Results 141 to 150 of about 1,412,360 (277)

Biological Network Inference With GRASP: A Bayesian Network Structure Learning Method Using Adaptive Sequential Monte Carlo. [PDF]

Front Genet, 2021
Yu K, Cui Z, Sui X, Qiu X, Zhang J.
europepmc   +1 more source

Nanoscale Optical Inhomogeneities From Compositional Segregation Within Individual GaN‐on‐Si Quantum Wells

Advanced Science, EarlyView.
This work visualizes local variations in luminescence and relates them to nanoscale chemical inhomogeneities in single InxGa1−xN quantum wells. We demonstrate that the elemental segregation is only inherent to quantum wells with high indium content. Density functional theory shows this to be the result of strain‐induced phase stabilization, explaining ...
Jing‐Yang Chung, Tara P. Mishra, Zackaria Mahfoud, Thomas E. Gage, Jianguo Wen, Katherine P. Rice, Isabelle Martin, Li Zhang, Govindo J. Syaranamual, Stephen J. Pennycook, Silvija Gradečak, Pieremanuele Canepa, Michel Bosman   +12 more
wiley   +1 more source

Computationally efficient application of Sequential Monte Carlo expectation maximization to confined single particle tracking. [PDF]

Control Conf ECC Eur, 2021
Lin Y, Andersson SB.
europepmc   +1 more source

Valuation of R&D Sequential Exchange Options using Monte Carlo approach [PDF]

This article describes a methodology for evaluating R&D investment projects using Monte Carlomethods. R&D projects generally involves multiple phases with or without overlapping. R&D investments are made often in a phased manner, with the commencement of
Flavia Cortelezzi, Giovanni Villani
core  

Multiscale Modelling of the Electrocatalysis of Microenzymes: Insights Into the Performance of Microperoxidase at an Aqueous/Graphene Interface and Their Exploitation to Improve Performance

Advanced Science, EarlyView.
A novel multiscale MD/DFT framework to elucidate microenzyme adsorption and electron transfer is reported. This method reveals distinct configurations for microperoxidase‐11 on graphene and those best suited for electron transfer. Rate constants align with the limited experimental data, establishing this framework as a tool for optimizing microenzyme ...
Milan Mijajlovic, Cheng Hu, Yuhui Sun, Matthew J. Penna, Meisam V. Kiamahalleh, Wenrong Yang, Mark J. Biggs   +6 more
wiley   +1 more source

Enhanced Antibacterial Properties of Lyotropic Liquid Crystalline Nanoparticles via Curvature Modulation

Advanced Science, EarlyView.
Lipid nanostructured particles with increasing negative Gaussian curvature progress from vesicles to P‐cubosomes and D‐cubosomes. This curvature hierarchy enhances interaction with bacterial membranes, promotes membrane remodeling and leakage, and potentiates daptomycin activity against MRSA.
Xiangfeng Lai, Shuhong Wang, Chenguang Ding, Xenia Kostoulias, Anton P. Le Brun, Hsien‐Yi Hsu, Jhih‐Hang Jiang, Yajun Wang, Richard A. Strugnell, Anton Y. Peleg, Hsin‐Hui Shen   +10 more
wiley   +1 more source

Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations

Advanced Science, EarlyView.
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford, Matthew Tamasi, Elena Di Mare, Adam J. Gormley   +3 more
wiley   +1 more source

Cutting-Edge Monte Carlo Framework: Novel “Walk on Equations” Algorithm for Linear Algebraic Systems

Axioms
In this paper, we introduce the “Walk on Equations” (WE) Monte Carlo algorithm, a novel approach for solving linear algebraic systems. This algorithm shares similarities with the recently developed WE MC method by Ivan Dimov, Sylvain Maire, and Jean ...
Venelin Todorov, Ivan Dimov
doaj   +1 more source

Sequential monte carlo samplers

, 2002
This paper shows how one can use Sequential Monte Carlo methods to perform what is typically done using Markov chain Monte Carlo methods. This leads to a general class of principled integration and genetic type optimization methods based on interacting particle systems.
Del Moral, Pierre, Doucet, Arnaud
openaire   +2 more sources

Cation Diffusion‐Mediated Displaced Reaction‐Transformation in Green Steelmaking

Advanced Science, EarlyView.
The removal of O lattice atoms by environmental H2 at the surface of Fe3O4 results in Fe enrichment, driving the inward diffusion of Fe cations into the bulk. Through hopping between unoccupied and initially occupied sites, cation diffusion triggers a spatially displaced reaction‐transformation and drives subsequent dynamic phase transformations and ...
Guangyi Guo, Paul Paciok, Baptiste Bienvenu, Longqi Bai, Barak Ratzker, Marc Heggen, Xuyang Zhou, Dierk Raabe   +7 more
wiley   +1 more source