Removal of Stripes in Remote Sensing Images Based on Statistics Combined with Image Enhancement

A method to remove stripes from remote sensing images is proposed based on statistics and a new image enhancement method.The overall processing steps for improving the quality of remote sensing images are introduced to provide a general baseline.Due to the differences in satellite sensors when producing images,subtle but inherent stripes can appear at the stitching positions between the sensors.These stitchingstripes cannot be eliminated by conventional relative radiometric calibration.The inherent stitching stripes cause difficulties in downstream tasks such as the segmentation,classification and interpretation of remote sensing images.Therefore,a method to remove the stripes based on statistics and a new image enhancement approach are proposed in this paper.First,the inconsistency in grayscales around stripes is eliminated with the statistical method.Second,the pixels within stripes are weighted and averaged based on updated pixel values to enhance the uniformity of the overall image radiation quality.Finally,the details of the images are highlighted by a new image enhancement method,which makes the whole image clearer.Comprehensive experiments are performed,and the results indicate that the proposed method outperforms the baseline approach in terms of visual quality and radiation correction accuracy.

基于Stripes的在线测试系统的设计与开发

本文首先介绍了在线测试系统的研究意义及现存的问题,在经典测试理论的基础上,阐述了整个系统的设计思想、技术路线、开发平台的选择、系统总体框架、实现的功能以及具体的实现方法。以"大学英语"课程为例,对基于Stripes框架的在线测试系统进行了开发。

基于Stripes框架的Ajax应用与研究

Web 2.0时代已经到来,而如何能让Web2.0网站有更好的用户体验以及更快的数据传输一直是开发者所面临的重要问题。Ajax作为Web2.0中的一个关键技术,其在提高用户体验、减少网络传输方面有着无可替代的作用;而另一个新生的MVC框架Stripes,以其配置文件少、学习周期短,也正成为Java开发者的宠儿。正是基于此,文中提出了一种整合Stripes+Ajax的架构,目的是让开发人员以最快最简洁的方式进行Ajax开发,同时文中还提出了Stripes在Ajax中的多种数据传输格式,提出了多种Ajax数据传输方案。

Research on the Dark Stripes Extraction Algorithm for Measuring Diameter with Diffraction

The optical diffraction is a major means of minute diameter measurements. Since the light intensity of the diffraction fringe, mainly distributed in the central bright stripes, and that will lead to a relatively low SNR for the signal of the senior stripes. The traditional dark stripes extraction algorithm affected greatly by the noise. So this paper presents an algorithm that could effectively eliminate the gross errorcaused by the noise. Than by curve fitting the local signal of the diffraction pattern with the least square principle, the system could achieve a high measurement precision.

Characteristic Analysis and Comprehensive Control for the Horizontal Stripes of High-Grade Automotive Panels in Continuous Annealing

As to the horizontal stripes defect which exist on the surface of the high-grade automotive panels in continuous annealing process, an effective comprehensive control method is proposed on the basis of full consideration of the equipment and technological features of continuous annealing line. With five field tests as basis, the generation mechanism of the defect was analysised in detail and the comprehensive control measures were put forward. According to actual situation, a detailed technical plan was worked out .Then the relevant technologies were applied to a 1850 continuous annealing line. The statistics shows that this program acquired good effects. The incidence of horizontal stripes defect decreased from 100% to 2.78%. Meanwhile, the surface quality of strip also improved effectively, which created a larger economic benefit.

A morphology-stitching method to improve Landsat SLC-off images with stripes

Stripes are artifacts in satellite images caused by various factors such as hardware defects. In some cases, these artifacts are introduced by some mitigating algorithms like Landsat SLC-off （Scan Line Corrector） gap-filling methods of LLHM （Local Linear Histogram Matching） and AWLHM （Adaptive Window Linear Histogram Matching）, which leave stripes as a byproduct. To improve Landsat SLC-off images with stripes,we propose an algorithm involving some hypothetical stripe-crossing stitch lines using the mean pixel value of the stitch lines.

