With the advent of next-generation sequencing technology, it has become convenient and cost efficient to thoroughly characterize the microbial diversity and taxonomic composition in various environmental samples. Millions of sequencing data can be generated, and how to utilize this enormous sequence resource has become a critical concern for microbial ecologists. One particular challenge is the OTUs (operational taxonomic units) picking in 16S rRNA sequence analysis. Lucky, this challenge can be directly addressed by sequence clustering that attempts to group similar sequences. Therefore, numerous clustering methods have been proposed to help to cluster 16S rRNA sequences into OTUs. However, each method has its clustering mechanism, and different methods produce diverse outputs. Even a slight parameter change for the same method can also generate distinct results, and how to choose an appropriate method has become a challenge for inexperienced users. A lot of time and resources can be wasted in selecting clustering tools and analyzing the clustering results. In this study, we introduced the recent advance of clustering methods for OTUs picking, which mainly focus on three aspects: (i) the principles of existing clustering algorithms, (ii) benchmark dataset construction for OTU picking and evaluation metrics, and (iii) the performance of different methods with various distance thresholds on benchmark datasets. This paper aims to assist biological researchers to select the reasonable clustering methods for analyzing their collected sequences and help algorithm developers to design more efficient sequences clustering methods.

SUMMARYA next-generation network (NGN) is an advanced network that exploits multiple broadband and QoSenabled transport technologies to provide telecommunication services. The principles and requirements of convergence of wireless sensor networks are likely to deliver all the desired benefits of NGN and should be carefully studied.In this paper, we focus on the power consumption topic, which is a fundamental concern in wireless multimedia sensor networks (WMSNs). Node placement in WMSNs has considerable impact on network lifetime. In this paper, we have investigated and developed a power-efficient node placement scheme (PENPS) in linear WMSNs, which can minimize the average energy consumption per node and maximize the network lifetime. The analysis of PENPS and the comparison of performance with the equal-spaced placement scheme (EPS) show that PENPS scheme can significantly decrease the average energy consumption per node, which can prolong the lifetime of sensor nodes and sensor networks effectively. Copyright q

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