Alan Turing’s Patterns in Nature, and Beyond
Near the end of his life, the great mathematician Alan Turing wrote his first and last paper on biology and chemistry, about how a certain type of chemical reaction ought to produce many patterns seen in nature.
Called “The Chemical Basis of Morphogenesis,” it was an entirely theoretical work. But in following decades, long after Turing tragically took his own life in 1954, scientists found his speculations to be reality.
First found in chemicals in dishes, then in the stripes and spirals and whorls of animals, so-called Turing patterns abounded. Some think that Turing patterns may actually extend to ecosystems, even to galaxies. That’s still speculation — but a proof published Feb. 11 in Science of Turing patterns in a controlled three-dimensional chemical system are even more suggestion of just how complex the patterns can be.
How Turing Patterns Work
At the heart of any Turing pattern is a so-called reaction-diffusion system. It consists of an “activator,” a chemical that can make more of itself; an “inhibitor,” that slows production of the activator; and a mechanism for diffusing the chemicals.
Many combinations of chemicals can fit this system: What matters isn’t their individual identity, but how they interact, with concentrations oscillating between high and low and spreading across an area. These simple units then suffice to produce very complex patterns.
Proving Their Existence
Even though what appeared to be Turing patterns were immediately evident in nature, it wasn’t easy to be sure they were produced by reaction-diffusion systems, rather than some other mechanism.
The breakthrough came during the 1980s, when chemists were able to produce Turing patterns in the laboratory, on thin slabs of gel. In these controlled systems, the reactions could be closely followed, simulated on computers and unambiguously demonstrated as true Turing patterns.
At left in each photograph is a real seashell. At right is a computer-generated image of a pattern produced by a Turing pattern simulation.
At left in each photograph is the eye of a popper fish. At right is a computer-generated image of a pattern generated by a Turing pattern simulation.
Brent Constantz builds cement like corals do
Biomineralization expert Brent Constantz of Stanford University was inspired to make a new type of cement for buildings by the way corals build reefs. The process of making this cement actually removes carbon dioxide – a greenhouse gas, thought to cause global warming – from the air. The company Constantz founded, called Calera, has a demonstration plant on California’s Monterrey Bay. The installation takes waste CO2 gas from a local power plant and dissolves it into seawater to form carbonate, which mixes with calcium in the seawater and creates a solid. It’s how corals form their skeletons, and how Constantz creates cement.
This butterfly could hold the secret to letting you see in the dark
The opalescent wings of the Morpho butterfly embody a perfect marriage of aesthetic beauty and biological functionality. Scientists believe that a better understanding of this creature’s wings and their chemical makeup could have big implications for imaging technologies like night vision goggles that rely on sensing heat, rather than visible light.
Now, a team of GE researchers has taken an important step in accomplishing exactly that.
One of the biggest problems facing thermal imaging technologies is temperature management. The sensors in a heat-sensing device have to be cooled constantly, otherwise the image you see becomes washed out with old, and therefore insignificant, heat measurements. Imagine watching a person walk across a room while wearing thermal imaging goggles — if the thermal sensor’s temperature wasn’t kept in check, you’d be able to see a sort of thermal ghost trailing behind the person as they moved across your field of vision.
Physics World’s Tim Wogan explains the challenges of regulating the heat of thermal sensors:
The most sensitive thermal imagers require liquid-helium refrigeration. Since the heat sinks required are relatively large and power-hungry, this limits the minimum size and efficiency of the sensors. These requirements pose severe challenges for those designing portable equipment, such as thermal-imaging goggles. Indeed, goggles pose a particular problem because an ideal pair would be transparent to visible light, which is difficult to achieve with heat sinks in the way.
This is where the Morpho butterfly swoops in to save the day. The scales that cover the Morpho’s iridescent wings reflect light at some wavelengths, while absorbing it at others; these absorption/reflection properties can even change depending on the wings’ temperature, shifting the color of the wings in the process.
This is a pretty inspired biological feature, and it’s one that scientists believe could be put to use in thermal imaging sensors; but what researchers are really impressed with is the chitin that the scales of the Morpho wings are actually made of.
Chitin has a much lower heat capacity than the materials that are used in contemporary thermal sensors; lower heat capacity, in turn, eliminates the need for bulky, energy-hungry cooling methods. In the thermographic video featured here, you can see a Morpho butterfly responding quickly to heat pulses distributed first across the whole butterfly structure, and then onto localized regions of the wings.
