“It’s about the felt presence of immediate experience in the absence of theory.”

Terence McKenna

Art by: 3mmI

]]> http://trustusonline.org/2013/05/22/the-psychedelic-art-of-damon-soule/feed/ 0 trustusonline http://trustusonline.org/2013/05/22/army-of-underwater-vehicles-to-unravel-ocean-mysteries/ http://trustusonline.org/2013/05/22/army-of-underwater-vehicles-to-unravel-ocean-mysteries/#comments Wed, 22 May 2013 16:10:22 +0000 trustusonline http://trustusonline.org/?p=12374 ]]>

Mr. Spock may think space is the final frontier, but Earth’s deep oceans are just as mysterious and unknown. Now, one scientist says thousands of people could explore the oceans using cheap, remotely controlled robots.

“The deep has even more cool stuff than space,” said Eric Stackpole, a researcher at NASA Ames Research Center in Mountain View, Calif.

For instance, there’s a possibility that alien life exists on distant exoplanets, but scientists know for sure that hundreds or thousands of undiscovered species lurk beneath the waves, Stackpole said Sunday (May 19) here at the 2013 Maker Faire Bay Area, a two-day celebration of DIY science, technology and engineering.

And it’s not just scientists who can do the discovering: Interested amateurs could launch an army of these DIY submarines to reveal the mysteries of the deep.

Stackpole is the co-founder of OpenROV, an organization that has created an open-source, underwater vehicle that can explore up to 328 feet (100 meters) beneath the ocean’s surface.

The submarine is the size of a shoebox and is made with off-the-shelf, $10 electronics, such as thrusters and motors, and laser-cut acrylic. It wirelessly connects to a remote controller, and can descend at 3.28 feet (1 meter) per second.

So far, these rovers have plumbed the depths of the flooded Hall City Cave in northern California, which is rumored to harbor gold, and spent time at the Aquarius Underwater Laboratory off Key Largo, Fla., where aquanauts spend 10 days underwater. An open remotely operated vehicle (ROV) has even dived beneath the ice in the Ross Sea in Antarctica, where penguins also got cozy with the underwater vehicle.

Citizen science

The proliferation of underwater robots could change how scientists explore the deep. The expense of building underwater robots has typically meant that researchers get grant money to answer existing questions about the ocean. But so much of the deep is unexplored that citizens could reveal many different insights simply by chance, Stackpole said.

“I don’t think you have to ask questions to get answers,” Stackpole told LiveScience. “I think the kind of things that we’ve discovered just by chance — the transistor, penicillin — were because people were just [looking] around and saw something interesting.”

ROVs could also help researchers answer much bigger scientific questions than they previously could.

For instance, a marine biologist who wants to know what a specific species of sea creature looks like around the world could rally citizen scientists to deploy their ROVs to answer the question.

“We’re in 50 countries, and we’ve been on every continent,” Stackpole said. “Let’s start exploring.”

Quantum computing took a giant leap forward on the world stage today as NASA and Google, in partnership with a consortium of universities, launched an initiative to investigate how the technology might lead to breakthroughs in artificial intelligence.

The new Quantum Artificial Intelligence Lab will employ what may be the most advanced commercially available quantum computer, the D-Wave Two, which a recent study confirmed was much faster than conventional machines at defeating specific problems . The machine will be installed at the NASA Advanced Supercomputing Facility at the Ames Research Center in Silicon Valley and is expected to be available for government, industrial, and university research later this year.

Google believes quantum computing might help it improve its Web search and speech recognition technology. University researchers might use it to devise better models of disease and climate, among many other possibilities. As for NASA, “computers play a much bigger role within NASA missions than most people realize,” says quantum computing expert Colin Williams, director of business development and strategic partnerships at D-Wave. “Examples today include using supercomputers to model space weather, simulate planetary atmospheres, explore magnetohydrodynamics, mimic galactic collisions, simulate hypersonic vehicles, and analyze large amounts of mission data.”

Quantum computers exploit the bizarre quantum-mechanical properties of atoms and other building blocks of the cosmos. At itse very smallest scale, the universe becomes a fuzzy, surreal place—objects can seemingly exist in more than one place at once or spin in opposite directions at the same time.

While regular computers symbolize data in bits, 1s and 0s expressed by flicking tiny switch-like transistors on or off, quantum computers use quantum bits, or qubits, that can essentially be both on and off, enabling them to carry out two or more calculations simultaneously. In principle, quantum computers could prove extraordinarily much faster than normal computers for certain problems because they can run through every possible combination at once. In fact, a quantum computer with 300 qubits could run more calculations in an instant than there are atoms in the universe.