Simulating to Formation of Stripes in Migmatite under Directional Pressure Using Stochastic Cellular Automaton

There are some different opinions on the formation of striped migmatite. Many striped migmatites are distributed around the plutonic rocks in the core of hot dome in nature. This shows that the pressure of intrusive rocks to wall rocks must play an important role in the formation of stripes. This paper, at first, discusses the effects of directional pressure (i. e. compressive stress from intrusive rock to wall rock) on particle migration and crystallization, and the physical mechanism of Ostwald maturation and its adjusting effect in crystalline growth. And then, on the basic principles of physics and chemistry, we lay down the stochastic evolutional rules of the formation of crystal nucleus, diffusion, crystallization and dissolution of leucosome (melt) particles; and,neglecting other restrictive conditions, we build an idealizedly simplified two-dimensional model of stochastic cellular automaton for the recrystallization of metamorphic rock under directional pressure, and realize it by writing a program of Windows on PC. Theoretical analyses and computer simulations show that, at the beginning, the free particles of leucosome are initially even distributed in the system and form many crystal nucleus ; then, the anisotropies of diffusion, crystallization and dissolution caused by the directional pressure together with the mechanisms of Ostwald maturation can make the nucleus successively grow to form lenses, unevenly disconnected stripes, and layer-stripe structure, which correspond to low, medium and high grades of metamorphism and migmatization, respectively; that is, the effect of the pressure of intrusive rock to wall rock alone can form streaked structure in migmatite. Moreover, cellular automaton, adopted in this paper, is a kind of discrete and local grid dynamic model, and is extremely suitable for simulating the evolution of spatiotemporal structure of real systems and analyzing micro-mechanism creating complex macro-phenomenon. We believe that cellular automata will have broad applications in the geosciences which is full of complicated natural phenomena.

Experimental study on temperature fluctuations on plate surface induced by coaxial-jet flow

In nuclear reactors,temperature fluctuations of fluids may cause fatigue damage to adjacent structures;this is referred to as thermal striping.Research on thermal striping in the upper plenum has mainly focused on fluid fields.Few experimental studies have been reported on solid structures in a fluid field with a coaxial jet.This study entailed an experimental study of the temperature fluctuations in the fluid and on a plate surface caused by a coaxial jet.The temperature fluctuations of the fluid and plate surfaces located at different heights were analyzed.The cause of the temperature fluctuation was analyzed using a transient temperature distribution.The results show that the mixing of the hot and cold fluids gradually becomes uniform in the positive axial direction.The average surface temperatures tended to be consistent.When the jet reaches the plate surface,the swing of the jet center,contraction and expansion of the cold jet,and changes in the jet shape result in temperature fluctuations.The intensity of the temperature fluctuation was affected by the position.More attention should be paid when the plate is located at a lower height,and between the hot and cold-fluid nozzles.

Yr5-virulent races of Puccinia striiformis f.sp.tritici possess relative parasitic fitness higher than current main predominant races and potential risk

Wheat stripe rust,caused by Puccinia striiformis f.sp.tritici(Pst),is one of the most destructive fungal diseases of wheat,and seriously threatens safe production of the crop worldwide.In China,new races historically appeared and rapidly developed to be predominant races and have resulted in ineffectiveness and replacement of wheat resistance cultivars as well as massive reduction in yield.In the present study,the relative parasitic fitness of the two newlyemerged Yr5-virulent races(TSA-6 and TSA-9)were compared with those of four currently predominant Chinese races(CYR31,CYR32,CYR33,and CYR34)based on evaluation on 10 Chinese wheat cultivars.As a result,there were significant differences in the relative parasitic fitness parameters among overall tested races based on multiple comparison(LSD)analysis(P<0.05).The principal component analysis(PCA)of overall parasitic fitness parameters indicated that the sporulation ability,infection and spore survivability,expansion capacity,and potential pathogenicity were the most important parasitic fitness attributes of the tested races.Based on the establishment of extracted three principal components and a comprehensive factor score mathematical models,evaluations of the parasitic fitness attributes of tested races showed that the level of relative parasitic fitness of the tested six races was:CYR32(1.15)>TSA-9(0.95)>TSA-6(0.92)>CYR34(0.29)>CYR31(–1.54)>CYR33(–1.77).The results indicated that two Yr5-virulent races TSA-9 and TSA-6 possessed relative parasitic fitness higher than races CYR34,CYR31,and CYR33,but lower than race CYR32,and have potential risks in developing to be predominant races.Therefore,continual monitoring of both Yr5-virulent races,and their variants is needed.The use of wheat cultivars(lines)with Yr5 resistance gene singly in wheat breeding is essential for being avoided,and is suggested to combine with other effective stripe rust resistance genes.

