Genetic and morphological variation and differentiation of South Korean natural populations of wild soybean, Glycine soja Sieb and Zucc

Genetic variation is the basis of crop improvement. As genetic background narrows in the cultivated germplasm, genes need to be introduced from new sources. Glycine soja is a wild relative of the cultivated soybean, glycine max (L.) Merr. It can be used in soybean breeding. Evaluation of wild soybean populations is not only necessary for use in cultivar improvement, will also provide information about origin, migration, evolution and natural selection of this species. Seeds were collected from six natural populations in South Korea to study the genetic variation and differentiation of wild soybean. The study was divided into two parts: (a) lab assay for 17 isozymes and one protein involving 35 loci; and (b) two-year greenhouse experiment, during which data for morphological traits were recorded. The average number of alleles per locus, 99% polymorphism and the expected heterozygosity in the total population were 2.1, 77.1% and 0.215, respectively. Nei\u27s gene differentiation (G\sb{\rm ST}) was 0.383. The average Nei\u27s genetic distance was 0.117. Populations were not significantly different in mean CV (coefficients of variation) for both years. However, 27 of the 33 individual morphological traits examined in 1989 and 31 of the 39 in 1990 differed significantly among populations. The average among-population variation per trait per degree of freedom was 84.38% in 1989 and 83.11% in 1990. Although there were no significant differences among populations in mean CV, those populations with high genetic variation also had high mean CV for morphological traits. There was no congruence between the isozyme and morphological data in terms of population relationships. Multilocus association analysis provided significant insight into the genetic structure of these natural populations. The analysis indicated that within each population, there were two to three dominant multilocus genotypes. The multilocus genotypes were biotypes at the morphological level. These different types might be the basic genetic division of mosaic self-pollinated plant populations, and the basic units in natural selection and evolution. The analysis also suggested that there was no migration among these six populations in recent history. The numbers of loci different between individuals were used as measures of genetic variation and genetic distance

A Phylogenetic Analysis of the Genus Fragaria (Strawberry) Using Intron-Containing Sequence from the ADH-1 Gene

The genus Fragaria encompasses species at ploidy levels ranging from diploid to decaploid. The cultivated strawberry, Fragaria×ananassa, and its two immediate progenitors, F. chiloensis and F. virginiana, are octoploids. To elucidate the ancestries of these octoploid species, we performed a phylogenetic analysis using intron-containing sequences of the nuclear ADH-1 gene from 39 germplasm accessions representing nineteen Fragaria species and one outgroup species, Dasiphora fruticosa. All trees from Maximum Parsimony and Maximum Likelihood analyses showed two major clades, Clade A and Clade B. Each of the sampled octoploids contributed alleles to both major clades. All octoploid-derived alleles in Clade A clustered with alleles of diploid F. vesca, with the exception of one octoploid allele that clustered with the alleles of diploid F. mandshurica. All octoploid-derived alleles in clade B clustered with the alleles of only one diploid species, F. iinumae. When gaps encoded as binary characters were included in the Maximum Parsimony analysis, tree resolution was improved with the addition of six nodes, and the bootstrap support was generally higher, rising above the 50% threshold for an additional nine branches. These results, coupled with the congruence of the sequence data and the coded gap data, validate and encourage the employment of sequence sets containing gaps for phylogenetic analysis. Our phylogenetic conclusions, based upon sequence data from the ADH-1 gene located on F. vesca linkage group II, complement and generally agree with those obtained from analyses of protein-encoding genes GBSSI-2 and DHAR located on F. vesca linkage groups V and VII, respectively, but differ from a previous study that utilized rDNA sequences and did not detect the ancestral role of F. iinumae

Influence of growth habit, nodulation, and nitrogen fertilization on the incidence of soybean charcoal rot and in vitro response of soybean cultivars to the toxin of M. phaseolina, causal fungus of the disease

