Bench Press

A picture may be worth a thousand words, but a video is worth, depending on the frame rate, a thousand pictures.

We previously posted a breathtaking set of pictures showing just how large the universe really is. But, although the images conveyed a sense of what is now referred to as the Ultra Deep Field but you haven’t seen anything, until you’ve watched a video construction of what the ultra-deep field looks like in 3D (courtesy of Tony Darnell at DeepAstronomy.com):

The key quote from the video:

“We pointed the most powerful telescope ever built by human beings at absolutely nothing for no other reason than because we were curious, and discovered that we occupy a very tiny place in the heavens.”

My thoughts:

1. Did you not get it just by watching the video? We occupy a very tiny place in the heavens.
2. Science video is a great way of reaching out to the public and communicating in a way that pure pictures and text cannot.
3. There’s something to be said about the spirit and essence of the scientific community: willing to explore “nothing” for the sake of exploring it, and still deriving great value from it.

If you like the video, check out Tony’s very informative (and amateur astronomer-friendly) site.

We previously discussed using the powerful Wolfram|Alpha tool to look up medical/biological information, but did you know it also works for astronomical information also?

The Wolfram|Alpha blog lists a couple of great tricks, including:

• the ability to identify the stars in the sky based on your location
• looking up information about a specific star’s distance, brightness, spectral class (astronomy nerds out there know the “Oh Be A Fine Girl Kiss Me!” classification system), mass, and even surface temperature!
• looking up information about the next lunar and solar eclipses, sunrises, and sunsets
• looking up general information about the planets in the solar system

What I find most impressive, however, is Wolfram|Alpha’s ability to generate graphical depictions of the information you’re looking for, whether it be understanding what you’ll see when you look up in the sky:

Visualizing the path of the sun for a particular day:

Or getting a sense of the 3-body-configuration of the sun, moon, and earth:

Chalk this up as yet another cool thing you can do with Wolfram|Alpha!

(Image credit: Wolfram|Alpha and Wolfram|Alpha blog)

Previously, Ben wrote a post about innovative use of the virtual world Second Life for simulating N-body problems. One of the groups behind the impressive OpenSim mod, the Meta Institute of Computational Astrophysics (MICA), is incredibly unique in that the organization itself is an exploration into the utility of emerging virtual world (VW) technologies (e.g. SecondLife) for scientific and academic work.

A group of scientists from the California Institute of Technology, Princeton, Drexel University, and the Massachusetts Institute of Technology founded MICA in the spring of 2008 in order to explore and take advantage of what they saw as a new frontier in collaboration and information dissemination. MICA’s goals are¹:

• Exploration, development and promotion of VWs and VR technologies for professional research in astronomy and related fields.
• To provide and develop novel social networking venues and mechanisms for scientific collaboration and communications, including professional meetings, effective telepresence, etc.
• Use of VWs and VR technologies for education and public outreach.
• To act as a forum for exchange of ideas and joint efforts with other scientific disciplines in promoting these goals for science and scholarship in general.

In addition to the collaborative research we’ve written about before MICA also “conducts weekly professional seminars, bi-weekly popular lectures, and many other regularly scheduled and occasional professional discussions and public outreach events, all of them in [SecondLife].” A screenshot of one of their astrophysics seminars can been seen below. MICA has also begun experimenting with various teaching formats for undergraduate and graduate level courses.

MICA members attending a weekly astrophysics seminar by Dr. M. Trenti, given in the StellaNova sim in SecondLife.

What really impresses me about MICA however is their belief in the platform.

[W]e wish to lead by example, and demonstrate the utility of VWs and immersive VR environments generally for scientific research in fields other than humanities and social sciences (where we believe the case is already strong). In that process, we hope to define the “best practices” and optimal use of VR tools in research and education, including scholarly communications. This is the kind of activity that we expect will engage a much broader segment of the academic community in exploration and use of VR technologies. Second, we hope to develop new research tools and techniques, and help lay the foundations of the informational environments for the next generation of VR-enabled Web.

Hopefully MICA’s innovative use of SecondLife will prompt other scientists to follow. I definitely want to check out one of the lectures one of these days.

(Exploring Use of Virtual Worlds as a Scientific Research Platform: The Meta-Institute for Computational Astrophysics)

We’ve mentioned before the power of Cloud Computing as a means of expanding the computational power in the hands of researchers and scientists (by “outsourcing” it to someone with excess computing capacity like Amazon or Google), such as those at CERN studying high-energy particle physics. So, it was very heartwarming to see a Chemical & Engineering News cover story on the use of new cloud computing systems by large biotech/pharmaceutical companies like Genentech, Pfizer, and Eli Lilly.

