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Decision-making for collision avoidance in complex maritime environments is a critical technology in the field of autonomous ship navigation. However, existing collision avoidance decision algorithms still suffer from unstable strategy exploration and poor compliance with regulations. To address these issues, this paper proposes a novel autonomous ship collision avoidance algorithm, the dynamically adjusted entropy proximal policy optimization (DAE-PPO). Firstly, a reward system suitable for complex maritime encounter scenarios is established, integrating the International Regulations for Preventing Collisions at Sea (COLREGs) with collision risk assessment. Secondly, the exploration mechanism is optimized using a quadratically decreasing entropy method to effectively avoid local optima and enhance strategic performance. Finally, a simulation testing environment based on Unreal Engine 5 (UE5) was developed to conduct experiments and validate the proposed algorithm. Experimental results demonstrate that the DAE-PPO algorithm exhibits significant improvements in efficiency, success rate, and stability in collision avoidance tests. Specifically, it shows a 45% improvement in success rate per hundred collision avoidance attempts compared to the classic PPO algorithm and a reduction of 0.35 in the maximum collision risk (CR) value during individual collision avoidance tasks.

This article considered the sampled-data control issue for a dynamic positioning ship (DPS) with the Takagi-Sugeno (T-S) fuzzy model. By introducing new useful terms such as second-order term of time, an improved Lyapunov-Krasovskii function (LKF) was constructed. Additionally, the reciprocally convex method is introduced to bound the derivative of LKF. According to the constructed LKF, the sampling information during the whole sampling period was fully utilized, and less conservatism was obtained. Then, the stability condition, robust performance, mode uncertainty and sampled-data controller design were analyzed by means of the linear matrix inequality (LMI). Finally, an example was given to demonstrate the effectiveness of the proposed method.

Based on the phase transition of vanadium dioxide(VO2), an ultra-broadband tunable terahertz metamaterial absorber is proposed. The absorber consists of bilayer VO2 square ring arrays with different sizes, which are completely wrapped in Topas and placed on gold substrate. The simulation results show that the absorption greater than 90% has frequencies ranging from 1.63 THz to 12.39 THz, which provides an absorption frequency bandwidth of 10.76 THz, and a relative bandwidth of 153.5%. By changing the electrical conductivity of VO2, the absorption intensity can be dynamically adjusted between 4.4% and 99.9%. The physical mechanism of complete absorption is elucidated by the impedance matching theory and field distribution. The proposed absorber has demonstrated its properties of polarization insensitivity and wide-angle absorption, and therefore has a variety of application prospects in the terahertz range, such as stealth, modulation, and sensing.

Wild Arachis species exhibit abundant genetic diversity for peanut improvement. However, the evolutionary history of their genomes is unclear. Here, through comparative oligopainting, we establish a one-to-one correspondence between microscopically observed chromosomes and sequenced pseudomolecules of Arachis duranensis , A. ipaensis , and cultivated peanut, and determine the 10 homoeologous groups (Hgs) of the A, B, F, K, and H genomes. Analysis of the telomere-to-telomere (T2T) genome assembly of A. hoehnei reveals that its genome is a diverging form of the A genome and is designated as genome A’. In addition, the unique small chromosome A08 is originated from two inversions and a substantial contraction of A'08. We propose a genome evolution model of the Arachis genus, where A’ bridges the A and B genomes. We further report an artificial hexaploid peanut derived from a hybrid of cultivated peanut and A. hoehnei , and identify differentially expressed genes against web blotch in A. hoehnei . Genome evolutionary history of wild Arachis species remains unclear. Here, the authors report the origin of small chromosome A08 and genome evolution of Arachis species via comparative oligopainting and genomic analysis of A. hoehnei .

We develop a theoretical model to account for the effect of learning goal orientation on creative performance by distinguishing two dimensions of intrinsic motivation as mediators. Challenge intrinsic motivation is concerned with the interest in and excitement of solving problems and tackling complex tasks, whereas enjoyment intrinsic motivation is concerned with the enjoyment of task activities for self-expression and self-entertainment. Results from a sample of 189 Chinese employees support this model and show that learning goal orientation had significant positive relationships with both dimensions of intrinsic motivation, but only challenge intrinsic motivation was significantly related to creative performance and mediated the positive relationship between learning goal orientation and creative performance. As predicted, intellectual stimulation, a dimension of transformational leadership, showed a moderating effect, such that learning goal orientation was less strongly related to challenge intrinsic motivation when intellectual stimulation was high. In addition, a moderated mediation effect was found, such that the mediating effect of challenge intrinsic motivation for the relationship between learning goal orientation and creative performance was weaker when intellectual stimulation was high. No such moderation effect was found for enjoyment intrinsic motivation, providing further support for the differential roles of these two dimensions of intrinsic motivation.

