Tuesday, June 22, 2010


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Using the NASA/ESA Hubble Space Telescope, astronomers from the Max Planck Institute for Astronomy in Heidelberg and the University of Cologne have completed a high precision study of one of the most massive young star clusters in the Milky Way. To this end, the scientific researchers compared two observations that were made ten years apart. Their unexpected findings: the members of the cluster are in no stable state of balance and have not yet "settled down".

Open stellar clusters such as the famous Pleiades will be held together forever: in the course of dozens of millions of years their different stars will disperse. Very massive and compact clusters are different. In the long term, this can lead to the development of massive aggregations of globular clusters, whose tightly-packed stars remain gravitationally bound to each other for billions of years.

With a mass of more than 10,000 suns packed into a volume with a diameter of a mere three light-years, the massive young star cluster in the giant nebula NGC 3603 is one of the most compact stellar clusters in the Milky Way. For comparison, in our immediate cosmic neighbourhood, there is only one single star of the same volume as the Sun. Could this massive open stellar cluster be a globular cluster in the making?

In order to unravel this question, a team of astronomers led by Wolfgang Brandner from the Max Planck Institute for Astronomy, Heidelberg, MPIA, tracked the movement of hundreds of the cluster's stars. Such a study can reveal whether the stars were in the process of drifting apart, or about to settle down, i.e. to achieve a long-term, stable state of balance. What is more, the measurements also serve to distinguish members of the star cluster from unrelated stars that, as viewed from Earth, just happen to fall along the same light of sight.

Measurements of this kind are difficult. Imagine a star moving sideways at a rate of a few kilometres per second, viewed from a distance of 20,000 light-years - the actual distance of NGC 3603 from Earth - such a star's position on the night sky would shift by no more than a few billionths of an angular degree per year, at the limit of the capability of today's most precise observation methods and instruments.

By using two observations, made ten years apart with the same camera aboard the Hubble Space Telescope, and by performing an intricate analysis to account for all possible disturbances, Brandner and his team were able to reach the required accuracy. All in all, the astronomers observed more than 800 stars. About 50 of these were identified as foreground stars, which are unrelated to the cluster. From the remaining sample of more than 700 - a quite varied selection in terms of different masses and surface temperatures - the astronomers were able to obtain sufficiently precise speed measurements for 234 cluster stars.

Boyke Rochau (MPIA), the paper's lead author, who performed the data analysis as part of his PhD work, explains: "Once our analysis was completed, we reached a precision of 27 millionths of an arc second per year. Imagine you are in Bremen, observing an object that is located in Vienna. Now the object moves sideways by the breadth of a human hair. That's a change in apparent position of about 27 millionths of an arc second."

The results for the motion of these cluster stars were surprising. According to widely accepted models, which reproduce what is actually observed in older globular clusters, the average stellar speed in a cluster like the one in NGC 3603 should depend on mass. Stars with lower mass should move faster, and those with higher mass should move more slowly. The stars for which precision measurements were possible represent a range of masses between 2 and 9 times that of the Sun. Yet their average speed does not appear to vary with mass at all, with all of them moving at about the same average speed of 4.5 km/s.

Apparently this very massive star cluster has not yet settled down. Instead, the stars' velocities still reflect conditions from the time the cluster was formed, approximately one million years ago.

The intriguing question of whether or not the massive young cluster in NGC 3603 will become a globular cluster remains open. Given the new results, it all depends on the speeds of the low-mass stars, which were too faint to allow for precise speed measurements with the Hubble Space Telescope.

Wolfgang Brandner says: "To find out whether or not our star cluster will disperse, we will need to wait for the next generation of telescopes, such as the James Webb Space Telescope or the European Extremely Large Telescope of the European Southern Observatory."

(Photo: NASA/ESA/Wolfgang Brandner (MPIA), Boyke Rochau (MPIA) and Andrea Stolte (Universität zu Köln))

Max Planck Institute


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An international research team has for the first time gathered a database of the oldest people in the world - those who lived beyond their 110th birthday. While searching for these "supercentenarians" and trying to find accurate documentation of their age, the researchers not only collected data for scientific purposes, but also documented the personal histories and wisdom of those who lived more than a century. They have now published their findings and the stories of many of their subjects in the book "Supercentenarians," which was coordinated by the Max Planck Institute for Demographic Research (MPIDR) in Rostock/Germany.

