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text:
APAC presented at the UN Treaty Negotiations
Hemantha Withanage, Executive Director of Centre for Environmental Justice (CEJ) – FoE Sri Lanka was part of a session panel titled Voices of the Victims at the UN Treaty on Transnational Corporations Session in Geneva, Switzerland.
Hemantha highlighted 2 main cases from Asia Pacific, 1 from Sri Lanka and the other from Philippines. He also raised the issue of how international financial institutions were protected by immunity leaving affected communities to raise redress and grievance through IFIs own accountability mechanisms only. These mechanisms are not enough to protect affected communities. Hence, the reason why we need a binding treaty on corporations is badly needed.
Read the full speech at the UN in Geneva below.
Name of the Session:The voices of the victims
Date and Time:27th Oct 2017
FoEI speaker:Hemantha Withanage
Draft statement (to be read in 5 minutes / 1500 words maximum):
Panel: The voices of the victims
Hemantha Withanage, Friends of the Earth – Centre for Environmental Justice, Sri Lanka
Mr. Chairman, It is extremely sad to see that we are losing control over our body, our culture, nature and the livelihoods. Neoliberalism remains the dominant global economic paradigm, despite the failed policies of privatization, deregulation and corporate globalization. It has led to the inability of states and governments to regulate the economy and protect the commons including the natural environment. Some of the great difficulties and threats created by the current system are faced by the women and men who defend the territories they have constructed historically and with the wisdom of our ancestors.
People are in a much more crisis when they don't have the rights to make decision over its own body, with respect to labour, sexual or other forms of exploitation, discrimination and disrespect. Transnational Corporations have taken over the decision-making role over all these territories, spirituality, ancestry and even our culture and our natural resources through commodification. The pollution of our water, air, soil, food and destruction of our forests, rivers, wetlands are all part of this crisis. I will cite few real examples to give you an idea of the extent of this crisis.
Mr. Chairman, We all know Water is a human right. The Human Right to Water and Sanitation was recognized as a human right by the United Nations General Assembly on 28 July 2010. The Universal Declaration on Human Rights of 1948 and International Covenant on Economic Social and Cultural Rights of 1966 implicitly recognized the Human Right to Water.
But the MARCOPPER MINING CORPORATION in the Philippines violated this right two decades ago with the 25 million USD loan extended by the Asian Development Bank for mining operations in the island of Marinduque, in the Philippines. In March 24, 1996 a drainage tunnel of Marcopper cracked, spilling millions of tons of mine tailings into the Boac River. The United Nations investigated the extent of the impact of the spill and identified unacceptable levels of heavy metals and toxic wastes in parts of the river.
This river had been an important source of food for the residents of Marinduque. Many residents suffered illnesses because of the toxic wastes which had been accumulating in the province's tributaries ever since Marcopper started operations in 1994. In April 2001, a case for recovery of damages was filed in the local Court by affected residents in Marinduque against Marcopper. After 16 years, the case is still in the trial stage and will most likely be dragged on for a few more years due to the financial and technical resources available to mining company and the inefficiencies of the justice system. Some plaintiffs have already died without getting due reparations. Other plaintiffs are senior citizens experiencing failing health. Aside from delays in the judicial system, Marcopper may also be able to escape liability by declaring itself insolvent and unable to pay the damages sought by plaintiffs.
UMA OYA RIVER DIVERSION PROJECT in Sri Lanka is an ongoing example for a criminal act and human rights violations. 22 km long tunnel is being constructed under the eastern side of the mountain range in Sri Lanka damaging the groundwater aquifer since 2013. More than 7500 houses are being cracked and some are sinking into the drained water aquifers and the tunnel and more than 50,000 people are being denied access to drinking water. Several kilometers of the rivers and streams including part of the Kirindi Oya(river) have been completely dried up. Many families, women and children are living in those unsafe houses which might fallen in any moment due to heavy rain. Vegetable and flower farmers have become development refugees and now serve as the labourers in the construction sites in the cities. The damage is much higher than the total value of the project. There is no adequate legal remedy through the court and very little compensation has been delivered so far. No compensation has received for over 90% of the affected people.
Mr. Chairman, The long history of human rights violations perpetrated by Transnational Corporations and/or their agents have been documented worldwide. Such violations include extrajudicial killings, enforced disappearance, and other forms of harassment. Moreover, TNCs have caused colossal damage to the environment, leaving local communities unsafe and without sources of livelihood. Extending liability to IFIs will mitigate the difficulty in holding TNCs to account for their violations, as well as in identifying the transnational character of companies.
Lack of due diligence, weak safeguard measures, weak environmental impacts assessments process, lack of listening to public voices and lack of good governance and the unavailability of the legally binding instruments are few reasons for this damage.
IFIs such as ADB, WB, IaDB, EBRD and the AIIB have been obligated to establish Environmental and Social Safeguard Policies. These policies have emerged through decades of pressure from civil society and project affected communities pushing IFIs towards taking environmental and social responsibility of their lending operations and consequent adverse impacts. Local communities have often questioned these policies in their implementation and scope, as various IFIs fail to deliver their respective safeguards. The ADB's own Independent Evaluation Department in a report in 2015 identified widening gaps in ADB's safeguards policy and its implementation mechanism.
As the IFIs are protected by immunity, affected communities can only raise issues of redress and grievance through the IFIs own Accountability Mechanisms. These mechanisms serve as the only institutional platform through which project – affected people can elevate their grievances and call for remedy against harm and damages caused by IFI projects. Thus, lack of real remedial action on the ground and tedious and lengthy complaint filing and investigation processes leave local communities completely dependent on IFI responses, as immunity leads the courts and national judiciary to be inaccessible for harmed local communities.
With weak safeguards delivery and inefficient grievance mechanisms IFIs are left unaccountable of their actions. There needs to be a binding treaty, which yields IFIs to be accountable. As all IFIs are investing public funds there has to be a way for them to be accountable to the public. In the era of climate change, inequality and the new Sustainable Development Goals, the only way IFIs will be made responsible is through binding checks and balances in their operation. At present the immunity privilege of IFIs poses as a fundamental obstacle to their accountability and leads to an increased threat of harm from their actions in the future.
I propose there should be no immunity to the IFIs. Similarly, the tribunals or the accountability mechanisms do not have teeth to tackle these issues.
Mr. Chairman, The landmark judgement on the proposed Eppawela phosphate Mining project in Sri Lanka by the Freeport McMoran in year 2000, the Supreme Court of Sri Lanka stated
"The ancient chronicles record that when the King (Devanampiya Tissa) 247-207 B.C. was on a hunting trip (around 223 B.C.) the Arahat Mahinda, son of the Emperor Asoka of India, preached to him "O Great king, the birds of the air and the beasts have as equal a right to live and move about in any part of the land as thou. the land belongs to the people and other living beings; thou are only the guardian of it …."
Thus, governments have no rights to give away our territories and natural resources to TNCs against the wishes of our communities who hold the right over such territories. The TNCs or the IFIs are not the owners of our resources and our nature. They should be liable for the destruction of our territories. The UN Binding Treaty should be able to establish liability of IFIs that knowingly fund and continue to support companies responsible for human rights violations and environmental disasters. This will provide another layer of protection for those aggrieved by abuses committed by TNCs.
"We are ready to curb transnational corporations' impunity by driving the Treaty to the next level, after states adopt the chair's recommendations and conclusions towards the 2018 session when the zero draft of the Chair is negotiated. Any attempt by states to block or derail this process denying the right of affected people to justice will go down in history. The time to dismantle the walls of impunity is now"
Hemantha Withanage
Centre for Environmental Justice
Program Area: Economic Justice and Resisting Neoliberalism, Environmental Human Rights Defenders
Member Group: Centre for Environmental Justice

redpajama_set_name: RedPajamaCommonCrawl


text:
Political News » World News
December 11, 2020	| By Sikh Siyasat Bureau
Washington DC: The members of United states congress and international legal and human rights experts have urged India to uphold the right of peaceful protest and engage with protesting farmers productively following the norms of democracy.
Speaking at a webinar jointly organised by American Sikh Caucus Committee and United Sikhs on International Human Rights Day the co-chair of American Sikh congressional caucus Congressman John Garamendi stated, "As Co-Chair of the American Sikh Caucus in Congress, my office has received first hand accounts of the horrific crackdowns on protestors who are trying to peacefully express their disapproval of India's recent agricultural reform legislation. There is no excuse for brutally suppressing the voices of these protestors, and I implore the Indian government to cease its violent actions against its citizens and honor their peaceful assembly." Congressman T J Cox stated that the issue of protesting farmers has received due attention and support from the US Congress. He urged India to uphold the civil liberties and ensure the safety of the protesting farmers. He said all Americans stand in solidarity with the Punjabi farmers.
A view of the Zoom conference
International human rights expert and Member of UN global Steering committee Dr Iqtidar Cheema said that Freedom of peaceful assembly is endorsed by article 20 of UN Universal Declaration of Human Rights, Article 21 of UN international Covenant on Civil and Political Rights and article 5 of UN Declaration on Human Rights Defenders. He said that regrettably instead of taking appropriate measures to address the concerns of the protesting farmers; Government of India decided to use the state-led repression against the peaceful protestors. Police has used brutal force against the peaceful protesters and water cannon which are against the covenants of the UN.
Dr Daljit Singh eminent jurist and ex-Vice Chancellor of Riyat Bahara University explained the newly introduced laws in the context of Indian constitution. The webinar has also heard from Cathy Osten, Connecticut State Senator, Sukh Dhaliwal, Member of Canadian Parliament, Preet Gill, Member British parliament and other human rights experts and activists from India, US, Canada, Australia and UK.
Harpreet Sindhu, Director of American Sikh Caucus committee thanked the law makers and experts for their participation in the webinar. Dr Pritpal Singh, coordinator AGPC thanked the law makers and experts for standing in solidarity with the protesting farmers.
Related Topics: American Sikh Caucus Committee (ASCC), Farmers Protests 2020, Farmers' Issues and Agrarian Crisis in Punjab, Farmers' Struggle, Sikh Diaspora, Sikh News USA, Sikhs in United States, Sikhs in USA, United Sikhs


text:
NHS 'resistant to innovation from SMEs', survey finds
Three-quarters of small to medium-sized enterprises in the health technology sector have rated their experience of working with the NHS as "difficult" or "very difficult."
85% of UK-based SMEs identified overly-long decision-making times and finding the appropriate person in an organisation to speak to as barriers to working with the NHS, a new survey conducted by Health 2.0 has found.
Over 80% of respondents reported that NHS procurement processes are too complicated, while nearly 60% felt that there is a resistance within the Service to working with private-sector companies.
Moreover, only 30% of UK-based respondents said they have worked with Academic Health Science Networks (AHSNs), the organisations set up in April 2013 to work with the NHS, academia and the private sector to encourage innovation.
Commenting on the findings, Health 2.0's international director for health, Pascal Lardier, said: "it's very tough trying to do business with the NHS - a change of culture is needed from the decision-makers with budgets. There is a need for entrepreneurs to contribute to innovation in health to help health services cope with increasing demand and decreasing funds."
Nevertheless, health technology entrepreneurs are optimistic about the future. Half of those surveyed currently have revenues of $500,000 or less, but half of that group believe that, in 12 months' time, they will be earning $0.5-$1 million.
125 health sector SMEs responded to the survey, of which 82 (67%) were from the UK, 22 (18%) from the rest of Europe, 12 from the US (10%) and six (5%) from the rest of the world. Most sell their innovations to public and private hospitals, followed by clinicians and national health authorities, while 30% sell direct to patients and the public.
92% of the SMEs see a need for entrepreneurs to contribute to health innovations, and three-quarters believe that patients and health consumers are driving demand. However, when asked if healthcare professionals are encouraging e-health innovation, 37% agreed, 32% disagreed and 30% "sat on the fence," says Health 2.0.
44% felt the ecosystem - including health authorities, universities, medical centres and mentoring programmes – is not supporting their business, and 53% report that health data is not open and available to entrepreneurs.
And 59% says access to early-stage finance is "not good." Only a quarter believe that a long-term view is taken on health investments, with 47% saying this is not the case.
Eight UK groups pick up SBRI funding
UK SMEs get chance to access £5m SBRI fund
SMEs call for action to boost specialty pharma
http://www.health2.com.com


To be considered for the Headwaters New Play Festival, a play must never have had a professional production and the playwright must be available to attend the workshop week (August 23-27, 2016).
One of our goals this year is to more accurately reflect the diversity of human experience by including a play by a female playwright.
The deadline for submissions for the 2016 Headwaters New Play Festival is February 28th, 2016.
Responses will be sent out by March 15th, 2016. CRT will provide travel, housing, and a food stipend for the selected playwrights. Plays read at the festival will be considered for full production in CRT's 2017 season.
Creede Repertory Theatre, Attn: Headwaters, PO Box 269, Creede, CO 81130.


