For 75 years, scientists have vainly searched for particles of dark matter, the invisible substance believed to pervade deep space and to glue galaxies together. Next year, in a vat of chilled liquid buried deep in a cave in central Italy, the universe may finally be ready to give up this great secret. An international team of physicists is preparing XENON100, a simple experiment with a huge ambition: to record the moment when a bit of dark matter—known as a weakly interacting massive particle, or WIMP—smacks into the nucleus of an atom of liquid xenon, triggering a flash of light and an electric charge. “We definitely have a chance to see these events,” says Columbia University physicist and XENON team leader Elena Aprile.
According to the latest theories and observations, the universe has about six times as much dark matter as the atomic matter that makes up our ordinary world. But even though uncounted billions of dark-matter particles pass through Earth (and right through you, in fact) every second, they cannot be seen; they have no electric charge and interact so infrequently with atomic matter that the only way we can hope to find them is by laying a clever trap.
Currently there are about 10 teams of scientists devising experiments to discern the elusive moment when a stray WIMP nudges an atom of ordinary matter, but the latest version of XENON will be by far the most sensitive. All the experiments are lodged far below Earth’s surface to shield the detectors from background radiation. The Italian Gran Sasso National Laboratory is located nearly 4,600 feet beneath the top of a mountain, in caverns off a highway tunnel.
XENON100 is a scaled-up version of XENON10, one of Aprile’s earlier dark-matter experiments. It uses liquid xenon, an inert gas at room temperature, to catch WIMPs. The detector is a stainless-steel cylinder surrounded by a protective “castle” made of two kinds of lead and a layer of polyethylene to screen out residual background interference. Inside, 330 pounds of xenon will be chilled to –140 degrees Fahrenheit. Xenon’s attractive property is that it gives off a brief flash of light if a WIMP bumps into the nucleus of one of its atoms. A set of sensors on the cylinder bottom records this signal, while sensors on top detect the minuscule release of electrons liberated by the WIMP. By reading the two signals and measuring the time interval between them, researchers can fix the point of impact within the cylinder in three dimensions.
Dark matter is not necessarily composed of WIMPs—theorists have identified a host of other possible dark-matter particles—but they are the leading candidates because their presence would close a loophole in the reigning theory of particle physics, called the standard model. To address this discrepancy, scientists have proposed that all particles have large-mass counterparts, or superpartners. The neutralino, even with a mass at least 50 times that of a proton, would be the lightest of these. It is a prime WIMP candidate.
If XENON100 uncovers the long-rumored neutralino, it will mark another huge step in science’s grand humbling of humanity. “Copernicus discovered we’re not the center of the universe,” says Yale physicist Daniel McKinsey, a member of the XENON10 team. “If we find dark matter, we will discover that we are not even made of the stuff that composes most of the universe.”
Guy Gugliotta
Sunday, December 02, 2007
About 250 million years ago...
About 250 million years ago, some disaster wiped out 90 percent of life on Earth, a cataclysm known as the Permian-Triassic extinction. Around the same time, volcanoes a million times bigger than Mount Saint Helens erupted, spewing enormous clouds of dust and gas into the sky and covering the ground with 2 million square miles of molten lava. Did the volcanic eruptions cause the extinctions? The answer depends on which event occurred first and how long each took—and right now, scientists just don’t know.
Such is the case with most of the big questions about the history of the Earth, says Paul Renne, director of the Berkeley Geochronology Center: “Often, our arguments about causality depend on timing.” That’s why he and hundreds of other scientists around the world have joined Earthtime, a 10-year endeavor to nail down the sequence of past events on Earth by refining scientists’ techniques for measuring deep time. The project was started by Sam Bowring, an expert in geologic time at MIT, and Douglas Erwin, a paleontologist at the National Museum of Natural History, who conceived of Earthtime during a transcontinental flight together a decade ago. “If we really want to understand the history of the Earth, we have to push our dating tools to their limits,” Bowring says.
Over the past 10 years, such tools have become astonishingly accurate and precise. Take radioisotope dating, which scientists do by measuring the relative abundance of certain forms of elements (like potassium-40) called isotopes and then using the known decay rates of those elements to calculate the age of the minerals in which they are found. In the 1970s, scientists using radioisotope dating could pinpoint the age of a 100 million-year-old rock to within a few million years. Today Bowring and others have whittled the uncertainty down to less than 100,000 years.
But a few glitches are preventing scientists from making the most of these improvements. First, separate labs using the same dating techniques employ slightly different materials and methods, leading to different results. This didn’t matter when measurements of deep time were rough. Now that the science is more exact, though, small inconsistencies due to experimental error can spark big disagreements. “It’s when we sharpen our tools that these discrepancies turn up more glaringly,” Renne says.
