We present a high-power mid-infrared single-frequency pulsed fiber laser (SFPFL) with a tunable wavelength range from 2712.3 to 2793.2 nm. The single-frequency operation is achieved through a compound cavity design that incorporates a germanium etalon and a diffraction grating, resulting in an exceptionally narrow seed linewidth of approximately 780 kHz. Employing a master oscillator power amplifier configuration, we attain a maximum average output power of 2.6 W at 2789.4 nm, with a pulse repetition rate of 173 kHz, a pulse energy of 15 μJ and a narrow linewidth of approximately 850 kHz. This achievement underscores the potential of the mid-infrared SFPFL system for applications requiring high coherence and high power, such as high-resolution molecular spectroscopy, precision chemical identification and nonlinear frequency conversion.

Turbulent emulsions are ubiquitous in chemical engineering, food processing, pharmaceuticals and other fields. However, our experimental understanding of this area remains limited due to the multiscale nature of turbulent flow and the presence of extensive interfaces, which pose significant challenges to optical measurements. In this study, we address these challenges by precisely matching the refractive indices of the continuous and dispersed phases, enabling us to measure local velocity information at high volume fractions. The emulsion is generated in a turbulent Taylor–Couette flow, with velocity measured at two radial locations: near the inner cylinder (boundary layer) and in the middle gap (bulk region). Near the inner cylinder, the presence of droplets suppresses the emission of angular velocity plumes, which reduces the mean azimuthal velocity and its root mean squared fluctuation. The former effect leads to a higher angular velocity gradient in the boundary layer, resulting in greater global drag on the system. In the bulk region, although droplets suppress turbulence fluctuations, they enhance the cross-correlation between azimuthal and radial velocities, leaving the angular velocity flux contributed by the turbulent flow nearly unchanged. In both locations, droplets suppress turbulence at scales larger than the average droplet diameter and increase the intermittency of velocity increments. However, the effects of the droplets are more pronounced near the inner cylinder than in the bulk, likely because droplets fragment in the boundary layer but are less prone to break up in the bulk. Our study provides experimental insights into how dispersed droplets modulate global drag, coherent structures and the multiscale characteristics of turbulent flow.

This paper presents a millimeter-wave end-fire dual-polarized (DP) array antenna with symmetrical radiation patterns and high isolation. The DP radiation element is formed by integrating a quasi-Yagi antenna (providing horizontal polarization) into a pyramidal horn antenna (providing vertical polarization), resulting in a DP radiation element with a symmetrical radiation aperture. To efficiently feed the DP element while maintaining high isolation, a mode-composite full-corporate-feed network is employed, comprising substrate-integrated waveguide supporting the TE10 mode and substrate-integrated coaxial line supporting the TEM mode. This design eliminates the need for additional transition structures, achieving excellent mode isolation and a reduced substrate layer number. A 1 × 4-element DP array prototype operating at 26.5–29.5 GHz using low temperature co-fired ceramic technology was designed, fabricated, and measured. The test results indicate that the prototype achieves an average gain exceeding 10 dBi for both polarizations within the operating band. Thanks to the symmetrical DP radiation element and mode-composite full-corporate-feed network, symmetrical radiation patterns for both polarizations are observed in both the horizontal and vertical planes, along with a high cross-polarization discrimination of 22 dB and polarization port isolation of 35 dB.

We propose an analytical approach based on the Frenet–Serret (FL) frame field, where an FL frame and the corresponding curvature and torsion are defined at each point along magnetic field lines, to investigate the evolution of magnetic tubes and their interaction with vortex tubes in magnetohydrodynamics. Within this framework, simplified expressions for the Lorentz force, its curl, the dynamics of flux tubes and helicity are derived. We further perform direct numerical simulations on the linkage between the magnetic and vortex tubes and investigate the effect of the initial angle $\theta$, ranging from $0^{\,\circ}$ to $45^{\,\circ}$, on their evolution. Our results show that magnetic tubes with non-zero curvature generate Lorentz forces, which in turn produce dipole vortices. These dipole vortices lead to the splitting of the magnetic tubes into smaller structures, releasing magnetic energy. Both magnetic and vortex tubes exhibit quasi-Lagrangian behaviour, maintaining similar shapes during initial evolution and consistent relative positions over time. A vortex tube with strength comparable to that of the magnetic tube, where the kinetic energy induced by the vortex tube is of the same order as the magnetic energy in the magnetic tube, can inhibit magnetic tube splitting by disrupting the formation of vortex dipoles. Additionally, minor variations in the angular configuration of the vortex tubes significantly influence their interaction with the magnetic field and the evolution of large-scale flow structures.

