The detection of mycotoxins in food is urgently needed because they pose a significant threat to public health. In this study, we developed a quantitative detection platform for mycotoxins by integrating multicolor upconversion nanoparticle barcode technology with fluorescence image processing using a smartphone-based portable device. The multi-colored upconversion nanoparticle encoded microspheres (UCNMs) were used as encoded signals for detecting different mycotoxins simultaneously. After indirect competitive immunoassays using UCNMs, images could be captured by the portable device and the camera of a smartphone. Then, a self-written Android application, which is an HSV-based image recognition program installed on a smartphone, analyzed images and offered a reliable and accurate result in less than 1 min. The quantitative detection platform of mycotoxins proved to be feasible and reliable, and the limit of detection (LOD) was 1 ng, which was lower than that obtained from standard assays. This study demonstrates a method for detecting mycotoxins in food and other point of care analysis.
In this paper, a stability analysis problem is studied for a class of two-dimensional (2-D) discrete-time systems with time-varying and distributed delays described by the second Fornasini-Marchesini (FM) model. First, new 2-D polynomials-based summation inequalities are proposed to estimate summation terms in the forward difference of Lyapunov-Krasovskii functional (LKF). The inequalities can reduce to 2-D Jensen inequalities and 2-Dfinite-sum inequalities by designing slack matrices and arbitrary vectors. Second, a new augment LKF is constructed, which makes full use of the delay changing information. By the Lyapunov stability theory, sufficient conditions for asymptotic stability of 2-D discrete-time systems are derived in the form of linear matrix inequalities. Finally, two simulation examples are given to demonstrate the effectiveness of the proposed methods. INDEX TERMS Two-dimensional systems, time-varying delays, distributed delays, summation inequalities, Lyapunov-Krasovskii functional.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.