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Nov 13

Blood camera to spot invisible stains at crime scenes.

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Reported by Helen Knight 12 November 2010 in NewScientist

Hands off...(Image: Henning Kaiser/AFP/Getty Images)

Call it CSI: Abracadabra. A camera that can make invisible substances reappear as if by magic could allow forensics teams to quickly scan a crime scene for blood stains without tampering with valuable evidence.

The prototype camera, developed by Stephen Morgan, Michael Myrick and colleagues at the University of South Carolina in Columbia, can detect blood stains even when the sample has been diluted to one part per 100.

At present, blood stains are detected using the chemical luminol, which is sprayed around the crime scene and reacts with the iron in any blood present to emit a blue glow that can be seen in the dark. However, luminol is toxic, can dilute blood samples to a level at which DNA is difficult to recover, and can smear blood spatter patterns that forensic experts use to help determine how the victim died. Luminol can also react with substances like bleach, rust, fizzy drink and coffee, causing it to produce false positives.

The camera, in contrast, can distinguish between blood and all four of these substances, and could be used to spot stains that require further chemical analysis without interfering with the sample.

To take an image of a scene, the camera beams pulses of infrared light onto a surface and detects the infrared that is reflected back off it. A transparent, 8-micrometre-thick layer of the protein albumin placed in front of the detector acts as a filter, making a dilute blood stain show up against its surroundings by filtering out wavelengths that aren’t characteristic of blood proteins.

By modifying the chemical used for the filter, it should be possible to detect contrasts between a surface and any type of stain, says Morgan. “With the appropriate filter, it should be possible to detect [sweat and lipids] in fingerprints that are not visible to the naked eye,” he says. “In the same way you could also detect drugs on a surface, or trace explosives.”

Read more in Analytical Chemistry, DOI: 10.1021/ac101107v

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Nov 11

Data-Driven Computer Science

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Submitted by Edward Benson on Monday, 22 March 2010 in Haystack Blog MIT CSAIL Research

Does a growing segment of computer science have more in common with particle physics than algorithm design?

Consider five small factoids:

  • When David Karger posted about List.it’s growing user adoption (more than 14,000!) a few weeks ago, the primary benefit he cited were the mounds of usage data the Haystack group now has available to analyze
  • Any major systems conference today is bound to have several star papers from the big industry players — Google, Yahoo, Microsoft, Facebook, etc — containing research made possible by company-proprietary data sets
  • Academics in natural language processing struggle to compete with companies like Google when it comes to algorithms that need lots of data. Google simply has so much data, and so many computers, that they can do heavy computational lifting others can not.
  • One of the prizes in Yahoo!’s Key Scientific Challenges contest is access to a portfolio of their private data sets for research
  • The Eyebrowse project is motivated, in part, by the fact that as researchers, we have no idea how people actually use the web. This is the sole privilege of companies like Google, Microsoft, and Yahoo! that own and run advertisement networks that track your movements across the web. Among other things, Eyebrowse is a research project to help researchers gain access to this information.

It is clear that there is a growing subset of computer science that is not about computers, but rather about the information we suddenly have available as a result of computers. What’s interesting is that this new type of study is found scattered throughout the subfields of computer science, yet it is distinctly different in nature than traditional computer science research. This begs the question of whether we need to adapt our existing approaches to research and education to reflect this new type of work.

Does the research start at the generation of the data set, for example, or the analysis of it? This is an incredibly important question because a good data set will make or break a research paper. Should PhD students be spending their first two years building and marketing a platform — essentially running a startup company — and then the following four years analyzing the usage data it generated? Should they take a lesson from Business School students and embed themselves in corporations, providing them access to proprietary data sets for study? Should they limit themselves to studying only public data sets?

Who pays to build data sets? Good data sets are expensive to obtain. Particle physicists spend billions of dollars constructing particle accelerators just so they can record a few milliseconds of good data. But governments willingly provide the money and resources to help them gather this data because there isn’t a market for gluon data. There is, however, a market for your social networking behavior and web advertising clicks, so we shouldn’t hold our breaths waiting for the NSFs of the world to fund a multi-billion dollar social network just to gather behavioral data.

Should we require researchers to publish data sets alongside their papers? My sense from biology students is that some biology labs today defensively guard their data to make sure they beat others to publication. How do we avoid data hoarding while still respecting the fact that generating a good data set takes a lot of insight and work?

If trends continue, datasets will become an increasingly important fuel for computer science research. Hopefully we can learn from the other scientific disciplines about how to cope with being data-driven and adopt community standards that encourage an environment of collaboration and sharing.