And believe it or not, we can make these wings even more impressive — and with carbon nanotubes, no less! Writes Wogan:
Building on previous work by other researchers that revealed that decorating a material surface with carbon nanotubes enhances its ability to absorb infrared radiation, [a research team led by analytical chemist Radislav Potyrailo] showed that the [Morpho’s wings] absorbed infrared better if carbon nanotubes were added to the exposed surface. As a bonus, because carbon nanotubes have excellent thermal conductivity, the decoration helped to diffuse heat through the chitin away from the site of irradiation, thus providing a molecular heat sink.
In other words, Potyrailo and his colleagues showed that treating Morpho scales with carbon nanotubes not only enhances their ability to absorb radiation at wavelengths relevant to thermal imaging, it actually improves their ability to diffuse heat.
The question that remains is: how do researchers translate the functionality of nanotube-doped butterfly wings into a synthetic thermal sensor? Poryrailo and his team have already created an ersatz version of Morpho wings, but they still need a way to incorporate the chitin that grants them their unique heat-dissipating abilities. Once they do that, however, the researchers believe it could mark a major shift toward cheap, more effective thermal-imaging devices.
Humpback whale secret may help helicopters fly faster
DLR Institute of Aerodynamics and Flow Technology / DLR Institute of Aeroelasticity
Helicopters can deliver military troops or rescue the wounded in tight spaces, but their rotating blade design also puts a hard limit on their speed and maneuverability. Now researchers have begun flight-testing an unlikely fix inspired by the underwater ballet of humpback whales.
The potentially cheap solution uses small bumps along the front edge of the helicopter blades similar to bumps found on the large pectoral fins of humpback whales. Such bumps give an aerodynamic edge that delays the moment of “stalling” when there’s not enough lift to keep the whale from sinking — or a helicopter from stalling out at top speeds.
“Stalling is one of the most serious problems in helicopter aerodynamics — and one of the most complex,” said Kai Richter from the DLR Institute of Aerodynamics and Flow Technology in Germany.
Helicopters face a speed limit because their backward-moving rotor blade goes against their forward motion of flight. That problem leads to turbulence and loss of lift, as well as strong forces acting on the rotor, which eventually cause the helicopter to stall out.
German researchers patented the bump idea for helicopters, under the name “Leading-Edge Vortex Generators.” Wind tunnel experiments led to a test flight with a helicopter carrying 186 rubber bumps —each less than a quarter of an inch long — glued to its four rotor blades.
“The pilots have already noticed a difference in the behavior of the rotor blades,” Richter said. “The next step is a flight using special measuring equipment to accurately record the effects.”
If testing goes well, existing helicopters could get a speed boost with simple retrofits. New helicopters could have the design built into their titanium blades during manufacturing.
The natural bump design already helps humpback whales swim at speeds of up to 16.5 miles per hour, or about five times faster than the fastest human swimmer.
“Research has shown that these bumps cause stalling to occur significantly later underwater and increase buoyancy,” said Holger Mai from the DLR Institute of Aeroelasticity in Germany. “Flow phenomena in water are similar to those in air; they just need to be scaled accordingly.”
Source: Innovation News Daily
Slime Mold Grows Network Just Like Tokyo Rail System
Talented and dedicated engineers spent countless hours designing Japan’s rail system to be one of the world’s most efficient. Could have just asked a slime mold.
When presented with oat flakes arranged in the pattern of Japanese cities around Tokyo, brainless, single-celled slime molds construct networks of nutrient-channeling tubes that are strikingly similar to the layout of the Japanese rail system, researchers from Japan and England report Jan. 22 in Science. A new model based on the simple rules of the slime mold’s behavior may lead to the design of more efficient, adaptable networks, the team contends.
Every day, the rail network around Tokyo has to meet the demands of mass transport, ferrying millions of people between distant points quickly and reliably, notes study coauthor Mark Fricker of the University of Oxford. “In contrast, the slime mold has no central brain or indeed any awareness of the overall problem it is trying to solve, but manages to produce a structure with similar properties to the real rail network.”
The yellow slime mold Physarum polycephalum grows as a single cell that is big enough to be seen with the naked eye. When it encounters numerous food sources separated in space, the slime mold cell surrounds the food and creates tunnels to distribute the nutrients. In the experiment, researchers led by Toshiyuki Nakagaki, of Hokkaido University in Sapporo, Japan, placed oat flakes (a slime mold delicacy) in a pattern that mimicked the way cities are scattered around Tokyo, then set the slime mold loose.
