As avionics systems become increasingly complex, traditional fault prediction methods are no longer sufficient to meet modern demands. This paper introduces four advanced fault prediction methods for avionics components, utilising a multi-step prediction strategy combined with a stacking regressor. By selecting various standard regression models as base regressors, these base regressors are first trained on the original data, and their predictions are subsequently used as input features for training a meta-regressor. Additionally, the Tree-structured Parzen Estimator (TPE) algorithm is employed for hyperparameter optimisation. The experimental results demonstrate that the proposed stacking regression methods exhibit superior accuracy in fault prediction compared to traditional single-model approaches.

The objective of this study was to investigate the effects of different cockpit primary flight display (PFD) interface designs on pilot cognitive efficiency and cognitive load. This study designed five optimised PFD interfaces and conducted interface cognition experiments to assess cognitive responses across six different PFD interface designs, including the original design. It compared various subjective and objective metrics across different interface designs and evaluated the impact of each design factor on cognitive task performance. The experimental results show that the PFD interface in the original interface design performs better under different flight symbol designs, and the interface with 50% increase in font size performs better among interface designs with different font sizes with relatively lower cognitive load. This study provides experimental support and optimization suggestions for the optimal design of cockpit PFD interface, which can help improve pilots’ perception and operational capabilities, and thus enhance task performance efficiency and flight safety. Future research can investigate the effects of various design factors on the cognitive effects of the interface to enhance the ongoing improvement and optimisation of interface design.

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.

Aircraft ground taxiing contributes significantly to carbon emissions and engine wear. The electric towing tractor (ETT) addresses these issues by towing the aircraft to the runway end, thereby minimising ground taxiing. As the complexity of ETT towing operations increases, both the towing distance and time increase significantly, and the original method for estimating the number of ETTs is no longer applicable. Due to the substantial acquisition cost of ETT and the need to reduce waste while ensuring operational efficiency, this paper introduces for the first time an ETT quantity estimation model that combines simulation and vehicle scheduling models. The simulation model simulates the impact of ETT on apron operations, taxiing on taxiways and takeoffs and landings on runways. Key timing points for ETT usage by each aircraft are identified through simulation, forming the basis for determining the minimum number of vehicles required for airport operations using a hard-time window vehicle scheduling model. To ensure the validity of the model, simulation model verification is conducted. Furthermore, the study explores the influence of vehicle speed and airport scale on the required number of ETTs. The results demonstrate the effective representation of real-airport operations by the simulation model. ETT speed, airport runway and taxiway configurations, takeoff and landing frequencies and imbalances during peak periods all impact the required quantity of ETTs. A comprehensive approach considering these factors is necessary to determine the optimal number of ETTs.

This study presents observations of coherent modes (CMs) in a spherical tokamak using a microwave interferometer near the midplane. The CMs within the 30–60 kHz frequency range were observed during electron cyclotron resonance heating only, and the frequency of the CMs increased proportionally with the square root of the electron temperature near $R = 0.7m$. Generally, these modes displayed bursting and chirping signatures with strong density rise and fall. Their appearance indicated an increase in the intensity of hard x rays, suggesting a deterioration in energetic electron confinement. Furthermore, the effect of CMs on the intensity of energetic electron-driven whistler waves was observed. They decreased when CMs were present and gradually increased with the decrease in CM intensity. The CMs may influence the intensity of whistler waves by affecting the energetic electron confinement.

Ultrafast optical probing is a widely used method of underdense plasma diagnostic. In relativistic plasma, the motion blur limits spatial resolution in the direction of motion. For many high-power lasers the initial pulse duration of 30–50 fs results in a 10–15 μm motion blur, which can be reduced by probe pulse post-compression. Here we used the compression after compressor approach [Phys.-Usp. 62, 1096 (2019); JINST 17 P07035 (2022)], where spectral broadening is performed in thin optical plates and is followed by reflections from negative-dispersion mirrors. Our initially low-intensity probe beam was down-collimated for a more efficient spectral broadening and higher probe-to-self-emission intensity ratio. The setup is compact, fits in a vacuum chamber and can be implemented within a short experimental time slot. We proved that the compressed pulse retained the high quality necessary for plasma probing.

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.

Schistosoma species have traditionally been arranged in groups based on egg morphology, geographical origins, and the genus or family of snail intermediate host. One of these groups is the ‘S. indicum group’ comprising species from Asia that use pulmonate snails as intermediate hosts. DNA sequences were obtained from the four members of this group (S. indicum, S. spindale, S. nasale and S. incognitum) to provide information concerning their phylogenetic relationships with other Asian and African species and species groups. The sequences came from the second internal transcribed spacer (ITS2) of the ribosomal gene repeat, part of the 28S ribosomal RNA gene (28S), and part of the mitochondrial cytochrome c oxidase subunit 1 (CO1) gene. Tree analyses using both distance and parsimony methods showed the S. indicum group not to be monophyletic. Schistosoma indicum, S. spindale and S. nasale were clustered among African schistosomes, while S. incognitum was placed as sister to the African species (using ITS2 and 28S nucleotide sequences and CO1 amino acid sequences), or as sister to all other species of Schistosoma (CO1 nucleotide sequences). Based on the present molecular data, a scenario for the evolution of the S. indicum group is discussed.

