Rethinking the Meat-Guzzler
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At a time when resource conservation is at the forefront, the days of eating 200 pounds of meat a year may also be on the way out.
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Tycho:  The memories of those who came of age in the eighties have become a kind of ghastly rummage sale, a tilled up cemetery where icons lay tilted over bones draped in ancient finery.  Pork caught a preview of Transformers on Monday, and he claims that it is not, in fact, heresy - but I don't know how calibrated our respective tastes are.  I was going to make a statement about how any constantly shifting image could entertain him, enthrall him, command him, until I realized that this viewing was late at night, in the twilight period we call Pork After Hours, when his medication wanes and his blood is frenzied by some dark moon.  For him to have focused on anything at any time after nine o'clock is actually high praise.
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Comment is free: Jay Rayner: Yes, the big chains need to be kept in check, but opponents overlook their social benefits
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Consumers are being misled by pork that is labelled free range, animal welfare groups say.
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Beware the Internet's meat puppets. And sock puppets. And trolls and shills and astroturfing and other forms of dubious online marketing.
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Meat eaters its time to switch dishes and go veggie as latest research shows that people who eat diets rich in plant foods have a lower risk of serious diseases such as cancer.
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A public-health doctor discovers that poor diet, not airborne microbes, is the cause of pellagra, a debilitating and often fatal disease. He's bucking the medical establishment, though, and his findings are not universally accepted.
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Time to put on those tin foil hats again
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By Emma D. Sapong, The Buffalo News, N.Y.  Feb.
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In response to a previous article from the Symfony blog, Paul Jones has pulled together some thoughts to some of the comments they made.   As the author of a relatively popular benchmarking article, I feel compelled to respond to this bit of misguided analysis from the Symfony camp about benchmarks.   Paul talks about the "straw-man arguments" presented in the Symfony article, including some references to Paul's previous benchmarks. He's even broken it down into a point-by-point response to make each point clear.
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Hold the roast beef, pass the cocktail wieners on toothpicks. Eat off paper plates (napkins are even better), and don't dare sit down.
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There's an old parable that goes like this:A man is sentenced to death by the king. In desperation, he asks that his life be spared if he can teach a pig to sing. The king agrees, and gives the man a year. Walking the man back to his cell, a guard comments that it seems like a foolish bargain; he doesn't really expect to be able to do it, does he? The man replies, "A lot can happen in a year. The king could die. I could die. Or who knows, maybe the pig will learn to sing."(Maybe it's an allegory. Or a fable. I can never keep these things straight.)I'm using the pig story to segu&#233; into Bayesian spam filters. But first, a quick trip back to spam filters in general. E-mail spam has been around for a while, and different schemes have been developed to determine whether a piece of e-mail is (probably) legit, or whether it's spam. One way is to create a blacklist of senders: Nothing from, say, 123junk.com is allowed into your inbox. Another is a whitelist: If you aren't an approved sender (e.g., mom, dad, Cousin Jimmy), you're mail won't go through. A third is the 'word search,' which looks for the kinds of words that rarely make it into a legitimate e-mail: "Viagra" springs to mind, and there are plenty of others that can't be printed on a family Web site. All of these anti-spam techniques have problems, mostly because they were either too narrowly focused to be effective, or because they were too easy for spammers to get around.But then came a different kind of spam filter - one based on the work of an obscure mathematician from the 18th century. One that works.Reverend TomThomas Bayes was an English Presbyterian minister and mathematician who lived from 1702 to 1761 in and near London. He only published two things while he was alive: a paper that tried to prove that God wants everyone to be happy, and another defending the accuracy of the calculus. After he died, though, is when Bayes's most important work was published. Called "Essay towards solving a problem in the doctrine of chances," it was discovered by an acquaintance (one Richard Price, for those of you who like the details) who sent it to the Royal Society which published it in its Philosophical Transactions in 1763.Out of that paper came what's called Bayes's Rule or Bayes's Theorem. It's a formula for guessing how likely it is that something will happen based on two or more independent events. Imagine you want to know what the chances of your 1986 Toyota Corolla making it cross country. Some "independent events" that might stop you are your engine failing, your transmission failing, your tires failing, and so on.To apply Bayesian probability here, you would figure the odds of each of those things, then input those numbers into Bayes's formula (which, by the way, is fairly simple). Let's say you figure the chance of your engine failing is 10%, the chance of your transmission failing is 15%, and the chance of your tires failing is 30%. Popping the numbers into Rev. Tom's formula tells you that the chance of your trip being ruined by any one of these things is actually less than 1%. Happy trails.