How long can humans live? It’s a natural question, but age researchers agree that it is now obsolete; there is no upper limit to life expectancy in sight. Scientific data shows that records are being broken every year. Today there is not only a dramatically increasing number of centenarians, but also more and more men and women who live to 110 years old or older - the supercentenarians.

"Investigating very old age has always been difficult for demographers," says Heiner Maier from the MPIDR. "Science has been plagued by myths and fairy tales." Most claims of modern day Methuselahs appear promising at first glance, but usually turn out to be unverifiable. Entries in the Guinness Book of World Records aren’t reliable either; their validation is often based solely on documents provided by the families of those who reached an advanced age and are not independently confirmed by scientists.

Now, in an ambitious international effort, researchers in 15 nations have spent the last ten years searching their countries for people who reached the age of 110 or more. Together they found over 600 supercentenarians (in the USA, Canada, Japan, Australia, France, Italy, Spain, Germany, Switzerland, Belgium, the United Kingdom and in the Nordic countries). Of the 600, nearly 20 lived beyond 115.

The new data was used to create the International Database on Longevity (IDL), http://www.supercentenarians.org/. "The IDL is the first reliable record of scientifically verified data about supercentenarians on an international scope", says Heiner Maier from the MPIDR. "It is the best existing account of mortality beyond the age of 110."

Finding the supercentenarians was an unusual task for the demographers, as they could not rely on standard statistical methods. In each country the scientists designed their own strategy of how to identify probable candidates of the super old, and then prove their age by locating official documents that confirmed their date of birth and date of death (or current age if still living).

But there were challenges. In the late 19th century, when the supercentenarians were born, many countries didn’t have a central birth register, and often original documents were lost, misplaced or forgotten. So the scientists needed to search through a massive amount of certificates, census lists, death registers and the paper files of universities and health and security administrations to identify supercentenarians.

The findings varied between countries. In the United States 341 supercententarians were eventually found (309 women and 32 men), whereas in the much smaller country of Denmark only two women were verified as being over 110. In some cases going through all of the records would have been logistically impossible. In Germany, for instance, the researchers would have had to sort through records of roughly 8000 Residence Registry Offices. Luckily, however, researchers found a much faster method - they asked the Office of the German President for help. The President keeps a directory of residents older than 100 in order to send birthday congratulations. With the list in hand the researchers easily tracked down 17 supercentenarians.

The record holder in longevity is still the French woman Jeanne Calment, who died in 1997 at the age of 122. The book "Supercentenarians" celebrates her life - how she met the painter Vincent van Gogh when she was 13, how she later allowed herself one glass of port and one cigarette a day, and how she liked good food and wine, including cakes and chocolate, which she ate every day. When the demographers James Vaupel and Bernard Jeune, two of the authors of "Supercentenarians," visited her at age 120, she remarked that the most important thing in her long life was that "I had fun. I am having fun."

Chris Mortensen’s long life is also detailed in the book. Born in Denmark, he died at 115 in the United States. Still the record holder as the world’s oldest living man, at his advanced age he still smoked cigars, and lived as long as the Dutch woman Hendrikje van Andel-Schipper. Despite being born prematurely with a weight of only three pounds, she nevertheless avoided major life-threatening diseases until her nineties, when she was diagnosed with a breast cancer, and ultimately died of stomach cancer. The African American woman Bettie Wilson who died at the age of 115 even survived a gall bladder surgery at age 114. And Elizabeth Bolden, also an African American woman, who was deeply religious and had ten great-great-great grandchildren, was allegedly completely mentally fit and was able to recount all the major details of her life on her 112th birthday.

What is striking is that many of the super old avoided dementia, at least until shortly before they died. Now researchers want to expand the use of the International Database on Longevity (IDL) and use its data to investigate mortality at advanced age and the reasons for an extra long life. But these reasons are still elusive. So far the only thing for certain is that being a woman is clearly advantageous, since ninety percent of those celebrating their 115th birthday were women. Having ancestors who lived exceptionally long played as little a role as economic background and half of the supercentenarians had no children. It is unclear, however, whether this evidence will remain constant with future supercentenarians. The search for the secret of super old age has only just begun.

