The california aggie
Science &Technology
wednesday, may 23, 2012 3
Smoking drug effective in treating drinking
Strategical plants
‘It would save hundreds of lives every year’ By ERIC C. LIPSKY Aggie Science writer
A new study by UC San Francisco researchers indicates that the drug varenicline, a drug used to help stop smoking, can be used to reduce drinking. Varenicline, commonly known by the brand name Chantix, has been FDAapproved since 2006 for helping people to stop smoking, but only recently did the researchers theorize that the drug could reduce alcohol consumption and began testing the drug on rats. After yielding results that indicated this drug could be effective in reducing drinking, human testing was done and a significant re-
duction in heavy drinking was found. Howard Fields, professor of neurology at UCSF and director of the Ernest Gallo Clinic and Research Center, and his colleagues split the participants into two groups and gave one group a placebo and the other group varenicline. He said that they started seeing results around the third week of testing. “We didn’t know what we were going to find,” Fields said. “We thought we would see something similar to the rat reduction.” The results confirmed the researchers’ hypothesis. Fields believes the drug to be a great treatment for
See SMOKING, page 6
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Could anti-smoking drug help curb drinking?
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Spacecraft “Dawn” reaches the Asteroid Belt Mission begins exploring asteroid Vesta
By BRIAN RILEY Aggie Science Writer
Last July a NASA-sponsored spacecraft called “Dawn” slipped into orbit about the first of its planned destinations — the asteroid Vesta, which is the second-largest asteroid in the Asteroid Belt between Mars and Jupiter. About 5 percent of meteorites recovered after falling to earth are believed to have come from Vesta’s surface. The Asteroid Belt is the name given to hundreds of thousands of asteroids, both large and small, that orbit the Sun in a band of space that stretches partway between the orbits of Mars and Jupiter. Were the asteroids once a planet in the past that broke apart? “Quite the opposite,” said Christopher T. Russell, the principal investigator of the Dawn mission. “The material tried to accumulate into a planet but never was able do so.” Russell coordinates and directs the science aspects of the Dawn mission as a part of his work as a professor in the Institute of Geophysics and Planetary Physics at UC Los Angeles. The Jet Propulsion Laboratory (JPL) in Pasadena is in charge of the actual operation and flight of the space vehicle. Elizabeth Palmer is a first-year graduate student who is working as a research assistant under Russell’s guidance at UC Los Angeles. She studied astronomy as an undergraduate at Case Western Reserve University in Cleveland, Ohio, but ended up deciding that planetary science was a better fit for what she wanted to do. She was able to find a planetary science internship at JPL. While at JPL, Palmer began learning about the technique of interpreting radar signals which have been bounced or grazed off the surface
rior taste. Thankfully, we learned our lesson by ... uh, making all of these bananas clones of each other. Well, live and learn. Researchers have Amy learned their lesson someStewart what, as they are working to make resistant hybrids that are still tasty enough for the mass market. Some species of plant are much more resistant to being eaten, and in fact are sometimes the ones doing the eating. Take a species of pitcher plant, Darlingtonia calmagine that a fire has ifornica. This plant is also just devastated a small area of forest. Trees have called the cobra lily for its burned to the ground, leav- almost predatory trickery. The basic strategy of ing stumps and cracked the pitcher plant is to lure trunks. All of the small bushes or grasses are com- hapless insects inside of its container, which is full of pletely blackened. digestive juices. What’s left? Tiny seeds. Why can’t the bug just The healing of the forest is fly out again, if they manpartially accomplished by age to get out of the deadthese seeds that only gerly liquid fast enough? Well, minate after a fire. When the inside of the container the old, dry trees burn down, the fire breaks these is slippery, first of all. It also has clear arseeds’ doreas, like litmancy and allows The next time you bite into an tle winnew, fresh apple, remember that what dows. The fly jumps up trees to you’re eating is an ovary to what it grow. thinks is an This exescape route, ample bumps against the wall and shows how plants are evofalls back into the liquid. lutionarily advanced organisms. Though they can’t Rinse and repeat until the insect is dead. Plants walk around like animals are more diabolical than we can, they are capable of a give them credit for. great deal of strategy, as well as offensive and defen- Most plants aren’t carnivorous and are just consive action. Simple defenses are com- tent to grow and spread mon among the plant king- their genes. This must indom, all to make them less volve some strategy as well, though. The leaves palatable or even deadare the organs that absorb ly to their many enemies. Thorns, pricks, irritants and the most sunlight; if the poisons are all to make sure plant grows in the deep forthat they won’t be devoured est and ends up covered by shade, how can they get the as soon as they sprout. sunlight that they so des Except, of course, the perately need? parts they they want to be They either must grow eaten. huge leaves (which is of The next time you bite ten what you’ll see in the into an apple, remember deep underbrush of a tropthat what you’re eating is an ovary. The idea from the ical rainforest) or they must plant’s point of view is that change where the leaves an animal will eat the entire grow. sweet, juicy fruit and walk a It’s difficult to see in real distance away before defe- time, but if you’re able to find fast-motion growth of cating out the seeds. a plant on YouTube, find Seeds reach the ground one and watch it. You’ll nowith ready-made fertilizer, tice that often, the stem will and the plant has successgrow in one direction, stop, fully spread its genes. then take a stem in a dif Human-cultivated fruit ferent direction. This is ofhas bypassed some of ten because the original these evolutionary mechstem wasn’t getting enough anisms, with worrying resunlight and it just wasn’t sults. The most common type of banana is called the worth the energy it would Cavendish banana, a seed- take to completely grow it. Roots do this, too. When less banana first cultivata plant is just starting to ed in the 1860s. In order grow its roots, they usuto propagate more trees, ally spread in all direcfarmers have to carefully tions. Soon enough, they remove and transplant the find that one location hapunderground stem where pens to have more nutrithey want the new plant to ents than another. The secgo. tion of roots in the low-nu When Panama disease, trient place will die, and the a fungal infection, nearplant now has more energy ly wiped out the entire bato spread in the place with nana population of the popular Gros Michel strain, the highest nutrition. breeders scrambled to find So when you look at a plant, remember that you’re a new type of banana that was resistant to the disease. looking at one of nature’s most strategical organisms. The result was the Dwarf Cavendish, a strain chosen for its hardiness and ease of AMY STEWART can be reached at science@ transport rather than supe- theaggie.org.
