text:
Persado Selects Cloudera to Train Its Engineering and Analytics Teams for Big Data Success
Custom-Tailored Professional Training Program From Cloudera University Addresses Big Data Skills Gap to Give Global Marketing Engineering Firm a Competitive Edge
PALO ALTO, CA--(Marketwired - Oct 2, 2013) - Cloudera, the leader in enterprise analytic data management powered by Apache Hadoop™, today announced that Persado, the global leader in Marketing Language Engineering, selected Cloudera University as its training vendor of choice to educate its technical teams on Hadoop and other advanced data analytics and management technologies. Leveraging the unparalleled expertise of Cloudera's education team, Persado engineers and data analysts successfully completed an intensive weeklong training and certification program on Apache Hadoop, Apache Hive, Apache Pig and Cloudera Impala. Cloudera customized a curriculum to give the Persado team the necessary tools and skills to support its marketing language engineering platform at scale and deliver quantifiably improved marketing campaigns on behalf of its rapidly growing global customer base.
Knowledge Is Power: Overcoming Internal Skills Gap Is the First Step to Hadoop Success
Business data holds limitless opportunities for increased insight into both consumer behavior and proclivities, which in turn promotes better brand engagement and increased conversions. No one knows this better than Persado, the pioneer and global leader in marketing language engineering. Persado ensures brands are delivering the most effective marketing message to their target audience at every digital interaction by utilizing a systematic methodology that employs math, computational linguistics and big data to provide brands with the absolute best click-through, response and conversion rates possible. Persado enables these brands to truly understand why their customers click, respond and buy.
To assure the highest quality experience for both clients and their end users, Persado's engineering team collaborates with renowned statisticians and data analysts to develop innovative ways of generating the precise marketing content that will deliver the highest engagement across any digital encounter.
Given the challenge of supporting ongoing data collection and querying at scale, Persado's data warehouse plays a critical role in its marketing language engineering value chain, assuring a steady and unobstructed multidirectional flow of information. Persado's data warehouse team ensures its infrastructure can support its data scientists' needs, delivering easy access to information and significantly less time to insight.
In 2010, the company made a strategic decision to migrate its legacy relational database management system (RDBMS) to a more flexible, scalable and cost-effective Big Data capable environment. As its analytics and reporting needs continued to become increasingly complex and time sensitive, Persado also needed to find a way to efficiently collect, aggregate and process its data from disparate sources like MongoDB, MySQL config servers and Apache logs. With its powerful data processing and analytics capabilities, Hadoop quickly emerged as the clear choice to quickly and efficiently extend Persado's existing data infrastructure.
As the deployment matured and Persado's analytics and reporting requirements became increasingly sophisticated, they looked to move the 'center of gravity' in their datacenter towards Hadoop, however, there were too few Big Data engineers on staff to sufficiently grow its capabilities and scale its systems. Persado's engineering leadership team determined that training its technical teams on the Hadoop technology stack would be the fastest path to ensuring they could support both the near- and long-term objectives of their Big Data deployment.
After evaluating several vendors, Persado selected Cloudera to develop an intensive weeklong program focused on Apache Hadoop, Apache Hive and Apache Pig to deliver onsite instruction at its corporate datacenter in Athens, Greece. The team's decision to work with Cloudera was based on various factors, chief among them being Cloudera's unrivaled domain expertise and the quality of its training and certification programs, its ability to mobilize and support private corporate training in Europe, its strong commitment to the Apache open source community and many contributions to advancing the Hadoop platform and its reputation for being a great organization with which to work.
"Working with Cloudera delivered significant benefits almost immediately, since no other company offers a full data analyst training program targeted at both developers and analysts working with Big Data in Hadoop, which was one of our biggest priorities," said Xinyu Huang, VP of Engineering at Persado. "Equally important to us was knowing that our staff was being trained on the world's most relevant, comprehensive, and production-tested open-source distribution of the Apache Hadoop stack."
Collaborating closely with Persado, Cloudera was able to develop a tailored curriculum that leveraged insights from the engineers who built the Hadoop platform to maximize the course's return. Cloudera's experienced instructor offered interactive training onsite throughout the week, helping to significantly shorten the Persado team's learning curve so that the participants were able to immediately apply their newfound skills in the context of their own data objectives and development use case.
"Cloudera has the most knowledgeable and largest number of full-time Hadoop trainers in mainland Europe, which helped us to save time, money and productivity," Huang continued. "They created an exceptional program for our team, incorporating best practices developed from our engineers and their own experiences in real world production deployments to offer invaluable insights into the use cases that are shaping the Hadoop market today."
With the new skills and expertise gained through its customized training program from Cloudera University, Persado's engineering and data analyst teams are now well equipped to maximize and extend the company's Hadoop deployment, enabling them to uncover deeper, more meaningful insights to drive greater value for their customers.
"Not only has Cloudera training prepared us for success today, but it has given us the tools to face and prevail over our Big Data challenges in the future," said Huang.
"Persado is leading the way in marketing innovation leveraging the power of Big Data," said Sarah Sproehnle, Vice President of Educational Services at Cloudera. "Hadoop training has empowered and prepared Persado's technical teams to support the unique needs of their data platform and maximize its potential. Their forward-thinking implementation of Hadoop was already helping to augment and extend the capabilities of their data warehouse, driving increased business intelligence and competitive advantage across their global organization. Now, having equipped Persado's staff with the knowledge and skills to better support its platform and address future growth at the speed of innovation, the sky's the limit in terms of business potential."
Learn More About How Persado Equipped Its Team to Address the Challenges and Opportunities of Big Data
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\section{Introduction}

The star formation history, metallicity, and current star formation
rate all contribute to the observed colors of a galaxy.  Remarkably,
these factors work in concert to yield a fairly well defined locus in
galaxy color-color space (Strateva et al.~2001).  Deviations from this
locus as well as the morphology of the locus itself, can lead to
significant insight into the underlying processes taking place within
galaxies.  Many previous studies have utilized the broad-band colors
of galaxies to investigate the star formation histories and
metallicities of galaxies (e.g. Tinsley 1972; Searle et al.~1973;
Tinsley \& Gunn 1976; Balcells \& Peletier 1994; Roberts \& Haynes
1994; de Jong 1996; Bell \& de Jong 2000; Galaz et al.~2002; Gavazzi
et al.~2002; Bell et al.~2003; MacArthur et al.~2004; Zackrisson,
Bergvall \& Ostlin 2005; Driver et al.~2006; Skibba et al.~2008).

The advent of large surveys such as the Sloan Digital Sky Survey
(SDSS; York et al.~2000) and the Two Micron All Sky Survey (2MASS;
Skrutskie et al.~2006) has created a wealth of uniform data and the
statistical foothold to investigate the bimodality of galaxies (Baldry
et al.~2004; Kauffmann et al.~2003, 2004), luminosity function
(Blanton et al.~2001; Ball et al.~2006), and the average properties of
nearby galaxies (Blanton et al.~2003a, 2003b, 2005; Geha et al.~2006; Maller et
al.~2008; Skibba et al.~2008). While the large optical and infrared
surveys have made large contributions to our understanding of galaxy
evolution, they only trace the stellar component of galaxies and do
not trace other baryonic material such as cold gas.

Galaxies in the local universe span a range of star formation
histories -- from blue, gas-rich, low-surface-brightness (LSB) galaxies
that are slowly turning their gas into stars with low star forming
efficiencies, to red, gas-poor galaxies, that have formed the bulk of
their stars in the past.  Stars dominate the visible light output of
most galaxies, and thus galaxies detected by traditional optical or
infrared imaging have well developed stellar populations.  In
contrast, the natural way to identify gas-rich, less evolved galaxies
is by their 21 cm HI radio emission.  Aside from its importance for
global star formation, a sample of galaxies with both gaseous and
stellar information allows for a more complete census of the local
baryons (a constraint vital to the calibration of n-body simulations;
Governato et al.~2007; Brooks et al.~2009).

Previous studies have combined large HI surveys with optical and infrared samples, namely the Arecibo Duel Beam and Slice Surveys with the Two
Micron All Sky Survey (2MASS; Jarrett et al.~2000; Rosenberg et
al.~2005) and the merging of HIPASS with SuperCOSMOS (Hambly et al.~2001; Hambly, Irwin \& MacGillivary 2001b; Hambly et al.~2001c;
Doyle et al.~2005).  Rosenberg et al.~(2005) were able to
probe the baryonic content of a large sample of galaxies, but were
limited by the shallow depth of 2MASS, which does not have data for
many of the LSB galaxies in the sample.  The HIPASS/SuperCOSMOS sample of Doyle et al.~(2005) contains optical data for more than 3600 HI selected galaxies but also suffers from the shallow depth of the SuperCOSMOS optical data.

Recent studies have combined the Parkes HI Equatorial Survey (ES) with
the SDSS (Disney et al.~2008; Garcia-Appadoo et al.~2009; West et
al.~2009; hereafter W09).  The deep SDSS optical data provides
information about the stellar content for \emph{all} ES HI sources
where the two surveys overlap.  In addition, the uniform, accurate,
and well-calibrated photometry of the HI-selected ES/SDSS sample
allows for a more detailed exploration of the factors affecting galaxy
colors, particularly for galaxies with large reservoirs of gas.  The
optical colors are reasonably sensitive to age, although IR colors are
needed to constrain metallicity (Bell et al.~2003).  There is thus an
unavoidable degeneracy between age and metallicity when using only the
optical colors available with SDSS (Bell \& de Jong 2001; Bell et
al.~2003).  Our sample does not have a complete set of near IR
counterpart data and some of our results will reflect this limitation.

In this paper, we briefly describe the ES/SDSS sample in \S2 and
examine the colors of HI-selected galaxies by comparing them to
stellar population synthesis models (\S3.1) and the colors of
optically selected galaxies (\S3.2).  We also investigate how line
emission affects the broadband colors of gas-rich galaxies (\S3.3). We
demonstrate an increased dispersion in the colors of galaxies at low
masses, and investigate its possible origins (\S3.4).  We summarize
and discuss our results in \S4.

