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American/Iranian to Be First Female Space Tourist
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Joined: 03 Mar 2005
Posts: 1166
Location: SantaFe, New Mexico
Posted: Thu Aug 31, 2006 9:13 am
Post subject: American/Iranian to Be First Female Space Tourist
To my Iranian friends:
With all the things going on in troubled times, I thought you all would appreciate some good news for a change... Something to celebrate!
American to Be First Female Space Tourist
It's been the entrepreneur's lifelong dream to truly slip the bounds of Earth. into space. Her $20-million journey is scheduled for next month.
By David Holley, Times Staff Writer
August 31, 2006
MOSCOW As high-tech entrepreneur Anousheh Ansari rose to wealth and prominence after immigrating to the United States from Iran as a teenager, she never lost her childhood dream of being an astronaut. She often spoke of watching "Star Trek" as a girl in pre-revolutionary Iran, of staring at the night sky and dreaming big dreams.
Now she is preparing to see her lifelong dream come true.
Ansari signed up this year to be a space tourist at the price of about $20 million, aiming to visit the International Space Station aboard a Russian Soyuz spacecraft. She began training in March and was second in line for the next liftoff after Japanese entrepreneur Daisuke Enomoto.
But last week, Russian space authorities said Enomoto had failed a medical examination and Ansari, 39, would blast off next month with a two-man crew, becoming the first female space tourist.
"I had to pinch myself to make sure that I'm not dreaming and it's really happening," Ansari said Wednesday at a news conference in Star City, a cosmonaut training center about 25 miles northeast of Moscow.
"Ever since I was a child, I always used to gaze up at the stars and wonder what's out there in the universe, and wonder if there are others like me pondering the same question somewhere else out there," she said. "I always was interested and fascinated by the mystery of the universe."
Ansari said she expected the high point of her journey to be the moment when she first saw Earth as "a blue, glowing globe against the dark background of the cosmos."
The chairwoman and cofounder of Prodea Systems Inc. is scheduled to begin a 10-day space journey Sept. 14 or 18, flying with Spanish-born U.S. astronaut Michael Lopez-Alegria and Russian cosmonaut Mikhail Tyurin. She will return with the two-man crew now aboard the International Space Station.
The launch date depends on whether the U.S. shuttle Atlantis makes a visit to the space station before then. Weather permitting, the shuttle is scheduled to lift off sometime from Sept. 6 to 8, Russian officials said.
Three men have preceded Ansari into space as tourists, all on Soyuz flights.
Ansari, a U.S. citizen, immigrated in 1984 at 16 and went on to study electrical engineering and computer science at George Mason University. She and her husband, Hamid Ansari, founded Texas-based Telecom Technologies Inc. in 1993, which is where she made her fortune.
She won Working Woman magazine's entrepreneurial excellence award in 2000 and was featured on its cover. The next year, Fortune magazine listed her among the 40 richest Americans younger than 40 who had earned their wealth. It placed her assets at $180 million.
Ansari and others in her family were the key financial backers for a prize designed to spur commercial spaceflight: The $10-million Ansari X Prize was captured by SpaceShipOne, a small rocket built by aircraft designer Burt Rutan, after it blasted into space twice in five days in 2004.
She said she supported the project partly because she wanted to buy a ticket to space once commercial trips became available.
"I'm hoping that not only my flight but the life I've lived so far become an inspiration for our youth anywhere in the world, especially women and girls around the world, to pursue their dream, whatever that may be," Ansari said Wednesday.
A 1999 article in the Dallas Morning News gave some insight into Ansari's spirit as a child. Her father was vice president of a wine company when the Iranian revolution began in 1979, and the firm was abruptly shut down.
The next year, as a seventh-grader, Ansari organized students to perform a political play similar to "Animal Farm," satirizing Iranian religious fanatics, but school administrators banned it.
"I really got into trouble," she recalled in 1999. "Whenever we didn't have a teacher or a substitute, we did the play in the classroom just for students."
At a recent appearance, Ansari wore a U.S. flag patch on one shoulder and a patch with Iranian colors on the other. She explained why at her news conference.
"I have a lot of roots in Iran and feel very close to the Iranian people and the culture of the country," she said. "By wearing the two patches, I can demonstrate that both of the countries had something to do with making me the person I am today."
Hamid Ansari, asked how he felt about his wife's pending visit to space, said in an interview at Star City that it was "both exciting and nerve-wracking."
"She always knew it was her destiny to go up there," he said. "She didn't know when. But she was determined to get there. This isn't a joy ride for her. She wants to make this feasible for the public. It's more than a 10-day trip. It's a lifetime commitment."
While at the International Space Station, she said, she expects to help with experiments, communicate through a ham radio, make educational videos illustrating some of the laws of physics, and take photos so she can share the experience with others.
After her journey, she expects to tour schools to promote interest in science and technology.
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Joined: 23 Sep 2005
Posts: 297
Posted: Thu Aug 31, 2006 1:25 pm
Post subject:
Certainly any successful Iranian is a source of pride for all of us. Certainly, how a successful Iranian chooses to spend his or her money is his or her prerogative.
But a question does arise. With all the multi-millionaire Iranians in the world, why is it that none has ever spent a red cent in betterment of Iran? Why is it that the opposition is panhandling from the US? Is it because most successful Iranians dont give a hoot about Iran or the plight of the Iranians that are held captive in their own country? Perhaps it is because these successful Iranians have given up hope on the opposition, since many of its members in the past have been disappointing sell outs and con artists.
Either way, it is a travesty that there are so many successful Iranians with the means to fight for Iran, but not a single one (as far as I know) has stepped up.
I am Dariush the Great King, King of Kings, King of countries containing all kinds of men, King in this great earth far and wide, son of Hystaspes, an Achaemenian, a Persian, son of a Persian, an Aryan, having Aryan lineage
Naqshe Rostam
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Joined: 03 Mar 2005
Posts: 1166
Location: SantaFe, New Mexico
Posted: Thu Aug 31, 2006 7:20 pm
Post subject:
dorood Amir,
Well it is a very good question in general, and individuals must make their choices how to best spend their money.
But in this young lady's case Amir, if you think about where she was coming from in 7th grade, and that she relates it here today....plus the obvious fact that she is Iranian born, and a woman....do you not think her being up there constitutes a political statement in support of the opposition, in and of itself? A $20 million dollar political statement, delivered simply by her presence in space.
If that is not inspiration to Iranian women locked by dogma inside their homes in Iran today, under veil and threat on emerging.....I really can't imagine a more inspiring example of freedom....can you?
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Reporters often suspect that government officials attempt to prevent the whole story from getting out. Occasionally, we get proof.
I have a story in today's paper about Downforce Racing, the group organizing this year's Baltimore Grand Prix, missing benchmarks set by its contract with the city. The group has also twice delayed selling tickets for the Labor Day racing festival. Some of the information for the story came from an email that was apparently sent to me by mistake.
I contacted the Maryland Stadium Authority, a quasi-public state agency, to see if the group had finalized its contract. A spokeswoman informed me that the executive director said they had. I then asked for a copy. That's when things got interesting.
A Stadium Authority attorney emailed the spokeswoman about my request and, apparently unwittingly, sent the email to me as well. The attorney told the spokeswoman that the contract had in fact not been finalized. There had been a March 15 deadline. She wrote that the situation "could present some PR problems" for Downforce and instructed her to "refrain from discussing this with the Sun."
"At this point, I would give the Sun no information until we find out if [Downforce Racing] has the necessary signatures," Cynthia M. Hahn, an assistant attorney general, said in an email to the stadium authority's spokeswoman.
I sent a follow-up email asking the Stadium Authority and the attorney why it would be concerned about the public perception of Downforce Racing and why they would avoid discussing this with the Sun. They did not respond.
Take a look at the string of emails below:
From: Scharper, Julie
Sent: Wednesday, April 04, 2012 4:15 PM
To: 'Hahn, Cynthia'; Hardesty, Jan
Cc: Frenz, Michael J.
Subject: RE: Agreement with Downforce Racing
Hello all,
I assume that you did not mean to include me on this email. But, now that you have, the content of the email will be mentioned in the story we will be running in tomorrow's paper about the state of the contract with Downforce.
Could you please explain why you felt it was the responsibility of the MSA and the AG's office to protect Downforce from "some PR problems"? We would also like to know why Ms. Hahn advised Ms. Hardesty to avoid discussing the contract with the Sun.
Thank you.
Julie Scharper
Julie Scharper
City Hall reporter
The Baltimore Sun
o. 410.332.6602
c. 410.206.6303
From: Hahn, Cynthia [mailto:email@example.com]
Sent: Tuesday, April 03, 2012 7:01 PM
To: Hardesty, Jan; Scharper, Julie
Cc: Frenz, Michael J.
Subject: RE: Agreement with Downforce Racing
HI, Jan,
Downforce RAcing has never returned a fully executed counterpart of the contrac to MSA, unless MIke has received it over the last 48 hours. Last I heard, Mike had advised Reck that we needed a properly executed counterpart, and Reck said he would provide it. That was last week, before I left on vacation. I have received nothing since.
MSA's receipt of the signed copy is critical for a few reasons. First and most obviously, until we receive their signed counterpart, their is not contract. That leads to the second part that is relevant for PIA disclosure purposes: If there is no final contract, there is nothing to produce. Draft and partially executed versions of contracts are exempt from disclosure. Mike's signed copy is not subject to disclosure, until DFR signs off on teh agreement--and signs off properly in a manner that is legally binding.
Bottom line: MSA has nothing to disclose to the Sun yet. Because this could present some PR problems for DFR, I will contact their attorney. You should refrain from discussing this with the Sun until Reck has a chance to get MIke his properly signed counterpart.
If Mike has it, then MSA's counterparty signed by Mike can be released. I do have the pdf of it that Pam sent over to me. However, the original of the pdf is likely retained by Mike and Pam.
I will copy you, Mike and Pam on my communication to Reck's attorney. At this point, I would give the Sun no information until we find out if Reck has the necessary signatures.
From: Hardesty, Jan [firstname.lastname@example.com]
Sent: Tuesday, April 03, 2012 4:32 PM
To: Scharper, Julie
Cc: Frenz, Michael J.; Hahn, Cynthia
Subject: RE: Agreement with Downforce Racing
Julie –
Thanks for the official ask. I've just checked with Mike, and the contract with Downforce Racing, signed March 15, 2012, is with our counsel, Cynthia Hahn. Cynthia is in the Attorney General's Office and she is on vacation right now.
I will attempt to get you a copy some other way, but we may have to wait until Cynthia gets back.
Will keep you apprised and make every effort to get to you soonest.
From: Scharper, Julie [mailto:firstname.lastname@example.com]
Sent: Tuesday, April 03, 2012 3:10 PM
To: Hardesty, Jan
Subject: Agreement with Downforce Racing
Hi Jan,
Nice to chat with you as usual. Here is a MPIA letter for the agreement with Downforce racing, as per your request.
Julie Scharper
The Baltimore Sun
P.O. Box 1377
Baltimore, MD 21278-0001
Dear Ms. Hardesty:
I am writing to request certain documents under the Maryland Public Information Act.
Specifically, I request access to, and copies of, the following:
The agreement between Downforce Racing and the Maryland Stadium Authority for the 2012 Baltimore Grand Prix.
I am not seeking any information that is exempt from disclosure under the Public Information Act. Please let me know which exceptions are applicable to any information withheld or redacted.
If possible, I would like to obtain these records in electronic format. If that is not possible, I would like to select which portions of the records to retain after inspection.
If you have questions or need more information, please contact me by telephone or email.
I look forward to hearing from you promptly, as specified in the law.
Julie Scharper
Latest Sun Investigates
Julie Scharper
City Hall reporter
The Baltimore Sun
o. 410.332.6602
c. 410.206.6303

