Results 41 to 50 of about 60,582 (310)
Markov and Semi-Markov Chains, Processes, Systems, and Emerging Related Fields
Probability resembles the ancient Roman God Janus since, like Janus, probability also has a face with two different sides, which correspond to the metaphorical gateways and transitions between the past and the future [...]
P.-C.G. Vassiliou, Andreas C. Georgiou
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Let {Xi, i _? 1} denote a sequence of variables that take values in {0, 1} and suppose that the sequence forms a Markov chain with transition matrix P and with initial distribution (q, p) = (P(X1 = 0), P(X1 = 1)). Several authors have studied the quantities Sn, Y (r) and AR(n), where Sn = ?n i=1 Xi denotes the number of successes, where Y (r) denotes ...
Omey, Edward, Van Gulck, Stefan
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Plasmonic Enhancement of Fluorescence and Protein Dynamics in Living Mammalian Cells
This study demonstrates plasmonic enhancement of the function of fluorescent voltage sensing proteins (genetically encoded voltage indicators, (GEVIs), QuasAr6) in live mammalian cells. Coupling to plasmonic nanoparticles does not just increase fluorescence, but influences the protein photocycle, creating a hybrid sensor with its response speed to ...
Marco Locarno +16 more
wiley +1 more source
An estimate for an expectation of the simultaneous renewal for time-inhomogeneous Markov chains
In this paper, we consider two time-inhomogeneous Markov chains ${X_{t}^{(l)}}$, $l\in \{1,2\}$, with discrete time on a general state space. We assume the existence of some renewal set C and investigate the time of simultaneous renewal, that is, the ...
Vitaliy Golomoziy
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The Importance Markov chain is a novel algorithm bridging the gap between rejection sampling and importance sampling, moving from one to the other through a tuning parameter. Based on a modified sample of an instrumental Markov chain targeting an instrumental distribution (typically via a MCMC kernel), the Importance Markov chain produces an extended ...
Andral, Charly +3 more
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Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
20 pages, 4 figures. The new version introduces and studies toggle Markov chains and proves cutoff for rowmotion Markov chains of Boolean ...
Colin Defant, Rupert Li, Evita Nestoridi
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Segregating Markov Chains [PDF]
Dealing with finite Markov chains in discrete time, the focus often lies on convergence behavior and one tries to make different copies of the chain meet as fast as possible and then stick together. There is, however, a very peculiar kind of discrete finite Markov chain, for which two copies started in different states can be coupled to meet almost ...
Timo Hirscher, Anders Martinsson
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Super‐Resolution Ultrasound Based Cell Tracking With Polymeric Nanobubbles
This study presents a super‐resolution ultrasound platform for tracking cells in vivo. Biocompatible polymeric nanobubbles are used as highly echogenic intracellular labels. Following the injection of cells and microbubbles, ultrasound localization microscopy (ULM) can dynamically match the microvascular architecture and individual cell trajectories ...
Junlin Chen +19 more
wiley +1 more source
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao +4 more
wiley +1 more source

