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Two-dimensional inlet is usually used in the wide-speed-range aircraft which has a higher flying velocity region. It is difficult to meet more requirements under both low-speed and high-speed flow conditions. Although the inlet perfor-mance could be improved by using jets to control shock waves on compression ramps, the existing jet excitation only push the shock wave toward the cowl, which may not achieve optimal performance. The optimization of jet control parameters is a significant problem. The effects of different optimization variables on inlet performance were investigated at Ma=6 based on Isight with the Hooke-Jeeves optimization method, in which different jet parameters were selected as optimization variables, flow coefficient was selected as constraint condition and maximum total pressure recovery coefficient was selected as objective function for optimization. The result show that the Hooke-Jeeves optimization method is able to optimize inlet with jet control. The optimized inlet can meet the requirements of flow coefficients. The total pressure recovery coefficient after optimizing the jet angle is increased by 18% compared to the inlet without jet, and the total pressure recovery coefficient after combination optimization is increased by 2.82% compared to only optimizing the jet angle.

Summary: The recycling of spent batteries is an important concern in resource conservation and environmental protection, while it is facing challenges such as insufficient recycling channels, high costs, and technical difficulties. To address these issues, a review of the recycling of spent batteries, emphasizing the importance and potential value of recycling is conducted. Besides, the recycling policies and strategies implemented in representative countries are summarized, providing legal and policy support for the recycling industry. Moreover, a comprehensive classification and comparison of recycling technologies identify the characteristics and current status of different approaches. The integrated recycling technology provides a better recycling performance with zero-pollution recycling of spent battery. Biorecycling technology is expected to gain a broad development prospect in the future owing to the superiority of energy-saving and environmental protection, high recycling efficiency, via microbial degradation, enzymatic degradation, etc. Consequently, as for the existing recycling challenges of waste batteries, developing new recycling technology and perfecting its recycling system is an indispensable guarantee for the sustainable development of waste battery. Meanwhile, theoretical support is offered for the recycling of spent batteries.

In this paper, the autonomous landing of the parafoil used for aerial vehicles is investigated through the numerical approach. The coupled parafoil-vehicle dynamics model is developed based on the multibody method. The transition process from aircraft flight to parafoil glide is designed in a global system framework. To deal with large flexible deformations during the deployment process, the parafoil canopy is approximated as interacting symmetric subparts using the geometric division method. The pseudo-spectral method is employed to generate a reference trajectory for the landing target. As the system dynamics are introduced into constraint conditions, the generated trajectory is beneficial to improve landing precision. In addition, other optimization objectives, including minimal energy consumption and obstacle avoidance, are considered in trajectory planning. The enhanced proportional integral control is designed to follow the reference trajectory. The neural network inversion model is used to reduce the coupling effect between the longitudinal and the directional control channels. There is a coupling effect that the two controls both are implemented through left and right trailing-edge deflections. An adaptive output allocation method is proposed to ensure that the directional control always is effective in particular when one side reaches saturation. Finally, simulations for autonomous landing under different conditions are carried out to validate the integrated system.

Abstract Background The treatment and management of patients suffering from hypophosphatemic rickets (HR) remain a major challenge for dental practitioners and affected patients. Objectives To report a case of HR presenting with specific dental findings and to review the dental manifestations and treatment of HR patients. Methods Case: A 32-year-old male presented with multiple dental abscesses and short stature. A thorough history was taken followed by clinical oral examination, and relevant radiological investigation was done. Literature research: In 2020, electronic literature searches were carried out in PubMed and complemented by a careful assessment of the reference lists of the identified relevant papers. Articles and reports fulfilled the inclusion criteria: indexed reviews, case series and case reports in English and restricted to human studies were considered. Results The intraoral examination revealed multiple dental abscesses and general periodontal disease; the radiographic examination showed poorly defined lamina dura, large pulp chambers and periapical lesions. Based on the contents of the 43 articles identified in the search, the current knowledge of dental manifestations, treatment and management of HR was summarized. Conclusions As HR is a multisystem disease, multidisciplinary care is needed. By summarizing current evidences, we proposed an evidence-based dental management and provided recommendations on diagnosis and treatment of the disease. It is of profound clinical significance to acquire knowledge of the dental manifestations and provide optimal treatment options for patients.

