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NPR Newscast
4min 45sec
February 28, 2010 The Falkland Islands are back in the news, now that Britain has allowed the first oil wells to be dug in the South Atlantic island nation. So host Guy Raz checks in with Stephanie Pearson of Outside magazine, who profiled this remote land of quirky sheepherders, dangerous minefields and one of the largest albatross populations on Earth.
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February 28, 2010 More than 700 people are now confirmed dead after Saturday's 8.8 magnitude earthquake in Chile. The epicenter was off the Pacific coast, near Concepcion, the country's second-biggest city. Reporter Annie Murphy is on the way to that city, and talks to host Guy Raz about the wreckage she's seen on the way: buckled highways, overpasses turned into rubble, and towns where damaged water systems have forced residents to start bucket brigades from the nearest natural water source.
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The epicenter of the quake was 70 miles from Concepcion, Chile's second-largest city. (AP)
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February 28, 2010 Survivors huddled around the rubble of their homes and wandered the streets, fearing aftershocks, a day after one of the strongest earthquakes in history. Reports said some towns "disappeared from the map."
February 28, 2010 Last week, American and Mexican officials met in Washington to ramp up efforts to combat illegal drug use and the problems it causes. Some of those issues are all too visible in the U.S., where addiction touches the lives of millions, as well as in Mexico, where thousands of soldiers, police, prosecutors and civilians have been murdered in the battle between the government and drug traffickers. Liane Hansen speaks with Gil Kerlikowske, the Director of the White House Office of National Drug Control Policy, about recent efforts to stem the flow of drugs from Mexican by decreasing the demand in the U.S.
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February 28, 2010 With the rainy season fast approaching, the need for housing in Haiti is nearing a crisis level. An innovative manufacturer and designer of modular homes in Miami plans to begin building homes in Haiti within the next few weeks. InnoVida is shipping 1,000 homes to Haiti that can be assembled in a matter of days. NPR's Greg Allen reports.
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February 28, 2010 Earthquakes and other natural disasters are deadlier and more destructive than they were a couple of hundred years ago. Host Liane Hansen speaks with Roger Bilham, a seismologist at the University of Colorado at Boulder to find out why.
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February 28, 2010 The 8.8 magnitude quake in Chile on Saturday morning struck one of the most seismically active zones in the world. In fact, the largest quake ever recorded — a 9.5 in 1960 — was centered nearby.
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February 28, 2010 Earlier this month, five French-speaking journalists spent a week in a house in the French countryside. No cell phones, no TV. They could use only Twitter and Facebook in their reporting. Host Liane Hansen speaks to Janic Tremblay of Radio Canada to find out how the experiment turned out.
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February 28, 2010 The Pacific Tsunami Warning Center in Hawaii has lifted its alert throughout the Pacific. The alert was issued to 53 countries after an 8.8-magnitude earthquake struck Chile early Saturday morning. Host Liane Hansen updates the latest on the aftermath of the Chilean earthquake and tsunami.
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February 28, 2010 With U.S. forces scheduled to begin withdrawal from Iraq this summer, Iraq must now take the lead in rebuilding itself. Iraqi scientists and engineers will hold the key to the future, and Iraqi women hope to be a part of that. Liane Hansen speaks to Dr. Alkazragy and Dr. Mustafa, two female Iraqi scientists who are visiting scholars at American universities. The doctors have asked that their first names be withheld for security concerns.
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February 28, 2010 Weather problems, a death on the luge track, organization issues and a disappointing medals performance. The Vancouver games have had their setbacks. But coming into the closing ceremony, Canadians have plenty of reasons to feel good.
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February 28, 2010 All is right with the world: Canada took the gold in the men's curling competition at the Winter Games in Vancouver. With Kevin Martin, the Michael Jordan of curling, in the lead, they beat Norway 6-3.
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February 28, 2010 American Steve Holcomb and his four-man "Night Train" sled made bobsled history at the Olympic sliding track in Whistler Saturday. They won the gold medal, something Americans haven't done in the sport in 62 years. The finish also adds to the record medal haul for Americans at a single Winter Olympics.
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February 28, 2010 Saturday's earthquake in Chile killed at least 300 people and has caused millions, if not billions of dollars in damage. Host Liane Hansen speaks with Chile's ambassador to the United States, Jose Goni, about the Chilean government's efforts to help those in need.
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15 minutes outside of Port-au-Prince, along the shoulder of National Road 2, a sign from the Department of Tourism instructs people not to throw garbage. But this site has now become a makeshift dump, where rubble from the Jan. 12 earthquake is piled as far as the eye can see.
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February 28, 2010 From the early days after the earthquake, planners have been trying to develop a long-term recovery plan to address some of Haiti's long-standing problems. But competing needs — rebuilding infrastructure, providing social services, restoring forests — are making it difficult to work out a comprehensive plan for recovery.
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Saul Goodman
|Saul Goodman
|Breaking Bad / Better Call Saul character
|First appearance
|"Better Call Saul"
|Created by
|Portrayed by
|Bob Odenkirk
|Full name
|James Morgan McGill
|Charles McGill (brother)
|Significant other(s)
|Kim Wexler
James Morgan "Jimmy" McGill, also known as Saul Goodman, is a fictional character in Breaking Bad and the titular character of its spin-off series Better Call Saul. He is portrayed by Bob Odenkirk and was created by series creator Vince Gilligan and Peter Gould, a writer on the series.[1] Saul is a criminal lawyer and can be easily found in the yellow pages of Albuquerque. Throughout Breaking Bad, he acts as Walter White and Jesse Pinkman's attorney and accomplice. His made-up name is a play on words to better attract clients: "'S'all good, man!" becomes the faux-Jewish "Saul Goodman". He is also known for his low-budget television commercials and print advertisements in Albuquerque, wherein he advertises mainly under the tagline "Better Call Saul!". For the first season of Better Call Saul, Odenkirk earned a Primetime Emmy Award for Outstanding Lead Actor in a Drama Series nomination.[2]
Character biography[edit]
Breaking Bad[edit]
Shortly after meeting Walter White, Saul reveals that his real name is not Goodman, and that he is actually Irish, not Jewish, as his name would imply. He explains that he has chosen his name because it sounded Jewish: "My real name's McGill. The Jew thing I just do for the homeboys. They all want a pipe-hitting member of the tribe, so to speak." [3] Saul claims to have had multiple wives in the past, one of whom he says he caught having sex with his stepfather. At a certain point, he developed a short-lived romantic relationship with his secretary.
Saul does business out of a highly stylized office in a cheap strip mall. With a repertoire that includes small-time drug busts, fraudulent insurance claims, class actions, and his overbearing manner, he might seem disreputable to police and certain other lawyers. However, despite his flamboyant appearance, Saul is a highly competent extra-legal operator, adept at sniffing out legal loopholes and able to negotiate good deals for his clients. He has deep ties with Albuquerque, New Mexico's most influential criminals, such as Gus Fring. He also employs the services of a veteran private investigator named Mike Ehrmantraut, who executes often illegal commands from Saul and Gus such as cleaning up crime scenes and bugging homes. Saul is not completely without integrity, however; he is shown to honor the ethics of his profession, particularly the attorney-client privilege, and is reluctant to involve himself with violence or murder.
Little is known of Saul's legal education. In one episode, a diploma is shown in Saul's office, indicating that "Saul Goodman" holds a Master of Arts degree in Political Science from the University of American Samoa. However, this is a fake credential, as Saul's last name is actually McGill. However, it was revealed in Better Call Saul that Saul actually attended this institution's accredited law school via a correspondence program.[4]
Saul is introduced in the season 2 episode "Better Call Saul". Walt and Jesse contact Saul, after Jesse points out to Walt that they don't need a "criminal lawyer" (as in a lawyer who defends criminals) but a "criminal lawyer" (as in a lawyer who is a criminal). Walter hires Saul to keep Jesse's associate Badger out of prison and goes to extreme lengths (including bribery, kidnapping, and a death threat) to ensure Saul prevents Badger from incriminating Walt.[3] Saul soon becomes a regular character on Breaking Bad.
Season 2[edit]
Following Badger's arrest for selling meth, Walt and Jesse contact Saul for legal representation, as Jesse knows him from successfully defending Emilio twice, and getting him released almost immediately from jail. Walt, posing as Badger's uncle "Mr. Mayhew", hires him to keep Badger out of prison. Unfortunately, while meeting Badger at the police station he catches a glimpse of DEA agents Hank Schrader and Steven Gomez, and deduces that they are interested in his client and plans to make a deal with the DEA for Badger to testify against his dealer "Heisenberg" (Walt's criminal alias). Walt offers Saul $10,000 to keep Badger from talking to the DEA, but Saul refuses, claiming to be "morally outraged." Walt and Jesse then take more desperate measures, kidnapping Saul at gunpoint and taking him to the desert to threaten him into keeping Badger from testifying. However, Saul quickly points out it would make more sense to have Badger killed in prison, but Walt and Jesse reject this solution. Recognizing "Mr. Mayhew" from Walt's hacking cough, he quickly offers to be their lawyer, accepting payment of six dollars on the spot to establish a confidential attorney-client relationship. To throw the DEA off Walt and Jesse's trail, Saul proposes the use of James Edward Kilkely (aka Jimmy "In-and-Out"), a man who fits Heisenberg's description and is a professional fall guy who takes the rap for other peoples' crimes for a fee. In exchange for $80,000 ($50,000 of which goes to Saul for a finders' fee) and a decoy pound of meth, Saul has Badger cooperate with the authorities and a sting operation leads to Jimmy's arrest. When Mike figures out who Walt is, Saul–intrigued by the DEA's interest in Walt's product–proposes that Walt hire him as his consigliere, in the same vein as Tom Hagen from The Godfather. Walt ultimately accepts the offer.[3]
In an effort to help pay for Walt's cancer treatment, his son Walter Jr. sets up the website, www.savewalterwhite.com,[5] which requests and collects donations. Saul tells Walt that it is a perfect opportunity to launder money. Saul arranges for a wave of fake donations drawn from Walt's drug money. When Jesse discovers that his girlfriend Jane Margolis has died in his bed from a heroin overdose, he contacts Walt, who contacts Saul. Saul sends Mike to clean up the crime scene and mitigate Jesse's involvement with Jane's death.[6]
Season 3[edit]
After Walt sells $1.2 million of meth to Gus Fring, Saul pushes Walt to take Gus's lucrative offer to continue cooking. Saul also accepts a job from Jesse, using Jesse's half of the earnings to purchase Jesse's parents' house at a dramatically lowered price, by strong-arming Jesse's parents and attorney with a potential lawsuit concerning the undisclosed meth lab Jesse was running out of the basement. [7]
After Walt reveals that his wife Skyler has threatened to expose him, Saul assures Walt that she wouldn't talk due to blowback on the family, but Saul secretly hires Mike to bug the Whites' house as insurance. Forced to leave early when Walt comes home, Mike witnesses the cartel hitmen Leonel and Marco Salamanca entering with an axe and quickly places a call to Gus to call them off. Per Gus' direction, Saul has not been informed of this threat to Walt. [8]
Mike later brings Walt to Saul after Walt creates a disturbance at Skyler's office, and attempts to talk Walt into cooking meth again. After Saul admits that he bugged Walt's house, Walt attacks and subsequently fires him. Furious, Saul stops laundering Walt's drug money. Jesse then approaches Saul with two bags of meth he has cooked himself using Walt's procedure, and asks to set up a deal. He meets with Gus' henchman Victor to make the exchange, only to see he has been given half of the money – the other half goes to Walt. [9] Saul sets up an intervention between Walt and Jesse, offering to give Walt a percentage of Jesse's future deals. Walt returns Jesse's half, coldly informing both of them that he has now accepted Gus' offer and will be cutting Jesse out of the business. Saul quickly dumps Jesse as a client in favor of the much higher profits Walt can produce, and once again goes to work laundering Walt's money – this time for a dramatically reduced percentage. [10]
When Hank deduces the existence of the RV Walt and Jesse use to cook meth, Walt calls Saul in a panic. Saul scolds him for not having a contingency plan. After Hank locates the RV with Walt and Jesse trapped inside, Walt calls Saul for assistance. Saul has his secretary Francesca masquerade as a cop to tell Hank that his wife Marie has been severely injured in a car accident to give Walt and Jesse time to destroy the RV. Saul later feels guilty for taking part in such a cruel ruse.[11]
After Walt murders two drug dealers and Jesse goes on the run, Mike storms into Saul's office and intimidates him into revealing Jesse's whereabouts. Saul gives Mike a fake address, however, and secretly meets with Walt and Jesse. He expresses dismay at having been put in a difficult position. [12]
Season 4[edit]
After Jesse murders cartel meth cook Gale Boetticher at the end of season three, Saul fears he will be next. He locks up his offices, puts a security guard at the door, and starts scanning his offices for bugging devices. [13]
Saul suggests to Skyler she should buy a laser tag business to launder Walt's drug money. Skyler dismisses the idea, and instead sets her sights on purchasing the car wash Walt has previously worked for. When the owner Bogdan refuses to sell, Skyler and Walt ask Saul for help. Saul suggests they accuse Bogdan of harboring al-Qaeda terrorists, but Walt dismisses that plan, reasoning that Bogdan is not an Arab. Eventually, they concoct a plan to force Bogdan to sell: Skyler hires Saul's henchman Kuby to perform a fake environmental audit on the car wash and threaten to shut it down, forcing Bogdan to sell for a relatively low price. [14]
When Walt says that he fears his meth business will go under, Saul mentions that he knows someone who can, for a fee, arrange for him to disappear and start over with a new identity. Walt rejects this idea.[15]
When Walt angrily blows up the Dodge Challenger he'd bought for Walt Jr. but which Skyler insisted Walt return, Saul helps deal with the legal consequence and cover up the incident. After paying Saul for his services, Walt asks for a list of hit men he could hire to kill Gus. Saul advises against it since Mike knows all of the contacts, and hiring outside of his network carries the risk of encountering undercover cops. [16]
Meanwhile, Skyler's former boss and lover Ted Beneke tells her that his business is being audited for tax fraud. Since Skyler was his bookkeeper, she could also be implicated. At the audit, Skyler acts completely ignorant of accounting practices. The IRS agent, believing the fraud was simply a mistake, orders Ted to pay back taxes and fines. Ted, however, refuses to comply. Skyler, against Saul's advice, arranges for Ted to receive enough money to pay his IRS debt by having Saul manufacture a fake relative who leaves Ted a sizable inheritance. When Saul follows up, he finds that Ted is not using the money to pay the IRS. With no other options, Skyler has Saul's men—Huell and Kuby—force Ted to write the check. They succeed, but in Ted's attempt to flee, he trips and seriously injures himself.[17]
Gus coerces Walt into a meeting, where he informs him that he is going to kill Hank to cover their tracks, and threatens to kill Walt and his family if he tries to intervene. Walt barges into Saul's office and takes him up on his earlier offer to go into hiding. Walt also asks Saul to anonymously tip the DEA that Hank is being targeted. Saul eventually agrees, provided Gus' name isn't mentioned. Afterward, Saul gives Jesse back his money and prepares to flee Albuquerque temporarily until the fallout between Walt and Gus is over.[17]
Season 5[edit]
In the fifth season, it is revealed that Saul tasked Huell to pickpocket a ricin-filled cigarette from Jesse, but didn't know that Walt would use it to poison Jesse's girlfriend's son Brock.[18] Saul attempts to end his partnership with Walt, but Walt backs him into a corner and intimidates him back into compliance. As Walt, Jesse, and Mike set up their own meth operation in the vacuum left by Gus's demise, Saul helps them find a meth lab and equips them with a team led by Todd Alquist. [19] Saul helps Mike when the DEA comes close to catching him.[20]
Jesse asks Saul to deliver his share of the drug money to Mike's granddaughter and the family of Drew Sharp, a child shot by Todd for witnessing a train heist, but Saul refuses.[21] After Hank discovers that Walt is Heisenberg, Saul advises Walt to kill his brother-in-law, a suggestion Walt angrily rejects.[22] Later, when Jesse is picked up by the police and interrogated by Hank, Saul bails him out of custody. After arranging a meeting between Walt and Jesse to discuss how to handle Hank's investigation, Saul arranges with his contact to set Jesse up with a new identity far away from Albuquerque. However, Jesse realizes Saul's complicity in Brock's poisoning and beats a confession out of him. Saul subsequently advises Walt to call in a hit on Jesse.[18]
After Hank and Gomez are killed and Walt's criminality is exposed, Saul decides to set himself up with a new identity. He and Walt spend several days in a basement together while Saul's extractor, Ed, makes the necessary arrangements. Walt asks Saul to help him find hitmen to kill Hank's murderers, but Saul instead advises Walt to turn himself in to avoid a lengthy and humiliating federal investigation against Skyler. Walt again attempts to threaten Saul into complying, but breaks down in a coughing fit. With his transportation ready, Saul leaves Walt and heads for a new life in Omaha, Nebraska.[23]
Better Call Saul[edit]
In April 2013, it was announced that a spin-off series focusing on Saul is being developed by Breaking Bad creator Vince Gilligan and writer Peter Gould; the latter wrote the episode that introduced the character. Gilligan had considered it in a July 2012 interview: "I like the idea of a lawyer show in which the main lawyer will do anything it takes to stay out of a court of law. He'll settle on the courthouse steps, whatever it takes to stay out of the courtroom. That would be fun—I would like that."[24] In early TV commercials Saul Goodman claims to represent clients in personal injury, car accidents, traffic tickets, drug dealing, bond fraud, DUI and slip and fall accidents.[25] In July 2013, Gilligan commented that the series had yet to be green-lit but he and Gould are "full speed ahead on trying to get going." In developing the series, they were considering making it a half-hour show with a comedic tone but said that they might still choose to go with a one-hour drama like Breaking Bad and would not reveal whether it would be a prequel or sequel series until after Breaking Bad finished its run.[26]
On September 11, 2013, it was announced that the series had been approved by AMC and given the confirmed title Better Call Saul, and is a prequel in a one-hour format.[27] The series premiered on February 8, 2015 on AMC.[28]
Season 1[edit]
|This section may be too long to read and navigate comfortably. (February 2015)
|This section needs additional citations for verification. (February 2015)
As he predicted, Saul – now going by the alias Gene – is managing a Cinnabon in Omaha, Nebraska, but is afraid someone from his past will discover him.
The series starts in 2002, when Saul, operating under his real name Jimmy McGill, is an underpaid public defender working difficult cases and defending hopeless clients in the Albuquerque court system, although he originally hails from Cicero, Illinois. His office, which doubles as his home, is located in the back of a nail salon, and he is desperate for actual clients. Jimmy also takes care of his older brother Charles "Chuck" McGill, formerly a powerful lawyer and partner in the law firm Hamlin, Hamlin & McGill (HHM) that is housebound by sudden onset of electromagnetic hypersensitivity that Jimmy secretly believes is a psychological breakdown; he often asks name partner Howard Hamlin to cash out Chuck's share of $17 million because he does not believe he will ever return to work, but Howard believes he will. Jimmy is friends with his ex-girlfriend Kim Wexler, who is a lawyer at HHM and provides him with inside information.
Jimmy receives a promising phone call from two prospective clients, County Treasurer Craig Kettleman and his wife, Betsy, who are accused of stealing $1.6 million from the county treasury, but they go with HHM. Desperate for their business, Jimmy enlists the help of twin con artists Lars and Cal, revealing he was a con artist nicknamed "Slippin' Jimmy," who feigned falls in front of businesses to get money; he went straight after Chuck pulled strings to get him out of prison on an indecent exposure charge relating to an incident where Jimmy defecated in the open sunroof of an a man named Chet who wronged him, not knowing children were inside. Jimmy was given a job in the mail room of HHM, got a law degree from the University of American Samoa, and passed the state bar exam. However, Howard refused to hire him, and Jimmy is still bitter at him for it.[29]
The plan is for the twins to jump in front of Betsy's car and Jimmy will save her from the scam, winning her trust. The twins incorrectly target a car driven by an elderly woman, and the trio are driven out to the desert to be killed by the woman's grandson, Tuco Salamanca. A hysterical Jimmy reveals the con aimed at the Kettlemans, which makes one of Tuco's lieutenants, Ignacio "Nacho" Varga, convince Tuco to let everyone go, but Nacho later meets with Jimmy and tells him he needed him alive for help in robbing the Kettlemans of the money for himself. Jimmy refuses, but Nacho senses Jimmy will eventually succumb to his criminal urges.
Jimmy anonymously warns the Kettlemans, who go missing soon after with their house ransacked. Nacho is arrested when a neighbor saw his van parked in front of the Kettlemans' house, but he proclaims innocence and names Jimmy his lawyer, threatening him with death if he is not released. Jimmy concludes the Kettlemans staged the whole thing and actually ran away. Mike – who is working as the courthouse parking lot attendant and often argues with Jimmy about parking validation – believes him and hints the Kettlemans are likely hiding near their house; sure enough, Jimmy finds them camping in the wilderness behind their home with the stolen money.[30] The Kettlemans bribe Jimmy to assure his silence. Nacho is released, but he accuses Jimmy of informing the Kettlemans and threatens repercussions.
Using the bribe money, Jimmy plans to buy an office. He exacts revenge upon Howard for earlier asking him not to use the McGill name for his business by advertising on a billboard in an ad that copies HHM's look. Howard orders Kim to serve Jimmy a cease and desist, so Jimmy organizes a filmed publicity stunt while the billboard is being taken down that makes it look like he saved the life of the billboard worker.[31] The stunt gets Jimmy new clients that do not pan out (including a rancher who wants to have his property secede from the United States; and a family dad who has invented a toilet meant to spout words of encouragement to kids who need toilet-training only said phrases end up sounding sexual in nature), but after he drafts a will for an elderly woman, Kim encourages him to pursue elder law. Chuck is hospitalized from being tasered by police after stealing a neighbor's newspaper to discover Jimmy's stunt. The doctor recommends committing Chuck, but Howard convinces the DA to make sure that Chuck is not committed. Jimmy realizes that if Chuck were committed, he would become his legal guardian and thus have the authority to request and receive Chuck's severance payment from HHM, but decides against it.
Mike requests Jimmy to be his lawyer after detectives from Philadelphia question him about the murder of two police officers, but he just needs Jimmy to spill coffee on one of the detectives so he can steal their notes. Jimmy does so after initially refusing, and he wonders how Nacho and Mike instinctively sensed he had a criminal streak.[32] Meanwhile, Kim is demoted after the Kettlemans refuse a plea deal and they return to Jimmy, threatening to expose the bribe if he does not get Craig fully exonerated. Feeling guilty about Kim, Jimmy has Mike break into the Kettlemans home to steal the money; although the $1.6 million is his for the taking, Jimmy feels he must do the right thing and hand it to the authorities. Jimmy admits to the Kettlemans that the money and his bribe money is with the DA, and they cannot blackmail him because Betsy is guilty of bribery and she would also be arrested. Craig decides to admit guilt and accept Kim's plea deal, saving her career but ruining Jimmy's.[33]
Jimmy enters elder law and visits numerous nursing homes to network. He discovers that nursing home Sandpiper Crossing controls the pension and Social Security of their residents by giving them a monthly allowance after deducting fees and putting the rest in savings. Jimmy analyzes Sandpiper's invoices and finds evidence of Sandpiper systematically overcharging, making them guilty of fraud and forming grounds for a class action lawsuit. Sandpiper bans Jimmy from the premises, so he resorts to rummaging through its dumpster in an effort to find shredded documents, eventually finding an incriminating one. With a solid case against Sandpiper, Chuck decides to become Jimmy's co-counsel and assist him in the case. Sandpiper Crossing's attorneys agree to meet, and although they deny that the home is defrauding its residents, they concede that some of them were overcharged and are willing to compensate. However, Jimmy presents evidence of Sandpiper Crossing engaging in illicit interstate commerce, making them eligible for a RICO lawsuit. Chuck demands that Sandpiper Crossing pay $20 million in settlement fees, which the attorneys refuse. The case invigorates Chuck and he finds himself able to leave the house.
Chuck convinces Jimmy to refer the case to HHM due to its sheer size. Howard offers to give Jimmy a monetary reward, but still refuses to hire him or let him work on the case. Feeling cut out, Jimmy does not release the case to HHM. The next day, Jimmy informs Chuck that he will accept Howard's deal after all, having discovered that Chuck used his phone in the middle of the night to call Howard before their meeting. Jimmy deduces that Chuck called Howard to cut him out of the case, and also deduces that it was Chuck, not Howard, who had been keeping him out of HHM since the beginning - Jimmy accuses Chuck of this, who admits to it being true, and who in turn accuses Jimmy of not being a "true" lawyer and says Jimmy could never be an associate for HHM, as he has not changed from being "Slippin' Jimmy", and a con man with a law degree is dangerous. Feeling hurt and betrayed that Chuck still considers him a crook after how hard he worked to straighten out and take care of him, Jimmy cuts ties with him.[34]
After suffering a nervous breakdown while ranting to a bingo parlor about the state of his life, Jimmy returns to Cicero, Illinois for a sabbatical. He is reunited with his partner-in-crime Marco Pasternak and they start scamming people again. Marco tempts him to stay, but concern for his elderly clients, Chuck, and a job offer from the law firm of Davis & Mane in Santa Fe sways Jimmy to return to New Mexico. Marco dies of a heart attack during one last con, his final words telling Jimmy how happy he was doing what they are best at since he was miserable in his legitimate job. Later wearing Marco's gold ring and remembering his last words, Jimmy ultimately decides not to take the job with Davis & Mane, as he no longer feels obliged to "do the right thing".[35]
- ^ "Vince Gilligan Talks BREAKING BAD, the Saul Goodman Spinoff, the Behind-the-Scenes Documentary, and More". Collider. 2013-09-13. Retrieved 2013-09-23.
- ^ Hipes, Patrick (July 16, 2015). "Emmy Nominations 2015 – Full List". Deadline.com. Retrieved July 16, 2015.
- ^ a b c "Better Call Saul". Breaking Bad. Season 2. Episode 8. April 26, 2009. AMC.
- ^ "RICO". Better Call Saul. Season 1. Episode 8. March 23, 2015. AMC.
- ^ www.savewalterwhite.com
- ^ "Phoenix". Breaking Bad. Season 2. Episode 12. May 24, 2009. AMC.
- ^ "Caballo Sin Nombre". Breaking Bad. Season 3. Episode 2. March 28, 2010. AMC.
- ^ "I.F.T". Breaking Bad. Season 3. Episode 3. April 4, 2010. AMC.
- ^ "Green Light". Breaking Bad. Season 3. Episode 4. April 11, 2010. AMC.
- ^ "Más". Breaking Bad. Season 3. Episode 5. April 10, 2010. AMC.
- ^ "Sunset". Breaking Bad. Season 3. Episode 6. April 25, 2010. AMC.
- ^ "Full Measure". Breaking Bad. Season 3. Episode 13. June 13, 2010. AMC.
- ^ "Box Cutter". Breaking Bad. Season 4. Episode 1. July 17, 2011. AMC.
- ^ "Open House". Breaking Bad. Season 4. Episode 3. July 31, 2011. AMC.
- ^ "Cornered". Breaking Bad. Season 4. Episode 6. August 21, 2011. AMC.
- ^ "Problem Dog". Breaking Bad. Season 4. Episode 7. August 28, 2011. AMC.
- ^ a b "Face Off". Breaking Bad. Season 4. Episode 12. October 9, 2011. AMC.
- ^ a b "Confessions". Breaking Bad. Season 5. Episode 11. August 25, 2013. AMC.
- ^ "Hazard Pay". Breaking Bad. Season 5. Episode 3. July 29, 2012. AMC.
- ^ "Buyout". Breaking Bad. Season 5. Episode 6. August 19, 2012. AMC.
- ^ "Blood Money". Breaking Bad. Season 5. Episode 9. August 11, 2013. AMC.
- ^ "Buried". Breaking Bad. Season 5. Episode 10. August 18, 2013. AMC.
- ^ "Granite State". Breaking Bad. Season 5. Episode 11. September 22, 2013. AMC.
- ^ Andreeva, Nellie (April 9, 2013). "AMC Eyes 'Breaking Bad' Spinoff Toplined By Bob Odenkirk". Deadline.com. Retrieved January 20, 2015.
- ^ "Is Saul Goodman a Car Accident or Personal Injury Lawyer?". David Azizi Legal Blog. 2014-09-12.
- ^ O'Neal, Sean (2013-07-03). "Breaking Bad spinoff that was in development now in super-serious development". The A.V. Club. Retrieved 2013-09-23.
- ^ O'Neal, Sean (2013-09-11). "Breaking Bad's prequel spinoff about Saul Goodman is basically a go at AMC". The A.V. Club. Retrieved 2013-09-23.
- ^ Roots, Kimberly (November 20, 2014). "Better Call Saul Gets Two-Night February Premiere on AMC". TVLine. Retrieved November 20, 2014.
- ^ "Mijo". Better Call Saul. Season 1. Episode 2. February 9, 2015. AMC.
- ^ "Nacho". Better Call Saul. Season 1. Episode 3. February 16, 2015. AMC.
- ^ "Hero". Better Call Saul. Season 1. Episode 4. February 23, 2015. AMC.
- ^ "Five-O". Better Call Saul. Season 1. Episode 9. March 9, 2015. AMC.
- ^ "Bingo". Better Call Saul. Season 1. Episode 7. February 23, 2015. AMC.
- ^ "Pimento". Better Call Saul. Season 1. Episode 9. March 30, 2015. AMC.
- ^ "Marco". Better Call Saul. Season 1. Episode 10. April 6, 2015. AMC.
Further reading[edit]
- Josh Ralske (August 7, 2013). "'Better Call Saul!' The Best of Saul Goodman on Breaking Bad". TWC Central.
External links[edit]
- Saul Goodman – official site
- Saul Goodman at AMC
- Saul Goodman at the Internet Movie Database
- Better Call Saul
- Breaking Bad characters
- Fictional American people of Irish descent
- Fictional alcohol abusers
- Fictional antiheroes
- Fictional characters from Illinois
- Fictional characters from New Mexico
- Fictional characters introduced in 2009
- Fictional consiglieri
- Fictional lawyers
- Fictional characters who became a protagonist in a spin-off