Lilly has demonstrated the viability of cloud computing in pharmaceutical R&D, according to Dave Powers, the firm’s associate information consultant for discovery IT. "We were recently able to launch a 64-machine cluster computer working on bioinformatics sequence information, complete the work, and shut it down in 20 minutes," he says, describing a project the firm executed using Amazon’s Elastic Compute Cloud (EC2) service. "It cost $6.40. To do that internally—to go from nothing to getting a 64-machine cluster installed and qualified—is a 12-week process."

What was most interesting about the article was the assessment of the cost/benefit analysis that the companies each went through before adopting the technology, something which is important to understand both for researchers/companies interested in adopting cloud computing techniques as well as for technologists/developers striving for broad adoption of their own special technologies. This particular case is especially enlightening as it flips the conventional wisdom – who said that all pharma IT systems and managers are slow to embrace change?

There are 4 key factors that seemed to play a role in “tipping” the large bio/pharma companies: (1) cost, (2) maturity, (3) third parties, and (4) the ability to achieve sizable benefits on a number of scales.

1. Cost: This is usually the “easy” part of new technologies. After all, if a technology is being considered as an alternative to conventional approaches, it usually has major cost or efficiency advantages. In this case, Cloud promoters/IT experts were able to make the case that the cost of buying, setting up, qualifying, and supporting IT infrastructure needed to support all internal demand for computing resources was much greater than the cost of outsourcing some computing needs to Cloud Computing providers. This cost, of course, is measured not only in terms of IT dollars spent,  but also in terms of the time needed to set up, qualify, and develop the necessary IT infrastructure as well as the potential dollars a company might lose by being less nimble.
2. Maturity: One of the major obstacles that new technologies face is that nobody trusts them. After all, why trust a new player with an unproven product for your ultra-important needs (especially when your job is on the line if your needs aren’t fulfilled), when your current setup is working “good enough”? In the case of Cloud Computing, however, the availability of well-known vendors (Microsoft, Google, Amazon, Rackspace, etc) who have had years of experience developing their own systems and product offering has been instrumental in wearing down the traditional resistance that new technologies tend to face. Amazon, especially, has built a well-known cloud platform (their Elastic Compute Cloud more commonly referred to as EC2), with:
   • Easy-to-use web interface
   • Range of offerings that are attractive to many customers (e.g. targeted offerings which distinguish the needs of web application providers versus high-performance scientific computing clusters)
   • Support for standard enterprise software to minimize the amount of re-work that CIOs/IT people will need to do
   • Professional SLA (service-level agreement) which legally obligates Amazon to provide a certain level of service
   • Simple billing system
3. Third party: The existence of third party players on a particular type of technology provide two things to companies interested in adopting a new type of technology. First, it is proof of a concept’s maturity. If a technology really is great, then there will be companies that aim to provide services or add-on products for users of that technology. Second, it simplifies the job of using the technology, as there will be companies who specialize in providing support and useful add-ons. In the case of Cloud Computing, there are a number of providers who specialize in helping companies deploy Cloud computing software or manage their use of computing resources. Companies like Eucalyptus and CycleComputing can provide support (for a fee) for companies interested in setting up their own cloud, and open source projects like Hadoop and research papers on how to use Amazon’s EC2 to do proteomics research not only validate Cloud Computing but provide free advice on how to set up research “clouds”!
4. Benefits achievable on multiple scales: Too often, new technologies promise grand benefits which can only be realized on very specific scales. Small pilots and full-scale transformations are not how companies make decisions and do not reflect the reality of how technology is used. Technology that only delivers significant benefits in small pilots or only work if all old technology is replaced by a new one will be very challenging to adopt. The beauty of the Cloud efforts detailed in the article is that they cover a wide range of scales. Benefits are easily realized regardless of if you outsource your entire IT infrastructure, or if you choose to only use the Cloud some of the time, or selectively avoid using the Cloud when regulatory concerns dictate it.

This is not to say that the adoption of cloud computing in these cases went perfectly smoothly. Amazon does experience service outages and there are still issues to be sorted out regarding SLAs and regulatory concerns, but their adoption by companies in an industry known for conservative IT practices is something that can and should be learned from.

(Image credit)

The heartbeat of the news.

Ever since June 25, 2009, Michael Jackson’s death has been the talk of the nation, his face plastered over web articles, newspapers, and television stations. His death broke the record for the number of users on Yahoo news at any one point in time, topping even President Barack Obama’s inauguration, and even Google believed its servers were under attack due to the sudden spike in web searches for the moon-walking legend. However, have you ever wondered why the news of the King of Pop’s untimely death has stayed in the media for so long, while other news topics, such as the death of another cultural icon, Farrah Fawcett, quickly died out?

