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Ship detection has been an area of focus for high-frequency surface wave radar (HFSWR). The detection and identification of ship formation have proven significant in early warning, while studies on the formation identification are limited due to the complex background and low resolution of HFSWR. In this paper, we first establish a spatial distribution model of ship formation in HFSWR. Then, we propose a cascade identification algorithm of ship formation in the clutter edge. The proposed algorithm includes a preprocessing stage and a two-stage formation identification stage. The Faster R-CNN is introduced in the preprocessing stage to locate the clutter regions. In the first stage, we propose an extremum detector based on connected regions to extract suspicious regions. The suspicious regions contain ship formations, single-ship targets, and false targets. In the second stage, we design a network connected by a convolutional neural network (CNN) and an extreme learning machine (ELM) to identify two densely distributed ship formations from inhomogeneous clutter and single-ship targets. The experimental results based on the factual HFSWR background demonstrate that the proposed cascade identification algorithm is superior to the extremum detector combined with the classical CNN algorithm for ship formation identification. Meanwhile, the proposed algorithm performs well in weak formation and deformed formation identification. [ABSTRACT FROM AUTHOR]

This paper proposes a method for the intelligent detection of high-frequency surface wave radar (HFSWR) targets. This method cascades the adaptive constant false alarm (CFAR) detector variability index (VI) with the convolutional neural network (CNN) to form a cascade detector (VI)CFAR-CNN. First, the (VI)CFAR algorithm is used for the first-level detection of the range–Doppler (RD) spectrum; based on this result, the two-dimensional window slice data are extracted using the window with the position of the target on the RD spectrum as the center, and input into the CNN model to carry out further target and clutter identification. When the detection rate of the detector reaches a certain level and cannot be further improved due to the convergence of the CNN model, this paper uses a dual-detection maps fusion method to compensate for the loss of detection performance. First, the optimized parameters are used to perform the weighted fusion of the dual-detection maps, and then, the connected components in the fused detection map are further processed to achieve an independent (VI)CFAR to compensate for the (VI)CFAR-CNN detection results. Due to the difficulty in obtaining HFSWR data that include comprehensive and accurate target truth values, this paper adopts a method of embedding targets into the measured background to construct the RD spectrum dataset for HFSWR. At the same time, the proposed method is compared with various other methods to demonstrate its superiority. Additionally, a small amount of automatic identification system (AIS) and radar correlation data are used to verify the effectiveness and feasibility of this method on completely measured HFSWR data. [ABSTRACT FROM AUTHOR]

Investigating the dynamic evolution process of the ocean and ionosphere in sudden sea conditions poses a challenging problem. To address this objective, this study utilizes actual data from high-frequency surface wave radar (HFSWR) to analyze, validate, summarize, and characterize the echo properties of the ocean and ionosphere during the severe Typhoon Muifa. By employing the short-time Fourier transform (STFT) method, the HFSWR ocean and ionosphere echoes stimulated by typhoon-induced gravity waves are observed, and the joint gravity wave features of the ocean and ionosphere echoes at different time scales are extracted. Additionally, the phase-space reconstruction method is employed to characterize the dynamical evolution of the joint gravity wave features in higher-dimensional space. Furthermore, the chaotic dynamics behavior of the joint gravity wave features is analyzed using the largest Lyapunov exponents. By combining the gravity wave features with chaotic dynamics, this study introduces a method to characterize the joint gravity wave features. The extraction of joint gravity wave features in HFSWR echoes stimulated by typhoons, along with the construction of a chaotic characterization scheme for the gravity wave features, provides an innovative approach and a solid technical foundation for studying the ocean and ionosphere using HFSWR under sudden sea conditions. [ABSTRACT FROM AUTHOR]