Recommender systems are widely used in e-commerce, movies, music, social media, and other fields because of their personalized recommendation functions. The recommendation algorithm is used to capture user preferences, item characteristics, and the items that users are interested in are recommended to users. Matrix factorization is widely used in collaborative filtering algorithms because of its simplicity and efficiency. However, the simple dot-product method cannot establish a nonlinear relationship between user latent features and item latent features or make full use of their personalized information. The model of a neural network combined with an attention mechanism can effectively establish a nonlinear relationship between the potential features of users and items and improve the recommendation accuracy of the model. However, it is difficult for the general attention mechanism algorithm to solve the problem of attention interaction when the number of features between the users and items is not the same. To solve the above problems, this paper proposes an attention interaction matrix factorization (AIMF) model. The AIMF model adopts a symmetric structure using MLP calculation. This structure can simultaneously extract the nonlinear features of user latent features and item latent features, thus reducing the computation time of the model. In addition, an improved attention algorithm named slide-attention is included in the model. The algorithm uses the sliding query method to obtain the user’s attention to the latent features of the item and solves the interaction problem among different dimensions of the user, and the latent features of the item.

The behavior of a nanosecond pulsed sliding discharge plasma actuator with the ambient pressure from 27 to 101 kPa is experimentally investigated. The electric characteristics, discharge morphologies, and surface temperature distribution of the actuator supplied by constant voltages are studied under different pressure conditions. The threshold pressure for sliding discharge establishment is 54–75 kPa in this paper. The results show that the positive peak value of the current tends to increase as the pressure decreases. Time-integrated discharge images indicate that plasma luminosity and uniformity are enhanced under low-pressure conditions. The discharge morphology of the actuator at 27 kPa displays an alternating distribution of bright and dark stripes. The infrared thermal results demonstrate that decreasing the pressure increases the actuator's surface temperature, intensifies the intensity of spanwise temperature oscillations, and improves the homogeneity in the streamwise direction.

Due to size limitations and the working environment near the ground, small low-altitude unmanned aerial vehicles (UAVs) cannot carry large-area solar cells and energy storage devices. Solar energy alone has only a limited effect on the improvement of their endurance. To solve this problem, this study proposes the combination of solar energy technology and dynamic soaring technology to improve the endurance of small UAVs. Then, the optimal energy acquisition strategy based on the combination of solar energy and dynamic soaring technology is analyzed in terms of energy. The motion equations and energy acquisition and consumption models of a small solar UAV based on horizontal wind shear are established. Moreover, an optimal trajectory planning problem with the maximum charging power of rechargeable batteries as the optimization objective is proposed. The optimal trajectory is solved based on the hp adaptive pseudo-spectral method, and the optimal trajectory combining the two technologies is simulated and compared with the constant-altitude constant-velocity (CACV) trajectory of the UAV using only solar technology. The simulation results show that under the flight background of tmission = 6:00 (summer sunrise) and β = 0.125 s−1 (wind gradient of the wind shear), the optimized O-type trajectory decreased the energy consumption power by 39.86% and increased the solar energy acquisition power by 86.34% compared to the CACV trajectory. Consequently, the small UAV stores more energy in the rechargeable batteries to improve the endurance performance. Compared to the environment where the sun is located on the leeward side of the wind shear, the environment where the sun is located on the windward side of the wind shear can enable the UAV to acquire more energy through the optimized O-type trajectory.

Floquet topological insulators (FTIs) have richer topological properties than static systems. In this work, we designed different domain wall (DW) structures consisting of a Floquet photonic lattice with opposite helical directions. We investigated the existence and types of edge states in three shared coupling structures and the impact of these shared coupling structures on edge states. When two opposite helical lattices share a straight waveguide array coupling, the edge states are localized on the straight waveguide. When two opposite helical lattices share a clockwise (or anticlockwise) helical waveguide array coupling, the DWs consist of zigzag and bearded edges, but the positions of the zigzag and bearded edges of the shared clockwise waveguide array are different from those of the shared anticlockwise waveguide array. The slope and transmission rate of the edge states both vary with the degree of coupling between the shared waveguides. The characteristics of these edge states, such as transmission speed and band gap width, are also affected by the incidence angle, modulation phase factor, and helical radii, and the methods for controlling the edge states in different shared coupling structures are provided. This will help deepen our understanding of how topological structures influence the electronic and photonic properties of materials. This could also lead to combining topology with metasurface-based structured light, which would highlight many novel properties with great application potential for various fields, such as imaging, metrology, communication, quantum information processing, and light–matter interaction.

