We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and searches for dispersed fast transient signals including fast radio bursts (FRB), pulsars, and ultra-long period objects (ULPO). With the visibility data, CRACO can localise the transient events to arcsecond-level precision after the detection. Here, we describe the CRACO system and report the result from a sky survey carried out by CRACO at 110-ms resolution during its commissioning phase. During the survey, CRACO detected two FRBs (including one discovered solely with CRACO, FRB 20231027A), reported more precise localisations for four pulsars, discovered two new RRATs, and detected one known ULPO, GPM J1839 $-$10, through its sub-pulse structure. We present a sensitivity calibration of CRACO, finding that it achieves the expected sensitivity of 11.6 Jy ms to bursts of 110 ms duration or less. CRACO is currently running at a 13.8 ms time resolution and aims at a 1.7 ms time resolution before the end of 2024. The planned CRACO has an expected sensitivity of 1.5 Jy ms to bursts of 1.7 ms duration or less and can detect $10\times$ more FRBs than the current CRAFT incoherent sum system (i.e. 0.5 $-$2 localised FRBs per day), enabling us to better constrain the models for FRBs and use them as cosmological probes.

This paper develops a novel full-state-constrained intelligent adaptive control (FIAC) scheme for a class of uncertain nonlinear systems under full state constraints, unmodeled dynamics and external disturbances. The key point of the proposed scheme is to appropriately suppress and compensate for unmodeled dynamics that are coupled with other states of the system under the conditions of various disturbances and full state constraints. Firstly, to guarantee that the time-varying asymmetric full state constraints are obeyed, a simple and valid nonlinear error transformation method has been proposed, which can simplify the constrained control problem of the system states into a bounded control problem of the transformed states. Secondly, considering the coupling relationship between the unmodeled dynamics and other states of the controlled system such as system states and control inputs, a decoupling approach for coupling uncertainties is introduced. Thereafter, owing to the employed dynamic signal and bias radial basis function neural network (BIAS-RBFNN) improved on traditional RBFNN, the adverse effects of unmodeled dynamics on the controlled system can be suppressed appropriately. Furthermore, the matched and mismatched disturbances are reasonably estimated and circumvented by a mathematical inequality and a disturbance observer, respectively. Finally, numerical simulations are provided to demonstrate the effectiveness of the proposed FIAC strategy.

To investigate the flame acceleration to detonation in 2.0 and 0.5 mm planar glass combustion chambers, the experiments have been conducted utilising ethylene/oxygen mixtures at atmospheric pressure and temperature. The high-speed camera has been used to record the revolution of flame front and pressure inside the combustion chamber. Different equivalence ratios and ignition locations have been considered in the experiments. The results show that the detonation pressure in the 2 mm thick chamber is nearly three times of Chapman-Jouguet pressure, while detonation pressure in the 0.5 mm thick chamber is only 45.7% of the Chapman-Jouguet value at the stoichiometric mixture. This phenomenon is attributed to the larger pressure loss in the thinner chamber during the detonation propagation. As the value of equivalence ratio is 2.2, the detonation cannot be produced in the 2 mm thick chamber, while the detonation can be generated successfully in the 0.5 mm thick chamber. This phenomenon indicates that the deflagration is easily to be accelerated and transformed into the detonation, due to a larger wall friction and reflection. Besides, the micro-obstacle has been added into the combustor can shorten the detonation transition time and reduces the distance of the detonation transition.

In this paper, a brand-new adaptive fault-tolerant non-affine integrated guidance and control method based on reinforcement learning is proposed for a class of skid-to-turn (STT) missile. Firstly, considering the non-affine characteristics of the missile, a new non-affine integrated guidance and control (NAIGC) design model is constructed. For the NAIGC system, an adaptive expansion integral system is introduced to address the issue of challenging control brought on by the non-affine form of the control signal. Subsequently, the hyperbolic tangent function and adaptive boundary estimation are utilised to lessen the jitter due to disturbances in the control system and the deviation caused by actuator failures while taking into account the uncertainty in the NAIGC system. Importantly, actor-critic is introduced into the control framework, where the actor network aims to deal with the multiple uncertainties of the subsystem and generate the control input based on the critic results. Eventually, not only is the stability of the NAIGC closed-loop system demonstrated using Lyapunov theory, but also the validity and superiority of the method are verified by numerical simulations.