Amur tiger stripes:individual identification based on deep convolutional neural network

The automatic individual identification of Amur tigers(Panthera tigris altaica)is important for population monitoring and making effective conservation strategies.Most existing research primarily relies on manual identifi-cation,which does not scale well to large datasets.In this paper,the deep convolution neural networks algorithm is constructed to implement the automatic individual identification for large numbers of Amur tiger images.The experimental data were obtained from 40 Amur tigers in Tieling Guaipo Tiger Park,China.The number of images collected from each tiger was approximately 200,and a total of 8277 images were obtained.The experiments were carried out on both the left and right side of body.Our results suggested that the recognition accuracy rate of left and right sides are 90.48%and 93.5%,respectively.The accuracy of our network has achieved the similar level compared to other state of the art networks like LeNet,ResNet34,and ZF_Net.The running time is much shorter than that of other networks.Consequently,this study can provide a new approach on automatic individual identification technology in the case of the Amur tiger.

The roles of R2R3-MYBs in regulating complex pigmentation patterns in flowers

Pigmentation patterns are ubiquitous in nature.Visually striking pigmentation patterns are not only aesthetically appealing,but also crucial to pollinator interaction and plant fitness.The formation of complex floral pigmentation patterns mainly relies on the spatiotemporal expression of R2R3-MYB transcription factors and is often associated with certain floral development programs,such as floral organ identity,symmetry,which likely provide key information to initiate the patterning.For a complex pigmentation pattern to form,at least a pair of activator and inhibitor is required,despite their interaction might vary depending on the system being investigated.The regulation of pigmentation pattern involves multiple molecular mechanisms,such as transcriptional regulation,small RNA,transposon-mediated gene silencing,and methylation of gene body.Identifying these regulators can be facilitated by using single-cell and spatial transcriptomics as well as innovative plant transformation technologies.Moreover,plant organ development and pigmentation patterns are often interdependent,but current methods of describing patterns are static.Therefore,more precise and quantitative measurements are needed to elucidate the developmental mechanisms underlying complex pigmentation patterns in flowers.

Dynamics of the inner electron radiation belt:A review

The Van Allen radiation belts are an extraordinary science discovery in the Earth magnetosphere and consist of two electron belts.The inner Van Allen belt contains electrons of 10s to 100s keV;the outer belt consists mainly of 0.1-10 MeV electrons.Their dynamics have been analyzed for decades.The newly-launched Van Allen Probes provide unprecedented opportunities to investigate the inner belt more thoroughly.Data from this advanced mission have allowed scientists to demonstrate that the inner belt was formed not only through inward transport of outer belt electrons but Cosmic Ray Albedo Neutron Decay(CRAND)has also played an important role.In addition,the inner belt electrons show energy-dependent variations and present“zebra stripe”structures in the energy spectrum.At the same time,scientists have further confirmed that the electrons in the inner radiation belt get lost through coulomb collision and wave-particle interaction.Despite these advances,important questions remain unanswered and require further investigation.The launch of Macao Science Satellite-1 mission,with its low inclination angle and low altitude orbit,will provide advanced radiation belt data for better understanding of the structure and dynamics of the inner electron radiation belt.

Fine mapping and transcriptome sequencing reveal candidate genes conferring all-stage resistance to stripe rust on chromosome arm 1AL in Chinese wheat landrace AS1676

