Ballistic electronic transport in Quantum Cables

We studied theoretically ballistic electronic transport in a proposed mesoscopic structure - Quantum Cable. Our results demonstrated that Qauntum Cable is a unique structure for the study of mesoscopic transport. As a function of Fermi energy, Ballistic conductance exhibits interesting stepwise features. Besides the steps of one or two quantum conductance units ($2e^2/h$), conductance plateaus of more than two quantum conductance units can also be expected due to the accidental degeneracies (crossings) of subbands. As structure parameters is varied, conductance width displays oscillatory properties arising from the inhomogeneous variation of energy difference betweeen adjoining transverse subbands. In the weak coupling limits, conductance steps of height $2e^2/h$ becomes the first and second plateaus for the Quantum Cable of two cylinder wires with the same width.Comment: 11 pages, 5 figure

Identification of nonlinear lateral flow immunoassay state-space models via particle filter approach

This is the post-print of the Article. The official published version can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, the particle filtering approach is used, together with the kernel smoothing method, to identify the state-space model for the lateral flow immunoassay through available but short time-series measurement. The lateral flow immunoassay model is viewed as a nonlinear dynamic stochastic model consisting of the equations for the biochemical reaction system as well as the measurement output. The renowned extended Kalman filter is chosen as the importance density of the particle filter for the purpose of modeling the nonlinear lateral flow immunoassay. By using the developed particle filter, both the states and parameters of the nonlinear state-space model can be identified simultaneously. The identified model is of fundamental significance for the development of lateral flow immunoassay quantification. It is shown that the proposed particle filtering approach works well for modeling the lateral flow immunoassay.This work was supported in part by the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, Natural Science Foundation of China under Grants 61104041, International Science and Technology Cooperation Project of Fujian Province of China under Grant 2009I0016

A hybrid EKF and switching PSO algorithm for joint state and parameter estimation of lateral flow immunoassay models

This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, a hybrid extended Kalman filter (EKF) and switching particle swarm optimization (SPSO) algorithm is proposed for jointly estimating both the parameters and states of the lateral flow immunoassay model through available short time-series measurement. Our proposed method generalizes the well-known EKF algorithm by imposing physical constraints on the system states. Note that the state constraints are encountered very often in practice that give rise to considerable difficulties in system analysis and design. The main purpose of this paper is to handle the dynamic modeling problem with state constraints by combining the extended Kalman filtering and constrained optimization algorithms via the maximization probability method. More specifically, a recently developed SPSO algorithm is used to cope with the constrained optimization problem by converting it into an unconstrained optimization one through adding a penalty term to the objective function. The proposed algorithm is then employed to simultaneously identify the parameters and states of a lateral flow immunoassay model. It is shown that the proposed algorithm gives much improved performance over the traditional EKF method.This work was supported in part by the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, Natural Science Foundation of China under Grants 61104041, International Science and Technology Cooperation Project of Fujian Province of China under Grant 2009I0016

Inference of nonlinear state-space models for sandwich-type lateral flow immunoassay using extended Kalman filtering

Copyright [2011] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, a mathematical model for sandwichtype lateral flow immunoassay is developed via short available time series. A nonlinear dynamic stochastic model is considered that consists of the biochemical reaction system equations and the observation equation. After specifying the model structure, we apply the extend Kalman filter (EKF) algorithm for identifying both the states and parameters of the nonlinear state-space model. It is shown that the EKF algorithm can accurately identify the parameters and also predict the system states in the nonlinear dynamic stochastic model through an iterative procedure by using a small number of observations. The identified mathematical model provides a powerful tool for testing the system hypotheses and also inspecting the effects from various design parameters in a both rapid and inexpensive way. Furthermore, by means of the established model, the dynamic changes of the concentration of antigens and antibodies can be predicted, thereby making it possible for us to analyze, optimize and design the properties of lateral flow immunoassay devices.This work was supported in part by the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, Natural Science Foundation of Fujian Province of China under Grants 2009J01280 and 2009J01281

