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Home University Observer
Budgeting students out of University
Peter Molloy
With an increase of 66 per cent to the registration fee, Peter Molloy investigates the impact of this on students.
Last week's budget was never going to be a herald of glad tidings. It's a straightforward fact that this country is experiencing a severe economic downturn, and in such a climate it must be accepted as a pragmatic necessity that financial constraints and re-adjustments have to be imposed.
Yet what was striking about last Tuesday's pronouncements, and what it seems will remain as the enduring popular image of Budget '08, is that some of the severest of these restrictions and impositions appear to have been made upon sections of Irish society least able to bear them.
Domestic media attention throughout the last seven days has been firmly focused upon the Government's decision to curtail subsidised medical services to the elderly. Public sentiments of uncertainty and unease about the merits of this step, although verging at moments upon the hysterical, would nonetheless appear valid.
However, what it seems had been largely overlooked in the midst of this collective outpouring of dissatisfaction is another, equally inequitable provision of this year's Budget – the unilateral move to increase the third-level Registration fee by €600 from the 2009/10 academic year onwards.
With even the most objective and dispassionate analysis, such a step is extreme and unprecedented. At a single stroke, the standard annual obligation for all college students has been raised from €900 to €1500 – an increase of 66 per cent.
Closer to home again is the particularly relevant fact that for students of this university, the new yearly bill will now amount to a grand total of €1650, once the ever-debatable annual levy for UCD's new Student Centre is taken into account.
In short, it would seem enormously difficult to argue against an assertion that the overall financial burden for Irish students has been compounded considerably in the last few days. So what practical effects might be expected?
It must be fundamentally recognised that despite barbed remarks aired in public over the last few months about pampered, affluent Irish students, the reality of the student demographic is considerably greyer than the black and white polarisation such commentary implies.
For every student prince or princess out there, fraught only by choosing between the relative merits of Club XXI on a Monday, or Club 92 on a Saturday, there is a significant proportion of students for whom paying such fees is more challenging than awaiting the opening of the parental pocketbook.
Aside from the obvious grouping of those from marginal or impoverished backgrounds, other groups within student society, such as mature students, have already felt a significant financial pinch as things stood before 14th October.
The options facing those students now are less then optimistic. One seemingly obvious remedy – having students seek part-time employment to fund their studies – is a great deal less than satisfactory.
Such an instinctive response ignores the basic reality that the very recession which has triggered the Government's drastic moves has had a very real effect on the labour market as well, trickling right down to the level of 19 and 20-year-olds working evenings and weekends as lounge staff or shop assistants.
Simply put – the jobs just aren't all that widely available any more.
Anyone dubious about this is best advised to take the empirical approach to research, dust down their CV, and start footing it from shop to pub searching for part-time work.
Anecdotal evidence from students suggests that calls to interview may be quite some time in materialising. In any case, a crude solution to the problem like this skips around the rather crucial logic that the more time students spend working inevitably results in less discretionary time available for study and course work.
Particularly for a university like UCD, where criticism exists towards the negative effect that semesterisation and continuous assessment has on extra-curricular activity, such an outcome will ultimately have a detrimental effect on general student life, and the continued existence of university clubs and societies. Undoubtedly, this is something, which should, in the proper order of things, come just after academics in student priorities.
It may also be worth examining just how this new development ties in to that much larger issue dominating contemporary Irish student politics – the greatly increased speculation about fees being re-introduced to third-level education. The salient point about this year's budget is that the move to increase student registration fees has not by any means cancelled out the prospect of full fees being re-introduced.
If that were the case, and if this development represented some form of compromise between the mooted intent of the government and the opposition of a large segment of student society, than at least the worst fears of some students would have been allayed.
However, it seems instead that this rise exists independently of any ultimate plans to resurrect college fees. In other words, if and when such measures do see fruition, then they will be imposed on top of this already stringent financial requirement.
Certain fundamental problems with last week's news also become apparent if one is tempted to play accountant and query where exactly these funds will ultimately end up.
Despite the instinctive and understandable student tendency to outrage at the mere mention of college fees, strong and compelling arguments in support of such a move do exist. Chief amongst these points is the observation made by government figures that the increase in revenue engendered would represent capital which could be diverted straight back into third-level education.
It is claimed that this would bring about a resultant improvement in infrastructure, facilities and staff, and all the long-term benefits to students that this would mean. As unpalatable as the prospect of fees may remain to some students, this essential truism at least may make that bitter bill somewhat easier to swallow.
Worryingly, however, such a general reassurance appears notable in its absence from this current increase in student financial obligations. Basic Registration fees have now risen, but as of yet, no firm guarantee whatsoever has emerged to suggest that the increased funds generated from 2009 onwards will ever be used to further investment in Irish education.
Put baldly, Irish students can be forgiven for a suspicion that the money they part with from next year on may not have any direct benefit for them – an unease shared last week by Vice-President for Students, Dr Martin Butler. "I don't know what's going to happen, will we get the balance between the €900 and the €1600… will it become part of the student charge, and can it then be used to enhance the student experience. I don't know that"
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Not Too Big To Fail
The Facts about Mike Perry and IndyMac
OIG Audits
Private Litigation
IMB Messages
← "It is beyond irresponsible to restart these affordable-housing allocations without first dealing with the underlying problems at Fannie Mae and Freddie Mac," Sen. Bob Corker (R., Tenn.)
"When people stopped trusting any institutions or having any values, they could easily be spun into a conspiratorial vision of the world…..At the core of this strategy is the idea that there is no such thing as objective truth. This notion allows the Kremlin to replace facts with disinformation… →
"I think its un-American: anti-free markets and fair competition, if you are in business and you lobby the government for any other reason than to ask them to please leave you and your industry (mostly) alone. Crony capitalism; businesses that are dependent on government favors (revenues, subsidies, guarantees, monopolies, regulation, etc.) is too rampant these days…
Posted by nottoobigtofail.org
…Jeb Hensarling is right and my kind of principled politician.", Mike Perry
Potomac Watch
K Street's Biggest Opponent
Jeb Hensarling has been a lonely figure fighting earmarks, subsidies and tax preferences. It's time more Republicans joined him.
House Financial Services Committee Chairman Jeb Hensarling (R., Texas). Carolyn Kaster/Associated Press
By Kimberley A. Strassel
Texas gave America the Lone Ranger, and then—because it is a generous sort of place—in 2002 it gave the country an updated version of him: Rep. Jeb Hensarling. The Republican has spent a decade riding herd on cronyists who give capitalism a bad name by giving or taking special government favors. With the coming dawn of a Republican Congress, we're about to see if the rest of the GOP sees the wisdom of joining Mr. Hensarling's posse.
Washington's Lone Ranger was at it again this week in the fight over reauthorizing the Terrorism Risk Insurance Program, a "temporary" program created in 2002 that requires taxpayers to absorb the costs of insurance payouts after an attack. Mr. Hensarling earlier this year set his sights on the program and methodically elevated the subject of its industry payoffs into a Washington hot topic, causing one unnamed industry lobbyist in October to gripe about the reauthorization delay: "If Jeb Hensarling were not in Congress, a bill would have passed with enormous support." The Texan didn't get all the reforms he wanted in the reauthorization bill that did pass this week, but he got some. And he made his point.
The episode was classic Hensarling. The congressman stepped down from the House leadership after the 2012 election to become chairman of the House Financial Services Committee, where he could be at the center of restoring what he calls the "bedrock" GOP principle of "free enterprise." From that perch, Mr. Hensarling has doggedly worked to dismantle crony government programs that reward the well-connected business elite. While his efforts have rarely resulted in total victory, they have created flash points and forced his fellow conservatives to publicly justify their mercantilist tendencies.
Take his longtime fight to eliminate Fannie Mae and Freddie Mac, the government-backed housing giants that were central to the 2008 crash. Mr. Hensarling has yet to get a House vote on his proposal, though this focus has helped put uncomfortable attention on those pushing only watered-down reform. Earlier this year, he led a battle against plans to roll back reforms to the federal flood-insurance program. The House passed that atrocity, but only after former Majority Leader Eric Cantor (to great outrage) did the insurance lobby's bidding and bypassed Mr. Hensarling on the way to a vote.
This fall he provoked a debate over reauthorization of the Export-Import Bank, which exists to provide cheap financing for select industry players. The bank was set to die; all the GOP had to do was nothing. The House instead caved and threw Ex-Im reauthorization into a September funding bill, though Mr. Hensarling was able to limit its extension to June—when he intends to have that fight all over again.
Such fights in the next Congress will be even more worth watching. Corporate America invested heavily this midterm in getting a Republican Senate, in part because it wants nothing more than to get back to the good old Tom DeLay days of mutual GOP-Fortune 500 back scratching. The K-Street lobbyists are about to put enormous pressure on Republicans. Lobbyists will line up three deep outside the offices of John Boehner and Mitch McConnell, demanding that the leadership ignore Hensarling-style reforms.
Which gets to the other reason the Hensarling battle over free markets is about to matter more: All eyes are now on the GOP. Republicans are happy to criticize obvious (and Obama -backed) recipients of government largess: the Solyndras of the world. Yet few have been willing to shut down larger programs that pay off entire industries and send dollars back to their state businesses. This is why many voters see the GOP as the party of the "rich and powerful" and Democrats get traction with their populist catchphrases.
In a May speech to the Heritage Foundation, Mr. Hensarling noted that the world of earmarks, subsidies and tax preferences has caused "many to view success with suspicion. That in turn makes it easier for liberals to mislead with calls for bigger government to ensure 'fairness.' " Conservatives, he said, have ceded that word to the left, when they should be talking about how "everyone must be bound by the same rules."
This ought to be the Republican rejoinder to the Elizabeth Warrens of Congress, who like to complain that Washington is rigged on behalf of billionaires and giant companies. It absolutely is. But Democrats are the ones who are champions of big government, which exists to reward the politically connected, and to hide those rewards within legislation and backroom bureaucratic payoffs. The left isn't concerned so much about government payoffs as it is about controlling who gets them. The GOP has a yawning opening to make this case, and position itself as the party that truly represents Main Street.
Yet to do that, they'll have to rediscover some principles. A lot of Republicans have used the excuse of a bottlenecked Democratic Senate as a reason not to follow Mr. Hensarling in his rides to kill off the likes of Fannie, Ex-Im or TRIA. They have no such excuse now.
Posted on December 12, 2014, in Postings. Bookmark the permalink.	Leave a comment.
Short, fabulous June 1, 2019, NY Post article and even more fabulous AG Barr. Spot on. As I said in my July 11, 2018, ten year anniversary paper, this is similar to how the left and liberal media lied about the financial crisis. As a result, the mainstream narrative about the crisis remains false to this day……..
"Excerpt from Sunday August 26, 2018, the Los Angeles Times front-pager on Senator McCain's passing. I agree about the honor part and understand his suffering unfairly at the hands of his own government being terrible. I had it much worse on that front. But we all know that nothing can compare…
"With due respect to Martin Feldstein's economic bona fides, it seems somewhat disingenuous to suggest the Federal Reserve should "Save Low Interest for a Rainy Day" (op-ed, July 27) as if this inefficient monetary-policy tool is an asset to be drawn upon at some future date, similar to a saver's nest egg…
"Abuses in the mortgage-backed securities industry led to a financial crisis that devastated millions of Americans. Today's agreement holds Wells Fargo responsible for originating and selling tens of thousands of loans that were packaged into securities and subsequently defaulted.", Alex Tse, acting U.S. Attorney for the Northern District of California…
Mr. Angelides: "Our goal was to create a record (The Financial Crisis Inquiry Commission Final Report) and history that could not easily be rewritten by ideologues or by Wall Street and its flunkies."
nottoobigtofail.org on "In the accuracy department, h…
ty on "In the accuracy department, h…
Mark Nelson on "Imagine if our President forc…
Mark Nelson on "It's maddening. It's disappoi…
Mark Nelson on "What do you think of the Well…

