COLERAIN TOWNSHIP, Ohio, March 19, 2014 (ENS) – Hazmat crews are cleaning up about 10,000 gallons of crude oil that spilled from a broken underground pipeline into an Ohio nature reserve Monday night.
The oily mess has affected close to one mile of a creek running through the Oak Glen Nature Preserve. Crews are vacuuming up the oil that covers the surface of a pond, but Steven Renninger of the US EPA says it could take more than a week before cleanup at the Hamilton County park is complete.
Renninger says the oil is being vacuumed up by truck-mounted equipment and placed in holding tanks for later disposal. After the pond is cleaned, crews will remove oil on the creek bed.
The damaged pipe is part of the Sunoco Logistics crude oil interstate pipeline operated by Mid-Valley Pipeline Co. Both companies are subsidiaries of Sunoco, an American oil company based in Pennsylvania. The 1,100 mile pipeline starts in Longview, Texas and ends in Samaria, Michigan, about 12 miles north of Toledo, Ohio.
The Colerain Fire Department responded to reports of a oil smell at about 8 pm Monday. They found "petroleum product" in the Oak Glen Nature Preserve near Blue Rock Road.
It took more than five hours before a Mid-Valley Pipeline crew was able to shut down the line. By early Tuesday morning crews had contained the leak and began repair work on the 20-inch pipeline.
The pipe was laid in the mid-1950s, before the land was identified as one of four conservation areas owned and operated by Great Parks of Hamilton County.
The Ohio Department of Transportation began investigating today but officials have yet to pinpoint the cause of the pipeline break.
The cause the leak is under investigation by the U.S. Environmental Protection Agency and the Ohio Environmental Protection Agency.
It is the 40th leakage or spillage incident since 2006 along this pipeline, according to the U.S. Department of Transportation's Pipeline and Hazardous Materials Safety Administration.
"As drilling increases in Ohio, so too will the burden on infrastructure to transport these products to market, often overseas. With the increase in pipelines cutting through our preserves and farmland, comes a greater risk of future spills and leaks.
"Our thoughts are with those impacted by Monday's leak, and it is our hope that damage to drinking water can be avoided," Auciello said.
The Great Miami River, about a quarter of a mile away, appears to have been spared, although tests are not yet complete, says a spokesperson for the Ohio Environmental Protection Agency.


On the death of Edward the Confessor the throne of England was claimed by William, Duke of Normandy.
When Edward took refuge in Normandy after the Danes conquered England, he stayed at the palace of William. He was very kindly treated there, and William said that Edward had promised in gratitude that William should succeed him as king of England.
One day in the year 1066 when William was hunting with a party of his courtiers in the woods near Rouen, a noble came riding rapidly toward him shouting, "Your Highness, a messenger has just arrived from England, bearing the news that King Edward is dead and that Harold, the son of Earl Godwin, has been placed on the English throne."
William at once called his nobles together and said to them, "I must have your consent that I enforce my claim to England's throne by arms."
The barons gave their consent. So an army of sixty thousand men was collected and a large fleet of ships was built to carry this force across the channel.
During the months of preparation William sent an embassy to the English court to demand of Harold that he give up the throne. Harold refused.
Soon all England was startled by the news that William had landed on the English coast at the port of Hastings with a large force.
Harold immediately marched as quickly as possible from the north to the southern coast. In a week or so he arrived at a place called Senlac nine miles from Hastings, in the neighborhood of which town the Norman army was encamped. He took his position on a low range of hills and awaited the attack of William. His men were tired with their march, but he encouraged them and bade them prepare for battle.
On the morning of October 14, 1066, the two armies met. The Norman foot-soldiers opened the battle by charging on the English stockades. They ran over the plain to the low hills, singing a war-song at the top of their voices; but they could not carry the stockades although they tried again and again. They therefore attacked another part of the English forces.
William, clad in complete armor, was in the very front of the fight, urging on his troops. At one time a cry arose in his army that he was slain and a panic began. William drew off his helmet and rode along the lines, shouting, "I live! I live! Fight on! We shall conquer yet!"
The battle raged from morning till night. Harold himself fought on foot at the head of his army and behaved most valiantly. His men, tired as they were from their forced march, bravely struggled on hour after hour.
But at last William turned their lines and threw them into confusion. As the sun went down Harold was killed and his men gave up the fight.
From Hastings William marched toward London. On the way he received the surrender of some towns and burned others that would not surrender. London submitted and some of the nobles and citizens came forth and offered the English crown to the Norman duke.
On the 25th of December, 1066, the "Conqueror," as he is always called, was crowned in Westminster Abbey by Archbishop Ealdred. Both English and Norman people were present. When the question was asked by the Archbishop, "Will you have William, Duke of Normandy, for your king?" all present answered, "We will."
At first William ruled England with moderation. The laws and customs were not changed, and in a few months after the battle of Hastings the kingdom was so peaceful that William left it in charge of his brother and went to Normandy for a visit.
While he was gone many of the English nobles rebelled against him, and on his return he made very severe laws and did some very harsh things. He laid waste an extensive territory, destroying all the houses upon it and causing thousands of persons to die from lack of food and shelter, because the people there had not sworn allegiance to him.
He made a law that all lights should be put out and fires covered with ashes at eight o'clock every evening, so that the people would have to go to bed then. A bell was rung in all cities and towns throughout England to warn the people of the hour. The bell was called the "curfew," from the French words "couvre feu," meaning to cover fire.
To find out about the lands of England and their owners, so that everybody might be made to pay taxes, he appointed officers in all the towns to report what estates there were, who owned them, and what they were worth. The reports were copied into two volumes, called the "Domesday Book." This book showed that England at that time had a population of a little more than a million.
William made war on Scotland, and conquered it. During a war with the king of France the city of Mantes (mont) was burned by William's soldiers. As William rode over the ruins his horse stumbled and the king was thrown to the ground and injured. He was borne to Rouen, where he lay ill for six weeks. His sons and even his attendants abandoned him in his last hours. It is said that in his death struggle he fell from his bed to the floor, where his body was found by his servants.


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CASE at Curie: One school's experience with test trials
by Julie Siple July 26, 2005 August 15, 2016
As Chicago high schools prepared for the second round of CASE tests, Catalyst checked developments at Curie High School, whose scores on the Tests of Achievement and Proficiency (TAP) generally are a few points above citywide averages. The school system is developing the Chicago Academic Standard Exams to help ensure that teachers are teaching and students are learning the academic standards adopted by the Reform Board in 1997. The first tests, for second-semester freshman courses, were piloted last spring. Exams for first-semester courses for both freshmen and sophomores were piloted in January. Written by a dozen Chicago teachers, the exams eventually may count toward course grades and admission to special programs.
Four days into the post-holiday blizzard, Juan Troncoso's English teacher at Curie High School has not returned to school, and Juan, a freshman, is getting worried. He wants to prepare for the upcoming CASE exams, but isn't sure what to study.
"I'm just waiting for the teacher to come," says Juan. "Hopefully she comes Monday."
Teachers are uneasy, too.
All week, another English teacher Sarah Levine has been reviewing the board-assigned literature with her students, going over terms and working on analysis. But she isn't sure what they will find on the CASE. She's concerned that her students may not remember details of a text they read last quarter, but she is hopeful that the CASE will test higher-level thinking skills, the skills she feels she is supposed to be teaching. "I'm depending on them to focus on argument skills and writing skills—not just recall," she says.
Recalling the multiple-choice questions from the freshman tests piloted last spring, English Department Chair Vera Wallace sees the CASE pushing teachers away from higher-order thinking skills. If a large proportion of the questions ask students to recall facts or draw simple inference, she says, the test result won't show whether a student is capable of higher-level thinking. She worries that such an exam might encourage teachers to teach more facts and fewer skills.
For Curie, says Wallace, the challenge is incorporating the board-assigned texts into a thematic curriculum that stresses concepts like discrimination, and love and hate. That has been especially difficult at the freshman level, where texts range from Romeo and Juliet to The Pearl.
Philip Hansen, the board's chief accountability officer, notes that exams in every subject have "constructed-response" sections, which require students to write a short essay or explanation. He also says that once the underlying programs of study are in place, teachers will see they have time for other activities. "As teachers move along this process, they will find it doesn't take 40 weeks to teach the standards. There is that flexibility where teachers can do other work."
Up in Curie's Math Department, teachers have been going over practice tests in algebra and geometry all week, but not many are optimistic their students will do well. David Drymiller sits at his desk and shakes his head; he says the sample algebra test the board supplied is too hard. "Each problem is layered; each question tests five or six concepts," he explains. "If students miss one of those ideas, they don't know where to begin."
Telkia Rutherford, the board's manager of mathematics support, says that to improve student performance on the algebra exam, teachers need to develop an integrated curriculum that includes geometric concepts, probability and statistics.
Too difficult?
Margaret Small promotes just such a program, the Interactive Mathematics Program (IMP), but she, too, believes the sample algebra exam is too difficult. There are too many questions, and the equations are more complex than necessary to test each skill, she says. Developed with funding from the National Science Foundation, IMP is a four-year curriculum aimed at mixed-ability classes. "We've spent three months getting students talking, thinking, believing they can solve problems," she says. "Then they'll take this and think, 'I can't do math.'" Small believes that the exam should be designed like a driver's test, measuring basic skills without being tricky or complex.
Last spring, only 25 percent of CPS freshmen passed the test.
Accountability Officer Hansen attributes that to a numberof factors: The programs of study were still in draft form; the exams carried no value for students; the exams were given the last week of school. "This year teachers have a better understanding of the expectations," he says, adding that he expects better results.
In Curie's Social Studies Department, Robert Zell is up in arms. Zell, a World Studies teacher, contends the board has "shirked its duty on the CASE." He says it provided only a broad outline of the material to cover, a few sample questions and no inservice training. Plus, he says, he has only a history book while the board wrote a curriculum that goes beyond history. "I'm putting up an overhead and showing students the areas that will be on the test, and I'm telling them, we didn't cover this because sources weren't available."
Pushing their lunches aside, other social studies teachers say the outline the board provided has far too much material to cover in depth. Department Chair Raymond Garson agrees that the board should establish standards and help schools reach them. "But they need to focus more," he says. "What areas specifically are we going to cover?"
"There's always been a large amount of material," says Barbara McCarry, the board's coordinator of social science support. "We need to figure out what teachers used to cover that they are now skipping, and what they are now adding. Next year, we'll enter the new millennium. We'll have the whole 20th century to decipher."
Last spring, McCarry met with social studies teachers from across the city to get their reaction to the proposed course of studies. She said she'll have another meeting to review how the first semester went.
Last year, social studies teachers said that sophomores did not arrive with a good understanding of history before the Civil War; as a result, the sophomore curriculum now includes brief reviews of earlier material. Another result of McCarry's meeting with teachers is that World Studies takes a regional approach, and its exam gives students the option of writing on Africa or on Europe for each constructed-response question.
While Zell says he did not receive enough preparatory materials, the Office of Student Assessment says it sent a variety to every school. They included programs of study, a chart showing how many questions would be asked in each category and sample test questions. According to Hansen, a total of $850,000 was allotted to high schools for new textbooks this year.
Down in Curie's Science Department, the concern is that the exam will require too much intuitive and critical thinking. Chemistry teacher Steve Samuels says that many students do not arrive with the ability to think step by step through a problem. Yet he believes CASE may lead classes in the right direction. "It's difficult for our students to think intuitively," he says. "But hopefully, I'll see a question, and I'll think, 'I should have thought about teaching that way.'"
Once testing is under way, Samuels says he is pleased with the chemistry test. "It was well-written," he explains. "I was impressed." Although he is not yet sure how his students did, he says his class covered all the material that was on the exam.
Algebra teacher Drymiller says the exam was, as he expected, very difficult. He says terminology was a problem, too. He cites a question in which students were given an equation and asked to make it a "real life" problem, a direction many of his students didn't understand.
Zell is trying to determine how some of the questions on the World Studies exam connect to the program of study. "That's what we'll spend some of our common planning time doing," he says. "We'll figure it out so we're better prepared next time." He hopes the board will provide a study guide next semester.
Levine says that on the English test, the constructed-response question did require students to do some analysis. But she takes issue with how the question was asked, contending it wasn't clear to students what they were supposed to do. She says it also included words that students did not understand, such as "grapples."
With the testing winding down, teachers are beginning to think about the next step—grading. The board has assigned each school a time to bring the multiple-choice sections in for immediate scoring. Teachers should have the scores in time for first-semester grades, which must be recorded by Jan. 29, a five-day extension from the original date. This year, schools may decide how to use the results. At Curie, the Math Department has decided not to figure them into grades. The English Department is allowing each teacher to decide individually.
Schools are grading the constructed-response questions on their own, using rubrics, or guides, provided by the board. Teachers may grade their own students, an issue that the board has struggled with. While that raises questions of validity, says Hansen, it also allows teachers to see the strengths and weaknesses of their students. The grading rules may change once CASE counts for something, he adds.
At Curie, each department is deciding on its own how to organize the process. In the Math Department, Chair Maryann Blaszak plans to have each teacher select a question and grade it across all classes. "That way, no teacher will say, 'Well, I like Johnny Jones, and his answer is wrong, but I'm still going to give him a four,'" she explains. Blaszak set aside time on the testing days for grading, but she suspects teachers will not finish and may have to do it during free periods or take the work home.
Juan takes no chances
During the first pilot, the board did not require that teachers grade the constructed-response questions. As a result, according to Susan Ryan in the Office of Student Assessment, many of the tests were never graded.
As Catalyst goes to press, Curie teachers are still grading tests, and Juan Troncoso is waiting for his scores. Not all students are so concerned, he says. But a low score on the Iowa Tests of Basic Skills landed Juan in summer school last year, and he isn't taking any chances that a low score on CASE could send him back. This year, he wants a vacation.
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CASE closed, new exam in the works
In "Catalyst Chicago"
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redpajama_set_name: RedPajamaCommonCrawl


