Making ‘Social Media’ Social

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At HostingCon 2010, I joined (Curtis) R. Curtis, Nick Longo and Matt Balleck on a panel to discuss how hosters and entrepreneurs can optimize social media for branding, traffic and sales. When you start talking “social media,” you’re almost guaranteed a great turnout, and this session was no exception. The standing room-only crowd asked some great questions of the panel, and despite my blog audience-selected attire, many flagged me down to keep the conversation going.

The session allotted each presenter a few minutes to share some best practices from their experience with Twitter, Facebook and YouTube before the floor was opened to questions. Nick Longo led off with an excellent rundown of Rackspace’s high-level Twitter strategy. He discussed how the company approaches social media and the paramount importance of engaging employees and personal networks to connect with people to share a value-rich message. His personal strategy when it comes to posting on Twitter is to load the channel with value for his audience … even when that value isn’t directly related to his company. By focusing on his audience’s interests and injecting business content only where relevant, he’s built a fantastic following.

vidiSEO‘s Matt Ballek, stepped up to the microphone next and brought the thunder by sharing some much-appreciated tips about how businesses can optimize their YouTube videos. If pictures are worth a thousand words, his “YouTube Video SEO – How to Optimize Your YouTube Video” interactive presentation is probably worth a few million, so I’d highly recommend you check it out to learn about the four pillars of optimizing your videos.

Following those future Hall of Famers, the pressure was on when I stepped up to the podium. Luckily, my presentation didn’t turn out to be a “Casey at the Bat” situation. I shared some of our social media successes with the crowd by explaining how and why #showmemyserver, the #500Club and The Planet Server Challenge worked as well as they did. If you’ve been around the neighborhood here for a while, you’re well versed with those campaigns, and if you’re unfamiliar, scroll down to the last paragraph to learn how you can earn the chance watch a video of my presentation. In the meantime, take a look at the slides we covered:

(Curtis) R. Curtis batted cleanup on the panel by sharing a few tips and tricks for businesses on Facebook. He touched on the fact that “personal” nature of the medium makes it tough to sell to users, but that shouldn’t dissuade businesses and entrepreneurs from building qualitative connections with customers by allowing them to connect and interact with the company and each other.

Given my presentation’s focus on user engagement, it seems only fitting that this blog have an opportunity for you to earn a bonus by becoming a part of the conversation. Leave a comment below with a few “words of wisdom” you’ve gleaned from your experience with social media, and I’ll email you a link to a video of my presentation. Along with my brilliant speech delivery, you’ll get a peek at “the hipster look.”

What else could you want?

-Kevin

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The 2010 Perseids Meteor Shower

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A Geminid meteor. Image credit: Jimmy Westlake via JPL

YAY! My second favorite meteor show of the year is coming up this week. The Perseids shower comes to us compliments of the Comet 109P/Swift-Tuttle. The shower peaks on August 12 – 13, it’s a must see.

The shower seems to radiate from the constellation Perseus, which will be rising in the Northeastern Sky by 9 pm (your local time). I’ve heard predictions of up to 50 meteors per hour because the debris trail is especially favorable this year. PLUS!! The moon will be setting early on ensuring dark skies.

Don’t worry too much about being able to spot the constellation Perseus (here’s a little chart all the same), just look up. Several years ago I was coming home from a class learning how to start IV’s on poor Bram (he is now a college professor), anyway I was riding in the back seat of a hatchback at about 9:30 to 10 pm and had my head back so I was looking straight up out of the back of the car, I saw all kinds of meteors. So as long as you don’t have too many clouds (oh please-please-please no clouds for me), you will be able to see the bits of comet strike our atmosphere at 38 miles per second (61 km/sec). What actually happens is a little more complicated than what you might think:

This explanation from the US National Weather Service:

What we actually see “burning up” in our atmosphere is the air undergoing a compaction and compression ahead of the fast-moving meteoroid called incandescence. Compression is a heating process and the air ahead of a meteoroid glows brightly as the meteoroid moves quickly through our atmosphere, most of the time at speeds greater than 10 miles per second. This is why our spacecraft have to have heat shields upon re-entering our Earth’s atmosphere. Without the heat shields, the spacecraft would vaporize due to temperatures approaching several thousand degrees F.

If all goes really well I might try and get some images, that great one at the top of this post by Jimmy Westlake is on the JPL site: How to See the Best Meteor Showers of the Year: Tools, Tips and ‘Save the Dates’. Be sure to check it out!  BTW, they have a larger version of Mr. Westlake’s picture too.

My favorite shower? The Orinoids in October. Why? FIREBALLS!!

BTW Rob reminded me of this:

We have the opportunity to help out an effort to spatially analyze the Perseids meteor shower….No wait!

This is:
Easy
Costs nothing
Only requires a laptop and your eyes
It’s a fun geeky thing to do!

Check out the Perseid Project.

I’ll be participating clouds permitting.  (please-please-please no clouds!)

NCBI ROFL: What’s in a name? Part III: Why Dennis is a dentist. | Discoblog

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seashellsWhy Susie sells seashells by the seashore: implicit egotism and major life decisions.

“Because most people possess positive associations about themselves, most people prefer things that are connected to the self (e.g., the letters in one’s name). The authors refer to such preferences as implicit egotism. Ten studies assessed the role of implicit egotism in 2 major life decisions: where people choose to live and what people choose to do for a living. Studies 1-5 showed that people are disproportionately likely to live in places whose names resemble their own first or last names (e.g., people named Louis are disproportionately likely to live in St. Louis). Study 6 extended this finding to birthday number preferences. People were disproportionately likely to live in cities whose names began with their birthday numbers (e.g., Two Harbors, MN). Studies 7-10 suggested that people disproportionately choose careers whose labels resemble their names (e.g., people named Dennis or Denise are overrepresented among dentists). Implicit egotism appears to influence major life decisions. This idea stands in sharp contrast to many models of rational choice and attests to the importance of understanding implicit beliefs.”

Bonus table:
table1

seashells

Photo: flickr/geishaboy500

Related content:
Discoblog: NCBI ROFL: What’s in a name? Part I: U.G.H. you’re going to D.I.E.
Discoblog: NCBI ROFL: What’s in a name? Part II: Why Kevin Kouzmanoff strikes out so much.
Discoblog: NCBI ROFL: Beauty week: Better choose that baby name wisely!

WTF is NCBI ROFL? Read our FAQ!