Jon Kleinberg, Jure Leskovec, and Lars Backstroma, from the computer science department at Cornell, sought to answer these types of questions by tracking the life-cycle of news articles for a three month period during 2008. Their research included 20,000 mainstream media sites and over 90 million articles. Using a complex algorithm which could identify certain phrases in different news articles such that the computer could mark them as being of the same subject (a task that has proven to be very difficult time and time again), the team tracked the movement of news using across blogs and news sites across the Internet. Armed with an extensive pool of data to sift through and analyze, the three researchers discovered an astounding pattern that was shared throughout most news topics.

They found a consistent rhythm as stories rose into prominence and then fell off over just a few days, with a “heartbeat” pattern of handoffs between blogs and mainstream media. In mainstream media, they found, a story rises to prominence slowly then dies quickly; in the blogosphere, stories rise in popularity very quickly but then stay around longer, as discussion goes back and forth. Eventually though, almost every story is pushed aside by something newer.

Before research like this was done, many editors and journalists perceived something they described to be a “news cycle.” However, with no quantifiable data, there was no way to be confident whether this was just their perceptions or an actual phenomenon. With the information collected by these Cornell researchers, they believe the latter to be the case and have started to create mathematical models which would accurately describe the life-cycle of news.

The slow rise of a new story in the mainstream, the researchers suggest, results from imitation – as more sites carried a story, other sites were more likely to pick it up. But the life of a story is limited, as new stories quickly push out the old. A mathematical model based on the interaction of imitation and recency predicted the pattern fairly well, the researchers said, while predictions based on either imitation or recency alone couldn’t come close.

This type of news excites me because it shows how technology and the Internet have produced a tangible result (in this case, a physical model to the life cycle of a news article) to a question that would have been unsolvable 20 years ago. Truly the capabilities of technology to solve even the most abstract problems are limitless.

(Image Credit)

One of the ways in which scientists can reach out to the public with new social media techniques is through online video, and this is a lesson that the University of Nottingham has learned well. This past week, I found three informative sites that scientists at the University of Nottingham have contributed to:

• Sixty Symbols – a site dedicated to helping the layperson understand those crazy symbols that they see in physicist’s and astronomer’s equations and work



• Periodic Table of Videos – a site which has an informational video for nearly every element in the periodic table
• Test-Tube – an award-winning site which tries to document the daily life of a scientist, including the triumphs, failures, and the monotony/drama that occurs in between

The interesting thing, at least to me, is that the videos succeed not only in conveying interesting concepts in, hopefully, an easy-to-understand format, but that they do what textbooks and slides and figures and online encyclopedia’s can never do: they humanize the science and the scientists behind them. And, if that happens effectively, then social media may be the most powerful scientific tool ever.

If you read our last post on the N-body problem and want to try your hand at playing around with simulations of this enduring problem, then this article from Wired Science may be music to your N=2 ears. A group of developers from virtual world developer Genkii and astrophysicists from the Meta Institute of Computational Astrophysics have put together a simulation tool using the open source OpenSim (an implementation of Linden Lab’s popular SecondLife virtual world engine) to run N-body problem simulations and aim to publish their results in the Journal of Virtual Worlds Research.

As to why the developers chose to use OpenSim (from their ArXiV pre-print):

“From the point of view of an astrophysicist dealing with gravitational N-body simulations, virtual worlds such as OpenSim are N-body simulators, with two extra features: a surprisingly elaborate graphics module, and a bug in the equations of motion. As to the latter: whereas objects should attract each other via Newton’s inverse-square law of gravity, objects in OpenSim fall straight down. However, that “bug” is easily fixed. We have done so, and we discuss our first results in this paper.”

The most interesting aspect of this work is not only that it was possible, but that, should virtual world administrators choose to allow it, these tools can be bundled into almost any virtual world running off an OpenSim compatible setup!

We have modified the standard physics engine of OpenSim using a plugin. Server administrators can select to replace the standard physics engine with our plugin at server-initialization time, region by region … Though [the example above] shows only one avatar in view on a remote “desert island,” a similar simulation could, in principle, take place anywhere on an OpenSim grid, and any user present could collaborate to construct the initial conditions, discuss the outcome with other avatars, save data from the simulation, etc.

Now, the current simulation has a limit: it can only simulate up to 50 bodies – but I’d like to think of this as just one powerful example of how virtual world technology might be used in the future to power new types of simulations and empower scientists to collaborate over them.

(Image credit: ArXiV pre-print of publication)

The “2.0” moniker is often abused to hype up connections with the new dynamic web applications of today. This is why I’ve co-opted it to describe a new application which is to WebMD’s 1.0 as Gmail/Twitter are to old-school webmail/message boards.