The problem of accurate source localization has been an area of focus in high-frequency surface wave radar (HFSWR) applications. However, antenna pattern distortion (APD) decreases the direction-of-arrival (DOA) estimation performance of the multiple signal classification (MUSIC) algorithm. Up to now, limited studies have been conducted on the calibration of antenna pattern distortion for phased arrays in HFSWR. In this paper, we first analyze the effect of APD on the performance of the MUSIC algorithm through estimation of accuracy and angular resolution. We demonstrate that using the actual pattern (or say APD) can improve DOA estimation performance. Based on this proposition, we propose a novel iterative calibration method that employs the first-order sea clutter data and can jointly estimate DOA and APD in an iterative way. To obtain available calibration points, we introduce the extraction methods of the first-order sea clutter spectrum and single-DOA spectrum points. Meanwhile, in each iteration, the Beamspace MUSIC algorithm and artificial hummingbird algorithm (AHA) are utilized to estimate the DOA and APD, respectively. Numerical results reveal a good coincidence between the actual pattern and the estimated APD. We also apply this method to process the experimental data of HFSWR. We obtain the APD vector of the real phased array and improve the direction-finding performance of several real ship targets using this vector. Both numerical and experimental results prove the correctness of our proposed calibration method. [ABSTRACT FROM AUTHOR]

The gravity wave produced by typhoons has been an essential subject of study that concerns numerous researchers. The damage to human beings and infrastructure in coastal regions caused by typhoon disasters annually is very severe, and analyzing gravity wave variation is a reliable approach to research typhoons. High-frequency surface wave radar (HFSWR) as an over-the-horizon radar can achieve real-time monitoring of an extensive sea area and space. This paper derived the gravity wave perturbation spectrum by handling high-frequency surface wave radar data during typhoons. The gravity wave spectrum data were examined by applying the chaos examination approaches of the Lyapunov exponent and phase-space reconstruction to the gravity wave spectrum data after processing and extraction. The reconstructed phase space had a specific shape in a certain direction, with the maximum Lyapunov exponent greater than zero. The gravity wave spectrum data are suggested to have chaotic properties through two chaos examination approaches. This paper demonstrated that the gravity waves observed by a radar have chaotic properties through the measurement data of HFSWR. While the chaotic properties suggest that observed gravity wave data are predictable in the short term, they are unpredictable in the long term. Predicting gravity wave data is important for understanding the chaotic properties of the atmosphere and for future gravity wave prediction. [ABSTRACT FROM AUTHOR]

In radar array signal processing, weak nonstationary polarization signal direction of arrival (DOA) estimation is a challenging and significant issue when both strong and weak nonstationary signals coexist. Time-frequency (T-F) analysis is an effective method to deal with nonstationary signals. In the last decade, spatial time-frequency distributions (STFDs) have been proposed for multiple dual-polarization antenna arrays and efficaciously used for nonstationary signal DOA estimation. In this article, we introduced a novelty means for estimating weak nonstationary polarization signal DOA by utilizing spatial polarimetric time-frequency distributions (SPTFDs) of cross terms when there are strong nonstationary polarization interference signals and additive Gaussian white noise. The cross terms' SPTFDs are considered via a replaceability matrix for data covariance in multiple signal classification (MUSIC) and the estimation of signal parameters using the rotational invariance technique (ESPRIT). Combining the STFDs of cross terms with polarization information about weak nonstationary signals improves signal DOA estimation accuracy. The combined MUSIC and ESPRIT are used in the algorithm to further ensure the success probability and accuracy of DOA estimation. Through simulation analyses, the proposed algorithm is more suitable for the required application scenarios than other algorithms and is superior to other algorithms. [ABSTRACT FROM AUTHOR]

