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Interval process is a preferable model for time-varying uncertainty propagation of dynamic systems when only the range of uncertainties can be obtained. However, for nonlinear systems, except Monte Carlo (MC) simulation, there are still few efficient uncertainty propagation methods under the interval process model. This paper develops a non-intrusive and semi-analytical uncertainty propagation method, named ‘Convex Model Linearization Method (CMLM)’, by constructing a linearization formulation of a nonlinear system in a non-probabilistic sense. First, the criterion to evaluate the difference between the original system and the linearization formulation is derived, represented by discrepancy of middle-point, radius, and correlations of response. By minimizing these three parameters, the coefficients of linear equations will be optimized to obtain the linearization formulation of the original system. Then, the analytical equations are built to calculate uncertainty response under the interval process, without time-consuming analysis of the original system. To further improve the efficiency of the linearization process, Chebyshev-polynomial is introduced to approximate the nonlinear dynamic analysis. Two numerical examples that duffing oscillator and vehicle ride are set to tested the proposed CMLM. Compared to MC method, with comparable uncertainty response precision, the CMLM just need 1%-10% times of dynamic analysis of the nonlinear system. Furthermore, a practical launch vehicle ascent trajectory problem with black-box dynamics is solved by, respectively, the CMLM and MC method. The results verify the capacity of the CMLM to deal with black-box problems and show that the CMLM performs better in terms of accuracy, efficiency and robustness.

Morphing aircraft can flexibly change its aerodynamic shape to adapt to the varying flight conditions during a flight. Compared with the traditional fixed shape aircraft, it has a very obvious advantage. This paper proposed a solution flow based on the multi-fidelity model for the morphing aircraft with morphing wings, and the optimal trajectory and morphing rules are studied. The angle of attack, Mach number, sweep angle and axial position of the morphing wing are defined as variables for generating training data for building the multi-fidelity Kriging model, which is used to predict the aerodynamic performance of the aircraft. Based on the hp-adaptive pseudospectral method, the model is used as aerodynamic input to establish the optimization process of morphing rules, and the trajectory optimization is carried out for the contrast fixed wing aircraft and morphing aircraft with the goal of minimum fuel consumption, respectively. The control parameters such as morphing parameters, angle of attack and engine control parameters are optimized simultaneously while meeting the flight mission requirements. The results show that the morphing aircraft has higher climbing and descending efficiency, and the optimal trajectory has obvious advantages. Moreover, the research flow proposed in this paper is universal, which can effectively reduce the CFD calculation cost and improve the efficiency of trajectory optimization of the variable shape vehicle.

It is computationally expensive to perform a large number of flow analysis by using high-fidelity CFD simulation. The paper proposes a fast flow-analysis method based on the proper orthogonal decomposition(POD) and back propagation based neural network(BPNN). First samples are generated in the geometric parameter space. Then a POD model is built to map the high-dimensional flow-field data to low-dimensional base modal coefficients, and further a BPNN model is fitted from geometric parameters to base modal coefficients to achieve fast flow prediction. During constructing the POD and BPNN model, the partitioning strategy and K-means clustering are implemented to improve modeling efficiency, as well as to reduce model training time. The results of predicting the steady flow of variable geometries show that: at subsonic, the trained model possesses good accuracy, especially in predicting the pressure isolines of the flow field and the pressure coefficient distribution of the airfoil. The average prediction errors of the lift and drag coefficient are smaller than 0.4%, while they are smaller than 1.4% at transonic. The shock location can be well predicted as well.

Time-variant reliability-based design optimization (tRBDO) can rationally consider the time-variant uncertainties in engineering structures and find the optimal design that can keep reliable throughout its whole life cycle. However, solving the tRBDO involves a nested double-loop procedure and requires excessive computational cost. In this paper, a novel decoupled method called sequential approximate time-variant reliability analysis and optimization (SATO) is proposed to improve the efficiency of tRBDO. First, a two-step method is proposed to transform the original tRBDO problem into an equivalent deterministic optimization problem according to the results of time-variant reliability analysis (TRA). Second, a novel approximate TRA (ATRA) method based the least-square method is proposed to reduce the computational cost of TRA. Finally, the proposed SATO method decouples the original double-loop procedure in tRBDO into a sequential process of ATRA and deterministic optimization. Test results of a complicated welded beam problem verify that the proposed method can achieve similar accuracy and much higher efficiency than the compared methods. A rocket inter-stage structure problem demonstrates the capability of the proposed method in practical engineering applications.