\section{Data}

The HI data for our sample come from the Parkes Equatorial Survey (ES;
Garcia-Appadoo et al.~2009), a blind HI survey of the southern sky
that covers a velocity range from -1280 to 12700 km/s with an RMS
noise of 13 mJy, using the multibeam receiver on the 64m radio
telescope in Parkes, Australia.  The ES, which is described in detail
in an accompanying paper (Garcia-Appadoo et al.~2009), circles the
celestial equator between -6 $< \delta <$ +10 and contains over 1000
sources in 5738 square degrees.  The raw data forms part of the HI
Parkes All Sky Survey (HIPASS; Barnes et al.~2001; Meyer et al.~2004;
Zwaan et al.~2004; Wong et al.~2006), carried out with the same
instrument over the entire sky between -90 $< \delta <$ +25.  However,
the ES fields were searched much earlier (Garcia-Appadoo et al.~2009)
in readiness for comparison with SDSS data.  While the
search techniques were much the same as those of the HIPASS team and rely
heavily on their procedures, the source lists are not identical.  For
example, the completeness limit of the ES list is 30\% fainter than
the HIPASS limit.  This difference is mainly due to our ability to
follow-up and confirm a higher proportion of the fainter sources, a
process that would be impractical with the larger survey.  The
velocity resolution of the ES HI spectra is 18.0 km\ s$^{-1}$ and the
3$\sigma$ HI mass limit of the survey is $10^6\times
D^2_{\rm{Mpc}}M_{\odot}$, assuming a 200 km\ s$^{-1}$ HI galaxy profile.  For
detailed descriptions of the data acquisition, calibration and
reliability see Garcia-Appadoo et al.~(2009) and the HIPASS analysis
contained in Barnes et al.~(2001), Meyer et al.~(2004), and Zwaan et
al.~(2004).

The optical data for this study come from the Sloan Digital Sky Survey
(SDSS; York et al.~2000; Gunn et al.~1998; Fukugita et al.~1996; Hogg
et al.~2001; Smith et al.~2002; Stoughton et al.~2002; Pier et
al.~2003; Ivezi{\'c} et al.~2004; Gunn et all. 2006) Data Release 2
(DR2; Abazajian et al.~2004) sky area.  The DR2 area is 3324 deg$^2$,
about half of which overlaps with the equatorial ES region discussed
above.  Because the SDSS photometric software ({\tt PHOTO}; Lupton et
al.~2002) was not optimized for angularly large galaxies, all of the
photometry presented for the ES/SDSS survey has been re-processed
using the techniques described in W09.  The W09 study describes the
optical sample selection and matching to ES and presents the updated
SDSS photometry for 195 HI-selected galaxies using both a sky
subtraction procedure that is optimized for angularly large galaxies
and a correction for the over-deblending (``shredding'') of nearby
galaxies by the SDSS pipeline photometry.  While more recent SDSS data releases (e.g. DR7; Abazajian et al. 2009) may contain more of the optical counterparts to ES sources, the re-processed photometry is essential for accurate photometric studies and only exists for the DR2 sample (W09).

To be included in the ES/SDSS sample, each candidate galaxy had to
meet 4 criteria: 1) the ES recessional velocity must agree to within
twice the velocity width (as measured by the W$_{20}$ value) of the
optically derived redshift; 2) there must be no more than 1
detectable, spatially resolved galaxy within the ES beam at the same
redshift; 3) the candidate galaxy must not extend across two or more
SDSS fields; and 4) all galaxies must be at least 1$^{\prime}$ away
from any saturated foreground stars.  For additional details on
catalog matching, see W09.

\section{Results}
\subsection{Modeling the Colors of HI-selected Galaxies}

Figure \ref{grrigas} shows the extinction corrected $r-i$ colors of the galaxies in our HI
selected sample as a function of their $g-r$ color. The galaxies are color-coded according to their gas
fraction.  The gas fraction ($f_{gas}$) is defined as:

\begin{equation}
f_{gas}\equiv\frac{1.4M_{HI}}{1.4M_{HI}+M_{\star}},
\end{equation}

\noindent where M$_{HI}$ is the HI mass and M$_{\star}$ is the stellar
mass determined using color-dependent mass-to-light ratios that have
been corrected for a Kroupa initial mass function (Bell et al.~2003;
Pizagno et al. 2005; see W09).  The factor of 1.4 corrects for the
mass in helium.  We have neglected the molecular gas component, which
is measured to be small in low-mass, LSB galaxies that dominate
our sample (M$_{H_2}$/M$_{HI}<0.1$; Schombert et al. 1990; Matthews et al. 2005).  No molecular gas measurements (CO) exist for any of our sample galaxies. However, recent CO observations of nearby galaxies give some insight to the range molecular gas content in galaxies of similar morphological type. We estimate that the molecular to neutral gas fraction (M$_{H_2}$/M$_{HI}$) may be as high at 0.5 for some of the early-type spirals in the ES/SDSS sample (Leroy et al. 2009). Thus, we may be underestimating the gas fractions in a small number of our galaxies.

\begin{figure}
\centering
\plotone{f1.eps}
\caption[$r-i$ vs $g-r$ for HIPASS/SDSS sample galaxies.]{$r-i$ vs
$g-r$ for ES/SDSS sample galaxies.  All photometric corrections
have been applied to these data. Galaxies have been
color coded according to their gas fractions.}
\label{grrigas}
\end{figure}

Figure \ref{grrigas} shows several important trends.
First, the HI-selected galaxies occupy a well-defined locus in color,
as seen in other SDSS studies (Strateva et al.~2001; Blanton et
al.~2003a; Baldry et al.~2004; Maller et al.~2008).  Second, the gas
fraction scales with galaxy color such that bluer galaxies have a
larger fraction of their baryonic mass in gas, as has also been
reported for less uniform samples (Kannappan 2004).  Third, the
scatter in color-color space is large for gas-rich galaxies.

To interpret the trends observed in Figure \ref{grrigas}, we compared
the colors of the ES/SDSS sample galaxies to theoretical predictions
by running a series of Bruzual \& Charlot (2003) population synthesis
models at various metallicities and star formation histories.  The
models use the Chabrier (2003) initial mass function (IMF) to model
the stellar populations with a range of stellar masses of
0.6M$_{\odot} \leq m \leq 120{\rm M}_{\odot}$, at 6 different
metallicities (0.005, 0.02, 0.2, 0.4, 1 and 2.5 times solar) and 10
different star formation histories (SFH).  The SFHs are modeled as
having either (1) an exponentially decreasing star formation rate
(SFR; $e^{-t/\tau}$) with $\tau$ values of 8, 4, 2, and 1 Gyr (these
models have mean, mass-weighted stellar ages of 7.4, 8.6, 10.0, and
11.0 Gyr respectively); (2) an exponentially increasing SFR with
$\tau$ values of 8, 4, 2, and 1 Gyr (mean stellar ages of 4.6, 3.4,
2.0 and 1.0 Gyr respectively); (3) a continuous SFR ($\tau=\infty$;
mean stellar age of 6 Gyr); or (4) an instantaneous event of star
formation ($\tau=0$; mean stellar age of 12 Gyr).  For each model we
assume that 12 Gyr has elapsed since the first formation of stars (Dalcanton \& Bernstein 2002; Brooks et al. 2009) and
extract the SDSS model colors at that epoch.  We do not include dust
in any of the population models because we have corrected for the
internal extinction of the galaxies using the measured rotation
velocities (HI line widths) and the prescription of Tully et
al. (1998), where galaxies with the same rotation velocity are assumed
to have similar internal dust extinction. The uncertainty in this
correction is $\sim$ 0.1 magnitudes and may increase the scatter of
our photometry. However, many of the galaxies in the SDSS/ES sample
have little or no dust correction due to their slow rotation (Tully et
al. 1998; Dalcanton et al. 2004; see W09 for more details).

Each Bruzual \& Charlot (2003) model was run without gas recycling --
the population of stars maintains the same metallicity throughout the
star formation history.  While this does not accurately mimic the
chemical evolution of individual galaxies (which are some amalgamation
of ages and metallicities), it does provide a set of specific model
comparisons by which to compare the mean properties of observed
systems.

Figure \ref{bc1} shows the resulting population grid for the $r-i$
colors as a function of $g-r$.  The
``horizontal'' lines are lines of constant metallicity and the
``vertical'' lines are lines of constant $\tau$ (a proxy of mean
stellar age).  Tracks of constant age are well separated in $g-r$, making $g-r$ a good probe of stellar age.  On the other hand, the $r-i$ color is
only marginally sensitive to metallicity and the aforementioned
degeneracy is apparent at all sub-solar metallicities.  These grids
bracket all reasonable continuous star formation histories, but
bracket only a narrow region of $g-r$ vs. $r-i$ color space.  Although SDSS provides photometry in 5 different photometric passbands, most of our color analysis uses only the $g$, $r$ and $i$-bands. For most of our galaxies, the $u$ and $z$ bands yield photometry with large uncertainties that does not help us differentiate between models or constrain photometric relationships.  Because the $u$-band is sensitive to the star formation rate (Hopkins et al. 2003), we have included $u$-band photometry in a limited amount of our analysis.

\begin{figure}
\centering
\plotone{f2.eps}
\caption{$r-i$ vs $g-r$ for HI selected galaxies. Galaxies have been color
coded according to their gas fractions.  Bruzual \& Charlot (2003)
population synthesis grids have been overplotted for various continuous SFH and
metallicities. The SFH are
given by $\tau$ values for an exponential SFR starting at 12 Gyr ago.
($e^{-t/\tau}$).  Metallicities are plotted in comparison to solar.}
\label{bc1}
\end{figure}

The ES/SDSS sample galaxies have been overplotted and color-coded
according to their gas fractions, as in Figure 1. At the red end of
the galaxy distribution, the colors are well explained by the model
grids.  The redder galaxies are consistent with having SFHs that have
been declining to the present.  These results are in agreement with
previous work by Bell et al.\ (2003) as well as Juneau et al.~(2005),
who demonstrate that galaxies with large stellar masses formed most of
their star in the first 3 Gyr after their formation.  The reddest
galaxies also have colors indicative of super-solar metallicities.
These red ($g-r >$ 0.6), high-metallicity galaxies are all early-type spiral, lenticular or elliptical galaxies.

The data and models in Figure \ref{bc1} suggest that the red galaxies
formed almost all of their stars in the distant past and have been
undergoing little to no star formation since, in spite of containing
HI at the present.  Some mechanism is therefore responsible for the
continued presence of HI.  The cannibalization of gas rich dwarfs or
infall from ``cold mode'' accretion (Katz et al.~2003; Brooks et
al.~2009) might be sufficient to explain the current small reservoir
of gas, which is only a small fraction of the galaxies' baryonic mass.
Regardless of the physical process by which these galaxies acquired or
maintained gas, the presence of HI suggests that recent star formation
is likely to have taken place.  Indeed, all of the galaxies redder
than $g-r$ $>$ 0.5 have SDSS spectra that contain emission lines. In
spite of the aperture bias in SDSS fiber spectroscopy (fibers are only
3$^{\prime\prime}$ in diameter), these spectra can be useful for
determining gross spectroscopic properties .Based on their location on
a Baldwin-Phillips-Terlevich diagram (Baldwin, Phillips \& Terlevich
1981), five of the 156 emission-line galaxies are consistent with
hosting an AGN.  All five of the galaxies with AGN have PetroR90 radii (radii containing 90\% of the Petrosian flux) larger than 30$^{\prime\prime}$.  Therefore, their disk emission (not the AGN) dominates the integrated photometry and they are included in remainder of the analysis. The majority of the galaxies in the ES/SDSS sample have emission lines that
suggest that current star formation is underway in these galaxies.

