A fleet of aircraft can be seen as a set of degrading systems that undergo variable loads as they fly missions and require maintenance throughout their lifetime. Optimal fleet management aims to maximise fleet availability while minimising overall maintenance costs. To achieve this goal, individual aircraft, with variable age and degradation paths, need to operate cooperatively to maintain high fleet availability while avoiding mechanical failure by scheduling preventive maintenance actions. In recent years, reinforcement learning (RL) has emerged as an effective method to optimise complex sequential decision-making problems. In this paper, an RL framework to optimise the operation and maintenance of a fleet of aircraft is developed. Three cases studies, with varying number of aircraft in the fleet, are used to demonstrate the ability of the RL policies to outperform traditional operation/maintenance strategies. As more aircraft are added to the fleet, the combinatorial explosion of the number of possible actions is identified as a main computational limitation. We conclude that the RL policy has potential to support fleet management operators and call for greater research on the application of multi-agent RL for fleet availability optimisation.

In this paper, we investigate the constrained attitude control problem of hypersonic vehicles (HVs). An improved prescribed performance dynamic surface control method is proposed based on an adaptive scaling strategy. Because of the uncertain time-varying disturbances, the controlled state may violate the constraint in the prescribed performance control (PPC) framework. An adaptive scaling strategy is introduced in the PPC method to avoid state violation. The performance function is scaled with respect to the state adaptively. Moreover, a nonlinear disturbance observer is used to compensate the sum of external and other internal disturbances of the system. The proposed method improves the system dynamic performance while ensuring the system robustness. Furthermore, the stability of the closed-loop system is proved by Lyapunov analysis. Finally, numerical simulations are implemented to verify the effectiveness of the PPC method and superiority over other methods.

In recent years, there has been significant momentum in applying deep learning (DL) to machine health monitoring (MHM). It has been widely claimed that DL methodologies are superior to more traditional techniques in this area. This paper aims to investigate this claim by analysing a real-world dataset of helicopter sensor faults provided by Airbus. Specifically, we will address the problem of machine sensor health unsupervised classification. In a 2019 worldwide competition hosted by Airbus, Fujitsu Systems Europe (FSE) won first prize by achieving an F1-score of 93% using a DL model based on generative adversarial networks (GAN). In another comprehensive study, various modified and existing image encoding methods were compared for the convolutional auto-encoder (CAE) model. The best classification result was achieved using the scalogram as the image encoding method, with an F1-score of 91%. In this paper, we use these two studies as benchmarks to compare with basic statistical analysis methods and the one-class supporting vector machine (SVM). Our comparative study demonstrates that while DL-based techniques have great potential, they are not always superior to traditional methods. We therefore recommend that all future published studies of applying DL methods to MHM include appropriately selected traditional reference methods, wherever possible.

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, an adaptive neural output-constrained control algorithm is proposed for a class of non-affine kinetic kill vehicle (KKV) systems. The key point is that the non-affine control law can be designed and the output of the KKV system conform to the output limit with the aid of the proposed method. Due to the aerodynamic moments, the actual control torque is non-affine, which can be addressed by introducing an integral process to the design of the controller. Besides, in order to improve the control precision, a nonlinear mapping is put forward so that the output constraint can be transformed to the constraint of the introduced dynamic signal that can be simply achieved. From the simulation results it can be concluded that the states of the KKV system can track the desired trajectories in spite of different working conditions and the control precision is higher compared with other control methods.

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.

We examined the effect of an antimicrobial stewardship program (ASP), procalcitonin testing and rapid blood-culture identification on hospital mortality in a prospective quality improvement project in critically ill septic adults. Secondarily, we have reported antimicrobial guideline concordance, acceptance of ASP interventions, and antimicrobial and health-resource utilization.

Background: Enhanced recovery after surgery (ERAS) concept has been implemented in many surgical specialties, with improved surgical and clinical outcomes, all while decreasing hospital cost. We have established a single center ERAS protocol for Anterior Cervical Discectomy and Fusion (ACDF) same-day surgeries. Methods: A retrospective analysis of prospective collected data of all patients undergoing one to two level ACDF surgeries at the CHUM based on a patient selection criteria’s list. Demographics, BMI, patient report outcome measures (NDI, VAS, mJOA), operative time, wake up time, time in recovery room and time till discharge were analysed. Complications were also noted. Results: When compared to our pre-ERAS group, our study showed that an ERAS protocol in select patients is not associated with any peri-operative complications, no 30-day / 90-day readmissions, nor any conversion to admission. All patients were safely discharged as planned. Operative length was similar. There was no dysphagia noted. There was improvement in all PROMs. Conclusions: ERAS protocol for ACDF same day surgeries in carefully selected patients is safe and provide same clinical outcomes. Meticulous surgical techniques, close post operative observation with a follow-up telephone call the next day are all key in assuring a safe and successful surgery and patient discharge.

