The genus Paris in the broad concept is an economically important group in the monocotyledonous family Melanthiaceae (tribe Parideae). The phylogeny of Paris was controversial in previous morphology-based classification and molecular phylogeny. Here, the complete cp genomes of eleven Paris taxa were sequenced, to better understand the evolutionary relationships among these plants and the mutation patterns in their chloroplast (cp) genomes. Comparative analyses indicated that the overall cp genome structure among the Paris taxa is quite similar. The triplication of trnI-CAU was found only in the cp genomes of P. quadrifolia and P. verticillata. Phylogenetic analyses based on the complete cp genomes did not resolve Paris as a monophyletic group, instead providing evidence supporting division of the twelve taxa into two segregate genera: Paris sensu strict and Daiswa. The sister relationship between Daiswa and Trillium was well supported. We recovered two fully supported lineages with divergent distribution in Daiswa; however, none of the previously recognized sections in Daiswa was resolved as monophyletic using plastome data, suggesting that the infrageneric relationships and biogeography of Daiswa species require further investigation. Ten highly divergent DNA regions, suitable for species identification, were detected among the 12 cp genomes. This study is the first successful attempt to provide well-supported evolutionary relationships in Paris based on phylogenomic analyses. The findings highlight the potential of the whole cp genomes for improving resolution in phylogeny as well as species identification in phylogenetically and taxonomically difficult plant genera.

Paris Linnaeus (1573: 367) is a temperate genus of about 27 species of perennial herbs distributed in Eurasia (Li 1998, Ji et al. 2007). Most species are restricted to East Asia, chiefly to China (19 species), with the Yunnnan-Guizhou Plateau in southwest China as the centre of species diversity (Li 1998). Paris is well known in China for its medicinal value. Those species with a thick rhizome have been used as medicinal herbs for more than 2,000 years in China owing to its analgesic, haemostatic, anti-tumor, and anti-inflammatory activities (Long et al. 2003). More than 40 commercial drugs and health products have been developed in China with Paris used as raw material (Li et al. 2015).

Paris variabilis, a new species from the Wumengshan Mountains, southwestern China, is described and illustrated. The new species is placed in Paris section Euthyra. The new taxon was determined to be most morphologically similar to P. vietnamensis but differs in its oblong leaf blades with an acute apex, stamens 2–4 × petal number, greenish yellow filaments and an enlarged, purplish red style base. The phylogenetic placement of this species was assessed based on nuclear ribosomal ITS DNA sequences data. The results of morphological and phylogenetic analyses support the status of the taxon as a new species.

The detection and recognition of traffic signal image is an important content in intelligent transportation system. It can be applied to driver assistance system to effectively recognize traffic signal signs on the road, so as to reduce the occurrence of traffic accidents. At the same time, it also provides strong technical support for the future unmanned driving system. The main content of this paper is based on the deep learning method, using YOLOv3 and YOLOv4 algorithm to detect and recognize the traffic signal image on the road. The experimental results show that the recognition result of YOLOv4 network is better than that of YOLOv3 network.

Counting the number of distinct elements distributed over multiple data holders is a fundamental problem with many real-world applications ranging from crowd counting to network monitoring. Although a number of space and computationally efficient sketch methods (e.g., the Flajolet-Martin sketch and the HyperLogLog sketch) for cardinality estimation have been proposed to solve the above problem, these sketch methods are insecure when considering privacy concerns related to the use of each data holder's personal dataset. Despite a recently proposed protocol that successfully implements the well-known Flajolet-Martin (FM) sketch on a secret-sharing based multiparty computation (MPC) framework for solving the problem of private distributed cardinality estimation (PDCE), we observe that this MPC-FM protocol is not differentially private. In addition, the MPC-FM protocol is computationally expensive, which limits its applications to data holders with limited computation resources. To address the above issues, in this paper we propose a novel protocol DP-DICE, which is computationally efficient and differentially private for solving the problem of PDCE. Experimental results show that our DP-DICE achieves orders of magnitude speedup and reduces the estimation error by several times in comparison with state-of-the-arts under the same security requirements.

Counting the number of distinct elements distributed over multiple data holders is a fundamental problem with many real-world applications ranging from crowd counting to network monitoring. Although a number of space and computationally efficient sketch methods (e.g., the Flajolet-Martin sketch and the HyperLogLog sketch) for cardinality estimation have been proposed to solve the above problem, these sketch methods are insecure when considering privacy concerns related to the use of each data holder's personal dataset. Despite a recently proposed protocol that successfully implements the well-known Flajolet-Martin (FM) sketch on a secret-sharing based multiparty computation (MPC) framework for solving the problem of private distributed cardinality estimation (PDCE), we observe that this MPC-FM protocol is not differentially private. In addition, the MPC-FM protocol is computationally expensive, which limits its applications to data holders with limited computation resources. To address the above issues, in this paper we propose a novel protocol DP-DICE, which is computationally efficient and differentially private for solving the problem of PDCE. Experimental results show that our DP-DICE achieves orders of magnitude speedup and reduces the estimation error by several times in comparison with state-of-the-arts under the same security requirements.

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Background Paris yunnanensis (Melanthiaceae) is a traditional Chinese medicinal plant of significant pharmaceutical importance. Due to previous taxonomic confusion, a congeneric species, Paris liiana, has been mistaken for P. yunnanensis and cultivated on a large scale, leading to the mixing of commercial products (i.e., seedlings and processed rhizomes) of P. yunnanensis with those of P. liiana. This may have adverse effects on quality control in the standardization of P. yunnanensis productions. As the lack of PCR amplifiable genomic DNA within processed rhizomes is an intractable obstacle to the authentication of P. yunnanensis products using PCR-based diagnostic tools, this study aimed to develop a PCR-free method to authenticate commercial P. yunnanensis products, by applying genome skimming to generate complete plastomes and nrDNA arrays for use as the molecular tags. Results Based on a dense intraspecies sampling of P. liiana and P. yunnanensis, the robustness of the proposed authentication systems was evaluated by phylogenetic inferences and experimental authentication of commercial seedling and processed rhizome samples. The results indicate that the genetic criteria of both complete plastomes and nrDNA arrays were consistent with the species boundaries to achieve accurate discrimination of P. yunnanensis and P. liinna. Owing to its desirable accuracy and sensitivity, genome skimming can serve as an effective and sensitive tool for monitoring and controlling the trade of P. yunnanensis products. Conclusion This study provides a new way to solve the long-standing problem of the molecular authentication of processed plant products due to the lack of PCR amplifiable genomic DNA. The proposed authentication system will support quality control in the standardization of P. yunnanensis products in cultivation and drug production. This study also provides molecular evidence to clarify the long-standing taxonomic confusion regarding the species delimitation of P. yunnanensis, which will contribute to the rational exploration and conservation of the species.