NASA model of asteroid Vesta.
of a planetary body and received on Earth. She hopes to be able to do the same type of work interpreting microwave transmissions from Dawn that have grazed the surface of Vesta in order to determine aspects of Vesta’s make-up, such as whether ice is present on the surface and in what amount. “It’s an opportunistic experiment that’s not perfect, since it’s hard to alter such concrete mission plans to the way that would be most ideal for our microwave experiment to work best,” Palmer said. “We are just waiting and hoping the geometry will work at some point.” If Dawn is able to successfully graze signals off Vesta, which are then successfully received here, Palmer will be able to compare that data with experimental data obtained from meteorites found on Earth. This mineral material was likely knocked off Vesta’s surface as a result of ancient
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collisions in space. Dawn gets its name from its primary purpose, which is the study of our solar system’s early history. Russell often stresses that he views Dawn as being a kind of time machine traveling back in time, since both Vesta and Dawn’s second target, Ceres, have likely preserved evidence of the Solar System’s formation in the contours of their crust and in their composition. Both Vesta and Ceres were formed 4.6 billion years ago. Dawn is currently scheduled to leave Vesta in August later this year and enter orbit about Ceres, the largest asteroid, in February 2015. According to Russell, it is the longterm thrust enabled by Dawn’s efficient ion-propulsion system which made the mission cost-effective and a visitation to two asteroids possible as a project goal. BRIAN RILEY can be reached at science@theaggie.org.
Crowdsource for truly unique musical experiences Researchers create the ultimate personalized music search engine By HUDSON LOFCHIE Aggie Science Writer
Our technological prowess is increasing every day, but the machines we use are still limited by the knowledge that the designers put into them. Researchers have started experimenting with a branch of computer science called “machine learning,” where computers can learn and adapt. The name evokes sinister Terminator imagery, but researchers at UC San Diego have been using machine learning to develop the most advanced music search engine ever created. The researchers are using the same methodology in their system as hospitals use to train new doctors. “When doctors learn how to diagnose diseases, they are trained to find patterns in patient data that indicate which disease the patient has. With many patients, patterns begin to emerge,” said Gert Lanckriet, a professor of electrical engineering at the UC San Diego Jacobs School of Engineering. People identify music by its characteristics, just like doctors identify diseases based on symptoms; is it jazz, rock or dubstep? Is it happy or sad, slow or fast, energizing or relaxing, piano or saxophone? The researchers started with a library of about 13,000 songs in their program, called Herd It, and started labeling each song with tags like those above. The program would then
Screenshot of Herd It game.
analyze patterns in the music and associate those patterns with the tags. As more songs were tagged, Herd It began to learn for itself what patterns constituted each genre or style, and it began to make its own tag suggestions. The re-
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searchers would simply confirm or reject the program’s suggestions. The more data Herd It received from confirmations and rejections, the better it became at suggesting tags. “The algorithms continuously adapt,”
said Doug Turnbull, a graduate student working in Lanckriet’s lab on the project. “People labeled music for us in the fun context of a game. People label the song with any tag [they think is appropriate] and we use the most common ones.” The music streaming service Pandora already does something similar. However, Pandora pays music experts to label songs. Each expert at Pandora takes about 30 minutes to tag each song by hand, making Pandora’s process very expensive. As such, Pandora has only about 900,000 songs in their library, compared to the near 20 million in the iTunes library. Herd It is an AI (artificial intelligence) that can tag any song it encounters in a matter of seconds, using plain english terminology to describe genre, feelings and settings. It does the same thing that paid musicologists do, but cheaper, faster and in simpler terms. The program works by analyzing the waveform of a song and identifying patterns in the frequencies that are indicative of each tag. The machine learning process is a continuous feedback loop. Users confirm or reject the program’s predictions, the machine learns something, and then it refines its predictions for the next guess. Every little bit of input from a user refines the algorithms’ accuracy on its future guesses.
See MUSIC, page 4