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YODEL Delivery service, still utter crap! why?!
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24-03-2013, 12:10
Ginger Nut
Forum Member
Join Date: Feb 2006
Posts: 14,441
Originally Posted by
Where i live its been sunny intervals all day its no less than 4 degrees and no snow in sight.
Also why does that mean they can pretend they attempted a delivery !
I did wonder if you might live somewhere the weather has been alright. I suppose it is possible the item bounced thru a regional depot affected by the weather.
However, I didn't read your OP completely to see they'd claimed delivery. In light of that then it's just down to their legendary shitness then.
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In this handout photo provided by NASA, the space shuttle Enterprise... News PhotoAirport,Arm Sling,Kennedy Airport,NASA,New York City,Photography,Science and Technology,Space,Space Exploration,Space Shuttle,USA,Vertical,YellowPhotographer HandoutCollection: Getty Images News 2012 Getty ImagesNEW YORK, NY - MAY 13: In this handout photo provided by NASA, the space shuttle Enterprise is held aloft by a yellow sling and a set of cranes after it was removed from the top of NASA's 747 Shuttle Carrier Aircraft early Sunday morning on May 13, 2012 at John F. Kennedy (JFK) International Airport in New York City. The 747 was towed backwards so that Enterprise could be lowered. The shuttle will be placed on a barge that will move by tugboat up the Hudson River to the Intrepid Sea, Air & Space Museum in June. The shuttle will be lifted by crane and placed on the flight deck of the Intrepid, where it will be on exhibit to the public starting this summer in a temporary climate-controlled pavilion. (Photo by Kim Shiflet/NASA via Getty Images)


