By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm and a partially coupled generalised extended stochastic gradient algorithm to estimate the parameters of a multivariable output-error-like system with autoregressive moving average noise from input-output data. The key is to divide the identification model into several submodels based on the hierarchical identification principle and to establish the parameter estimation algorithm by using the coupled relationship between these submodels. The simulation test results indicate that the proposed algorithms are effective. • This paper decomposes a multivariable output-error autoregressive moving average-like (M-OEARMA-like) system into several subsystems by means of the hierarchical identification principle. • A partially coupled generalised extended projection (PC-GEPJ) algorithm is proposed for M-OEARMA-like system by making use of the coupling identification concept.

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Currently, there is no curative treatment for inflammatory bowel disease (IBD), which has an increased risk of colitis-associated cancer. Corticosteroids are the main clinical IBD therapeutics but have significant side effects. Even heavy corticosteroid use can result in the failure of IBD treatment which may lead to resective surgery. In this study, we designed one type of new drug-delivery system (DDS) delivering dexamethasone (DEX), an anti-inflammation corticosteroid, for IBD therapy. This DDS was screened by hydrogen-bonding-induced facile self-assembly of natural and safe polyphenols and polymers. The nanoparticles fabricated from tannic acid and Pluronic F-68 have a uniform spherical shape. With approximately 10% DEX loaded, PPNP-DEX showed responsive release behavior in the presence of esterase. Moreover, PPNP-DEX exhibited great potential in radical scavenging at inflammation sites. Drug retention rates can also be enhanced in mice with colitis compared with healthy controls because of this inflammation targeting ability. Owing to all these advantages, PPNP-DEX achieved remarkable treatment efficacy in colitis mice compared with PPNP or free DEX. This study demonstrates PPNP as a promising drug-delivery platform for IBD therapy. More importantly, it provides a new design strategy of therapeutics for various inflammatory diseases.

SummaryThis article is concerned with the parameter identification problem of nonlinear dynamic responses for the linear time‐invariant system by means of an impulse excitation signal and discrete observation data. Using the impulse signal as the input, the impulse response experiment is carried out and the dynamical moving sampling is designed to generate the measured data for deriving new identification algorithms. By applying the moving window data that contain the dynamical information of the system to be identified, an objective function with respect to the parameters of the systems is constructed according to the impulse response. In accordance with different functional relations between the system parameters and the system output response, the unknown parameter vector of the system is separated into a linear parameter vector and a nonlinear parameter vector. Based on the separated parameter vectors, two subidentification models are constructed and a separable identification algorithm is presented through the gradient search to improve the accuracy. Moreover, for the purpose of enhancing the estimation accuracy and capturing the dynamical feature of the systems, the moving window data are employed to develop the separable identification algorithm. The performance of the proposed separable identification method is illustrated via a numerical example.