Earthtime’s goal is to synchronize the numerous watches worn by scientists who study deep time, then use them to create one superaccurate chronology of Earth’s past. To do this, Bowring and his colleagues have distributed a set of reference materials called standards (rock samples with known ages) and tracers (small quantities of isotopes with a known composition) to help make different labs’ results consistent. Until now, labs have used varying standards and tracers, which has led to differing results. Bowring hopes to eliminate such problems by giving everyone the same starting point.
Bowring and his fellow keepers of deep time are also searching for rock beds where scientists can test how well dates derived by different methods agree. And they are looking for new samples of ancient material to fill in details about ancient events. For instance, next year the ship JOIDES Resolution is scheduled to drill into the floor of the Pacific Ocean to extract rock cores that will span the period from about 53 million to 18 million years ago, a time of vast climate change.
If it works, Earthtime should enable scientists to study new, previously unappreciated aspects of Earth’s past. Erwin compares the endeavor to the Human Genome Project, in which scientists mapped the sequence of our genes. “The fundamental goal of the Human Genome Project wasn’t the genome itself—it was figuring out what our genes do,” Erwin says. “Our goal is to produce a better timescale so we can go out and start asking a whole new set of questions.”
Erika Check Hayden
Such is the case with most of the big questions about the history of the Earth, says Paul Renne, director of the Berkeley Geochronology Center: “Often, our arguments about causality depend on timing.” That’s why he and hundreds of other scientists around the world have joined Earthtime, a 10-year endeavor to nail down the sequence of past events on Earth by refining scientists’ techniques for measuring deep time. The project was started by Sam Bowring, an expert in geologic time at MIT, and Douglas Erwin, a paleontologist at the National Museum of Natural History, who conceived of Earthtime during a transcontinental flight together a decade ago. “If we really want to understand the history of the Earth, we have to push our dating tools to their limits,” Bowring says.
Over the past 10 years, such tools have become astonishingly accurate and precise. Take radioisotope dating, which scientists do by measuring the relative abundance of certain forms of elements (like potassium-40) called isotopes and then using the known decay rates of those elements to calculate the age of the minerals in which they are found. In the 1970s, scientists using radioisotope dating could pinpoint the age of a 100 million-year-old rock to within a few million years. Today Bowring and others have whittled the uncertainty down to less than 100,000 years.
But a few glitches are preventing scientists from making the most of these improvements. First, separate labs using the same dating techniques employ slightly different materials and methods, leading to different results. This didn’t matter when measurements of deep time were rough. Now that the science is more exact, though, small inconsistencies due to experimental error can spark big disagreements. “It’s when we sharpen our tools that these discrepancies turn up more glaringly,” Renne says.
Earthtime’s goal is to synchronize the numerous watches worn by scientists who study deep time, then use them to create one superaccurate chronology of Earth’s past. To do this, Bowring and his colleagues have distributed a set of reference materials called standards (rock samples with known ages) and tracers (small quantities of isotopes with a known composition) to help make different labs’ results consistent. Until now, labs have used varying standards and tracers, which has led to differing results. Bowring hopes to eliminate such problems by giving everyone the same starting point.
Bowring and his fellow keepers of deep time are also searching for rock beds where scientists can test how well dates derived by different methods agree. And they are looking for new samples of ancient material to fill in details about ancient events. For instance, next year the ship JOIDES Resolution is scheduled to drill into the floor of the Pacific Ocean to extract rock cores that will span the period from about 53 million to 18 million years ago, a time of vast climate change.
If it works, Earthtime should enable scientists to study new, previously unappreciated aspects of Earth’s past. Erwin compares the endeavor to the Human Genome Project, in which scientists mapped the sequence of our genes. “The fundamental goal of the Human Genome Project wasn’t the genome itself—it was figuring out what our genes do,” Erwin says. “Our goal is to produce a better timescale so we can go out and start asking a whole new set of questions.”
Erika Check Hayden
From the smartest artificial brain to the first artificial life
The Blue Brain Project
Scientists rely on computer models to understand the toughest concepts in science: the origin of the universe, the behavior of atoms, and the future climate of the planet. Now a computer model is being designed to take on the human brain. Neuroscientist Henry Markram of the Brain Mind Institute at the École Polytechnique Fédérale in Lausanne, Switzerland, has spent the last 15 years painstakingly mapping cells from the living brains of rats so that he can create a neuron-by-neuron simulation of the brain. With assistance from IBM (whose nickname, Big Blue, helped name the project), Markram hopes to have a virtual human brain, with all its 100 billion neurons, functioning by 2015.
Scientists still don’t understand many of the most essential functions of the brain, like memory or the fundamentals of brain disease and treatment. Markram’s model will electronically mirror the real brain’s biological behaviors, imitating mathematically the interactions among individual neurons and the effects of neurotransmitters on those cells.
