Courtesy jasonpearce Housing for Haitians may already be on hand. Sturdy, earthquake and hurricane proof, shipping containers often sit empty in port yards because exporting empty containers is not cost effective.
Pernille Christensen, at Clemson’s School of Architecture, along with Martha Skinner and Doug Hecker, have been working to develop a method to convert the shipping containers into homes.
“Because of the shipping container’s ‘unibody’ construction they are also very good in seismic zones and exceed structural code in the United States and any country in the world,” associate professor Hecker said.
“You get people back in their communities and it strengthens those communities,” Christensen said. “They work on their home, not a temporary shelter, and then they work with their neighbors to rebuild the neighborhood. It leads to a healthier and safer community. And these are places often in dire need of better housing.”
I recorded this live with internet broadcast, on 09th January 2010 during the Closing Ceremony of IYA2009 | International Year of Astronomy. You can hear how Vincenzo Giorgio of Thales Alenia Space, the Principal Sponsor of IYA2009, International Year of Astronomy is saying hinhis address @ the closing ceremony of IYA2009 live from Padua, Italy
The manufacture of replacement body parts just might happen this year. Organovo just took delivery of the world's first production grade 3D bio-printer developed for them by Invetech.
The printer includes two print heads, one for placing human cells, and the other for placing a hydrogel, scaffold, or support matrix. The position of a capillary tip, can position droplets of "ink" containing virtually any cell type, with micron accuracy.
"Invetech plans to ship a number of 3D bio-printers to Organovo during 2010 and 2011 as a part of the instrument development program. Organovo will be placing the printers globally with researchers in centers of excellence for medical research." Organovo press release
Courtesy ESACan it be true? Yes, for a mere $5,544 dollars round-trip airfare to Greenland! In March 2009, the European Space Agency launched the Gravity field and steady-state Ocean Circulation Explorer (GOCE) into orbit around our planet, which is now transmitting detailed data about the Earth’s gravity. The GOCE satellite uses a gradiometer to map tiny variations in the Earth’s gravity caused by the planet’s rotation, mountains, ocean trenches, and interior density. New maps illustrating gravity gradients on the Earth are being produced from the information beamed back from GOCE. Preliminary data suggests that there is a negative shift in gravity in the northeastern region of Greenland where the Earth’s tug is a little less, which means you might weigh a fraction of a pound lighter there (a very small fraction, so it may not be worth the plane fare)!
In America, NASA and Stanford University are also working on the gravity issue. Gravity Probe B (GP-B) is a satellite orbiting 642 km (400 miles) above the Earth and uses four gyroscopes and a telescope to measure two physical effects of Einstein’s Theory of General Relativity on the Earth: the Geodetic Effect, which is the amount the earth warps its spacetime, and the Frame-Dragging Effect, the amount of spacetime the earth drags with it as it rotates. (Spacetime is the combination of the three dimensions of space with the one dimension of time into a mathematical model.)
Quick overview time. The Theory of General Relativity is simply defined as: matter telling spacetime how to curve, and curved spacetime telling matter how to move. Imagine that the Earth (matter) is a bowling ball and spacetime is a trampoline. If you place the bowling ball in the center of the trampoline it stretches the trampoline down. Matter (the bowling ball) curves or distorts the spacetime (trampoline). Now toss a smaller ball, like a marble, onto the trampoline. Naturally, it will roll towards the bowling ball, but the bowling ball isn’t ‘attracting’ the marble, the path or movement of the marble towards the center is affected by the deformed shape of the trampoline. The spacetime (trampoline) is telling the matter (marble) how to move. This is different than Newton’s theory of gravity, which implies that the earth is attracting or pulling objects towards it in a straight line. Of course, this is just a simplified explanation; the real physics can be more complicated because of other factors like acceleration.
Courtesy noneSo what is the point of all this high-tech gravity testing? First of all, our current understanding of the structure of the universe and the motion of matter is based on Albert Einstein’s Theory of General Relativity; elaborate concepts and mathematical equations conceived by a genius long before we had the technology to directly test them for accuracy. The Theory of General Relativity is the cornerstone of modern physics, used to describe the universe and everything in it, and yet it is the least tested of Einstein’s amazing theories. Testing the Frame-Dragging Effect is particularly exciting for physicists because they can use the data about the Earth’s influence on spacetime to measure the properties of black holes and quasars.
