In a tail wagging the dog reversal, researchers have found that simple chemical reactions can mix a solution. Usually, chemicals are stirred to enhance a reaction, but a new study finds that the reverse is also true: Simple chemical reactions can trigger fluid flows, reports a paper in the January 29 Physical Review Letters.

The research has implications for many chemical reactions, including those inside stars or when carbon dioxide stored deep in the earth encounters water, says study coauthor Anne De Wit of the Université Libre de Bruxelles in Belgium.

De Wit and her colleagues wondered what would happen to fluid flows if the reacting liquids were left alone and not stirred. The researchers watched a very simple reaction — the neutralization that occurs between hydrochloric acid and sodium hydroxide, a common chemical base — in the absence of stirring.

The researchers carefully injected the denser sodium hydroxide into a container and then added the hydrochloric acid. The sodium hydroxide stayed on the bottom and the hydrochloric acid sat on top. Where the two reactive chemicals met, the reaction’s products — table salt and water — began to form. As the salty solution formed, it crept upward and hit the lower-density acid, creating tendrils that started to mix the solution. But the same didn’t happen below the reaction line. This difference in how the reaction product interacted with each of its chemical parents drove the mixing the team observed.

These asymmetrical patterns, the researchers say, distinguish mixing during a chemical reaction from what happens when two nonreactive liquids meet, which may look more like diffusion or other kinds of mixing.

“These kinds of beautiful patterns can be observed with very well-known reactions,” says study coauthor Christophe Almarcha, also of the Université Libre de Bruxelles. “This is quite fascinating for someone who’s done this reaction hundreds of times.”

The researchers also describe reaction-driven mixing mathematically by creating a model that predicted a pattern that looked like the real thing. The model can be tweaked to predict patterns for other chemical reactions, which would vary widely, Almarcha says.

“Our little model system says ‘pay attention,’” De Wit says. “If there are reactions, then new things will happen.” For instance, if stored carbon leaches into an aquifer and starts reacting with water, “those reactions will trigger flows, which will enhance the mixture,” she says.

Image and Video: C. Almarcha/Université Libre de Bruxelles

Read More http://www.wired.com/wiredscience/2010/01/self-stirring-liquids/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+wiredscience+%28Blog+-+Wired+Science%29#ixzz0fbKMWnPY

I learned an interesting fact about Fibonacci numbers recently. Fibonacci numbers can be used to approximately convert from miles to kilometers and back.

Here is how.

Take two consecutive Fibonacci numbers, for example 5 and 8. And you’re done converting. No kidding – there are 8 kilometers in 5 miles. To convert back just read the result from the other end – there are 5 miles in 8 km!

Another example. Let’s take the consecutive Fibonacci numbers 21 and 34. What this tells us is that there are approximately 34 km in 21 miles and vice versa. (The exact answer is 33.79 km.)

If you need to convert a number that is not a Fibonacci number, just express the original number as a sum of Fibonacci numbers and do the conversion for each Fibonacci number separately.

For example, how many kilometers are there in 100 miles? Number 100 can be expressed as a sum of Fibonacci numbers 89 + 8 + 3. Now, the Fibonacci number following 89 is 144, the Fibonacci number following 8 is 13 and the Fibonacci number following 3 is 5. Therefore the answer is 144 + 13 + 5 = 162 kilometers in 100 miles. This is less than 1% off from the precise answer, which is 160.93 km.

Another example, how many miles are there in 400 km? Well, 400 is 377 + 21 + 2. Since we are going the opposite way now from miles to km, we need the preceding Fibonacci numbers. They are 233, 13 and 1. Therefore there are 233 + 13 + 1 = 247 miles in 400 km. (The correct answer is 248.55 miles.)

Just remember that if you need to convert from km to miles, you need to find the preceding Fibonacci number. But if you need to convert from miles to km, you need the subsequent Fibonacci number.

If the distance you’re converting can be expressed as a single Fibonacci number, then for numbers greater than 21 the error is always around 0.5%. However, if the distance needs to be composed as a sum of n Fibonacci numbers, then the error will be around sqrt(n)·0.5%.

Here’s why it works.

Fibonacci numbers have a property that the ratio of two consecutive numbers tends to the Golden ratio as numbers get bigger and bigger. The Golden ratio is a number and it happens to be approximately 1.618.

Coincidentally, there are 1.609 kilometers in a mile, which is within 0.5% of the Golden ratio.

Now that we know these two key facts, we can figure out how to do the conversion. If we take two consecutive Fibonacci numbers, F_n+1 and F_n, we know that their ratio F_n+1/F_n is 1.618. Since the ratio is approximately the same as kilometers per mile, we can write F_n+1/F_n = [mile]/[km]. It follows that F_n·[mile] = F_n+1·[km], which translates to English as “n-th Fibonacci number in miles is the same as (n+1)-th Fibonacci number in kilometers”.

That’s all there is to it. A pure coincidence that the Golden ratio is almost the same as kilometers in a mile.

A system that turns brain waves into FM radio signals and decodes them as sound is the first totally wireless brain-computer interface.

For now, 26-year-old Erik Ramsey, left almost entirely paralyzed by a horrific car accident 10 years ago, can only express vowel sounds with the system. That’s less than can be accomplished with wired brain-computer interfaces. But it’s still a promising step.

“All the groups working on BCIs are working toward wireless solutions. They are very superior,” said Frank Guenther a Boston University cognitive scientist who helped developed Ramsey’s system.

In the last decade, brain-computer interfaces, or BCIs, have made the jump from speculation to preliminary medical reality. Since Wired reported on quadriplegic BCI pioneer Matthew Nagle four years ago (”He’s playing Pong with his thoughts alone“), the interfaces have been used to steer wheelchairs, send text messages and even to Tweet. They’re so advanced that some researchers now worry about BCI ethics — what happens when healthy people get them? And they’re concerned about the threat posed by hackers.