Unmanned aerial vehicles (UAVs) have recently been widely applied in a comprehensive realm. By enhancing computer photography and artificial intelligence, UAVs can automatically discriminate against environmental objectives and detect events that occur in the real scene. The application of collaborative UAVs will offer diverse interpretations which support a multiperspective view of the scene. Due to the diverse interpretations of UAVs usually deviating, UAVs require a consensus interpretation for the scenario. This study presents an original consensus-based method to pilot multi-UAV systems for achieving consensus on their observation as well as constructing a group situation-based depiction of the scenario. Taylor series are used to describe the fuzzy nonlinear plant and derive the stability analysis using polynomial functions, which have the representations $V(x )={m_{\textrm{1} \le l \le N}}({{V_\textrm{l}}(x )} )$ and ${V_l}(x )={x^T}{P_l}(x )x$. Due to the fact that the ${\dot{P}_l}(x )$ in ${\dot{V}_l}(x )={\dot{x}^T}{P_l}(x )x + {x^T}{\dot{P}_l}(x )x + {x^T}{P_l}(x )\dot{x}$ will yield intricate terms to ensure a stability criterion, we aim to avoid these kinds of issues by proposing a polynomial homogeneous framework and using Euler's functions for homogeneous systems. First, this method permits each UAV to establish high-level conditions from the probed events via a fuzzy-based aggregation event. The evaluated consensus indicates how suitable is the scenario collective interpretation for every UAV perspective.

The purpose of this study was to explore the electroencephalogram (EEG) features sensitive to situation awareness (SA) and then classify SA levels. Forty-eight participants were recruited to complete an SA standard test based on the multi-attribute task battery (MATB) II, and the corresponding EEG data and situation awareness global assessment technology (SAGAT) scores were recorded. The population with the top 25% of SAGAT scores was selected as the high-SA level (HSL) group, and the bottom 25% was the low-SA level (LSL) group. The results showed that (1) for the relative power of $\beta$1 (16–20Hz), $\beta$2 (20–24Hz) and $\beta$3 (24–30Hz), repeated measures analysis of variance (ANOVA) in three brain regions (Central Central-Parietal, and Parietal) × three brain lateralities (left, midline, and right) × two SA groups (HSL and LSL) showed a significant main effect for SA groups; post hoc comparisons revealed that compared with LSL, the above features of HSL were higher. (2) for most ratio features associated with $\beta$1 ∼ $\beta$3, ANOVA also revealed a main effect for SA groups. (3) EEG features sensitive to SA were selected to classify SA levels with small-sample data based on the general supervised machine learning classifiers. Five-fold cross-validation results showed that among the models with easy interpretability, logistic regression (LR) and decision tree (DT) presented the highest accuracy (both 92%), while among the models with hard interpretability, the accuracy of random forest (RF) was 88.8%, followed by an artificial neural network (ANN) of 84%. The above results suggested that (1) the relative power of $\beta$1 ∼ $\beta$3 and their associated ratios were sensitive to changes in SA levels; (2) the general supervised machine learning models all exhibited good accuracy (greater than 75%); and (3) furthermore, LR and DT are recommended by combining the interpretability and accuracy of the models.

Aiming at alleviating the adverse influence of coupling unmodeled dynamics, actuator faults and external disturbances in the attitude tracking control system of tilt tri-rotor unmanned aerial vehicle (UAVs), a neural network (NN)-based robust adaptive super-twisting sliding mode fault-tolerant control scheme is designed in this paper. Firstly, in order to suppress the unmodeled dynamics coupled with the system states, a dynamic auxiliary signal, exponentially input-to-state practically stability and some special mathematical tools are used. Secondly, benefiting from adaptive control and super-twisting sliding mode control (STSMC), the influence of the unexpected chattering phenomenon of sliding mode control (SMC) and the unknown system parameters can be handled well. Moreover, NNs are employed to estimate and compensate some unknown nonlinear terms decomposed from the system model. Based on a decomposed quadratic Lyapunov function, both the bounded convergence of all signals of the closed-loop system and the stability of the system are proved. Numerical simulations are conducted to demonstrate the effectiveness of the proposed control method for the tilt tri-rotor UAVs.

The Australian SKA Pathfinder (ASKAP) is being used to undertake a campaign to rapidly survey the sky in three frequency bands across its operational spectral range. The first pass of the Rapid ASKAP Continuum Survey (RACS) at 887.5 MHz in the low band has already been completed, with images, visibility datasets, and catalogues made available to the wider astronomical community through the CSIRO ASKAP Science Data Archive (CASDA). This work presents details of the second observing pass in the mid band at 1367.5 MHz, RACS-mid, and associated data release comprising images and visibility datasets covering the whole sky south of $\delta_{\text{J2000}}=+49^\circ$. This data release incorporates selective peeling to reduce artefacts around bright sources, as well as accurately modelled primary beam responses. The Stokes I images reach a median noise of 198 $\mu$Jy PSF$^{-1}$ with a declination-dependent angular resolution of 8.1–47.5 arcsec that fills a niche in the existing ecosystem of large-area astronomical surveys. We also supply Stokes V images after application of a widefield leakage correction, with a median noise of 165 $\mu$Jy PSF$^{-1}$. We find the residual leakage of Stokes I into V to be $\lesssim 0.9$–$2.4$% over the survey. This initial RACS-mid data release will be complemented by a future release comprising catalogues of the survey region. As with other RACS data releases, data products from this release will be made available through CASDA.

