To optimize flapping foil performance, in the current study we apply deep reinforcement learning (DRL) to plan foil non-parametric motion, as the traditional control techniques and simplified motions cannot fully model nonlinear, unsteady and high-dimensional foil–vortex interactions. Therefore, a DRL training framework is proposed based on the proximal policy optimization algorithm and the transformer architecture, where the policy is initialized from the sinusoidal expert display. We first demonstrate the effectiveness of the proposed DRL-training framework, learning the coherent foil flapping motion to generate thrust. Furthermore, by adjusting reward functions and action thresholds, DRL-optimized foil trajectories can gain significant enhancement in both thrust and efficiency compared with the sinusoidal motion. Last, through visualization of wake morphology and instantaneous pressure distributions, it is found that DRL-optimized foil can adaptively adjust the phases between motion and shedding vortices to improve hydrodynamic performance. Our results give a hint of how to solve complex fluid manipulation problems using the DRL method.

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.

Although a coaxial compound helicopter can takeoff without propeller in the normal condition, the distance should be as short as possible for obstacle avoidance when the vehicle operates in a confined area with heavy loads. Therefore, a suitable propeller control is required to improve the takeoff performance while the total power consumption is no more than the available power. The path is predicted by applying trajectory optimisation. Several varying takeoff parameters, including attitude, liftoff speed and obstacle height, are considered for optimum global performance. Three path indicators are proposed. Apart from typical distance and pilot workload, path sensitivity is quantified based on deviation from takeoff parameter variation. Results indicated that low propeller thrust at hover and moderate allocation on the propeller through flight is recommended. The aircraft achieves significantly improved takeoff performance compared to flight with pure rotors while maintaining the maximum takeoff weight. The distance is shortened by 12.6%, and the longitudinal pilot workload is alleviated by 9.8% and 7.3% from mean and maximum power frequency aspects. Besides, the path is less sensitive to takeoff parameter variations, such as speed, altitude and height.

This study aimed to investigate the relationship between bone quality in terms of metabolism, homeostasis of elements, bone mineral density (BMD), and microstructure and keel-bone fractures in laying hens (Gallus gallus domesticus). One hundred and twenty 17 week old Lohmann White laying hens with normal keel bones were individually housed in furnished cages for 25 weeks. Birds were then euthanased and dissected to assess keel-bone status at 42 weeks. Serum and keel-bone samples from normal keel (NK) and fractured keel (FK) hens were collected to determine the previously mentioned bone quality parameters. The results showed FK hens to have higher levels of the components of osteocalcin, greater alkaline phosphatase activity in serum and keel bones, and greater tartrate-resistant acid phosphatase (TRAP) activity in keel bones, compared to NK hens. Additionally, FK hens also had higher concentrations of Li, B, K, Cu, As, Se, Sn, Hg, and Pb, but lower concentrations of Na, P, and Ca. Moreover, FK hens showed decreased bone microstructural parameters including bone volume/tissue volume, trabecular number, degree of anisotropy, connectivity density, and BMD, but increased trabecular separation. Meanwhile, no differences were detected in serum TRAP activity, trabecular thickness, bone surface, or bone surface/bone volume. Results showed laying hens with keel-bone fractures to have differences in bone metabolism, elements of home-ostasis, bone microstructure parameters, and BMD. These results suggest that keel-bone fractures may be associated with bone quality.

The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.

We use a continuous wavelet transform to analyse the daily hemispheric sunspot area data from the Greenwich Royal Observatory during cycles 12–24 and then study the cause of the appearance or disappearance of the Rieger-type periodicity in the northern and southern hemispheres during a certain cycle. The Rieger-type periodicity in the northern and southern hemispheres should be developed independently in the two hemispheres. This periodicity in the northern hemisphere is generally anti-correlated with the long-term variations in the mean solar cycle strength of hemispheric activity, but the correlation of the two parameters in the southern hemisphere shows a weak correlation. The appearance or disappearance of Rieger-type periodicity in the northern and southern hemispheres during a certain solar cycle is not directly correlated with their corresponding hemispheric mean activity strength but should be related to the strength of the hemispheric activity during sunspot maximum times, which hints the Rieger-type periodicity is more related to temporal evolution of toroidal magnetic field. The Rieger-type periodicity in the two hemispheres disappears in those solar cycles with relatively weak hemispheric activity during sunspot maximum times. The reason for the disappearance of this periodicity may be due to the combined influence of relatively weak toroidal magnetic fields and torsional oscillations, the differential rotation parameters vary through the solar cycle and may not remain more or less unchanged during some time, which does not permit the strong growth of magnetic Rossby waves.

