The improvement of the accuracy and real-time performance of sector traffic flow prediction is of great significance to air traffic management decision-making. Sectors operate under complex spatial structures and time dimensions. Some neural network methods adopt sequence order to gradually transmit information, which makes it difficult to achieve complete parallel training. Not only does it take too long to train, resulting in low training efficiency, but it is also easy to lose the effective correlation information of long sequence data. To this end, a sector traffic flow prediction method based on attention-improved graph convolutional transformer (AGC-T) network is proposed to improve the current traffic prediction problem for sectors. First, the graph structure information and historical traffic data of the sector are input into the graph convolutional network improved based on the attention mechanism to fully capture the spatial relationship with sectors as nodes. Combined with the transformer’s multi-head self-attention mechanism, it can directly focus on the sequence data at any position without gradually transmitting information. Not only does it improve efficiency through parallel training, but the encoder-decoder structure can also mine the information features in the traffic data, focus on the traffic data features of key nodes and more accurately predict sector traffic. Finally, the operation traffic data of sectors in typical areas in central and southern China are taken as an example to analyse the model. The results show that compared with other prediction models, the AGC-T model $RSME$, $MAE$ and ${R^2}$ are 45.16%, 46.78% and 2.63% higher than the GCN model in the 15-min single-day traffic prediction task, and 41.74%, 35.27% and 1.20% higher than the GRU model. In the single-week traffic prediction task, $RSME$, $MAE$ and ${R^2}$ are 37.12%, 40.54% and 3.55% higher than the GCN model, and 35.15%, 35.17% and 0.65% higher than the GRU model, respectively, showing better prediction performance. This study will help air navigation service providers (ANSP) to make sector traffic predictions more accurately, thereby implementing more scientific and reasonable traffic management measures.

Single-cell tornado-like vortices (TLVs) exhibit periodic wandering fluctuations around the time-averaged vortex core, a phenomenon known as vortex wandering, which constitutes the most prominent periodic behaviour in such flows. The coupling between vortex motion and wandering creates complex swirl dynamics, posing significant analytical challenges. However, the limited availability of experimental studies on vortex wandering decomposition hampers a deeper understanding of this phenomenon. To address this gap, a tornado simulator was designed to generate a controllable single-cell TLV, and high-frequency velocity data were obtained using particle image velocimetry. A sparsity-promoting dynamic mode decomposition (sp-DMD) method was developed to decouple coherent structures and analyse dynamic characteristics. Results show that as the swirl ratio increases, the vortex structure becomes more diffuse, with significant reductions in intensity. Vortex wandering is present across all swirl conditions, with its periodicity strongly modulated by the swirl ratio. Importantly, sp-DMD identified two primary modes, the time-averaged mode (first mode), representing the dominant rotational vortex motion, and the vortex-wandering-dominated modes (second and third conjugate modes), which correspond to persistent periodic velocity fluctuations and contribute the most significant pulsations. These modes exhibit a pair of oppositely rotating vortices symmetrically revolving around the central flow axis. Visualisations of the Q criterion reveal a symmetric dipole pattern. This suggests that rotational and shear effects are likely responsible for the periodic movement of the vortex core. Furthermore, as the swirl ratio increases, the energy of the vortex-wandering-dominated modes diminishes, and motion transitions from high-energy, organised dynamics to low-energy, disordered behaviour.

To address the complexity and excessive reliance on expert experience in tuning fuzzy Proportional-Integral-Derivative (PID) controller parameters, this study proposes a variable-rate spraying control system that integrates an improved Beetle Antennae Search (IBAS) algorithm with fuzzy PID control. To evaluate the feasibility of the system, a mathematical transfer function of the variable-rate spraying system was constructed, and a flow control simulation platform was established for simulation analysis. To overcome the limitations of conventional BAS, which is prone to premature convergence and limited search precision, the IBAS algorithm was developed. The improvements include a hybrid disturbance strategy to enhance individual search capability and a simulated annealing mechanism to prevent the algorithm from being trapped in local optima. Using the IBAS algorithm, the proportional and quantization factors of the fuzzy PID controller were optimized offline to obtain the optimal parameters. The IBAS-fuzzy PID controller was then compared in simulation with conventional PID, fuzzy PID, and BAS-optimized fuzzy PID controllers. The simulation results demonstrated that the IBAS-fuzzy PID algorithm achieved higher flow control accuracy than existing methods. To further validate the effectiveness of the improved algorithm under practical conditions, field experiments were conducted. The results indicated that the IBAS-optimized fuzzy PID controller outperformed the three other control methods in terms of flow control accuracy. Overall, both simulation and field results confirm that the proposed IBAS algorithm for fuzzy PID parameter optimization significantly enhances response speed, control precision, and overshoot reduction, providing a novel approach and potential application for variable-rate spraying technology.

