Search

With the rapid advancements in computer vision, ship detection models based on deep learning have been more and more prevalent. However, most network methods use expensive costs with high hardware equipment needed to increase detection accuracy. In response to this challenge, a lightweight real-time detection approach called YOLOSeaShip is proposed. Firstly, derived from the YOLOv7-tiny model, the partial convolution was utilized to replace the original 3×1 convolution in the ELAN module to further fewer parameters and improve the operation speed. Secondly, the parameter-free average attention module was integrated to improve the locating capacity for the hull of a ship in an image. Finally, the accuracy changes of the Focal EIoU hybrid loss function under different parameter changes were studied. The practical results trained on the SeaShips (7000) dataset demonstrate that the suggested method can detect and classify the ship position from the image more efficiently, with mAP of 0.976 and FPS of 119.84, which is ideal for real-time ship detection applications.

Abstract In order to enhance the performance of safety and fuel economy of connected hybrid electric vehicles (CHEVs), a novel distributed hierarchical platoon control scheme of CHEVs is proposed. First, the non‐linear dynamic model of CHEVs platooning is established to accurately depict the multi‐process coupling characteristics of CHEVs. Then, a distributed hierarchical control framework for CHEVs platooning is proposed, which is consisted of a upper model predictive control (MPC) law and a lower energy management control law. The upper MPC control law is built to produce the desired accelerations of every vehicle in the platoon and the lower fuzzy‐based energy management control law is constructed to ensure the engine maintain at the rang of optimum working point and the motor work with the high efficiency of CHEVs platooning. Finally, the results manifest that the effectiveness of proposed platoon control scheme for CHEVs.

Abstract mRNA therapeutics are revolutionizing the pharmaceutical industry, but methods to optimize the primary sequence for increased expression are still lacking. Here, we design 5’UTRs for efficient mRNA translation using deep learning. We perform polysome profiling of fully or partially randomized 5’UTR libraries in three cell types and find that UTR performance is highly correlated across cell types. We train models on our datasets and use them to guide the design of high-performing 5’UTRs using gradient descent and generative neural networks. We experimentally test designed 5’UTRs with mRNA encoding megaTALTM gene editing enzymes for two different gene targets and in two different cell lines. We find that the designed 5’UTRs support strong gene editing activity. Editing efficiency is correlated between cell types and gene targets, although the best performing UTR was specific to one cargo and cell type. Our results highlight the potential of model-based sequence design for mRNA therapeutics.

Jaw cyst is a fluid-containing cystic lesion that can occur in any part of the jaw and cause facial swelling, dental lesions, jaw fractures, and other associated issues. Due to the diversity and complexity of jaw images, existing deep-learning methods still have challenges in segmentation. To this end, we propose MARes-Net, an innovative multi-scale attentional residual network architecture. Firstly, the residual connection is used to optimize the encoder-decoder process, which effectively solves the gradient disappearance problem and improves the training efficiency and optimization ability. Secondly, the scale-aware feature extraction module (SFEM) significantly enhances the network’s perceptual abilities by extending its receptive field across various scales, spaces, and channel dimensions. Thirdly, the multi-scale compression excitation module (MCEM) compresses and excites the feature map, and combines it with contextual information to obtain better model performance capabilities. Furthermore, the introduction of the attention gate module marks a significant advancement in refining the feature map output. Finally, rigorous experimentation conducted on the original jaw cyst dataset provided by Quzhou People’s Hospital to verify the validity of MARes-Net architecture. The experimental data showed that precision, recall, IoU and F1-score of MARes-Net reached 93.84%, 93.70%, 86.17%, and 93.21%, respectively. Compared with existing models, our MARes-Net shows its unparalleled capabilities in accurately delineating and localizing anatomical structures in the jaw cyst image segmentation.

