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WASHINGTON– The Commission on Security and Cooperation in Europe (U.S. Helsinki Commission) today received the Torch of Liberty award from NCSJ, the organization advocating for Jews in the former Soviet Union. The honor marks the first time NCSJ has bestowed the award on an organization rather than an individual for work improving and protecting the lives of Jews in Russia, Ukraine and the Baltic states.
Prior to the fall of the Soviet Union, and since, the Helsinki Commission has closely watched the plight of Jewish communities, helping to protect them from repressive policies carried over from the Soviet era. To this day the Helsinki Commission continues to monitor developments affecting minority groups throughout Europe and advocates on their behalf.
"Between 1976 and the late-1980s, much of the Commission's work focused on dissidents and the plight of Soviet Jews," said Commission Co-Chair Congressman Alcee L. Hastings (D-FL) in accepting the award on the Commission's behalf. "We struggled together to aid many thousands of persecuted refuseniks who had been stranded in a form of limbo – unable to function productively at home but denied the right to seek their happiness elsewhere."
In announcing the award today, NCSJ chairman Richard Stone said, "As one of the organizations that supported the creation of the U.S. Helsinki Commission, NCSJ is proud to present this award to the Commission in recognition of its distinguished service and leadership in the advocacy movement to preserve, protect and defend Jewish life in the former Soviet Union."
"The tireless work the Helsinki Commission undertook on behalf of thousands in the Soviet Union whose voices and freedom were denied ultimately paid off," said Commission Chairman Senator Benjamin L. Cardin (D-MD). "I'm convinced that the persistent drumbeat of the combined efforts of the Helsinki Commission, NCSJ, and others will continue to bring about changes still needed in our world."
Past recipients of the Torch of Liberty award include House Majority Leader Steny Hoyer and former Senator Gordon Smith, both of whom have served on the Helsinki Commission.


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text: This article has been automatically clipped from the The Eagle County Blade January 13, 1910, organised into a single column, then optimised for display on your computer screen. As a result, it may not look exactly as it did on the original page. The article can be seen in its original form in the page view.


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Oh, but it gets better:
One with the wrong label, of course:
Come to think of it, Jonathan H., Booklet, Suzanne M., Megan T., & Anony M., the French probably won't be too pleased, either. ;)
- Related Wreckage: It Sends a Message, Alright
When professional cakes go horribly, hilariously wrong.
wow... That last one is hilarious. Bad enough Irish hate being associated with Italians up here in Brooklyn, I hope for that baker's sake, they don't operate in NY. guess it could have been worse. Could have been a Union Jack. >_>
Yup, as someone who's quite proud to be Irish, I'm quite pissed! THAT'S NOT AN IRISH FLAG!
Minimalism at its worst!
Groom. Who would've known?
Irish Flag... geeze
I kind of like the Groom cake. So understated.
Irish flag.
I love Cake Wrecks, Jen!
Miss Vintage Vixen
The color in the photo of the "Irish flag" might be off... could well be green/white/orange
It's too bad about the football cake - it otherwise would have been a non-wreck!
If you think the Irish are going to be pissed, imagine how the French will feel.
I love the random capitalization in the baby shower cake. Baby is good, and so is for, but who would have a small b followed by capital OY? And why would the same person who did that have capital S, lower case h and o, then HALF of the W is capital and half is lower case, with the ending of the word capital? It just blows the mind.
Of course nothing says groom like the word groom in semi-fancy capital letters, written in purple in 12 point font on a sheet cake that can only be described as a sea of brown. At least the brown looks like frosting, unlike some of the other brown cakes... (I said sheet cake, S-H-E-E-T!)
The only thing that would be better with the football cake would be if it said "49 in a star" and was on a square cake.
Wedding cooking? What more is there to say?
And I love the "Irish" flag. Too bad the word Irish wasn't in quotes.
Today's wrecks are all shouting out "I want Sprinkles"!!!
Blog Comment
That is SOOOO funny!
End of blog comment
My husband saw the "Groom" cake and was indignant that it wasn't even an option at our wedding.
Yep, that's a foalball, all right, if I ever saw one.
WV: moime--said by Miss Piggy as she comes to terms with the fact that she is not a native French speaker.
Waht do you mean that's not the Irish flag *smirk*
Wow, these are just AWESOME, Jen. Thanks for making my bad morning much better.
I love that the Wilton letter press set was used for the groom cake! I guess they didn't want to run the risk of "ruining" it with sloppy handwriting LOL
The "Groom" cake could actually be a mandate from the bride's, um, Godfather. As in, "You're gonna shower and get a haircut and not embarrass us at this 'family' event, aren't you, Mickey? 'Cuz otherwise, Uncle Vito's gonna take care of you."
WV: psychu-- It's Friday the 13th, and I need a day off already.
That flag cake says "Irish I was a French flag". LOL.
It's not a "foalball", it's a "foolball."
Don't read Cake Wrecks when bossman is walking by. The snickering, red face and eye tearing is unprofessional for a receptionist!
Ah, well. The French client would gave probably washed that cake down with wine, anyway. :-)
Go Irish!
Haha, Oh, SNAP on that last one!
To me the "Irish" cake looked black, yellow, and red, which would actually be the Belgian flag. But, the lighting could just be really off too.
Word verification: hillappi
These cakes are hillappious!
I guess French is the new Irish...?
How long does one cook a wedding, and at what temperature?
WV: rearan. Spelling errors keep rearan their ugly heads on Cake Wrecks!
The baby cake looks like it's for comebody who's expecting quadruplets. But, on the other hand, it says "bOY," not "bOYs."
Could these maybe be samples to display at the bakery rather than cakes people ordered?
Of course, that wouldn't explain the "Irish" flag. Or who would want to buy a "foalball shape cake" (or is that "foolball shape cake"?).
The "groom" cake seems like a real time-saver. In fact, county clerk's offices could save a lot of work if they just pre-printed marriage licenses with "Bride" and "Groom," and skipped filling in the individual names. Especially since then people wouldn't need to get a new license for second or third marriages.
I don't think it's a foalball or a football. I think it's a foul ball because it's not even the right COLOR! who ever heard of a white football? and foalball makes me think of pony poop. and again, it's not brown!
Maybe the "Groom" cake is someone trying to give a hint to someone with less than ideal personal hygiene?
If my stepmom had seen that first cake, she would've ordered one for our baby shower. We wouldn't tell her the name we'd picked out before our son was born, and wow, was she MAD!
WV: sibbs--Still won't tell when his sibbs come along!
Are you trying to say that the Irish have tempers? Well, are you!!?
I'm waiting for the cake that says "cake" - I admire haonesty.
WV: dizentme "'Zat you?" "Nope, dinzentme!" (2 bee red allowed)
The last cake was the best.
Although, the labeling was good too. LOL
~Amy B-H
Man, nobody wins with that last cake, do they?
Coincidentally the Irish are playing the French is some match (probably soccer) soon. Guess this way the bakeries don't have to pick sides, whoever wins, the cake will be sold :P
Or thats what they like to think
Does anyone know when the Foalball world cup will be? I'm really rooting for the Omaha Bambis.
Ha ha
Viva La Ireland!
Does this mean that the cake maker is going to surrender?
Well at least it wasn't the Union Jack. The Irish would really be made then.
Maybe its just a weird picture quality, but the "groom" cake looks photo-shopped. The part where each of the letters meet the cake is a little bit pixelated and looks unnatural. I know this is a mom and pop operation, but perhaps you guys should look into getting some photo authenticating software?
A big part of what makes these cakes funny is reading or imagining the back story. That's tainted by running across the occasional obvious photo shop because it makes me wonder if some other cakes are just better photoshops.
Perhaps my laptop isn't rendering the colours as they should, but to me, that "Irish" flag doesn't look even remotely French. It's "Black - Yellow - Red" which is the BELGIAN flag, which I would know, being Belgian.
(BTW, I never admitted to that, as they said when King Boudewijn wasn't dead yet: "There are only two real Belgian, and they can't make a third.")
Perhaps it would be beneficial to click on the picture so you can view it actual size before claiming that it is an "obvious photo shop." And while we're on the subject, who in their right mind would photoshop a cake?
Ah well. This particular cake was photographed during a wedding by a legitimate wedding photographer. He was actually called into the back room by an employee who was too ashamed to bring the cake out to the reception. The employee wanted a record of the cake before it was cut up in the back room and served to the guests.