text:
Q: Group by one field with all values from the other If I have a table that has two fields (client, service) and lets say the table look like this:
client | Service
  1    |   A
  1    |   B
  1    |   C
  2    |   A
  2    |   D

I want to do a select statement that I can have all services from each client so the result would look like this
client  | Service
  1     | A, B, C
  2     | A, D

Is it possible in SQL? I am using oracle 10g

A: You can use listagg in this case -
select client,
       listagg(service, ', ') within group (order by service) as service
from the_table
group by client;

listagg can be used either as an aggregate function or as an analytic function.
Read more from here- link

redpajama_set_name: RedPajamaStackExchange


text:
\section{Introduction}\label{intro}
Galaxy masses are an essential link between theories for galaxy formation
and observations of the galaxy population and the evolution thereof.
In the local universe masses can be measured accurately by
modeling the luminosity distribution and the dynamical structure of galaxies
\citep[see, e.g.,][]{cappellari05}.
Scaling relations such as the fundamental plane for early-type galaxies
\citep{djorgovskidavis87,dressler87}
and the Tully-Fisher relation for spiral galaxies
\citep{tully77}
can be used to measure the evolution of the mass-to-light ratio ($M/L$)
from high redshift to the present
\citep{franx93}.
This technique has been applied successfully and has provided
constraints on the formation epoch of massive early-type galaxies out to $z\sim 1.3$
\citep[e.g.,][]{vandokkumstanford03}.

The number of galaxies with dynamically measured masses
at intermediate redshifts ($z\sim 1$) is small, because obtaining those is
observationally expensive. Furthermore, those samples are severely
hampered by selection effects
\citep[see][]{vanderwel05}. Therefore, it is not yet possible
to obtain directly the galaxy mass density at high redshift.
Also, even though the redshift at which dynamical masses can be measured
is steadily increasing, the most active era of galaxy formation, $z\ge 2$,
is not accessible in that respect with the current generation of instruments.
For all of these reasons, one has to rely on less accurate mass estimates to
construct a picture of the high-$z$ galaxy population
\citep{shapley03,papovich03,forster04,labbe05,shapley05}
and the evolution of the mass density with redshift
\citep{bell04b,drory04,faber05}.
In these studies, broadband photometry is compared with
predictions from stellar population models
\citep[most commonly,][]{bruzual03}
in order to constrain the physical properties of high $z$-galaxies, and
thereby their stellar masses.

However, the uncertainties in mass estimates obtained by fitting the spectral energy distributions
(SEDs) of galaxies are large. It is well-known that
parameters such as age, dust content and metallicity are degenerate,
leaving $M/L$ uncertain. The lack of knowledge of the stellar initial mass function (IMF)
leads to a (probably large) systematic uncertainty.
Comparisons of photometric mass estimates with dynamical mass measurements
are essential to establish their robustness and accuracy.
\citet{bell01} have shown that the optical colors of spiral galaxies
correlate well with their $M/L$.
At $z\sim 1$ \citet{vanderwel05} have demonstrated that optical
colors correlate well with dynamically determined $M/L$ for early-type galaxies.
These results suggest that full SEDs should provide good constraints
on masses and $M/L$.
\begin{deluxetable*}{lccccccccccc}
\tabletypesize{\scriptsize}
\tablecolumns{11}
\tablewidth{0pt}
\tablenum{1}
\tablecaption{Photometry}
\tablehead {
\colhead{ID} &
\colhead{$b_{435}$} &
\colhead{$v_{606}$} &
\colhead{$i_{775}$} &
\colhead{$z_{850}$} &
\colhead{$J$} &
\colhead{$K$} &
\colhead{$3.6\mu$} &
\colhead{$4.5\mu$} &
\colhead{$5.8\mu$} &
\colhead{$8.0\mu$}\\
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{}}
\startdata
 CDFS-1 & $24.49 \pm 0.12$ & $23.79 \pm 0.11$ & $22.10$ & $20.95$ & $19.95$ & $18.12$ & $16.68$ & $16.46$ & $16.44 \pm 0.08$ & $15.73 \pm 0.08$  \\
 CDFS-2 & $24.95 \pm 0.18$ & $23.33 \pm 0.07$ & $21.51$ & $20.45$ & $19.52$ & $17.79$ & $16.54$ & $16.40$ & $16.43 \pm 0.08$ & $15.87 \pm 0.09$  \\
 CDFS-3 & $25.70 \pm 0.33$ & $23.69 \pm 0.10$ & $22.47$ & $21.44$ & $20.53$ & $18.84$ & $17.47$ & $17.05$ & $17.50 \pm 0.21$ & $17.03 \pm 0.24$  \\
 CDFS-4 & $24.02 \pm 0.08$ & $22.70 \pm 0.04$ & $21.01$ & $19.98$ & $18.88$ & $17.04$ & $15.79$ & $15.62$ & $15.53 \pm 0.04$ & $15.27 \pm 0.05$  \\
 CDFS-5 & $>26.4$          & $23.90 \pm 0.12$ & $21.91$ & $21.24$ & $20.24$ & $18.52$ & $17.53$ & $17.60$ & $17.45 \pm 0.20$ & $17.98 \pm 0.50$  \\
 CDFS-6 & $25.23 \pm 0.23$ & $22.66 \pm 0.04$ & $20.98$ & $20.39$ & $19.57$ & $17.94$ & $17.18$ & $17.08$ & $16.96 \pm 0.13$ & $16.87 \pm 0.21$  \\
 CDFS-7 & $25.32 \pm 0.25$ & $23.48 \pm 0.08$ & $22.01$ & $20.92$ & $19.78$ & $17.86$ & $16.39$ & $16.14$ & $15.83 \pm 0.05$ & $15.95 \pm 0.09$  \\
CDFS-12 & $24.41 \pm 0.11$ & $23.75 \pm 0.10$ & $22.24$ & $21.28$ & $20.31$ & $18.50$ & $17.15$ & $16.93$ & $17.04 \pm 0.14$ & $16.45 \pm 0.15$  \\
CDFS-13 & $25.49 \pm 0.28$ & $23.14 \pm 0.06$ & $21.40$ & $20.42$ & $19.41$ & $17.62$ & $16.50$ & $16.36$ & $16.39 \pm 0.08$ & $16.26 \pm 0.12$  \\
CDFS-14 & $24.97 \pm 0.18$ & $23.28 \pm 0.07$ & $21.56$ & $20.55$ & $19.56$ & $17.79$ & $16.37$ & $16.33$ & $16.15 \pm 0.06$ & $15.97 \pm 0.10$  \\
CDFS-15 & $24.89 \pm 0.17$ & $22.67 \pm 0.04$ & $20.99$ & $20.37$ & $19.51$ & $17.85$ & $16.99$ & $17.08$ & $16.45 \pm 0.08$ & $16.83 \pm 0.20$  \\
CDFS-16 & $25.07 \pm 0.20$ & $22.67 \pm 0.04$ & $21.02$ & $20.34$ & $19.50$ & $17.73$ & $16.81$ & $16.87$ & $16.87 \pm 0.12$ & $16.87 \pm 0.21$  \\
CDFS-18 & $24.60 \pm 0.13$ & $23.03 \pm 0.05$ & $21.48$ & $20.46$ & $19.36$ & $17.52$ & $16.19$ & $16.03$ & $15.95 \pm 0.05$ & $15.66 \pm 0.07$  \\
CDFS-19 & $23.52 \pm 0.05$ & $22.17 \pm 0.02$ & $20.86$ & $20.17$ & $19.32$ & $17.62$ & $16.43$ & $16.23$ & $16.01 \pm 0.06$ & $15.84 \pm 0.08$  \\
CDFS-20 & $26.20 \pm 0.49$ & $23.34 \pm 0.07$ & $21.62$ & $20.46$ & $19.42$ & $17.50$ & $16.14$ & $15.96$ & $16.07 \pm 0.06$ & $15.60 \pm 0.07$  \\
CDFS-21 & $24.30 \pm 0.10$ & $22.86 \pm 0.05$ & $21.18$ & $20.58$ & $19.78$ & $18.19$ & $17.05$ & $17.02$ & $16.67 \pm 0.10$ & $16.36 \pm 0.13$  \\
CDFS-22 & $25.23 \pm 0.23$ & $22.68 \pm 0.04$ & $20.81$ & $20.08$ & $19.12$ & $17.38$ & $16.33$ & $16.41$ & $16.22 \pm 0.07$ & $16.10 \pm 0.11$  \\
CDFS-23 & $26.12 \pm 0.46$ & $25.43 \pm 0.41$ & $23.12$ & $21.91$ & $20.84$ & $19.16$ & $17.64$ & $17.46$ & $17.54 \pm 0.22$ & $16.67 \pm 0.18$  \\
CDFS-25 & $>26.4$          & $24.49 \pm 0.19$ & $22.58$ & $21.42$ & $20.34$ & $18.76$ & $17.37$ & $17.28$ & $16.89 \pm 0.13$ & $16.66 \pm 0.17$  \\
CDFS-29 & \nodata          & $22.43 \pm 0.03$ & $21.40$ & $20.46$ & $19.65$ & $18.10$ & $16.79$ & $16.53$ & $16.75 \pm 0.11$ & $15.86 \pm 0.09$  \\
\enddata

\tablecomments{
Photometry of the high-redshift field galaxy sample.
IDs are the same as in van der Wel et al. (2005b).
All magnitudes within a $5''$-diameter aperture of PSF-matched images.
The two lower-limits that occur in the table are $3\sigma$-limits.
Object CDFS-29 falls outside the $b_{435}$ ACS mosaic.
The photometry in the columns without listed errors have errors
on all individual objects of 0.05 mag or less.
The typical errors on the $i_{775}$, $z_{850}$, $J$, $K$, $3.6\mu$, and $4.5\mu$
data points are 0.02, 0.01, 0.01, 0.01, 0.01, and 0.01 mag, respectively.
\label{tab1}}
\end{deluxetable*}
This has been tested directly for local galaxies by \citet{drory04b},
who establish the reliability of the ``photometric masses''.

