Biomedical subjects

Biao Huang

Publications and source records attributed to Biao Huang.

5 recordsLinked to original sources

PubMed2026

A homogeneous immunoassay based on AlphaLICA technology for detecting florfenicol residues in animal-derived foods.

Florfenicol (FF), a broad-spectrum amide antibiotic widely used in livestock, poultry, and aquaculture, poses potential threats to food safety and public health due to its residual accumulation. In this study, a novel homogeneous immunoassay based on Amplified Luminescent Proximity Homogeneous Assay (AlphaLICA) technology was developed for the first time for rapid screening of FF residues in milk and egg matrices. By covalently immobilizing the FF-BSA conjugate and goat anti-mouse IgG onto luminescent and photosensitive microspheres, respectively, the method achieved wash-free, homogeneous quantitative detection through a competitive immunoreaction. Under optimized conditions, the assay exhibited a linear range of 0.2-16.2 ng mL-1, with a limit of detection of 9.7 pg mL-1 and a limit of quantification of 183 pg mL-1. The intra- and inter-batch coefficients of variation ranged from 3.08% to 5.70% and 2.44% to 7.09%, respectively. Spike recovery rates in milk and egg matrices ranged from 93.18% to 107.17% (RSD ≤ 5.57%). Cross-reactivity with 11 other common antibiotics, including chloramphenicol and thiamphenicol, was below 0.1%, demonstrating excellent specificity. Comparative analysis with a commercial ELISA kit showed high consistency (r2 = 0.9332, p < 0.001). With high sensitivity, strong specificity, simple operation, and a detection time of only 10 min, this method provides a reliable technical platform for high-throughput, rapid monitoring of FF residues in milk and egg matrices.

Journal Article↗

PubMed2004

Multi-loop decentralized PID control based on covariance control criteria: an LMI approach.

PID control is well known and widely applied in industry and many design algorithms are readily available in the literature. However, systematic design of multi-loop or decentralized PID control for multivariable processes to meet certain objectives simultaneously is still a challenging task. Designing multi-loop PID controllers such that the process variables satisfy the generalized covariance constraints is studied in this paper. A convergent computational algorithm is proposed to calculate the multi-loop PID controller for a process with stable disturbances. This algorithm is then extended to a process with random-walk disturbances. The feasibility of the proposed algorithm is verified by applying it to several simulation examples.

Journal Article↗

PubMed2003

[Identification of Puumala like viruses in China].

BACKGROUND: To confirm if Puumala like viruses exist in China. METHODS: RNA was extracted from lungs of bank voles captured in the Northeast China, partial S segments genome of Puumala viruses were amplified and sequenced. RESULTS: 926 bp cDNA of S segments of Puumala like virus was amplified and sequenced. The phylogenetic analysis revealed that the Puumala like viruses found in China were most close to that found in Far East region of Russia. CONCLUSIONS: Puumala like virus does exist in Northeast China, and the nucleotides sequence of the viruses have high homolog to Puumala viruses found in Russia.

Animals↗

PubMed2002

Detection of abrupt change and applications in sensor decalibration monitoring.

The primary objective of fault detection is to detect abrupt undesirable changes in a process at an early stage. This early detection has a potential of preventing loss of production and equipment damage due to these undesirable changes, thus reducing process downtime. This paper details the implementation of some parametric fault detection techniques for sensor decalibration monitoring. A parametric fault detection approach that is handled in depth in this paper is the local approach. This approach developed by Benveniste, Basseville, and Moustakides [Benveniste, A., Basseville, M., and Moustakides, G., The asymptotic local approach to change detection and model validation. IEEE Trans. Autom. Control AC-32 (7), 583-592 (1987)] offers a computationally inexpensive way to attain the objective of monitoring changes in model parameters. However, the algorithm in its original formulation is not applicable to certain processes such as sensors. Therefore, the local approach is coupled with other estimation algorithms such as the input independent Kalman filter to derive a robust sensor decalibration monitoring algorithm. The proposed fault detection algorithm is applied to a pilot scale process for evaluation of its performance.

Algorithms↗

PubMed2002

Controller performance analysis with LQG benchmark obtained under closed loop conditions.

This paper proposes a new method for obtaining a linear quadratic Gaussian (LQG) benchmark in terms of the variances of process input and output from closed-loop data, for assessing the controller performance. LQG benchmark has been proposed in the literature to assess controller performance since the LQG tradeoff curve represents the limit of performance in terms of input and output variances. However, an explicit parametric model is required to calculate the LQG benchmark. In this work, we propose a data driven subspace approach to calculate the LQG benchmark under closed-loop conditions with certain external excitations. The optimal LQG-benchmark variances are obtained directly from the subspace matrices corresponding to the deterministic inputs and the stochastic inputs, which are identified using closed-loop data with setpoint excitation. These variances are used for assessing the controller performance. The method proposed in this paper is applicable to both univariate and multivariate systems. Profit analysis for the implementation of feedforward control to the existing feedback-only control system is also analyzed under the optimal LQG performance framework. The proposed method is illustrated through a simulation example and an application on a pilot scale process.

Benchmarking↗