(Photo: Max Planck Society)

Max Planck Institute


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A new computational model sheds light on the workings of the human visual system and could help advance artificial-intelligence research, too.

Researchers at MIT’s McGovern Institute for Brain Research have developed a new mathematical model to describe how the human brain visually identifies objects. The model accurately predicts human performance on certain visual-perception tasks, which suggests that it’s a good indication of what actually happens in the brain, and it could also help improve computer object-recognition systems.

The model was designed to reflect neurological evidence that in the primate brain, object identification — deciding what an object is — and object location — deciding where it is — are handled separately. “Although what and where are processed in two separate parts of the brain, they are integrated during perception to analyze the image,” says Sharat Chikkerur, lead author on a paper appearing this week in the journal Vision Research, which describes the work. “The model that we have tries to explain how this information is integrated.”

The mechanism of integration, the researchers argue, is attention. According to their model, when the brain is confronted by a scene containing a number of different objects, it can’t keep track of all of them at once. So instead it creates a rough map of the scene that simply identifies some regions as being more visually interesting than others. If it’s then called upon to determine whether the scene contains an object of a particular type, it begins by searching — turning its attention toward — the regions of greatest interest.

Chikkerur and Tomaso Poggio, the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences and at the Computer Science and Artificial Intelligence Laboratory, together with graduate student Cheston Tan and former postdoc Thomas Serre, implemented the model in software, then tested its predictions against data from experiments with human subjects. The subjects were asked first to simply regard a street scene depicted on a computer screen, then to count the cars in the scene, and then to count the pedestrians, while an eye-tracking system recorded their eye movements. The software predicted with great accuracy which regions of the image the subjects would attend to during each task.

The software’s analysis of an image begins with the identification of interesting features — rudimentary shapes common to a wide variety of images. It then creates a map that depicts which features are found in which parts of the image. But thereafter, shape information and location information are processed separately, as they are in the brain.

The software creates a list of all the interesting features in the feature map, and from that, it creates another list, of all the objects that contain those features. But it doesn’t record any information about where or how frequently the features occur.
At the same time, it creates a spatial map of the image that indicates where interesting features are to be found, but not what sorts of features they are. It does, however, interpret the “interestingness” of the features probabilistically. If a feature occurs more than once, its interestingness is spread out across all the locations at which it occurs. If another feature occurs at only one location, its interestingness is concentrated at that one location.

Mathematically, this is a natural consequence of separating information about objects’ identity and location and interpreting the results probabilistically. But it ends up predicting another aspect of human perception, a phenomenon called “pop out.” A human subject presented with an image of, say, one square and one star will attend to both objects about equally. But a human subject presented an image of one square and a dozen stars will tend to focus on the square.

Like a human asked to perform a visual-perception task, the software can adjust its object and location models on the fly. If the software is asked to identify only the objects at a particular location in the image, it will cross off its list of possible objects any that don’t contain the features found at that location.

By the same token, if it’s asked to search the image for a particular kind of object, the interestingness of features not found in that object will go to zero, and the interestingness of features found in the object will increase proportionally. This is what allows the system to predict the eye movements of humans viewing a digital image, but it’s also the aspect of the system that could aid the design of computer object-recognition systems. A typical object-recognition system, when asked to search an image for multiple types of objects, will search through the entire image looking for features characteristic of the first object, then search through the entire image looking for features characteristic of the second object, and so on. A system like Poggio and Chikkerur’s, however, could limit successive searches to just those regions of the image that are likely to have features of interest.

John Reynolds, an associate professor in the Systems Neurobiology Laboratory at the Salk Institute for Biological Studies, finds Poggio and Chikkerur’s model intriguing because of its convergence with work that he and others have been doing on the physiology of the brain. “It holds the potential for linking underlying biology to information processing in a way that’s new and exciting,” Reynolds says. He points out, for instance, that while some neurological diseases, such as Alzheimer’s disease and schizophrenia, have physiological characteristics that can be studied independently, their relationship to the diseases’ cognitive effects is not always clear. “We’d like to be able to link those to failures of behavior and perception,” Reynolds says, “and those are naturally expressed in terms of these questions that Tommy’s raising, which is what computations are being performed.”