In this paper we extend, for the first time, the comparison between
dynamical and photometric masses to $z=1$.
We use our sample of early-types with velocity dispersions \citep{vanderwel05},
and rest-frame UV-through-IR photometry.
We investigate the scatter between dynamical and photometric masses,
both at $z=0$ and $z=1$, and how this depends on the photometry included
in the SED fits, and the model assumptions.
Furthermore, we investigate systematic differences between dynamical and
photometric masses.
We note that photometric masses are never absolute, as dark
matter fractions and numbers low-mass stars are unconstrained from the
photometry \citep[see, e.g.,][]{gerhard01,cappellari05}.
However, photometric masses have been used to obtain
"relative masses" at higher redshifts, and to determine the relative
mass evolution
\citep[e.g.,][]{dickinson03,rudnick03,bell04b,rudnick06}.
We test here explicitly whether the relative photometric masses
at $z=0$ and $z=1$ are consistent with the dynamical masses.
The only assumption we make is that
high- and low-redshift early-types have the same kind of stellar population
(IMF, metallicity), with  (obviously) different ages.
This assumption underlies all work with relative photometric masses.

We specifically address the question whether the rest-frame near-infrared
(near-IR) helps to constrain the masses.
Because the near-IR is less sensitive to extinction than the optical,
extending SED fitting to the near-IR helps to lift the degeneracy between
age and extinction.
On the other hand, the stellar population models are less reliable at
wavelengths longer than $1\mu$ than in the optical \citep{maraston05}.
Furthermore, optical-to-near-IR colors have been shown to
correlate less well with $M/L$ than optical colors \citep{bell01}.
The advance of IRAC \citep{fazio04} provides access to the rest-frame IR
at high redshift, and it is assumed that this will allow for 'cheap' mass determinations
through SED fitting for large numbers of distant galaxies.
It is clear that extending the fit SEDs to the IR and thus obtaining
mass estimates needs to be tested.

This paper is organized as follows:
we describe the dynamical masses of the galaxy samples in Section \ref{dyn}.
The photometry, the stellar population models, and our fitting method to
obtain stellar masses are described in Section \ref{phot}.
In Section \ref{results} we present our results, discussing the
consistency of the models with our empirical results, and the dependence on the
fit wavelength range.
In Section \ref{discussion} we discuss the biases that are revealed
by this work, and how this affects estimates of
high-$z$ galaxy masses and the evolution of the mass density.
Throughout we use the Vega magnitude system
(based on the \citet{kurucz92} A0V model spectrum),
and the concordance cosmology,
$(\Omega_M,\Omega_{\Lambda},h)=(0.3,0.7,0.7)$.

\section{Dynamical Masses of Early-Type Galaxies}\label{dyn}
Dynamical masses are computed as
$M_{dyn}=Cr_{\rm{eff}}\sigma_c^2 /G$,
where $C$ is a constant,
$\sigma_c$ is the central velocity dispersion,
$r_{\rm{eff}}$ is the effective radius and
$G$ is the gravitational constant.
\citet{kochanek94},
assuming spherical symmetry, no rotation and fixed anisotropy,
has shown that the velocity dispersion of the
dark matter in elliptical galaxies equals the central line-of-sight
velocity dispersion, as measured within a $2''\times 4''$ sized aperture.
This implies $C=4$ if $M_{dyn}$ is
assumed to be twice the mass within the effective radius.
In terms of the dispersions we use
(corrected to an $3\farcs4$-diameter aperture at the distance
of the Coma cluster), we would have to use $C=4.11$, taking
the differences in aperture and distance between the samples
into account.
\begin{figure*}[t]
\begin{center}
\leavevmode
\hbox{%
\epsfxsize=18cm
\epsffile{f1.eps}}
\figcaption{\small
Various model spectra for a range of ages and parameters.
The labels 'BC03' identify Bruzual \& Charlot (2003) models;
the label 'M05' identifies the Maraston (2005) model.
Metallicity and IMF slope are also indicated ($x=1.35$ corresponds
to the Salpeter IMF).
The indicated ages run from top to bottom.
M05 does not provide realistic spectra for $\lambda>2.5\mu$.
Note the difference in optical-to-near-IR slope
between the BC03 and M05 models.
\small
\label{models}}
\end{center}
\end{figure*}
In the literature, $C=5$ is used more often
\citep[e.g.,][]{jorgensen96}.
Therefore, we choose to use $C=5$ throughout this paper in order for the
masses to remain consistent with previous studies.
This number is based on an isotropic density model,
projected onto an $r^{1/4}$-law and integrated out to $2.5r_{eff}$,
which 75\% of the total mass.
\citep[see, e.g.,][]{cappellari05}.
In units of solar masses, the dynamical mass becomes
$M/M_{\odot}=1.17\times10^6~r_{\rm{eff}} \sigma_c^2$,
with $r_{\rm{eff}}$ in $kpc$ and $\sigma_c$ in $km~s^{-1}$.
We note, however, that the precise value of $C$ does
not affect our analysis as long as it does not evolve with redshift.

\citet{vanderwel05} provide internal velocity dispersions
and structural parameters for 29 galaxies in the Chandra Deep Field-South
(CDF-S).
We exclude four galaxies with late-type morphologies, four
early-types with spectra with low signal-to-noise ratios ($S/N<12~\AA^{-1}$),
and one early-type that falls outside the IRAC mosaic.  We then have a sample
of 20 early-type galaxies with a median redshift of $z=0.98$.
The median mass of this sample is $1.5\times 10^{11}M_{\odot}$.
As a low-redshift comparison sample we use 23
early-type galaxies in the nearby ($z=0.024$)
Coma cluster with measured $\sigma_c$ and $r_{\rm{eff}}$
\citep{dressler87,faber89}.
The median mass of this sample, $M=1.8\times10^{11}M_{\odot}$,
is comparable to that of the $z\sim 1$ sample.

\section{Derivation of Stellar Masses from Photometry}\label{phot}

\subsection{Photometric Data}
A large range of photometric data is available for the CDF-S.
GOODS provides ACS imaging in 4 filters (F435W, F606W, F775W, F850LP,
hereafter $b_{435}$, $v_{606}$, $i_{775}$, $z_{850}$
\citep{giavalisco04}), ESO provides
$J$- and $K$-band imaging, and IRAC GTO observations from the
\textit{Spitzer Space Telescope} are available
(channels 1-4; $3.6\mu$, $4.5\mu$, $5.8\mu$, and $8.0\mu$, respectively).
The photometry is described by \citet{vanderwel06}
and is presented here in Table \ref{tab1}.
The magnitudes are measured within a fixed aperture
with a diameter of $5\farcs0$, using
registered and PSF-matched images.

For the local sample of Coma galaxies we need photometry
that samples a similar rest-frame wavelength range as
we have for the $z\sim 1$ sample.
\citet{faber89} and \citet{scodeggio98} provide the optical surface photometry,
and \citet{pahre98} provide the $K$-band surface photometry.
We use the effective surface brightnesses and effective radii in
the $B$-, $V$-, $I$-, and $K$-bands to compute the colors
within apertures of 67'', used by Faber et al., which typically corresponds
to $4r_{\rm{eff}}$ at the distance of the Coma cluster.
The average colors are
$B-V=0.96$, $V-I=1.18$, and $I-K=1.96$.
The Coma galaxies are the only sample in the literature with K-band
photometry suitable for this study. The fact that these are cluster
galaxies, and not field galaxies as the galaxies in our distant sample
are, does not limit the interpretation of our results.
The differences between the two samples are reproduced through modeling
their SEDs, adopting the relevant parameters which might differ (such as
age, SFH, and dust content) as free parameters in the fit.
The only assumption is that they have similar stellar
populations in terms of IMF and metallicity.

\subsection{Stellar Population Models}\label{secmodels}
For our purpose we need stellar population models that provide
synthetic spectra over a large wavelength range ($0.3-4\mu$).
In recent years,
\citet{bruzual03}
(hereafter, BC03)
and
\citet{maraston05}
(hereafter, M05),
have provided such spectra.
M05 provide realistic spectra only up to $2.5\mu$,
limiting our SED fitting range to the $4.5\mu$-channel. This
is not a severe limitation as the photometric
errors in the two longest-wavelength channels are much larger than in the other two channels
(see Table \ref{tab1}), and observed $4.5\mu$ at $z\sim 1$
corresponds to the reddest filter ($K$) available
for the nearby sample.

Significant differences between the models occur for all ages of interest
for this study.
For ages $0.5-2~\rm{Gyr}$, the M05 model is much redder in the optical-to-nearIR
than BC03, because of the very different implementation of the
Thermally-Pulsating Asymptotic Giant Branch (TP-AGB) phase.
\null
\vbox{
\begin{center}
\leavevmode
\hbox{%
\epsfysize=9cm
\epsffile{f2_new.eps}}
\figcaption{\small
Evolution of $B-I$ (a) and $B-K$ (b) with age
for different models and different model parameters.
The differences between the BC03 and M05 models for similar
sets of parameters are striking.
For ages $<3$ Gyr differences up to 0.5 mag occur in $B-I$,
in $B-K$ even up to 1.4 mag.
For older ages, the agreement is good in $B-I$,
whereas in $B-K$ the difference is $\sim 0.5$ mag.
The tracks are limited to ages from 0.5-20 Gyr.
\small
\label{age_col}}
\end{center}}
For ages older than ~3 Gyr, the M05 model is bluer
in optical-to-near-IR colors than the BC03 model because of the cooler
Red Giant Branch (RGB) stars of the Padova tracks \citep[][used by BC03]{girardi00},
with respect to those of the Cassisi tracks \citep[][used by M05]{cassisi00}.
M05 adopt
the fuel consumption approach, and calculates luminosity contributions
from different stellar types by the amount of fuel used during a
certain evolutionary stage,
whereas BC03 follow the isochrone synthesis approach, and characterize
the properties of the stellar population per mass bin.

We consider SSP models from M05 with solar and super-solar metallicity
($Z_{\odot}$ and $2.2Z_{\odot}$) and a Salpeter IMF
with mass limits $0.1M_{\odot}$ and $100M_{\odot}$
(these limits are used throughout the paper).
For the BC03 model we also consider models with two different metallicities
($Z_{\odot}$ and $2.5Z_{\odot}$) and, in addition,
a solar-metallicity model with a 'top-heavy', or 'flat' IMF with slope of
$x=0.35$ (instead of $x=1.35$, which is the Salpeter IMF).
The model with a flat IMF has been
shown to provide a better match to the evolution of $M/L$ in the optical
and in the near-IR simultaneously
\citep{vanderwel06}.
We do not consider IMFs with different shapes at the low-mass end.
The reason is that varying this shape  changes all mass estimates by a constant factor. In other words, the high- and low-redshift
samples are affected similarly by the choice of parametrization
of the low-mass end of the IMF.

