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Aiming at the challenges to the accurate and stable heading control of underactuated unmanned surface vehicles arising from the nonlinear interference caused by the overlay and the interaction of multi interference, and also the uncertainties of model parameters, a heading control algorithm for an underactuated unmanned surface vehicle based on an improved backpropagation neural network is proposed. Based on applying optimization theory to realize that the underactuated unmanned surface vehicle tracks the desired yaw angle and maintains it, the improved momentum of weight is combined with an improved tracking differentiator to improve the robustness of the system and the dynamic property of the control. A hyperbolic tangent function is used to establish the nonlinear mappings an approximate method is adopted to summarize the general mathematical expressions, and the gradient descent method is applied to ensure the convergence. The simulation results show that the proposed algorithm has the advantages of strong robustness, strong anti-interference and high control accuracy. Compared with two commonly used heading control algorithms, the accuracy of the heading control in the complex environment of the proposed algorithm is improved by more than 50%.

In this paper, a novel dynamic surface sliding mode control (DSSMC) method, combined with a lateral velocity tracking differentiator (LVTD), is proposed for the cooperative formation control of underactuated unmanned surface vehicles (USVs) exposed to complex marine environment disturbances. Firstly, in view of the kinematic and dynamic models of USVs and the design idea of a virtual control law in a backstepping approach, the trajectory tracking control problem of USVs’ cooperative formation is transformed into a stabilisation problem of the virtual control law of longitudinal and lateral velocities. Then, aiming at the problem of differential explosion caused by repeated derivation in the process of backstepping design, the first-order low-pass filter about the virtual longitudinal velocity and intermediate state quantity of position is constructed to replace differential calculations during the design of the control law, respectively. In order to reduce the steady-state error when stabilising the virtual lateral velocity control law, the integral term is introduced into the design of the sliding mode surface with a lateral velocity error, and then the second-order sliding mode surface with an integral is structured. In addition, due to the problem of controller oscillation and the role of the tracking differentiator (TD) in active disturbance rejection control (ADRC), the LVTD is designed to smooth the state quantity of lateral velocity. Subsequently, based on the dynamic model of USV under complex marine environment disturbances, the nonlinear disturbance observer is designed to observe the disturbances and compensate the control law. Finally, the whole cooperative formation system is proved to be uniformly and ultimately bounded, according to the Lyapunov stability theory, and the stability and validity of the method is also verified by the simulation results.

Addressing the complexity of cigarette ingredients and the challenges in brand identification, a cigarette brand identification model based on Projection Pursuit based on Fisher's Criterion (PPF) and hyperspectral technology was proposed. Firstly, the PPF projection algorithm was employed to conduct spectral similarity analysis on the original spectra as well as those processed with Multiplicative Scatter Correction (MSC), first-order derivative (1st D), and second-order derivative (2ndD). Secondly, feature wavelength selection was carried out using Successive Projections Algorithm (SPA) and Genetic Algorithm (GA) to enhance the classification performance in subsequent steps. Finally, cigarette brand identification models were established using Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) algorithms, and the personality of the model was evaluated. The results indicated that, in the combination of hyperspectral technology and the PPF projection algorithm, the second-order derivative (2nd D) served as the optimal band processing method, significantly enhancing the spectral separability. The recognition model established based on 2ndD-SPA-SVM emerged as the best model, achieving an overall classification accuracy of 94. 58% and 92. 50% for the training and test sets respectively. Moreover, a greater difference in the proportion of leaf silk and expanded silk among different brand formulations led to a lower similarity value between categories and a higher recognition accuracy. This model can provide a new efficient, fast, accurate, and non-destructive classification and discrimination method for cigarettes of different grades. It offered theoretical support for the application of hyperspectral technology in cigarette brand maintenance, tobacco blend formulation design, and other scenarios. [ABSTRACT FROM AUTHOR]

