Tuesday, February 17, 2015

Heart Health, Explosive Gas, and Mexican Mollies (2/8/15)

Last Sunday's program with Dr. Jennifer Shaw from the OSU Department of Integrative Biology, was about how we might learn something about our own body chemistry by studying some amazing fish from Mexico.

I kicked us off with a new song called "Team Science." This is a topic I've wanted to work into a song for a while - how scientists always work as part of an enormous team. Since Jennifer made an unexpected connection with another researcher, using Dr. Michi Tobler's fish evolution studies to further her investigation of how we humans regulate hydrogen sulfide, it seemed like a great way to illustrate the point that scientists do not work alone.

Brand new song, "Team Science"

Hydrogen sulfide is an important signaling molecule that helps our bodies know when to grow new blood vessels, among other things. On it's own, it's a poisonous gas, and it stinks. So of course we wanted to smell it!

Jennifer prepares to release some hydrogen sulfide gas.

Adding powder to water to release the gas.

Jennifer wafts the gas gently so I won't get a harmful dose. I take a whiff - whew! Smells like rotten eggs!

Dr. Tobler's fish are nearly identical except that one group evolved the ability to live in hydrogen sulfide springs. Since the two fish are so similar we can assume that any genetic differences probably have something to do with processing hydrogen sulfide. This can help us figure out which genes are most involved, by comparing how genes are expressed between the two types of fish, when they live with and without hydrogen sulfide in their water. 

And guess what, we humans have a lot in common with fish! The same mechanisms are at work in our own bodies.

Amazing Mexican Mollies that live just fine in pools poisoned by hydrogen sulfide.

Nearly identical mollies collected from nearby pools without hydrogen sulfide. These fish can't survive in the sulfide pools.

Jennifer's lab setup - this is how she delivers hydrogen sulfide to the fish in her experiments.

Hydrogen sulfide is something our bodies need, in small amounts. Too much is poison. There are human diseases related to both having too much and having too little hydrogen sulfide available in our bodies. Understanding how these sulfide tolerant fish can manage will help us figure out how to correct the balance when it goes wrong for us! 

Tuesday, February 3, 2015

Higgs Boson Found! Now What? (1/25/15)

Last Sunday's program was a doozie! My guest was Dr. Flera Rizatdinova from the physics department at OSU. Flera analyzes data from the Large Hadron Collider (LHC).

So we were talking about particle physics and it went long - very long. It's good though, because there were lots of questions. I think particle physics is really fun to think about.

When you hear an explanation in particle physics and it feels like you don't understand it, that's probably because it's very weird how things work on the smallest scales. Fundamental particles don't behave like things we're used to. Particle physicists understand all the mathematical models that describe particle behaviors. Yet even they seem to have trouble describing what's "really" going on.

So with that in mind, I'll take a stab at summarizing the program. We started with a sneak peek at my new song and video "Quarks and Electrons." Then I tried to give a quick summary of the Standard Model of Particle Physics. 

I tried to give a quick overview of the Standard Model of particle physics. There were lots of questions!

Basically Quarks (up and down, held together by gluons) and Electrons are the fundamental particles that make up regular matter - all the stuff you and I can touch or see. The Quarks and Leptons have mass. The Gauge Bosons, including Photons and Gluons, cary forces. The Higgs Boson gives other particles their masses.

Here's a chart. It's something like the periodic table of elements, only everything here is a fundamental particle, which means that as far as we know it can't be broken down into smaller parts:

Standard Model of Particle Physics
And that's it. If the universe is a giant Lego playset, then these are all the types of Lego bricks we know about. 

However, we also know the Standard Model is missing pieces! 

Until recently we didn't have the Higgs Boson on the chart. We thought it might exist but until we gathered good evidence for it from the LHC (Large Hadron Collider) we didn't know for sure. Now we do.

Other particles are probably missing as well, and we're looking for them next. 

For one thing, there's dark matter. We know it exists because we can observe its effects on galaxies. But from its properties we can tell it isn't made out of anything on the list.

Another problem is gravity. The other fundamental forces have their particles - for example electromagnetic force is carried by photons - but gravity is not accounted for.

And we don't understand a whole lot about exactly how the Higgs Boson gives particles their masses. It's possible there are several different kinds of Higgs Bosons yet to be found.

Physicists have guessed at many ways of extending the Standard Model. (One example is "Super Symmetry.") These hypotheses all include the model as we know it, and add additional particles of different sorts. All of the extended models make mathematical sense, but which one is right? Which one represents the way the world actually is? The only way to tell is to run an experiment. That's where the LHC comes in.

We took a break at this point to remind ourselves that fundamental particles are real. We had a cloud chamber set up to detect them. The chamber is filled with evaporated alcohol. Whenever a particle zips through it leaves a trail of droplets that you can see. We could see lines appear that let us know muons were zipping through. Muons are generated by particles from outer space slamming into our atmosphere - we call those "cosmic rays."

Looking for particle trails in the cloud chamber!