In Figure \ref{models} we show the spectra of the three BC03 models and the
M05 model for ages of 0.5, 1, 2, and 5 $Gyr$.
The difference between the BC03 models with different metallicities,
shown in the left-hand panel, is subtle,
except for the longest wavelengths.
The BC03 models with different IMF slopes (middle panel) show much larger
variation. This is primarily a difference in overall energy output,
which is simply due to the larger numbers of giants in the case of a flat IMF,
especially at young ages.
A secondary, but actually more interesting difference is the different
evolution of the slope, i.e., color, of the SED in models with different IMFs.
Such differences in color evolution are also apparent when comparing the
BC03 models to those of M05, shown in the right-hand panel.
For ages younger than $2.5~Gyr$, the M05 model predicts much
higher luminosities in the $K$-band than the BC03 model, whereas the optical
luminosities are similar.
The differences in color evolution are demonstrated more clearly in
Figure \ref{age_col}.
For ages older than 3 Gyr the optical colors from different models agree well.
For ages younger than that differences of up to 1 magnitude in $B-I$
occur between BC03 and M05 models with the same model parameters.
For the near-IR differences occur for all ages and can increase up to
1.4 magnitudes in $B-K$.

\subsection{Fitting Method}\label{method}
We use redshifted model spectra to compute apparent magnitudes, $m_{mod}$,
allowing the age (and, optionally, the star-formation history (SFH) and the
dust content) to vary, and normalizing the calculated magnitudes
to match the observed magnitudes, $m_{obs}$, to obtain the photometric mass.
$m_{obs}$ are the color magnitudes given in Table \ref{tab1},
including a correction from fixed aperture magnitudes to total
magnitudes as measured in the $K$-band.
The resulting total fluxes are multiplied by 0.75
to match the aperture in which the dynamical mass is calculated
(see Section \ref{dyn}).
The derived stellar mass includes the dark, compact remnants of
massive stars, but not the gas lost due to stellar winds and supernovae ejecta.
The best-fitting model is selected on the basis of the root mean square
of $m_{mod}-m_{obs}$ ($\rm{RMS}$), weighing with the inverse square
of the photometric errors. A certain minimum error is assumed to avoid that the
data points with the largest errors are effectively ignored in the SED fits.
When the IRAC data are used in the fit, a minimum error of 0.10 mag is
adopted. When the IRAC data are not used, we use 0.03 mag. The choices are
based on the relative uncertainties in the photometric
zeropoints of the different datasets.
However, the precise value
of the minimum error does not profoundly affect the fitting results
for the samples as a whole

For the SSP models described in the previous section,
there is a unique relation between color and age. Subsequently, age
determines $M/L$, and thus $M_{phot}$.
The differences between the models, discussed in the previous section
and shown in Figure \ref{age_col},
will cause mass estimates derived from SED to differ.
Most notably, the different trends with age will cause
systematic biases in mass estimates of young (high-$z$) galaxies
relative to old (low-$z$) galaxies.

In Figure \ref{rms} we show, as an example, the fitting results for object CDFS-2,
using the SSP models.
In the top panel we show how $\log(M_{phot})$ of the best-fitting BC03 model
(with solar metallicity and a Salpeter IMF)
changes if different wavelength ranges are used in the fit.
\null
\vbox{
\begin{center}
\leavevmode
\hbox{%
\epsfysize=9cm
\epsffile{f3_new.eps}}
\figcaption{\small
The quality of the SED fit, quantified by the root mean square ($\rm{RMS}$) of
the difference between the calculated model magnitudes and the observed magnitudes,
of object CDFS-2 at $z=0.96$, as an illustration of the fitting method.
The upper panel shows how the results vary by changing the
wavelength range included in the fit, using the BC03 model
with solar metallicity and a Salpeter IMF.
\textit{dashed line:} result for fitting $i_{775}$, $z_{850}$, and $J$.
\textit{solid line:} result for fitting $i_{775}$, $z_{850}$, $J$, $K$, $3.6\mu$ and $4.5\mu$.
\textit{dotted line:} result for fitting $i_{775}$, $z_{850}$, $J$, $K$, $3.6\mu$, $4.5\mu$, $5.8\mu$ and $8.0\mu$.
Including the rest-frame near-IR in the fit leads to a somewhat higher $M/L$.
The bottom panel shows how the results vary when modeling $i_{775}$ through $4.5\mu$
using different models.
\textit{solid red line:} result for the BC03 model with Solar metallicity and a Salpeter IMF.
\textit{dashed red line:} result for the BC03 model with super-solar metallicity.
\textit{dotted red line:} result for the BC03 model with a top-heavy IMF.
\textit{solid blue line:} result for the M05 model with solar metallicity and a Salpeter IMF.
Different models clearly yield different $M/L$ ratios.
The broad minimum obtained for the M05 model can be explained by the slow
evolution of the optical-to-near-IR color (see Figure \ref{age_col}),
and the consequently poorly constrained age.
\small
\label{rms}}
\end{center}}
In the bottom panel we show how the results vary from model to model,
fitting the SEDs from $i_{775}$ to $4.5\mu$.
$\log(M_{phot})$ of the best-fitting models vary by a factor of 3,
indicating the level of the systematic uncertainty in the photometric
mass estimate.
Note that the quality of the fits is generally good:
the $\rm{RMS}$ of the best-fitting model is typically only $\sim 0.02$ mag.

To further illustrate our SED fitting method,
we show in Figure \ref{seds}
the SEDs of three $z\sim 1$ early-types and two different, best fitting model spectra
for each of those. Those model spectra are the SSP models with solar
metallicity and a Salpeter IMF of BC03 and M05, which are fit
to the $i_{775}$, $z_{850}$, and $J$ data-points, i.e., the rest-frame optical.
While similar in the rest-frame optical,
the two models differ from each other in the rest-frame near-infrared.
\null
\vbox{
\begin{center}
\leavevmode
\hbox{%
\epsfysize=9cm
\epsffile{f4.eps}}
\figcaption{\small
SEDs and model spectra of three typical $z\sim 1$ early-type galaxies.
The model spectra, which are for SSPs
with solar metallicity and a Salpeter IMF,
are fit to the three shortest wavelength data-points shown here
($i_{775}$, $z_{850}$, and $J$), with age as the only free parameter besides
the normalization.
The BC03 model under-predicts the fluxes in the redder bands, whereas
the M05 model makes better predictions.
\small
\label{seds}}
\end{center}}
The BC03 spectrum predicts systematically lower flux levels than the M05 model.
The $K$, $3.6\mu m$, and $4.5\mu m$ data-points agree better with the M05 model
than with the BC03 model.
As a consequence, when we fit the $i_{775}$ through $4.5\mu m$ SEDs of these galaxies,
the best-fitting age increases for the BC03 model in order to match
the redness of the SEDs. No older ages are found when the M05 is used.
This behavior is typical for the galaxies in our sample.
As we will show in the subsequent sections, whether or nor including
the near-infrared in the SED fits has profound consequences on the
resulting photometric mass estimates.

\section{Systematic Uncertainties in Photometric Mass Estimates}\label{results}
\subsection{Rest-Frame Optical SED Fits}\label{opt}
In this section we compare photometric and dynamical mass estimates.
We begin by fitting the rest-frame optical SEDs, as previous work
has shown that a single rest-frame optical color like $B-R$ can
be used well to estimate $M/L$ \citep{bell01}
For the local sample we use the $B$-, $V$-, and $I$-bands in the fit,
and for the distant sample we use $i_{775}$, $z_{850}$, and $J$.

We start with mass estimates resulting from fits  of  the SSP
model from BC03 with solar metallicity and a Salpeter IMF.
The left-hand panel of Figure \ref{MMstandardopt} shows
$M_{dyn}$ vs. $M_{phot}$ for the sample of local early-type galaxies.
On the right-hand side we show the same relation for the distant galaxies.
\begin{figure*}[t]
\begin{center}
\leavevmode
\hbox{%
\epsfxsize=15cm
\epsffile{f5.eps}}
\figcaption{\small
(a) Comparison between dynamical and photometric masses
of early-type galaxies in the Coma cluster at $z=0.024$.
The photometric masses are obtained by fitting the photometric SEDs
($B$, $V$, $I$) by model spectra from BC03 for
a SSP with solar metallicity and a Salpeter IMF.
Age and mass are the only free parameters.
The dotted line indicates the best-fitting line with slope 1,
indicating the average deviation.
$\sigma$ is the standard deviation from that line.
(b) Comparison between dynamical and photometric masses
of the distant field early-type galaxies.
Photometric masses are obtained by fitting the photometric SEDs
from $i_{775}$, $z_{850}$, and $J$ by the same BC03 model as used for the local galaxies.
The dotted line, the same as in panel (a), is shown as a reference.
The dashed line is the best-fitting line with slope 1 to the distant
field sample, excluding two galaxies
with velocity dispersions lower than $100~km~s^{-1}$.
The errors on the photometric masses are obtained through Monte-Carlo
simulations.
\small
\label{MMstandardopt}}
\end{center}
\end{figure*}

\begin{deluxetable*}{lccccccc}[b]
\tabletypesize{\scriptsize}
\tablecolumns{8}
\tablewidth{0pt}
\tablenum{2}
\tablecaption{SED fitting results}
\tablehead {
\colhead{Model} &
\colhead{$\Delta$} &
\colhead{$\sigma_1$} &
\colhead{$\delta_1$} &
\colhead{$<\rm{rms}>$} &
\colhead{$<Age>$}&
\colhead{$<SFH>$} &
\colhead{$<A_V>$}\\
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{} &
\colhead{$mag$} &
\colhead{$Gyr$} &
\colhead{$Gyr$ or \%} &
\colhead{$mag$}}
\startdata
\multicolumn{8}{c}{$z=1$: $i_{775}$ , $z_{850}$ , $J$}\\
\hline
BC03, $Z_{\odot}$           &  $ -0.11\pm 0.07 $ & $ 0.25 \pm 0.03  $ & $ -0.20 \pm 0.07 $ &    0.03 & 2.0 & \nodata & \nodata \\
BC03, $Z_{\odot}$, $x=0.35$ &  $ -0.37\pm 0.07 $ & $ 0.27 \pm 0.03  $ & $ -0.70 \pm 0.06 $ &    0.03 & 1.8 & \nodata & \nodata \\
BC03, $2.5Z_{\odot}$        &  $  0.00\pm 0.06 $ & $ 0.24 \pm 0.02  $ & $ -0.32 \pm 0.05 $ &    0.04 & 1.1 & \nodata & \nodata \\
M05, $Z_{\odot}$            &  $ -0.23 \pm 0.06 $ & $ 0.22 \pm 0.03  $ & $ -0.33 \pm 0.05 $ &   0.05 & 1.7 & \nodata & \nodata \\
M05, $2.2Z_{\odot}$         &  $ -0.08 \pm 0.08 $ & $ 0.27 \pm 0.03  $ & $ -0.48 \pm 0.06 $ &   0.05 & 0.7 & \nodata & \nodata \\
\hline
\multicolumn{8}{c}{$z=1$: $i_{775}$ , $z_{850}$ , $J$ , $K$ , $3.6\mu$ , $4.5\mu$}\\
\hline
BC03, $Z_{\odot}$                          &  $ 0.15 \pm 0.06 $ & $ 0.22 \pm 0.04  $ & $ 0.08  \pm 0.05 $ &  0.10 & 3.9 & \nodata & \nodata \\
BC03, $Z_{\odot}$, $\tau$                  &  $ 0.03 \pm 0.06 $ & $ 0.23 \pm 0.03  $ & $ -0.04 \pm 0.03 $ &  0.04 & 3.0 & 0.97    & 0.56    \\
BC03, $Z_{\odot}$, double burst (10\%)     &  $ 0.07 \pm 0.06 $ & $ 0.23 \pm 0.04  $ & $  0.00 \pm 0.05 $ &  0.07 & 2.9 & 10\%    & 3.52$^*$  \\
BC03, $Z_{\odot}$, double burst (30\%)     &  $ 0.01 \pm 0.07 $ & $ 0.24 \pm 0.03  $ & $ -0.06 \pm 0.04 $ &  0.06 & 2.5 & 30\%    & 1.87$^*$  \\
BC03, $Z_{\odot}$, $x=0.35$                &  $ -0.02\pm 0.07 $ & $ 0.22 \pm 0.03  $ & $ -0.39 \pm 0.05 $ &  0.09 & 3.4 & \nodata & \nodata \\
BC03, $2.5Z_{\odot}$                       &  $ 0.23 \pm 0.07 $ & $ 0.25 \pm 0.04  $ & $ -0.23 \pm 0.06 $ &  0.08 & 1.3 & \nodata & \nodata \\
M05, $Z_{\odot}$                           &  $ -0.26 \pm 0.07$ & $ 0.24 \pm 0.04  $ & $ -0.19 \pm 0.06 $ &  0.09 & 3.1 & \nodata & \nodata \\
M05, $Z_{\odot}$, $\tau$                   &  $ -0.24\pm 0.07 $ & $ 0.27 \pm 0.04  $ & $ -0.17 \pm 0.06 $ &  0.05 & 3.7 & 0.15    & 0.36    \\
M05, $Z_{\odot}$, double burst (10\%)     &  $ -0.28\pm 0.07 $ & $ 0.29 \pm 0.03  $ & $ -0.21 \pm 0.07 $ &  0.07 & 2.2 & 6.1\%   & 1.74$^*$  \\
M05, $Z_{\odot}$, double burst (30\%)     &  $ -0.32\pm 0.07 $ & $ 0.27 \pm 0.03  $ & $ -0.25 \pm 0.06 $ &  0.05 & 2.3 & 23\%    & 1.41$^*$  \\
M05, $2.2Z_{\odot}$                        &  $ -0.08 \pm 0.08$ & $ 0.27 \pm 0.05  $ & $ -0.37 \pm 0.06 $ &  0.09 & 1.5 & \nodata & \nodata \\
\hline
\multicolumn{8}{c}{$z=1$: $b_{435}$ , $v_{606}$ , $i_{775}$ , $z_{850}$ , $J$}\\
\hline

