Most college freshmen fill their dorm rooms with clothes, books, and electronics. Thiago Olson also brought his fusion reactor. But Vanderbilt University drew the line: No do-it-yourself reactors in the dorm! Instead, his device was housed in a nearby laboratory.

Olson’s project was motivated by the challenge of doing fusion—and by the same promise that has inspired thousands of physicists over the past half century. Nuclear fusion is the energy source that powers the sun; if channeled correctly, it could become a major source of clean energy here on Earth. Fusion occurs when the nuclei of two atoms are forced so close to each other that they bind together, releasing a great deal of energy in the process. Because positively charged nuclei forcefully repel each other, though, high temperatures are needed to bring about a union. Most fusion reactors are therefore enormous machines, like the $3.5 billion National Ignition Facility that recently opened in California.

Olson and a small cadre of other amateur nuclear engineers have found a simpler way. They are creating home-grown reactors, welding and wiring the devices in their backyards, garages, and basements (much to the alarm of neighbors). The hazards to the community are slim, the main ones being heavy use of electricity and short-range radiation that can be of risk to the “fusioneers” themselves.

43: Percentage of American freight that moves between cities by rail, the Association of American Railroads reports. One train can carry the same load as 280 trucks. Freight trains can move a ton of cargo 457 miles on a gallon of fuel, versus 130 miles for a full-size tractor trailer.

1: Percentage of all passenger intercity trips of more than 50 miles made by rail in the United States. Ninety percent of them are by car, 7 percent by air, and 2 percent by bus.

Physicist Michael Roukes and his colleagues at Caltech have developed a microscopic device that can measure the mass of a single molecule in real time. Chemists use such sensitive weighings to help determine the chemical identities of unknown substances. The Caltech team says that its system could eventually allow scientists to analyze thousands of different proteins in a matter of milliseconds using much smaller samples than before.

While the Obama administration hashes out plans for cutting future carbon emissions, engineers are quietly working on schemes to deal with carbon by putting it back where it came from: underground. The concept of storing carbon in rock—known as geologic carbon sequestration —has been dogged by concerns about cost, stability, and environmental impact. But recent findings suggest that it could be an effective way to clean up the carbon mess.

On the quarter-mile walk between his office at the École Polytechnique Fédérale de Lausanne in Switzerland and the nerve center of his research across campus, Henry Markram gets a brisk reminder of the rapidly narrowing gap between human and machine. At one point he passes a museumlike display filled with the relics of old supercomputers, a memorial to their technological limitations. At the end of his trip he confronts his IBM Blue Gene/P—shiny, black, and sloped on one side like a sports car. That new supercomputer is the center­piece of the Blue Brain Project, tasked with simulating every aspect of the workings of a living brain.

Markram, the 47-year-old founder and codirector of the Brain Mind Institute at the EPFL, is the project’s leader and cheerleader. A South African neuroscientist, he received his doctorate from the Weizmann Institute of Science in Israel and studied as a Fulbright Scholar at the National Institutes of Health. For the past 15 years he and his team have been collecting data on the neocortex, the part of the brain that lets us think, speak, and remember. The plan is to use the data from these studies to create a comprehensive, three-dimensional simulation of a mammalian brain. Such a digital re-creation that matches all the behaviors and structures of a biological brain would provide an unprecedented opportunity to study the fundamental nature of cognition and of disorders such as depression and schizophrenia.

Until recently there was no computer powerful enough to take all our knowledge of the brain and apply it to a model. Blue Gene has changed that. It contains four monolithic, refrigerator-size machines, each of which processes data at a peak speed of 56 tera­flops (teraflops being one trillion floating-point operations per second). At $2 million per rack, this Blue Gene is not cheap, but it is affordable enough to give Markram a shot with this ambitious project. Each of Blue Gene’s more than 16,000 processors is used to simulate approximately one thousand virtual neurons. By getting the neurons to interact with one another, Markram’s team makes the computer operate like a brain. In its trial runs Markram’s Blue Gene has emulated just a single neocortical column in a two-week-old rat. But in principle, the simulated brain will continue to get more and more powerful as it attempts to rival the one in its creator’s head. “We’ve reached the end of phase one, which for us is the proof of concept,” Markram says. “We can, I think, categorically say that it is possible to build a model of the brain.” In fact, he insists that a fully functioning model of a human brain can be built within a decade. Markram spent some time with DISCOVER to explain how.

As his friends flocked to social networks like Facebook and MySpace, Alessandro Acquisti, an associate professor of information technology at Carnegie Mellon University, worried about the downside of all this online sharing. “The personal information is not particularly sensitive, but what happens when you combine those pieces together?” he asks. “You can come up with something that is much more sensitive than the individual pieces.”

Acquisti tested his idea in a study, reported earlier this year in Proceedings of the National Academy of Sciences. He took seemingly innocuous pieces of personal data that many people put online (birthplace and date of birth, both frequently posted on social networking sites) and combined them with information from the Death Master File, a public database from the U.S. Social Security Administration. With a little clever analysis, he found he could determine, in as few as 1,000 tries, someone’s Social Security number 8.5 percent of the time. Data thieves could easily do the same thing: They could keep hitting the log-on page of a bank account until they got one right, then go on a spending spree. With an automated program, making thousands of attempts is no trouble at all.

The problem, Acquisti found, is that the way the Death Master File numbers are created is predictable. Typically the first three digits of a Social Security number, the “area number,” are based on the zip code of the person’s birthplace; the next two, the “group number,” are assigned in a predetermined order within a particular area-number group; and the final four, the “serial number,” are assigned consecutively within each group number. When Acquisti plotted the birth information and corresponding Social Security numbers on a graph, he found that the set of possible IDs that could be assigned to a person with a given date and place of birth fell within a restricted range, making it fairly simple to sift through all of the possibilities.

Welcome to the unnerving world of data mining, the fine art (some might say black art) of extracting important or sensitive pieces from the growing cloud of information that surrounds almost all of us. Since data persist essentially forever online—just check out the Internet Archive Wayback Machine, the repository of almost everything that ever appeared on the Internet—some bit of seemingly harmless information that you post today could easily come back to haunt you years from now.

Pictured: A generator at the European Synchrotron Radiation Facility (ESRF) in France powers what are known as “kicker magnets,” which help direct beams of high-energy electrons that whiz around the facility at high speeds. Other magnets wiggle the circulating particle beams, causing them to emit intense X-rays. ESRF’s accelerator is the most powerful synchrotron light source in Europe. Researchers at the facility use this energetic radiation to probe the structures of diverse targets that include superstrong glass, fossils trapped in amber, and proteins produced by malaria parasites.