BnlR:A multi-omics database with various tools for Brassica napus research and breeding

In the post-genome-wide association study era,multi-omics techniques have shown great power and poten-tial for candidate gene mining and functional genomics research.However,due to the lack of effective data integration and multi-omics analysis platforms,such techniques have not still been applied widely in rape-seed,an important oil crop worldwide.Here,we report a rapeseed multi-omics database(BnlR;http:/l yanglab.hzau.edu.cn/BnlR),which provides datasets of six omics including genomics,transcriptomics,variomics,epigenetics,phenomics,and metabolomics,as well as numerous"variation-gene expression-phenotype"associations by using multiple statistical methods.In addition,a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets.BnlR is the most comprehensive multi-omics database for rapeseed so far,and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms.

Research on recognition algorithm for gesture page turning based on wireless sensing

When a human body moves within the coverage range of Wi-Fi signals,the reflected Wi-Fi signals by the various parts of the human body change the propagation path,so analysis of the channel state data can achieve the perception of the human motion.By extracting the Channel State Information(CSI)related to human motion from the Wi-Fi signals and analyzing it with the introduced machine learning classification algorithm,the human motion in the spatial environment can be perceived.On the basis of this theory,this paper proposed an algorithm of human behavior recognition based on CSI wireless sensing to realize deviceless and over-the-air slide turning.This algorithm collects the environmental information containing upward or downward wave in a conference room scene,uses the local outlier factor detection algorithm to segment the actions,and then the time domain features are extracted to train Support Vector Machine(SVM)and eXtreme Gradient Boosting(XGBoost)classification modules.The experimental results show that the average accuracy of the XGBoost module sensing slide flipping can reach 94%,and the SVM module can reach 89%,so the module could be extended to the field of smart classroom and significantly improve speech efficiency.

BnVIR:bridging the genotype-phenotype gap to accelerate mining of candidate variations underlying agronomic traits in Brassica napus

Dear Editor,Genetic variations,which range from single nucleotide polymor-phisms(SNPs)and short insertion/deletions(InDels)to large-scale structural variations(SVs),are the basis of phenotypic diversity.Understanding the effect of genetic variations on traits is critical for uncovering the genetic architecture of various phe-notypes.

Design and analysis of a range-extended acidity detector based on a Nile red laser with tandem cuvette system

A range-extended acidity detector based on Nile red was designed and analyzed in this work. In light of the good lasing property and solvatochromism characteristic of Nile red/ethanol solution, we have obtained laser spectra of sulfuric acid in different concentrations doped in this substrate. Moreover, to expand the acidity detection range, we proposed a tandem cuvette system containing rhodamine 6G/ethanol and Nile red/ethanol. Consequently, the detection range could be enlarged from 26 nm to 40 nm, by changing not only the wavelength peak but also by the intensity ratio of dual-wavelength laser output. In addition, by changing the detection and substrate materials, the whole detection range could be expanded, and therefore a wide range of applications in polarity and acidity detection could be implemented via this method.