We spend way too much time verifying these things before they ever make it onto Cake Wrecks.
I want that "Irish" cake to leave on the front porch for my neighbour to find. Once he's calmed down, he'll eat it anyway, if I'm any judge of character. Just better not let him see me with it...
ooh-la-la! What a barrage of cluelessness today! Not only to do the Irish flag wrong, but then to label it? do you think they realized they screwed up and tried to "fix" it? boy does that look stupid written down on the bottom like that. mais oui! maybe the guests were too drunk to notice the colors were off. hey, it's got stripes, right? pour them a pint and they'll be fine! (the French, however, might be cheesed... ;P )
and wedding cooking? who orders a cookie for a wedding? there should have been a question mark after cooking. like "you seriously wanted to order a cookie for you wedding?" (although "wedding baking?" might have been more appropriate.) wedding cooking? is making me think of hot dogs riding poo waves.
and Mike--maybe the maybe was a large Jewish boy? hard delivery perhaps? Oy! Arguably though, the only lower case letter is "b". The rest are maybe just small capitals my a minimally skilled icing piper who can't seem to make letters of uniform size.
and "s-h-e-e-t cake!" you're funny! seriously, minimalism aside (what, NO decoration?) purple and brown just don't seem to harmonize on cake, do they?
"Coincidentally the Irish are playing the French is some match (probably soccer) soon."
What we in Europe know as "Real Football" as opposed to that strange game involving a lot of prima donnas in padding.
And it doesn't come much more real than France playing the ROI.
That said, the French probably wouldn't mind being associated with the Irish because they are dreadfully fond of them and have historically come to the aid of the Irish in their struggles against the wicked English.
And the Americans against the wicked English.
In fact, pretty much anyone against the wicked English.
There's a pattern emerging there.
It could have been worse, you know.
Good thinking, Tara! Very somber suggestion on the serious chocolate desert. or dessert. with no-flower minimalism, it could go either way. Maybe it would be a good "breakup" cake--as if hygiene were the reason for the split.
@anon 11:41, that's a great back story! hmm...either a peeved m-i-l who didn't know the name, or a clueless coworker who just ordered a cake in a jiffy. name? who cares? let's have cake and open presents!
and Taggie, zoom in on the cake. you'll see the writing better, and the unevenness of the letters. plus, it's a perfect match for the purple perimeter dots.
As someone said it is a strange coincidence that this "Irish Flag" shows up just in time for "the soccer game of the year"(there is one nearly every Saturday here...).
As long as it's not the English the French wouldn't probably mind much about this wreck!
I take the opportunity to thank you for your blog,it's a real treat to read it every day!
so, Jon in France, what's your take on that foul ball? is it a hybrid between an American football and European football (soccer)? It's just the wrong color for American, but the right shape with the train tracks/stitches down the center. but then it's white. With a star. not that it resembles a soccer ball much either.
Either this decorator ran out of chocolate icing (perish the thought!) or is sports clueless. maybe the same baker of the baseball X?
OMG, I am laughing so hard right now! These are pathetically hilarious!
Wreck on!
Jen, you should be proud. The French (kings of pastry!) are fans of your blog. Of course, it IS a blog about wrecked cakes *blush on behalf of the US* but a source of endless amusement! Mes amis, bon jour!
I just started watching Clean House, and I'm addicted! I have about 20 episodes on my DVR. Whatever happened to that other show, Clean Sweep?
These are so funny!
Come visit me at http://festiveflops.blogspot.com/
for some really bad decorating! I am desperate for more photos!
I read that sports cake as "Foolball Cake"....which may be more appropriate, all things considered.
I especially love the bits of crumbs (and let's hope that's what they are) around the word on the GROOM cake. Nice touch. Oi.
Is it wrong that I'm starting to want someone to make me a cake that says, "TEH STOOOOPID, IT BURNNZZ!"?
Exactly like that, I mean every word as typed.
I just don't get it. If you are intelligent enough to make a great little football cake, what happens when it's time to write an inscription? I really want to know! It's clear that this decorator isn't stupid! How does it happen?
Oh yes, this Frenchie is highly offended by that last one... OK, I couldn't even type that with a straight face. :P
Oh, I finally got the book today and it was (pardon the pun) the icing on the cake to an already good day. :)
What are the random nuggets on the Groom cake...Yech!
The French flag/Irish cake - maybe it was Irish coffee/whiskey flavored? *snort*
I'm sorry. Looking at it again, it looks like the pixelation I noticed earlier could occurred when the picture was being converted to jpeg format. Overly compressed jpeg pictures can get weird distortions in them.
Fish cake, it says fish cake. Fish don't respect any single nationality, it's all good.
I honestly think this is the funniest post, ever, on this blog. And that is saying a lot!
Um, that was supposed to be "fish flag." Apparently fish do have their own nation and it has a confusing flag.
Truly! These are too stupid to be real. I agree with some of the other comments: How can someone smart & talented enough to create these cakes be so far off base? http://blog.sweetservices.com/sweetscandyblog/
At least the football-shaped cake was shaped like a football. That put it ahead of some of the other football cakes we've seen.
snicker! very funny!
Yes, I am baker.
Piped it myself on my chest.
That way I am sure.
what's with the random icing partial outline on the wedding cooking cookie? (head tilt) huh
I love the fact the cake was football shaped, looked like a football (somewhat) and they still felt the need to label it.
Maybe the baby's name was "Aboy"? With the weird names parents are picking for their offspring nowadays, who really knows...
'Course, it'd still be misspelled with the odd spacing, but at least it'd be less vague.
That "Groom" cake totally reminds me of the "Winter" cake.
Wasn't the Irish tricolor given to them by the French?
Maybe the Groom cake is a last name? ... At least it's MY last name. course even if it was, that still makes for a dull cake.
taggie2b: it's the dramatic color change from brown to purple that makes the JPEG artifacts (aka fuzzies) show up so clearly. In most pictures of this compression level, you would not really notice, because the colors blend much more smoothly.
(Lesson here: don't use purple and brown together. ever.)
-- abadidea
About the Irish flag with French colors... The French won the match! We'll see who wins this Wednesday... Pretty funny that it appeared before the match and it ended up "coincidentally" being the winning team!!
I watched the game, by the way. That is some premonition! Jen and John, where is the cake from? Do you have some background or story on it?
On the last cake: heck knows what Howard Goodall and Rowan Atkinson would make of that! (They wrote a song named, "I Hate the French," sung by Goodall.)
That "Groom" cake reminds me of the cake with the snowman that just said "Winter".
That French/Irish cake is especially poignant after this week's football match - and the infamous "Hand of Frog" incident.
Perhaps the decorator was a psychic, who was foretelling how France will steal something that belongs to Ireland, through the medium of cake decoration.
Lyk omg, foalball shape cakes! I luuuuuvvv those! XD
Le bleu, blanc et rouge POUR LA GAGNEE
(The blue, white and red ftw)
-twirls mustache-
-eats baguette-
My brain just exploded with the hilarity of the last cake.
P.S. My cerebrum too!
I am thoroughly enjoying your website and slowly working my way back in time through it. Some of the wrecks are hilarious while others should be classified as artwork. I couldn't help but notice that you enjoy making sport of others. This indicates that possibly you feel a teensy weens bit superior (he said with tongue in cheek). However, be advised that on the post for Sunday Sweets: Tour De Force, Pt 3, Sunday, November 15, 2009 you committed a major grammatical faux pas. At the end of the post, you wrote, "Thanks again to all of the bakers who gave their time and effort during our tour! I'm sure I speak for the thousands of people who got sugar buzzes thanks to your efforts when I say, Your the 'Best!'" Yikes! Please note that "Your the Best" is not a good thing. I found this website that may help explain things. http://www.copyblogger.com/5-common-mistakes-that-make-you-look-dumb/. Thank-you for listening. Happy Cake Crumbs Day to you. *Note Here* The author of the above missive is not a member of the Grammar Police and has no afiliation to the website mentioned. Mike
Hey Mike,
It was a joke. See, what we did their was insert bad grammer and punctuasion as a nod two what we do every day. I think moist people got it.
Thanks thouh!
Barnes & Noble
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A Cake Wreck is any cake that is unintentionally sad, silly, creepy, inappropriate - you name it. A Wreck is not necessarily a poorly-made cake; it's simply one I find funny, for any of a number of reasons. Anyone who has ever smeared frosting on a baked good has made a Wreck at one time or another, so I'm not here to vilify decorators: Cake Wrecks is just about finding the funny in unexpected, sugar-filled places.