Background Idiopathic pulmonary fibrosis (IPF) is identified as a chronic, progressive lung disease, predominantly marked by enhanced fibroblast proliferation and excessive deposition of extracellular matrix. The intricate interactions between diverse molecular pathways in fibroblasts play a crucial role in driving the pathogenesis of IPF.

A trajectory-based guidance strategy is proposed for the three-dimensional terminal return task of an uncrewed space vehicle (USV). The overall guidance scheme consists of reference trajectory planning and robust trajectory tracking modules. The trajectory planning algorithm involves determining the motion of the USV to achieve a prescribed target under multiple constraints. The altitude-domain-based USV model is firstly proven to be differentially flat utilizing the dynamic pressure and position of the USV as flat outputs. The original trajectory planning problem is reformulated in a lower-dimensional flat output space. The discretization of the planning problem is then achieved using the pseudospectral method, based on which an initial guess technique is designed in order to accelerate the solving speed of the planning algorithm. Subsequently, a feedforward linearization-based trajectory tracking guidance law is designed using the differential flatness property of the altitude-domain model. Simulation results in different scenarios show that the proposed guidance strategy provides a satisfactory guidance solution.

This paper introduces three new gust load alleviation control strategies, which are based on variable camber technology, to achieve the design requirements for the safety, economy, and comfort of modern civil aircraft. These strategies involve adjusting the inner and outer flap differential of wings, spoilers, and ailerons to alter the aerodynamic shape of the aircraft structure, resulting in drag reduction and gust load alleviation during stepped cruise flights. Furthermore, a logic design is provided for both the cruise drag reduction function and the gust load alleviation function. To validate the effectiveness of the proposed gust load alleviation control strategies, simulation results are presented, utilizing ride quality and wing root bending moment changes as the evaluation criteria. The presented approaches ultimately lead to the development of an optimal scheme that meets the desired design requirements.

Although gene expression divergence has long been postulated to be the primary driver of human evolution, identifying the genes and genetic variants underlying uniquely human traits has proven to be quite challenging. Theory suggests that cell-type-specific cis-regulatory variants may fuel evolutionary adaptation due to the specificity of their effects. These variants can precisely tune the expression of a single gene in a single cell-type, avoiding the potentially deleterious consequences of trans-acting changes and non-cell type-specific changes that can impact many genes and cell types, respectively. It has recently become possible to quantify human-specific cis-acting regulatory divergence by measuring allele-specific expression in human-chimpanzee hybrid cells—the product of fusing induced pluripotent stem (iPS) cells of each species in vitro. However, these cis-regulatory changes have only been explored in a limited number of cell types. Here, we quantify human-chimpanzee cis-regulatory divergence in gene expression and chromatin accessibility across six cell types, enabling the identification of highly cell-type-specific cis-regulatory changes. We find that cell-type-specific genes and regulatory elements evolve faster than those shared across cell types, suggesting an important role for genes with cell-type-specific expression in human evolution. Furthermore, we identify several instances of lineage-specific natural selection that may have played key roles in specific cell types, such as coordinated changes in the cis-regulation of dozens of genes involved in neuronal firing in motor neurons. Finally, using novel metrics and a machine learning model, we identify genetic variants that likely alter chromatin accessibility and transcription factor binding, leading to neuron-specific changes in the expression of the neurodevelopmentally important genes FABP7 and GAD1. Overall, our results demonstrate that integrative analysis of cis-regulatory divergence in chromatin accessibility and gene expression across cell types is a promising approach to identify the specific genes and genetic variants that make us human.

