In this paper, we investigate the attitude manoeuver planning and tracking control of the flexible satellite equipped with a coilable mast. Due to its flexible beamlike structure, the coilable mast experiences bending and torsional modal vibrations in multi-direction. The complex nonlinear coupling and other external disturbances significantly impact the achievement of high-precision attitude control. To overcome these challenges, a robust attitude tracking controller is proposed for easy implementation by the Attitude Determination and Control System (ADCS). The controller consists of a disturbance compensator, feedforward controller and output feedback controller. The compensator, based on a Nonlinear Disturbance Observer (NDO), effectively compensates for the cluster disturbances caused by vibrations, environmental factors and parameter perturbations. The feedforward controller tracks the desired path in the nominal satellite model. Furthermore, the output feedback controller enables large-angle manoeuver control of the satellite and evaluates the suppression effect of the controlled output on the observation error of cluster disturbances used the ${L_2}$-gain. Simulation results demonstrate that the proposed controller successfully achieves high-precision attitude tracking control during large-angle manoeuvering.

Autonomous fabric manipulation is a challenging task due to complex dynamics and potential self-occlusion during fabric handling. An intuitive method of fabric-folding manipulation first involves obtaining a smooth and unfolded fabric configuration before the folding process begins. However, the combination of quasi-static actions like pick & place and dynamic action like fling proves inadequate in effectively unfolding long-sleeved T-shirts with sleeves mostly tucked inside the garment. To address this limitation, this paper introduces an enhanced quasi-static action called pick & drag, specifically designed to handle this type of fabric configuration. Additionally, an efficient dual-arm manipulation system is designed in this paper, which combines quasi-static (including pick & place and pick & drag) and dynamic fling actions to flexibly manipulate fabrics into unfolded and smooth configurations. Subsequently, once it is confirmed that the fabric is sufficiently unfolded and all fabric keypoints are detected, the keypoint-based heuristic folding algorithm is employed for the fabric-folding process. To address the scarcity of publicly available keypoint detection datasets for real fabric, we gathered images of various fabric configurations and types in real scenes to create a comprehensive keypoint dataset for fabric folding. This dataset aims to enhance the success rate of keypoint detection. Moreover, we evaluate the effectiveness of our proposed system in real-world settings, where it consistently and reliably unfolds and folds various types of fabrics, including challenging situations such as long-sleeved T-shirts with most parts of sleeves tucked inside the garment. Specifically, our method achieves a coverage rate of 0.822 and a success rate of 0.88 for long-sleeved T-shirts folding. Supplemental materials and dataset are available on our project webpage at https://sites.google.com/view/fabricfolding.

Ultra-processed plant-based foods, such as plant-based burgers, have gained in popularity. Particularly in the out-of-home (OOH) environment, evidence regarding their nutritional profile and environmental sustainability is still evolving. Plant-based burgers available at selected OOH sites were randomly sampled in Amsterdam, Copenhagen, Lisbon and London. Plant-based burgers (patty, bread and condiment) (n 41) were lab analysed for their energy, macronutrients, amino acids and minerals content per 100 g and serving and were compared with reference values. For the plant-based burgers, the median values per 100 g were 234 kcal, 20·8 g carbohydrates, 3·5 g dietary fibre and 12·0 g fat, including 0·08 g TFS and 2·2 g SFA. Protein content was 8·9 g/100 g, with low protein quality according to amino acid composition. Median Na content was 389 mg/100 g, equivalent to 1 g salt. Compared with references, the median serving provided 31% of energy intake based on a 2000 kcal per day and contributed to carbohydrates (17–28%), dietary fibre (42%), protein (40%), total fat (48%), SFA (26%) and Na (54%). One serving provided 15–23% of the reference values for Ca, K and Mg, while higher contributions were found for Zn, Mn, P and Fe (30–67%). The ultra-processed plant-based burgers provide protein, dietary fibre and essential minerals and contain relatively high levels of energy, Na and total fats. The amino acid composition indicated low protein quality. The multifaceted nutritional profile of plant-based burgers highlights the need for manufacturers to implement improvements to better support healthy dietary habits, including reducing energy, Na and total fats.

In a recent survey of nematodes associated with tobacco in Shandong, China, the root-lesion nematode Pratylenchus coffeae was identified using a combination of morphology and molecular techniques. This nematode species is a serious parasite that damages a variety of plant species. The model plant benthi, Nicotiana benthamiana, is frequently used to study plant-disease interactions. However, it is not known whether this plant species is a host of P. coffeae. The objectives of this study were to evaluate the parasitism and pathogenicity of five populations of the root-lesion nematode P. coffeae on N. benthamiana. N. benthamiana seedlings with the same growth status were chosen and inoculated with 1,000 nematodes per pot. At 60 days after inoculation, the reproductive factors (Rf = final population densities (Pf)/initial population densities (Pi)) for P. coffeae in the rhizosphere of N. benthamiana were all more than 1, suggesting that N. benthamiana was a good host plant for P. coffeae. Nicotiana. benthamiana infected by P. coffeae showed weak growth, decreased tillering, high root reduction, and noticeable brown spots on the roots. Thus, we determined that the model plant N. benthamiana can be used to study plant-P. coffeae interactions.