Stripe rust, caused by Puccinia striiformis f. sp. tritici(Pst), threatens wheat production worldwide, and resistant varieties tend to become susceptible after a period of cultivation owing to the variation of pathogen races. In this study, a new resistance gene against Pst race CYR34 was identified and predicted using the descendants of a cross between AS1676, a highly resistant Chinese landrace, and Avocet S, a susceptible cultivar. From a heterozygous plant from a F7recombinant inbred line(RIL) population lacking the Yr18 gene, a near-isogenic line(NIL) population was developed to map the resistance gene. An allstage resistance gene, YrAS1676, was identified on chromosome arm 1AL via bulked-segregant exomecapture sequencing. By analyzing a large NIL population consisting of 6537 plants, the gene was further mapped to the marker interval between KA1A_485.36 and KA1A_490.13, spanning 485.36–490.13 Mb on1AL. A total of 66 annotated genes have been reported in this region. To characterize and predict the candidate gene(s), an RNA-seq was performed using NIL-R and NIL-S seedlings 3 days after CYR34 inoculation. Compared to NIL-S plants, NIL-R plants showed stronger immune reaction and higher expression levels of genes encoding pathogenesis-associated proteins. These differences may help to explain why NIL-R plants were more resistant to Pst race CYR34 than NIL-S plants. By combining fine-mapping and transcriptome sequencing, a calcium-dependent protein kinase gene was finally predicted as the potential candidate gene of YrAS1676. This gene contained a single-nucleotide polymorphism. The candidate gene was more highly expressed in NIL-R than in NIL-S plants. In field experiments with Pst challenge,the YrAS1676 genotype showed mitigation of disease damage and yield loss without adverse effects on tested agronomic traits. These results suggest that YrAS1676 has potential use in wheat stripe rust resistance breeding.

Transcriptome analysis reveals different response of resistant and susceptible rice varieties to rice stripe virus infection

Rice stripe disease,caused by rice stripe virus (RSV) which is transmitted by small brown planthopper (SBPH,Laodelphax striatellus Fallen),resulted in serious losses to rice production during the last 2 decades.Research on the molecular differences between resistant and susceptible rice varieties and the interaction between rice and RSV remains inadequate.In this study,RNA-Seq was used to analyze the transcriptomic differences between the resistant and susceptible rice varieties at different times post RSV infection.Through Gene Ontology (GO) annotation,the differentially expressed genes (DEGs) related to transcription factors,peroxidases,and kinases of 2 varieties at 3 time points were identified.Comparing these 2 varieties,the DEGs associated with these 3 GOs were numerically less in the resistant variety than in the susceptible variety,but the expression showed a significant up-or down-regulation trend under the conditions of|log_2(Fold change)|>0&P_(adj)<0.05 by significance analysis.Then through Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation,DEGs involved in some pathways that have a contribution to disease resistance including plant hormone signal transduction and plant–pathogen interaction were found.The results showed that resistance responses regulated by abscisic acid (ABA) and brassinosteroids (BR) were the same for 2 varieties,but that mediated by salicylic acid (SA) and jasmonic acid (JA)/ethylene (ET) were different.The DEGs in resistant and susceptible varieties at the 3 time points were identified in both PAMP-triggered immunity (PTI) and Effector proteintriggered immunity (ETI),with that most of the unigenes of the susceptible variety were involved in PTI,whereas most of the unigenes of the resistant variety were involved in ETI.These results revealed the different responses of resistant and susceptible varieties in the transcription level to RSV infection.

Strip segmentation of oceanic internal waves in SAR images based on TransUNet

The development of oceanic remote sensing artificial intelligence has made possible to obtain valuable information from amounts of massive data.Oceanic internal waves play a crucial role in oceanic activity.To obtain oceanic internal wave stripes from synthetic aperture radar(SAR)images,a stripe segmentation algorithm is proposed based on the TransUNet framework,which is a combination of U-Net and Transformer,which is also optimized.Through adjusting the number of Transformer layer,multi-layer perceptron(MLP)channel,and Dropout parameters,the influence of over-fitting on accuracy is significantly weakened,which is more conducive to segmenting lightweight oceanic internal waves.The results show that the optimized algorithm can accurately segment oceanic internal wave stripes.Moreover,the optimized algorithm can be trained on a microcomputer,thus reducing the research threshold.The proposed algorithm can also change the complexity of the model to adapt it to different date scales.Therefore,TransUNet has immense potential for segmenting oceanic internal waves.