D-Wave, which bills itself as the first commercial quantum computer company, has backers that include Amazon.com founder Jeff Bezos and the CIA’s investment arm In-Q-Tel. It sold its first quantum computing system, the 128-qubit D-Wave One, to the military contractor Lockheed Martin in 2011. Earlier this year it upgraded that machine to a 512-qubit D-Wave Two—reputedly for about $15 million, which might be roughly what the new Quantum Artificial Intelligence Lab paid for its device.

The collaboration between NASA, Google, and the Universities Space Research Association (USRA) aims to use its computer to advance machine learning, a branch of artificial intelligence devoted to developing computers that can improve with experience. Machine learning is a matter of optimizing behavior that may be easier for quantum computers than conventional machines.

For instance, imagine trying to find the lowest point on a surface covered in hills and valleys. A classical computer might start at a random spot on the surface and look around for a lower spot to explore until it cannot walk downhill anymore. This approach can often get stuck in a local minimum, a valley that is not actually the very lowest point on the surface. On the other hand, quantum computing could make it possible to tunnel through a ridge to see if there is a lower valley beyond it.

“Looks like win-win-win to me—Google, NASA, and USRA bring unique skills and an interest in novel applications to the field,” says Seth Lloyd, a quantum-mechanical engineer at MIT. “In my opinion, the focus on factoring and code-breaking for quantum computers has overemphasized the quest for constructing a large-scale quantum computer, while slighting other potentially more useful and equally interesting applications. Quantum machine learning is an example of a smaller-scale application of quantum computing.”

Over the years, many critics have questioned whether D-Wave’s machines are actually quantum computers and whether they are any more powerful than conventional machines. The standard approach toward operating quantum computers, called the gate model, involves arranging qubits in circuits and making them interact with each other in a fixed sequence. In contrast, D-Wave starts off with a set of noninteracting qubits—a collection of supercomputing loops kept at their lowest energy state, called the ground state—and then slowly, or “adiabatically,” transforms this system into a set of qubits whose interactions at its ground state represent the correct answer for the specific problem the researchers programmed it to solve.

Many scientists have wondered whether the approach D-Wave used was vulnerable to disturbances that might keep qubits from working properly. But independent researchers recently found that D-Wave’s computers can actually solve certain problems up to 3,600 times faster than classical computers. Before choosing the D-Wave Two, NASA, Google, and USRA ran the computer past a series of benchmark and acceptance tests. It passed, in some cases by a giant margin.

USRA will invite researchers across the United States to use the machine. Twenty percent of its computing time will be open to the university community at no cost through a competitive selection process, while the rest of it will be split evenly between NASA and Google. “We’ll be having some of the best and brightest minds in the country working on applications that run on the D-Wave hardware,” Williams says.

“You are so used to the support of concepts that when your concepts leave you, although it is your true state, you get frightened and try to cling to them again.”

Nisargadatta Maharaj

Art by: Dunno. You know? Lemme know!

The beauty of numbers and their connection to the pure geometry of space time and the universe is shown in his fractal diagrams. Fractals are shapes that when decomposed into pieces, the pieces are the same or similar to the whole. His is currently studying how all fractals arise from limits and how E=MC2 is itself a fractal. When he first started drawing he had no traditional math training and could only draw what he saw as math. Eventually a physicist saw his drawings and helped him get traditional mathematics training to be able to describe in equations the complex geometry of his drawings. He is currently a student studying mathematics in Washington state where he is learning traditional mathematics so he can better describe what he sees in a more traditional form. Many of the captions were written before he had any traditional math training. His drawing of E=MC^2 is based on the structure of space time at the quantum level and is based on the concept that there is a physical limit to observation which is the Planck length. It shows how at the smallest level, the structure of space time is a fractal. He does his own fractal diagrams and can also create new ones by request. His price for originals depends on the difficulty of the fractal. So sit back and enjoy the beauty of naturally occurring mathematics in pure geometric form connecting E=MC2 (energy) to art. All are HAND DRAWN using only a pencil, ruler and compass.

For the first time, scientists at Cambridge’s Department of Chemistry have been able to map in detail the pathway that generates “aberrant” forms of proteins which are at the root of neurodegenerative conditions such as Alzheimer’s.

They believe the breakthrough is a vital step closer to increased capabilities for earlier diagnosis of neurological disorders such as Alzheimer’s and Parkinson’s, and opens up possibilities for a new generation of targeted drugs, as scientists say they have uncovered the earliest stages of the development of Alzheimer’s that drugs could possibly target.

The study, published today in the journal PNAS, is a milestone in the long-term research established in Cambridge by Professor Christopher Dobson and his colleagues, following the realisation by Dobson of the underlying nature of protein ‘misfolding’ and its connection with disease over 15 years ago.

The research is likely to have a central role to play in diagnostic and drug development for dementia-related diseases, which are increasingly prevalent and damaging as populations live longer.

