Toy Big Bang, and a Model for the Real Thing Igor I. Smolyaninov and Yu-Ju Hung

Metamaterials can be used to create desktop black holes and simulate multiverses; now a physicist is using them to prove time travel can’t happen.

In a new paper, University of Maryland professor and metamaterial theorist Igor Smolyaninov says mapping light distribution in a metamaterial can serve as a model for the flow of time. The model shows that the forward direction of time is unrelenting; you cannot curve back on time and go back to where you started. You just have to build a desktop Big Bang to prove it.

Metamaterials can help with this, because they are engineered to exhibit properties that don’t exist naturally. You can manipulate a metamaterial to make space-like dimensions appear time-like, Smolyaninov writes. The way that light moves in such a metamaterial is akin to the way that a particle moves through spacetime (click through toTech Review’s arXiv blog for a more thorough explainer).

In such a metamaterial, the pattern of light rays spreads out — the separation of their “world lines” increases — as time goes by. And the light scatters, which is an analogue for entropy, the thermodynamic arrow of time that tells us things fall apart.

To test this theory, Smolyaninov and a colleague built a Big Bang simulator, placing plastic strips on a gold substrate. Tech Review explains that the “light rays” shining through it are actually plasmons (a clump of excited electrons in a conducting material) that propagate across the surface of the metal. The plastic strips distort their light.

So why does this show time travel is impossible? Smolyaninov says that while light rays can be curved and appear to turn back on themselves, they would not be in a time-like dimension when they do so. And any light ray traveling in a time-like dimension would not be able to go back to its former location.

On the plus side, Smolyaninov has already showed how metamaterials can help us study extra-dimensional multiverses. So even if we can’t travel back in time, maybe we could visit alternate universes, in which the past was already different.

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The Adult Visual Cortex Neurons in the brain’s visual pathway can transmit images to the brain faster than the conscious mind can assess them. But hook a computer to that brain and its visual pathway becomes a supercharged analysis tool Nrets via Wikimedia

Brain-machine interfaces hold potential for a variety of ends, from helping the neurologically or physically disabled communicate and interact with their environments, to creating thought-controlled computers that augment the brain with computing power. A group of researchers at Columbia are turning that model on its ear, using brain power to augment computing tasks. Their device couples the human brain and computers to perform tasks neither could do as efficiently on their own.

The device, known as C3Vision (cortically coupled computer vision) taps into the fast processing power of the brain to help computer programs manage complex problem, particularly those posed by image recognition. An electroencephalogram (EEG) cap on the head of a human user is used to detect neurological signals in the brain. The computer then flashes images up on the screen at a rate of about ten per second. The conscious brain doesn’t even have time to adequately consider each image, but the subconscious is hard at work.

The system is great at working our problems that computer language has a problem tackling. For instance, it’s easy enough to search for a picture of a bicycle on the Web, but it’s far more difficult for a search engine like Google or Bing to search for something that looks “odd” or perhaps “silly.” The brain, however, can take these less-defined, more abstract qualifiers and very quickly assess whether or not an image fits the term.

The conscious brain doesn’t even have to get involved. The images flash too quickly for a person to rate his or her interest in each one, but the visual pathways in the brain move much more quickly. Machine-learning algorithms can quickly detect the neurological signals that represent the brain’s interest in a given image, and helps the computer to rank the images for interest. If the person sees something interesting or different, the computer knows it even if the person does not.

As such, the system has been used in tests to accurately scan satellite images for the presence of surface-to-air missiles faster than either a human or a machine could alone. Which accounts for DARPA’s interest in the technology; the DoD research arm has sunk $4.6 million into the development of the tech via a spinoff from the university. But the tech could also be used for a variety of other tasks that require the analysis of large volumes of visual data.

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Skeletal Muscle Longitudinal view of human skeletal muscle. Wikimedia Commons

Future stitches could be made out of your own muscle cells, ensuring proper re-growth of injured muscle tissues.

Researchers in Massachusetts are implanting injured mice with microthreads coated with human muscle cells, reports Technology Review. The threads are made of the same proteins the human body uses to heal wounds, and when seeded with muscle cells, they act as a scaffold for the construction of healthy tissue.

In a study presented earlier this month, George Pins, associate professor of bioengineering at Worcester Polytechnic Institute, and his colleagues sliced out 30 percent of the lower leg muscle in some mice. They took microthreads made of the protein fibrin and coated them with human muscle cells that had been discarded during surgery, Tech Review says. Then they implanted the microthreads into the mouse muscle wounds.