BC03, $Z_{\odot}$, $x=1.35$      &  $ -0.18 \pm 0.07 $ & $ 0.28 \pm 0.03  $ & $ -0.28 \pm 0.07 $ & 0.30 & 1.8 & \nodata & \nodata \\
BC03, $\tau$, $A_V$              &  $ -0.05 \pm 0.07 $ & $ 0.24 \pm 0.03  $ & $ -0.15 \pm 0.06 $ & 0.20 & 2.1 & 0.29    & 0.28 \\
BC03, double burst, $A_V$        &  $ -0.03 \pm 0.07 $ & $ 0.28 \pm 0.03  $ & $ -0.12 \pm 0.06 $ & 0.24 & 2.7 & 15\%    & 0.60$^*$ \\
M05, $Z_{\odot}$, $x=1.35$       &  $ -0.31 \pm 0.07 $ & $ 0.28 \pm 0.04  $ & $ -0.41 \pm 0.06 $ & 0.24 & 1.4 & \nodata & \nodata \\
M05, $\tau$, $A_V$               &  $ -0.23 \pm 0.07 $ & $ 0.25 \pm 0.03  $ & $ -0.33 \pm 0.06 $ & 0.22 & 1.7 & 0.13    & 0.22 \\
\enddata
\tablecomments{
SED fitting results for the high-$z$ sample.
The photometry used in the fits is indicated for the $z\sim 1$ sample.
For the $z=0$ sample similar rest-frame wavelength coverages are used (see text for the exact filter sets).
$\delta_1$ is the average $\log(M_{\rm{phot}}/M_{dyn})$, and $\sigma_1$ is the scatter therein.
$\Delta\equiv \delta_1-\delta_0$.
We use $\delta_0$ from single burst models to calculate $\Delta$, also in case
of more complicated SFHs and dust-extinction.
$x=0.35$ indicates models with a flat IMF (with slope 0.35 instead of 1.35 which is the slope of the Salpeter IMF).
$SFH$ indicates either the average time-scale $\tau$ of the exponentially declining star-formation rate,
or the average percentage of stellar mass involved in a secondary burst. This percentage
ranges between 0\% and the adopted burst strength, which indicates that not all galaxies
are necessarily fit better by a double burst model than by a single burst model.
$A_V$ is the extinction in the rest-frame $V$ band.
Those values marked with a $*$ indicate the attenuation of the secondary burst, the
primary burst is assumed to be dust-free.
\label{tab2}}
\end{deluxetable*}

\begin{figure*}
\begin{center}
\leavevmode
\hbox{%
\epsfxsize=18cm
\epsffile{f6_new.eps}}
\figcaption{\small
Comparison between dynamical and photometric masses
of distant field early-type galaxies as in Figures \ref{MMstandardopt},
including $i_{775}$, $z_{850}$, and $J$ in the fits.
The photometric masses are obtained by using different models.
Panel (a) shows the results for the BC03 model
with super-solar metallicity ($2.5Z_{\odot}$) and a Salpeter IMF.
Panel (b) shows the results for the BC03 model
with solar metallicity and a top-heavy IMF
(with $x=0.35$ instead of $x=1.35$ (Salpeter)).
Panel (c) shows the results from the M05 model with solar
metallicity and a Salpeter IMF.
Panel (d) shows the results from the M05 model with $2.2Z_{\odot}$
and a Salpeter IMF.
$\Delta$ is inconsistent with zero in panels
a and c, which indicates a discrepancy between the models
and the observed SEDs and $M/L$.
Also, we note that $\delta_i$ is smaller than zero in all cases
(the dashed and dotted lines lie below the line $M_{phot}=M_{dyn}$),
which indicates the presence of dark matter or a larger
number of low-mass stars than assumed in the Salpeter IMF.
\small
\label{MMmodels2}}
\end{center}
\end{figure*}

To quantify the difference between $M_{phot}$ and $M_{dyn}$,
we introduce the parameter $\delta_i = \log(M_{phot}/M_{dyn})$,
where the subscript $i=0$ or $i=1$ refers to the redshift of the sample.
$\delta_0 = -0.10\pm0.04$, which means that photometric masses are
$20 \pm 8\%$ smaller than dynamical masses for the low-redshift sample.
For the high-$z$ sample we find $\delta_1=-0.20 \pm 0.07$.
The fact that $\delta_i<0$ may be explained by dark matter, or
an underestimate of the number of low-mass stars in these galaxies.
It is more relevant that $\delta_1$ and $\delta_0$ are consistent with
each other:
the photometry does not allow us to constrain the low-mass
end of the IMF and the dark matter fraction.
Therefore, we normalize the low-$z$ photometric masses such that, on average,
they are equal to the dynamical masses.
The $z\sim 1$ photometric mass estimates are changed by the same amount such
that the normalized offset between $M_{phot}$ and $M_{dyn}$ at $z\sim 1$
can be expressed as $\Delta = \delta_1 - \delta_0$.
Thus, for the above, we have $\Delta = -0.11 \pm 0.07 $, i.e.,
the normalized $z\sim 1$ photometric masses are consistent with the dynamical
masses (they are marginally smaller, by $22 \pm 14\%$).
The fact that $\Delta$ is consistent with zero means that the differences
between the SEDs of the low- and high-redshift samples are correctly
transformed into a difference in $M/L$ by this BC03 model.
\begin{figure}
\begin{center}
\leavevmode
\hbox{%
\epsfxsize=9cm
\epsffile{f7.eps}}
\figcaption{\small
The relation between color and $M/L$ for the models used to
infer photometric mass estimates,
compared with observed galaxy colors and dynamically
obtained $M/L$.
Open circles represent the local early-type sample;
filled circles represent the $z\sim 1$ early-type sample.
Panel (a) shows $M/L_B$ and $B-I$.
The BC03 models with a Salpeter IMF agree better
with observations than the M05 models.
Panel (b) shows $M/L_K$ and $B-K$.
In this case, the M05 model agrees better with the data than the
BC03 models.
\small
\label{ML_col}}
\end{center}
\end{figure}
As can be seen, $M_{phot}$ and $M_{dyn}$ correlate well;
the scatter around the average $M_{phot}/M_{dyn}$
is a factor of 1.50 for the local sample and a factor of 1.78 for the
distant sample
(these and all other modeling results for the high-$z$ sample are
summarized in Table \ref{tab2}).

In order to investigate systematic effects,
we perform SED fits with different model parameters.
We show the results for the high-redshift galaxies in
Figure \ref{MMmodels2}.
If we fit a super-solar metallicity BC03 model (panel a)
we obtain  $\delta_1=-0.32\pm0.05$ and $\Delta=0.00\pm 0.06$.
If we adopt a flat  IMF (panel b), we find $\delta_1=-0.70\pm  0.06$
and $\Delta=-0.37 \pm 0.07$.
Thus, if IMF and metallicity are unconstrained the average photometric
mass of the high-$z$ sample is uncertain by at least a factor of 5 in an absolute sense.
The differential $M/L$ from $z=1$ to $z=0$ is uncertain by a factor of 2.3.

Now we explore the M05 models, using the same ages, metallicities and
IMF as for the BC03 models.
In panel c of Figure \ref{MMmodels2} we show the $z\sim 1$ results
if we adopt the M05 model with solar metallicity and a Salpeter IMF
(see also Table \ref{tab2}).
We find that $\Delta=-0.23\pm 0.06$, which is significantly smaller
than what was found for the BC03 model and also significantly smaller
than zero:
the normalized high-$z$ photometric masses are a factor of $1.7\pm 0.2$ smaller
than the dynamical masses.
We find better agreement for the super-solar metallicity M05 model
(panel d of Figure \ref{MMmodels2}): $\Delta=-0.08\pm0.08$.
The disagreement between the BC03 and M05 models implies a systematic
uncertainty of a factor of 1.3 in the normalized high-$z$ mass estimates.
This is much smaller than the uncertainty due to unconstrained metallicity
and IMF.
The scatter in $M_{phot}/M_{dyn}$ is similar to that obtained with the
BC03 models (a factor of 1.65-1.85).

