Explore the vast range of titles available.

An unmanned surface vehicle (USV) plans its global path before the mission starts. When dynamic obstacles appear during sailing, the planned global path must be adjusted locally to avoid collision. This study proposes a local path planning algorithm based on the velocity obstacle (VO) method and modified quantum particle swarm optimization (MQPSO) for USV collision avoidance. The collision avoidance model based on VO not only considers the velocity and course of the USV but also handles the variable velocity and course of an obstacle. According to the collision avoidance model, the USV needs to adjust its velocity and course simultaneously to avoid collision. Due to the kinematic constraints of the USV, the velocity window and course window of the USV are determined by the dynamic window approach (DWA). In summary, local path planning is transformed into a multiobjective optimization problem with multiple constraints in a continuous search space. The optimization problem is to obtain the USV’s optimal velocity variation and course variation to avoid collision and minimize its energy consumption under the rules of the International Regulations for Preventing Collisions at Sea (COLREGs) and the kinematic constraints of the USV. Since USV local path planning is completed in a short time, it is essential that the optimization algorithm can quickly obtain the optimal value. MQPSO is primarily proposed to meet that requirement. In MQPSO, the efficiency of quantum encoding in quantum computing and the optimization ability of representing the motion states of the particles with wave functions to cover the whole feasible solution space are combined. Simulation results show that the proposed algorithm can obtain the optimal values of the benchmark functions and effectively plan a collision-free path for a USV.

Terrestrial fossils from the Palaeogene of Tibet could help us to better understand the past climate and environment in this area. We herein report a new late Eocene non-marine fossil site from southern Nima Basin, central Tibet, SW China, including abundant insects and fishes. These fossils are similar to those from the late Eocene (∼39.5–37 Ma) Lunpola–Nima sediment depo-centres in sharing the dominating aquatic bug Aquarius lunpolaensis and cyprinid fishes. Chalcolestes tibetensis sp. nov., the oldest representative of the modern family Lestidae, is described. Lestidae were previously only recorded in Western Europe, and the oldest records were from the uppermost Eocene of France and the UK. The present discovery demonstrates that Lestidae already had a broad distribution during the Eocene and probably originated much earlier. The recent representatives of Chalcolestes occur in the low-altitude ponds or lakes of Western Palaearctic. Together with the other freshwater fossils in this site, this new discovery indicates a humid climate and low altitude for the Nima Basin and nearby basins in the middle part of the Bangong Nujiang suture zone.

This paper addresses the problem of integration of Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) for the purpose of developing a low-cost, robust and highly accurate navigation system for unmanned surface vehicles (USVs). A tightly-coupled integration approach is one of the most promising architectures to fuse the GNSS data with INS measurements. However, the resulting system and measurement models turn out to be nonlinear, and the sensor stochastic measurement errors are non-Gaussian and distributed in a practical system. Particle filter (PF), one of the most theoretical attractive non-linear/non-Gaussian estimation methods, is becoming more and more attractive in navigation applications. However, the large computation burden limits its practical usage. For the purpose of reducing the computational burden without degrading the system estimation accuracy, a quaternion-based adaptive unscented particle filter (AUPF), which combines the adaptive unscented Kalman filter (AUKF) with PF, has been proposed in this paper. The unscented Kalman filter (UKF) is used in the algorithm to improve the proposal distribution and generate a posterior estimates, which specify the PF importance density function for generating particles more intelligently. In addition, the computational complexity of the filter is reduced with the avoidance of the re-sampling step. Furthermore, a residual-based covariance matching technique is used to adapt the measurement error covariance. A trajectory simulator based on a dynamic model of USV is used to test the proposed algorithm. Results show that quaternion-based AUPF can significantly improve the overall navigation accuracy and reliability.

Methicillin-resistant Staphylococcus aureus (MRSA) is a frequent cause of difficult-to-treat, often fatal infections in humans 1 , 2 . Most humans have antibodies against S. aureus , but these are highly variable and often not protective in immunocompromised patients 3 . Previous vaccine development programs have not been successful 4 . A large percentage of human antibodies against S. aureus target wall teichoic acid (WTA), a ribitol-phosphate (RboP) surface polymer modified with N -acetylglucosamine (GlcNAc) 5 , 6 . It is currently unknown whether the immune evasion capacities of MRSA are due to variation of dominant surface epitopes such as those associated with WTA. Here we show that a considerable proportion of the prominent healthcare-associated and livestock-associated MRSA clones CC5 and CC398, respectively, contain prophages that encode an alternative WTA glycosyltransferase. This enzyme, TarP, transfers GlcNAc to a different hydroxyl group of the WTA RboP than the standard enzyme TarS 7 , with important consequences for immune recognition. TarP-glycosylated WTA elicits 7.5–40-fold lower levels of immunoglobulin G in mice than TarS-modified WTA. Consistent with this, human sera contained only low levels of antibodies against TarP-modified WTA. Notably, mice immunized with TarS-modified WTA were not protected against infection with tarP -expressing MRSA, indicating that TarP is crucial for the capacity of S. aureus to evade host defences. High-resolution structural analyses of TarP bound to WTA components and uridine diphosphate GlcNAc (UDP-GlcNAc) explain the mechanism of altered RboP glycosylation and form a template for targeted inhibition of TarP. Our study reveals an immune evasion strategy of S. aureus based on averting the immunogenicity of its dominant glycoantigen WTA. These results will help with the identification of invariant S. aureus vaccine antigens and may enable the development of TarP inhibitors as a new strategy for rendering MRSA susceptible to human host defences. Strains of methicillin-resistant Staphylococcus aureus use a prophage-encoded glycosyltransferase to alter the glycosylation of their wall teichoic acid and thereby evade antibody-mediated immune responses.

