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.

The bevelled nozzle is a promising noise control approach and has been tested to suppress the noise levels in supersonic circular jets, but not in rectangular jets so far. In this study, implicit large-eddy simulations are performed to analyse the noise control of supersonic rectangular jets with single- and double-bevelled nozzles. Three nozzle pressure ratios ($NPR = 2.3$, 3.0 and 5.0) are considered to form two over-expanded cold jets and one under-expanded cold jet, exhausted from a baseline convergent–divergent rectangular nozzle with an aspect ratio of 2.0. Results show that, with the increase of $NPR$, the oscillation of the jet plume is switched from a symmetrical mode to a flapping mode (preferential in the minor-axis plane), then to a helical mode, together with a reduction of the screech frequency. The amplitude of the screech tone is the strongest in the flapping jet, and the turbulent mixing noise is the most prominent in the helically oscillating jet. The single-bevelled nozzle induces asymmetric shock-cell structures and deflects the jet plumes, and the double-bevelled nozzle primarily enables the enhancement of the shear-layer mixing and shortens the lengths of the jet potential cores. With the bevelled nozzles, the gross thrusts of the baseline nozzle are increased by $0.05 \sim 7.38$ %. Details on the characteristics of far-field noise in the jets with/without the bevel cuts and their noise control mechanisms are discussed using the Ffowcs Williams–Hawkings acoustic analogy, dynamic mode decomposition and spatio-temporal Fourier transformation. Results suggest that the noise control has a close relationship with the destruction of well-organized coherent structures and the suppression of upstream-propagating guided-jet modes, which interrupt the feedback mechanism accounting for the generation of screech tones in the supersonic rectangular jets.

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.

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.

Fiber Bragg grating-based Raman oscillators are capable of achieving targeted frequency conversion and brightness enhancement through the provision of gain via stimulated Raman scattering across a broad gain spectrum. This capability renders them an exemplary solution for the acquisition of high-brightness, specialized-wavelength lasers. Nonetheless, the output power of all-fiber Raman oscillators is typically limited to several hundred watts, primarily due to limitations in injectable pump power and the influence of higher-order Raman effects, which is inadequate for certain application demands. In this study, we introduce an innovative approach by employing a graded-index fiber with a core diameter of up to 150 μm as the Raman gain medium. This strategy not only enhances the injectable pump power but also mitigates higher-order Raman effects. Consequently, we have successfully attained an output power of 1780 W for the all-fiber Raman laser at 1130 nm, representing the highest output power in Raman fiber oscillators with any configuration reported to date.

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.

Robot pick-and-place for unknown objects is still a very challenging research topic. This paper proposes a multi-modal learning method for robot one-shot imitation of pick-and-place tasks. This method aims to enhance the generality of industrial robots while reducing the amount of data and training costs the one-shot imitation method relies on. The method first categorizes human demonstration videos into different tasks, and these tasks are classified into six types to symbolize as many types of pick-and-place tasks as possible. Second, the method generates multi-modal prompts and finally predicts the action of the robot and completes the symbolic pick-and-place task in industrial production. A carefully curated dataset is created to complement the method. The dataset consists of human demonstration videos and instance images focused on real-world scenes and industrial tasks, which fosters adaptable and efficient learning. Experimental results demonstrate favorable success rates and loss results both in simulation environments and real-world experiments, confirming its effectiveness and practicality.