To illustrate the results described above,
we show in Figure \ref{ML_col}a
the relation between optical color ($B-I$) and $M/L$ for the models
and the observed galaxies.
The BC03 models with a Salpeter IMF reproduce the colors and $M/L$ rather well,
whereas the BC03 model with the flat IMF and the M05 models do not.
For the high-$z$ galaxies, the M05 model under-predicts $M/L$,
which explains that this model gives $\Delta<0$.

\begin{figure*}
\begin{center}
\leavevmode
\hbox{%
\epsfxsize=15cm
\epsffile{f8.eps}}
\figcaption{\small
A comparison between dynamical and photometric masses
as in Figure \ref{MMstandardopt},
but now including the rest-frame near-IR in the SED fits.
For the local Coma sample, the $B$-, $V$-, $I$-, and $K$-band
data-points are used.
The average photometric mass is not affected
by the changed wavelength coverage:
the dotted line has not shifted significantly
with respect to Figure \ref{MMstandardopt}.
For the distant sample, $i_{775}$ through $4.5\mu$
are used to obtain photometric masses.
There is a systematic increase with respect
to the masses obtained with the optical SEDs alone:
the dashed line has shifted with respect to
Figure \ref{MMstandardopt}.
Now, $\Delta> 0$, which implies that stellar
masses at $z\sim 1$ are overestimated relative
to $z=0$.
\small
\label{MMstandard}}
\end{center}
\end{figure*}

\subsection{Rest-Frame Optical and Near-IR SED Fits}\label{optnir}

We now extend the SED fits to the rest-frame $K$-band.
The local galaxies are fit with the $B$-, $V$-, $I$-, and $K$-band
photometry.
The distant galaxies are now fit with $i_{755}$ through $4.5\mu$.
Similar to Figure \ref{MMstandardopt}, we show in Figure \ref{MMstandard}
the results if we adopt the BC03 model with solar metallicity and a Salpeter
IMF.
We now find $\delta_1=0.08\pm 0.05$, i.e., the high-$z$ photometric
masses have increased by almost a factor of 2 with respect
to the photometric masses obtained from the optical SEDs alone.
This is not the case for the local sample ($\delta_0=-0.07\pm 0.03$),
which implies that $\Delta$ has increased significantly,
to $\Delta=0.15\pm 0.06$.
Thus, the normalized high-$z$ stellar masses are now a factor of 1.4 larger
than the dynamical masses.
A similar increase in $\Delta$ is found for the other BC03 SSP models
(see panels a and b of Figure \ref{MMmodels1} and Table \ref{tab2}).
For the model with a flat IMF this means that $\Delta$ is consistent
with zero, but we have shown in the previous section
that such a model provides a very poor fit to the rest-frame optical
colors and $M/L$.

For the M05 SSP models (panels c and d of Figure \ref{MMmodels1})
the effect of including the near-IR is very different.
It is still true that the high-$z$ photometric
masses increase somewhat, but that is also the case for the local sample.
The net effect is that $\Delta$ does not change significantly.
For the solar metallicity model we find $\Delta=-0.26\pm0.07$
and for the super-solar metallicity we find $\Delta=-0.08\pm0.08$.

The most important consequence of the above results is the large difference
between the masses inferred from the BC03 and M05 models
with the same parameters.
Normalized masses at $z\sim 1$ obtained with a BC03 model are 2-2.5
times larger than normalized masses obtained with a M05 model.
This implies that there is an intrinsic systematic uncertainty
in photometric mass estimates of at least a factor of 2.5.
We stress that our results are not caused by the different redshifts
of the samples: the same rest-frame wavelength is sampled
for the low- and high-redshift samples. The age difference between
the samples reveals the systematic problems.
In principle, tests such as described here do not require
a range in redshift, but in the local universe there
is no suitable sample of relatively simple stellar systems with ages
of 1-2 Gyr and dynamically measured masses.

In Figure \ref{ML_col}b we show the relation between $B-K$
and $M/L_K$ for the models and the observed galaxies.
The M05 models reproduce the galaxy colors and $M/L$
better than the BC03 models.
Note that in the optical the reverse is the case
(see Figure \ref{ML_col}a).
Qualitatively, we may understand that extending SED fits
to the near-IR does not constrain mass estimates much further:
the optical-to-near-IR color (e.g., $B-K$)
does not constrain $M/L$ very well.
Reversely, the M05 model, which predicts the lack of strong evolution
in $B-K$ cannot distinguish well between galaxies with low
and high $M/L$.
As a side-effect, the scatter in $M_{phot}/M_{dyn}$ is similar to that
found when the SED fits are restricted to the optical,
a factor of 1.65-1.85 for all models described above.

The relatively high masses inferred with the BC03 model
for the $z\sim 1$ galaxies
are the result of the relatively high near-IR luminosities of the galaxies.
According to the model these imply old age and high $M/L$
(see Figures \ref{age_col} and \ref{ML_col}).
Another possible explanation for the high near-IR luminosities
is the presence of dust-obscured stellar populations that
do not contribute to the optical luminosity.
Generally speaking, models with more complex
star-formation histories might yield younger ages
and lower $M/L$.
We explore models with exponentially declining star-formation rates
and models with a dust-obscured,
secondary burst of star-formation that occurs
$2~\rm{Gyr}$ after the initial burst.

We adopt a fixed contribution to the stellar mass
of the secondary burst and leave age and extinction
as free parameters.
Leaving the secondary burst strength as a free parameter
results in a very large scatter in $M_{phot}/M_{dyn}$
as the three free parameters are degenerate.
If we assume that a secondary burst
accounts for 10\% of the total stellar mass,
we find $\Delta=0.07\pm 0.06$ (where $\delta_0$ is taken from
the results obtained with the SSP model as the effect of a secondary
burst does not affect the SEDs of the old local early-types).
The galaxies responsible
for the decrease in $\Delta$ typically have a $0.1~\rm{Gyr}$
old secondary stellar population that is highly obscured ($A_V\sim 4$).
Similar results are obtained if the secondary burst
strength is increased to 30\% ($\Delta=0.01\pm0.07$).
Models with exponentially declining star-formation rates
also improve the results for the BC03 model if
we allow for the presence of dust ($\Delta=0.03\pm 0.06$).
Hence, models with a more complex SFH can successfully
reproduce the SEDs of $z\sim 1$ early-type galaxies
that yield photometric masses that are consistent
with their dynamical masses.
Also, the quality of the fits is better for the
models with more complicated star-formation histories
than for the SSP model (see Table \ref{tab2}).
We note that these type of models do not improve the results
for the super-solar metallicity BC03 model ($\Delta>0.2$, see Table \ref{tab2}).
The M05 model fits do not change significantly
if a model with a complex star-formation history is used
($\Delta<-0.2$, see Table \ref{tab2}).

\begin{figure*}
\begin{center}
\leavevmode
\hbox{%
\epsfxsize=17cm
\epsffile{f9_new.eps}}
\figcaption{\small
A comparison between dynamical and photometric masses
as in Figure \ref{MMstandard} (fitting rest-frame
optical through near-IR SEDs). The same set of models as in
Figure \ref{MMmodels2} are used.
For any BC03 model, $\Delta$ increases significantly
when the near-IR is included in the SED fits.
For the M05 model $\Delta$ does not significantly change.
\small
\label{MMmodels1}}
\end{center}
\end{figure*}

\subsection{Rest-Frame UV and Optical SED Fits: Constraints on the Star-Formation History}\label{uv}
Finally, we explore the effect of extending the analysis to
the rest-frame UV. The UV is strongly affected by (small traces of)
star-formation, and is expected to cause less accurate mass estimates.
On the other hand, this sensitivity to young stars may allow to constrain
the SFH and dust content, which we below adopt as free parameters.

As a baseline, we adopt the BC03 and M05 SSP models with solar metallicity
and a Salpeter IMF. We now fit the SEDs using the $b_{435}$, $v_{606}$, $i_{775}$,
$z_{850}$, and $J$ photometry. Because of the problems detailed in the
previous section, we omit the rest-frame near-IR. The results are shown in the
left-hand panels of Figure \ref{MMUVBC} (BC03) and Figure \ref{MMUVM}
(M05). The scatter in $M_{phot}/M_{dyn}$ is a factor of $\sim 1.9$,
similar to the scatter obtained without the $b_{435}$ and $v_{606}$ photometry.
The quality of the fits has decreased significantly: for the BC03 model, the
average $\rm{RMS}$ is now 0.30 mag (it is 0.03 mag without the two
shortest-wavelength filters); for the M05 model this is 0.24 mag, instead of
0.05 mag. This indicates that, at least for the UV part of the SEDs, an SSP
model provides poor fits.

Now we allow for an exponentially declining star-formation rate with
timescale $\tau$, instead of assuming a single burst.
Since star-formation is usually related to extinction by dust,
we consequently adopt $A_V$ as a free parameter as well.
The results are shown in the middle and panel of Figure \ref{MMUVBC}
(BC03) and the right-hand panel of Figure \ref{MMUVM} (M05).
The scatter in $M_{phot}/M_{dyn}$ decreases marginally and is
now comparable (a factor of $\sim 1.7$)
to what we found when we excluded the UV
and assumed a dust-free SSP.
Also, the fits are somewhat better,
as the average $\rm{RMS}$ is now $\sim 0.2~\rm{mag}$ for both models.
The fact that the $\rm{RMS}$ remains much higher
than for the optical SED fits is
most likely caused by the large errors in the $b_{435}$-band photometry.

In Table \ref{tab2} we show the average values of age, $\tau$, and $A_V$.
The inferred values for the extinction are quite large: $A_V\sim 0.25$ for both
models. Age and $\tau$ are $\sim 2.1$ and $\sim 0.29~Gyr$ for the BC03 model
with dust and $\sim1.7$ and $\sim 0.13~Gyr$ for the M05 model with dust. This
implies an average SFR of $\sim 1~M_{\odot}~yr^{-1}$. Assuming that this
continues to decline
exponentially between the epoch of observation and the present, the
average stellar mass increases by no more than $\sim 0.2\%$ after $z\sim 1$.
The galaxy with the highest SFR would increase its stellar mass by $8.0\%$.
The models imply that residual star-formation is not very relevant for the
galaxies in our sample, and, barring interactions or mergers, have assembled
most of their stellar mass by $z\sim 1$.

\begin{figure*}
\begin{center}
\leavevmode
\hbox{%
\epsfxsize=17cm
\epsffile{f10_new.eps}}
\figcaption{\small
Comparison between dynamical and photometric masses (using the BC03 model)
of distant field early-type galaxies as in Figure \ref{MMstandardopt}.
Here we modeled the rest-frame UV+optical SEDs:
all photometric data points between $b_{435}$
and $J$ are used in the fits.
In panel (a) we assume, as a starting point, a dust-free SSP
with solar metallicity and a Salpeter IMF.
In panel (b), $\tau$ and $A_V$ are free parameters.
In panel (c), the strength of a secondary burst that occurs
$2~\rm{Gyr}$ after the initial burst and $A_V$
(only applied to the secondary burst) are free parameters.
See Table \ref{tab2} for the inferred ages, and average values of
$\tau$ and $A_V$.
\small
\label{MMUVBC}}
\end{center}
\end{figure*}

Finally, we test a BC03 model in which a dusty, secondary burst of
star-formation occurs $2~\rm{Gyr}$ after the dust-free initial burst.
This is the same model as used in the previous section, but now we adopt
the strength of the secondary burst as a free parameter as well, along
with age and $A_V$:
we allow the secondary burst to
vary in strength between 0\% to 30\% of the final stellar mass.
The results are shown in the right-hand panel of Figure
\ref{MMUVBC}. The scatter in
$M_{phot}/M_{dyn}$ is a factor of 1.9, which is similar to what was
found when modeling the rest-frame optical SEDs with a dust-free SSP model.

To investigate the applicability of the double burst model, it is more
interesting to look at individual galaxies. The fits of 11 out of 20
galaxies clearly improve by allowing a dusty, secondary burst. With a single burst,
these seven galaxies are assigned ages of $1.2~\rm{Gyr}$.
These galaxies are fit significantly better by a $\sim 0.3~\rm{Gyr}$
old secondary burst involving, on average, $12\%$ of the final stellar mass
and an extinction of $A_V\sim 0.65$.
This young population is superimposed on a 2 Gyr older, dust-free population.

\section{Summary and Discussion}\label{discussion}
In this paper we have compared photometric and dynamical
masses of early-type galaxies at both high ($z\sim 1$) and low redshifts.
The uncertainties were analyzed quantitatively.
We start this discussion with summarizing our main conclusions.

