With the increase of crewed space missions and the rise of space microbiology, the research of microbes grown under microgravity environment has been attracting more attention. The research scope in space microbiology has been extended beyond pathogens directly related to spaceflight. Y. pestis, the causative agent of plague, is also of interest to researchers. After being cultivated for 40 consecutive passages in either simulated microgravity (SMG) or normal gravity (NG) conditions, the Y. pestis strain 201 cultures were analysed regarding their phenotypic features. By using crystal violet staining assays, increased biofilm amount was detected in Y. pestis grown under SMG condition. Besides that, the damage degrees of Hela cell caused by SMG-grown Y. pestis were found diminished in comparison to those under NG condition. Consistent with this observation, the death course was delayed in mice infected with SMG-grown Y. pestis, suggesting that microgravity condition can contribute the attenuated virulence. RNA-seq-based transcriptomics analysis showed that a total of 218 genes were differentially regulated, of which 91 upregulated and 127 downregulated. We found that dozens of virulence-associated genes were downregulated, which partially explained the reduced virulence of Y. pestis under SMG condition. Our study demonstrated that long-term exposure to SMG influences the pathogenesis and biofilm formation ability of Y. pestis, which provides a novel avenue to study the mechanism of physiology and virulence of this pathogen. Microgravity enhanced the ability of biofilm formation and reduced the virulence and cytotoxicity of Y. pestis. Many virulence-associated genes of Y. pestis were differentially regulated in response to the stimulated microgravity. However, there is no molecular evidence to explain the enhanced biofilm formation ability, which requires further research. Taken together, the phenotype changes of Y. pestis under SMG conditions can provide us a new research direction of its potential pathogenesis.

Grain refinement has been applied to enhance the materials strength for miniaturization and lightweight design of nuclear equipment. It is critically important to investigate the low-cycle fatigue (LCF) properties of grain refined 316LN austenitic stainless steels for structural design and safety assessment. In the present work, a series of fine-grained (FG) 316LN steels were produced by thermo-mechanical processes. The LCF properties were studied under a fully reversed strain-controlled mode at room temperature. Results show that FG 316LN steels demonstrate good balance of high strength and high ductility. However, a slight loss of ductility in FG 316LN steel induces a significant deterioration of LCF life. The rapid energy dissipation in FG 316LN steels leads to the reduction of their LCF life. Dislocations develop rapidly in the first stage of cycles, which induces the initial cyclic hardening. The dislocations rearrange to form dislocations cell structure resulting in cyclic softening in the subsequent cyclic deformation. Strain-induced martensite transformation appears in FG 316LN stainless steels at high strain amplitude (Δε/2 = 0.8%), which leads to the secondary cyclic hardening. Moreover, a modified LCF life prediction model for grain refined metals predicts the LCF life of FG 316LN steels well.

The X-Shooter Spectral Library (XSL) contains more than 800 spectra of stars across the color-magnitude diagram, that extend from near-UV to near-IR wavelengths (320-2450 nm). We summarize properties of the spectra of O-rich Long Period Variables in the XSL, such as phase-related features, and we confront the data with synthetic spectra based on static and dynamical stellar atmosphere models. We discuss successes and remaining discrepancies, keeping in mind the applications to population synthesis modeling that XSL is designed for.

In this paper, a Chebyshev-collocation spectral method is developed for Volterra integral equations (VIEs) of second kind with weakly singular kernel. We first change the equation into an equivalent VIE so that the solution of the new equation possesses better regularity. The integral term in the resulting VIE is approximated by Gauss quadrature formulas using the Chebyshev collocation points. The convergence analysis of this method is based on the Lebesgue constant for the Lagrange interpolation polynomials, approximation theory for orthogonal polynomials, and the operator theory. The spectral rate of convergence for the proposed method is established in the L∞-norm and weighted L2-norm. Numerical results are presented to demonstrate the effectiveness of the proposed method.

It is a challenging task to discover information from a large amount of data in an open domain.1 In this paper, an event network framework is proposed to address this challenge. It is in fact an empirical construct for exploring open information, composed of three steps: document event detection, event network construction and event network analysis. First, documents are clustered into document events for reducing the impact of noisy and heterogeneous resources. Secondly, linguistic units (e.g., named entities or entity relations) are extracted from each document event and combined into an event network, which enables content-oriented retrieval. Then, in the final step, techniques such as social network or complex network can be applied to analyze the event network for exploring open information. In the implementation section, we provide examples of exploring open information via event network.

In this paper, we consider an optimal control problem governed by Stokes equations with H1-norm state constraint. The control problem is approximated by spectral method, which provides very accurate approximation with a relatively small number of unknowns. Choosing appropriate basis functions leads to discrete system with sparse matrices. We first present the optimality conditions of the exact and the discrete optimal control systems, then derive both a priori and a posteriori error estimates. Finally, an illustrative numerical experiment indicates that the proposed method is competitive, and the estimator can indicate the errors very well.

In the paper, we present an efficient two-grid method for the approximation of two-dimensional nonlinear reaction-diffusion equations using a expanded mixed finite-element method. We transfer the nonlinear reaction diffusion equation into first order nonlinear equations. The solution of the nonlinear system on the fine space is reduced to the solutions of two small (one linear and one non-linear) systems on the coarse space and a linear system on the fine space. Moreover, we obtain the error estimation for the two-grid algorithm. It is showed that coarse space can be extremely coarse and achieve asymptotically optimal approximation as long as the mesh sizes satisfy . An numerical example is also given to illustrate the effectiveness of the algorithm.