Damn You Einstein, You Liberal You | The Intersection

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Joe Romm has found and had a massive amount of fun with the Conservapedia entry denouncing relativity as a liberal plot. Go read his post. I’ll just quote a bit:

I don’t see how that story of Jesus healing somebody proves action at a distance instantaneously…. Silly conservatives. You would need to demonstrate that the healing took place exactly when Jesus spoke to disapprove the special theory of relativity – rather than say a fraction of a second later.

Warning: If you read Romm’s post or the Conservapedia entry on which it is based, you will be entering a true bizarro world–one in which fidelity to biblical literalism not only leads to the rejection of everything we know, but further, to the generation of extraordinarily wacky scientific-sounding psuedo-arguments.

Just as it does on evolution, actually.


The dog’s world of large effect QTLs | Gene Expression

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Szusza_pekingeseA major issue in human genomics over the past few years has been the case of the “missing heritability“. Roughly, we know that for many traits, such as height, most of the variation in the trait within the population is controlled by variation in the genes of the population. The height of your parents is an extremely good predictor of your height in a developed nation. If you’re adopted, the height of your biological parents is an extremely good predictor of your height in a developed nation, not the height of your adoptive parents. Though a new paper claims to have resolved some of the difficulty, one of the major issues in human height genetics has been the lack of large effect quantitative trait locus. In plain English, a gene which can explain a lot of the variation in the trait. Rather, many have posited that continuous quantitative traits like height are controlled by variation in innumerable common genes of small effect size, or, by innumerable rare genes of large effect size. The same may be an issue with personality genetics, or so is claimed by a recent paper unable to find common variants (though an eminent geneticist pointed out in the comments some problems with the paper itself).

ResearchBlogging.orgOne would assume that the same problem would crop up across the tree of life. But a geneticist once told me that he considered biology the science where all rules have exceptions. Many exceptions. A new paper in PLoS Biology paints a fundamentally different picture of the genetic architecture of many morphological traits in the domestic dog, A Simple Genetic Architecture Underlies Morphological Variation in Dogs:

Dogs offer a unique system for the study of genes controlling morphology. DNA from 915 dogs from 80 domestic breeds, as well as a set of feral dogs, was tested at over 60,000 points of variation and the dataset analyzed using novel methods to find loci regulating body size, head shape, leg length, ear position, and a host of other traits. Because each dog breed has undergone strong selection by breeders to have a particular appearance, there is a strong footprint of selection in regions of the genome that are important for controlling traits that define each breed. These analyses identified new regions of the genome, or loci, that are important in controlling body size and shape. Our results, which feature the largest number of domestic dogs studied at such a high level of genetic detail, demonstrate the power of the dog as a model for finding genes that control the body plan of mammals. Further, we show that the remarkable diversity of form in the dog, in contrast to some other species studied to date, appears to have a simple genetic basis dominated by genes of major effect.

The paper uses powerful statistical and computational techniques, but the main results are relatively straightforward (assuming you don’t get stressed out by terms such as “random effect in the linear mixed model”). First, they delved a little into the evolutionary history and the general topography of the genomics of various dog breeds, wolves, as well as stray “village dogs” (I assume these are simply these are like the “pariah dogs” of India). Though village dogs had domestic ancestors they’ve gone feral, so they’re an interesting contrast with the new breeds created since the 19th century, as well as the wild ancestors of all dogs, wolves.

Three statistics were used to explore demographic history: linkage disequilibrium (LD), runs of homozygosity (ROH), and haplotype diversity. Inbred individuals have many ROH. They may have one individual show up relatively recently in their ancestry over and over, so it makes sense that they’d have many loci where both copies of the gene are identical by descent and state. Obviously purebred dogs have high ROH. They also have low haplotype diversity. Even the average person on the street is familiar with the freakish inbreeding which goes into the production of many purebred canine lineages, and their lower life expectancy vis a vis the maligned “mutt.” LD decayed much more quickly in wolves than in the dogs, village and purebred. Remember that LD indicates correlations of alleles across loci. It can be caused by selection at a SNP, which rises in frequency so quickly that huge swaths of the adjacent genome of that particular SNP “hitchhike” along before recombination can break up the association to too great an extent. Admixture between very distinctive populations can also produce LD, which again will decay with time due to recombination. Finally, another way LD can occur is through bottlenecks, which like positive selection can increase particular gene frequencies and their associated genomic regions rather rapidly through stochastic processes. It is the last dynamic which probably applies to all dogs: they went through a major population bottleneck during the domestication process, so the genomic pattern spans village and purebred lineages since it is an echo of their common history. Finally haplotype diversity is simply ascertaining the diversity of haplotypes across particular genomic windows. An interesting find in these results is that village dogs actually have lower ROH and higher haplotype diversity than wolves. That suggests that the wolves in this sample went through a major population bottleneck, while village dogs have maintained a larger effective population.

A general finding from the aforementioned examination is that different breeds tended to be genetically rather distinct. This follows naturally from the origin of modern purebreds as tight and distinct inbred lineages. This genome-wide distinctiveness though is a perfect background condition to test for similarities within the genome which correlate with specific morphological similarities across the breeds. And they did find quite a bit:

We searched for the strongest signals of allelic sharing by scanning for extreme values of Wright’s population differentiation statistic FST…cross the breeds. The 11 most extreme FST regions of the dog genome contained SNPs with FST?0.57 and minor allele frequency (MAF [major allele frequency -Razib])?0.15 (Table 1). Six of these regions are strongly linked to genetic variants known to affect canine morphology: the 167 bp insertion in RSPO2 associated with the fur growth and texture…an IGF1 haplotype associated with reduced body size…an inserted retrogene (fgf4) associated with short-leggedness…and three genes known to affect coat color in dogs (ASIP, MC1R, and MITF…Two other high FST regions correspond to CFA10.11465975 and CFA1.97045173, which were associated with body weight and snout proportions, respectively, in previous association studies….Two known coat phenotypes (fur length and fur curl…) also exhibited extreme FST values. Only a limited number of high FST regions were not associated with a known morphological trait (Figure 2, black labels). Here, we focus on illuminating the potential targets of selection for these regions as well as identifying genomic regions that associate with skeletal and skull morphology differences among breeds.