High-resolution particle image velocimetry (PIV) particle-to-velocity analyses using small interrogation areas (IAs) often require substantial processing time. To overcome this limitation, a generative adversarial network (GAN)-based model is proposed to achieve spatio-temporal super-resolution (SR) reconstruction from low-resolution PIV data with large IAs, thereby significantly reducing post-processing time. Time-resolved PIV measurements of plasma-induced vortex flows, covering vortex formation, growth, transition and breakdown stages, are employed to train and evaluate the model with multi-scale vortical structures. By sequentially constructing spatial and temporal datasets, the GAN-based model enables reliable SR reconstruction at different scaling factors. Reconstruction accuracy is systematically assessed using time-averaged, instantaneous and phase-averaged velocity fields. At SR factors of $\times$4 and $\times$8, the reconstructed fields closely match high-resolution references, effectively capturing both fluctuating velocities and small-scale vortical structures. In contrast, $\times$16 reconstructions exhibit diminished accuracy due to the loss of fine-scale information from highly downsampled inputs. For time-averaged fields, high-resolution reconstructions reliably capture plasma jet characteristics at all SR factors. To enhance generalisation, transfer learning is introduced to fine tune the parameters of SR-related layers in the generator, enabling accurate reconstructions under varying vortex dynamics. In addition, the efficiency gains in PIV particle-to-velocity analysis and the fundamental limitations on achievable SR factors imposed by spatio-temporal data correlations are discussed. This study demonstrates that GAN-based spatio-temporal SR models offer a promising approach to accelerate PIV analyses while maintaining high reconstruction fidelity with diverse flow conditions.

Investigations into the effects of polymers on small-scale statistics and flow patterns were conducted in a turbulent von Kármán swirling (VKS) flow. We employed the tomographic particle image velocimetry technique to obtain full information on three-dimensional velocity data, allowing us to effectively resolve dissipation scales. Under varying Reynolds numbers ($R_\lambda =168{-}235$) and polymer concentrations ($\phi =0{-}25\ {\textrm{ppm}}$), we measured the velocity gradient tensor (VGT) and related quantities. Our findings reveal that the ensemble average and probability density function (PDF) of VGT invariants, which represent turbulent dissipation and enstrophy along with their generation terms, are suppressed as polymer concentration increases. Notably, the joint PDFs of the invariants of VGT, which characterise local flow patterns, exhibited significant changes. Specifically, the third-order invariants, especially the local vortex stretching, are greatly suppressed, and strong events of dissipation and enstrophy coexist in space. The local flow pattern tends to be two-dimensional, where the eigenvalues of the rate-of-strain tensor satisfy a ratio $1:0:-1$, and the vorticity aligns with the intermediate eigenvector of the rate-of-strain tensor, while it is perpendicular to the other two. We find that these statistics observations can be well described by the vortex sheet model. Moreover, we find that these vortex sheet structures align with the symmetry axis of the VKS system, and orient randomly in the horizontal plane. Further investigation, including flow visualisation and conditional statistics on vorticity, confirms the presence of vortex sheet structures in turbulent flows with polymer additions. Our results establish a link between single-point statistics and small-scale flow topology, shedding light on the previously overlooked small-scale structures in polymeric turbulence.

Visual Simultaneous Localization and Mapping (vSLAM) is essentially limited by the static world assumption, which makes its application in dynamic environments challenging. This paper proposes a robust vSLAM system, RFN-SLAM, which is based on ORB-SLAM3 and does not require preset dynamic labels and weighted features to process dynamic scenes. In the feature extraction stage, an enhanced efficient binary image BAD descriptor is used to improve the accuracy of static feature point matching. Through the improved RT-DETR target detection network and FAST-SAM instance segmentation network, RFN-SLAM obtains semantic information and uses a novel dynamic box detection algorithm to identify and eliminate the feature points of dynamic objects. When optimizing the pose, the static feature points are weighted according to the dynamic information, which significantly reduces the mismatch and improves the accuracy of positioning. Meanwhile, 3D rendering of the neural radiation field is used to remove dynamic objects and render them. Experiments were conducted on the TUM RGB-D dataset, Bonn dataset, and self-collected dataset. The results show that in terms of positioning accuracy, RFN-SLAM significantly outperforms ORB-SLAM3 in dynamic environments. It also achieves more accurate positioning than other advanced dynamic SLAM methods and successfully realizes accurate 3D reconstruction of static scenes. In addition, on the premise of ensuring accuracy, the real-time performance of RFN-SLAM is effectively guaranteed.