Second, the data from the GOCE satellite will help accurately measure the real acceleration due to gravity on the earth, which can vary from 9.78 to 9.83 meters per second squared around the planet. This will help scientists analyze ocean circulation and sea level changes, which are influenced by our climate and climate change. The information that the GOCE beams back will also assist researchers studying geological processes such as earthquakes and volcanoes.
So, as I gobble down another mouthful of leftover turkey and mashed potatoes, I can feel confident that my holiday weight gain and the structure of the universe are of grave importance to the physicists of the world!
For the first time, a team led by Yale University researchers has used nanosensors to measure cancer biomarkers in whole blood. The new device is able to read out biomarker concentrations in a just a few minutes. Extremely small concentrations are being measured, the equivalent of detecting a single grain of salt within a swimming pool size volume of liquid.
"The new device could also be used to test for a wide range of biomarkers at the same time, from ovarian cancer to cardiovascular disease, Reed said. Science Daily.
Authors of the paper, "Label-free biomarker detection from whole blood", include Eric Stern, Aleksandar Vacic, Nitin Rajan, Jason Criscione, Jason Park, Mark Reed and Tarek Fahmy (all of Yale University); Bojan Ilic (Cornell University); David Mooney (Harvard University).
Distinct components within the sensor perform purification and detection. A microfluidic purification chip simultaneously captures multiple biomarkers from blood samples and releases them, after washing, into purified buffer for sensing by a silicon nanoribbon detector. This two-stage approach isolates the detector from the complex environment of whole blood, and reduces its minimum required sensitivity by effectively pre-concentrating the biomarkers. Nature Nanotechnology, Dec 13, 2009
MRAM (magnetoresistive random access memory) flips the magnetisation of a region 180 degrees relative to another permanently magnetised region to store a 0 or a 1. MRAM is nanosecond fast but if made too small and close together will "cross talk".
FeRAM (ferroelectric random access memory) use small external electric fields to polarize ferroelectric crystals. FeRAMs low energy requirement and speed advantage is offset by the requirement that every memory bit requires a space hogging capacitor.
PCRAM (phase-change random access memory) use laser light or current to change a materials structure. If the current pulse is long, the material orders itself into its crystalline state (a conductor). If the pulse is short, the material cools abruptly into the amorphous state (an insulator). These memory regions can be made quite small, but the downside is that the melting requires lots of energy.
RRAM (resistive random access memory) use high voltages to drive off or reabsorb oxygen bound within molecules like titanium oxide. When the oxygen leaves, it leaves behind holes in the crystal and excess electrons that are available for conduction. This process requires almost no electrical current, making them very energy efficient. Another exciting property is that RRAMs can represent more than a 0 or 1. They are able to adopt any number of values for their resistance (memristors) which could make them models for the analogue computational elements (synapses) inside the human brain.
Racetrack memory moves tiny domains of magnetism along wires. The domains are moved along the wire by a current and written or read when they pass sensor heads. If the wires can be coiled into 3 D, the memory per volume will increase several hundred times.
Source: New Scientist
Living organisms are very good at making sense out of what they see. Designing machines that can recognize objects when seen from an angle or at various distances is challenging. Facial or gesture recognition is becoming common in our computing devices.
In an attempt to improve upon current state of the art visual systems, scientists are attempting to reverse engineer biological visual systems.
Huge advances have been recently made in visualizing the structure of our visual cortex (hardware) but the inner workings of the neuronal systems (software) remain a mystery. Mimicking natural selection, scientists are testing thousands of software algorithms at a time.
Using graphical processors from game playing computers (such as those found in the PlayStation 3 and high-end NVIDIA graphics cards), scientists have discovered better visual modeling systems.
"The best of these models, drawn from thousands of candidates, outperformed a variety of state-of-the-art vision systems across a range of object and face recognition tasks."
"GPUs are a real game-changer for scientific computing. We made a powerful parallel computing system from cheap, readily available off-the-shelf components, delivering over hundred-fold speed-ups relative to conventional methods,"
Courtesy SaperaudLooking for a winter “project”? Why not invent something during your hibernation. You might make a million dollars! Or, in the case of an Amsterdam artist slash space engineer, who must enjoy a good laugh, you could invent a wacky mirror and convince the Royal Netherlands Academy of Arts and Sciences to give you 80,000 Euros for your amazing “scientific instrument”! Called the Cyclops Mirror, when you look through it, your right eye sees your left eye and vice versa. As you get closer your reflection turns into a single cycloptic eye. Cool. But 80,000 Euro cool? Haven’t I seen this at the House of Mirrors at the carnival?
