A unique microbiome that metabolizes lactate rather than ethanol for n-caproate production was obtained from a fermentation pit used for the production of Chinese strong-flavour liquor (CSFL). The microbiome was able to produce n-caproate at concentrations as high as 23.41 g/L at a maximum rate of 2.97 g/L/d in batch trials without in-line extraction. Compared with previous work using ethanol as the electron donor, the n-caproate concentration increased by 82.89%. High-throughput sequencing analysis showed that the microbiome was dominated by a Clostridium cluster IV, which accounted for 79.07% of total reads. A new process for n-caproate production was proposed, lactate oxidation coupled to chain elongation, which revealed new insight into the well-studied lactate conversion and carbon chain elongation. In addition, these findings indicated a new synthesis mechanism of n-caproate in CSFL. We believe that this efficient process will provide a promising opportunity for the innovation of waste recovery as well as for n-caproate biosynthesis.

Abstract-Given a set of objects and a query q, a point p is called the reverse k nearest neighbor (RkNN) of q if q is one of the k closest objects of p. In this paper, we introduce the concept of influence zone which is the area such that every point inside this area is the RkNN of q and every point outside this area is not the RkNN. The influence zone has several applications in location based services, marketing and decision support systems. It can also be used to efficiently process RkNN queries. First, we present efficient algorithm to compute the influence zone. Then, based on the influence zone, we present efficient algorithms to process RkNN queries that significantly outperform existing best known techniques for both the snapshot and continuous RkNN queries. We also present a detailed theoretical analysis to analyse the area of the influence zone and IO costs of our RkNN processing algorithms. Our experiments demonstrate the accuracy of our theoretical analysis.

The origins of cultivated chrysanthemums have attracted considerable attention, but they remain poorly known. Here, we reconstructed the phylogeny of representative well-known cultivars and wild species of the genus Chrysanthemum using chloroplast genomes and the nuclear LEAFY gene. Our results suggest that geographic and ecological factors may determine the opportunities for wild species to be involved in the origin of the cultivars. The wild species C. indicum, C. zawadskii, C. dichrum, C. nankingense, C. argyrophyllum, and C. vestitum were likely directly or indirectly involved as paternal species of most of the chrysanthemum cultivars examined in this study. Yet, the maternal species is supported to be a lineage of an extinct wild Chrysanthemum species and its subsequent cultivars, as all accessions of chrysanthemum cultivars sampled formed a strongly supported clade, distinct from all other species of Chrysanthemum in the plastome tree. Thus, the cultivated chrysanthemums originated from multiple hybridizations involving several paternal species rather than only two or a few wild species, with an extinct species and its subsequent cultivars serving as the maternal parents. This finding is consistent with Chrysanthemum having high rates of hybridization and gene flow, which has been demonstrated within previous studies; nevertheless, it is important to unravel the role of an extinct wild Chrysanthemum species as the ultimate maternal parent species for all the chrysanthemum cultivars. Our results also suggest that C. vestitum from Tianzhu and Funiu Mountains in Anhui and Henan Provinces of China represent two distinct cryptic species.

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Abstract-Skyline computation has many applications including multi-criteria decision making. In this paper, we study the problem of efficient processing of continuous skyline queries over sliding windows on uncertain data elements regarding given probability thresholds. We first characterize what kind of elements we need to keep in our query computation. Then we show the size of dynamically maintained candidate set and the size of skyline. We develop novel, efficient techniques to process a continuous, probabilistic skyline query. Finally, we extend our techniques to the applications where multiple probability thresholds are given or we want to retrieve "top-k" skyline data objects. Our extensive experiments demonstrate that the proposed techniques are very efficient and handle a high-speed data stream in real time.