM
There are so many things to address before getting down to a review of this movie - and why I liked it so much - but I've managed to whittle it down to a couple of topics. First, does it pay tribute to the late Stan Lee? You bet! The Marvel Studios logo has been redesigned to be a visual celebration of Lee. Also, Lee's penultimate cameo - there's reportedly one more in "Avengers: Endgame" - happens about 30 minutes in. He's reading a magazine in a subway car. Second, this film is not, as many uninformed moviegoers have thought, an example of a male character being turned into a female character. No male actor has been replaced by a female actor to placate any socio-political movement. Let the record show that Captain Marvel always was a female character, and that, in the world portrayed here, men and women are equals, in every way. End of conversation.
Now, let the review begin!
Three worlds, three planets, are visited in "Captain Marvel." Hala is the home of the valiant Kree civilization, who are in the midst of a war with the malevolent Skrull civilization, who are capable of shapeshifting and will stop at nothing to take over the universe. Then there's Torfa, where members of the elite Kree Starforce, under the command of Yon-Rogg (Jude Law) head to rescue one of their own. Torfa is also where one of Starforce's "noble warrior heroes," Vers (Brie Larson), puts up a great fight, but suddenly vanishes, and finds herself transported to the relatively backward planet C-53.
It's a place that the Kree like to call a sh**hole (yes, the scriptwriters managed to get in a President Donald Trump reference), maybe because of the way people there behave or where they shop. Look! There's a Blockbuster Video! There's a Radio Shack! Oh, right. The Kree put letters and numbers on distant planets. This is Earth, and the year is 1995.
Vers may be a fish out of water here, especially because of her futuristic wardrobe, but there's also a familiarity about the place to her. Has she been here before? That's hard to tell because she's been having difficulty remembering her past, including where she's from, how she got to Hala and, most important, how she ended up with a couple of photon blasters for hands.
Then she starts meeting people, and I think it's both safe and a good idea to reveal that "Captain Marvel" is a prequel to all of the previous Avengers movies. That should make it easier for viewers to understand what's going on with her first encounters, with a much younger Nick Fury (Samuel L. Jackson), who still has two good eyes, and maintains a desk job at Strategic Homeland Intervention, Enforcement and Logistics Division AKA S.H.I.E.L.D., and with Agent Coulson (Clark Gregg), the "new guy" at S.H.I.E.L.D.
As with pretty much every other superhero movie, whether it's from the Marvel universe or the DC universe, there's a whole lot of storytelling going on, with plenty of characters, to boot. Most of the events here take place on C-53 ... sorry, on Earth. But they eventually involve Vers' search for her past, her relationship with her Kree-based Supreme Intelligence figure (Annette Bening), realizing that the name she goes by is actually part of her real name: Carol Danvers, and how she got her astounding powers, which go up a notch in intensity when she starts glowing.
Amid the excellent visual effects, there's also some enjoyable screen chemistry between Larson and Jackson, a terrific and wryly comic performance from Ben Mendelsohn as the Skrull leader Talos, and some purrfect acting by a cat named Goose (sorry, bad pun).
The film carries a big-time anti-war sentiment and a strong message about how different beings - whether they're Kree or Skrull or human - should treat each other. And it has a couple of appearances by the legendary Infinity Stone known as the Tesseract. It features a good ending that screams out for a sequel, and a nicely tied-in second ending in the middle of the credits, followed by the best of the three endings after the credits go to black.
Ed Symkus writes about movies for More Content Now. He can be reached at esymkus@rcn.com
Written by Anna Boden, Ryan Fleck, and Geneva Robertson-Dworet
Directed by Anna Boden and Ryan Fleck
With Brie Larson, Samuel L. Jackson, Ben Mendelsohn, Jude Law, Annette Bening
Rated PG-13
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text:
Riorges est une commune française située dans le département de la Loire en région Auvergne-Rhône-Alpes.

Géographie
Riorges, commune de la Loire, s'étend sur  en bordure ouest de la ville de Roanne.

Elle est limitée :
 au sud, par les communes de Villerest et Ouches ;
 à l'ouest, par Saint-Léger-sur-Roanne et Pouilly-les-Nonains ;
 au nord, par Mably et Saint-Romain-la-Motte.

Son territoire est composé de deux plateaux séparés par une large vallée parcourue par la rivière le Renaison et le ruisseau le Marclet, limité au nord-est par une ancienne zone marécageuse dans laquelle coule le ruisseau Oudan.

Son paysage est un semi bocage ; plus de la moitié de la commune reste encore naturellement agricole.

Géologie
Les plateaux de Riorges sont constitués de terrains sédimentaires (alluvions oligocènes de la deuxième période de l'ère tertiaire) ayant pour origine l'hydrographie qui a précédé celle de la Loire.

D'épaisseur variable, ces couches d'alluvions recouvrent les formations du Stampien moyen et inférieur.