Objective To systematically evaluate the disinfection efficacy of the two most frequently used disinfectants, sodium hypochlorite and glutaraldehyde, and their effects on the surface properties of four different dental impression materials. Methods A systematic literature search was performed in four databases until May 1st, 2022 to select the studies which evaluated disinfection efficacy of disinfectants or surface properties of dental impressions after chemical disinfection. Main results A total of 50 studies were included through electronic database searches. Of these studies, 13 studies evaluated disinfection efficacy of two disinfectants, and 39 studies evaluated their effects on the surface properties of dental impressions. A 10-minute disinfection with 0.5–1% sodium hypochlorite or 2% glutaraldehyde was effective to inactivate oral flora and common oral pathogenic bacteria. With regard to surface properties, chemical disinfection within 30 min could not alter the dimensional stability, detail reproduction and wettability of alginate and polyether impressions. However, the wettability of addition silicone impressions and the dimensional stability of condensation silicone impressions were adversely affected after chemical disinfection, while other surface properties of these two dental impressions were out of significant influence. Conclusions Alginate impressions are strongly recommended to be disinfected with 0.5% sodium hypochlorite using spray disinfection method for 10 min. Meanwhile, elastomeric impressions are strongly recommended to be disinfected with 0.5% sodium hypochlorite or 2% glutaraldehyde using immersion disinfection method for 10 min, however, polyether impression should be disinfected with 2% glutaraldehyde.

The suppression of uncommanded motion of aircraft at high angles of attack (α) is a research topic of continuous concern in the aviation field. Aiming at the suppression of uncommanded roll-yaw motion of a canard aircraft at high angles of attack, an experimental method of virtual flight test based on reinforcement learning is proposed in this paper. In the virtual flight experiment, the agent was trained to control the jet actuators, so as to suppress the uncommanded roll-yaw motion. Force measurements were conducted to obtain the performance of the jet actuators in a low-speed wind tunnel. The results show that when the spanwise jet actuator and the reverse jet actuator were working on the same side, their control effects were suppressed by each other. Then, the stability augmentation control law was trained through virtual flight experiments based on a reinforcement learning algorithm (TD3), and the uncommanded motion was successfully suppressed. The time histories of the reinforcement learning agent’s action in tests were analyzed, showing that the agent can avoid the coupling relationship between two kinds of jet actuators during tests.

Previous attempts at active flutter suppression have been based on driving the deflection of multiple pairs of discontinuous mechanical control surfaces. Here, we explore the effects of trailing-edge Circulation Control (CC) for flutter control on flexible wings. To avoid the problem that the nonlinear aeroelastic model is difficult to establish accurately, we trained a closed-loop control strategy based on the model-free deep reinforcement learning algorithm through aeroelastic wind tunnel testing. The results show that the strategy can intelligently select the appropriate jet intensity according to the real-time state of the flexible wing. The oscillation amplitude of flutter can be reduced by 92%. The air consumption required for unsteady CC to suppress flutter is reduced by 37% compared to steady CC. This study aims to provide an innovative control method and strategy for active flutter suppression of large aspect ratio flexible wings.

A special vortex evolution process was found near the Coanda surface for circulation control airfoil with pulsed actuation. For the jet-on process, two successive shedding vortices from the lower lip edge and the separation vortex on the Coanda surface collide and interact with each other, and periodic vortex shedding forms after several vortex shedding and collision cycles. For the jet-off process, the periodic shedding vortices were replaced by a row of vortices with reverse rotation direction from the upper lip edge, and then reverse vortices broke into small-scale vortices.

Abstract Peri-implantitis is a common reversible disease after tooth implantation, caused by a variety of pathogenic microorganisms. Based on non-surgical or surgical treatment principles, supplementation by local or systemic drugs might enhance treatment efficacy. Porphyromonas gingivalis (Pg) (ATCC 33,277) and Prevotella intermedius (Pi) (ATCC 25,611) were used as test strains. The effects of Pln 149 on the biofilm formation and growth of four periodontal pathogens were evaluated by RT-PCR, fluorescence microscopy, and scanning electron microscopy. The antibacterial mechanism was tested by the patch-clamp technique. The cytotoxicity of Pln 149 (125 µg/ml) to bone marrow stromal cell (BMSC) was assessed using an MTT assay. Pln 149 exhibited significant inhibitory effects on Pg and Pi (P

Abstract Objective To explore the influencing factors of age at onset of pain and severe pain in patients with Hartofilakidis type I developmental dysplasia of the hip (DDH). Methods A retrospective study of 83 patients with DDH treated at our hospital from January 2017 to June 2021 was conducted. The age at onset of pain, patients’ demographic data, and radiographic parameters were collected. Multiple linear regression was used to determine the influencing factors of age at onset of pain. Cox regression analysis was used to determine the influencing factors of severe pain attacks. Results According to the results of multiple linear regression analysis, when the distance between the medial femoral head and the ilioischial line increased by one millimetre, the age at onset of pain decreased by 1.7 years (β = − 1.738, 95% CI − 1.914–[− 1.561], p