“There are no disease modifying therapies for Alzheimer’s and dementia at the moment, only limited treatment for symptoms. We have to solve what happens at the molecular level before we can progress and have real impact,” said Dr Tuomas Knowles, lead author of the study and long-time collaborator of Professor Dobson.

“We’ve now established the pathway that shows how the toxic species that cause cell death, the oligomers, are formed. This is the key pathway to detect, target and intervene – the molecular catalyst that underlies the pathology.”

In 2010, the Alzheimer’s Research Trust showed that dementia costs the UK economy over £23 billion, more than cancer and heart disease combined. Just last week, PM David Cameron urged scientists and clinicians to work together to “improve treatments and find scientific breakthroughs” to address “one of the biggest social and healthcare challenges we face.”

The neurodegenerative process giving rise to diseases such as Alzheimer’s is triggered when the normal structures of protein molecules within cells become corrupted.

Protein molecules are made in cellular ‘assembly lines’ that join together chemical building blocks called amino acids in an order encoded in our DNA. New proteins emerge as long, thin chains that normally need to be folded into compact and intricate structures to carry out their biological function.

Under some conditions, however, proteins can ‘misfold’ and snag surrounding normal proteins, which then tangle and stick together in clumps which build to masses, frequently millions, of malfunctioning molecules that shape themselves into unwieldy protein tendrils.

The abnormal tendril structures, called ‘amyloid fibrils’, grow outwards around the location where the focal point, or ‘nucleation’ of these abnormal “species” occurs.

Amyloid fibrils can form the foundations of huge protein deposits – or plaques – long-seen in the brains of Alzheimer’s sufferers, and once believed to be the cause of the disease, before the discovery of ‘toxic oligomers’ by Dobson and others a decade or so ago.

A plaque’s size and density renders it insoluble, and consequently unable to move. Whereas the oligomers, which give rise to Alzheimer’s disease, are small enough to spread easily around the brain – killing neurons and interacting harmfully with other molecules – but how they were formed was until now a mystery.

The new work, in large part carried out by researcher Samuel Cohen, shows that once a small but critical level of malfunctioning protein ‘clumps’ have formed, a runaway chain reaction is triggered that multiplies exponentially the number of these protein composites, activating new focal points through ‘nucleation’.

It is this secondary nucleation process that forges juvenile tendrils, initially consisting of clusters that contain just a few protein molecules. Small and highly diffusible, these are the ‘toxic oligomers’ that careen dangerously around the brain cells, killing neurons and ultimately causing loss of memory and other symptoms of dementia.

The researchers brought together kinetic experiments with a theoretical framework based on master equations, tools commonly used in other areas of chemistry and physics but had not been exploited to their full potential in the study of protein malfunction before.

The latest research follows hard on the heels of another ground breaking study, published in April of this year again in PNAS, in which the Cambridge group, in Collaboration with Colleagues in London and at MIT, worked out the first atomic structure of one of the damaging amyloid fibril protein tendrils. They say the years spent developing research techniques are really paying off now, and they are starting to solve “some of the key mysteries” of these neurodegenerative diseases.

“We are essentially using a physical and chemical methods to address a biomolecular problem, mapping out the networks of processes and dominant mechanisms to ‘recreate the crime scene’ at the molecular root of Alzheimer’s disease,” explained Knowles.

“Increasingly, using quantitative experimental tools and rigorous theoretical analysis to understand complex biological processes are leading to exciting and game-changing results. With a disease like Alzheimer’s, you have to intervene in a highly specific manner to prevent the formation of the toxic agents. Now we’ve found how the oligomers are created, we know what process we need to turn off.”

NASA is funding research into 3D-printed food. Mechanical engineer Anjan Contractor received a $125,000 grant from the agency to build a prototype 3D printer with the aim of automating food creation. It’s hoped the system could provide astronauts food during long-distance space travel, but its creator has the loftier aim of solving the increasing food shortages around the world by cutting down on waste. The software for the printer will be open-source, while the hardware is based on the open-source RepRap Mendel 3D printer.

The concept is to use basic “building blocks” of food in replaceable powder cartridges. By combining each block, a wide range of foods should be able to be created by the printer. The cartridges will have a lifespan of 30 years, more than long enough to enable long-distance space travel. After proving his system works on a basic level by printing chocolate, Contractor will start his project within the next few weeks by attempting to print a pizza.

As Quartz reveals, the pizza printer will first print a layer of dough, which will be cooked while being printed, before mixing tomato powder with water and oil to print a tomato sauce. The topping for the pizza will be a nondescript “protein layer.” It’s early days for the project, but if it’s successful it would be a real milestone on the way towards a Star Trek-style Replicator.

“Try to acquire the weird practice of savouring your mistakes, delighting in uncovering the strange quirks that led you astray.”

Daniel Dennet (Seven Tools for Thinking)

Art by: Dunno. You know? Lemme know!