Les « vallées » des cours d'eau sont constituées d'alluvions récentes (matériaux d'atterissements, de sable et de graviers) favorables à l'existence de nappes phréatiques.

Climat
La station météorologique de Météo-France installée sur la commune et mise en service en 1919 permet de connaître en continu l'évolution des indicateurs météorologiques. Le tableau détaillé pour la période 1981-2010 est présenté ci-après.

Hydrographie
Il existe deux bassins versant dont la pente longitudinale est dirigée d'ouest en est vers la Loire.

Le bassin sud du Renaison avec ses affluents : le Marclet et la Goutte Marcellin. Sa crue décennale est de  cubes par seconde. Le débit d'étiage est d'environ  cube par seconde.

Le bassin nord de l'Oudan avec un affluent rive droite le Combray, sa crue décennale est de  cubes par seconde.

Urbanisme

Typologie
Riorges est une commune urbaine, car elle fait partie des communes denses ou de densité intermédiaire, au sens de la grille communale de densité de l'Insee.
Elle appartient à l'unité urbaine de Roanne, une agglomération intra-départementale regroupant  et  en 2017, dont elle est une commune de la banlieue.

Par ailleurs la commune fait partie de l'aire d'attraction de Roanne, dont elle est une commune du pôle principal. Cette aire, qui regroupe , est catégorisée dans les aires de  à moins de .

Occupation des sols

L'occupation des sols de la commune, telle qu'elle ressort de la base de données européenne d'occupation biophysique des sols Corine Land Cover (CLC), est marquée par l'importance des territoires agricoles (52,1 % en 2018), néanmoins en diminution par rapport à 1990 (58,1 %). La répartition détaillée en 2018 est la suivante :
prairies (47,9 %), zones urbanisées (38 %), zones industrielles ou commerciales et réseaux de communication (7,2 %), zones agricoles hétérogènes (2,4 %), espaces verts artificialisés, non agricoles (1,9 %), terres arables (1,8 %), forêts (0,7 %).

L'IGN met par ailleurs à disposition un outil en ligne permettant de comparer l'évolution dans le temps de l'occupation des sols de la commune (ou de territoires à des échelles différentes). Plusieurs époques sont accessibles sous forme de cartes ou photos aériennes : la carte de Cassini (), la carte d'état-major (1820-1866) et la période actuelle (1950 à aujourd'hui).

Histoire

Politique et administration

Tendances politiques et résultats

Liste des maires

Jumelages

Démographie
En , la commune comptait . L'évolution du nombre d'habitants est connue à travers les recensements de la population effectués dans la commune depuis 1793. Une réforme du mode de recensement permet à l'Insee de publier annuellement les populations légales des communes à partir de 2006. Pour Riorges, commune de plus de , le recensement est annuel et la collecte porte sur un échantillon d'adresses tirées au hasard et représentant environ 8 % de la population.

Culture locale et patrimoine

Lieux et monuments

 Château de Beaulieu ;
 Église Saint-Martin ;
 Salle Le Scarabée.

Personnalités liées à la commune
 Charles Devillié (1850-1905), artiste peintre impressionniste, mort à Riorges.
 Joanny Augé (1853-1925), député, conseiller général de la Loire et maire de Roanne, est mort à Riorges.
 Laurent Chabry (1855-1894), médecin et biologiste, mort à Riorges.
 Guy Ribes (1948), artiste peintre et faussaire français, né à Riorges.
 Philippe Vecchi (1964-2017), journaliste, animateur / producteur radio et TV, s'est suicidé dans la maison parentale située à Riorges.
 RTG 2013/2014 : turbotrain exploité par la SNCF parrainé par la ville de Riorges.

Espaces verts et fleurissement
En 2014, la commune de Riorges bénéficie du label « ville fleurie » avec « deux fleurs » attribuées par le Conseil national des villes et villages fleuris de France au concours des villes et villages fleuris.

Héraldique

 Un Lion rampant, symbole des premiers seigneurs de Roanne.
 Armes de l'abbaye bénédictine d'Ainay à Lyon, dont releva le prieuré de Riorges depuis le  jusqu'à la Révolution.
 Armes attribuées à Mathilde d'Anjou. Elles rappellent le souvenir des Dames de Beaulieu, prieuré dépendant de l' Ordre de Fontevraud fondé en 1115 et qui dura jusqu'au début de la Révolution.
 Symbole révolutionnaire français d'après le revers des pièces de 2 sols, frappées en métal de cloches au Moulin de Beaulieu sur les bords du Renaison.