Multi-degree-of-freedom piezoelectric motors have the advantages of high torque and resolution, simple structure, and direct drive, which are widely used in robot wrist joints, deep-sea mechanisms, medical equipment, and space mechanisms. To solve the problems of high force/torque coupling degree and ball low stator and rotor bonding strength of the traditional traveling wave type three-degree-of-freedom piezoelectric spherical motor, a new structure of ball-hinged piezoelectric spherical motor is proposed. Through coordinate transformation and force analysis, the driven mathematical model of the spherical motor is given. The model shows that the three degrees of freedom of the motor are coupled with each other. According to the mathematical model of the spherical motor, the mechanical properties of the motor are analyzed by the computer simulation. The results show that the stalling torque coefficient kt has a linear relationship with the friction coefficient ε and the stator preload Fc, has a nonlinear relationship with the stator radius R and the rotor radius r, and increases with the increase of R and decreases with the increase of r. The no-load speed of motor ωn is not related to the friction coefficient ε and the stator preload Fc, and increases with the increase of R and decreases with the increase of r. The anisotropic characteristics of torque and speed of a spherical motor are further analyzed, which lays a theoretical foundation for the drive control of a spherical motor.

A Kevlar tether usually exhibits strong nonlinearity in engineering applications, bringing new challenges to the modeling of tether dynamics. The nonlinear mechanical behaviors, including creep behavior, nonlinear stiffness, hysteresis effect, and dynamical property of a Kevlar tether, are investigated through a series of experiments. The longitudinal loading experiment setup is established, from which the relationships between tether deformation, tension, and time can be obtained. The creep process of Kevlar tethers is divided into three stages, namely, linear creep stage, deceleration creep stage, and long-term creep stage. This paper studied the longitudinal nonlinear stiffness of a Kevlar tether, whose nonlinearity is fitted by the cubic function model. The hysteresis effect under single loading and unloading is fitted well by the Kawabata stress-strain model, which verifies the correctness and validity of Kawabata model. The nonlinear dynamical model, which includes the elastic force, hysteresis force, and damping force, is established to describe the general dynamical property of the Kevlar tether. The experiment results verify the correctness of the dynamical model form. To simplify the analysis, a simplified model is proposed to describe the dynamical property of the Kevlar tether, and the parameters have a good consistency. The works in this paper contribute to the accurate modeling of flexible tether and lay the foundation for the further research of tether dynamics and control.

Unmanned aerial vehicles (UAVs) multi-area coverage-path planning has a broad range of applications in agricultural mapping and military reconnaissance. Compared to homogeneous UAVs, heterogeneous UAVs have higher application value due to their superior flexibility and efficiency. Nevertheless, variations in performance parameters among heterogeneous UAVs can significantly amplify computational complexity, posing challenges to solving the multi-region coverage path-planning problem. Consequently, this study studies a clustering-based method to tackle the multi-region coverage path-planning problem of heterogeneous UAVs. First, the constraints necessary during the planning process are analyzed, and a planning formula based on an integer linear programming model is established. Subsequently, this problem is decomposed into regional allocation and visiting order optimization subproblems. This study proposes a novel clustering algorithm that utilizes centroid iteration and spatiotemporal similarity to allocate regions and adopts the nearest-to-end policy to optimize the visiting order. Additionally, a distance-based bilateral shortest-selection strategy is proposed to generate region-scanning trajectories, which serve as trajectory references for real flight. Simulation results in this study prove the effective performance of the proposed clustering algorithm and region-scanning strategy.

This study presents a numerical investigation of suction control in an aggressive S-shaped air intake with large boundary ingestion. The results show that the variation of suction control parameters such as suction location, suction pipe diameter, and suction angle all have an impact on the effectiveness of the flow control. In general, further upstream suction, such as near the throat, is favorable for the decrease of the second flow intensity and the area of the low-energy fluid region at the exit of the S-shaped inlet. However, it is bad for the total pressure recovery and the circumferential total pressure uniform distribution. From the perspective of the uniformity of the total pressure distribution at the air intake exit, there is an optimal location for suction between the throat and the separation start point. A bigger suction pipe diameter brings better effects as the suction location and suction angle keep constant, due to more low-energy fluid being sucked out. But this doesn’t mean the largest mass flow suction results in the biggest improvement. Overall, sucking at the 1st bend, with suction angle and suction pipe diameter equaling 15 degrees and 12 mm, respectively, is the optimal suction scheme here. Since the change rule of the cross-section area along the centerline has not changed during suction control, the second flow and complex surface streamline at the air intake exit cannot be eliminated, though they can be decreased a lot with reasonable suction control. Similarly, owing to large boundary ingestion, the remarkable low-energy fluid region always exists despite the significant reduction of the separation and second flow, which is very different from the results of this kind of micro-suction executed in the non-BLI S-duct. To pursue a higher improvement, suction combined with vortex generator vanes has been further studied. Corresponding results analysis shows that the hybrid flow control method has great potential and should be investigated in detail in the future.