redpajama_set_name: RedPajamaCommonCrawl


How do bloggers really make tons of money from their blogs?
This is a question I'm sure every blogger has been asked. The word blogger has appeared on many of my online profile. This has prompted some of my friends to ask me the same question. Many people are very sceptical when you tell them that many bloggers make 6- figure incomes from their blog. I don't really blame them. Three years ago, I had no clue how a blogger could generate so much income from a blog. Now I know better.
I have also come to realise that not all bloggers make money from their blogs- at least, not the eye-popping amounts attributed to elite bloggers.
There are many reasons for this. Many people don't have a clue, the same way I didn't a few years ago. Some are so rich that they only want to blog as a hobby or they don't know ways to monetise their blogs. Whatever their reasons may be, they are leaving money on the table. I am a firm believer in blogging for money and encouraging others to do the same thing. What's the point is putting so much effort into your blog contents and not make money from it? You might as well remain in a 9-5 job for life. If you want to blog for money read Ruth Soukup's Book, How to blog for Money.
Here's 6 ways bloggers make money from their blogs.
What is affiliate marketing? Well, here's what I know. Affiliate marketing is when you promote a product or service you like on your website to your readers. When somebody buys that product or service, you receive a commission. Affiliate marketing is very popular amongst bloggers. In fact, affiliate marketing represents a huge percentage of income for most bloggers. Take Michelle Schroeder-Gardner, for instance. She is one lady blogger I admire. Learn how she went from $0 in affiliate income to $50,000 or more in per month. Her course, Making Sense of Affiliate Marketing comes highly recommended. If you are a blogger and you want to make money through affiliate marketing, you must take this course. Follow her step-by-step affiliate marketing strategy course that shows you how to earn money through affiliate marketing and make more money blogging. Don't leave money on the table any longer. Join the course here!
So many bloggers create their own courses which they sell through their websites. Some of these courses are popular and successful and make tones of money for the blogger. An example is Making Sense of Affiliate Marketing, which I have discussed above.
Other digital products that bring massive income for some bloggers are Plugins, Apps, Themes or videos. I think the most profitable digital product is E-Book. Bloggers are self -publishing books and selling through their websites for maximum profit. Others go through Amazon as well. ProBlogger has a collection of E-books on their website. I haven't read them but the books come highly recommended.
This is one of the most popular ways for bloggers to make money with their blogs- by placing ads in their website. There are different popular ad networks such as Media.net. Chitika etc. but the most popular ad network appears to be Google AdSense. The way it works is that Goole chooses adverts that are relevant to your blog niche for you. All you have to do is place the banners on your site. You decide where in your website you want to place the ads. Many bloggers, especially new ones, are known to make lots of money through Google AdSense. Some of the networks can only place ads on your site if you have a huge number of views pay day on your blog.
There is a lot of information out how on how to join these networks- depending of course on the number of your page views. Without doubt, huge page views is the sure- fire way to monetise through adverts. So, drive traffic to your site and start making money. Just remember, it is not a get rich quick scheme. Be patient and consistent. It will pay off. I am doing the same.
Bloggers, especially the ones with huge page views per day, earn money through placing private adverts on their websites. You can either wait for advertisers to come to you or you can contact them directly. If you are looking to monetise this way, I suggest that you add a page to your site for advertisements telling prospects that you are accepting adverts. You will be setting the pricing for your advert in this case.
Many bloggers sell memberships to their dedicated readers as a way of monetising their blogs. The yearly membership fees can be quite steep but they seem to offer value for money because they are popular, especially amongst elite bloggers. If you have a dedicated readership and a great product, you may want to add membership to your blog. The money generated from memberships is recurring income. Great way to make money as a blogger. Check out Jason Chesters' tutorial on how to create a 6-figure membership site.
6. Bloggers also make money by offering coaching or consulting services.
If you are ever overwhelmed with your blog, consider hiring a coach – and be prepared to pay a high prize in most cases, but it will be worth it. I am considering getting a coach myself.
There many more ways bloggers make tons of money blogging. I hope you are now convinced that you can make money from blogging. If so, why don't you start you own blog today.
If you find this blog helpful, please share, like or comment.


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Q: How to keep Realm data in the same order as entered I have an application where I need to keep the data in the same order as it is entered.  The data is entered into a List property.  Everything works great until I have to delete an item.  When the delete occurs the last item on the List takes the place of the one that was deleted.  The UITableView shows the correct number of items but is not synchronized with the realm List.
An example would be if I had data:
1, 2, 3, 4, 5, 6
I then delete:
3
The realm data looks like this:
1, 2, 6, 4, 5
The tableview looks like this:
1, 2, 4, 5, 6
The desired result of the realm data would match the tableview output.
Is there any way to keep the order of the data from changing after items are deleted?

A: Objects in a Realm are inherently unordered. If you wish to retrieve objects in a specific order that you control, you can do so by inserting them into a List property of an object, or by sorting the Results that you use to retrieve them.

redpajama_set_name: RedPajamaStackExchange


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How has Earth's core stayed as hot as the sun's surface for billions of years?
How has Earth's core stayed as hot as the sun's surface for billions of years? : Read more
orsobubu
these are all stupid and unsupported theories; no physical mechanism to trap all that heat during 5 billion years, no physical mechanism to explain the starting incredibly high temperature the core should have had due to the merger of planetesimals, no physical mechanism to explain the high temperature of the original dust disk around the sun, no physical mechanism to explain an hypotetical gravitational collapse of the new condensed planet earth, no physical mechanism to explain the amount of energy producing the heat by radioactivity decay, no data to show the huge loss of temperature from the core during past earth's life, no data to show the necessary production of many types of radioactive isotopes as a result of the fission process, no physical mechanism to explain why the same heat creation process is not ongoing in all the other solar system solid bodies
The earth remains a hard nut to crack. Our deepest attempts are only small pricks. We found it saturated with super-heated high pressure water. This water should be highly conductive. Our crust might have an electrical character to it. There might even be electrical layers in the earth, like there is above the earth.
Some studies show the gravity reaches a maximum at a shell, with a decrease in gravity inside that shell in the center. The gravity gradient under the shell might be opposite the gravity gradient above that shell. A pulling up force at the center. Wouldn't that be wild.
This water would easily flash at the surface and give a huge source of power. But it would not be free. Like other geo-hydro sites, there are contaminates in the steam and water. High maintenance and replacement repair.
Jan Steinman
www.EcoReality.org
orsobubu said:
these are all stupid and unsupported theories…
Uhm… would you care to present your credentials, and documentation for your beliefs?
Didn't think so!
"Where does all that heat come from? It is not from the sun. While it warms us and all the plants and animals on Earth's surface, sunlight can't penetrate through miles of the planet's interior. Instead, there are two sources. One is the heat that Earth inherited during its formation 4.5 billion years ago. The Earth was made from the solar nebula (opens in new tab), a gigantic gaseous cloud, amid endless collisions and mergers between bits of rock and debris called planetesimals. This process took tens of millions of years. An enormous amount of heat was produced during those collisions, enough to melt the whole Earth. Although some of that heat was lost in space, the rest of it was locked away inside the Earth, where much of it remains even today. The other heat source: the decay of radioactive isotopes, distributed everywhere in the Earth."
This is view is interesting in the article. The giant impact for the origin of our Moon does not feature a fully formed Earth as we see today but a proto-earth and a proto-moon that evolves after the giant impact, thus both earth and moon must continue to grow in size and mass until what we see today. Explaining how Earth evolved in the solar nebula and Venus evolved so very differently, from the same nebula and postulated protoplanetary disc, remains very challenging. This model interpretation presented explaining the heat today, could have some holes in it.
NASA scientist explains why Venus is Earth's 'evil twin' (video)
Scientists and engineers from NASA and the European Space Agency want to know a whole lot more about why Venus resembles Earth in so many ways, and yet is so strikingly different. NASA scientist explains why Venus is Earth's 'evil twin' (video) : Read more
forums.space.com
WisdomLost
I've heard the isotope/radiation theory, and thought it was an interesting guess. Personally, I always thought the core was active due to the tidal effect of our relatively large moon.
With the constant churning of the moon's pull, the mantle stays relatively fluid, and the core oscillates within that "fluid". Resulting friction would produce a lot of heat.
I don't know a lot about the inner workings of Mars, but also assumed the lack of a large moon accounted for the dead core (though recent seismic readings suggest it's not as dead as we thought).
Venus is just plain hot. Solar accounts for the extreme temperature at the surface, but I don't know if the core is active. Same for Mercury. There are no other "rock" planets in our solar system to compare to, so my guess probably couldn't be "proven" by comparison. However, we do see evidence of active cores on moons orbiting large gas giants.
Reactions: rod
Perhaps there is heat/cooling problems in the solar system, whether Earth or some small moons or other planets. I have read over the years different reports that indicate heat/cooling issues come up when showing how something remains hot over a 4.5 Gyr solar system model.
theglassisempty
It does take that long to cool off, do the math. And, there is residual radioactivity keeping up the temperature. Your ramblings are the only unsupported "theories" around here . . . . .
Some interesting comments here in various posts. Who, what, when, where, how, and why are good investigative questions to ask.
For example, what was the original core temperature of Earth when it was a proto-earth before the giant impact with Theia - creating the Moon? The proto-earth is not the same size or mass as we live on today but smaller in size and mass. Initial conditions must be defined, heat loss rates, heat sources for adding heat, etc., accretion growth rates, etc.
https://www.scientificamerican.com/article/why-is-the-earths-core-so/, Why is the earth's core so hot? And how do scientists measure its temperature?
There are some model answers in the link but IMO, still not very good and lacking details.