1)
After allowing for a systematic offset,
the scatter in $M_{phot}/M_{dyn}$, which quantifies the random uncertainty
in photometric mass estimates of individual
early-type galaxies at $z\sim 1$, is a factor of $\sim 1.75$ ($\sigma=0.25$).
We find no significantly different random uncertainties for different models
and different wavelength ranges used in the fits,
i.e., including IRAC data in the SED fits does not provide
significantly more accurate mass estimates.

2) For SSP models from BC03 and rest-frame optical SED fits we find that the
photometric masses of the $z\sim 1$ galaxies are consistent
with the dynamical masses after normalization with respect to
the $z=0$ galaxies.
This normalization is the difference between
the photometric and dynamical masses of the low-$z$ comparison sample.
When the SED fits are extended to the rest-frame near-IR
the normalized $z\sim 1$ mass estimates increase by a factor of 2:
the $z\sim 1$ photometric masses are are larger than the dynamical masses.
For the SSP model with a top-heavy IMF ($x=0.35$ instead of $x=1.35$)
there is no such discrepancy, but in that case
optical SED fits underestimate the $z\sim 1$ masses by a factor of 2.3.

If we allow for more complex star-formation histories and dust-extinction,
the $z\sim 1$ mass estimates decrease,
such that the discrepancy seen for the BC03 models with a Salpeter IMF
and solar metallicity disappears.
For example, a model with a secondary, obscured burst of star formation
provides good results and increases the quality of the fits.
\null
\vbox{
\begin{center}
\leavevmode
\hbox{%
\epsfxsize=8.5cm
\epsffile{f11.eps}}
\figcaption{\small
Comparison between dynamical and photometric masses (using the M05 model)
of distant field early-type galaxies as in Figure \ref{MMstandardopt},
modeling the rest-frame UV+optical SEDs: all photometric data points
between $b_{435}$ and $J$ are used in the fits.
In panel (a) we assume, as a starting point, a dust-free SSP.
In panel (b), $\tau$ and $A_V$ are free parameters.
See Table \ref{tab2} for the best-fitting model properties.
\small
\label{MMUVM}}
\end{center}}
If correct, these results imply the presence of a significant
population (at least 10\% in mass) of young stars ($\sim 0.1~\rm{Gyr}$)
that are highly obscured ($A_V\sim 4$) in roughly half of
the $z\sim 1$ population.
It remains to be seen whether this is the case.
Mid-IR observations will constrain this scenario.

3)
We find very different results when we use the M05 model with solar
metallicity.
That model produces normalized mass estimates from the optical SEDs
of the $z\sim 1$ galaxies that are too low by a factor of 1.7.
The most striking difference with the BC03 model
is revealed when the SED fits are extended to the near-IR:
the normalized mass estimates at $z\sim 1$ do not change significantly,
which implies that the normalized high-$z$ mass estimates remain too low.
More complex models do not change these results significantly.
Most importantly, the differences between the results
obtained with the BC03 and M05 SSP models with identical
model parameters imply a systematic uncertainty
of a factor of 2.5 in photometric mass estimates obtained from near-IR
SED fits.
Hence, extending SED fits from the optical to the near-IR
does not provide better mass estimates of high-$z$
early-type galaxies, because of uncertainties
intrinsic to the stellar population models.

4) Adopting the SFH and dust-extinction as free parameters, and
extending the SED fits to the rest-frame UV, do not
increase the quality of the SED fits, nor
decrease the random uncertainty in the photometric masses.
For our sample, fitting the rest-frame optical SEDs is optimal to constrain
the masses.
Fits of UV+optical SEDs of several individual galaxies, however,
improve significantly by adopting the SFH as a free parameter.

The above results demonstrate that both models
have problems in either the optical (M05) or the near-IR (BC03,
barring significant, obscured stellar populations).
This conclusion relies on two assumptions.
First, we assume that all local and distant galaxies have similar dynamical
structures.
In other words, we assume that invoking $5r_{\rm{eff}}\sigma_c^2 /G$
as $M_{dyn}$ for both low- and high-redshift early-types
does not introduce systematic effects.
This assumption appears to be reasonable, as FP studies
have shown that all nearby ellipticals and S0s to follow the same relation
\citep[e.g.][]{jorgensen96}, and \citet{treu04} showed
that high redshift ellipticals have the same structure as low redshift
ellipticals.
Second, we assume that local and distant galaxies can be fit with
models with the same metallicity and IMF.
By that we ignore, for example, the possibility that the galaxies
in our $z\sim 1$ sample evolve strongly in metallicity.
However, in order to remove the inconsistency found for the BC03 model,
the distant galaxies would have to be more metal-rich than the local
galaxies.
This seems unlikely.
On the contrary, \citet{jorgensen05} show evidence for metal enrichment
between $z\sim 0.8$ and the present.
We also note that mergers between early-type galaxies,
which are likely very important in
shaping the mass-function of the early-type galaxy population
\citep[e.g.,][]{vandokkum05},
do not affect our conclusions much because the stellar populations
themselves do not change.

The differences between the models are not restricted to the range of ages
of the galaxies described in this paper ($\gtrsim 1~\rm{Gyr}$).
On the contrary, the largest differences are found for even younger ages
(i.e., low $M/L$, see Figures \ref{age_col} and \ref{ML_col}).
This implies that mass estimates of young or star-forming
galaxies may also be systematically uncertain.
This is in particular relevant to
studies at $z>2$, where SED fits are the only available method for estimating
galaxy masses
\citep[e.g.,][]{forster04,daddi04,shapley05,labbe05,mobasher05}.
This work suggests that more than one type of model should be used
when performing SED fits,
as the difference will give an indication of the systematic uncertainty.

It is essential that the models are improved, hopefully
leading to consistent predictions of the SEDs, given the
IMF, star formation history and metallicity.
Therefore, a better understanding of the near-IR properties of stellar populations is required.
Our work provides a new tool to verify the predictions of the models,
a method that can be exploited more thoroughly by
obtaining a large sample of early-type galaxies with a wide range in redshift,
accurate dynamical masses and abundance measurements from spectroscopy,
star-formation activity from UV and mid-IR photometry, and mass estimates
derived from multi-wavelength imaging, including the rest-frame near-IR.
Only when the model discrepancies are resolved can the full potential of IRAC
for measuring stellar masses of distant galaxies be realized.

redpajama_set_name: RedPajamaArXiv


The Maccabees (2002-2016) were an indie rock band from London, UK. The line-up consisted of Orlando Weeks (vocals), Hugo White (guitar), Felix White (guitar, vocals), Rupert Jarvis (bass) and Sam Doyle (drums), who replaced Robert Dylan Thomas. Weeks stated once that the band came up with the name by flicking through the Bible and picking out a random word. Despite adopting a name with religious connotations, he affirmed that none of the band are religious.
Debuting in 2004 with the You Make Noise I Make Sandwiches EP (released on Haircut Records), they released their first single X-Ray on Promise Records on November 28, 2005. Receiving just little significant exposure - some evening play on XFM London radio station - the band however scored a minor indie hit with their second post-punk influenced single Latchmere released in April 2006 on Fierce Panda Records.
Then inking a deal with the Polydor imprint (and former home of The Cure) Fiction Records the bands first studio album, Colour It In, was released on May 4, 2007 .
To date (late September 2007) they have released three (widely available) singles from the album (First Love, About Your Dress and Precious Time) with a fourth and final single Toothpaste Kisses released on October 8, 2007.
On May 4, 2009 the band released Wall of Arms, their second album. Preceded by the single Love You Better on April 27th. Markus Dravs, who collaborated in the past with artists such as Björk, Arcade Fire and Coldplay, produced the album. The album has been recorded in various cities including Liverpool and Paris, unlike their first long-player which was recorded in "dribs and drabs" like frontman Orlando Weeks said.
On January 9, 2012 the Maccabees released Given To The Wild, their third album. The band worked on the album at both Rockfield Studios in Wales and their rehearsal space in London's Elephant and Castle district, before decamping to Suffolk to finish the record.
Marks to Prove It, their last album, was released in 2015.
Guitarist Felix White was initially in a band called Jack's Basement with fellow friend Jack Peñate. Felix and Hugo White are brothers, along with Will White, who is the frontman of another band called Talk Taxis. Former drummer Robert Dylan Thomas left the band in 2008. There was also another group called Maccabees, who were an indie pop band from Florida in late 90s.


Three of the world's 50 best restaurants can be found in the Danish capital.
The World's 50 Best Restaurants list was revealed at a ceremony in New York City on Monday evening and little Denmark was well-represented.
Three Copenhagen restaurants made the list, with Noma leading the way. Rene Redzepi's restaurant was ranked fifth, a fall of two spots from last year's ranking. Noma has topped the list three times.
"The Scandi gastronomy movement that has taken hold across the world started at a renovated warehouse in Copenhagen in 2003 when René Redzepi took it upon himself to revive and update Nordic food using contemporary cooking methods," the World's 50 Best Restaurants Academy wrote. "Noma has since gone on to change the way dining rooms operate and put foraging for ingredients firmly in the spotlight.
Denmark's first-ever three-star Michelin restaurant Geranium came in at number 28 on the list. That marked a huge jump from last year's 51st place ranking for head chef Rasmus Koefoed and company.
Michelin-starred Copenhagen restaurant Relæ came in at number 40 and was named the winner of the Sustainable Restaurant Award for the second time.
"Chef Christian Puglisi and front-of-house head Kim Rossen set up Relæ in 2010 after meeting at Noma," the academy wrote. "The influence of René Redzepi's restaurant is clear, but Puglisi is not constrained by New Nordic principles, using ingredients from Italy and further afield.
The title of best in the world was given to Osteria Francescana from Modena, Italy, which leapfrogged last year's victor El Celler de Can Roca from Catalonia, Spain into top spot.
The only other Nordic restaurant to make the top 50 was Fäviken Magasinet in Järpen, Sweden.
The World's 50 Best Restaurants List is compiled by a group of nearly one thousand leading figures in the international restaurant industry.


