Numerical Investigations on Wedge Control of Separation of a Missile from an Aircraft

To make the missile safely separate from the internal weapons bay, a wedge flow control device is mounted on the front of the bay to control the variation of flow during the separation. The numerical simulations of missile separation without and with wedge flow control device under different sizes are carried out. The flow fields of different separation processes are obtained and discussed; the aerodynamic parameters and trajectory parameters of missile of different cases are illustrated and compared. Results show that, the wedge flow control device can accelerate the missile separation and has the effect of regulating the angular motion of missile. The influence of the wedge height is stronger than that of its length on the center of gravity motion and angular motion of missile

Generation of ring-shaped optical vortices in dissipative media by inhomogeneous effective diffusion

By means of systematic simulations we demonstrate generation of a variety of ring-shaped optical vortices (OVs) from a two-dimensional input with embedded vorticity, in a dissipative medium modeled by the cubic-quintic complex Ginzburg-Landau equation with an inhomogeneous effective diffusion (spatial-filtering) term, which is anisotropic in the transverse plane and periodically modulated in the longitudinal direction. We show the generation of stable square- and gear-shaped OVs, as well as tilted oval-shaped vortex rings, and string-shaped bound states built of a central fundamental soliton and two vortex satellites, or of three fundamental solitons. Their shape can be adjusted by tuning the strength and modulation period of the inhomogeneous diffusion. Stability domains of the generated OVs are identified by varying the vorticity of the input and parameters of the inhomogeneous diffusion. The results suggest a method to generate new types of ring-shaped OVs with applications to the work with structured light.Comment: 24 pages, 5 figures; Nonlinear Dynamics, in pres

Effect of a Jet Control Device on the Process of Missile and Internal Weapons Bay Separation

To ensure that the missile is safely separated from the internal weapons bay, the jet is used to control the process of missile separation, which is mounted on the front edge of the bay. The length-to-depth ratio of the bay was L/D=8, the diameter of the missile was d1 =0.178 m, the diameter of the jet was d2 =0.05 m . The FLUENT software was combined with our group-developed code under the platform of a user-defined function (UDF) to solve the flow field and the six-degrees-of-freedom (6DOF) of missile. The detached eddy simulation method and dynamic mesh technology were used in the numerical calculations. The boundary condition of missile, bay, and aircraft was no-slip wall condition. The boundary condition of the jet was the pressure-inlet. The pressure far-field boundary was selected as other boundaries. The constraint of the ejection device on the missile was considered. It was found that the jet control device thickens the shear layer, so the shear layer with more gradual velocity gradients, which is beneficial to the separation of missile. The distance between the internal weapons bay and the missile in the positive z-direction with the jet is 1.74 times that without the jet at t=0.5 s. In the case of the jet control device, the pitching angle of the missile ranged from 0.93° to -3.94° , the angular motion range of the missile with the jet is smaller than that without. The jet can make the characteristics of the flow field friendly, and enable the missile to separate from the bay quickly, stably, and safely

An Integrated Analysis of miRNA and mRNA Expressions in Non-Small Cell Lung Cancers

Using DNA microarrays, we generated both mRNA and miRNA expression data from 6 non-small cell lung cancer (NSCLC) tissues and their matching normal control from adjacent tissues to identify potential miRNA markers for diagnostics. We demonstrated that hsa-miR-96 is significantly and consistently up-regulated in all 6 NSCLCs. We validated this result in an independent set of 35 paired tumors and their adjacent normal tissues, as well as their sera that are collected before surgical resection or chemotherapy, and the results suggested that hsa-miR-96 may play an important role in NSCLC development and has great potential to be used as a noninvasive marker for diagnosing NSCLC. We predicted potential miRNA target mRNAs based on different methods (TargetScan and miRanda). Further classification of miRNA regulated genes based on their relationship with miRNAs revealed that hsa-miR-96 and certain other miRNAs tend to down-regulate their target mRNAs in NSCLC development, which have expression levels permissive to direct interaction between miRNAs and their target mRNAs. In addition, we identified a significant correlation of miRNA regulation with genes coincide with high density of CpG islands, which suggests that miRNA may represent a primary regulatory mechanism governing basic cellular functions and cell differentiations, and such mechanism may be complementary to DNA methylation in repressing or activating gene expression

Isolation and identification of pathogens of Morchella sextelata bacterial disease

Morel mushroom (Morchella spp.) is a rare edible and medicinal fungus distributed worldwide. It is highly desired by the majority of consumers. Bacterial diseases have been commonly observed during artificial cultivation of Morchella sextelata. Bacterial pathogens spread rapidly and cause a wide range of infections, severely affecting the yield and quality of M. sextelata. In this study, two strains of bacterial pathogens, named M-B and M-5, were isolated, cultured, and purified from the tissues of the infected M. sextelata. Koch’s postulates were used to determine the pathogenicity of bacteria affecting M. sextelata, and the pathogens were identified through morphological observation, physiological and biochemical analyses, and 16S rRNA gene sequence analysis. Subsequently, the effect of temperature on the growth of pathogenic bacteria, the inhibitory effect of the bacteria on M. sextelata on plates, and the changes in mycelial morphology of M. sextelata mycelium were analyzed when M. sextelata mycelium was double-cultured with pathogenic bacteria on plates. The results revealed that M-B was Pseudomonas chlororaphis subsp. aureofaciens and M-5 was Bacillus subtilis. Strain M-B started to multiply at 10–15°C, and strain M-5 started at 15–20°C. On the plates, the pathogenic bacteria also produced significant inhibition of M. sextelata mycelium, and the observation of mycelial morphology under the scanning electron microscopy revealed that the inhibited mycelium underwent obvious drying and crumpling, and the healthy mycelium were more plump. Thus, this study clarified the pathogens, optimal growth environment, and characteristics of M. sextelata bacterial diseases, thereby providing valuable basic data for the disease prevention and control of Morchella production

