The role of turbulence in high-mass star formation: Subsonic and transonic turbulence are ubiquitously found at early stages

Posted by dbos Peking

Kavli Affiliate: Ke Wang | First 5 Authors: Chao Wang, Ke Wang, Feng-Wei Xu, Patricio Sanhueza, Hauyu Baobab Liu | Summary: Context. Traditionally, supersonic turbulence is considered to be one of the most likely mechanisms to slow down the gravitational collapse in dense clumps, thereby enabling the formation of massive stars. However, several recent studies […]


Continue.. The role of turbulence in high-mass star formation: Subsonic and transonic turbulence are ubiquitously found at early stages

Experimental demonstration of picometer level signal extraction with time-delay interferometry technique

Posted by dbos Cornell

Kavli Affiliate: Dan Luo | First 5 Authors: Mingyang Xu, Yujie Tan, Yurong Liang, Jiawen Zhi, Xiaoyang Guo | Summary: In this work, we have built an experimental setup to simulate the clock noise transmission with two spacecrafts and two optical links, and further demonstrated the extraction of picometer level signal drowned by the large […]


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Large-scale Foundation Models and Generative AI for BigData Neuroscience

Posted by dbos Peking

Kavli Affiliate: Ran Wang | First 5 Authors: Ran Wang, Zhe Sage Chen, , , | Summary: Recent advances in machine learning have made revolutionary breakthroughs in computer games, image and natural language understanding, and scientific discovery. Foundation models and large-scale language models (LLMs) have recently achieved human-like intelligence thanks to BigData. With the help […]


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Masked Space-Time Hash Encoding for Efficient Dynamic Scene Reconstruction

Posted by dbos Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Zilong Chen, Guokang Wang, Yafei Song, Huaping Liu | Summary: In this paper, we propose the Masked Space-Time Hash encoding (MSTH), a novel method for efficiently reconstructing dynamic 3D scenes from multi-view or monocular videos. Based on the observation that dynamic scenes often contain substantial […]


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Comprehensive Bayesian analysis of FRB-like bursts from SGR 1935+2154 observed by CHIME/FRB

Posted by dbos MIT

Kavli Affiliate: Kiyoshi W. Masui | First 5 Authors: Utkarsh Giri, Bridget C. Andersen, Pragya Chawla, Alice P. Curtin, Emmanuel Fonseca | Summary: The bright millisecond-duration radio burst from the Galactic magnetar SGR 1935+2154 in 2020 April was a landmark event, demonstrating that at least some fast radio burst (FRB) sources could be magnetars. The […]


Continue.. Comprehensive Bayesian analysis of FRB-like bursts from SGR 1935+2154 observed by CHIME/FRB

A geometrical model of cell fate specification in the mouse blastocyst

Posted by dbos Rockefeller

Kavli Affiliate: Eric D. Siggia | Authors: Archishman Raju and Eric Siggia | Summary: The lineage decision that generates the epiblast and primitive endoderm from the inner cell mass (ICM) is a paradigm for cell fate specification. Recent mathematics has formalized Waddington’s landscape metaphor and proven that lineage decisions in detailed gene network models must […]


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DyExplainer: Explainable Dynamic Graph Neural Networks

Posted by dbos Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang | Summary: Graph Neural Networks (GNNs) resurge as a trending research subject owing to their impressive ability to capture representations from graph-structured data. However, the black-box nature of GNNs presents a significant challenge in terms of comprehending […]


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Linear magneto-conductivity as a DC probe of time-reversal symmetry breaking

Posted by dbos Berkeley

Kavli Affiliate: Joel E. Moore | First 5 Authors: Veronika Sunko, Chunxiao Liu, Marc Vila, Ilyoun Na, Yuchen Tang | Summary: Several optical experiments have shown that in magnetic materials the principal axes of response tensors can rotate in a magnetic field. Here we offer a microscopic explanation of this effect, and propose a closely […]


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An Iteratively Decoupled Algorithm for Multiple-Network Poroelastic Model with Applications in Brain Edema Simulations

Posted by klaurent Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Mingchao Cai, Mingchao Cai, , , | Summary: In this work, we present an iteratively decoupled algorithm for solving the quasi-static multiple-network poroelastic model. Our approach employs a total-pressure-based formulation with solid displacement, total pressure, and network pressures as primary unknowns. This reformulation decomposes the original problem […]


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An Iteratively Decoupled Algorithm for Multiple-Network Poroelastic Model with Applications in Brain Flow Simulations

Posted by klaurent Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Mingchao Cai, Meng Lei, Jingzhi Li, Jiaao Sun, Feng Wang | Summary: In this work, we present an iteratively decoupled algorithm for solving the quasi-static multiple-network poroelastic model. Our approach employs a total-pressure-based formulation with solid displacement, total pressure, and network pressures as primary unknowns. This reformulation […]


Continue.. An Iteratively Decoupled Algorithm for Multiple-Network Poroelastic Model with Applications in Brain Flow Simulations