Voir aussi

Bibliographie

Articles connexes
 Liste des communes de la Loire

Liens externes

 Riorges sur le site de l'Institut géographique national
 Site de la mairie

Notes et références

Notes et cartes
 Notes

 Cartes

Références

Commune dans la Loire
Villes et villages fleuris
Unité urbaine de Roanne
Aire urbaine de Roanne

redpajama_set_name: RedPajamaWikipedia


text:
declare class FormidableError extends Error {
    internalCode: number;
    httpCode?: number;
    constructor(message: string, internalCode: number, httpCode?: number);
}

declare const errors: {
    FormidableError: typeof FormidableError;
} & Record<
    | "missingPlugin"
    | "pluginFunction"
    | "aborted"
    | "noParser"
    | "uninitializedParser"
    | "filenameNotString"
    | "maxFieldsSizeExceeded"
    | "maxFieldsExceeded"
    | "smallerThanMinFileSize"
    | "biggerThanMaxFileSize"
    | "noEmptyFiles"
    | "missingContentType"
    | "malformedMultipart"
    | "missingMultipartBoundary"
    | "unknownTransferEncoding",
    number
>;

export = errors;

redpajama_set_name: RedPajamaGithub


Visualising the microbiome: using EMPeror on a mobile device - Duration: 89 seconds.
Moving pictures of the human microbiome - Duration: 37 seconds.
QIIME VirtualBox Install Tutorial - Duration: 4 minutes, 56 seconds.
QIIME EC2 tutorial - Duration: 7 minutes, 48 seconds.


text:
The Iowa Legislature > Legislators > Legislator Print Permanent Link
Representative Pam Jochum View All Years
General Assembly: 82 (01/08/2007 - 01/11/2009) ▼
General Assembly: 88 (01/14/2019 - 01/10/2021)
Compiled Historical Information
Party Affiliation: Democrat
Assemblies Served:
Senate: 83 (2009) - 88 (2019)
House: 75 (1993)
81 (2005) - 82 (2007)
Home County: Dubuque
President Video:
Pam Jochum
Serving eighth term in House.
Instructor at Northeast Iowa Community College.
Graduated from Wahlert High School. Received B.A. in speech communication from Loras College.
Memberships and Activities
Past chairperson, Dubuque County Democratic Party; past organizer for candidates From the School House to the White House; past national delegate, and presidential staff at 1984 Democratic National Convention. Member of Dubuque Coordinated Community Response to Stop Family Violence, National Catholic Basketball Tournament, Dubuque County Association for Retarded Citizens, League of Women Voters, Northend Neighborhood Association, Ark Advocates, Downtown Master Plan, Farmers Union, Iowa Citizen Action Network, CROP Walk, Alzheimer's Memory Walk, Greater DBQ Development Corporation, and IPERS Investment Board.
Birth and Residence
Born in 1954 in Dubuque. Resides in Dubuque.
One daughter.
Text above from Iowa Official Register/Other
Information from State Historical Society of Iowa resources
82nd GA (2007)
Appropriations Subcommittee
Administration and Regulation Appropriations Subcommittee
Former Memberships
State Government (Chair) (01/08/2007 - 11/04/2007)
Justice System Appropriations Subcommittee (01/08/2007 - 11/04/2007)
Public Retirement Systems Committee (03/01/2007 - 01/13/2008)
Legislation Sponsored
Subcommittee Assignments


Q: I built a four-bedroom house in 1998 and lived in the house for 19 years. My house was fully paid off in 2006. I bought a new piece of land and built a house on it in 2017 – the handover for this house was 30 November 2017.
The loan on this house is $750,000, and this loan is a residential investment loan. Can I move this loan to my paid-off house, and can I change my residential investment loan into a home loan?
My paid-off house is currently being rented out, and as there is no interest to deduct it against, I have to pay tax on the income.
A: Thanks for your question, Anurka – it is one we get regularly. The short answer is no; you cannot just move debt that was used for your new PPOR (principal place of residence) to your old PPOR when you decide to rent it out.
Property 1: Owned 100% by Jane Brown and valued at $1,000,000. It was purchased in July 2000, is fully paid off and has been Jane's PPOR for the entire period of ownership. Jane met and married John Smith in January 2005.
It is extremely important to note that the main purpose of this arrangement cannot be to obtain a tax benefit, otherwise you risk getting into trouble with the Tax Office under Part IVA of the Income Tax Assessment Act (the anti-avoidance rule for income tax). You would therefore need specific advice for your circumstances.
• You need to keep capital gains tax (CGT) in mind. In the above scenario, there was no CGT, but you will need to seek advice to ensure that there will not be any CGT on the sale.
• In this example, stamp duty would be applicable in at least some states of Australia, so you would need to weigh up the cost of stamp duty versus the benefit.
"There are limited circumstances in which you might be able to 'sell' part or all of the property to a family member"
- Debt cannot be transferred between different properties.
- In some circumstances, a property can be sold in parts to reallocate debt.
- You need to check whether CGT and stamp duty are applicable.


underground loaders. We are the manufacturer of coal mining machine,roadheader,coal loader,tunnel mucking loader,backfilling machine,concerte pumping machine and so on. underground loaders manufacturer, supplier.
Elon Musk's new video of his underground tunnel project will ... May 11, ... We manufacture roadheader tunneling equipment for mining and construction.
Roadheader for tunneling. ... for rehabilitation of existing tunnels, and excavation of underground ... tunneling equipment for mining and construction.
Alibaba.com offers 64 underground roadheader products. About 34% of these are mine drilling rig, 34% are mining machinery parts. A wide variety of underground roadheader options are available to you, such as core drilling rig, rotary drilling rig.
EQUIPMENT . ASSEMBLY POINT . EMERGENCY EXIT . ... Underground Surface Sandvik supply Customer supply ... ROADHEADER IN TUNNELING. S.