The theory of street-level bureaucracy and its relevant data have proven the expected duties of the frontline staff of local government may be excessive but their time spent working remains quite low. Using data from participatory observations of street-level officials in a Chinese city, this study reveals the logic of this labour input paradox. Organizational climate incentive and promotional incentive jointly influence the time allocation of street-level bureaucrats. The organizational climate incentive reflects the weak incentive characteristic of the maintenance function of labour; promotional incentives have a strong impact on motivation, which is characteristic of the promotional function of labour. These findings reveal the costs of the New Public Management movement in an organization lacking an effective promotion mechanism and a positive organizational climate incentive. This is a snapshot of the dilemma faced by China’s public organization reforms, but it is also a problem other country must solve.

To evaluate the efficacy and mechanistic bases of the intravenous injection of arsenic trioxide at clinical-relevant doses for treating an imiquimod-induced psoriasis-like mouse model.After inducing psoriasis-like skin lesions on the back of mice with imiquimod, mice in each group were injected with a clinical dose of arsenic trioxide through the tail vein. The changes in the gene expression, protein expression and distribution of relevant inflammatory factors were evaluated in the inflicted skin area, for mechanisms underlying the efficacy of intravenous AsClinical dose of AsClinical dosage of As

Efficient aerodynamic design optimization method is of great value for improving the aerodynamic performance of little UAV's airfoil. Using engineering or semi-engineering estimation method to analyze aerodynamic forces in solving aerodynamic optimization problems costs little computational time, but the accuracy cannot be guaranteed. However, CFD method ensuring high accuracy needs much more computational cost, which is unfordable for optimization. Surrogate-based optimization can reduce the number of high-fidelity analyses to increase the optimization efficiency. However, the cost of CFD analyses is still huge for aerodynamic optimization due to multiple design variables, multi-optimal and strong nonlinearities. To solve this problem, a two-stage aerodynamic optimization method based on early termination of CFD convergence and variable-fidelity model is proposed. In the first optimization stage, the solutions by early termination CFD convergence and the convergenced CFD solutions are regarded as low-and high-fidelity data respectively for building variable-fidelity model. Then, the multi-island genetic algorithm is used in the global optimization based on the built variable-fidelity model. The modeling efficiency can be greatly improved due to many cheap low-fidelity data. In the second stage optimization, the global optimum from the first optimization stage is treated as the start of the Hooke-Jeeves algorithm to search locally based on convergenced CFD computations in order to acquire better-optimum. The proposed method is utilized in optimizing the aerodynamic performance of the airfoil of little UAV, and is compared with the EGO method based on single-fidelity Kriging surrogate model. The results show that the present two-level aerodynamic optimization method consumes less time.

Aeromonas dhakensis is an important ubiquitous Gram-negative and freshwater bacterium detected in different reservoirs. It can cause invasive diseases in humans. Herein, we report the first case in Mainland China of a fulminant death of a 29-year-old man as a result of a new, unexpected association between septicemic A. dhakensis and hepatitis B viral infection (HBV). Herein, the patient died from multiple organ failure 5 d postadmission after the ingestion of Snakehead Fish meal. The isolated bacterium was initially misidentified as Aeromonas hydrophila using VITEK-2, while whole-genome sequencing (WGS) revealed that the isolate is A. dhakensis. WGS revealed the occurrence of three antimicrobial genes of resistance: imiH, cphA2, and blaOXA-12; besides, major virulence factors were detected. In silico, multilocus sequence typing (MLST) showed that our A. dhakensis 17FW001 belonged to a novel sequence type (ST557). A comparative genomic analysis of our isolate with nine selected Aeromonas species was done, which elucidated the pathogenicity of our A. dhakensis. In conclusion, we reported for the first time the association between A. dhakensis and HBV in Mainland China. We revealed that septicemic A. dhakensis could result in severe adverse clinical outcomes that end up with unexpected fulminant death especially when it is accompanied with HBV and sheds light on the virulence of A. dhakensis and the high rate of its misdiagnosis that requires to urgently consider screening of all cases of A. dhakensis for HBV in the future. Besides, caution should be taken while dealing with snakeheads which act as a vector for A. dhakensis.