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Digital mammography is one of the most promising options to diagnose breast cancer which is the most common cancer in women. However, its effectiveness is enfeebled due to the difficulty in distinguishing actual cancer lesions from benign abnormalities, which results in unnecessary biopsy referrals. To overcome this issue, computer aided diagnosis (CADx) using machine learning techniques have been studied worldwide. Since this is a classification problem and the number of features obtainable from a mammogram image is infinite, a feature selection method that is tailored for use in the CADx systems is needed.
We propose a feature selection method based on multiple support vector machine recursive feature elimination (MSVM-RFE). We compared our method with four previously proposed feature selection methods which use support vector machine as the base classifier. Experiments were performed on lesions extracted from the Digital Database of Screening Mammography, the largest public digital mammography database available. We measured average accuracy over 5-fold cross validation on the 8 datasets we extracted.
Selecting from 8 features, conventional algorithms like SVM-RFE and multiple SVM-RFE showed slightly better performance than others. However, when selecting from 22 features, our proposed modified multiple SVM-RFE using boosting outperformed or was at least competitive to all others.
Our modified method may be a possible alternative to SVM-RFE or the original MSVM-RFE in many cases of interest. In the future, we need a specific method to effectively combine models trained during the feature selection process and a way to combine feature subsets generated from individual SVM-RFE instances.
Applications of artificial intelligence and machine learning techniques in medicine are now common and computer aided diagnosis (CADx) systems are one of those successful applications. Breast cancer, the most common cancer in women and second largest cause of death [1], is the disease which CADx systems are expected to be employed most successfully. To apply CADx systems, various imaging methods are available to reflect the inside tissue structure of breasts. Digital mammography using low-dose x-ray is one of those methods and is the most popular one worldwide. It has advantages over other methods such as sonar or magnetic resonance imaging (MRI) due to low cost and wide availability [2]. With digital mammography devices, doctors are able to find abnormal lesions which cannot be recognized using clinical palpation on breasts. CADx systems are applied on those images to detect and diagnose abnormalities. Since the early detection of breast cancer is important to ensure successful treatment of the disease, recent advances in research community have concentrated on improving the performance of CADx systems. Improvements in CADx systems can be obtained by solving two classification tasks: (1) detect more abnormalities or (2) distinguish actual malignant cancers from benign ones. Detecting abnormalities from a digitized mammogram is a relatively easy task and many improvements have been achieved while the latter is still a major area of research [3]. To achieve better performance, both classic and modern machine learning approaches such as Bayesian networks [4], artificial neural networks [5,6] and support vector machines (SVMs) [5,7] have been applied. However, the performance of CADx systems is still not as high as required for practical usage. This problem can be partially solved by using a better feature selection method that optimally fits to the mammogram classification problem [3].
We propose a new feature selection method for SVMs in this paper. Our method is based on SVM-Recursive Feature Elimination (SVM-RFE) [8] and its ensemble variant Multiple SVM-RFE [9]. We have conducted a comparison of the classification performance with baseline methods and two other SVM-RFE based feature selection methods, JOIN and ENSEMBLE, proposed by other groups [10]. To compare performances of methods, we prepared a dataset consisting of mass and calcification lesions extracted from Digital Database of Screening Mammography (DDSM) [11], the largest publicly available mammogram database.
Let us suppose that a data set consists of N examples x1,..., xN each of which has P features {1,..., P}.
Let xn = (x1, n,..., xP, n) be the n-th example where n ∈ {1,..., N}, and the i-th feature value, i ∈ {1,..., P}, of the n-th example is denoted by xi, n. Class labels of the N examples will be denoted by y = (y1,..., yN).
In this paper, we only consider a binary classification problem because we are interested in distinguishing benign and malignant examples. Overall, the labeled data set is expressed as {(x1, y1),..., (xN, yN)}.
SVM is one of the most popular modern classification methods. Based on the structural risk minimization principal, SVM defines an optimal hyperplane between samples of different class labels. The position of the hyperplane is adjusted so that the distance from the hyperplane to a nearest sample, or margin, is maximized.
Moreover, if the SVM cannot define any hyperplane that separates examples in linear space, it can use kernel functions to send examples to any kernel space where the hyperplane can separate examples. Although we can use any kernel function meeting Mercer's Theorem for SVM, we consider widely-used the linear and Gaussian radial basis function (RBF) kernels only in this research.
SVM is a powerful classification method but it has no feature selection method. Therefore, a wrapper-type feature selection method, SVM-RFE, was introduced [8]. SVM-RFE generates ranking of features by computing information gain during iterative backward feature elimination. The idea of information gain computation is based on Optimal Brain Damage (OBD) [12]. In every iterative step, SVM-RFE sorts the features in working set in the order of difference of the obejective functions and removes a feature with the minimum difference. Defining IG(k) as information gain when k-th feature is removed, overall iterative algorithm of SVM-RFE is shown in Algorithm 1.
ENSEMBLE and JOIN
SVM-RFE [8] has two parameters that need to be determined. The first parameter decides how many features should be used to obtain best performance. The second parameter specifies what portion of features should be eliminated in each iteration. To resolve this issue, a simple approach can be easily
Algorithm 1 SVM-RFE
Require: Feature lists R = [] and S = [1,..., P]
1: while S ≠ [] do
2: Train a SVM with features in S
3: for all k-th feature in S do
4: Compute IG(k)
5: end for
6: e = arg mink(IG(k))
7: R = [e, R]
8: S = S - [e]
9: end while
10: return R
implemented. First, we separate given training set into a partial training set and a hold-out set. Then, we apply Algorithm 2 with some parameter 'threshold'.
Score of each feature subset Ro is computed as
where err(Ro) is the error of SVM trained using Ro and tested with hold-out set. Using this method, we can obtain a feature subset R which yields reasonably small amount of error on trained dataset. Utilizing this algorithm as base, Jong et al. [10] proposed two methods, ENSEMBLE and JOIN to combine multiple rankings generated by SVM-RFE as in Algorithm 3 and 4.
In this paper, we used 25% of training set as hold-out set and used same sets of thresholds and cutoffs as in [10], i.e., {0.2, 0.3, 0.4, 0.5, 0.6, 0.7} and {1, 2, 3, 4, 5}.
Algorithm 2 SVM-RFE(threshold)
Require: Ranked feature lists R = [], Ri = [] where i = 1,..., P and S' = [1,..., P]
1: i = 1
2: while S' ≠ [] do
3: Train an SVMs using a partial trainset with features in S'
4: for all features in S' do
5: Compute ranking of features as in SVM-RFE
6: end for
7: Ri = S'
8: Eliminate threshold percent of lesser-important features from S'
9: i = i + 1
10: end while
11: R = Ro where Ro yields minimum score on hold-out set.
12: return R
Algorithm 3 ENSEMBLE(v1, v2,.., vk)
1: for threshold v ∈ {v1, v2,..., vk} do
2: Rv = SVM-RFE(v)
3: end for
4: return a majority vote classifier using SVMs trained by .
Algorithm 4 JOIN(cutoff, v1, v2,..., vk)
1: for threshold v ∈ {v1, v2,..., vk} do
2: Rv = SVM-RFE(v)
3: end for
4: R = features selected at least cutoff times in {}
5: return a SVM trained with R
Multiple SVM-RFE with bootstrap
Multiple SVM-RFE (MSVM-RFE) [9] is a recently introduced SVM-RFE-based feature selection algorithm. It exploits an ensemble of SVM classifiers and cross validation schemes to rank features. First, we make T subsamples from the original training set. Then, supposing that we have T SVMs trained using different subsamples, we calculate the corresponding discriminant information gain associated with each feature of each SVM. To compute this information gain, we use the same method as in SVM-RFE [8]. Exploiting the objective function of SVM, and its Lagrangian solution λ, we can derive a cost function
where H is a matrix with elements yqyrK(xq, xr) and 1 is a N dimensional vector of ones while K(·) is a kernel function and 1 ≤ q, r ≤ N. Since we are looking for the subset of features that has the best discriminating power between classes, we compute the difference in cost function for each elimination of i-th input feature, leaving Lagrangian multipliers unchanged. Therefore, the ranking for the i-th feature of j-th SVM can be defined as
where H(-i) denotes that i-th feature was removed from all elements in H. Then, considering DJj as a weight vector of features for j-th SVM, we normalize all T weight vectors such as DJj = DJj/||DJj||. This gives us T weight vectors each with P elements. Here, each element in the vector stands for a information gain achieved by eliminating the corresponding feature. After normalizing weight vectors for each SVM, we can compute each feature's ranking score
with μi and σi defined as:
The algorithm then applies this method to the training set with k-fold cross validation scheme. If we perform 5-fold cross validation and generate 20 subsamples in each fold, we will eventually have T = 100 SVMs to combine. The overall MSVM-RFE algorithm is described in Algorithm 5.
Algorithm 5 MSVM-RFE
Require: Ranked feature lists R = [] and S' = [1,..., P]
1: while S' ≠ [] do
2: Train T SVMs using T subsamples with features in S'
3: for all j-th SVM 1 ≤ j ≤ T do
4: for all i-th feature 1 ≤ i ≤ P do
5: Compute DJji
6: end for
7: Compute DJj = DJj/||DJj||
8: end for
9: for all feature l ∈ S' do
10: Compute cl using Equation (1)
11: end for
12: e = arg minl(c(l)) where l ∈ S'
13: R = [e, R]
14: S' = S' - [e]
15: end while
16: return R
One should note that original MSVM-RFE proposed in [9] uses cross-validation scheme when generating subsamples. However, we omitted this step because combining boosting into the original MSVM-RFE algorithm with cross-validation scheme is very complex and may confuse the purpose of this study.
Multiple SVM-RFE with boosting
When making subsamples, original MSVM-RFE uses the bootstrap approach [13]. This ensemble approach builds replicates of the original data set S by random re-sampling from S, but with replacement N times, where N is the number of examples. Therefore, each example (xn, yn) may appear more than once or not at all in a particular replicate subsample. Statistically, it is desirable to make every replicate differ as much as possible to gain higher improvement of the ensemble. The concept is both intuitively reasonable and theoretically correct. However, as the architecture of MSVM-RFE uses simple bootstrapping, it naturally follows that utilizing another popular ensemble method, boosting [14], instead of bootstrapping for two reasons. First, boosting outperforms bootstrapping on average [15,16], and secondly, boosting of SVMs generally yields better classification accuracy than bootstrap counterpart [17]. Therefore, to make use of ensemble of SVMs effectively, it may be worthwhile to use boosting instead of bootstrapping. For this reason, we applied AdaBoost [14], a classic boosting algorithm, to MSVM-RFE algorithm instead of bootstrapping in this work.
Unlike the simple bootstrap approach, AdaBoost maintains weights of each example in S. Initially, we assign same value of weight to n-th example D1(n) = 1/N where 1 ≤ n ≤ N. Each iterative process consists of four steps. At first, the algorithm generates a bootstrap subsample according to weight distribution at t-th iteration Dt. Next, it trains an SVM using the subsample. Third, it calculate the error using the original example set S. Finally it updates the weight value so that the probability of correctly classified examples is decreased while that of incorrect ones is increased. This update procedure makes next bootstrap pick more incorrectly classified examples, i.e. difficult-to-classify examples than easy-to-classify ones. The iterative re-sampling procedure MAKE_SUBSAMPLES() using AdaBoost algorithm is described in Algorithm 6.
Algorithm 6 MAKE_SUBSAMPLE
Require: S = {(xn, yn)}, D1(n) = 1/N, n = 1,..., N;
1: for j = 1 to T do
2: Build a bootstrap Bj = {(xn, yn)|n = 1,..., N} based on weight distribution Dj
3: Train a SVM hypothesis hj using Bj
5: if ϵj≥ 0.5 then
6: Goto line 2
7: end if
8: αj = (1/2)ln((1 - ϵj)/ϵj), αj ∈ R
9: Dj+1(n) = (Dj(n)/Zj) × exp(-αjynhj(xn)) where Zj is a normalization factor chosen so that Dj+1 also be a probability distribution
10: end for
11: return Bj, αj where 1 ≤ j ≤ T
In addition to modifying re-sampling method, we made a change in ranking criterion of original MSVM-RFE. In this MSVM-RFE with Boosting method, the weight vector DJj of j-th SVM undergoes one more process between normalization and feature ranking score calculation. Since the contribution of each SVM in ensemble to the overall classification accuracy is unique, we multiply another weight factor to the normalized feature weight vector DJj. The new weight factor is obtained from the weight of hypothesis classifier calculated during the re-sampling process of AdaBoost. By multiplying this weight αj to DJj, we can grade the overall feature weight more coherently. The overall iterative algorithm of MSVM-RFE with AdaBoost is described in Algorithm 7.
Algorithm 7 MSVM-RFE with AdaBoost
Require: Ranked feature lists R = [] and S'= [1,..., P]
1: MAKE_SUBSAMPLES(Bt, αt); t = 1,..., T
2: while S' ≠ [] do
3: Train T SVMs using Bt, with features in set S'
4: Compute and normalize T weight vectors DJj as in MSVM-RFE where 1 ≤ j ≤ T
5: for j = 1 to T do
6: DJj = DJj × ln(αj)
7: end for
8: for all feature l ∈ S' do
9: Compute the ranking score cl using Eq. (1)
10: end for
11: e = argminl(cl) where l ∈ S'
12: R = [e, R]
13: S' = S' - [e]
14: end while
15: return R
Note that we took logarithm of hypothesis weights instead of raw values in order to avoid radical changes in ranking criterion. Since boosting algorithm overfits by nature and SVM, the base classifier, is relatively strong classifier, the error rate of hypothesis increases drastically as iteration in MAKE_SUBSAMPLES() progresses. We have witnessed this overfitting problem by preliminary experiment and solved the problem by taking logarithm to the hypothesis weight. Computation time of MSVM-RFE with boosting can also be explained here. From our experiments, we found that there is no significant difference between the original MSVM-RFE and MSVM-RFE with boosting as the number of subsamples generated by MAKE_SUBSAMPLES() decreases.
Lastly, unlike the conventional boosting algorithm application, we only exploit bootstrap subsamples generated by the algorithm and dismiss trained SVMs for the following reasons:
• We are primarily interested in feature ranking and not the aggregation of weak hypotheses.
• Since we are using SVM-RFE for eventual classification method, this require a certain criterion to pick appropriate number of features from different boosted models.
In preliminary experiments using same number of features and simple majority-voting aggregation, SVM-RFE using boosted models did not show significance in accuracy improvement. However, we could find some evidences that ensemble of SVMs can be useful in mammogram classification.
In this section, we first describe dataset, features and experimental framework we used. Then we draw results of the experiments including analysis on them.
The DDSM database provides about 2500 mammogram cases that were gathered from 1988 to 1999. Four U.S. medical institutions offered the data to construct DDSM. This includes Massachusetts General Hospital (MGH), Wake Forest University School of Medicine (WFUSM), Sacred Heart Hospital (SHH) and Washington University in St. Louis (WU). All mammogram cases we used in this paper contain one or more abnormalities which can be classified into benign or malignant group following their biopsy results. Table 1 summarizes the statistics of abnormalities from each digitizer type and institution.
Table 1. Dataset Information
Mammogram data from DDSM were gathered and preprocessed through the following steps. First, we extracted meta information from text file in the database. These features are based on Breast Imaging Reporting and Data System (BI-RADS) introduced by the American College of Radiology [18]. Table 2 summarizes these encoded features. We employed a rank ordering system proposed by other group when encoding these features [19]. Next, we computed statistical features that are popular in image processing community. The statistical features are computed using intensity level of pixels in the region of interest in each case. We used same features which are used in another study [6] and the exact formulas are described in [20]. We also normalized these statistical features after extracting because their raw values were too big compared to BI-RADS features and to facilitate SVM to train efficiently with respect to time.
Table 2. BI-RADS mammographic features
Performance comparison
In sum, we prepared a total of 16 datasets each with 8 and 22 features, from each mass and calcification lesion of each institution. All SVM-RFE based methods are tested using 5-fold cross validation on each dataset. We computed area under Receiver Operating Characteristic (ROC) curves (Az) using the output of SVMs and feature ranking produced by each method.
Before comparing the methods explained in the previous section, we did some preliminary experiments comparing different kernels and parameters to find optimal kernel and parameters. The result of this experiment is summarized in Table 3 and Table 4. We used the best-performing parameter and kernel (radial basis function, or RBF) from this experiment of this study.
Table 3. Comparison of kernels in terms of maximum Az value of mass dataset
Table 4. Comparison of kernels in terms of maximum Az value of calcification dataset
The overall performance comparison result is summarized from Table 5 through Table 8. Note that numbers in parenthesis of JOIN methods are cutoff values used. Analyzing the result, it is clear that the MSVM-RFE based methods outperforms baseline classifiers, SVM and other SVM-RFE feature selection methods, ENSEMBLE and JOIN in the majority of cases although SVM-RFE dominated in 4 out of 16 datasets. Comparing the two MSVM-RFE based algorithms, we could find that MSVM-RFE with boosting can achieve better or at least competitive performance especially in datasets with 22 features. In 3 out of 4 mass datasets, MSVM-RFE with boosting outperformed any other methods under consideration. Although the original MSVM-RFE method yielded the best performance in 3 out of 4 calcification datasets, we think the MSVM-RFE with boosting has yet more margin to be improved as we already mentioned in the previous chapter. Any method that can effectively exploit the trained SVMs during feature selection progress may be the future key improvement for MSVM-RFE with boosting.
Table 5. Comparison of methods by maximum Az value using 8 features (Mass)
Table 6. Comparison of methods by maximum Az value using 8 features (Calcification)
Table 7. Comparison of methods by maximum Az value using 22 features (Mass)
Table 8. Comparison of methods by maximum Az value using 22 features (Calcification)
In this paper, a new SVM-RFE based feature selection method was proposed. We conducted experiments on real world clinical data, and compared our method with baseline and other feature selection methods using SVM-RFE. Results show that our method outperforms in some cases and is at least competitive to others in other cases. Therefore, it can be a possible alternative to SVM-RFE or the original MSVM-RFE. Future works include investigation of specific methods to effectively combine models trained during the feature selection process and ways to combine feature subsets generated from individual SVM-RFE instances.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
SY carried out the study, designed and implemented the algorithms, conducted experiments and drafted this manuscript. SK supervised and instructed all research progress, and participated in the algorithm design and critical analysis of results. Both authors read and approved the final manuscript.
The work of SK was supported by the Special Research Grant of Sogang University 200811028.01.
This article has been published as part of BMC Medical Informatics and Decision Making Volume 9, Supplement 1, 2009: 2008 International Workshop on Biomedical and Health Informatics. The full contents of the supplement are available online at http://www.biomedcentral.com/1472-6947/9?issue=S1.
American Cancer Society: Cancer Facts and Figures. American Cancer Society, 250 Williams Street, NW, Atlanta, GA; 2008.
Elmore J, Armstrong K, Lehman C, Fletcher S: Screening for breast cancer.
The Journal of the American Medical Association 2005, 293:1245-1256.
Lo J, Bilska-Wolak A, Baker J, Tourassi G, Floyd C, Markey M: Computer-Aided Diagnosis in breast imaging: Where do we go after detection? In Recent Advances in Breast Imaging, Mammography and Computer-Aided Diagnosis of Breast Cancer. Edited by Suri J, Rangayyan R. SPIE Press; 2006:871-900.
Fischer E, Lo J, Markey M: Bayesian networks of BI-RADS descriptors for breast lesion classification.
Proc of the 26th IEEE EMBS, San Francisco, CA, USA 2004, 2:3031-3034.
Wei L, Yang Y, Nishikawa R, Jiang Y: A Study on Several Machine-Learning Methods for Classification of Malignant and Benign Clustered Microcalcifications.
IEEE Transactions on Medical Imaging 2005, 24:371-380. PubMed Abstract
Panchal R, Verma B: Characterization of Breast Abnormality Patterns in Digital Mammograms Using Auto-associator Neural Network. In ICONIP (3), Volume 4234 of Lecture Notes in Computer Science. Edited by King I, Wang J, Chan L, Wang DL. Springer; 2006:127-136.
Land WH Jr, Mckee D, Velazquez R, Wong L, Lo J, Anderson F: Application of Support Vector Machines to breast cancer screening using mammogram and clinical history data.
In Proc SPIE, Volume 5032 of Medical Imaging 2003: Image Processing Edited by Sonka FJM. 2003, 546-556.
Guyon I, Weston J, Barnhill S, Vapnik V: Gene Selection for Cancer Classification using Support Vector Machines.
Duan K, Rajapakse J, Wang H, Azuaje F: Multiple SVM-RFE for gene selection in cancer classification with expression data.
IEEE Transactions on Nanobioscience 2005, 4(3):228-234. PubMed Abstract
Jong K, Marchiori E, Sebag M, Vaart A: Feature selection in proteomic pattern data with support vector machines.
Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) 2004, 41-48.
Heath M, Bowyer K, Kopans D, Moore R, Kegelmeyer W: The Digital Database for Screening Mammography. In Proc of the 5th IWDM. Edited by Yaffe M. Medical Physics Publishing; 2001:212-218.
LeCun Y, Denker JS, Solla SA: Optimal Brain Damage. In Advances in Neural Information Processing Systems. Morgan Kaufmann; 1990:598-605.
Efron B: Bootstrap Methods: Another Look at the Jackknife.
Freund Y, Schapire RE: A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting.
Bauer E, Kohavi R: An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants.
Tan PN, Steinbach M, Kumar V: Introduction to Data Mining. Addison Wesley; 2005.
Kim HC, Pang S, Je HM, Kim D, Bang S: Pattern Classification Using Support Vector Machine Ensemble.
American College of Radiology: Breast Imaging Reporting and Data System (BI-RADS). Reston, VA, USA: American College of Radiology; 1998.
Lo J, Gavrielides M, Markey M, Jesneck J: Computer-aided classification of breast microcalcification clusters: Merging of features from image processing and radiologists. In Medical Imaging 2003: Image Processing. Volume 5032. Edited by Sonka M, Fitzpatrick J. SPIE Press; 2003::882-889.
Zhang P, Verma B, Kumar K: Neural vs. statistical classifier in conjunction with genetic algorithm based feature selection.


