An implementation of cellular automaton model for single-line train working diagram

According to the railway transportation system＇s characteristics, a new cellular automaton model for the single- line railway system is presented in this paper. Based on this model, several simulations were done to imitate the train operation under three working diagrams. From a different angle the results show how the organization of train operation impacts on the railway carrying capacity. By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest. Many slow-trains have to wait in-between neighbouring stations to let the fast-train（s） pass through first. So the slow-train will advance like a wave propagating from the departure station to the arrival station. This also resembles the situation of a highway jammed traffic flow. Furthermore, the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity. After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged, all three carrying capacities are improved greatly as shown by simulation. It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transportation system.

Water and nitrogen transport characteristics of single-line interference infiltration under film hole irrigation with muddy water and fertilizer

Based on the experimental data,this study investigated the effect of sand content of muddy water on water and nitrogen transport characteristics of the single-line interference infiltration under film hole irrigation with muddy water and fertilizer.The relationship between the single-line interference infiltration parameters,the sand content,the wetting front movement distances,and the sand content were all established.The model of the cumulative infiltration volume of per unit film pore area,the vertical and horizontal wetting front movement distance of the free surface,and the wetting front movement distance of the interference center with sand content and infiltration time were proposed.Reveal the law of the change of soil water content and the distribution of NO_(3)^(-)-N content based on different muddy water sand content.The results indicate that at the same infiltration time,as the muddy water sand content increases,the cumulative infiltration volume per unit pore area decreases.The infiltration index of the free infiltration and the single-line interference vary little when the sand content increases,mainly are around 0.64 and 0.58.The relationship between infiltration parameters a,b and the sand content is linear function.At the same location,the more the sand content,the smaller the wetting front movement distance in free surface and the single-line interference surface,the less the NO_(3)^(-)-N content.

An improved Gmapping algorithm based map construction method for indoor mobile robot

With the rapid development in the service,medical,logistics and other industries,and the increasing demand for unmanned mobile devices,mobile robots with the ability of independent mapping,localization and navigation capabilities have become one of the research hotspots.An accurate map construction is a prerequisite for a mobile robot to achieve autonomous localization and navigation.However,the problems of blurring and missing the borders of obstacles and map boundaries are often faced in the Gmapping algorithm when constructing maps in complex indoor environments.In this pursuit,the present work proposes the development of an improved Gmapping algorithm based on the sparse pose adjustment(SPA)optimizations.The improved Gmapping algorithm is then applied to construct the map of a mobile robot based on single-line Lidar.Experiments show that the improved algorithm could build a more accurate and complete map,reduce the number of particles required for Gmapping,and lower the hardware requirements of the platform,thereby saving and minimizing the computing resources.

Multivariate competing endogenous RNA network characterization for cancer microRNA biomarker discovery:a novel bioinformatics model with application to prostate cancer metastasis

Background:MicroRNAs(miRNAs)are post-transcriptional regulators with potential as biomarkers for cancer management.Datadriven competing endogenous RNA(ceRNA)network modeling is an effective way to decipher the complex interplay between miRNAs and spongers.However,there are currently no general rules for ceRNA network-based biomarker prioritization.Methods and results:In this study,a novel bioinformatics model was developed by integrating gene expression with multivariate miRNA-target data for ceRNA network-based biomarker discovery.Compared with traditional methods,the structural vulnerability in the human long non-coding RNA(lncRNA)–miRNA–messenger RNAs(mRNA)network was comprehensively analyzed,and the single-line regulatory or competing mode among miRNAs,lncRNAs,and mRNAs was characterized and quantified as statistical evidence for miRNA biomarker identification.The application of this model to prostate cancer(PCa)metastasis identified a total of 12 miRNAs as putative biomarkers from the metastatic PCa-specific lncRNA–miRNA–mRNA network and nine of them have been previously reported as biomarkers for PCa metastasis.The receiver operating characteristic curve and cell line qRT-PCR experiments demonstrated the power of miR-26b-5p,miR-130a-3p,and miR-363-3p as novel candidates for predicting PCa metastasis.Moreover,PCa-associated pathways such as prostate cancer signaling,ERK/MAPK signaling,and TGF-βsignaling were significantly enriched by targets of identified miRNAs,indicating the underlying mechanisms of miRNAs in PCa carcinogenesis.Conclusions:A novel ceRNA-based bioinformatics model was proposed and applied to screen candidate miRNA biomarkers for PCa metastasis.Functional validations using human samples and clinical data will be performed for future translational studies on the identified miRNAs.