subset: commoncrawl


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Grey's Anatomy, Who's Zoomin who: A Resident's Review
As I sat twitching while the writers managed, once again, to make a blunder out of what happens in real medicine I had a very illuminating thought. What if I stop considering Grey's Anatomy a medically oriented show and rather begin considering it as a world within itself, seperated from the world I live in.
I prefer to think of it as a spin-off from Desperate Housewives. I mean, what is the real difference? Everyone is sleeping with everyone.Its a sopa opera within itself. It's own imaginary world.
Shall we explore this world:
In Seattle Grace Hospital Surgery is the only residency. This is why Surgery must handle all medical issues. In Seattle Grace Hospital there is no medical hierarchy, there is no accountabiity, interns do Everything without supervision. Attendings sleep with interns, the staff sleeps with everyone and surgery interns are so friendly that they feel perfectly comfortable discussing masturbation, sex, and even strip naked, at every oppurtunity, in public. None of this has any consequence on their proffesional reputation. In the world of Grey's anatomy, when hearing hoofbeats, think Zebras. I love this world. Oh why can't the Mad House be in Seattle?
The season finale seemed more about the internal conflicts than about actual medicine. It was intended to make sure we come back when the super-six return for a second season.
1. Mr. Fragrin and the Cirrhosis.
In Cirrhosis of the liver scar tissue replaces healthy liver tissue. Most commonly this happens as a result of alcoholism but other, more rare diseases, can cause it as well. Due to the decrease in productions of proteins by the liver Ascites often results, a condition where fluid accumulates in the peritoneal cavity, the abdomen. Yang and Izzy perform an abdominocentesis and the patient dies during the procedure. In order to prove that the death was not of their doing they perform an unauthorized autopsy.
Paging Surg-path intern you're needed in the morgue! (For the death of your own career).
These 'expert' pathologists discover that he had a condition also known to cause cirrhosis (much more rarely though) called Hemochromatosis. It is a genetic disease that causes excessive absorption of iron from food. This iron accumulates in the liver, pancreas, skin and heart and can cause Cirrhosis, Jaundice, Heart Failure and Diabetes (Often called 'Bronze Diabetes').
It's much more rare than alcoholism but we must think Zebras. For fun, I suggest attempting to perform your own unauthorized autopsy. I take no responsibilty for what happens.
2. Gonadal Hermaphrodism: A case of a man, Burke's best friend, who presented with hematuria (microscopic amounts of blood in the urine) that led to a cystoscopy. During the procedure a mass was found that was later diagnosed as an ovary.
The condition is a congenital defect that is present at birth. The genitalia are usually ambiguous and these children need surgery to correct the appearance. A finding such as this in a thirty year old male is unlikely in that he would have surely known about his condition.
The story gets more convoluted for drama, his wife is pregnant. His condition makes it impossible for the baby to be his and so Burke discovers the wife's infidelity, which he now must disclose. Talk about a bummer? how would you like to find out you have ovaries and a wife who cheats. Poor Burke doesn't know he's got a doozy coming his way next season!
Paging Surge-Psych!! Surge-Endocrinology! Surge-gyn!
Paging some sanity in an impossible world.
The story of Yang's pregnancy doesn't really continue. We are left to wait for next season.
As for Dempsey and Pompeo (Meredith), the last scene is a cliff hanger as Dempsey's wife spontaneously appears and says to Meredith:
"Hi, I'm Mrs. Shepard, and you must be the bimbo who's screwing my husband!"
I bet they're seperating, otherwise, why would Dempsey be sleeping in a trailor?
BTW Ms. Pompeo, my wife hates your eyebrows. Sorry, she made me put that in.
Until next season, this is the MMM signing off on my round-table of a mediocre medically oriented soap opera.


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PLANK SOURDOUGH PIZZA is masterminded by Global Baker Dean Brett scheneider and the same team that
developed and operates the successful Baker and Cook chain of artisan bakeries and food stores.
Our pizza base is made with the same long fermentation process as the famous sourdough bread that we make at Baker & Cook.
We use a combination of flours and slowly ferment it for up to 48 hours at 8°C using only our natural wild yeast (levain), salt, water & extra virgin olive oil.
After pressing out the traditional way (not rolling pins here!) we carefully top them with our selected quality ingredients, we blast them at 380°C - 400°C until the crust is super pillowy soft with a touch of crispness.
Make sure you don't waste the outer crust as that's best dipped in our infused olive oils on the table.


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Best PC monitors at cheapest price
Looking for inexpensive computer monitors? Get feedback and suggestions on list of the best PC monitors.
I want to buy a secondary monitor for my PC and want to connect it to my existing system. I would like to know which are the best but cheapest PC monitors available in India. If possible suggest something below 5k.


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The seventh edition of ETech has now concluded. Save the date for the next ETech: March 9-12, 2009 in San Jose, California.
Check out the highlights from the 2008 event:
How does technology help you perceive things that you never noticed before? How does it help you be found, or draw attention to issues, objects, ideas, and projects that are important, no matter their size or location?
At the 2008 version of ETech, the O'Reilly Emerging Technology Conference, we'll take a wide-eyed look at the brand new tech that's tweaking how we are seen as individuals, how we choose to channel and divert our energy and attention, and what influences our perspective on the world around us:
Body Hacking. Genomics Hacking. Brain Hacking. Sex Hacking. Food Hacking. iPhone Hacking.
If you can't open it, you don't own it. Take over the everyday aspects of your life and take your senses to the next level.
DIY Aerial Drones. DIY Talking Things. DIY Spectrum. DIY Apocalypse Survival.
As technology becomes more accessible you'll get to do it all on your own. Self-empowerment starts here.
Emerging Tech of India, Cuba, and Africa. International Political Dissidents.
Different environments incubate new ideas and technologies. What these societies bring out will shake up your cultural assumptions and provide a wider world view.
Visualize Data and Crowds. Ambient Data Streaming.
Dynamic systems require new methods of data capture and interaction. Open a window on the methods experts use to interpret and harness collective intelligence.
Good Policy. Energy Policy. Defense Policy. Genetic Policy. Corruption.
Policy inevitably lags behind technology advances. Learn about some areas where it's catching up, where it's not, and how these boundaries shape our creativity and freedom.
Alternate Reality Games. Emotions of Games. Sensor Games.
Games provide a platform for experimentation on so many levels. The ones we'll see engage their players in new and unexpected ways.
ETech 2008 will cover all of these topics and more. We put on stage the speakers and the ideas that help our attendees prepare for and create the future, whatever it might be. Great speakers are going to pull us forward with them to see what technology can do... and sometimes shouldn't do. From robotics and gaming to defense and geolocation, we'll explore promising technologies that are just that--still promises--and renew our sense of wonder at the way technology is influencing and altering our everyday lives.
"There's more good stuff here, more new directions, than we've had at ETech in years, which is only to be expected, as the market starts to digest the innovations of Web 2.0 and we are now featuring the next wave of hacker-led surprises." Read more of Tim O'Reilly's thoughts on why ETech is our most important conference.


