From 24 January 2020 to 18 May 2020, Chaoshan took measures to limit the spread of coronavirus disease 2019 (COVID-19), such as restricting public gatherings, wearing masks and suspending classes. We explored the effects of these measures on the pathogen spectrum of paediatric respiratory tract infections in Chaoshan. Pharyngeal swab samples were collected from 4075 children hospitalised for respiratory tract infection before (May–December 2019) and after (January–August 2020) the COVID-19 outbreak. We used liquid chip technology to analyse 14 respiratory pathogens. The data were used to explore between-group differences, age-related differences and seasonal variations in respiratory pathogens. The number of cases in the outbreak group (1222) was 42.8% of that in the pre-outbreak group (2853). Virus-detection rates were similar in the outbreak (48.3%, 590/1222) and pre-outbreak groups (51.5%, 1468/2853; χ2 = 3.446, P = 0.065), while the bacteria-detection rate was significantly lower in the outbreak group (26.2%, 320/1222) than in the pre-outbreak group (44.1%, 1258/2853; χ2 = 115.621, P < 0.05). With increasing age, the proportions of respiratory syncytial virus (RSV) and cytomegalovirus (CMV) infections decreased, while those of Mycoplasma pneumoniae and adenovirus infections increased. Streptococcus pneumoniae, CMV and rhinovirus infections peaked in autumn and winter, while RSV infections peaked in summer and winter. We found that the proportion of virus-only detection decreased with age, while the proportion of bacteria-only detection increased with age (Table 2). Anti-COVID-19 measures significantly reduced the number of paediatric hospitalisations for respiratory tract infections, significantly altered the pathogen spectrum of such infections and decreased the overall detection rates of 14 common respiratory pathogens. The proportion of bacterial, but not viral, infections decreased.

Although prenatal exposure to high ambient temperatures were reported to be associated with preterm birth, limited research assessed the impact of weather-related extreme heat events (EHE) on birthweight, particularly by trimester. We, therefore, investigated the impact of prenatal EHE on birthweight among term babies (tLBW) by trimester and birthweight percentile. We conducted a population-based case–control study on singleton live births at 38–42 gestational weeks in New York State (NYS) by linking weather data with NYS birth certificates. A total of 22,615 cases were identified as birthweight <2500 gram, and a random sample of 139,168 normal birthweight controls was included. EHE was defined as three consecutive days with the maximum temperatures of ≥32.2 °C/90 °F (EHE90) and two consecutive days of temperatures ≥97th percentile (EHE97) based on the distribution of the maximum temperature for the season and region. We estimated odds ratios (ORs) and 95% confidence intervals (95% CI) with multivariable unconditional logistic regression, controlling for confounders. Overall exposure to EHE97 for 2 d was associated with tLBW (OR 1.05; 95% CI 1.02, 1.09); however, the strongest associations were only observed in the first trimester for both heat indicators, especially when exposure was ≥3 d (ORs ranged: 1.06–1.13). EHE in the first trimester was associated with significant reduction in mean birthweight from 26.78 gram (EHE90) to 36.25 gram (EHE97), which mainly affected the 40th and 60th birthweight percentiles. Findings revealed associations between multiple heat indicators and tLBW, where the impact was consistently strongest in the first trimester.

The hydroxyapatite nanoparticles (nHAPs) were synthesized rapidly by the self-assembled dual-frequency ultrasonic method. The ultrasonic time and power effect on the morphology and phase composition of nHAPs were investigated through field-emission scanning electron microscopy (FE-SEM), X-ray diffraction, energy dispersive spectrometer (EDS) spectrometer, and Fourier transform infrared spectroscopy, which showed that the most uniform nanoparticles were obtained when the ultrasonic time was 30 min and the ultrasonic power was 280 W. Cytotoxicity and hemolysis tests showed that an indistinctive cytotoxic effect was within the concentration of 25–400 μg/mL and the hemolytic ratio was below 2.0% at concentration of 25–200 μg/mL, respectively, revealing a good biocompatibility of nHAPs. By loading tetracycline hydrochloride onto nHAPs spheres, the drug release results showed that the drug loading and encapsulation efficiency were (26.34 ± 2.99)% and (52.68 ± 5.98)%, respectively. The drug-loaded sample shows a slow-release property, indicating that nHAPs may be promising as drug carriers.