To help students understand the concept of above the line versus below the line behaviors and make a commitment to promoting above the line behaviors at their school.
While one presenter is talking, have another draw a line across the paper. Write "above the line" on top of the line and "below the line" under the line, with arrows pointing up and down, respectively (i.e. copy the graphic on the handout).
Write the group's answers on the poster in the appropriate locations.
Ask the group to brainstorm answers to these questions: What happens at our school when students engage in above the line behaviors? What happens when they engage in below the line behaviors?
Ask students to commit to having more above the line behaviors and fewer below the line behaviors in their classroom.
Find a place to display the poster as a reminder to the students of their commitment.


text:
The Appleton Ladies' Potato Race @ Ensemble Theatre
by Manan Luthra March 28, 2019 May 3, 2019
Like I've experienced a few times in my short journalistic career, Ensemble Theatre's The Appleton Ladies' Potato Race is a show that I must review with a grain of salt. Weary of the fact I'm not female, nor from a regional area, a play that exclusively focuses on the female gaze and the gender politics of a small country town makes me something like the Bess Denyar of a real-life Upper Middle Bogan – high-paying job, bearded Aussie husband, and twin boys aside (last time I checked at least).
Luckily, even with that being the case, there's still a whole lot to enjoy in Ensemble's latest 90-minute spectacle.
The beauty of playwright Melanie Tait's script is its creation of characters that can resonate with the audience on both an individual and collective level, closing the gender, age and location-based gaps one could reasonably expect between a play of this nature and a lower North Shore demographic. For the older members of the audience, there's the dominant Bev Armstrong (Valerie Bader) and the submissive Barb Ling (Merridy Eastman), an odd couple-esque duo and the Appleton locals least willing to change the 30-year-old race. For the parents, there's Nikki Armstrong (Amber McMahon), the local longtime champion of the potato race and the mum who yells as the teenage Saturday sport referee, asks to speak to the manager, and probably has kids named Jaxxon and Keightlynn. Alongside the misunderstood and racially discriminated migrant Rania Hamid (Sapidah Kian), those born and raised in the city will find the main character Penny Anderson (Sharon Millerchip) a hit way too close to home in her highly progressive, highly educated, and at times highly annoying nature as she tries to provide equal prize money to the male and female winners of the potato race. Together, this quintet manage to draw on their differences to tell Tait's story exactly the way it was supposed to be told, with their ensemble work the show's biggest strength and a further credit to Priscilla Jackman's already well-known directorial skill.
On an individual level, the performances are a little more mixed. In a play that is intended to be both comedic and affirming of the strength of women, much of the latter is left to Eastman, Millerchip and Kian, who struggle to reconcile the demands of this with the comedy they also have to provide. Of these three, it is Eastman's character development, one of the play's most important, that is the most sudden (and therefore the least impactful); if we were given adequate time to reflect on this development like we are that of the other characters, whose moments of reflection bring about well-orchestrated pauses in comedic action, then the play's themes would resonate more strongly. Khan, even though taking on the play's smallest role, manages to have a strong stage presence, providing a unique perspective on the play's central themes that just avoids being cliché. Millerchip and McMahon – the former of which could be considered something of a white saviour; make of that what you will – hardly ever drop from the high bar they set themselves and deserve acclaim for their comedic performances, which includes a knockout dance routine in an 80s flashback scene. It must be said, though, that the real delight of the show is Bader. Don't ask me why, but there's something about watching old people interact with technology that never ceases to be funny. Yet, even when she's not talking about 'The Facebook', the clear attention she has paid to the character and innate understanding of how an individual deals with unprecedented social change makes her the unexpected pick of the cast.
Couple the existing merits of the performance with a banging Tegan Nicholls soundtrack (which, obviously, features Hot Potato) and an inventive Michael Scott-Mitchell set design (albeit only noticeable around the end of the play) and, as usual, I'm continually impressed with Ensemble's attention to detail.
Ultimately, even though there might be a development or two missing, the comedic strength of TALPR's team makes the show worth watching. It'll be interesting to see how this fares alongside Ensemble's immediate follow-up The Last Five Years, but in any case, Appleton should be the next stop on your theatrical road trip.
Once in Royal David's City @ New Theatre
The Last Five Years @ Ensemble Theatre
Manan Luthra
The man behind the magic, Manan has been reviewing for some time now but has only just started to go solo. Sydney born and bred but Indian by heritage, when he's not watching theatre you can catch him talking cricket, thinking about cricket, watching cricket, or pretending to be at the cricket. A gin and tonic enthusiast, he loves a good chat and is more than excited to be running this website. Reach him on Twitter @sotareviews, or reviews@stateoftheart.net.au.
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OKLAHOMA CITY - The Office of Management and Enterprise Services has released a report on the calculations of averted costs to the State of Oklahoma from the implementation of State Question 781 which was passed by the state's citizens in November of 2016, along with State Question 780, more commonly known as the "Oklahoma Smart Justice Reform Act."
In accordance with 57 O.S. § 632, which requires these calculations to be performed "no later than July 31 of the year following the effective date of [SQ 781], and no later than July 31 every year thereafter," OMES analyzed data provided by the Oklahoma Department of Corrections, the District Attorney's Council, the Oklahoma Department of Mental Health and Substance Abuse Services, and Oklahoma and Tulsa County Jails for the calculation.


Typically, at the end of job interview the interviewer asks you, "Do you have any questions for me? ". This is a very tricky situation – you may kill the deal by asking the wrong questions. I prefer asking something very neutral, like "How many people work on the project ", or "What would be my role if you 'd hire me ". The job interview is not the right place for showing your attitude.
Bruce Eckel has published a blog where he lists a number of questions you may ask your perspective employer during a job interview. Even though Bruce tries to be careful in asking questions, you can still feel that he 's a senior guy who will eventually ask for some special arrangements like working from home or having flexible hours. My only advice to you is this – be careful during the interview. Get the offer first, and only after that ask your questions – you can always reject the offer if you don 't like the answers. Also, Bruce is a very respected person in the Java community, and his impeccable reputation allows him to ask more questions than a regular Java-Joe can.
I also enjoyed reading comments to Bruce 's blog. IMHO, most of these questions would kill the deal, and most likely none of these responders would actually ask these questions during the interview.
Some time ago I wrote an article on the interviewing process , which might be useful for people who are just starting dealing with job market.


Even reserve Army attorneys say that Fort Campbell "missed something" that allowed a prominent for-profit college to recruit active duty soldiers at dozens of events two years ago before the school was temporarily banned from recruiting active-duty service members.
Between 2014 and 2015, the University of Phoenix paid the installation's Morale, Welfare and Recreation office $250,000 and was allowed to sponsor nearly 90 events. The office hosts recreational events for solders and their families.
A recent report by Reveal, an online publication by the Center for Investigative Reporting, raised new questions about how the Army allows for-profit colleges to recruit active-duty service members on its installations around the world.
One of the biggest questions will be how President Donald Trump's administration will address the issue.
Many of those for-profit institutions like University of Phoenix have come under fire in recent years by critics who say they don't deliver on what they promise, and data that shows graduation rates far lower than more traditional, two- and four-year colleges and universities.
The Center for Investigative Reporting obtained a contract between the University of Phoenix and Fort Campbell, which shows 89 events in a year sponsored by the for-profit university. The contract allowed the school to collect personal information of attendees if approved by the installation.
During that time, the university was allowed to insert promotional materials into packets given to incoming soldiers, display banners promoting the institution at events that ranged from large concerts to family-oriented Easter egg hunts.
Reveal reported two years ago about similar agreements by the University of Phoenix at other military installations, which were the subject of a rule implemented under President Barack Obama that limited how much federal money — like that from the federal G.I. Bill — could go to for-profit institutions.
The Defense Department banned the University of Phoenix from recruiting on military installations, but lifted that ban just three months later.
Since then, Fort Campbell has "tightened" its parameters in contracts with the installation and for-profit schools, Fort Campbell spokesman Bob Jenkins said. Jenkins acknowledged that many for-profit schools have been identified by the Pentagon for using predatory tactics against soldiers, and "badgering" soldier-students.
"We just want to make sure the soldier's are taken care of," Jenkins said.
Jenkins said there are no current contracts between the University of Phoenix and Fort Campbell.
The agreement has Sean Marvin, an Army Reserve judge advocate general and the legal director of Veterans Education Success, questioning the oversight of contracts like those between the installation and University of Phoenix.
Marvin said he would expect any contract between the installation and a third party would get "a legal review" by someone at Fort Campbell, but "somebody missed this."
"I tend to wonder how much they were tracking that executive order in the first place,' he said.
Jenkins said Fort Campbell vets all potential sponsors. They must have formal agreements with the installation. Without that agreement, Jenkins said the installation likely wouldn't consider a relationship like that with University of Phoenix.
The news also comes as public schools across Tennessee promote veteran-friendly areas and are creating or building new space to aid those students.
Austin Peay State University, Middle Tennessee State, the University of Memphis and the University of Tennessee all say they are "veteran-friendly" schools.
APSU is the only state school to have a satellite campus at Fort Campbell and opened one of the first military student centers in the state in 2010.
Jenkins said the relationship with APSU is different because it's a local university, and "a reputable school."
APSU pays to sponsor events and actively recruits soldiers, according to Bill Persinger, executive director of public relations and marketing at APSU, but said Fort Campbell "has become much more strict about what is allowed on post from a recruiting standpoint," like only recruiting within its own building.
UT, by contrast, does not recruit on military installations, said Amy Blakely, assistant director of media and internal relations for UT, but does invite service members and veterans to campus.
In Fall 2016, about a quarter of APSU's 10,000-student population were considered "military-related." This fall, UT has about 900 students attending using federal VA benefits, Blakely said.


first), now it's time to try it for yourself.
be easily flashed through the network.
You can find it in the lower left part of the editor, under the operation tab (labeled "Remote Upload").
Please make sure to check the readme of the Ariadne-bootloader with the instructions on how to flash your Arduino with our bootloader.


text:
Scheppach may refer to:
Scheppach (company), German manufacturer of cement mixers and other machinery
Scheppach (Bretzfeld), village within Bretzfeld, Hohenlohe district, Baden-Württemberg, Germany

redpajama_set_name: RedPajamaWikipedia


text:
Shaw Thing
Wolfsburg want Luke Shaw from Manchester United as he enters final year of contract
Left-back's long-term Old Trafford future is unclear as he looks to finally win over Jose Mourinho with his fitness and performances
Anthony Chapman
LUKE SHAW is a reported target for German giants Wolfsburg.
The Mail claims Manchester United's inconsistent left-back could be heading to the Bundesliga before deadline day on August 9.
Luke Shaw is wanted by German giants WolfsburgCredit: Getty Images
Shaw has entered the final year of his Old Trafford contract and there are currently no plans to extend it.
The England international has said he hopes to win over Jose Mourinho with his performances in order to earn an extension.
But Wolfsburg could now make an offer to take Shaw off the Special One's hands once and for all.
However, it's said that the 23-year-old has no plans to leave the Theatre of Dreams.
The left-back has entered the final year of his Old Trafford contractCredit: USA TODAY Sports
And Shaw's exit would also leave United scrambling to find a replacement with less than a fortnight of the transfer window remaining.
He looks set to start the first game of the season against Leicester, with Diogo Dalot injured and Matteo Darmian heading to Napoli on loan.
But Mourinho's squad will be boosted by the imminent returns of Victor Lindelof and Phil Jones from World Cup duty, with Marcus Rashford, Romelu Lukaku and Paul Pogba also approaching the end of their holidays.
Meanwhile, young goalie Joel Pereira could be heading on loan to Vitoria Setubal following the arrival of Lee Grant from Stoke.
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Jose Mourinho says "I wouldn't pay to watch us after Manchester United's defeat to Liverpool
Shaw has expressed a desire to stay at United and impress boss Jose MourinhoCredit: PA:Press Association
Shaw is set to start the season opener against Leicester with Matteo Darmian close to joining NapoliCredit: Getty Images
WRIGHT MOVE
My football career ended in scandal but now I earn £500k as model on OnlyFans


text:
Arvind Sreenath () (born 8 April 1984) is a former Indian cricketer who played for Karnataka and the Royal Challengers Bangalore. He made his Twenty20 International debut for India against South Africa on 2 October 2015.

International career
A left-arm quick bowler, Aravind was called up to India's One Day International squad for the series against England in October 2011 but did not play.

Aravind made his Twenty20 International debut for India against South Africa on 2 October 2015.

Aravind played for India internationally only once. After he made his debut for India against South Africa in October 2015, he never came back in international cricket or played international cricket.

Domestic career
In the 2011 Champions League Twenty20, Arvind played in six matches as his team, the Royal Challengers, made it to the final, losing to the Mumbai Indians.

Arvind overcame a career-threatening accident a couple of years ago and made his first-class debut in 2008. He is known for his ability to bowl both left arm fast and left arm spin.

Retirement
On 27 February 2018, after winning the Vijay Hazare trophy final, Aravind announced his retirement from all forms of cricket.

References

External links

1984 births
Living people
Indian cricketers
India Twenty20 International cricketers
Royal Challengers Bangalore cricketers
Karnataka cricketers
South Zone cricketers
Cricketers from Bangalore