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Eiko Jones is a well known underwater photographer from Campbell River, British Columbia, Canada. His pictures have been published widely and he is currently creating a library of stock photos of pacific salmon.
His pictures are amazing, so I asked him directly to share some of his photo secrets. You don't need an expensive underwater camera rig to take great shots. Anyone can benefit from some or all of Eiko's top five photo tips!


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Goats Cheese & Spinach Pizza
Member recipe by rosebraisby
ServingsServes 1 - 1 Pizza
A lip smacking tasty pizza that tops take-away anyday! :)
This recipe has been submitted by the Good Food community. Sign in or create a My Good Food account to upload your own recipe creations. Please note that all recipes will be moderated but they are not tested in the Good Food kitchen.
Save to My Good Food
- For the dough:
- 175g plain white flour
- 1/2 cup of warm water
- 1 tsp dried yeast
- 1 tsp sugar
- For the topping:
- 8 black pitted olives, halved
- A handful of baby spinach leaves
- 100g goat cheese, thinly sliced
- 6 tbsp red onion chutney
- 2 tbsp tomoato puree
- Mix the yeast, sugar and water together. Leave to sit in a warm place for about 7 minutes (until the yeast and sugar has dissolved).
- Add flour and mix to make a firm dough (adding extra flour if necessary). Roll out the dough with a rolling pin and now you have your pizza base.
- Spread the tomato purée on first evenly. Then place the baby spinach leaves on (I always try to make a nice pattern)
- Bang the goats cheese on the pizza dollop lots of small spoonfuls of the chutney on too. Bake in the oven for 10 minutes at a fairly high heat, then enjoy!


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"get your performance Videod "
School performance filming is the perfect way to capture all the hard work and effort that goes into a school production of any kind. This might be a school play, a Christmas event, a musical or any other production involving children of all ages. While there's no substitute for being there on the evening, having a high quality DVD to treasure the event is something that many parents now want and that's why Videod offer school performance filming for our customers.
There are also other benefits to the filming of a school event. Selling copies of the DVD can be an excellent way for the school to help raise some much needed funds. The money may be dedicated to a charity involved with the event or may be used to help develop school facilities – benefitting the children and future generations for years to come.
From a teacher's viewpoint, the creation of video content from the event has a number of uses. For older students who are more serious about the undertaking, it is an excellent way to review performance, highlight what worked and what didn't and allow the children to see the event from a spectator's viewpoint. And even for younger kids, it can help boost their confidence and allow them to see how brilliant they were on stage.
We can film and edit the production for you and supply as many DVDs, Blu Rays or upload the footage for you alternatively we can provide a private link for you to email out which alllows anyone wanting to purchase a copy of the footage access to a preview and order options like this example which keeps everything simple.
All of our crews are DBS checked so parents can be completely confident about the people working around their children. We have worked in schools, colleges and dance classes around the country as well as with theatre groups and other artistic performance clubs. Our experience means we can create a top quality production from the event that will be to the standard of those you see on TV and will take the kids feel like the superstars they already are!
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Excellent attentive and prompt service! Equipment was in great condition! Hire a camera much more expensive!
Video Cameras have been fantastic easy delivery and collection with superb customer service
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"The hardships of poverty and displacement are tempered with hope, determination and the will to survive in this well-researched debut historical novel."—Publishers Weekly
"Offers a good sketch of Victorian life with some nice historical shadings."—Kirkus Reviews
"Jonatha Ceely has caught perfectly the beauty, cruelty, and the very essence of one England about to transmute into another. The struggles of her young Mina may be behind us now, but they are vivid and wrenching, and the life she makes for herself is truly wonderful. A lovely book."—Anne Rivers Siddons


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On April 8, 1966, Time magazine created an uproar with a stark, black and red cover that asked "Is God Dead?"
Laity and clergy alike were outraged.
Time received somewhere around 3,500 angry letters to the editor, the most it had ever received for a single article. The idea that God could die was outrageously unthinkable to some and outright blasphemy to others. Which was incredibly ironic considering the day Time published its infamous edition.
April 8, 1966 was Good Friday.
The day God died.
We don't usually speak about Good Friday in such a provocative way. Instead, we talk about the death of Jesus. Doing so may not seem like a big deal on the surface, but there's a subtle heresy at play. In speaking of the death of Jesus on Friday, we – whether intentionally or not – acknowledge that the man from Nazareth died, but we protect God from any real suffering, let alone death. While the idea of God being incapable of suffering, much less death, may seem like orthodoxy 101, such a separation of Jesus' human and divine nature is an ancient heresy known as nestorianism.
Actual orthodoxy declares that Jesus was/is "truly god and truly man," and therefore his human and divine nature are inseparably intertwined.
This is easy enough to accept when Jesus is hanging out with his disciples doing cool stuff like walking on water and raising people from the dead, but when it comes time to talk about the crucifixion, our insistence on the dual nature of Christ conspicuously become less insistent.
The idea that death could enter into the life of God is simply too scandalous.
We need God to be above that, bigger than that, more powerful than that.
God needs to be Superman times a thousand – invincible, all powerful, and immortal – or how else could God be God?
And yet, as the German theologian Jürgen Moltmann reminds us, it wasn't just a man from Nazareth that hung on the cross.
It was God.
When the crucified Jesus is called the "image of the invisible God," the meaning is that this is God, and God is like this. God is not greater than he is in this humiliation. God is not more glorious than he is in this self-surrender. God is not more powerful than he is in this helplessness. God is not more divine than he is in his humanity. The nucleus of everything that Christian theology says about 'God' is to be found in this Christ event. – The Crucified God, 205
The One who hung on that tree so long ago wasn't just a poor carpenter from a backwater town. It was the Lord of all creation. It was the One who said "Let there be light" that was abandoned in the darkness. It was the One who breathed life into dirt who took his last breath on that cross.
It was God who died on the cross on Good Friday.
That doesn't mean God ceased to exist anymore than we cease to exist when we die, but make no mistake.
God died on Good Friday.
And it's a scandal we still struggle with today, not just because of what it says about God, but also because of what it says about us and the life we are called to live as followers of a crucified God.
It's a scandal of disappointment and embarrassment
A crucified God is a total and complete rejection of the John Wayne Jesus we crave in American Christianity. The kind of super manly, guns a-blazing action hero we fetishize in so many corners of the American church is nowhere to be found on the cross. What we find instead is a humble carpenter who rides into town on a donkey, only to be arrested, beaten, and stripped of both clothes and dignity before ultimately being put to death in the most humiliating way possible.
For a Church that is increasingly insecure about its eroding power and influence in the world and desperately wants to portray Jesus as an über-manly hero who stands ready to lead the charge as we vanquish our enemies and wrestle control of the world from their cold dead heads, it's disappointing, uncomfortable, and embarrassing to be confronted with the truth that we worship a crucified God who said "no" to conquest, choosing instead to die naked and alone for the enemies we seek to vanquish.
It's a scandal of unwanted inclusion
We may hang crosses prominently in the front of our churches, but the cross has become a sanitized symbol that makes few, if any demands on our lives.
Though we may revere it as an important symbol, we have forgotten that,
The symbol of the cross in the church points to the God who was crucified not between two candles on an altar, but between two thieves in the place of the skull, where the outcasts belong, outside the gates of the city…It is a symbol which therefore leads out of the church and out of religious longing into the fellowship of the oppressed and abandoned. On the other hand, it is a symbol which calls the oppressed and godless into the church and through the church into the fellowship of the crucified God. – The Crucified God, 40
While we sanctify discrimination in the name of religious freedom, the crucified God declares that God stands with the outcast and abandoned, even and especially when they have been cast out and abandoned in the name of God.
It's a scandal of radical self-denial
The crucifixion of God is a visceral reminder that the cross is the way of Jesus. There is no Christianity without a crucified Christ and therefore there is no discipleship without picking up our own cross and all the suffering and loss that comes with it.
But radical self-denial and painful self-sacrifice has no place in a me-centric society or in a Church which has realized that biblical weight loss strategies, financial peace, and beating the drums of theological war (and actual war) are all far more effective at filling the pews than calling people to live a cruciform life.
And so, the identity of the one hanging on cross remains a scandal today.
Not so much because we can't agree on the theological nuances of hypostatic union, but because we still can't accept a crucified God whose power is made perfect in weakness.
Because we don't want to embrace unwanted neighbors, let alone serve them in any way.
And because as much as we may preach self-denial, actually living a self-sacrificing life that puts others' needs before our own is simply too much to ask.
The latter half of this post originally appeared in a Good Friday reflection I wrote a couple of years ago.