text:
Fun Things To Do This Weekend Around Lafayette, October 10 – 12, 2014
October and cooler weather means festivals here in Acadiana! Great food, music, and other family friendly entertainment makes for a great weekend with plenty of options!
October and cooler weather means festivals here in Acadiana! Great food, music, and other family friendly entertainment makes for a great weekend with plenty of options!
The 3rd Annual Rougarou Fest will be held on October 25th from 10 AM -10 PM in downtown Houma.
To win free tickets to see Sesame Street Live's 'Make A NEW FRIEND' at the Cajundome, October 24-26, be sure to wake up with CJ and Debbie Ray in the morning on 99.9 KTDY!
This vintage video of downtown Lafayette shows how far downtown has evolved into what it is today. The old cars, the fashion of people on the streets, and the buildings, many of which are still there.
The 1st annual Poche Plantation Mini Pot Jambalaya Cook Off will be held on Sunday, October 26th on the beautiful grounds of the historic Poche Plantation in Convent, LA...
Lafayette Police will be utilizing a new alert system to keep area residents appraised of crucial information as it becomes available.
$5 gets you "All You Can Eat" pancakes, sausage, coffee, milk, juice, and soft drinks at the Kiwanis Zydeco Pancake Breakfast!
The Ragin' Cajuns soccer and vollyeball teams play at home while football travels to Boise, ID!
The 5th Annual Jambalaya Cook-Off will be held on Saturday, September 27 will kick off with the first-ever "Wranglers and Wheels Ride."
Acadia Parish residents will be able to safely dispose of their household hazardous waste products on Saturday, October 4th from 8 AM to 12 PM.
Posted on Youtube in 2011, this video for www.hotroomm.com is just starting to circulate of Ali Landry naked in a bathtub (yes she stands up) covered in only a small amount of suds.
Ragin' Cajuns athletics gears up for another exciting weekend!