So what is a glyph anyway?
The term "glyph" comes from the Ancient Egyptian times when they used pictures in order to tell a story.
When I create a glyph I start with three (and only three) questions.
You want to stick to three questions so that it won't be overwhelming for the little ones when you try to analyze the turkey glyphs and create data charts.
Each answer can be determined by looking at a child's turkey.
For example, If I look at the turkeys above me I can see that three of the children are staying home for Thanksgiving and two of them are going out of town.
I can tell this because of the way they made their legs.
I also love to integrate language arts by having them complete a turkey glyph book that they can read and share with their family. These turkeys make adorable shelf sitters or centerpieces on their Thanksgiving table.
They also look cute if you forego the paper bag and just make them flat.
My friend Deedee Wills saw these in the hallway at her school and snapped a picture for me.
The one below is my fave!! So much character!!
After your sweeties have assembled their turkeys make sure that you take that next step and analyze and record the data. This is a great way to do math that is authentic and meaningful!
These are included in my Thanksgiving unit that has been completely revised!
This unit is packed full of enough stuff to get you through the month of November.
You can check them out by clicking on the cover below.
I love your pic included with your blog! Adorable!!!
I really like the addition of the glyph book! Another great idea.
I have been trying to figure out what a glyph is. Got it!


text:
NewsNation/World
Equipment operator surrenders in Phila. building collapse
PHILADELPHIA -- A heavy-equipment operator with a lengthy rap sheet who is accused of being high on marijuana when a downtown building collapsed onto a thrift store, killing six people, surrendered yesterday to face charges in the deaths, police said.
Sean Benschop faces six counts of involuntary manslaughter, 13 counts of recklessly endangering another person and one count of risking a catastrophe. A warrant had been issued for his arrest and police had been searching for him.
Authorities believe Benschop, 42, had been using an excavator Wednesday when the remains of the four-story building toppled onto an attached Salvation Army thrift store, killing two employees and four customers and injuring 13 others.
Deputy Mayor Everett Gillison said a toxicology report showed evidence that Benschop was high on marijuana. That finding, combined with witness statements and evidence from the scene, led to the decision Friday to raid his North Philadelphia home and later seek an arrest warrant, he said. Benschop didn't return phone messages.
As the criminal investigation heated up, at least two survivors sued the demolition contractor and building owner, alleging gross recklessness at the job site.


← Yesterday's super quick leg workout!
You may have noticed that I haven't been blogging on this website for a while.
While I have loved Twenty Something Diaries and it has been a great starting-blog for me, I have decided it is time to progress and move on over to my own, personalised website which is now up and running!
So I would just like to take this opportunity to thank you for following me this far, and ask you to please visit my new shiny blog which I will be updating regularly!
I hope you enjoy it and I really hope to see you lovely followers over there!
Your new blog on bloglovin'?


text:
\section*{Background}

The analysis of microarray data has attracted continuous interest over the
past years in the Bioinformatics community (see e.g. \cite{gent03}). The
problem consists in obtaining the gene expression level from the
experimental measurements, which are the emitted fluorescence intensities
from different sites in the array.  On general grounds one expects that
the experimental signal can be decomposed into two contributions:
\begin{equation}
I = I_{\rm bg} + I_{\rm SP} (c)
\label{eq:01}
\end{equation}
where $I_{\rm SP} (c)$ is the specific signal due to the hybridization
of the surface-bound probe sequence with a complementary target
sequence. This quantity depends on the concentration $c$ of the
complementary strand in solution (target). The non-specific term $I_{\rm
bg}$ has different origins. It arises due to spurious effects such as
incomplete hybridization where probe sequences bind to only partially
complementary targets or due to other optical effects.

Models based upon the physical chemistry of hybridization (see
e.g. \cite{held03}) predict a linear increase of the specific signal
until saturation is approached. In case of highly expressed genes
the specific part of the signal $I_{\rm SP}(c)$ dominates the total
signal intensity $I$ and hence one can safely make the approximation
$I \approx I_{\rm SP} (c)$. For lowly expressed genes, as well as for
sequences with a low binding affinity, the specific and the non-specific
contribution to the total intensity can be of comparable magnitude. In
this case an accurate estimate of $I_{\rm bg}$ is crucial to draw
reliable conclusions concerning the expression level; estimates based
on the intensity distribution over the whole chip suggest that this is
the case for roughly a quarter or half of the probes~\cite{ferr09}. Once
the background is calculated the gene expression level is then computed
from background subtracted data $I - I_{\rm bg}$.

In this paper we present an algorithm for the calculation of the
background level for Affymetrix expression arrays, also known as
GeneChips.  In these arrays the probe sequences come in pairs: for
each perfect match (PM) probe, which is exactly complementary to the
transcript sequence in solution, there is a second probe with a single
non-complementary nucleotide with respect to the specific target. The
latter is called mismatch (MM) probe.

Several algorithms for background analysis of Affymetrix chips are
available. Some of these use the MM intensities as corrections for
non-specific hybridization, while others rely on PM intensities only. For
instance, the Affymetrix MAS 5.0 software (Microarray Analysis Suite
version 5.0) uses the difference $(I^{\rm PM} - I^{\rm MM})$ as estimator
of the specific signal; an adjusted MM intensity (ideal MM) is used in the
case the MM intensity exceeds the PM signal~\cite{affy01}. The
Robust Multiarray Algorithm (RMA)~\cite{iriz03} uses a different type
of subtraction scheme which does not involve the MM intensities. The
more recent version of this algorithm GCRMA performs background
subtraction using information on the probe sequence composition
through the calculation of binding affinities~\cite{wu04}. The position-dependent
nearest-neighbor model (PDNN)~\cite{zhan03} fits the background intensity
using weight factors which depend on the position along the probe. The free
energy parameters then enter in a nonlinear function. In the VSN
algorithm~\cite{hube02} a generalized log transform is used to background
correct the data. A study dedicated to the performance of different
algorithms showed that the type of background subtraction used has a large
effect on the global performance of the algorithms~\cite{iriz06}. It is
therefore not surprising that the background issue has attracted a lot
of interest by the scientific community.

In this paper we present an algorithm for background estimation
which combines information from the sequence composition and physical
neighbors on the chip. This algorithm relies on previous work by the
authors~\cite{krol08}. While the previous algorithm performed well with
respect to the accuracy of the background estimation, the computational
effort (per probe) involved was a severe limiting factor concerning its
practical usability.  The main cause of this significant computational
effort was the iterative minimization of a cost function with nonlinear
terms. The algorithm presented in this work involves a different cost
function which is quadratic in the parameters.  Its minimization can
be performed via standard matrix computations of linear algebra. The
algorithm is fast and accurate and is therefore suited for large
scale analysis.

This paper is organized as follows. In Methods we discuss the optimization
step from singular value decomposition and we provide the details of the
selected cost function.  In Results a test of the algorithm on about 360
Genechips from recent (2006 onwards) experiments from the Gene Expression
Omnibus (GEO) is presented. Finally, the advantages of this scheme and
its overall performance as background subtraction method is highlighted.

\section*{Methods}

\subsection*{Approach}

The general assumption is that the (natural) logarithm of the background
intensity can be approximated by a function linear in some fitting
parameters $\omega_{\alpha}$. Once these parameters are set to their
optimal values ${\bar \omega}_\alpha$ an estimate of the background
intensity for the $i$-th ($i=1,2,\ldots N_{dim}$) PM probe can be
obtained as
\begin{equation}\label{eq:back_est}
\log I^{\rm est}_{i, {\rm bg}} =
\sum_{\alpha}  \Omega_{i \alpha} {\bar \omega}_\alpha,\quad\quad
\alpha=1,2,\ldots N_f
\end{equation}
where $N_f$ is the number of fitting parameters. $\Omega_{i \alpha}$
is a sequence- and position-dependent element of the $N_{dim}\times
N_f$-dimensional matrix $\Omega$, which will be defined below.

The optimized values for the model parameters $\bar{\omega}_\alpha$
are obtained by minimizing the difference (of the logarithms) of the
observed and estimated intensities
\begin{eqnarray}\label{eq:function_s}
S &=&  \frac{1}{K}\sum_{k\in\mathcal{K}} \left(\log I_k - \sum_\alpha \Omega_{k
\alpha} \omega_\alpha
\right)^2
\end{eqnarray}
i.e.~solving a linear least square problem.  The sum extends over the
training set $\mathcal{K}$ which is a subset (with $K$ elements) of
the intensities of all annotated features. The choice of the elements
of $\mathcal{K}$ will be discussed later (see Data Set - Parameter
Optimization).  The minimum is found by imposing vanishing partial
derivatives of $S$ w.r.t. $\omega_\alpha$. This yields the following $N_f$
linear equations

\begin{equation}
\label{eq:lin_eq}
\left. \frac{\partial S}{\partial \omega_\alpha} \right|_{\bar\omega} =
\sum_{k\in\mathcal{K}} \Omega_{k \alpha} \left(\log  I_k-\sum_\beta
\Omega_{k\beta}
\omega_\beta \right) = 0,
\end{equation}

which can be rewritten as
\begin{equation}\label{eq:normaleq}
\sum_\beta  M_{\alpha \beta} \bar \omega_\beta = \Gamma_\alpha.
\end{equation}
Here, we have introduced the matrix
\begin{equation}\label{eq:matrixM}
M_{\alpha \beta} = \sum_{k\in\mathcal{K}} \Omega_{k \alpha} \Omega_{k \beta}
\end{equation}
and the vector $\Gamma_\alpha$
\begin{equation}\label{eq:vectorGamma}
\Gamma_{\alpha} = \sum_{k\in\mathcal{K}} \Omega_{k \alpha} \log I_k.
\end{equation}
(Note that $M = \Omega^{T} \Omega$ is symmetric and $\dim(M)=N_{f}\times
N_{f}$).

The solution of Eq.~(\ref{eq:normaleq}) is given by the vector
\begin{equation}\label{eq:sol_omegabar}
\bar\omega = M^{-1} \Gamma
\end{equation}
of the optimal parameter values. If the matrix $M$ is singular,
$M^{-1}$ has to be replaced by its pseudoinverse $M^{+}$ which can
be obtained by means of Singular value decomposition (SVD).  In this
work a standard SVD algorithm based on Golub and Reinsch is used (see
e.g. \cite{golu70,golu96}).

Due to the symmetry of $M$ only half of the off-diagonal elements need
to be generated, hence reducing the computational effort. For the chips
tested in this paper with dimensions up to $1164 \times 1164$ features,
the computational time on a standard PC (x86\_64 Intel Core 2 Duo with
3GHz, 3 GB RAM) required to estimate the background intensities is 8
to 10 seconds for the larger chips, and faster for the smaller ones.
This makes our algorithm an order of magnitude faster than our previous
version \cite{krol08}, 3 to 5 times faster than GC-RMA, PDNN and MAS5,
and about twice as slow as RMA and DFCM (Bioconductor packages were
used for the testing).  Note that for our algorithm, the time estimate
includes both reading in the CEL-file and the background calculation,
as it is done in one step.

This computation involves the generation of the matrix $M$ and vector
$\Gamma$ (from Eqs.~(\ref{eq:matrixM}) and (\ref{eq:vectorGamma})), the
SVD of $M$ to solve Eq.~(\ref{eq:normaleq}) and the estimation of the
background intensity for all PM probes through Eq.~(\ref{eq:back_est}).
Differently from other approaches in which the cost function is
minimized by means of Monte Carlo methods~\cite{ono08} or other dynamical
algorithms~\cite{krol08}, the solution of SVD provides the exact minimum
of the cost function Eq.~(\ref{eq:function_s}). Hence, there is no risk
in getting stuck in local minima different from the global one.