Many of these genes are familiar to you in all likelihood because they have the same functional significance in humans. The key difference is effect size. Since the paper is open access I’ll spare you the alphabet soup of genes and their association with canine morphological traits. There are many of them that pop up by examining differences between breeds in morphology (and similarities) and their allele frequencies. The top line is the prediction of trait which can occur via just a few genes. They constructed a regression model where a set of independent variables, genes, can predict the value of a given dependent variable, the trait:

Using forward stepwise regression, we combined potential signals into a multi-SNP predictive model for each trait. In the models of body weight, ear type, and the majority of measured traits, most of the variance across breeds could typically be accounted for with three or fewer loci…Correlated traits (e.g., femur length and humerus length) yielded similar SNP associations. For the 55 traits, the mean proportion of variance explained by the top 1-, 2-, and 3-SNP models was R2 = 0.52, 0.63, and 0.67, respectively….After controlling for body size, mean proportion of variance explained by these models was still appreciable—R2 = 0.21, 0.32, and 0.4, respectively.

R2 indicates the proportion of variance in the dependent variable explained by variance in the independent variables. The values for this model are very high. By contrast, a gene for height in humans is a find if it can explain 2% in the trait value variance.

The above found SNPs which could explain variation across breeds which are inbred and highly distinctive in genes and traits. Could the same SNPs explain variance within breeds? Yes:

Most of the variance in body size was explained by the IGF1 locus where we observe a single marker with R2 = 50% and R2 = 17% of variance in breed and village dogs, respectively. The top 3-SNPs explain R2 = 38% of the variance in body weight in village dogs, although the 6-SNP model explains less. The lower R2 in non-breed dogs than breed dogs may be a consequence of lower LD observed in village dogs reducing the strength of association between these markers and the causal body size variants. Alternatively, the lower R2 may also be a consequence of non-genetic factors such as diet or measurement error affecting the observed village dog weights, the smaller range of body sizes observed in the non-breed dog sample, or perhaps to overfitting of the model based on the particular breeds included in the dataset. Nevertheless, R2 = 38% is significantly better than association scans for morphometric traits in humans utilizing denser marker arrays….

Dogs and humans have a long history together. But some of these dogs have a very short history. As noted in the discussion many canine lineages which are purebred are products of Victorian era breeding crazes, and were selected for strange characteristics which were transmitted in a discrete fashion. The recency of the lineages combined with the peculiarities of the breeding programs of this era and dog fanciers generally may explain some of the genetic architecture of canines. The authors note that domestic animals subject to more gradual selection may not, and do not, exhibit the same tendency. Perhaps humans are more like goats or wheat, and less like dogs? The authors note the contrast in loci which exhibit population wide variation:

In humans, high-FST regions are associated with hair and pigmentation phenotypes, disease resistance, and metabolic adaptations…In contrast, the strongest signals of diversifying selection in dogs are all associated with either body size/shape or hair/pigmentation traits, and therefore are unlikely to have been under selection for disease resistance, metabolic adaptations, or behavior. In total, the 11 highest FST regions identified across purebred dogs are all associated with body size/shape or hair phenotypes, including three genomic regions that had not been detected in previous association studies.

The rationale for this study is the utility of dogs as model organisms for humans. They’re taxonomically rather close to us, so their genetics may give us insight into human conditions. The main worry though for me is that the best models here are inbred dogs, where the markers adduced are most valid, but it seems possible they’re the least promising set of models because they have all sorts of genetic peculiarities. But all practicality aside, a fascinating paper.

Image Credit: Jon Radoff and Angela Bull in 2002

Citation: Boyko AR, Quignon P, Li L, Schoenebeck JJ, Degenhardt JD, & et al. (2010). A Simple Genetic Architecture Underlies Morphological Variation in Dogs PLoS Biology : 10.1371/journal.pbio.1000451

Inception and the Neuroscience of Sleep | Science Not Fiction

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sleepingChristopher Nolan’s Inception is a film about a time when we have the power to enter into each other’s dreams, and actively steer the dream’s course to implant an idea in the dreamer.

The film raises the issue of how much we understand about the neuroscience of dreams. Due to its need for invasive experiments, neuroscience typically works with non-human animals, which raises a significant difficulty: how do you know that a rat is dreaming? You can’t wake it up from REM sleep and ask. (Well, you can, but don’t expect a cogent response.) There’s no accepted objective indicator that a person or animal is having a dream, as opposed to sleeping. But, we can still learn something useful by looking at the neuroscience of sleep.

The neuroscience of sleep has told us a few important things over the years. For example, we know that our pattern of sleep and wakefulness (the “circadian rhythm”) has much of its basis in the activity of the suprachiasmatic nucleus, a rice-grained-sized group of cells just above where the optic nerves from our eyes crossover. We know that our free running rhythm—what we go to if we are completely in the dark, with no indicator of solar activity—is slightly over 24 hours, and that the length of the rhythm can be affected by things like cannabinoids found in pot. We know that the brain activity of a person dreaming is very similar to that of an awake person—were it not for the fact that our body is paralyzed during dreaming, we’d probably do a lot of things we’d regret.

While we’ve made a lot of progress in understanding sleep, we’ve a long way to go to understand dreaming. What makes it a challenge, perhaps as big a challenge as understanding consciousness itself, is the subjective aspect of dreaming. For example, we know that vivid dreaming occurs during REM sleep in humans. We also know that other animals have REM sleep. Do they also dream? How can we know, since, as I mentioned above, we can’t wake them during REM sleep and ask (the way we determined this fact with humans)? How we can go from objective facts like the presence of REM sleep to subjective ones, like a dream of a pink elephant bouncing down along a high tension power line (from one of my own dreams) is as unclear as how we get from neurons firing to awareness. Nonetheless, significant work has occurred on some of the neuronal correlates of REM sleeping in rodents and songbirds.

The most intriguing result from recent work is that during sleeping, the brain appears to “play back” patterns of activity that occurred during the day. For example, Matt Wilson and colleagues have found that patterns of “place cell” activity — brain cells that light up, like crumbs left on Hansel and Gretel’s path in the woods, corresponding to a specific path that the animal (in these experiments, a rodent) took during the day — and this playback seems to be integral to the animal learning the path it took. In birdsong, from work by Dan Margoliash and others, we’ve learned that birds playback patterns of activity almost identical to singing while they sleep, and again, it seems to be integral to the bird learning its large repertoire of over a million syllables. Why does the brain play back patterns of daytime activity at night? It isn’t completely understood, but some backstory on memory research helps motivate one hypothesis.

It’s been known for some time that a structure called the hippocampus is responsible for acquisition of new memories. Without it, we still have our memories, but anything new that happens is completely lost (think of the movie Memento, one of Christpher Nolan’s previous films) — we are stuck in the continual present. Real-life patient HM taught us this many years ago, after he had this structure removed as part of an experimental operation to cure his epilepsy. He, and many similar cases, lose all memory but for those events that happened some time before the loss of their hippocampus, typically a few months. Over time, the idea has emerged that perhaps the hippocampus “trains” the neural networks in other regions of the brain to store memories through repeated playback during sleep. Like crickets trying to attract females in the night, in the world of memory nothing succeeds like persistent repetition.