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Temperature for April 1946
In April 1946 the average high temperature in Palm Springs, CA was 0.0°F, and this was 87.7°F cooler than the average of 87.7°F. The hottest day in April 1946 was 0 April when the temperature reached 0.0°F. Overnight the average temperature in April is 55.0°F and in 1946 the average overnight temperature was 55.0°F cooler at 0.0°F.


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Injection Moulded Cases
Customers that require high volume case batches or have items that are being sold inclusive of their case may be searching for a more cost effective casing solution.
Injection moulded cases are a good alternative for strict budgets and are ideal for products requiring minimum protection, low security and are relatively light in weight.
Consort offer a range of injection moulded cases for this market with sizes ranging from (135 x 95 x 32) to (530 x 305 x 120) and lots in between.
Please see list of sizes available:


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Page 1 of 2
As of 4/2/2020, our current hours are Monday and Tuesday 10:00 am-12:00 pm at the Newtown Pantry and Thursday and Friday 10:00 am – 12:00 pm at the Amelia Pantry. We are CLOSED on Wednesday. The Drive-Through Pantry may be visited every two weeks.
Due to the current COVID-19 public health crisis, these hours are subject to change at any time without notice. Please contact IPM at (513) 561-3932 or check our website before visiting the pantry.


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Get buy now orders for your priced products. Boost your eCommerce Product Catalog conversion rate with innovative, fully customisable order form.
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Last weekend was Turkey's Camel Beauty Contest and Camel Wrestling Festival.
Top 10 Biggest Design Flaws In The U.S.S. Enterprise.
Wired's Absurd Creature of the Week: The Beautiful Octopus Whose Sex Is All About Dismemberment.
Anonymously send glitter to people you hate (NSFW language).
ICYMI, Friday's links are here, and include movie scenes that happened in real life, a close-up video of lava pouring into water, a huge mouse trap and ping pong ball chain reaction, and celebrities who look like mattresses.


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Missing colors in Windows 8 [closed]
I'm having a problem with LibreOffice that started when I upgraded to windows 8. Since the switch, LO is unable to render fill colors anywhere in the interface. Does anyone know what's going on?
This means many of my icons are whited out (such as the alignment tools and arrowheads) and I'm unable to draw colored shapes. It wasn't a problem until now, but it's silly having to work around it rather than just fix it. It happens in every part of the suite, not just writer.
I'm on Win8 x64, here are captures of what's happening, note that the circle is currently set to a Violet fill: http://imgur.com/a/rP9hd


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Video - Baghdad/Adhamiya, Iraq - In Adhamiya there is a famous place known as the Royal Cemetery. Each of the kings of Iraq's short-lived monarchy, Faisal, Ghazi, and Faisal the 2nd are buried here. Under the Ottoman Empire, this place was selected to be the location for an Islamic College in Baghdad. With the upheaval of World War I and the eventual collapse of the Ottoman Empire, construction was never completed.
King Faisal I, the first king of Iraq, completed its construction years later, but after his death, it was chosen to be his burial place. From this point on, it was chosen as the burial place for the Iraqi Hashemites. Faisal I's wife, Huzaima Bint Nasir, as well as his son Ghazi, and his grandson Faisal II are each buried here.
With the overthrow of the monarchy in 1958, the cemetery languished in disrepair and was all but forgotten. In 1987, Saddam Hussein, in an effort to renew interest in Iraq's monarchy, remodeled the Cemetery, improving its stark appearance. His efforts brought the Royal Cemetery to the beautiful monument that stands today.
After the fall of Saddam's government, in 2003, Shari Ali, the heir-apparent to Iraq's monarchy, made his first appearance in Iraq at the cemetery, beginning an effort to re-assert the importance of the monarchy. This effort was short-lived.
United States Military, and Coalition troops entered the Royal Cemetery shortly after the fall of Baghdad, and the marble stone covering Faisal I's tomb was damaged while they were searching for weapons stockpiled by insurgents in the area. Although the monarchy seems to have finally been cast aside in favor of Modernity, it remains to be seen whether this symbol of Iraq's past will hold any lasting influence upon its future.
If you appreciate our work, please consider making a donation, or becoming a paying subscriber, to support the work of Iraqi journalists. Although we are dedicated to continuing to offer this work for free, it is primarily with the support of our viewers that we can continue our work. Please feel free to contact us if you have any comments, suggestions for stories, or other feedback!