(Is this counterintuitive? Maybe. Check out another example at Process Software.In 2002, Paul Graham changed the spam war forever when he published an article called "A Plan for Spam". In it, he demonstrated how Bayes's work could be used to sort out spam from legitimate e-mail.Instead of calculating the odds of whether your car will make it across the country, Graham used Bayesian techniques to determine how likely a piece of mail is to be spam. It bases this on how likely each word is to be in a spam message.(By the way, the word "word" is misleading. Bayesian filters also take into account things like Web links, text colors, and font size.)Thus, the more spam messages (and good messages) you get, the more information a Bayesian filter has and the better it gets at identifying junk. A lot of very good anti-spam products are based on Bayesian techniques.And they work very, very well.Basic trainingFirst, a Bayesian filter has to be trained; you need to tell it these are legit messages and these are spam. (Every Bayesian filter has a simple way to do this, usually by having you put all your spam in one mailbox. It then scans that Spam box for spam, and your Inbox for legit mail.)The filter looks at the words in every message to get an idea of what spam looks like. For example, if the word "buy" appears in 100 spam messages and only one legit message, it might be given a score of .99 - there's a 99% chance a message with "buy" in it is spam.On the other hand, the word "column" would (for me) be the opposite; it might appear in 99 legit messages and only one spam, and thus get a score of .01 or one percent.After going through this training process, the Bayesian software ends up with a list of words and their spammish probabilities (often called a "corpus"). When a new message arrives, the filter looks through the words in it and gives each a score based on those 'training' messages. Then it uses Bayes's formula to come up with a score for the message as a whole. If that's above a certain threshold, the message is tagged as spam and either marked, deleted, or separated.But the real beauty of the Bayesian-filter system comes next, when spam gets through. It's bound to do that, because spammers always try new tricks - they put in long passages of poetry, or try to disguise words with odd misspellings, or come up with other ways to sneak by. When a piece of spam ends up in your Inbox, a Bayesian filter has an extra option: one to mark it as junk. Sometimes it's a button or menu choice, other times you just need to move the message to a Spam folder. It also works the other way: Legit messages may land in the Spam box for various reasons, and they must be re-routed. Either way, the filter now knows what the newest kind of spam looks like.Bayesian filters work because they aren't dependent on things that might change: the way words are spelled, or where a message comes from. All they care about is what you say is spam. At least one filter, POPFile, actually lets you set up categories beyond just 'spam' and 'not spam,' so you can teach it to automatically sort out messages on a particular topic.There are a lot of technical ideas out there for curbing the flow of spam, but I'm willing to bet that none of them will work very well. Stopping spam is up to us, and Reverend Bayes has given us a powerful tool.Andrew Kantor is a technology writer, pundit, and know-it-all who covers technology for the Roanoke Times. He's also a former editor for PC Magazine and Internet World. Read more of his work at kantor.com. His column appears Fridays on USATODAY.com.
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Life & style: With sales of gourmet rashers on the rise, it seems we can't get enough bacon. Tim Hayward cures his own
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From fast-food chains to Congress, moves are afoot to reduce animal suffering and ensure food safety
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Why do we gossip? Evolution may hold some surprising answers.
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Earmarks are only pork when someone else is feasting on them. On your plate, they're veggies. They are the train that takes you to visit Aunt Betty, or the health clinic down the street, or the waste treatment plant that makes your water safer to drink. They're not all bridges to nowhere. They're also bicycle trails to somewhere.
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Coming to terms with very big boxes Meat Cast Last week, thousands of you did the right thing by tuning into our first Meat Cast on blade servers. You're now smarter than the average data center hack and have the blade scene down. Go ahead - lord your knowledge over friends, family and co-workers.â¦