BU’s Own Project Runway
Comments(0) Looks like a winner
Comments(0) When you vote in an election, your choice is surely not influenced by anything as superficial as a candidate’s looks, right?
Right?
New research from MIT political scientists shows that the appearances of politicians do indeed strongly influence voters — and that people around the world have similar ideas about what a good politician looks like. While few political observers would be surprised to learn that good looks earn votes, the MIT researchers have quantified a phenomenon that is more often assumed to be true than rigorously measured.
“Ever since Aristotle, people have written about the concern that charismatic leaders who speak well and look good can sway votes even if they do not share the people’s views,” acknowledges Gabriel Lenz, an associate professor in the Department of Political Science at MIT, and a co-author of the study.
To test this idea, though, Lenz and his colleagues showed voters in the United States and India pairs of candidate photos from real election matchups in Brazil and Mexico. When asked which candidate would make a better elected official, the participants in the study, regardless of where they lived, largely selected the same candidates. Moreover, their choices corresponded closely to the outcomes of those Brazilian and Mexican races, meaning the public attribution of good looks to a candidate is a leading indicator of a campaign’s result.
“We were a little shocked that people in the United States and India so easily predicted the outcomes of elections in Mexico and Brazil based only on brief exposure to the candidates’ faces,” says Lenz. “These are all different cultures, with different political traditions and different histories.”
In the study, the researchers showed voters pairs of candidates from 122 elections in Mexico and Brazil. The participants in the study were asked which candidate would be a better elected official. Respondents in India and the United States agreed with each other about 75 percent of the time when asked which candidate seemed superior; a group of respondents in the United States and Mexico agreed with each other about 80 percent of the time.
In turn, simply knowing which candidate the participants judged to have a superior appearance allowed the researchers to correctly predict the winner in 68 percent of Mexican elections and 75 percent of some Brazilian elections. “These are very large effects,” the authors note in the working paper, “Looking like a Winner: Candidate Appearance and Electoral Success in New Democracies,” which will be published in the journal World Politics this fall.
Lenz conducted the study along with Chappell Lawson, also an associate professor of political science at MIT, Michael Myers, a research affiliate with MIT’s Department of Political Science, and Andy Baker, a political scientist at the University of Colorado.
The paper is an “interesting and innovative study,” writes Panu Poutvaara, an economist at the University of Helsinki who also studies the influences of candidate appearances, responding to questions by e-mail. In Poutvaara’s view, by helping to confirm the general connection between good looks and ballot-box success, the study paves the way for future research that should address precisely why voters favor good-looking candidates: “Is it because voters either enjoy watching good-looking politicians on TV, or think that they are better in social interactions?”
Lenz and his colleagues are addressing this question from a slightly different angle in additional, ongoing research. In a forthcoming study, they find that “low-information voters” are especially likely to choose candidates based on looks. “These are people who don’t know much about politics, but watch a lot of TV,” says Lenz. The researchers are currently writing a paper based on this latter project.
Bursting a bubble?
Comments(0) Understanding the processes that cause volcanic eruptions can help scientists predict how often and how violently a volcano will erupt. Although scientists have a general idea of how these processes work — the melting of magma below the volcano causes liquid magma and gases to force their way to Earth’s surface — eruptions happen so rarely, and often with little warning, that it can be difficult to study them in detail.
One volcano that volcanologists believe they understand fairly well is Italy’s Stromboli, which has been erupting every five to 20 minutes for thousands of years, spewing fountains of ash and magma several meters into the sky. For several decades, scientists have pretty much used one theory to explain what is causing huge amounts of gas to erupt so frequently: swimming-pool-sized bubbles that travel through a few hundred meters of molten magma before popping at the surface.