\subsection*{Data Set - Parameter Optimization}

As mentioned above, probes in Affymetrix form PM/MM pairs. Consider
now a target sequence at a concentration $c$ in solution. The analysis
of Affymetrix spike-in data (see e.g. \cite{burd06}) shows that not only the
PM signal increases with increased target concentration $c$ but also
the MM intensity. This is an indication that a single MM nucleotide
only partially prevents probe-target hybridization. Therefore the
intensity of MM probes can also be decomposed in a non-specific
and specific part as in Eq.~(\ref{eq:01}). Supported by Affymetrix
spike-in data analysis, our assumption is that the non-specific part of
the hybridization is about equal for PM and MM probes: $I_{bg}^{(PM)}
\approx I_{bg}^{(MM)}$. The specific part of the signal is different in
those two cases; equilibrium thermodynamics suggests a constant ratio
$I_{SP}^{(PM)}(c)/I_{SP}^{(MM)}(c) = const. > 1$, independent of the
target concentration, as observed in experiments~\cite{ferr09}.

These insights are useful for the selection of probes for the optimization
set $\mathcal{K}$ in Eq.~(\ref{eq:function_s}): $\mathcal{K}$ includes
all MM probes whose intensities are below a certain threshold $I_0$
and whose corresponding PM intensities also fulfill $I^{\rm PM}_k <
I_{0}$ (a similar selection criterion was recently used by Chen et
al.~\cite{chen09}). The threshold $I_0$ is chosen on the basis of
the total distribution of the intensities. $\mathcal{K}$ contains a
significant fraction of the mismatch probes: typically $35\%$.
Since the specific signal of MM intensities is lower than that of
their corresponding PM's, they provide more reliable information on the
background. The coordinates and sequences of the probes in $\mathcal{K}$
are then fitted to the intensities of these probes yielding the parameters
$\omega$. With those newly acquired parameters $\omega$ the background
signal of all MM probes is estimated base upon the assumption $I_{bg}^{(PM)}
\approx I_{bg}^{(MM)}$.

\subsection*{The matrix $\Omega$}

The choice of the matrix elements of $\Omega$ is dictated by input from
physical chemistry as well as by the architecture of the microarray.
Different schemes involving different choices for $\Omega$ with
a varying number of parameters $N_f$ were tested.  Given a choice of
$\Omega$ and in particular the number $N_f$ of fitting parameters, the
accuracy of the background estimation is reflected by the value of $S$
from the minimization of Eq.~(\ref{eq:function_s}). While the addition
of fitting parameters always yields lower values of $S$, a too large set
of fitting parameters runs the risk of ``overfitting". The final choice
of $\Omega$ is a compromise between a minimization of $S$ and the use of the
smallest possible set of parameters.

In the present model the number of parameters is $N_f=50$.
Similarly to the previous work \cite{krol08} these parameters can be
split into two groups: a first group describes the correlation of the
background intensities with features which are physical neighbors on the
chip; the second group are nearest-neighbor parameters which describe
affinities for non-specific hybridization to the chip.

\subsubsection*{Physical Neighbors on the Chip}

The first $18$ parameters $\omega_\alpha$ describe the correlation of the
background intensity with physical neighboring sequences in the array.
Let $(x_i,y_i)$ be the coordinate of the $i$-th MM sequence $s(i)$. Then,
its eight neighbors are located at $(x_i\pm 1,y_i)$, $(x_i \pm 1,y_i\pm1)$,
and $(x_i, y_i\pm 1)$.
As there is evidence that base-specific interactions (purine/pyrimidine
asymmetry) might influence the hybridization process in
general~\cite{bind05}, we furthermore distinguish between probes
whose central nucleotide is either A/G (purine) or C/T (pyrimidine).
Then, the corresponding matrix elements in case of purines can be
written as
\begin{eqnarray}
\Omega_{i 1} &=& \delta_{s(i)}^{A/G}
\label{eq:alpha1} \\
\Omega_{i \alpha} &=& \delta_{s(i)}^{A/G} \log I (x_i+p_\alpha,
y_i+q_\alpha),
\quad \ \ 2 \leq \alpha \leq 9
\label{eq:alpha2_9}
\end{eqnarray}
with
\begin{equation}\nonumber
  \delta_{s(i)}^{A/G} =
\left\{
\begin{array}{cl}
1 &\rm{if\ the\ 13^{th}\ nucleotide\ is\ purine\ (A\ or\ G)} \\
0 &\rm{otherwise}
\end{array}
\right.
\end{equation}
and
\begin{eqnarray}\nonumber
 p_2=p_4=p_7=q_7=q_8=q_9&=&1\\ \nonumber
 p_6=p_9=q_2=q_3&=&0\\\nonumber
 p_3=p_5=p_8=q_4=q_5=q_6&=&-1,\nonumber
\end{eqnarray}
so that the intensities of the neighboring features explicitly enter
the calculation of the background intensity of $(x_i,y_i)$ as matrix
elements $\Omega_{i \alpha}$ ($2 \leq \alpha \leq 9$).  In analogy to
Eqs.~(\ref{eq:alpha1},\ref{eq:alpha2_9}) we define $\Omega_{i\alpha}$
with $10\leq\alpha\leq 18$ corresponding to the sequences with a central
pyrimidine.

\subsubsection*{Nearest-Neighbor Free Energy Parameters}

The second contribution to the background model arises from the sequence
composition. Let us first label the 16 dinucleotides according to the
order $\{CC, GC, AC, TC, CG, GG, AG\ldots TT\}$. We then define
the next 16 matrix elements as
\begin{eqnarray}
\Omega_{i \alpha} &=& \sum_{l=1}^{24} \delta_{l, l+1}^{\alpha-18} (s(i)),
\quad \quad \quad\quad
19 \leq \alpha \leq 34
\label{eq:alpha19_35}
\end{eqnarray}
where
\begin{equation}\nonumber
\delta_{l, l+1}^\gamma (s) =
\left\{
\begin{array}{cl}
1 &\rm{if\ nucleotides\ at\ l\ and\ l+1\ form\ pair\ of\ type}\ \gamma \\
0 &\rm{otherwise}
\end{array}
\right.
\end{equation}
according to the order given above. The sum runs over all the 24
dinucleotides along a probe sequence. The matrix element
$\Omega_{\alpha i}$ is equal to the number of dinucleotides of a given
type in the sequence $s(i)$. For instance, if the sequence $s(i)$
contains $4$ dinucleotides of type $CC$ and $2$ of type $GC$, then
$\Omega_{i, 19} = 4$ and $\Omega_{i, 20} = 2$. Hybridization
thermodynamics predicts $\log I \propto \Delta G$ where $\Delta
G$ is the hybridization free energy. In the nearest-neighbor model
\cite{bloo00} the free energy is written as a sum of dinucleotide terms.
Therefore, the parameters $\omega_\alpha$ ($19 \leq \alpha \leq 35$) are
the analogues of the free energy parameters of the nearest-neighbor model.

\subsubsection*{Position-Dependent Nearest-Neighbors}

Finally, we consider the possibility that the hybridization strength is
``modulated" along the sequence by a parabolic weight as
\begin{eqnarray}
\Omega_{i \alpha} &=& \sum_{l=1}^{24} \delta_{l, l+1}^{\alpha-35} (s(i))
\ (l - l_m)^2,
\quad\quad
35 \leq \alpha \leq 50
\label{eq:alpha35_50}
\end{eqnarray}
where $l_m=12.5$,~i.e. each dinucleotide is given a parabolic weight
according to its position relative to the center at $l_m$ of the
sequence. Thus, possible ``unzipping" effects of the DNA-RNA duplex
are approximately accounted for by Eq.~(\ref{eq:alpha35_50}).

The introduction of a position-dependence effect is in analogy with work
done by other groups~\cite{zhan03,naef03,bind05,zhan07}. However, we
do not introduce a position-dependent weight for each position along the
25-mer sequences. Instead, we limit ourselves to a parabolic modulation
of the parameters along the chain, which drastically reduces the number
of parameters involved in the model.

\subsubsection*{Invariances}

Given the definition of $\Omega$ above it can be shown that
Eq.~(\ref{eq:normaleq}) permits multiple solutions. Therefore, the optimal
parameters $\bar\omega_\alpha$ are not unique.  Consider a set of optimal
parameters $\bar{\omega}_\alpha$ which minimizes the cost function $S$
(Eq.~(\ref{eq:function_s})). Let us then add a constant $\lambda$
to the $16$ nearest-neighbor parameters
\begin{equation}
\bar{\omega}'_\alpha = \bar{\omega}_\alpha + \lambda.
\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \
(19 \leq \alpha \leq 34)
\label{eq:inv1}
\end{equation}
From Eq.~(\ref{eq:alpha19_35}) we obtain
\begin{equation}
\sum_{\alpha =19}^{34} \Omega_{i \alpha} \bar{\omega}'_\alpha =
\sum_{\alpha =19}^{34} \Omega_{i \alpha} \bar{\omega}_\alpha + 24 \lambda
\label{eq:shift1}
\end{equation}
because $\Omega_{i \alpha}$ counts the frequency of the dinucleotide
$\alpha$ in the sequence corresponding to feature $i$ and because there are $24$
dinucleotides in a $25$-mer probe sequence. Now, also consider
\begin{equation}
\bar{\omega}'_1 = \bar{\omega}_1 - 24 \lambda
\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \
\bar{\omega}'_{10} = \bar{\omega}_{10} - 24 \lambda,
\label{eq:shift2}
\end{equation}
while $\bar{\omega}'_\alpha = \bar{\omega}_\alpha$ for all other
$\alpha$.  We conclude that the reparametrization of~Eqs.~(\ref{eq:inv1})
and~(\ref{eq:shift2}) yields
\begin{equation}
\sum_{\alpha =1}^{50} \Omega_{i \alpha} \bar{\omega}'_\alpha =
\sum_{\alpha =1}^{50} \Omega_{i \alpha} \bar{\omega}_\alpha
\label{eq:inv2}
\end{equation}
since the shifting of Eq.~(\ref{eq:shift2}) compensates the one introduced
by Eq.~(\ref{eq:shift1}). This reparametrization, valid for any real
$\lambda$, leaves $S$ invariant, and produces a zero eigenvalue of the
matrix $M$ of Eq.~(\ref{eq:matrixM}).

Similarly, one can verify that there is at least a second zero
eigenvalue: a shift of the position-dependent nearest-neighbor
parameters $\bar{\omega}_\alpha' = \bar{\omega}_\alpha + \lambda$
(for $35 \leq \alpha \leq 50$) as well as of $\bar{\omega}_1' =
\bar{\omega}_1 - 1150\lambda$, $\bar{\omega}_{10}' = \bar{\omega}_{10}
- 1150\lambda$ leaves $S$ invariant. To obtain the latter equations
Eq.~(\ref{eq:alpha35_50}) and $\sum_{l=1}^{24}(l-l_m)^2=1150$ have to
be applied.

Having zero eigenvalues, the matrix $M$ is therefore not invertible;
the SVD thus provides the appropriate pseudo-inverse as discussed above.
Accidental degeneracies or quasi-degeneracies of M could also occur,
yielding eigenvalues close to zero in machine precision. These are, however,
rare, and were actually never found in the calculations presented here.