The status of Schistosoma sinensium (samples from Thailand and from Sichuan, China) relative to other species of the genus Schistosoma was investigated using DNA sequences from the mitochondrial cytochrome c oxidase subunit 1 (CO1) gene (partial) and the nuclear ribosomal DNA second internal transcribed spacer 2 (ITS2). Trees inferred from these sequences place S. sinensium as sister to the S. japonicum group and suggest a basal position in the clade utilizing snails of the family Pomatiopsidae. The sequence differences between specimens of S. sinensium from China and Thailand are at least as great as between S. malayensis and S. mekongi. Schistosoma sinensium is probably best regarded as a species complex.

Echinococcosis poses a significant threat to public health. The Chinese government has implemented prevention and control measures to mitigate the impact of the disease. By analyzing data from the Chinese Center for Disease Control and Prevention and the State Council of the People’s Republic of China, we found that implementation of these measures has reduced the infection rate by nearly 50% between 2004 to 2022 (from 0.3975 to 0.1944 per 100,000 person-years). Nonetheless, some regions still bear a significant disease burden, and lack of detailed information limites further evaluation of the effects on both alveolar and cystic echinococcosis. Our analysis supports the continuing implementation of these measures and suggests that enhanced wildlife management, case-based strategies, and surveillance systems will facilitate disease control.

To accelerate high-intensity heavy-ion beams to high energy in the booster ring (BRing) at the High-Intensity Heavy-Ion Accelerator Facility (HIAF) project, we take the typical reference particle 238U35+, which can be accelerated from an injection energy of 17 MeV/u to the maximal extraction energy of 830 MeV/u, as an example to study the basic processes of longitudinal beam dynamics, including beam capture, acceleration, and bunch merging. The voltage amplitude, the synchronous phase, and the frequency program of the RF system during the operational cycle were given, and the beam properties such as bunch length, momentum spread, longitudinal beam emittance, and beam loss were derived, firstly. Then, the beam properties under different voltage amplitude and synchronous phase errors were also studied, and the results were compared with the cases without any errors. Next, the beam properties with the injection energy fluctuation were also studied. The tolerances of the RF errors and injection energy fluctuation were dictated based on the CISP simulations. Finally, the effect of space charge at the low injection energy with different beam intensities on longitudinal emittance and beam loss was evaluated.

This study presents novel findings on stochastic electron heating via a random electron cyclotron wave (ECW) in a spherical tokamak. Hard x ray measurements demonstrate the time evolution of hard x ray counts at different energy bands, consistent with predictions from the stochastic heating model. The ECW heating rate shows a positive correlation with applied power, confirming the effectiveness of stochastic heating. Remarkably, the ECW-driven plasma current remains insensitive to ECW incidence angle, consistent with model predictions. The observed stochastic heating of electrons offers potential for exploring innovative non-inductive current drive modes in spherical tokamaks. This research contributes to the understanding of plasma behaviour and motivates the development of new models for non-inductive current drive in fusion devices.

In 2007, Andrews introduced Durfee symbols and k-marked Durfee symbols so as to give a combinatorial interpretation for the symmetrized moment function $\eta _{2k}(n)$ of ranks of partitions. He also considered the relations between odd Durfee symbols and the mock theta function $\omega (q)$, and proved that the $2k$th moment function $\eta _{2k}^0(n)$ of odd ranks of odd Durfee symbols counts $(k+1)$-marked odd Durfee symbols of n. In this paper, we first introduce the definition of symmetrized positive odd rank moments $\eta _k^{0+}(n)$ and prove that for all $1\leq i\leq k+1$, $\eta _{2k-1}^{0+}(n)$ is equal to the number of $(k+1)$-marked odd Durfee symbols of n with the ith odd rank equal to zero and $\eta _{2k}^{0+}(n)$ is equal to the number of $(k+1)$-marked Durfee symbols of n with the ith odd rank being positive. Then we calculate the generating functions of $\eta _{k}^{0+}(n)$ and study its asymptotic behavior. Finally, we use Wright’s variant of the Hardy–Ramanujan circle method to obtain an asymptotic formula for $\eta _{k}^{0+}(n)$.

Vortex shedding in the wake of a cylinder in uniform flow can be suppressed via the application of a porous coating; however, the suppression mechanism is not fully understood. The internal flow field of a porous coated cylinder (PCC) can provide a deeper understanding of how the flow within the porous medium affects the wake development. A structured PCC (SPCC) was three-dimensionally printed using a transparent material and tested in water tunnel facilities using flow visualisation and tomographic particle image velocimetry at outer-diameter Reynolds numbers of $Re = 7 \times 10^{3}$ and $7.3 \times 10^{4}$, respectively. The internal and near-wall flow fields are analysed at the windward and mid-circumference regions. Flow stagnation is observed in the porous layer on the windward side and its boundary is shown to fluctuate with time in the outermost porous layer. This stagnation region generates a quasi-aerodynamic body that influences boundary layer development on the SPCC inner diameter, that separates into a shear layer within the porous medium. For the first time via experiment, spectral content within the separated shear layer reveals vortex shedding processes emanating through single pores at the outer diameter, providing strong evidence that SPCC vortex shedding originates from the inner diameter. Velocity fluctuations linked to this vortex shedding propagate through the porous layers into the external flow field at a velocity less than that of the free stream. The Strouhal number linked to this velocity accurately predicts the SPCC vortex shedding frequency.

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.