So if in REM sleep the brain is repeating patterns of activity from periods of wakefulness, perhaps that process helps the brain to remember, over the long term, the items that are temporarily stored in the hippocampus.

What is not understood from these studies, which were done in rodents and song birds after all, is the basis of all the strange subjective aspects of dreaming — such as how or why in our dreaming we seem to borrow from real experience while adding a good dollop of stuff from elsewhere. This aspect of dreaming seems like it would be crucial in order to have any hope of building a dream experience a la Inception. There is not a whole lot of creative potential in simply regurgitating the day’s brain patterns.

Until these and many other mysteries of dreaming are solved, what the research is showing is that the best way to architect a dream is to architect the experience you have during wakefulness, since dreaming appears to be a lot about learning patterns you were exposed to while awake. Our understanding of the coupling is not clear enough to think about designing dreams by structuring our awake behavior, but perhaps with further research we will come to that point where we can do inception of ideas into our own heads.

Image: Midlands Rat Club
Corrections: Aug 11, 2010: “…neuroscience typically works with animals, rather than humans…” adjusted to “…neuroscience typically works with non-human animals.” Reference to length of circadian rhythm also adjusted.


How to Bring Armageddon the Right Way | Science Not Fiction

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Science fiction without science is merely fiction. There are gray levels in how well the science is portrayed in television and cinema, however. For the third straight year, Discover Magazine and the National Academy’s Science and Enterainment Exchange hosted a science-of-science-fiction panel at San Diego Comic-Con, and this year’s theme was “Abusing Science in Science Fiction.” Each panelist provided two video clips from sci-fi television or cinema: one of science done right, and one where the science, well, wasn’t done right.

I’ve always maintained that in science fiction TV and cinema good science should be jettisoned in deference to drama as a last resort only–and then when you have all your other ducks in a row. If the science is solid in the large bulk of your work, we’ll make the leap with you when you get a bit more… speculative. Some works stick to grounded science well, some do not.

Therefore, for my clips, I chose two instances of the same type of event–the impact of a comet/asteroid with Earth — one done well (Deep Impact), one that could have been done better (Armageddon).

Since Deep Impact’s science is fairly solid, and their science advisor (they actually had one!)Armageddon once told me “We pretty much get our mistakes out of the way in the first five minutes”, there’s little to say. There’s plenty to say with the Armageddon clip I chose — which was the first 40 seconds of the movie. The opening of Armageddon purports to show what is called the K/T Event — the asteroid or comet impact 65 million years ago that caused most of life on Earth, including the dinosaurs, to meet extinction.

The opening narration, done by Charlton Heston doing his best Moses voice, starts out:

It hit with the force of 10,000 nuclear weapons.

Here’s where getting the science right would have improved the drama. To be more correct, Charlton Heston wouild have said:

It hit with the force of over 19 million 1 megaton nuclear weapons.

Or

It hit with a force almost 1.5 billion times the atomic bomb dropped on Hiroshima.

While Charlton narrates, the video shows the impact, and a blast wave traveling over the entire planet. While normally willing to suspend disbelief happily, from a science standpoint this movie lost me in the first 30 seconds when I first saw it in the theatre. The blast would not have traveled that far. What the video could have shown, and Charlton could have described in his best “The Dinosaurs Have Been Smote” voice was the several-hundred-foot-high tsunami that raced away from the impact. Or the chunks of impactor and target rock that fell back to Earth as secondary impacts, setting most of the world’s forests on fire.

What Charlton says instead is:

A trillion tons of dirt and rock hurtled into the atmosphere.

That’s about 1/10 the mass of the impactor (assuming it was an asteroid), so that number isn’t too bad, but, where’s the drama? What is the result of this? He continues with:

…creating a suffocating blanket of dust the sun was powerless to penetrate for a thousand years.

Probably not that long, the dust probably settled out faster than that — without the sun’s life-giving radiation, it would not have taken long for Earth’s ecosystem to collapse.

It happened before. It will happen again.

Yay! They got something right! It’s clear that had the folks who made Armageddon stuck to known science, they could have made this scene simultaneously more realistic and more dramatic.

If you missed the panel, weren’t able to attend Comic-Con, or were turned away at the door because the room was packed, here’s the video:

The “Science of Science Fiction” panel will be back at San Diego Comic-Con again next year — hopefully in a much larger space (and hopefully it will still be in San Diego).


Books nerds like | Gene Expression

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The Less Wrong community is having a book discussion and offering up recommendations. I’m currently reading Lives of Confucius: Civilization’s Greatest Sage Through the Ages (long time readers will know that I’m a particular fan of Xun Zi though). It is revising my view of the “received orthodoxy” as to the development of state sponsored Confucianism during the Han dynasty. A good complement to The Authentic Confucius, which is less a historical work and more a religio-philosophical exegesis of the sage’s life. I did finish Empires of the Word, but I will review it at some point so I won’t say more than I would recommend it, though with a critical eye.

Tropical Depression 5 Forms, Headed for the Gulf Coast | The Intersection

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TD5 Aug 10The good news is that nobody expects it to strengthen much due to environmental conditions.

The bad news is that it is a tropical storm system in the Gulf of Mexico. Period.

That means we’ll have to watch this one closely, and now that storm season is picking up, let me recommend a few blogs to keep track of for hurricane stuff: Eric Berger’s SciGuy, and Jeff Masters’ Wunderblog.

They’re already following the storm and will have more soon, as will I.


The beautifully brutal life of gulls | The Loom

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GullbandingThis week I’m on the Island of Science Writing. Today we wandered rocky coves with Tufts University biologist Julie Ellis, an expert on gulls. She showed us how to catch and band juvenile herring gulls–and how to recognize the matted remains of juvenile herring gulls coughed up by their great black-backed gulls predators. Life here is pretty, and yet not so pretty. But always interesting for writing about.


Brainless slime mould makes decisions like humans | Not Exactly Rocket Science

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Physarum

A couple arrive at a fancy restaurant and they’re offered the wine list. This establishment only has two bottles on offer, one costing £5 and the other costing £25. The second bottle seems too expensive and the diners select the cheaper one. The next week, they return. Now, there’s a third bottle on the list but it’s a vintage, priced at a staggering £1,000. Suddenly, the £25 bottle doesn’t seem all that expensive, and this time, the diners choose it instead.

