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Fluoroquinolones are a widely used class of antibiotics, with a large variety, which are frequently monitored in the aqueous environment, threatening ecological and human health. To date, effective degradation of fluoroquinolone antibiotics remains a major challenge. Focused on the broad-spectrum degradation of fluoroquinolone antibiotics, a novel biomimetic peroxidase nanozyme named Hemin-His-Fe (HHF)-peroxidase nanozyme was synthesized through a green and rapid "one-pot" method involving hemin, Fmoc- L -His and Fe2+ as precursors. After systematic optimization of the reaction conditions, fluoroquinolone antibiotics can be degraded by the HHF-peroxidase nanozyme when supplemented with H2O2 in acidic environments. Through validation and analysis, it was proved that the generated strong oxidative hydroxyl radicals are the main active species in the degradation process. In addition, it was verified that this method shows great universal applicability in real water samples. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: In this study, a novel approach is proposed to achieve the uniformly dispersed Ru nanoparticles with N coordination loaded on three‐dimensionally ordered macro/mesoporous carbon (3DOMMC) through simultaneous pyrolysis of Ru3+ and cyanamide on 3DOMMC. In an alkaline medium, the synthesized catalysts exhibit exceptional hydrogen evolution reaction (HER) performance. Specifically, Ru‐N/3DOMMC demonstrates a significantly low overpotential of 13.8 mV to achieve a current density of 10 mA·cm–2, and it exhibits a mass activity 17.5 times higher than that of commercial Pt/C. The outstanding performance could be attributed to the ultrahigh Ru dispersion and more efficient contact between active sites and reactant, which derived from the large specific surface area and interconnective three‐dimensionally macro/mesopores of 3DOMMC. [ABSTRACT FROM AUTHOR]

Summary: This article investigates the robust steady‐state matrix‐weighted fusion (MWF) filtering problem for multisensor multichannel autoregressive (AR) signal with multiple uncertainties, which can be transformed into the state estimation problems in the state space representation. The uncertainties include the random parameter matrices, uncertain noise variances (UNVs), one‐step random measurement delay, missing measurements, and packet dropouts. Three Bernoulli distributed stochastic variables with known conditional probabilities are introduced to describe the networked stochastic uncertainties. The AR signal model under consideration is transformed into a state space model only with UNVs via using a combined method, which is composed of the state space method, the augmented method, and the fictitious noise method. Based on the worst‐case system with conservative upper bounds of UNVs, the robust local steady‐state one‐step and multi‐step signal predictors are proposed by using the minimax robust estimation method. Subsequently, the distributed fusion signal predictors weighted by matrices are addressed. The robustness of the proposed signal predictors is proved by the introduced augmented noises and permutation matrices. Simulation experiment demonstrates the correctness and effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

To satisfy the increasing demand for soybeans, identifying and sorting high-vigor seeds before sowing is an effective way to improve the yield. Polarized hyperspectral imaging (PHI) technology is here proposed as a rapid, non-destructive method for detecting the vigor of naturally aged soybean seeds. First, the spectrum of 396.1–1044.1 nm was collected to automatically extract the region of interest (ROI). Then, first derivative (FD), Savitzky–Golay (SG), multiplicative scatter correction (MSC), and standard normal variate (SNV) preprocessed hyperspectral and polarized hyperspectral data (0°, 45°, 90°, and 135°) for the soybean seeds was obtained. Finally, the seed vigor prediction model based on polarized hyperspectral components such as I, Q, and U was constructed, and partial least squares regression (PLSR), back-propagation neural network (BPNN), generalized regression neural network (GRNN), support vector regression (SVR), random forest (RF), and blending ensemble learning were applied for modeling analysis. The results showed that the prediction accuracy when using PHI was improved to 93.36%, higher than that for the hyperspectral technique, with a prediction accuracy up to 97.17%, 98.25%, and 97.55% when using the polarization component of I, Q, and U, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a nondestructive detection method for egg freshness based on infrared thermal imaging technology. We studied the relationship between egg thermal infrared images (different shell colors and cleanliness levels) and egg freshness under heating conditions. Firstly, we established a finite element model of egg heat conduction to study the optimal heat excitation temperature and time. The relationship between the thermal infrared images of eggs after thermal excitation and egg freshness was further studied. Eight values of the center coordinates and radius of the egg circular edge as well as the long axis, short axis, and eccentric angle of the egg air cell were used as the characteristic parameters for egg freshness detection. After that, four egg freshness detection models, including decision tree, naive Bayes, k-nearest neighbors, and random forest, were constructed, with detection accuracies of 81.82%, 86.03%, 87.16%, and 92.32%, respectively. Finally, we introduced SegNet neural network image segmentation technology to segment the egg thermal infrared images. The SVM egg freshness detection model was established based on the eigenvalues extracted after segmentation. The test results showed that the accuracy of SegNet image segmentation was 98.87%, and the accuracy of egg freshness detection was 94.52%. The results also showed that infrared thermography combined with deep learning algorithms could detect egg freshness with an accuracy of over 94%, providing a new method and technical basis for online detection of egg freshness on industrial assembly lines. [ABSTRACT FROM AUTHOR]

The initial-boundary value problem for a wave equation with nonlinear averaged damping and nonlocal nonlinear source term is considered. We provide the sufficient conditions of finite time blow-up for weak solutions with suitable conditions on initial data by an ordinary differential inequality for an appropriately chosen functional. [ABSTRACT FROM AUTHOR]

This work is devoted to studying a wave equation with degenerate nonlocal nonlinear damping and source terms. By potential well theory, we show the asymptotic stability of energy in the presence of a degenerate damping of polynomial type when the initial energy is small. Also, we firstly derive some sufficient conditions on initial data which lead to finite time blow-up. [ABSTRACT FROM AUTHOR]

We describe what we believe is a new phase-shifting algorithm called a double three-step algorithm developed to reduce the measurement error of a three-dimensional shape-measurement system, which is based on digital fringe-projection and phase-shifting techniques. After comparing the performance of different existing phase-shifting algorithms, we present the new double three-step algorithm based on the error analysis of the standard three-step algorithm. In this algorithm, three-step phase shifting is done twice with an initial phase offset of 60[degrees] between them, and the two obtained phase maps are averaged to generate the final phase map. Both theoretical and experimental results showed that this new algorithm worked well in significantly reducing the measurement error.

In this paper, we consider initial boundary value problem of the generalized Boussinesq equation with nonlinear interior source and boundary absorptive terms. We establish firstly the local existence of solutions by standard Galerkin method. Then we prove both the global existence of the solution and a general decay of the energy functions under some restrictions on the initial data. We also prove a blow‐up result for solutions with positive and negative initial energy respectively. [ABSTRACT FROM AUTHOR]

In this paper, we consider the initial boundary value problem for generalized logarithmic improved Boussinesq equation. By using the Galerkin method, logarithmic Sobolev inequality, logarithmic Gronwall inequality, and compactness theorem, we show the existence of global weak solution to the problem. By potential well theory, we show the norm of the solution will grow up as an exponential function as time goes to infinity under some suitable conditions. Furthermore, for the generalized logarithmic improved Boussinesq equation with damped term, we obtain the decay estimate of the energy. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]