Visual exploration is a task in which a camera-equipped robot seeks to efficiently visit all navigable areas of an environment within the shortest possible time. Most existing visual exploration methods rely on a static camera fixed to the robot’s body to control its own movements. However, coupling the orientation of camera with robot’s body limits the extra degrees of freedom to obtain more visual information. In this work, we adjust the camera orientation during robot motion by using a novel camera view planning (CVP) policy to improve the exploration efficiency. Specifically, we reformulate the CVP problem as a reinforcement learning problem. However, two new challenges need to be addressed: 1) determining how to learn an effective CVP policy in complex indoor environments and 2) figuring out how to synchronize it with the robot motion. To solve the above issues, we create a reward function considering factors such as exploration area, observed semantic objects, and the motion conflicts between the camera and the robot’s body. Moreover, to better coordinate the policies of the camera and the robot’s body, the CVP policy takes the body actions and the egocentric 2D spatial maps with exploration, occupancy, and trajectory information into account to make motion decisions. Experimental results show that after using the proposed CVP policy, the exploration area is expanded by 21.72% and 25.6% on average in the small-scale indoor scene with few structured obstacles and large-scale indoor scene with cluttered obstacles, respectively.

Spodoptera frugiperda (Lepidoptera: Noctuidae), commonly known as the fall armyworm (FAW), is an invasive pest known for its rapid migration, strong adaptability, and wide host range. Small heat shock proteins (sHsps) are a specific class of Hsps associated with the molecular mechanisms of insect growth and development and the response to abiotic stresses, such as extreme temperatures, ultraviolet (UV) rays, and pesticides. Herein, six sHsps, SfsHsp11.2, SfsHsp15.8, SfsHsp20.2, SfsHsp21.4, SfsHsp22, and SfsHsp26.6, were successfully cloned and identified from FAW. The six SfsHsps all have an α-crystallin domain in their amino acid sequences. Furthermore, we investigated the expression patterns of these six SfsHsps in different tissues and developmental stages of FAW using real-time quantitative polymerase chain reaction. Their expression levels in adult FAW were also analysed under extreme temperatures (36°C and 4°C) and UV-A stress for different durations (0, 30, 60, 90, and 120 min). Our findings revealed distinct expression profiles for the six SfsHsps in different FAW tissues and developmental stages. Notably, under temperature and UV-A stress, most SfsHsp genes were significantly upregulated in adults. Our findings strongly indicate that SfsHsps are crucial in the development and stress response of S. frugiperda.

High gain greater than 106 is crucial for the preamplifiers of joule-class high-energy lasers. In this work, we present a specially designed compact amplifier using 0.5%Nd,5%Gd:SrF2 and 0.5%Nd,5%Y:SrF2 crystals. The irregular crystal shape enhances the gain length of the laser beam and helps suppress parasitic oscillations. The amplified spontaneous emission (ASE) induced by the high gain is analyzed through ray tracing. The balance between gain and ASE is estimated via numerical simulation. The gain spectral characteristics of the two-stage two-pass amplifier are examined, demonstrating the advantages of using different crystals, with bandwidths up to 8 nm and gains over 106. In addition, the temperature and stress distributions in the Nd,Gd:SrF2 crystal are simulated. This work is expected to contribute to the development of high-peak-power ($\ge$terawatt-class) high-energy (joule-class) laser devices.

Submerged flexible aquatic vegetation exists widely in nature and achieves multiple functions mainly through fluid–structure interactions (FSIs). In this paper, the evolution of large-scale vortices above the vegetation canopy and its effect on flow and vegetation dynamics in a two-dimensional (2-D) laminar flow are investigated using numerical simulations under different bending rigidity $\gamma$ and gap distance d. According to the variation of large-scale vortex size and intensity, the evolution process is divided into four distinct zones in the streamwise direction, namely the ‘developing’ zone, ‘transition’ zone, ‘dissipation’ zone and ‘interaction’ zone, and different evolution sequences are further classified. In the ‘developing’ zone, the size and intensity of the large-scale vortex gradually increase along the array, while they decrease in the ‘dissipation’ zone. The supplement of vegetation oscillating vortices to large-scale vortices is the key to the enhancement of the latter. The most obvious dissipation of large-scale vortices occurs in the ‘transition’ zone, where the position of the large-scale vortex is significantly uplifted. The effects of $\gamma$ and d on the evolution of the large-scale vortex are discussed. In general, the features of vegetation swaying vary synchronously with those of large-scale vortices. The flow above the canopy is dominated by large-scale vortices, and the development of flow characteristics such as time-averaged velocity profile and Reynolds stress are closely related to the evolution of large-scale vortices. The flow inside the canopy, however, is mainly affected by the vortex shed by the vegetation oscillation, which leads to the emergence of negative time-averaged velocity and negative Reynolds stress.