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Matt Wieters
Johnson Pitches O's Past Jays
Steve Johnson pitched the Orioles past the Jays in game two of the series.
Britton And Davis Lead The Way As O's Topple Tigers
Zach Britton returned to the big leagues Saturday night, pitching the Orioles past the Detroit Tigers 3-2.
Gausman Makes Stop in Bowie on his Way to High-A Frederick
On his way to Frederick, Gausman made a stop at Double-A Bowie on Wednesday afternoon.
Sox Top O's In Series Finale
Wednesday night, the Orioles stole one away from the Boston Red Sox when, after being no-hit for five innings, they put together a big inning out of nowhere. Thursday, an inning that SHOULD HAVE been big evaporated on the Orioles out of nowhere, and it led to a come from behind win for the Sox. […]
Big Inning Lifts Birds Past Sox, 5-3
Being no-hit by Red Sox right hander Aaron Cook, the Orioles turned on a dime in the sixth of Wednesday night and put together the big inning the propelled them to a 5-3 win.
Reynolds Leads O's Past Sox
Mark Reynolds slugged two home runs in the Orioles 7-1 victory over the Red Sox
Royals Take Tillman Deep, Beat Up O's
After winning four consecutive starts, Tillman (L, 5-2) was hit hard Saturday by the Royals.
Machadon't Stop! Rookies Lead O's Over Royals
Manny Machado's call-up Thursday night was one greeted with surprise, optimism, excitement, and fear by almost everyone in Orioles Nation.
O's Drop Machado's Debut, Win Streak Snapped At Five
Machado went 2-4 with a single and triple in his major league debut.
O's Sweep Mariners on Big Day For Johnson Family
Exactly 23 years after his father, former Orioles pitcher Dave Johnson, won his first major league game, Steve Johnson shut down the Seattle Mariners to pick up his first ML win.