Identification of Genome-Wide Variations among Three Elite Restorer Lines for Hybrid-Rice

Rice restorer lines play an important role in three-line hybrid rice production. Previous research based on molecular tagging has suggested that the restorer lines used widely today have narrow genetic backgrounds. However, patterns of genetic variation at a genome-wide scale in these restorer lines remain largely unknown. The present study performed re-sequencing and genome-wide variation analysis of three important representative restorer lines, namely, IR24, MH63, and SH527, using the Solexa sequencing technology. With the genomic sequence of the Indica cultivar 9311 as the reference, the following genetic features were identified: 267,383 single-nucleotide polymorphisms (SNPs), 52,847 insertion/deletion polymorphisms (InDels), and 3,286 structural variations (SVs) in the genome of IR24; 288,764 SNPs, 59,658 InDels, and 3,226 SVs in MH63; and 259,862 SNPs, 55,500 InDels, and 3,127 SVs in SH527. Variations between samples were also determined by comparative analysis of authentic collections of SNPs, InDels, and SVs, and were functionally annotated. Furthermore, variations in several important genes were also surveyed by alignment analysis in these lines. Our results suggest that genetic variations among these lines, although far lower than those reported in the landrace population, are greater than expected, indicating a complicated genetic basis for the phenotypic diversity of the restorer lines. Identification of genome-wide variation and pattern analysis among the restorer lines will facilitate future genetic studies and the molecular improvement of hybrid rice

SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies

Abstract Spatial transcriptomic studies are becoming increasingly common and large, posing important statistical and computational challenges for many analytic tasks. Here, we present SPARK-X, a non-parametric method for rapid and effective detection of spatially expressed genes in large spatial transcriptomic studies. SPARK-X not only produces effective type I error control and high power but also brings orders of magnitude computational savings. We apply SPARK-X to analyze three large datasets, one of which is only analyzable by SPARK-X. In these data, SPARK-X identifies many spatially expressed genes including those that are spatially expressed within the same cell type, revealing new biological insights.http://deepblue.lib.umich.edu/bitstream/2027.42/173866/1/13059_2021_Article_2404.pd

Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis

Abstract Background Dimensionality reduction is an indispensable analytic component for many areas of single-cell RNA sequencing (scRNA-seq) data analysis. Proper dimensionality reduction can allow for effective noise removal and facilitate many downstream analyses that include cell clustering and lineage reconstruction. Unfortunately, despite the critical importance of dimensionality reduction in scRNA-seq analysis and the vast number of dimensionality reduction methods developed for scRNA-seq studies, few comprehensive comparison studies have been performed to evaluate the effectiveness of different dimensionality reduction methods in scRNA-seq. Results We aim to fill this critical knowledge gap by providing a comparative evaluation of a variety of commonly used dimensionality reduction methods for scRNA-seq studies. Specifically, we compare 18 different dimensionality reduction methods on 30 publicly available scRNA-seq datasets that cover a range of sequencing techniques and sample sizes. We evaluate the performance of different dimensionality reduction methods for neighborhood preserving in terms of their ability to recover features of the original expression matrix, and for cell clustering and lineage reconstruction in terms of their accuracy and robustness. We also evaluate the computational scalability of different dimensionality reduction methods by recording their computational cost. Conclusions Based on the comprehensive evaluation results, we provide important guidelines for choosing dimensionality reduction methods for scRNA-seq data analysis. We also provide all analysis scripts used in the present study at www.xzlab.org/reproduce.html .http://deepblue.lib.umich.edu/bitstream/2027.42/173850/1/13059_2019_Article_1898.pd

A novel nonparametric computational strategy for identifying differential methylation regions

Abstract Background DNA methylation has long been known as an epigenetic gene silencing mechanism. For a motivating example, the methylomes of cancer and non-cancer cells show a number of methylation differences, indicating that certain features characteristics of cancer cells may be related to methylation characteristics. Robust methods for detecting differentially methylated regions (DMRs) could help scientists narrow down genome regions and even find biologically important regions. Although some statistical methods were developed for detecting DMR, there is no default or strongest method. Fisher’s exact test is direct, but not suitable for data with multiple replications, while regression-based methods usually come with a large number of assumptions. More complicated methods have been proposed, but those methods are often difficult to interpret. Results In this paper, we propose a three-step nonparametric kernel smoothing method that is both flexible and straightforward to implement and interpret. The proposed method relies on local quadratic fitting to find the set of equilibrium points (points at which the first derivative is 0) and the corresponding set of confidence windows. Potential regions are further refined using biological criteria, and finally selected based on a Bonferroni adjusted t-test cutoff. Using a comparison of three senescent and three proliferating cell lines to illustrate our method, we were able to identify a total of 1077 DMRs on chromosome 21. Conclusions We proposed a completely nonparametric, statistically straightforward, and interpretable method for detecting differentially methylated regions. Compared with existing methods, the non-reliance on model assumptions and the straightforward nature of our method makes it one competitive alternative to the existing statistical methods for defining DMRs.http://deepblue.lib.umich.edu/bitstream/2027.42/173440/1/12859_2022_Article_4563.pd