In this paper, a super-twisting disturbance observer (STDO)-based adaptive reinforcement learning control scheme is proposed for the straight air compound missile system with aerodynamic uncertainties and unmodeled dynamics. Firstly, neural network (NN)-based adaptive reinforcement learning control scheme with actor-critic design is investigated to deal with the tracking problems for the straight gas compound system. The actor NN and the critic NN are utilised to cope with the unmodeled dynamics and approximate the cost function that are related to control input and tracking error, respectively. In other words, the actor NN is used to perform the tracking control behaviours, and the critic NN aims to evaluate the tracking performance and give feedback to actor NN. Moreover, with the aid of the STDO disturbance observer, the problem of the control signal fluctuation caused by the mismatched disturbance can be solved well. Based on the proposed adaptive law and the Lyapunov direct method, the eventually consistent boundedness of the straight gas compound system is proved. Finally, numerical simulations are carried out to demonstrate the feasibility and superiority of the proposed reinforcement learning-based STDO control algorithm.

The target backsheath field acceleration mechanism is one of the main mechanisms of laser-driven proton acceleration (LDPA) and strongly depends on the comprehensive performance of the ultrashort ultra-intense lasers used as the driving sources. The successful use of the SG-II Peta-watt (SG-II PW) laser facility for LDPA and its applications in radiographic diagnoses have been manifested by the good performance of the SG-II PW facility. Recently, the SG-II PW laser facility has undergone extensive maintenance and a comprehensive technical upgrade in terms of the seed source, laser contrast and terminal focus. LDPA experiments were performed using the maintained SG-II PW laser beam, and the highest cutoff energy of the proton beam was obviously increased. Accordingly, a double-film target structure was used, and the maximum cutoff energy of the proton beam was up to 70 MeV. These results demonstrate that the comprehensive performance of the SG-II PW laser facility was improved significantly.

Lift alleviation by a mini-spoiler on aerofoils, unswept and swept wings encountering an isolated counter-clockwise vortical gust was investigated by means of force and velocity measurements. The flow separation region behind the spoiler remains little affected during the gust encounter. The maximum lift reduction is found for the static stall angle of attack. The change in the maximum lift during the gust encounter is approximately equal to that in steady freestream. The comparison with plunging aerofoils reveals that, for the same maximum gust and plunge velocity, the effectiveness of the mini-spoiler is much better in travelling gusts. This reveals the importance of the streamwise length scale of the incident gust. For the unswept wing, there is some three-dimensionality of the flow separation induced by the mini-spoiler near the wing tip. The magnitude of the lift reduction can be estimated using the aerofoil data and by making an aspect ratio correction for the reduced effective angle of attack. For the swept wing, the mini-spoiler can disrupt the formation of a leading-edge vortex induced by the incident vortex on the clean wing and can still reduce the maximum lift.

As a typical plasma-based optical element that can sustain ultra-high light intensity, plasma density gratings driven by intense laser pulses have been extensively studied for wide applications. Here, we show that the plasma density grating driven by two intersecting driver laser pulses is not only nonuniform in space but also varies over time. Consequently, the probe laser pulse that passes through such a dynamic plasma density grating will be depolarized, that is, its polarization becomes spatially and temporally variable. More importantly, the laser depolarization may spontaneously take place for crossed laser beams if their polarization angles are arranged properly. The laser depolarization by a dynamic plasma density grating may find application in mitigating parametric instabilities in laser-driven inertial confinement fusion.