Reynolds speculates that, in the future, Poggio and Chikkerur’s model could be expanded so that, in the same way that it makes predictions about human eye movement, it could predict the cognitive deficits associated with disease. “It might suggest a way of reaching down into the biology and saying, ‘Look, this is the kind of mechanism that may be failing in those people,’” Reynolds says. “That could lead to treatments.”

(Photo: Sharat Chikkerur)

Massachusetts Institute of Technology


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Researchers at Purdue University have developed a potential new tool for medical diagnostics, testing food and water for contamination, and crime-scene forensics.

The technique uses a combination of light and electric fields to position droplets and tiny particles, such as bacteria, viruses and DNA, which are contained inside the drops.

Other methods using either light or electric fields separately are able to position droplets or the particles they contain, but the new "hybrid optoelectric" device is able to do both, making it potentially practical for sensors and industrial processes, said mechanical engineering doctoral student Aloke Kumar.

Ordinarily, the particles inside droplets are detected when they randomly fall on a sensor's surface. However, the new method could improve sensor efficiency by actively moving particles to specific regions on an electronic chip for detection or analysis.
"This new hybrid technique is universal in the sense that we can manipulate a range of droplet and particle sizes, going all the way from microliter drops to particles a few nanometers long," said Steven T. Wereley, a professor of mechanical engineering who is working with Kumar.

The method offers promise for future "lab-on-a-chip" technology, using electronic chips to analyze biological samples for medical and environmental applications. Sensors based on the technique could make possible a new class of chemical analyses, or assays, with point-of-care devices in a doctor's office or hospitals.

Such sensors might be used to quickly analyze blood, urine and other bodily fluids for a range of applications, including drug screening; paternity testing; detecting coronary artery disease, tumors and various inherited diseases including cystic fibrosis; and detecting infectious diseases and bacteria, viruses and fungi that are difficult to culture using conventional laboratory methods.

"This technique also would be good for DNA tests, such as those used on the TV program 'CSI,' to identify crime suspects using only a small blood sample," Wereley said. "The idea is to use a chip to quickly carry out laboratory procedures called polymerase chain reaction and capillary electrophoresis. The new technology also should be good for testing food and water for pathogens such as E. coli or salmonella."

Critical to the technology are electrodes made of indium tin oxide, a transparent and electrically conductive material commonly used in consumer electronics for touch-screen displays. Liquid drops are positioned on the electrodes, and the infrared laser heats up both the electrodes and the droplets. Then electric fields in the electrodes cause the heated liquid to produce a "microfluidic vortex" of circulating liquid. This vortex enables researchers to position the particles in the circulating liquid by moving the infrared laser. The particles accumulate only where the laser is shined.

"Sensors are one of the immediate applications of this technology,” said Kumar, who may continue the work as a postdoctoral researcher at the Oak Ridge National Laboratories, where he will complete a two-year Eugene Wigner Fellowship starting this month. "We should be able to improve the efficiency of sensors at least 10 times."

Findings were detailed in a research paper appearing June 1 in the journal Langmuir. The paper was written by Kumar, Wereley and former Purdue doctoral student Han-Sheng Chuang, now a postdoctoral researcher at the University of Pennsylvania. The research is based at the Birck Nanotechnology Center at Purdue's Discovery Park.

Purdue has filed a U.S. patent application on the design.

The technique might be used to manufacture sensors and other devices by modifying a phenomenon called the coffee-ring effect, which causes residue to form when liquid evaporates. Because the particles in the residue form only where the infrared laser shines, the procedure might be used to precisely position particles to create structures and circuits for biosensors and electronics.

"We have successfully used this technique to create spatially controlled microassemblies, and we hope that this would interest other research groups looking into the coffee-ring effect," Kumar said.

(Photo: Craig Snoeyink/Purdue University Birck Nanotechnology Center)

Purdue University


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Researchers at McGill's department of natural resources, the National Research Council of Canada, the University of Toronto and the SETI Institute have discovered that methane-eating bacteria survive in a highly unique spring located on Axel Heiberg Island in Canada's extreme North. Dr. Lyle Whyte, McGill University microbiologist, explains that the Lost Hammer spring supports microbial life, that the spring is similar to possible past or present springs on Mars, and that therefore they too could support life.