Now, don't you have a photo you want to send me? ;)
We don't have any copies of Cake Wrecks for sale here, autographed or otherwise. We decided the shipping and handling costs would be too high to make it worth your while. So instead, buy your copies locally or online and then order personalized bookplates: it's cheaper, easier, and I think even looks a bit nicer.
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text:
Louisville beats Michigan 82-76 for NCAA title
Published 11:34 pm Monday, April 8, 2013
ATLANTA — Rick Pitino capped the greatest week of his life with the prize he wanted most of all.
Luke Hancock produced another huge game off the bench, scoring 22 points, and Pitino became the first coach to win national titles at two schools when relentless Louisville rallied from another 12-point deficit to beat Michigan 82-76 in the NCAA championship game Monday night.
This title came on the same day Pitino was announced as a member of the latest Hall of Fame class, a couple of days after his horse won a big race on the way to the Kentucky Derby, and a few more days after his son got the head coaching job at Minnesota.
This was the best feeling of all. The Cardinals (35-5) lived up to their billing as the top overall seed in the tournament, though they sure had to work for it.
Louisville trailed Wichita State by a dozen in the second half of the national semifinals, before rallying for a 72-68 victory. This time, they fell behind by 12 in the first half, though a stunning spurt at the end of the period wiped out the entire deficit.
"I had the 13 toughest guys I've ever coached," said Pitino, who plans to follow through on a promise he made to his players if they won the title — by getting a tattoo.
No one was tougher than Hancock, named the most outstanding player. He came off the bench to hit four straight 3-pointers after Michigan got a boost from an even more unlikely player.
Freshman Spike Albrecht made four straight from beyond the arc, too, blowing by his career high before the break with 17 points. Coming in, Albrecht was averaging 1.8 points a game and had not scored more than seven all season.
While Albrecht didn't do much in the second half, Hancock finished what he started for Louisville. He buried another 3 from the corner with 3:20 remaining to give the Cardinals their biggest lead, 76-66. Michigan wouldn't go away, but Hancock wrapped it up by making two free throws with 29 seconds left.
While Pitino shrugged off any attempt to make this about him, there was no doubt the Cardinals wanted to win a national title for someone else — injured guard Kevin Ware.
Watching again from his seat at the end of the Louisville bench, his injured right led propped up on a chair, Ware smiled and slapped hands with his teammates as they celebrated in the closing seconds, the victory coming just 30 miles from where he played his high school ball.
Any pain he was feeling from that gruesome injury in the regional final, when he landed awkwardly, snapped his leg and was left writhing on the floor with the bone sticking through the skin, was long gone as he hobbled gingerly onto the court with the aid of crutches, backing in a sea of confetti and streamers.
Louisville again came out wearing Ware's No. 5 on the back of their warmup jerseys, which said "Ri5e to the Occasion" on the front. When the title belonged to the Cardinals, Ware put on a championship cap and got a big hug from Pitino. Then, they lowered the basket so the injured player could cut a strand out of the net.
This one belonged to him as much as anyone on the court.
"These are my brothers," Ware said. "They got the job done. I'm so proud of them, so proud of them."
Peyton Siva added 18 points for the Cardinals, who closed the season on a 16-game winning streak, and Chane Behanan chipped in with 15 points and 12 rebounds as Louisville slowly but surely closed out the Wolverines (31-8).
Michigan was in the title game for the first time since the Fab Five lost the second of two straight championship games in 1993. Players from that team, including Chris Webber, cheered on the latest group of young stars.
But, like the Fab Five, national player of the year Trey Burke and a squad with three freshman starters came up short in the last game of the season.
The first half might've been the most entertaining 20 minutes of the entire tournament.
Burke started out on fire for Michigan, hitting his first three shots and scoring seven points to match his output from the semifinal victory over Syracuse, when he made only 1-of-8 shots.
Then, when Burke picked up his second foul and had to go to the bench for the rest of the half, Albrecht took control. The kid whose nickname comes from his first pair of baseball spikes showed he's a pretty good hoops player, knocking down one 3-pointer after another to send the Wolverines to a double-digit lead.
When Albrecht blew by Tim Henderson with a brilliant hesitation move, Michigan led 33-21 and Louisville was forced to call timeout. The freshman was mobbed on the Michigan bench, like the Wolverines had already won the national title, with one teammate waving a towel in tribute.
Not so fast. Not against Louisville.
The Cardinals kept coming back.
"We just went into war right there with a great Michigan team," Hancock said. "We needed a rally and we've been doing it for a couple of games straight, being down. We just had to wait and make our run."
Burke, who played only six minutes in the first half because of foul trouble, finished with 24 points and did his best to give Michigan its first championship since 1989. But he couldn't do it alone. Albrecht was held scoreless after the break, and no one else posted more than 12 points for the Wolverines.
Still, it was quite a run for a fourth-seeded team that knocked off No. 1-seeded Kansas with the greatest comeback of the tournament, rallying from 14 points down in the second half to beat the Jayhawks in the round of the 16.
But they came up against the ultimate comeback team in the final.
"I've had a lot of really good teams over the years, and some emotional locker rooms, and that was the most emotional we've ever had," Michigan coach John Beilein said. "The team unity we had, the sacrifice we had from five seniors who did not get to play very much, to these young guys buying into the team concept.
"We feel bad about it. There are some things we could have done better and get a win, but at the same time, Louisville is a terrific basketball team. We have not seen that quickness anywhere."
Louisville had already pulling off a stunning rally in the Big East championship game — down by 16 in the second half, they won by 17 — and another against Wichita State. They surged back again behind their own ace off the bench.
Hancock matched Albrecht from the 3-point stripe. Then, trapping the youngster and knocking the ball away, he set up a fast break that ended with Siva flipping up a lob that Montrezl Harrell slammed through for a dunk, capping a stunning 16-3 run in less than 4 minutes that gave the Cardinals their first lead of the night, 37-36.
Glenn Robinson III made two free throws with two seconds left to give Michigan a 38-37 lead at halftime.
But everyone knew this game was just getting started.
And when it was done, Pitino, Ware and the Cardinals were celebrating in the middle of the mammoth Georgia Dome, assuring the national title will stay in the bluegrass another year.
Last season, it was Kentucky winning it all, the same team that gave Pitino his first title in 1996.
Now, he's got another one — right down the road in Louisville.


text:
And a macaron mouse pad?
And Macarons on a greeting card..? What do you think? Hot chocolate?I'll take tea at the Paris Ritz* on a note card or a stamp.A bouquet from Aquarelle?Never mind. I'll have a Marie-Antoinette rose on a mug please.Quite a few of you have asked for ParisBreakfast notecards and prints and whatnot..
Enfin you can drink your coffee out of a ParisBreakfast cup!
Much more stuff is coming - like Angelina etc I promise.
Please visit my brand new ZAZZLE*
And excuse my birthday suit..I'm still new at this.


text:
Shipping Policy
Thank you for visiting and shopping at Rudi's Gourmet Imports.
Following are the terms and conditions that constitute our Shipping Policy.
All orders are processed within 1-3 business days. Orders are not shipped or delivered on weekends or holidays.
If we are experiencing a high volume of orders, shipments may be delayed by a few days. Please allow additional days in transit for delivery. If there will be a significant delay in shipment of your order, we will contact you via email or telephone.
PLEASE NOTE: Once your product has shipped, Rudi's Gourmet Imports is not responsible for lost or stolen packages.


text:
Hm. Let's see...
Oh! I know. How about this:
Think of a place. A happy place.
A place where chocolate-dipped demon mummies can never, ever reach you - much less wrap you in their fudgy arms and squeeze the life-breath out of you.
Are you imagining that happy place? Are you there?
Ok, good.
You may now proceed.
Forty six pounds of cake, to be precise, and fifty five pounds of chocolate ganache. It's a testament to the baker's skill that I could never get within arm's reach of this thing, for fear of it suddenly coming to life like in Night at the Museum.
Still, you've got to appreciate the humor of where they chose to start cutting:
Thanks to Wreckporter Jessica Y., who featured it here in her article for Orlando Weekly, and also to Paul J., the baker/sculptor, who's been an awfully good sport about all this.
In fact, you can check out progress shots of Paul sculpting the demon mummy (warning: a live model was used, & she's nekkid!) at his FB album here.


