Oh wow, it didn’t take long for me to renew:

1. My domain registration.
2. My interest in blogging. 

Things are safe on the blog front for now, and like always, there are many big things in store for Jacks of Science which will one day come to delicious fruition for all.

So anyway, I’m researching in the U.S. this summer on a work placement. Living here I’ve had the privilege of experiencing the finer details of life which Canada lacks. Mainly, White Castle and an abundance of unsweetened iced tea but I still can’t figure out what’s the deal with the Imperial Units. 

When I’m homesick I just use Google for conversions to S.I. units. If that fails, which it has yet to, UnitConversion. But I admit, even meters, kilograms, and seconds can get a bit boring after a while. When that happens I have no choice but to use WeirdConverter (Turns out I only weigh 11% of a whale testicle).

If you’ve ever played Katamari Damacy for Playstation 2 then you’ll know exactly what I mean. Info-rich game facts appear on the pause screen informing you that your Katamari ball is the size of 5 swordfish or perhaps 35 grandmas in width. Katamari Damacy is a great educational tool. It gives a unique sense of scale and teaches you that all measurements are relative.

There are plenty of obscure units to express our measurements in. Which begs the question: what made us settle on the standard units we did? It all boils down to an ongoing quest for finding a high accuracy measurement and agreeing internationally on a particular definition. Here are some of the weirdo ways our favorite units are defined:

• The Meter. Kind of a cop out, but if you get this crazy notion to fix (?) the speed of light in a vacuum at a constant number, like 299 792 458 meters per second, you can use the distance that light travels in 1/299 792 458 seconds to get a distance known as a meter. But wait, how do they know long is a second?
• The Second. Scientists needed a time measurement that was a bit more precise than “one Mississippi”, so they set a second as the duration of 9,192,631,770 cycles of microwave light absorbed or emitted by a cesium atom moving between 2 energy levels at a temperature of 0 kelvin. But wait, how hot is a kelvin?
• The Kelvin. The International Atomic Energy Agency developed a standardized composition of pure water called Vienna Standard Mean Ocean Water. They carefully obtained the triple point and absolute zero point of this water and set them as 273.15 kelvin and 0 kelvin respectively. You can divide this interval to get the individual units of degrees.

Jacks of Science is a bit of an experiment.

I hypothesized that the site would become a flourishing group science blog as far back as 2006.

To observe this desired blog state I devised a simple theory. I would mix a solution from a staff of student bloggers in different fields such as Physics, Biology, Geology, and Chemistry.

Would I be able to find reactants that formed a homogeneous mixture or a highly reactive substance on the brink of explosion?! Even if I found writers that worked coherently together, would I continue to get decent results over time? 

I figured that the greatness of Jacks of Science would be directly correlated with post diversity. Many authors would lead to diversity in post subject matter, writing style, humor, complexity, geekiness, and length. However, in theory, things are much different than in experiment. As you may have noticed, this diversity of authors ended up just being a diverse range of posts authored by me. I didn’t follow through on my original plan of finding other writers since I was busy trying to become a better blogger myself.

The original intention of the site has been lost but, 102 posts later, as my domain renewal date draws nearer, you’re looking at the results of the Jacks of Science experiment. Full of random art doodled on my class notes (which now includes my 1st and 2nd year!), to pro-piracy open science discussion, to science DJ mixes, to my most popular article: Science Valentines.

So I’m trying to draw some conclusions about the data so far. As far as the traffic indicates the site is growing in popularity but I’m just not sure if things are working out. Blogging is a lot of fun, but the Jacks of Science initiative, as originally imagined, has been stagnant for some time. It doesn’t seem to be going anywhere for a variety of reasons off the top of my head.

• No clear audience that I’m writing for!
• No incentive for new writers to be part of the site!
• I can only post once a week by myself (quality over quantity)!
• Science is boring (and thus cannot reach a wide enough audience)!
• My single column blog theme is too narrow!

I’m out of Ontario on a co-op placement this summer. I’ve had to dust off my first year chemistry brain synapses because I’m researching small clusters of water molecules. Like in any research project, one must ask oneself, and be able to explain to ones family, why is my research important?