The greatest challenge in pressure reconstruction from the measured velocity fields is that the error of material acceleration is significantly contaminated due to error propagation. Particularly for flows with moving boundaries, accurate boundary velocities are difficult to obtain due to error propagation, and a complex boundary processing technique is needed to treat the moving boundaries. The present work proposes a machine-learning-based method to determine the pressure for incompressible flows with moving boundaries. The proposed network consists of two neural networks: one network, named the boundary network, is used to track the Lagrangian boundary points; the other physics-informed neural network, named the flow network, is adopted to approximate the flow fields. These two networks are coupled by imposing boundary conditions. We further propose a new dynamic weight strategy for the loss terms to guarantee convergence and stability. The performance of the proposed method is validated by two examples: the flow over an oscillating cylinder and the flow around a swimming fish. The proposed method can accurately determine the pressure fields and boundary motion from synthetic particle image velocimetry (PIV) flow fields. Moreover, this method can also predict the boundary and pressure at a given instant without supervised data. Finally, this method was applied to reconstruct the pressure from the two-dimensional and three-dimensional PIV velocities of the left ventricle. All of the results indicate that the proposed method can accurately reconstruct the pressure fields for flows with moving boundaries and is a novel method for surface pressure estimation.

Rhopalosiphum padi is an important grain pest, causing severe losses during crop production. As a systemic insecticide, flonicamid can control piercing-sucking pests efficiently. In our study, the lethal effects of flonicamid on the biological traits of R. padi were investigated via a life table approach. Flonicamid is highly efficiently toxic to R. padi, with an LC50 of 9.068 mg L−1. The adult longevity and fecundity of the R. padi F0 generation were markedly reduced under the LC25 and LC50 concentrations of flonicamid exposure. In addition, negative transgenerational effects on R. padi were observed under exposure to lethal concentrations of flonicamid, with noticeable decreases in the reproductive period, adult longevity, total longevity, and total fecundity of the F1 generation under the LC25 concentration of flonicamid. Furthermore, the third nymph stage (N3), preadult stage, duration of the adult pre-reproductive period, duration of the total pre-reproductive period, reproductive period, adult longevity, total longevity, and total fecundity of the F1 generation were significantly lower under treatment with the LC50 concentration of flonicamid. The life table parameters were subsequently analysed, revealing that the intrinsic rate of increase (rm) and the net reproductive rate (R0) were significantly lower but that the finite rate of increase (λ) and the mean generation time (T) were not significantly different under the LC25 and LC50 concentrations of flonicamid. These data are beneficial for grain aphid control and are critical for exploring the role of flonicamid in the integrated management of this key pest.

In this paper, we study the rapid transition in Richtmyer–Meshkov instability (RMI) with reshock through three-dimensional double-layer swirling vortex rings. The rapid transition in RMI with reshock has an essential influence on the evolution of supernovas and the ignition of inertial confinement fusion, which has been confirmed in numerical simulations and experiments in shock-tube and high-energy-density facilities over the past few years. Vortex evolution has been confirmed to dominate the late-time nonlinear development of the perturbed interface. However, few studies have investigated the three-dimensional characteristics and nonlinear interactions among vortex structures during the transition to turbulent flows. The coexistence of co-rotating and counter-rotating vortices is hypothesized to induce successive large-scale strain fields, which are the main driving sources for rapid development. The three-dimensional effect is reflected in the presence of local swirling motion in the azimuthal direction, and it decreases the translation velocity of a vortex ring. Large-, middle- and small-scale strain fields are employed to describe the development process of RMI with reshock, e.g. vorticity deposited by the reshock, formation of the coexistence of the co-rotating and counter-rotating vortices, iterative cascade under the amplification of the strain fields and viscous dissipation to internal energy. This provides theoretical suggestions for designing practical applications, such as the estimation of the hydrodynamic instability and mixing during the late-time acceleration phase of the inertial confinement fusion.

