149 research outputs found

    Universality of residence-time distributions in non-adiabatic stochastic resonance

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    We present mathematically rigorous expressions for the residence-time and first-passage-time distributions of a periodically forced Brownian particle in a bistable potential. For a broad range of forcing frequencies and amplitudes, the distributions are close to periodically modulated exponential ones. Remarkably, the periodic modulations are governed by universal functions, depending on a single parameter related to the forcing period. The behaviour of the distributions and their moments is analysed, in particular in the low- and high-frequency limits.Comment: 8 pages, 1 figure New version includes distinction between first-passage-time and residence-time distribution

    Brillouin propagation modes in optical lattices: Interpretation in terms of nonconventional stochastic resonance

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    We report the first direct observation of Brillouin-like propagation modes in a dissipative periodic optical lattice. This has been done by observing a resonant behavior of the spatial diffusion coefficient in the direction corresponding to the propagation mode with the phase velocity of the moving intensity modulation used to excite these propagation modes. Furthermore, we show theoretically that the amplitude of the Brillouin mode is a nonmonotonic function of the strength of the noise corresponding to the optical pumping, and discuss this behavior in terms of nonconventional stochastic resonance

    Quantum dynamics in strong fluctuating fields

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    A large number of multifaceted quantum transport processes in molecular systems and physical nanosystems can be treated in terms of quantum relaxation processes which couple to one or several fluctuating environments. A thermal equilibrium environment can conveniently be modelled by a thermal bath of harmonic oscillators. An archetype situation provides a two-state dissipative quantum dynamics, commonly known under the label of a spin-boson dynamics. An interesting and nontrivial physical situation emerges, however, when the quantum dynamics evolves far away from thermal equilibrium. This occurs, for example, when a charge transferring medium possesses nonequilibrium degrees of freedom, or when a strong time-dependent control field is applied externally. Accordingly, certain parameters of underlying quantum subsystem acquire stochastic character. Herein, we review the general theoretical framework which is based on the method of projector operators, yielding the quantum master equations for systems that are exposed to strong external fields. This allows one to investigate on a common basis the influence of nonequilibrium fluctuations and periodic electrical fields on quantum transport processes. Most importantly, such strong fluctuating fields induce a whole variety of nonlinear and nonequilibrium phenomena. A characteristic feature of such dynamics is the absence of thermal (quantum) detailed balance.Comment: review article, Advances in Physics (2005), in pres

    Evaluation of the impact of iPSC differentiation protocols on transcriptomic signatures.

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    Human induced pluripotent stem cells (iPSC) have the potential to produce desired target cell types in vitro and allow for the high-throughput screening of drugs/chemicals at population level thereby minimising the cost of drug discovery and drug withdrawals after clinical trials. There is a substantial need for the characterisation of the iPSC derived models to better understand and utilise them for toxicological relevant applications. In our study, iPSC (SBAD2 or SBAD3 lines obtained from StemBANCC project) were differentiated towards toxicologically relevant cell types: alveolar macrophages, brain capillary endothelial cells, brain cells, endothelial cells, hepatocytes, lung airway epithelium, monocytes, podocytes and renal proximal tubular cells. A targeted transcriptomic approach was employed to understand the effects of differentiation protocols on these cell types. Pearson correlation and principal component analysis (PCA) separated most of the intended target cell types and undifferentiated iPSC models as distinct groups with a high correlation among replicates from the same model. Based on PCA, the intended target cell types could also be separated into the three germ layer groups (ectoderm, endoderm and mesoderm). Differential expression analysis (DESeq2) presented the upregulated genes in each intended target cell types that allowed the evaluation of the differentiation to certain degree and the selection of key differentiation markers. In conclusion, these data confirm the versatile use of iPSC differentiated cell types as standardizable and relevant model systems for in vitro toxicology

    Evaluation of the impact of iPSC differentiation protocols on transcriptomic signatures

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    \ua9 2024 The Authors. Human induced pluripotent stem cells (iPSC) have the potential to produce desired target cell types in vitro and allow for the high-throughput screening of drugs/chemicals at population level thereby minimising the cost of drug discovery and drug withdrawals after clinical trials. There is a substantial need for the characterisation of the iPSC derived models to better understand and utilise them for toxicological relevant applications. In our study, iPSC (SBAD2 or SBAD3 lines obtained from StemBANCC project) were differentiated towards toxicologically relevant cell types: alveolar macrophages, brain capillary endothelial cells, brain cells, endothelial cells, hepatocytes, lung airway epithelium, monocytes, podocytes and renal proximal tubular cells. A targeted transcriptomic approach was employed to understand the effects of differentiation protocols on these cell types. Pearson correlation and principal component analysis (PCA) separated most of the intended target cell types and undifferentiated iPSC models as distinct groups with a high correlation among replicates from the same model. Based on PCA, the intended target cell types could also be separated into the three germ layer groups (ectoderm, endoderm and mesoderm). Differential expression analysis (DESeq2) presented the upregulated genes in each intended target cell types that allowed the evaluation of the differentiation to certain degree and the selection of key differentiation markers. In conclusion, these data confirm the versatile use of iPSC differentiated cell types as standardizable and relevant model systems for in vitro toxicology

    Accountability in the East Asian economic miracle, crisis and recovery

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    Despite claims that accountability enables 'good governance' proper, its specific origins, character and limitations are not yet fully clear. In order to explicate the nature of accountability better this paper will, therefore, formulate and apply its own comparative framework to the case of the East Asian economic miracle, crisis and recovery in particular. In so doing it finds that, even when accountability emerged as a mid-crisis issue that was dramatically reconfigured for any due recovery later, it was not itself then sufficiently explicated for all the implications and consequences to be realized fully. Once it is explicated more fully, however, the further implications and consequences of changing accountability for economic governance question precisely what is to be expected from accountability per se

    What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology

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    Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations—e.g., random noise—cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being “suboptimal”. Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the “neural code”. Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise—via stochastic resonance or otherwise—than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing “noise benefits”, and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology
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