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"People tend to conform their factual beliefs to ones that are consistent with their cultural outlook, their world view," Braman says. The Cultural Cognition Project has conducted several experiments to back that up. Participants in these experiments are asked to describe their cultural beliefs. Some embrace new technology, authority and free enterprise. They are labeled the "individualistic" group. Others are suspicious of authority or of commerce and industry. Braman calls them "communitarians." In one experiment, Braman queried these subjects about something unfamiliar to them: nanotechnology — new research into tiny, molecule-sized objects that could lead to novel products. "These two groups start to polarize as soon as you start to describe some of the potential benefits and harms," Braman says. The individualists tended to like nanotechnology. The communitarians generally viewed it as dangerous. Both groups made their decisions based on the same information. "It doesn't matter whether you show them negative or positive information, they reject the information that is contrary to what they would like to believe, and they glom onto the positive information," Braman says.

"Basically the reason that people react in a close-minded way to information is that the implications of it threaten their values," says Dan Kahan, a law professor at Yale University and a member of The Cultural Cognition Project. Kahan says people test new information against their preexisting view of how the world should work. "If the implication, the outcome, can affirm your values, you think about it in a much more open-minded way," he says. And if the information doesn't, you tend to reject it. In another experiment, people read a United Nations study about the dangers of global warming. Then the researchers told the participants that the solution to global warming is to regulate industrial pollution. Many in the individualistic group then rejected the climate science. But when more nuclear power was offered as the solution, says Braman, "they said, you know, it turns out global warming is a serious problem."And for the communitarians, climate danger seemed less serious if the only solution was more nuclear power.

By reworking a theory first proposed by physicists in the 1920s, the researchers discovered a new way to predict important characteristics of a new material before it's been created. The new formula allows computers to model the properties of a material up to 100,000 times faster than previously possible and vastly expands the range of properties scientists can study. "The equation scientists were using before was inefficient and consumed huge amounts of computing power, so we were limited to modeling only a few hundred atoms of a perfect material," said Emily Carter, the engineering professor who led the project. "But most materials aren't perfect," said Carter, the Arthur W. Marks '19 Professor of Mechanical and Aerospace Engineering and Applied and Computational Mathematics. "Important properties are actually determined by the flaws, but to understand those you need to look at thousands or tens of thousands of atoms so the defects are included. Using this new equation, we've been able to model up to a million atoms, so we get closer to the real properties of a substance." By offering a panoramic view of how substances behave in the real world, the theory gives scientists a tool for developing materials that can be used for designing new technologies. Car frames made from lighter, strong metal alloys, for instance, might make vehicles more energy efficient, and smaller, faster electronic devices might be produced using nanowires with diameters tens of thousands of times smaller than that of a human hair.

"As far as we can tell, this is the first time this type of behavior has been reported in cells that are part of a larger organism," says Peter T. Cummings, John R. Hall Professor of Chemical Engineering, who directed the study that is described in the March 10 issue of the Public Library of Science journal PLoS ONE. The discovery was the unanticipated result of a study the Cummings group conducted to test the hypothesis that the freedom with which different cancer cells move - a concept called motility - could be correlated with their aggressiveness: That is, the faster a given type of cancer cell can move through the body the more aggressive it is. "Our results refute that hypothesis—the correlation between motility and aggressiveness that we found among three different types of cancer cells was very weak," Cummings says. "In the process, however, we began noticing that the cell movements were unexpectedly complicated." Then the researchers' interest was piqued by a paper that appeared in the February 2008 issue of the journal Nature titled, "Scaling laws of marine predator search behaviour." The paper contained an analysis of the movements of a variety of radio-tagged marine predators, including sharks, sea turtles and penguins. The authors found that the predators used a foraging strategy very close to a specialized random walk pattern, called a Lévy walk, an optimal method for searching complex landscapes. At the end of the paper's abstract they wrote, "...Lévy-like behaviour seems to be widespread among diverse organisms, from microbes to humans, as a 'rule' that evolved in response to patchy resource distributions." This gave Cummings and his colleagues a new perspective on the cell movements that they were observing in the microscope. They adopted the basic assumption that when mammalian cells migrate they face problems, such as efficiently finding randomly distributed targets like nutrients and growth factors, that are analogous to those faced by single-celled organisms foraging for food. With this perspective in mind, Alka Potdar, now a post-doctoral fellow at Case Western Reserve University and the Cleveland Clinic, cultured cells from three human mammary epithelial cell lines on two-dimensional plastic plates and tracked the cell motions for two-hour periods in a "random migration" environment free of any directional chemical signals. Epithelial cells are found throughout the body lining organs and covering external surfaces. They move relatively slowly, at about a micron per minute which corresponds to two thousandths of an inch per hour. When Potdar carefully analyzed these cell movements, she found that they all followed the same pattern. However, it was not the Lévy walk that they expected, but a closely related search pattern called a bimodal correlated random walk (BCRW). This is a two-phase movement: a run phase in which the cell travels primarily in one direction and a re-orientation phase in which it stays in place and reorganizes itself internally to move in a new direction. In subsequent studies, currently in press, the researchers have found that several other cell types (social amoeba, neutrophils, fibrosarcoma) also follow the same pattern in random migration conditions. They have also found that the cells continue to follow this same basic pattern when a directional chemical signal is added, but the length of their runs are varied and the range of directions they follow are narrowed giving them a net movement in the direction indicated by the signal.