As we look to the bluer galaxies in Figure \ref{bc1}, the
inferred metallicities are lower and the SFHs move toward a constant star
formation rate ($\tau=\infty$).  This shift is likely due to a decrease in
star formation efficiency.  We define star formation efficiency as the efficiency in converting gas into stars.  As discussed above, we neglect the role of molecular gas (the state of gas from which stars form),  which should be irrelevant for the bluer galaxies in our sample. Recent studies (that included the molecular component) have seen a similar decrease in star formation efficiency in nearby, HI-dominated galaxies (Bigiel et al. 2008).  Although we do not resolve the HI emission, the failure to convert large amounts of HI into stars in the blue galaxies constitutes a decrease in star forming efficiency.  Such a decrease slows the rate of star
formation, keeping metallicities low and gas fractions high, allowing
stars to form at the present day.

The bluest galaxies ($g-r <$ 0.3) are best modeled by SFHs that have
increasing SFRs.  This area of the model parameter space has been
ignored by previous galaxy studies (Kauffmann et al.~2003; Brinchmann
et al.~2004; Salim et al.~2005; Johnson et al.~2007).  Gas infall
might serve to increase the HI surface density and subsequently the
SFR in these galaxies.  Although recent bursts have likely occurred in
these galaxies, the already blue $g-r$ colors of these do not change
significantly when recent bursts are added to the models (see \S 3.3).

Many of the bluest galaxies in the ES/SDSS sample have colors that
are not consistent with any of the Bruzual \& Charlot models.  Most of these
galaxies have $r-i$ colors that are too blue to be explained by any
iteration of the models. The LSB nature of many of these systems
suggests that for even small SFR, emission lines might be able to
dominate the broadband colors (Zackrisson et al.~2001; Magris, Binette
\& Bruzual 2003; Anders \& Alvensleben 2003; Zackrisson,
Bervall \& {\" O}stlin 2005; Zackrisson, Bergvall, \& Leitet 2008).  We investigate this possibility in detail in \S3.3.

Finally, there are a five galaxies that seem to be too red in
 $r-i$ to be explained by any population models.  Two of these
 galaxies have a saturated star nearby that is most likely affecting
 their colors.  One of the galaxies has very large photometric
 uncertainties because of its low surface brightness and the other two
 have very compact cores, which suggests the presence of AGN.  If we
 compute the colors for these two galaxies excluding the central
 region, using a shell with radial boundaries defined to be from half
 of the Petrosian radius to the Petrosian radius, both galaxies fall
 back to or below the model grids when their central core is excluded.

\subsection{The Colors of HI vs. Optically Selected Galaxies}

Although the trends seen in Figure \ref{grrigas} have been noted in
optically selected SDSS samples (e.g. Strateva et al.~2001; Blanton et
al.~2003a), the HI selection introduces a systematic shift in the
color distribution of the ES/SDSS sample galaxies.  Figure
\ref{grri_main} shows the $r-i$ vs. $g-r$ colors for the ES/SDSS
sample plotted on top of a volume limited sample drawn from the SDSS
DR4 sample (Adelman-McCarthy et al.~2006). All galaxies have been
k-corrected and corrected for Milky Way extinction.  We used the Milky
Way extinction values from Schlegel et al. (1998) and calculated
K-corrections using the IDL package {\tt kcorrect\_v3.2} (Blanton et
al. 2003b).  The Blanton et al. (2003b) k-correction method uses
empirically-derived eigenspectra to generate model spectra from SDSS
photometry.  All of the galaxies (both SDSS DR4 and ES/SDSS) were corrected
using the same method to $z$=0.  Most of the k-corrections were smaller than 0.01 magnitudes in all bands.  No data in Figure
\ref{grri_main} have been corrected for internal extinction.  The
reddening vector (derived from Schlegel et al.~1998) has been included
to show that any correction to either data set is almost perfectly
aligned with the galaxy locus.

\begin{figure}
\centering
\plotone{f3.eps}
\caption{$r-i$ vs $g-r$ for HI selected galaxies (colored symbols)
plotted with a volume selected sample of galaxies from SDSS (contours).  No internal extinction has been applied to these data but a
reddening vector has been plotted for reference.  Galaxies in the
thesis sample have been color coded according to their gas
fractions. Note that the HI selected sample appears to have colors
that are shifted off of the SDSS galaxy locus. }
\label{grri_main}
\end{figure}

The HI-selected galaxies do not show the color bimodality seen in previous SDSS studies (e.g. Blanton et al.~2003a; Baldry et al.~2004).  Figure \ref{smassur} shows the $u-r$ colors as a function of stellar mass for the ES/SDSS galaxies (colored according to gas fraction) and the SDSS DR4 sample (contours).  The bimodal galaxy distribution (blue and red sequence) is easily seen in the SDSS DR4 galaxies, but is absent from the ES/SDSS galaxies.  The HI selection of the ES/SDSS galaxies identifies gas-rich galaxies that are on the blue sequence and are currently in the process of star formation.  Like in Figure \ref{grri_main}, the ES/SDSS galaxies in Figure \ref{smassur} appear to be offset from the SDSS DR4 sample (bluer in $g-r$ or redder in $r-i$).  Figure \ref{smassur} also demonstrates the ability of an HI-selected sample to recover galaxies with small stellar masses; the ES/SDSS sample has a significant number of galaxies with stellar masses below 10$^8$ M$_{\odot}$.

\begin{figure}
\centering
\plotone{f4.eps}
\caption{The $u-r$ colors as a function of stellar mass for the ES/SDSS galaxies (colored according to gas fraction) and the SDSS DR4 sample (contours).  The bimodal galaxy distribution (blue and red sequence) is easily seen in the SDSS DR4 galaxies, but absent from the ES/SDSS galaxies.  The HI selection of the ES/SDSS galaxies identifies gas-rich galaxies that are on the blue sequence and are currently in the process of star formation.}
\label{smassur}
\end{figure}

It is clear from Figure \ref{grri_main} that the HI selected sources
fall to one side of the SDSS galaxy distribution, such that they are
either bluer in $g-r$ or redder in $r-i$. This offset is particularly
pronounced at the red end of the color distribution where the color
dispersion is small.  As noted in the previous section, the redder
galaxies have SFHs that suggest that almost all star formation occurred
in the distant past.  The presence of HI in these systems may indicate
a recent acquisition of HI and a subsequent ignition of star
formation, as confirmed by their SDSS spectra.  This temporary increase
in SFR due to late-time accretion would naturally explain why the red HI
selected galaxies are slightly bluer in $g-r$ than the rest of the
SDSS galaxy population (Figure \ref{grri_main}).

To constrain the amount of recent star formation needed to produce the
observed color offset between the ES/SDSS galaxies and the ``main'' SDSS
sample, we re-ran the same series of Bruzual \& Charlot (2003)
population synthesis codes as in Figure \ref{bc1}, but with the
addition of a recent burst of star formation.  We generated an
initial model with $g-r$ and $r-i$ colors of 0.75 and 0.3
respectively ($\tau$=2; Z=Z$_{\odot}$). We
then added a single instantaneous burst (delta-peak) of star formation to the continuous model
and varied the time of the burst from 2 Gyr to 100
Myr in the past.  We also varied the burst strength from 0.1-10\% of the
integrated star formation.  The resulting models were most sensitive
to the time at which the burst was placed. The models that most
closely matched the slight $g-r$ bluing were bursts placed at 300 Myr
in the past with 1\% of the past integrated star formation occurring in
the burst.

Figure \ref{bursttime} shows the evolutionary track for the best
matched model burst (300 Myr in the past) with symbols plotted every
50 Myr since burst. The figure demonstrates that there is a rapid and
short-lived change in color that occurs in the first few Myrs and is
followed by a slow reddening for hundreds of Myrs.  Colors bluer than
$g-r$ $<$ 0.4 and $r-i$ $<$ 0.2 are observed only for very short
durations ($<$1 Myr).  By 100 Myr the colors have reddened to within
$\Delta g-r$=0.15 and $\Delta r-i$=0.05 of their initial value and
continue to redden for hundreds of Myr.  This ``bottleneck'' in the
burst evolution suggests that the small color offset observed in
Figure \ref{grri_main} could be sufficiently long lived to be due to a
burst in the past few hundred Myr.

\begin{figure}
\centering
\plotone{f5.eps}
\caption{The $r-i$ vs. $g-r$ evolution of a single Bruzual \& Charlot
  model with the addition of an instantaneous burst of star formation
  that produced 1\% of the total stellar mass of the galaxy and
  occurred 300 Myr in the past (solid line). The Bruzual \& Charlot
  continuous star formation grid (from Figure \ref{bc1}) is plotted
  for reference (dashed lines). The continuous model to which the
  burst was added corresponds to a red galaxy from the ES/SDSS sample
  ($\tau$=2, Z=Z$_{\odot}$; $g-r$ and $r-i$ colors of 0.75 and 0.3
  respectively). Colored symbols are plotted every 50 Myr starting 50
  Myr before the burst. Colors bluer than $g-r$ $<$ 0.4 and $r-i$ $<$
  0.2 are observed only for very short durations ($<$1 Myr).  By 100
  Myr the colors have reddened to within $\Delta g-r$=0.15 and $\Delta
  r-i$=0.05 of their initial value and continue to redden for hundreds
  of Myr.}
\label{bursttime}
\end{figure}

Figure \ref{bc2} shows the ES/SDSS galaxies and the model grids for
continuous star formation with an additional 1\% burst occurring
300 Myr in the past.  The red HI selected galaxies in the burst model
have $\tau \sim3$, compared to the $\tau \sim4$ seen in the burst-free
models.  By comparing the difference between the grids in Figure
\ref{bc1} and \ref{bc2} with the offset observed in Figure
\ref{grri_main}, it is clear that the HI selected galaxies in the
burst case (Figure \ref{bc2}) occupy the same model space ($\tau
\sim3$) as the SDSS ``main'' galaxies in the burst-free case (Figure
\ref{bc1}).  Unfortunately, our inability to correct for internal
extinction in the SDSS ``main'' sample prohibits us from overlaying
accurate grids on Figure \ref{grri_main}, which would be highly
instructive.  However, ``blinking'' back and forth between Figures
\ref{bc1} and \ref{bc2} confirms that a recent burst can explain
the offset of the red galaxies.

\begin{figure}
\centering
\plotone{f6.eps}
\caption{$r-i$ vs $g-r$ for HI selected galaxies.  All photometric
  corrections have been applied to these data. Galaxies have been
  color coded according to their gas fractions.  Bruzual \& Charlot
  (2003) population synthesis grids have been overplotted for various
  SFH and metallicities after 12 Gyrs of star formation. The SFH are
  given by $\tau$ values for an exponential SFR ($e^{-t/\tau}$).
  These grids include an instantaneous burst of star formation that
  produced 1\% of the stellar mass, 300 Myr in the past.}
\label{bc2}
\end{figure}

It is important to note that the addition of the burst may effect the
colors of the blue galaxies as well.  A single instantaneous burst
produces extremely blue colors for very short times. However, in
reality, the bursts are not instantaneous, but instead last for a
finite amount of time with some exponential decrease (10-300 Myr
depending on galaxy type; McQuinn et al. 2009).  If a significant
fraction of the star formation has occurred in the very recent past,
then some of the blue colors may be due to recent bursts. However,
rising SFRs are still required to explain the bulk of the galaxies
with colors bluer than $g-r <$0.3.