The purpose of this paper is to establish a transition strategy for tilt-rotor vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) based on an optimal design method. Firstly, The flyable transition corridor was calculated based on both the UAV’s dynamic equations and its aerodynamic and dynamic characteristics. The dynamic equations of the UAV were organized into state equation forms. The initial and final value constraints of the control and state variables in the transition process were recorded, as were the constraints of the transition process. The transition strategy design problem was transformed into an optimal control problem with constraints, while the Gauss pseudospectral method (GPM) was employed to transform and solve the problem. In addition, performance indicators were designed based on the transition quality requirements for transition time, attitude stability, and control continuity. Sensitivity was analyzed according to different index terms with different dimensions and effects. Finally, the rationality of the transition strategy designed in this paper was verified according to different simulation scenarios.

For a quadrotor unmanned aerial vehicle (UAV), this paper proposes an adaptive sliding mode control (SMC) strategy enhanced with a disturbance observer to attain precise trajectory and attitude tracking performance while compensating for the detrimental impacts of actuator faults and disturbances. First, an adaptive SMC strategy that utilizes an integral sliding surface is presented to enhance the fault-tolerance capabilities of the studied quadrotor UAV against actuator faults. In addition, a disturbance observer is further created to compensate for the disturbances. By integrating the proposed adaptive SMC strategy with the designed disturbance observer, both actuator faults and disturbances can be effectively accommodated. It was theoretically demonstrated that the system is stable while using the proposed adaptive fault-tolerant control strategy. The effectiveness and benefits of the proposed strategy is verified with comparative simulation results under different faulty scenarios.

Model uncertainties and external disturbances present significant challenges for controlling fixed-wing unmanned aerial vehicles (UAVs). An adaptive smooth second-order time-varying nonsingular fast terminal sliding mode control method is proposed in this paper for attitude and airspeed control of fixed-wing UAVs with model uncertainties and external disturbances. This control method does not require information about the bounds of disturbances and can avoid overestimation of the control gains. A radial basis function neural network observer is designed to mitigate the influence caused by sudden disturbances. The convergence of the attitude and airspeed controllers is proven by using the Lyapunov stability theory. Simulation results demonstrate the effectiveness of the proposed method for controlling a six-degrees-of-freedom fixed-wing UAV.

Autonomous landing is one of the key technologies for unmanned aerial vehicles (UAVs) which can improve task flexibility in various fields. In this paper, a vision-based autonomous landing strategy is proposed for a quadrotor micro-UAV based on a novel camera view angle conversion method, fast landing marker detection, and an autonomous guidance approach. The front-view camera of the micro-UAV video is first modified by a new strategy to obtain a top-down view. By this means, the landing marker can be captured by the onboard camera of the micro-UAV and is then detected by the YOLOv5 algorithm in real time. The central coordinate of the landing marker is estimated and used to generate the guidance commands for the flight controller. After that, the guidance commands are sent by the ground station to perform the landing task of the UAV. Finally, the flight experiments using DJI Tello UAV are conducted outdoors and indoors, respectively. The original UAV platform is modified using the proposed camera view angle-changing strategy so that the top-down view can be achieved for performing the landing mission. The experimental results show that the proposed landing marker detection algorithm and landing guidance strategy can complete the autonomous landing task of the micro-UAV efficiently.

