ABC News - Dr. Anthony Atala, director of the Wake Forest Institute for Regenerative Medicine, currently heads up more than 300 researchers in the Wake Forest University lab who are working on growing more than 30 different organs and body tissues.
Currently, scientists are able to create some types of tissues for human transplant use. The simplest kind are flat, simple structures such as skin that consist of one cell type. Tubular structures that involve two cell types, such as blood vessels, are also possible using current techniques and technology. Most recently, scientists have been able to create hollow organs, like the stomach and bladder, that only require two cell types but have a more complex shape.
What still lies out of reach are the solid organs, such as the liver or kidneys.
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With a new manufacturing technology, researchers at KTH Microsystem Technology hope to bring mass innovation capabilities to smaller companies and markets — just as affordable computers have dramatically increased innovation in information technology.
Production of silicon micro- and nanosensors with today’s technologies requires a full-scale clean-room laboratory costing millions of euros – facilities that few organisations can afford. What’s more, integrated-circuit manufacturing technologies used in sensor production are highly standardised processes, optimised for extremely large production volumes of hundreds of millions of devices per year. These sensors, known as Micro Electromechanical Systems (MEMS), are engineered from thin slices of silicon, the same material used to manufacture integrated circuits and other micro-sized electronic devices.
Researchers at KTH Microsystem Technology have demonstrated a manufacturing concept that could pave the way toward simple, inexpensive “printing” of 3D silicon structures
Schematic of the 3D printing process and an image of a manufactured microstructure
Advanced Functional Materials - 3D Free-Form Patterning of Silicon by Ion Implantation, Silicon Deposition, and Selective Silicon Etching
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Google research budget will be twice as large as DARPA in 2012
Google will be spending about $6 billion on research and development in 2012
Google reported revenues of $10.65 billion for the first quarter which ended March 31, 2012, an increase of 24% compared to the first quarter of 2011 ($8.58 billion). But minus traffic acquisition costs, Google pulled in $8.14 billion in revenue. Google spent about $1.5 billion on research and development. Google spent about 18% of revenue (after traffic acquisition) on research and development.
In the last quarter of 2011, top US public companies for R&D spending were:
Microsoft $2.517 billion
Intel $2.401 billion
IBM $1.6 billion
Google $1.44 billion
Oracle $1.226 billion
Apple $842 million
Darpa has an annual budget of about $3.2 billion which is a quarterly budget of $800 million.
Microsoft and Intel are each over three times the R&D budget of DARPA.
I expect Google to increase its R&D to match its 24% growth. This should put Google ahead of IBM in R&D spending in 2012. If Google is able to maintain growth then in 2014 it could have the largest R&D spending.
Intel, IBM and Microsoft have had relatively little revenue growth. Microsoft did have about 4.5-6% revenue growth in its first quarter. Intel and IBM have had flat revenue.
Internet advertising is still projected to grow in the double digits each year.
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NY Times- Inside Google’s secretive X laboratory, known for inventing self-driving cars and augmented reality glasses, a small group of researchers began working several years ago on a simulation of the human brain. Google scientists created one of the largest neural networks for machine learning by connecting 16,000 computer processors, which they turned loose on the Internet to learn on its own.
The neural network taught itself to recognize cats, which is actually no frivolous activity. This week the researchers will present the results of their work at a conference in Edinburgh, Scotland.
The Google research team, led by the Stanford University computer scientist Andrew Y. Ng and the Google fellow Jeff Dean, used an array of 16,000 processors to create a neural network with more than one billion connections. They then fed it random thumbnails of images, one each extracted from 10 million YouTube videos.
“It is worth noting that our network is still tiny compared to the human visual cortex, which is a million times larger in terms of the number of neurons and synapses,” the researchers wrote.
Despite being dwarfed by the immense scale of biological brains, the Google research provides new evidence that existing machine learning algorithms improve greatly as the machines are given access to large pools of data.
There is an estimate that Google had computational capacity of 40 petaflops at the beginning of 2012
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Nasa Space Flight - SpaceX and Orbital both fired their new engines. SpaceX’s Merlin 1D rumbled for a full mission duration firing, while Orbital’s AJ-26 continued its testing ahead of its debut on their Antares launch vehicle
The Spacex Merlin D has improved performance. Thrust is increased from 95,000 lbf (sea level) to 140,000 lbf (sea level). Added throttle capability for range from 70-100 percent. Currently, it is necessary to shut off two engines during ascent. The Merlin 1D will make it possible to throttle all engines. Structure was removed from the engine to make it lighter.
The Merlin D has improved manufacturability. A simplified design is used lower cost manufacturing techniques. Reduced touch labor and parts count. Increased in-house production at SpaceX.
The engine firing was for 185 seconds with 147,000 pounds of thrust, the full duration and power required for a Falcon 9 rocket launch.
The extra power and multiple restart elements are major steps towards achieving the highly complex task of making Falcon 9 reusable, a vehicle known as F9r or Grasshopper.
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MIT engineers have developed a fuel cell that runs on the same sugar that powers human cells: glucose. This glucose fuel cell could be used to drive highly efficient brain implants of the future, which could help paralyzed patients move their arms and legs again.
The fuel cell, described in the June 12 edition of the journal PLoS ONE, strips electrons from glucose molecules to create a small electric current. The researchers, led by Rahul Sarpeshkar, an associate professor of electrical engineering and computer science at MIT, fabricated the fuel cell on a silicon chip, allowing it to be integrated with other circuits that would be needed for a brain implant.
The new twist to the MIT fuel cell described in PLoS ONE is that it is fabricated from silicon, using the same technology used to make semiconductor electronic chips. The fuel cell has no biological components: It consists of a platinum catalyst that strips electrons from glucose, mimicking the activity of cellular enzymes that break down glucose to generate ATP, the cell’s energy currency. (Platinum has a proven record of long-term biocompatibility within the body.) So far, the fuel cell can generate up to hundreds of microwatts — enough to power an ultra-low-power and clinically useful neural implant.
“It will be a few more years into the future before you see people with spinal-cord injuries receive such implantable systems in the context of standard medical care, but those are the sorts of devices you could envision powering from a glucose-based fuel cell,” says Benjamin Rapoport, a former graduate student in the Sarpeshkar lab and the first author on the new MIT study.
Rapoport calculated that in theory, the glucose fuel cell could get all the sugar it needs from the cerebrospinal fluid (CSF) that bathes the brain and protects it from banging into the skull.
Power Extraction from Cerebrospinal Fluid by an Implantable Glucose Fuel Cell. Conceptual schematic design for a system that harvests power from the cerebrospinal fluid, showing a plausible site of implantation within the subarachnoid space. The inset at right is a micrograph of one prototype, showing the metal layers of the anode (central electrode) and cathode contact (outer ring) patterned on a silicon wafer. Image Credit: Meninges and Vascular Anatomy courtesy of the Central Nervous System Visual Perspectives Project, Karolinska Institutet and Stanford University.
PlosOne - A Glucose Fuel Cell for Implantable Brain–Machine Interfaces
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