 Although degeneracies between the time, duration and strength of the
 star formation events in the models prevent an exact characterization
 of the bursts in the HI selected galaxies, we can safely claim that a
 new generation of stars has been formed in the last few hundred Myr
 in the red systems (a large instantaneous burst has a similar
effect on the integrated colors as a small exponentially decreasing
burst). The bursts require no more than 1\% of the mass
 to be involved as long as the burst was in the last 300 Myr.

 We note that the bluer $g-r$ colors in the red ES/SDSS galaxies may not be solely due to main sequence stars, since most blue main sequence stars will have ceased their hydrogen burning after a few hundred Myr; the $g-r$ color of a main sequence turnoff star at 300 Myr is $\sim$0.0 (Sarajedini et al.~2004; Covey et al.~2007). We suggest that another possibility for the blue
 $g-r$ colors we see in the red HI selected galaxies could be due
 to an elevated level of BHeB stars left over from a recent burst of
 star formation. These stars are seen several hundred Myr after a star
 formation event (Dohm-Palmer et al.~2002).

\subsection{Modeling Galaxy Colors with Emission Lines}

Even with the addition of bursts, the colors of many ES/SDSS galaxies
do not fall on the Bruzual \& Charlot (2003) model grids.  Unlike the
red galaxies, which can be easily explained, the majority of the
discrepant galaxies are significantly bluer in $r-i$ than any models
can predict.  These systems also have high gas fractions and most have
low surface brightness. No matter what parameters we alter in the
Bruzual \& Charlot models, we cannot produce a stellar population with
very blue $r-i$ colors.

We show that the discrepant colors can be explained by including the
emission lines that dominate the spectra of these outlying galaxies.
The blue colors and high gas fractions of the discrepant galaxies
suggest that they are actively forming stars.  Because these
galaxies also have low surface brightnesses, it is possible that
emission lines produced by HII regions contribute significantly to
their luminosity.  HII regions produce numerous emission lines in the
$g$ and the $r$ bands. H$\alpha$ dominates in the $r$-band while [OIII]
and H$\beta$ dominate in the $g$-band.  In contrast, the $i$-band has almost no
emission lines.  Therefore, in an HII region, we would expect the
$r-i$ color to be significantly bluer than the underlying stellar
continuum and the $g-r$ color to change only slightly. This suggests that $i$-band luminosity may be a better indicator of the underlying stellar mass than $g-r$. It also implies that the $g-r$ color should be used to compute color dependent mass-to-luminosity ratios (the emission lines tend to cancel out; see below).

We can test this idea using the SDSS spectroscopic fibers, which were
often placed on HII regions for LSB galaxies.  By comparing the colors
of HII regions (derived from SDSS spectra) with the integrated colors
of the galaxies that host them, we can quantify color changes produced
by HII regions.

We first selected 10 ES/SDSS galaxies with SDSS spectroscopy and
required that they have large H$\alpha$ equivalent widths ($>$ 300
\AA).  Four of the spectra selected are shown in Figure \ref{spectra}.
All of the selected spectra have good signal-to-noise ($>$ 50) and are
dominated by emission line features.  We visually inspected each
galaxy to ensure that all of the spectra selected (and shown in Figure
\ref{spectra}) are from fibers placed on high surface brightness HII
regions.  We convolved the $g$, $r$ and $i$ SDSS filter curves with
each spectrum and converted the computed flux density to AB magnitudes
using the relation that a magnitude 0 object has a flux density of
3631 Jy (Oke \& Gunn 1983). We then compared the integrated colors of
the 10 galaxies derived in W09 with the HII region colors derived from
the spectra.

\begin{figure}
\centering
\plotone{f7.eps}
\caption{SDSS fiber spectra for 4
galaxies in the ES/SDSS sample with strong emission line features.
All of the fibers for these spectra were placed on top of HII regions
in the galaxies.  The flux axis is in units of 10$^{-17}$
ergs/s/cm$^2$\AA.}
\label{spectra}
\end{figure}

Figure \ref{em1} shows the resulting differences between the HII
region and the integrated color of each galaxy.  The colors derived
from fibers placed on HII regions are plotted as black symbols and the
integrated galaxy colors derived from images (W09) are plotted as
red diamonds.  Blue lines
connect a galaxy's integrated color to the color of the
3$^{\prime\prime}$ diameter aperture around the HII regions.  The HII region
colors are bluer in $r-i$ by $\sim$0.5$^{m}$ and all but 2 become bluer
in $g-r$ by $\sim$0.2$^{m}$, compared to the integrated colors.  This result
confirms the hypothesis that emission lines can make the $r-i$ color
blue enough to explain the colors we see in the ES/SDSS sample.
However, contrary to our initial expectation, the $g-r$ color does change
considerably.  The bluer $g-r$ colors near HII regions can be
explained as being produced by a young underlying stellar
population. More surprisingly, the colors near two of HII regions are
redder in $g-r$ than the integrated light from the galaxies.  This
difference may reflect the presence of dust localized to the HII region.

To further test the emission line hypothesis as well as to confirm the
reason for the $g-r$ color change in Figure \ref{em1}, we added model emission lines to
the computed Bruzual \& Charlot model colors.  Theoretical models for
line emission in galaxies are given by Kewley et al.~(2001) using the
{\tt STARBURST99-MAPPINGS III} code.  The models cover a range of
metallicities, ionization states, electron densities, and assumption
about the burst lengths.  For each model, the wavelength of every line
and its energy are provided.  We convolved these energies with the
SDSS filters and converted the computed flux densities into AB
magnitudes.  We added the emission line output to the Bruzual \&
Charlot colors using a scaling coefficient that determines the
strength of the emission line relative to the true stellar
continuum. This coefficient is directly proportional to the SFR and
can be used to estimate the range of possible SFRs for a galaxy.  The
final models are not fully self consistent, because the ionizing
radiation for the emission line spectrum does not come directly from the
Bruzual \& Charlot spectrum.  However, because the star formation is
highly localized in late-type galaxies, it is possible for the
ionizing radiation in isolated HII regions to be different than that
of the broader component of stars

\begin{figure}
\centering
\plotone{f8.eps}
\caption{$r-i$ vs. $g-r$
color difference between the integrated colors of 10 galaxies (red
diamonds) and the ``fiber'' magnitudes computed from the HII region
spectra (black symbols).  The blue lines connect each galaxy's
integrated color to its HII region color.  All of the galaxies get
bluer in $r-i$ and all but 2 get bluer in $g-r$}
\label{em1}
\end{figure}

When adding the {\tt STARBURST99-MAPPINGS III} emission-line models to
the Bruzual \& Charlot outputs, we ensured that the adopted gas
metallicity matched the assumed stellar metallicity.  Because there
are only 3 overlapping metallicities, we limited our analysis to 0.2
Z$_{\odot}$, 0.4 Z$_{\odot}$ and solar metallicity populations.  In reality most
of the galaxies where emission lines dominate are low mass and gas
rich and thus are unlikely to have high metallicities.  Even values of
0.2 Z$_{\odot}$ might be too high for these systems (Tremonti et
al.~2004).

Figures \ref{emissionsim} and \ref{emissionsim2} show the colors
($r-i$ vs.$g-r$ and $u-r$ vs. $g-r$ respectively) that result from
adding emission lines to a single Bruzual \& Charlot model ($\tau$=8
Gyr; Z=0.4Z$_{\odot}$). This particular model was chosen because it lies on the red end of the blue population and intersects the ES/SDSS color-color locus.  The colored symbols represent different star
formation rates.  In Figure \ref{emissionsim}, the model galaxy's
$r-i$ color becomes bluer as star formation is increased, while the
$g-r$ color is almost unchanged. A similar effect is seen in the $u-r$
color in Figure \ref{emissionsim2}.  This confirms that the non-zero
$g-r$ color offsets near HII regions must indeed be due to stellar
populations and or dust.

\begin{figure}
\centering
\plotone{f9.eps}
\caption{The $r-i$ vs. $g-r$ colors of the ES/SDSS galaxies with the addition of
  emission lines to an underlying stellar population for a single
  Bruzual \& Charlot model galaxy ($\tau$=8 Gyr; Z=0.4 Z$_{\odot}$). The
  colored symbols represent different star formation rates. The
  galaxy's $r-i$ color becomes bluer as star formation is increased,
  while the $g-r$ color goes almost unchanged.}
\label{emissionsim}
\end{figure}

\begin{figure}
\centering
\plotone{f10.eps}
\caption{The $u-r$ vs. $g-r$ colors of the ES/SDSS galaxies with the addition of  emission lines to an underlying stellar population for a single
  Bruzual \& Charlot model galaxy ($\tau$=8 Gyr; Z=0.4 Z$_{\odot}$). The
  colored symbols represent different star formation rates.}
\label{emissionsim2}
\end{figure}

In Figure \ref{sb99grids}, we show stellar population grids similar to those in Figure \ref{bc1}, but with an 8 Myr long continuous burst of star formation.  Black lines indicate emission line models with an electron density of 10 cm$^{-3}$ and an ionization parameter of 5$\times10^6$ cm~s$^{-1}$.  Red lines have the same electron density but an ionization parameter of 8$\times10^7$ cm~s$^{-1}$. This plot demonstrates that adding emission lines of
varying strength can explain all of the discrepant blue galaxies.  While 8 Myr may be short for some realistic starburst events, it successfully demonstrates the effect of current (or recent) star formation on the colors of galaxies.

\begin{figure}
\centering
\plotone{f11.eps}
\caption{$r-i$ vs. $g-r$ colors for the HI selected
  galaxies.  Color coding indicates the gas fractions of the
  galaxies. The grids represent 2 different linear combinations of the
  STARBURST99-MAPPINGS III emission line models and the Bruzual \&
  Charlot population synthesis models.  The Bruzual \& Charlot models
  are identical to those shown in Figure \ref{bc1}.  All emission line
  models use an 8 Myr continuous burst of star formation.  Black lines
  indicate emission line models with an electron density of 10
  cm$^{-3}$ and an ionization parameter of 5$\times10^6$ cm\ s$^{-1}$.  Red
  lines have the same electron density but an ionization parameter of
  8$\times10^7$ cm\ s$^{-1}$.  Solid lines have SFR densities of
  1.2$\times10^{-3}$ M$_\odot$\ yr$^{-1}$\ kpc$^{-2}$ and 3.7$\times10^{-3}$
  M$_\odot$\ yr$^{-1}$\ kpc$^{-2}$ for the two models (black and red)
  respectively.  The dashed lines have SFRs 3 times larger than the
  solid lines.  These models clearly describe the colors of all of the
  galaxies that are not fit by normal populations of stars.}
\label{sb99grids}
\end{figure}

