We explore numerically the complex dynamics of multilayer networks (consisting of three and one hundred layers) of cubic maps in the presence of noise-modulated interlayer coupling (multiplexing noise). The coupling strength is defined by independent discrete-time sources of color Gaussian noise. Uncoupled layers can demonstrate different complex structures, such as double-well chimeras, coherent and spatially incoherent regimes. Regions of partial synchronization of these structures are identified in the presence of multiplexing noise. We elucidate how synchronization of a three-layer network depends on the initially observed structures in the layers and construct synchronization regions in the plane of multiplexing noise parameters “noise spectrum width – noise intensity”
Category: mapping
The default mode network (DMN) is a set of interconnected brain regions known to be most active when humans are awake but not engaged in physical activities, such as relaxing, resting or daydreaming. This brain network has been found to support a variety of mental functions, including introspection, memories of past experiences and the ability to understand others (i.e., social cognitions).
The DMN includes four main brain regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), the angular gyrus and the hippocampus. While several studies have explored the function of this network, its anatomical structure and contribution to information processing are not fully understood.
Researchers at McGill University, Forschungszentrum Jülich and other institutes recently carried out a study aimed at better understanding the anatomy of the DMN, specifically examining the organization of neurons in the tissue of its connected brain regions, which is known as cytoarchitecture. Their findings, published in Nature Neuroscience, offer new indications that the DMN has a widespread influence on the human brain and its associated cognitive (i.e., mental) functions.
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Hello and welcome! My name is Anton and in this video, we will talk about the discovery of the most massive superstructure in the nearby universe — Quipu.
https://arxiv.org/abs/2501.19236
Bohringer et al., Astronomy and Astrophysics, 2025
https://en.wikipedia.org/wiki/Sachs%E2%80%93Wolfe_effect.
Similar videos:
https://youtu.be/wp8zHG1g7bc.
#quipu #superstructure #cosmos.
0:00 Largest superstructure in the universe — Quipu.
0:45 Laniakea discovery of 2014
1:25 Shapley concentration.
2:35 Cosmological issues: Hubble Tension and S8 tension.
3:45 New study mapping galaxies and the discovery.
5:15 Additional findings and implications.
6:25 What is this though?
7:20 Confirming predictions and how this was found.
8:40 What’s next?
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Caption: “I really like to do research because every day you have a hypothesis, you have a design, and you make it happen,” says MIT Associate Professor Xiao Wang.
In today’s AI news, Google launched its much-anticipated new flagship AI model, Gemini 2.0 Pro Experimental, on Wednesday. The announcement was part of a series of other AI model releases. The company is also making its reasoning model, Gemini 2.0 Flash Thinking, available in the Gemini app.
In other advancements, LinkedIn is testing a new job-hunting tool that uses a custom large language model to comb through huge quantities of data to help people find prospective roles. The company believes that artificial intelligence will help users unearth new roles they might have missed in the typical search process.
S Deep Research feature, which can autonomously browse the web and create research reports. ‘ + s up from hitting $50 million ARR, or the yearly value of last month s case for why they are the best positioned to take over TikTok And, in this episode, a16z Partner Marc Andrusko chats with Mastercard’s Chief AI and Data Officer Greg Ulrich about Mastercard’s long history of using AI, the opportunities (and potential risks) associated with integrating generative AI into fraud detection, determining what tech to employ based on use cases, and the best advice he’s ever gotten.
Then, power your AI transformation with an insightful keynote from Scott Guthrie, Executive Vice President, Cloud + AI Group at Microsoft, and other industry experts. Watch this keynote presentation from NYC stop on Microsoft’s AI Tour.
We close out with this insightful discussion with Malcolm Gladwell and Ric Lewis, SVP of Infrastructure at IBM. Learn how hardware capabilities enable the matrix math behind large language models and how AI is transforming industries—from banking to your local coffee shop.
Three months after its launch from NASA’s Kennedy Space Center in Florida, the agency’s Europa Clipper has another 1.6 billion miles (2.6 billion kilometers) to go before it reaches Jupiter’s orbit in 2030 to take close-up images of the icy moon Europa with science cameras.
Meanwhile, a set of cameras serving a different purpose is snapping photos in the space between Earth and Jupiter. Called star trackers, the two imagers look for stars and use them like a compass to help mission controllers know the exact orientation of the spacecraft—information critical for pointing telecommunications antennas toward Earth and sending data back and forth smoothly.
In early December, the pair of star trackers (formally known as the stellar reference units) captured and transmitted Europa Clipper’s first imagery of space. The picture, composed of three shots, shows tiny pinpricks of light from stars 150 to 300 light-years away. The starfield represents only about 0.1% of the full sky around the spacecraft, but by mapping the stars in just that small slice of sky, the orbiter is able to determine where it is pointed and orient itself correctly.
Large-angle Lorentz Four-dimensional scanning transmission electron microscopy for simultaneous local magnetization, strain and structure mapping
Posted in mapping, nanotechnology | Leave a Comment on Large-angle Lorentz Four-dimensional scanning transmission electron microscopy for simultaneous local magnetization, strain and structure mapping
The authors present an approach to simultaneously map local magnetization, strain, atomic structure at nanoscale. It provides direct visualization of strainmagnetic coupling in ferromagnetic materials, opening avenues for studying nanomagnetism.
A new way to study 3D maps of galaxies in the cosmos without compressing the data is revealing new information about the dark universe.
SPHEREx could, though (in a way).
To be fair, SPHEREx won’t rival the JWST’s ability to observe highly localized regions of the universe that are confined to the infrared section of the electromagnetic spectrum. However, unlike the JWST, it is an all-sky survey. Whereas the $10 billion JWST is great at observing things like specific nebulas and relatively narrow but tremendously dimensional deep fields, SPHEREx is intended to image the entire sky as seen from Earth.
“We are literally mapping the entire celestial sky in 102 infrared colors for the first time in humanity’s history, and we will see that every six months,” said Nicky Fox, associate administrator for NASA’s Science Mission Directorate. “This has not been done before on this level of color resolution for our old sky maps.”
Summary: New research highlights a functional hierarchy in the brain’s processing of space and time. In posterior areas, like the occipital cortex, space and time are tightly linked and processed by the same neurons.
In anterior regions, such as the frontal cortex, space and time are processed independently, with distinct neural populations forming “time maps” for specific durations. Intermediate regions, like the parietal cortex, display mixed processing mechanisms, bridging spatial and temporal integration.
This study offers fresh insights into how the brain integrates two fundamental dimensions of human experience and reveals the unique coding strategies across cortical regions.