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Category: computing

It seems that biofeedback is a thing of future. By having brain activity feedback, you can train meditation, attention, improve sleep, control gadgets, artificial limbs, carts for impaired, and even computer I/O. Everything starts with proper biosensor and controller. Biological signals are very low voltage – microvolts. In order to distinguish them from noisy environment, a precision electronics is required. Brain activity signals are somewhat different from myograms or ECG, they can be analyzed as power spectrum that represent brain activity phases like Alpha, Beta, Theta. There has be a numerous modules developed to acquire brain signals. If you want low to develop sensors by yourself, you could grab a Neurosky platform which is a small size PCB with sensor and microcontroller interfaces.

With it you can read raw EEG signals with sampling 512Hz and do with them what you want. USART interface enables you to connect it yo Arduino or Raspberry Pi where you can calculate all sort of things and extract control signals. Of course you can read processed power spectrum as well to detect activities like attention, meditation and other activities. Eye blink detection is also an option. Great thing is that you can use this module to read ECG activity as well. Module incorporates AC noise filter which can be configured for 50HZ or 60Hz.

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In a development beneficial for both industry and environment, UC Santa Barbara researchers have created a high-quality coating for organic electronics that promises to decrease processing time as well as energy requirements.

“It’s faster, and it’s nontoxic,” said Kollbe Ahn, a research faculty member at UCSB’s Marine Science Institute and corresponding author of a paper published in Nano Letters (“Molecularly Smooth Self-Assembled Monolayer for High-Mobility Organic Field-Effect Transistors”).

zwitterionic molecule of the type secreted by mussels to prime surfaces for adhesion

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Nice.

Scientists in Australia have developed a quantum bit that’s 10 times more stable than existing technologies, and the new record could vastly expand the kinds of calculations quantum computers can perform.

Whereas conventional computers process information recorded in binary bits that either take a 0 or 1 value, quantum computers use quantum bits – also called qubits – that can occupy 0, 1, or a superposition that can be both at the same time.

The new qubit developed by researchers from the University of New South Wales (UNSW) is called a “dressed” quantum bit, because the team combined the single atom at its heart with an electromagnetic field.

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Great advancement around how to make QC available on small scale devices.

Researchers from the Institute for Quantum Computing (IQC) at the University of Waterloo led the development of a new extensible wiring technique capable of controlling superconducting quantum bits, representing a significant step towards to the realization of a scalable quantum computer.

“The quantum socket is a wiring method that uses three-dimensional wires based on spring-loaded pins to address individual qubits,” said Jeremy Béjanin, a PhD candidate with IQC and the Department of Physics and Astronomy at Waterloo. He and Thomas McConkey, PhD candidate from IQC and the Department of Electrical and Computer Engineering at Waterloo, are lead authors on the study that appears in the journal Physical Review Applied as an Editors’ Suggestion and is featured in Physics. “The technique connects classical electronics with quantum circuits, and is extendable far beyond current limits, from one to possibly a few thousand qubits.”

One promising implementation of a scalable quantum computing architecture uses a superconducting qubit, which is similar to the electronic circuits currently found in a classical computer, and is characterized by two states, 0 and 1. Quantum mechanics makes it possible to prepare the qubit in superposition states, meaning that the qubit can be in states 0 and 1 at the same time. To initialize the qubit in the 0 state, superconducting qubits are brought down to temperatures close to −273 degrees Celsius inside a cryostat, or dilution refrigerator.

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(Phys.org)—Over the past few decades, quantum effects have greatly improved many areas of information science, including computing, cryptography, and secure communication. More recently, research has suggested that quantum effects could offer similar advantages for the emerging field of quantum machine learning (a subfield of artificial intelligence), leading to more intelligent machines that learn quickly and efficiently by interacting with their environments.

In a new study published in Physical Review Letters, Vedran Dunjko and coauthors have added to this research, showing that quantum effects can likely offer significant benefits to .

“The progress in machine learning critically relies on processing power,” Dunjko, a physicist at the University of Innsbruck in Austria, told Phys.org. “Moreover, the type of underlying information processing that many aspects of machine learning rely upon is particularly amenable to quantum enhancements. As quantum technologies emerge, quantum machine learning will play an instrumental role in our society—including deepening our understanding of climate change, assisting in the development of new medicine and therapies, and also in settings relying on learning through interaction, which is vital in automated cars and smart factories.”

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