Results 31 to 40 of about 47,776 (252)

Crossed source-detector geometry for a novel spray diagnostic: Monte Carlo simulation and analytical results [PDF]

, 2005
Sprays and other industrially relevant turbid media can be quantitatively characterized by light scattering. However, current optical diagnostic techniques generate errors in the intermediate scattering regime where the average number of light ...
Churmakov, D. Y., Meglinski, I. V., Jermy, Mark C., Romanov, V. P., Berrocal, Edouard   +4 more
core  

Stem Cell Differentiation Disperses Transcriptional Clusters via a Conserved Surface‐Condensate Trajectory

Advanced Science, EarlyView.
Stem cell differentiation follows a conserved surface condensate trajectory: H3K27ac super enhancers nucleate large RNA polymerase II clusters that grow and unfold before transcriptional activity disperses them. This work reveals how biophysical forces at enhancer surfaces dynamically build and dismantle stem cell transcription hubs, reshaping cell ...
Tim Klingberg, Irina Wachter, Agnieszka Pancholi, Matthias Akyel, Yomna Gohar, Priya Kumar, Ana Miguel Fernandes, Yuzhi Bao, Alica Schmidt‐Heydt, Marcel Piepers, Alicia Günthel, Marcel Sobucki, Elisa Kämmer, Süheyla Eroğlu‐Kayıkçı, Stephan Allgeier, Sylvia Erhardt, Vasily Zaburdaev, Carmelo Ferrai, Lennart Hilbert   +18 more
wiley   +1 more source

Monte Carlo methods

, 2018
Monte Carlo methods are those designed to obtain numerical answers with the use of random numbers . This chapter discusses random engines, which provide a pseudo-random pattern of bits, and their use in for sampling a variety of nonuniform distributions,
Joseph F. Boudreau, Eric S. Swanson
core   +1 more source

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

Advanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi, Minying Low, Peng Xiu, Kresten Lindorff‐Larsen, Yong Wang   +4 more
wiley   +1 more source

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy

Advanced Intelligent Discovery, EarlyView.
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang, Andrew Bai, Alexandra Bermudez, Yunqi Hong, Zoe Latham, Iris Sloan, Michael Liu, Vishrut Goyal, Cho‐Jui Hsieh, Neil Y. C. Lin   +9 more
wiley   +1 more source

A‐optimal model‐based design of experiments for processes with uncertain inputs

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Model‐based design of experiments (MBDoE) techniques are tools for selecting experimental conditions that enable accurate parameter estimation for mechanistic models. Most MBDoE approaches assume that the selected experimental conditions will be implemented perfectly, without uncertainties in the independent variables.
Bright Ofori, Iman Moshiritabrizi, Anh‐Duong Vo, Kimberley B. McAuley   +3 more
wiley   +1 more source

High performance FPGA implementation of the mersenne twister

, 2008
Efficient generation of random and pseudorandom sequences is of great importance to a number of applications [4]. In this paper, an efficient implementation of the Mersenne Twister is presented. The proposed architecture has the smallest footprint of all
Shrutisagar Chandrasekaran, Amira, A, Chandrasekaran, S, Abbes Amira   +3 more
core   +1 more source