Since the launch of the double world-class (DWC) project in 2015, China has entered into a new stage of building world-class universities. What makes China give up the existing projects for a new one? Towards the end of its first five-year cycle, has the version 2.0 of building world-class universities in China achieved the desired results? This study tries to answer these questions by giving an explanation about the relevant policies and an overview of changes brought by the DWC project. Based on the data and documents released by the Chinese government, selected universities and some international organizations as well as an extensive literature review, we find that this new project has been functioning effectively and has achieved remarkable preliminary success. However, there still remain problems such as vicious competition among institutions and unhealthy academic utilitarianism due to the heavy competitive pressure. Meanwhile, the project takes a selective concentration approach that sacrifices the majority to benefit the minority, which may exacerbate the already imbalanced development of China’s higher education system and hinder its overall development in the long run.

Introduction: We analyzed the clinical characteristics of COVID-19 fecal/perianal swab nucleic acid-positive patients in our hospital and evaluated the effect of SARS-CoV-2 on the gastrointestinal tract. Methodology: Ninety-seven patients in the Fifth Affiliated Hospital of Sun Yat-sen University from January 17, 2020 to March 2, 2020 with fecal/perianal swab samples were selected as subjects and the results of real-time fluorescence reverse transcriptase-PCR SARS-CoV-2 nucleic acid detection of fecal/perianal swabs were used to divide subjects into positive and negative groups. Results: Fecal/perianal swabs of 53.61% (52/97) patients were positive including 31 males (59.62%) and 21 females (40.38%). The negative group had more females than males (P = 0.001). The distribution of case classification based on the most severe condition observed after admission was different between groups: five (5.15%) critical type patients were all from the positive group (P = 0.029). There was no statistical difference in clinical manifestations between the groups. In the positive group, the mean nucleic acid-negative conversion time was 14.13 ± 8.61 days, which was significantly later than the negative group (6.98 ± 5.16 days; P < 0.001). In the positive group, 92% (48/52) had nucleic acid-negative conversion with a mean nucleic acid-negative conversion time of 22.58 ± 10.30 days. Among them, 41 (78.85%) cases were delayed compared with pharynx/nasal swab nucleic acid-negative conversion time. Conclusions: The positive rate of fecal/perianal swab nucleic acid in male patients was higher than that in female patients. Fecal/perianal swab nucleic acid positive may be an indicator of critical conditions in those with COVID-19.

Time-variant reliability analysis (TRA) is widely utilized to assess the performance of engineering structures under various time-variant uncertainties. Recently, the time discretization-based TRA (TDTRA) methods have been developed, which can achieve satisfactory accuracy but need to excessively perform most probable point (MPP) searches at many equidistant time instants. To improve the efficiency of TDTRA, this paper proposes a TRA method based on approximating the MPP trajectory, referred to as AMPPT. First, this paper introduces a new concept of the MPP trajectory (MPPT), which is defined as the moving path of the MPP in the U-space when time changes. Then, a one-dimensional Kriging model is constructed to approximate the MPPT by the adaptive sampling method, which only performs MPP searches at several critical time instants. To further improve the computational efficiency, a warm-starting strategy is proposed to accelerate the MPP search. Then, the approximated MPPT is employed to transform the time-variant response into an equivalent Gaussian process. Finally, the spectral decomposition method and Monte Carlo simulation are used to compute the time-variant reliability. Comparative studies on four numerical examples and one practical engineering example of the solid rocket engine shell verify that the proposed AMPPT outperforms TDTRA in terms of both accuracy and efficiency. Test results also indicate that the efficiency gain of the proposed AMPPT comes from not only the reduction in the number of MPP searches but also the acceleration of the MPP search itself.