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Artificial Intelligence in Precision Cardiovascular Medicine
Author + information
- Received March 12, 2017
- Accepted March 22, 2017
- Published online May 22, 2017.
Author Information
- Chayakrit Krittanawong, MDa,b,∗ (Chayakrit.Krittanawong{at}Mountsinai.org),
- HongJu Zhang, PhDc,
- Zhen Wang, PhDd,e,
- Mehmet Aydar, PhDb,f and
- Takeshi Kitai, MD, PhDb,g
- aDepartment of Internal Medicine, Icahn School of Medicine at Mount Sinai St. Luke's and Mount Sinai West, New York, New York
- bDepartment of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio
- cDivision of Cardiovascular Disease, Department of Medicine, Mayo Clinic, Rochester, Minnesota
- dRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota
- eDivision of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
- fDepartment of Computer Science at Kent State University, Kent, Ohio
- gDepartment of Cardiovascular Medicine, Kobe City Medical Center General Hospital, Kobe, Japan
- ↵∗Address for correspondence:
Dr. Chayakrit Krittanawong, Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, St. Luke's and Mount Sinai West, 1000 10th Avenue, New York, New York 10019.
Central Illustration
Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates. Over the past decade, several machine-learning techniques have been used for cardiovascular disease diagnosis and prediction. Each problem requires some degree of understanding of the problem, in terms of cardiovascular medicine and statistics, to apply the optimal machine-learning algorithm. In the near future, AI will result in a paradigm shift toward precision cardiovascular medicine. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI's application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine.
In the near future, artificial intelligence (AI) techniques, such as machine learning, deep learning, and cognitive computing, may play a critical role in the evolution of cardiovascular (CV) medicine to facilitate precision CV medicine. CV clinical care currently faces practical challenges pertaining to cost reductions in prevention and treatment, low cost-effectiveness, overutilization, inadequate patient care, and high readmission and mortality rates. Productive interactions between physicians and data scientists are needed to enable clinically meaningful automated and predictive data analysis. To date, big data, such as "omics" data, human gut microbiome sequencing, social media, and cardiac imaging, are too large and heterogeneous, and change too quickly, to be stored, analyzed, and used. AI has the potential to exploit big data and be used in advanced patient care. In fact, cardiovascular diseases (CVDs) are complex and heterogeneous in nature, as they are caused by multiple genetic, environmental (e.g., air pollution), and behavioral factors (e.g., diet and gut microbiome). At present, many more advancements need to be made to predict outcomes accurately and effectively, rather than assessing a simple score system or traditional CV risk factors. Deep-learning AI is a new machine-learning technique that plays a vital role in areas such as image recognition (e.g., Facebook's facial recognition system [Menlo Park, California], self-driving cars, speech recognition (e.g., Apple's Siri [Cupertino, California], Google Brain [Mountain View, California], Amazon's Alexa Voice [Seattle, Washington]), Google DeepMind AlphaGo, mobile apps (e.g., Cardiogram app [San Francisco, California]), machine vision software in cameras, IBM Watson (North Castle, New York), and robots. Deep-learning AI using big data can be used in pattern recognition in heterogeneous syndromes and image recognition in CV imaging. For example, AI can classify new genotypes or phenotypes of heart failure (HF) with preserved ejection fraction (HFpEF), and novel diagnostic echocardiographic parameters could potentially lead to novel targeted therapy. In addition, to date, 2-dimensional speckle-tracking echocardiography (2D-STE) quantitation cannot sufficiently assess left ventricular ejection fraction because left ventricular ejection fraction is commonly calculated by manually tracing boundaries or via the time-honored "eyeball" method, which lack reproducibility and precision. Therefore, AI may improve the accuracy of 2D-STE quantitation and other cardiac imaging methods. In the 21st century, the paradigm is shifting from traditional statistical tools to the use of AI in CV medicine to enable precision CV medicine. Big data can be used to automatically generate new hypotheses, instead of physicians having to initiate hypotheses. In our opinion, rather than replacing physicians, AI will assist them in making better clinical decisions. The objective of this paper is to outline the role of AI applications, such as machine learning, deep learning, and cognitive computing, in enabling precision CV medicine, and discuss the potential future direction of AI in clinical practice. Going forward, future studies in CV research should focus on more complex and heterogeneous diseases using AI by moving beyond traditional statistical tools. To illustrate some of the points addressed here, this paper focuses on examples of AI algorithms in CV medicine.
Big Data
The term big data refers to extremely large datasets that cannot be analyzed, searched, interpreted, or stored using traditional data-processing methods. Big data include data from mobile phone applications, wearable technology, social media, environmental and lifestyle-related factors, sociodemographics, "omic" data (e.g., genomics, metabolomics, proteomics), and data from standardized electronic health records (EHRs) or precision medicine platforms. Whereas big data by themselves are useless, the processing of big data to make predictions or decisions using AI has the potential to transform the current practice of clinical care. Big data analytics using AI may potentially facilitate identification of novel genotypes or phenotypes of heterogeneous syndromes, such as HFpEF, Takotsubo cardiomyopathy, hypertrophic cardiomyopathy, primary pulmonary hypertension (PH), hypertension (HTN), and coronary artery disease, leading to personalized, targeted therapy. Big data analytics using AI can also support important clinical decisions, such as selection of antiplatelet agents in individuals who are post–percutaneous coronary intervention, anticoagulant agents in individuals with nonvalvular atrial fibrillation (AF), and pharmacogenomics in individuals. Furthermore, big data analytics has the potential to identify unknown risk factors for acute coronary syndrome (ACS), spontaneous coronary artery dissection (SCAD), or Brugada syndrome, and even the controversial issue of statins in the older population (age >75 years). Although big data utilization in CV medicine is still in its infancy, big data analytics have recently been implemented in CV medicine.
Traditional statistics versus machine learning
In the big data realm, AI techniques, such as machine learning, are revolutionizing the way physicians make clinical decisions and diagnosis, and have the potential to improve the estimated CVD risk scores to automate prediction. In traditional statistics, such as the logistic regression model, the c-statistic is a standard measure of predictive accuracy. However, current predictive scores, such as congestive HF, hypertension, age ≥75 years, diabetes mellitus, and prior stroke, vascular disease, age 65 to 74 years, and sex category (CHA2DS2-VASc), dual antiplatelet therapy, and the Framingham risk score, were developed using large trials or cohorts with ill-defined moderated values of c-statistics (e.g., 0.79 for men in Framingham risk score, 0.83 for women in Framingham risk score, 0.65 for CHA2DS2-VASc score, 0.66 for Anticoagulation and Risk Factors in Atrial Fibrillation, 0.70 and 0.68, respectively, in the ischemic and bleeding models in dual antiplatelet therapy) (1–4). Although the dual antiplatelet therapy study involved 25,682 patients at 452 sites in 11 countries, big data analytics using precision medicine platforms could involve millions of patients for exploration and validation. In 2013, the American Heart Association/American College of Cardiology guideline was developed by estimating atherosclerotic CVD using the pooled cohort equations from sex- and race-specific proportional hazards models, but its c-statistics are not well-defined in African Americans (0.713 in men and 0.818 in women) (5). Cook et al. (6) reviewed the guideline and found overestimation of the pooled cohort equations in primary prevention external cohorts. They subsequently suggested that real-time calibration of risk prediction equations is feasible with big data analytics (6). Therefore, the increasing availability of automated real-time decision support tools using AI applications in EHRs will likely reduce the need for simple scoring systems such as these.
Machine Learning
Machine learning, a popular subdiscipline of AI, represents various techniques for solving complicated problems with big data by identifying interaction patterns among variables. In contrast to traditional statistics, machine learning is focused on building automated clinical decision systems (such as readmission and mortality score systems) that help physicians make more accurate predictions, rather than simple estimated score systems.
Machine learning can be categorized into 3 learning types: supervised; unsupervised; and reinforcement. In supervised learning, algorithms use a dataset labeled by humans to predict the desired and known outcome. Supervised learning is great for classification and regression problems, but it requires a lot of data and is time-consuming because the data have to be labeled by humans. Conversely, unsupervised learning seeks to identify novel disease mechanisms, genotypes, or phenotypes from hidden patterns present in the data. In unsupervised learning, the objective is to find the hidden patterns in the data without feedback from humans. For example, teaching medical residents (labels) before they see the patients can be termed supervised learning. In contrast, allowing medical residents to see patients (no labels), then allowing them to learn from their mistakes (errors) and come up with their own plans (optimize) can be termed unsupervised learning. Some algorithms, such as artificial neural networks (ANNs), can be trained using supervised or unsupervised learning to optimize the accuracy of automated prediction. Last, reinforcement learning can be viewed as a hybrid of supervised and unsupervised learning. The aim of reinforcement learning is to maximize the accuracy of algorithms using trial and error.
Learning curves and area under the curve (AUC) are important considerations in the choice of a machine-learning algorithm, whereas c-statistics are important in the choice of traditional data-processing methods. As with traditional statistics, machine learning requires sufficient training datasets (also known as sample size in traditional statistics) and the right algorithms to optimize its performance on the training dataset before testing. In traditional statistics, alpha should not be more than 0.05, whereas in machine learning, there should be no underfitting (suboptimal data) or overfitting (noisy data). Overfitting commonly occurs when a model is excessively complex relative to the size of the training dataset (i.e., too many parameters) that may not be valid for the testing dataset. For example, for a machine trying to learn what SCAD or acute myocardial infarction is, we start by training it with keywords such as "chest pain," "female," "age 30 to 50," "physical/emotional factors," and "h/o fibromuscular dysplasia"; the machine detects in the initial phase that all SCAD features have "chest pain," "female," "age 30 to 50," "physical/emotional factors," and "h/o fibromuscular dysplasia." If training continues with the same key words, the machine may also falsely deduce that all SCAD features must have "chest pain," "female," "age 30 to 50," and "h/o fibromuscular dysplasia," and that all "chest pain," "female," "age 30 to 50," and "history fibromuscular dysplasia" are SCAD. This may potentially include atherosclerotic acute myocardial infarction or Takotsubo cardiomyopathy, which is called overfitting to data. In contrast, AI may potentially exclude SCAD in men, SCAD without fibromuscular dysplasia, or 51-year-old women with SCAD. This problem is called underfitting to data.
An excellent example of the use of machine learning is the prediction of the survival of patients with HFpEF. Shah et al. (7) created an unsupervised learning model across 46 different variables to identify intrinsic structures within patients with HFpEF; they identified 3 distinct groups. Subsequently, they performed supervised learning to predict the difference in desired outcomes (mortality and hospitalization) among the groups. However, the limitation of unsupervised learning is that the initial cluster pattern needs to be corrected without bias; therefore, the study needs to be validated with other cohorts.
Supervised learning
Supervised learning algorithms have been successfully applied to problems in the prediction, diagnosis, and treatment of CVD as well as image analysis in CV imaging. Various algorithms can be trained using supervised learning. For example, we trained a machine for 30 potential variables (such as C-reactive protein, erythrocyte sedimentation rate, cysteine, QTc interval, E/A ratio, and SYNTAX score [an angiographic tool]). Subsequently, the algorithms generated a prediction model using weighted variables from the training dataset. Next, we applied the algorithms to a new dataset (testing dataset) to predict ACS risk; the machine then calculated the ACS risk from the 30 potential variables in the new dataset. The prediction accuracy depends on the algorithm, dataset, and hypothesis. Different algorithms are appropriate for different hypotheses, and so an understanding of the advantages and disadvantages of each algorithm is required to apply it in the optimal manner and potentially test the hypotheses. Knowing the goals and the appropriate techniques for hypotheses is critical for machine learning to be carried out effectively and accurately.
Algorithms that can be used in supervised learning include ANN, support vector machine (SVM), decision tree, random forests, naive Bayes classifier, fuzzy logic, and K-nearest neighbor (KNN). Each algorithm has its own advantages and disadvantages. Supervised learning problems can be categorized into classification (predict categories), regression (predict values), and anomaly detection (predict unusual patterns) problems. Factors for selecting optimal algorithms include data characteristics, training time, learning curves, and number of parameters and features. ANN and SVM are the 2 most popular algorithms because they are compatible with large and complex data (e.g., "omic" data) and can process data with higher accuracy than other supervised learning algorithms.
ANNs, which mimic the human neuron concept, perform well for image processing of electrocardiographic (ECG) and echocardiographic data. ANNs: 1) can be used in nonlinear relations; 2) conditions where traditional statistical analyses fail; 3) have a higher predictive accuracy than linear or logistic regression; 4) are very flexible in various data types; and 5) can be used with deep-learning algorithms. Their limitations include: 1) data overfitting; 2) lengthy computation time; and 3) having more parameters than most supervised learning algorithms.
In contrast to ANNs, SVMs are less prone to overfitting and need less memory. They have been shown to perform well for text classification in EHRs and pattern recognition in echocardiographic imaging to stratify CV risk and help physicians make decisions (8,9). In addition, an SVM is feasible for nonlinear data or large and complex data, such as "omic" data, because kernel functions, a shortcut to expedite learning process, can be applied to SVMs to enhance their accuracy and reduce processing time (10,11). However, selection of kernel functions is very important, as the wrong choice can lead to an increase in the error percentage. Other algorithms, such as decision tree, naive Bayes classifier, and random forest, have lower accuracy than ANN and SVM, but are relatively easy to use and can be used with small datasets. The decision tree algorithm is easy to understand and is unlikely to encounter overfitting because of the relatively small dataset. It can be used with a series of yes/no questions to classify data into categories and also be used in clinical decision-making or CV risk prediction in simple tasks (12). The random forest algorithm is an extension of the decision tree algorithm, in which decision trees are combined and each decision tree is independently trained. Random forest algorithms have been used in coronary computed tomography angiography, readmission for HF patients, and HF risk and survival prediction models (13–17). In addition, random forests can easily perform leave-1-out predictions (i.e., sensitivity analysis in meta-analysis) and are relatively robust to selection bias.
The naive Bayes classifier is a simple probabilistic classifier derived from Bayes' theorem. It performs very well on small training datasets and can be used in text classification problems, such as in CV risk factor identification and decision-making systems (18,19). Fuzzy logic functions are similar to human reasoning and decision-making in which logic returns values (e.g., 10% possibility of SCAD, 30% possibility of acute myocardial infarction, 15% possibility of pericarditis) instead of straight true/false or yes/no answers (e.g., definitely SCAD and not SCAD). Fuzzy logic has been used in various areas, such as for prediction of early-stage coronary artery disease, mortality prediction after cardiac surgery, and cardiac arrhythmia detection (20–23). K-nearest neighbor is one of the simplest nonparametric methods. It executes quickly on small training datasets and can be used in ECG interpretation problems (24,25); however, K-nearest neighbor requires more space and time for large datasets.
Limitations of supervised learning
In supervised learning, small training datasets can lead to inaccurate decisions in testing datasets if the training datasets are biased; therefore, supervised learning requires large datasets to train the model and validation by other datasets. Supervised learning also requires the training datasets to be manually labeled to predict only known output results (e.g., mortality and readmission rate). Furthermore, even though multiple functions can fit a given training dataset on which supervised learning subsequently makes assumptions about the "best" function that fits the data, it can cause bias that guides the learning algorithm to prefer to one hypothesis or function over another.
Unsupervised learning
In unsupervised learning, unlabeled data are used to predict unknown results and the algorithm has to determine how to discover the hidden patterns in the dataset. Unsupervised learning is often used in deep learning, and has been implemented in self-driving vehicles and robots as well as being used in speech- and pattern-recognition applications. In CV clinical care, unsupervised deep learning with 2D- and 3-dimensional (3D)-STE data may enable identification of novel phenotypes of cardiomyopathy or HFpEF, and can potentially be used in precision medicine platforms or the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine program to identify genotypes of HTN or ACS. The algorithms used in unsupervised learning can be classified into: 1) clustering algorithms; and 2) association rule-learning algorithms. Clustering algorithms can be used to cluster unlabeled data into different groups. A cluster is a collection of data items that are "similar" to 1 cluster and "dissimilar" to other clusters and is used when there are no obvious natural groupings, in which case the data may be difficult to explore. For example, Google News can be shown to customers in different ways to match their online lifestyles. Association rule-learning algorithms help to uncover relationships between seemingly unrelated data items. For example, 70% of patients who had angioedema with angiotensin-converting enzyme inhibitors also have angioedema with angiotensin receptor-neprilysin inhibitors. Another example of an association rule is novel drug-drug interaction.
Limitations of unsupervised learning
One major limitation of unsupervised learning is difficulty identifying the initial cluster pattern, which could potentially lead to biases. Because the final cluster pattern is dependent on the initial cluster pattern, this could result in inaccurate decisions. Therefore, it needs validation in several cohorts. In addition, some complex problems lead to limitations that are not easily overcome without supervised training; thus, it may require manually labeled data to identify the optimal algorithm. For example, noisy data, such as 3D-STE images, have to be manually denoised before predictions can be successful. Thus, for the best results, unsupervised learning may require manual hand coding in some parts, unsupervised algorithms in other parts, and subsequent validation.
Deep Learning
Deep learning mimics the operation of the human brain using multiple layers of artificial neuronal networks that can generate automated predictions from input (training datasets). Deep learning has become a hot topic in AI because it is a growing field and appears promising. Deep learning can be very powerful in image recognition (e.g., facial recognition in Facebook, image search in Google), and can potentially be used in CV imaging (e.g., 2D-STE, 3D-STE, angiography, cardiac magnetic resonance). It can also be trained in an unsupervised manner for unsupervised learning tasks (e.g., novel drug-drug interaction). Furthermore, there is no limitation on working memory. It also works well with noisy data, such as strain imaging and 3D-STE data. Deep-learning algorithms will facilitate use of artificial real-time CV imaging with better spatial and temporal resolution, potentially improving the quality of care and reducing costs.
Deep learning has recently been implemented in CV medicine, more specifically, in CV imaging. Deep learning with neuronal network algorithms can be recurrent neural networks (RNN), convolutional, and deep neural networks. Wang and Kong (26) used a supervised convolutional neural network model to predict end-systolic and end-diastolic volumes in cardiac magnetic resonance. Convolutional neural networks and RNN are dominant in image and speech recognition. RNNs have proven effective in many difficult machine-learning tasks, such as image captioning (27) and language translation (28). Choi et al. (29) used an RNN to predict HF 9 months before diagnosis made by physicians and found that the RNN (AUC: 0.777) was superior to supervised machine-learning algorithms. Google developed a deep neural network known as Google DeepMind AlphaGo that defeated human champions in the Go game in March 2016. Kannathal et al. (30) used a deep neural network to classify the ECG signals of cardiac patients into normal, abnormal, and life-threatening states, and found the classification to be correct in approximately 99% of test cases.
Deep learning has proven to be better than other machine-learning techniques, such as SVM, because deep learning can use multiple layers and transformations, compared with the 2 layers used by SVM.
Limitations of deep learning
Deep learning is usually nonlinear analysis and has many parameters and multiple layers; thus, overfitting may be a major challenge that could lead to poor predictive performance. Increasing the size of the training dataset or decreasing the number of hidden layers may help to avoid overfitting. Deep learning also requires a large training dataset, which necessitates collaboration between institutions and EHR linkage (e.g., the American Heart Association Precision Medicine Platform). Furthermore, deep-learning analysis requires deep-learning–capable machines, such as graphics processing unit-accelerated computing, for example, NVIDIA DIGITS DevBox (Santa Clara, California) and Amazon EC2. Setting up a neural network using deep-learning algorithms is also time-consuming. Finally, deep learning with multiple layers may increase the training time without improvement in precision.
Clinical implications of deep learning
Deep learning can perform tasks without human assistance in industry (e.g., self-driving, playing Go, learning math to write math textbooks, reading scientific publications to answer questions, watching movies to answer questions, machine vision software in cameras, phones, and robots). Implementation of deep learning in CV medicine includes the following. First, unsupervised deep learning may facilitate exploration of novel factors in score systems or add hidden risk factors to existing models. Second, deep learning can be used to classify novel genotypes and phenotypes from heterogeneous CVDs, such as HFpEF, HTN, pulmonary hypertension, and cardiomyopathy. Third, automated deep-learning prediction models can predict risk of bleeding and stroke by weighting between CHA2DS2-VASc and the hypertension, abnormal renal function, abnormal liver function, stroke, bleeding, labile international normalized ratios, elderly, drug therapy, and alcohol intake (known as HAS-BLED) scores to facilitate optimal doses and anticoagulant therapy duration in nonvalvular AF patients. Fourth, deep learning may also help to identify additional stroke risk factors (e.g., left atrial appendage, left atrial strain on echocardiography, real-time risks from wearables) and incorporate those factors into new models for anticoagulant therapy. Last, with deep learning, left ventricular ejection fraction may be predicted from ECG patterns or coronary calcium score from echocardiography.
Cognitive Computing
Cognitive computing involves self-learning systems using machine learning, pattern recognition, and natural language processing to mimic the operation of human thought processes. In cognitive computing, a system or device is trained by machine-learning or deep-learning algorithms. The goal of cognitive computing is to create automated computerized models that can solve problems without human assistance (Central Illustration).
IBM Watson, a well-known example of cognitive computing, continuously learns from datasets (e.g., EHR, social media, stock market) and can predict outcomes using multiple algorithms more accurately than humans. Sengupta et al. (31) developed an associative memory classifier, a cognitive computing machine-learning algorithmic approach, to classify constrictive pericarditis from restrictive cardiomyopathy, and demonstrated its feasibility for automated interpretation of STE data. An associative memory classifier (accuracy: 93.7%; AUC: 96.2%) proved to be better than random forest (accuracy: 88.3%; AUC: 94.2%) and SVM (accuracy: 87.4%; AUC: 92.2%). With a set of select STE variables, the associative memory classifier achieved an AUC of 89.2%. Four echocardiographic variables (e′, E/e′, and septal and posterior wall thickness) had an AUC of 94.2%. Fifteen STE and 4 echocardiographic variables (e′, E/e′, septal, and posterior left ventricle wall thickness) showed incremental diagnostic value in distinguishing constrictive pericarditis from restrictive cardiomyopathy.
Cognitive computing systems can also reason creatively about data, patterns, and situations, and extend models with new pieces. Cognitive computing can leverage machine learning to extend the ability of HF diagnosis efficiently by helping physicians discover diagnosis patterns that they may not observe by themselves. Therefore, implementation of deep learning in cognitive computing systems can be used for classification of novel diseases, genotypes, phenotypes, or unknown drug-drug interaction.
The implementation of deep learning with unsupervised features for big data analytics holds significant potential for identifying novel genotypes and phenotypes in heterogeneous CV diseases, such as Brugada syndrome, HFpEF, Takotsubo cardiomyopathy, white-coat hypertension, HTN, pulmonary hypertension, familial AF, and metabolic syndrome. Furthermore, the development of AI application and precision medicine platforms will facilitate precision CV medicine. In the future, cognitive computers, such as IBM Watson, will be standard in health care facilities and assist physicians with their decision making and prediction of patient outcomes. Many technology companies, such as IBM, Apple, and Google, are investing heavily in health care analytics to facilitate precision medicine. We believe that AI will not replace physicians, but it is important that physicians know how to use AI sufficiently to generate their hypotheses, perform big data analytics, and optimize AI applications in clinical practice to bring on the era of precision CV medicine. However, ignorance of the challenges of AI may overshadow the impact of AI on CV medicine. Machine learning, deep learning, and cognitive computing are promising and can potentially change the way in which medicine is practiced, but physicians need to be prepared for the upcoming AI era.
The authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Bijoy K. Khandheria, MD, served as Guest Editor for this paper.
Listen to this manuscript's audio summary by JACC Editor-in-Chief Dr. Valentin Fuster.
- Abbreviations and Acronyms
- acute coronary syndrome
- atrial fibrillation
- artificial intelligence
- artificial neural network
- area under the curve
- cardiovascular
- cardiovascular disease
- electrocardiographic
- electronic health record
- heart failure
- HFpEF
- heart failure with preserved ejection fraction
- hypertension
- recurrent neural network
- spontaneous coronary artery dissection
- speckle-tracking echocardiography
- support vector machine
- Received March 12, 2017.
- Accepted March 22, 2017.
- 2017 American College of Cardiology Foundation
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text:
Posted: Nov. 6, 2014
Postcard-perfect Jar Island is the kind of place where nobody locks their doors at night, where parents can sleep easy, knowing their daughters are tucked away safe and sound in their beds.
But bad things can happen, even to good girls . . . and sometimes, the only way to make things right is to do something wrong.
Lillia used to trust boys, but not anymore. Not after what happened this summer. And she'll do whatever it takes to protect her little sister from the same fate.
Kat is over the rumors, the insults, the cruel jokes made at her expense. It all goes back to one person--her ex-best friend. Someone needs to teach her a lesson, and, with Lillia and Mary behind her, Kat feels up to the task.
Four years ago, Mary left Jar Island because of a boy. But she's not the same girl anymore. Now that she's got friends who have her back, he's going to be in big trouble.
Three very different girls who come together to make things right. Will they go too far?


