Genome-wide analysis of the synonymous codon usage patterns in apple

Apple（Malus×domestica） has been proposed as an important woody plant and the major cultivated fruit trees in temperate regions. Apple whole genome sequencing has been completed, which provided an excellent opportunity for genome-wide analysis of the synonymous codon usage patterns. In this study, a multivariate bioinformatics analysis was performed to reveal the characteristics of synonymous codon usage and the main factors affecting codon bias in apple. The neutrality, correspondence, and correlation analyses were performed by Codon W and SPSS（Statistical Product and Service Solutions） programs, indicating that the apple genome codon usage patterns were affected by mutational pressure and selective constraint. Meanwhile, coding sequence length and the hydrophobicity of proteins could also influence the codon usage patterns. In short, codon usage pattern analysis and determination of optimal codons has laid an important theoretical basis for genetic engineering, gene prediction and molecular evolution studies in apple.

Analysis of temporal and spatial usage patterns of dockless bike sharing system around rail transit station area

In order to study the spatiotemporal characteristics of the dockless bike sharing system(BSS)around urban rail transit stations,new normalized calculation methods are proposed to explore the temporal and spatial usage patterns of the dockless BSS around rail transit stations by using 5-weekday dockless bike sharing trip data in Nanjing,China.First,the rail transit station area(RTSA)is defined by extracting shared bike trips with trip ends falling into the area.Then,the temporal and spatial decomposition methods are developed and two criterions are calculated,namely,normalized dynamic variation of bikes(NDVB)and normalized spatial distribution of trips(NSDT).Furthermore,the temporal and spatial usage patterns are clustered and the corresponding geographical distributions of shared bikes are determined.The results show that four temporal usage patterns and two spatial patterns of dockless BSS are finally identified.Area type(urban center and suburb)has a great influence on temporal usage patterns.Spatial usage patterns are irregular and affected by limited directions,adjacent rail transit stations and street networks.The findings can help form a better understanding of dockless shared bike users behavior around rail transit stations,which will contribute to improving the service and efficiency of both rail transit and BSS.

Exploring the user platform preference and user interest preference of Chinese scholarly articles:A comparison based on usage metrics

In order to comparatively investigate usage patterns of journal official sites and pay-for-access platform and then to support decision-making,this study selected academic papers,published during 2014-2015,of 61 Chinese open access journals indexed by CSSCI and CSCD in eight disciplines,"Library,Information and Archival Science","Management Science","Economics","Pedagogy","Computer Science","Earth Science","Math"and"Biology".Chinese usage patterns in user platform preferences and user interest preferences were explored by analyzing usage data from journal official sites and pay-for-access platforms.Operatively,comparisons of user platform preferences were implemented by descriptive statistics and correlation analysis and comparisons of user interest preferences were explored by Jaccard similarity coefficient and co-word analysis.It proved that there were differences in user platform preferences and user interest preferences between journal official sites and pay-for-access platforms.However,factors that affect usage patterns were very complicated.How to probe into the mechanism of contributory factors and then verify them was still an important problem to be solved in further study.

SOCIAL TAGGING DYNAMICS UNDER SYSTEM RECOMMENDATION AND RESOURCE MULTIDIMENSIONALITY

Social tagging systems have attracted plenty of research endeavors recently. The dynamic models of tag generation or tag usage are one of the key subjects of inquiry. However, the existing models do not well explain the ＂staged＂ power-law distribution of tag usage frequencies as observed in various social tagging systems. To cope with this, a new tag-generation model is proposed in this paper, which is based on a preferential selection mechanism influenced by the combinatorial effects of system recommendation and resource multidimensionality. Furthermore, to validate the model, the simulative results under different parameter combinations are compared with the distributions of tag usage frequencies in datasets from three famous social tagging systems, namely Delicious.com, Last.fin and Flickr. For different categories of resources of the three systems, three tag usage patterns can be identified, namely the power-law distribution with two plateaus, the power-law distribution with one plateau, and the standard power-law distribution. All the three patterns can be well fitted and explained by the proposed model.

An Investigation of English Articles' Acquisition by Chinese Learners of English

英语冠词习得过程是二语习得领域研究热点之一。本研究调查了高级,中级,中下英语水平学习者对英语冠词的掌握情况,研究结果表明中国学生英语冠词的使用正确率从高到低排序为:the,a/an,Φ。中级及中下级英语水平学习者存在the与a/an使用过度而零冠词使用不足的情况;高级水平者倾向于将零冠词泛化。不同语境中冠词运用正确率的对比分析表明:中级水平者类指名词前以及固定搭配中冠词的运用相对困难;高级水平者[-HK](假定听话者未知)语境中的冠词用法掌握较差。本研究对英语冠词教学有一定的启示作用。

A scheduling algorithm with dynamic properties in mobile grid

Mobile grid is a branch of grid computing that incorporates mobile devices into the grid infrastructure. It poses new challenges because mobile devices are typically resource-constrained and exhibit unique characteristics such as instability in network connections. New scheduling strate- gies are imperative in mobile grid to efficiently utilize the devices. This paper presents a scheduling algorithm that con- siders dynamic properties of mobile devices such as avail- ability, reliability, maintainability, and usage pattern in mo- bile grid environments. In particular, usage patterns caused by voluntarily or involuntarily losing a connection, such as switching off the device or a network interruption could be important criteria for choosing the best resource to execute a job. The experimental results show that our scheduling al- gorithm provides superior performance in terms of execution time, as compared to the other methods that do not consider usage pattern. Throughout the experiments, we found it es- sential to consider usage pattern for improving performance in the mobile grid.

Storage capacity model for cloud download

With the rise and world wide deployment of cloud utilities, the principle of the cloud download is proposed to provide high-quality file content distribution by using dedicated servers as cloud cache to guarantee the data availability and enhance the data transfer rate. As the system scales up to a large population, how to design appropriate storage capacity of cloud cache is a key challenge for cloud download. In this paper, primary elements impacting on storage capacity are explored through deliberating in large-scale commercial cloud download system, i.e. general user usage pattern and available period. And based on statistical analysis of real-world traces, we formulate storage capacity related to these two elements, which is the original contribution different from all previous works. This model gives guidance of potential system policy design. Finally, the effectivity of this model is demonstrated by simulation results compared with empirical data of practical system.