Traditional bulky and complex control devices such as remote control and ground station cannot meet the requirement of fast and flexible control of unmanned aerial vehicles (UAVs) in complex environments. Therefore, a data glove based on multi-sensor fusion is designed in this paper. In order to achieve the goal of gesture control of UAVs, the method can accurately recognize various gestures and convert them into corresponding UAV control commands. First, the wireless data glove fuses flexible fiber optic sensors and inertial sensors to construct a gesture dataset. Then, the trained neural network model is deployed to the STM32 microcontroller-based data glove for real-time gesture recognition, in which the convolutional neural network-Attention mechanism (CNN-Attention) network is used for static gesture recognition, and the convolutional neural network-bidirectional long and short-term memory (CNN-Bi-LSTM) network is used for dynamic gesture recognition. Finally, the gestures are converted into control commands and sent to the vehicle terminal to control the UAV. Through the UAV simulation test on the simulation platform, the average recognition accuracy of 32 static gestures reaches 99.7%, and the average recognition accuracy of 13 dynamic gestures reaches 99.9%, which indicates that the system’s gesture recognition effect is perfect. The task test in the scene constructed in the real environment shows that the UAV can respond to the gestures quickly, and the method proposed in this paper can realize the real-time stable control of the UAV on the terminal side.

Recently, there has been a surge in interest in exploring how common macroeconomic factors impact different economic results. We propose a semiparametric dynamic panel model to analyze the impact of common regressors on the conditional distribution of the dependent variable (global output growth distribution in our case). Our model allows conditional mean, variance, and skewness to be influenced by common regressors, whose effects can be nonlinear and time-varying driven by contextual variables. By incorporating dynamic structures and individual unobserved heterogeneity, we propose a consistent two-step estimator and showcase its attractive theoretical and numerical properties. We apply our model to investigate the impact of US financial uncertainty on the global output growth distribution. We find that an increase in US financial uncertainty significantly shifts the output growth distribution leftward during periods of market pessimism. In contrast, during periods of market optimism, the increased uncertainty in the US financial markets expands the spread of the output growth distribution without a significant location change, indicating increased future uncertainty.

For the pulse shaping system of the SG-II-up facility, we propose a U-shaped convolutional neural network that integrates multi-scale feature extraction capabilities, an attention mechanism and long short-term memory units, which effectively facilitates real-time denoising of diverse shaping pulses. We train the model using simulated datasets and evaluate it on both the simulated and experimental temporal waveforms. During the evaluation of simulated waveforms, we achieve high-precision denoising, resulting in great performance for temporal waveforms with frequency modulation-to-amplitude modulation conversion (FM-to-AM) exceeding 50%, exceedingly high contrast of over 300:1 and multi-step structures. The errors are less than 1% for both root mean square error and contrast, and there is a remarkable improvement in the signal-to-noise ratio by over 50%. During the evaluation of experimental waveforms, the model can obtain different denoised waveforms with contrast greater than 200:1. The stability of the model is verified using temporal waveforms with identical pulse widths and contrast, ensuring that while achieving smooth temporal profiles, the intricate details of the signals are preserved. The results demonstrate that the denoising model, trained utilizing the simulation dataset, is capable of efficiently processing complex temporal waveforms in real-time for experiments and mitigating the influence of electronic noise and FM-to-AM on the time–power curve.

Stimulated Raman scattering is a third-order nonlinear optical effect that is not only effective for wavelength converting laser output, but also for single longitudinal-mode output due to the absence of spatial hole burning. Diamond is a prominent Raman-active medium that has significant potential for linewidth narrowing and wavelength converting lasers at high power levels due to its high thermal conductivity, long Raman frequency shift and wide spectral transmission range. In this work we utilize diamond in a resonantly mode-matched external cavity to achieve cascaded Raman conversion of a 1064 nm laser. By fine-tuning the length of this external cavity, we can obtain narrow linewidth emission at 1240 and 1485 nm. When operating at maximum power, the measured linewidths were more than twofold narrower than the linewidth of the fundamental field. In addition, the noise levels of the Stokes fields are lower than that of the fundamental field throughout the entire noise frequency range, and the intrinsic linewidth of the second Stokes field, which is expressed at the hertz level (~3.6 Hz), is decreased by approximately three orders of magnitude compared to that of the pump. This work represents the first measurement and analysis of the linewidth and noise characteristics of cascaded diamond Raman lasers and, significantly, offers a new means by which high-power, narrow linewidth laser output can be produced from wavelength-converted laser systems.