text:
College Photos
Photos: TCU bounces back against Kansas; Horned Frogs cheerleaders put on show
Photo: Tony Gutierrez/AP
Kansas tight end Jimmay Mundine (41) escapes tackle attempts by TCU safety Sam Carter (17) and cornerback Jason Verrett, bottom right, as he heads to the end zone for a score after grabbing a pass from quarterback Jake Heaps in the second half of an NCAA college football game, Saturday, Oct. 12, 2013, in Fort Worth, Texas. TCU won 27-17. (AP Photo/Tony Gutierrez)
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DLD Conference 2012 - DLD Nightcap
President and editor-in-chief of The Huffington Post Media Group,... News PhotoArianna Huffington,Arts Culture and Entertainment,Attending,Business,Celebrities,Chairperson,Conference - Event,Corporate Business,Davos,Digital Life Design,Executive Editor,Finance,Financial Occupation,Founder,Horizontal,President,Publisher,Switzerland,The Media,WealthPhotographer Nadine RuppCollection: Getty Images Entertainment 2012 Getty ImagesDAVOS, SWITZERLAND - JANUARY 25: President and editor-in-chief of The Huffington Post Media Group, Arianna Huffington, Nicolas Berggruen, billionaire investor and founder of Berggruen Holdings Inc. and Staffan Ahrenberg, chairman and publisher Cashiers D'Art attend the Burda DLD Nightcap 2011 at the Steigenberger Belvedere hotel on January 25, 2012 in Davos, Switzerland. DLD (Digital - Life - Design) is a global conference network on innovation, digital, science and culture which connects business, creative and social leaders, opinion-form science and culture which connects business, creative and social leaders, opinion-formers and investors for crossover conversation and inspiration. (Photo by Nadine Rupp/Getty Images)