Within a couple days, the cells integrated into the mouse tissue; after a week, the microthreads started to degrade. After 10 weeks, the wound was full of human cells, according to Pins.

Traumatic muscle injuries often don’t heal well because scar tissue can prevent them from functioning properly. And for muscle regenerationtechniques to work, the tissue must align properly, or the muscles won’t contract.

The wounded mice had less scar tissue, suggesting the microthread technique could solve that problem, Tech Review reports. And the microthreads seemed to simulate native wound healing, signaling other cells to migrate to the wound area and grow new tissue in the right alignment. The researchers believe the microthreads even stimulated the mice to regrow their own tissue, not just human cells, but they need confirmation.

The next step is to determine whether the new human tissue behaves like real muscle.

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Paul the Predicting Octopus Perhaps Paul was simply very in tune with his cognitive abilities. Mbz1 viaWikimedia

It’s long been regarded as pseudo-science or simple lore, but precognition – that is, the ability to not just predict but to actually perceive the future – is getting a fair shake in some scientific circles lately. A research paper titled Feeling the Future from Cornell Professor Daryl Bem shows some statistically significant results coming from a series of experiments empirically testing the human mind powers of premonition and precognition. If his results are replicated elsewhere, it may change the way researchers look at the brain, its perception of time, and exactly what its limitations are.

That’s not to say that storefront psychics really can read your palm, or that one can see the future simply by thinking hard about it. But Bem’s empirical, straightforward science suggests the brain does have some ability to perceive what’s coming. The science is sound enough that Bem’s paper found a home in the prestigious Journal of Personality and Social Psychology, which will publish the piece shortly. It also received a fairly lengthy write-up in Psychology Today.

Bem’s research on what he calls psi – meaning “anomalous processes of information or energy transfer that are currently unexplained in terms of known physical or biological mechanisms” – attempts to explore and explain precognition (conscious awareness of a future event) and premonition (affective apprehension of a future event). To do so he conducted nine experiments on more than 1,000 Cornell students.
For an in-depth break down of Bem’s methodologies, you can access a preview of his paper (PDF). But his methodology is consistent throughout: Take an established psychological response to a certain stimuli, then flip it around so the stimulus comes after the response and see if the response is still the same. The results weren’t overwhelming, but they were statistically significant.

For instance, in one experiment Bem gathered 100 subjects, half male and half female. Using a computerized system, they then played a game in which two curtains were displayed on the screen and the subjects had to choose which one had a picture hiding behind it. Some of these pictures were neutral in content. Others were chosen at random by the computer from a database of semi-erotic and erotic photos (hey, looks like science isn’t boring after all).

The result: In cases where an erotic photo was lurking behind the curtain the subjects were able to accurately identify which curtain it was behind with 53.4 percent accuracy – not a huge statistical spike but significantly better than the 50 percent accuracy rate that could be expected by chance. The accuracy rates were not as high for non-stimulating images, which fell more or less in line with raw statistical chance. This suggests that the subjects could somehow sense the erotic stimuli that awaited them before it happened.

In another experiment Bem reversed the priming effect wherein subjects are subliminally tipped off before identifying a photo as positive or negative. Bem found that by subliminally tipping off subjects after – rather than before – showing the image, they still were able to categorize the pictures more quickly as if the brain knew that the subliminal hint was coming even though it hadn’t happened yet.

We won’t declare the Earth shattered just yet, but other cognitive researchers are taking notice of Bem’s work. Apparently there have been hundreds of requests for replication packages so other scientists can re-test Bem’s experiments and see if the results come back the same. If they do, we may have to reconsider how we perceive our own cognition. But you already knew I was going to say that, didn’t you?

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Decellularized Hearts A heart is washed of its cells, leaving behind only the structural skeleton that gives the tissue its shape. Courtesy of University of Minnesota

Research presented at Sunday’s American Association for the Study of Liver Diseases in Boston marked a preliminary but potentially groundbreaking development in the search for the lab-engineered organs of the future. Scientists at the Institute for Regenerative Medicine at Wake Forest University Baptist Medical Center have engineered the first functioning miniature livers from human liver cells ever created in a lab setting. The technique could open up new avenues for engineering a range of vital tissues in the lab.

To create the mini livers, the team took animal livers and washed out the animal cells with a mild detergent, a method known as “decellularization” that leaves behind only the cellular scaffold that gives the organ its structure. They then piped human cells into place via the natural vessel network that remains in the liver after the decellularization process. Connected to a bioreactor – a machine that mimics the conditions inside a living body by feeding nutrients and oxygen to the organ – the human cells began to form human liver tissue, albeit in miniature stature.

