THE EFFECTIVENESS OF GENETIC ALGORITHM IN CAPTURING CONDITIONAL NONLINEAR OPTIMAL PERTURBATION WITH PARAMETERIZATION “ON-OFF” SWITCHES INCLUDED BY A MODEL

In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP), the ‘on-off’ switch caused by moist physical parameterization in prediction models prevents the conventional adjoint method from providing correct gradient during the optimization process. To address this problem, the capture of CNOP, when the "on-off" switches are included in models, is treated as non-smooth optimization in this study, and the genetic algorithm (GA) is introduced. After detailed algorithm procedures are formulated using an idealized model with parameterization "on-off" switches in the forcing term, the impacts of "on-off" switches on the capture of CNOP are analyzed, and three numerical experiments are conducted to check the effectiveness of GA in capturing CNOP and to analyze the impacts of different initial populations on the optimization result. The result shows that GA is competent for the capture of CNOP in the context of the idealized model with parameterization ‘on-off’ switches in this study. Finally, the advantages and disadvantages of GA in capturing CNOP are analyzed in detail.

The High Precision Open Boundary Conditions Designed for Transient Waves

In Rels. [2-4] there is an Adaptive. Open Boundary Condition (AOBC) designed for transient waves which overcomes the limitation of the existing Open BoundaryCondition (OBC) and can be used for the cases of waves with arbitrary incidentangles. In this article a new family of high order AOBC has been designed on the basisof the above mentioned AOBC with the first order.In comparison with all other OBC with the same order, this new family of AOBC has the highest precision.

ON THE HIGH PRECISION ADAPTIVE OPEN BOUNDARY CONDITIONS FOR TRANSIENT WAVES

The adaptive open boundary conditions (AOBC) designed by Chen and Zou for transient waves overcome the limitation of the existing open boundary conditions (OBC) and can be used for the cases of waves with arbitrary incident angles. In this paper a new family of AOBC has been designed on the basis of the AOBC with first order mentioned above. In comparing with all other OBC with the same order, this new family of AOBC has the highest precision. It can be generalized into 3D problems without difficulty and its forms in different curvilinear coordinate systems can be got very easily. The distinguished advantages above mentioned of the AOBC will be discussed in this paper.

Chromatographic Analysis of Chemical Composition of the Genus Rhododendron Plants Growing on the Mountain of Evota （South Yakutia）

The data on chemical compounds of three Rododendron species （Rh. adamsii Rehd., Rh. aureum Georgi. and Rh. lapponicum subsp, parvifolium （Adams） T. Yamaz.） from the mountain of Evota top in South Yakutia are shown. Extracts of these plants was analyzed by method of planar chromatography in thin layers using different specific detectors to exposure of some groups of biologically active matters. During the researches, it was established that polyphenol compounds of different degree of condensment prevail in rhododendron composition; catechines, flavonoids, coumarins, saponins, essential oils, phenol carboxylic acids and arbutin are present too. Due to detected features, all the researched species of rhododendrons are perspective for practical using in food industry and as adaptogenes for maintenance of people health in the conditions of north.

Analysis on Characteristics of Architectural Environment of Traditional Villages in Southwest Mountainous Area:Taking Heijing Ancient Town of Chuxiong as an Example

The formation of the ancient town of Heijing conforms to the natural conditions and local conditions,and makes effective use of the natural mountains,water bodies,trees and other resources of the ancient town,so that the ancient town and nature rely on each other and unify harmoniously.Through the analysis of the environmental characteristics of the ancient town,this paper further explores its cultural connotation.

Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model

Using the conditional nonlinear optimal perturbation(CNOP) approach, sensitive areas of adaptive observation for predicting the seasonal reduction of the upstream Kuroshio transport(UKT) were investigated in the Regional Ocean Modeling System(ROMS). The vertically integrated energy scheme was utilized to identify sensitive areas based on two factors: the specific energy scheme and sensitive area size. Totally 27 sensitive areas, characterized by three energy schemes and nine sensitive area sizes, were evaluated. The results show that the total energy(TE) scheme was the most effective because it includes both the kinetic and potential components of CNOP. Generally, larger sensitive areas led to better predictions. The size of 0.5% of the model domain was chosen after balancing the effectiveness and efficiency of adaptive observation. The optimal sensitive area OSen was determined accordingly. Sensitivity experiments on OSen were then conducted, and the following results were obtained:(1) In OSen, initial errors with CNOP or CNOP-like patterns were more likely to yield worse predictions, and the CNOP pattern was the most unstable.(2) Initial errors in OSen rather than in other regions tended to cause larger prediction errors. Therefore, adaptive observation in OSen can be more beneficial for predicting the seasonal reduction of UKT.