When gas fuel is used in solid oxide fuel cells, methane cracking occurs at high temperature in the Ni-based anode, forming granular carbon deposition in the active site of the anode, and finally completely wrapped Ni metal, greatly losing the electrochemical performance. Therefore, it is very necessary to add a reforming catalytic layer in the anode of the battery. The methane is reformed into CO and H2 fuel before entering the anode, and the place where methane cracking occurs is mostly transferred to the reforming layer, which reduces the catalytic reforming burden of the Ni-based anode, so as to effectively improve the battery performance. In this paper, Sr2Fe1.5Mo0.5O6 with double perovskite structure was synthesized and prepared, which maintained very good stability in high temperature REDOX atmosphere and had high electrical conductivity. The combination of GDC and SFM can increase the reaction site of the three-phase interface of the reforming layer, and also help to improve the thermal expansion matching between the reforming layer and anode. In this paper, the electrochemical performance of straight cell coated with SSFM-GDC reforming layer has been studied. Low concentration gas in coal mine contains methane, oxygen, nitrogen, and water hydrogen sulfide, etc., and its reaction process in solid oxide fuel cells is complicated. Therefore, studying the reaction mechanism of low concentration gas in solid oxide fuel cells has important practical significance for promoting its application.

Fish body measurement is essential for monitoring fish farming and evaluating growth. Non-destructive underwater measurements play a significant role in aquaculture management. This study involved annotating images of fish in aquaculture settings and utilized a line laser for underwater distance calibration and fish body inclined-angle calculation. The YOLOv8 model was employed for fish identification and key-point detection, enabling the determination of actual body dimensions through a mathematical model. The results show a root-mean-square error of 6.8 pixels for underwater distance calibration using the line laser. The pre-training YOLOv8-n, with its lower parameter counts and higher MAP values, proved more effective for fish identification and key-point detection, considering speed and accuracy. Average body length measurements within 1.5 m of the camera showed a minor deviation of 2.46% compared to manual measurements. The average relative errors for body length and width were 2.46% and 5.11%, respectively, with corresponding average absolute errors. This study introduces innovative techniques for fish body measurement in aquaculture, promoting the digitization and informatization of aquaculture processes. [ABSTRACT FROM AUTHOR]

Feline panleukopenia virus (FPV) is a single-stranded DNA virus that can infect cats and cause feline panleukopenia, which is a highly contagious and fatal disease in felines. The sequence of FPV is highly variable, and mutations in the amino acids of its capsid protein play crucial roles in altering viral virulence, immunogenicity, host selection, and other abilities. In this study, the epidemiology of FPV was studied using 746 gastrointestinal swab samples derived from cats that presented gastrointestinal symptoms specifically, diarrhea or vomiting during the period spanning from 2018 to 2022. The overall prevalence of FPV-positive patients among these samples was determined to be 45.4%. Capsid (virion) protein 2 (VP2) gene of each FPV-positive sample was sequenced and amplified, yielding 65 VP2 sequences. Among them, six VP2 gene sequences were detected in the majority of the samples test positive for FPV, and these positive samples originated from a diverse range of geographical locations. These isolates were named FPV-6, FPV-10, FPV-15, FPV-251, FPV-271 and FPV-S2. Additionally, the substitution of Ala300Pro (A300P) in VP2 was detected for the first time in feline-derived FPV (FPV-251). FPV-251 isolate, with this substitution in VP2 protein, exhibited stable proliferative capacity in Madin-Darby canine kidney (MDCK) cells and A72 cells. FPV-271 was selected as the FPV control isolate due to its single amino acid difference from VP2 protein of FPV-251 at position 300 (FPV-271 has alanine, while FPV-251 has proline). After oral infection, both FPV-251 and FPV-271 isolates caused feline panleukopenia, which is characterized by clinical signs of enterocolitis. However, FPV-251 can infect dogs through the oral route and cause gastrointestinal (GI) symptoms with lesions in the intestine and mesenteric lymph nodes (MLNs) of infected dogs. This is the first report on the presence of an A300P substitution in VP2 protein of feline-derived FPV. Additionally, FPV isolate with a substitution of A300P at VP2 protein demonstrated efficient replication capabilities in canine cell lines and the ability to infect dogs. [ABSTRACT FROM AUTHOR]