This paper concentrates on the trajectory tracking problem for a stratospheric airship subject to underactuated dynamics, unmeasured velocities, modeling inaccuracies and environmental disturbances. First, a coordinate transformation is performed to solve the underactuated issue, which simultaneously permits a priori assignment of the tracking accuracy. Second, a finite-time observer is integrated into the control structure to offer the exact information of unmeasured velocities and uncertainties in an integral manner. Then, by combining the backstepping technique with the method of adding a power integrator, a new output-feedback control strategy is derived with several salient contributions: (1) the airship’s position errors fall into a predetermined residual region near zero within a finite settling time and stay there, while all the closed-loop signals maintain bounded during operation; and (2) no artificial neural networks and filters are adopted, resulting in a low-complexity control property. Furthermore, the presented method can be extended readily to a broad range of second-order mechanical systems as its design builds upon a transformed system model. Rigorous mathematical analysis and simulations demonstrate the above theoretical findings.

Influenza virus infections can lead to a number of secondary complications, including sepsis. We applied linear regression models to mortality and hospital admission data coded for septicaemia from 1998 to 2019 in Hong Kong, and estimated that septicaemia was associated with an annual average excess mortality rate of 0.23 (95% CI 0.04–0.40) per 100 000 persons per year and an excess septicaemia hospitalisation rate of 1.73 (95% CI 0.94–2.50) per 100 000 persons per year. The highest excess morbidity and mortality was found in older adults and young children, and during influenza A(H3N2) epidemics.

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.

For a common micro-satellite, orbiting in a circular sun-synchronous orbit (SSO) at an altitude between 500 and 600km, the satellite attitude during off-nadir imaging and staring-imaging operations can be up to ±45 degree on roll and pitch angles. During these off-nadir pointing for both multi-trip operation and staring imaging operations, the spacecraft body is commonly subject to high-rate motion. This posts challenges for a spacecraft attitude determination subsystem called Gyro Stellar Inertial Attitude Estimate (GS IAE), which employs gyros and star sensors to maintain the required attitude knowledge, since star trackers will severely degrade attitude estimation accuracies when the spacecraft is subject to high-rate motion. This paper analyses the star motion-induced errors for a typical star tracker, models the star motion-induced errors to assess the performance impact on the attitude estimation accuracy, and investigates the adaptive extended Kalman filter design in the GS IAE while evaluating its effectiveness.

Ice breaking has become one of the main problems faced by ships and other equipment operating in an ice-covered water region. New methods are always being pursued and studied to improve ice-breaking capabilities and efficiencies. Based on the strong damage capability, a high-speed water jet impact is proposed to be used to break an ice plate in contact with water. A series of experiments of water jet impacting ice were performed in a transparent water tank, where the water jets at tens of metres per second were generated by a home-made device and circular ice plates of various thicknesses and scales were produced in a cold room. The entire evolution of the water jet and ice was recorded by two high-speed cameras from the top and front views simultaneously. The focus was the responses of the ice plate, such as crack development and breakup, under the high-speed water jet loads, which involved compressible pressure ${P_1}$ and incompressible pressure ${P_2}$. According to the main cause and crack development sequence, it was found that the damage of the ice could be roughly divided into five patterns. On this basis, the effects of water jet strength, ice thickness, ice plate size and boundary conditions were also investigated. Experiments validated the ice-breaking capability of the high-speed water jet, which could be a new auxiliary ice-breaking method in the future.

We report on experimental observation of non-laminar proton acceleration modulated by a strong magnetic field in laser irradiating micrometer aluminum targets. The results illustrate the coexistence of ring-like and filamentation structures. We implement the knife edge method into the radiochromic film detector to map the accelerated beams, measuring a source size of 30–110 μm for protons of more than 5 MeV. The diagnosis reveals that the ring-like profile originates from low-energy protons far off the axis whereas the filamentation is from the near-axis high-energy protons, exhibiting non-laminar features. Particle-in-cell simulations reproduced the experimental results, showing that the short-term magnetic turbulence via Weibel instability and the long-term quasi-static annular magnetic field by the streaming electric current account for the measured beam profile. Our work provides direct mapping of laser-driven proton sources in the space-energy domain and reveals the non-laminar beam evolution at featured time scales.

In this paper, a pulsed spark discharge plasma actuator array is deployed to control laminar–turbulent transition in a Mach 3.0 flat-plate boundary layer, and the subtle flow structures are visualized by nanoparticle planar laser scattering (NPLS) technique. Results show that the onset location of turbulence can be brought upstream by plasma actuation, corresponding to forced boundary-layer transition. Hairpin vortex packets evolved from the thermal bulbs play a vital role in the breakdown of laminar flow. With the help of a machine learning tool, all the relevant structures induced by plasma actuation are extracted from NPLS images, and a conceptual model of the hairpin vortex generation is proposed, including three stages: production and lift-up of the high-vorticity region, formation of the $\varLambda$ vortex and evolution of the hairpin vortex.

To investigate the influences of dietary riboflavin (RF) addition on nutrient digestion and rumen fermentation, eight rumen cannulated Holstein bulls were randomly allocated into four treatments in a repeated 4 × 4 Latin square design. Daily addition level of RF for each bull in control, low RF, medium RF and high RF was 0, 300, 600 and 900 mg, respectively. Increasing the addition level of RF, DM intake was not affected, average daily gain tended to be increased linearly and feed conversion ratio decreased linearly. Total tract digestibilities of DM, organic matter, crude protein (CP) and neutral-detergent fibre (NDF) increased linearly. Rumen pH decreased quadratically, and total volatile fatty acids (VFA) increased quadratically. Acetate molar percentage and acetate:propionate ratio increased linearly, but propionate molar percentage and ammonia-N content decreased linearly. Rumen effective degradability of DM increased linearly, NDF increased quadratically but CP was unaltered. Activity of cellulase and populations of total bacteria, protozoa, fungi, dominant cellulolytic bacteria, Prevotella ruminicola and Ruminobacter amylophilus increased linearly. Linear increase was observed for urinary total purine derivatives excretion. The data suggested that dietary RF addition was essential for rumen microbial growth, and no further increase in performance and rumen total VFA concentration was observed when increasing RF level from 600 to 900 mg/d in dairy bulls.

