Lifeboat Foundation

A team led by Lida Kanari now reports a new system for distinguishing cell types in the brain, an algorithmic classification method that the researchers say will benefit the entire field of neuroscience. Blue Brain founder Professor Henry Markram says, “For nearly 100 years, scientists have been trying to name cells. They have been describing them in the same way that Darwin described animals and trees. Now, the Blue Brain Project has developed a mathematical algorithm to objectively classify the shapes of the neurons in the brain. This will allow the development of a standardized taxonomy [classification of cells into distinct groups] of all cells in the brain, which will help researchers compare their data in a more reliable manner.”

The team developed an algorithm to distinguish the shapes of the most common type of neuron in the neocortex, the pyramidal cells. Pyramidal cells are distinctively tree-like cells that make up 80 percent of the neurons in the neocortex, and like antennas, collect information from other neurons in the brain. Basically, they are the redwoods of the brain forest. They are excitatory, sending waves of electrical activity through the network, as people perceive, act, and feel.

The father of modern neuroscience, Ramón y Cajal, first drew pyramidal cells over 100 years ago, observing them under a microscope. Yet up until now, scientists have not reached a consensus on the types of pyramidal neurons. Anatomists have been assigning names and debating the different types for the past century, while neuroscience has been unable to tell for sure which types of neurons are subjectively characterized. Even for visibly distinguishable neurons, there is no common ground to consistently define morphological types.

Continue reading “Blue Brain solves a century-old neuroscience problem” »

When Genevieve posted about optical tweezers, I noticed the similarity with acoustic tweezers, so I needed to post this article as well, so as to add to hers.

A new algorithm recently helped scientists levitate multiple objects using sound waves in very strategic positions. It marked the first time that sound helped capture numerous objects in various positions. The findings were recently published in the journal Proceedings of the National Academy of Science. It was funded by the Engineering and Physical Sciences Research Council (EPSRC) in the United Kingdom.

Continue reading “Researchers Use Sound to Make a Range of Objects Float for the First Time” »

DNA computers have to date only been able to run one algorithm, but a new design shows how these machines can be made more flexible—and useful.

Computer scientists at the University of California, Davis, and the California Institute of Technology have created DNA molecules that can self-assemble into patterns essentially by running their own program. The work is published March 21 in the journal Nature.

“The ultimate goal is to use computation to grow structures and enable more sophisticated molecular engineering,” said David Doty, assistant professor of computer science at UC Davis and co-first author on the paper.

The system is analogous to a computer, but instead of using transistors and diodes, it uses molecules to represent a six-bit binary number (for example, 011001). The team developed a variety of algorithms that can be computed by the molecules.

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A team of researchers at the Rochester Institute of Technology invented a “toilet seat-based cardiovascular monitoring system” that could help hospitals monitor patients for risk of congestive heart failure — a toilet, in other words, that detects whether your heart is about to give out.

“This system will be uniquely positioned to capture trend data in the home that has been previously unattainable,” reads the paper, published in the journal JMIR Mhealth Uhealth.

Integrated into the seat is a device that measures heart rate, blood pressure, and blood oxygenation levels. Algorithms will take in all that data and notify health practitioners if the patient’s condition deteriorates.

Imagine a future where electronic text messaging is tracked by an intelligent algorithm that can identify truth from lies. A new study from two US researchers suggests this kind of online polygraph is entirely possible, with early experiments showing a machine learning algorithm can separate truth from lies based just on text cues over 85 percent of the time.

It was 100 times faster on a routine task.

In a recent study, LawGeex, a legal tech startup, challenged a group of 20 experienced lawyers to test their skills and knowledge against its AI-powered algorithm.

A legal battle

Continue reading “This AI outperformed 20 corporate lawyers at legal work” »

The latest Facebook hack should have shown everyone nothing is safe. Researchers have now shown how easy it is to steal data from people doing research.

Engineers at the University of California say they have demonstrated how easy it would be to snoop on biotech companies making synthetic DNAll you need is an audio recording, they say. Place a smartphone near a DNA synthesizer, record the sound, run the recording across algorithms trained to discern the clicks and buzzes that particular machine makes, and you’ll know exactly what combination of DNA building blocks it is generating.

Researchers devise method for snooping on DNA synthesis using acoustic recordings. But is it a real threat?

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Artificial intelligence can automatically sort out data, but it struggles for some particularly complex datasets – a quantum algorithm could do better.