Lifeboat Foundation: Safeguarding Humanity
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Blog – Page 64

Researchers have innovatively merged protein structural data with genetic sequences to construct evolutionary trees, revealing deep-rooted relationships among species.

A species is a group of living organisms that share a set of common characteristics and are able to breed and produce fertile offspring. The concept of a species is important in biology as it is used to classify and organize the diversity of life. There are different ways to define a species, but the most widely accepted one is the biological species concept, which defines a species as a group of organisms that can interbreed and produce viable offspring in nature. This definition is widely used in evolutionary biology and ecology to identify and classify living organisms.

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In a bold new theory, researchers from Microsoft, Brown University, and other institutions suggest that the universe might be capable of teaching itself how to evolve. Their study, published on the preprint server arXiv, proposes that the physical laws we observe today may have emerged through a gradual learning process, akin to Darwinian natural selection or self-learning algorithms in artificial intelligence.

This radical idea challenges traditional cosmology by imagining a primitive early universe where physical laws like gravity were far simpler or even static. Over time, these laws “learned” to adapt into more complex forms, enabling the structured universe we observe today. For instance, gravity might have initially lacked distinctions between celestial bodies like Earth and the Moon. This progression mirrors how adaptable traits in biology survive through natural selection.

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The coordinated activity of brain cells, like birds flying in formation, helps us behave intelligently in new situations, according to a study led by Cedars-Sinai investigators. The work, published in the peer-reviewed journal Nature, is the first to illuminate the neurological processes known as abstraction and inference in the human brain.

“Abstraction allows us to ignore irrelevant details and focus on the information we need in order to act, and inference is the use of knowledge to make educated guesses about the world around us,” said Ueli Rutishauser, PhD, professor and Board of Governors Chair in Neurosciences at Cedars-Sinai and co-corresponding author of the study. “Both are important parts of cognition and learning.”

Humans often use these two cognitive processes together to rapidly learn about and act appropriately in new environments. One example of this is an American driver who rents a car in London for the first time.

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Why everything in the universe has a pattern which can be identified and understood to determine outcomes, properties, effects of almost everything. I am saying that couldn’t the universe be like patternless, non-deterministic and chaotic. For example why the gravitational force between any two objects has a pattern which always obeys universal law of gravitation and can be predetermined. Couldn’t be the gravitational force between any two given objects would have no pattern and would be completely random and non-deterministic. Is this property of universe in which everything has a pattern is a complete matter of chance or it is a property of even something fundamental.

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Deep down, the particles and forces of the universe are a manifestation of exquisite geometry.

By A. Garrett Lisi & James Owen Weatherall

Modern physics began with a sweeping unification: in 1687 Isaac Newton showed that the existing jumble of disparate theories describing everything from planetary motion to tides to pendulums were all aspects of a universal law of gravitation. Unification has played a central role in physics ever since. In the middle of the 19th century James Clerk Maxwell found that electricity and magnetism were two facets of electromagnetism. One hundred years later electromagnetism was unified with the weak nuclear force governing radioactivity, in what physicists call the electroweak theory.

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“This is one of the only triple systems where we can tell a story this detailed about how it evolved,” said Dr. Emily Leiner.

What can fast-spinning stars known as “blue lurkers” teach us about star formation and evolution? This is what a recent study being presented at the 245th American Astronomical Society meeting hopes to address as a team of researchers investigated the potential processes responsible for how an unusually fast-spinning blue lurker-white dwarf star within the open star cluster M67 could have evolved into what we see today. This study has the potential to help researchers better understand the formation and evolution of stars throughout the cosmos and what mysterious behavior they can exhibit.

Located approximately 2,800 light-years from Earth, M67 is estimated to be between 3.2 and 5 billion years old. While the exact number of stars within M67 remains up for debate, astronomers used NASA’s Hubble Space Telescope to identify this blue lurker as being part of a triple star system with the appearance of our Sun. However, it’s the unique spin rate of this star that grabbed the attention of astronomers, who postulate that it gathered material from one of the two other stars, resulting in a spin rate of four days. For context, Sun-like stars typically take approximately 30 days to complete one orbit.

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