\section*{Results}

We analyzed a total of 366 CEL-files which are publicly available from the
GEO server (www.ncbi.nlm.nih.gov/geo). Table~\ref{Tab:overview_organisms_en} gives an overview of the
distribution of CEL-files over the twelve different organisms considered
in this study. The array size for an organism might vary depending on
the GSE accession number, since the most recent Affymetrix chips tend
to use smaller features, thus more probes can be accommodated on the
same surface area. For instance the Human HGU-133A contains $712^2$
features, while the Human Genome U133 Plus 2.0 Array goes to $1164^2$
features. The last column of Table~\ref{Tab:overview_organisms_en} lists the attained minimum value
$\bar S_{min}$, which ranges from $0.017$ for Escheria Coli to $0.11$
for Oryza Sativa.  $\bar S_{min}$ estimates the mean squared deviation
of the logarithm of the estimated background intensity from the actual
background value. For instance $\bar S_{min}=0.01$ corresponds to a
$10\%$ deviation, while $\bar S_{min}=0.1$ corresponds to a $37\%$
deviation.

\begin{table}[!t]
\centering
{\begin{tabular}{lllcl}
 Organism & GEO \# & Chiptype (dimension) & \# files & $\bar S_{min}$ \\%\midrule
\hline
&GSE4847         & ATH1-121501 (712x712)&     18      &       0.0259\\
{A. Thaliana}
&GSE7642        &  ATH1-121501 (712x712) &   12      &       0.0544\\
&GSE9311        &   ATH1-121501 (712x712) &  8       &       0.0546\\%\midrule
\hline
{C. Elegans} &
GSE6547         &   Celegans (712x712)  & 25      &       0.0361\\
&GSE8159        &   Celegans (712x712)   &7       &       0.0396\\%\midrule
\hline
{D. Melanogaster} &
GSE3990         &   Drosophila\_2 (732x732)    & 6       &       0.0620\\
&GSE6558        &    DrosGenome1  (640x640) &24      &       0.0605\\%\midrule
\hline
D. Rerio &GSE4859      & Zebrafish (712x712) &       8       &       0.0357\\%\midrule
\hline
&GSE11779&  E\_coli\_2 (478x478)  &  3       &       0.0869\\
{E. Coli}
&GSE2928        &   Ecoli (544x544)   &12      &       0.0172\\
&GSE6195        &    E\_coli\_2 (478x478)  &4       &       0.0664\\%\midrule
\hline
&GSE10433&  HG-U133A\_2 (732x732)  &  12      &       0.0757\\
&GSE5054        &    HG-U133A (712x712)&20      &       0.0392\\
{H. Sapiens}
&  & HG-U133A\_2 (732x732) &  & \\
&GSE7148        &    HG-U133A (712x712)  &14      &       0.0296\\
&GSE8514        &    HG-U133\_Plus\_2 (1164x1164)  &15      &       0.0738\\%\midrule
\hline
&GSE11897&   MOE430A (712x712)& 11      &       0.0640\\
&  & MOE430B (712x712) &  & \\
{M. Musculus}
&  & Mouse430\_2 (1002x1002) &  & \\
&GSE6210        &   Mouse430\_2    &12      &       0.0594\\
&GSE6297        &   Mouse430\_2    &24      &       0.0325\\%\midrule
\hline
O. Sativa & GSE15071 & Rice (1164x1164)  &20      &       0.1157\\%\midrule
\hline
&GSE4494 &   RG\_U34A (534x534)   &59      &       0.0488\\
{R. Norvegicus}
&GSE7493        &   Rat230\_2 (834x834)  & 9       &       0.0497\\
&GSE8238        &   Rat230\_2 (834x834)  & 4       &       0.0640\\%\midrule
\hline
S. Aureus & GSE7944   & S\_aureus (602x602) &       6       &       0.0746\\%\midrule
\hline
{S. Cerevisiae} &
GSE6073 &    YG\_S98 (534x534) & 12      &       0.0283\\
&GSE8379        &   YG\_S98 (534x534)  & 8       &       0.0180\\%\midrule
\hline
X. Laevis & GSE3368   & Xenopus\_laevis (712x712) &       20      &       0.0514\\
\hline
\end{tabular}}
\caption{Overview over organisms and number of CEL-files
 analyzed}
\label{Tab:overview_organisms_en}
\end{table}

Table~\ref{Tab:params1} provides a summary of the optimal parameters as
calculated from the Singular Value Decomposition for the minimization
of the cost function of Eq.~(\ref{eq:function_s}).  The parameters
$\bar{\omega}_1$ and $\bar{\omega}_{10}$ are associated to constant
intensities for purines and pyrimidines. Their magnitudes are not unique
due to the reparametrization as discussed in Eqs.~(\ref{eq:inv1}) to
(\ref{eq:inv2}). If information on neighboring probes is disregarded,
the value of $S$ typically increases by 45\%; if the sequence information
is not directly used, then it will increase by 52\%. In the following we
analyze the parameters associated to the local physical neighbors
and to the nearest-neighbor free energy.

\begin{table}
\centering
\scriptsize
\begin{tabular}{c|ccc|cc|cc|c}
&\multicolumn{3}{c}{A. Thaliana} &\multicolumn{2}{c}{C. Elegans}
&\multicolumn{2}{c}{D. Melanogaster} &\multicolumn{1}{c}{D. Rerio}
\\
GEO no  & GSE4847 & GSE7642 & GSE9311 & GSE6547 & GSE8159 & GSE3990 & GSE6558 &
GSE4859 \\
\hline
$\bar{\omega}_1$        &0.178  &0.196  &0.261  &0.379  &0.520  &0.270  &0.421  &0.338
\\
$\bar{\omega}_2$        &0.050  &0.056  &0.042  &0.047  &0.050  &0.022  &0.025  &0.041
\\
$\bar{\omega}_3$        &0.051  &0.056  &0.041  &0.034  &0.042  &0.024  &0.024  &0.050
\\
$\bar{\omega}_4$        &-0.013 &-0.012 &-0.013 &-0.012 &-0.016 &-0.005 &-0.011 &-0.012
\\
$\bar{\omega}_5$        &-0.013 &-0.011 &-0.012 &-0.010 &-0.012 &-0.003 &-0.010 &-0.008
\\
$\bar{\omega}_6$        &0.186  &0.198  &0.224  &0.168  &0.271  &0.228  &0.195  &0.140
\\
$\bar{\omega}_7$        &0.004  &0.005  &0.003  &0.003  &0.005  &0.001  &0.005  &0.006
\\
$\bar{\omega}_8$        &0.002  &0.009  &0.003  &0.002  &0.005  &0.001  &0.006  &0.002
\\
$\bar{\omega}_9$        &0.013  &0.027  &0.010  &0.008  &0.008  &0.009  &0.012  &0.014
\\
$\bar{\omega}_{10}$     &-0.174 &-0.192 &-0.258 &-0.375 &-0.517 &-0.267 &-0.418 &-0.334
\\
$\bar{\omega}_{11}$     &0.063  &0.060  &0.059  &0.058  &0.062  &0.042  &0.057  &0.068
\\
$\bar{\omega}_{12}$     &0.069  &0.064  &0.064  &0.052  &0.059  &0.046  &0.061  &0.075
\\
$\bar{\omega}_{13}$     &-0.017 &-0.015 &-0.016 &-0.011 &-0.012 &-0.012 &-0.013 &-0.016
\\
$\bar{\omega}_{14}$     &-0.018 &-0.016 &-0.019 &-0.010 &-0.009 &-0.011 &-0.014 &-0.012
\\
$\bar{\omega}_{15}$     &0.258  &0.299  &0.328  &0.301  &0.459  &0.336  &0.316  &0.246
\\
$\bar{\omega}_{16}$     &0.004  &0.006  &0.005  &0.005  &0.009  &0.002  &0.008  &0.007
\\
$\bar{\omega}_{17}$     &0.002  &0.007  &0.003  &0.003  &0.006  &0.001  &0.007  &0.004
\\
$\bar{\omega}_{18}$     &0.013  &0.025  &0.012  &0.012  &0.015  &0.009  &0.016  &0.016
\\
\hline
$\bar{\omega}_{19}$ & 0.068 & 0.138 & 0.143 & 0.149 & 0.155 & 0.159 & 0.217 & 0.140
\\
$\bar{\omega}_{20}$ & 0.052 & 0.191 & 0.169 & 0.090 & 0.157 & 0.124 & 0.152 & 0.140
\\
$\bar{\omega}_{21}$ & -0.021 & -0.038 & 0.006 & -0.033 & 0.030 & -0.060 & -0.033 & -0.069
\\
$\bar{\omega}_{22}$ & -0.021 & 0.051 & 0.056 & -0.025 & 0.072 & -0.084 & 0.003 & -0.068
\\
$\bar{\omega}_{23}$ & -0.032 & -0.162 & -0.147 & -0.038 & -0.121 & -0.060 & -0.094 & -0.104
\\
$\bar{\omega}_{24}$  & 0.041 & 0.075 & 0.072 & 0.024 & 0.015 & 0.030 & 0.048 & 0.035
\\
$\bar{\omega}_{25}$ & -0.063 & -0.221 & -0.162 & -0.122 & -0.140 & -0.172 & -0.200 & -0.190
\\
$\bar{\omega}_{26}$ & -0.060 & -0.130 & -0.119 & -0.118 & -0.109 & -0.173 & -0.154 & -0.181
\\
$\bar{\omega}_{27}$ & 0.000 & -0.008 & -0.047 & 0.035 & -0.041 & 0.052 & 0.035 & 0.055
\\
$\bar{\omega}_{28}$ & 0.036 & 0.148 & 0.076 & 0.062 & 0.063 & 0.105 & 0.096 & 0.128
\\
$\bar{\omega}_{29}$ & -0.026 & -0.058 & -0.069 & -0.046 & -0.044 & -0.065 & -0.085 & -0.052
\\
$\bar{\omega}_{30}$ & -0.050 & -0.032 & -0.093 & -0.065 & -0.052 & -0.106 & -0.102 & -0.078
\\
$\bar{\omega}_{31}$ & 0.057 & 0.037 & 0.056 & 0.082 & 0.012 & 0.133 & 0.103 & 0.130
\\
$\bar{\omega}_{32}$ & 0.093 & 0.180 & 0.173 & 0.125 & 0.112 & 0.211 & 0.181 & 0.221
\\
$\bar{\omega}_{33}$ & 0.011 & -0.074 & -0.021 & -0.008 & -0.026 & 0.015 & -0.036 & 0.001
\\
$\bar{\omega}_{34}$ & -0.009 & -0.017 & -0.016 & -0.023 & -0.014 & -0.035 & -0.047 & -0.022
\\
Corr. Coeff   & 0.775 & 0.686 & 0.738 & 0.814 & 0.700 & 0.754 & 0.826 & 0.705
\\