But they may be wrong, according to new research by Jenny Suckale, a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS), who has developed a sophisticated computer model to simulate Stromboli’s magma flow. In a two-paper series published July 20 in The Journal of Geophysical Research, Suckale suggests that giant gas bubbles can’t be driving the Stromboli eruptions because such bubbles aren’t compatible with the basic laws of fluid dynamics, or the science of how fluids move. Instead of large bubbles that pop at the top of Stromboli’s conduits — pipelike openings that connect the volcano’s magma chamber to the Earth’s surface — Suckale thinks that the eruptions are caused by a spongelike plug located within the conduit, similar to a cork in a champagne bottle, that fractures every few minutes as a result of pressure created by significantly smaller bubbles.
Although all volcanoes are different — some are driven by gas while others are driven by rising magma or interactions with water — Suckale says that figuring out Stromboli would be “an important step forward for volcanology” because scientists don’t really know the details of how most volcanoes function. Rethinking how Stromboli works could also shed light on the processes of volcanoes that appear to be driven by similar mechanisms as Stromboli, such as Mount Erebus in Antarctica, which has been continuously active since the 1970s.
Scaling Stromboli
Despite having a wealth of data about Stromboli, volcanologists have really only applied one model to explain Stromboli’s continuous eruptions, Suckale says. According to the so-called “big bubble paradigm,” as magma rises to Stromboli’s surface, pressure drops, and this creates gas bubbles that merge together and can become several meters wide. Eventually, these bubbles explode at the top of the conduit.
But the problem with this theory, according to Suckale, is that it conflicts with the basic principles of fluid dynamics. Specifically, magma doesn’t have enough surface tension (created when two fluids meet) or viscosity (a measure of a fluid’s resistance) to maintain bubbles larger than a few dozen centimeters. She thinks that many researchers have assumed that bubbles inside Stromboli behave similarly to bubbles in a tank of water. “People take lab models as an analog for the volcano, but the scale is so different, and fluid dynamics is so dependent on scale,” she explains.
To test the theory, Suckale and co-authors and EAPS professors Brad Hager and Lindy Elkins-Tanton, as well as Jean-Christophe Nave, a lecturer in MIT’s Department of Mathematics, developed a computer model of the inner volcano’s mixture of gas and magma and the bubbles that can rupture or merge. By changing certain parameters, such as scale, she discovered that it would be physically impossible for massive gas bubbles in Stromboli to survive for longer than a second because of the lack of stabilizing forces, such as surface tension and viscosity.
Suckale still believes there are gas bubbles inside Stromboli that are created by some unknown source located underneath the volcano. But she thinks these bubbles are significantly smaller — perhaps only several centimeters thick — and accumulate beneath a porous plug that covers part of the volcano. As the bubbles exert greater pressure on the plug, it eventually fractures, causing gas, rocks and liquid to scatter into the sky. This could explain why samples of Stromboli rock contain many tiny crystals — because the top of Stromboli is a spongelike plug of crystals and gas bubbles that releases lots of gas every few minutes.
Kathy Cashman, a geologist at the University of Oregon, says Suckale’s modeling work “greatly advances” volcanologists’ understanding of the bubbles inside Stromboli and may also shed light on noneruptive processes in volcanoes that could also be transferring gas to the atmosphere. “Jenny’s work sits at the boundary of these two types of gas transfer, and her modeling may help to address very fundamental issues related to volatile budgets of both the magma and the atmosphere,” Cashman says. But she cautions that Suckale’s work represents a “first step” toward modeling a very complex system, and that future modeling efforts should address the effect that crystals may have on bubble behavior.
Suckale agrees, but for now, she is working to develop a new model to explain how she thinks the theorized Stromboli plug works, why it could cause such constant eruptions and what this might say about other volcanoes that erupt frequently.
Temporary Contemporary Art
Comments(0) Visual, Accomplished Alumni
Comments(0) A plane that lands like a bird
Comments(0) Everyone knows what it’s like for an airplane to land: the slow maneuvering into an approach pattern, the long descent, and the brakes slamming on as soon as the plane touches down, which seems to just barely bring it to a rest a mile later. Birds, however, can switch from barreling forward at full speed to lightly touching down on a target as narrow as a telephone wire. Why can’t an airplane be more like a bird?