We found that varying the electron density and burst length (8 Myr
continuous vs. instantaneous) did not have a major effect on the
output models. All significant changes in color are driven by the
ionization parameter and by the global normalization of the emission
line spectrum, which is directly proportional to the SFR (the emission
lines are generated for a specific value of the SFR).  Solid lines in
Figure \ref{sb99grids} have SFR densities of 1.2$\times10^{-3}$
M$_\odot$~yr$^{-1}$~kpc$^{-2}$ and 3.7$\times10^{-3}$
M$_\odot$~yr$^{-1}$\ kpc$^{-2}$ for the two models (black and red)
respectively.  The dashed lines have SFRs 3 times larger than the
solid lines.  For typical galaxies in our sample, we estimate SFRs of
0.004-0.2 M$_\odot$~yr$^{-1}$ in the emission line dominated regions.
These are reasonable SFRs for small, blue galaxies (van Zee 2001;
Hunter \& Elmegreen 2004; Salzer et al.~2005).  We estimated the SFR
density of the ES/SDSS sample using the $u$-band luminosity as a proxy
for SFR (Hopkins et al.~2003).  We found that the SFR densities range
from 0.0001 to 0.02 M$_\odot$~yr$^{-1}$~kpc$^{-2}$.  This range is
consistent with the star formation rate densities required to produce
the blue offset in the galaxies in Figure \ref{emissionsim}.  While
the models might not be perfectly self-consistent as discussed above,
they do demonstrate that strong emission lines can certainly affect
the colors of galaxies.  We note that the ``pitched roof'' shaped grids are a result of how the emission lines are affected by slight changes in the metallicity.  It is clear that the span of these models can
easily explain the galaxies that the stellar population models cannot
and that many low mass, blue galaxies must have colors that are
dominated by emission lines (e.g. Zackrisson et al.~2005).

The emission line effect may also amplify the underlying color offset discussed in the previous section by making galaxies appear bluer in $r-i$ than they actually are.  However, the colors of the red galaxies in the offset region are dominated by their stellar populations and not likely affected by the emission line colors.

\subsection{The Increase in Color Dispersion}

The analysis above demonstrates that the observed colors of the
ES/SDSS sample can be well explained by stellar population models
including emission lines, and that the general trend in color is due
to decreasing mean stellar age with increasing gas fraction. However,
while this explains most of the general trends seen in the color
distribution in Figure \ref{grrigas}, it does not fully explain the increase in the dispersion of color from red to blue galaxies.  The narrow
dispersion at red colors grows to a much larger value before the
photometric uncertainties become large enough to be solely responsible
for the discrepancy.  Although some of the increased dispersion is likely due to the onset of emission line dominated colors, this cannot account for the entirety of the color dispersion.

To explore how the dispersion in color relates to other physical
quantities, we performed a principal component analysis (PCA) on the
$r-i$ vs. $g-r$ colors.  The result aligns the principal axis (P1)
with the galaxy color-color locus and sets the secondary axis (P2)
perpendicular to P1.  P1 and P2 can be expressed in term of the $g-r$
and $r-i$ colors of the galaxies by

\begin{equation}
P1= 0.6(r-i)+0.8(g-r)-\langle 0.6(r-i)+0.8(g-r)\rangle
\end{equation}

\noindent and

\begin{equation}
P2=0.8(r-i)-0.6(g-r)-\langle 0.8(r-i)-0.6(g-r)\rangle,
\end{equation}

\noindent where the angle brackets indicate the mean of the enclosed quantity for the sample (the resulting eigenvalues are 6.2 and 0.8 for the eigenvectors pointing along the P1 and P2 axis respectively).

Figure \ref{pca} shows the result of the PCA coordinate
transformation.  Error bars were calculated using the uncertainties in
the $g$, $r$ and $i$-band photometry.  The P2 axis serves as an
indicator of dispersion from the galaxy locus and we compare the P2
values to other physical parameters below.

\begin{figure}
\centering
\plotone{f12.eps}
\caption{Principal axis of the galaxy color-color relation after PCA.  Galaxies are color coded according to their gas fraction.  Error bars were calculated using the uncertainties in the $g$, $r$ and $i$-band photometry.}
\label{pca}
\end{figure}

We quantified the dispersion in the P2 axis by calculating the rms P2 scatter in bins of P1. Figure \ref{p1p2} shows the resulting change in color dispersion along the principal axis.  The error bars indicate the photometric uncertainty in the P2 value.  As seen in Figures \ref{pca} and \ref{grrigas}, blue galaxies have a significantly larger color dispersion than red galaxies.

Changes in observable properties of the galaxies, such as stellar
mass, rotation velocity, surface density and surface brightness might be related to a change in their color dispersion.  As seen in previous work on the
ES/SDSS sample, many of these physical properties are related to
each other (Disney et al.~2008; Garcia-Appadoo et al.~2009) and a
change in one property is likely to show up as a variation in the
others.

\begin{figure}
\centering
\plotone{f13.eps}
\caption{The rms scatter in the P2 axis as a function of P1.  The error bars indicate the combined photometric error of the data points in each bin.}
\label{p1p2}
\end{figure}

To examine how the change in color dispersion relates to the physical
properties of the ES/SDSS galaxies, we plotted the P2 PCA values as a
function of stellar mass, rotation velocity (measured from half of the
20\% HI velocity width), surface brightness and stellar surface
density (calculated by measuring the average stellar mass density
within the 90\% Petrosian radius). Figure \ref{varp2} shows that
changes in the physical properties trace the change in dispersion
very well.  In addition, Figure \ref{varp2} has been color coded
according to gas fraction.  As seen in previous studies, the gas
fractions also correlate with the physical properties of the ES/SDSS
galaxies (Garcia-Appadoo et al.~2009).  We quantified the change in
color dispersion by plotting the rms scatter in the P2 axis as a
function of the four physical properties (Figure \ref{sigp2}).  All
four properties correlate with the rms scatter in the P2 variable.  We
computed the Spearman's rank correlation coefficient for each relation
to test which property best correlates with the color dispersion.  We
calculated Spearman's $\rho$ values of 0.92, 0.82, 0.89 and 0.96 for
the stellar mass, velocity, surface brightness and surface density
respectively.  The stellar density shows the best correlation with
color dispersion with the lowest density galaxies having the highest
color dispersion.

\begin{figure}
\centering
\plotone{f14.eps}
\caption{P2 PCA axis as a function of stellar mass (a), velocity width (b), $i$-band surface brightness (c) and stellar surface density (d).  Points have been color coded according to their gas fractions.}
\label{varp2}
\end{figure}

The increase in color dispersion as a function of surface brightness
and stellar surface density may probe a change in the star formation
process.  At the low surface brightnesses, the stochastic nature of
star formation (Stinson et al.~2007), and the dominance of emission
lines in low-mass galaxies, controls the observed colors and creates a
larger color dispersion, while the colors of higher surface brightness
systems are dominated by stellar populations (and to a smaller extent
recent bursts of star formation, as discussed above).  Because the
surface brightness and stellar surface density are tied closely to other properties of the ES/SDSS galaxies (Disney et al.~2008), this change in color dispersion may be evidence for a significant change in the way stars form in
galaxies.

\begin{figure}
\centering
\plotone{f15.eps}
\caption{The rms scatter in the P2 axis as a function of stellar mass (a), velocity width (b), $i$-band surface brightness (c) and stellar surface density (d).  The error bars represent the combined photometric error in each bin.}
\label{sigp2}
\end{figure}

While the stellar mass, surface brightness and stellar surface density change smoothly, the velocity width shows a statistically significant (4 $\sigma$) jump at a velocity of 80 km~s$^{-1}$.  Previous studies have found that the  rotation velocity in galaxies correlates with transitions in their disk properties.  Dalcanton, Yoachim \& Bernstein (2004) showed that the presence of dust lanes in a sample of edge-on disk galaxies is related to rotation
speed.  At $V_c < 120$ km~s$^{-1}$, no dust lanes are present in their
galaxies.  Disk instabilities occurring at $V_c > 120$ km~s$^{-1}$ act to
collapse the dust to a small scale height and produce a larger optical
depth.  Star formation efficiency is also increased above this
velocity threshold, affecting the SFH and colors of the faster rotators
(Verde et al.~2002; Dalcanton et al.~2004).   Lee et al.~(2007) find an additional transition around 50 km~s$^{-1}$, where the dispersion in H$\alpha$ EW dramatically increases.  This transition is interpreted as a possible change from large-scale star formation in spiral galaxies to stochastic star formation in irregular systems (e.g. Stinson et al.~2007).  We observe a transition in the color dispersion at 80 km~s$^{-1}$ (Figure \ref{sigp2}b) that lies in between the Dalcanton and Lee transitions.  The transition in the ES/SDSS sample may be a result of a similar physical process, namely the change from well-organized star formation in massive disks to an irregular stochastic process in lower mass systems

To illustrate the differences between systems across the velocity
transition, we randomly selected 5 $gri$ composite images of galaxies
from the low velocity (V$_{rot}$ $<$ 80 km~s$^{-1}$) population (top row of
Figure \ref{locus}) and 5 images from the high velocity population (V$_{rot}$
$>$ 80 km~s$^{-1}$; bottom row of Figure \ref{locus}).  Figure \ref{locus} reveals a clear morphological distinction between the two populations, with the higher velocity systems having higher surface brightnesses, earlier morphological types and a more organized distribution of stars (an indication of large scale star formation).

\begin{figure*}
\centering
\plotone{f16.eps}
\caption{5 randomly selected $gri$ composite images of galaxies from the slowly rotating regime (V$_{rot}$ $<$ 80 km~s$^{-1}$; top row) and 5 composite images from the faster regime (V$_{rot}$ $>$ 80 km~s$^{-1}$; bottom row). [A higher resolution version of this figure is available from ADS and the Astronomical Journal.]}
\label{locus}
\end{figure*}

\section{Discussion}

We used the population synthesis models of Bruzual \& Charlot (2003) to
model the SFHs and metallicities of galaxies in the ES/SDSS sample.
We found that red galaxies have super-solar metallicities and have SFHs that are consistent with them forming the bulk of their stars in the distant past.  These red galaxies have presumably exhausted their early gas supply but have recently acquired gas through mergers and infall. Although the infalling gas is likely low metallicity and could in principle dilute the metallicity, the small amount of gas in red galaxies (low gas fractions) is not enough to make an observable difference in the average metallicity of the ES/SDSS systems.