RNA sequencing has been widely used as an essential tool to probe gene expression. While standard practices have been established to analyze RNA-seq data, it is still challenging to interpret and remove artifactual signals. Several biological and technical factors such as sex, age, batches, and sequencing technology have been found to bias these estimates. Probabilistic estimation of expression residuals (PEER), which infers broad variance components in gene expression measurements, has been used to account for some systematic effects, but it has remained challenging to interpret these PEER factors. Here we show that transcriptome diversity-a simple metric based on Shannon entropy-explains a large portion of variability in gene expression and is the strongest known factor encoded in PEER factors. We then show that transcriptome diversity has significant associations with multiple technical and biological variables across diverse organisms and datasets. In sum, transcriptome diversity provides a simple explanation for a major source of variation in both gene expression estimates and PEER covariates.

This paper proposes an adaptive fault-tolerant control strategy for a hybrid vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) to simultaneously compensate actuator faults and model uncertainties. With the proposed adaptive control schemes, both actuator faults and model uncertainties can be accommodated without the knowledge of fault information and uncertainty bounds. The proposed control scheme is constructed with two separate control modules. The low-level control allocation module is used to distribute the virtual control signals among the available redundant actuators. The high-level control module is constructed with an adaptive sliding mode controller, which is employed to maintain the overall system tracking performance in both faulty and uncertain conditions. In the case of actuator faults and model uncertainties, the adaptive scheme will be triggered to generate more virtual control signals to compensate the virtual control error and maintain the desired system tracking performance. The effectiveness of the proposed control strategy is validated through comparative simulation tests under different faulty and uncertain scenarios.

This paper presents an active fault-tolerant control strategy for quadrotor helicopters to simultaneously accommodate sensor faults and external disturbances. Unlike most of the existing fault diagnosis and fault-tolerant control schemes for quadrotor helicopters, the proposed fault diagnosis scheme is able to estimate sensor faults while eliminating the effect of external disturbances. Moreover, the proposed fault-tolerant control scheme is capable to eliminate the adverse effect of external disturbances as well by designing a disturbance observer to effectively estimate the unknown external disturbances and integrating with the designed integral sliding-mode controller. In this case, the continuous operation of the quadrotor helicopter is ensured while avoiding the unexpected control chattering. In addition, the stability of the closed-loop system is theoretically proved. Finally, the effectiveness and advantages of the proposed scheme are validated and demonstrated through comparative numerical simulations of the quadrotor helicopter under different faulty and uncertain scenarios.

The vibration of flexible structures in spacecraft, such as large space deployable reflectors, solar panels and large antenna structure, has a great impact on the normal operation of spacecraft. Accurate vibration control is necessary, and the control of angular displacement is a difficulty of accurate control. In the traditional control method, the mode space control has a good effect on suppressing low-order modes, but there is control overflow. The effect of traveling wave control on low-order modes is worse than the former, but it has the characteristics of broadband control. It can better control high-order modes and reduce control overflow. In view of the advantages and disadvantages of the two control methods, based on Timoshenko beam theory, this paper uses vector mode function to analyze the modal of spacecraft cantilever beam structure, establishes the system dynamic equation, and puts forward an optimized traveling wave control method. As a numerical example, three strategies of independent mode space control, traditional traveling wave control and optimized traveling wave control are used to control the active vibration of beam angle. By comparing the numerical results of the three methods, it can be seen that the optimal control method proposed in this paper not only effectively suppresses the vibration, but also improves the robustness of the system, reflecting good control performance. An innovation of this paper is that the Timoshenko beam model is adopted, which considers the influence of transverse shear deformation and moment of inertia on displacement and improves the accuracy of calculation, which is important for spacecraft accessory structures with high requirements for angle control. Another innovation is that the optimized traveling wave control method is exquisite in mathematical processing and has good results in global and local vibration control, which is not available in other methods.