The model will also be adjustable so that it can explore unusual physiology (a higher-functioning left hemisphere, say, or a weakened hippocampus) and environmental changes (like the effects of taking a pharmaceutical).
The data can then be interpreted via computer images. “We are building a generic template,” Markram says, “which will allow us to reconstruct a brain according to any specifications.”
To grind through the immense amount of data, IBM has custom-tailored one of its most powerful supercomputers, capable of processing more than 22 trillion operations per second. With this computer, Markram has created a preliminary model of a neocortical column—a set of about 10,000 cells that work together—equivalent to one in the brain of a 2-week-old rat. “We have achieved the ability to build a brain microcircuit, an elementary unit, and now it’s just a matter of scaling up,” he says.
Many of Markram’s colleagues think that he is too ambitious, that a model of billions of neurons, no matter how intricate, cannot tell much about the functions of a real brain. “People think that it is impossible,” he admits. “They believe that we don’t understand enough about the brain to build it.” He counters that mysteries of brain circuitry will be resolved as the project moves forward over the years.
If the Blue Brain team succeeds, scientists will for the first time have a meaningful physical model of the human brain. So could a fully functioning virtual brain have the ability to create thoughts of its own? Markram isn’t counting on it, but he will be watching closely if Blue Brain begins to make its own decisions, providing unique outputs to identical inputs in a way that is beyond chance or chaos theory and achieving something that has never been observed in a computer: consciousness. “Once we build the whole brain,” he says, “if consciousness emerges, we will be able to study it systematically and understand exactly how it emerges.”
Susan Kruglinski
Scientists rely on computer models to understand the toughest concepts in science: the origin of the universe, the behavior of atoms, and the future climate of the planet. Now a computer model is being designed to take on the human brain. Neuroscientist Henry Markram of the Brain Mind Institute at the École Polytechnique Fédérale in Lausanne, Switzerland, has spent the last 15 years painstakingly mapping cells from the living brains of rats so that he can create a neuron-by-neuron simulation of the brain. With assistance from IBM (whose nickname, Big Blue, helped name the project), Markram hopes to have a virtual human brain, with all its 100 billion neurons, functioning by 2015.
Scientists still don’t understand many of the most essential functions of the brain, like memory or the fundamentals of brain disease and treatment. Markram’s model will electronically mirror the real brain’s biological behaviors, imitating mathematically the interactions among individual neurons and the effects of neurotransmitters on those cells.
The model will also be adjustable so that it can explore unusual physiology (a higher-functioning left hemisphere, say, or a weakened hippocampus) and environmental changes (like the effects of taking a pharmaceutical).
The data can then be interpreted via computer images. “We are building a generic template,” Markram says, “which will allow us to reconstruct a brain according to any specifications.”
To grind through the immense amount of data, IBM has custom-tailored one of its most powerful supercomputers, capable of processing more than 22 trillion operations per second. With this computer, Markram has created a preliminary model of a neocortical column—a set of about 10,000 cells that work together—equivalent to one in the brain of a 2-week-old rat. “We have achieved the ability to build a brain microcircuit, an elementary unit, and now it’s just a matter of scaling up,” he says.
Many of Markram’s colleagues think that he is too ambitious, that a model of billions of neurons, no matter how intricate, cannot tell much about the functions of a real brain. “People think that it is impossible,” he admits. “They believe that we don’t understand enough about the brain to build it.” He counters that mysteries of brain circuitry will be resolved as the project moves forward over the years.
If the Blue Brain team succeeds, scientists will for the first time have a meaningful physical model of the human brain. So could a fully functioning virtual brain have the ability to create thoughts of its own? Markram isn’t counting on it, but he will be watching closely if Blue Brain begins to make its own decisions, providing unique outputs to identical inputs in a way that is beyond chance or chaos theory and achieving something that has never been observed in a computer: consciousness. “Once we build the whole brain,” he says, “if consciousness emerges, we will be able to study it systematically and understand exactly how it emerges.”
Susan Kruglinski
Citizen Journalism versus Expert journalism
Citizen journalism is being hindered and may even be dying at the hands of citizens themselves, a growing number of media experts believe.
The fad journalism model is being brought down by poorly written and poorly presented content that is greatly inferior to content produced by experts, they say. To put it bluntly, if you need information on a subject, would you rather rely on the edited and proofread opinion of an expert, or the misspelled musings from some guy sitting in his basement?
Steve Boriss, associate director of the Center for the Application of Information Technology at Washington University in St. Louis announced on his blog Thursday that “citizen journalism is dead. Expert journalism is the future.”
By Leah McBride Mensching .
If journalism is the report of an event or something just happened, may be a Citizen journalist who happened to be on the site, actually living the experience, could be a better writer than somebody living miles away.