In this paper, we study the numerical solution of singularly perturbed time-dependent convection-diffusion problems. To solve these problems, the backward Euler method is first applied to discretize the time derivative on a uniform mesh, and the classical upwind finite difference scheme is used to approximate the spatial derivative on an arbitrary nonuniform grid. Then, in order to obtain an adaptive grid for all temporal levels, we construct a positive monitor function, which is similar to the arc-length monitor function. Furthermore, the ε-uniform convergence of the fully discrete scheme is derived for the numerical solution. Finally, some numerical results are given to support our theoretical results.

A spectral Jacobi-collocation approximation is proposed for Volterra delay integro-differential equations with weakly singular kernels. In this paper, we consider the special case that the underlying solutions of equations are sufficiently smooth. We provide a rigorous error analysis for the proposed method, which shows that both the errors of approximate solutions and the errors of approximate derivatives decay exponentially in L∞ norm and weighted L2 norm. Finally, two numerical examples are presented to demonstrate our error analysis.

The miscible displacement of one incompressible fluid by another in a porous medium is governed by a system of two equations. One is elliptic form equation for the pressure and the other is parabolic form equation for the concentration of one of the fluids. Since only the velocity and not the pressure appears explicitly in the concentration equation, we use a mixed finite element method for the approximation of the pressure equation and mixed finite element method with characteristics for the concentration equation. To linearize the mixed-method equations, we use a two-grid algorithm based on the Newton iteration method for this full discrete scheme problems. First, we solve the original nonlinear equations on the coarse grid, then, we solve the linearized problem on the fine grid used Newton iteration once. It is shown that the coarse grid can be much coarser than the fine grid and achieve asymptotically optimal approximation as long as the mesh sizes satisfy h = H2 in this paper. Finally, numerical experiment indicates that two-grid algorithm is very effective.

In this paper, we investigate the Galerkin spectral approximation for elliptic control problems with integral control and state constraints. Firstly, an a posteriori error estimator is established,which can be acted as the equivalent indicatorwith explicit expression. Secondly, appropriate base functions of the discrete spacesmake it is probable to solve the discrete system. Numerical test indicates the reliability and efficiency of the estimator, and shows the proposed method is competitive for this class of control problems. These discussions can certainly be extended to two- and three-dimensional cases.

The Chinese black honey bee is a distinct honey bee subspecies distributed in the Xinjiang, Heilongjiang and Jilin Provinces of China. We conducted a study to investigate the genetic origin and the parasite/pathogen profile on Chinese black honeybees. The phylogenetic analysis indicated that Chinese black honeybees were two distinct groups: one group of bees formed a distinct clade that was most similar to Apis mellifera mellifera and the other group was a hybrid of the subspecies, Apis mellifera carnica, Apis mellifera anatolica and Apis mellifera caucasica. This suggests that the beekeeping practices might have promoted gene flow between different subspecies. Screening for pathogens and parasites showed that Varroa destructor and viruses were detected at low prevalence in Chinese black honeybees, compared with Italian bees. Further, a population of pure breeding black honeybees, A. m. mellifera, displayed a high degree of resistance to Varroa. No Varroa mites or Deformed wing virus could be detected in any examined bee colonies. This finding suggests that a population of pure breeding Chinese black honeybees possess some natural resistance to Varroa and indicated the need or importance for the conservation of the black honeybees in China.

Our main purpose in this paper is to propose the piecewise Legendre spectral-collocation method to solve Volterra integro-differential equations. We provide convergence analysis to show that the numerical errors in our method decay in $h^{m}N^{-m}$-version rate. These results are better than the piecewise polynomial collocation method and the global Legendre spectral-collocation method. The provided numerical examples confirm these theoretical results.

In this paper, we consider a singularly perturbed convection-diffusion problem. The problem involves two small parameters that gives rise to two boundary layers at two endpoints of the domain. For this problem, a non-monotone finite element methods is used. A priori error bound in the maximum norm is obtained. Based on the a priori error bound, we show that there exists Bakhvalov-type mesh that gives optimal error bound of (N−2) which is robust with respect to the two perturbation parameters. Numerical results are given that confirm the theoretical result.

A posteriori error estimates of semidiscrete mixed finite element methods for quadratic optimal control problems involving linear parabolic equations are developed. The state and co-state are discretised by Raviart-Thomas mixed finite element spaces of order k, and the control is approximated by piecewise polynomials of order k (k ≥ 0). We derive our a posteriori error estimates for the state and the control approximations via a mixed elliptic reconstruction method. These estimates seem to be unavailable elsewhere in the literature, although they represent an important step towards developing reliable adaptive mixed finite element approximation schemes for the control problem.

A Legendre-collocation method is proposed to solve the nonlinear Volterra integral equations of the second kind. We provide a rigorous error analysis for the proposed method, which indicate that the numerical errors in L2-norm and L∞-norm will decay exponentially provided that the kernel function is sufficiently smooth. Numerical results are presented, which confirm the theoretical prediction of the exponential rate of convergence.