In this paper, we propose a novel online informative path planner for 3-D modeling of unknown structures using micro aerial vehicles. Different from the explore-then-exploit strategy, our planner can cope with exploration and coverage simultaneously and thus obtain complete and high-quality 3-D models. We first devise a set of evaluation metrics considering the perception constraints of the sensor for efficiently evaluating the coverage quality of the reconstructed surfaces. Then, the coverage quality is utilized to guide the subsequent informative path planning. Specifically, our hierarchical planner consists of two planning stages – a local coverage stage for inspecting surfaces with low coverage quality and a global exploration stage for transiting the robot to unexplored regions at the global scale. The local coverage stage computes the coverage path that takes into account both the exploration and coverage objectives based on the estimated coverage quality and frontiers, and the global exploration stage maintains a sparse roadmap in the explored space to achieve fast global exploration. We conduct both simulated and real-world experiments to validate the proposed method. The results show that our planner outperforms the state-of-the-art algorithms and especially decreases the reconstruction error (at least 12.5% lower on average).

The existing studies on vortex rings have concentrated on non-zero circulation. However, the cases of zero circulation may also be significantly noteworthy on both theoretical and practical grounds. As the first attempt on this subject, in this paper a family of viscous laminar vortex rings with zero circulation and a moderate ratio of core radius to ring radius is studied using numerical simulations of the incompressible Navier–Stokes equations. This unusual zero circulation is achieved by assigning a special layered vorticity distribution with alternate signs to the vortex core. At the initial moment, the ring is axisymmetric, swirl-free and of a circular cross-section. It is found that the axial symmetry and the non-swirl nature of the vortex ring are preserved during the evolution, and the vortex ring endures a transition from the initial layered structure to a shell structure, then degenerates to an ordinary vortex ring with non-zero circulation at last. Significant vorticity cancellation is observed due to the interactions among the layered structures. A new Reynolds number, based on the absolute value of vorticity, is applied to the zero-circulation vortex rings in the present work. For such vortex rings, cases of both zero and non-zero vortical impulse can happen, unlike the ordinary ones with only non-zero vortical impulse. Additionally, it is found that the vortical impulse can be irrelevant to the ring diameter. The study may shed light on modelling certain real flows characterised by distinct vortex structures or configurations.

Nutrition intervention is an effective way to improve flesh qualities of fish. The effect of feed supplementation with glutamate (Glu) on flesh quality of gibel carp (Carassius gibelio) was investigated. In trial 1, the fish (initial weight: 37.49 ± 0.08 g) were fed two practical diets with 0 and 2% Glu supplementation. In trial 2, the fish (37.26 ± 0.04 g) were fed two purified diets with 0 and 3% Glu supplementation. The results after feeding trials showed that dietary Glu supplementation increased the hardness and springiness of muscle, whether using practical or purified diets. Glu-supplemented diets increased the thickness and density of myofibres and collagen content between myofibres. Furthermore, Glu promoted muscle protein deposition by regulating the IGF-1-AKT-mTOR signalling pathway, and enhanced the myofibre hypertrophy by upregulating genes related to myofibre growth and development (mef2a, mef2d, myod, myf5, mlc, tpi and pax7α). The protein deposition and myofibre hypertrophy in turn improved the flesh texture. In addition, IMP content in flesh increased when supplementing Glu whether to practical or to purified diet. Metabolomics confirmed that Glu promoted the deposition of muscle-flavoured substances and purine metabolic pathway most functioned, echoed by the upregulation of key genes (ampd, ppat and adsl) in purine metabolism. The sensory test also clarified that dietary Glu improved the flesh quality by enhancing the muscle texture and flavour. Conclusively, dietary Glu supplementation can improve the flesh quality in this fish, which can further support evidence from other studies more generally that improve flesh quality of cultured fish.

We propose a two-sided market entry game and present experiments studying coordination behavior in the game. The two-sided market in the game is operated by an intermediary monopoly platform, serving two sides (i.e., customers and service providers) and featuring asymmetric agents, cross-side network effects, and endogenous market capacity. The game has multiple pure-strategy Nash equilibria if at least one side has a high willingness to enter the market and the other side’s willingness is not very low. We conduct a laboratory experiment involving three treatments corresponding to different combinations of willingness to enter the market among customers and service providers. The experimental results indicate that willingness to enter the market and cross-side network effects significantly influence coordination behavior in two-sided markets. When the multiple pure-strategy Nash equilibria are Pareto ranked on both sides, customers and service providers can coordinate their behavior to the payoff-dominant equilibrium via tacit coordination under strategic uncertainty. However, when the multiple pure-strategy Nash equilibria are Pareto ranked on one side but Pareto equivalent on the other side, coordination failure and disequilibrium occurred, and the equilibria cannot predict the aggregate behavior well. Our experimental results indicate that a thriving two-sided market should coordinate both sides on board.

