Calculation of the Autocorrelation Function of the Stochastic Single Machine Infinite Bus System

Critical slowing down (CSD) is the phenomenon in which a system recovers more slowly from small perturbations. CSD, as evidenced by increasing signal variance and autocorrelation, has been observed in many dynamical systems approaching a critical transition, and thus can be a useful signal of proximity to transition. In this paper, we derive autocorrelation functions for the state variables of a stochastic single machine infinite bus system (SMIB). The results show that both autocorrelation and variance increase as this system approaches a saddle-node bifurcation. The autocorrelation functions help to explain why CSD can be used as an indicator of proximity to criticality in power systems revealing, for example, how nonlinearity in the SMIB system causes these signs to appear.Comment: Accepted for publication/presentation in Proc. North American Power Symposium, 201

Effect of spin on electron motion in a random magnetic field

We consider properties of a two-dimensional electron system in a random magnetic field. It is assumed that the magnetic field not only influences orbital electron motion but also acts on the electron spin. For calculations, we suggest a new trick replacing the initial Hamiltonian by a Dirac Hamiltonian. This allows us to do easily a perturbation theory and derive a supermatrix sigma model, which takes a form of the conventional sigma model with the unitary symmetry. Using this sigma model we calculate several correlation functions including a spin-spin correlation function. As compared to the model without spin, we get different expressions for the single-particle lifetime and the transport time. The diffusion constant turns out to be 2 times smaller than the one for spinless particles.Comment: 7 pages, revtex, result of the spin correlation function corrected, Appendix adde

Sorting and separation of microparticles by surface properties using liquid crystal-enabled electro-osmosis

Sorting and separation of microparticles is a challenging problem of interdisciplinary nature. Existing technologies can differentiate microparticles by their bulk properties, such as size, density, electric polarizability, etc. The next level of challenge is to separate particles that show identical bulk properties and differ only in subtle surface features, such as functionalization with ligands. In this work, we propose a technique to sort and separate particles and fluid droplets that differ in surface properties. As a dispersive medium, we use a nematic liquid crystal (LC) rather than an isotropic fluid, which allows us to amplify the difference in surface properties through distinct perturbations of LC order around the dispersed particles. The particles are placed in a LC cell with spatially distorted molecular orientation subject to an alternating current electric field. The gradients of the molecular orientation perform two functions. First, elastic interactions between these pre-imposed gradients and distortions around the particles separate the particles with different surface properties in space. Second, these pre-imposed patterns create electro-osmotic flows powered by the electric field that transport the sorted particles to different locations thus separating them. The demonstrated unique sorting and separation capability opens opportunities in lab-on-a-chip, cell sorting and bio-sensing applications

New records of Praethecacineta halacari (Schulz) (Suctorea: Ciliophora) from Taiwan, Tanzania and Canada

The present study reports on a range extension of the suctorian species Praethecacineta halacari to the region of He-Ping-Dao, north-east of Taiwan (West Pacific Ocean), Matemwe, the east coast of Unguja, Zanzibar, Tanzania (West Indian Ocean) and Nova Scotia, Canada (West Atlantic Ocean). Praethecacineta halacari is reported here for the first time from Taiwan, Tanzania and Canada. Earlier records include the Caspian Sea, Western Australia, Brazil, India, and various coastal sites in Europe