I was able to build a Vuforia 3d object recognition software for UWP to run on windows 10 and I have to say the tracking is alot better than openCV. Two things I noticed were that when the app was built and run once an object was recognized the camera feed would stop but the AR object would still move according to the location of the object marker. This does not happen in play mode in Unity. The second and more important issue for my use is that the app would stop tracking if another window went into focus like chrome browser. Is it possible to keep the app running at tracking even when the focus has changed to another window? Thanks in advance.


text:
Eastwood Rounds Out The Cast Of "American Sniper"
By TBA on	 March 21, 2014 2 - FILM NEWS, Attachments (Film)
by: Sammy Mink
Four stars have been recruited for Clint Eastwood's AMERICAN SNIPER, "Homeland's" Navid Negahban, "Nashville's" Eric Close, Rey Gallegos from "Gang Related" and Eric Ladin from "Boardwalk Empire."
Based on the book "American Sniper: The Autobiography of the Most Lethal Sniper in US Military History" by Chris Kyle, Scott McEwen and Jim DeFelice, it's the true story of Kyle who holds the military record for most confirmed sniper kills at 150.
Negahban will play a local Iraqi who wants to help the SEALs find their target, Gallegos has been cast as Tony, the head of the SEAL team and Ladin will play a Californian surfer-turned-SEAL. There's no word yet on who Close's character might be. The foursome join Bradley Cooper who will star as marksman Chris Kyle and Sienna Miller who plays his wife.
Close is repped by Gersh and Untitled Entertainment, Ladin is set up at Innovative Artists and Main Title Entertainment, Rey is at GVA and Jeff Goldberg Management, Negahban is with House of Representatives.
— VIEW THE UPDATED SALES LISTING —


