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The arithmetic optimization algorithm (AOA) is a new metaheuristic algorithm inspired by arithmetic operators (addition, subtraction, multiplication, and division) to solve arithmetic problems. The algorithm is characterized by simple principles, fewer parameter settings, and easy implementation, and has been widely used in many fields. However, similar to other meta-heuristic algorithms, AOA suffers from shortcomings, such as slow convergence speed and an easy ability to fall into local optimum. To address the shortcomings of AOA, an improved arithmetic optimization algorithm (IAOA) is proposed. First, dynamic inertia weights are used to improve the algorithm’s exploration and exploitation ability and speed up the algorithm’s convergence speed; second, dynamic mutation probability coefficients and the triangular mutation strategy are introduced to improve the algorithm’s ability to avoid local optimum. In order to verify the effectiveness and practicality of the algorithm in this paper, six benchmark test functions are selected for the optimization search test verification to verify the optimization search ability of IAOA; then, IAOA is used for the parameter optimization of support vector machines to verify the practical ability of IAOA. The experimental results show that IAOA has a strong global search capability, and the optimization-seeking capability is significantly improved, and it shows excellent performance in support vector machine parameter optimization.

Flowers with more petals are of more ornamental value. It is well known that AGAMOUS (AG) is the core member of the C-class gene which plays an essential role in double flower formation and identification of stamens and carpels in Arabidopsis thaliana. We searched C-class genes in the genome of the carnation, and found two AG orthologs (DcaAGa, DcaAGb). Phylogenetic analysis showed that the two genes were closely related to the euAG subclade. Then we searched the genomes of other Caryophyllales plants (Beta vulgaris, Spinacia oleracea, Chenopodium quinoa) for C-class genes, and found that their C-class genes all belonged to the euAG subclade. Semi-quantitative PCR (sq-PCR) analysis indicated that the expression of DcaAG genes in the single flower phenotype was higher than that in the double flower phenotype. Quantitative real-time RT-PCR (qRT-PCR) analysis showed that the expressions of DcaAG genes in the flower bud were significantly different from those in the root, stem, and leaf between the single and double flower phenotype carnations, and that DcaAG genes were specifically expressed in the stamen and carpel of carnation. Moreover, the expression of other floral organ identity genes (AP1 and AP2, PI and AP3, SEP1 and SEP3 corresponding to the A-, B-, and E-class of genes, respectively) showed no significant difference in all floral organs between the single and double flower phenotype carnations, suggesting that C-class (DcaAG) genes might play an important role in the double flower phenotype in carnation. Petal loss or decrease, precocious flowering, silique shortening, and seed sterility were observed in 35S::DcaAGa and 35S::DcaAGb transgenic Arabidopsis plants. All these results show that DcaAG genes might affect the petal number negatively and have a specific function in stamen and carpel development in carnation.

Reconfigurable computing is that the logical resources in the system can be reconfigured according to the real-time changing data flow to achieve different calculation functions. The reconfigurable computing system has both high efficiency on hardware and universality of software. The field programmable gate array (FPGA)-based real-time simulator for active distribution networks (ADNs) requires a long compilation time for case modification, with low efficiency and low versatility, making it inconvenient and difficult for users. To solve the problem of long compile time with a new case, a universal design of the FPGA-based real-time simulator for ADNs based on reconfigurable computing is proposed in this paper. It includes the universal design of the simulation parameter configuration, the simulation initial value setting, the linear equations solving module and the simulation result output module. The proposed universal design of the simulator makes the modification and change of the cases and parameters without recompiling and further improves the simulation efficiency. Simulation results are conducted and compared with PSCAD/EMTDC to validate the correctness and effectiveness of the universal design.

Aquaporins (AQPs) are associated with the transport of water and other small solutes across biological membranes. Genome-wide identification and characterization will pave the way for further insights into the AQPs’ roles in the commercial carnation (Dianthus caryophyllus). This study focuses on the analysis of AQPs in carnation (DcaAQPs) involved in flower opening processes. Thirty DcaAQPs were identified and grouped to five subfamilies: nine PIPs, 11 TIPs, six NIPs, three SIPs, and one XIP. Subsequently, gene structure, protein motifs, and co-expression network of DcaAQPs were analyzed and substrate specificity of DcaAQPs was predicted. qRT-PCR, RNA-seq, and semi-qRTRCR were used for DcaAQP genes expression analysis. The analysis results indicated that DcaAQPs were relatively conserved in gene structure and protein motifs, that DcaAQPs had significant differences in substrate specificity among different subfamilies, and that DcaAQP genes’ expressions were significantly different in roots, stems, leaves and flowers. Five DcaAQP genes (DcaPIP1;3, DcaPIP2;2, DcaPIP2;5, DcaTIP1;4, and DcaTIP2;2) might play important roles in flower opening process. However, the roles they play are different in flower organs, namely, sepals, petals, stamens, and pistils. Overall, this study provides a theoretical basis for further functional analysis of DcaAQPs.