Initially, the slime mold dispersed evenly around the oat flakes, exploring its new territory. But within hours, the slime mold began to refine its pattern, strengthening the tunnels between oat flakes while the other links gradually disappeared. After about a day, the slime mold had constructed a network of interconnected nutrient-ferrying tubes. Its design looked almost identical to that of the rail system surrounding Tokyo, with a larger number of strong, resilient tunnels connecting centrally located oats. “There is a remarkable degree of overlap between the two systems,” Fricker says.
The researchers then borrowed simple properties from the slime mold’s behavior to create a biology-inspired mathematical description of the network formation. Like the slime mold, the model first creates a fine mesh network that goes everywhere, and then continuously refines the network so that the tubes carrying the most cargo grow more robust and redundant tubes are pruned.
The behavior of the plasmodium “is really difficult to capture by words,” comments biochemist Wolfgang Marwan of Otto von Guericke University in Magdeburg, Germany. “You see they optimize themselves somehow, but how do you describe that?” The new research “provides a simple mathematical model for a complex biological phenomenon,” Marwan wrote in an article in the same issue of Science.
Fricker points out that such a malleable system may be useful for creating networks that need to change over time, such as short-range wireless systems of sensors that would provide early warnings of fire or flood. Because these sensors are destroyed when disaster strikes, the network needs to efficiently re-route information quickly. Decentralized, adaptable networks would also be important for soldiers in battlefields or swarms of robots exploring hazardous environments, Fricker says.
The new model may also help researchers answer biological questions, such as how blood vessels grow to support tumors, Fricker says. A tumor’s network of vessels start out as a dense, unstructured tangle, and then refine their connections to be more efficient.
Not a scratch
Scorpions may have lessons to teach aircraft designers
The north African desert scorpion, Androctonus australis, is a hardy creature. Most animals that live in deserts dig burrows to protect themselves from the sand-laden wind. Not Androctonus. It usually toughs things out at the surface. Yet when the sand whips by at speeds that would strip paint away from steel, the scorpion is able to scurry off without apparent damage. Han Zhiwu of Jilin University, in China, and his colleagues wondered why.
Their curiosity is not just academic. Aircraft engines and helicopter rotor-blades are constantly abraded by atmospheric dust, and a way of slowing down this abrasion would be welcome. Dr Han suspects that scorpions may provide an answer. As he writes in Langmuir, he has discovered that the surface of Androctonus’s exoskeleton is odd. And when that oddness is translated into other materials it seems to protect them, as well.
Dr Han’s investigations began by scouring the pet shops of Changchun, where the university is located, for scorpions. Having obtained his specimens, he photographed them under a microscope, using ultraviolet light. This made the animals’ exoskeletons, which are composed of a sugar-based polymer called chitin, fluoresce—thus revealing details of their surface features. The team found that Androctonus armour is covered with dome-shaped granules that are 10 microns high and between 25 and 80 microns across. These, they suspected, were the key to its insouciance in the face of sandstorms.
To check, they took further photographs. In particular, they used a laser scanning system to make a three-dimensional map of the armour and then plugged the result into a computer program that blasted the virtual armour with virtual sand grains at various angles of attack. This process revealed that the granules were disturbing the air flow near the skeleton’s surface in ways that appeared to be reducing the erosion rate. Their model suggested that if scorpion exoskeletons were smooth, they would experience almost twice the erosion rate that they actually do.
Having tried things out in a computer, the team then tried them for real. They placed samples of steel in a wind tunnel and fired grains of sand at them using compressed air. One piece of steel was smooth, but the others had grooves of different heights, widths and separations, inspired by scorpion exoskeleton, etched onto their surfaces. Each sample was exposed to the lab-generated sandstorm for five minutes and then weighed to find out how badly it had been eroded.
The upshot was that the pattern most resembling scorpion armour—with grooves that were 2mm apart, 5mm wide and 4mm high—proved best able to withstand the assault. Though not as good as the computer model suggested real scorpion geometry is, such grooving nevertheless cut erosion by a fifth, compared with a smooth steel surface. The lesson for aircraft makers, Dr Han suggests, is that a little surface irregularity might help to prolong the active lives of planes and helicopters, as well as those of scorpions.
Source: The Economist
The Wisdom of Crowds
Excerpt from the book “The Wisdom of Crowds” by James Surowiecki, one of the most interesting book I’ve ever read.
Imagine that you are French. You are walking along a busy pavement in Paris and another pedestrian is approaching from the opposite direction. A collision will occur unless you each move out of the other’s way. Which way do you step?