B\"{a}cklund transformations for high-order constrained flows of the AKNS hierarchy: canonicity and spectrality property

New infinite number of one- and two-point B\"{a}cklund transformations (BTs) with explicit expressions are constructed for the high-order constrained flows of the AKNS hierarchy. It is shown that these BTs are canonical transformations including B\"{a}cklund parameter $\eta$ and a spectrality property holds with respect to $\eta$ and the 'conjugated' variable $\mu$ for which the point $(\eta, \mu)$ belongs to the spectral curve. Also the formulas of m-times repeated Darboux transformations for the high-order constrained flows of the AKNS hierarchy are presented.Comment: 21 pages, Latex, to be published in J. Phys.

A hidden constant in the anomalous Hall effect of a high-purity magnet MnSi

Measurements of the Hall conductivity in MnSi can provide incisive tests of theories of the anomalous Hall (AH) effect, because both the mean-free-path and magnetoresistance (MR) are unusually large for a ferromagnet. The large MR provides an accurate way to separate the AH conductivity $\sigma_{xy}^A$ from the ordinary Hall conductivity $\sigma_{xy}^N$. Below the Curie temperature $T_C$, $\sigma_{xy}^A$ is linearly proportional to $M$ (magnetization) with a proportionality constant $S_H$ that is independent of both $T$ and $H$. In particular, $S_H$ remains a constant while $\sigma_{xy}^N$ changes by a factor of 100 between 5 K and $T_C$. We discuss implications of the hidden constancy in $S_H$.Comment: 5 pages, 4 figures. Minor change

A novel switching delayed PSO algorithm for estimating unknown parameters of lateral flow immunoassay

In this paper, the parameter identification problem of the lateral flow immunoassay (LFIA) devices is investigated via a new switching delayed particle swarm optimization (SDPSO) algorithm. By evaluating an evolutionary factor in each generation, the velocity of the particle can adaptively adjust the model according to a Markov chain in the proposed SDPSO method. During the iteration process, the SDPSO can adaptively select the inertia weight, acceleration coefficients, locally best particle pbest and globally best particle gbest in the swarm. It is worth highlighting that the pbest and the gbest can be randomly selected from the corresponding values in the previous iteration. That is, the delayed information of the pbest and the gbest can be exploited to update the particle’s velocity in current iteration according to the evolutionary states. The strategy can not only improve the global search but also enhance the possibility of eventually reaching the gbest. The superiority of the proposed SDPSO is evaluated on a series of unimodal and multimodal benchmark functions. Results demonstrate that the novel SDPSO algorithm outperforms some well-known PSO algorithms in aspects of global search and efficiency of convergence. Finally, the novel SDPSO is successfully exploited to estimate the unknown time-delay parameters of a class of nonlinear state-space LFIA model.This work was supported in part by the Royal Society of the U.K., the Alexander von Humboldt Foundation of Germany, the Natural Science Foundation of China under Grant 61403319, the Fujian Natural Science Foundation under Grant 2015J05131, and the Fujian Provincial Key Laboratory of Eco-Industrial Green Technology

Synthesis of as-grown superconducting MgB_2 thin films by molecular beam epitaxy in UHV conditions

As-grown superconducting MgB_2 thin films have been grown on SrTiO_3(001), MgO(001), and Al_2O_3(0001) substrates by a molecular beam epitaxy (MBE) method with novel co-evaporation conditions of low deposition rate in ultra-high vacuum. The structural and physical properties of the films were studied by RHEED, XRD, electrical resistivity measurements, and SQUID magnetometer. The RHEED patterns indicate three-dimensional growth for MgB_2. The highest T_c determined by resistivity measurement was about 36K in these samples. And a clear Meissner effect below T_c was observed using magnetic susceptibility measurement. We will discuss the influence of B buffer layer on the structural and physical properties.Comment: 9 pages with 4 figures, ISS2003 proceedin