The coast–ship bistatic high-frequency surface wave radar (HFSWR) not only has the anti-interference advantages of the coast-based bistatic HFSWR, but also has the advantages of maneuverability and an extended detection area of the shipborne HFSWR. In this paper, theoretical formulas were derived for the coast–ship bistatic radar, including the first-order sea clutter scattering cross-section and the Doppler frequency shift of moving targets. Then, simulation results of the first-order sea clutter spectrum under different operating conditions were given, and the range of broadening of the first-order sea clutter spectrum and its influence on target detection were investigated. The simulation results show the broadening ranges of the right sea clutter spectrum and left sea clutter spectrum were symmetric when the shipborne platform was anchored, whereas they were asymmetric when the shipborne platform was underway. This asymmetry is primarily a function of platform velocity and radar frequency. Based on experimental data of the coast–ship bistatic HFSWR conducted in 2019, the broadening range of the sea clutter and the target frequency shift were analyzed and compared with simulation results based on the same parameter configuration. The agreement of the measured results with the simulation results verifies the theoretical formulas. [ABSTRACT FROM AUTHOR]

An accurate and stable prediction of the corrosion rate of natural gas pipelines has a major impact on pipeline material selection, inhibitor filling process, and maintenance schedules. At present, corrosion data are impacted by non-linearity and noise interference. The traditional corrosion rate prediction methods often ignore noise data, and only a small number of researchers have carried out in-depth research on non-linear data processing. Therefore, an innovative hybrid prediction model has been proposed with four processes: data preprocessing, optimization, prediction, and evaluation. In the proposed model, a decomposing algorithm is applied to eliminate redundant noise and to extract the primary characteristics of the corrosion data. Stratified sampling is applied to separate the training set and the test set to avoid deviation due to the sampling randomness of small samples. An improved particle swarm optimization algorithm is applied to optimize the parameters of support vector regression. A comprehensive evaluation of this framework is also conducted. For natural gas pipelines in southwest China, the coefficient of determination and mean absolute percentage error of the proposed hybrid model are 0.925 and 5.73%, respectively, with better prediction performance compared to state-of-the-art models. The results demonstrate the best approach for improving the prediction accuracy of the proposed hybrid model. This can be applied to improve the corrosion control effect and to support the digital transformation of the corrosion industry. [ABSTRACT FROM AUTHOR]

Melatonin is an antioxidant that is widely distributed in plants and animals. It is a conservative molecule. In early studies, scientists often used isolation and identification techniques to observe whether the endogenous melatonin cycle in plants was related to the external photoperiod, plant growth, and development cycles, including seed germination, plant rooting, and floral induction. With the development of isolation and identification technology, there is ample evidence that plants possess a variety of melatonin-synthesis pathways. The comprehensive application of molecular biology, genomics, and computational biology has also led to a comprehensive understanding of the physiological functions of plant melatonin. In this paper, we not only highlight the candidate genes from Arabidopsis thaliana and Oryza sativa that might be contributing to increasing plant endogenous melatonin but also elucidate and characterize the role of melatonin in plant growth and development in response to biotic and abiotic stresses. [ABSTRACT FROM AUTHOR]

Salt and alkaline stress is one of the important problems restricting agricultural production and afforestation projects. This kind of stress will greatly limit the growth and development of forest trees. Recently, melatonin has been gradually realized as a strong kind of antioxidant due to its important regulatory and protective roles in the process of plant growth and development. This study takes Xin Lin 1 (Populus cathayana × canadansis 'Xin Lin 1') as the research object, and measures the changes of physiological indexes at different time points to verify the alleviation effect of melatonin under salt and alkaline stress. In this experiment, plants have different behaviors in the face of different levels of exogenous melatonin. Among them, low concentrations of melatonin (50 μM and 100 μM) were more helpful to reduce the levels of MDA and osmotic regulators in leaves. At this level, the SOD and CAT content in the leaves increased significantly. Melatonin at 800 μM was more inclined to induce POD, but its activity was not significantly induced. Overall, melatonin contributes to the secretion of ABA in plants and has a tendency to inhibit the content of SA. It is worth mentioning that the 100 μM melatonin treatment was more conducive to the secretion of IAA. To sum up, this experiment proves that melatonin has a dose effect in alleviating stress. [ABSTRACT FROM AUTHOR]