text:
Who is Chubbyemu? Wiki Biography, age, real name, girlfriend, net worth
Naked Science 2010
as Thanks
1 Early life, family
3.1 Medical career
3.2 YouTube career
4 Fat loss story
6 Hobbies and interesting facts
7 Social media presence
8 Appearance
11.1 Thanks
Chubbyemu is a popular YouTuber, who uploads many videos on medical topics since he is a doctor in real life. He started his channel on YouTube with "Let's play" videos, but then switched to medical themes and achieved great success. Let's find out more about his real name, age, girlfriend and net worth.
I grew up with the saying "Hide your strength. Bide your time." from my parents. Sometimes it might appear to you there is no strength to hide at all. That you are getting kicked while down. But maybe those are the times you are building yourself for that very moment sometime soon, where you can speak loudly, and the entire world will listen ? . . . #friday #selfie #a7sii #a7rii #portrait #mood #motivation #strength #time #speak #sonyimages #photography #chubbyemu #quotes #quotestoliveby #instaportrait #portraitphotography #portraiture #selfportrait #quoteoftheday #quotesaboutlife
A post shared by Chubbyemu (@chubbyemus) on Mar 2, 2018 at 2:02pm PST
Early life, family
Bernard "Chubbyemu" was born under the sign of Virgo on 14 September 1984, in the United States – his real surname is unknown for the moment. He now resides in Philadelphia, Pennsylvania. His parents came from Taiwan to the US in 1975 with only $300 in their pockets – his mother was the youngest daughter in the family, and according to old Tai traditions, she wasn't supposed to get any inheritance from her family. Bernard's father was the oldest son in his family, but his relatives were strongly against him leaving Taiwan, so they told him they were not going to support him or give him anything if he left. So when they arrived in the US, they had to sleep at Bernard's uncle's couch, while his father was getting a degree in nuclear engineering, and his mother worked in a bank. Bernard said that this taught him and his sibling sister to clench their teeth and to go your way to your dream life, for which he felt very grateful, and used this pattern in his future life, overcoming many difficulties in his own way. Bernard once mentioned in one of his Instagram posts that no one in his life who he had taken seriously, had ever told him he couldn't do something. He always felt much support from his family and close friends, so it took him to little time to recover from a failure, or from an uncomfortable situation.
Bernard matriculated from his local high school in 2002. In the last two years of school he worked at three jobs for more than 80 hours a week, and felt exhausted, and could have quit one of them since he had enough money, but giving up was not his thing – so he held all three positions, studying at school at the same time. Later he entered the University of Illinois, and graduated in 2006, eventually getting his Ph.D. and becoming a Clinical Adjunct Professor.
Chubbyemu
Medical career
After graduating from the University of Illinois, Bernard started working in the field of medicine, having been an intern in a pharmaceutical company in Chicago. Then he turned his career path to the sphere of toxicology, and it helped him to face the most awkward situations, when people got into trouble by drinking poisonous liquids: in such cases Bernard could see with his own eyes what happens with their internal organs, and it helped him considerably in his future YouTube career. Later he switched his attention to the sphere of oncology and began working in that field, and where his main specialization is now, which means his work is connected with the results of experimental and clinical research in hematology and oncology, working hand in hand with experimental therapeutics in chemotherapy and immunotherapy.
His YouTube channel called "Chubbyemu" was created on 25 September 2015. Bernard said that he created it to have something that he could call his own, to leave traces after him. His subscribers increased very slowly, such that he even wanted to delete his channel, and didn't upload any videos for a whole month in December 2016 while deciding on a new approach. Quitting YouTube was not acceptable to him, so he decided to switch from video games videos to popular medicine topics. Bernard is now famous for his breaking down the medical terminology in his videos and explaining the Latin or other linguistic roots of a word, explaining the names of diagnosis and other interesting medical terminology. In 2019 his channel has around 300 videos which in general have attracted more than 81 million views, many of which now tell the stories of people who faced awkward situations and needed medical help. His new videos such as "A Dad Mistakenly Drank A Lava Lamp At Bedtime. This Is What Happened To His Kidneys" and "A Toddler Chewed Lead Paint Off His Toys. This Is What Happened To His Brain" have over two million views in just a couple of months.
Fat loss story
There was a period in Bernard's life when he decided he had to lose some weight as it was more than 220lbs (99kgs), admitting that he often felt he was about to give up. Though he had a special plan for weight loss and had several specialists who worked with him he didn't feel strong enough to accomplish his goal. He felt hungry all day long when he was on his caloric deficit, every meal was not enough for him to feel full, and he had a lot of cardio sessions, which were quite exhausting, up to 11 a week. His coach Shelby Starnes helped him a lot and guided him through his weight loss way. Bernard shared that he needed the help of experts because he strongly believed that watching a couple of videos on YouTube didn't make you an expert in anything, so he doesn't advise anyone to use tips and advice from YouTube which relate to one's health or treatment. At the end of his journey, he weighed around 163lbs (73kgs) and felt much better since he wasn't on his caloric deficit anymore. He shared his way on his YouTube channel, making a lot of Q&A videos and update videos.
Bernard once shared that social life was not so important for him since he enjoyed his jobs and the things he did alone. He says that all his friends are 20+ years older than him, they all have families and kids and he was lucky if they had an opportunity to meet at a dinner once a month. He's never mentioned that he has a girlfriend or wife, saying many times that his professional work and YouTube take all his time. He doesn't have any kids.
Hobbies and interesting facts
According to his own words, Bernard's biggest hobby is playing video games., which he started in 2004 when such games as "Half Life 2", "Halo 2" and "World of Warcraft: Cataclysm" were launched. Recently he has been playing such games as "Overwatch" and "The Last Guardian". He does some bodybuilding with his coach Shelby Starnes when he is in his program of losing or gaining weight. Bernard also mentioned he loved travelling and taking pictures, and would like to spend more time doing it, but doesn't have that spare time.
Bernard is quite active on various social media platforms. Besides his main social media account on YouTube which has more than 1.1 million subscribers, he also has an Instagram account on which he mostly shares selfies with some thoughtful and motivational messages and new video announces; the profile is followed by 3,600 people. He also has a Twitter account which is read by more than 6,500 followers, and his Facebook page is followed by around 2,000 people.
Chinese video sharing sites have this feature where comments can scroll at the top as the video plays. For my videos, without even seeing this picture, you can take a wild guess where that goes. And here it is. pic.twitter.com/AIPbWF1rWl
— Chubbyemu (@chubbyemu) December 6, 2018