This study investigates the sampled-data admissibility problem for a singular system. The objective of this paper is to design a sampled-data controller to ensure the admissibility of a singular system and to construct an appropriate Lyapunov–Krasovskii functional (LKF) to get less conservative results for the sampled-data singular system. To accomplish these objectives, the system is converted into a time-delay system by the input delay approach firstly, and both lower and upper bounds of the delay are considered. Secondly, by introducing a suitable LKF, the admissibility criteria are obtained. Then, when estimating the derivative of the LKF, a relaxation variable is introduced by the method of reciprocally convex inequality, and it is proved that the conservatism is reduced. Finally, two numerical examples are given to prove that the designed sampled-data controller can ensure the states of the systems under the influence of external interference.

Existing research on auto-berthing of ships has mainly focused on the design and implementation of controllers for automatic berthing. For the real automatic docking processes, not only do external environmental perturbations need to be taken into account but also motion paths, docking strategies and ship mechanical constraints, which are important influential factors to measure autonomous docking methods. Through a literature review of ship path planning and motion control for automatic berthing, it is found that many studies ignore the interference of the actual navigational environment, especially for ships sailing at slow speed when berthing, or do not consider the physical constraints of the steering gear and the main engine. In this paper, we propose a hybrid approach for autonomous berthing control systems based on a Linear Quadratic Regulator (LQR) and Covariance Matrix Adaptation Evolution Strategy (CMA-ES), which systematically addresses the problems involved in the berthing process, such as path planning, optimal control, adaptive berthing strategies, dynamic environmental perturbations and physically enforced structural constraints. The berthing control system based on the LQR and modified LQR-CMA-ES have been validated by simulation work. The simulation results show that the proposed method is able to achieve the automatic docking of the ship well and the system is robust and well adapted to environmental disturbances at slow speed when docking.

The APETALA2 (AP2)/ethylene response factor plays vital functions in response to environmental stimulus. The ethylene response factor (ERF) subfamily B3 group belongs to the AP2/ERF superfamily and contains a single AP2/ERF domain. Phylogenetic analysis of the ERF subfamily B3 group genes from Arabdiposis thaliana, Gossypium arboreum, Gossypium hirsutum , and Gossypium raimondii made it possible to divide them into three groups and showed that the ERF subfamily B3 group genes are conserved in cotton. Collinearity analysis identified172 orthologous/paralogous gene pairs between G. arboreum and G. hirsutum ; 178 between G. hirsutum and G. raimondii ; and 1,392 in G. hirsutum . The GhERF subfamily B3 group gene family experienced massive gene family expansion through either segmental or whole genome duplication events, with most genes showing signature compatible with the action of purifying selection during evolution. Most G. hirsutum ERF subfamily B3 group genes are responsive to salt stress. GhERF13.12 transgenic Arabidopsis showed enhanced salt stress tolerance and exhibited regulation of related biochemical parameters and enhanced expression of genes participating in ABA signaling, proline biosynthesis, and ROS scavenging. In addition, the silencing of the GhERF13.12 gene leads to increased sensitivity to salt stress in cotton. These results indicate that the ERF subfamily B3 group had remained conserved during evolution and that GhERF13.12 induces salt stress tolerance in Arabidopsis and cotton.

Rivaroxaban is a direct oral anticoagulant (DOAC) that directly inhibits coagulation factor Xa and exerts its anticoagulant effects. Although rivaroxaban generally exhibits predictable pharmacokinetic (PK) and pharmacodynamic (PD) profiles, significant interindividual variability in therapeutic responses exists. Research on the role of genetic factors in the clinical variability of rivaroxaban is relatively new and extensive. In this review, 12 pharmacogenetic studies on rivaroxaban were summarised, and 25 reported gene polymorphic sites were summarised, including (rs1045642, rs4148738, rs1128503, rs2032582, rs4728709, rs3789243 and rs3213619, (rs2231142, rs2231137, rs3114018, rs2622604 and rs1481012), (rs35599367, rs2242480, rs4646437 and rs12333983), (rs776746, rs15524, rs4646450), (rs890293), (rs4244285 and rs12248560), (rs7212506), (rs1738023 and rs1738025). The review provided an overview of the current state of research on rivaroxaban gene polymorphisms. However, due to the significant heterogeneity of existing studies and the lack of consistency in results, the evidence to date has limited impact. Therefore, larger-scale, global, multi-centre clinical trials are needed in the future to validate potential gene loci for testing.

This paper addresses the path tracking problem of underactuated unmanned surface vessels (USVs) in the presence of unknown external disturbances. A fixed-time adaptive integral sliding mode control (AISMC) method, incorporating a nonlinear disturbance observer (NDO), is proposed. Initially, a three-degree-of-freedom dynamic model of the USV is developed, accounting for external disturbances and model uncertainties. Based on the vessel’s longitudinal and transverse dynamic position errors, a virtual control law is designed to ensure fixed-time convergence, thereby enhancing the position error convergence speed. Next, a fixed-time NDO is introduced to estimate real-time external perturbations, such as wind, waves, and currents. The observed disturbances are fed back into the control system for compensation, thereby improving the system’s disturbance rejection capability. Furthermore, a sliding mode surface is designed using a symbolic function to address the issue of sliding mode surface parameter selection, leading to the development of the adaptive integral sliding mode control strategy. Finally, compared with traditional SMC and PID, the proposed AISMC-NDO offers higher accuracy, faster convergence, and improved robustness in complex marine environments.