text:
The other day I was having a conversation with a female friend of mine. It was a Sunday, and naturally she asked if I had done much with my day. I told her I hadn't even stepped out the house and then came the second question. She now wanted to know if I went to a church service. I told her I didn't and that was were our argument started. She said she would only marry a God fearing man and I asked her what that had to do with attendance in church.
Nigeria is an overly religious nation and if I dare say it, this is one of the biggest issues we face as far as social progression is concerned. Can you believe that on a road in Benin City I was able to count 16 churches in 1km. That is to say Usain Bolts would run past 16 churches in under two minutes in this city. But for all this presence of God in Benin there are very few cities in Nigeria as dangerous as this one. If we cannot accept anything else, let us at least accept that the current religious scene in Nigeria is marked with hypocrisy. How do we explain being one of the most religious countries in the world and also one of the most corrupt? An oxymoron if I ever saw one.
I have no problem with people believing whatever it is that soothes their soul, but when ideas drawn from these belief systems start to affect others then it become a problem. I will give an example. Earlier this year a law was passed to send homosexuals in Nigeria to prison for 14 years. Sadly, as I expected this was greeted with cheers by Nigerians on the premise that it was termed an abomination in the bible. This is the questions I pose to these so called Christians: What would Jesus do? Is the fundamental philosophy of being a Christian not being Christ-like? I cannot tell you for certain what Jesus would have done, but I am certain he wouldn't lock anyone up for 14years. That in itself is immoral and if you support such measure of marginalisation then you are part of the Nigerian problem.
And when did religious grounds become valid for law making in a secular state? We were all up in arms with Yerima's insinuation of child marriage on religious grounds, but when it suited our agendas we were all happy to accept religion as grounding for law making. And why stop at anti-gay laws, how about anti-adultery laws, laws against fornication,….did you know that the bible also regards eating shrimp to be an abomination in Leviticus! Where are the state laws to regulate these sins, or have we decided to pick and choose because it is easy to accept restrictions that do not restrict us. If you are a man and have watched girl-on-girl porn then you aren't even qualified to have a negative opinion on homosexuality. For as long as religion has existed men have bent and twisted it to suit our needs and that is all that is happening in Nigeria today. I will stop here before I go into essay mode and rant on, but you can expect more posts of this nature. We need to drop this religious charade and get into the habit of learning to respect others even if we have clashing spiritual ideologies. It is almost as if the average Nigerian cannot comprehend that someone else can have a different idea of life to theirs, like we have some sort of monopoly of the truth.