text:
SEOUL, South Korea — North Korea fired four suspected short-range missiles into its eastern waters Thursday, South Korean defense officials said, in an apparent effort to protest ongoing U.S.-South Korean military exercises that Pyongyang calls a rehearsal for invasion.
The launches, however, weren't expected to raise tension as North Korean routinely tests short-range missiles and it has recently sought better ties with South Korea in what outside analysts say is an attempt to win badly-needed foreign investment and aid. The rival Koreas this month held their first reunions of Korean War-divided families in more than three years.
The projectiles that landed off the North's eastern coast were believed to be short-range missiles with a range of more than 200 kilometers (about 125 miles). The South Korean Defense Ministry officials who discussed the launches spoke anonymously, citing ministry rules.
The officials said they were trying to learn exactly what North Korea launched and that South Korea has bolstered its monitoring on North Korea.
Yonhap news agency, citing an unidentified military official, reported the North Korean projectiles were suspected to be ballistic Scud missiles or an upgraded version of its newly developed surface-to-ship KN-02 missiles.
In Washington, State Department spokeswoman Jen Psaki said the U.S. was closely monitoring the situation and urged North Korea to exercise restraint and take steps to improve relations with its neighbors.
Kim Yong-hyun, a professor of North Korea studies at Seoul's Dongguk University, said the launches won't be a prelude to provocation. He said the North appears to have intended to protest the South Korean-U.S. military drills that began Monday or to grab international attention as there has been little progress over a push to resume disarmament-for-aid negotiations.
Yang Moo-jin, a professor at the University of North Korean Studies in Seoul, said the North also carried out such launches to examine its weapons.
Last year, North Korea furiously reacted to the same South Korean-U.S. military drills by issuing a torrent of fiery rhetoric and threats to launch nuclear missiles against Seoul and Washington. Last year's drills came after North Korea conducted its third nuclear test. The U.S. took the unusual step of sending nuclear-capable bombers in a show of its resolve to protect its ally.
North Korea hasn't issued any harsh rhetoric against the current drills after their start. Seoul and Washington have said the annual drills are defensive in nature.
Pyongyang earlier threatened to scrap the arrangement for the family reunions in anger over the drills but later allowed them to proceed after high-level talks with Seoul. South Korea on Monday offered sending vaccines and disinfectants to North Korea after the country recently reported its first outbreak of foot-and-mouth disease since January 2012.
Earlier Thursday, North Korea presented to the media a South Korean missionary who it says was arrested last year for allegedly trying to establish underground Christian churches in the country. South Korea urged North Korea to quickly release him.
The Korean Peninsula officially remains at war because the 1950-53 Korean War ended with an armistice, not a peace treaty. About 28,500 American troops are stationed in South Korea to deter potential aggression from North Korea.
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text: This collection of newspaper clippings, announcements of gallery shows, obituaries, magazine articles or exhibit catalogs features artists and architects who have lived or worked in the San Francisco Bay Area. Information dates from the late 1960s to the present; each folder varies in depth and scope. The entries may include citations to scrapbooks created by the Library, magazine articles or books. Please check the Subject File under Artists for articles about other local artists who may not have an individual file.


text:
Sigrid Adriaenssens and Branko Glišić, assistant professors of civil and environmental engineering at Princeton University, co-taught a course on German thin-shell structures in the fall of 2012 that has resulted in the exhibition "Evolution of German Shells: Efficiency in Form."
This video provides an overview of the undergraduate course and the exhibition that it produced. The exhibition is on display from 9 a.m. to 6 p.m. Monday to Friday through April in the Friend Center Engineering Library.
The course, "A Social and Multi-dimensional Exploration of Structures," included a weeklong field visit to Germany, where students visited landmark shell structures and met with architects and engineers involved in thin-shell construction. Germany was the birthplace of modern shell architecture in the 1920s, and it is where shell engineering is still the most advanced in the 21st century.
"In engineering, students usually don't go on field trips, but in other disciplines like art and architecture, students are encouraged to go and see the works of Monet or Le Corbusier," Adriaenssens said.
Both Adriaenssens and Glišić consider the field trip to have been a cornerstone of the class.
"The idea of this class was really to expose them to all these real-life settings," Glišić said.
Adriaenssens said that another key goal of the Germany trip was to meet with the engineers and architects who designed many of the buildings they visited.
"Actually going to an office and seeing what engineers do in a day was very revealing for our students," she said.
The original shell structures, inspired by forms found in nature such as eggshells, were made of concrete. However, today engineers and architects employ other materials such as wood and plastic or steel and glass.
After their trip, the students created models of the structures they studied using different techniques. Those models now form the exhibition in the Friend Center.
The students also created short documentaries about five different structures: Balz House, Grötzingen Theater, Leipzig Markthalle, Mannheim Multihalle and the Museum of Hamburg History.


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text:
From NPR News, this is ALL THINGS CONSIDERED. I'm Robert Siegel.
And I'm Audie Cornish.
Looming over the recovery from Super Storm Sandy is what to do about next Tuesday's election? The prospect that some voters could still be displaced or without power a week from today has election officials trying to come up with alternative plans.
It even has some people talking about the highly unusual step of delaying the vote, as NPR's Pam Fessler reports.
PAM FESSLER, BYLINE: It's something that a lot of people don't really want to contemplate right now, holding an orderly election in communities where homes, businesses and even lives have been lost, and where just getting through tomorrow is a big enough challenge.
Here's New Jersey's Governor Chris Christie today when asked about his state's plans for next week's vote.
GOVERNOR CHRIS CHRISTIE: I don't give a damn about Election Day. It doesn't matter a lick to me. At the moment, I've got a much bigger fish to fry than that, so do the people of the state of New Jersey.
FESSLER: Although he says his lieutenant governor, who oversees elections, is looking into contingency plans.
Right now, election officials throughout the region are still trying to assess the extent of the damage. In Connecticut, hundreds of local officials will hold a conference call tomorrow morning to decide what should be done to ensure that those in the hardest hit areas of the state can vote.
NED FOLEY: If emergency generators can make polling places open, you know, it might be possible to hold an election even if power hasn't been fully restored in a particular community.
FESSLER: Ned Foley is an election law expert at Ohio State University. He says there are other options too, including using emergency paper ballots that polling sites usually have on hand in case voting machines break down. Or, he says, absentee ballot rules can be loosened for those who have been evacuated to a location that has electricity.
FOLEY: They may be able to download an emergency ballot even if power is not restored back home.
FESSLER: He says almost anything would be preferable to what could be called the response of last resort: postponing the vote for those affected by the storm. It's a remedy fraught with potential problems, says John Fortier, election expert with the Bipartisan Policy Center in Washington.
JOHN FORTIER: It is not a good thing to postpone an election. Obviously if there's a necessity, you can't do it, there has to be some accommodation. But how that accommodation is done is murky territory.
FESSLER: Murky because, while Congress set Election Day as the Tuesday after the first Monday in November, the law leaves some wiggle room for states. But few states have concrete plans on what to do in such a major emergency. Fortier says one potential problem with a delay is having some voters cast ballots after most of the rest of the country has voted, and the outcome of the presidential race may already be known.
FORTIER: You don't want to go down that road unless you absolutely have to.
FESSLER: Not only will it invite legal challenges, it raises questions of fairness. Much better, he says, is to plan for these things in advance. Pam Fessler, NPR News, Washington.
Copyright © 2012 NPR. All rights reserved. Visit our website terms of use and permissions pages at www.npr.org for further information.
NPR transcripts are created on a rush deadline by an NPR contractor. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR's programming is the audio record.


text:
Notice: This Wiki is now read only and edits are no longer possible. Please see: https://gitlab.eclipse.org/eclipsefdn/helpdesk/-/wikis/Wiki-shutdown-plan for the plan.