But as amazing as these early BCIs are, they’re far from street-ready. Systems based on translating electrical signals captured by electrodes on patients’ scalps are notoriously slow, capable of producing about one word a minute. If researchers put electrodes directly into patients’ brains, the results are better — but that raises the possibility of dangerous infection. And from a purely practical point of view, wires just get in the way.

The implant system tested by Ramsey, as described in a paper published Wednesday in Public Library of Science ONE, was originally developed by Philip Kennedy, founder of Neural Signals, a company that specializes in BCIs. Several electrodes are implanted in Ramsey’s cerebral cortex. Beneath the skin of his skull is an amplifier that gathers the electrodes’ signals, and an FM transmitter that sends them to a nearby computer.

Using a neurological model constructed by Guenther, Ramsey’s brain activity is mapped to corresponding mouth and jaw movements. Another program decodes the signals, and synthesizes them in the sound of a tinny, but human-like voice.

“The system produces the sound output in about 50 milliseconds. That’s the time it takes for sound output to come from a motor cortex command in a normal individual,” said Guenther.

The three wires in Ramsey’s brain are only sufficient for making vowel sounds, said Guenther. But the researchers plan to add more electrodes, perhaps as many as 32. That would be more difficult to control, but would also allow Ramsey’s thoughts to better mimic natural tongue and jaw movements, ultimately letting him form consonants as well.

For now, the computer that translates Ramsey’s mental broadcasts is still in a laboratory. “But our goal is to have him transmit directly to a laptop,” said Guenther.

Image: A schematic at left and CT scans at right of the wireless brain-computer interface. PLoS ONE.

[Brandon Keim]

Intricate cellular components are often cited as evidence of intelligent design. They couldn’t have evolved, I.D. proponents say, because they can’t be broken down into smaller, simpler functional parts. They are irreducibly complex, so they must have been intentionally designed, as is, by an intelligent entity.

But new research comparing mitochondria, which provide energy to animal cells, with their bacterial relatives, shows that the necessary pieces for one particular cellular machine — exactly the sort of structure that’s supposed to prove intelligent design — were lying around long ago. It was simply a matter of time before they came together into a more complex entity.

The pieces “were involved in some other, different function. They were recruited and acquired a new function,” said Sebastian Poggio, a postdoctoral cell biologist at Yale University and co-author of the study published Monday in the Proceedings of the National Academy of Sciences.

Mitochondria are descended from free-living bacteria, which several billion years ago were swallowed by complex cells. The mitochondria soon became central to the cells’ function.

Mitochondria couldn’t have lasted in their new home without the help of a protein machine called TIM23, which delivers other proteins harvested from the cell’s body. Bacteria don’t possess TIM23, suggesting that it evolved in mitochondria. This seems to pose a cellular chicken-and-egg question: How could protein transport evolve when it was necessary to survive in the first place?

The essential paradox applies to other protein-transporting cell systems, providing disbelievers of evolution with a key part of their critique. As articulated by intelligent design proponent Michael Behe, “This constant, regulated traffic flow in the cell comprises another remarkably complex, irreducible system. All parts must function or the system breaks down.”

According to evolutionary theory, however, cellular complexity is reducible. It requires only that existing components be repurposed, with inevitable mutations providing extra ingredients as needed. Flagella, the hairlike propellers used by bacteria to move, are one example of this. Their component parts are found throughout cells, performing other tasks.

Intelligent design mavens once cited flagella as evidence of their theory. Scientific fact dispelled that illusion. The mitochondria study does the same for protein transport.

“This analysis of protein transport provides a blueprint for the evolution of cellular machinery in general,” write the researchers, led by molecular biologist Trevor Lithgow at Australia’s Monash University. “The complexity of these machines is not irreducible.”

When they analyzed the genomes of proteobacteria, the family that spawned the ancestors of mitochondria, Lithgow’s team found two of the protein parts used in mitochondria to make TIM23.

The parts are located on bacterial cell membranes, making them ideally positioned for TIM23’s eventual protein-delivering role. Only one other part, a molecule called LivH, would make a rudimentary protein-transporting machine — and LivH is commonly found in proteobacteria.

The process by which parts accumulate until they’re ready to snap together is called preadaptation. It’s a form of “neutral evolution,” in which the buildup of the parts provides no immediate advantage or disadvantage. Neutral evolution falls outside the descriptions of Charles Darwin. But once the pieces gather, mutation and natural selection can take care of the rest, ultimately resulting in the now-complex form of TIM23.

“It hasn’t been possible up until this point to trace any of those proteins back to a bacterial ancestor,” said Dalhousie University cell biologist Michael Gray, one of the researchers who originally described the origins of mitochondria, but was not involved in the new study. “These three proteins don’t perform precisely the same function in proteobacteria, but with a simple mutation could be transformed into a simple protein transport machine that could start the whole thing off.”

“You look at cellular machines and say, why on earth would biology do anything like this? It’s too bizarre,” he said. “But when you think about it in a neutral evolutionary fashion, in which these machineries emerge before there’s a need for them, then it makes sense.”

Citation: “The reducible complexity of a mitochondrial molecular machine.” By Abigail Clements,1, Dejan Bursac, Xenia Gatsos, Andrew J. Perry, Srgjan Civciristova, Nermin Celik, Vladimir A. Likic, Sebastian Poggio, Christine Jacobs-Wagner, Richard A. Strugnell, and Trevor Lithgow. Proceedings of the National Academy of Sciences, Vol. 106 No. 33, August 25, 2009.

Image: Journal of Cell Science
Source: Brandon Keim