From nuclear reactors filled with heavy water to pouring out some Bling H2O on the concrete for our fallen homies, we need be able to accurately understand water in any context. 

By computing how water molecules interact with each other on a small scale one may be able to gain insight into the bigger picture. An interesting property of a group of 2-5 water molecules is that they are most likely to form a ring structure. However, this is not the case for 6 or more water molecules as more stable structures are available (Xantheas). One might wonder if this small scale phenomena has macro consequences leading to the watery characteristics we have come to appreciate and adore. 

For example, starting from just 2 hydrogens and an oxygen, would it be possible to predict that ice floats at the top of your glass of water instead of sinking to the bottom? The ab initio techniques I use on my daily grind are designed to do just that. I input a list of electrons and protons into my computer and it outputs a fantastic amount of data on that system (but not the ice density in particular). Computation is a powerful tool in understanding properties emergent in chemical systems.

This study of emergencies has been an ongoing battle for all flavors of scientists in understanding nature. Physicists want to understand how the classical laws of our daily lives are emergent from quantum mechanics (subscription required). Some biologists want to understand the sociality emergent in bee colonies (or ant colonies). Chemists want to predict crystal structures [PDF] emergent in clusters of molecules. Computation is an essential tool for understanding many if not all of these situations.

My work brings up an interesting philosophical question about the scientific theories we use to describe the world. Are our theories of biology, chemistry, and physics really discontinuous? Desiraju [PDF] argues that our current model of chemistry is incompatible with biology and that there exists a new model of chemistry on the forefront which cannot be expressed in terms of physics and mathematics. The thought is this a little disconcerting to me. Not being able to compute everything implies that we would never be able to build The Matrix! 

Anyway, call me a reductionist computational scientist but I’m pretty sure computation will one day be able to fill in the blanks of our models of science. Admittedly, it hinges on the discovery of a grand unified theory to build upon, but I’ll leave that to the theoretical physicists. From there on out, it’s all computation baby!

Simple image processing can be fun and easy with Photoshop. Various books have even been published on the use of Photoshop in forensic science!

I recently watched a Lynda.com tutorial on using Photoshop for Biomedical research and Photoshop for Research Methods and Workflows. The latter included a step-by-step guide for image processing techniques from analyzing protein expression in microarrays to obtaining penetration data in tissue sample. But I think it’s safe to assume that most reader’s aren’t concerned with biomedical research, so I decided to take the measurement idea and run with it.

In this post I’ll outline some applications of Photoshop’s measurement tools which should not be missed! Note that this tutorial assumes you already have basic knowledge of opening images, working with layers, and making selections.

Measuring the Lean of a Leaning Tower of Jenga

How would one go about comparing the leanosity of this Leaning Tower of Jenga compared to the real Leaning Tower of Pisa?

1. Just use the Ruler Tool across the edge of the tower and read it off the “A value” in the Options toolbar across the top of the window 
2. Alternatively you can select Record Measurements from the Analysis drop down menu and scroll over Measurements Log to Angle.

Turns out the real Leaning Tower is about 86.03°. Pretty accurate lean!

Adobe writes “Circularity is the calculation 4pi(area/perimeter^2). A value of 1.0 indicates a perfect circle. As the value approaches 0.0, it indicates an increasingly elongated polygon. Values may not be valid for very small selections”.

One can do many interesting things with this measurement. For example, you may be interested in comparing the circularity of your head to that of a friends.

I was more interested in the practical measurement of the circularity of the moon during the lunar cycle as depicted above.

1. Use the Magic Wand to select the emptiness of space
2. Invert the selection with Select > Inverse, and subtracted the moons from the selection I wasn’t interested in using the Rectangular Marquee. 
3. Goto Analysis and Record Observations in a manner similar to the previous example.
4. Record the value of the Circularity heading in the Measurement Log.

All werewolves know that there are approximately 30 days between each full moon. Using this fact, along with Photoshop, and a digital camera one could determine the day of the month based on circularity alone!