The subzero water is so salty that it doesn't freeze despite the cold, and it has no consumable oxygen in it. There are, however, big bubbles of methane that come to the surface, which had provoked the researchers' curiosity as to whether the gas was being produced geologically or biologically and whether anything could survive in this extreme hypersaline subzero environment. "We were surprised that we did not find methanogenic bacteria that produce methane at Lost Hammer," Whyte said, "but we did find other very unique anaerobic organisms - organisms that survive by essentially eating methane and probably breathing sulfate instead of oxygen."

It has been very recently discovered that there is methane and frozen water on Mars. Photos taken by the Mars Orbiter show the formation of new gullies, but no one knows what is forming them. One answer is that there could be that there are springs like Lost Hammer on Mars. "The point of the research is that it doesn't matter where the methane is coming from," Whyte explained. "If you have a situation where you have very cold salty water, it could potentially support a microbial community, even in that extreme harsh environment." While Axel Heiberg is already an inhospitable place, the Lost Hammer spring is even more so. "There are places on Mars where the temperature reaches relatively warm -10 to 0 degrees and perhaps even above 0ºC," Whyte said, "and on Axel Heiberg it gets down to -50, easy. The Lost Hammer spring is the most extreme subzero and salty environment we've found. This site also provides a model of how a methane seep could form in a frozen world like Mars, providing a potential mechanism for the recently discovered Martian methane plumes."

(Photo: McGill U.)

McGill University


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An international team of scientists, led by Penn State Distinguished Professor Donald Schneider, has announced its completion of a massive census in which they identified the quasars in one quarter of the sky. The team's work is part of the Sloan Digital Sky Survey (SDSS), a nearly decade-long discovery-and-research effort using a 2.5 meter telescope located at Apache Point Observatory in New Mexico. The completed catalog of quasars, which will be published in the June 2010 issue of the Astronomical Journal, includes 105,783 quasars, more than 96 percent of which were discovered by the SDSS.

"Quasars are hundreds of times more luminous than our entire galaxy, yet they generate this tremendous power in regions similar in scale to that of our much smaller solar system," said Schneider. "The best explanation of this extraordinary phenomenon is that we are witnessing the light energy emitted by material falling into black holes with masses of hundreds of millions of times, or even more than a billion times, that of our Sun."

James Gunn, Eugene Higgins professor of astronomy at Princeton University, has served since the inception of the SDSS project as the SDSS project scientist. The SDSS has obtained images of the sky and detailed spectroscopic information for over one-million objects.

"Our original goal for the SDSS was to determine the distances to over a million galaxies and 100,000 quasars," said Gunn. "This was viewed as an extremely ambitious goal as, at the time we were designing the survey, fewer than 6,000 quasars had been identified. We are pleased that we were able to exceed our goals for both galaxies and quasars."

President Obama awarded Gunn the National Medal of Science in October of 2009 in recognition of his leadership of the SDSS.

A number of Penn State scientists made key contributions to the SDSS quasar effort. The design of the method used to select the quasars was led by Penn State Postdoctoral Scholar Gordon Richards (now an associate professor at Drexel University).

"This set of quasars will be of great use to the scientific community," said Richards. "In addition to the census itself, the quasar survey has made a number of key discoveries, including finding the most distant known objects in the universe and a number of gravitational lenses."

While at Penn State, Richards, along with graduate student Michael Weinstein (now at Connecticut College), used the early SDSS observations to develop a technique of measuring distances to quasars based solely on their colors in the SDSS images. This technique has led to the ability to identify more than 1 million high-probability quasar candidates in the SDSS data archives.

Niel Brandt, distinguished professor of astronomy and astrophysics, Senior Research Associate Daniel Vanden Berk (now an associate professor at St. Vincent College), and Postdoctoral Scholar Nicholas Ross (now a postdoctoral scholar at Lawrence Berkeley National Laboratory) also were Penn State members of the SDSS quasar team.

"The quasar survey required the contributions of dozens of scientists from around the world," said Vanden Berk. "Terabytes of image information had to be analyzed to identify quasar candidates, and the candidates had to be observed with spectrographs to determine whether or not they were indeed quasars."

(Photo: Sloan Digital Sky Survey)

Penn State University




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