Bluer galaxies have lower metallicities and their mean stellar ages
are younger (increasing $\tau$ values).  The gas fractions suggests
that these blue systems have at least as much gas as they do
stars. Previous studies have indicated that these types of galaxies are less massive and have disks that are stable against collapse, making their
star formation much less efficient.  They have also likely retained
much of their initial HI and are slowly converting it into stars as is
suggested by the large (or negative) $\tau$ values.  As galaxies pass
the threshold for disk stability, their star formation becomes
sporadic and there is a clear dispersion in the colors due to
variations in burst age, burst strength and superimposed emission
lines.  The idealistic Bruzual and Charlot models are likely only
loose guides for these systems, as their star formation histories no
longer follow smooth exponential functions.

Figure \ref{bc1} indicates that there are a few galaxies in the regime of exponentially increasing SFR (negative $\tau$ values).  This is not surprising as there are few mechanisms that will increase the SFR of a galaxy.  The likely culprit for these systems is the infall of gas.  As gas is accreted, the gas densities in the galaxies will increase and local gravitational collapse will become more efficient.  This will increase the SFR as well as the eventual metallicity of the galaxy, pushing its $g-r$ colors to the blue (more recent star formation) and its $r-i$ colors slightly to the red (more metals).

We also showed that HI selected galaxies are offset from the SDSS galaxy locus, especially at the red end, and that this is likely due to bursts of star formation in the past few hundred Myr.  The gas that induces these recent bursts is not primordial and is best explained by the accretion of gas rich dwarfs.

The bluest galaxies in the ES/SDSS sample are not explained by population synthesis models alone.  Their colors can be modeled only with the inclusion of emission lines.  We showed that emission line spectra with reasonable SFRs can explain the colors of the bluest galaxies in our sample.

We also showed that the distribution of galaxies at the red end of the
color-color locus has a very small dispersion that continues to rise
into the blue regime. This change in dispersion appears to correlate
with stellar mass, rotation velocity, surface brightness and
especially stellar surface density. It is possible that the change in
dispersion is evidence for a significant change in the way stars form
in galaxies at a given mass scale.  Massive galaxies have unstable
disks and efficiently convert most of their primordial reservoirs of
gas into stars in the first few Gyrs after their formation.  These
galaxies are bulge dominated and have redder, older and more massive
populations of stars.  We do see a sharp transition in the color
distribution at a rotation velocity of 80 km~s$^{-1}$.  This
transition may be related to previous results that have found sharp
transitions in galaxy properties as a function of rotational velocity
(Dalcanton et al.~2004; Lee et al.~2007).  However, further
investigations are required to explore the various velocity
transitions as a function of galaxy properties.

It may also be the case that the increase in dispersion is nothing
more than a selection effect related to the surface brightness. As the
surface brightness of a system decreases, the effect of a single burst
of stars on the color becomes increasingly large, possibly explaining
the increase in scatter.  This effect might explain the onset of
emission line dominated colors in the bluest galaxies as they can
influence of the colors of galaxies devoid of massive stellar
populations.

We note that the change in color dispersion is not easily seen in the
volume selected SDSS data.  Applying the HI selection identifies a low
dispersion subsample of the SDSS galaxies, most notably at the red
end.  As mentioned above, the red HI selected galaxies appear to be
bluer in $g-r$ than the ``main'' SDSS sample. These two features are
likely related.  It is possible that the large distribution in color
at the red end of the SDSS main sample is due to the diversity of gas
content.  Because most of the red galaxies in SDSS exhausted their
original supply of gas long ago, this dispersion may be an indication
of the spread in time since the last major gas infall.  We leave
further discussion of the ``color offset'' to future study.

\section{Acknowledgments}
AAW and JJD acknowledge the support of NSF grant 0540567, the Royalty
Research Fund, and ADVANCE. AAW also acknowledges support from the
Astronaut Scholarship Foundation. JJD was partially supported by the
Wyckoff Faculty Fellowship.  Many thanks are extended to the anonymous
referee for his/her many useful suggestions for improving this
manuscript. The authors would like to thank Mike Blanton, Marla Geha,
Beth Willman, Paul Hodge, Suzanne Hawley, Tom Quinn, Peter Yoachim,
Anil Seth, and Vandana Desai for useful discussions while completing
this project.  We also thank John Bochanski for technical assistance
and Adam Burgasser for his financial support and insistence that this
project reach completion.

Funding for the Sloan Digital Sky Survey (SDSS) and SDSS-II has been
provided by the Alfred P. Sloan Foundation, the Participating
Institutions, the National Science Foundation, the U.S. Department of
Energy, the National Aeronautics and Space Administration, the
Japanese Monbukagakusho, and the Max Planck Society, and the Higher
Education Funding Council for England. The SDSS Web site is
http://www.sdss.org/.

The SDSS is managed by the Astrophysical Research Consortium (ARC) for
the Participating Institutions. The Participating Institutions are the
American Museum of Natural History, Astrophysical Institute Potsdam,
University of Basel, University of Cambridge, Case Western Reserve
University, The University of Chicago, Drexel University, Fermilab,
the Institute for Advanced Study, the Japan Participation Group, The
Johns Hopkins University, the Joint Institute for Nuclear
Astrophysics, the Kavli Institute for Particle Astrophysics and
Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences
(LAMOST), Los Alamos National Laboratory, the Max-Planck-Institute for
Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New
Mexico State University, Ohio State University, University of
Pittsburgh, University of Portsmouth, Princeton University, the United
States Naval Observatory, and the University of Washington.

\bibliographystyle{apj}

redpajama_set_name: RedPajamaArXiv


text:
Sandwich bread
Walter Sands' Favorite Bread Machine Bread
114 Reviews 4.7 out of 5 stars
This bread may be prepared and baked right in the machine (1 1/2-pound or larger models), or prepared in the machine, then removed, shaped, given a final rise and baked in a conventional oven. Either way, it's a good, down-to-earth white sandwich bread.
This is a variation on a recipe from Walter Sands, one-time president and owner of the King Arthur company. A member of just one of the many generations of the Sands family associated with the business, Walter made this bread faithfully once a week for years. Because of his arthritic hands, he used a bread bucket with a crank, which kneaded hundreds of loaves of this fragrant, soft sandwich bread with all its happy associations. We've modified Walter's recipe here for use in a bread machine.
1 loaf
1 1/4 to 1 1/3 cups (283g to 301g) lukewarm water, depending on the time of year (more in the winter, less in the summer)
1 heaping tablespoon (21g) honey or 1 heaping tablespoon (15g) granulated sugar
1 1/2 teaspoons instant yeast
1/3 cup (37g) Baker's Special Dry Milk or nonfat dry milk
2 tablespoons (28g) butter
2 teaspoons (12g) salt
Place the ingredients in your bread machine in the order recommended by the manufacturer, and program the machine for white or basic bread, or for the dough cycle. Press Start.
If you're using the dough cycle, after the cycle is complete, allow the dough to continue to rise in the machine until it's doubled in bulk.
Remove the dough, shape it into a loaf, and place it in a 9" x 5" loaf pan. Let it rise until almost doubled.
Bake the bread in a preheated 350°F oven for 35 to 40 minutes. Cool, and offer to a friend.
Peter Reinhart's Super Sprout Bread
Honey Oatmeal Bread
King Arthur's 100% Whole Wheat Sandwich Bread
Artisan Hearth Bread
SAF Red Instant Yeast - 16 oz.
4.9 out of 5 stars 1825 Reviews

redpajama_set_name: RedPajamaCommonCrawl


text:
Artificial nanostructures lead to breakthrough in creating invisibility cloaks, stealth technology
(Nanowerk News) Controlling and bending light around an object so it appears invisible to the naked eye is the theory behind fictional invisibility cloaks.
It may seem easy in Hollywood movies, but is hard to create in real life because no material in nature has the properties necessary to bend light in such a way. Scientists have managed to create artificial nanostructures that can do the job, called metamaterials. But the challenge has been making enough of the material to turn science fiction into a practical reality.
The work of Debashis Chanda at the University of Central Florida, however, may have just cracked that barrier. The cover story in the March edition of the journal Advanced Optical Materials ("Materials Selections and Growth Conditions for Large-Area, Multilayered, Visible Negative Index Metamaterials Formed by Nanotransfer Printing"), explains how Chanda and fellow optical and nanotech experts were able to develop a larger swath of multilayer 3-D metamaterial operating in the visible spectral range. They accomplished this feat by using nanotransfer printing, which can potentially be engineered to modify surrounding refractive index needed for controlling propagation of light.
"Such large-area fabrication of metamaterials following a simple printing technique will enable realization of novel devices based on engineered optical responses at the nanoscale," said Chanda, an assistant professor at UCF.
The nanotransfer printing technique creates metal/dielectric composite films, which are stacked together in a 3-D architecture with nanoscale patterns for operation in the visible spectral range. Control of electromagnetic resonances over the 3-D space by structural manipulation allows precise control over propagation of light. Following this technique, larger pieces of this special material can be created, which were previously limited to micron-scale size.
By improving the technique, the team hopes to be able to create larger pieces of the material with engineered optical properties, which would make it practical to produce for real-life device applications. For example, the team could develop large-area metamaterial absorbers, which would enable fighter jets to remain invisible from detection systems.
Source: University of Central Florida


Bloomberg's Global Data division, our technology drives our business. The tools we create and the software we design will allow us to meet the evolving data needs of our clients and enable us to drive our products.
We are looking for talented individuals that possess a unique combination of business acumen, technical skills, domain knowledge, and interpersonal skills that will analyze business needs and utilize technology for increasing automation, improving data quality, and reducing time to market.
Through process analysis they will discover opportunities, define requirements, and implement new technology components. In the ETL Data Analyst/Engineer role you will collaborate with other data teams, core business managers and engineers to develop and deliver these cross-cutting technical solutions.