(1) Background: Personalized product customization is an important direction in the development of the chair industry. This paper studies an intelligent design method for the rapid realization of personalized office chair customization; (2) Methods: based on the case-based reasoning (CBR) method, the characteristic attributes of office chair patterns are analyzed, and an attribute model is established. According to office chair data and customer demand, an intelligent design model using multi-layer weighted k-nearest neighbor (K-NN) for chair patterns is developed using the entropy weight method and an analytic hierarchy process. In addition, an example is employed for verification of the K-NN and multi-layer weighted K-NN retrieval models; (3) Results: both models are able to effectively retrieve chair type cases that meet the target requirements from the office chair pattern base; the case matching similarity of the multi-layer weighted K-NN retrieval model was higher, with an average increase of about 3.9%, and the chair pattern case results obtained by setting different customer needs are different, indicating that the case can be selected according to different customer preferences, which is more conducive to personalized product customization design; (4) Conclusions: The multi-layer weighted K-NN model for intelligent chair pattern design proposed in this paper is more conducive to personalized product customization design.

Based on the non-Fourier heat conduction wave model, the thermal wave scattering near the opening in the platinum–rhodium glass fiber leaky plate structure is studied by using complex function method and conformal mapping method, and the general solution of the thermal wave scattering problem is given. The boundary condition of the open surface is adiabatic. The influence of the geometrical and physical parameters of the leaky plate on the temperature distribution in the plate is analyzed, and the numerical results of the temperature concentration are given. This study can provide theoretical basis and reference data for the design and optimization of the opening structure of platinum–rhodium glass fiber leaky plate.

Swing usually occurs in the maneuver process of a tethered combination, which is constituted of a platform, a tether and a target (i.e., space debris) for capture. Therefore, a dynamical model of the space tethered combination was established, based on the maneuver of the mission platform in a short time. The conditions for the three swing formations of the tethered combination were obtained according to the analysis of the dynamical model. In order to solve the swing problem, anti-swing control strategies, based on linear feedback control, approximate linearization control and variable structure control, were proposed, respectively. Furthermore, simulation results verified the correctness and effectiveness of the above strategies. To test the validity of the control strategies, a ground experiment setup was built according to the similarity of dynamics. The experimental results show that linear feedback control and approximate linearization control can suppress the in-plane and out-of-plane swing of the combination rapidly.

With the application to engineering practice, the study of the scattering of thermal waves using innovative and comprehensive methods is becoming increasingly important. The thermal wave scattering by an elliptic subsurface hole in a block with two boundaries is discussed based on the non-Fourier heat conduction equation, employing the complex function method and the conformal mapping method, and a general solution for the thermal wave scattering is given. The numerical results of temperature distributions around a subsurface hole are presented and the effects of geometrical and physical parameters on the temperature distributions were analyzed. The wave number, the shape and position of the hole, the scale of the block, and the frequency of the heat load were found to have great effects on distributions and variations of temperature. The findings of this study could be helpful in providing better understandings of infrared thermal wave imaging, the physical inverse problem, and the evaluation of internal holes in materials.

This paper proposes and investigates a piezoelectric energy harvesting system based on the flow induced vibration of a piezoelectric composite cantilever pipe. Dynamic equations for the proposed energy harvester are derived considering the fluid-structure interaction and piezoelectric coupling vibration. Linear global stability analysis of the fluid-solid-electric coupled system is done using the numerical continuation method to find the neutrally stable vibration mode of the system. A measure of the energy harvesting efficiency of the system is proposed and analyzed. A series of simulations are conducted to throw light upon the influences of mass ratio, dimensionless electromechanical coupling, and dimensionless connected resistance upon the critical reduced velocity and the normalized energy harvesting efficiency. The results provide useful guidelines for the practical design of piezoelectric energy harvester based on fluid structure interaction and indicate some future topics to be investigated to optimize the device performance.