Businesses use this tactic all the time – an extremely expensive option is used to make mid-range ones suddenly seem like attractive buys. The strategy only works because humans like to compare our options, rather than paying attention to their absolute values. In the wine example, the existence of the third bottle shouldn’t matter – the £25 option costs the same amount either way, but in one scenario it looks like a rip-off and in another, it looks like a steal. The simple fact is that to us, a thing’s value depends on the things around it. Economists often refer to this as “irrational”.

But if that’s the case, we’re not alone in our folly. Other animals, from birds to bees, make choices in the same way. Now, Tanya Latty and Madeleine Beekman from the University of Sydney, have found the same style of decision-making in a creature that’s completely unlike any of these animals – the slime mould, Physarum polycephalum. It’s a single-celled, amoeba-like creature that doesn’t have a brain.

Physarum spends most of its life as a large mat called a ‘plasmodium’, which is a single cell that contains many nuclei. The plasmodium searches for food by moving along like an amoeba and sending out a network of tendrils. Its search patterns are very sophisticated for a brainless organism. A Japanese group found that if they placed the mould among food sources arranged like Tokyo’s urban centres, it created a network that closely resembled Tokyo’s actual railway system. The slimy network was optimised to transport nutrients to the main plasmodium.

Scientists have long since discovered that you can run simple decision-making experiments with Physarum by presenting it with several food sources and seeing how it behaves. Typically, the plasmodium touches all the potential meals and then either ‘decides’ to move towards one, or splits itself among many.

Latty and Beekman did one such test using two food sources – one containing 3% oatmeal and covered in darkness (known as 3D), and another with 5% oatmeal that was brightly lit (5L). Bright light easily damages Physarum, so it had to choose between a heftier but more irritating food source, and a smaller but more pleasant one. With no clear winner, it’s not surprising that the slime mould had no preference – it oozed towards each option just as often as the other.

But things changed when Latty and Beekman added a third option into the mix – a food source containing 1% oatmeal and shrouded in shadow (1D). This third alternative is clearly the inferior one, and Physarum had little time for it. However, its presence changed the mould’s attitude toward the previous two options. Now, 80% of the plasmodia headed towards the 3D source, while around 20% chose the brightly-lit 5L one.

These results strongly suggest that, like humans, Physarum doesn’t attach any intrinsic value to the options that are available to it. Instead, it compares its alternatives. Add something new into the mix, and its decisions change. The presence of the 1D option made the 3D one more attractive by comparison, even though the 3D and 5L alternatives were fundamentally unchanged.

This style of ‘comparative valuation’ may seem uncannily human, but it’s also one that’s shared by hummingbirds, starlings, honeybees and many other animals. In fact, Latty and Beekman think that it’s a “common feature of biological decision-making”. Certainly, it’s a much easier process – comparing two nearby options is less “computationally intensive” than making absolute judgments about each of them.

But how does Physarum make decisions at all without a brain? The answer is deceptively simple – it does so by committee. Every plasmodium is basically a big sac of fluid, where each part rhythmically contracts and expands, pushing the fluid inside back-and-forth. The rate of the contractions depends on what neighbouring parts of the sac are doing, and by the local environment. They happen faster when the plasmodium touches something attractive like food, and they slow down when repellent things like sunlight are nearby.

Despite being a single cell, each part of the plasmodium acts like a tiny individual, reacting to information from its environment. By combining these reactions, the entire plasmodium flows towards things it likes and away from things it doesn’t, all without a single conscious thought. It’s the ultimate in collective decision-making and it allows Physarum to perform remarkable feats of “intelligence”, including simulating Tokyo’s transport network, solving mazes, and even driving robots.

Reference: Proc Roy Soc B http://dx.doi.org/10.1098/rspb.2010.1045

Image by Johnna Gott

More on Physarum: Slime mould attacks simulates Tokyo rail network

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PCA, Razib around the world (a little) | Gene Expression

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price_fig1I have put up a few posts warning readers to be careful of confusing PCA plots with real genetic variation. PCA plots are just ways to capture variation in large data sets and extract out the independent dimensions. Its great at detecting population substructure because the largest components of variation often track between population differences, which consist of sets of correlated allele frequencies. Remeber that PCA plots usually are constructed from the two largest dimensions of variation, so they will be drawn from just these correlated allele frequency differences between populations which emerge from historical separation and evolutionary events. Observe that African Americans are distributed along an axis between Europeans and West Africans. Since we know that these are the two parental populations this makes total sense; the between population differences (e.g., SLC24A5 and Duffy) are the raw material from which independent dimensions can pop out. But on a finer scale one has to be cautious because the distribution of elements on the plot as a function of principal components is sensitive to the variation you input to generate the dimensions in the first place.

I can give you a concrete example: me. I showed you my 23andMe ancestry painting yesterday. I didn’t show you my position on the HGDP data set because I’ve shared genes with others and I don’t want to take the step of displaying other peoples’ genetic data, even if at a remove. But, I have reedited some “demo” screenshots and placed where I am on the plot to illustrate what I’m talking about above. The first shot is my position on the two-dimensional plot of first and second principal components of genetic variation from the HGDP data set.


gsa-lillymendel-worldNo surprise that I’m in the Central/South Asian cluster. But what may surprise you is that I’m not in the South Asian cluster, I’m in the Central Asian cluster. In the Central Asian cluster are Uyghurs and Hazaras. These are two hybrid populations, a mixture of West and East Eurasian elements. The Uyghurs are likely the outcome of a process of admixture between the Iranian and Tocharian Indo-European populations of the cities of the Tarim basin, and later Turkic speaking settlers who arrived in the wake of the expansion and later collapse of the first Uyghur Empire (the historical connection between the current Uyghurs and ancient Uyghurs is tenuous at best, and complicated). The Hazaras are a more recent population, likely emerging as the product of intermarriages between Mongol soldiers who arrived in the 13th century, and indigenous women, Persians, Turks, and assorted Indo-Iranian groups between the Zagros and Khyber Pass. It is somewhat ironic that I’m on the edge of the Hazara cluster since they are almost certainly in part descended from Genghis Khan’s family, and my own surname is Khan. But I know that my Y chromosomal lineage is R1a1, very common across Central and Southern Eurasia, and not a Mongolian one at all.