Lancashire coach Peter Moores believes Andrea Agathagelou has the ability to force his way into the Red Rose first team next season.
The South African is hoping to return to Lancashire League side Rishton next year after an impressive debut season as pro at Blackburn Road.
But he also turned heads at Old Trafford, finishing second leading run-scorer in Lancashire second XI's Championship campaign as well as helping them to the final of the Second XI Trophy while on a 12-month scholarship at the club.
And, with financial restrictions meaning Lancashire are unlikely to add to their squad over the winter and look certain not to have an overseas player next year, Moores feels Agathagelou could secure a place in the Red Rose side.
"He's an exciting cricketer and an exciting individual," said the former England coach. "When you speak to him, he's very confident. Not in an arrogant way but in a very focused and driven way.
"He had a tough start when he first came over last season because he had to get used to English conditions with the ball moving around a bit more.
"Then he found his feet and some form followed. Like all really good players, he cashed in.
"He was hungry to get runs and get runs again and then get runs again.
"He finished in the second team very strongly, getting runs in big games.
"He's young, and he'll make mistakes, but he looks like he's made of the right stuff. He's got a clear vision of what he wants, he's very positive and he's got talent.
"It's a great chance for him to come over with a view that if he does well, he could possibly push himself into first team cricket."
Although mainly a batsman, Agathagelou can also bowl leg-spin and keep wicket which, with Gareth Cross now the only senior wicketkeeper at Old Trafford following the departure of Luke Sutton, could come in useful.
Former South African Under-19 player Agathagelou, who turned 21 earlier this month, has continued his good form back at home this winter and scored a half-century in a first-class game for North West against Eastern Province last week.
Meanwhile Rishton all-rounder John Seedle has joined Ribblesdale League side Settle as player-coach for next season.
Seedle has had three spells at Blackburn Road – and also spent time at Accrington and Church – and has been at Rishton since 2006 for his latest time. He was part of the title-winning team in 2007.


pa iistam vai nee...bet izskataas labi!
Hey, what are you using for shooting and postediting?
love the photos on the website; no idea what all the comments are all about!!
photoshop?:)))) nerealjno kak-to:))))) no super!
ho4esh ugadaju... eto bilo v 4etverg! :))) klassno zape4atlil!


The Idaho Real Estate Center was founded in 2006 with a mission to provide unparalleled service to our clients and to make the experience of selling a home as positive and rewarding as possible. We truly care about the wants and needs of our clients. Our goal is to earn your trust, not just your business, and this is accomplished through our commitment to service, our vast knowledge of the real estate market, our positive attitude and our uncompromising integrity.
We know the decision to sell your home can be overwhelming. What is my home worth? Is now the right time to sell These, and many other questions, are probably consuming your thoughts. Then there's advertising your home, showings, contracts to negotiate, paperwork to complete, contingencies to schedule, etc. Rest assured our team will be with you every step of the way. Our knowledge of the real estate market and its neighborhoods will help you properly price your home and we will lead you through the negotiating and closing process to a positive conclusion.
We hope you will select us as a part of your team in this very important transaction. If, while making your decision, you have any questions or concerns, please do not hesitate to contact us.
Ask for a Free Home Evaluation: Our free market analysis will look at active, sold, and pending homes that may affect the value of your property. The Idaho Real Estate Center Team will provide you with detailed information on comparable properties to help you establish a marketing value for your home.
Sell Your Home with a Professional: With years of experience, and a commitment to staying on the leading edge of technology, our marketing systems are incredibly effective in maximizing the value of your home.
See What's on The Market: Use our state-of-the-art technology to search homes for sale in Idaho.
lConnect with a Professional: The Idaho Real Estate Center Team is standing by to assist you. Call or email us with any questions or if you're ready to get started.
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This is the required certification course to use the Big Hollow Shooting Range. No pre-registration required. Simply show up and upon completion of the ~2 hour course, you may purchase a range membership ($25/individual; $30/family). For more information, call our main office at (319) 753-8260.


text:
I Married a Muchkin
Tom Palazzolo |
Sale Format(s): DVD
Chicago filmmaker Tom Palazzolo's new documentary combines several of the filmmaker's longtime obsessions: the recording of the rituals and festivals that exist around the margins of popular culture, a documentation of remarkable but unrecognized Chicagoans, and the pursuit of his own unique brand of social commentary. These come together naturally in his telling of the story of the diminutive Mary Ellen St. Alban, whose vaudeville career began at the age of eleven and peaked in Hollywood in 1946 with her appearance as "Princess of the Elves" in Three Wise Fools. A year later she abandoned show business to marry Pernell St. Alban, best known for having played a Munchkin in The Wizard of Oz. The couple opened the Midget Club on Chicago's south side, which remained a well-publicized institution for 31 years.
Chesterton, Indiana's annual WIZARD OF OZ parade (as well as their many Oz-themed festivities) provides the backdrop for I MARRIED A MUNCHKIN, Tom Palazzolo's study of the life and career of Mary Ellen St. Aubin. Self-described as "normal, but little," Mary Ellen details her early start in show business as a performer in an all-dwarf vaudeville act, her brief appearance in 1946's THREE WISE FOOLS, her 1948 marriage to former Munchkin Parnell St. Aubin and their subsequent retirement from entertainment to run a bar (called the Midget Club) in the South Side of Chicago. Two other former Munchkins (Margaret Pellegrini and Clarence Swensen) briefly appear among the day's revelry. Also included is a postscript (shot some time after the initial film) featuring Mary Ellen briefly describing the original size of her role in THREE WISE FOOLS, which originally featured a line and an ill-fated "flying" effect. - Tom Fritsche
This title is available on Fandor:
https://www.fandor.com/films/i_married_a_munchkin
Purchase this Film


text:
\section{Introduction}
The classes of galaxies known as Luminous, Ultraluminous and
Hyperluminous Infrared Galaxies (LIRGs, ULIRGs and HyLIRGs), have been
a major subject of focus in observational cosmology since initial,
groundbreaking studies such as those of Soifer et al. (1986) and
Sanders et al. (1987). These objects, discovered in abundance by the
Infrared Astronomical Satellite (\emph{IRAS}), were found to possess
an array of extreme properties, including an excessive energy output,
effectively manifested as a large infrared/optical ratio (Sanders et
al. 1989). It is now widely accepted that the combination of a
powerful UV-photon source and the presence of substantial amounts of
dust are responsible for such extreme luminosities of the order of
$10^{10}$--$10^{14}$$L_{\odot}$ (e.g. Sanders $\&$ Mirabel 1996, Genzel et
al. 1998). Determining the nature of the central energy source has
been the subject of numerous subsequent studies, very often
supplemented by multiwavelength data (e.g. Gregorich et al. 1995,
Genzel et al. 1998, Rigopoulou et al. 1999, Klaas et al. 2001, Tacconi
et al. 2002, Alonso-Herrero et al. 2005). These have revealed
populations dominated by powerful starburst activity, but with a
non-negligible Active Galactic Nucleus (AGN) contribution found to
increase with bolometric luminosity (e.g. Veilleux et al. 1997, Tran
et al. 2001, Brand et al. 2006).

The processes responsible for energy production and radiation transfer
in the interstellar medium of such obscured systems are primarily
evaluated by studying galaxy Spectral Energy Distributions (SEDs), sometimes replacing
spectroscopic diagnostics in determining the nature of the central engine.  For infrared-luminous
objects, these processes are greatly influenced by the composition,
temperature and distribution of interstellar dust. Quantifying the
infrared energy budget is, therefore, key in determining the generic
properties of a galaxy and, as it is directly coupled to the central
energy source, important in estimating the integrated cosmic star
formation history. Cases where photometric data is scarce, benefit from
various methods of data extrapolation and interpolation: construction
of infrared SEDs has been a popular approach of modelling emission
from dusty systems, either directly from first principles or
semi-empirically, bridging together contributions from different parts
of the interstellar medium (e.g. Guiderdoni et al. 1998, Calzetti et
al. 2000, Rowan-Robinson 2000). Such models have enabled the
examination of sources with extreme properties and
pronounced infrared luminosity, either by solely considering star formation processes or
including contribution from AGN. In addition, establishing
correlations between monochromatic flux densities or luminosities has
proven extremely advantageous and has conveniently been used as a
first order approximation of the infrared energy budget, as well as a
diagnostic for the physical processes in galaxies, adopted extensively
in evolution studies (e.g. Franceschini et al. 2001).

In this paper we investigate the properties of 43 infrared-luminous
galaxies from one of the first deep \emph{Spitzer} far-IR
surveys. This sub-sample is part of a population of 178 sources
detected at 70\,$\mu$m by the Multiband Imaging Photometer on
\emph{Spitzer} (MIPS) (hereafter the 70\,$\mu$m population), down to a
limiting flux density of 4\,mJy at 5$\sigma$. In Symeonidis et
al. 2007 (hereafter S07), we gave a brief overview of the sources'
properties and derived Star Formation Rate (SFR) estimates. Here, we aim to gain qualitative insight into their
physical properties, primarily with respect to dust, comparing them to similar objects in the local universe. For
this purpose and to quantitatively characterise the sample, we fit our
photometry with three starburst dust models and a set of empirical
local galaxy templates.

The paper is set out as follows: Section 2 introduces our selection criteria for the
sub-sample, including an overview of infrared colours. Section 3
analyses and compares the model SED templates, associating the quality
of fits to the properties of the sources. We investigate the infrared
energy budget, with reference to SED characteristics such as the
continuum slope and far-IR peak, in section 4. Finally, section 5
focuses on the derivation of a set of equations to calculate the total
infrared luminosity in the range 8--1000\,$\mu$m, with at least one
MIPS band, for starburst-type sources. Our conclusions
and discussion are presented in section 6. In all subsequent calculations, we have employed the following values: $H_o=71$ kms$^{-1}$Mpc$^{-1}$, $\Omega_M=0.3$ and  $\Omega_{\Lambda}=0.7$.