MIT researchers have demonstrated a new control system that allows a foam glider with only a single motor on its tail to land on a perch, just like a pet parakeet. The work could have important implications for the design of robotic planes, greatly improving their maneuverability and potentially allowing them to recharge their batteries simply by alighting on power lines.
Birds can land so precisely because they take advantage of a complicated physical phenomenon called “stall.” Even when a commercial airplane is changing altitude or banking, its wings are never more than a few degrees away from level. Within that narrow range of angles, the airflow over the plane’s wings is smooth and regular, like the flow of water around a small, smooth stone in a creek bed.
A bird approaching its perch, however, will tilt its wings back at a much sharper angle. The airflow over the wings becomes turbulent, and large vortices — whirlwinds — form behind the wings. The effects of the vortices are hard to predict: If a plane tilts its wings back too far, it can fall out of the sky. Hence the name “stall.”
The smooth airflow over the wings of a normally operating plane is well-understood mathematically; as a consequence, engineers are highly confident that a commercial airliner will respond to the pilot’s commands as intended. But stall is a much more complicated phenomenon: Even the best descriptions of it are time-consuming to compute.
Reap the whirlwind
To design their control system, MIT Associate Professor Russ Tedrake, a member of the Computer Science and Artificial Intelligence Laboratory, and Rick Cory, a PhD student in Tedrake’s lab who defended his dissertation this spring, first developed their own mathematical model of a glider in stall. For a range of launch conditions, they used the model to calculate sequences of instructions intended to guide the glider to its perch. “It gets this nominal trajectory,” Cory explains. “It says, ‘If this is a perfect model, this is how it should fly.’” But, he adds, “because the model is not perfect, if you play out that same solution, it completely misses.”
So Cory and Tedrake also developed a set of error-correction controls that could nudge the glider back onto its trajectory when location sensors determined that it had deviated from it. By using innovative techniques developed at MIT’s Laboratory for Information and Decision Systems, they were able to precisely calculate the degree of deviation that the controls could compensate for. The addition of the error-correction controls makes a trajectory look like a tube snaking through space: The center of the tube is the trajectory calculated using Cory and Tedrake’s model; the radius of the tube describes the tolerance of the error-correction controls.
The control system ends up being, effectively, a bunch of tubes pressed together like a fistful of straws. If the glider goes so far off course that it leaves one tube, it will still find itself in another. Once the glider is launched, it just keeps checking its position and executing the command that corresponds to the tube in which it finds itself.
The measure of air resistance against a body in flight is known as the “drag coefficient.” A cruising plane tries to minimize its drag coefficient, but when it’s trying to slow down, it tilts its wings back in order to increase drag. Ordinarily, it can’t tilt back too far, for fear of stall. But because Cory and Tedrake’s control system takes advantage of stall, the glider, when it’s landing, has a drag coefficient that’s four to five times that of other aerial vehicles.
A high-speed video of the researchers’ computer-controlled glider landing on a suspended string perch.
Video courtesy of Russ Tedrake and Rick Cory (view more videos and images)
From spy planes to fairies
For some time, the U.S. Air Force has been interested in the possibility of unmanned aerial vehicles that could land in confined spaces and has been funding and monitoring research in the area. “What Russ and Rick and their team is doing is unique,” says Gregory Reich of the Air Force Research Laboratory. “I don’t think anyone else is addressing the flight control problem in nearly as much detail.” Reich points out, however, that in their experiments, Cory and Tedrake used data from wall-mounted cameras to gauge the glider’s position, and the control algorithms ran on a computer on the ground, which transmitted instructions to the glider. “The computational power that you may have on board a vehicle of this size is really, really limited,” Reich says. Even though the MIT researchers’ course correction algorithms are simple, they may not be simple enough.