Background A cluster of pneumonia cases were reported by Wuhan Municipal Health Commission, China in December 2019. A novel coronavirus was eventually identified, and became the COVID-19 epidemic that affected public health and life. We investigated the psychological status and behavior changes of the general public in China from January 30 to February 3, 2020. Methods Respondents were recruited via social media (WeChat) and completed an online questionnaire. We used the State-Trait Anxiety Inventory, Self-rating Depression Scale, and Symptom Checklist-90 to evaluate psychological status. We also investigated respondents’ behavior changes. Quantitative data were analyzed by t-tests or analysis of variance, and classified data were analyzed with chi-square tests. Results In total, 608 valid questionnaires were obtained. More respondents had state anxiety than trait anxiety (15.8% vs 4.0%). Depression was found among 27.1% of respondents and 7.7% had psychological abnormalities. About 10.1% of respondents suffered from phobia. Our analysis of the relationship between subgroup characteristics and psychological status showed that age, gender, knowledge about COVID-19, degree of worry about epidemiological infection, and confidence about overcoming the outbreak significantly influenced psychological status. Around 93.3% of respondents avoided going to public places and almost all respondents reduced Spring Festival-related activities. At least 70.9% of respondents chose to take three or more preventive measures to avoid infection. The three most commonly used prevention measures were making fewer trips outside and avoiding contact (98.0%), wearing a mask (83.7%), and hand hygiene (82.4%). Conclusions We need to pay more attention to public psychological stress, especially among young people, as they are likely to experience anxiety, depression, and psychological abnormalities. Different psychological interventions could be formulated according to the psychological characteristics of different gender and age groups. The majority of respondents followed specific behaviors required by the authorities, but it will take time to observe the effects of these behaviors on the epidemic.

Reduced-order models such as dynamic mode decomposition (DMD) and proper orthogonal decomposition (POD) have been extensively utilized to model unsteady flow. Although the major flow patterns can be captured by DMD and POD, due to the linear assumption, the modeling accuracy is low for complex and strongly nonlinear flow structures such as shock wave and vortex. To improve the accuracy and robustness of predicting unsteady flow, this work proposes a novel modeling method based on a hybrid reduced-order model. Since the flow can be regarded as a fusion of the main flow and the residual flow from a modeling perspective, the hybrid reduced-order model is constructed by DMD and POD, which are, respectively, used to obtain different flow properties. First, DMD is applied in describing the main flow, which contains the dominant modes determining most properties of the flow. Then, POD combining the long short-term memory is conceived to model the residual flow that the DMD cannot capture, to further enhance the modeling accuracy. The proposed method is validated by modeling two unsteady flows, which are the flow past a two-dimensional circular cylinder at Reynolds number 100 and the forced oscillation of an airfoil at transonic speed. The results indicate that the proposed method with proper modeling efficiency gains better accuracy and robustness than the existing methods. In particular, this approach has better forecasting accuracy of shock wave and vortex.

Data-driven multi-objective evolutionary algorithm provides an effective way to solve multi-objective optimization problems with computationally expensive black-box functions. In this paper, a data-driven multi-objective evolutionary algorithm based on combinatorial parallel infilling (DDMOEA-CPI) is proposed. The DDMOEA-CPI uses the Kriging model in lieu of the real function, and combines the infilling criteria based on the multi-objective lower confidence bound (MLCB), as well as the maximum Kriging error of the Pareto front, in order to guide the population evolution to quickly obtain the accurate Pareto solutions. Within the criteria, the hyper volume improvement function is used to select new samples from the solutions of the MLCB. A set of benchmark tests in 20 dimensions are taken to validate and evaluate the performance of the DDMOEA-CPI. The results show that the proposed method behaves well in the convergence and diversity of Pareto solutions.

The Radial Basis Function (RBF) network is one of the most widely used surrogate models in multidisciplinary design optimization. However, one of the challenges of applying the RBF network to engineering problems is how to efficiently optimize its width parameters. In this work, a novel space division–based width optimization (SDWO) method is proposed to decompose the complex multivariable width optimization into several small-scale single-variable width optimizations. The SDWO method consists of two main steps. First, a two-stage fuzzy clustering algorithm is carried out to group the samples and divide the input space into several overlapping local regions, and the overlapping degree is controlled by a dimensionless expansion factor. Second, in each local region, one small-scale local RBF network (LRBFN) is constructed by solving a single-variable optimization problem when the LRBFN is needed for prediction. All these LRBFNs are independent of each other and can be constructed in parallel. The proposed method is efficient and particularly suitable for large sample sets. Test results of four sample sets verify that the proposed SDWO method has better performance than the conventional width optimization method in terms of both training efficiency and approximation accuracy. An inter-stage structure optimization is carried out, which demonstrates the efficiency of the proposed method in practical engineering applications.

