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The stochastic Green's function method (SGFM), which simulates the source spectra of small earthquakes based on the ω−2 model and follows the scaling law of earthquakes to synthesize into a large earthquake, is a practical ground motion simulation method in areas lacking suitable small earthquake records. However, one of the problems in the application of the SGFM is that the source spectrum synthesized from small earthquakes shows a fall‐off in the mid‐frequency band, as the number of fault divisions of the large earthquake increases. To solve this problem, this study proposes an improved method, which introduces a correction coefficient for the source spectrum according to the ω−2 model and considers the variation of subfault rise time with the rupture process. Taking the 1994 Northridge earthquake as an example, the ground motion simulation results of the improved method are compared with observed records. The results show that only introducing the correction coefficient causes larger amplitude of simulation results than observed records. Only considering the variation of subfault rise time can improve the fall‐off problem to some extent, but the accuracy of ground motion simulation at observation points has no significant improvement. By simultaneously introducing the correction coefficient and considering the variation of subfault rise time, the simulation results are in good agreement with observed records and are able to reproduce the directivity effect at the forward observation points. Therefore, the improved SGFM proposed in this study is an effective and reliable tool for ground motion simulation. Key Points: The problem of source spectrum fall‐off for simulating ground motion using stochastic Green's method was pointed outAn improved method introducing a correction coefficient and considering the variation of subfault rise time simultaneously was proposedThe effectiveness of improved method was verified by comparison of the simulated and observed results of the 1994 Northridge earthquake [ABSTRACT FROM AUTHOR]

Objective: Lung adenocarcinoma poses a major global health challenge and is a leading cause of cancer-related deaths worldwide. This study is a review of three molecular biomarkers screened by machine learning that are not only important in the occurrence and progression of lung adenocarcinoma but also have the potential to serve as biomarkers for clinical diagnosis, prognosis evaluation and treatment guidance. Methods: Differentially expressed genes (DEGs) were identified using comprehensive GSE1987 and GSE18842 gene expression databases. A comprehensive bioinformatics analysis of these DEGs was conducted to explore enriched functions and pathways, relative expression levels, and interaction networks. Random Forest and LASSO regression analysis techniques were used to identify the three most significant target genes. The TCGA database and quantitative polymerase chain reaction (qPCR) experiments were used to verify the expression levels and receiver operating characteristic (ROC) curves of these three target genes. Furthermore, immune invasiveness, pan-cancer, and mRNA-miRNA interaction network analyses were performed. Results: Eighty-nine genes showed increased expression and 190 genes showed decreased expression. Notably, the upregulated DEGs were predominantly associated with organelle fission and nuclear division, whereas the downregulated DEGs were mainly associated with genitourinary system development and cell-substrate adhesion. The construction of the DEG protein-protein interaction network revealed 32 and 19 hub genes with the highest moderate values among the upregulated and downregulated genes, respectively. Using random forest and LASSO regression analyses, the hub genes were employed to identify three most significant target genes.TCGA database and qPCR experiments were used to verify the expression levels and ROC curves of these three target genes, and immunoinvasive analysis, pan-cancer analysis and mRNA-miRNA interaction network analysis were performed. Conclusion: Three target genes identified by machine learning: BUB1B, CENPF, and PLK1 play key roles in LUAD development of lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

The current study is focused on the effect of target materials (quartz plate, copper sheet, and quartz plate with a grounded copper sheet on the back) on the propagation of atmospheric-pressure helium plasma jets. The dynamics of ionization waves (IWs) and the relative amount of reactive oxygen species (OH and O) in the IW front were compared by using spatial and temporal images and relative optical emission spectroscopy. Our measurements show that the targets can significantly affect the propagation and intensity of the IWs. In addition, strong OH emission lines were detected when the IWs impinged upon the damp surface. Numerical simulations have been carried out to explain the experimental observation. The propagation velocity of IWs predicted by the simulation was in good agreement with the experimental results. Simulation results suggest that the density and velocity of IWs mainly depend on the electric field between the high voltage electrode tip and the target. Analysis indicates that the targets could change the electric field distribution between the high voltage electrode and targets and thus affect the dynamics and the density of the IWs, the generation of reactive oxygen species, and the corresponding sterilization efficiency. [ABSTRACT FROM AUTHOR]

In this work, a novel non-thermal atmospheric-pressure microplasma array (APMPA) has been characterized. The APMPA employs 16 parallel capillaries with an inner diameter of 200 µm and arranged in a square configuration. Our measurements show that the stable plasma plumes can be generated by the APMPA and then spread along the dielectric surface. Both the power in the plasma source region and the one transferred onto the dielectric surface are calculated by plotting Lissajous figures. The power strongly depends on the applied voltage, frequency, and the distance between the nozzles and the dielectric surface. In addition, the temperature of N2 molecules in APMPA plasmas is calculated by using optical emission spectroscopy. The temporally resolved images of the APMPA plasmas show that the total emission intensities for the case of positive half-period is much higher than that of negative half-period. In order to describe the performance of the APMPA, the optical emission of the APMPA is compared with a single tube plasma jet with the same configuration and cross section area, and the result illustrates the APMPA can provide a higher density plasma and larger treatment area which may have a beneficial effect on various applications. [ABSTRACT FROM AUTHOR]

The brush-shape device mainly consisting of the well-aligned and microns-thick hollow quartz fibers can be used to generate an atmospheric and homogeneous cold plasma jet for biomedical applications. Addition of a trace amount of O2 into the feed gas greatly altered the electrical properties of the plasma jet, thus had an obvious effect on the sterilization efficiency. The uniformity of the brush-shape plasma jet along its transverse direction was well consistent with the uniform distribution of sterilization efficiency. The atmospheric He plasma jet containing 1% O2 may kill all the Candida albicans cells with a population of 105 spores within an exposure time of 180 s. Analysis indicates that both O radicals and charged species can be an important contributor in this plasma inactivation. [ABSTRACT FROM AUTHOR]

It remains a challenge to generate the uniform and large-area cold plasma at atmospheric pressure. In this paper, we report a method to generate a reliable and homogeneous brush-shaped plasma plume running at atmospheric pressure. The plasma brush (110 mm in length and 10 mm in width) is mainly composed of well-aligned and hollow optical fibers. Current–voltage measurements indicate that the brush-shaped plasma plume consists of glowlike pulsed discharge with their pulsewidths of several microseconds. The generation of the \He/O2 glowlike discharge is further proved by the uniform distribution of O atoms along the transverse location of the plasma brush. This brush-shaped plasma plume is used for the application in the plasma inactivation of Candida albicans cells. About 97% of Candida albicans cells with a population of 10^5 spores are killed when exposed to the \O2/\He (volume ratio: 5/95) brush-shaped plasma plume for 150 s. Analysis indicates that plasma-activated species, such as O radicals, may play a crucial role in killing the resistant Candida albicans cells. [ABSTRACT FROM AUTHOR]