We quantify the level of stochasticity in the dynamics of two mutually coupled semiconductor lasers. Specifically, we concentrate on a regime in which the lasers synchronize their dynamics with a non-zero lag time, and the leader and laggard roles alternate irregularly between the lasers. We analyse this switching dynamics in terms of the number of forbidden patterns of the alternate time series. The results reveal that the system operates in a stochastic regime, with the level of stochasticity decreasing as the lasers are pumped further away from their lasing threshold. This behaviour is similar to that exhibited by a single semiconductor laser subject to external optical feedback, as its dynamics shifts from the regime of low-frequency fluctuations to coherence collapse.
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http://dx.doi.org/10.1098/rsta.2009.0241 | DOI Listing |
Transl Lung Cancer Res
December 2024
Penn State Cancer Institute, Penn State Health Milton S. Hershey Medical Center, Penn State College of Medicine, Penn State University, Hershey, PA, USA.
Background: Predictive biomarkers for immune checkpoint inhibitors (ICIs), e.g., programmed death ligand-1 (PD-L1) tumor proportional score (TPS), remain limited in clinical applications.
View Article and Find Full Text PDFCommun Biol
January 2025
Department of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA.
Gene expression is a dynamic and stochastic process characterized by transcriptional bursting followed by periods of silence. Single-cell RNA sequencing (scRNA-seq) is a powerful tool to measure transcriptional bursting and silencing at the individual cell level. In this study, we introduce the single-cell Stochastic Gene Silencing (scSGS) method, which leverages the natural variability in single-cell gene expression to decipher gene function.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Mathematics and Computer Science, Faculty of Science, Port Said University, Street 15, Port Said, 42521, Egypt. Electronic address:
Studying and analysing the various phases and key proteins of cell cycles is essential for the understanding of cell development and differentiation. To this end, mechanistic models play an important role towards a system level understanding of the interactions between cell cycle components. Many quantitative models of cell cycles have been previously constructed using either stochastic or deterministic approaches.
View Article and Find Full Text PDFEnviron Int
January 2025
Key Laboratory of Water and Sediment Sciences, Ministry of Education, College of Environmental Sciences and Engineering, Peking University, Beijing 100871 China; State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Beijing 100871 China. Electronic address:
Water diversion projects effectively mitigate the uneven distribution of water resources but can also influence aquatic biodiversity and ecosystem functions. Despite their importance, the impacts of such projects on multi-domain microbial community dynamics and the underlying mechanisms remain poorly understood. Utilizing high-throughput sequencing, we investigated bacterial, archaeal, and fungal community dynamics along the eastern route of the South-to-North water diversion project during both non-water diversion period (NWDP) and water diversion period (WDP).
View Article and Find Full Text PDFBiochem Biophys Res Commun
January 2025
Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), CONICET-Universidad de Buenos Aires, Buenos Aires, C1428EGA, Argentina; Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, C1428EGA, Argentina. Electronic address:
Technological innovation can drive scientific inquiry by allowing researchers to answer questions that were once out of reach. Eukaryotic mRNA synthesis was not so long ago thought of as a deterministic, sequential process in which transcriptional regulators and general transcription factors assemble in an orderly fashion into chromatin to, ultimately, activate RNA polymerase II. Advances in fluorescence microscopy techniques have revealed a much more complex scenario, wherein transcriptional regulators dynamically engage with chromatin in a more stochastic, probabilistic way.
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