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Nov 07

Soccer: Is scoring goals a predictable Poissonian process?

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By A. Heuer1, C. Müller1,2 and O. Rubner in EPL (Europhysics Letters), Volume 89, Number 3

1 Westfälische Wilhelms Universität Münster, Institut für Physikalische Chemie – Corrensstr. 30, 48149 Münster, Germany, EU
2 Westfälische Wilhelms Universität Münster, Institut für Organische Chemie – Corrensstr. 40, 48149 Münster, Germany, EU

Abstract

The non-scientific event of a soccer match is analysed on a strictly scientific level. The analysis is based on the recently introduced concept of a team fitness (Eur. Phys. J. B, 67 (2009) 445) and requires the use of finite-size scaling. A uniquely defined function is derived which quantitatively predicts the expected average outcome of a soccer match in terms of the fitness of both teams. It is checked whether temporary fitness fluctuations of a team hamper the predictability of a soccer match. To a very good approximation scoring goals during a match can be characterized as independent Poissonian processes with pre-determined expectation values. Minor correlations give rise to an increase of the number of draws. The non-Poissonian overall goal distribution is just a consequence of the fitness distribution among different teams. The limits of predictability of soccer matches are quantified. Our model-free classification of the underlying ingredients determining the outcome of soccer matches can be generalized to different types of sports events.

Read more in EPL(Europhysics Letters) 89 38007, 2010. 

If you like it, you can also read:

  1. Self-affirmation model for football goal distributions
  2. Beckham as physicist?
  3. An image recognition system for the measurement of soccer ball spin characteristics
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Nov 06

Quantum computing: Quantum RAM

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Miles Blencowe1 in Nature 468, 44-45 (4 November 2010) | doi:10.1038/468044a; Published online 3 November 2010

Abstract

Hybrid quantum systems have been suggested as a potential route to building a quantum computer. The latest research shows that they offer a robust solution to developing a form of random access memory for such a machine.

Most of us have shared the frustration of a desktop computer grinding almost to a halt when running a data-intensive application — opening a high-resolution digital photograph, for example — or running one application too many at the same time. Some have also experienced the (usually short-lived) improvement in speed that comes from installing expensive additional memory called random access memory (RAM).

  1. Miles Blencowe is in the Department of Physics and Astronomy, 6127 Wilder Laboratory, Dartmouth College, Hanover, New Hampshire 03755, USA.
    Email: miles.p.blencowe@dartmouth.edu

 Read more in News & Views, Nature 468, 44-45 (4 November 2010)

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Nov 03

Ozzy Osbourne’s Genome Reveals Some Neandertal Lineage

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Reported by Katherine Harmon, October 26, 2010 in Scientific American

What genetic oddities does rock’s Prince of Darkness and beheader of bats have entangled deep in his genetic code? Knome, the company that analyzed Ozzy’s full genome, divulges some of the details in a Q&A

Ozzy Osbourne HEAVY MENDEL: Scientists have thousands of interesting new mutations uncovered in Ozzy Osbourne’s genome to puzzle over. Image: WIKIMEDIA COMMONS/KAISERJNR

The one-time front man for heavy metal band Black Sabbath has joined the likes of DNA co-discoverer James Watson and Harvard University professor Henry Louis Gates on the short roster of people to have their full genome sequenced and analyzed.

Ozzy Osbourne let a little blood to submit to the testing in July. Cofactor Genomics, a Saint Louis–based company, sequenced Osbourne’s genome; Knome, Inc., which also helped raise money for the project, analyzed the data.

For his part, Osbourne was at first skeptical about the project, he explained in his October 24 Sunday Times of London column. But the platinum-record artist then began to wonder if he, in fact, might have something to offer science.

“I was curious,” he wrote in his column. “Given the swimming pools of booze I’ve guzzled over the years—not to mention all of the cocaine, morphine, sleeping pills, cough syrup, LSD, Rohypnol…you name it—there’s really no plausible medical reason why I should still be alive. Maybe my DNA could say why.”

But what can a bunch of genetic code tell us about someone’s propensity to become the ordained “Godfather of Heavy Metal” or to bite the head off a live bat on stage?

Scientific American spoke with Jorge Conde, co-founder and chief executive of Cambridge, Mass.–based Knome, and Nathan Pearson, the company’s director of research, who had sat down with Ozzy earlier to go over the results of the analysis.

Ozzy and his wife Sharon Osbourne will also relay some of the results—more “Down to Earth” than via “Ozzmosis”—Friday at the TEDMED 2010 meeting in San Diego.

[An edited transcript of the interview follows.]

