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.

Ediacaran cap dolostone atop Marinoan glacial deposits contains complex sedimentary structures with extremely negative δ13Ccarb values in close association with oscillations in palaeoclimatic and oceanographic proxy records. However, the precise geological, geochronological and geochemical context of the cap dolostone is not clarified, which hampers us from correctly interpreting the extremely negative δ13Ccarb values and their causal relationships with the Snowball Earth hypothesis. In this study, we conducted detailed in situ geochronological and geochemical analyses on the calcite within the cap dolostone from the Ediacaran Doushantuo Formation in South China in order to define its formation and relationship to the Snowball Earth hypothesis. Petrographic observations show that formation of dolomite pre-dates precipitation of calcite and pyrite, which pre-dates quartz cementation in the basal cap carbonate. Calcite cement within the cap dolostone yielded a U–Pb age of 636.5 ± 7.4/17.8 Ma (2σ, MSWD = 1.6, n = 36/40), which is within uncertainty of a published dolomite U–Pb age of 632 ± 17 Ma (recalculated as 629.3 ± 16.7/22.9 Ma). These age constraints negate the possibility that the calcite cement was formed by late Ediacaran or Cambrian hydrothermal activity. The rare earth element distribution patterns suggest a dominant seawater origin overprinted by subsequent early Ediacaran hydrothermal activity. The combined age, petrographic and geochemical data suggest oxidization of methane clathrates in response to complicated interplay between eustasy and isostatic rebound and hydrothermal fluids.

Early in the COVID-19 pandemic, the World Health Organization stressed the importance of daily clinical assessments of infected patients, yet current approaches frequently consider cross-sectional timepoints, cumulative summary measures, or time-to-event analyses. Statistical methods are available that make use of the rich information content of longitudinal assessments. We demonstrate the use of a multistate transition model to assess the dynamic nature of COVID-19-associated critical illness using daily evaluations of COVID-19 patients from 9 academic hospitals. We describe the accessibility and utility of methods that consider the clinical trajectory of critically ill COVID-19 patients.

The Dayao Paleolithic site, located in Inner Mongolia on the eastern margin of China's vast northwestern drylands, was a lithic quarry-workshop utilized by Pleistocene human migrants through the region. Determining the age of this activity has previously yielded controversial results. Our magnetostratigraphic and OSL dating results suggest the two artifact-bearing paleosols are correlated with MIS 5 and 7, respectively. Correlating paleoclimatic data with marine δ18O records leads us to conclude that two sandy gravel layers containing many artifacts in the lower part of the Dayao sequence were formed during MIS 9 and 11, if not earlier. Our results reveal that the earliest human occupation at the Dayao site occurred before ca. 400 ka during a relatively warm and moist interglacial period, similar to several subsequent occupations, documenting the earliest and northernmost archaeological assemblage yet reported in China's arid northwest. We conclude that the northward and southward displacements of the East Asian summer monsoon rain belt during past interglacial-glacial cycles were responsible for the discontinuous human occupation detected at the Dayao site. The penetration of this precipitation regime into dryland ecologies via the Huanghe (Yellow River) Valley effectively created a corridor for hominin migration into China's arid northwest.

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.

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.

Coronavirus disease (COVID-19) is a “disaster of uncertainty” with ambiguity about its nature and trajectory. These features amplify its psychological toxicity and increase the number of psychological casualties it inflicts. Uncertainty was fueled by lack of knowledge about the lethality of a disaster, its duration, and ambiguity in messaging from leaders and health care authorities. Human resilience can have a buffering effect on the psychological impact. Experts have advocated “flattening the curve” to slow the spread of the infection. Our strategy for crisis leadership is focused on flattening the rise in psychological casualties by increasing resilience among health care workers. This paper describes an approach employed at Johns Hopkins to promote and enhance crisis leadership. The approach is based on 4 factors: vision for the future, decisiveness, effective communication, and following a moral compass. We make specific actionable recommendations for implementing these factors that are being disseminated to frontline leaders and managers. The COVID-19 pandemic is destined to have a strong psychological impact that extends far beyond the end of quarantine. Following these guidelines has the potential to build resilience and thus reduce the number of psychological casualties and speed the return to normal – or at least the new normal in the post-COVID world.

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.

Supported by (1) medical research grants CMRPG3C0041/42 from Chang Gung Memorial Hospital and NRRPG2H0031 from Ministry of Science and Technology, Taiwan to Chemin Lin (2) NMRPG3G6031/32 from Ministry of Science and Technology, Taiwan to Shwu-Hua, Lee (3) the KKHo International Charitable Foundation to Tatia Lee.