The final goal of this research, of course, is to find a means to engineer donor livers in the lab to close the supply-demand gap between those who need livers for transplant and the shortage of donor organs on hand. But engineered livers could also be used to test drugs for safety and efficacy in the lab.

Animal livers have been created in the lab using this process before, but it was never clear if researchers could do the same with human cells. Now that they’ve demonstrated the ability, the next step will be to get one into a living animal and see how it functions. Then, ostensibly, they’ll try to grow larger, more complex organs equivalent to full-grown human organs. As such, the era of made-to-order livers is still a ways off. But this important step forward for bio-engineering could contribute not only to lab-grown livers, but also to other engineered tissues that are in short supply, like kidneys or pancreases.

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H’andy Sana 210 The Sana 210 reads your heart rhythm when you press your fingertips to each of its sensors. John B. Carnett

High-risk patients can lose hours and thousands of dollars to in-hospital heart monitoring, but now physicians can regularly check in from afar. German cellphone maker H’andy’s Sana 210 needs only 30 seconds to measure heart rhythm and send it to a doctor. When your heart moves, it sends electricity through your body; the Sana uses the same electric sensors as a hospital electrocardiogram (ECG) to record those pulses through your fingertips. The diagnostic is not as accurate as a hospital ECG, which uses more electrodes closer to the heart, but it does provide enough info for doctors to monitor patients who have abnormal rhythms.

As with any test, a clean reading is crucial. After three sensors under the phone’s steel frame pick up the signal from your fingers, it passes through two barriers devised to cancel interference caused by tiny movements in a patient’s arms and shoulders. A filter sits above the circuit board to physically deflect sound frequencies higher than the heart’s approximate 150 hertz. After that, the phone’s processor runs an algorithm that extracts the rhythm. This translates into a single ECG wave, which patients can text-message to their doctor.

H’andy is readying an update, with the ability to read blood pressure and temperature, to submit to the FDA next year.

H’andy Sana 210

Size: 4 x 2.3 x 0.7 in
Camera: 1.2 megapixels
Network: GSM only
Price: Price not set
Get it: handysana.com

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The Atlantic Wind Connection The proposed undersea transmission cable would link offshore wind projects up and down the mid-Atlantic coast. TheGoogle

Last night, Google announced that it has agreed to invest heavily in a proposed $5 billion, 350-mile power transmission backbone that would provide infrastructure for future offshore wind projects along the mid-Atlantic coast. But even with the backing of one of the world’s mightiest tech companies, various financial investment firms, and many important officials in government, the transmission line is going to be something of a technological trick.

The Atlantic Wind Connection (AWC) will stretch from New Jersey to Virginia, moving power up and down the shoreline to the highest capacity markets along the coast. As envisioned, it would eventually link some 6,000 megawatts worth of offshore wind turbines into the land-based transmission system, supplementing traditional power infrastructure with enough power to serve some 1.9 million households. Even before wind farms are constructed, the AWC would ferry cheaper power from southern Virginia to expensive energy markets in New Jersey.

The cable itself will be copper lined with about 2 inches of insulation, and it will be big; each foot of cable will weigh about 30 pounds. To bury it in the seafloor a jet plow – a tool that shoots ocean water into the sea floor at high to pressures to blast a trench – will cut a path for the cable, which will eventually be covered over again with sediment.

There are already some undersea transmission lines running off the Atlantic Coast, but this is the first line that will collect power from generators along the way. This presents a particular technological challenge. The AWC will carry direct current rather than alternating current like the onshore grid. DC is more efficient at moving power over long distances, but DC works best for point-to-point transmission rather than lines that have many inputs and outputs along the way.

To make the AWC work efficiently, the system will employ a series of substations along the way that section it off into a series of direct journeys rather than long line with lots of entry and exit points. Like offshore oil platforms, these intermittent platforms will absorb the power from future wind farms and introduce it to the grid via four connection point in Virginia, Delaware, and southern and northern New Jersey, saving wind developments the trouble and expense of having to build their own connections to shore. That in turn should lower the cost of entry for offshore wind projects, hopefully spurring development along the coast and making way for a future where alternative energies make up a bigger share of America’s energy portfolio.