Whew - we are about halfway through the program now! We talked about how the LHC (Large Hadron Collider) at CERN works by slamming protons together at very high energies. The protons plus energy create a whole bunch of new particles. These decay, or fall apart into smaller pieces.

The particles we're looking for, the unfamiliar ones, do not exist long enough for the detector to detect them. Instead we detect the pieces they generate. From those pieces, we have to work backwards to see if we have evidence that one of the new particles was there.

I demonstrated my "photon detector" by taking this photo. The ATLAS detector at the LHC works in a similar way, only it records lots of different types of particles in addition to photons.

This is a very hard problem to solve. The ATLAS detector collects information from millions of particles per second. All those signals are mixed up together. It's difficult to tell one particle from another.

Flera uses computer programs to help her sort through the data. She's part of a large team that includes scientists from all over the world. They each tackle a different piece of that hard problem. Together they can decipher the signals from the ATLAS detector to find out if any exotic particles were created in the proton collisions.

Scientists are still working on the data generated last time the LHC was running. Next time they turn it on it will run at a higher energy. This increases the chances that exotic particles will be formed. It's exciting to think that the new data set may add to our fundamental model of the universe!

Coming up next:

February 8, 2015
Heart Health, Explosive Gas, and Mexican Mollies
With Jennifer H. Shaw, Ph.D., Department of Zoology, OSU
Regulation of hydrogen sulfide in our bodies is important to our health, but how do our cells know exactly how much to make? Find out how some special fish from Mexico can help us understand our own body chemistry!

Friday, January 16, 2015

Teaching Computers to Predict (1/11/2015)

Last Sunday we presented the first of the current series of four Born To Do Science programs a the Stillwater Public Library. My guest was Allan Axelrod, who studies machine learning. 

Allan has developed an algorithm (or set of computer instructions) he calls EIEIO, which helps computers get clever about how they collect and analyze data in situations where numbers are collected continuously, but the entire set cannot be seen at once.

The situation that brought about the need for this algorithm is this: How do we monitor carbon sequestration sites for potentially dangerous leaks of CO2 back into the atmosphere?

We began with a song inspired by Allan's whimsical EIEIO acronym.

Introducing the topic with a song.

We had some discussion about whether carbon sequestration (storing waste carbon dioxide under ground) is a good idea in the first place. I know it's a controversial topic! But we needed to put a pin in that, in order to get to Allan's algorithm. Given that CO2 is already being sequestered under ground, it's good that people like Allan are coming up with ways to monitor it!

We set up a game to mimic the situation Allan has to deal with. There are monitoring stations on the ground spread over a large and hard-to-get-to area of land. Each one takes CO2 measurements every hour. The computer can use this information to model the system and attempts to predict leaks before they occur.

The problem is that all the current CO2 data is not available instantly. Drones are used to fly by each station and pick up the data. The question is - should the drones visit every station once, then every station again, etc.? Or is there a more useful way of gathering the data?

One of our sampling stations "collecting" data.

For the game, we set up seven sampling stations around the room. Two volunteers became drones, and two others were the computer. The computer sent drones from station to station collecting data. The computer then tried to make good decisions about where to send them next based on the numbers collected.

(If you're wondering - I created a set of measurements for each station ahead of time. The station-masters flipped through a stack of cards slowly, one every ten seconds. Each card they put down represented taking a measurement. At each station, the drones collected all the measurements taken since the last visit.)

The object of the game was to find a leak (if the numbers went high enough, they turned red on the page representing a leak) as quickly as possible.

A "drone" picks up data from a sampling station.

The "computer" analyzes data, trying to decide where to send the drones next.


The kids tried a couple of basic strategies. One was to send drones randomly to different stations and hope to find the leak. Another was to notice if the numbers were going up from a given station and send drones back there, or to a nearby station. It was challenging to process all those numbers during the game. But sending drones to a station where the numbers were rising is very similar to Allan's actual strategy!

If I'd had the chance to test the game out first, I would have changed a few things about how we did it to make it easier and clearer for the kids to think about strategy. But we did successfully get a handle on the basics of how the station, drones, and computers work together in real life.

Allan answers questions.

Allan's strategy with the EIEIO algorithm is to compare data collected from each station to the numbers the computer would have predicted. A "metric" - a measure of how close the numbers are to the predicted value - is calculated for each station. The stations that are the farthest off get the next drone visits.

This way the computer can collect the numbers it most needs next at any given time.

Allan has tried several versions of his algorithm on several sample data sets and compared the results of his EIEIO strategy to the strategy of sending drones methodically or randomly to all the stations every time. His EIEIO results are much better!

Taking info on Allan's computer class at the library.
Allan teaches a computer class on designing videos and video games at the Stillwater Public Library.

Looks like I forgot something but I can't remember what.
Can I get witness for science!
Sunday January 25 - Particle physics with Dr. Flera Rizatdinova! We've found the Higgs Boson, so what's next for the ATLAS detector at CERN?