Sample Projects available for Download
- 1 Sample Projects Available For Download
- 1.1 Importing a Shape File
- 1.2 Several Ebola Scenarios
- 1.3 Ebola Zoonotic Reservoir Model
- 1.4 Four Different Dengue Fever Scenarios
- 1.5 Avian Influenza (e.g. H7N9) Scenario
- 1.6 Malaria Population Replay Demonstration
- 1.7 Food borne disease
- 1.8 Migratory Birds Demonstration
- 1.9 Evacuation Demonstration
- 1.10 (Asia) Mosquito Density Model
- 1.11 Automated Experiment Example
- 1.12 Multi-Population Example
- 1.13 Multi-Population Pajek Graph Example
- 1.14 Square Lattice Example
- 1.15 Mexico/USA H1N1 Scenario
- 1.16 Global Earth Science Models
- 1.17 Global Geographic Models Only
- 1.18 Super-Continent Examples
- 1.19 Chicken Pox
Sample Projects Available For Download
The STEM home page contains several example projects users can import and run with STEM. These projects are intended to help users learn how scenarios are constructed and how to create their own. The examples demonstrate some, but not all, of the models available in STEM. Please see the documentation on Creating a STEM Scenario for more information on how scenarios are build as well as video tutorials. For users that want to add their own disease models (new disease and new code) please see Creating a new Disease Model Plug-in.
STEM is designed to allow collaboration and sharing of work by simply importing and exporting projects from your workspace. For information on how to import a project, please see: Importing and Exporting Projects
Sample Projects include:
- Ebola Scenarios
- Malaria population replay demonstration
- Food borne disease: Beef production from a cattle population
- Evacuation (Demonstration of Migration Edges)
- Chickenpox: The ChickenPox example scenario shows how to use the new aging (demographic) population model. The initial conditions in this example start the population far from equilibrium.
- Asia Mosquito Density Model Demonstrates how the earth science data can be used to generate seasonal mosquito density estimates in Asia. Requires the Global Geography Models and the Global Earth Science Models.
- Automated Experiment Example Demonstrates the automated experiment feature in STEM and how it is used to fit unknown EPI parameters to a reference incidence data set
- Global Earth Science Models for release 1.2.1 and later Continent-level models of Earth Science Data including elevation, rainfall, temperature, and vegetation coverage. OBSERVE: You need to access the STEM update site and install the "STEM Earth Science Data for 2010" plugin to use these models.
- Global Earth Science Models for STEM release 1.2.0 and earlier Continent-level models of Earth Science Data including elevation, rainfall, temperature, and vegetation coverage.
- Multi-Population Example Demonstrates a simplified multi-population disease model with anopheles mosquitoes and humans
- Pajek Import Example Demonstrates a simplified multi-population disease model where the entire graph is created using the new Pajek Import facility
- Square Lattice Example Demonstrates both population migration and disease spread on a Square Lattice
The Ebola scenarios require the latest STEM Integration build on or after Sept 26, 2014. The malaria replay demonstration requires a build from Mar 16, 2012 or later The evacuation intervention demo requires a build from July 15, 2011 or later The Automated Experiment Example requires a STEM build from Sept 2, 2010 or later The Multi-population Example requires a STEM build from Aug 31, 2010 or later The Square Lattice demo described below requires STEM version dated July 1, 2010 or later The SuperContinentExample project requires GlobalGeography to exist in the STEM workspace before it any of the examples can run
Some of the example projects you can download are very large as they contain continents or even groups of continents. Before you try to run any of these large scenarios you must make sure you allocate enough system memory for STEM. If you don't do this the application may hang or crash with a "Heap Space" error. To allocate enough memory in Windows, create a shortcut for launching STEM. You may place this anywhere (e.g., on your desktop or on the quicklaunch bar).
Right click on the shortcut. Select "Properties" You should see a field in the Properties Dialogue labeled Target: to the right in the text field you will see something like
C:\stem_builds\stem\STEM.exe -vmargs -Xms812M -Xmx812M
To launch STEM with more memory you must add "virtual machine arguments" to the target line. For example, Target:
C:\stem_builds\stem\STEM.exe -vmargs -Xms896M -Xmx896M
Should work for the demo projects available.
On MAC OS X, using the finder, navigate to where the STEM application is located, right click and select "Show Package Content". Navigate to Contents->MacOS and open the STEM.ini file in an editor. Change the -Xms and the -Xmx lines to increase the memory, e.g. -Xms896M -Xmx 896M or more depending on how much memory is available.
Importing a Shape File
You can download the .shp file example here. This example shows how to import geographic regions from a Shapefile and to create migration edges between these regions from a Pajek File. The files are located in the "Shapefile and Pajek" folder of the project. When importing the Shapefile the column "STUSPS" must be used for region IDs, since the Pajek File references these IDs. Please see the documentation on
Working with Graphs
- Composing a Graph
- Creating a Custom Graph (new) seasonal migration
- Visualizing and Editing Graphs with the STEM Graph Editor
- Importing a Graph from a Pajek File
- Importing a Graph from an Esri Shapefile
Several Ebola Scenarios
You can download the ebola models here. This archive contains multiple projects and multiple scenarios for Ebola. The archive also contains the Ebola model itself which can be opened and edited with the STEM model generator. Click on the page Ebola How To for more information on how to install and run the models. For more information on the model itself please see the page Ebola Models
Ebola Zoonotic Reservoir Model
This Downloadable Scenario contains an archive EbolaZoonoticReIntroduction. The archive contains two sub-folders.
EbolaSingleNode and org.eclipse.stem.ebola2
Both of these folders should be extracted and placed directly in your stem workspace. Do NOT put them in a subfolder inside the workspace
org.eclipse.stem.ebola2 contains the metamodel with extensions to the ebola model to support modeling of reintroduction of ebola from a zoonotic reservoir.
EbolaSingleNode is a standards STEM project with a single node scenario. The disease decorator within instantiates the custom org.eclipse.stem.ebola2 ebola model
See: STEM_Model_Creator for information on metamodels and the model generator
Four Different Dengue Fever Scenarios
This folder contains four different scenarios (in four project folders) of dengue disease transmission in order to show behaviors observed from three dengue models with different levels of complexity. Details of each model can be obtained in our JTB paper (Hu. et al, "The effect of antibody-dependent enhancement, cross immunity, and vector population on the dynamics of dengue fever", 2013.) and wiki page on the Dengue Fever Disease Models. Additional information on these downloadable dengue scenarios may be found on the page Downloadable Dengue Scenarios and in the readme.pdf file contained in the download.
To run the scenarios, first download the archive DengueScenarios.zip then extract the archive. You will see four subfolders, DengueVerySimpleModelTest, DengueHostVectorModelDemo, and DengueInAustralia. There are four separate STEM projects you can run. The DengueHostVectorModelDemo contains two scenarios within.
To import the project, run stem and then:
>File>Import>Existing Projects Into Workspace
>Select 'Next'
Make sure the radio button 'Select root directory' is checked (and no the archive button). Then Browse or navigate to the parent folder 'Dengue Scenarios'.
>Select 'Next'
You can then import all three scenarios.
Avian Influenza (e.g. H7N9) Scenario
In response to 2013 China H7N9 outbreak in China we created an Avian Influenza Model and the following downloadable scenario. This scenario shows the possible disease propagation on the map of China seeded in Shanghai, China. The model includes air travel. By tuning the disease parameters, one can study sensitivity of spatial and temporal disease diffusion. In particular the scenario shows how the epidemic would change if direct human-to-human transmission were to occur (in the 2013 epidemic the only human cases came from poultry-to-human transmission.
Stochastic H7N9 simulation with poultry-poultry and poultry-human transmission. Watch on YouTube Poultry-Human Transmission
Stochastic H7N9 simulation including poultry-poultry, poultry-human, and human-human transmission (with air travel). Watch on YouTube Human-Human Transmission
Malaria Population Replay Demonstration
In this demo, we are reading in a time series of Anopheles population data for 71 regions in Thailand and use it to drive a model of Malaria transmission. Seasonal counts of anopheles mosquitos are recorded, as well as counts of births and deaths. You'll notice that the data being read in was recorded earlier using the CSV logger in STEM and that the ExternalDataSourcePopulationModel is configured to read data from the folder containing the run parameter file as well as an XMI serialized version of the decorator generating the data. This gives us the flexibility to replay population data for more exotic kinds with non-tranditional labels. The same rule applies for disease model data read by an ExternalDataSourceDiseaseModel.
If your data files were not generated by STEM, you can still use an ExternalDataSourcePopulationModel and point it directly to the folder containing CSV data files. The folder must contain a file Count_x.csv (where x is the administrative level of the regions recorded in the file, e.g. 2) and use the same format as STEM log files. The folder can optionally contain the files 'Births_x.csv' and 'Deaths_x.csv' to indicate the number of births and deaths of the population in each time step. This information is feed into any disease model using the external data source population model. If births and deaths data is not available, it is assumed that any increase in population is due to births only (zero deaths) and any decrease is due to deaths only (no births). Similarly, if there is a mismatch in the reported birth and deaths compared to the reported total count, the birth and deaths are adjusted to make up for the difference. This can happen for instance if you recorded data from a STEM simulation that had population migration as part of the model.