text: This is a Hand Carved Mask of a Fanged Man (possibly the Devil), which measures 8" high by 6.75" wide by 5" deep. There are holes for the eyes, as well as openings above the inside corners of the eyes and below the bulbous nose. There is a small man with frog-like legs hanging down and grasping the mask's forehead, which may be part of a headdress. The style of the wood carving is simple but well-proportioned, characteristic of work done in Mexico. The mask is unpainted and unmarked. This Hand Carved Mask of a Fanged Man is in good condition. There is an interior crack with two nails to hold this section together. The age of this repair is unknown.


text:
Carling(redirected from Carling Beer)
Also found in: Dictionary.
Will(iam). born 1965, British Rugby Union footballer; captain of England (1988--96)
(naval architecture)
A short girder or timber running fore and aft, used to support or stiffen a ship's deck, or to frame an opening in the deck where beams have been cut.


text:
Please answer two of the following questions. In your answers, you must refer to TWO specific scenes from the reading to support your answer.
1. What role do postmodern themes play in the text? (Which do you see as being most significant? How are they used?)
2. What significant role does Paradise Pickles and Preserves play in the story? (Not just in terms of plot, but in terms of theme or symbol.)
3. To what extent are race, social class, and religion important in this text? What specific elements of each take on predominant importance, and with what consequences?
How do the concept and the reality of "the Untouchable" function in the novel?
4. Why does Roy switch back and forth among time present and various times past? What effect does she intend this to have on the reader? (Does it work?)
5. Is "time as destroyer" the novel's most insistent theme? How are the blue Plymouth, the pickle factory, Rahel's toy wristwatch (which always reads "ten to two"), and other objects related to this theme?
6. What is the significance of Velutha's role in the story?
7. How does Roy portray the twins' extraordinary spiritual connection, their "single Siamese soul," the fragile, wonder-filled world of their childhood, their often magical vision, and their differences? What might be her purpose for creating such a strong connection between the twins? (Is this simply a character trait, or does this connection function thematically?)
8. What importance does Roy ascribe to story, storytelling, and playacting? Why?
9. In what ways are the Kochamma women subjected to male dominance, indifference, and even cruelty, and in what ways are they decisive in their own lives, the life of their family, and the affairs of their community?
10. Roy has said that her architectural studies determined her novel's structure. In what ways can we view the novel's plan and construction as architectural? In what ways is the novel's "architecture" related to the significance of actual buildings in the novel?
11. So far, what would you identify as the most significant key motifs or theme in the story? Which scenes or characters illustrate this theme most clearly?
12. How is the idea of boundaries explored? Who enforces boundaries? Who breaks them? What moral judgments are made? (By the author or by the characters.)
13. What is the significance of the title, The God of Small Things? (Who or what is the God of Small Things?)
14. What function does Pappachi's moth serve in the book?
15. What does the book have to say about the changes to the world brought about by modernity, development and globalization, etc.?
16. What does the author seem to be saying about the nature of history and of memories in The God of Small Things?
17. The God of Small Things is filled with strong images. From variously shaped "Holes in the Universe" to bursting jackfruits to Pappachi's moth, Roy weaves a very sense-ridden story. Identify two strong similes or images used in the book, and discuss *why* they worked so well.
18. Michiko Kakutani of the New York Times praised Roy's "marvelous job of conjuring the anomalous world of childhood, its sense of privilege and frustration, its fragility, innocence and unsentimental wisdom." Do you agree with this? Why/why not?
19. In what way is this a fundamentally political text? What does Roy seem to be criticizing or advocating?
20. Create a detailed character sketch of Ammu, Baby Kochamma, Velutha, Chako, Mammachi, Pappachi, or Margaret. (Be sure to include your thoughts and opinions on the character, not just a literal description.)
21. How do you think Caste affects Rahel and Estha's outlook on life and people? (If you'd rather, you may discuss Ammu, Chacko, or Baby Kochamma instead of the twins.)
22. What is the significance of the name "Baby" Kochamma? (Why 'baby'?)
23. In what way do characters in the text illustrate a crisis of identity? What point do you think Roy is using this pattern to make?