Feeding whole prey to felids has shown to benefit their gastrointestinal health. Whether this effect is caused by the chemical or physical nature of whole prey is unknown. Fifteen domestic cats, as a model for strict carnivores, were either fed minced mice (MM) or whole mice (WM), to determine the effect of food structure on digestibility, mean urinary excretion time (MUET) of 15N, intestinal microbial activity and fermentation products. Faeces samples were collected after feeding all cats a commercially available extruded diet (EXT) for 10 d before feeding for 19 d the MM and WM diets with faeces and urine collected from day 11 to 15. Samples for microbiota composition and determination of MUET were obtained from day 16 to 19. The physical structure of the mice diet (minced or not) did not affect large intestinal fermentation as total SCFA and branched-chain fatty acid (BCFA), and most biogenic amine (BA) concentrations were not different (P > 0·10). When changing from EXT to the mice diets, the microbial community composition shifted from a carbolytic (Prevotellaceae) to proteolytic (Fusobacteriaceae) profile and led to a reduced faecal acetic to propionic acid ratio, SCFA, total BCFA (P < 0·001), NH3 (P = 0·04), total BA (P < 0·001) and para-cresol (P = 0·08). The results of this study indicate that food structure within a whole-prey diet is less important than the overall diet type, with major shifts in microbiome and decrease in potentially harmful fermentation products when diet changes from extruded to mice. This urges for careful consideration of the consequences of prey-based diets for gut health in cats.

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.

Paravulvus zhongshanensis sp. nov., isolated from soil in a location at Jiangsu Province, China, is described and illustrated based on morphological, morphometric and molecular characterizations. The new species is characterized by its body 1.17–1.53 mm long, lip region offset by marked constriction and 12.1–13.8 μm broad, mural tooth deltoid and 9.6–11.7 μm long, neck 278–360 μm long, pharyngeal expansion 164–208 μm long or occupying more than one-half (54–62%) of total neck length, uterus 32.5–35.3 μm long or 1.0–1.1 times the corresponding body diameter, V = 47.8–53.4, paravulvae absent, female tail subcylindrical conoid (30.5–39.5 μm, c = 36.0–45.5, c′ = 1.7–2.2) with widely rounded end, and male unknown. The new species was compared with six known species of the genus including Paravulvus acuticaudatus, Paravulvus confusus, Paravulvus hartingii, Paravulvus iranicus, Paravulvus loofi and Paravulvus microdontus mainly by similarities in having conical tail and c′ value larger than 1.3. The rRNA and mitochondrial cytochrome oxidase subunit 1 genes of the new species were obtained and were used for reconstructing the phylogenetic relationships of the new species.

For a hypersonic-speed aircraft with a flat fuselage structure that has narrow space for a traditional wheel-type landing gear retraction, a novel type of wheel-ski landing gear is designed, which is different from traditional landing gears in force distribution and actuation methods. In order to capture the direction control performance of an aircraft with the wheel-ski landing gear, the aircraft ground taxiing nonlinear dynamic mathematical model is built based on a certain type of aircraft data. The experiment of the wheel-ski landing gear actuator and the differential brake control system is carried out to verify that the electric wheel-ski actuator model with the pressure sensor is in good agreement with the test results, indicating the model validity and the speediness of the differential brake response. Then a new fuzzy combined direction rectifying control law is designed based on the optimisation method and the fuzzy control theory. Comparing with the PD wheel-ski differential brake control, the direction rectifying efficiencies increase higher than 140% during the whole taxiing process. In addition, the combined control law can also decrease the overshoots of the yaw angle responses effectively. Finally, the stability and robustness of the designed combined direction control law are verified under various working conditions.

This paper studied the use of eye movement data to form criteria for judging whether pilots perceive emergency information such as cockpit warnings. In the experiment, 12 subjects randomly encountered different warning information while flying a simulated helicopter, and their eye movement data were collected synchronously. Firstly, the importance of the eye movement features was calculated by ANOVA (analysis of variance). According to the sorting of the importance and the Euclidean distance of each eye movement feature, the warning information samples with different eye movement features were obtained. Secondly, the residual shrinkage network modules were added to CNN (convolutional neural network) to construct a DRSN (deep residual shrinkage networks) model. Finally, the processed warning information samples were used to train and test the DRSN model. In order to verify the superiority of this method, the DRSN model was compared with three machine learning models, namely SVM (support vector machine), RF (radom forest) and BPNN (backpropagation neural network). Among the four models, the DRSN model performed the best. When all eye movement features were selected, this model detected pilot perception of warning information with an average accuracy of 90.4%, of which the highest detection accuracy reached 96.4%. Experiments showed that the DRSN model had advantages in detecting pilot perception of warning information.

As a basic flow model for engineering applications, wall-bounded turbulent flow has been widely studied in the field of aero-optics, but the flow control methods that could effectively suppress aero-optical effects are relatively rare. As an urgent requirement in engineering application, the concept of the steady wall blowing and suction is proposed by the author. Firstly, the author briefly described the flow model and physical method. Secondly, the choice of disturbance type is given. Then, the results of wall blowing-suction, suction and blowing ways based on steady and unsteady disturbance are compared. Finally, it is concluded that employing the high steady wall blowing disturbance (A = 0.2) could realise aero-optical suppression by around 20%. Besides, the steady wall suction scheme contributes to about 70%–80% reduction effect within a wide amplitude range (A = 0.2–1.0), which suppresses this effect by maintaining laminar state downstream contrasted by the baseline case.

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.