Results 61 to 70 of about 460,152 (328)

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

open access: yesMolecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes   +20 more
wiley   +1 more source

Stochastic Methods for Analysis of Complex Hardware-Software Systems

open access: yesТруды Института системного программирования РАН, 2018
In this paper we consider Markov analysis of models of complex software and hardware systems. A Markov analysis tool can be used during verification processes of models of avionics systems.
A. A. Karnov, S. V. Zelenov
doaj   +1 more source

Markov chain analysis of regional climates [PDF]

open access: yesNonlinear Processes in Geophysics, 2010
We present a novel method for regional climate classification that is based on coarse-grained categorical representations of multivariate climate anomalies and a subsequent Markov chain analysis.
S. Mieruch   +4 more
doaj   +1 more source

Distributed Averaging via Lifted Markov Chains

open access: yes, 2009
Motivated by applications of distributed linear estimation, distributed control and distributed optimization, we consider the question of designing linear iterative algorithms for computing the average of numbers in a network.
Jung, Kyomin   +2 more
core   +3 more sources

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

open access: yesAdvanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

STABILITY OF LINEAR SYSTEMS WITH MARKOVIAN JUMPS

open access: yesSelecciones Matemáticas, 2016
In this work we will analyze the stability of linear systems governed by a Markov chain, this family is known in the specialized literature as linear systems with Markov jumps or by its acronyms in English MJLS as it is denoted in [1].
Jorge Enrique Mayta Guillermo
doaj   +1 more source

Method for Determining the Number of States of the Markov Model of Damage Accumulation in Predicting the Technical Condition of a Fiber-Optic Cable

open access: yesProceedings of the International Conference on Applied Innovations in IT, 2021
Estimation of the residual service life of operating fiber-optic cables is an urgent t ask. Usually this problem is solved based on the use of the Markov chain model. However, due to the nonlinear dependence of the probability of rejection on the rate of
Elena Ionikova   +2 more
doaj   +1 more source

Interfacial Yield Stress Response in Synthetic Mucin Solutions

open access: yesAdvanced Materials Interfaces, EarlyView.
The solution rheology of novel synthetic mucins mimicking natural mucin domains is studied. Like many natural mucin solutions, apparent solid‐like rheology is seen. However, no bulk structural features are found to explain it. Interfacial rheology and robust modelling reveal that this arises from molecular associations at the air–water interface ...
Sumit Sunil Kumar   +7 more
wiley   +1 more source

Convergence in distribution for filtering processes associated to Hidden Markov Models with densities

open access: yes, 2013
Consider a filtering process associated to a hidden Markov model with densities for which both the state space and the observation space are complete, separable, metric spaces.
Kaijser, Thomas
core   +1 more source

Optimizing Metamaterial Inverse Design with 3D Conditional Diffusion Model and Data Augmentation

open access: yesAdvanced Materials Technologies, EarlyView.
A generative AI model, the 3D conditional diffusion model (3D‐CDM), is introduced to enhance the inverse design of voxel‐based metamaterials. A data augmentation technique based on topological perturbation expands the dataset, further improving generation quality and accuracy.
Xiaoyang Zheng   +2 more
wiley   +1 more source

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