In this paper, we review the status of the multifunctional experimental platform at the National Laboratory of High Power Laser and Physics (NLHPLP). The platform, including the SG-II laser facility, SG-II 9th beam, SG-II upgrade (SG-II UP) facility, and SG-II 5 PW facility, is operational and available for interested scientists studying inertial confinement fusion (ICF) and a broad range of high-energy-density physics. These facilities can provide important experimental capabilities by combining different pulse widths of nanosecond, picosecond, and femtosecond scales. In addition, the SG-II UP facility, consisting of a single petawatt system and an eight-beam nanosecond system, is introduced including several laser technologies that have been developed to ensure the performance of the facility. Recent developments of the SG-II 5 PW facility are also presented.

The morphology, composition, and structure of precipitates in an Al–Si–Mg–Hf alloy after heat treatment at 560°C for 20 h were studied by means of Cs-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), energy dispersive X-ray spectrometry (EDS), high-resolution transmission electron microscopy (HRTEM), and first-principle calculations. Precipitates with three kinds of morphologies were observed. The rectangular and square precipitates were predominantly (Si2−xAlx)Hf phases, while the nanobelt-like precipitate is the Si2Hf phase. First-principle calculations were used to show that the Si6 and Si8 sites were the most favorable sites for Al incorporation in the orthorhombic Si2Hf phase.

The effects of pre-treatments on the precipitate microstructures of an Al–Zn–Mg–Cu alloy are investigated. Meanwhile, the creep-rupture behavior of the under-aged and peak-aged alloys are comparatively analyzed. Additionally, the effects of pre-treatment on the fracture mechanisms are discussed. It is found that the precipitate microstructures are sensitive to pre-treatments. The intragranular precipitates of the peak-aged alloy are larger than those of the under-aged. The precipitate free zone of the peak-aged alloy is wider than that of the under-aged. Some large intergranular precipitates appear on the grain boundaries of the under-aged alloy, and induce the nucleation of microvoids. Eventually, the creep fracture of the under-aged alloy is accelerated. Therefore, the differences in microstructures lead to the shorter creep-rupture life of the under-aged alloy, compared to the peak-aged alloy.

We have developed efficient numerical algorithms for solving 3D steady-state Poisson-Nernst-Planck (PNP) equations with excess chemical potentials described by the classical density functional theory (cDFT). The coupled PNP equations are discretized by a finite difference scheme and solved iteratively using the Gummel method with relaxation. The Nernst-Planck equations are transformed into Laplace equations through the Slotboom transformation. Then, the algebraic multigrid method is applied to efficiently solve the Poisson equation and the transformed Nernst-Planck equations. A novel strategy for calculating excess chemical potentials through fast Fourier transforms is proposed, which reduces computational complexity from O(N2) to O(NlogN), where N is the number of grid points. Integrals involving the Dirac delta function are evaluated directly by coordinate transformation, which yields more accurate results compared to applying numerical quadrature to an approximated delta function. Numerical results for ion and electron transport in solid electrolyte for lithiumion (Li-ion) batteries are shown to be in good agreement with the experimental data and the results from previous studies.

Experimental observations show that a strong magnetic field has a dramatic influence on the sedimentation of RBCs, which motivates us to model the sedimentation of red blood cell (RBC) under strong external magnetic body force. To model the sedimentation of a RBC in a square duct and a circular pipe, a recently developed technique derived from the lattice Boltzmann and the distributed Lagrange multiplier/fictitious domain methods (LBM-DLM/FD) is extended to employ the mesoscopic network model for simulations of the sedimentation of a RBC in flow. The flow is simulated by the LBM with a strong magnetic body force, while the network model is used for modeling RBC deformation. The fluid-RBC interactions are enforced by the Lagrange multiplier. The sedimentation of RBC in a square duct and a circular pipe is simulated, which demonstrates the developed method's capability to model the sedimentation of RBCs in various flows. Numerical results illustrate that the terminal settling velocity increases incrementally with the exerted body force. The deformation of RBC has a significant effect on the terminal settling velocity due to the change in the frontal area. The larger the exerted force, the smaller the frontal area and the larger the RBC deformation become. Additionally, the wall effect on the motion and deformation of RBC is also investigated.

In this paper, we present an adaptive, analysis of variance (ANOVA)-based data-driven stochastic method (ANOVA-DSM) to study the stochastic partial differential equations (SPDEs) in the multi-query setting. Our new method integrates the advantages of both the adaptive ANOVA decomposition technique and the data-driven stochastic method. To handle high-dimensional stochastic problems, we investigate the use of adaptive ANOVA decomposition in the stochastic space as an effective dimension-reduction technique. To improve the slow convergence of the generalized polynomial chaos (gPC) method or stochastic collocation (SC) method, we adopt the data-driven stochastic method (DSM) for speed up. An essential ingredient of the DSM is to construct a set of stochastic basis under which the stochastic solutions enjoy a compact representation for a broad range of forcing functions and/or boundary conditions.

