The mere fact that people are doing experiments which explore time travel, and publishing their results in respected peer-reviewed journals is pretty damn amazing. The article, http://www.physorg.com/news/2011-03-grandfather-paradox.html talks about a series of experiments that are being performed by folks at MIT and elsewhere to see exactly what is preventing the grandfather paradox from occurring during time travel.
“Ah!” You might say – just make time travel against the laws of physics, and you can avoid the whole issue. Unfortunately, or perhaps fortunately, travel on the so-called “closed timelike curves,” or “CTCs” is allowed by general relativity. The problem has been how to resolve issues like the case when you show a mathematician a proof from the future and she proceeds to publish _that_proof_. The question about where that proof came from is left as an exercise for the reader. For all the details, you can read the complete paper at Physics Review Letters: http://prl.aps.org/abstract/PRL/v106/i4/e040403
It appears that our friends at NYC Resistor and Alpha One Labs may have some interesting neighbors – apparently some fish in the Hudson River have been mutating in order to evade the high levels of dioxin and other toxins in the water. http://www.sciencenews.org/view/generic/id/69976/title/Packing_away_the_poison
The problem, of course, is that as soon as something eats _those_ fish, they get an even heftier dose of the toxin – and so it goes. The article over at Science News is actually pretty interesting, and demonstrates how living systems can quickly evolve to adapt to new circumstances. As always, I am a sucker for mutant monsters and toxic waste…
Thank to help from several of my fellow HacDCers, I have my HacDC website access working again, and you know what that means- more SCIENCE content! Today a quick pointer to a fascinating article on the computer simulation of a mammalian brain – or at least an important portion of one- the neocortical column from a common laboratory mouse. The cool thing is that they generated much of the data needed to run the simulation (at the scale of one processor per neuron right now) by using laboratory robots to generate a huge number of experiments on living mouse cells, the data from which were put directly into the simulator. Very, very interesting approach, and an equally cool result- reproducible prediction of the brain’s response to stimuli by the model, which matches perfectly with what is observed in the living mouse. We are getting close to where we are only Moore’s Law away from being able to do the same thing with a human brain. If you read the article here: http://seedmagazine.com/content/article/out_of_the_blue/ be sure and ask me about my related funny Terry Sejnowski story.
For those folks that saw the Biomolecular Cryptology talk at This article in Technology Review talks about how DNA can be used to also encode data. This approach leverages some deep properties of DNA biology, transcription and translation to enable a “public key” approach in which proteins (or their virtual equivalent) can be exchanged as a kind of public key, allowing the decoding of the underlying data encoded in DNA. It is an interesting compliment to the so-called DNA stegnography, in which messages are encoded directly in the DNA bases, in something like a Caesar Cipher.
The paper appears to have some weaknesses in the cryptography, but I am nowhere near expert enough to be an effective judge- I wish that the paper has better references. Perhaps some of our HacDC cryptography experts would be interested in giving it a go!
The details can be found in the paper here on arxiv.
One of the key steps in the development of molecular-scale assembly is the creation of similarly-sized assembly tools that have sufficient accuracy and reproducibility to place atoms in exactly where they need to be, following a predefined plan. Researchers in New York and China have been able to create a nanoscale robot that can place molecular components accurately at atomic scale. The real breakthrough appears to be the unique error-correcting mechanisms that they implemented.
The details can be found in this paper in Nature Nanotechnology, and a nice overview is here at the NanoWerk blog.