Genome assembly of KA105,a new resource for maize molecular breeding and genomic research

Superior inbred lines are central to maize breeding as sources of natural variation.Although many elite lines have been sequenced,less sequencing attention has been paid to newly developed lines.We constructed a genome assembly of the elite inbred line KA105,which has recently been developed by an arti-ficial breeding population named Shaan A and has shown desirable characteristics for breeding.Its pedigree showed genetic divergence from B73 and other lines in its pedigree.Comparison with the B73 reference genome revealed extensive structural variation,58 presence/absence variation(PAV)genes,and 1023 expanded gene families,some of which may be associated with disease resistance.A network-based integrative analysis of stress-induced transcriptomes identified 13 KA105-specific PAV genes,of which eight were induced by at least one kind of stress,participating in gene modules responding to stress such as drought and southern leaf blight disease.More than 200,000 gene pairs were differentially correlated between KA105 and B73 during kernel development.The KA105 reference genome and transcriptome atlas are a resource for further germplasm improvement and surveys of maize genomic variation and gene function.

Differential gene network analysis from single cell RNA-seq

Study of gene expression has been arguably the most active research field in functional genomics.Over the last two decades,various high-throughput technologies,from gene expression microarray to RNA-seq,have been widely applied to the wholegenome profiling of gene expression.The commonality of these experiments is that they measure the gene expression levels of"bulk"sample,which pools a large number(often in the scale of millions)of cells,and thus the measurements reflect the average expression

PID Neural Net work Decoupling Control Based on Hybrid Particle Swarm Optimization and Differential Evolution

For complex systems with high nonlinearity and strong coupling,the decoupling control technology based on proportion integration differentiation(PID)neural network(PIDNN)is used to eliminate the coupling between loops.The connection weights of the PIDNN are easy to fall into local optimum due to the use of the gradient descent learning method.In order to solve this problem,a hybrid particle swarm optimization(PSO)and differential evolution(DE)algorithm(PSO-DE)is proposed for optimizing the connection weights of the PIDNN.The DE algorithm is employed as an acceleration operation to help the swarm to get out of local optima traps in case that the optimal result has not been improved after several iterations.Two multivariable controlled plants with strong coupling between input and output pairs are employed to demonstrate the effectiveness of the proposed method.Simulation results show t hat the proposed met hod has better decoupling capabilities and control quality than the previous approaches.

A novel differentiated services supporting scheme for optical burst switched networks

In this letter, we analyze the drawback of tail-dropping contention resolution in optical burst switched networks. Once contention occurs, we adopt modified head-dropping policy to resolve contention. This policy drops the head of the contending burst only if the overlapping region of the two bursts is less than the whole contending burst size, otherwise drops the whole contending burst. In order to have a better support of differentiated service, a new burst assembly policy, namely, Priority-based proportional mixed burst assembly, is proposed. Simulation results show that the proposed scheme performs very well in terms of performance metrics such as the times of contention and packet loss probability.

Priority-Based Mixed Assembly Supporting Differentiated Service for Optical Burst Switched Networks

In order to have a better support of differentiated service, we propose Priority-based mixed burst assembly, in which packets of different priorities are assembled in a burst with an assigned proportion, and the priorities are lined in an ascending order in a burst from head to tail. Simulation results show that the proposed scheme performs very well in terms of latency and packet loss probability.

A Teletraffic Model for Service Differentiation in OPS Networks

This paper present a formal teletraffic model for service diferentiation in optical packet switched networks by utilizing the wavelength domain.Expressions for the time congestion are derived.Simulation results are also reported.

A Hybrid Mathematical Model of Tumor-Induced Angiogenesis with Blood Perfusion

Angiogenesis, the growth of new blood vessel from existing ones, is a pivotal stage in cancer development,and is an important target for cancer therapy. We develop a hybrid mathematical model to understand the mechanisms behind tumor-induced angiogenesis. This model describes uptake of Tumor Angiogenic Factor（TAF）at extracellular level, uses partial differential equation to describe the evolution of endothelial cell density including TAF induced proliferation, chemotaxis to TAF, and haptotaxis to extracellular matrix. In addition we also consider the phenomenon of blood perfusion in the micro-vessels. The model produces sprout formation with realistic morphological and dynamical features, including the so-called brush border effect, the dendritic branching and fusing of the capillary sprouts forming a vessel network. The model also demonstrates the effects of individual mechanisms in tumor angiogenesis： Chemotaxis to TAF is the key driving mechanisms for the extension of sprout cell; endothelial proliferation is not absolutely necessary for sprout extension; haptotaxis to Extra Cellular Matrix（ECM） gradient provides additional guidance to sprout extension, suggesting potential targets for anti-angiogenic therapies.