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impressive, particularly if it works like it does in the video the whole time. paper here http://mi.eng.cam.ac.uk/~qp202/

Well, impressive indeed... have to try it out...

Globular clusters in our galaxy would be the remnants of dwarf galaxies eaten by our galaxy the milky way ! This assumption is quite revolutionary and would support an accretion model of the universe rather than the formation of huge galaxies. So what about the formation of giant black holes in the center of galaxies...?

Anyone out there still doing propulsion stuff? Two more papers just waiting to get busted... http://arxiv.org/abs/0908.1429v1 http://arxiv.org/abs/0908.1803

One reply to Pacome, though the discussion exceeds by far the relevance of the topic already. Baryonic DM is strictly limited by cosomology, if one believes in these models, of course. Anyway, even though most DM is cold, we are constantly bombarded by some DM particles that come together with cosmic radiation, solar wind etc. etc. If DM easily interacted with normal matter, we would have found it long ago. In the paper they consider DM as neutralinos, which are neither baryonic nor strongly or electromagnetically interacting.

well then I agree, how the fu.. they want to collect them !!!

This is really cool. I know one of the authors and he is a good guy... the only thing that leaves me unsatisfied is that if the whole issue is related to thermal effects one should have seen the Pioneer effect all the time and not only at about 10 AU... ...or is there some thermal process that kicked in only at this distance?

Here's an update on this theory: NASA Releases New Pioneer Anomaly Analysis "The mysterious force acting on the Pioneer spacecraft seems to be falling exponentially. That's a strong clue that on-board heat is to blame, says NASA." Heat emission 'most likely cause' of pioneer anomaly "What's more interesting is that, contrary to the original analysis conducted all those years ago, the deceleration does seem to be decelerating at an exponential rate -- just as one might expect from the radioactive decay of plutonium-238, which powers the two spacecraft. Turyshev concludes, "The most likely cause of the Pioneer anomaly is the anisotropic emission of on-board heat.""

"The BICEP2 data would eliminate about 90% of inflationary models, Andrei Linde, a cosmologist at Stanford University in California, told a packed auditorium at MIT the day after the BICEP2 announcement (see picture below). Many of those models do not produce gravitational waves at detectable levels, said Linde, who is one of the founders of inflation theory." Is there any hope for LISA now?

Of course - the data is more proof that GWs exist!!

so you don't expect any impact on the science objectives of Lisa at all?

love this one ... it seems to take physicist to explain to the AI crowd what they are actually doing ... Deep learning is a broad set of techniques that uses multiple layers of representation to automatically learn relevant features directly from structured data. Recently, such techniques have yielded record-breaking results on a diverse set of difficult machine learning tasks in computer vision, speech recognition, and natural language processing. Despite the enormous success of deep learning, relatively little is understood theoretically about why these techniques are so successful at feature learning and compression. Here, we show that deep learning is intimately related to one of the most important and successful techniques in theoretical physics, the renormalization group (RG). RG is an iterative coarse-graining scheme that allows for the extraction of relevant features (i.e. operators) as a physical system is examined at different length scales. We construct an exact mapping from the variational renormalization group, first introduced by Kadanoff, and deep learning architectures based on Restricted Boltzmann Machines (RBMs). We illustrate these ideas using the nearest-neighbor Ising Model in one and two-dimensions. Our results suggests that deep learning algorithms may be employing a generalized RG-like scheme to learn relevant features from data.

We humans take for granted our remarkable ability to predict things that happen around us. Here, a deep learning model trained from real-world videos and a 3D graphics engine was able to infer physical properties of objects against humans.

Wisdom of crowds under a new perspective: a motivation for the island model?

first science results reported in Nature (as far as I know) from the Yutu-2 and Chang'e mission .... and they look very good!

Sure they are very useful! It will be even better if they manage to fit the data to modeled circulation of the lunar magma ocean that was formed posterior to the "Theia" body collision with Earth. The collision was the cause of the magma ocean in the first place. The question now is how this circulation pattern of the lava-moon "froze" in time upon phase transition to solid. Because, what crystallizes last in sequence, is more rich in "incompatible" with the crystal structure, elements, we might combine data+models to predict their location. Those incompatible tracers are mainly radioactively decaying elements that produce heat (google publications about lunar KREEP elements (potassium (K), rare earth elements(REE), and phosphorus(P)). By knowing where the KREEP is: - we know where to dig for them mining (if they are useful for something, eg. Phosphorus for plants to be grown on the Moon) - we avoid planning to build the future human colony on top of radioactives, of course. The hope is that the Moon, due to lack of plate tectonics, has preserved this "signature of the freezing sequence". Let's see.

thanks Nasia! very interesting comment

The best paper on transformation optics written ever :-)

Concerning the fabrication... as usual, no idea. I agree that this is the main drawback of MM, and certainly difficult to overcome. I would double check that number, because its value is related with the beam shape of Fig. 1 A. I believe that the simulations are correct, it's just a detail.

wow ... still publishing despite babysitting and new job!!

Of interest Ana ?

The mantles of Earth and other rocky planets are rich in magnesium and oxygen. Due to its simplicity, the mineral magnesium oxide is a good model for studying the nature of planetary interiors. New work studied how magnesium oxide behaves under the extreme conditions deep within planets and found evidence that alters our understanding of planetary evolution.

