Lifeboat Foundation

The Norwegian Academy of Science and Letters today announced the 2020 Kavli Prize Laureates in the fields of astrophysics, nanoscience, and neuroscience. This year’s Kavli Prize honors scientists whose research has transformed our understanding of the very big, the very small and the very complex. The laureates in each field will share USD 1 million.

This year’s Kavli Prize Laureates are:

Turn the ToF camera on the Samsung Galaxy S20+, Galaxy Note 10+, and Galaxy S10 5G to a night vision that lets you see in the dark with this app.

Published recently in Nature, an international team of researchers has observed a massive, rotating disk galaxy just 1.5 billion years after the Big Bang —1.5 billion years earlier in cosmic history than astronomers had expected to find such a galaxy based on previous studies. The research has fueled debate about how galaxies in the early Universe assembled.

The observations were made using one of the most powerful radio telescopes in the world, the Atacama Large Millimeter/submillimeter Array (ALMA), in the Atacama Desert in northern Chile.

“This is an exciting discovery for astronomers because it provides clues as to how large-scale structure began to form in the Universe,” said Dr. Alfred Tiley from the UWA node of the International Centre for Radio Astronomy Research (ICRAR).

HUNDREDS have defied strict coronavirus lockdown regulations to gather in Trafalgar Square, London, to protest the death of George Floyd in the US.

Russia has lost its long-held monopoly as the only country able to ferry astronauts to the International Space Station following the flawless manned launch by US company SpaceX.

The Russian space agency congratulated the United States and Elon Musk’s SpaceX on the first crewed flight ever by a private company, but experts said the launch should be a wakeup call for Roscosmos.

“The success of the mission will provide us with additional opportunities that will benefit the whole international programme,” cosmonaut Sergei Krikalev, Roscosmos executive director for crewed space programmes, said in a brief video address.

VIENNA — We all know that one person who can eat whatever they like and never gain a pound. Ice cream at 2 in the morning? Bring it on. A third, or fourth, slice of pizza? Sure, why not. For the rest of us, the genetic perks that these individuals enjoy can be frustrating to say the least. Now, a groundbreaking new international study appears to have zeroed in on the so-called “skinny gene” that help keep such individuals thin.

Scientists from Austria, Canada, and Estonia say that lower, or deficient, levels of the gene Anaplastic Lymphoma Kinase (ALK) are significantly linked to skinniness and bodily resistance to weight gain.

Most research projects focusing on weight loss and gain search for genes that cause obesity. This study is novel due to the fact that it focuses specifically for a gene linked to thinness instead.

EL PUEBLO SE ESTÁ DESPERTANDO🇦🇷💪🏻

Presidente, el pueblo se cansó de su falta de empatía, ya no cree en usted ni en la “cuarentena”.

Miles de comercios y pymes se están fundiendo, la mayoría no recibió ayuda del gobierno.

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The Dawn of AI :

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Discovering and optimizing commercially viable materials for clean energy applications typically takes more than a decade. Self-driving laboratories that iteratively design, execute, and learn from materials science experiments in a fully autonomous loop present an opportunity to accelerate this research process. We report here a modular robotic platform driven by a model-based optimization algorithm capable of autonomously optimizing the optical and electronic properties of thin-film materials by modifying the film composition and processing conditions. We demonstrate the power of this platform by using it to maximize the hole mobility of organic hole transport materials commonly used in perovskite solar cells and consumer electronics. This demonstration highlights the possibilities of using autonomous laboratories to discover organic and inorganic materials relevant to materials sciences and clean energy technologies.

Optimizing the properties of thin films is time intensive because of the large number of compositional, deposition, and processing parameters available (1, 2). These parameters are often correlated and can have a profound effect on the structure and physical properties of the film and any adjacent layers present in a device. There exist few computational tools for predicting the properties of materials with compositional and structural disorder, and thus, the materials discovery process still relies heavily on empirical data. High-throughput experimentation (HTE) is an established method for sampling a large parameter space (4, 5), but it is still nearly impossible to sample the full set of combinatorial parameters available for thin films. Parallelized methodologies are also constrained by the experimental techniques that can be used effectively in practice.