A monocopter, which is a biology-inspired aircraft based on the samara, has been proved to have passive flight stability. However, due to the asymmetry of its configurations and the constant rotation during flight, its flight dynamics equation is complex. In this paper, the longitudinal stability of a monocopter is systematically analyzed. The longitudinal motion of the monocopter is used as the main research object in this paper. By transforming the body axis coordinate frame to the semi-body axis coordinate frame, its longitudinal dynamics equation is greatly simplified. Then, a fourth-order state space matrix of the longitudinal motion of the monocopter is established, and its longitudinal stability is analyzed at different pitch angles of the wing. Furthermore, the fourth-order state space matrix is simplified into a third-order matrix, and the Rouse criterion is used to analyze the stability of the simplified state space. A set of sufficient conditions is obtained as the criterion for longitudinal stability. Based on this criterion, it is found that the product of inertia Iyzb is a very important factor affecting the stability. Then, the inertial parameters of the aircraft are modified, which greatly expands the range of the pitch angle that maintains longitudinal stability. Finally, the six-degree-of-freedom nonlinear flight dynamic simulation is performed to verify the rationality of the longitudinal stability criterion.

Rice, a staple food crop worldwide, is pivotal in agricultural productivity and public health. Automatic classification of typical rice pests and diseases is crucial for optimizing rice yield and quality in practical production. However, infrequent occurrences of specific pests and diseases lead to uneven dataset samples and similar early-stage symptoms, posing challenges for effective identification methods. In this study, we employ four image enhancement techniques—flipping, modifying saturation, modifying contrast, and adding blur—to balance dataset samples throughout the classification process. Simultaneously, we enhance the basic RepVGG model by incorporating the ECA attention mechanism within the Block and after the Head, resulting in the proposal of a new classification model, RepVGG_ECA. The model successfully classifies six categories: five types of typical pests and diseases, along with healthy rice plants, achieving a classification accuracy of 97.06%, outperforming ResNet34, ResNeXt50, Shufflenet V2, and the basic RepVGG by 1.85%, 1.18%, 3.39%, and 1.09%, respectively. Furthermore, the ablation study demonstrates that optimal classification results are attained by integrating the ECA attention mechanism after the Head and within the Block of RepVGG. As a result, the classification method presented in this study provides a valuable reference for identifying typical rice pests and diseases.

Micro burner is the fundamental element of a micro energy power system. The performance, output power, and efficiency of the system are directly involved by the combustion stability, efficiency, and temperature distribution of the exterior wall. Owing to the small combustion space of the micro burner and the resident short time of the premixed fuel/air, the fuel is difficult to burn completely, resulting in poor burning efficiency and flame stability. Therefore, the study of micro burner technology is the focus of current research to improve combustion performance. This article introduces the micro power system, micro combustion technology, and combustion status and characteristics, focusing on four kinds of micro combustion technology. The purpose is tantamount to fully understand the current status of micro combustion technology and compare the characteristics of different combustion technologies. For improving output power and efficiency of the power system, the combustion stability and performance are enhanced, which provides theoretical support for the effective realization of micro scale combustion and application.

Online detection of yarn roll’s margin is one of the key issues in textile automation, which is related to the speed and scheduling of bobbin (empty yarn roll) replacement. The actual industrial site is characterized by uneven lighting, restricted shooting angles, diverse yarn colors and cylinder yarn types, and complex backgrounds. Due to the above characteristics, the neural network detection error is large, and the contour detection extraction edge accuracy is low. In this paper, an improved neural network algorithm is proposed, and the improved Yolo algorithm and the contour detection algorithm are integrated. First, the image is entered in the Yolo model to detect each yarn roll and its dimensions; second, the contour and dimensions of each yarn roll are accurately detected based on Yolo; third, the diameter of the yarn rolls detected by Yolo and the contour detection algorithm are fused, and then the length of the yarn rolls and the edges of the yarn rolls are calculated as measurements; finally, in order to completely eliminate the error detection, the yarn consumption speed is used to estimate the residual yarn volume and the measured and estimated values are fused using a Kalman filter. This method overcomes the effects of complex backgrounds and illumination while being applicable to different types of yarn rolls. It is experimentally verified that the average measurement error of the cylinder yarn diameter is less than 8.6 mm, and the measurement error of the cylinder yarn length does not exceed 3 cm.