text: http://androidforums.com – Hi all :) I am a 3rd year Engineering student. I have got a project on Android application- silent features in my college. We have to develop an android app which will put the phone in silent mode for all incoming calls, expect for those the user selects (for these selected contacts the phone should ring). Is there any online tutorials available for android where i can start learning android programming ? As i don't have much time left to join any classes for the same. This project has to be submitted within 3 weeks. I need help regarding my project :confused: Can anybody help me w (General)


text:
Call It Spring Cream leatherette t-bar high heel peep toe 'rehder' court shoe
Item No.0520108244
Item No.0520108244
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This cream leatherette T-bar 'Rehder' shoe from Call it Spring has a buckle fastening strap, a peep toe and stiletto heel.
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Subject to exceptions, Debenhams is happy to exchange or refund your purchase within 28 days of delivery. Please check here for more details on our returns policy and exceptions.


text:
Most Popular in:
Excerpt Only
Flavor Bites: cis-3-Hexenyl Formate
By: John Wright
Posted: July 31, 2012, from the July 2012 issue of P&F magazine.
Delivering green notes to berry and other fruit flavors, and savory flavors
This is only an excerpt of the full article that appeared in P&F Magazine. The full content is not currently available online.


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The PDC is the pinnacle of the Microsoft events calendar as far as I'm concerned: it's the flagship event for developers, offering the most comprehensive, future-looking, technically deep, densely-packed set of sessions from Microsoft speakers you can find anywhere. This year is no exception: we've got a great line up and speculation is mounting about some of the new technologies we'll be introducing. Lots of surprises await and I guarantee that you'll miss out on some really cool stuff if you're not there in person. Registration is going faster than we expected and the event is starting to fill up quickly.
The PDC comes off the back of one of the most important product releases for Microsoft in years: of course, I'm talking about Windows 7. We've held back on announcing most of the deep Windows breakout sessions so far (stay tuned), but today we're announcing something rather special: a Windows 7 bootcamp presented by key leaders from around the product engineering team and others who have been deeply involved in the product development process. This will be the single most densely-packed day we can put together on the subject of Windows development: we'll take a bottom-up approach to our newest operating system, covering everything from kernel changes to new DirectX 11 features like compute shaders and the hardware-accelerated 2D and text rendering engines that will eventually supplant the venerable GDI libraries.
Confirmed speakers include:
The bootcamp is the day before the PDC itself starts and takes place in the Los Angeles Convention Center.
And the best part is – it's absolutely free! Normally we'd charge several hundred dollars for a pre-conference event like this, but the Windows team has agreed to sponsor this event to ensure that nobody misses out because of the tough economic climate. You can attend the bootcamp free even if you haven't signed up for the rest of the PDC (although we'd love you to join us for the rest of the event).
We've got limited space, so don't delay in signing up. See you there!
That is a shame that it is only for one day as I am on another course that day. I wonder if the content from the bootcamp will be available anywhere to download after the event. I am interested in what Yochay Kiriaty has to say.
I missed out this workshop, wondering when i would get to download this workshop.
Its been two weeks. When will the video of this session be available, as we were promised?
Tim, I am a power user and prefer the clean interface of WinXP over Vista and Win7. Win7 does have some nice eye candy and I like the jump lists and previews and such. However, I see some serious problems. First of all, pinned taskbar icons don't use space efficiently. If you do small icons and add a lot of them, you end up with a very inconvenient scrollbar instead of having the icons wrap like they did in QuickLaunch. Also, in Windows Explorer, when I drill down inside folders in the content pane, the folder list pane often isn't refreshing/adjusting, which is very irritating. In general, I'm annoyed when things are hidden/obfuscated and I have to go searching for them. Please fix these problems and keep my comments in mind when you're designing UI "improvements". Thanks.


text:
Rumsfeld's Rules
"I was right and he was wrong."
In many ways, that was the lesson of Donald Rumsfeld's event at The Heritage Foundation called Rumsfeld's Rules: Leadership Lessons in Business, Politics, War and Life, based on his new book of the same name.
Rumsfeld has collected these "rules," which are mostly thoughts or ideas, since he was young. He kept them in a shoebox until then-President Gerald Ford asked to see them. So he had them typed up and gave copies to Ford and senior staff.
Many of the "rules" come from other people, including Margaret Thatcher and Winston Churchill.
Although Rumsfeld has faced a lot of criticism even from the right over his actions after 9/11 and leading up to the war in Iraq, he remains a traditional conservative.
Rumsfeld offered advice on everything from how to put together a board of directors to why the Law of the Sea Treaty is a bad idea (see: capitalism).
Some of his best insight was on the intersection of businessmen and the president's cabinet. While the proportion of people in the cabinet who had private-sector experience was 70 to 80 percent under Ronald Reagan, it is only 22 percent under the current administration.
Part of that, he explains, is due to the difficulty of getting good people into office. Many of the presidential-appointed positions were vacant for much of his six years as secretary of defense due to the number of clearances the appointees required.
He acknowledged the frustration of a permanent bureacracy and referred to a Hyman Rickover quote: "If you are going to sin, sin against God, not the bureaucracy. God will forgive you but the bureaucracy won't."
Many of Rumsfeld's arguments follow tried-and-true conservative logic, but that makes them no less relevant. "The advantage of the private sector is you do other things and you go out of business," he said. "In government, it just goes on and on and on. It's other people's money and it can't fail."


text:
Animals - Page 3
Pet Diseases on the Rise in NJ [AUDIO]
15 Cute But Deadly Animals
Top 10 Trendy Male and Female Dog Names
This Ultimate Dog Tease Video Never Gets Old
Tips to Keep Your Pet Safe in an Emergency
Emergencies come without warning. Having an evacuation plan will increase your chances of staying safe in emergency situations. If you own a pet, you should include them in your evacuation plans and know what to do in the event you are forced to leave your pet behind. Here are some tips on how to keep your pet safe during an emergency.
Why Are Elks Dying in New Mexico?
Did Your Dog Make The Most Talkative List?
Turtle Causes 3 Car Accident in Galloway Township
If you had your choice between hitting a turtle on the road or causing an accident, what would you do? In Galloway Township police say a 3 car pileup was caused when a motorist in an Infiniti slowed to avoid hitting a turtle on the While Horse Pike.
Chase, The Trenton Thunder Bat Dog Dies
Chase, the beloved bat-retrieving dog at Trenton Thunder games died Monday at the age of 13, the stadium announced today.


