A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core

Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.

Research Progress of Titanium Polypropylene Mesh in Breast Reconstruction

To investigate the application of titanium polypropylene mesh in breast reconstruction.In this study,we selected the literature data in recent 4 years to analyze the application of titanium polypropylene mesh in breast reconstruction.Using the keywords of"breast reconstruction,""titanium polypropylene mesh,^^"application"and"research progress,we analyzed and summarized the related research progress of titanium polypropylene mesh in breast reconstruction.The research was conducted using the analysis of titanium polypropylene mesh,titanium polypropylene mesh in breast reconstruction surgery advantages,adverse complications related to titanium polypropylene mesh in breast reconstruction surgery and preventive measures.By constantly improving these aspects in the research process,the current study has certain value,and may guide the research work of titanium mesh in breast reconstruction.

True-color real-time imaging and spectroscopy of carbon nanotubes on substrates using enhanced Rayleigh scattering

白光照亮的围单人赛的碳 nanotubes (SWCNT ) 应该由于散布的回声瑞利显得有颜色。然而，底层上的 SWCNT 的真彩成像没被报导，因为 SWCNT 和散布的强壮的底层的极其低的散布紧张。这里，我们证明散布的瑞利能被接口偶极子改进效果极大地提高。底层上的因而丰富多彩的 SWCNT 能被宽地 supercontinuum 激光照明直接在一台光显微镜下面想象，它便于单个 SWCNT 的高产量 chirality 赋值。这条途径，称为的瑞利成像显微镜学，没被限制为 SWCNT，但是对许多 nanomaterials 广泛地适用，它使丰富多彩的 nanoworld 能在光显微镜下面被探索。

Scanning electron microscopy imaging of single-walled carbon nanotubes on substrates

Scanning electron microscopy （SEM） plays an indispensable role in nanoscience and nanotechnology because of its high efficiency and high spatial resolution in characterizing nanomaterials. Recent progress indicates that the contrast arising from different conductivities or bandgaps can be observed in SEM images if single-walled carbon nanotubes （SWCNTs） are placed on a substrate. In this study, we use SWCNTs on different substrates as model systems to perform SEM imaging of nanomaterials. Substantial SEM observations are conducted at both high and low acceleration voltages, leading to a comprehensive understanding of the effects of the imaging parameters and substrates on the material and surface-charge signals, as well as the SEM imaging. This unified picture of SEM imaging not only furthers our understanding of SEM images of SWCNTs on a variety of substrates but also provides a basis for developing new imaging recipes for other important nanomaterials used in nanoelectronics and nanophotonics.