Surrogate-Based Optimization (SBO) is becoming increasingly popular since it can remarkably reduce the computational cost for design optimizations based on high-fidelity and expensive numerical analyses. However, for complicated optimization problems with a large design space, many design variables, and strong nonlinearity, SBO converges slowly and shows imperfection in local exploitation. This paper proposes a trust region method within the framework of an SBO process based on the Kriging model. In each refinement cycle, new samples are selected by a certain design of experiment method within a variable design space, which is sequentially updated by the trust region method. A multi-dimensional trust-region radius is proposed to improve the adaptability of the developed methodology. Further, the scale factor and the limit factor of the trust region are studied to evaluate their effects on the optimization process. Thereafter, different SBO methods using error-based exploration, prediction-based exploitation, refinement based on the expected improvement function, a hybrid refinement strategy, and the developed trust-region-based refinement are utilized in four analytical tests. Further, the developed optimization methodology is employed in the drag minimization of an RAE2822 airfoil. Results indicate that it has better robustness and local exploitation capability in comparison with those of other SBO methods. Keywords: Airfoil, Design optimization, Kriging model, Surrogate-based optimization, Trust-region method

This study numerically investigates the effects of plate vibration and deformation on the combustion performance, the shock wave structure, the mixing characteristics and the flame structure for transverse hydrogen injection. The finite-rate method is used to simulate combustion. Results show that plate vibration causes the combustion performance to oscillate both temporally and spatially, while plate deformation can only change the static characteristics of the flow. Plate vibration and deformation increase the intensity and number of shock wave reflections in different ways. In addition, both plate vibration and deformation increase the momentum flux ratio and the jet penetration depth, which enhances mixing. Finally, plate vibration widens the flame and moves it upward to a greater extent than plate deformation.

Mucosal associated invariant T (MAIT) cells play a critical role in Helicobacter pylori (H. pylori)-induced gastritis by promoting mucosal inflammation and aggravating mucosal injuries (1, 2). However, the underlying mechanism and key molecules involved are still uncertain. Here we identified OX40, a co-stimulatory molecule mainly expressed on T cells, as a critical regulator to promote proliferation and IL-9 production by MAIT cells and facilitate mucosal inflammation in H. pylori-positive gastritis patients. Serum examination revealed an increased level of IL-9 in gastritis patients. Meanwhile, OX40 expression was increased in mucosal MAIT cells, and its ligand OX40L was also up-regulated in mucosal dendritic cells (DCs) of gastritis patients, compared with healthy controls. Further results demonstrated that activation of the OX40/OX40L pathway promoted IL-9 production by MAIT cells, and MAIT cells displayed a highly-activated phenotype after the cross-linking of OX40 and OX40L. Moreover, the level of IL-9 produced by MAIT cells was positively correlated with inflammatory indexes in the gastric mucosa, suggesting the potential role of IL-9-producing MAIT cells in mucosal inflammation. Taken together, we elucidated that OX40/OX40L axis promoted mucosal MAIT cell proliferation and IL-9 production in H. pylori-induced gastritis, which may provide potential targeting strategies for gastritis treatment.

Pelvic floor dysfunction has caused pain to the lives of the majority of female patients, and repeated visits to the hospital for treatment have also caused inconvenience to patients. Therefore, a portable pelvic floor dysfunction rehabilitation training system is designed to help female patients with personalized and private treatment. The pelvic floor dysfunction rehabilitation system realizes the independent training mode selection through the APP client, assists the pelvic floor muscle rehabilitation training through the electrical stimulation module, and can realize the recovery situation of the pelvic floor muscle strength in real time through the AD acquisition module. The experimental results show that the pelvic floor dysfunction rehabilitation training system implements bipolar electrical stimulation pulses, and the EMG signals collected at the same time clearly show the EMG signal strength and strength maintenance time.