Its a big one!

my best Pakistani friend's blog (I recommend to follow it)

Nice. Though would have liked a better example ..

this is a parody on the Norvig-Chomsky debate that has been going on for the last year or so. You can read more about it here: http://norvig.com/chomsky.html

Asimov's Foundation meets ACT's Tipping Point Prediction?

still, some interesting thoughts in there ... "Then you have the 50-year cycles of violence. Turchin describes these as the building up and then the release of pressure. Each time, social inequality creeps up over the decades, then reaches a breaking point. Reforms are made, but over time, those reforms are reversed, leading back to a state of increasing social inequality. The graph above shows how regular these spikes are - though there's one missing in the early 19th century, which Turchin attributes to the relative prosperity that characterized the time. He also notes that the severity of the spikes can vary depending on how governments respond to the problem. Turchin says that the United States was in a pre-revolutionary state in the 1910s, but there was a steep drop-off in violence after the 1920s because of the progressive era. The governing class made decisions to reign in corporations and allowed workers to air grievances. These policies reduced the pressure, he says, and prevented revolution. The United Kingdom was also able to avoid revolution through reforms in the 19th century, according to Turchin. But the most common way for these things to resolve themselves is through violence. Turchin takes pains to emphasize that the cycles are not the result of iron-clad rules of history, but of feedback loops - just like in ecology. "In a predator-prey cycle, such as mice and weasels or hares and lynx, the reason why populations go through periodic booms and busts has nothing to do with any external clocks," he writes. "As mice become abundant, weasels breed like crazy and multiply. Then they eat down most of the mice and starve to death themselves, at which point the few surviving mice begin breeding like crazy and the cycle repeats." There are competing theories as well. A group of researchers at the New England Complex Systems Institute - who practice a discipline called econophysics - have built their own model of political violence and

It's not the scientific activity described in the article that is uninteresting, on the contrary! But the way it is described is just a bad joke. Once again the results itself are seemingly not sexy enough and thus something is sold as the big revolution, though it's just the application of the oldest scientific principles in a slightly different way than used before.

"Cast your name into deep space in style!"

Interesting approach, but with 99.9% probability they will miserably fail (at least in terms of their time schedule) simply because the technology is untested. I haven't read the refs (which miss by the way important works of E. Ahedo et al. on magnetic nozzle acceleration by ambipolar effects), but 1. using water means that you produce oxygen radicals which will erode chamber walls (ionisation efficiency is not 100% and experimental tests haven't been performed yet). 2. Electronic excitation (and radiation), rotational excitation, vibrational excitation, and dissociation are all processes which consume energy and reduce ionisation efficiency drastically. 3. It is a miniaturised Helicon thruster. Theoretical analysis probably does not consider near field effects. Far field models are probably not applicable due to the size of the thruster. I expect some surprises during thruster testing. In any case - good luck!

Apparently, there is only one qualification constraint regarding CubeSat propulsion which is related to volatile propellant. Since they use water as propellant and are also the owner of the CubeSat it is actually up to them how they qualify their thruster. Given that it is also possible to qualify the thruster within 18 months - since they define what "qualification" means.

Extension of standard model to explain a number of unexplained phenomena.

There has been much recent interest in accelerating materials discovery. High-throughput calculations and combinatorial experiments have been the approaches of choice to narrow the search space. The emphasis has largely been on feature or descriptor selection or the use of regression tools, such as least squares, to predict properties. The regression studies have been hampered by small data sets, large model or prediction uncertainties and extrapolation to a vast unexplored chemical space with little or no experimental feedback to validate the predictions. Thus, they are prone to be suboptimal. Here an adaptive design approach is used that provides a robust, guided basis for the selection of the next material for experimental measurements by using uncertainties and maximizing the 'expected improvement' from the best-so-far material in an iterative loop with feedback from experiments. It balances the goal of searching materials likely to have the best property (exploitation) with the need to explore parts of the search space with fewer sampling points and greater uncertainty.

Can AI create the next wonder material? http://www.nature.com/news/can-artificial-intelligence-create-the-next-wonder-material-1.19850?WT.ec_id=NATURE-20160505&spMailingID=51301208&spUserID=MTEzODM0NjYzMzgS1&spJobID=920498312&spReportId=OTIwNDk4MzEyS0

The International Space Apps Challenge is now over, it is interesting to have a look at the solutions ...

what sort of "app" is this e.g. http://spaceappschallenge.org/challenge/brightest-night/solution/132 "We started of by trying to set our camera in raw mode, howsoever this can't be done for current logitech modules and without a high risk of permanently destroying the camera (reflashing the EEPROM). we use a logitech c920 and captured a raw image from it using guvcview on ArchLinux we then wrote some python code to calculate the average BGR value of our Image. We are currently workin on automiztion, but this will take much longer as there will be a lot of reverse engineering of the USB-Protocol needed."

c'mon really! To name a few: - Tour of the Solar System ... that is one of the numerous specialities of the ACT. - Satellite data correlation tool ... solution is flawed, but I really like the idea. Lot of added value. I definitely think are interestung stuffs to do there for cheap. - Aurora project: Model & Data ... space weather not interesting?! - Kepler ... a classic Do not expect the solutions to be tremendous just after 3 days of work, but the proposed list of challenges are "seeds" for innovation to me.