23andmepcazoomZoom! Now we’ve constrained the input data set to the Central/South Asian groups. First, look at the Kalash. They’re strange, which is no surprise, they’re an inbred mountain group in Pakistan who have not adopted Islam. The Pakistani Taliban looks to be ending them as we speak. I really would prefer that they were just thrown out of the data set for this zoom view, because on this fine grained scale I don’t think they add much at all. They’re just an example of what long term endogamy can do to your allele frequencies. The bigger picture is the axis between the populations of Pakistan, and those of Central Asia. Observe that I’ve changed position. Whereas when taking world wide genetic variation into account I clustered with Central Asians, now I’m 2/3 of the way to the South Asian cluster. I will tell you that I’ve shared “genes” with around 50 South Asians now, from various parts of the subcontinent, and in the 23andMe plot they overlay the South Asians nearly perfectly. I’ve put labels at the approximate ethno-linguistic position. I’m an outlier. 23andMe tells me that I’m 43% “East Asian.” The typical South Asian is in the 10-30% range. My first assumption was that I have a lot of ancient South Indian, which just shows up as East Asian in their algorithm. With this in mind I tried sharing with a lot of South and East Indians, and found out two interesting points. First, South Indians seem no higher than 30-35% East Asian. Bengalis on the other hand are more East Asian, with Bangladeshis more East Asian than West Bengalis. My sample size for Bengalis is small, so take that with caution. Second, the PCA plots put the South Indians firmly in the South Asian cluster, but the Bengalis trail out toward my own position. This indicates again that different methods are telling you slightly different things. The PCA is only a thin slice of variation, but it’s highly informative of between population differences. A Bengali and a South Indian with the same “East Asian” fraction in the ancestry painting nevertheless have consistently different positions on the PCA, with Bengalis closer to the East Asians. Additionally, there’s an ethnic Persian in this zoom plot that I’m describing, and they are positioned near the Balochi. But on the world wide plot they’re on the margins of the European cluster. Another illustration that position of an element is sensitive to the input data because of how the dimensions are generated.

Blaine Bettinger, who inspired me to post this, told a story with his ancestry painting which was plausible. What can I say? First, I have less than 1% African ancestry. This could be noise. But, I do observe that the South Asians with Muslim names are enriched in the set of those who I’ve shared genes with and who have less than 1%, but not 0%, African ancestry. Just as Muslim South Asians have non-trivial West Asian ancestry, I suspect that many of us have Sub-Saharan African ancestry through the same dynamic. Sub-Saharan African soldiers were prominent across South Asia with the arrival of Muslims. Bengal even has a period of rule by Abyssinian rulers. But the bigger issue for me is the East Asian component. Here is a figure from a paper published 4 years ago:

journal.pgen.0020215.g005

The figure is showing Fst value comparing Indian Americans with Europeans and East Asians. Fst measures between population differences in allele frequency, in this case the alleles being 207 indels. Take a look at the Bengalis. These are West Bengalis, who I believe have a lesser East Asian component, but even there the allele frequency difference to East Asians is near that of Europeans. The Assamese, who speak a language very close to Bengali, are similar. Assam was ruled by a Tibeto-Burman people for nearly 600 years. The Oriya speakers, from the southwest of Bengal, are more distant from East Asians. As one goes south and east, and west and north, the distance from East Asians increases. This shouldn’t be that surprising, but nice to confirm. The fact that the genetic distance increases as one goes south means that for northeast South Asia you need to complexify the model from a two-way admixture with “ancient North Indians” and “ancient South Indians.” Set next to these two is an East Asian element, which is also clear in the Indo-Aryan peoples of Nepal.

Sheikh Hasina, Khaleda ZiaOf course anyone who knows Bengalis won’t be totally surprised by an East Asian component to their ancestry. To the left are head shots of the two women who have dominated Bangladeshi politics for the past two decades, Khaleda Zia and Sheik Hasina. They’re both Bengalis, but they do look different, and I know many people who look like one or the other (or a combination). My family is from one of most easternmost districts of Bengali, next to Tripura. In fact my late maternal grandmother lived in Tripura for some of her childhood (she was almost trampled to death by the Maharani of Tripura’s insane elephant as a young girl!). When I was a young child I once saw a black and white photo from my father’s college days, and I was curious who the Asiatic looking young man in the middle of the photograph was. Turns out it was my father! Sometimes our expectations affect how we perceive people. I have never perceived my father to have an Asian cast to his features as a more mature man, but others have told me that he does still exhibit them.

There is still the question of how Bengalis came to have this particular admixture. I think the most plausible scenario probably synthesizes conventional village-to-village intermarriage and isolation-by-distance, along with some component of migrationism. Tribes such as the Chakma have left Burma in historical time. The Chakma of Bangladesh now speak a dialect of Bengali, not their ancestral Sino-Tibetan tongue. I believe that a non-trivial portion of Bengalis have ancestors who were tribal people who shifted their religious identity to that of Hinduism or Islam (from Theravada Buddhism in the case of the Chakma, or animism in the case of the Garos before their Christianization). But eastern South Asia is adjacent to mainland Southeast Asia, and it stands to reason that continuous gene flow would over time would also have introduced East Asian alleles into the Bengali gene pool.

Image Credit: TopNews.in

LHC – First Inverse Picobarn! | Cosmic Variance

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Back in May, I gave a talk at the annual Phenomenology Symposium at UW Madison, showing some of the first physics results from the CMS experiment. At that point we had a data sample of proton-proton collisions corresponding to 1 inverse nanobarn.

This past weekend the LHC crossed a major threshold: 1 inverse picobarn delivered to the experiments – a factor of a thousand more collisions. By late next year we are all hoping to have recorded another factor of a thousand, for a total of 1 inverse femtobarn.

In an earlier post I explained these funny units, inverse whatever-barns. The point here, though, is that as we record exponentially greater numbers of collision events, with the proton beam energy 3.5 times greater than that at the Tevatron at Fermilab we will begin to really probe an unexplored mass scale in the search for new particles. What lies there is completely unknown.

So far the LHC experiments CMS and ATLAS have presented results on about a quarter of the data sample recorded so far, at the biennial International Conference on High Energy Physics, held this year in Paris. To sum it up in a sentence, both experiments have rediscovered our familiar standard model friends, among which the W and Z bosons and the top quark are the most massive.

The W and Z are both produced in proton-proton collisions by the collision of quarks with antiquarks. You should visualize the incoming beam protons as being composed not just of two “up” quarks (charge +2/3) and one “down quark (charge -1/3), but as sort of seething, roiling mass of quarks, antiquarks, and gluons. When the protons collide any two of these constituents, if they have enough energy, can annihilate to form a a W or Z boson.