The presence of dispersed-phase droplets can result in a notable increase in a system's drag. However, our understanding of the mechanism underlying this phenomenon remains limited. In this study, we use three-dimensional direct numerical simulations with a modified multi-marker volume-of-fluid method to investigate liquid–liquid two-phase turbulence in a Taylor–Couette geometry. The dispersed phase has the same density and viscosity as the continuous phase. The Reynolds number $Re\equiv r_i\omega _i d/\nu$ is fixed at 5200, the volume fraction of the dispersed phase is up to $40\,\%$, and the Weber number $We\equiv \rho u^2_\tau d/\sigma$ is approximately 8. It is found that the increase in the system's drag originates from the contribution of interfacial tension. Specifically, droplets experience significant deformation and stretching in the streamwise direction due to shear near the inner cylinder. Consequently, the rear end of the droplets lags behind the fore head. This causes opposing interfacial tension effects on the fore head and rear end of the droplets. For the fore head of the droplets, the effect of interfacial tension appears to act against the flow direction. For the rear end, the effect appears to act in the flow direction. The increase in the system's drag is attributed primarily to the effect of interfacial tension on the fore head of the droplets which leads to the hindering effect of the droplets on the surrounding continuous phase. This hindering effect disrupts the formation of high-speed streaks, favouring the formation of low-speed ones, which are generally associated with higher viscous stress and drag of the system. This study provides new insights into the mechanism of drag enhancement reported in our previous experiments.

This study conducts experimental investigations into wake-induced vibration (WIV) of a circular cylinder placed downstream of an oscillating cylinder. Surprisingly, it is observed that the previously identified WIV phenomenon, characterized by a sustained increase in amplitude at higher reduced velocities, does not occur when the upstream cylinder oscillates at large amplitudes. Instead, a different phenomenon, which we refer to as the ‘wake-captured vibration’, becomes dominant. The experiments reveal a negative correlation between the vortex-induced vibration amplitude response of the upstream cylinder and the WIV amplitude response of the downstream cylinder. Through a quasi-steady and linear instability analysis, the study demonstrates that the previously proposed wake-displacement mechanism may not be applicable for predicting the cylinder WIV response in the wake of an oscillating body. This is because the lift force gradients across the wake, measured through stationary cylinder experiments, decrease significantly when the upstream cylinder vibrates at higher amplitudes. Consequently, actively controlled vibration experiments are conducted to systematically map the hydrodynamic properties of the downstream cylinder vibrating in the wake of an oscillating cylinder. The findings align with observations from free-vibration experiments, and help to explain the amplitude and frequency response of WIV. Additionally, wake visualization through particle image velocimetry is conducted to provide further insights into the complex wake and vortex–body interactions.

Tryptophan (Trp) is an essential amino acid acting as a key nutrition factor regulating animal growth and development. But how Trp modulates food intake in pigs is still not well known. Here, we investigated the effect of dietary supplementation of Trp with different levels on food intake of growing pigs. The data showed that dietary Trp supplementation with the standardised ileal digestibility (SID) Trp to lysine (Lys) ratio at both 0·18 and 0·20 significantly increased the food intake by activating the expression of orexigenic gene agouti-related peptide (AgRP) and inhibiting the expression of anorexigenic gene pro-opiomelanocortin (POMC), cocaine- and amphetamine-regulated transcript (CART) and melanocortin receptor 4 (MC4R) in the hypothalamus. Meanwhile, the level of anorexigenic hormones appetite-regulating peptide YY (PYY) in the duodenum and serum and leptin receptor in the duodenum were also significantly decreased. Importantly, both the kynurenine and serotonin metabolic pathways were activated upon dietary Trp supplementation to downregulate MC4R expression in the hypothalamus. Further mechanistic studies revealed that the reduced MC4R expression activated the hypothalamic AMP-activated protein kinase (AMPK) pathway, which in turn inhibited the mammalian target of rapamycin (mTOR)/S6 kinase 1 (S6K1) activity to stimulate food intake. Together, our study unravels the orexigenic effect of dietary Trp supplementation in pigs and expands its potential application in developing nutrition intervention strategy in pig production.