Why did Ozzy want to have his genome sequenced?
Jorge Conde: The main question for Ozzy was: Is there any information in there that could explain Ozzy?

I think he was curious about how he had managed to survive a pretty hard life in a lot of ways. So there were some questions around that—how substance use had affected him and how he metabolized things. He was also interested in specific health questions—he was diagnosed with a Parkinson’s-like condition. He was also very interested in what we could tell him about his ancestry.

Nathan Pearson: He was really curious to know about his Parkinson’s-like symptoms, so we looked pretty closely in his genome for that kind of stuff. We found a few hints, but we couldn’t tell him why he has symptoms like a tremor. And frankly, his history of drug abuse probably contributed to that, too.

He asked us good questions about dopamine. Many of the variants in his genome are about how the brain processes dopamine.

Is Ozzy the first rock star to have his full genome sequenced?

Conde: Yes, as far as I know. I can definitely tell you he’s the first prince of darkness to have his genome sequenced and analyzed.

Can we see in his genome any traces of his legendary rock-and-roll lifestyle—or evidence of his body’s efforts to repair any damage?
Conde: We cannot find the “Ozzy Osbourne” gene. But what we did see, as one of our scientists refers to it, is a lot of interesting smoke—but not any specific fire. We found many variants—novel variants—in genes associated with addiction and metabolism that are interesting but not quite definitive.

So can his genomes tell us anything about his ability to survive so many years of hard partying?
Pearson: I talked with Ozzy, and we looked at the genome with an eye toward the nerves. If you think about what makes Ozzy unusual, it’s that he’s a world-class musician, he has an addictive personality, he has a tremor, he’s dyslexic, he gets up very early in the morning. And many of these can be traced back to the nervous system.

One variant involves a gene that makes CLTCL1, which is a really interesting protein. When a cell takes in things from the outside membrane, it pulls itself in like a basket to pull things in. It does this in all kinds of cells, including nerve cells. He has two copies of an unusual variant that makes a grossly different version of the protein than most people produce. Here’s a gene that’s central to how nerve cells communicate with each other, so it’s curious to us to see a grossly different protein variant. It’s thought provoking.

We didn’t find anything that can explain to you from point A to point B why Ozzy can think up good songs or why he is so addicted to cocaine, but we found some things that would be interesting to follow up on.

Such as?
Pearson: Alcohol dehydrogenase genes. They’re involved in breaking down alcohol when you drink. Ozzy has an unusual variant near one of his alcohol dehydrogenase genes, ADH4, that help regulate how much of the protein gets made. Given his troubles with alcohol in the past, obviously we would like to clarify why his body responds differently than other people’s.

Did his genome show any predisposition for serious diseases?

Pearson: He’s a 61-year-old healthy guy, and that speaks for itself. That suggests he’s done okay in the genetic lottery.

It also speaks to how early on we are in this field. Genome-wide association studies are notoriously weak in identifying variants that strongly determine our health. They look at variants that are common in the population. Those are easy to look at, but variants don’t get to be common in the population if they’re very harmful. It’s clear now that you have to look also—and especially—at rare variants. And like everyone, Ozzy carries several hundred thousand variants that have never been seen by scientists. It’s going to be a while before we get enough data as a society to understand those variants.

Were there any big surprises hiding in his genome?
Pearson: For a long time we thought that Neandertals didn’t have any descendents today, but it turns out that Asians and Europeans have some evidence of Neandertal lineage—like a drop in the bucket. We found a little segment on Ozzy’s chromosome 10 that very likely traces back to a Neandertal forebearer.

Ozzy, of course, was tickled to hear this. But Knome founder George Church‘s genome has about three times as much Neandertal, which we thought was funny.

What has Ozzy’s response to the findings been so far?
Pearson: From what I can tell, Ozzy was really very sincerely interested in this. He is really very engaged. As I was leaving Ozzy’s home, I was in the atrium—and I think he had thought I had already left for my cab, but I could hear him say to his assistant [in an Osbourne-like accent], “That was really interesting.”

What can we learn from Ozzy’s genome?

Pearson: I think one lesson is understanding music. It’s a pretty interesting thing we do at humans—that some of us can synchronize to a beat, that we like to sing songs. But we don’t understand it well genetically, so one of the open questions is we’ll get a better understanding of what makes a good musician, what kinds of variants help us keep a beat, make a good tune. I think looking ahead, sequencing the genomes of more musicians would be a good idea.

If you could sequence any other celebrity genomes, whose would you choose?
Pearson: Ozzy suggested Keith Richards. Our partners who did the sequencing suggested we sequence Ozzie Smith, the baseball player, as a control. He’s always been a good teetotaler.

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