\section{Introducing the Sample}

\subsection{Data sets and Selection Criteria}

Our main data set is a 70\,$\mu$m image of the Extended Groth Strip (EGS) field, taken by MIPS. In this $\sim$0.5 deg$^{2}$ field,
178 sources were recovered down to a limiting flux density of 4 mJy at
5$\sigma$. We direct the reader to Davis et al. (2007) and S07 for a detailed
description of all data sets acquired through the All-Wavelength
Extended Groth Strip International Survey (AEGIS). In this section, we briefly refer to
the Deep Extragalactic Evolutionary Probe 2
(DEEP2) spectroscopic survey, the \emph{Spitzer} Infrared Array Camera (IRAC)
survey and the MIPS survey.

70 and 90 per cent of the MIPS 70\,$\mu$m area is also covered by the
IRAC survey and MIPS 24 and 160\,$\mu$m images, respectively. Within the
overlap areas of all 8, 24 and 160\,$\mu$m images, we recover 100
per cent of our targets, a
total of 122 sources (hereafter, the \emph{full sample}). Of these, 103 also appear in the remaining three IRAC
bands (3.6, 4.5 and 5.8\,$\mu$m). DEEP2 obtained optical spectra for $\sim$14,000 objects in the EGS
with a limiting magnitude of $R_{AB}=24.1$, using the DEIMOS
spectrograph on the Keck telescopes (Davis et al. 2003). In the
overlapping area ($\sim$75 per cent) between the MIPS 70\,$\mu$m image
and the DEEP2 EGS survey, 43 reliable (quality factor $\ge$3)
spectroscopic redshifts ($z_{spec}$) were retrieved in the range
$0.1<z<1.2$, with a mean of 0.57 and a median of 0.51. For the
remaining objects, some made the photometric cut but were assigned a
poor quality redshift.

\begin{table*}
\begin{minipage}{126mm}
\caption{The redshift sample (43 sources) - Object cardinal numbers
  with the prefix EGS70 referring to the 70$\mu$m EGS survey, coordinates,
  spectroscopic redshifts, R-band magnitudes (AB), measured flux densities
  at 24, 70 and 160\,$\mu$m. The MIPS 24\,$\mu$m calibration
  uncertainty is 10 per cent, whereas for MIPS 70 and 160\,$\mu$m it is 20 and 30 per cent, respectively.}
\begin{tabular}{|c|c|c|c|c|c|c|c|}
ID & ra (J2000)& dec (J2000)& z$_{spec}$ & R mag (AB) &f$_{24}$ &f$_{70}$&f$_{160}$ \\
& h m s& deg min arc&  & &(mJy)  &(mJy)  & (mJy)  \\
\hline
      EGS70-41 &  14 24 26.1  & +53 37 23.0 &      0.45 &       20.9 &    1.3 &     44.1    &      117.6 \\
      EGS70-51 &  14 24 34.3  & +53 36 05.4 &      0.22 &       18.6 &   0.9 &    6.9 &     29.1 \\
      EGS70-55 &  14 24 28.2  & +53 36 44.6 &      0.67 &       21.6 &   0.6 &     16.9 &     60.0 \\
      EGS70-58 &  14 25 02.8  & +53 31 25.5 &      0.69 &       22.3 &   0.3 &     10.4 &      115.2 \\
      EGS70-67 &  14 24 30.1  & +53 35 42.9 &      0.96 &       22.1 &    1.0 &     11.6 &     85.7 \\
      EGS70-70 &  14 24 41.5  & +53 33 43.2 &      0.78 &       21.3 &   0.46 &     14.6 &      104.5 \\
      EGS70-72 &  14 24 55.0  & +53 30 04.6 &      0.39 &       20.4 &   0.76 &     11.8 &     23.0 \\
      EGS70-76 &  14 24 29.6  & +53 31 21.3 &      0.73 &       22.6 &   0.11 &     10.5 &     10.2 \\
      EGS70-77 &  14 23 43.1  & +53 35 06.1 &      0.42 &       19.2 &    1.4 &     22.3 &      148.8 \\
      EGS70-78 &  14 24 08.2  & +53 31 22.3 &      0.37 &       20.3 &    1.0 &     15.5 &     57.2 \\
      EGS70-82 &  14 23 49.6  & +53 31 35.4 &       1.03 &       23.4 &   0.38 &     21.7 &     64.3 \\
      EGS70-84 &  14 23 48.8  & +53 30 09.0 &      0.77 &       22.0 &   0.99 &     13.9 &     99.3 \\
      EGS70-85 &  14 24 01.2  & +53 27 54.4 &      0.43 &       19.9 &   0.95 &     12.0 &     38.1 \\
      EGS70-88 &  14 23 49.4  & +53 26 29.8 &      0.78 &       21.5 &    1.68 &     40.0 &      111.5 \\
      EGS70-93 &  14 23 16.1  & +53 30 47.4 &       1.2 &       22.6 &   0.69 &     14.1 &      130.5 \\
      EGS70-94 &  14 23 30.9  & +53 28 22.5 &       1.02 &       21.7 &   0.67 &     11.5 &     82.5 \\
      EGS70-98 &  14 23 35.4  & +53 26 12.3 &      0.29 &       20.1 &    1.85 &     14.9 &     48.3 \\
     EGS70-100 &  14 23 31.6  & +53 26 25.1 &      0.3 &       19.3 &    2.5 &     35.9 &     68.7 \\
     EGS70-103 &  14 23 39.6  & +53 22 32.0 &      0.25 &       19.0 &   0.9 &     12.9 &     60.6 \\
     EGS70-110 &  14 23 18.2  & +53 24 53.5 &      0.42 &       21.3 &   0.5 &     30.5 &     48.6 \\
     EGS70-114 &  14 23 01.6  & +53 24 20.7 &      0.66 &       20.8 &    1.1 &     16.6 &     76.8 \\
     EGS70-115 &  14 23 12.7  & +53 22 16.0 &      0.38 &       20.1 &    1.2 &     14.2 &     57.5 \\
     EGS70-120 &  14 23 22.8  & +53 19 29.2 &      0.57 &       21.6 &   0.5 &    8.9 &     25.8 \\
     EGS70-121 &  14 23 00.1  & +53 21 51.9 &      0.78 &       22.1 &   0.7 &    7.7 &     25.2 \\
     EGS70-122 &  14 22 50.0  & +53 22 53.3 &      0.28 &       19.4 &    1.0 &     14.6 &     74.1 \\
     EGS70-124 &  14 22 39.1  & +53 24 20.3 &      0.85 &       21.3 &    1.1 &     13.9 &     61.1 \\
     EGS70-125 &  14 22 47.3  & +53 22 20.2 &      0.25 &       20.7 &   0.7 &     11.3 &     44.5 \\
     EGS70-126 &  14 23 14.7  & +53 17 59.5 &      0.42 &       21.2 &   0.6 &     29.5 &     41.4 \\
     EGS70-134 &  14 22 56.3  & +53 17 10.1 &      0.75 &       21.9 &   0.4 &    4.8 &     46.2 \\
     EGS70-137 &  14 23 05.7  & +53 15 28.1 &      0.48 &       20.1 &   0.75 &     14.4 &      103.5 \\
     EGS70-138 &  14 22 22.3  & +53 21 58.2 &      0.42 &       21.1 &   0.26 &    7.5 &     32.5 \\
     EGS70-140 &  14 22 25.4  & +53 20 30.0 &      0.46 &       19.4 &   0.57 &     10.7 &     43.8 \\
     EGS70-141 &  14 22 11.8  & +53 19 50.0 &      0.70 &       22.7 &   0.54 &     11.4 &    7.3 \\
     EGS70-144 &  14 22 36.8  & +53 15 01.1 &      0.19 &       19.3 &   0.75 &     13.0 &     37.0 \\
     EGS70-146 &  14 22 18.1  & +53 16 43.6 &      0.46 &       20.1 &   0.64 &    8.9 &     28.5 \\
     EGS70-147 &  14 21 54.3  & +53 19 51.4 &      0.67 &       22.3 &   0.49 &    8.8 &     44.2 \\
     EGS70-149 &  14 22 21.1  & +53 14 33.9 &      0.51 &       20.3 &   0.69 &     14. &     64.6 \\
     EGS70-150 &  14 21 55.4  & +53 18 10.4 &      0.74 &       22.0 &   0.71 &    6.1 &     22.1 \\
     EGS70-152 &  14 22 31.1  & +53 12 37.5 &      0.37 &       20.0 &   0.98 &     13.1 &      124.4 \\
     EGS70-155 &  14 22 17.7  & +53 14 32.7 &      0.17 &       18.6 &    1.2 &     16.7 &     11.2 \\
     EGS70-158 &  14 21 37.5  & +53 17 17.8 &      0.93 &       22.1 &    1.4 &     30.2 &      143.4 \\
     EGS70-165 &  14 21 55.9  & +53 14 22.1 &      0.77 &       21.7 &    2.8 &     16.7 &     28.0 \\
     EGS70-172 &  14 21 41.1  & +53 15 03.8 &      0.48 &       23.1 &   0.2 &     13.2 &     85.7 \\
\end{tabular}
\end{minipage}
\end{table*}

For the purpose of this work we select a sub-sample of the 70 $\mu$m
population (table 1) (hereafter, the \emph{redshift sample}), which we
require to be within the common area of the IRAC 8\,$\mu$m and the
MIPS 24 and 160\,$\mu$m images, in order to sample the entire
available infrared SED. The criteria are as follows:
\begin{itemize}
\item 8\,$\mu$m photometry from the IRAC survey
\item 24 and 160\,$\mu$m photometry from the MIPS surveys
\item a reliable spectroscopic redshift from DEEP2
\end{itemize}
It is the latter criterion which forms the basis of the
selection, as the former two are always satisfied within the overlap
regions. 34 objects in the redshift sample also appear in the 3.6,
4.5 and 5.8\,$\mu$m IRAC bands. The MIPS (24, 70 and 160\,$\mu$m)
colours of the redshift and full samples are similar (figure
\ref{fig:mipscolours}); apart from a few objects at the
extremes of the 160/70 colour, for the majority of the population the
received flux at 160\,$\mu$m is more than twice that at 70\,$\mu$m and
shows no dependence on redshift or the strength of the 24\,$\mu$m mid-IR emission.

\begin{figure}
\epsfig{file=fig1,width=8cm}
\caption{Infrared colours for the full sample - ratio of 160\,$\mu$m $\nu f_{\nu}$ to 70\,$\mu$m $\nu
  f_{\nu}$ versus 24\,$\mu$m $\nu f_{\nu}$. Asterisks represent
  R\,$>$\,24.1 sources with no z$_{spec}$, while the rest of the
  symbols are divided into z\,$\leq$\,0.5 (empty circles), z $>$ 0.5 (filled
  circles) and R\,$<$\,24.1 sources with no z$_{spec}$ (crosses). The blue diamond symbol corresponds to the object we identified as AGN-dominated (see discussion in section 2.2). }
\label{fig:mipscolours}
\end{figure}

\begin{figure}
\epsfig{file=fig2,width=8cm}
\caption{The optical to far-IR SEDs of the 43 objects in the redshift
  sample. They are split into 3 luminosity classes - Starbursts (red),
  LIRGs (green) and ULIRGs (blue). Due to the flux density limits of
  the 70\,$\mu$m survey, an increase in total infrared luminosity
  corresponds to increasing redshift, with all starbursts at z $\leq$
  0.25 and all ULIRGs at z\,$\geq$\,0.65. The AGN-dominated SED (see section 2.2) is shown in black. The photometry
  (\textit{BRIJK}, 3.6, 4.5, 5.8, 8, 24, 70 and 160\,$\mu$m) is
  redshift-corrected.}
\label{fig:seds}
\end{figure}

\subsection{Spectral Energy Distributions}
The SEDs of the 43 sources in the redshift sample are shown in figure
\ref{fig:seds}. They are separated into three groups with respect to
the total infrared luminosity in the 8--1000\,$\mu$m range ---
Starbursts ($10^{10}-10^{11} L_{\odot}$), LIRGs ($10^{11}$--$10^{12}$
$L_{\odot}$) and ULIRGs ($10^{12}-10^{13} L_{\odot}$) (see section 4). The SED of an object which displays a clear power-law near-IR
continuum is in black. This was eliminated through examination of IRAC colours
commonly used to identify objects whose SED is AGN-dominated (e.g. Lacy
et al. 2004, Stern et al. 2005).