Call number: LD2668 .T4 AGRN 1988 Y8Master of ScienceAgronom

An Interactive Differential Evolution Algorithm Based on Backtracking Strategy Applied in Interior Layout Design

The Interior layout model is to optimize the arrangement position of each room to maximize the comfort and quality of life of residents. Due to the complexity of the Interior layout problem, the computation of fitness function costs lots of time. To reduce the high computational cost while maintaining the solution performance. An interactive differential evolution algorithm based on Backtracking operator (IDE-BO) is proposed as the solver of the Interior layout model. The human-computer interaction mechanism of IDE benefits the automatic adjustment of fitness parameters that best meet the user’s subjective preferences to achieve the optimal solution. At the same time, the backtracking strategy can also help jump out when the algorithm falls into local optimization. The IDE is compared to other two conventional optimization methods based on two different layout scenarios. The experimental results show that in interior layout model IDE-BO is better than conventional interactive genetic algorithm (IGA) and IDE which do not use BO strategy, the super-performance of IDE-BO in complex situations in terms of execution time and convergence rate

Design and Control of a Nonlinear Series Elastic Cable Actuator Based on the Hill Muscle Model

The bionic design of muscles is a research hotspot at present. Many researchers have designed bionic elastic actuators based on the Hill muscle model, and most of them include an active contraction element, passive contraction element and series elastic element, but they need more parametric design of mechanical structure and control under the guidance of Hill muscle model. In this research, a nonlinear series elastic cable actuating mechanism is designed in which the parameters of the elastic mechanism are optimized based on the Hill muscle model to fit the nonlinear passive elasticity of a muscle. Through the force–position relationship determined by the Hill muscle model, the output force and position of a nonlinear series elastic cable actuator are controlled to simulate the active contraction performance of a muscle. The experiments show that the proposed design and control method can make the nonlinear cable actuator have good muscle-like output force–displacement characteristics

Design and Assist-as-Needed Control of Flexible Elbow Exoskeleton Actuated by Nonlinear Series Elastic Cable Driven Mechanism

Exoskeletons can assist the daily life activities of the elderly with weakened muscle strength, but traditional rigid exoskeletons bring parasitic torque to the human joints and easily disturbs the natural movement of the wearer’s upper limbs. Flexible exoskeletons have more natural human-machine interaction, lower weight and cost, and have great application potential. Applying assist force according to the patient’s needs can give full play to the wearer’s remaining muscle strength, which is more conducive to muscle strength training and motor function recovery. In this paper, a design scheme of an elbow exoskeleton driven by flexible antagonistic cable actuators is proposed. The cable actuator is driven by a nonlinear series elastic mechanism, in which the elastic elements simulate the passive elastic properties of human skeletal muscle. Based on an improved elbow musculoskeletal model, the assist torque of exoskeleton is predicted. An assist-as-needed (AAN) control algorithm is proposed for the exoskeleton and experiments are carried out. The experimental results on the experimental platform show that the root mean square error between the predicted assist torque and the actual assist torque is 0.00226 Nm. The wearing experimental results also show that the AAN control method designed in this paper can reduce the activation of biceps brachii effectively when the exoskeleton assist level increases

Design and Control of a Nonlinear Series Elastic Cable Actuator Based on the Hill Muscle Model

The bionic design of muscles is a research hotspot at present. Many researchers have designed bionic elastic actuators based on the Hill muscle model, and most of them include an active contraction element, passive contraction element and series elastic element, but they need more parametric design of mechanical structure and control under the guidance of Hill muscle model. In this research, a nonlinear series elastic cable actuating mechanism is designed in which the parameters of the elastic mechanism are optimized based on the Hill muscle model to fit the nonlinear passive elasticity of a muscle. Through the force–position relationship determined by the Hill muscle model, the output force and position of a nonlinear series elastic cable actuator are controlled to simulate the active contraction performance of a muscle. The experiments show that the proposed design and control method can make the nonlinear cable actuator have good muscle-like output force–displacement characteristics