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 impacts of guanidinoacetic acid (GAA) and coated folic acid (CFA) on growth performance, nutrient digestion and hepatic gene expression, fifty-two Angus bulls were assigned to four groups in a 2 × 2 factor experimental design. The CFA of 0 or 6 mg/kg dietary DM folic acid was supplemented in diets with GAA of 0 (GAA−) or 0·6 g/kg DM (GAA+), respectively. Average daily gain (ADG), feed efficiency and hepatic creatine concentration increased with GAA or CFA addition, and the increased magnitude of these parameters was greater for addition of CFA in GAA− diets than in GAA+ diets. Blood creatine concentration increased with GAA or CFA addition, and greater increase was observed when CFA was supplemented in GAA+ diets than in GAA− diets. DM intake was unchanged, but rumen total SCFA concentration and digestibilities of DM, crude protein, neutral-detergent fibre and acid-detergent fibre increased with the addition of GAA or CFA. Acetate:propionate ratio was unaffected by GAA, but increased for CFA addition. Increase in blood concentrations of albumin, total protein and insulin-like growth factor-1 (IGF-1) was observed for GAA or CFA addition. Blood folate concentration was decreased by GAA, but increased with CFA addition. Hepatic expressions of IGF-1, phosphoinositide 3-kinase, protein kinase B, mammalian target of rapamycin and ribosomal protein S6 kinase increased with GAA or CFA addition. Results indicated that the combined supplementation of GAA and CFA could not cause ADG increase more when compared with GAA or CFA addition alone.

Multi-dimensional aerodynamic database technology is widely used, but its model often has the curse of dimensionality. In order to solve this problem, we need projection to reduce the dimension. In addition, due to the lack of traditional method, we have improved the traditional flow field reconstruction method based on artificial neural networks, and we proposed an array neural network method.

In this paper, a set of flow field data for the target problem of the fixed Mach number is obtained by the existing CFD method. Then we arrange all the sampled flow field data into a matrix and use proper orthogonal decomposition (POD) to reduce the dimension, whose size is determined by the first few modals of energy. Therefore, significantly reduced data are obtained. Then we use an arrayed neural network to map the flow field data of simplified target problem and the flow field characteristics. Finally, the unknown flow field data can be effectively predicted through the flow field characteristic and the trained array neural network.

At the end of this paper, the effectiveness of the method is verified by airfoil flow fields. The calculation results show that the array neural network can reconstruct the flow field of the target problem more accurately than the traditional method, and its convergence speed is significantly faster. In addition, for the case of high angle flow field, the array neural network also performs well. There are no obvious jumps, and huge errors are found in results. In general, the proposed method is better than the traditional method.

Coated copper sulphate (CCS) could be used as a Cu supplement in cows. To investigate the influences of copper sulphate (CS) and CCS on milk performance, nutrient digestion and rumen fermentation, fifty Holstein dairy cows were arranged in a randomised block design to five groups: control, CS addition (7·5 mg Cu/kg DM from CS) or CCS addition (5, 7·5 and 10 mg Cu/kg DM from CCS, respectively). When comparing Cu source at equal inclusion rates (7·5 mg/kg DM), cows receiving CCS addition had higher yields of fat-corrected milk, milk fat and protein; digestibility of DM, organic matter (OM) and neutral-detergent fibre (NDF); ruminal total volatile fatty acid (VFA) concentration; activities of carboxymethyl cellulase, cellobiase, pectinase and α-amylase; populations of Ruminococcus albus, Ruminococcus flavefaciens and Fibrobacter succinogenes; and liver Cu content than cows receiving CS addition. Increasing CCS addition, DM intake was unchanged, yields of milk, milk fat and protein; feed efficiency; digestibility of DM, OM, NDF and acid-detergent fibre; ruminal total VFA concentration; acetate:propionate ratio; activity of cellulolytic enzyme; populations of total bacteria, protozoa and dominant cellulolytic bacteria; and concentrations of Cu in serum and liver increased linearly, but ruminal propionate percentage, ammonia-N concentration, α-amylase activity and populations of Prevotella ruminicola and Ruminobacter amylophilus decreased linearly. The results indicated that supplement of CS could be substituted with CCS and addition of CCS improved milk performance and nutrient digestion in dairy cows.

In this article, we investigate the horizontal trajectory tracking problem for an underactuated stratospheric airship subject to nonvanishing external disturbances and model uncertainties. By transforming the tracking errors into new virtual error variables, we can specify the transient and steady-state tracking performance of the resulting nonlinear system quantitatively, which means that under the proposed control scheme, the tracking errors will converge to prescribed residual sets around the origin before a preselected finite time with decay rates no less than a preassignable value. To address unknown items, minimal learning parameter (MLP) techniques for neural networks (NNs) approximation are employed, which efficaciously relax the computational burden, enhance the robustness against dynamics uncertainties and provide an improved property for disturbances rejection. A finite-time convergent observer (FTCO) is incorporated into the control framework to realise output-feedback control, ensuring that estimation errors are bounded during operation and approach zero within a finite time. Stability analysis proves that all the closed-loop signals are uniformly bounded. The effectiveness and advantages of the proposed control strategy are verified by simulation results.