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Energy from the Sun Parabolic solar troughs harvest sunlight at a solar thermal power installation in California. kjkolb via The

The U.S. may be years behind some European nations and China when it comes to taking advantage of solar power tech, but even global superpowers have to start somewhere. Secretary of the Interior Ken Salazar has approved the first large-scale solar energy projects to be built on public lands, a first step in unlocking the acres upon acres of federal and state managed real estate for clean energy production.

The approval paves the way for two projects: The Imperial Valley Solar Project managed by Texas-based Tessera Solar, a 6,360-acre site that will harvest up to 709 megawatts from 28,360 solar dishes, and the Chevron Lucerne Valley Solar Project, managed by Chevron and pulling in up to 45 megawatts from 40,500 solar panels. Together they will be able to power somewhere between 226,000 and 566,000 typical homes.

Both projects were approved under what the Department of the Interior calls its “fast track” program, though those who have been waiting for years for bureaucracy to catch up with both the technology and the times might not care to call it that. But now that they’re approved, the administration does want the companies to get their projects up and running quickly. Under the stimulus act, developers that have their projects under construction by the end of this year qualify for a good deal of public funding – specifically, $273 million for Tessera and $31 million for Chevron.

The slow approval process mostly stems from the fact that most of these public lands are managed for conservation purposes, so they are strictly governed by rules regarding the environmental ramifications of any construction taking place there, even seemingly green construction like solar farms. Both projects survived rigorous environmental review and must take extensive actions not to disrupt surrounding ecosystems. But it the projects can get off the ground without causing an oil spill or otherwise fouling their sites, they could serve as important proving grounds for further green energy development elsewhere on public lands.

Perhaps its no coincidence this announcement came on the same day Energy Secretary Steven Chu also announced the White House will become a source of solar power, receiving photovoltaic panels and a solar water heater on the roof by the end of spring. Presumably it’s a sign of the administration’s commitment to a green energy future, though it also goes to show just how slow Washington can be when it comes to implementing green initiatives

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Volcanic eruptions are ill-famed for their hazardous effects on the environment, climate, landscape and people. Volcanic ash can blanket the landscape for miles, while the ash clouds can disrupt aircraft travel. What if there was a way to predict them in advance? Well, the disastrous effects could be tamed a little. Researchers at the universities of Leeds, Purdue, Indiana and Addis Ababa have been investigated volcanic activity occurring in the remote Afar desert of Northern Ethiopia from 2005 to 2009.

The team studied a rare sequence of 13 magmatic events, where hot molten rock was intruded into a crack between the African and Arabian plates. It was found that the location of each intrusion was linked and these findings could help in predicting more accurately the location where volcanic eruptions could strike. The study has demonstrated that volcanic eruptions can influence each other.

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Mapping the Brain’s Circuitry When mapped and color-coded, the brain can be a beautiful thing. Human Connectome Project

It took cartographers and explorers thousands of years to map every nook, cranny, and crevasse of planet Earth. Now, a consortium of researchers from across the U.S. is going to try to map the entire human brain in just five. Working with $30 million and just half a decade, the Human Connectome Project aims to create a first-of-its-kind map of the brain’s complex circuitry, detailing every connection linking thousands of different regions of the brain.

The team consists of 33 researchers at nine different institutions, including Washington University School of Medicine in St. Louis and the University of Minnesota, the lead universities in the effort and the sites where much of the brain-scanning will take place. Their success will depend in part on another HCP grant to another research consortium headed up by Massachusetts General Hospital and UCLA that will develop advanced, custom brain scanners with higher spatial resolution and increased sensitivity. The funds themselves come from various bodies within the National Institutes of Health.

How big is the project? It’s at least 90 billion neurons big, but that doesn’t even convey the enormity and complexity of the human brain. There are something like 150 trillion synapses – the connections between neurons across which signals pass – that electrical signals must negotiate. These neurons and the connections between them make up the circuitry of the brain, and the HCP aims to create a better picture of that circuitry than we’ve ever had before.

The project aims to tap state-of-the-art brain scanning technologies, including diffusion imaging, various MRI methods, and magnetoencephalography to map not just how messages move through the brain, but how various regions work together via networks and networks of networks to achieve the complexity that is the human mind. With map resolutions down to the voxel – small swaths of grey matter containing about one million neurons each – researchers estimate the HCP will generate about one petabyte of data, which will require its own supercomputer to process.

All that scanning, data gathering, and analysis should pay off though, HCP researchers say. The end result will be an open platform that other neuroscientists can use to test their own theories, hypotheses, and findings against. Such a map should help scientists find their way to deeper understandings of how the brain works as well as cures for complicated neurological disorders.

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