Lifeboat Foundation

https://youtube.com/watch?v=0zOL6-u5GJo

This is the second novel in “Remembrance of Earth’s Past”, the near-future trilogy written by China’s multiple-award-winning science fiction author, Cixin Liu.

In The Dark Forest, Earth is reeling from the revelation of a coming alien invasion — four centuries in the future. The aliens’ human collaborators have been defeated but the presence of the sophons, the subatomic particles that allow Trisolaris instant access to all human information, means that Earth’s defense plans are exposed to the enemy. Only the human mind remains a secret.

Continue reading “The Dark Forest by Liu Cixin (Part 2) — Science Fiction Audiobook” »

https://youtube.com/watch?v=Zc7ysvsa6U0

This is the second novel in “Remembrance of Earth’s Past”, the near-future trilogy written by China’s multiple-award-winning science fiction author, Cixin Liu.

In The Dark Forest, Earth is reeling from the revelation of a coming alien invasion — four centuries in the future. The aliens’ human collaborators have been defeated but the presence of the sophons, the subatomic particles that allow Trisolaris instant access to all human information, means that Earth’s defense plans are exposed to the enemy. Only the human mind remains a secret.

Continue reading “The Dark Forest by Liu Cixin (Part 1) — Science Fiction Audiobook” »

Human beings are capable of processing several sound sources at once, both in terms of musical composition or synthesis and analysis, i.e., source separation. In other words, human brains can separate individual sound sources from a mixture and vice versa, i.e., synthesize several sound sources to form a coherent combination. When it comes to mathematically expressing this knowledge, researchers use the joint probability density of sources. For instance, musical mixtures have a context such that the joint probability density of sources does not factorize into the product of individual sources.

A deep learning model that can synthesize many sources into a coherent mixture and separate the individual sources from a mixture does not exist currently. When it comes to musical composition or generation tasks, models directly learn the distribution over the mixtures, offering accurate modeling of the mixture but losing all knowledge of the individual sources. Models for source separation, in contrast, learn a single model for each source distribution and condition on the mixture at inference time. Thus, all the crucial details regarding the interdependence of the sources are lost. It is difficult to generate mixtures in either scenario.

Taking a step towards building a deep learning model that is capable of performing both source separation and music generation, researchers from the GLADIA Research Lab, University of Rome, have developed Multi-Source Diffusion Model (MSDM). The model is trained using the joint probability density of sources sharing a context, referred to as the prior distribution. The generation task is carried out by sampling using the prior, whereas the separation task is carried out by conditioning the prior distribution on the mixture and then sampling from the resulting posterior distribution. This approach is a significant first step towards universal audio models because it is a first-of-its-kind model that is capable of performing both generation and separation tasks.

Researchers from The University of Queensland have discovered the active compound from an edible mushroom that boosts nerve growth and enhances memory.

Professor Frederic Meunier from the Queensland Brain Institute said the team had identified new active compounds from the mushroom, Hericium erinaceus.

Researchers have discovered lion’s mane mushrooms improve brain cell growth and memory in pre-clinical trials. Image UQ.

Considering a “computer” as anything that processes information by taking an input and producing an output leads to the obvious questions, what kind of objects could perform computations? And how small can a computer be? As transistors approach the limit of miniaturisation, these questions are more than mere curiosities, their answers could form the basis of a new computing paradigm.

In a new paper in EPJ Plus (“Towards Single Atom Computing via High Harmonic Generation”) by Tulane University, New Orleans, Louisiana, researcher Gerard McCaul, and his co-authors demonstrate that even one of the more basic constituents of matter — atoms — can act as a reservoir for computing where all input-output processing is optical.

“We had the idea that the capacity for computation is a universal property that all physical systems share, but within that paradigm, there is a great profusion of frameworks for how one would go about actually trying to perform computations,” McCaul says.

Imagine going for an MRI scan of your knee. This scan measures the density of water molecules present in your knee, at a resolution of about one cubic millimeter – which is great for determining whether, for example, a meniscus in the knee is torn. But what if you need to investigate the structural data of a single molecule that’s five cubic nanometers, or about ten trillion times smaller than the best resolution current MRI scanners are capable of producing? That’s the goal for Dr. Amit Finkler of the Weizmann Institute of Science’s Chemical and Biological Physics Department.

In a recent study (Physical Review Applied, “Mapping Single Electron Spins with Magnetic Tomography”), Finkler, PhD student Dan Yudilevich and their collaborators from the University of Stuttgart, Germany, have managed to take a giant step in that direction, demonstrating a novel method for imaging individual electrons. The method, now in its initial stages, might one day be applicable to imaging various kinds of molecules, which could revolutionize the development of pharmaceuticals and the characterization of quantum materials.

The experimental set-up: A 30-micron-thick diamond membrane with one sensor, on average, at the top of each column, magnified 2,640 times (top) and 32,650 times (bottom)

Some researchers are driven by the quest to improve a specific product, like a battery or a semiconductor. Others are motivated by tackling questions faced by a given industry. Rob Macfarlane, MIT’s Paul M. Cook Associate Professor in Materials Science and Engineering, is driven by a more fundamental desire.

“I like to make things,” Macfarlane says. “I want to make materials that can be functional and useful, and I want to do so by figuring out the basic principles that go into making new structures at many different size ranges.” (Image: Adam Glanzman)

Not only were women in ancient Egypt responsible for the nurturance and admonition of children, but they could also work at a trade, own and operate a business, inherit property, and come out well in divorce proceedings. Some women of the working class even became prosperous. They trained in medicine as well as in other highly skilled endeavors. There were female religious leaders in the priesthood, but in this instance, they were not equal to the men. In ancient Egypt, women could buy jewelry and fine linens. At times, they ruled as revered queens or pharaohs.

The role of women in ancient Egypt diminished during the late dynastic period but reappeared within the Ptolemaic dynasty. Both Ptolemy I and II put the portraits of their wives on the coins. Cleopatra VII became a very powerful figure internationally. However, after her death, the role of women receded markedly and remained virtually subservient until the 20th century.

Scientists could finally send more powerful mirrors to space to hunt for exoplanets.

Scientists have found a way to bring bigger telescope mirrors into space, potentially allowing for more exoplanet discoveries.