Food borne disease
African Swine Fever
new! This downloadable scenario contains both spacial and non-spacial African Swine Fever models. Please visit the African Swine Fever for details.
1. Beef Production
The BeefArgentina scenario is a model of beef production and consumption in Argentina using the new SlaughterHouse and FoodConsumer classes. The graph containing the cattle population, cattle transportation and slaughterhouses was created with the Pajek importer. The edges for beef transportation from this graph to the Argentina graph were created with the Graph Editor. Disease transmission from cattle to beef to human is also modeled.
Three of the nodes in the Pajek imported graph shown in the left image contain cattle populations. Cattle are born there and transported to the two nodes that contain slaughterhouses. In these nodes cattle is transformed to beef by using the SlaughterHouse class. The SlaughterHouse also models disease transmission in the transformation process (for example: 90% of infectious cattle transform to infectious beef and 10% to non-infectious beef). Beef is transported from the SlaughterHouse nodes to certain regions in Argentina as shown in the right image. In the Argentina graph beef consumption is modeled using the FoodConsumer class. This class also models disease transmission from beef to humans by consumption.
The downloadable archive contains the Pajek file for the graph.
2. A scenario for modelling the transmission of Salmonella to pigs, pork and humans
Food poisoning is caused in many cases by Salmonella. In this model the spread of Salmonella from farm to fork is demonstrated for the production and consumption of pork in Germany based on findings from the scientific literature. It shows the spread of Salmonella among pigs in a barn, the contamination of pork by infected carcasses in slaughterhouses, and the infection of humans with contaminated pork.
Salmonellosis in pigs
The infection of pigs with Salmonella is modelled with a compartment model (SIR). Soumpasis and Butler (2009) calculated that the transmission parameter β equals 0.165. They reviewed the literature and found that infected pigs stop shedding Salmonella after 16 days (1/γ = 16 -> γ = 0.0625) and that pigs become susceptible to salmonellosis after 42 days (1/𝛼 = 42 days -> 𝛼 = 0.0238).
The scenario is set on a farm for pig fattening with a population of 400 pigs (called "PigFattening") in one barn (300 m2). Thus, there are 0.75 m2 per pig. 1 % of the population (= 4 pigs) was assumed to be infected with Salmonella. A reason for the appearance of Salmonella in pigs on a farm could be that the farmer buys several pigs of which four are already infected, for example. Pigs were fattened for 120 days. The model calculated 16 % of the pigs to be infected with salmonellosis. According to Methner et al. (2011), 13.8 % of 1830 fattening pigs were infected with Salmonella, meaning that the result of the model parameters published by Soumpasis and Butler (2009) is alright for an approximation.
Transport of pigs to slaughterhouses and contamination of pork with Salmonella
Pigs were transported to one slaughterhouse in Hamburg and Braunschweig each (60 % and 40 % of the population, respectively). Transport was assumed to take one day. The possibility of infection during transport and lairage was not calculated. There are several publications with models for the transmission of pathogens during lairage and slaughter. These are usually complex models with compartments different from the standard SIR compartment models. Van der Gaag et al. (2004), for example, use an enhanced compartment model, in which a carrier state and an additional state of infection (S-I-I-C) are proposed for carcasses. This model is currently not yet implemented in STEM and this is why only the prevalence of Salmonella in pork was used. In 2009, 2.5 % of the pork samples in Germany were Salmonella positive (BfR, 2011). Thus, the transmission rate was calculated using the published 14 % of infected pigs (Methner et al., 2011) and 2.5 % contaminated pork. This takes into account that roughly 70 % of the contamination of pork is a result of the pig being infected and 30 % is due to cross-contamination of pork from non-infected pigs with contaminated surfaces or machines (Berends et al., 1997). The contamination rates can be calculated from these values:
0.991 |
0.009 |
0.875 |
0.125 |
0.991 |
0.009 |
The transformation of pig to pork was set to 1:200, meaning that a fattened pig – weighing about 100 kg on average – was processed to 200 pieces of pork (500 g each). Pork is transported to several shops in northern and central Germany and is sold instantly at 100 %. An increase of the Salmonella concentration due to inappropriate cooling and the possibility that not all units of pork might be sold were not taken into account.
Infection of humans with salmonellosis from pork and human-to-human transmission
According to a study from The Netherlands, 95 % of all human salmonellosis cases are foodborne and only 5 % from human-to-human transmission (Berends et al., 1998). In 2009, 31,400 human salmonellosis cases were reported in Germany (RKI, 2012). In general, about 20 % of salmonellosis cases can be attributed to the consumption of pork (Steinbach and Kroell, 1999) (here: 6280 cases). However, this model computes the spread of foodborne Salmonella for only a part of Germany with much smaller numbers of pigs for only a part of the year. This is why the number of infected humans is much smaller in the described model.
How the Salmonella scenario was built in STEM
We started with a new model (PopulationModelGER.model) and dragged a population model for the country of interest into the new model (here: DEU_1_population.model). We defined the so called "population models" (symbol: man standing) for each population (human, pig, pork) and dragged them into the new model, by right clicking on the "PopulationModelGER.model" and then clicking on "Display canonical graph". A window opened showing the chosen country with nodes containing the area and the human population.
By right clicking we added a node, named it, and defined its size. Next we right clicked this new node and added population labels for each population we wanted to assign to this node. The pig farm needed a label for the pig population (called "PigFattening") and we added new nodes for slaughterhouses. (Because pigs are processed to pork, these nodes need labels for both pig and pork populations.) To define the transport of pigs from the farm to a slaughterhouse, we highlighted both nodes (Ctrl + left click), chose "Add migration edge," and named the population to be transported (here: "PigFattening") and how many pigs would move.
While the "rate" is a percentage of the whole population in the farm, checking the box "Use Absolute Value" enabled us to specify how many individual pigs should move each time interval. "Period" defines this time interval (default is 86400000 ms = 1 day). Pork migrates from slaughterhouses to retail and from there to the counties. This way all the retail facilities were connected to slaughterhouses on one side and to county nodes on the other side. We added the "Pork" population to retail and county nodes, clicked "Save Graph," and "Quit." Moving to Project Explorer, we defined new diseases for the transmission of salmonellosis between pigs and from pig to pork. Here we entered the data found in the literature, dragged the diseases into our model (here: PopulationModelGER.model), and defined a new model (SalmonellaDiseaseModelGER.model) that contained the PopulationModelGER.model and a new disease for human salmonellosis (HumanSalmonellosis.standard Deterministic SI).
Next we defined a last model for the transmission of Salmonella from pig to pork (SlaughterhouseDiseaseModelGER.model). This contained the SalmonellaDiseaseModelGER.model and two other items: the food consumer and the food transformer. We created both by clicking the plant symbol "Create a new Population Transformer"and picking the population transformer "Slaughter House" to transform pig to pork. When we entered the correct name of the source and target population, the diseases were chosen automatically (if there is only one disease like in this description). We chose which node should represent the slaughterhouse by picking the target location, choosing "select within project," and highlighting a node (here: SlaughterHH). We used the "Food Yield Multiplier" to define how many units of pork are processed from one pig and "Disease Mapping" to configure the proportion of pork that would be either free of or contaminated with Salmonella. After we finished this population transformer, we defined another one for the second slaughterhouse (here: SlaughterBR).
We added another population transformer called "Food Consumer" to our scenario to model the consumption of pork by humans. In this case we did not pick a target location because we assumed the whole human population should be able to eat pork.
We placed the two food transformers and the food consumer in the model "SlaughterhouseDiseaseModelGER.model" and dragged the latter into a new scenario. As always, when we built the scenario, we included a sequencer and defined a disease initializer. In order to start the transmission of Salmonella between pigs, we right clicked on the disease "SalmPig.standard Deterministic SIR" and clicked "Create new Initializer." We then chose the pig population ("PigFattening") and defined the number or fraction of pigs being infected. The location was the pig farm.
In our scenario, the pigs fattened for 120 days with no migration of pigs from the pig farm to the slaughterhouses until day 120. To reflect this, we used a migration trigger with a predicate (120 days) and migration modifiers (definition of the proportion of pigs migrating to either slaughterhouse).
