58 research outputs found

    Non-contact rack and pinion powered by the lateral Casimir force

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    The lateral Casimir force is employed to propose a design for a potentially wear-proof rack and pinion with no contact, which can be miniaturized to nano-scale. The robustness of the design is studied by exploring the relation between the pinion velocity and the rack velocity in the different domains of the parameter space. The effects of friction and added external load are also examined. It is shown that the device can hold up extremely high velocities, unlike what the general perception of the Casimir force as a weak interaction might suggest.Comment: 4 pages, submitted for publication on 17 Jan 0

    Normal and lateral Casimir force: Advances and prospects

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    We discuss recent experimental and theoretical results on the Casimir force between real material bodies made of different materials. Special attention is paid to calculations of the normal Casimir force acting perpendicular to the surface with the help of the Lifshitz theory taking into account the role of free charge carriers. Theoretical results for the thermal Casimir force acting between metallic, dielectric and semiconductor materials are presented and compared with available experimental data. Main attention is concentrated on the possibility to control the magnitude and sign of the Casimir force for applications in nanotechnology. In this respect we consider experiments on the optical modulation of the Casimir force between metal and semiconductor test bodies with laser light. Another option is the use of ferromagnetic materials, specifically, ferromagnetic dielectrics. Under some conditions this allows to get Casimir repulsion. The lateral Casimir force acting between sinusoidally corrugated surfaces can be considered as some kind of noncontact friction caused by zero-point oscillations of the electromagnetic field. Recent experiments and computations using the exact theory have demonstrated the role of diffraction-type effects in this phenomenon and the possibility to get asymmetric force profiles. Conclusion is made that the Casimir force may play important role in the operation of different devices on the nanoscale.Comment: 27 pages, 13 figures; Invited keynote lecture at the 2nd International Conference on Science of Friction, Ise-Shima, Mie, Japan, September 13-18, 2010; to appear in J. Phys.: Conf. Se

    The active inference approach to ecological perception: general information dynamics for natural and artificial embodied cognition

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    The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents—who shape and are shaped by their environment—offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework (AIF) makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in a naturalistic and information-theoretic foundation, using the principle of free energy minimization. The latter provides a theoretical basis for a unified treatment of particles, organisms, and interactive machines, spanning from the inorganic to organic, non-life to life, and natural to artificial agents. We provide a brief introduction to AIF, then explore its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics/AI research. We conclude the paper by considering implications for machine consciousness

    Large scale dynamic interactions and functional organization of the intrinsic connectivity networks during activation tasks

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    The research explores the functional architecture of the brain using fMRI in combination with behavioral and cognitive paradigms. Studying large-scale dynamic interactions of the brain's intrinsic connectivity networks (ICNs) forms the basis of the presented work. ICNs are networks of brain structures that display synchronous activity. Since the discovery of the default mode network in the resting brain, researchers have documented a handful of cortical, cerebellar and subcortical networks with a high level of similarity across subjects. There is striking convergence between ICNs observed in the resting brain and those elicited in activation tasks. ICNs can form when engaging in complex naturalistic tasks such as engaging in a simulated driving experience. ICNs can be identified using “blind source separation methods” such as Independent Components Analysis—a method well-suited for naturalistic and model-free activation-task designs. Most functional connectivity studies have examined the relationship between brain structures over extended periods of time. More recent work suggests that functional connectivity strength exhibits non-stationary fluctuations across longer time scales. Currently, little is known about how brain networks or ICNs interact during complex cognition or when externally engaged in a task. Two experiments are presented along with the methods used to study large-scale network interactions while subjects are engaged in complex social cognition as well as basic oculo-motor function. Although the tasks differ in terms of the cognitive and perceptual processes involved, both experiments utilize a similar visually guided paradigm. This similarity enables us to study the effect of the task on the observed large-scale ICN functional interactions and to better our understanding of the functional significance of these functional dynamic organizations. Moreover, visually-guided paradigms can induce synchronous and unified experience across subjects, which allows us to study the common event-related and stimulus-driven interactions. Finally, large-scale network organization at various time scales is also discusse

    Model-based design for seizure control by stimulation.

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    Squeeze and Nonlinear Effects in Trivelpiece-Gould and Electron AcousticWaves /

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    We study the enhanced damping of Trivelpiece-Gould modes in a nonneutral plasma column, due to application of a Debye-shielded cylindrically symmetric squeeze potential [phi]₁. Damping of these plasma modes is caused by additional Landau resonances at energies En for which the particle bounce frequency [omega]b(En) and the wave frequency [omega] satisfy [omega] = n[omega]b(En). In the first chapter we assume a smooth squeeze of finite width and find that additional resonances induced by the squeeze cause substantial damping, even in the large wave phase velocity compared to thermal velocity regime. For [omega]/ k >> (T /m) and [phi]₁ << T , the resonance damping rate has a I[phi]₁IÂČ dependence. This dependence agrees with the simulations and experimental results. In chapter 2 a narrow partition-like squeeze is added to an unsqeezed 1D plasma and we evaluate the plasma heating, caused by cylindrically symmetric plasma modes. As in chapter 1, collisionless heating is enhanced by the squeeze, due to additional resonances, even when [omega]/k >> (T /m). Adding collisions to the theory broadens these resonances and also creates a boundary layer at the separatrix between trapped and passing particles. This further enhances the heating at [omega]/k vs < 1, where vs is the separatrix velocity. We study the nonlinear interaction of TG waves in chapter 3. We obtain corrections to the forms and frequencies of weakly nonlinear modes. Futhermore, we study the decay instability between a dominant axial mode m = 2 and a small amplitude mode m = 1, using both analytical and numerical techniques. In chapter 4, we study nonlinear interactions of the novel Electron Acoustic Waves in a 1D plasma. Here, we use a weakly nonlinear analysis of a 1D Vlasov-Poisson system, in a modified Maxwellian equilibrium, flattened at the phase velocity of the waves. Using numerical simulation of the 1D Vlasov-Poisson system, we study the unstable collapse of an EAW mode m = 2 to an EAW mode m = 1 and compare the numerically-obtained exponential growth rates to the analytically obtained result
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