As many of you know, WebMD is a leading health information internet portal, providing a wide range of medical information for both casual patients who browse the site and medical professionals. But, while the information WebMD provides is rich and valuable, it is still a static website, valuable, but not dynamic or intuitive or mobile.

Wolfram Research (maker of popular computational algebra system/scientific computing software Mathematica)’s new WolframAlpha search engine attacks the first two challenges. One of the fundamental problems with traditional portals like WebMD is that to find specific information, the user needs to have some idea of where the information is or how it’s stored/used in conjunction with other information – in other words, it requires contextual knowledge. For example, to figure out how to determine if someone is overweight, the user needs to know:

1. That BMI is the relevant metric
2. Where to find how to calculate BMI and where/how to get the information that goes into the BMI formula
3. Compare BMI with relevant comparisons
4. Understand the limitations and implications of the BMI metric

WolframAlpha tries to simplify this by reducing the dependence of the quality of the search results on contextual knowledge. In the BMI example above, WolframAlpha hasn’t quite solved how to easily and quickly answer steps 1 and 4, but it has made it much easier to do steps 2 and 3. For instance, the BMI of a person who is 5’ 10” and weighs 165 lbs and the relevant comparisons (to the US population as a whole, and to clinical definitions of “overweight”, etc.) What’s incredible is that WolframAlpha won’t only provide you with the data, if it’s feasible, it will even provide you with charts and graphs to illustrate them. While this is a far cry from Jeopardy-playing supercomputers, it is a much welcomed change to the current heavily context-dependent search paradigm.

And, WolframAlpha does a lot more than that. On their sample page of examples of health/medical requests, WolframAlpha breaks out several other capabilities:

• find growth charts/body statistics
• compute calories burned
• figure out Blood Alcohol Content levels
• estimate risks/mortality rates for diseases
• look up diagnoses by ICD-9 code
• understand medical test results
• look up information about drugs, hospitals, and public health information

Very cool, and, despite the more technical bent to information, much more usable than a standard search engine query for finding relevant health information. There is great promise in this technology, especially if it’s natural language processing algorithms improve to the point where it can provide useful information for healthcare professionals or curious/nervous patients (perhaps by combing through/organizing the information in WebMD’s healthcare-professional-oriented).

(Image Credits)

Most of the time scientists develop Youtube videos to illustrate a concept, they usually result in creations which only a mother could love. That’s why when there is a good video, we should celebrate. Enter Tom McFadden, a Human Biology course associate at Stanford University who, in addition to helping students grasp biology, dabbles in a little hip-hop on the side.

Here’s McFadden “explaining” the role of Hox in regulating body pattern development to the tune of what sounds like Jay-Z’s “Money Ain’t a Thang”:

There are more videos at McFadden’s youtube page – I’m a big fan of “I Just Want a Function” – which takes some basic population ecology and spits it out to the tune of Jay-Z’s “I Just Want to Love Ya”:

I’m a population (population) – of big cane toads (gotta love the toads).
It aint where I live, but where I’m about to grow (talkin’ about australia).
I just want a function, to show who I am (exponential baby),
To see if I’ll crash (mo’ toads, mo’ problems), or if I’ll expand.

Now that’s applying technology (YouTube, social media) to science!

Thanks to the internet the enterprise of playing practical jokes on the world has become incredibly easy and every year now I look forward to seeing what hilarious items pop up throughout the internet. So here’s a quick list of some of my favorite tech/science April Fools jokes for 2009:

Google masters artificial intelligence. The brilliant people over at Google continue to amaze by creating the world’s first “artificial intelligence tasked-array system” which they’ve dubbed the Cognitive Autoheuristic Distributed-Intelligence Entity (CADIE). Apparently it’s already cranking out changes at Google: “Earlier today, for instance, CADIE deduced from a quick scan of the visual segment of the social web a set of online design principles from which she derived this intriguing homepage.”

Gmail Autopilot. Thanks to CADIE e-mail’s even easier than before. By using the Gmail Autopilot one can set simple sliders to manage all your e-mail without going through the hassle of reading and writing. E-mail will never be the same again. Nigeria may become more wealthy though…

Let Gmail Autopilot handle all your e-mail conversations.

Tiny black hole on Earth created by Large Hadron Collider. CERN admits that the real reason they shut down the LHC was due to the creation of a “tiny black hole” that they have “kept under quarantine” and are monitoring as we speak.

Qualcomm, on the cutting edge of Bioengineering. Qualcomm best known for it’s CDMA technology for wireless networks has delved into cutting edge research to improve wireless network coverage around the world. The video below takes an exclusive look behind the scenes of Qualcomm’s latest work.

Happy April Fools!