Results 61 to 70 of about 88,706 (269)

Three-dimensional earthward fast flow in the near-Earth plasma sheet in a sheared field: comparisons between simulations and observations [PDF]

open access: yesAnnales Geophysicae, 2009
Three-dimensional configuration of earthward fast flow in the near-Earth plasma sheet is studied using three-dimensional magnetohydrodynamics (MHD) simulations on the basis of the spontaneous fast reconnection model.
K. Kondoh, M. Ugai
doaj   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

open access: yesAdvanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu   +8 more
wiley   +1 more source

Cosmic Vine: High abundance of massive galaxies and dark matter halos in a forming cluster at z = 3.44

open access: yesAstronomy & Astrophysics
The Cosmic Vine is a massive protocluster at z = 3.44 in the JWST CEERS field, offering an ideal laboratory for studying the early phases of cluster formation.
Sillassen Nikolaj B.   +12 more
doaj   +1 more source

The STELLA Robotic Observatory on Tenerife

open access: yesAdvances in Astronomy, 2010
The Astrophysical Institute Potsdam (AIP) and the Instituto de Astrofísica de Canarias (IAC) inaugurated the robotic telescopes STELLA-I and STELLA-II (STELLar Activity) on Tenerife on May 18, 2006.
Klaus G. Strassmeier   +11 more
doaj   +1 more source

Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning

open access: yesAdvanced Science, EarlyView.
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen   +6 more
wiley   +1 more source

Integrated geophysical‐petrological modeling of lithosphere‐asthenosphere boundary in central Tibet using electromagnetic and seismic data

open access: yesGeochemistry, Geophysics, Geosystems, 2014
We undertake a petrologically driven approach to jointly model magnetotelluric (MT) and seismic surface wave dispersion (SW) data from central Tibet, constrained by topographic height. The approach derives realistic temperature and pressure distributions
Jan Vozar   +6 more
doaj   +1 more source

stMixer for Scalable Mosaic Integration and Label Transfer in Spatial Histology and Multi‐Omics

open access: yesAdvanced Science, EarlyView.
stMixer is an unsupervised framework for scalable integration and label transfer across spatial histology and multi‐slide multi‐omics data with incomplete modality overlap. It combines self‐looped cross‐attention, multimodal metric learning, and graph‐guided cluster voting to align heterogeneous sections, correct batch effects, and propagate ...
Qixing Yang   +3 more
wiley   +1 more source

Cosmic Topology

open access: yesScholarpedia, 2015
Cosmic Topology is the name given to the study of the overall shape of the universe, which involves both global topological features and more local geometrical properties such as curvature. Whether space is finite or infinite, simply-connected or multi-connected like a torus, smaller or greater than the portion of the universe that we can directly ...
openaire   +1 more source

Cosmic shells [PDF]

open access: yesPhysical Review D, 2002
When a potential for a scalar field has two local minima there arise spherical shell-type solutions of the classical field equations due to gravitational attraction. We establish such solutions numerically in a space which is asymptotically de Sitter.
Hosotani, Y.   +3 more
openaire   +2 more sources

Accurately Deciphering Tissue Heterogeneity From Spatial Multi‐Modal and Multi‐Omics With STransformer

open access: yesAdvanced Science, EarlyView.
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li   +9 more
wiley   +1 more source

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