TSC1 enables plastid development under dark conditions, contributing to rice adaptation to transplantation shock

Since its domestication from wild rice thousands of years ago, rice has been cultivated largely through transplantation. During transplantation from the nursery to the paddy field, rice seedlings experience transplantation shock which affects their physiology and production.However, the mechanisms underlying transplantation shock and rice adaptation to this shock are largely unknown. Here,we isolated a transplant-sensitive chloroplast-deficient（tsc_1）rice mutant that produces albino leaves after transplantation.Blocking light from reaching the juvenile leaves and leaf primordia caused chloroplast deficiencies in transplanted tsc_1 seedlings. TSC_1 encodes a noncanonical adenosine triphosphate-binding cassette（ABC） transporter homologous to At NAP_（14） and is of cyanobacterial origin. We demonstrate that TSC_1 controls plastid development in rice under dark conditions, and functions independently of light signaling.However, light rescued the tsc_1 mutant phenotype in a spectrum-independent manner. TSC_1 was upregulated following transplantation, and modulated the iron and copper levels, thereby regulating prolamellar body formation during the early P_4 stage of leaf development. Therefore, TSC_1 is indispensable for plastid development in the absence of light,and contributes to adaptation to transplantation shock.Our study provides insight into the regulation of plastid development and establishes a framework for improving recovery from transplantation shock in rice.

Spectral transfer-learning-based metasurface design assisted by complex-valued deep neural network

Recently,deep learning has been used to establish the nonlinear and nonintuitive mapping between physical structures and electromagnetic responses of meta-atoms for higher computational efficiency.However,to obtain sufficiently accurate predictions,the conventional deep-learning-based method consumes excessive time to collect the data set,thus hindering its wide application in this interdisciplinary field.We introduce a spectral transfer-learning-based metasurface design method to achieve excellent performance on a small data set with only 1000 samples in the target waveband by utilizing open-source data from another spectral range.We demonstrate three transfer strategies and experimentally quantify their performance,among which the“frozen-none”robustly improves the prediction accuracy by∼26%compared to direct learning.We propose to use a complex-valued deep neural network during the training process to further improve the spectral predicting precision by∼30%compared to its real-valued counterparts.We design several typical teraherz metadevices by employing a hybrid inverse model consolidating this trained target network and a global optimization algorithm.The simulated results successfully validate the capability of our approach.Our work provides a universal methodology for efficient and accurate metasurface design in arbitrary wavebands,which will pave the way toward the automated and mass production of metasurfaces.

A fast and automatic full-potential finite volume solver on Cartesian grids for unconventional configurations

To meet the requirements of fast and automatic computation of subsonic and transonic aerodynamics in aircraft conceptual design,a novel finite volume solver for full potential flows on adaptive Cartesian grids is developed in this paper.Cartesian grids with geometric adaptation are firstly generated automatically with boundary cells processed by cell-cutting and cell-merging algorithms.The nonlinear full potential equation is discretized by a finite volume scheme on these Cartesian grids and iteratively solved in an implicit fashion with a generalized minimum residual（GMRES） algorithm.During computation,solution-based mesh adaptation is also applied so as to capture flow features more accurately.An improved ghost-cell method is proposed to implement the non-penetration wall boundary condition where the velocity-potential of a ghost cell is modified by an analytic method instead.According to the characteristics of the Cartesian grids,the Kutta condition is applied by specially computing the gradients on Kutta-faces without directly assigning the potential jump to cells adjacent wake faces,which can significantly improve the solution converging speed.The feasibility and accuracy of the proposed method are validated by several typical cases of sub/transonic flows around an ONERA M6 wing,a DLR-F4 wing-body,and an unconventional figuration of a blended wing body（BWB）.The validation cases demonstrate a fast convergence with fully automatic grid treatment and computation,and the results suggest its capacity in application for aircraft conceptual design.