Tedrake believes, however, that computer processors powerful enough to handle his and Cory’s control algorithms are only a few years off. In the meantime, his lab has already begun to address the problem of moving the glider’s location sensors onboard, and although Cory will be moving to California to take a job researching advanced robotics techniques for Disney, he hopes to continue collaborating with Tedrake. “I visited the air force, and I visited Disney, and they actually have a lot in common,” Cory says. “The air force wants an airplane that can land on a power line, and Disney wants a flying Tinker Bell that can land on a lantern. But the technology’s similar.”
Nobody’s home
Comments(0) Foreclosed homes dot the American landscape — they make up about one in 12 houses with under $1 million left on the mortgage. These foreclosures drive down home prices, both because they add to the housing supply and because the financial firms that acquire the houses want to unload them promptly.
However, since foreclosures often occur in economically struggling areas, it is hard to determine how much of the drop in a home’s value is due to its foreclosure, and how much can be blamed on the economy in general.
Now, in a recent working paper, MIT economist Parag Pathak and two Harvard researchers, John Y. Campbell and Stefano Giglio, have put a price tag on foreclosures. Specifically, they’ve determined how much a foreclosure dents a home’s value, as opposed to a home going on the market because the owner has died or declared bankruptcy. Moreover, they’ve demonstrated how much foreclosures depress the prices of the houses around them, a finding that should capture the attention of home-owners and policy-makers.
In the study, “Forced Sales and House Prices,” which will be published in the American Economic Review, Pathak, Campbell and Giglio examined 1.8 million home sales in Massachusetts from 1987 to 2009. By looking in granular detail at real-estate prices, the researchers have concluded that a foreclosure reduces the value of a house by 27 percent, on average.
“It’s not surprising that there is a discount due to foreclosure,” says Pathak. “But it is surprising that it’s so large.”
By contrast, other types of forced sales lower home prices by smaller amounts. When a house is sold after the death of an owner, Pathak and his co-authors found, the price drops 5 to 7 percent on average. When an owner declares bankruptcy, the value sinks 3 percent.
The researchers believe that their discovery of the gaps between these various price reductions is a key to isolating the effects of foreclosures. Because the declines in value are so disparate, yet occur among comparable homes in the same times and places, the reductions in value are not all attributable to the same overarching economic conditions. Instead, the researchers suggest in the paper, a central cause of the larger foreclosure discount is that the condition of foreclosed houses often deteriorates much more than it does for other kinds of houses whose ownership changes hands.
Lower benchmarks
This tendency of foreclosed homes to fall into disrepair lies behind the other main finding of Pathak, Campbell and Giglio: The presence of a foreclosed house in a neighborhood reduces the value of the homes around it. In their estimation, the value of a home drops by 1 percent, on average, if it is within roughly 250 feet of a foreclosed home. This paper represents the first time economists have been able to cleanly quantify how much nearby foreclosures affect prices of inhabited homes.
“This can happen for multiple reasons,” says Pathak. First of all, he notes, “If you live near a foreclosed house, it may not be maintained.” Neighborhood appearances enhance real-estate value, and ill-maintained houses make an area less desirable.
Secondly, even without visible deterioration of foreclosed houses, such homes, when resold quickly for a discount, can affect neighborhood values. “A home-buyer’s benchmark [for a fair price] will usually include houses in the same neighborhood,” Pathak says. Therefore, average local values can sink even without visible blight.
The study is a “very valuable and important paper,” says Christopher Mayer PhD ’93, a professor and dean at Columbia Business School in New York, who thinks it will open up more research on whether foreclosures cause other foreclosures, a process he calls “contagion.” Even though Pathak, Campbell and Giglio found that foreclosures only dent the values of neighboring homes, Mayer questions whether there may be a tipping point “at which a neighborhood starts to fall apart.”
The Obama administration has weighed a variety of proposals aimed at limiting foreclosures. In June, the White House directed $1.5 billion of a newly created “Hardest Hit Fund” to help homeowners in five states — Arizona, California, Florida, Michigan and Nevada — suffering from high numbers of foreclosures.