Selection of the Most Scenic Viewpoints on an Island Based on Space–Time Perception: The Case of Nan’ao Island, China

Selecting the most scenic viewpoints in an island forest park can provide a scientific basis for island ecotourism planning. In this paper, considering the influence of climatic conditions on sightseeing, landscape factors, accessibility factors, and seasonal change factors are selected from the perspective of time and space to analyze the landscape spatiotemporal characteristics, and the construction of a landscape spatiotemporal perception evaluation model and the analysis of influencing factors are carried out. The results show that the evaluation model for landscape spatiotemporal perception factors can quantitatively describe tourists’ comprehensive perception of a landscape in different regions and time periods in ecotourism areas, and can identify the spatiotemporal characteristics of landscape perception. Case studies preliminarily prove the feasibility of the model and calculation process. This method provides a strong reference for the development and planning of island tourism, especially providing new ideas and methods for the design of sightseeing routes in the development and planning of small-scale scenic viewpoints, which can enrich island tourism planning

Modeling and Optimizing of NH₄⁺ Removal from Stormwater by Coal-Based Granular Activated Carbon Using RSM and ANN Coupled with GA

As a key parameter in the adsorption process, removal rate is not available under most operating conditions due to the time and cost of experimental testing. To address this issue, evaluation of the efficiency of NH4+ removal from stormwater by coal-based granular activated carbon (CB-GAC), a novel approach, the response surface methodology (RSM), back-propagation artificial neural network (BP-ANN) coupled with genetic algorithm (GA), has been applied in this research. The sorption process was modeled based on Box-Behnben design (BBD) RSM method for independent variables: Contact time, initial concentration, temperature, and pH; suggesting a quadratic polynomial model with p-value 2 = 0.9762. The BP-ANN with a structure of 4-8-1 gave the best performance. Compared with the BBD-RSM model, the BP-ANN model indicated better prediction of the response with R2 = 0.9959. The weights derived from BP-ANN was further analyzed by Garson equation, and the results showed that the order of the variables’ effectiveness is as follow: Contact time (31.23%) > pH (24.68%) > temperature (22.93%) > initial concentration (21.16%). The process parameters were optimized via RSM optimization tools and GA. The results of validation experiments showed that the optimization results of GA-ANN are more accurate than BBD-RSM, with contact time = 899.41 min, initial concentration = 17.35 mg/L, temperature = 15 °C, pH = 6.98, NH4+ removal rate = 63.74%, and relative error = 0.87%. Furthermore, the CB-GAC has been characterized by Scanning electron microscopy (SEM), X-ray diffraction (XRD) and Brunauer-Emmett-Teller (BET). The isotherm and kinetic studies of the adsorption process illustrated that adsorption of NH4+ onto CB-GAC corresponded Langmuir isotherm and pseudo-second-order kinetic models. The calculated maximum adsorption capacity was 0.2821 mg/g

Bimodal Emotion Recognition Model for Minnan Songs

Most of the existing research papers study the emotion recognition of Minnan songs from the perspectives of music analysis theory and music appreciation. However, these investigations do not explore any possibility of carrying out an automatic emotion recognition of Minnan songs. In this paper, we propose a model that consists of four main modules to classify the emotion of Minnan songs by using the bimodal data—song lyrics and audio. In the proposed model, an attention-based Long Short-Term Memory (LSTM) neural network is applied to extract lyrical features, and a Convolutional Neural Network (CNN) is used to extract the audio features from the spectrum. Then, two kinds of extracted features are concatenated by multimodal compact bilinear pooling, and finally, the concatenated features are input to the classifying module to determine the song emotion. We designed three experiment groups to investigate the classifying performance of combinations of the four main parts, the comparisons of proposed model with the current approaches and the influence of a few key parameters on the performance of emotion recognition. The results show that the proposed model exhibits better performance over all other experimental groups. The accuracy, precision and recall of the proposed model exceed 0.80 in a combination of appropriate parameters