The W and Z are the “carriers” of the weak force in the standard model. For commonplace processes like nuclear decay (like cesium-137, for example) it’s the weak force which allows it to happen. We describe the process as involving a “virtual” W boson which exists fleetingly, by grace of the uncertainty principle, with a mass thousands of times less than its true mass of 80 GeV. It’s this virtuality that makes the weak force weak, in fact, for nuclear processes.

But at the energies of the incoming proton constituents, there is plenty to make real W bosons, and also Z bosons. (We don’t ordinarily see the effects of Z bosons in nuclear processes, because Z’s can only couple a particle to its own antiparticle…) Now, if you have a real W or Z boson sitting there, it will decay in about 10-23 seconds to a quark and an antiquark or to leptons. In the case of the W, which has electric charge +1 or -1, it decays to a charged lepton and its associated neutrino about 33% of the time, and the rest of the time to quark-antiquark pairs. A Z boson will decay to a charged lepton (e, mu, or tau) and antilepton about 10% of the time, or to a pair of neutrinos about 20% of the time, and the rest of the time to a quark-antiquark pair.

The LHC experiments cannot really see the quark-antiquark decays of the W and Z – there is just too much background from quark-quark, quark-gluon, and gluon-gluon scattering giving two outgoing quarks or gluons. When a quark or gluon emerges sideways from one of these collisions it sort of shatters into a collimated spray of high energy particles that we call a jet. This all is governed by the strong force, which, being stronger than the weak force, has much higher rate than the W- and Z-producing processes.

But, ah, the leptonic decays of the W and Z! The sweetest is the lepton-antilepton decay of the Z. About 7% of the time a Z will decay to an electron-positron pair or a muon-antimuon pair. These particles come screaming out of the collision region into the detector carrying about half the Z’s total mass-energy of 91.2 GeV. This makes them readily identifiable and reconstructible. High energy electrons and muons leave a very straight track in our charged particle tracking system. Electrons then lose all their energy in the dense calorimeter surrounding the tracker. Muons, being 200 times more massive, tend to sail on through the calorimeter and magnet coil out to the muon tracking system that forms the true bulk of the CMS experiment. Here is a cool display of one of the first such events recorded in CMS:

Zmumu

In fact, the astute reader who knows the size of an atomic nucleus will conclude that the muons in the picture above must have traveled straight through quite a number of nuclei to reach the outer parts of the detector! This is because muons interact only via the weak and electromagnetic forces with nuclear matter, and, those forces are quite weak compared with the strong force.

With two muons, one can calculate the mass of the parent particle from which they came, using relativistic formulae. And by ICHEP the CMS experiment had recorded enough muon pair events to make the following beautiful graph showing the spectrum of masses from which opposite sign muon pairs arose. In the plot, at the far right end, the peak from the Z boson at 91.2 GeV is clear as a bell:

mumu

At lower masses one can see the peaks from the upsilon (Y), which is a bound state of a bottom and an antibottom quark, the J/psi which is a bound state of charm-anticharm, and lighter resonances. The broad smear of “continuum” muon pair production comes from virtual photons – the electromagnetic interaction.

These data, and similar data from eletron-positron pairs, is extremely important for calibrating the experiment. By measuring the position of the Z peak we can see whether we have properly calibrated our charge particle momentum scale, and then use that to calibrate the calorimeters via the Z to ee signal. The Z is our standard candle here, but as the saying goes, in high energy physics yesterday’s sensation is today’s calibration (and tomorrow’s background).

All these results and more are there for the world to see at the ICHEP web site. There are plenty more results, including the first glimpse of top-antitop events, and the results of some searches for new phenomena.

Nothing startling has come out yet, and we are eagerly awaiting the exponentially growing samples to analyze, with which we will push past the Tevatron sensitivity in a number of areas. But don’t count the Tevatron out just yet! The CDF and Dzero experiments have recorded thousands of times more collisions and results are still pouring out. And, oops, it’s time for me to go to that CDF analysis meeting now…


I am interviewed in a hot tub | Bad Astronomy

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That was not a typo. My friend/part-time stalker Ashley Paramore interviewed me at TAM 8 during the "Skeptics in the Tub" after-hours get-together. So yeah, we’re in swimsuits, and she interviews me. It was my first time being interviewed in a hot tub, so that all by itself is rather exciting to me. For you, seeing me partially naked may curb that somewhat. YMMV.

The background audio is a bit loud, but it’s not too hard to hear us. The red color is due to low light conditions plus the weird lighting outside at the casino.

As usual when someone interviews me, I’m a smartass for the first few minutes, but then we get down to business: my tattoo, Bad Universe, Universe Today, Pamela Gay, and skepticism. I listened to the interview, and I have to say I pontificate an awful lot for a guy standing around in swim trunks. Still, I’m glad I got a chance to say some of that stuff. The last three minutes or so are actually rather important… they’re important issues to me, but also, I think, to the skeptic community at large. And I’ll have more to say on that subject hopefully soon.


Hawking: If Humans Survive a Couple Centuries, We’ll Get Off This Rock | 80beats

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stephen-hawking-3Listen, people of Earth: Everything’s going to be fine. All we have to do is survive another century or two without self-destructing as a species. Then we’ll get off this rock, spread throughout space, and everything will be all right.

If this is not your idea of “optimism,” then you are not Stephen Hawking. The esteemed physicist garnered headlines, and some eye-rolls, after telling Big Think last week that humanity needs to leave the Earth in the future or face extinction.

He’s not knocking climate scientists’ attempts to figure things out on Earth–he’s just thinking long term. “There have been a number of times in the past when our survival has been touch-and-go,” explains Hawking at Big Think, mentioning the Cuban Missile Crisis, and “the frequency of such occasions is likely to increase in the future…. Our population and our use of the finite resources of the planet earth are growing exponentially along with our technical ability to change the environment for good or ill,” while “our genetic code still caries our selfish and aggressive instincts” [The Atlantic].

Combined with Hawking’s statement earlier this year that it might be dangerous to contact aliens because they could come and wipe us out, the physicist’s latest warning makes it feel like he’s increasingly a member of the gloom-and-doom crowd. But not so. He’s just the kind of person who thinks on the long, long term.

Let’s jump back to another publicly engaged scientist: Carl Sagan’s message in Cosmos that the stars await… if we don’t destroy ourselves.