Our ANOVA-DSM consists of offline and online stages. In the offline stage, the original high-dimensional stochastic problem is decomposed into a series of low-dimensional stochastic subproblems, according to the ANOVA decomposition technique. Then, for each subproblem, a data-driven stochastic basis is computed using the Karhunen-Loève expansion (KLE) and a two-level preconditioning optimization approach. Multiple trial functions are used to enrich the stochastic basis and improve the accuracy. In the online stage, we solve each stochastic subproblem for any given forcing function by projecting the stochastic solution into the data-driven stochastic basis constructed offline. In our ANOVA-DSM framework, solving the original highdimensional stochastic problem is reduced to solving a series of ANOVA-decomposed stochastic subproblems using the DSM. An adaptive ANOVA strategy is also provided to further reduce the number of the stochastic subproblems and speed up our method. To demonstrate the accuracy and efficiency of our method, numerical examples are presented for one- and two-dimensional elliptic PDEs with random coefficients.

In this study, we present a new numerical model for crystal growth in a vertical solidification system. This model takes into account the buoyancy induced convective flow and its effect on the crystal growth process. The evolution of the crystal growth interface is simulated using the phase-field method. A semi-implicit lattice kinetics solver based on the Boltzmann equation is employed to model the unsteady incompressible flow. This model is used to investigate the effect of furnace operational conditions on crystal growth interface profiles and growth velocities. For a simple case of macroscopic radial growth, the phase-field model is validated against an analytical solution. The numerical simulations reveal that for a certain set of temperature boundary conditions, the heat transport in the melt near the phase interface is diffusion dominant and advection is suppressed.

This paper investigates the modulational instability of a linearly polarized ultra-intense laser pulse propagating in electron–positron plasmas. Based on the wave equation, which contains vacuum polarization and magnetization effects, the nonlinear dispersion relation and the growth rate of instability are obtained and the effects of plasma number density and laser intensity on the growth rate are analyzed. Numerical results show that if the laser intensity is high enough, the modulational instability growth rate induced by vacuum polarization and magnetization nonlinearity can dominate the modulational instability growth rate induced by the nonlinearity associated with a relativistic effect and ponderomotive force.

An efficient implementation of PNP-cDFT, a multiscale method for computing the chemical potentials of charged species is designed and evaluated. Spatial decomposition of the multi particle system is employed in the parallelization of classical density functional theory (cDFT) algorithm. Furthermore, a truncation strategy is used to reduce the computational complexity of cDFT algorithm. The simulation results show that the parallel implementation has close to linear scalability in parallel computing environments. It also shows that the truncated versions of cDFT improve the efficiency of the methods substantially.

The pathological mechanism of restenosis is primarily attributed to excessive proliferation of vascular smooth muscle cells (VSMC). The preventive effects of ethanol extract of Dunaliella salina (EDS) on balloon injury-induced neointimal formation were investigated. To explore its molecular mechanism in regulating cell proliferation, we first showed that EDS markedly reduced the human aortic smooth muscle cell proliferation via the inhibition of 5′-bromo-2′-deoxyuridine (BrdU) incorporation at 40 and 80 μg/ml. This was further supported by the G0/G1-phase arrest using a flow cytometric analysis. In an in vivo study, EDS at 40 and 80 μg/ml was previously administered to the Sprague–Dawley rats and found that the thickness of neointima, and the ratio of neointima:media were also reduced. EDS inhibited VSMC proliferation in a dose-dependent manner following stimulation of VSMC cultures with 15 % fetal bovine serum (FBS). Suppressed by EDS were 15 % FBS-stimulated intracellular Raf, phosphorylated extracellular signal-regulated kinases (p-Erk) involved in cell-cycle arrest and proliferating cell nuclear antigen. Phosphorylated focal adhesion kinase (p-FAK) was also suppressed by EDS. Also active caspase-9, caspase-3 and cleaved poly(ADP-ribose) polymerase (PARP) protein expression levels were increased by administration with EDS; the apoptotic pathway may play an important role in the regulatory effects of EDS on cell growth. These observations provide a mechanism of EDS in attenuating cell proliferation, thus as a potential intervention for restenosis.