Lifeboat Foundation

Researchers have captured the signal of neutrinos from a nuclear reactor using a water-filled neutrino detector, a first for such a device.

In a mine in Sudbury, Canada, the SNO+ detector is being readied to search for a so-far-undetected nuclear-decay process. Spotting this rare decay would allow researchers to confirm that the neutrino is its own antiparticle (see Viewpoint: Probing Majorana Neutrinos). But while SNO+ team members prepare for that search, they have made another breakthrough by capturing the interaction with water of antineutrinos from nuclear reactors [1]. The finding offers the possibility of making neutrino detectors from a nontoxic material that is easy to handle and inexpensive to obtain, key factors for use of the technology in auditing the world’s nuclear reactors (see Feature: Neutrino Detectors for National Security).

The SNO+ detector was inherited from the earlier Sudbury Neutrino Observatory (SNO) experiment. Today the detector is filled with a liquid that lights up when charged particles pass through it. But in 2018, to calibrate the detector’s components and to characterize its intrinsic radioactive background signal after the experiment’s upgrade, it contained water. The antineutrino signal was observed when, after completing those measurements, the researchers took the opportunity to carry out additional experiments before the liquid was switched out.

Simulations and an experiment aboard the International Space Station show that changes in the system’s repulsive forces are behind the alignment of particles embedded in an electrified plasma.

“If we could see the air we fly in, we wouldn’t,” is a common saying among glider pilots. The invisible turbulent pockets that accompany soaring thermals present hazards to small aircraft, but today’s observational tools struggle to measure such wind features at high spatial resolutions over large distances. Now Yunpeng Zhang of the University of Science and Technology of China and his colleagues demonstrate how adapting a remote-sensing technology called pulsed coherent Doppler lidar (PCDL) enables long-range wind detection with submeter resolution [1].

PCDL senses wind speeds by detecting the frequency shift when a laser pulse scatters off dust particles in the air. By measuring the time taken for this scattered light to return to the detector, the technique allows wide-region profiling of wind speeds. This large-scale sampling comes at the cost of measurement precision, however. Measuring the laser’s travel time requires short-duration pulses, but short pulses transmit little total energy for a given laser power, and this energy is necessarily dispersed over a wide frequency range.

To avoid this trade-off, Zhang and his colleagues imprinted a phase-modulation pattern within each transmitted pulse using an electro-optic modulator. This pattern broke the link between pulse duration and spatial resolution, allowing a more flexible pulse duration. As a result, their setup achieved a spatial resolution of 0.9 m at a distance of 700 m (compared to a 3-m resolution at 300 m for a conventional instrument) and was able to detect the wind from an electric fan on a rooftop 329 m away.

Elon Musk/courtesy of Yichuan Cao/NurPhoto via Getty Images

In 2022, Elon Musk’s Neuralink tried – and failed – to secure permission from the FDA to run a human trial of its implantable brain-computer interface (BCI), according to a Reuters report published Thursday.

Citing seven current and former employees, speaking on the condition of anonymity, Reuters reported that the regulatory agency found “dozens of issues” with Neuralink’s application that the company must resolve before it can begin studying its tech in humans.

The company also showcased other executives, which could alleviate concern that Musk has been too distracted by his other business ventures. They also talked about “meat and potato” topics like cutting costs, improving margins, and EV-charging infrastructure.

The keys to winning the EV race will come down to product appeal, software or user interface, controlling cost, and consistent execution, he said.

“And Tesla right now is one generation ahead of the other automakers,” Fields said, though rivals like Ford and Hyundai are making a lot of progress. “Tesla still has the leg-up on the competition, and I think they demonstrated that yesterday.”

This video was creating using multiple AI tools. Script was generated using ChatGPT, the noration voice was generated with Elevenlabs.io, background audio was generated with AudioLDM model and finally images were created with Stable Diffusion using Illuminati Diffusion v1.1 model. The script itself was a source for prompts at image generation stage.

There were still some human input. Particularly I generated several images for each part of the script and choose the most appealing ones. I did also manually combine noration with background music. But mostly it was done in a way that each part of the process might be completely automated.

Continue reading “‘We are the future’ — automatic content creation experiment” »

Conor russomanno, founder and CEO of openbci eva esteban, embedded software engineer at openbci

Galea is an award-winning platform that merges next-generation biometrics with mixed reality. It is the first device to integrate a wide range of physiological signals, including EEG, EMG, EDA, PPG, and eye-tracking, into a single headset. In this session, Conor and Eva will provide a live demonstration of the device and its capabilities, showcasing its potential for a variety of applications, from gaming to training and rehabilitation. They will give an overview of the different hardware and software components of the system, highlighting how it can be used to analyze user experiences in real time. Attendees will get an opportunity to ask questions at the end.

John Danaher, Senior Lecturer in Law at the National University of Ireland (NUI) Galway:

“Understanding Techno-Moral Revolutions”

Continue reading “CHM Seminar Series: Understanding Techno-Moral Revolutions — John Danaher” »

Not peer-reviewed yet but a submitted paper.

The ‘presented images’ were shown to a group of humans. The ‘reconstructed images’ were the result of an fMRI output to Stable Diffusion.

In other words, #stablediffusion literally read people’s minds.

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