Millimetre-wave (mmWave) technology continues to draw great interest due to its broad applications in wireless communications, radar, and spectroscopy. Compared to pure electronic solutions, photonic-based mmWave generation provides wide bandwidth, low power dissipation, and remoting through low-loss fibres. However, at high frequencies, two major challenges exist for the photonic system: the power roll-off of the photodiode, and the large signal linewidth derived directly from the lasers. Here, we demonstrate a new photonic mmWave platform combining integrated microresonator solitons and high-speed photodiodes to address the challenges in both power and coherence. The solitons, being inherently mode-locked, are measured to provide 5.8 dB additional gain through constructive interference among mmWave beatnotes, and the absolute mmWave power approaches the theoretical limit of conventional heterodyne detection at 100 GHz. In our free-running system, the soliton is capable of reducing the mmWave linewidth by two orders of magnitude from that of the pump laser. Our work leverages microresonator solitons and high-speed modified uni-traveling carrier photodiodes to provide a viable path to chip-scale, high-power, low-noise, high-frequency sources for mmWave applications.

Lakes receive large amounts of terrestrially derived dissolved organic matter (tDOM). However, little is known about how aquatic microbial communities interact with tDOM in lakes. Here, by performing microcosm experiments we investigated how microbial community responded to tDOM influx in six Tibetan lakes of different salinities (ranging from 1 to 358 g/l). In response to tDOM addition, microbial biomass increased while dissolved organic carbon (DOC) decreased. The amount of DOC decrease did not show any significant correlation with salinity. However, salinity influenced tDOM transformation, i.e., microbial communities from higher salinity lakes exhibited a stronger ability to utilize tDOM of high carbon numbers than those from lower salinity. Abundant taxa and copiotrophs were actively involved in tDOM transformation, suggesting their vital roles in lacustrine carbon cycle. Network analysis indicated that 66 operational taxonomic units (OTUs, affiliated with Alphaproteobacteria , Actinobacteria , Bacteroidia , Bacilli , Gammaproteobacteria , Halobacteria , Planctomycetacia , Rhodothermia , and Verrucomicrobiae ) were associated with degradation of CHO compounds, while four bacterial OTUs (affiliated with Actinobacteria, Alphaproteobacteria, Bacteroidia and Gammaproteobacteria ) were highly associated with the degradation of CHOS compounds. Network analysis further revealed that tDOM transformation may be a synergestic process, involving cooperation among multiple species. In summary, our study provides new insights into a microbial role in transforming tDOM in saline lakes and has important implications for understanding the carbon cycle in aquatic environments.

With the rapid development of biomedical sciences, a great number of documents have been published to report new scientific findings and advance the process of knowledge discovery. By the end of 2013, the largest biomedical literature database, MEDLINE, has indexed over 23 million abstracts. It is thus not easy for scientific professionals to find experts on a certain topic in the biomedical domain. In contrast to the existing services that use some ad hoc approaches, we developed a novel solution to biomedical expert finding, BMExpert, based on the language model. For finding biomedical experts, who are the most relevant to a specific topic query, BMExpert mines MEDLINE documents by considering three important factors: relevance of documents to the query topic, importance of documents, and associations between documents and experts. The performance of BMExpert was evaluated on a benchmark dataset, which was built by collecting the program committee members of ISMB in the past three years (2012-2014) on 14 different topics. Experimental results show that BMExpert outperformed three existing biomedical expert finding services: JANE, GoPubMed, and eTBLAST, with respect to both MAP (mean average precision) and P@50 (Precision). BMExpert is freely accessed at http://datamining-iip.fudan.edu.cn/service/BMExpert/.

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