\hline
$\bar{\omega}_{35}$ & 0.020 & 0.016 & 0.016 & 0.019 & 0.013 & 0.016 & 0.012 & 0.018
\\
$\bar{\omega}_{36}$ & 0.020 & 0.010 & 0.012 & 0.021 & 0.011 & 0.016 & 0.016 & 0.017
\\
$\bar{\omega}_{37}$ & 0.025 & 0.025 & 0.022 & 0.029 & 0.019 & 0.028 & 0.027 & 0.031
\\
$\bar{\omega}_{38}$ & 0.024 & 0.019 & 0.019 & 0.028 & 0.016 & 0.028 & 0.023 & 0.031
\\
$\bar{\omega}_{39}$ & 0.026 & 0.036 & 0.034 & 0.030 & 0.030 & 0.027 & 0.031 & 0.033
\\
$\bar{\omega}_{40}$  & 0.021 & 0.021 & 0.020 & 0.026 & 0.021 & 0.022 & 0.023 & 0.026
\\
$\bar{\omega}_{41}$ & 0.028 & 0.039 & 0.035 & 0.036 & 0.031 & 0.035 & 0.038 & 0.039
\\
$\bar{\omega}_{42}$ & 0.027 & 0.032 & 0.031 & 0.035 & 0.028 & 0.033 & 0.033 & 0.038
\\
$\bar{\omega}_{43}$ & 0.023 & 0.024 & 0.026 & 0.024 & 0.023 & 0.019 & 0.021 & 0.021
\\
$\bar{\omega}_{44}$ & 0.020 & 0.013 & 0.017 & 0.022 & 0.015 & 0.015 & 0.017 & 0.016
\\
$\bar{\omega}_{45}$ & 0.024 & 0.028 & 0.028 & 0.030 & 0.024 & 0.027 & 0.029 & 0.029
\\
$\bar{\omega}_{46}$ & 0.025 & 0.025 & 0.029 & 0.030 & 0.024 & 0.028 & 0.029 & 0.030
\\
$\bar{\omega}_{47}$ & 0.020 & 0.022 & 0.020 & 0.022 & 0.021 & 0.015 & 0.019 & 0.016
\\
$\bar{\omega}_{48}$ & 0.017 & 0.012 & 0.012 & 0.019 & 0.013 & 0.010 & 0.014 & 0.011
\\
$\bar{\omega}_{49}$ & 0.023 & 0.029 & 0.026 & 0.028 & 0.023 & 0.023 & 0.028 & 0.026
\\
$\bar{\omega}_{50}$ & 0.023 & 0.023 & 0.023 & 0.028 & 0.021 & 0.024 & 0.026 & 0.026
\\
Corr coeff & -0.679 & -0.618 & -0.679 & -0.759 & -0.631 & -0.683 & -0.783 &
-0.658
\\
\end{tabular}{}
\caption{Optimized parameter values as obtained from the minimization
of Eq.~(\ref{eq:function_s}). Magnitudes and signs of the parameters are
approximately constant across different experiments. The correlation
coefficients are the Pearson correlations between the nearest-neighbor
parameters and the free energy parameters measured in hybridization
experiments in aqueous solution \cite{sugi95}.}
\label{Tab:params1}
\end{table}

\subsection*{Parameters of physical neighbors in the Chip}

The parameters $\bar{\omega}_{2}$ to $\bar{\omega}_{9}$ and
$\bar{\omega}_{11}$ to $\bar{\omega}_{18}$ describe the coupling of
the background intensities to the physically neighboring features on the
chip. As already mentioned, our estimate of the PM background is based
on the non-specific intensity of the MM sequence. An Affymetrix chip
is designed such that MM and PM are found in rows at equal $y$-coordinates.
In addition, given a PM at $(x, y)$, the corresponding MM feature is at
$(x, y+1)$.

Figure~\ref{fig:neighbors_350} schematically represents the influence
of the neighboring intensities on the background value. The strength
of the correlation of the eight neighboring spots (i.e.~the magnitude
and sign of the corresponding $\bar \omega_\alpha$) with the central MM
feature is indicated by the color.
\begin{figure}[h!]
\centerline{{neighbors_350.eps}}
\caption{\textbf{Correlations with neighboring features:}
Schematic representation of the neighboring parameters on the
array. The inset numbers indicate the corresponding parameter(s)
$\bar{\omega}_{\alpha}$,~e.g. 3/12 represents $\bar{\omega}_{3}$,
$\bar{\omega}_{12}$ respectively. $\bar{\omega}_2$ through
$\bar{\omega}_{9}$ are related to purines, $\bar{\omega}_{11}$
to $\bar{\omega}_{18}$ to pyrimidines. The bar to the right gives the
intensity scale of the parameters.  The dashed pattern indicates
negative values. Box on the left indicates the rows of corresponding
PM and MM pairs. The central feature (position $(x,y)$) is a MM;
its corresponding PM is located just below it $(x,y-1)$, its intensity
has the strongest correlation with the central MM feature. The features
in $(x \pm 1,y-1)$}
\label{fig:neighbors_350}
\end{figure}

The numbers in Fig.~\ref{fig:neighbors_350} identify the associated parameters $\bar{\omega}_\alpha$.
For example $\bar{\omega}_6$ and $\bar{\omega}_{15}$ are associated to the intensity at $(x,y-1)$
with respect to the reference MM intensity with coordinates $(x,y)$.
There does not seem to be any evidence that the middle-nucleotide
classification in purines and pyrimidines reveals any insight concerning
the background. Instead, our results show that the absolute values of two
''corresponding`` (purine-pyrimidine pair) $\bar{\omega}_{\alpha}$'s
are generally of the same order of magnitude.  Across all species,
we find typical average outputs of
\begin{eqnarray}\nonumber
&\lbrace\bar{\omega}_{2/11},\ldots,\bar{\omega}_{9/18}\rbrace\approx
&\lbrace 0.04,0.04,-0.015,-0.015,0.30,0.005,0.005,0.015\rbrace.\nonumber
\end{eqnarray}
Since $\bar{\omega}_{6}$, $\bar{\omega}_{15}$ respectively, reflects the
correlation of the MM signal with its corresponding PM. As expected its
magnitude is greatest among all parameter values. Next, the MM intensity
shows strong correlations with its direct nearest neighbors positioned at
$(x\pm1,y)$,~i.e. $\bar{\omega}_{2/11}$ and $\bar{\omega}_{3/12}$. Hence,
the stronger the MM-neighboring intensities, the stronger their influence
on the background signal of MM.  However, in order to somehow compensate
for strong MM-neighboring signals which might be caused by the presence
of complementary target sequences, parameters $\bar{\omega}_{4/13}$
and $\bar{\omega}_{5/14}$ have negative sign. The remaining three
parameters,~i.e.~the top three neighbors limit their influence to a
basically negligible minimum which appears to indicate the weak sequence
correlation in $y$-direction as previously found.  The results indicate
that the influence of neighboring intensities on the background noise
is significant. In fact, our analysis shows that $\approx 30\%$ of
$\log I_{i,bg}^{est}$ are constituted by neighboring probes in terms of
absolute intensities (see Table~\ref{Tab:local_percentage}). It appears that for a few probes,
the latter might even play a crucial role.

It is unlikely that the correlations summarized in Fig~\ref{fig:neighbors_350}
could be explained only as simple optical effects,
as light from bright probes spilling into their neighborhood.
Indeed, optical effects
should produce an isotropic correlation pattern in the $x$ and $y$
directions which is not seen in our analysis. Another cause for this
correlation might be that neighboring probes share common sequences,
as is the case in Affymetrix chips~\cite{krol08}.

\begin{table}[h!]
\centering
\begin{tabular}{l|ll}
X. Laevis & 74500.CEL & 76190.CEL \\
 & 35\% & 37\% \\
\hline
C. Celegans & 201989.CEL & 201994.CEL \\
 & 43\% & 52\% \\
\hline
H. Sapiens & 263931.CEL & 263930.CEL \\
 & 41\% & 39\% \\
\hline
S. Cerevisiae & 207569.CEL & 207570.CEL \\
 & 29\% & 29\%
\end{tabular}{}
\caption{Influence of neighboring spot on background intensity in \%
of eight (randomly chosen) CEL-files of different organisms.}
\label{Tab:local_percentage}
\end{table}

\subsection*{Nearest-Neighbor Parameters}

The parameters $\bar{\omega}_{\alpha}$ ($19\leq\alpha\leq 34$) are
the analogues of the nearest-neighbor free energy parameters. The
nearest-neighbor model is commonly used to study the thermodynamics
of hybridization of nucleic acids in solution (see e.g. \cite{bloo00}). In
this model it is assumed that the stability and thus the hybridization
free energy $\Delta G$ of a dinucleotide depends on the orientation and
identity of the neighboring base pairs. For RNA/DNA duplexes there are
16 hybridization free energy parameters which were measured in aqueous
solution by Sugimoto et al.~\cite{sugi95}.

Recent experiments~\cite{hooy09} focusing on specific hybridization show
a good degree of correlation between the hybridization free energies in
solution and those directly determined from microarray data. Concerning
background data, we also expect a certain degree of correlation between
the parameters $\bar{\omega}_{\alpha}$ ($19\leq\alpha\leq 34$) and
their corresponding Sugimoto free energy parameters.

In order to test the relationship between the experimentally determined
so-called Sugimoto parameters and our results, we calculate the
correlation coefficient between these two sets. The results are reported
in Table~2. In general, the correlation coefficients vary between $0.53$
and $0.83$ with a median value of $0.71$. Figure~2 shows two typical
results for C. Elegans and D. Melanogaster. Both plots indicate that
the relationship between $\bar{\omega}_{\alpha}$ ($19\leq\alpha\leq
34$) and the nearest-neighbor free energy parameters of~\cite{sugi95}
is approximately linear.

\begin{figure}[!t]
\centerline{[width=12cm,height=16cm]{pX_CElegans_DMela.eps}}
\caption{\textbf{Fitted vs. solution hybridization free energies:}
Pair Parameters $\bar{\omega}_{\alpha}$ ($19\leq\alpha\leq 34$),
as obtained from the minimization of Eq.~(\ref{eq:lin_eq}) as function of
$\Delta G_{\alpha}$, the nearest-neighbor stacking free energy obtained
from DNA/RNA hybridization in solution~\cite{sugi95}. Plots refer
to two GSE training data sets of a) C. Elegans and b) Drosophila
Melanogaster. Each point on the $y$-axis is the averaged value
over all CEL-files representing its GSE-set. The error bars are the
standard deviation.  Notation of DNA pairs are from 5' to 3' end. The
straight lines are linear fits; correlation coefficients of each GSE
set in legend.}
\label{fig:sugi_worm_fly}
\end{figure}

\subsection*{Position-dependent nearest neighbor parameter}

Figure~\ref{fig:parabsugi_worm_fly} shows a plot of position-dependent nearest-neighbor parameters
$\bar{\omega}_{35}$ to $\bar{\omega}_{50}$ as obtained from the
minimization of the cost function of Eq.~(\ref{eq:function_s}) for four
different sets of experiments. The data are plotted as function of the
corresponding nearest neighbor free energy parameters of~\cite{sugi95}. We
note that in all experiments shown there is a negative correlation between
the two data sets. The parameters $\bar{\omega}_{35}$ to $\bar{\omega}_{50}$
reflect the difference in effective free energy between the ends and the
middle of the probe sequence. Since weakly binding probes suffer more from
end-effects (unzipping, etc.), $\bar{\omega}_{35}$ to $\bar{\omega}_{50}$
and their corresponding nearest-neighbor free energy parameters are
negatively correlated. Hence, the negative correlation in Fig.~3
and those observed in all other cases (see correlation coefficients
reported in Table~2) indicates that the dominant contribution to the
background intensity comes from the middle nucleotides. This conclusion
complies with other types of analysis which use position-dependent
free energy parameters (see e.g.~\cite{bind05,zhan03}).