text:
St. Joseph, MO Police
Search for Police Arrests in St. Joseph City, Missouri. Results may include: Booking #: Mugshot, Age: Gender: Race: Arresting Agency: Booking Date: Charges: Bond:
St. Joseph, Missouri Jail and Mugshot Information
St. Joseph, Missouri, is a city located near the border of Missouri and Kansas, and it has a population of 76,442 people. St. Joseph is located in Buchanan County. St. Joseph has a council-manager form of government. The Mayor of the city is Bill McMurray. The City Manager is J. Bruce Woody.
City of St. Joseph
1100 Frederick Ave.
St. Joseph City Website
Bill McMurray, Mayor
bmcmurray@stjoemo.org
J. Bruce Woody, City Manager
bwoody@stjoemo.org
For the year 2016, St. Joseph had a crime index of 477.1, which is higher than the United States national crime index of 278.0. During that year, there were 7 murders, 49 rapes, 104 robberies, and 268 assaults. There were also 749 reported burglaries, 3,221 reported thefts, 576 reported auto thefts, and 13 reported arsons. As of January 2019, there were 305 registered sex offenders living in St. Joseph.
In the year 2016, there were 5,584 crimes reported in St. Joseph, which gave the city a crime rate of 7,306 per 100,000 persons. This is higher than the Missouri state crime rate of 3,364 per 100,000 persons and the United States national crime rate of 2,745 per 100,000 persons. Property crime was the most common crime in St. Joseph.
St. Joseph, Missouri Police Station Information
The St. Joseph Police Department is located on Faraon Street, and the Chief of Police is Chris Connally. Divisions within the department include administration, patrol, detectives, support services, and traffic.
St. Joseph Police Department
501 Faraon St
St Joseph, MO 64501
St. Joseph Police Dept
St. Joseph Police Facebook
Chris Connally, Chief of Police
cconnally@stjoemo.org
Active warrants for St. Joseph Police Department can be viewed online.
St. Joseph Docket and Warrants
Inmates are held at the Buchanan County Jail, which is located on St. Joseph on the property with the Buchanan County Sheriff's Office. The jail can house 224 inmates. Visitation with inmates is on Saturday and Sunday, from 9 am to 12 pm and from 1 pm to 5 pm. Visitation appointments must be made in advance. Each inmate is allowed one 20-minute visitors per visitation day.
Buchanan County Jail
Buchanan Corrections Division
Police Records Requests in St. Joseph, Missouri
Police records may be requested from the Records Unit.
St. Joseph Records Unit


text:
Q: How to recognise a song by listening using Echonest for iOS? I want to implement a functionality similar to the one integrated in Shazam app. I want my app by pressing to a button to "listen" for a song and after some time to "guess" the song or give some predictions using Echonest api for iOS. I was searching the web and so far I've learned the I need to send the fingerprint to the Echonest server and give me response with the song info. But somewhere I've read that that functionality will be no more available. Also tried to upload the whole mp3 file to their server and the response is always an empty one. Does anyone has experience with this issue and tell me where I'm wrong?
I've used echoprint but no success.

redpajama_set_name: RedPajamaStackExchange


In 2014 I was invited to participate in Adobe System's "Random Acts of Creativity" campaign as one of a few selected artists to create a site-specific temporary installation. The final project, using over 2500 photographs pinned to thirty individual boards, was assembled and installed over six days on-site.
I shot all of the photographs over a four month period in my studio using a mountain of stockpiled materials. For the installation itself, no preliminary drawings were created, rather a carefully orchestrated process was put into action. Everything was chosen and built on the spot. I was hoping to create a sensation that felt like the sober architecture was put through a fantastic kaleidoscope, and judging by the enthusiastic reaction, I succeeded.
A visitor cannot see all fifteen columns in a single glance since they bend around the facade, and so the journey reveals its delights slowly, inviting pedestrians to look up from their phones and inspect the details. Although the installation was only up for six days in June, I used my complete photographic record to begin my photo construction series.


A three-week expedition off the coast of Costa Rica has just expanded our knowledge of deep sea ecosystems in the region.
What do you do when you have too much data?
Radiotelemetry is the use of tiny radio transmitters, worn by animals, which emit radio waves that can be detected several hundred meters away.
If you've ever walked past a bee's nest on a hot summer day, you've probably been too focused avoiding getting stung, rather than stopping to wonder how all those bees stay cool.


text:
Call our office at 866-849-2536 to schedule a speaker from WFA or WFC for your next event!
EARLY VOTING for Spring Nonpartisan Elections
WFC Launches 2022 Community Events!
"YOUR BACKYARD: OWN IT!"
Elkhorn Community Center
Elkhorn, WI
SPRING PRIMARY ELECTION
LEAD WI
REGISTRATION OPENS
LEAD WISCONSIN
Hey, teens! Reserve your spot HERE!
If you're 19+ and want to invest in the next generation, contact us HERE!
Equipping teens to become effective godly leaders who engage the culture
from a Biblical perspective.
2020-2021 Legislative Directory
your FREE copy today!
Responding to the Transgender Issue:
Parent Resource Guide
Are you struggling to find the right words to help your child navigate transgender issues?
If so, "The Parent Resource Guide" was written with you in mind!
It is a carefully researched resource providing parents with practical ways to address the transgender issue with their children.
Grab your free copy HERE.
Call our WFC office at 888-378-7395 to obtain a print copy for a suggested donation of $5.
It is the mission of Wisconsin Family Action to advance Judeo-Christian principles and values in Wisconsin by strengthening, preserving, and
promoting marriage, family, life and religious freedom. Our vision is a Wisconsin where God is honored, families thrive, human life is cherished
and religious freedom flourishes.
CLICK here to invest in your family, faith, freedom and future!
Because of our desire to serve and help families, our ministry is making resources available that can be useful in creating a wise giving plan.
Click HERE for more information on how you can significantly impact the Kingdom while strengthening and building families.
What You Need To Know About School Choice in Wisconsin
Pro-Life Legislation and License Plates
Ballot Drop Boxes & An Endorsed Gubernatorial Candidate
National School Choice Week is this week. Wisconsin is a national leader in school choice, being the first state to offer a voucher program for income-eligible families. That program began in Milwaukee and has now expanded to Racine and the entire state. At least one school in the voucher program now offers a virtual voucher option. Other educational choices include homeschooling, with one of the best homeschool laws in the country, open enrollment, and public charter schools that are independent from the typical school district board.
Julaine Appling, president of Wisconsin Family Action and Wisconsin Family Council, encourages parents to take this week to look into the best possible options for their children's education: "The education of children is vitally important. Who educates a child, where he or she is educated, and what is taught in both academics and beyond matters—and matters greatly. It behooves parents who are interested in exploring Wisconsin's educational options to get the information early, ask questions, visit schools, and certainly pray, asking God for wisdom and direction as they consider what is best for their children."
More details are available HERE. Registration windows for several options open in early February.
Earlier this week, state Senator Julian Bradley (R-Franklin) and state Representatives Donna Rozar (R-Marshfield) and Calvin Callahan (R-Tomahawk) began circulating for legislative cosponsors a bill similar to the Texas Heartbeat law in that it would prohibit abortions once the heartbeat of an unborn child is detected. Nearly 50 years after the horrific and wrongly decided Roe v. Wade, we have technology that clearly shows even very early in a pregnancy that this is a human life, not just a mass of cells. Ultrasounds allow mothers to hear an unborn baby's heartbeat as early as six weeks. We are grateful for the bold steps these legislators are taking on behalf of unborn life.
On that note, as we observe Sanctity of Life Month, we need to mention the Choose Life Wisconsin license plates that are available. Right now, over 2,100 of these unique plates are on the road. The tax-deductible $25 a year fee goes to Choose Life Wisconsin and is then distributed as grants to Wisconsin's pregnancy care centers to help them in their work to encourage women to either keep their babies or put them up for adoption rather than have an abortion. Pictured left is our Executive Vice President, Micah Pearce, presenting Anchor of Hope with a check made possible by the Choose Life Wisconsin donations! Wisconsin Family Council partners with Pro-Life Wisconsin on this program.
Julaine Appling briefly explains the value of Choose Life Wisconsin, saying, "Since May of 2018, Choose Life Wisconsin has distributed over $150,000 to more than 30 Wisconsin pregnancy care centers. These centers are the very best pro-life ground game we have, as they offer real help to men and women, as well as work hard to save babies. As president of Choose Life Wisconsin, I can say we are honored to be part of this effort."
Learn more about the proposed legislation HERE and HERE. Get your own Choose Life Wisconsin license plate HERE.
WISN reported earlier this week that, "An appeals court has ruled voters can use ballot drop boxes for Wisconsin's February primary." It's important to note that this ruling "stays Waukesha County Circuit Judge Michael Bohren's order from earlier this month banning ballot drop boxes."
While this news can be discouraging in the wake of our state and nation wrestling with election integrity, remember that the surest way for someone elected who doesn't share your values to be elected is to NOT vote. At the end of the day, we don't "wrestle against flesh and blood, but against principalities, against powers, against the rulers of the darkness of this age, against spiritual hosts of wickedness in the heavenly places" (Ephesians 6:12). And better yet, the God we serve is the God "who goes with you, to fight for you against your enemies, to save you" (Deuteronomy 20:4).
In regard to elections, we would be remiss to not mention that Wednesday afternoon Wisconsin Family Action Political Action Committee (WFA PAC) endorsed Rebecca Kleefisch for governor. Julaine Appling, WFA PAC Director, commented, "WFA PAC is proud to endorse Rebecca Kleefisch for governor of Wisconsin. Rebecca has a solid conservative track record. She understands and is committed to strengthening, preserving, and promoting Wisconsin's best natural resource—her families. Supporting economic growth through job creation and a commitment to reducing the tax burden are proof-positive that Rebecca understands that when Wisconsin's families are strong and independent, Wisconsin is strong."
Additional endorsements for the fall elections will be coming out over the next several months.
WEEKLY RADIO COMMENTARY. "WISCONSIN FAMILY CONNECTION" – Airing this week on over 20 stations statewide. Click HERE to listen to this week's Wisconsin Family Connection, "School Choice Knowledge — It's Powerful!" Read the complete radio commentary HERE. Subscribe to our podcasts HERE!
ARCHIVED:
Week of January 17, 2022 – Impacting Election Consequences
Week of January 10, 2022 – Proclaiming the Sanctity of Human Life
Week of January 3, 2022 – A Rare Supreme Court Session
"WISCONSIN FAMILY MINUTE"
A daily program for Christian radio stations! Click HERE for our daily program; listen or download! Click HERE to subscribe to your Wisconsin Family Minute podcasts! Find your local station HERE. If the Christian radio station you listen to isn't carrying "Wisconsin Family Minute," please encourage them to do so. Contact us at 866-849-2536 or info@wifamilycouncil.org.
HOME FRONT – VCY AMERICA
WFC President Julaine Appling, joined by WFC Exec VP Micah Pearce, hosts VCY America's "Home Front" program every Wednesday afternoon (Sept.-May) at 3:15 p.m. CLICK HERE to listen to the archived episodes. On this week's program, Julaine and Micah announce a new series of WFC's community events, talk School Choice, and give some legislative updates, including the introduction of Wisconsin's version of a heartbeat bill and wrap up with an election reminder. Click HERE to listen to this week's program.
VCY AMERICA TV30 "InFocus"
Julaine Appling, WFC president, is a regular guest (one Monday per month) on VCY America's TV 30 "InFocus" live, call-in program with Jim Schneider which airs on Monday evenings from 7:00-8:00 p.m. (Sept. through May). Click HERE to watch archived episodes. Livestream "InFocus" HERE. Julaine joined Jim Monday, January 10, 2022. Watch the show HERE. Her next appearance on InFocus will be Monday, February 14, 2022, at 7 p.m.
STAND UP FOR THE TRUTH – Q90FM
Julaine Appling is an occasional guest on Q90's "Stand Up for the Truth" program hosted by David Fiorazo (9-10 a.m., M-F). Julaine most recently joined David on Tuesday, September 21, 2021. Listen in HERE. Listen to the previous Julaine's most recent appearance on the podcast, Monday, November 22, HERE. Julaine's next appearance is scheduled for February 10 at 10 A.M.. You can tune-in live HERE.
–WFA's president Julaine Appling is available to speak to your group, church, school, civic organization, and other events. Call 866-849-2536 to schedule.
–Dave Lingle, Wisconsin Family Council's Director of Church Relations, is available to speak in churches. Call 920-342-1928 for more information.
Wisconsin Family Action is your voice for marriage, family, life and religious liberty in The Badger State.
Partner with us today!