An obvious trend in the SEDs is the reduction of the stellar bump with
respect to the infrared continuum, for objects of increasing luminosity and, as this is a flux limited survey, redshift. A similar observation was made by Alonso-Herrero et
al. (2006), who found the stellar bump greatly reduced or completely
wiped out in local ULIRGs. This could be a direct consequence of an
increasing AGN versus starburst dominance, indicating
the tendency towards a power-law near-IR continuum or simply due to
the fact that the more
infrared-luminous galaxies will be
fainter in the optical because of increased extinction. For the lower-redshift objects, the 6.2 and/or 7.7\,$\mu$m PAH
features are redshifted into the  8\,$\mu$m band, which displays a
clear increase in flux. Contrary to the pronounced differences in the near-IR, the mid/far-IR
(24-160\,$\mu$m) part of the SEDs makes them indistinguishable; this
has also been noted by other authors, e.g. Klaas et al. (2001) and it is
potentially indicative of the fact that far-IR emission is independent from the nature of
the central energy source.

\section{SED fitting}

In past years, there have been numerous efforts to characterise and
reproduce galaxy SEDs with model templates (e.g. Rowan-Robinson 1980,
1995, Appleton et al. 2004). These have been developed either
semi-empirically or by applying detailed radiation transfer
calculations; in either case there has been reasonable success
with respect to the models' representation of real systems
(e.g. Efstathiou $\&$ Rowan-Robinson 1990, Granato 1994, Silva 1998,
Rowan-Robinson et al. 2005, Efstathiou, Rowan-Robinson $\&$
Siebenmorgen 2003, Siebenmorgen $\&$ Kr\"ugel 2007). Our motive for SED
fitting is to determine the infrared energy
budget of each source and gain insight into its physical
properties. Since the redshift sample mostly displays SEDs typical of
starburst galaxies, we
require models of radiative transfer through
dusty media, considering solely starburst processes. Accordingly,
object 165, whose SED we evaluate as AGN-dominated (see section 2.2), is not included in our
analysis. Nevertheless, we do not exclude a strong AGN contribution in the remaining galaxies. Simply, at this stage, due to the
extremely obscured nature of these objects, we cannot reach any further
conclusions without exploring their multiwavelength properties, which
is beyond the scope of this paper.

We use the Chary $\&$ Elbaz (2001, hereafter CE01), Dale $\&$ Helou
(2002, hereafter DH02) and Siebenmorgen $\&$ Kr\"ugel (2007, hereafter
SK07) libraries, selected on account of their diverse frameworks
and the fact that they span a wide range in infrared luminosity ($10^{9}$ --$10^{14}
L_{\odot}$), from star-forming galaxies to HyLIRGs. In
subsection 3.1 we touch upon the main characteristics of the models
that are relevant to our study. For a more detailed report, we refer
the reader to the relevant papers.

\begin{figure*}
\epsfig{file=fig3,width=15cm}
\caption{SEDs for the first 21 objects from the redshift sample fitted
  with the CE01 (black dashed curve), DH02 (red dotted curve) and
  our empirical templates (blue dot-dashed curve). Only the best-matched (lowest $\chi^2$)
  template is shown. The filled circles are Spitzer
broadband data for the redshift sample, including calibration errors of 10 per cent
for the IRAC and MIPS 24\,$\mu$m photometry, 20 per cent for MIPS
70\,$\mu$m and 30 per cent for MIPS 160\,$\mu$m. All photometry has
  been colour-corrected and redshift-corrected so the plots are at z$\sim$0.}
\label{fig:badsed}
\end{figure*}

\begin{figure*}
\epsfig{file=fig4,width=15cm}
\caption{SEDs for the remaining 21 objects from the redshift sample
  fitted with the CE01 (black dashed curve), DH02 (red dotted curve)
  and our
  empirical templates (blue dot-dashed curve). Only the
  best-matched (lowest $\chi^2$) template is shown. The filled circles are Spitzer
broadband data for the redshift sample, including calibration errors of 10 per cent
for the IRAC and MIPS 24\,$\mu$m photometry, 20 per cent for MIPS
70\,$\mu$m and 30 per cent for MIPS 160\,$\mu$m. All photometry has
  been colour-corrected and redshift-corrected so the plots are at z$\sim$0.}
\label{fig:badsed2}
\end{figure*}

\begin{figure*}
\epsfig{file=fig5,width=15cm}
\caption{SEDs for the first 21 objects from the redshift sample fitted
  with the SK07 templates. The red curves represent the matches with
  the lowest $\chi^2$ values (see section 3.3), fitted on 8, 24, 70
  and 160\,$\mu$m photometry. The green curve represents the match
  with the lowest $\chi^2$ value when fitted on 3.6, 4.5, 5.8, 8, 24,
  70 and 160\,$\mu$m photometry. The filled circles are Spitzer
broadband data for the redshift sample, including calibration errors of 10 per cent
for the IRAC and MIPS 24\,$\mu$m photometry, 20 per cent for MIPS
70\,$\mu$m and 30 per cent for MIPS 160\,$\mu$m. All photometry has
  been colour-corrected and redshift-corrected so the plots are at z$\sim$0.}
\label{fig:goodsed}
\end{figure*}

\begin{figure*}
\epsfig{file=fig6,width=15cm}
\caption{SEDs for the remaining 21 objects from the redshift sample
  fitted with the SK07 templates. The red curves represent the matches
  with the lowest $\chi^2$ values (see section 3.3), fitted on 8, 24,
  70 and 160\,$\mu$m photometry. The green curve represents the match
  with the lowest $\chi^2$ value when fitted on 3.6, 4.5, 5.8, 8, 24,
  70 and 160\,$\mu$m photometry. The filled circles are Spitzer
broadband data for the redshift sample, including calibration errors of 10 per cent
for the IRAC and MIPS 24\,$\mu$m photometry, 20 per cent for MIPS
70\,$\mu$m and 30 per cent for MIPS 160\,$\mu$m. All photometry has
  been colour-corrected and redshift-corrected so the plots are at z\,$\sim$\,0.}
\label{fig:goodsed2}
\end{figure*}

\subsection{The dust models}

The CE01 SED templates are based on the models of Silva et al. (1998,
hereafter S98). S98 employ a stellar population synthesis framework,
using Simple Stellar populations (SSP) of different age and
metallicity, including circumstellar dust shells/outflows of AGB
stars that continuously enrich the ISM. Two types of environments are
responsible for the infrared continuum - dust emission associated with
starforming molecular clouds and a cirrus component associated with
the intensity of the stellar field. CE01 generate template SEDs, in
the UV--submm range, of four prototypical galaxies, Arp 220, NGC 6090,
M82, and M51, corresponding to four luminosity classes: ULIRGs, LIRGs,
starbursts and normal galaxies. They partition the four SEDs into mid
and far-infrared components and interpolate between them to create a
set of templates with a range of luminosities, from which they select
the ones which correspond to observed ranges of \emph{IRAS} and
Infrared Space Observatory (\emph{ISO}) colours.

The DH02 templates are based on the work of Desert, Boulanger $\&$
Puget (1990, hereafter DBP90). DBP90 introduce an empirical model
combining emission from Very Large Grains (VLGs) in thermal
equilibrium, stochastically heated Very Small Grains (VSGs) and
Polycyclic Aromatic Hydrocarbon (PAH) features, in radiation fields of
varying intensity. DH02 produce a set of semi-empirical infrared SEDs,
the shape of which is determined by the intensity $U$ of the
interstellar radiation field. They develop a power law dependence of
the dust mass on the value of $U$, the outcome of which is a collection
of dusty environments immersed in a range of radiation fields,
representing a mixture of active and quiescent regions. Their SEDs are
further constrained by \emph{IRAS} and \emph{ISO} observations of
local star-forming galaxies with $L_{IR}$ ranging from  $10^{8}$ to
$10^{12} L_{\odot}$. In addition they vary the emissivity index
$\beta$, which relates the emissivity of dust grains to
the wavelength of emission.

The SK07 model SEDs are built on the formulation of Kr\"ugel $\&$
Siebenmorgen (1994), who present a modified definition of a starburst
nucleus: instead of a central radiating point source, they employ a
configuration where stars are distributed throughout the volume,
introducing `Hot Spots' - dust regions enveloping OB
stars. Correspondingly, in their calculations, the dust temperature is
varied both in the locality of each star as well as with distance from
the nucleus. Furthermore, since part of the stellar flux is absorbed
within the hot spot and re-radiated in the IR, their formulation replaces some OB stars by
IR-emitting hot spots. This has the effect of reducing the overall
temperature, whilst keeping mid-IR emission unchanged, as this is
considered to be linked to the density of dust within the hot
spot. All other stars are treated separately and are assumed to
contribute to the far-IR part, `cirrus' component of the SED. Their
library of $\sim$\,7000 templates ranges in 5 free parameters, in
physically acceptable combinations: radius of dust emitting region,
total luminosity, visual extinction and hot spot
dust density. The fifth
parameter, $L_{OB}/L_{tot}$, represents the percentage of the total
infrared luminosity that originates from OB stars, compared to the
contribution from the general stellar population and a result it has a direct effect
on the near-IR flux and the representation of the near-IR stellar bump.