\begin{figure}[!t]
\centerline{[width=12cm,height=16cm]{parabX_CElegans_DMela.eps}}
\caption{\textbf{Fitted vs. solution hybridization (position
dependent) free energies: }Same as in Fig.~\ref{fig:sugi_worm_fly} for parabolic pair
parameters,~i.e.  $\Delta G_{\alpha}$ vs. $\bar{\omega}_{\alpha}$
($35\leq\alpha\leq 50$) for a) C. Elegans and b) D. Melanogaster}
\label{fig:parabsugi_worm_fly}
\end{figure}

\subsection*{Comparing estimated vs. measured background}

In this section we compare the estimated background signal (as given in
Eq.~(\ref{eq:back_est})) with the intensities of given probe
sets corresponding to non-expressed genes in the samples analyzed.
We start with publicly available data taken from spike-in experiments
on HGU95A chips (www.affymetrix.com) where genes have been spiked-in at
known concentrations, ranging from $0$ to $1024$ pM (picoMolar). The
data at $0$ pM correspond to the absence of transcript in solution.
Figure~\ref{fig:37777and209606}a compares the measured and predicted background for probeset
37777\_at. Except for probes 2 and 15 for which the measured signal is
higher than the predicted background, there is a nice agreement between
our prediction and the experimental background intensity: the standard
deviation of the absolute difference between the intensity of the PM
and $I^{\rm est}$ is $28$ in Affymetrix intensity units. Also shown are
the background estimations as obtained with other algorithms (the data
for PDNN is missing in Fig.~\ref{fig:37777and209606}a due to the unavailability of one of the
supporting files from Bioconductor packages). Figure~\ref{fig:37777and209606}b presents the
same information for probeset 209606\_at. Here, the standard deviation
is $7$ in Affymetrix intensity units.
\begin{figure}[!t]
\centerline{[width=12cm,height=16cm]{fig4.ps}}
\caption{\textbf{Computed vs. true background (spike-in
experiments)}Experimental results ($I0PM$) and theoretical
predictions of the algorithms discussed here for a) probeset
37777\_at (HGU95A, 1521a99hpp\_av06.CEL) and b) 209606\_at
(HGU133A,12\_13\_02\_U133A\_Mer\_Latin\_Square\_Expt10\_R1.CEL) spiked-in
at concentration $c=0$, i.e. absent from the hybridizing solution.
All comparison were performed using freely available packages from the
Bioconductor project.}
\label{fig:37777and209606}
\end{figure}

Next, we go beyond the spike-in experiments. To select non-expressed
genes we considered probe sets with very low expression values as
obtained from the RMA algorithm. In Figure~\ref{fig:AThandCEl} the PM intensities as well
as the calculated background signal of two probesets from A. Thaliana
and C. Elegans experiments are shown. The absolute intensities of
both probesets are very low. As a consequence, we can safely
assume these genes are not expressed and hence any measured signal
can be attributed to the background.

\begin{figure}[!t]
\centerline{[width=12cm,height=16cm]{AThGSE4847_GSM107_256610_at_CElGSE8159_GSM1995_175270_at.eps}}
\caption{\textbf{Computed background vs. low expressed genes data:} Experimental results (solid black line) and theoretical prediction
(dashed red line) of probeset a) 256610\_at (A. Thaliana, GSE4847,
GSM109107.CEL) and b) 175270\_at (C. Elegans, GSE8159, GSM201995.CEL)}
\label{fig:AThandCEl}
\end{figure}
Figures~\ref{fig:37777and209606} and~\ref{fig:AThandCEl}  both show that
the present model captures the essentials of and correctly predicts
background intensities. Both Figures are representative for the
CEL-files analyzed in this work.

\section*{Discussion}
We have presented a background subtraction scheme for Affymetrix
GeneExpression arrays which is both, accurate and usable on a standard
x86\_64 Intel Core 2 PC. The algorithm centers around a cost function
which is quadratic in its fitting parameters. This allows for a rapid
minimization, through linear algebra, in particular through singular
value decomposition. The accuracy of the present algorithm is very
similar to that of a background algorithm previously presented by the authors
\cite{krol08}. The latter had been tested on Affymetrix spike-in data and its
performance was compared to background schemes such as MAS5, RMA and
GCRMA. Regarding spike-in data, the analysis had shown that the
proposed algorithm is definitely more accurate than background
computations done with MAS5 and RMA, but also improves on GCRMA~\cite{krol08}.

The proposed algorithm has two categories of fitting parameters. The
first category exploits correlations between features which are neighbors
on the chip. The second category is based on the strong similarity
between probe-target hybridization and duplex stability in solution, and
involves stacking free energies in analogy to those in the nearest-neighbor
model. Existing algorithms are either of the first ~\cite{affy01}
or the second~\cite{wu04,iriz06,zhan03} category, but not both.

The background subtraction scheme has been tested on 360 GeneChips
from publicly available data of recent expression experiments. Since
the fitted values for the same parameters in different experiments
do not show much variation, the algorithm is robust and can be easily
transferred to other experiments.

Due to its speed and accuracy the present method is suited for
large scale computations. An R-package integrating the background
analysis scheme with the computation of expression values from
background subtracted data will be made freely available to the
community (a preliminary version of this package can be found in
\url{http://itf.fys.kuleuven.ac.be/~enrico/ilm.html}).  The performance
of this approach is discussed in \cite{muld09}.

\section*{Competing interests}
The authors declare that they have no competing interests.

\section*{Authors contributions}
EC and GB planned and supervised the research. KMK wrote the code for
data analysis and analyzed the data. KMK and EC wrote the paper.

\section*{Acknowledgements}
  \ifthenelse{\boolean{publ}}{\small}{}
We acknowledge financial support from FWO (Research Foundation - Flanders)
grant n. G.0311.08.  Stimulating discussions with N. Naouar are gratefully
acknowledged.

redpajama_set_name: RedPajamaArXiv


lol, I think you're still missing the point Vid……..
i did read it.. i dont like today tonight!
i think you should read benno's comment again, slowly this time.
andrew B…. i dont favour 20 to 1.
i said it a great concept for a show…. and regardless if its on any ch.
today tonight??? are u kidding???
Saturdays numbers make me so happy, ABC leading TEN followed by 7 & 9!
ABC 1st for Sat. Well done. Wonder what the commercials think of that.
Vid, nobody here is claiming to be an 'expert' in television – it all comes down to taste. RichoTB doesn't like Medium because he isn't in the target demographic for the show. I don't like 20 to 1 because i like quality television 🙂 If ratings = quality, then by the same logic, Today Tonight is one of the highest quality shows around….
9's Friday night sit coms aren't doing too well in the Southern markets, beaten by The Simpsons rpts and smashed by Better Homes.
I'll be interested to see how the IPL matches went last night/this morning on One.
I guess the only way we can really judge the secondary channels in terms of numbers of viewers for programmes is maybe against the Pay TV channels.
Obviously the ratings will be down on what they were on Ten last year.
@vid – yes – absolutely we are all entitled to our opinions – but all of yours seem to obsess about 20-1 – more than anyone else here and more than anyone else comments about their own fave shows – to the point where we expect to see an appraisal of 20-1 here every Friday from you after the Thur night ep. Sure – it rates OK, but doesn't set the world on fire and no doubt it rates as a direct consequence of the lack of options available on Thursday night and many viewers settling on a show that requires little or no thought to follow.
And next week it is on Tue 9.30 as well. I'd be surprised if that one pulls anymore than 600k given that it is a last minute change from 9 and the printed guides we all see in the Sunday papers will still show Ramsey at that time.
@RichoTB… what makes u an expert at television???
i can say what i like… 20 to 1 is a great concept..no matter if its on 2,7,9,10,sbs.
its proven itself time and time again as u can see with the ratings.
I watched Medium for 5 minutes last night and turned it off. Bad writing, bad acting, and a joke of a storyline. That's a reason for its terrible ratings, numb3rs and Law and Order usually get a lot more in the 8.30 Friday slot.
And vid, its obvious you're Bert's makeup assistant. Quit picking fights with people.
Thursday Night Live got 34,000. In regards to the week's top 100 which is released on Sundays, no ONE programs will make it based on the figures that i have seen.
i don't think that Ten's Friday nights are a failure. The only reason that Ten slipped into fourth was because all its programs from 7.30 were repeats and as such not must-see.
Impressive numbers for Better Homes. It really seems to hit it's stride over the winter months. Midsommer Murders also did really well, pushing abc to third for the night, and ten to fourth. Ten's Friday lineup would have to be considered a failure.
Well actually Ryan there has only been one season of Rafters, it was just split over 2008 and 2009. One episode dropped below 1.7, because it was up against the high rating cricket on 9. It's average in 2009 was just over 1.8m, which was only down 100k from the 2008 average of just over 1.9m (not down 200-400k as you previously stated).
The fact it finished with over 2mill just goes to show there is a lot of life left in it yet.
i didnt say anything bad about u.. why are u so negative??
I reckon vid works in the production of 20-1. Or maybe he's Bert himself!
Anyone know how Thursday Night Live rated last night??? Did any of the One HD shows make the top 100 this week???
ryan, you are aware Rafters finished with over 2mill….which was higher than it's debut. But I see you're being delusional as always with your Channel Ten spectacles on.