Q fever is a worldwide zoonosis caused by Coxiella burnetii (Cb). From January 2018 to November 2019, plasma samples from 2,382 patients with acute fever of unknown cause at a hospital in Zhuhai city of China were tested using metagenomic next-generation sequencing (mNGS). Of those tested, 138 patients (5.8%) were diagnosed with Q fever based on the presence of Cb genomic DNA detected by mNGS. Among these, 78 cases (56.5%) presented from Nov 2018 to Mar 2019, suggesting an outbreak of Q fever. 55 cases with detailed clinical information that occurred during the outbreak period were used for further analysis. The vast majority of plasma samples from those Cb-mNGS-positive patients were positive in a Cb-specific quantitative polymerase chain reaction (n = 38) and/or indirect immunofluorescence assay (n = 26). Mobile phone tracing data was used to define the area of infection during the outbreak. This suggested the probable infection source was Cb-infected goats and cattle at the only official authorized slaughterhouse in Zhuhai city. Phylogenic analysis based on genomic sequences indicated Cb strains identified in the patients, goat and cattle were formed a single branch, most closely related to the genomic group of Cb dominated by strains isolated from goats. Our study demonstrates Q fever was epidemic in 2018–2019 in Zhuhai city, and this is the first confirmed epidemic of Q fever in a contemporary city in China., Author summary Generally, the clinical diagnosis of acute Q fever, which is caused by Coxiella burnetii, is based on serologic methods that detect the presence antibodies produced by the body to fight the infection. However, the lag time between becoming infected and production of antibodies limits early diagnosis using this method. Here, we confirmed an epidemic of human Q fever in Zhuhai, a contemporary city in China, using clinical metagenomic next-generation sequencing (mNGS) and cell phone location data. Our results indicate that Cb-infected goats and cattle at the only official authorized slaughterhouse in Zhuhai were the likely infection source for the Q fever epidemic. More importantly, we demonstrate that mNGS is a useful tool for rapid and effective public health responses to acute bacterial infections.

In engineering design, the performance of the system and the budget of design uncertainty should be balanced, which means that it is best to optimize design variables and allocate the manufacturing uncertainty simultaneously. This work formulates this problem as an uncertainty optimization problem, where the input uncertainty is modeled by the probability method and both the design variables and the uncertainty magnitude are included in the optimization variables. A sequence optimization framework is proposed to solve the optimization problem. The Taylor-based first-order method is used to translate the probability constraint into a deterministic constraint. A correction coefficient is calculated by the dimensional adaptive polynomial chaos expansion method to improve the accuracy of the uncertainty analysis. The constraint translation and the correction coefficient calculation are executed sequentially. The accuracy and effectiveness of the proposed framework are validated by three benchmark problems, including a mathematical problem, a cantilever I-beam, and a ten-bar truss case.

CD103 is considered as a surface marker for the resident immune cells. However, little is known about the intrinsic function of CD103 in infection and inflammation. In this study, we found that CD103 was highly expressed in CD4+T cells of the gastric mucosa from patients with H. pylori-positive gastritis. Mucosal resident CD103+CD4+T cells exhibited an increase in the CD45RO+CCR7− effector memory phenotype and high expression of the chemokine receptors CXCR3 and CCR9 compared with those in CD103−CD4+T cells. An In vitro coculture study demonstrated that H. pylori-specific antigen CagA/VacA-primed dendritic cells (DCs) induced proliferation and IFN-γ, TNF as well as IL-17 production by CD103+CD4+T cells from patients with H. pylori-positive gastritis, while blocking CD103 with a neutralizing antibody reduced proliferation and IFN-γ, TNF, and IL-17 production by CD103+CD4+T cells cocultured with DCs. Moreover, immunoprecipitation revealed that CD103 interacted with TCR α/β and CD3ζ, and activation of CD103 enhanced the phosphorylation of ZAP70 induced by the TCR signal. Finally, increased T-bet and Blimp1 levels were also observed in CD103+CD4+T cells, and activating CD103 increased T-bet and Blimp1 expression in CD4+T cells. Our results explored the intrinsic function of CD103 in gastric T cells from patients with H. pylori-positive gastritis, which may provide a therapeutic target for the treatment of gastritis.