Background: There are many cognitive tests that detect mild cognitive impairment (MCI) and dementia such as the Montreal Cognitive Assessment (MoCA) and Rowland Universal Dementia Assessment Scale (RUDAS). The comparative performance of these screening tests for identifying MCI and dementia is unknown. Methods: The MoCA and RUDAS were administered during baseline visits for patients in the Calgary Neurosciences Program. Those that enrolled in the Prospective Registry of Persons with Memory Symptoms (PROMPT) had their scores related to their final clinical diagnosis. Cut-off scores of 26 for the MoCA and 22 for the RUDAS were used to indicate a positive result. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of both cognitive scores were compared. Results: The sensitivity, specificity, PPV, NPV, and accuracy of the MoCA (n = 125) was 89.3%, 72.7%, 93.9%, 59.3%, and 86.4%, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of the RUDAS (n = 125) was 47.6%, 100%, 100%, 29.0%, 56.8%, respectively. Conclusions: In patients with cognitive complaints presenting to a specialist clinic, the MoCA was more sensitive and accurate than the RUDAS for a final clinician diagnosis of mild cognitive impairment or dementia when using the standard cut-offs.

Background: The Montreal Cognitive Assessment (MoCA) and Rowland Universal Dementia Assessment Scale (RUDAS) are tests used to detect mild cognitive impairment (MCI) and dementia. However, it has been suggested that the MoCA may not be appropriate for diverse populations, and that the relatively newer RUDAS may be better suited as a universal cognitive test. Methods: The MoCA and RUDAS were administered at baseline visits for participants enrolled in the Prospective Registry of Persons with Memory Symptoms (PROMPT). Test scores were compared for patients with different levels of educational attainment, first language, and race using the Kruskal-Wallis test. Results: The difference in MoCA (0.029) and RUDAS (0.0041) scores between patients with different levels of educational attainment (n = 141) was significant. The difference in MoCA (0.62) and RUDAS (0.78) scores between patients with a different first language (n = 141) was not significant. The difference in MoCA (0.64) and RUDAS (0.96) scores between patients of different race (n = 141) was not significant. Conclusions: The difference between MoCA and RUDAS scores remained consistent regardless of level of educational attainment, first language and race. The results suggest that the RUDAS may not be more appropriate than the MoCA in detecting MCI and dementia across diverse populations.

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.

Progressive capillary waves on the interface between two homogeneous fluids confined in a channel with rigid walls parallel to the undisturbed interface are investigated. This problem is formulated as a system of integrodifferential equations that can be solved numerically via a boundary integral equation method coupled with series expansions of the unknown functions. With this highly accurate scheme and numerical continuation, we explore the global bifurcation of periodic travelling waves. It is found that there are two types of limiting profile, self-intersecting and boundary-touching, which appear either along a primary branch bifurcating from infinitesimal periodic waves or on an isolated branch existing above a certain finite amplitude. For particular sets of parameters, these two types of bifurcation curves can intersect, which can be viewed as a secondary bifurcation phenomenon occurring on the primary branch. Based on asymptotic and numerical analyses of the almost limiting waves, it is found that the boundary-touching solutions feature a circular geometry, i.e. the interface is pieced together by circular arcs of the same radius. A theoretical investigation yields the necessary conditions for the existence of these extreme waves, whereby we can predict the limiting configurations for most parameter sets. The comparisons between theoretical predictions and numerical results show good agreement.

Since 2014, Chinese courts have placed tens of millions of court judgments online. We analyze the promise and pitfalls of using this new data source, highlighting takeaways for readers facing similar issues using other collections of legal texts. Drawing on 1,058,986 documents from Henan Province, we identify problems with missing data and call on scholars to treat variation in court disclosure rates as an urgent research question. We also outline strategies for learning from a corpus that is vast and incomplete. Using a topic model of administrative litigation in Henan, we complicate conventional wisdom that administrative lawsuits are an extension of contentious politics that give Chinese citizens an opportunity to challenge the state. Instead, we find a high prevalence of administrative cases that reflect an underlying dispute between two private parties, suggesting that administrative lawsuits are often an attempt to enlist help from the state in resolving an underlying civil dispute.

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.