Watch more videos on complexity and emergence: https://bit.ly/3TxyQBmThe world works at different levels—fundamental physics, physics, chemistry, biology, ps…
The recent development of AI presents challenges, but also great opportunities. In this clip I will discuss the topiv in general.
… whar hasn’t worked perfectly is AI sound post-production, I apologize smile
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The total solar eclipse isn’t the only reason to keep your eyes to the sky this year. For the first time in 80 years, a star system 3,000 light years away will be visible to the naked eye thanks to a once-in-a-lifetime nova outburst.
NASA announced that the nova, which will create a “new” star in the night sky, will light up the night sky some time between now and September and be as bright as the North Star. One of only five recurring novae in our galaxy, it will be visible for a week before it fades back down.
Jonathan Blazek, an assistant professor of physics at Northeastern University, says this is an exciting moment for amateur astronomers and astrophysicists alike. It’s not technically a new star, just a star that is now bright enough for people to see more clearly, Blazek says, but it provides an opportunity to see and understand the cosmos in a new way.
After three years of collecting scores of data on hundreds of stars, the ULLYSES (Ultraviolet Legacy Library of Young Stars as Essential Standards) survey conducted by NASA’s Hubble Space Telescope officially ended in December 2023, culminating in 220 total stars examined during the survey on data regarding their size, distance from Earth, temperature, chemical characteristics, and rotational speed. Additionally, ULYYSES also contains another 275 stars from the Hubble archive, providing researchers with several decades of new stellar data and holds the potential to help astronomers gain new insights into stellar formation and evolution throughout the universe.
Hubble image of a star-forming region known as the Tarantula Nebula, which contains massive, young blue stars, which was observed during the ULYYSES survey (top panel). Artist’s illustration of a cooler, redder, young star smaller than our Sun that is still gathering material from its planet-forming disk (bottom panel). (Credit: NASA, ESA, STScI, Francesco Paresce (INAF-IASF Bologna), Robert O’Connell (UVA), SOC-WFC3, ESO)
“I believe the ULLYSES project will be transformative, impacting overall astrophysics – from exoplanets, to the effects of massive stars on galaxy evolution, to understanding the earliest stages of the evolving universe,” said Dr. Julia Roman-Duval, who is Implementation Team Lead for ULLYSES and an Associate Astronomer at the Space Telescope Science Institute (STScI). “Aside from the specific goals of the program, the stellar data can also be used in fields of astrophysics in ways we can’t yet imagine.”
A new theoretical framework for plastic neural networks predicts dynamical regimes where synapses rather than neurons primarily drive the network’s behavior, leading to an alternative candidate mechanism for working memory in the brain.
The brain is an immense network of neurons, whose dynamics underlie its complex information processing capabilities. A neuronal network is often classed as a complex system, as it is composed of many constituents, neurons, that interact in a nonlinear fashion (Fig. 1). Yet, there is a striking difference between a neural network and the more traditional complex systems in physics, such as spin glasses: the strength of the interactions between neurons can change over time. This so-called synaptic plasticity is believed to play a pivotal role in learning. Now David Clark and Larry Abbott of Columbia University have derived a formalism that puts neurons and the connections that transmit their signals (synapses) on equal footing [1]. By studying the interacting dynamics of the two objects, the researchers take a step toward answering the question: Are neurons or synapses in control?
Clark and Abbott are the latest in a long line of researchers to use theoretical tools to study neuronal networks with and without plasticity [2, 3]. Past studies—without plasticity—have yielded important insights into the general principles governing the dynamics of these systems and their functions, such as classification capabilities [4], memory capacities [5, 6], and network trainability [7, 8]. These works studied how temporally fixed synaptic connectivity in a network shapes the collective activity of neurons. Adding plasticity to the system complicates the problem because then the activity of neurons can dynamically shape the synaptic connectivity [9, 10].
Our universe is getting bigger and bigger really fast — something all the theories about space agree on, but none of them can totally explain. Now, there’s a new idea in town: Maybe our universe is expanding because it keeps bumping into and soaking up “baby” universes.
When scientists look at the afterglow of the Big Bang, known as the cosmic microwave background, they see that our universe is swelling up quicker and quicker. To make sense of this, physicists use something called the Standard Cosmological Model, which says there’s this weird stuff called dark energy pushing the universe to expand.
A team from the Dalian Institute of Chemical Physics made a breakthrough in converting methane to formic acid using oxygen at room temperature through a high-pressure electro-Fenton process, achieving significantly higher efficiency and productivity than traditional methods.
Direct conversion of methane (CH4) and oxygen (O2) to value-added chemicals is important for natural gas industries. However, challenges remain due to the difficulty of O2 activation in forming active oxygen species for CH4 activation under mild conditions.
Recently, a research group led by Prof. Dehui Deng, Assoc. Prof. Xiaoju Cui and Liang Yu from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences (CAS) realized the electrochemical conversion of CH4 by O2 to formic acid (HCOOH) at room temperature. This study was published in the Journal of the American Chemical Society.
Birds flock. Locusts swarm. Fish school. Within assemblies of organisms that seem as though they could get chaotic, order somehow emerges. The collective behaviors of animals differ in their details from one species to another, but they largely adhere to principles of collective motion that physicists have worked out over centuries. Now, using technologies that only recently became available, researchers have been able to study these patterns of behavior more closely than ever before.
In this episode, the evolutionary ecologist Iain Couzin talks with co-host Steven Strogatz about how and why animals exhibit collective behaviors, flocking as a form of biological computation, and some of the hidden fitness advantages of living as part of a self-organized group rather than as an individual. They also discuss how an improved understanding of swarming pests such as locusts could help to protect global food security.
Listen on Apple Podcasts, Spotify, Google Podcasts, TuneIn or your favorite podcasting app, or you can stream it from Quanta.
The team of scientists set about investigating this by analyzing 59 early B-type blue supergiants located in the Large Magellanic Cloud, a satellite galaxy of the Milky Way, and creating novel stellar simulations.
“We simulated the mergers of evolved giant stars with their smaller stellar companions over a wide range of parameters, taking into account the interaction and mixing of the two stars during the merger,” study leader and IAC researcher Athira Menon said in a statement. “The newly born stars live as blue supergiants throughout the second-longest phase of a star’s life, when it burns helium in its core.”
The team’s findings suggest that blue supergiants slip into an evolutionary gap in conventional stellar physics — a phase of stellar evolution where astronomers would not expect to see stars. The question is, Can this explain the remarkable properties of blue supergiant stars? It seems the answer is yes.