That's what we did to build our scenario. Now you can start the simulation.
Berends BR, Van Knapen F, Snijders JM, Mossel DA. Identification and quantification of risk factors regarding Salmonella spp. on pork carcasses. Int J Food Microbiol. 1997 May 20; 36(2-3):199-206. PubMed PMID: 9217109.
Berends BR, Van Knapen F, Mossel DA, Burt SA, Snijders JM. Impact on human health of Salmonella spp. on pork in The Netherlands and the anticipated effects of some currently proposed control strategies. Int J Food Microbiol. 1998 Nov 10; 44(3):219-29. PubMed PMID: 9851601.
BfR (Federal Institute for Risk Assessment). BfR Wissenschaft – Erreger von Zoonosen in Deutschland im Jahr 2009. Hartung, M. and Kaesbohrer, A. (eds.); 2011
Methner U, Rammler N, Fehlhaber K, Rösler U. Salmonella status of pigs at slaughter--bacteriological and serological analysis. Int J Food Microbiol. 2011 Nov 15; 151(1):15-20. Epub 2011 Aug 3. PubMed PMID: 21872961.
RKI (Robert Koch-Institut), SurvStat, http://www3.rki.de/SurvStat, accessed on April 11th 2012
Soumpasis I, Butler F. Development and application of a stochastic epidemic model for the transmission of Salmonella Typhimurium at the farm level of the pork production chain. Risk Anal. 2009 Nov 29 (11):1521-33. Epub 2009 Jul 31. PubMed PMID: 19659452
Steinbach G, Kroell U. [Salmonella infections in swine herds--epidemiology and importance for human diseases]. Dtsch Tierarztl Wochenschr. 1999 Jul; 106 (7):282-8. German. PubMed PMID: 10481371.
Van der Gaag, M.A., Vos, F., Saatkamp, H.W., van Boven, M., van Beek, P., Huirne, R.B.M. A state-transition simulation model for the spread of Salmonella in the pork supply chain. European Journal of Operational Research 2004 Aug 1; 156 (3): 782-798, ISSN 0377-2217, 10.1016/S0377-2217(03)00141-3; (http://www.sciencedirect.com/science/article/pii/S0377221703001413).
Migratory Birds Demonstration
The Migratory Birds project demonstrates how the Seasonal Migration Edge Graph Generator can be used together with a Seasonal Migratory Population Model to create models where animals migrate seasonally between regions.
known issue: If you edit this model and if you replace the finite difference solver with a Stochastic Solver the birds will not migrate. This occurs because the stochastic solver requires that you have a disease model in your scenario (and this example scenario only includes the population). The issue only applies to use of a stochastic solver. The simple fix is to create a disease and add it to your model. You can keep a transmission rate of 0.0. Then it will run fine. Remember to set the target population or your disease to 'birds' matching the name of the population.
Evacuation Demonstration
The evacuation demonstration project aims to demonstrate how interventions can be used in STEM to control an outbreak. In this simple example, we have two regions (Square 0 and Square 1). The regions are connected by symmetrical migration edges moving 5 % of the population from region 0 to region 1, and 5 % of the population from region 1 to 0 in each time step. Hence the total population count is preserved in each region.
Region 1 has a hospital. The hospital is represented by a intervention label inside the HospitalGraph.graph file. You'll see that the hospital has the capacity to vaccinate 50 people per time step (daily).
In the scenario "NoEvacuationsScenario", an outbreak occurs in region 0 and no intervention takes place. Via migration the disease also spreads to region 1.
In "EvacuationScenario", after more than 5 cases per day occurs in region 0, an intervention policy is triggered. The policy does the following:
1. It cuts off any migration of people from region 1 to region 0.
2. It increases the migration of people from region 0 to region 1 (where the hospital is).
3. It increases the vaccination capacity of the hospital from 50 per day to 100 per day.
Once the number of cases in region 0 drops below 5 per day again, migration and vaccination are set back to their original settings
In the figure below, you'll see that the policy triggers around time step 6 and the population numbers starts dropping in region 0 due to evacuation. Correspondingly, the population increases in region 1. When the outbreak is under control at around time step 25, the migration is balanced out and the population numbers converges back towards the original values.
If we look at the cumulative disease deaths occurring in both scenarios, the figure below indicates that by evacuating and increasing vaccination capacity, a total of about 65 lives are saved.
(Asia) Mosquito Density Model
This downloadable scenario demonstrates how the earth science data can be used to generate seasonal mosquito density estimates in Asia. Before you try to run this scenario you much also install the STEM Earth Science Data Feature for the year 2010 (the year used in this example). The scenario (configured for Asia) also requires the Global Geography Models and the Global Earth Science Models available on the STEM Downloads page. You can easily reconfigure this scenario for the entire globe or for other selected regions. The screenshot below shows the Asia Mosquito Model running as downloaded. On the right hand side in the Project Explorer the scenario is expanded to show how it is constructed. The model contains the prebuild Global Geography Model (Human) for Asia along with its polygons, nodes, and edges, as well as the corresponding Asia earth science model (this in turn contains rainfall, temperature, vegetation, and elevation data for the same regions of Asia). These, together with an Anopheles Initializer, are contained in a parent model simply called Asia. The parent model along with the STEM population model for Anopheles are placed in the parent scenario. Users may easily modify this to study other regions. In the future the Anopheles model will be used as part of a complete vector disease model for Malaria and other conditions.
Notice: You probably need to change the reference population and reference population density in the STEM preferences to ensure the map colors are not saturated. When STEM determines the intensity of the color used to fill regions on the map, it takes the actual count (in case the number of Anopheles mosquitos) and divides by the reference population. The number between 0 and 1 (if it's larger than 1 it's set to 1) determines the intensity of the color. See screenshot below for numbers that are reasonable for this particular scenario:
Automated Experiment Example
In this example, we have been given historical incidence data for a disease with unknown epi parameters and we want to try and determine what those parameters are. All we know is that the first cases showed up in Stockholm. If you import the demo project into your workspace, the reference incidence data is located under the "Recorded Simulations/Reference" folder in the Incidence_1.csv file (the other files in the folders are not used in this example).
We decide to try and fit an SIR model to the incidence data, and we would like to determine three unknown parameters:
1. What was the transmission rate of the outbreak?
2. How long were infected individuals shedding viruses (i.e. recovery rate)?
Given these two parameters it's possible to determine the reproductive number of the disease, an important epi parameter.
We also have one more unknown we would like to estimate
3. What was the initial background immunity to the disease.
Next, open the "Experiments" folder in the project explorer and double click "AutomatedExperiment.autmaticexperiment" it to bring up its editor. Select the top node in the editor and look at its properties in the properties view.
Automatic Experiment Editor
You will notice that the automatic experiment will run a scenario called "AutomatedExperiment.scenario". This is a basic SIR scenario where with a few initial cases of the disease occuring in Stockholm, as well as an inoculator to initialize the background herd immunity. You will also see that the algorithm being used to fit parameters to the reference is called "Nelder-Mead", and that an error function called "Simple error function" is used. Nelder-Mead is a well-known numerical model optimization algorithm, and the "Simple error function" calculates a normalized root mean square error between the incidence reported in the reference and the incidence calculated by the model simulation. The incidence is aggregated over all locations that are common between the model and the reference.
You'll also see that the maximum number of iterations is 1000. This means that at most 1000 simulations are run before either the algorithm stops or it restarts itself using the optimal set of parameter values found so far. If "Reinit" is false, the algorithm stops after either a solution having an error tolerance smaller than the one specified (1E-6) is found, or the maximum number of iterations is reached. If "Reinit" is true, the algorithm restarts itself again and stops only when the the solution converges towards the same minimum twice.
If you expand the top node "AutomatedExperiment.autmaticexperiment" in the editor you'll see that the automated experiment has 3 parameters it attempts to fit:
1. transmissionRate. The initial guess is 0.8 and the algorithm will use a step size of 0.2 when walking the parameter space for this parameter. Also, the maximum and minimim values for this parameter is 0.001 and 10. You can modify any of these values in the properties view.
2. recoveryRate. The initial guess is 0.2, step is 0.3 and the parameter value is between [0.001, 2.0]
3. inoculatedPercentage. The initial guess is 20, the step is 30 and the parameter is between [0,100]
All three parameters also reference the model the parameter belong to, in this case the first two reference the disease model and the last reference the inoculator.
