Results 161 to 170 of about 63,806 (262)

Topological strings

Nuclear Physics B, 1989
David Montano, Jacob Sonnenschein
openaire   +1 more source

Investigating Phase Separation in Genome Folding via Multiscale Computational Modeling

Advanced Science, Volume 13, Issue 24, 27 April 2026.
Phase separation is emerging as a multiscale organizing principle of genome folding across scales, from nucleosomes and transcriptional condensates to chromatin domains and nuclear compartments. By integrating physics‐based simulations with data‐driven inference, computational modeling now links molecular interactions to nuclear architecture and points
Jiahu Tang, Cibo Feng, Haibin Su, Xiakun Chu   +3 more
wiley   +1 more source

Les Houches lectures on matrix models and topological strings

, 2004
In these lecture notes for the Les Houches School on Applications of Random Matrices in Physics we give an introduction to the connections between matrix models and topological strings.
Marino, Marcos
core  

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes

Advanced Intelligent Systems, Volume 8, Issue 4, April 2026.
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera, Gaurav Duggal, Rolf Müller   +2 more
wiley   +1 more source

Borel singularities and Stokes constants of the topological string free energy on one-parameter Calabi-Yau threefolds

Journal of High Energy Physics
We study the Borel plane of the topological string free energy on all hypergeometric one-parameter Calabi-Yau models close to singular points in moduli space, focusing on the location of Borel singularities and the value of the associated Stokes ...
Simon Douaud, Amir-Kian Kashani-Poor
doaj   +1 more source

Associations between sleep disturbance and cerebrospinal fluid Aβ, and shared proteomic signatures in Alzheimer's disease

Alzheimer's &Dementia, Volume 22, Issue 4, April 2026.
Abstract INTRODUCTION Sleep disturbance is increasingly recognized as a risk factor for Alzheimer's disease (AD), but longitudinal clinical evidence linking sleep behaviors to cerebrospinal fluid (CSF) amyloid beta (Aβ) dynamics and related proteomic signatures remains limited.
Tianbai Li, Meichen Liu, Peng Zhang, Song Li, Tao Qiu, Xinhui Qiu, Bo Sun, Huaibin Cai, Cong Liu, Junliang Yuan, Weidong Le, Alzheimer's Disease Neuroimaging Initiative   +11 more
wiley   +1 more source

Accelerated epigenetic aging as a modifier of homocysteine‐associated cognitive decline: Findings from NHANES

Alzheimer's &Dementia, Volume 22, Issue 4, April 2026.
Abstract INTRODUCTION Hyperhomocysteinemia represents a modifiable risk factor for cognitive decline and dementia, yet the role of epigenetic aging mechanisms in mediating this association remain poorly characterized, limiting development of targeted interventions.
Haoxuan Li, Yuhan Chen, Zhe Wang, Yankun Wang, Ran Bi, Jiayu Hou, Huan Chen, Zixuan Zhang, Zhenhao Guo, Zhuo Chen, Huixian Cui, Sha Li   +11 more
wiley   +1 more source

Emergence in string theory and Fermi gases

Journal of High Energy Physics
The Emergence Proposal suggests that some Swampland criteria, in particular on large field distances, are a consequence of the emergent nature of dynamics for fields in the infrared.
Jarod Hattab, Eran Palti
doaj   +1 more source

Mechanism‐Aware Deep Learning Maps the Redox Landscape of Cancer‐Relevant Antioxidants

Chemistry–Methods, Volume 6, Issue 4, April 2026.
A mechanism‐aware deep learning framework links chemical structure to redox biology, enabling pathway‐specific prediction of antioxidant mechanisms across six core reactive oxygen species‐regulatory systems and outperforming structure‐only baseline by learning biologically grounded rather than purely chemical similarity rules.
Shiva Satija, Saveena Solanki, Gaurav Ahuja   +2 more
wiley   +1 more source