Computer Model Recreates Realistic Touch Sensation

Neuroscientists from the University of Chicago have developed a computer model that can simulate the response of nerves in the hand to any pattern of touch stimulation on the skin. The tool reconstructs the response of more than 12,500 nerve fibers with millisecond precision, taking into account the mechanics of the skin as it presses up against and moves across objects.

The software will allow scientists to see how entire populations of nerve fibers respond when we interact with objects. This model will allow scientists to better understand how the nerve responds to touch, and can be used to build realistic sensations into bionic hands for amputees.

GPS Data Reveal How Sheepdogs Herd Sheep

Scientists using GPS technology have figured out how sheepdogs efficiently herd sheep. This may help in developing robots that can perform similar activities and other applications.

They find that the dogs follow two basic instructions which allows them to tightly reign in the sheep and move them towards a single direction. The two instructions are to (1) collect the sheep when they are loose and (2) move them forward when they are gathered.

The scientists also attached gps devices on the sheep and the dog and observed how the movements of the animals appear on screen. They also built a computer model that simulates an efficient way of herding the sheep.

Surprisingly, the two models are similar.

This discovery can help in developing applications for use by robots in activities such as crowd control, cleaning up the environment, herding of livestock, keeping animals away from sensitive areas, and collecting or guiding groups of exploring robots.

Computer Simulation Accurately Predicts Blood Vessel Growth

Bioengineers from the University of Utah created a computer simulation that accurately maps blood vessel growth. This can help in the further treatments to provide better blood supply to skin grafts and implanted ligament and tendon, as well as tissues damaged by diabetes and heart attack.

The image on the left in green, show real blood vessels growing in culture while the right image in red, is the computer simulation of the blood vessel growth. The simulation is based on the study and use of real blood vessels from rats.

Additionally, the top images show real and simulated blood vessel growth when vessel fragments are placed in an "extracellular matrix" of collagen with a relatively low density. The middle and bottom images show how blood vessel growth is impeded when they are placed in collagen matrix with medium and higher density, respectively.

The physical and mechanical properties of the collagen are highlighted by the simulation showing that a denser collagen matrix makes it hard for blood vessels to form a network. By accurately predicting the growth and spread of the blood vessels, bioengineers can prepare implantable tissues that already contain blood vessels that match a patient's blood vessel structure.

This technology can provide better treatment by replacing damaged heart tissues, reconstructing ligaments and tendon, and skin grafts to stimulate blood flow to promote healing of diabetic ulcers.

Largest Dinosaur Argentinosaurus Huinculensis Walking Digitally Simulated

The Argentinosaurus huinculensis, one of the largest dinosaurs ever discovered has been digitally reconstructed to study how it walks. The Argentinosaurus is a dinosaur that lived around 94 million years ago. The virtual model was reconstructed through a computer technique that involved the computing power of 30,000 desktop computers.

The Argentinosaurus (named after the country it was first found; Argentina) is the largest dinosaur ever discovered and is the longest and heaviest land animal ever. An adult 40 year old Argentinsaurus can reach a size of 37 meters and weighing around 75 to 100 tons. The herbivore lived during the Cretaceous period and was believed to have perished during the end of the Jurassic period with a few of its relatives surviving in South America.

The dinosaur is a social animal that moved in herds of 20 or more. It stripped vegetated areas of leaves, seed and fruit before moving on to find a new place to graze.

By digitally reconstructing how the Argentinosaurus moved, the study can contribute to the development of locomotion and movement technology as it applies to musculoskeletal systems and for developing robots.

Brain Waves From 12,000 Brain Neurons Simulated In A Computer

(c) Copyright: EPFL, Blue Brain Project

The Ecole Polytechnique Fédérale de Lausanne (EPFL) Blue Brain Project in Switzerland and the Allen Institute for Brain Science in the United States have built a computer model that simulates 12,000 neurons. This allows the scientists to learn more about brain waves and how neurons work and interact with each other.

The Computer visualization on the left shows the brain waves produced by 100 detailed models of nerve cells. The strength of the signal is represented by the following color scheme: green = weak signal, yellow = medium, red = strong.

Neurons behave differently from how computer chips operate. With computer chips, a steady stream of power is fed through it at a steady rate. Neurons transmit and process information that are sent in spikes.

The Blue Brain Project aims to complete a working computer model of the human brain. Although the project has simulated 12,000 neurons, it is still a far stride from a complete brain which has billions of neurons comprising the nervous system.

MIT News: MIT Develops A Continuum Model That Predicts The Flow of Granular Materials Like Sand

Sand is composed of finely divided rock and mineral particles. It is naturally occuring and granular. The actual composition of sand is highly variable, depending on the local rock sources and conditions, but the most common constituent of sand is silica (silicon dioxide, or SiO2), usually in the form of quartz.

Shifting sands
New model predicts how sand and other granular materials flow.

CAMBRIDGE, Mass. -- Sand in an hourglass might seem simple and straightforward, but such granular materials are actually tricky to model. From far away, flowing sand resembles a liquid, streaming down the center of an hourglass like water from a faucet. But up close, one can make out individual grains that slide against each other, forming a mound at the base that holds its shape, much like a solid.

Sand’s curious behavior — part fluid, part solid — has made it difficult for researchers to predict how it and other granular materials flow under various conditions. A precise model for granular flow would be particularly useful in optimizing processes such as pharmaceutical manufacturing and grain production, where tiny pills and grains pour through industrial chutes and silos in mass quantities. When they aren’t well-controlled, such large-scale flows can cause blockages that are costly and sometimes dangerous to clear.

Now Ken Kamrin of MIT’s Department of Mechanical Engineering has come up with a model that predicts the flow of granular materials under a variety of conditions. The model improves on existing models by taking into account one important factor: how the size of a grain affects the entire flow. Kamrin used the new model to predict sand flow in several configurations — including a chute and a circular trough — and found that the model’s predictions were a near-perfect match with actual results. A paper detailing the new model will appear in the journal Physical Review Letters.

“The basic equations governing water flow have been known for over a century,” says Kamrin, the Class of ’56 Career Development Assistant Professor of Mechanical Engineering. “There hasn’t been something similar for sand, where I can give you a cupful of sand, and tell you which equations will be necessary to predict how it will squish around if I squeeze the cup.”