text:
Like humans and other primates, female lemurs have a different smell when they're pregnant. And as a pair of primate experts recently discovered, the type of scent change depends on whether there's a boy or girl in utero.
Unlike chimpanzees, humans and apes, who all have dry schnozes, lemurs have damp noses like dogs. The little primates have a keen sense of smell, used to sniff out mates and identify individuals based on the pungent secretions they produce. The "eau de Lemur," as Christine Wilcox notes at Discover Magazine, is made up of 300 different compounds.
To see what lemur pregnancy smells like, Duke University's Christine Drea and Jeremy Chase Crawford, from the University of California, Berkeley, swabbed 12 lady lemurs' nether bits both prior to and during pregnancy.
These swabs revealed that a male baby was linked to a less complex bouquet, the scientists reported Wednesday in the journal Biology Letters. This marks the first time a sex-linked scent difference in pregnant animals has ever been found, the authors say.
Sex differences were reflected in the expectant moms' hormones, too. "The difference in hormone profiles between pregnant lemurs carrying sons and those carrying daughters is dramatic," Drea said in a press release.
Experimentally, it hasn't been verified if the animals react to the scent changes. But Drea said it's certainly possible lemurs could follow their noses to determine a baby's sex.
"It would be very odd," she told Discover, "for them not to be able to smell it based on all of the prior experiments."


text:
These speakers take me back... I was looking through my old project pictures and found these babies. Here's a simple how-to on converting a set of mobile speakers into some raver-iffic gear. I used a pair of old speakers that I had from middle school, (12 years ago or so??) and converted them for this auction we had back at the Y when I worked there, for the kids to spend there "bucks" that they earned through good deeds, behavior, homework etc. They were a big hit, so I thought I'd show 'em. You could do this with any of the newer mobile speaker sets, (those ones that fold shut) just keep in mind the open/close function, and glue accordingly.
- A mobile speaker set
- Fuzzy balls
- A glue gun & glue sticks
- Sandpaper


text:
Directory 2016 of Community Services for Homeless People in the Greater Montréal area
This bilingual directory of nearly 700 pages is an essential tool for community counsellors involved with the homeless. It features relevant resources designed to bring them assistance depending on their specific needs. It provides a unique and comprehensive collection of specialized organizations and services involved in this area.
The English Directory contains a detailed description of 400 organizations providing food aid for people on a low income. It is an important tool for people interested in self-help as well as for the staff of social agencies and all those who are in daily contact with the public: nurses, physicians, psychologists, social workers, those in charge of human resources or employees assistance programs.
The English section of this book of nearly 300 pages includes 4 chapters covering the following subjects:
To download the Directory, click here.


text:
I'm not sure who started it, but I want to take part.
So, for Day 1! How did I come to the subculture... Well, the very first goth I met was a girl called Rose or Rosie who was a few years older than me and at the first secondary school I attended. This secondary school was a state girls-only day school and we had a navy-blue uniform that was pretty conservative for state school uniforms (long skirts, shirts, ties, blazers), and she used to change into black dresses for the journey too and from school, much to the dismay of the staff, wore a "Vote Satan" t-shirt to P.E and had pentagrams drawn on her bag. I was just getting into Wicca at the time, and asked her if she was a Witch, but I was huge "fluffy-bunny" and I think I annoyed her. A fluffy-bunny is the Wiccan equivalent of a mall-goth or babybat, but they come in all ages, and some never realise stuff like that Wicca has only been around since the 1940's and that sparkly wands are just silly. I confess, I had a sparkly wand... Anyway, I thought she was cool, but at the same time I was terrified of her. There were a lot of rumours about her self-harming, that her and her goth friends slit each others wrists and drank blood, that she was on drugs, etc. etc. Now, I realise that it was a bunch of malicious nonsense, and it was probably the fact that she had to put up with that sort of bullying which made her snap when I asked her if she was a Witch too. I regret having believed the rumours, and regret being afraid of her, as she was probably really nice.


text:
Sean Ryan
Vice President, Media Relations
A former print journalist at The Richmond Times-Dispatch and Inside Business, Sean joined The Hodges Partnership in 2003 and leads Hodges' media relations team. He manages media relations strategy and helps place subject matter experts on CNN, FoxNews and MSNBC and more. Sean regularly helps place op-eds in top-tier papers like the New York Times, Washington Post and USA Today. He recently concluded a two-year project leading media relations efforts locally, regionally, nationally and internationally for Richmond 2015, the organizers of cycling's world championships, and also managed strategy for the University of Richmond for seven years.
Sean is head baseball coach for Benedictine College Prep and co-founder/editor of CollegeBaseballInsider.com. He just wrapped up his term as board president of the Down Syndrome Association of Greater Richmond (DSAGR) and serves on the boards of the Salvation Army Central Virginia Area Command and Commonwealth Community Trust. He was honored by Style Weekly as one of Richmond's "Top 40 Under 40" in 2011. A graduate of the University of Richmond, Sean and his wife and three children live in Richmond's Far West End.


text:
Alba, Fernando Alvarez de Toledo
Alba, Fernando Alvarez de Toledo
Born Oct. 29, 1507; died Dec. 11, 1582, in Lisbon. Duke, Spanish military leader, and statesman.
Alba distinguished himself in the Schmalkalden War of 1546–48 against the German Protestants and in the Spanish war against Pope Paul IV (1556–57). Thanks to his bravery, Catholic fanaticism, and dedication to the monarchy, he enjoyed the special confidence of the Spanish king, Philip II. Appointed as ruler by Philip in the insurrectionary Netherlands, Alba invaded the country with a strong army in the summer of 1567. After establishing a terrorist dictatorship ("Council of Troubles" and others), he condemned thousands to death, including Egmont and Horn. However Alba's policy and his introduction in 1571 of a tax—alcabala—led to a new revolutionary outburst in 1572, with which he was unable to cope. In 1573 he was recalled to Spain. In 1580 he led the Spanish army that conquered Portugal.


text:
You Can Now Look Like Teyana Taylor
LOL JK, but Teynana Taylor did launch a fitness website called Fade2Fit (I see what she did there) where you can waste money learning "her secret" by doing dance cardio routines and believing you'll look like her. I'm sure you will. The videos probably won't tell you to stop eating Taco Bell for breakfast though. I will. #toddcares
Dat ass:


text:
C6 Corvette Bilstein B8 24-029780
C6 Corvette Bilstein Sport Shocks - Rear are an excellent replacement shock for the performance minded Corvette owner. The Bilstein Sport Shocks are recommended for Corvette Owners with the factory Base Suspension that want a more aggressive handling posture and base suspension Corvettes when you are doing a Sway Bar upgrade. Most conventional shocks are cut from a tube with stamped internal parts. Bilstein shocks are formed through a unique extrusion process that leaves no seams. Bilstein Corvette Shocks feature a Monotube design with hardened chrome piston rods, Alloy rod guides and seals. The self adjusting piston is nitrogen filled and features Bilstein's patented "floating" dividing piston for exacting performance every time. Bilstein Corvette Shocks are as close as you can come to a handmade shock. Step up the performance of your suspension with Corvette Shocks from Bilstein. Sold as a pair (2) Rear Shocks 24-029780
Fitment: C6 Corvette, Grand Sport, Z06 and ZR1 (2005 to 2013) With Standard Suspension
Product Note: For Corvette's WITHOUT Electronic Suspension