text:
Kenya Forest Dwellers Say Government Evictions Leave Several Dead, Injured
NAIROBI, KENYA – Human Rights Watch says Kenyan security agencies have abused and evicted people in Mau forest in an unlawful manner. The rights group said nine people have died, including two children, in the eviction process that began in 2018.
The government maintains that the ongoing evictions are part of a wider effort to reclaim the forest, which is a key source of water and clean air for the country.
Human Rights Watch says that since June 2018, Kenyan wildlife service, police and county security personnel have been evicting families living in the Mau forest, in Kenya's Rift Valley region.
It says some of the evicted were physically abused and died in the process.
Otsieno Namwaya, the rights group's researcher in Kenya, said, "We are talking about nine deaths, not through shooting, but directly related to the eviction, because some were beaten, others were hit with tear gas canisters, others fell while running away and broke their legs, ribs, and later died. Young kids, at least two below 5 years, died in the process of eviction, but that's something we need to look into, not just ignore."
Moving thousands out
The allegation comes a month after Kenyan authorities announced a plan to move about 60,000 people out of the forest to protect it.
The government denies using force to clear out the forest.
The government has never at any one time evicted people from Mau; the government has never used force to get anybody out of Mau. What has been happening in Mau is a voluntary � people moving out of Mau voluntarily. So when you are saying people have been killed in Mau, nothing can be further from the truth than that, said government spokesman Cyrus Ogunda.
Earlier evictions
Bernard Sang, leader of the 2018 evictees, says he remembers the day security forces came to the part of the forest he called home.
This security personnel came on that day [eviction day] abruptly on date 6th and 7th and they started evicting us that day, he said. We were not given any notice. Several people were beaten, several were injured, several homes were torched. Some people's legs were broken.
Sang is one of 10,000 settlers allegedly evicted from the forest.
In August, the state gave the remaining communities in the forest 60 days to leave.
Sang says that despite the 60-day notice, people are still being forcibly evicted from Mau.
This government is very serious; they are evicting people now, he said. They are destroying their homes right now, even [before] the 60 days ultimatum given, they started beating people and destroying their property.
Mau forest covers 400,000 hectares (988,421 acres), which the government has tried to clear of settlers. Some environmentalists believe the human encroachment into forest areas has contributed to repeated droughts in the country.
Source: Voice of America
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text:
$300 Prize Pack- Bulletproof Backpack, T-Shirt, Ballistic Wallet Enter Today!
Groundbreaking Company Offers FREE Heirloom Seeds, When You Join Their Gardening Community
Gun Control — No Matter What Your Opinion, You Need To See This!
Congressman Trolls Zuckerberg in Most EPIC Way, Check Out What He Just Handed Him!
WHOA! Supreme Court Backs Trump In A HUGE WAY!
Daphne Moon December 4, 2017
The Supreme Court Handed Trump a major victory today by full enforcing the travel ban that Trump has fought to put into place since taking office. This ban covers countries who harbor terrorist or pose a threat to the American people.
While the liberals have argued this ban singles out Muslims, we rational thinkers know this isn't a 'war on Muslims' but a war on potential radical threats. This judgment is a huge move in putting America first! Here is what we've found.
As Reported By Barnini Chakraborty With Fox News:
White House Deputy Press Secretary Hogan Gidley called the ban "lawful and essential to protecting our homeland."
Gidley added in a written statement, "We look forward to presenting a fuller defense of the proclamation as the pending cases work their way through the courts."
"We are pleased that the Supreme Court has agreed to allow us to fulfill this most vital mission performed by any sovereign nation. DHS will continue to fully implement the President's robust and Constitutional counterterrorism agenda in accordance with the law," the Department of Homeland Security's acting press secretary, Tyler Q. Houlton, said.
Trump's travel ban has been challenged in separate lawsuits by Hawaii and the American Civil Liberties Union. Both have argued the ban discriminates against Muslims and should not go into effect under immigration laws.
"President Trump's anti-Muslim prejudice is no secret — he has repeatedly confirmed it, including just last week on Twitter," Omar Jadwat, director of the ACLU's Immigrants' Rights Project, said in a statement. "It's unfortunate that the full ban can move forward for now, but this order does not address the merits of our claims. We continue to stand for freedom, equality, and for those who are unfairly being separated from their loved ones. We will be arguing Friday in the Fourth Circuit that the ban should"…
Keep Reading More Here: Supreme Court permits full enforcement of Trump travel ban.
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text:
Area Code 503 in Oregon - OR
The 503 Area Code (or Area Code 503) is located in the state of OR. Area Code 503 is one of the 269 3-digit telephone area codes in the USA. It covers roughly 2.43 million unique phone numbers and 8.07 million individuals near the city of Portland
Area code 503 was put into service. In 1995 area code 503 was split to form area code 541. In 2000 area code 503 was partially overlaid with area code 971 and in 2008 the overlay was extended to all of area code 503.
State: Oregon - OR
Major City: Portland
Land area: 98,381 sq mi (254,806 km2)
Oregon - OR, The average home value is $2.45M.
Oregon - OR, The average resident's age is 58 y/o.
Oregon - OR, Income average is $41K.
Latitude: 42° N to 46° 18′ N Longitude: 116° 28′ W to 124° 38′ W
Time zone in Area Code 201: Pacific 18:08:26.
Major Cities in Area Code 503: Beaverton, OR>Gresham, OR>Hillsboro, OR>Keizer, OR>Lake Oswego, OR>Mcminnville, OR>Milwaukie, OR>Oregon City, OR>Portland, OR>Salem, OR>Tigard, OR>Tualatin, OR>West Linn, OR>Woodburn, OR


My husband and I moved from NYC to Portland, Oregon Nov. 11, 2005. John used to brew beer in our kitchen back east and living here in Portland reminded me of those days. According to the The Brewers Association of America, craft beer had a 17.8% increase in supermarket sales for 2006–more growth than any other alcohol beverage category in the supermarket sales channel. Portland has more than 28 microbreweries within its city limits which is more than any other city in the world. There seems to be a brewery or a pub on every corner. Beer is worshipped here, and in fact, it seems to create a subculture of "hopheads" in the know. It has a magical power over this town and it captured me in its web as well. I am not much of a beer drinker, more of a wine and vodka person. But through getting to know the founders and brewmasters behind these Portland breweries I began a love affair with the whole process as well as the product they created.
I wanted to understand the type of person behind a brewery and I wanted to know what it takes to stay on top, or at least, in the running. I interviewed a dozen founders/ceo's/brewmasters. I sat down with each of them, face to face for about an hour and asked a series of questions I felt were pertinent to their industry and to their involvement in it. I interviewed Kurt Widmer, one of the founders of Widmer Brothers Brewing, Brian McMenamin of the Mcmenamins chain, the founder of hair of the Dog, Alan Sprints, also John Balfe and Scott Barnum, the CEO of Pyramid Breweries and Mactarnahan, Karl Ockert, the Brewmaster and founder of Bridgeport Brewing, Ron Gansberg the founder of the Racoon Lodge and Mike De Kalb the founder and owner of the Laurelwood Brewing Co. and a few others. I have found them to be incredibly intelligent, kind, humble and witty. It is exhilarating talking to people who truly love what they do. Here are some of the photos I took and a few of the interviews.
at the Market St. Pub downtown Portland.
What direction do you think the Beer Craft industry is going?
"Lately it seems like it's growing again at a pretty good rate. It was flat for a while there and it had been growing in double digits for a long time. In the beginning days, in 1985, the city had 3 or 4 breweries now I don't even know how many there are. I think every pub should have a brewery if they could. We are seeing the industry mature a lot. The bigger guys are getting bought out and merging but I think there is still plenty of opportunity for the little guy to make this niche.
Do people approach you asking advice on how to do it?
"We get tons of phone calls, which is great but there is not enough time to sit down with every one of them, although you want to, you can't do that. You don't have a chance to retrospect very often because you're doing stuff all the time. This gives you a chance to think about what and why you're doing something.
I think it's healthy to combine brewing and the pub atmosphere, you create your own atmosphere. We make our own wine too, we grow a lot of our own herbs for the kitchens. We also grow hops just for fun not for real usage.
What do you think is the style trend for American micro breweries?
"Northwest that like hoppy beer but then in general the mass produced beer has appeal to a lot of people. As a small guy we have the opportunity to do all kinds of beers.
We have 23 breweries, one for each two pubs, more or less, different water sources, different age of hops, each brewer tinkers a little bit with the grain, they each like their own signatures on it. So the beers are all a little bit different in each one of the breweries.
Budweiser would shriek at that because they want their beers to taste the same the world over. If people don't like a beer we'll brew another one. We are also marketing to a general public but more in our own town, and they can drink any beer they like there, not just ours. Our beer is always associated with food. We are more restaurants than pubs now. Our food sales used to be 25% or 30% and now they are 65%.
How do the American craft brewers techniques compare to those of Europe?
"I think the basics are there. People thought we were nutty to have a fruit beer, our Ruby was the first one in Oregon but they've been doing it in Europe for a long time.
Do you see a big difference in beer styles in Europe as opposed to the United States?
Would you open a pub in Europe?
"We're kind of homebodies. We do everything ourselves. We don't have a team that goes out and opens new places. Our furtherest outpost I probably 3 hours from ground zero. It is hard to manage place the farther out it is.
"Have you thought about opening more restaurants in the Portland area?
"Yes, we're always looking. We just opened one on Killingsworth, the Chapel.
What do you think it takes to stay successful?
"We have at times barely survived, and even now we have places that don't make money, places that have never made money. But we have enough places that make money so it balances out. We make enough to keep going which is good. If someone starts this business the first two questions are 'how much money do you have and then, have you ever worked in the industry'? We get a lot of calls from people that have no experience with either brewing or kitchens who want to do what we do and we say, quit your job and go work in a brewpub for a year. They have to have enough money to open it and to float it.
What was your beginning like?
"We had a rough start, our dad helped us out. My brother owned a restaurant and I managed it when I was 21. Then we got into business together and opened a place. We got out of school, we were seven years apart, we were dumb, neither of us had any business experience. We bounced around a lot. We tried to figure out things for ourselves, the school of hard rocks. We survived that time, we are still learning every day. We were political science majors. I was thinking about going into law school. I never really knew him when we were little kids, we were far apart in age. We became best friend when we got older and we would want to go to that pub together, just because it sounded cool. We loved beer and we would drive all over the planet to try different beers. In 1978 or 79 there were only 15 beers available on tap in Oregon, total. We'd go to Washington state and sample different beers, it was fun. Mike opened a wholesaler caus he was really interested in importing beers and making that work. It was not successful, he was ahead of his time. He then got back in the pub business, where we are now. We were buying old dairy tanks and doing whatever we could just to make beer. Our first brewery was put together for just a few thousand bucks. It was a bunch of old stuff, whatever we could find. Our brewery was one step above making soup on the stove. It was just a bigger kettle. It was 'that tastes good, or that tastes bad, we have to throw that away'. We had successful pubs before we started brewing. The brewing was just a side note in 1985, when we started it.
"IPA, I like hops. Europe is very malt oriented, lesser hops. This is the beer I grew up on. The first Pyramid ale was great, filled with hops.
What is your opinion on going green?
Why do you think that there are so many breweries here in Portland?
"We have good hops close by, good grain, great water. The weather, brings more people in to drink beer. So there is the demand. The spirit up here is a bit more experimental, big companies do test marketing here.
Do you have a worthy competitor in the Oregon region?
Do you spend a lot of money on marketing your products?
"We didn't know marketing from a hole in the ground. For the pubs that was great. Then we started getting bigger properties, hotels, now we have a marketing department, although I am still afraid of it (laughs). Word of mouth has always been our kind of deal. We do a lot of marketing now, mostly for the big properties.
You have so many properties to manage, what is a typical day like for you?
"It's gotten a little crazier in the last couple of years. I don't know why. We are pretty hands on and we just opened 3 pubs in like 6 months, which is crazy. Now we just have a bunch of remodel projects. We do them ourselves. There are so many projects, just internally. A typical day is a lot of driving. Today I was in Eugene, then I stopped in Salem and then Portland. Tomorrow I have to go to the office, in Portland. Friday I am up in Seattle and Olympia.
I read that you have a $70 million empire. Is this close?
Why do you think there is the grass-roots spirit here? You grew up here and why do you think it's here?
What qualities do the McMenamin brothers possess that make you unique in this environment?
"We survived! I grew up a pretty introverted kid and had trouble in speech classes. I did learn, eventually how to communicate.