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Understanding large-scale patterns of biodiversity and their drivers remains significant in biogeography. Cherries species (Prunus subgenus Cerasus, Rosaceae) are economically and ecologically important in ecosystems and human agricultural activities. However, the mechanisms underlying the patterns of the species richness–environment relationship in Cerasus remain poorly understood. We collected and filtered worldwide specimen data to map the species richness of Cerasus at the global scale. The map of Cerasus species richness was created using 21,043 reliable recorded specimens. The center of Cerasus diversity was determined using spatial cluster analysis. Stepwise regression analysis was carried out using five groups of 21 environmental variables and an integrated model was included to assess the impact of the overall environment. We calibrated each of the four integrated models and used them to predict the global Cerasus species richness and that of the other continents. Our results revealed that Cerasus species have two centers of diversity (the southwest of China and Honshu Island in Japan) with differing environmental variables influencing the distribution patterns of these two centers. In the southwest of China, hygrothermal conditions are the main driving factor while in Japan, habitat heterogeneity is the main driving factor. The relationship between the abundance of Cerasus and the various groups of factors generally supports both the productivity and the habitat heterogeneity hypotheses. However, these hypotheses do not fully explain the Cerasus species richness pattern, indicating that other factors such as historical environment, topography, and human activities likely played a role in pattern formation. The high level of habitat heterogeneity and better hygrothermal conditions may have played an important role in the establishment of its globally consistent richness–climate relationship. Our results can provide valuable information for the classification and conservation of Cerasus natural resources as well as contribute to furthering our understanding of biogeography at a global scale. [ABSTRACT FROM AUTHOR]

As an effective way to accommodate the distributed renewable energy, microgrid participating in the electricity market competition is an inevitable trend. Because of severe uncertainty and poor dispatchability of the distributed renewable energy in the microgrid, how to counterbalance the deviation between microgrid's actual output/demand and cleared quantity from the market is an important issue needed to address. First, a multi‐energy trading framework is introduced where microgrids bid in a distribution electricity market (DEM). An arbitrageur is presented to buy and sell electricity between the DEM and the day‐ahead wholesale market (DAWM). In order to compensate the bid deviations of microgrids with uncertain output/demand in the DEM, the power to gas (P2G) technologies are applied by a microgrid when it has excess electricity, while the natural gas generating unit (NGGU) is applied when it has deficit electricity. Second, based on the multi‐energy trading framework, a joint stochastic equilibrium model for the DEM, DAWM, and the gas market (GM) is proposed. In addition, Monte Carlo simulation and scenario reduction techniques are applied to tackle the uncertainty in the actual output/demand of microgrids. Finally, the numerical examples show that the proposed multi‐energy trading model can compensate the deviation of the microgrids with uncertain output/demand in the DEM, and help to improve the market competitiveness of microgrids and the utilization of distributed renewable energy. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

A member of the NF-κB signaling pathway, PoAkirin1, was cloned from a full-length cDNA library of Japanese flounder (Paralichthys olivaceus). The full-length cDNA comprises a 5'UTR of 202 bp, an open reading frame of 564 bp encoding a 187-amino-acid polypeptide and a 521-bp 3'UTR with a poly (A) tail. The putative protein has a predicted molecular mass of 21 kDa and an isoelectric point (pI) of 9.22. Amino acid sequence alignments showed that PoAkirin1 was 99% identical to the Scophthalmus maximus Akirin protein (ADK27484). Yeast two-hybrid assays identified two proteins that interact with PoAkirin1: PoHEPN and PoC1q. The cDNA sequences of PoHEPN and PoC1q are 672 bp and 528 bp, respectively. Real-time quantitative reverse-transcriptase polymerase chain reaction analysis showed that bacteria could induce the expressions of PoAkirin1, PoHEPN and PoC1q. However, the responses of PoHEPN and PoC1q to the bacterial challenge were slower than that of PoAkirin1. To further study the function of PoAkirin1, recombinant PoAkirin1 and PoHEPN were expressed in Escherichia coli and would be used to verify the PoAkirin1-PoHEPN binding activity. These results identified two proteins that potentially interact with PoAkirin1 and that bacteria could induce their expression.