FFD (free-form deformation method) is one of the most commonly used parameterisation methods at present. It places the parameterised objects inside the control volume through coordinate system transformation, and controls the control volume through control points, thus realising the deformation control of its internal objects. Firstly, this paper systematically analyses and compares the characteristics and technical requirements of Bernstein, B-spline and NURBS (non-uniform rational b-splines) basic functions that can be adopted by FFD, and uses the minimum number of control points required to achieve the specified control effect threshold to express the control capability. Aiming at the problem of discontinuity at the right end in the actual calculation of B-spline basis function, a method of adding a small epsilon is proposed to solve it. Then, three basic functions are applied to the FFD parameterisation method, respectively, and the differences are compared from two aspects of the accurate expression of the model and the ability of deformation control. It is found that the BFFD (b-spline free-form deformation) approach owns better comprehensive performance when the control points are distributed correctly. In this paper, the BFFD method is improved, and a p-BFFD (reverse solution points based BFFD) method based on inverse solution is proposed to realise the free distribution of control points under the specified topology. Further, for the lifting body configuration, the control points of the p-BFFD method are brought closer to the airframe forming the EDGE-p-BFFD (edge constraints based p-BFFD) method. For the case in this paper, the proposed EDGE-p-BFFD method not only has fairly high parameterisation accuracy, but also reduces the expression error from 1.01E-3 to 1.25E-4, which is nearly ten times. It can also achieve effective lifting body guideline constraints, and has the ability of local deformation adapting to the configuration characteristics. In terms of the proportion of effective control points, the EDGE-p-BFFD method increases the proportion of effective control points from 36.7% to 50%, and the more control points, the more obvious the proportion increase effect. The new method also has better effect on the continuity of geometric deformation. At the same time, this paper introduces the independent deformation method of the upper and lower surfaces based on the double control body frames, which effectively avoids the deformation coupling problem of the simultaneous change of the upper and lower surfaces caused by the movement of control points in the traditional single control framework.

Effects of plasma non-uniformities and kinetic dispersiveness on the spontaneous excitation of geodesic acoustic mode (GAM) by reversed shear Alfvén eigenmode (RSAE) are investigated numerically. It is found that, due to the turning points induced by the shear Alfvén continuum structure, the nonlinear excitation of GAM is a quasiexponentially growing absolute instability. As the radial dependence of GAM frequency and pump RSAE mode structure are accounted for, the radially inward propagating GAM is preferentially excited, leading to core localized thermal plasma heating by GAM collisionless damping. Our work, thus, suggests that GAM excitation plays a crucial role in not only RSAE nonlinear saturation, but also anomalous fuel ion heating in future reactors.

The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.

We report the experimental results of the commissioning phase in the 10 PW laser beamline of the Shanghai Superintense Ultrafast Laser Facility (SULF). The peak power reaches 2.4 PW on target without the last amplifying during the experiment. The laser energy of 72 ± 9 J is directed to a focal spot of approximately 6 μm diameter (full width at half maximum) in 30 fs pulse duration, yielding a focused peak intensity around 2.0 × 1021 W/cm2. The first laser-proton acceleration experiment is performed using plain copper and plastic targets. High-energy proton beams with maximum cut-off energy up to 62.5 MeV are achieved using copper foils at the optimum target thickness of 4 μm via target normal sheath acceleration. For plastic targets of tens of nanometers thick, the proton cut-off energy is approximately 20 MeV, showing ring-like or filamented density distributions. These experimental results reflect the capabilities of the SULF-10 PW beamline, for example, both ultrahigh intensity and relatively good beam contrast. Further optimization for these key parameters is underway, where peak laser intensities of 1022–1023 W/cm2 are anticipated to support various experiments on extreme field physics.

The spatio-temporal variation of leaf chlorophyll content is an important crop phenotypic trait that is of great significance for evaluating crop productivity. This study used a soil-plant analysis development (SPAD) chlorophyll meter for non-destructive monitoring of leaf chlorophyll dynamics to characterize the patterns of spatio-temporal variation in the nutritional status of maize (Zea mays L.) leaves under three nitrogen treatments in two cultivars. The results showed that nitrogen levels could affect the maximum leaf SPAD reading (SPADmax) and the duration of high SPAD reading. A rational model was used to measure the changes in SPAD readings over time in single leaves. This model was suitable for predicting the dynamics of the nutrient status for each leaf position under different nitrogen treatments, and model parameter values were position dependent. SPADmax at each leaf decreased with the reduction of nitrogen supply. Leaves at different positions in both cultivars responded differently to higher nitrogen rates. Lower leaves (8th–10th positions) were more sensitive than the other leaves in response to nitrogen. Monitoring the SPAD reading dynamic of lower leaves could accurately characterize and assess the nitrogen supply in plants. The lower leaves in nitrogen-deficient plants had a shorter duration of high SPAD readings compared to nitrogen-sufficient plants; this physiological mechanism should be studied further. In summary, the spatio-temporal variation of plant nitrogen status in maize was analysed to determine critical leaf positions for potentially assisting in the identification of appropriate agronomic management practices, such as the adjustment of nitrogen rates in late fertilization.