Counting Candies in a Candy Bowl

1. Using the Magic Wand Tool, one can select a region of a single green colored M&M from this delicious bowl. 
2. Once you have a green M&M selected, choose the Similar option from the Select drop-down you can expand this selection to the entire image. You may have to play a bit with the tolerance of the initial selection. 
3. Once you have a decent selection, goto Analysis > Record Observations
4. By observing the Count heading of the Measurement Log you can see exactly how many M&M’s are selected.

I manually counted 74 and using the steps outlined above I got a count of 70. This technique could be used to count freckles, stars, or any distinctly colored/separated objects! 

Measuring the Efficacy of Teeth Whitening Products

You must have heard of these teeth whitening products by now. Typical they are hydrogen peroxide gel-based and bleach the yellow out of your gnarly coffee teeth. I searched all over the internet for a review of the damn things but all I could find was dentistry spam! Wouldn’t it be nice if someone actually reviewed them with real quantitative data? If you have Photoshop it’s way easier than you think.

1. Bring a close-up photo of your smile into Photoshop CS3 Extended
2. Use the Rectangular Marquee to select a sample of color on your teeth
3. Goto Analysis and Record Measurements. 
4. On the pop-up observations box just scroll over to “Mean Gray Value” and record that number. 
5. Repeat steps 1-4 throughout your whitening procedure and graph the whitening over time!

Note: The gray value will likely be a number from 0 to 255. Also, the pictures above are from actual dentistry work and not an over the counter bleaching product!

Calculating the Height of Kirsten Dunst

1. Access the Analysis menu option Set Measurement Scale > Custom so you can set a new measurement scale for the ruler tool. 
2. Once the Measurement Scale dialog box is open, click and drag using the Ruler tool across the edge of the book
3. Fill in the values for the logical book length as 9.2 inches and press Ok, all further Ruler measurements are scaled by this length. 
4. Use a series of Ruler measurements to total up Kirsten’s height.

I got a height of 67 inches, or 5’7. I guess I overshot her height a little bit according to Chickipedia.

Estimating the Number of Chickens in Africa

After way too much work, you select Africa and click Analysis > Record Measurements. There will be many measurement entries but the one with multiple values in count should be the combined selection of Africa and its islands. I obtained an area of 30.11 million square kilometers which compares well with the actual value of around 30 million km^2.

Unfortunately, you can’t use the Integrated Density in this case, since mean gray value which is a value from 0 to 255. Although, we can scale our mean gray value (36.32) by dividing it by 255 and multiplying by 125. I chose 125 as the maximum number of chickens per square kilometer. This gives a Mean Chicken Population/km^2 of 18.

Using the M.C.P./km^2 multiplied by area of Africa it is certain that there are around 542 million chickens. 18 Chickens per kilometer sort of seems like a lot when you consider the desert, but who knows!

As you can see, Photoshop is such a powerful tool it’s no wonder it cost $1000 to purchase! Can you think of any other interesting image measurements I could make?

We’ve all experienced those slow motion moments. Shooting for the winning basket at the buzzer, the loss of steering control on black ice, the taste of Ben & Jerry’s Chocolate Fudge Brownie, et cetera. All three of which are all amazing experiences to be felt at some point in life, yet film directors go ahead and cheapen these glorious moments by recording (or post-processing) them in slow motion. It’s kinda too bad!

It wasn’t always like that:

Did you know (I didn’t until very recently) that slow motion was an invention—patented, in fact? Who knew time could be patented? Back in 1904, an Austrian priest-turned-physicist named August Musger obtained a patent for a process by which he modified film projectors to produce slo-mo on screen. The irony was that August Musger (named after the slowest month?) was slo-pay, too. He lost his patent in 1914 because he failed to pay the fees for its renewal on time.

-Errol Morris and the Strange Power of Slo-mo, Ron Rosenbaum

At least we can be thankful that not everything is filmed in slow motion. Normal movies are filmed at 30 frames per second and that’s about my brains limit for number of frames of Tom Cruise’s face I can process and forget every second. But be careful! Dangerous new thousand/million fps high-speed cameras exist that use wild rotating prisms instead of shutters to capture frightening detail in even most tolerable celebrities.