The structured light projection (SLP) method occupies a crucial position in three-dimensional (3D) imaging technology. Different working wavelengths of structured light can be employed depending on the situation. However, there are few structured lights that can be modulated based on wavelength at present. Therefore, we have comprehensively investigated and designed a Dammann grating (DG) based on metasurface, which can be controlled through multi-beam interference (MBI) to achieve a change of the working wavelength. In this work, we can convert the straight waveguide to the helical waveguide by fine-tuning the related parameters of the incident lights and generate 5 × 5 diffraction spot arrays in the wavelength range of 480–510 nm and 950–1020 nm, respectively. Furthermore, the metasurfaces exhibit good performance. For example, their spread angles can be up to 44° × 44° and they can reach a conversion efficiency of over ≥50% while maintaining a contrast ratio of roughly 40%. Compared with traditional structured light, it can be used in different working wavelengths and has a broader application range in 3D sensing systems.

Dielectric barrier discharge (DBD) has been one of the most promising techniques for flow control, but the practical application needs a large plasma surface. A three-electrode sliding discharge plasma actuator (SDPA) can generate plasma filling the inter-electrode distance. In this study, the performance of an SDPA for practical flight at low pressures is reported. When the pressure decreases, plasma discharge becomes more intensive. Current peaks and power consumption of electrode 1 become higher at low pressure. Sliding discharge is fully developed at 54 kPa, and the plasma morphology resembles plumes. PIV results show vortex structures and an induced wall jet above the actuator surface. A ‘potential-arc-discharge’ is observed at 38 kPa, leading to an inhomogeneous surface temperature distribution and a velocity decrease of the jet.

Circulation control (CC) is used extensively to control the attitude of rudderless aircraft experiencing ground effect in take-off and landing phases. The investigation of ground effect on airfoil CC is necessary to improve flight performance and quality in proximity to the ground. The aerodynamics and flow field of a modified NACA0012 airfoil with CC in ground effect are investigated with numerical simulations. The compressible Reynolds-averaged Navier–Stokes equations with the shear-stress transport k−ω turbulence model equations are solved using the Finite Volume Method (FVM). Simulation results show that the ground effect changes the lift increment per unit jet momentum coefficient, and CC can reverse the polarity ground effect. The effective angle of attack αE and the downwash space downstream airfoil are altered by the ground effect resulting in variations of airfoil surface pressure and lift. Unlike the unbounded flow field, the jet attachment distance is not only determined by the jet momentum coefficient but it can change with the ride height, which is the distance from the ground to the center of the semicircular Coanda surface, for the same jet momentum coefficient.

We report for the first time a cavitation-induced pressure fluctuation decomposition developed from empirical mode decomposition (EMD) [Huang et al., Proc. R. Soc. London, Ser. A 454, 903–995 (1998)]. The idea is to decompose the nonlinear and non-stationary time series data into a finite and usually small number of “intrinsic mode functions” based on the local properties of the signal, which admit a well-behaved Fourier transform. With this transform, we can obtain frequency characteristics that give sharp identifications of imbedded structures. The cavitation evolution and excited pressure fluctuation around a cavitating propeller in the nonuniform wake are investigated using high-speed imaging and pressure sensors. By the EMD method, we separate the pressure fluctuations induced by different types of cavitation. The high frequency components of the pressure fluctuations are mainly caused by the collapse of sheet cavitation, followed by the shrinking and growth of sheet cavitation. Furthermore, the tip vortex cavitation leads to higher frequency but contributes less to pressure fluctuations. The periodical motion of the propeller contributes to the first blade frequency, and the pressure fluctuations induced by cavitation are superimposed on it.

The automatic detection of the thread roll’s margin is one of the kernel problems in the textile field. As the traditional detection method based on the thread’s tension has the disadvantages of high cost and low reliability, this paper proposes a technology that installs a camera on a mobile robot and uses computer vision to detect the thread roll‘s margin. Before starting, we define a thread roll‘s margin as follows: The difference between the thread roll‘s radius and the bobbin’s radius. Firstly, we capture images of the thread roll‘s end surface. Secondly, we obtain the bobbin’s image coordinates by calculating the image’s convolutions with a Circle Gradient Operator. Thirdly, we fit the thread roll and bobbin’s contours into ellipses, and then delete false detections according to the bobbin’s image coordinates. Finally, we restore every sub-image of the thread roll by a perspective transformation method, and establish the conversion relationship between the actual size and pixel size. The difference value of the two concentric circles’ radii is the thread roll’s margin. However, there are false detections and these errors may be more than 19.4 mm when the margin is small. In order to improve the precision and delete false detections, we use deep learning to detect thread roll and bobbin’s radii and then can calculate the thread roll’s margin. After that, we fuse the two results. However, the deep learning method also has some false detections. As such, in order to eliminate the false detections completely, we estimate the thread roll‘s margin according to thread consumption speed. Lastly, we use a Kalman Filter to fuse the measured value and estimated value; the average error is less than 5.7 mm.