An actively controllable cascaded proton acceleration driven by a separate 0.8 picosecond (ps) laser is demonstrated in proof-of-principle experiments. MeV protons, initially driven by a femtosecond laser, are further accelerated and focused into a dot structure by an electromagnetic pulse (EMP) on the solenoid, which can be tuned into a ring structure by increasing the ps laser energy. An electrodynamics model is carried out to explain the experimental results and show that the dot-structured proton beam is formed when the outer part of the incident proton beam is optimally focused by the EMP force on the solenoid; otherwise, it is overfocused into a ring structure by a larger EMP. Such a separately controlled mechanism allows precise tuning of the proton beam structures for various applications, such as edge-enhanced proton radiography, proton therapy and pre-injection in traditional accelerators.

We present an experimental study on the effects of polymer additives on the turbulent/non-turbulent interface (TNTI) in a fully developed round water jet. The Reynolds number based on the jet diameter is fixed at $Re=7075$. The Weissenberg number $Wi$ ranges from 24 to 86. We employ time-resolved simultaneous particle image velocimetry and laser-induced fluorescence measurements to investigate the local entrainment and engulfment process along the TNTI in two regimes: entrainment transition and enhancement regimes. In polymer-laden jets, the TNTI fluctuates more intermittently in the radial direction and more ambient fluid can be engulfed into the turbulent region due to the augmented large scale motion. Though the contribution of engulfment to the total flux increases with $Wi$, engulfment is still not the major contribution to the entrainment in polymer-laden jets. We further show that the local entrainment velocity is increased in both regimes compared with the pure water jet, due to two contributions: polymer elastic stress and the more intermittent character of the TNTI. In the entrainment transition regime, we observe smaller fractal dimension and shorter length of TNTI compared with the Newtonian case, consistent with previous numerical simulations (Abreu et al. J. Fluid Mech. vol. 934, 2022, A36); whereas those in the enhancement regime remain largely unchanged. The difference between the two regimes results from the fact that the jet flow decays in the streamwise direction. In the entrainment transition regime, turbulence intensity is strong enough to significantly stretch the polymers, resulting in a smoother TNTI in the inertial range. However, in the entrainment enhancement regime, the polymer’s feedback is not strong enough to alter the fractal dimension due to the low elasticity. The above mentioned differences of entrainment velocity and TNTI in the entrainment reduction/transition and enhancement regimes also explain the reduced and enhanced spreading rate of the viscoelastic jet observed in previous numerical simulations and experiments (Guimarães et al. J. Fluid Mech. 2020,vol. 899, A11; Peng et al. Phys. Fluids, 2023, vol. 35, 045110).

The interaction of a swimmer with unsteady vortices in complex flows remains a topic of interest and open discussion. The present study, employing the immersed boundary method with a flexible fin model, explores swimming behaviours behind a circular cylinder with vortex-induced vibration (VIV). Five distinct swimming modes are identified on the $U_r$–$G_0$ plane, where $U_r$ denotes the reduced velocity, and $G_0$ represents the fin’s initial position. These modes include drifting upstream I/II (DU-I/II), Karman gait I/II (KG-I/II), and large oscillation (LO), with the DU-II, KG-II and LO modes being newly reported. The fin can either move around or cross through the vortex cores in the KG-I and KG-II modes, respectively, for energy saving and maintaining a stable position. When the upstream cylinder vibrates with its maximum amplitude, a double-row vortex shedding forms in the wake, allowing the DU-II mode to occur with the fin to achieve high-speed locomotion. This is attributed to a significant reduction in the streamwise velocity caused by vortex-induced velocity. Furthermore, a symmetry breaking is observed in the fin’s wake in the DU-II mode, potentially also contributing to high-speed locomotion. Overall, compared to the case without an upstream cylinder, we demonstrate that a self-propelled fin gains hydrodynamic advantages with various swimming modes in different VIV wakes. Interestingly, increased power transferred from flows by the oscillating cylinder leads to a more favourable environment for the downstream fin’s propulsion, indicating that a fin in VIV wakes obtains more advantages compared to the vortex street generated by a stationary cylinder.