To start running the automated experiment, right click on the "AutomatedExperiment.autmaticexperiment" file in the project explorer and select Run. STEM will automatically switch to the Automated Experiment perspective and the Automated Experiment view.
You'll see a view with tab options on top ("Error Convergence", "Incidence vs Time" etc.). Select "Current Values". You'll be shown a scrolling list of parameter values and to the right you'll see the calculated normalized root mean square error for that set of parameters.
The history of parameter values and the associated error is shown in the Current Values view.
The "Error Convergence" shows a graph of the calculated error for each simulation and you'll notice how the error gets smaller and smaller. "Incidence vs Time" shows the latest incidence calculated by the current set of parameters compared to the reference incidence. Click the link below to see an animation demonstrating how the incidence is converging towards the reference.
The current calculated incidence versus the reference incidence Click here to see animation
"Error vs Time" shows the difference in incidence between the reference and the current model, compared to the difference in the best fit found so far. Finally, you can stop and restart an automated experiment using the "Contols" tab. When it looks like the algorithm has converged and the error is not changing much it is often useful to stop the experiment and restart it manually using the current optimal set of parameter values found. You can also specify any other parameter values on the Controls page and restart the experiment from those.
If you let the algorithm run until it completes (after about 340 simulations), it ends up with the following estimates for the parameters:
- transmissionRate: 1.199874
- recoveryRate: 0.30012
- inoculatedPercentage: 34.9852
You've probably already guessed it, but the reference data in this case was actually generated using a model with known parameter values. The values were 1.2 for transmission rate, 0.3 for recovery rate and the inoculated percentage was 35% (you can try plugging these values into the automated experiment, the error returned should be 0). You can force the algorithm to search for an even better fit by lowering the Tolerance parameter in the automated experiment (the tradeoff being that it takes longer to finish).
Each combination of parameter value tried and the resulting error is stored in a file called resultLog.csv in a folder AutoExpTempDir in the STEM workspace.
Multi-Population Example
Figure 1a-b. Square lattice world where the anopheles and human population is evenly distributed on each lattice square (a), and where there is a human village located in the center square (b). The edges are the common borders where both anopheles mosquitos and humans are mixing.
The Multi-Population example contains two scenarios of very much simplified Malaria models spreading across a 3x3 square lattice world. In the first example (Figure 1a), each node contains the same number of humans (50) and the same number of anopheles mosquitos (10,000). In the second example (Figure 1b), there is a village in the center square lattice containing 1,000 humans.
The disease is only spreading from infected humans to susceptible mosquitos or from infected mosquitos to susceptible humans, and it starts off by infecting 5 anopheles mosquitos in the upper left square. No infections transmit directly from human to human or mosquito to mosquito. The example also contains the log files from both scenarios, and a comparison between the incidence in the lower right square for both scenarios is shown in Figure 1c below. As can be seen, with the village in place, the incidence peaks about a week earlier for the lower right square. It should be noted, that in this simple sample model the mixing between anopheles members in two neighbouring nodes is at the same rate as the mixing between the human members of the very same nodes. In a real world example one would have to specify these rates seperately.
Figure 1c. Comparison of the daily incidence for both scenarios available in the Multi-Population example. In the scenario having a village in the center square, the incidence in the lower right square peaks about a week earlier than without the village.
Multi-Population Pajek Graph Example
Please find documentation for this downloadable scenario on the wiki page Importing a Pajek Graph.
Square Lattice Example
Figure 2. Square Lattice Example
The Square Lattice Example shows how a square lattice, migration edges, and initial population gradient can be used to model the interaction between an infected and uninfected population. It also demonstrates the hierarchy required to set up a SquareLatticeScenario.scenario: disease models must contain population models, and population models must contain initialized graphs, etc.
As illustrated in the figures that follow, the Square Lattice Example shows how to use migration edges to create two population gradients that cause a population to spread out over space and time. Only one of two populations is initially infected with a disease so you can see both the spread of disease within the original population as well as the eventual transmission from the infected population to the susceptible group when they meet. To accomplish this, the example uses both a standard population model and a Population Initializer (see Figure 1 below and the Tutorial on Using Structured Populations). The population initializer places an initial number of individuals at two separate locations at time zero. Migration edges exist (with equal migration rates) in both directions between all sites but, because there is a population gradient, the population spreads out or diffuses across the lattice.
Note that the components that appear when you click on SquareLatticeScenario.scenario (Figure 2, right) are hierarchical. The two population initializers are placed within the innermost option, HumanPopulation1.standard. The standard population object (HumanPopulation.standard) depends on the existence of the initialized graph and, therefore, is placed in the outer HumanPopulationModel. Both of these submodels are components or bundles that can be reused across many scenarios. Finally, the disease itself (Flu.standard) is a human disease that depends on a contained human model so it is placed in the outermost model of the hierarchy (FluLatticeModel). This too is a reusable component.
The Infector for the disease (FluInfector.standard) depends on a model of what is already known about the disease. An infector changes the state of a model by moving individuals from the susceptible state to the infectious state (given the presence of the indicated disease). As such, an infector is really part of the scenario - the topmost level in the hierarchy that contains ALL models.
In the figures below, you can see the initial population spread by migration edges. In the same simulation at runtime you can select the disease as the property to display and watch the disease spread.
Figures 3a-c. Spread of the Human Population by Migration Edges
The figures above show the spread of the population itself by migration edges. The population is seeded in the center (10x10) and in a node just left of center. The center population is much larger than the smaller seed to the left (the intensity is saturated). Only the population to the left is infected initially. Open the infector and the population initializer in the property editor to see the initial values. As the infected population on the left spreads, it eventually makes contact with and infects the main population spreading from the center.
Figures 4a-c. Spread of the Disease
The figures above show the same simulation but display the fraction of people infected as a function of time. Note that the intensity does not reflect the NUMBER of infections (only the fraction). When the infected population on the left reaches the much larger fully susceptible (but not yet infected) population spreading from the right, the intensity actually goes down as the fraction of people infected drops (initially) at the point of contact (see the middle image above). Eventually (right) the main population also becomes infected.
Mexico/USA H1N1 Scenario
The Mexico/USA H1N1 Scenario was created in the early spring of 2009 as a first attempt to measure the basic reproductive number, Ro, of the H1N1 virus. Little biosurveillance data was available but we knew that the first 10 people had been reported with H1N1 in NYC. At this time there were approximately 6000-7000 cases reported in Mexico City.
The Scenario makes use of STEMs model for air travel (calibrated against FAA data). The basic scenario was run repeatedly using a range of values for the transmission rate. For each run, we compared the number of people infectious in Mexico city at the time 10 people first appear with H1N1 in NYC. From this work we estimated Ro~1.7
The downloadable project contains this basic model without any expressed policies. The project also contains a second scenario that shows how to set up Modifiers, Predicates, and Triggers. In this case the Modifier changes the transmission rate based on a time trigger.
Global Earth Science Models
This downloadable project contains re-useable continent-level models of Earth Science Data including
- elevation
- rainfall
- temperature and
- vegetation coverage (NDVI)
Please note: You need to access the STEM update site and install the "STEM Earth Science Data for 2010" plugin to use these models. Instructions for adding this and other additional features may be found on the STEM Installation Guide.
Global Geographic Models Only
The Global Geographic Models project contains no runnable scenarios. Rather, is contains a set of pre-composed models for large regions of the world intended to be built upon in developing your own scenarios. These models, shown int he figure below, include a model for global air transportation, and a set of continent and super-continent models for geographic regions and people. After you download them, please expand them to see the inner components.
Super-Continent Examples
The Super-Continent Scenarios provide an examples of how to construct scenarios using the Global Model examples described above. These scenarios show how to model large regions such as the Americas, Europe+Africa, and Europe+Asia. The figure below expands the Eur-Africa Scenario. Note that the Inner Eur-Africa Model contains a model for Europe, a model for Africa, together with the connection between Spain and Morocco.
Chicken Pox
The Chicken Pox Scenario was created as an attempt to model a disease with lifelong immunity. An Aging Population Model is used to capture the different fractions of immune people for different age groups. Immunity acquired in one age group has an influence on the following age groups, since immune people age into these groups. Seasonal variations are achieved by using a Seasonal Population Model based on Interpolation of Sampling Points. The models are applied to geographic model of France. The following charts show the results for incidence and fraction of immune people for two different age groups.


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