\subsection{Our empirical templates}
In addition to the models and as a consistency check, we fit a set of
real galaxy templates, which we construct
by combining spectral and photometric data of local starbursts. The templates are built on a collection of mid-IR (5--38\,$\mu$m)
\emph{Spitzer} InfraRed Spectrograph (IRS) spectra (courtesy of Brandl et al. 2006) from the central
region of 16 local Starbursts, as well as \emph{IRAS} broadband
data (12, 25, 60 and 100\,$\mu$m) from the NASA Extragalactic Database
(NED). The far-IR/submm region (longward of 60\,$\mu$m) is fitted with
a modified black-body emission law, as it is considered to sample
emission from cool dust in equilibrium heated by the interstellar
medium. This
is of the form $B_{\lambda}(T)(1-e^{- \tau _{\lambda}})$, with a
wavelength dependent
optical depth
$\tau_{\lambda}=\tau_{100 \mu m}(100 \mu m/\lambda)^{\beta}$ (e.g. see
Klaas et al. 2001) and a dust emissivity index $\beta$. We assume a low opacity limit, so approximate the
term $(1-e^{- \tau _{\lambda}})$ by
$\lambda^{-\beta}$. Typical reported values of $\beta$ range between
1.5--2 (e.g. Dunne et al. 2000, Lisenfeld, Isaak $\&$ Hills 2000),
so we adopt $\beta$=1.5, consistent with studies of the far-IR emissivity of large
grains (Desert, Boulanger $\&$ Puget 1990). The greybody
temperature is allowed to vary in order to minimise $\chi^{2}$ on the
60--100\,$\mu$m region, resulting in a temperature range of 30--50
K. These 16 empirical SED templates vary with respect to total infrared
luminosity, position of far-IR peak and mid-IR continuum slope.

\begin{table*}
\begin{minipage}{126mm}
\caption{Parameters corresponding to the SK07 templates, fitted with
  photometry at 8, 24, 70 and 160\,$\mu$m, that produced the lowest
  $\chi ^2$ matches (used in subsequent calculations). The columns
  are as follows: Object ID, radius of the central nuclear region
  (kpc), ratio of the luminosity from OB stars to the total luminosity
  ($L_{OB}/L_{tot}$), total visual extinction measured from the
  surface to the centre of the starburst ($A_v$) and density within
  the hot spots $\rho$ ($cm^{-3}$). Where a range is quoted, e.g.
  $\rho$=100--10000, each of the matched models came up with a value of
  $\rho$  between those limits. Where there is a coma, e.g. 100, 10000,
  each of the matched models had either $\rho$ of 100 or 10000, but not in between.}
\begin{tabular}{|c|c|c|c|c|}
ID &  Nuclear radius & $L_{OB}/L_{tot}$  & $A_v$ & $\rho $ \\
 &  (kpc) & ($\%$) & & ($cm^{-3}$)\\
\hline
41 &0.35,3 &40,60 &35.9,72 & 100--5000\\
51 &3 & 40,90& 35.9,67.3& 10000\\
55 & 0.35,3 & 40,60& 35.9,72 &100--10000 \\
58 &0.35,1,3  & 40,60&119,144 & 5000,10000\\
67 &1,3  &60 & 35.4,35.9& 10000\\
70 &0.35,1 &40,60 &119,144 & 5000,10000\\
72  &1,3 &40  &2.2--35.9 &1000--10000\\
76  &0.35,1 & 40,60,90&35.9--119&100,10000 \\
77 &1,3 &40,60 & 35.9--72&2500, 10000 \\
78 & 3& 40,60& 35.9,72 &2500,10000  \\
82 & 1,3& 60,90&  18--72& 100--10000 \\
84 & 1,3& 60& 70.7,72 & 10000 \\
85 & 1,3& 40& 2.2,35.9 & 1000,10000\\
88 &0.35,3 & 60,90& 72,120& 10000 \\
93 &0.35,1 & 40,60&35.4--72 & 10000 \\
94 & 1,3& 40&35.4,35.9 & 10000 \\
98 & 1,3&40,60 &4.5--35.4 & 2500,10000  \\
100 &3 & 60,90&2.2--6.7& 100 \\
103 &1,3 & 40,60,90& 2.2--70.7& 100--10000 \\
110 & 0.35,1& 40,60,90& 35.4--144&1000,10000  \\
114 &3 &40 &17.9 & 2500  \\
115 & 3& 40,60& 2.2--72& 1000,10000  \\
120 & 1,3& 40&2.2--9 & 1000,2500  \\
121 & 1,3& 40,60&9--35.9 &  5000\\
122 & 0.35,3& 40,60&35.9--120 &5000,10000  \\
124 & 1,3& 40&17.9,35.9& 7500,10000 \\
125 & 3& 60& 2.2,4.5& 100 \\
126 & 0.35,1& 40,60,90&4.5--17.9 & 100 \\
134 & 1,3&40,60 & 70.7,72& 10000 \\
137 & 1,3& 40& 17.9--72&1000,10000  \\
138 & 1,3& 40& 35.9--72&1000,10000  \\
140 & 1,3&40,60 &9--70.7& 1000--10000 \\
141 & 0.35,1& 40,60&2.2--35.9 & 100--10000 \\
144 & 3&40,60 &2.2 & 100 \\
146 & 1,3&40 & 4.5--35.9&1000,10000  \\
147 &3 &40 &17.9,35.9 & 2500 \\
149 &1,3 & 40&6.7--35.9 & 1000--10000 \\
150 &1,3&60 &17.9,35.9&7500,10000  \\
152 & 1,3& 40,60& 70.7,72& 10000 \\
155 & 0.35,1&40,60,90 & 2.2--6.7& 100 \\
158 & 0.35,3& 40,60&35.9,72 & 2500--10000 \\
172 &0.35 & 40,60,90& 144& 2500\\
\end{tabular}
\end{minipage}
\end{table*}

\subsection{Model Comparison}
The best (lowest $\chi^2$) SED matches for the redshift sample are shown in figures
\ref{fig:badsed}--\ref{fig:goodsed2}. All photometry has been
colour-corrected according to the specifications in the IRAC and MIPS
data handbooks. With the CE01 and DH02 SEDs
we use all available IRAC photometry and the three MIPS bands. In the
case of our empirical SEDs, only the 8--160\,$\mu$m region is taken
into account, because the templates do not extend to short wavelengths. The SK07 models do not treat the near-IR emission in detail, so the fits are approached in two
ways: we fit the 3.6--160\,$\mu$m region (where IRAC photometry is
available) and the 8--160\,$\mu$m region separately. For the latter all
matches with similarly low $\chi^2$ values are kept, in order to increase the accuracy of the
results, since the library contains $\sim$7000 SEDs and limiting the number of
photometric points for the $\chi^2$, dramatically reduces the constraints
on the chosen templates. Furthermore, near-IR photometry is fit with slightly
increased errors in order to take into account the weakness of the
models in that region.

In the mid-IR ($\lambda_{rest}$\,$<$\,40\,$\mu$m) all templates
deliver the emission/absorption lines and continuum slope with the
same consistency; in some cases the 8\,$\mu$m colour-corrected flux
samples a PAH feature (e.g. objects 98, 100, 103, 122,
125). However, there are large discrepancies in the 10\,$\mu$m
silicate absorption depth. For the CE01 and DH02 templates it
seems to vary over a small range; this is not the case for the SK07
SEDs, where it can be 50--100 times below the continuum
(e.g. see objects 58, 70, 76, 82, 110). This is a direct consequence of
SK07 incorporating dust self-absorption in their models, an effect
assigned to increasing quantities of dust at low temperatures
(e.g. Mitchell $\&$ Robinson 1981), resulting in an overall shift
of the far-IR peak to longer wavelengths. Our photometry misses the
silicate feature so we cannot constrain its depth, nevertheless its
varied strength in the models is consistent with observations as it is commonly found in LIRG $\&$ ULIRG spectra (e.g. Hao et
al. 2007, Armus et al. 2007) and its existence is correlated with the
magnitude of extinction.

The differences between the templates are more striking in
the far-IR ($\lambda_{rest}$\,$>$\,40\,$\mu$m). The SK07 models are in good agreement with the
data. In addition, most 3.6--160\,$\mu$m fits result in templates
with similar characteristics to the 8--160\,$\mu$m fits, showing that the far-IR is well
constrained even without the $<$\,6\,$\mu$m region. On the contrary, DH02 and
CE01 often underproduce the 160\,$\mu$m flux, by an amount significantly
higher than the 30 per cent photometric uncertainty and up to a factor
of 10 in extreme cases (e.g. see objects 58,
70, 84, 93, 94, 110, 134, 137, 138, 152, 172 for which the effect is
more exaggerated). Moreover, it is worth noting that most objects for
which the far-IR is completely underestimated by
CE01 and DH02, have a ratio of
$L_{70}/L_{24}>$\,3.4 (table 3), suggesting that a steep mid-IR
continuum and a high far-IR flux are contradictory features in these templates.

\begin{figure*}
\epsfig{file=fig7,width=15cm}
\caption{The K-corrected, rest frame luminosity ratios $L_{70}/L_{24}$,
  $L_{160}/L_{70}$ as a function of the total infrared luminosity. All
  units are $L_{\odot}$ and the 1$\sigma$ uncertainties are shown.}
\label{fig:lumratios}
\end{figure*}

\begin{figure*}
\epsfig{file=fig8,width=15cm}
\caption{The position of the rest frame SED peak (in $\mu$m) as a
  function of the K-corrected, rest frame $L_{70}/L_{24}$ ratio (left panel) and
  $L_{160}/L_{70}$ ratio (right panel). $L_{24}$, $L_{70}$ and $L_{160}$ are
  in units of $L_{\odot}$ and the 1$\sigma$ uncertainties are shown. The colours correspond to the luminosity
  class: black for Starbursts, red for LIRGs and green for ULIRGS.}
\label{fig:lratiopeak}
\end{figure*}

Table 2 shows the parameters generated from the best matched
SK07 templates. The nuclear radius represents the region of total dust
emission from the entire stellar population, with the OB stars only
confined to the inner 350pc. The majority of best fit models are
described by a radius of 3kpc, suggesting
emission from extended regions of cool dust. In terms of visual
extinction, the matches span the whole
available range of $2 < A_v < 144$. Taking into account the
variations of $A_v$ for each object with respect to each template, it is
worth noting that only 5 out of 42 galaxies are matched solely with
$A_v<10$ templates, the remaining
appearing mostly with $A_{v} \sim$ 35 or 70, implying
high obscuration in these systems. Finally, the value of hot spot dust
density, which is directly related to the strength of mid-IR emission appears to have a
wide range in values, but in most objects it reaches the maximum
of $\rho$\,=\,10000\,cm$^{-3}$.

\begin{table*}
\begin{minipage}{126mm}
\caption{The infrared budget and SED characteristics of the redshift sample. Column 1
  classifies the objects according to their luminosity. Columns 2 and
  3 are the Object ID and redshift, columns 4 and 5 are the
  K-corrected, rest-frame
  $L_{70}/L_{24}$ and $L_{160}/L_{70}$ ratios. Columns 6 and 7 quote
  the average value of the total infrared luminosity $L_{IR}$ (in units of
  $\times 10^{10}L_{\odot}$) and its logarithm. The position of the
  far-IR turnover is displayed in column 8. All
  uncertainties are 1$\sigma$.}
\begin{tabular}{|c|c|c|c|c|c|c|}
Type & ID& $L_{70}/L_{24}$ & $L_{160}/L_{70}$ & $L_{IR} \times 10^{10}(L_{\odot})$ &$ log L_{IR}$ & peak (rest, $\mu$m) \\
\hline
&      51&       1.86&       1.52&       4.32$\pm$      0.23&       10.64&       140$\pm$
       14\\
&     155&       3.00&      0.17&       2.89$\pm$      0.2&       10.46&       55$\pm$
       2\\
SBs&     125&       4.10&      0.55&       6.35$\pm$      0.72&       10.81&       79$\pm$
       5\\
&     144&       5.56&      0.61&       4.10$\pm$      0.49&       10.61&       86$\pm$
       2\\
\hline
SB/LIRG&     103&       3.45&      0.95&       8.79$\pm$       1.31&       10.94&       98$\pm$
       28\\
\hline

