Search

Seagrass meadows are one of the most important marine ecosystems. Alkanes are the common hydrocarbon contaminants that can affect seagrass growth. In this study, a large spatial-scale investigation has been carried out on the alkane-degrading bacterial community structure in the rhizosphere and non-rhizosphere sediments of two seagrass species (Thalassia hemprichii and Halophila ovalis). AlkB gene was employed as a biomarker gene to study the alkane-degrading bacterial community structure. The results showed that the alpha diversity of the alkane-degrading bacterial community in T. hemprichii non-rhizosphere sediments was higher than that of its rhizosphere sediments. However, the alpha diversity of the alkane-degrading bacterial community in H. ovalis rhizosphere sediments was higher than that of its non-rhizosphere sediments in the open sea, but the result was contrast in the coast area. In addition, the alpha diversity of alkane-degrading bacterial communities in the coast area was higher than that of far away from the coast in the T. hemprichii rhizosphere and non-rhizosphere sediments. The phylogenetic analysis result revealed that the alkB sequences from the seagrass ecosystem were mainly affiliated with the class Alphaproteobacteria, and had the two novel lineages. Genus Agrobacterium was the most predominant alkane-degrading bacteria. These results contributed to disclose the geographical distribution pattern of alkane-degrading bacteria in the seagrass ecosystem of the South China Sea.

Seagrass meadows have seriously deteriorated in recent years. Seagrass associated phytate-mineralizing rhizobacteria potentially have functions related to seagrass nutrition, health and sustainable growth. The β-propeller phytases (BPPs) are the only phytase family in aquatic environments, but there are few studies on the BPP community structure of seagrass. In this study, clone libraries and quantitative PCR (qPCR) assays were used to compare the diversity and abundances of the BPP communities of Halodule endl, Halophila ovalis and Thalassia hemprichii in Xisha and Sanya, and to investigate the distribution characteristics of BPP genes in the rhizosphere sediment, which provedes insight into species specialty from phytic mineralization in subtropical and tropical seagrass ecosystems. The highest diversity of BPP genes was found for Thalassia hemprichii in Sanya Bay. Thalassia hemprichii in Sanya had higher abundances of BPPs, which were linked to Gammaproteobacteria. The BPP community diversity and OTUs of Thalassia hemprichii in Sanya were much higher than those of Thalassia hemprichii on Yongxing Island and Stone Island. The seagrass BPP communities had higher diversity and evenness from sampling sites with more human activity. The qPCR results showed that the abundance of phytate acid-degradating bacteria was approximately three times larger in Thalassia hemprichii rhizosphere sediment samples than in Halodule endl and Halophila ovalis rhizosphere sediment samples. This study highlighted that the diversity and abundances of bacteria genetically encoding BPP in the rhizosphere of Thalassia hemprichii were clearly higher than those of Halodule endl and Halophila ovalis. Further study of microbial phosphorus cycling will provide new insights into seagrass meadow ecosystems.

An algorithm for multipath time-delay estimation using the Gradient-type procedure to achieve the least-squares (LS) deconvolution is given to obtain a better resolution and estimation accuracy. It uses circular convolution to calculate the circulant matrix, instead of the program of traditional LS algorithm, making it more suitable to process long data. Compared with the matched filtering (MF) algorithm, it could obtain a time-delay resolution better than 1/B, and also be used in negative channels estimating.

When the near-field underwater acoustic image (UAI) measurement is carried out by the line array laid on the sea floor, the resolution of the conventional beamforming (CBF) acoustic image measurement method is poor, the sidelobe level is high, while the deconvolution algorithm has the effect of high resolution and low sidelobe. However, the direct deconvolution algorithm of the point spread function (PSF) shift-variant model has a large computational burden. This paper presents a non-uniform spatial resampling Richardson-Lucy (RL) fast algorithm, which based on energy distribution of conventional acoustic image measurement result make the original uniform space scanning to non-uniform spatial resampling. It can reduce the number of scanning grid, so as to reduce the amount of computation. Simulation results show that the fast RL algorithm can achieve the performance close to the original RL algorithm by reducing the computational amount by nearly an order of magnitude.

Item splitting is an effective approach to improve the prediction accuracy of contextual recommendations. In this approach, an item is split into two items under two alternative contextual conditions, respectively. In this work, complex splitting is proposed to get more specialised rating data and further improve the accuracy of the recommendations. The key to the approach is to select multiple contextual conditions for splitting the user or item. We translate this into a contextual conditions combinatorial optimisation problem based on a discrete binary particle swarm optimisation algorithm. The item or user is split into two different items or users according to those contextual conditions in optimal combination: one is rated in a context that meets all the contextual conditions of the best combination, and the other one is rated in a context that does not. In this way, more specialised rating data can be obtained, which results in a more accurate recommendation when the data is input into the recommendation algorithm. We evaluate our algorithm using a real-world dataset and the resulting experimental results demonstrate its validity and reliability.