Northeastern University (China)

About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).

Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form

Abstract: This paper focuses on the problem of adaptive neural network (NN) control for a class of nonlinear nonstrict-feedback systems via output feedback. A novel adaptive NN backstepping output-feedback control approach is first proposed for nonlinear nonstrict-feedback systems. The monotonicity of system bounding functions and the structure character of radial basis function (RBF) NNs are used to overcome the difficulties that arise from nonstrict-feedback structure. A state observer is constructed to estimate the immeasurable state variables. By combining adaptive backstepping technique with approximation capability of radial basis function NNs, an output-feedback adaptive NN controller is designed through backstepping approach. It is shown that the proposed controller guarantees semiglobal boundedness of all the signals in the closed-loop systems. Two examples are used to illustrate the effectiveness of the proposed approach.

Differential Evolution With an Individual-Dependent Mechanism

Abstract: Differential evolution (DE) is a well-known optimization algorithm that utilizes the difference of positions between individuals to perturb base vectors and thus generate new mutant individuals. However, the difference between the fitness values of individuals, which may be helpful to improve the performance of the algorithm, has not been used to tune parameters and choose mutation strategies. In this paper, we propose a novel variant of DE with an individual-dependent mechanism that includes an individual-dependent parameter (IDP) setting and an individual-dependent mutation (IDM) strategy. In the IDP setting, control parameters are set for individuals according to the differences in their fitness values. In the IDM strategy, four mutation operators with different searching characteristics are assigned to the superior and inferior individuals, respectively, at different stages of the evolution process. The performance of the proposed algorithm is then extensively evaluated on a suite of the 28 latest benchmark functions developed for the 2013 Congress on Evolutionary Computation special session. Experimental results demonstrate the algorithm’s outstanding performance.

Immunoassay of goat antihuman immunoglobulin G antibody based on luminescence resonance energy transfer between near-infrared responsive NaYF4:Yb, Er upconversion fluorescent nanoparticles and gold nanoparticles

Abstract: Near-infrared (NIR) light can penetrate biological samples and even tissues without causing sample damage and avoid autofluorescence from biological samples in fluorescence detection. Thus, a luminescence resonance energy transfer (LRET)-based immunoassay that can be excited by NIR irradiation is a promising approach to the analysis of biological samples. Here we demonstrate the use of NIR-to-visible upconversion nanoparticles (UCNPs) as an energy donor, which can emit a visible light upon the NIR irradiation, and gold nanoparticles (Au NPs) as an energy acceptor, which can absorb the visible light emitted from the donor, to develop a sandwich-type LRET-based immunoassay for the detection of goat antihuman immunoglobulin G (IgG). Amino-functionalized NaYF(4):Yb, Er UCNPs and Au NPs were first prepared and then conjugated with the human IgG and rabbit antigoat IgG, respectively. The NIR-excited fluorescence emission band of human IgG-conjugated NaYF(4):Yb, Er UCNPs (lambda(max) = 542 nm) partially overlaps with the visible absorption band of the rabbit antigoat IgG-conjugated colloidal Au NPs (lambda(max) = 530 nm), satisfying the requirement of spectral overlap between donors and acceptors for LRET. A LRET system was then formed when goat antihuman IgG was added to a mixture of human IgG-modified NaYF(4):Yb, Er UCNPs (donor) and rabbit antigoat IgG-modified Au NPs (acceptor). The sandwich-type immunoreactions between the added goat antihuman IgG (primary antibody) and the two different proteins (antigen and secondary antibody on the surface of the donors and acceptors, respectively) cross-bridge the donors and acceptors and thus shorten their spacing, leading to the occurrence of LRET from UCNPs to Au NPs upon NIR irradiation. As a result, the quenching of the NIR-excited fluorescence of the UCNPs is linearly correlated to the concentration of the goat antihuman IgG (in the range of 3-67 microg x mL(-1)) present in the system, enabling the detection and quantification of the antibody. Such sandwich-type LRET-based approach can reach a very low detection limit of goat antihuman IgG (0.88 microg x mL(-1)), indicating that this method is applicable for the trace protein detection. This approach is expected to be extended to the detection of other biological molecules once the donor and acceptor nanoparticles are modified by proper molecules that can recognize the target biomolecules.