&     141 &      0.96 &      0.10 &       36.54$\pm$       1.66 &       11.56 &       41$\pm$       3\\
&     121 &       1.59 &       1.04 &       72.07$\pm$       8.26 &       11.86 &       111$\pm$       17\\
&     150 &       1.62 &       1.29&       58.88$\pm$       9.01 &       11.77 &       117$\pm$       22\\
&      98 &       2.27 &      0.75 &       11.97$\pm$      1.0 &       11.08 &       95$\pm$       7\\
&     100 &       2.51 &      0.42 &       22.68$\pm$       1.48 &       11.36 &       64$\pm$       5\\
&      78 &       2.62 &       2.01 &       34.27$\pm$       1.03 &       11.53 &       141$\pm$       13\\
&     120 &       2.80 &      0.49 &       31.15$\pm$       2.84 &       11.49 &       78$\pm$       5\\
&     152 &       2.84 &       2.09 &       37.41$\pm$       8.58 &       11.57 &       140$\pm$       18\\
&     115 &       2.88 &       1.22 &       26.50$\pm$       7.93 &       11.42 &       114$\pm$       23\\
&      85 &       2.88 &      0.57 &       23.73$\pm$       2.32 &       11.37 &       84$\pm$       8\\
&      76 &       3.00 &      0.11 &       35.41$\pm$       3.65 &       11.55 &       50$\pm$       3\\
&      72 &       3.02 &      0.47&       13.81$\pm$      0.87 &       11.14 &       78$\pm$       5\\
&     147 &       3.03 &       1.26 &       74.57$\pm$       16.67 &       11.87 &       113$\pm$       22\\
 LIRGs &   122 &       3.24 &       1.15 &       12.11$\pm$       2.31 &       11.08 &       109$\pm$       13\\
&      77 &       3.33 &       2.08&       81.11$\pm$       16.14 &       11.91 &       135$\pm$       15\\
&     146 &       3.34 &      0.63 &       21.24$\pm$      0.98 &       11.33 &       90$\pm$       7\\
&     140 &       3.35 &       1.29 &       31.18$\pm$       4.74 &       11.49 &       119$\pm$       16\\
&     149 &       3.48 &      0.95 &       47.50$\pm$       7.27 &       11.68 &       107$\pm$       9\\
&      55 &       3.59 &      0.42 &       86.61$\pm$       3.77 &       11.94 &       79$\pm$       10\\
&     126 &       3.60 &      0.23 &       30.87$\pm$       1.90 &       11.49 &       58$\pm$       2\\
&      41 &       3.66 &      0.81 &       77.76$\pm$       8.38 &       11.89 &       110$\pm$       26\\
&     137 &       4.55 &       1.41 &       63.65$\pm$       4.0 &       11.80 &       121$\pm$       8\\
&     138 &       6.27 &      0.77 &       15.82$\pm$      0.59 &       11.20 &       99$\pm$       6\\
&     110 &       7.58 &      0.25 &       33.68$\pm$       3.37&       11.53&       67$\pm$       3\\
&     172 &       13.69 &      0.50 &       37.65$\pm$      0.12 &
11.58 &       85$\pm$       0\\
\hline
(U)LIRG &     134 &       3.79 &       1.48 &       83.94$\pm$       21.39 &       11.92 &       119$\pm$       15\\
\hline
&      67&       2.58&      0.56&       224.71$\pm$       2.74&       12.35&       86$\pm$
       9\\
&     114&       2.71&       1.27&       135.64$\pm$       1.54&       12.13&       119$\pm$
       9\\
&      82&       2.86&      0.30&       283.69$\pm$       39.97&       12.45&       57$\pm$
       3\\
&     124&       2.89&      0.38&       146.39$\pm$       8.87&       12.17&       75$\pm$
       5\\
ULIRGs&      93&       3.04&      0.40&       493.36$\pm$       55.53&       12.69&       76$\pm$
       7\\
&      84&       3.43&       1.27&       202.19$\pm$       8.25&       12.31&       118$\pm$
       13\\
&      88&       3.77&      0.23&       242.27$\pm$       15.29&       12.38&       65$\pm$
       2\\
&      94&       4.03&      0.49&       273.44$\pm$       2.96&       12.44&       82$\pm$
       5\\
&     158&       4.71&      0.43&       506.70$\pm$       111.65&       12.70&       77$\pm$
       20\\
&      70&       9.40&      0.69&       201.46$\pm$       27.19&       12.30&       93$\pm$
       15\\
&      58&       10.48&       1.06&       121.73$\pm$       16.74&       12.08&       108$\pm$
       18\\

\hline
\end{tabular}
\end{minipage}
\end{table*}

\subsection{Summary}

For the 8--160\,$\mu$m region, the SK07 models provide the best matches
to our sources' infrared SEDs. The fact that the CE01 and DH02 templates in most cases severely underestimate the far-IR, leads us to two
conclusions. Firstly, the notion of a single radiating source is an
over-simplification of a real system, which is more likely to be a
complex and clumpy 3-D configuration with a varying temperature
gradient. Secondly, we propose that these high-z objects have higher
obscuration and additional far-IR emission from a cold dust component that is not commonly seen in
local LIRGs/ULIRGs, on which the CE01 and DH02 templates are
based. Such excess far-IR flux would be a direct consequence of a large emitting dust region, where dust
in the immediate vicinity of young stars (and/or an AGN), would be
responsible for greatly attenuating the radiation field and hence
shielding the outer dust layers from direct UV illumination, resulting
in lower equilibrium temperatures. This scenario is well-expressed by the SK07
models; by including the treatment of hot spots around OB stars,
the average dust temperature is lowered, shifting the far-IR peak to
longer wavelengths, without a reduction in the mid-IR flux, which,
according to their framework, is only linked to the dust density in
the hot spot. In contrast, the CE01 and DH02 templates, which have been
found to work well with local sources, fail in this case, because
their formulation does not allow for the possibility of excess far-IR
flux independent from the mid-IR. These observations are further supported by our empirical
SED fits, which were included for the purpose
of comparing with real local galaxy data (see
section 3.2). The majority show considerable
discrepancies, failing to reproduce the far-IR SED shape (e.g. objects
77, 93, 110, 122), indicating that the greybody temperatures of 30--50\,K are too high and that dust
potentially colder than 30\,K is present in most systems.

In view of these results, our subsequent
 calculations consider only the SK07 fits to the
 8--160\,$\mu$m spectral region. The fact that
the near-IR part of the SED is not well-represented, is not important since we are
only concerned with pure dust emission in the 8--1000\,$\mu$m
 range. For each object, we take into account
all SK07 matches (figures \ref{fig:goodsed} and \ref{fig:goodsed2} and
table 2), to establish a valid error
margin in cases where the 160\,$\mu$m detection could either reside
on the peak or form part of the rising continuum (e.g. see objects
 115, 147, 152).

\section{SED characterisation}

\subsection{The Infrared Energy Budget}
With the aid of the best-matched SK07 templates, we perform
K-corrections and estimate the monochromatic rest frame
luminosities at 24, 70 and 160\,$\mu$m. In addition, by integrating the SEDs between
8--1000\,$\mu$m, we arrive at an array of values for the total infrared
luminosity ($L_{IR}$) for each
object, the average of which is then used as a final estimate.
 The sources in the redshift sample are categorised into
luminosity classes, following the
definition in Sanders $\&$ Mirabel (1996), revealing that it consists
of 12 per cent Starbursts, 62 per cent LIRGs and 26
per cent ULIRGs. Despite the uncertainties on $L_{IR}$ being
relatively large and stemming from the lack of photometry longward of 160\,$\mu$m,
only two objects move to a different luminosity class on account of
this (table 3).

\subsection{The mid-IR continuum slope and SED peak}
Conventional methods of characterising infrared galaxies include associating
flux ratios between various bands to physical
processes responsible for emission in the infrared (e.g. Xu et al. 2001;
Egami et al. 2004; Lutz et al. 2005; Verma et al. 2005). In
particular, the $f_{25}/f_{60}$ parameter has been applied
extensively in \emph{IRAS} studies of such systems, to quantify
relative AGN/starburst contributions with an indicative value of $f_{25}/f_{60}$\,$>$\,0.17 for AGN-dominated sources (e.g. de Grijp et
al. 1985, Miley et al. 1985, Soifer et al. 1989). This `warm/cold'
terminology is based on the implication that dust heated by an AGN
would reach higher temperatures and hence lower the continuum slope between 25 and
60\,$\mu$m (or 24 and 70\,$\mu$m in \emph{Spitzer}'s case) (e.g. Farrah et
al. 2005; Verma et al. 2005, Frayer et al. 2006). Calculating
the 25/60\,$\mu$m continuum slope using the model SEDs, reveals that
for $\sim$25 per cent of our sample the classical IRAS warm source
criterion of $f_{25}/f_{60}$\,$>$\,0.17 applies. However, the majority of
these objects peak at $\lambda>$\,100\,$\mu$m, indicating that the
flatter behaviour between 25 and 60\,$\mu$m is due to a shift in
infrared emission with elevated $\lambda>$\,90\,$\mu$m flux and reduced 60\,$\mu$m flux. Furthermore, from figure
\ref{fig:lumratios}, it is clear that the continuum slope throughout
the SED is completely independent from the total infrared
luminosity. Consequently, if it is true that the contribution of
AGN-dominated objects increases as a function of IR luminosity
(e.g. Brand et al. 2006), then the slope of the mid-IR continuum and
hence the $L_{70}/L_{24}$ ratio, fail to
quantify it. In addition, because of heavy obscuration,
emission from cool dust seems to be altering the mid-IR
continuum slope solely due to increased far-IR
emission. Various authors have
supported this idea; Chakrabarti et al. (2007) have modelled infrared
SEDs with varied starburst/AGN contributions, suggesting that the warm/cold classification of LIRGs/ULIRGs would be independent of the energy source, if sufficiently
obscured so that all the far-IR emission comes from large grains in
equilibrium. Similar observations (e.g.  Lutz et al. 1996, Klaas et
al. 1997) have put forward the notion that elevated
optical extinction can be responsible for a steep rise of the mid-IR continuum and hence can displace the ratio of the `cold -warm' components, resulting in an energy output mainly carried by the cold component.

To further investigate the properties of this sample, the wavelength at which the SEDs turn over into the
Rayleigh-Jean regime is estimated (table 3, column 8). We find that a
significant fraction of objects (40-60 per cent within 1$\sigma$) peak at wavelengths longward of
90\,$\mu$m independent of luminosity class. Despite
the large uncertainties, there is clearly a strong correlation with respect
to $L_{160}/L_{70}$, not surprising, since 70 and 160\,$\mu$m sample
either side of the peak and their ratio is directly related to the
far-IR turnover (figure \ref{fig:lratiopeak}, right panel). The same does not apply for the $L_{70}/L_{24}$
ratio, however, which shows no such dependence (figure \ref{fig:lratiopeak}, left panel).

Figures \ref{fig:lumratios} and \ref{fig:lratiopeak} display some
important properties of the sample, consistent with conclusions
from section 3. Generally, a simple black body spectrum displays a
temperature dependence through the position of the emission peak, the continuum
slope and the total luminosity. Consequently, if the
far-IR part of an SED were well-represented by a [modified] black body, for a sample of galaxies of
varying dust temperatures this would manifest itself
as: a) a positive correlation between mid-IR continuum slope and total infrared
luminosity (as they both increase with temperature) and b) a negative
correlation between mid-IR continuum slope and position of SED peak (as the former increases and the
latter decreases with temperature). However, if an extra cold dust
component is present, as we believe the case to be for the 70\,$\mu$m
sample, a \emph{single} temperature black body is not a
sufficiently accurate representation of the far-IR and these
correlations would not apply. This is what is observed in figures
\ref{fig:lumratios} and \ref{fig:lratiopeak}.

\begin{figure}
\epsfig{file=fig9,width=8cm}
\caption{The relation between $L_{IR}$ calculated using equation 1 (y-axis) and
  $L_{IR}$ calculated by integrating under the SEDs (x-axis). The
  solid line has a gradient of 1. The r.m.s. scatter off the line is 0.06
  dex.}
\label{fig:formulagood}
\end{figure}

\section{Equations for estimating the Total Infrared Luminosity}

Determining the infrared energy budget is crucial for
estimating the contribution to the infrared and submillimetre
backgrounds and plays an important role in establishing a value for
the infrared element of the cosmic star formation history. If the
available photometric data is not sufficient and hence unable to explicitly define
these contributions, a first order approximation of the infrared
energy budget can be attained through equations relating the total
infrared luminosity to the monochromatic luminosity in one or more bands.
In this section, we develop equations that can be used to estimate
$L_{IR}$, using 1 or more MIPS bands. However, note that all have been
derived using the typical form of starburst-type SEDs and have not
been tested on power-law SEDs of AGN-dominated sources.