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Mother-Child Photo Contest
Standard-Deviations
National Commentary
Beyond Bars
Extra Point
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Ogden Raptors
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Jail-Mugs
Ogden, UT (84404)
A mix of clouds and sun during the morning will give way to cloudy skies this afternoon. High 39F. Winds ESE at 10 to 15 mph..
Cloudy skies. A few flurries or snow showers possible. Low 33F. Winds SE at 5 to 10 mph.
Connie Schultz (new)
Schultz: Trump brays, and the congregation cheers
By Connie Schultz
The day after he ordered the strike that killed Iran's Maj. Gen. Qassem Soleimani, President Donald Trump showed up at an evangelical church in Miami to cast himself as a modern-day savior of Christianity.
This may be a bit confounding for those of you who remember that Trump rarely visited a church during the 2016 campaign, and when he did in Council Bluffs, Iowa, he pulled dollar bills out of his pocket when the communion plate passed his way. Well, look, if you're going to dwell on all that, you are never going to be invited to join Trump's newly founded Christian Church of Campaign Convenience.
Many of us find attending church to be a humbling endeavor. The sanctuary is a place where we can confess our sins to God, pass the peace of Christ, and reflect how, to quote my late mother, we can fix ourselves and help others.
Trump is having none of that. He doesn't even try to fake humility. For an hour, he stood before the Ministerio Internacional El Rey Jesus congregation, which repeatedly cheered "four more years," and brayed about how he has snatched Christianity from the jaws of the Christian-eating monster lurking somewhere out there where only he can see it, apparently.
"Evangelical Christians of every denomination and believers of every faith have never had a greater champion, not even close, in the White House, than you have right now," he said. "We've done things that nobody thought was possible. Together we're not only defending our constitutional rights. We're also defending religion itself, which is under siege."
For nearly two decades, I've been writing about this mythical religious persecution of Christians in America. Not one day in all of my years of practicing my Christian faith have I felt the least bit unsafe in doing so. The only ones attacking my Christianity are the far-right Christians who wield God as a weapon. They've produced some of the most hateful mail of my career.
Meanwhile, our Jewish brothers and sisters are increasingly endangered by right-wing extremists in this country. The president doesn't like to talk about that part of being Jewish in America. He did, however, offer this anti-Semitic take at a gathering of the Israeli American Council in Hollywood, Florida — almost a month to the day before he spoke to evangelicals:
"You're not going to vote for the wealth tax. Yeah, let's take 100 percent of your wealth away. No, no. Even if you don't like me — and some of you don't; some of you, I don't like at all, actually — and you're going to be my biggest supporters because you'll be out of business in about 15 minutes."
That's some Christianity Trump is peddling.
Let's end on a better note.
In this time of crisis in our country, I am forever seeking signs of hope. So often, I find them where I least expect. Last week, it was at the Grand Ole Opry in Nashville, Tennessee.
I grew up with country music, and still sing along to it, especially when I'm cooking. I've been wanting to form my own all-girl country music band since December 1963, when my grandma gave my little sister and me matching cowgirl outfits. I am always surfing my hate mail for possible band names. So far, Feral Feminists remains my favorite. Don't tell me a girl can't dream.
Anyway, there I was, sitting next to my husband on a crowded pew in the balcony of the Ryman Auditorium. The place was packed with white people who came to hear two hours and 15 minutes of country music at its best, from Tenille Arts and Dillon Carmichael, to Connie Smith and Joe Mullins & The Radio Ramblers.
A little after 9 p.m., the final act strolled onto the stage. The McCrary Sisters, a black gospel group, stepped up to four mics. They blew the roof off with "Amazing Grace."
They were the only black singers at the Grand Ole Opry on Jan. 3, and they got the only standing ovation of the night. In Nashville, Tennessee.
Every time I think about that, I smile.
Connie Schultz is a Pulitzer Prize-winning columnist and professional in residence at Kent State University's school of journalism. She is the author of two non-fiction books, including "...and His Lovely Wife," which chronicled the successful race of her husband, Sherrod Brown, for the U.S. Senate. Her novel, "The Daughters of Erietown," will be published by Random House in Spring 2020.
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Former McKay-Dee, Davis Hospital nurse sentenced to prison for stealing meds, spreading Hepatitis C
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Roy plane crash victim, operator of Ogden ski firm, contributed to industry, city
Ogden to finally get look inside 1887 time capsule found in old Ogden school
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Steven A. Porter
Logan restaurant owner given probation after admitting to forging checks, avoiding paying employees
1 man dead after being caught in avalanche up Farmington Canyon
Ogden doling out new money for arts, looking to inform interested artists
PHOTOS: Fremont wrestles Layton High
BEN DORGER, Standard-Examiner
Fremont High wrestles Layton High on Wednesday, Jan. 8, 2020, at Layton High School.
Diesel Brothers' lawyer assails attorneys' fees desired by environmental group
Weber State basketball readies for Portland State's pressure
From the Community: How the United Way of Northern Utah hopes to solve complex community problems
Ogden officials prepare for Census Bureau count, events to be held to get word out
Sen. Christensen won't run again, 3 others launch bids for District 19 seat
Utah lawmakers serving Weber County to take part in public forum in West Haven
Mobile preventive dental care clinics reach kids where they are — school
State will realign road at Pineview Dam to protect against falling rocks
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text:
Yaletown Condos
HANI FARAJ
info@vancouverhousefinders.com
VANCOUVER HOUSE FINDERS TEAM
TRG - THE RESIDENTIAL GROUP REALTY
1965 W 4th Ave
Vancouver, BC V6J 1M8
How Do You Prepare for an Open House?
By Hani Faraj 11/10/2020
Q: What Happens After the Inspection?
Harvey Bains
The Jack Of All Trades.
Talk about a "Jack of all trades", starting out as a meat cutter Harvey moved on to be a manager, to sales, to his final adventure as a REALTOR®. At just the age of 13, Harvey already had started to learn basic customer service skills at their family owned and operated business. At the age of 28 Harvey had opened up his own wholesale company and as a one man company took it from $0 to $800,000 in sales in just one year. Believing in building long-term relationships instead of sales has helped him strive in any professional field he has entered.
With his new journey as a REALTOR®, you the customer will realize right after the first meeting that he is there from start to finish with a commitment to provide the utmost respect and service to his clients. Harvey makes your buying or selling experience as comfortable as possible.
Get in touch today to begin your new adventure and be prepared to be amazed.
Was concerned about what I wanted and finding the right place for me at the right price.
Jordan Smith (Buyer)
Harvey, through his website, introduced us to an apartment that we eventually made an offer. Throughout the process, Harvey has proved himself as an excellent broker, friendly, patient and eager to please and be of service and to meet all our request.
We have not hesitation of having him again as our Agent should we in future be looking to buy any other house.
We would also have no hesitation recommending him to our relatives and friends.
Michael Chin (Buyer)
Harvey treats my funds as though they were his,meaning negotiated contracts with personal interest in obtaining best pricing for us in our purchase.We are now selling a property with Harvey, being our third deal with him,we continue to be extremely satisfied with his level of service.
Paul and Janine Levasseur, White Rock Bc (Buyer)
Can't say enough good things,we are extremely happy! Wouldn't use anyone else. Truly professional!
Paul and Janine Levasseur (Seller)
Harvey Bains was by far the best realtor I have dealt with to date. He was very proffesional and attentive to detail. I would definetly recommend Harvey to all my family and friends.
Bobi Bhangu, Kelowna (Buyer)
Harvey Bains Testimonials
Harvey was extremely knowledgeable and reliable. As first time buyers, he was very helpful in using our budget to help us find the property we were looking for. Harvey went above and beyond to help us finalize our purchase. I have recommended Harvey to several colleagues and they have all had the same positive experiences with him. We can't thank him enough
Harvey is very personable and professional. These qualities made it very easy for us to work with him and trust him when purchasing our home.
Kuljit Bhullar, Surrey BC (Buyer)
Harvey Bains was a pleasure to work with, always going above and beyond for us. Harvey was punctual, professional and knowledgeable. He has great attention to detail and always made the selling/showing process as easy as possible for our family. He even brought us moving boxes and offered to help us pack. Thank you so much Harvey!
Kali Collins, South Surrey (Seller)
We we're in the process of looking to purchase a restaurant but we don't know anybody we can trust, luckily Harvey told us he can help us do the purchase. He did an excellent job despite of us not being here in Vancouver in the first few weeks of purchase. He always inform us of anything that is going on about the market and find the best option for us.
Christian Geremia, Vancouver (Buyer)
Harvey followed up with us and showed genuine interest in our needs. Like most people, when you're buying a new home you're quite anxious and Harvey worked with us through all of our demands.
James Jesney, Vancouver, BC (Buyer)
Harvey is an agent I would recommend to anyone! He was so knowledgeable and professional. His determination in selling our condo was admirable. He often went above and beyond for us- spending as much time as we needed: answering questions and weighing out our options in a clear and concise manner. His down to earth personality put us at ease and helped us make the right decisions for our family. We were so pleased to have worked with him. Harvey was professional, ever timely, literally tireless, knowledgeable of his market, and well connected to the people of his trade. He was immensely positive to deal with, and made what could have been a stressful nightmare into a fun adventure - with a great outcome. Thank you Harvey!
Kuljeet Sandhu, Langley, BC (Seller)
Our experience with Harvey Bains was nothing but exceptional. He was on time for all meetings,looked after all our requests, followed up on all problems (generally arising from other realtor)negotiated as if it was his funds and still shows genuine concerns on our well being. The property we purchased was monitored by Harvey to cover all the legal and physical aspects of the sale. When my wife and I decide to sell our current home only Harvey will get the listing.Thanks again!
Paul and Janine Levasseur
Vancouver Properties
BY Hani Faraj
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