The full-wing solar-powered UAV has a large aspect ratio, special configuration, and excellent aerodynamic performance. This UAV converts solar energy into electrical energy for level flight and storage to improve endurance performance. The UAV only uses a differential throttle for lateral control, and the insufficient control capability during crosswind landing results in a large lateral distance bias and leads to multiple landing failures. This paper analyzes 11 landing failures and finds that a large lateral distance bias at the beginning of the approach and the coupling of base and differential throttle control is the main reason for multiple landing failures. To improve the landing performance, a heading angle-based vector field (VF) method is applied to the straight-line and orbit paths following and two novel 3D Dubins landing paths are proposed to reduce the initial lateral control bias. The results show that the straight-line path simulation exhibits similar phenomenon with the practical failure; the single helical path has the highest lateral control accuracy; the left-arc to left-arc (L-L) path avoids the saturation of the differential throttle; and both paths effectively improve the probability of successful landing.

An acute gastroenteritis (AGE) outbreak caused by a norovirus occurred at a hospital in Shanghai, China, was studied for molecular epidemiology, host susceptibility and serological roles. Rectal and environmental swabs, paired serum samples and saliva specimens were collected. Pathogens were detected by real-time polymerase chain reaction and DNA sequencing. Histo-blood group antigens (HBGA) phenotypes of saliva samples and their binding to norovirus protruding proteins were determined by enzyme-linked immunosorbent assay. The HBGA-binding interfaces and the surrounding region were analysed by the MegAlign program of DNAstar 7.1. Twenty-seven individuals in two care units were attacked with AGE at attack rates of 9.02 and 11.68%. Eighteen (78.2%) symptomatic and five (38.4%) asymptomatic individuals were GII.6/b norovirus positive. Saliva-based HBGA phenotyping showed that all symptomatic and asymptomatic cases belonged to A, B, AB or O secretors. Only four (16.7%) out of the 24 tested serum samples showed low blockade activity against HBGA-norovirus binding at the acute phase, whereas 11 (45.8%) samples at the convalescence stage showed seroconversion of such blockade. Specific blockade antibody in the population played an essential role in this norovirus epidemic. A wide HBGA-binding spectrum of GII.6 supports a need for continuous health attention and surveillance in different settings.

Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.

To evaluate the dynamic properties of a coupled structure based on the dynamic properties of its substructures, this paper investigates the dynamic substructuring issue from the perspective of response prediction. The main idea is that the connecting forces at the interface of substructures can be expressed by the unknown coupled structural responses, and the responses can be solved rather easily. Not only rigidly coupled structures but also resiliently coupled structures are investigated. In order to further comprehend and visualize the nature of coupling problems, the Neumann series expansion for a matrix describing the relation between the coupled and uncoupled substructures is also introduced in this paper. Compared with existing response prediction methods, the proposed method does not have to measure any forces, which makes it easier to apply than the others. Clearly, the frequency response function matrix of coupled structures can be derived directly based on the response prediction method. Compared with existing frequency response function synthesis methods, it is more straightforward and comprehensible. Through demonstration of two examples, it is concluded that the proposed method can deal with structural coupling problems very well.

This study aimed to investigate the clinical characteristics and to analyse the epidemiological features of coronavirus disease 2019 (COVID-19) patients during convalescence. In this study, we enrolled 71 confirmed cases of COVID-19 who were discharged from hospital and transferred to isolation wards from 6 February to 26 March 2020. They were all employees of Zhongnan Hospital of Wuhan University or their family members of which three cases were <18 years of age. Clinical data were collected and analysed statistically. Forty-one cases (41/71, 57.7%) comprised medical faculty, young and middle-aged patients (aged ⩽60 years) accounted for 81.7% (58/71). The average isolation time period for all adult patients was 13.8 ± 6.1 days. During convalescence, RNA detection results of 35.2% patients (25/71) turned from negative to positive. The longest RNA reversed phase time was 7 days. In all, 52.9% of adult patients (36/68) had no obvious clinical symptoms, and the remaining ones had mild and non-specific clinical symptoms (e.g. cough, sputum, sore throat, disorders of the gastrointestinal tract etc.). Chest CT signs in 89.7% of adult patients (61/68) gradually improved, and in the others, the lesions were eventually absorbed and improved after short-term repeated progression. The main chest CT manifestations of adult patients were normal, GGO or fibre streak shadow, and six patients (8.8%) had extrapulmonary manifestations, but there was no significant correlation with RNA detection results (r = −0.008, P > 0.05). The drug treatment was mainly symptomatic support therapy, and antibiotics and antiviral drugs were ineffective. It is necessary to re-evaluate the isolation time and standard to terminate isolation for discharged COVID-19 patients.