\subsection{Estimating $L_{IR}$ with all 3 MIPS bands}
 As the SED of an infrared-luminous galaxy has a distinct shape, its
 bolometric output can be approximated by summing contributions from
 four main sections: $<$\,24\,$\mu$m, 24--70\,$\mu$m, 70--160\,$\mu$m and $>$\,160\,$\mu$m. In a linear plot of $f_{\nu}$ versus $\nu$, flux shortward of 24\,$\mu$m and
 longward of 160\,$\mu$m is not as significant as the flux
 within that range. Therefore the $<$\,24\,$\mu$m and
 $>$\,160\,$\mu$m sections can be approximated by
 triangles of heights $L_{24}$ and $L_{160}$ and the sections
 within 24--160\,$\mu$m with trapezia of heights of $L_{24}$, $L_{70}$ and
 $L_{70}$, $L_{160}$. Summing these contributions and empirically
 accounting for the systematic offset in this approximation, we derive an
 equation to calculate the total infrared luminosity ($L_{IR}$) in the range
 8-1000\,$\mu$m:
\begin{equation}
L_{IR}=4.63\times 10^{-15}\times(8.3L_{24}+2.7L_{70}+L_{160})\times (1+z).
\label{eqn:lum1}
\end{equation}
The coefficients represent the width ($\Delta \nu$) of the bases of the sections
 in units of Hz, $L_{IR}$ is in units of $L_{\odot}$ and $L_{24}$,
 $L_{70}$ and $L_{160}$
are the monochromatic luminosity densities (in units of
 W/Hz) directly derived from the observed flux densities, without
 applying K-corrections. The factor (1+z) adjusts the bases $\Delta \nu$
 of the SED sections, as their width increases with redshift.

The validity of
 this method is demonstrated by comparing
the value of $L_{IR}$ derived by using the equation (y-axis) and the
average value of $L_{IR}$ derived by integrating under the best-matched
model SEDs (x-axis) (figure \ref{fig:formulagood}). There is very good
 agreement, with an r.m.s. deviation of 0.06
 dex from the true $L_{IR}$. We also test it on a different galaxy sample, by calculating the total infrared luminosity of 21
local infrared star-forming/starburst galaxies using MIPS photometry
from the \textit{Spitzer} Infrared Nearby Galaxy Survey
(SINGS) (Dale at al. 2005, hereafter D05) and estimated
distances quoted in Sanders et al. (2003). We fit the DH02 models on
the 24, 70 and 160\,$\mu$m photometry (like in D05) and integrate under
the 8-1000\,$\mu$m region of the best-fit curve, comparing the result with
$L_{IR}$ from equation 1. The agreement is very good, with an r.m.s. scatter of
0.05 (figure \ref{fig:sings}), confirming that this equation is not
 specific to high-z LIRGs/ULIRGs, but also applicable to normal
 infrared star-forming galaxies in the local universe.

\begin{figure}
\epsfig{file=fig10,width=8cm}
\caption{The relation between $L_{IR}$ calculated using equation 1
  (y-axis) and $L_{IR}$ calculated by integrating under the SEDs
  (x-axis) for 21 SINGS galaxies. The
  solid line has a gradient of 1. The r.m.s. scatter off the line is 0.05
  dex.}
\label{fig:sings}
\end{figure}

\begin{figure}
\epsfig{file=fig11,width=8cm}
\caption{The monochromatic rest frame luminosity at 24, 70 and
  160\,$\mu$m as a function of the total infrared luminosity for the
  redshift sample. The 1$\sigma$ uncertainties are shown. The r.m.s. scatter is 0.18, 0.11,
and 0.23 dex respectively.}
\label{fig:mono}
\end{figure}

\subsection{Estimating $L_{IR}$ with 1 MIPS band}
Naturally, a more luminous galaxy will also display higher luminosity
at the various infrared photometric bands (e.g. Elbaz et
al. 2002, Takeuchi et al. 2005). This would manifest itself as a
strong positive correlation between $L_{IR}$ and K-corrected
rest-frame monochromatic
luminosity at 24, 70 and 160\,$\mu$m (figure \ref{fig:mono}). As a
result, it could be used instead of equation 1, for estimating $L_{IR}$, in cases where only one photometric data point
from MIPS is available. For each plot in figure \ref{fig:mono}, we compute the least squares
best fit line through the data, equations 2--4:

\begin{equation}
\rm log \,L_{IR}=1.95 + 0.89\rm \;log\,L_{24},
\end{equation}

\begin{equation}
\rm log \,L_{IR}=1.16 + 0.92\rm \;log\,L_{70},
\end{equation}

\begin{equation}
 \rm log\,L_{IR}=1.49 + 0.9\rm \;log\,L_{160},
\end{equation}
 All luminosities are in units of $L_{\odot}$ and $L_{24}$, $L_{70}$ and
$L_{160}$ are in the rest frame. The r.m.s. offsets from the best line
fits are 0.18, 0.11, 0.23 dex for equations 2, 3 and 4 respectively. This intrinsic dispersion most likely stems from the
variation in the properties of each galaxy, the high
photometric uncertainties as well as the range of models used to
calculate each luminosity value; nevertheless, they are convenient in
cases where the luminosity of a galaxy is required only within an
order of magnitude or class.

\section{Summary and Conclusion}

We have examined a population of 70\,$\mu$m selected sources, in the region
of the Extended Groth Strip, focusing this study on the infrared
properties of 43 objects with
available spectroscopic redshifts (0.1\,$<$\,z\,$<$\,1.2). In the last
section, we derived a set of equations in order to estimate the total
IR luminosity with at least one MIPS band, applicable to objects with starburst-type SEDs. We would like to emphasise that our selection criteria did not
photometrically bias the redshift sample with respect to the full
sample or predispose our study to a particular type of galaxy. As
this is a flux limited survey (see section 2), the higher redshift objects are also more
luminous in the infrared and display lower optical flux. This implies that the sources with no
available spectroscopic redshift are also in the LIRG/ULIRG regime. In addition, the MIPS colours (figure
\ref{fig:mipscolours}) and SEDs (figure
\ref{fig:seds}) unanimously show that all objects are
photometrically similar in the mid and far-IR and their properties
diverge only in the optical and near-IR, not relevant for the
work described here.

By fitting 4 libraries of SED templates on our infrared photometry, we
have examined the properties of the sources and estimated the infrared energy budget, revealing 12 per cent starbursts, 62 per cent LIRGs
and 26 per cent ULIRGs. Evaluation of
the fits showed that the SK07 models perform better at reproducing the
far-IR SED; their formulation adopts a
two-component configuration of dust heated in the immediate locality
of massive young stars and cirrus-heated dust, essentially decoupling
mid and far infrared emission. As a result, since the total infrared
luminosity is not directly related to the position of the SED peak or
the steepness of the mid-IR continuum slope, with the SK07 templates
it is possible to represent objects with strong mid-IR emission and an
additional cold component. CE01 and DH02 employ a scenario with a
single radiating central source where temperature varies as a function
of distance from the centre. Although this has worked well with local
infrared galaxies, it completely underestimates our sources'
160\,$\mu$m flux, with a discrepancy of at least a factor of 2 and up
to 10 for extreme cases, since it does not allow for types of systems
with elevated far-IR emission. Our empirical local galaxy templates,
also mostly underestimate the far-IR region, indicative of the fact that an average
dust temperature of 30-50\,K is too high.

Considering all above
points, we propose that this deep
70\,$\mu$m survey has probed high-z LIRGs and ULIRGs, which are unlike local
counterparts: heavy
obscuration and large amounts of cold dust potentially lower than 30\,K, appear as a \emph{far-infrared excess}
component in the SEDs, causing a significant fraction to peak at
$\lambda>$\,90\,$\mu$m and steepening the continuum slope. The existence
of such objects has also been put forward by other authors; e.g. Marcillac et
al. (2006) have suggested that some high-z infrared-luminous objects display far-IR properties
divergent from those of local galaxies because of an additional cold
dust component, even if the strength of mid-IR emission is the same.
This has further implications: in such systems, the
continuum slope cannot be representative of various
galaxy characteristics such as dust temperature,
total infrared luminosity or the nature of the
central energy source. Figures \ref{fig:lumratios}
and \ref{fig:lratiopeak} demonstrate this: the mid-IR continuum slope (quantified
by the $L_{70}/L_{24}$ ratio) satisfies the IRAS warm source criterion
of $f_{25}/f_{60}$ $>0.17$ for sources with reduced 60\,$\mu$m
emission and increased $\lambda >$\,90\,$\mu$m flux, as opposed to
elevated 25\,$\mu$m emission and it is completely
dissociated from the position of the SED turnover and total infrared luminosity. As this is inconsistent with the representation of far-IR emission as
a single temperature black body, it is in line with our earlier
suggestion of the presence of an additional cold emissive
component.

It is worth noting that this 70\,$\mu$m sample is one of
the first far-IR-selected samples reaching such low flux-density
limits and additional similar surveys will
be of great importance in highlighting the differences (if any)
between local and high redshift infrared populations. The next infrared
observatory, \emph{Herschel}, will greatly benefit this work,
extending to the sub-mm part of the spectrum and, hence, enabling a
complete census of high-z infrared galaxy SEDs. Finally, we would like
to mention that in order to confirm our conclusions we have planned a
follow-up of the work described in this paper with
submillimetre observations using the Submillimetre Common-User Bolometer Array (SCUBA 2).

\section*{Acknowledgments}
M.S. has received support from the University of Oxford, department of Astrophysics. This work is based on observations made with the Spitzer Space Telescope, operated by the Jet Propulsion Laboratory, California Institute of Technology, under NASA contract 1407. We thank Pat Roche, Aprajita Verma, Steve Rawlings and Tom Mauch for useful discussions and comments.

redpajama_set_name: RedPajamaArXiv


text:
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        tagsRefs.child("tags").child("categorias");

        tagsRefs.addValueEventListener(new ValueEventListener() {
            @Override
            public void onDataChange(DataSnapshot dataSnapshot) {
                for (DataSnapshot dados : dataSnapshot.child("tags").getChildren()) {
                    System.out.println("tag EXTRAIDA NO taglist " + dados.getValue());
                     dados.getValue();   //HOW CAN I PUT THIS INTO AN ARRAY TO LATER ADD IN MY ArrayList tags??
                    String tagS = dados.getValue(String.class);
                    tags.addAll(tagS);
                }
            }

            @Override
            public void onCancelled(DatabaseError databaseError) {

            }
        });

        tagAdapter = new ArrayAdapter(getBaseContext(), android.R.layout.simple_list_item_2,
                android.R.id.text1,
                tags);

        tagList.setAdapter(tagAdapter);

        tagList.setOnItemClickListener(new AdapterView.OnItemClickListener() {
            @Override
            public void onItemClick(AdapterView<?> parent, View view, int position, long id) {

                selectedTag = (String) tagList.getItemAtPosition(position);

                setSelectedTag(selectedTag);

            }
        });

    }

here is my database:
h

A: This is happening because onDataChange() method is called asynchronously. This means that the statement that adds tags to your list is executed before onDataChange() method has been called. That's why your list is empty outside that method. So in order to use that lists, you need to use it inside the onDataChange().
For other approach, please visit this post and this post.
Hope it helps.