Although, these “super slow motion” cameras are not always used for evil. If anything, they can help us appreciate the beauty of physics in every day life. For example, observe these youtube compilations from the latest season of Brainiac:

Weren’t those cool? To help clear up my position on speeds of motion I’ve summarized my feelings in this graph: 

At the graph’s y-intercept, we observe the finite value of coolness that represents the regular speed of life. When one records life at 30 fps it just seems less cool, even though its meant to be at the same speed. Coolness decreases linearly as as you continue into slow motion-ness. But here is where the graph gets interesting. From this point, as frames per second increase (speed of video decreases), coolness approaches infinity, a value infinitely cooler than the speed of normal life. Moving past this discontinuity, boringness surpasses coolness and we observe exponential decay as speed of time approaches a state of Walt Disney.

This singularity of coolness occurs at a very precise frame per second which may never be measured experimentally. Although, under carefully controlled laboratory conditions, this state my be experienced cognitively, possibly by making a free-throw at the NCAA finals before the buzzer from a car skidding out of control while consuming Ben & Jerry’s Chocolate Fudge Brownie ice cream.

In closing, if Einstein’s relativity teaches us anything, it’s that we’re always cool relative to someone else. Thank you.

I don’t know about you, but I always start my day off with a bowl of knowledge from the Journal of Cereal Science with a healthy splash from the International Dairy Journal. But damn, it’s hard to keep up with advances in breakfast science, I mean DIAMOND SHREDDIES!?

That being said, I rarely have time to sift through journal RSS feeds and papers I can’t understand to actually find the gems. Wouldn’t it be great if you could get a computer algorithm to recommend you scientific literature tailored to your interests and skill level? What if you took it one step further, wouldn’t it be nice if you could get a computer to recommend you an interesting paper to write?

If you’ve ever been to Amazon, you’d know that algorithms are always at work tracking your incriminating purchases. This is pretty easy for Amazon, especially when you have keyworded items to purchase and review which are all on one site. Online scientific literature should be no exception. When you download a paper, or comment on it, blog about it, or cite/bookmark it, you should be building a unique profile.

But the current model of scientific publishing is closed-access, people are having a hard time. While it’s easy to index papers based on name, authors, and abstract, building a significant body of published literature is basically impossible. Although, research is being done.

Personally, I can’t wait until the subscription-based model of scientific publishing is finally abolished. Then scientists, journalists, policy-makers, and laymen of all nations could join hands and finally get down to business.

But finding cool papers is just the tip of the iceberg. With an open access model we’ll also be able to use algorithms to extract new and exciting conclusions from pools of existing data, find emerging fields of research, and publish fuzzy journals based on clustering algorithms (PDF) of relevant research.

It’s not out of our reach either, we have the technology! This post was inspired by a paper, published almost 20 years ago, Medical literature as a potential source of new knowledge, which was recently posted on Michael Nielsen’s blog.

The long and short of it: science, I’m talking to you, get up to speed, because it’s the 21st century!

My bro Kevin hollered this track at me a little while ago and I just recently re-discovered it on the ‘tube. I’ll admit, I’m a little disappointed that no one is paying attention to the physics prof and that the song implies that he’s so boring you need to drink cappuccino to stay awake. But I see where the prof went wrong… when they dropped the beat he should have gone Michelle Pfeiffer-style on them and started rapping about the big bang. Hmm, that gives me an idea…

Oh wow, does it ever take those LHC scientists a long time to get their particle collider up and running. Even after months of data crunching on my part, last April 1st I heard that the project was going to be delayed for 3 years! What can one do?

Well, it’s easy to see how logic and reason have their place in massive engineering feats like the LHC, but sometimes all a scientist needs is a bit of luck. Help the LHC scientists get a healthy serving of lucky charms by finding 11 rowdy leprechauns causing a ruckus in the ATLAS detector! 

(Click to enlarge) 

The first to find them all wins a shiny new god particle. 

It isn’t the first time he’s acted in a moving picture, but I can’t wait for his latest appearance in “The Fall“! Check out the movie trailer below to see who I’m referring to…

[youtube]http://youtube.com/watch?v=yQt0QjWHUjY[/youtube]

Scientists can dance if they want to. They can get other people to leave their friends behind?