For the more ambitious, you could invent something practical or even wacky and sell it online. For the environmentally friendly scientist, how about inventing a wooden cell phone? Too late. Check out this biodegradable wood phone that even has a camera. How about solar power technology? What soccer fan wouldn’t want a solar powered soccer ball shaped mini fan for those heated summer games. Or for those cold winter days, how about solar powered hat and mittens (I might have to get a set of these)!
Want to get rich quick in two ways? Invent some metal detector sandals and then go find some ancient treasures! Just strap on these groovy shoes and keep your hands free for carrying your treasure hoard. The detecting device strapped to your ankle is discretely hidden under your trousers so the neighbors don’t think you are on house arrest!
Check out these websites for more invention fun, get started on your next great creation and take over the world!
Courtesy Thomas Schultz
Even simple brains, like those in a mouse, are amazing. A brain the size of a thimble that requires almost no energy, can navigate through mazes, survive in severe weather, or escape from a cat. Will we ever create a computer capable of such adaptable and creative "thinking"? One approach is to reverse engineer the brain of a mouse, rat, or cat.
Dharmendra S. Modha is a team leader at IBM who is attempting to understand and build such a brain as cheaply as possible. Their latest achievement is a brain simulation with 1 billion spiking neurons and 10 trillion individual learning synapses.
Synapses are junctions between neurons and a key to how a brain learns. The strength of the chemical reactions within the synapses changes as the animal interacts with the environment These synaptic junctions are thought to encode our individual experience.
Regular computer architecture has a separation between computation and memory.
“Surely there must be a less primitive way of making big changes in the store than by pushing vast numbers of words back and forth through the von Neumann bottleneck. Not only is this tube a literal bottleneck for the data traffic of a problem, but, more importantly, it is an intellectual bottleneck that has kept us tied to word-at-a-time thinking instead of encouraging us to think in terms of the larger conceptual units of the task at hand. Thus programming is basically planning and detailing the enormous traffic of words through the von Neumann bottleneck, and much of that traffic concerns not significant data itself, but where to find it.”
The goal of a DARPA program known as SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) is to create new electronics hardware and architecture that can understand, adapt and respond to a a changing environment.
Cognitive computing is the quest to engineer mind-like intelligent machines by reverse-engineering the computational function of the brain.
There is no definition or specification of the human mind. But, we understand it as a collection of processes of sensation, perception, action, cognition, emotion, and interaction. Yet, the mind seems to integrate sight, hearing, touch, taste, and smell effortlessly into a coherent whole, and to act in a context-dependent way in a changing, uncertain environment. The mind effortless creates categories of time, space, and object, and interrelationships between these.
Courtesy NeilsPhotography Engineers are trying to design machines that can "think for themselves" when on surveillance or search and rescue missions. Somehow the machines has to look at its environment and decide what to do.
Have you ever tried to catch a fly? They are pretty good at seeing your hand and knowing just how to escape your grasp.
Can we figure out how a fly is able see, and find food, and escape from our fly swatters? With today's super microscopes, I am sure that we can visualize and model every nerve connection, muscle fiber, and eye facet.
David O’Carroll, a computational neuroscientist who studies insect vision at Australia’s University of Adelaide has been studying the optical flight circuits of flies, measuring their cell-by-cell activity. In a paper published in Public Library of Science Computational Biology, O’Carroll and fellow University of Adelaide biologist Russell Brinkworth describe an
algorithm composed of a series of five equations through which data from cameras can be run. Each equation represents tricks used by fly circuits to handle changing levels of brightness, contrast and motion, and their parameters constantly shift in response to input.
“It’s amazing work,” said Sean Humbert, who builds miniaturized, autonomous flying robots,
“For traditional navigational sensing, you need lots of payload to do the computation. But the payload on these robots is very small — a gram, a couple of Tic Tacs. You’re not going to stuff dual-core processors into a couple Tic Tacs.
Secret Math of Fly Eyes Could Overhaul Robot Vision Wired Science
Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology Computational Biology
We have constructed a full model for motion processing in the insect visual pathway incorporating known or suspected elements in as much detail as possible. We have found that it is only once all elements are present that the system performs robustly, with reduction or removal of elements dramatically limiting performance. The implementation of this new algorithm could provide a very useful and robust velocity estimator for artificial navigation systems.