Tuning field emission properties of boron nanocones with catalyst concentration

Single crystalline boron nanocones are prepared by using a simple spin spread method in which Fe3O4 nanoparticles are pre-manipulated on Si（lll） to form catalyst patterns of different densities. The density of boron nanocones can be tuned by changing the concentration of catalyst nanoparticles. High-resolution transmission electron microscopy analysis shows that the boron nanocone has a β-tetragonal structure with good crystallization. The field emission behaviour is optimal when the spacing distance is close to the nanocone length, which indicates that this simple spin spread method has great potential applications in electron emission nanodevices.

A method of multichannel chaotic phase modulation spread spectrum and its application in underwater acoustic communication

Direct-sequence spread spectrum （DSSS） communication possesses low probability of detection and has been widely used in confidential communications. However, pseudo-noise （PN） sequences, used as spreading code in conventional DSSS communications, possess peri- odic character and binary value. In hostile environments, these distinct characters may lead to some important parameters of signals being estimated accurately, and then lead to the leakage of transmitted information. To solve the problem, we propose the chaotic phase modulation （CPM） sequence alternating the PN sequences. CPM sequence has complex values and constant envelope, and also possesses large quantity and good correlation characteristics. Moreover, it has more hidden features than conventional sequences by modulating its phases using chaotic sequence. To improve the data rate, we apply it into the technique of multichannel communica-tion. Simulation results show this scheme＇s superior bit error ratio （BER） performance, which demonstrates its feasibility in underwater acoustic communications.

Qualitative and quantitative uncertainties in regional rainfall frequency analysis

Uncertainty exists widely in hydrological analysis, and this makes the process of uncertainty assessment very im- portant for making robust decisions. In this study, uncertainty sources in regional rainfall frequency analysis are identified for the first time. The numeral unite spread assessment pedigree （NUSAP） method is introduced and is first employed to quantify qual- itative uncertainty in regional rainfall frequency analysis. A pedigree matrix is particularly designed for regional rainfall frequency analysis, by which the qualitative uncertainty can be quantified. Finally, the qualitative and quantitative uncertainties are com- bined in an uncertainty diagnostic diagram, which makes the uncertainty evaluation results more intuitive. From the integrated diagnostic diagram, it can be determined that the uncertainty caused by the precipitation data is the smallest, and the uncertainty from different grouping methods is the largest. For the downstream sub-region, a generalized extreme value （GEV） distribution is better than a generalized logistic （GLO） distribution; for the south sub-region, a Pearson type III （PE3） distribution is the better choice; and for the north sub-region, GEV is more appropriate.