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Aiming at the problem that the array pattern has some deviation and disturbance caused by the array position error, which leads to the estimation performance degradation of direction of arrival (DOA) in multiple signal classification (MUSIC) algorithm, this paper uses Toeplitz preprocessing algorithm and proposes an array position error calibration algorithm based on matrix reconstruction theory. Firstly, the covariance matrix with array position error is preprocessed to restore the Toeplitz structure of the covariance matrix in the ideal case. Then, the nuclear norm optimization algorithm is utilized to construct a convex optimization function, the noise is suppressed for the processed covariance matrix, and this algorithm guarantees the accurate distribution of signal and noise subspace.Finally, the MUSIC algorithm is used to perform DOA estimation.Via the simulation results, the proposed algorithm improves the angular resolution of MUSIC algorithm with the existence of array position error, and decreases the effects leading by the low number of snapshots, thus it can increase the estimation accuracy.

AbstractCanthaxanthin and β-apo-8’-carotenoid ethyl ester are widely used as feed additives in poultry feed for enhancing the color of poultry products. The excessive intake of the two colorants can cause health damage. According to the European Food Safety Authority (EFSA), the acceptable daily intake (ADI) of canthaxanthin and β-apo-8’-carotenoid ethyl ester are 0.03 mg/kg·bw and 0.015 mg/kg·bw, respectively. Ultra-high-performance liquid chromatography-diode array detector (UPLC-DAD) was used to determine two colorants in chicken eggs and meat. A PRiME HLB solid-phase extraction cartridge was used to extract and clean-up the sample. BEH C18 column was used as the separation column, with water containing 0.1% formic acid and acetonitrile as the mobile phase. The limit of detection (LOD) was 0.05 mg/kg, and the limit of quantification (LOQ) was 0.1 mg/kg. The recoveries were between 90% and 104%. The daily intake of two colorants in chicken eggs and meat was evaluated based on the detection data, food consumption data and weight data of the population. The mean estimated daily intake (EDI) values of canthaxanthin through chicken eggs and meat were 1.09 µg/(kg·bw·d) and 0.013 µg/(kg·bw·d), respectively. The mean EDI value of β-apo-8’-carotenoid ethyl ester through eggs was 0.44 µg/(kg·bw·d). The results showed that eggs were the main contributor to the daily intake of two colorants. The mean hazard quotients (HQ) values of two colorants through chicken eggs and meat was within a safe range. [ABSTRACT FROM AUTHOR]

In this paper, the original RSEI model (including greenness index, humidity index, heat index and dryness index) and their contribution rate (%) are used to evaluate the change of ecological environment. To study how natural and anthropogenic changes in ecological environment affect ecosystem function and how these factors interact, CASA model was used to estimate the correlation between the net primary productivity of vegetation (NPP), population density and land use. This could reveal the influence factors of ecological environment change in the Wanjiang River Basin from 2000 to 2022. The results show that the combing RSEI and CASA models can effectively show the spatial-temporal variation and spatial distribution of NPP of vegetation in Wanjiang Basin. During this period, RSEI of the basin showed an overall upward trend, and the RSEI increased by about 0.1/ 10 a. The vegetation productivity in most areas was gradually improved, the ecological environment was restored, and the ecological environment quality was gradually improved. The average annual NPP simulated by CASA was 266.81 g C-m-2-a-1 The variation trend of NPP in vegetation showed a slight decrease, but the overall NPP level was basically unchanged. There is a significant correlation between NPP and population density, a negative correlation between NPP and population density areas such as city centers, and a positive correlation between NPP and population density in areas with frequent agricultural activities. From 2010 to 2020, there is a significant positive correlation between population density and land use. [ABSTRACT FROM AUTHOR]

Predicting abnormal conditions in flotation processes is vital for safety, efficiency, and product quality. However, existing studies lack predictions of abnormal working conditions in flotation processes and neglect temporal information in data. To address this, this paper proposes a novel approach for predicting abnormal work conditions in flotation processes. It utilizes a dual attention mechanism and multivariate information fusion. Features are extracted from froth images using the Xception model, a pre‐trained convolutional neural network. These features are combined with flotation process monitoring variables, creating fused data. An encoder and decoder time feature seq2seq (EDTF‐seq2seq) model with time and feature attention modules enables end‐to‐end information fusion and work condition prediction. The attention modules assign weights to each feature point, capturing the time–feature relationship and improving prediction accuracy. Four sets of experiments using real flotation process data validate the effectiveness of the proposed method, achieving favourable prediction accuracy. [ABSTRACT FROM AUTHOR]