We propose the tracking of long duration flows as a new network measurement primitive. Long-duration flows are characterized by their long lived nature in time, and may not have high traffic volumes. We propose an efficient data streaming algorithm to effectively track long duration flows. Our basic technique is to maintain only two Bloom filters at any given time. In each time duration, only old flows that appear in the current time duration get copied to the current Bloom filter. Our basic algorithm is further enhanced by sampling. Using real network traces, we show that our tracking algorithm is very accurate with low false positive and false negative probabilities. Using multi-faceted analysis, we show that more than 50% of hosts participating in long duration flows (duration no less than 30 minutes) are blacklisted by various public sources.

BackgroundCupressus gigantea, a rare and endangered tree species with remarkable medicinal value, is endemic to the Tibetan Plateau. Yet, little is known about the underlying genetics of the unique ecological adaptability of this extremely long-lived conifer with a large genome size. Here, we present its first de novo and multi-tissue transcriptome in-depth characterization.ResultsWe performed Illumina paired-end sequencing and RNA libraries assembly derived from terminal buds, male and female strobili, biennial leaves, and cambium tissues taken from adult C. gigantea. In total, large-scale high-quality reads were assembled into 101,092 unigenes, with an average sequence length of 1029 bp, and 6848 unigenes (6.77%) were mapped against the KEGG databases to identify 292 pathways. A core set of 41,373 genes belonging to 2412 orthologous gene families shared between C. gigantea and nine other plants was revealed. In addition, we identified 2515 small to larger-size gene families containing in total 9223 genes specific to C. gigantea, and enriched for gene ontologies relating to biotic interactions. We identified an important terpene synthases gene family expansion with its 121 putative members.ConclusionsThis study presents the first comprehensive transcriptome characterization of C. gigantea. Our results will facilitate functional genomic studies to support genetic improvement and conservation programs for this endangered conifer.Electronic supplementary materialThe online version of this article (10.1186/s12864-019-5584-6) contains supplementary material, which is available to authorized users.

Faecalibacterium prausnitzii is a beneficial human gut microbe and a candidate for next-generation probiotics. With probiotics now being used in clinical treatments, concerns about their safety and side effects need to be considered. Therefore, it is essential to obtain a comprehensive understanding of the genetic diversity, functional characteristics, and potential risks of different F. prausnitzii strains. In this study, we collected the genetic information of 84 F . prausnitzii strains to conduct a pan-genome analysis with multiple perspectives. Based on single-copy genes and the sequences of 16S rRNA and the compositions of the pan-genome, different phylogenetic analyses of F. prausnitzii strains were performed, which showed the genetic diversity among them. Among the proteins of the pan-genome, we found that the accessory clusters made a greater contribution to the primary genetic functions of F. prausnitzii strains than the core and specific clusters. The functional annotations of F. prausnitzii showed that only a very small number of proteins were related to human diseases and there were no secondary metabolic gene clusters encoding harmful products. At the same time, complete fatty acid metabolism was detected in F. prausnitzii. In addition, we detected harmful elements, including antibiotic resistance genes, virulence factors, and pathogenic genes, and proposed the probiotic potential risk index (PPRI) and probiotic potential risk score (PPRS) to classify these 84 strains into low-, medium-, and high-risk groups. Finally, 15 strains were identified as low-risk strains and prioritized for clinical application. Undoubtedly, our results provide a comprehensive understanding and insight into F. prausnitzii, and PPRI and PPRS can be applied to evaluate the potential risks of probiotics in general and to guide the application of probiotics in clinical application.