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text:
The Pathological Optimist
The Pathological Optimist (2017)
In the center of the recent Tribeca Film Festival scandal surrounding his film VAXXED: From Cover-up to Controversy stands Andrew Wakefield, discredited and stripped of his medical license …
Director: Miranda Bailey
The Pathological Optimist full movie online free
Watch The Pathological Optimist free online
Watch The Pathological Optimist full movie
Watch The Pathological Optimist movie free online
The Pathological Optimist Photos
Doctored
An investigation into the "monopoly" of the medical industrial complex and how Americans are viewed as patients.
Eamonn Investigates: The Alien Autopsy
Eamonn Investigates: The Alien Autopsy stream online free with English Subtitles
The Path of the Dragon
An informative documentary about the ancient practice of Kung Fu at the Shaolin Temple in China. The documentary centers on both the history of martial arts and the phenomenal impact…
Genre: Documentary, Short
In this installment of the "Why We Fight" propaganda film series, we have the account of Great Britain's last stand against the forces of Nazi Germany. This mainly focuses on…
Genre: Documentary, History, War
Osama Bin Laden: The Finish
The riveting inside story of the biggest manhunt in history, the search for Osama Bin Laden, including a startling new revelation on the origin of the plans for 9/11.
If It Bleeds We Can Kill It: The Making of 'Predator'
A behind-the-scenes look at the 1987 sci-fi/action film that has since become one of the modern classics, about a team of special forces soldiers who find themselves being stalked and…
Freedom Fighter looks at persecution around the world, while following the story of Majed El Shafie, an Egyptian man tortured and sentenced to death in Egypt for his faith. Now…
Country: Afghanistan,Canada,Pakistan
Genre: Biography, Documentary, Drama
Life in the Snow
Wildlife cameraman and television presenter Gordon Buchanan travels to northern Norway and the Austrian Alps to search for animals that have adapted to the snowy conditions and cold weather. The…
Genre: Documentary, Family
Breaking the Chain
IMDb: 10.0
It's a fate worse than death for countless animals: a life sentence of isolation and deprivation. Their only hope is PETA's Community Animal Project, a field team fighting against a…
Orgasm Inc.
Filmmaker Liz Canner takes a job editing erotic videos for a drug trial for a pharmaceutical company. Her employer is developing what they hope will be the first Viagra drug…
BRIDEGROOM tells the emotional journey of Shane and Tom, two young men in a loving and committed relationship – a relationship that was cut tragically short by a misstep off…
Genre: Documentary, Romance
Anti-Semitism in the 21st Century: The Resurgence
Anti-Semitism in the 21st Century: The Resurgence stream online free with English Subtitles


text:
Silverio v. CA, GR 94284, 8 April 1991
Silverio v. CA, GR 94284, 8 April 1991
On 26 January 1988, respondent People of the Philippines filed an Urgent ex parte Motion to cancel the passport of and to issue a hold-departure Order against accused-petitioner on the ground that he had gone abroad several times without the necessary Court approval resulting in postponements of the arraignment and scheduled hearings.
Overruling opposition, the Regional Trial Court, on 4 April 1988, issued an Order directing the Department of Foreign Affairs to cancel Petitioner's passport or to deny his application therefor, and the Commission on Immigration to prevent Petitioner from leaving the country. This order was based primarily on the Trial Court's finding that since the filing of the Information on 14 October 1985, "the accused has not yet been arraigned because he has never appeared in Court on the dates scheduled for his arraignment and there is evidence to show that accused Ricardo C. Silverio, Sr. has left the country and has gone abroad without the knowledge and permission of this Court"
Petitioner contends that respondent Court of Appeals erred in not finding that the Trial Court committed grave abuse of discretion amounting to lack of jurisdiction in issuing its Orders, dated 4 April and 28 July 1988, (1) on the basis of facts allegedly patently erroneous, claiming that the scheduled arraignments could not be held because there was a pending Motion to Quash the Information; and (2) finding that the right to travel can be impaired upon lawful order of the Court, even on grounds other than the "interest of national security, public safety or public health."
Whether or not the right to travel can be impaired upon lawful order of the Court, even on grounds other than the "interest of national security, public safety or public health.
The foregoing condition imposed upon an accused to make himself available at all times whenever the Court requires his presence operates as a valid restriction of his right to travel. A person facing criminal charges may be restrained by the Court from leaving the country or, if abroad, compelled to return. So it is also that "An accused released on bail may be re-arrested without the necessity of a warrant if he attempts to depart from the Philippines without prior permission of the Court where the case is pending.
Article III, Section 6 of the 1987 Constitution should be interpreted to mean that while the liberty of travel may be impaired even without Court Order, the appropriate executive officers or administrative authorities are not armed with arbitrary discretion to impose limitations. They can impose limits only on the basis of "national security, public safety, or public health" and "as may be provided by law"
Article III, Section 6 of the 1987 Constitution should by no means be construed as delimiting the inherent power of the Courts to use all means necessary to carry their orders into effect in criminal cases pending before them. When by law jurisdiction is conferred on a Court or judicial officer, all auxillary writs, process and other means necessary to carry it into effect may be employed by such Court or officer.
Petitioner is facing a criminal charge. He has posted bail but has violated the conditions thereof by failing to appear before the Court when required. Warrants for his arrest have been issued. Those orders and processes would be rendered nugatory if an accused were to be allowed to leave or to remain, at his pleasure, outside the territorial confines of the country. Holding an accused in a criminal case within the reach of the Courts by preventing his departure from the Philippines must be considered as a valid restriction on his right to travel so that he may be dealt with in accordance with law. The offended party in any criminal proceeding is the People of the Philippines. It is to their best interest that criminal prosecutions should run their course and proceed to finality without undue delay, with an accused holding himself amenable at all times to Court Orders and processes.
WHEREFORE, the judgment under review is hereby AFFIRMED. Costs against petitioner, Ricardo C. Silverio.


text:
Malý Háj () je osada města Hora Svaté Kateřiny v okrese Most v Ústeckém kraji. Nachází se zhruba 3 km na jih od Hory Svaté Kateřiny v nadmořské výšce 835 metrů. Osada se rozkládá podél silnice III/25220 z Hory Svaté Kateřiny přes Svahovou a Boleboř do Jirkova. Z původní zástavby zůstal stát jen kostel s farou a několik domů.

Název
Původní název vesnice Stolzenhan je složen ze dvou slov. První část stolz pochází ze střední horní němčiny a znamená zpupný nebo nádherný. Druhé slovo hain (háj) je staročeským označením pro panský les. Pojmenování Kleinhain se objevilo až na konci 18. století. V historických pramenech se jméno vyskytuje ve tvarech: zu Stolczenhain (1383), Sstolezenhan (1542), Sstolezhan (1555), Sstolczenheim (1606), Stoltzen Hahn (1651), Stolzenhan a Kleinhan (1787).

Historie
Nejstarší písemná zmínka o Malém Háji pochází až z roku 1549, kdy zdejší území patřilo k panství Červený Hrádek u Jirkova. Oblast byla kolonizována osadníky z Vestfálska na počátku 16. století. Tak vznikla nejen osada Malý Háj, ale i Rudolice v Horách. Noví obyvatelé se živili výrobou dřevěného uhlí. Zpracováním dřeva se obyvatelstvo živilo i v následujících staletích. Dřevo se vyváželo i do sousedního Saska. Malý Háj zůstal součástí červenohrádeckého panství až do zrušení poddanství v roce 1848.

Od roku 1896 patřil Malý Háj k Rudolicím v Horách jako jeho osada. V roce 1953 se Malý Háj a Rudolice v Horách staly osadami Hory Svaté Kateřiny.

Po válce byly opuštěné objekty demolovány, takže dnes tvoří Malý Háj jen několik domů, které slouží především k rekreaci.

Pamětihodnosti
 Klasicistní kostel Nejsvětější Trojice dokončený roku 1783 byl původně filiální kostel svatokateřinského kostela, v roce 1791 se stal lokálií a v roce 1852 byl povýšen na farní kostel. Po druhé světové válce a odsunu Němců kostel chátral. Byl opraven až v 90. letech 20. století. Hlavní oltář, kazatelna a varhany pocházejí ze zrušeného kláštera v Lounech. U kostela se nachází i fara a hřbitov s márnicí.
 Pomník obětem druhé světové války z roku 1991, který upomíná na poválečnou tragédii z června roku 1945, kdy bylo zastřeleno 8 německých obyvatel.
 Východně od Malého Háje se nachází vyhlídková Eduardova skála (908 m), které se v minulosti říkalo také Eduardův kámen. Z vrcholu je dobrý rozhled, zejména na obě osady a Horu Svaté Kateřiny.

Obyvatelstvo
Při sčítání lidu v roce 1921 zde žilo 109 obyvatel (z toho 54 mužů), kteří byli kromě jednoho cizince německé národnosti a všichni patřili k římskokatolické církvi. Podle sčítání lidu z roku 1930 měla vesnice 93 obyvatel německé národnosti, kteří se hlásili k římskokatolické církvi.

Odkazy

Reference

Literatura
 Philipp, Erich, Erinnerungsbuch der Gemeinden Gebirgsneudorf, Katharinaberg, Brandau, Einsiedl, Kleinhan, Rudelsdorf, Deutschneudorf, Deutscheinsiedel, Deisenhofen 1995, s. 211–233
 Philipp, Erich, Grenz-Heimat. Beiderseits der Schweinitz, Deisenhofen 2000, , s. 146–149

Externí odkazy

 Informace o osadě Malý Háj
 Malý Háj na stránkách Zaniklé obce

Vesnice v okrese Most
Zaniklá sídla v okrese Most
Sídla v Krušných horách
Hora Svaté Kateřiny
Červenohrádecké panství

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text:
Home Events Virtual Kristalnacht Commemoration & Film
Virtual Kristalnacht Commemoration & Film
In commemoration of Kristalnacht
Saul & Ruby's Holocaust Survivor Band
SAUL & RUBY'S HOLOCAUST SURVIVOR BAND, is a feature documentary (80 min.) directed and produced by Tod Lending, an Oscar nominated and national Emmy winning documentary filmmaker. It is a story full of comedy and tragedy as it follows the inspiring story of these two unique and unusual men. Their musical journey begins in total obscurity, playing in residential homes for the elderly and small Jewish community organizations, to then being invited to perform at venues across the country, including a coveted performance at the Kennedy Center's Millennium Stage.
Eventually, they make an extraordinarily emotional journey to Poland where they relive the joys of their youth and the ensuing horrors of Nazi occupied Poland.
This unique and compelling story is about having the courage to live one's dreams, finding purpose and meaning in life, the transcendent power of music, the complex experience of aging, surviving trauma, the power of love and family, and speaking out against anti-Semitism and bigotry. We are with Saul and Ruby every step of the way as they find joy, healing and comfort through music while confronting the past, and boldly facing the mortality of their existence today.
RSVP and you will receive a link to watch the film from the comfort and safety of your home.
We will come together on Zoom Wednesday, November 11th at 7:30 pm for the Annual Kristalnacht commemoration and to discuss the film.
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