Results 31 to 40 of about 29,538 (243)

Periodic Averaging Principle for Neutral Stochastic Delay Differential Equations with Impulses

open access: yesComplexity, 2020
In this paper, we study the periodic averaging principle for neutral stochastic delay differential equations with impulses under non-Lipschitz condition.
Peiguang Wang, Yan Xu
doaj   +1 more source

Three phosphatase families form a community: The phosphohydrolases that act upon inositol pyrophosphates

open access: yesFEBS Letters, EarlyView.
Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley   +1 more source

Modified Equations for Stochastic Differential Equations

open access: yesBIT Numerical Mathematics, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +3 more sources

PAK1 activation drives divergent resistance mechanisms to aromatase inhibition and tamoxifen in a luminal: A breast cancer model

open access: yesMolecular Oncology, EarlyView.
Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller   +10 more
wiley   +1 more source

Stochastic parareal algorithm for stochastic differential equations

open access: yesNumerical Algorithms
This paper analyzes the SParareal algorithm for stochastic differential equations (SDEs). Compared to the classical Parareal algorithm, the SParareal algorithm accelerates convergence by introducing stochastic perturbations, achieving linear convergence over unbounded time intervals.
Huanxin Wang   +3 more
openaire   +2 more sources

Algorithmic Solution of Stochastic Differential Equations [PDF]

open access: yesAlgorithms, 2010
This brief note presents an algorithm to solve ordinary stochastic differential equations (SDEs). The algorithm is based on the joint solution of a system of two partial differential equations and provides strong solutions for finite-dimensional systems of SDEs driven by standard Wiener processes and with adapted initial data.
openaire   +3 more sources

Small RNA pathways in mammalian oocytes

open access: yesFEBS Open Bio, EarlyView.
Three distinct small RNA pathways operate in mammalian oocytes: RNAi interference (RNAi), the microRNA (miRNA) pathway, and the PIWI‐associated RNA (piRNA) pathway. These pathways use small RNAs to guide sequence‐specific repression and contribute to oocyte biology by targeting genes and mobile elements or appear insignificant since different ...
Petr Svoboda, Josef Pasulka
wiley   +1 more source

The Optimal Discretization of Stochastic Differential Equations

open access: yesJournal of Complexity, 2001
The paper studies discrete time pathwise approximations of stochastic differential equations. An adaptive discretization is introduced that reflects local properties of the simulated trajectory. The corresponding error is shown to converge to zero in average with a certain rate.
Norbert Hofmann   +2 more
openaire   +1 more source

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane   +3 more
wiley   +1 more source

Bisimulation Relations Between Automata, Stochastic Differential Equations and Petri Nets [PDF]

open access: yesElectronic Proceedings in Theoretical Computer Science, 2010
Two formal stochastic models are said to be bisimilar if their solutions as a stochastic process are probabilistically equivalent. Bisimilarity between two stochastic model formalisms means that the strengths of one stochastic model formalism can be used
Mariken H.C. Everdij, Henk A.P. Blom
doaj   +1 more source

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