A convenient and fast multi-residue method for the efficient identification and quantification of 72 pesticides belonging to different chemical classes in red and white grape wines has been developed. The analysis was based on gas chromatography tandem quadrupole mass spectrometric determination (GC–MS/MS). The optimization strategy involved the selection of the amount of multi-walled carbon nanotubes (MWCNTs) and the number of cleanup procedure cycles for multi-plug filtration cleanup (m-PFC) to achieve ideal recoveries and reduce the sample matrix compounds in the final extracts. The optimized procedure obtained consistent recoveries between 70.2 and 108.8% (70.2 and 108.8% for white wine, and 72.3 and 108.4% for red wine), with relative standard deviations (RSDs) that were generally lower than 9.2% at the three spiking levels of 0.01, 0.05 and 0.1 mg/kg. The linearity was studied in the range between 0.002 and 0.1 mg/kg using pesticide standards prepared both in pure solvent and in the presence of the matrix, showing coefficients of determination (R2) higher than 0.9495 for all the pesticides. To improve accuracy, matrix-matched calibration curves were used for calculating the quantification results. Finally, the method was used successfully for detecting pesticide residues in commercial grape wines. [ABSTRACT FROM AUTHOR]

Consumer Perceived Corporate Social Responsibility Authenticity (CPCSRA) belongs to the field of micro Corporate Social Responsibility (CSR) research. In general, understanding the formation mechanism of CPCSRA could make it better able to play its role in several ways. Firstly, most previous studies do not empirically consider a key factor, i.e., the consumer perceived senior managers' involvement. We add this key factor into the independent variables of our formation mechanism. Secondly, most previous empirical research studies the relevant factors of consumer perceived CSR commitment as a whole. We study these relevant factors separately instead. Thirdly, we simultaneously choose the consumer perceived strategy-driven motive and consumer perceived value-driven motive as the mediating variables of our formation mechanism. Based on the above innovations, we comprehensively and systematically study the formation mechanism of CPCSRA. We use structural equation modeling to study the formation mechanism. For the convenience of data collection, our data are all from Chinese consumers. The study results show that three independent variables can directly affect CPCSRA. The three independent variables are consumer perceived level of invested resources, consumer perceived CSR efforts matching company and consumer perceived senior managers' involvement. Consumer perceived senior managers' involvement has the greatest effect. The two variables consumer perceived strategy-driven motive and consumer perceived value-driven motive play partial mediating effects on the relationship between independent variables and CPCSRA. Based on our empirical research, we put forward some feasible suggestions for company managers to increase company sustainability in market competition by promoting the formation of CPCSRA. [ABSTRACT FROM AUTHOR]

As bituminous binders greatly influence the engineering performance of gussasphalt concrete for bridge deck pavement, selecting appropriate bitumen is a critical procedure for mixture design. In this study, five different combinations of bituminous binder for potential use in the "Hong Kong–Zhuhai–Macao Bridge" project were prepared and tested. To meet the strict requirements of quality control, a new Guss-Mastic Asphalt (GMA) system was developed. Three key indices, Lueer fluidity, impact toughness, and dynamic stability, were used for GMA design and construction quality control. The test results show that the fluidity of the GMA mixtures was affected by the shear thinning phenomenon. After mixing for three hours, the Lueer value of all GMA mixtures met the requirements of pouring construction. Moreover, it was found that the influence of mixing time on GMA with styrene butadiene styrene (SBS) modified bitumen was different to other prepared mixtures. This difference is ascribed to the degradation of SBS during the blending process at an elevated temperature. Finally, the blended bitumen (30% Pen60/70 + 70% Trinidad lake asphalt (TLA)) was applied to the project of the Hong Kong–Zhuhai–Macao Bridge. [ABSTRACT FROM AUTHOR]