Residual deformation and failure are two critical issues in powder bed fusion (PBF) additive manufacturing (AM) of metal products. Residual deformation caused by the non-uniform residual stress distribution dramatically affects the quality of AM product and can result in catastrophic failure in operation. Therefore, the development of an effective numerical approach to predict residual deformation and failure characteristics of AM product is always a major concern in industrial applications.

In this paper, a numerical approach in predicting residual distortion, stress and failure in AM products is presented. The conventional inherent strain method used in welding process is modified to consider the specific characteristic of AM process, such as the influences of reheating and scanning pattern. This approach consists of three simulation steps including a detailed process simulation in small-scale, a onetime static mechanical finite element analysis in part-scale, and a material failure analysis. First, the inherent strains are calculated from a thermo-mechanical process simulation in small-scale, which considers AM process parameters, such as laser power, scanning speed and path. The physical state in deposited materials including powder, liquid and solid states are taken into account in the simulation by specifying the solidus and liquidus temperature and corresponding material properties. Then the inherent strains are applied layer by layer to the part-scale simulation, where the residual distortion and stress can be predicted efficiently. Finally, a Lagrange particle method is utilized to study the failure characteristics of AM products. Numerical examples are studied to investigate the effectiveness and applicability of present approach.

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.

A new developed spatially targeted mollusciciding technology for snail control was utilised in a research site. This study aims to analyse whether this technology can achieve rational effectiveness compared with the routine method. Snail density was monitored every spring and autumn from 2010 to 2017 at the research site and routine mollusciciding for snail control was then performed. After snail density monitoring in spring 2018, spatially targeted mollusciciding technology was adopted. Log-linear regression and nonlinear regression models were used for snail density prediction in autumn 2018 and the predicted value was compared with the actual snail density in autumn 2018 to verify the effectiveness of the spatially targeted mollusciciding. Monitoring results showed that overall snail density in the research site decreased from 2010 to 2018. The monitored snail density in autumn 2018 was 0.014/0.1 m2. Predicted by the log-linear regression model, the snail density in autumn 2018 would be 0.028 (95% CI 0.11–0.072)/0.1 m2. Predicted by the nonlinear regression model, the snail density growth in autumn 2018 in contrast to spring 2018 would be 79.79% (95% CI 54.81%–104.77%) and the actual value was 55.56%. Therefore, the effectiveness of the first application of spatially targeted mollusciciding was acceptable. However, the validation of its sustainable effectiveness still needs a replicated study comparing areas where targeted and untargeted methods are applied simultaneously and both snail abundance and human infection are monitored.

Guanidinoacetic acid (GAA) can improve the growth performance of bulls. This study investigated the influences of GAA addition on growth, nutrient digestion, ruminal fermentation and serum metabolites in bulls. Forty-eight Angus bulls were randomly allocated to experimental treatments, that is, control, low-GAA (LGAA), medium-GAA (MGAA) and high-GAA (HGAA), with GAA supplementation at 0, 0.3, 0.6 and 0.9 g/kg DM, respectively. Bulls were fed a basal diet containing 500 g/kg DM concentrate and 500 g/kg DM roughage. The experimental period was 104 days, with 14 days for adaptation and 90 days for data collection. Bulls in the MGAA and HGAA groups had higher DM intake and average daily gain than bulls in the LGAA and control groups. The feed conversion ratio was lowest in MGAA and highest in the control. Bulls receiving 0.9 g/kg DM GAA addition had higher digestibility of DM, organic matter, NDF and ADF than bulls in other groups. The digestibility of CP was higher for HGAA than for LGAA and control. The ruminal pH was lower for MGAA, and the total volatile fatty acid concentration was greater for MGAA and HGAA than for the control. The acetate proportion and acetate-to-propionate ratio were lower for MGAA than for LGAA and control. The propionate proportion was higher for MGAA than for control. Bulls receiving GAA addition showed decreased ruminal ammonia N. Bulls in MGAA and HGAA had higher cellobiase, pectinase and protease activities and Butyrivibrio fibrisolvens, Prevotella ruminicola and Ruminobacter amylophilus populations than bulls in LGAA and control. However, the total protozoan population was lower for MGAA and HGAA than for LGAA and control. The total bacterial and Ruminococcus flavefaciens populations increased with GAA addition. The blood level of creatine was higher for HGAA, and the activity of l-arginine glycine amidine transferase was lower for MGAA and HGAA, than for control. The blood activity of guanidine acetate N-methyltransferase and the level of folate decreased in the GAA addition groups. The results indicated that dietary addition of 0.6 or 0.9 g/kg DM GAA improved growth performance, nutrient digestion and ruminal fermentation in bulls.