If journalism is the comment on a fact that happened somewhere, an interesting and catching report of it, an expert journalist could be better.
But experience is not all.
You can be a good writer without being an expert writer, as much as you can be a lousy journalist in spite of all your experience.
Writing about is not all.
Writing about in an alluring way, catching the attention of the reader, that is journalism.
And the best journalist can be a citizen journalist who happens to be there and to write in the right way...
You are born a journalist, as much as you are born a writer or a painter.
What you learn later is just the tools to express what you have inside.
Writing is like painting in the brain of your reader.
The picture you are able to create is the sign of your talent, citizen or expert.
The fad journalism model is being brought down by poorly written and poorly presented content that is greatly inferior to content produced by experts, they say. To put it bluntly, if you need information on a subject, would you rather rely on the edited and proofread opinion of an expert, or the misspelled musings from some guy sitting in his basement?
Steve Boriss, associate director of the Center for the Application of Information Technology at Washington University in St. Louis announced on his blog Thursday that “citizen journalism is dead. Expert journalism is the future.”
By Leah McBride Mensching .
If journalism is the report of an event or something just happened, may be a Citizen journalist who happened to be on the site, actually living the experience, could be a better writer than somebody living miles away.
If journalism is the comment on a fact that happened somewhere, an interesting and catching report of it, an expert journalist could be better.
But experience is not all.
You can be a good writer without being an expert writer, as much as you can be a lousy journalist in spite of all your experience.
Writing about is not all.
Writing about in an alluring way, catching the attention of the reader, that is journalism.
And the best journalist can be a citizen journalist who happens to be there and to write in the right way...
You are born a journalist, as much as you are born a writer or a painter.
What you learn later is just the tools to express what you have inside.
Writing is like painting in the brain of your reader.
The picture you are able to create is the sign of your talent, citizen or expert.
Today's websites still do not fully meet the users' needs
It may once have been regarded as a specialised technology for specialised purposes, but few would dispute that the web is now an integrated business tool. It provides a new and different way to connect with customers and extend their brand experience with you. Moreover, today’s Web 2.0, with social networking and interactive capabilities, means that business-to-customer interactions are evolving and becoming increasingly social in nature.
The capabilities, philosophies and social dynamics behind Web 2.0 have transformed online interactions from technically limited, company-centric, individual experiences to rich, user-centric, social experiences. Many companies are realising that this phenomenon is changing the way business is done online. The proliferation of online communities, well-segmented audiences and the unparalleled volunteering of personal information represent new opportunities for engaging customers with your brand.
Consumers, though, are increasingly more sophisticated, not only expecting but demanding positive, online experiences that meet their needs and aspirations. Understanding what motivates your customers to initiate and build a relationship with your brand is crucial to influencing online decision making and increasing conversion rates.
The objective is to help people make decisions that we intend them to make without deceit. In marketing, a conversion occurs when a prospective customer takes our intended action. On a website, the point at which a customer makes a decision about interacting or transacting is defined as a conversion goal. Feeling satisfied, engaged or motivated to buy, donate or read more are examples of critical behaviours. Whatever a site’s conversion goal, it is now more about people than product or services.
Most people think that decision-making is guided by conscious, rational thought but emotion is also critical. In fact, it is often the driving factor behind starting the decision-making process. Moreover, decisions are not usually strictly emotional or rational. By understanding what motivates customers to keep clicking through a transaction and which design elements hit exactly the right note, we can improve their online experiences and measure the value delivered to them.
Mona Patel
The capabilities, philosophies and social dynamics behind Web 2.0 have transformed online interactions from technically limited, company-centric, individual experiences to rich, user-centric, social experiences. Many companies are realising that this phenomenon is changing the way business is done online. The proliferation of online communities, well-segmented audiences and the unparalleled volunteering of personal information represent new opportunities for engaging customers with your brand.
Consumers, though, are increasingly more sophisticated, not only expecting but demanding positive, online experiences that meet their needs and aspirations. Understanding what motivates your customers to initiate and build a relationship with your brand is crucial to influencing online decision making and increasing conversion rates.
The objective is to help people make decisions that we intend them to make without deceit. In marketing, a conversion occurs when a prospective customer takes our intended action. On a website, the point at which a customer makes a decision about interacting or transacting is defined as a conversion goal. Feeling satisfied, engaged or motivated to buy, donate or read more are examples of critical behaviours. Whatever a site’s conversion goal, it is now more about people than product or services.
Most people think that decision-making is guided by conscious, rational thought but emotion is also critical. In fact, it is often the driving factor behind starting the decision-making process. Moreover, decisions are not usually strictly emotional or rational. By understanding what motivates customers to keep clicking through a transaction and which design elements hit exactly the right note, we can improve their online experiences and measure the value delivered to them.
Mona Patel
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