Corona Virus Disease 2019 (COVID-19) due to the 2019 novel coronavirus (SARS-CoV-2) emerged in Wuhan city and rapidly spread throughout China. We aimed to compare arbidol and lopinavir/ritonavir(LPV/r) treatment for patients with COVID-19 with LPV/r only.In this retrospective cohort study, we included adults (age≥18years) with laboratory-confirmed COVID-19 without Invasive ventilation, diagnosed between Jan 17, 2020, and Feb 13, 2020. Patients, diagnosed after Jan 17, 2020, were given oral arbidol and LPV/r in the combination group and oral LPV/r only in the monotherapy group for 5-21 days. The primary endpoint was a negative conversion rate of coronavirus from the date of COVID-19 diagnosis(day7, day14), and assessed whether the pneumonia was progressing or improving by chest CT (day7).We analyzed 16 patients who received oral arbidol and LPV/r in the combination group and 17 who oral LPV/r only in the monotherapy group, and both initiated after diagnosis. Baseline clinical, laboratory, and chest CT characteristics were similar between groups. The SARS-CoV-2 could not be detected for 12(75%) of 16 patients' nasopharyngeal specimens in the combination group after seven days, compared with 6 (35%) of 17 in the monotherapy group (p0·05). After 14 days, 15 (94%) of 16 and 9 (52·9%) of 17, respectively, SARS-CoV-2 could not be detected (p0·05). The chest CT scans were improving for 11(69%) of 16 patients in the combination group after seven days, compared with 5(29%) of 17 in the monotherapy group (p0·05).In patients with COVID-19, the apparent favorable clinical response with arbidol and LPV/r supports further LPV/r only.

Morphing aircraft can meet requirements of multi-mission during the whole flight due to changing the aerodynamic shape, so it is necessary to study its morphing rules along the trajectory. However, trajectory planning considering morphing variables requires a huge number of expensive CFD computations due to the morphing in view of aerodynamic performance. Under the given missions and trajectory, to alleviate computational cost and improve trajectory-planning efficiency for morphing aircraft, an offline optimization method is proposed based on Multi-Fidelity Kriging (MFK) modeling. The angle of attack, Mach number, sweep angle and axial position of the morphing wing are defined as variables for generating training data for building the MFK models, in which many inviscid aerodynamic solutions are used as low-fidelity data, while the less high-fidelity data are obtained by solving viscous flow. Then the built MFK models of the lift, drag and pressure centre at the different angles of attack and Mach numbers are used to predict the aerodynamic performance of the morphing aircraft, which keeps the optimal sweep angle and axial position of the wing during trajectory planning. Hence, the morphing rules can be correspondingly acquired along the trajectory, as well as keep the aircraft with the best aerodynamic performance during the whole task. The trajectory planning of a morphing aircraft was performed with the optimal aerodynamic performance based on the MFK models, built by only using 240 low-fidelity data and 110 high-fidelity data. The results indicate that a complex trajectory can take advantage of morphing rules in keeping good aerodynamic performance, and the proposed method is more efficient than trajectory optimization by reducing 86% of the computing time.

The new coronavirus (SARS-CoV-2) outbreak originating from Wuhan, China, poses a threat to global health. While it’s evident that the virus invades respiratory tract and transmits from human to human through airway, other viral tropisms and transmission routes remain unknown. We tested viral RNA in stool from 73 SARS-CoV-2-infected hospitalized patients using rRT-PCR. 53.42% of the patients tested positive in stool. 23.29% of the patients remained positive in feces even after the viral RNA decreased to undetectable level in respiratory tract. The viral RNA was also detected in gastrointestinal tissues. Furthermore, gastric, duodenal and rectal epithelia showed positive immunofluorescent staining of viral host receptor ACE2 and viral nucleocapsid protein in a case of SARS-CoV-2 infection. Our results provide evidence for gastrointestinal infection of SARS-CoV-2, highlighting its potential fecal-oral transmission route.