Bernard has short dark-brown hair and brown eyes. He is around 5ft 4ins (1.65m) tall and now weighs around 163lbs (73kgs) since going through his weight loss program. As for his clothing style, he prefers classical looks and often wears shirts, trousers and blazers.
When u wear a suit to Walmart but can only afford the $0.84 generic brand soda ?
Posted by Chubbyemu on Saturday, April 22, 2017
According to authoritative sources, Bernard has managed to accumulate a net worth estimated to be around $350,000, from his YouTube channel which brings him around $6,500 per month, and from his professional medical activities, working full-time at the hospital. Bernard was highly motivated by achieving the milestone of one million subscribers on his YouTube channel, so he is most likely to continue uploading videos, which means his net worth is only going to grow in future.
Facebook https://www.facebook.com/chubbyemu/
Twitter https://twitter.com/chubbyemu?lang=en
Instagram https://www.instagram.com/chubbyemus/?hl=en
Naked Science 2010 TV Series documentary special thanks - 1 episode
Naked Science 2010 TV Series documentary Himself - Chief Scientist
Who is Kyle Richards' ex-husband Guraish Aldjufrie? His Wiki: Net Worth, Daughter Farrah Aldjufrie, Divorce, Affair, Nationality
Gnisselb 3 years ago Reply
Bernard is 6 feet tall… he has said it several time in his videos…
Kat Shedunkins 3 years ago Reply
He references an old girlfriend in his weight loss video.
Kimber Alexander 3 years ago Reply
His surname is Hsu.
Phil 2 years ago Reply
Bernard is helping people not kill themselves by over consumption.
There is a fallacy in the human experience that if a little is good ,more is better and a huge amount more is fantastic.
The real world is defined by balance.
Once human beings consume anything out of balance with what their bodies can stand ,they will damage it .
His video on the man who mass consumed vitamin c gummies and zinc is outstanding.
ALWAYS HEED THE CONSUMPTION WARNINGS ON ALL PRODUCTS YOU CONSUME.
Others have paid HUGE negative health prices that caused those warnings to be put there.
There are no shortcuts to maintaining good health.
Handfuls of vitamins won't get you there.
Good health requires you WORK AT IT EVERYDAY.
kind of sucks but that's the truth.
Many thanks to Bernard for putting out simple entertaining truthful videos to help people he will never know.
He's making a positive difference in the world everyday.
JD 1 year ago Reply
yup .. i agree. bernard has taught me alot of medical stuff that i never thought i would know and understand. to me he seems like a good doctor and a good man in general. thank you bernard
The Untold Truth About NCT Member – Jaehyun
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text:
The NM Political Report (https://nmpoliticalreport.com/2016/12/28/2016-top-stories-2-state-budget-situation-worsens/)
2016 Top Stories
2016 Top Stories #2: State budget situation worsens
By Matthew Reichbach | December 28, 2016
The state budget situation was the backdrop of so many other stories this year and will remain a large story that NM Political Report and others will continue to cover in 2017 and beyond.
Due in large part to the state's reliance on oil and gas revenues to fund the government, New Mexico earlier this year found itself facing a large budget deficit amid plummeting oil prices. The state constitution does not allow the state to run a deficit; every year, the Legislature must pass a balanced budget.
Previously: Top ten stories of 2016: 10-6; #5: NM Dems buck national trend, retake House; #4: Demesia Padilla resigns; #3: AG clears final behavioral health providers
During the 30-day regular session, the state House passed a version of the budget worth $6.32 billion, which actually included $30 million in new money. But by the time the Senate began discussing the budget, the situation worsened and the state braced for a whopping $359 million less in revenue than projected.
The Senate eventually passed a pared-down $6.2 billion budget bill. And this came hand-in-hand with "sweeps" of the state reserves and other one-time funds to cover state expenses.
But that wasn't the end of the story.
In Red River this August, legislators were told of a projected budget deficit of more than $450 million across two budget years.
Legislators called for a special session, which Gov. Susana Martinez said she wanted to be a short session. Martinez said she hoped that legislators would come into the session with a deal already in place to avoid wasting time and money.
Then, she put multiple crime bills to increase penalties on the call as part of the special session, injecting even more drama into the fraught process (the special session itself ranked number 6 on our list of top stories of 2016).
All this came just weeks before Election Day, with every district in both chambers up for election.
The Senate came into the special session, passed their own bills aimed at balancing the budget and went home. They weren't even in the Roundhouse for 24 hours.
The House, on the other hand, spent days debating crime bills and eventually finished the session by passing their altered versions of the Senate's budget bills. The Senate concurred, sending the budget bills to Martinez's desk.
Martinez signed the bills (but rescued $22 million in cuts for priorities of her education secretary).
As for the future, Legislators cannot use state reserves to use as a band-aid for the budget's red ink because they are depleted.
The state aims for reserves to be equal to 10 percent of state spending to account for fluctuations in the oil and gas industry. Instead, reserves are currently in negative territory.
Legislators will gather in January for a 60-day regular session and face a budget situation that could be worse than 2016.
2016 state budget
Latest projections for state budget: $1.1 billion in 'new money'
Analysts told lawmakers projections show New Mexico will have $1.1 billion in "new money" to spend compared to last year. But they also urged caution on how to spend that money, given the state's reliance on volatile oil and gas revenues and the need to replace the money legislators used money from various state programs in recent years.
Projection says $1.17 billion in new money, but analysts urge caution
View all State Budget articles →
Martinez signs bill slashing budget, but saves PED secretary priorities
Gov. Susana Martinez signed a bill passed during the recently-completed legislative special session that cut spending in most state agencies, but used her line-item veto authority to spare "below-the-line" funding for the Public Education Department. The bill was part of the effort to solve a budget problem that is estimated to leave the state hundreds of millions of dollars in the hole.
Official grilled over department's failure to collect $193 million in taxes
Courts announce budget reductions, say further would have big consequences
View all 2016 state budget articles →
2016 Top Stories #1: SNAP fraud scandal at HSD
In April, five employees of the state agency that processes key federal benefits to the poor made explosive testimonies in court—that their bosses instructed them to doctor emergency food aid applications to hurt the very people they're supposed to help. The following month, four more Human Services Department employees added their voices to the allegations.
2016 Top Stories #3: AG clears final behavioral health providers
2016 Top Stories #4: Demesia Padilla resigns
View all 2016 Top Stories articles →
State looks to diversify economy, rely on 'volatile' oil and gas revenue less
This week, Intel announced it would hire 300 more employees. Those new hires would bring the number of employees at its massive Rio Rancho plant to around 1,500, well below the peak of nearly 7,000 employees, decades ago.
Senate, House reach deal on $7 billion state budget
Senate panel pares back proposed tax increases