Investigation of Aegilops umbellulata for stripe rust resistance,heading date,and the contents of iron,zinc,and gluten protein

Aegilops umbellulata(UU)is a wheat wild relative that has potential use in the genetic improvement of wheat.In this study,46 Ae.umbellulata accessions were investigated for stripe rust resistance,heading date(HD),and the contents of iron(Fe),zinc(Zn),and seed gluten proteins.Forty-two of the accessions were classified as resistant to stripe rust,while the other four accessions were classified as susceptible to stripe rust in four environments.The average HD of Ae.umbellulata was significantly longer than that of three common wheat cultivars(180.9 d vs.137.0 d),with the exception of PI226500(138.9 d).The Ae.umbellulata accessions also showed high variability in Fe(69.74-348.09 mg kg^(-1))and Zn(49.83-101.65 mg kg^(-1))contents.Three accessions(viz.,PI542362,PI542363,and PI554399)showed relatively higher Fe(230.96-348.09 mg kg^(-1))and Zn(92.46-101.65 mg kg^(-1))contents than the others.The Fe content of Ae.umbellulata was similar to those of Ae.comosa and Ae.markgrafii but higher than those of Ae.tauschii and common wheat.Aegilops umbellulata showed a higher Zn content than Ae.tauschii,Ae.comosa,and common wheat,but a lower content than Ae.markgrafii.Furthermore,Ae.umbellulata had the highest proportion of γ-gliadin among all the species investigated(Ae.umbellulata vs.other species=mean 72.11%vs.49.37%;range:55.33-86.99%vs.29.60-67.91%).These results demonstrated that Ae.umbellulata exhibits great diversity in the investigated traits,so it can provide a potential gene pool for the genetic improvement of these traits in wheat.

Comparison of seismic fragility analysis methods for arch dams

This study focuses on the seismic fragility analysis of arch dams.The multiple stripe analysis(MSA),cloud analysis(CLA),and incremental dynamic analysis(IDA)methods are compared.A comprehensive dam-reservoir-foundation rock system,which considers the opening of contraction joints,the nonlinearity of dam concrete and foundation rock,the radiation damping effect of semi-unbounded foundation,and the compressibility of reservoir water,is used as a numerical example.225,80,and 15 earthquake records are selected for MSA,CLA,and IDA,respectively.The results show that MSA provides satisfactory fragility analysis,while both CLA and IDA have assumptions that may lead to deviations.Therefore,MSA is the most reliable method among the three methods and is recommended for the fragility analysis of arch dams.It is also shown that the choice of demand level affects the reliability of fragility curves and the effect of the material uncertainty on the fragility of the dam is not significant.

关于左C-wrpp半群的加细半格分解

令S是左C-wrpp半群,κ是其上的等价关系,研究一类特殊左C-wrpp半群S的加细半格分解,即κ是S上的同余时,左C-wrpp半群S的加细半格分解,得到左C-wrpp半群的加细半格分解结构的等价刻画.

黄淮麦区小麦资源中高温抗条锈性品种的筛选(英文)

[Objective] The study aimed to screen wheat cultivars with high temperature resistance to stripe rust from the wheat resources in Huanghuai growth area. [Method] Seedlings of 165 wheat cultivars from Huanghuai growth area were identified by wheat stripe rust under high temperature; then the wheat cultivars showing stripe rust at seedling stage were further used to identify the same resistance in field. [Results] 13 cultivars were proved to be stripe rust resistant under high temperature, and the expression stages of stripe rust in the 13 cultivars were revealed. The field identification results confirmed the identification results at seedling stage via inoculation of mixed stripe rust of physiological races. The stripe resistances of wheat cultivars were also proved to be non-race-specific. [Conclusion] Wheat resources in Huanghuai growth area are abundant in wheat cultivars with high temperature resistance to stripe rust.

小麦条锈病气象等级预测方法研究(英文)

[Objective] The aim of this study is to establish the model for forecasting wheat stripe rust occurrence condition using meteorological factors. [Method] Based on the data of wheat stripe rust occurrence degrees in its past prevalent years and the meteorological data at corresponding periods, the methods of grey correlation analysis and fuzzy mathematics were employed to establish the forecast model for four pathogenesis indices according to the time sequence before winter, Early March, Early April and Middle May. Thus, the criterion for forecasting the occurrence degree of wheat stripe rust was obtained based on the distribution method of arithmetic progression. [Result] The model corresponding to meteorological conditions for forecasting wheat stripe rust was successfully established. According to the verification, the forecasting results before winter and in Early Mar. were more severer than the real occurrence condition, while the forecasting results in Early Apr. and Middle May were basically consistent with real values. [Conclusion] The results of the present study may avail the control of wheat stripe rust in Henan Province.