text:
Crazy Ships
(If any tax is payable it will be calculated and shown at checkout.)
Preview (read now) Add to my own site Give this ebook to a friend Add to my wishlist Author's page Publisher's page
moreA brand new science fiction novel from the author of The Sex Gates and The Pet plague. Twins Steve and Jane grow up in a dystopic earth ruled by giant corporations. Faster than light space travel has been discovered, but extracts a terrible price. The immutable mathematics of the theory dictate that only half the ships leaving earth will make it to their destination, and of those which do, only half will return safely to earth; hence the name: Crazy Ships. With those odds, crews and colonists are drawn from the criminal class or from political prisoners and sentenced to serve on a ship.Just as Steve and Jane fall in love with each other, their parents fall afoul of the corporation ruling earth. They are separated from all they ever knew and loved and sentenced to become part of the crew on a crazy ship--but not the same ship, nor the one their parents are sentenced to. When each of their ships fails to make a jump, their troubles really begin. less
Double Dragon Publishing; September 2003
202 pages; ISBN 9781554040827
Read online, or download in secure PDF format
Title: Crazy Ships
Author: Darrell Bain
202 pages; ISBN 9781554040827
Read online, or download in secure PDF format
Title: Crazy Ships
Author: Darrell Bain
Buy, download and read Crazy Ships (eBook) by Darrell Bain today!
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The Girl on the Train 2015 US$ 9.99 336 pages
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Quick Specs
Total Downloads:345
Date Added:Feb. 12, 2007
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text: Donny Osmond | IBDB: The official source for Broadway Information IBDB: The official source for Broadway Information Official Broadway League sites: - sites - broadway.org broadwayleague.com broadwayfanclub.com kidsnightonbroadway.com stagespecs.org tonyawards.com Quick Search For: In This Category: All Show People/Org. Theatre Season View more items Donny Osmond Performer ( b. Dec 09, 1957 Ogden, Utah, USA ) Male Relations: Brother of Marie Osmond Productions ProductionsDate of ProductionsDonny & Marie[Special, Miscellaneous, Original] Starring: Donny Osmond Dec 09, 2010 - Jan 02, 2011Beauty and the Beast[Musical, Comedy, Original] Performer: Donny Osmond Gaston - Replacement (Sep 19, 2006 - ?)Apr 18, 1994 - Jul 29, 2007Little Johnny Jones[Musical, Revival] Starring: Donny Osmond [Johnny Jones]Mar 21, 1982 - Mar 21, 1982 Find out where Donny Osmond and are credited together © 2001-2015, The Broadway League, All Rights Reserved. (Copyright and Disclaimer)


text:
That mix of quantitative and qualitative market analysis sets our report apart. Our emphasis is on future revenue trends. We give you market predictions found only in our work. Our independent analysis can help you stay ahead of your competitors.
You can order our report, receiving the market information you need
Our report can benefit everybody interested in anti-obesity drug development, production, marketing and sales. You will find answers and predictions you need. Please order our report now, making sure you don't miss out.
Visiongain is a trading partner with the US Federal Government
CCR Ref number: KD4R6
NB: All visiongain reports are password locked so please let us know what license is most suitable for your business needs
Table of Contents
1. Executive Summary
1.1 The Anti-Obesity Drug Market Has Potential to Increase its Revenues
1.2 Aims, Scope and Format of the Report
1.3 Research and Analysis Methods
2. Introduction to the Anti-Obesity Drug Market
2.1 What is Obesity?
2.1.1 Obesity as a Chronic Disorder
2.1.2 Obesity in Children
2.2 Factors Leading to Obesity
2.2.1 Genetic Factors
2.2.2 Psychological Factors
2.2.3 Environmental, Behavioural and Social Factors
2.2.4 Drug Factors
2.2.5 Mental and Physical Disability Factors
2.2.6 Other Factors
2.2.7 Antecedent Illnesses and Treatments
2.3 Measurement of Obesity
2.3.1 How is Obesity Measured?
2.3.2 Weight-for-Height Tables
2.3.3 Waist Circumference
2.3.4 Body Mass Index (BMI)
2.4 Obesity Has High Socio-Economic Costs
2.4.1 Consequences of Obesity: Co-Morbidities Linked to Obesity
2.5 Obesity is a Rising Challenge in Many Countries
2.5.1 Obesity in Established Market
|SOURCE Reportlinker
Copyright©2010 PR Newswire.
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text:
There's no reason that millions of responsible gun owners should be punished for the actions of a few disturbed individuals. Gun bans have proven unsuccessful at curbing gun violence in the past and there's no reason to assume that it will work this time. Criminals will still acquire these weapons, therefore, the law abiding public will the only ones to suffer. Please sign my petition and help to protect our liberties.
Letter to
Oppose the ban on assault weapons
Trending petitions


text:
Men's New Italian Military-issue Slide Sandals, Blue
Item # WX2-230139
- Google+
- Details & Specs
New Italian Military-issue Slide Sandals, ON SALE!
Step to it! FOUND: a supply of slide-style Sandals manufactured for the feet of the Italian Military. Unfortunately, they made a few too many. But their loss is your gain! These guys are durable, comfortable and guaranteed not to break the bank.Slide in:
- Italian Military issue
- Anti-fungal, antibacterial and odor-fighting
- Non-skid honeycomb-patterned sole
- Dual top straps.
- Each approx. 12 ozs.
Condition: brand new, never issued. State Size, as available in the Shopping Cart. Medium width. Half sizes, order the next larger full size.
!!! Limited Quantities !!!
- Reviews
Men's New Italian Military-issue Slide Sandals, Blue is rated out of 5 by 13.Rated 4 out of 5 by lazyfarmer from OK Will using for quick trips outside when grass is wet OR last minute trips outside before bedDate published: 2015-06-19Rated 5 out of 5 by WILLIAM from my new summer sandal, around the house shoe. High quality.Date published: 2014-04-18Rated 5 out of 5 by EDWARD from Good sandal but were damage when they got to me so i return them should have been in box instead of plastic bag, boxes on to of sandal pushing down on top of sandal got them out of shape from boxes sitting on top of them o there travel here.So just credit my account.Date published: 2014-02-14Rated 5 out of 5 by KEN from GREAT SANDALSDate published: 2014-01-28Rated 4 out of 5 by MARK from Excellent sole support but rubs a little on the top of the foot - A little moleskin should fix that right upDate published: 2013-08-13Rated 5 out of 5 by WILLIAM from Well made & comfortable...Date published: 2013-07-28Rated 5 out of 5 by SCOTT from Unused, another good score from the GuideDate published: 2013-07-07Rated 5 out of 5 by WAYNE from Very comfortable, though I don't recommend wearing them for long walksDate published: 2013-07-05

 What is the length, heel to toe, on size 8?

Asked by: joeleander

 The length is 10 1/4" on a size 8.
Answered by: Customer Service

Date published: 2015-01-26

2015-10-04T11:30CST

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text:
1048-1070 Battlecreek Road
Commute to Downtown Forest Park
30 min 38 min 60+ min View Routes
Most errands require a car.
Score Details
Something missing? Add a place
1048-1070 Battlecreek Road has a Walk Score of 43 out of 100. This location is a Car-Dependent neighborhood so most errands require a car.
Nearby parks include Tara Stadium and Rum Creek Park.
Explore how far you can travel by car, bus, bike and foot from 1048-1070 Battlecreek Road.
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Real Estate Agent
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Jesper Schultz commented on the post, "I read all your stuff … now what?"
Matthew Reilly's 'Contest' was a page-turner for me – it's probably over in the hand-wavey scifi departement; but the action is nonstop, it has aliens, a sporting tournament setup, horror and suspense. Good stuff.
I was blown away by Fahy's Fragment, but felt that the sequel Pandemonium was too much over the top. Probably good for a summer…[Read more]
Jesper Schultz commented on the post, THE CHAMPION Episode #21
Awww yeah! Was 'dat one or two broken ribs, QB?
I'm torn every time the Krakens visit the CCKs. The Cloud Killers must emerge victorious yet again; but I'm also rootin' for the good ol'e Krakens?
Anyways – great episode, although I cannot see 'Schultzie' going unpunished, should the Krakens step in front of the Coranadillana Cloud Killers…[Read more]
@JZ: Of course you're torn. Glad you liked the episode.
Jesper Schultz commented on the post, Vote on the Krakens helmet for THE CHAMPION
Modified #2
Jesper Schultz commented on the post, Merry Christmas from Empty Set!
Yeaj! Now my reader resembles my shelf
I hope the new year brings you guys obscene wealth and success!
Merry Christmas from Denmark
Jesper Schultz replied to the topic What have *you* done to promote the Sigler Ascension? in the forum Reply To: What have *you* done to promote the Sigler Ascension?
I have written about the FDO on my blog several times. It's in Danish, but if you're so inclined, knock yourself out /JZ


text: More from SI Jason Spezza's no-trade list has 12 teams Jason Spezza's no-trade list has 12 teams Close Tweet0 Share0 Comment0 Share0 Share0 Stumble It0 Print0 More Home Ice Hobey Baker Award winner Johnny Gaudreau signs with Calgary Flames by amuir29 Email Posted: Fri Apr. 11, 2014 Updated: Sat Jun. 14, 2014 The Flames weren't about to let highly touted forward Johnny Gaudreau get away. (Fred Kfoury/Icon SMI)By Allan MuirA Calgary radio station reported, and Boston College has confirmed, that Eagles stars Johnny Gaudreau and Bill Arnold will turn pro and make their NHL debuts with the Calgary Flames on Sunday.Both players became eligible to sign with the NHL team after BC was eliminated from the Frozen Four by Union College on Thursday night. Gaudreau's three-year entry leave deal has a reported annual average value of $1.85 million; Arnold was given two years at $900k per.Arnold, a fourth-round selection of the Flames in 2010, was expected to turn pro as a graduating senior, but the addition of Gaudreau will surely catch the attention of Calgary's fans. The 20-year-old forward led the nation with 36 goals and 80 points as a junior and has won the Hobey Baker Award as the country's top player.This is a significant signing for the Flames, and not just because Gaudreau is their most intriguing prospect. He could have become an unrestricted free agent next summer had he chosen not to sign with Calgary, and there likely would have been a number of suitors willing to woo him if he'd waited. But this is a deal that works out well for both sides. He gets a clear path to the NHL with a rebuilding team, and Calgary gets him under contract ... even if they're not quite sure yet what they're getting. Gaudreau is as skilled as any prospect outside the NHL, but at just 5'-7" and 150 pounds, there are questions as to whether the 2011 fourth-rounder will ever be effective at the highest level of the game. His quest to prove that he belongs will begin Sunday in Vancouver. Promoted Stories Comments