For guitarists short on picks but long on expired credit cards, listen up–for the less musically inclined, listen up too because this is still pretty cool.
Agency Loducca Brazil has created a poster that converts plastic cards you were probably just going to toss or shred into new guitar picks. The MTV Green Picks Recycle Machine has been installed in bars, nightclubs, and various spots across São Paulo, and from the looks on those hip young faces in the spot below, upcycling plastic into picks has never been more in.


text:
Theoretical stability of the polarization in a thin semiconducting ferroelectric
Yukio Watanabe
The size effect in ferroelectrics is examined by considering the semiconductivity of the ferroelectric. This approach is applied to a theoretical investigation of the stability of the spontaneous polarization in a ferroelectric film on a semiconductor using a homogeneous Ginzburg-Landau theory. The band structure in the ferroelectric/insulator/semiconductor is rigorously incorporated in the theory, as if for a conventional semiconductor heterostructure such as GaAs/(Ga, Al)As. The carriers generated in the ferroelectric are found to change drastically the stability of the spontaneous polarization and its size effect. Numerical and simple analytical results are presented for (Formula presented) and, mostly, for (Formula presented) The spontaneous polarization in a single-domain ferroelectric on a semiconductor is shown to be bistable and induce a semiconductor space charge (Formula presented) The value of (Formula presented) is a tiny fraction of the spontaneous polarization and agrees with experimentally estimated values. Namely, the experimental quasiequilibrium (Formula presented) values are mostly intrinsically limited by the heteroband structure, not by the technological difficulties. Moreover, the (Formula presented) value for a finite insulator thickness was found to be mainly determined by the insulator thickness and the semiconductor properties of the ferroelectric, and was relatively insensitive to the ordinary ferroelectric properties and the trap densities at the interface. The theory forecasts possible limitations of the transistors using this structure. Nonetheless, a long retention of the semiconductor space-charge (Formula presented) by a very thin ferroelectric can be realized by the advancement of the technology. Additionally, the stability of very thin ferroelectrics on semi-insulating substrates and the switching of ferroelectrics on parent materials of the high-(Formula presented) superconductors are successfully explained.
https://doi.org/10.1103/PhysRevB.57.789
10.1103/PhysRevB.57.789
「Theoretical stability of the polarization in a thin semiconducting ferroelectric」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。
Ferroelectricity Chemistry 100%
Ferroelectric Material Material Science 90%
Semiconductor Chemistry 60%
Semiconductor Material Material Science 60%
Polarization Chemistry 50%
Value Physics 40%
Stability Physics 40%
Nonconductor Chemistry 30%
Watanabe, Y. (1998). Theoretical stability of the polarization in a thin semiconducting ferroelectric. Physical Review B - Condensed Matter and Materials Physics, 57(2), 789-804. https://doi.org/10.1103/PhysRevB.57.789
Theoretical stability of the polarization in a thin semiconducting ferroelectric. / Watanabe, Yukio.
In: Physical Review B - Condensed Matter and Materials Physics, Vol. 57, No. 2, 1998, p. 789-804.
Watanabe, Y 1998, 'Theoretical stability of the polarization in a thin semiconducting ferroelectric', Physical Review B - Condensed Matter and Materials Physics, vol. 57, no. 2, pp. 789-804. https://doi.org/10.1103/PhysRevB.57.789
Watanabe Y. Theoretical stability of the polarization in a thin semiconducting ferroelectric. Physical Review B - Condensed Matter and Materials Physics. 1998;57(2):789-804. doi: 10.1103/PhysRevB.57.789
Watanabe, Yukio. / Theoretical stability of the polarization in a thin semiconducting ferroelectric. In: Physical Review B - Condensed Matter and Materials Physics. 1998 ; Vol. 57, No. 2. pp. 789-804.
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title = "Theoretical stability of the polarization in a thin semiconducting ferroelectric",
abstract = "The size effect in ferroelectrics is examined by considering the semiconductivity of the ferroelectric. This approach is applied to a theoretical investigation of the stability of the spontaneous polarization in a ferroelectric film on a semiconductor using a homogeneous Ginzburg-Landau theory. The band structure in the ferroelectric/insulator/semiconductor is rigorously incorporated in the theory, as if for a conventional semiconductor heterostructure such as GaAs/(Ga, Al)As. The carriers generated in the ferroelectric are found to change drastically the stability of the spontaneous polarization and its size effect. Numerical and simple analytical results are presented for (Formula presented) and, mostly, for (Formula presented) The spontaneous polarization in a single-domain ferroelectric on a semiconductor is shown to be bistable and induce a semiconductor space charge (Formula presented) The value of (Formula presented) is a tiny fraction of the spontaneous polarization and agrees with experimentally estimated values. Namely, the experimental quasiequilibrium (Formula presented) values are mostly intrinsically limited by the heteroband structure, not by the technological difficulties. Moreover, the (Formula presented) value for a finite insulator thickness was found to be mainly determined by the insulator thickness and the semiconductor properties of the ferroelectric, and was relatively insensitive to the ordinary ferroelectric properties and the trap densities at the interface. The theory forecasts possible limitations of the transistors using this structure. Nonetheless, a long retention of the semiconductor space-charge (Formula presented) by a very thin ferroelectric can be realized by the advancement of the technology. Additionally, the stability of very thin ferroelectrics on semi-insulating substrates and the switching of ferroelectrics on parent materials of the high-(Formula presented) superconductors are successfully explained.",
author = "Yukio Watanabe",
doi = "10.1103/PhysRevB.57.789",
journal = "Physical Review B - Condensed Matter and Materials Physics",
publisher = "American Physical Society",
T1 - Theoretical stability of the polarization in a thin semiconducting ferroelectric
AU - Watanabe, Yukio
N2 - The size effect in ferroelectrics is examined by considering the semiconductivity of the ferroelectric. This approach is applied to a theoretical investigation of the stability of the spontaneous polarization in a ferroelectric film on a semiconductor using a homogeneous Ginzburg-Landau theory. The band structure in the ferroelectric/insulator/semiconductor is rigorously incorporated in the theory, as if for a conventional semiconductor heterostructure such as GaAs/(Ga, Al)As. The carriers generated in the ferroelectric are found to change drastically the stability of the spontaneous polarization and its size effect. Numerical and simple analytical results are presented for (Formula presented) and, mostly, for (Formula presented) The spontaneous polarization in a single-domain ferroelectric on a semiconductor is shown to be bistable and induce a semiconductor space charge (Formula presented) The value of (Formula presented) is a tiny fraction of the spontaneous polarization and agrees with experimentally estimated values. Namely, the experimental quasiequilibrium (Formula presented) values are mostly intrinsically limited by the heteroband structure, not by the technological difficulties. Moreover, the (Formula presented) value for a finite insulator thickness was found to be mainly determined by the insulator thickness and the semiconductor properties of the ferroelectric, and was relatively insensitive to the ordinary ferroelectric properties and the trap densities at the interface. The theory forecasts possible limitations of the transistors using this structure. Nonetheless, a long retention of the semiconductor space-charge (Formula presented) by a very thin ferroelectric can be realized by the advancement of the technology. Additionally, the stability of very thin ferroelectrics on semi-insulating substrates and the switching of ferroelectrics on parent materials of the high-(Formula presented) superconductors are successfully explained.
AB - The size effect in ferroelectrics is examined by considering the semiconductivity of the ferroelectric. This approach is applied to a theoretical investigation of the stability of the spontaneous polarization in a ferroelectric film on a semiconductor using a homogeneous Ginzburg-Landau theory. The band structure in the ferroelectric/insulator/semiconductor is rigorously incorporated in the theory, as if for a conventional semiconductor heterostructure such as GaAs/(Ga, Al)As. The carriers generated in the ferroelectric are found to change drastically the stability of the spontaneous polarization and its size effect. Numerical and simple analytical results are presented for (Formula presented) and, mostly, for (Formula presented) The spontaneous polarization in a single-domain ferroelectric on a semiconductor is shown to be bistable and induce a semiconductor space charge (Formula presented) The value of (Formula presented) is a tiny fraction of the spontaneous polarization and agrees with experimentally estimated values. Namely, the experimental quasiequilibrium (Formula presented) values are mostly intrinsically limited by the heteroband structure, not by the technological difficulties. Moreover, the (Formula presented) value for a finite insulator thickness was found to be mainly determined by the insulator thickness and the semiconductor properties of the ferroelectric, and was relatively insensitive to the ordinary ferroelectric properties and the trap densities at the interface. The theory forecasts possible limitations of the transistors using this structure. Nonetheless, a long retention of the semiconductor space-charge (Formula presented) by a very thin ferroelectric can be realized by the advancement of the technology. Additionally, the stability of very thin ferroelectrics on semi-insulating substrates and the switching of ferroelectrics on parent materials of the high-(Formula presented) superconductors are successfully explained.
U2 - 10.1103/PhysRevB.57.789
DO - 10.1103/PhysRevB.57.789
JO - Physical Review B - Condensed Matter and Materials Physics
JF - Physical Review B - Condensed Matter and Materials Physics