Pathak believes that there are housing-policy implications to the emerging understanding of the precise impact of foreclosures on neighboring home values. The work, he says, “speaks to whether or not we should have policies to prevent foreclosures. This is a fundamental issue in the housing market, so we’re trying to take a step in the direction of measuring how big a deal this effect is.”
Imaging fish on the fly
Comments(0) One of the most commonly studied laboratory animals is the zebrafish — a tiny fish with transparent embryos, or larvae, whose internal organs can be easily seen as they develop.
Because they are genetically similar to humans and have complex organs, biologists often use zebrafish as a model for human diseases such as cancer, liver disease and heart disease. However, one limitation of zebrafish studies is that it takes several minutes to visually examine each larva. This has kept researchers from using the fish in experiments that require a large number of animals, such as testing the effects of many different drugs.
With the aim of speeding up the process and enabling large-scale studies, engineers at MIT have developed a new technique that can analyze larvae in seconds. The researchers, led by Mehmet Fatih Yanik, associate professor of electrical engineering and computer science, describe the new technology in the July 18 issue of the journal Nature Methods. First authors of the Nature Methods paper are graduate students Carlos Pardo-Martin and Tsung-Yao Chang; co-authors are Bryan Koo, Cody Gilleland and Steve Wasserman.
“There is significant need for high-throughput [automated] studies on whole animals, at high resolution,” says Yanik. “People are currently doing this manually, which is too slow. Ours is the only system that can take a large library of chemicals and screen it on thousands of vertebrates.”
Although humans and zebrafish may not appear to be closely related, many zebrafish organs and much of its biochemistry are similar to those of humans. For example, zebrafish and humans share the same liver enzymes, so the fish are useful for testing drugs that might cause liver damage. They also make good subjects for studies of cancer, Parkinson’s disease, Alzheimer’s, diabetes, amyotrophic lateral sclerosis (ALS) and other diseases, says Yanik.
Zebrafish take only seven days to fully develop, and most of their organs are formed by the third day of development, which makes zebrafish studies faster than those with mice or other slow-growing mammals. Best of all, the transparency of the larvae lets researchers directly see the effects of drugs or genetic mutations.
However, inspecting the animals is tedious and time-consuming. “We have to manually look at each embryo in a dish, which involves a lot of positioning and repositioning,” says Leonard Zon, professor of hematology and oncology at Harvard Medical School, who was not involved in the research. “Having the ability to flow the embryos through a machine and image them on the fly is going to be very helpful.”
With the new MIT system, larvae are pumped from a holding area to an imaging platform, where they are automatically rotated so the area of greatest interest can be seen. This is important because if the larvae are in the wrong position, the yolk or pigmentation on the skin may block the organs that the researcher wants to observe. The animals remain unharmed throughout the process.
The microscope’s resolution is high enough to image individual cells, and the entire process takes about 19 seconds per animal, compared to about 10 minutes for manual inspection. To demonstrate the system’s effectiveness, the MIT team imaged the neurons that project from the zebrafish retina to the brain. The system could also be used to observe tumor growth, organ regeneration or stem-cell migration, says Yanik.
Development of the new technology was partially funded by a National Institutes of Health Director’s Innovator Award, the Packard Award in Science and Engineering, an Alfred Sloan Award in Neuroscience, and a SPARC grant from the Broad Institute.
Yanik’s team has applied for a patent on the device and is now looking into commercial applications to use the technology to screen large numbers of drugs on various zebrafish disease models. The researchers are also working on further speeding up the system and developing ways to process the huge amounts of data generated by the imaging machine.
Building a Roller Coaster with K’Nex
Comments(0) Saving Stellwagen
Comments(0) Who says Uncle Sam never admits mistakes? The long-awaited management plan for the vital Stellwagen Bank National Marine Sanctuary, released just after Independence Day, plainly admits that when it comes to protecting the precious sanctuary in the Gulf of Maine, about 25 miles east of Boston, the government goofed.