This paper addresses multiple task assignment and path-planning problems for a multiple unmanned surface vehicle (USVs) system. Since it is difficult to solve multi-task allocation and path planning together, we divide them into two sub-problems, multiple task allocation and path planning, and study them separately. First, to resolve the multi-task assignment problem, an improved self-organizing mapping (ISOM) is proposed. The method can allocate all tasks in the mission area, and obtain the set of task nodes that each USV needs to access. Second, aiming at the path planning of the USV accessing the task nodes, an improved genetic algorithm (IGA) with the shortest path is proposed. To avoid USV collision during navigation, an artificial potential field function (APFF) is proposed. A multiple USV system with multi-task allocation and path planning is simulated. Simulation results verify the effectiveness of the proposed algorithms.

This paper presents a new cooperative control strategy for dynamic positioning of multiple surface vessels subject to unknown time-varying environmental disturbances and input saturation. The vessels are assumed interconnected through a directed topology rather than bidirectional. Two control objectives are considered in this paper. The first one is to make these vessels track desired positions and headings, and the other control objective is to hold the desired formation. For these purposes, we propose a cooperative control which consists of finite-time disturbance observer, auxiliary dynamic system and dynamic surface control technique. A nonlinear finite-time observer is developed to estimate unknown time-varying disturbance. To tackle the input saturation problem, an auxiliary dynamic system is constructed. It is also proved that all signals in the closed-loop control system converge to a small neighborhood of equilibrium state via Lyapunov analysis. Simulation results are given to validate the effectiveness of the proposed control strategy.

Staphylococcus aureus peptidoglycan (PG) is densely functionalized with anionic polymers called wall teichoic acids (WTAs). These polymers contain three tailoring modifications: d -alanylation, α- O -GlcNAcylation, and β- O -GlcNAcylation. Here we describe the discovery and biochemical characterization of a unique glycosyltransferase, TarS, that attaches β- O -GlcNAc (β- O - N -acetyl- d -glucosamine) residues to S. aureus WTAs. We report that methicillin resistant S. aureus (MRSA) is sensitized to β-lactams upon tarS deletion. Unlike strains completely lacking WTAs, which are also sensitive to β-lactams, Δ tarS strains have no growth or cell division defects. Because neither α- O -GlcNAc nor β- O -Glucose modifications can confer resistance, the resistance phenotype requires a highly specific chemical modification of the WTA backbone, β- O -GlcNAc residues. These data suggest β- O -GlcNAcylated WTAs scaffold factors required for MRSA resistance. The β- O -GlcNAc transferase identified here, TarS, is a unique target for antimicrobials that sensitize MRSA to β-lactams.

This manuscript investigates an output feedback-tracking control problem of a dynamically positioned vessel with an input constraint. The vessel is exposed to model uncertainty and external disturbances. Compared with the existing results, the primary contribution is to develop a switch-control strategy for achieving collision avoidance and performance constraints by using an extended state observer (ESO), a collision-avoidance controller (CAC), a prescribed performance controller, and an auxiliary dynamic system (ADS). The switch control strategy combined two different controllers, and an extended state observer (ESO) is designed. The ESO is employed to recover velocity information as well as unknown model uncertainty and external disturbances. A collision-risk-analysis module is introduced to evaluate whether there exists a risk of collision avoidance. Based on the analysis, the CASC can choose between a CAC and a PPC. An ADS is constructed to handle the input constraints. The CAC is employed by using an artificial potential function, the ADS, and the ESO. The PPC is designed based on an error constraint function, the ADS, and the ESO. The stability of the closed-loop control system is analyzed based on the Lyapunov direct method. Simulations prove the effectiveness of the presented control strategy.

This paper addresses the swarm tracking problem of multiple unmanned surface vehicles subjected to unknown time-varying environmental disturbance and input saturation. The main control objective of this paper is that USVs cluster to follow the virtual leader with the desired position and heading and are required to maintain a specified position separation relative to both neighbor vehicles. In order to achieve the design goal, we mainly focus on three aspects. Firstly, to estimate the external disturbance accurately and improve the convergence speed, a finite-time disturbance observer is designed. Secondly, an auxiliary dynamic system is introduced to solve the input saturation problem. Thirdly, an output feedback controller based on a finite-time disturbance observer and an auxiliary dynamic system is designed to achieve swarm control of multiple unmanned surface vehicles. The stability of the system is proved by the Lyapunov directly method. Finally, the simulation results show that the proposed control strategy is effective.

Biofilms are major contributors to delayed wound healing and there is a need for clinically relevant experimental models to assess theranostics. Microorganisms release volatile organic compounds (VOCs) and the ability to identify these in infected cutaneous wounds could lead to efficient non-invasive diagnosis. The aims here were to develop and assess bacterial biofilm formation and identify their VOC profiles in an in vitro model and validate in human ex vivo incisional and excisional cutaneous wound models. Biofilm development was assessed using multiple microscopy techniques with biofilm-forming deficient controls and quantified using metabolic and biomass assays; and VOC production measured by gas chromatography-mass spectrometry. The production of most VOCs was affected by biofilm development and model used. Some VOCs were specific either for planktonic or biofilm growth. The relative abundance of some VOCs was significantly increased or decreased by biofilm growth phase (P < 0.05). Some Staphylococcus aureus and Pseudomonas aeruginosa VOCs correlated with biofilm metabolic activity and biomass (R ≤ −0.5; ≥0.5). We present for the first time bacterial biofilm formation in human ex vivo cutaneous wound models and their specific VOC profiles. These models provide a vehicle for human skin-relevant biofilm studies and VOC detection has potential clinical translatability in efficient non-invasive diagnosis of wound infection.