Remote center-of-motion (RCM) manipulators are a key issue in minimally invasive surgeries (MIS). The existing RCM parallel mechanisms (PMs) can only generate RCM motion based on the invariant RCM. To provide mobility for RCM, this paper designed a new family of RCM PMs with movable RCM that features a double-stage topological structure. Drawing mainly on configuration evolution and Lie-group, a general approach is proposed to design double-stage PMs with movable RCM. Feasible limbs for 2R1T RCM motion are enumerated and used to construct the secondary PM. Type synthesis of the primary PMs that realize movable RCM is accomplished based on the method presented. Different connection styles between the two stages that ensure the geometrical conditions of RCM motion are designed. Using different connection styles, double-stage PMs with movable RCM are constructed. These new RCM PMs can realize precise positioning of RCM by taking advantage of the primary PMs, which indicates their potential application prospects in MIS.

In this study, direct numerical simulation of the particle dispersion and turbulence modulation in a sonic transverse jet injected into a supersonic cross-flow with a Mach number of 2 was carried out with the Eulerian–Lagrangian point-particle method. One single-phase case and two particle-laden cases with different particle diameters were simulated. The jet and particle trajectories, the dispersion characteristics of particles, and the modulation effect of particles on the flow were investigated systematically. It was found that large particles primarily accumulate around shear layer structures situated on the windward side of the jet trajectory. In contrast, small particles exhibit radial transport, accessing both upstream and downstream recirculation zones. Moreover, small particles disperse extensively within the boundary layer and large-scale shear layers, evidently influenced by the streamwise vortices. The particles increase the mean wall-normal velocity near the wall in the wake region of the transverse jet, while reducing the mean streamwise and wall-normal velocities in outer regions. Particles significantly alter the flow velocity adjacent to shock fronts. In particular, the turbulent fluctuations near the windward barrel shock and bow shock are reduced, while those around the leeward barrel shock are increased. An upward displacement of the bow shock in the wall-normal direction is also observed due to particles. In the regions away from the shocks, small particles tend to amplify the Reynolds stress, while large particles attenuate the turbulent kinetic energy.

We investigate the coupling effects of the two-phase interface, viscosity ratio and density ratio of the dispersed phase to the continuous phase on the flow statistics in two-phase Taylor–Couette turbulence at a system Reynolds number of $6\times 10^3$ and a system Weber number of 10 using interface-resolved three-dimensional direct numerical simulations with the volume-of-fluid method. Our study focuses on four different scenarios: neutral droplets, low-viscosity droplets, light droplets and low-viscosity light droplets. We find that neutral droplets and low-viscosity droplets primarily contribute to drag enhancement through the two-phase interface, whereas light droplets reduce the system's drag by explicitly reducing Reynolds stress due to the density dependence of Reynolds stress. In addition, low-viscosity light droplets contribute to greater drag reduction by further reducing momentum transport near the inner cylinder and implicitly reducing Reynolds stress. While interfacial tension enhances turbulent kinetic energy (TKE) transport, drag enhancement is not strongly correlated with TKE transport for both neutral droplets and low-viscosity droplets. Light droplets primarily reduce the production term by diminishing Reynolds stress, whereas the density contrast between the phases boosts TKE transport near the inner wall. Therefore, the reduction in the dissipation rate is predominantly attributed to decreased turbulence production, causing drag reduction. For low-viscosity light droplets, the production term diminishes further, primarily due to their greater reduction in Reynolds stress, while reduced viscosity weakens the density difference's contribution to TKE transport near the inner cylinder, resulting in a more pronounced reduction in the dissipation rate and consequently stronger drag reduction. Our findings provide new insights into the physics of turbulence modulation by the dispersed phase in two-phase turbulence systems.

In recent years, dangerous gas leakage events occur frequently. Rapid and accurate location of gas leakage sources by mobile robots is the key to avoid the expansion of disasters. In order to solve the problem of discontinuous gas concentration gradient and sparse gas environment in three-dimensional space, particle filter, and whale swarm optimization algorithm are integrated to locate gas source. Firstly, the Z-shape search and comb search are used to locate the plume, and then, the particle filter algorithm is combined with the whale optimization method to guide the particle movement, and the random inertial disturbance term is designed to improve the convergence speed and search accuracy of the algorithm. Experimental results in three-dimensional environment show that the proposed information-driven particle filter whale optimization hybrid algorithm effectively guides the robot in localizing gas source within a certain range, significantly enhancing both the efficiency and accuracy of localization compared to other algorithms.