The answer is almost certainly to the right. Replay the same scene in many parts of Asia, however, and you would probably move to the left. It is not obvious why. There is no instruction to head in a specific direction (South Korea, where there is a campaign to get people to walk on the right, is an exception). There is no simple correlation with the side of the road on which people drive: Londoners funnel to the right on pavements, for example.
Instead, says Mehdi Moussaid of the Max Planck Institute in Berlin, this is a behaviour brought about by probabilities. If two opposing people guess each other’s intentions correctly, each moving to one side and allowing the other past, then they are likely to choose to move the same way the next time they need to avoid a collision. The probability of a successful manoeuvre increases as more and more people adopt a bias in one direction, until the tendency sticks. Whether it’s right or left does not matter; what does is that it is the unspoken will of the majority.
That is at odds with most people’s idea of being a pedestrian. More than any other way of getting around—such as being crushed into a train or stuck in a traffic jam—walking appears to offer freedom of choice. Reality is more complicated. Whether stepping aside to avoid a collision, following the person in front through a crowd or navigating busy streets, pedestrians are autonomous yet constrained by others. They are both highly mobile and very predictable. “These are particles with a will,” says Dirk Helbing of ETH Zurich, a technology-focused university.
Messrs Helbing and Moussaid are at the cutting edge of a youngish field: understanding and modelling how pedestrians behave. Its purpose is not mere curiosity. Understanding pedestrian flows makes crowd events safer: knowing about the propensity of different nationalities to step in different directions could, for instance, matter to organisers of an event such as a football World Cup, where fans from various countries mingle. The odds of collisions go up if they do not share a reflex to move to one side. In a packed crowd, that could slow down lots of people.
In 1995 Mr Helbing and Peter Molnar, both physicists, came up with a “social force” computer model that used insights from the way that particles in fluids and gases behave to describe pedestrian movement. The model assumed that people are attracted by some things, such as the destination they are heading for, and repelled by others, such as another pedestrian in their path. It proved its worth by predicting several self-organising effects among crowds that are visible in real life.
One is the propensity of dense crowds spontaneously to break into lanes that allow people to move more efficiently in opposing directions. Individuals do not have to negotiate their way through a series of encounters with oncoming people; they can just follow the person in front. That works better than trying to overtake. Research by Mr Moussaid suggests that the effect of one person trying to walk faster than the people around them in a dense crowd is to force an opposing lane of pedestrians to split in two, which has the effect of breaking up the lane next door, and so on. Everyone moves slower as a result.
Up close and personal
Another self-organising behaviour comes when opposing flows of people meet at a single intersection: think of parents trying to shepherd their children into school as other parents, their sprogs already dropped off, try to leave. As people stream through in one direction, the pressure on their side of the intersection drops. That gives those waiting on the other side more opportunity to go through, until pressure on their side is relieved. The result is a series of alternating bursts of traffic through the gates.
This oscillation in flows is clever enough to have got Mr Helbing wondering about its application to cars. Traffic-light systems currently operate on fixed cycles, with lights staying green on the basis of past traffic patterns. If those patterns are not repeated, drivers are left to idle their engines for too long at red signals, raising emissions and tempers. Mr Helbing thinks it is better to have decentralised, local systems, which—like parents at the school gates—can respond to a build-up of traffic and keep the lights on green for longer if need be. City authorities agree: Mr Helbing’s ideas will soon be implemented in Dresden and Zurich.
Trying to capture every element of pedestrian movement in an equation is horribly complex, however. One problem is allowing for cultural biases, such as whether people step to the left or the right, or their willingness to get close to fellow pedestrians. An experiment in 2009 tested the walking speeds of Germans and Indians by getting volunteers in each country to walk in single file around an elliptical, makeshift corridor of ropes and chairs. At low densities the speeds of each nationality are similar; but once the numbers increase, Indians walk faster than Germans. This won’t be news to anyone familiar with Munich and Mumbai, but Indians are just less bothered about bumping into other people.
Another problem with assuming people act like particles is that up to 70% of people in a crowd are actually in groups. That matters, as anyone trying to get past shuffling tourists knows. It also leads to some lovely fine-scale choreography when small groups are squeezed. Observations of pavement crowds in Toulouse in France show that clusters of three and four people naturally organise themselves into concave “V” and “U” shapes, with middle members falling back slightly. If a group of three people cared about moving quickly, they would behave like geese and form a convex “V”, with the middle member slightly in front to forge a path. Instead, they adopt a formation that enables them to keep communicating with each other; talking trumps walking.