Sagan was pushing urgency and vigilance, not gloominess. The same, I think, is true of Hawking—it’s why he calls himself an “optimist” despite his dire warnings of treacherous times ahead. Indeed, he says, if humanity can just get past the next 200 years without driving itself to extinction, then we’re good to go. Once we spread to different locations in space, no event contained to a single world—even a catastrophic one like all-out nuclear war or a massive asteroid strike—could do in the species by itself.

Hawking concludes the Big Think message about the necessity of a human future in space by saying, “That is why I’m in favor of manned, or should I say ‘personed’, space flight.” That is: Putting people back on the moon or take them to Mars wouldn’t be just a vainglorious gesture. The next phase of humanity demands it.

He’s far from the only one thinking far into the future. Take DISCOVER blogger Phil Plait, who, in his book Death from the Skies!, discusses audacious plans for our descendants to take way, way down the line to survive the slow dying and then death of the sun. (For a culture so plugged into now, it seems laughable to consider something billions of years down the line. But where Hawking may be proven wrong in his 100-200 years statement, he is clearly correct about the options for humanity’s long-term future: We’ll either leave the Earth or die before we get the chance.)

Or, if you want to go all the way to the far end of the optimism spectrum, take another future-obsessed theoretical physicist: Michio Kaku, whom I interviewed about his TV show Sci-Fi Science for the September issue of DISCOVER, on newsstands now. The outline of a Type I, or global, civilization is now emerging on the Earth, he says, with the Internet and even type I sports—like the FIFA World Cup. And whether or not you agree humans are doomed if they don’t leave the Earth for points beyond, he believes our future is out there.

“It’s not guaranteed we’ll [even] hit Type I,” he says. “But I’m optimistic.”

Related Content:
80beats: Stephen Hawking, For One, Does Not Welcome Our New Alien Overlords
DISCOVER: Stephen Hawking Is Making His Comeback
DISCOVER: Inside the World of Stephen Hawking
DISCOVER: Hawking’s Exit Strategy
Cosmic Variance: Hawking: Beware the Alien Menace!
Bad Astronomy: In Which I Disagree With Stephen Hawking

Image: NASA


Look at the Size of That Chinchilla Poop–to Know How Much It Rained | Discoblog

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chinchillaThe bigger the fossilized feces the more ancient rain. A team of paleontologists has uncovered this apparent correlation during a study of chinchilla scat at nine sites in South America’s Atacama Desert.

Claudio Latorre Hidalgo of Pontificia Universidad Católica de Chile in Santiago presented his findings on this rainfall metric at a talk held yesterday during the ongoing American Geophysical Union’s Meeting of the Americas. Science News, where we found the story, reports that Latorre Hidaglo looked at fossilized feces from middens–shared rodent poop piles that contain “fecal pellets cemented together by crystallized urine.”

Latorre Hidaglo’s team carbon dated organic bits from the largest twenty percent of the chinchilla pellets (so as to exclude pellets from rodent youth). Given information on rainfall from other sources, they correlated the larger feces with periods of greater rainfall. According to Science News, Latorre Hidaglo suggests that the more rain, the better the environment to support bigger chinchillas; the bigger the chinchillas, the bigger the chinchilla poop. The poop test, the researchers say, may provide a way to estimate past rainfall when other tests aren’t available.

The American Geophysical Union talk announcement advises researchers to keep digging into the middens for more information:

A correlation between the size of rodent droppings and rainfall quantities is enabling researchers to establish a new paleoclimate record. Plus, a study of the contents of middens accumulated long ago by rodents offers further insights into the Atacama’s past.

Related content:
Discoblog: Is Muskrat Poop the Next Penicillin?
Discoblog: Archeologists Find the Darnedest Things Digging Around in Hyena Poop
Discoblog: To Maintain Clean Nests, Social Insects Hold in Poop for a Very Long Time
Discoblog: Whale Shark Poops on Camera; Scientists Rejoice

Image: wikimedia / Rumpelstiltzkin


Has the Devilish Math Problem “P vs NP” Finally Been Solved? | 80beats

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VinayP is not equal to NP. Seems simple enough. But if it’s true, it could be the answer to a problem computer scientists have wrestled for decades.

Vinay Deolalikar, who is with Hewlett-Packard Labs, has sent to peers copies of a proof he did stating that P is not equal to NP. Mathematicians are reviewing his work now—a task that could go on for a long time. If he’s correct, Deolalikar will have figured out one of the Clay Mathematics Institute’s seven Millennium Prize Problems, for which they give $1 million prizes. (Grigory Perelman won one of the seven for solving the Poincaré conjecture, but turned down the money last month.)

What’s all the hubbub? First, an explainer:

The P versus NP question concerns the speed at which a computer can accomplish a task such as factorising a number. Some tasks can be completed reasonably quickly – in technical terms, the running time is proportional to a polynomial function of the input size – and these tasks are in class P. If the answer to a task can be checked quickly then it is in class NP [New Scientist].

That definition is pretty abstract, so here’s a more concrete example:

Clay imagines a college housing scenario wherein 400 students have applied for rooms at a college that can only accommodate 100 of them. A selection of 100 students must be paired together in rooms, but the dean of students has a list of pairings of certain students who cannot room together. The total possible number of pairings is ridiculously large — more than the total number of atoms in the universe — but the solutions, i.e. the list of pairings finally provided to the dean, is easy to check for errors: If one of the dean’s prohibited pairs is on the list, that’s an error [AOL News].

Thus, if P were equal to NP, it would mean that problems that are easy to check—like this roommate match-up—must also be easy to solve. But if Deolalikar is correct and in fact P is not equal to NP, as many mathematicians already believed, then that ain’t necessarily so. And that would have practical meaning, according to Michael Sipser of MIT.

Sipser … says that the P-versus-NP problem is important for deepening our understanding of computational complexity. “A major application is in the cryptography area,” Sipser says, where the security of cryptographic codes is often ensured by the complexity of a computational task. The RSA cryptographic scheme, which is commonly used for secure Internet transactions — and was invented at MIT — “is really an outgrowth of the study of the complexity of doing certain number-theoretic computations,” Sipser says [MIT News].

Deolalikar’s proof is now available to read online. New Scientist and Network World report that he pulled together tactics from different disciplines to show that an NP problem—whether a list of statements can be simultaneously correct or contradict one another—is not a P problem, because it can be easily checked but no computer can figure it out quickly from scratch.

In the days since the proof began to spread across the Internet, however, some math bloggers like Scott Aaronson have responded to the proof by saying yes, it’s lovely, but no, it probably isn’t going to stand.

Related Content:
80beats: Brilliant & Reclusive Russian Mathematician Doesn’t Need Your Prize Money
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Image: HP Labs