Mr Moussaid’s solution to such complexity has been to build a model based less on the analogy between humans and particles and more on cognitive science. Agents in this new model are allowed to “see” what’s in front of them; they then try to carve a free path through the masses to get to their destination. This approach produces the same effects of lane-formation in crowds as the physics-based models, but with some added advantages.
In particular, boffins think it could help make emergency evacuations safer. Simulating evacuations is a big part of what pedestrian modellers do—the King’s Cross underground fire in London in 1987 gave the field one of its starting shoves. One big danger in an emergency is that people will follow the crowd and all herd towards a single exit. That in turn means that the crowd may jam as too many people try to force their way through a single doorway.
The physics-based models do have an answer to this problem of “arching” (so called for the shape of the crowd that builds up around the exit). Their simulations suggest the flow of pedestrians through a narrow doorway can be smoothed by plonking an obstacle such as a pillar just in front of the exit. In theory, that should have the effect of splitting people into more efficient lanes. In practice, however, the idea of putting a barrier in front of an emergency exit is too counter-intuitive for planners to have tried.
The cognitive-science model offers a more palatable option, that of experimenting with the effects of changes in people’s visual fields. Mr Moussaid speculates that adaptable lighting systems, which use darkness to repel people and light to attract them, could be used to direct them in emergencies, for example.
Where the cognitive approach falls down is in the most packed environments. “At low densities, behaviour is cognitive and strategic,” says Mr Moussaid. “At high density, it’s about mass movement and physical pressures.” At a certain point crowds can shift from a controlled flow to a stop-and-go pattern, as people are forced to shorten their stride length and occasionally halt to avoid collisions. This kind of movement can develop into something much more frightening, known as crowd turbulence, when people can no longer keep a space between themselves and others. The physical forces that are imparted from one body to another when that happens are both chaotic and powerful: if someone falls over, others will be unable to avoid them.
Science meets religion
Working out precisely how and when these transitions happen is tough. Bringing a real-life situation under control once a stop-and-go pattern has started is equally hard. So the trick is to ensure that serious crowding is avoided in the first place. From big events such as the London Olympics to the design of new railway stations, engineering firms now routinely simulate the movement of people to try to spot areas where crowding is likely to occur.
A typical project involves using off-the-shelf software programs to identify potential bottlenecks in a particular environment, such as a stadium or a Tube station. These models specify the entry and exit points at a location and then use “routing algorithms” that send people to their destinations. Even a one-off event like the Olympics has plenty of data on pedestrian movement to draw on, from past games to other set-piece gatherings such as, say, city-centre carnivals, which enable some basic assumptions about how people will flow.
Once potential points of congestion are identified, more sophisticated models can then be used to go down to a finer level of detail. This second stage allows planners to change architectural designs for new locations and identify when to intervene in existing ones. “There should be many fewer crowd disasters given what we now know and can simulate,” says Mr Helbing.
The biggest test possible of these tools and techniques is the haj, the annual pilgrimage to Mecca in Saudi Arabia that Muslims are expected to carry out at least once in their lives if they can. With as many as 3m pilgrims making the journey each year, the haj has a long history of crowd stampedes and deaths. Indeed, video footage of a haj stampede is used by lots of modellers to validate their simulations of crowd turbulence.
The Saudi authorities have brought in consultants in recent years, focusing in particular on the layout of the Jamarat Bridge, where pilgrims perform a ritual in which they throw stones at three pillars. By making the crossing one-way, and changing the shape of the pillars so that people can stone them from a number of locations, they have improved the bridge’s safety.
But according to Paul Townsend of Crowd Dynamics, a consultancy that has worked on the pilgrimage, the risks remain significant. He thinks that the use of gates that could be opened and shut would help to manage the flow. Yet the haj presents some very specific difficulties beyond its sheer scale. Part of the problem is not having a clear idea of how many pilgrims will turn up, which makes planning difficult. Another issue is the nature of the crowd.
“Pilgrims on the haj have the attitude that, if I die there it is God’s will,” says Mr Townsend. “There is a willingness to get more and more dense in the space.” Scientists can model many aspects of pedestrian behaviour, but religious fervour is a step too far.
Source: The Economist
“At times of change, the learners are the ones who will inherit the world, while the knowers will be beautifully prepared for a world which no longer exists.”
“We become what we behold. We shape our tools and then our tools shape us.”