Customized Optimization for Vehicle Acoustic Statistical Energy Analysis

Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).

A Piecewise-Linear Compensated Bandgap Reference

A bandgap voltage reference is presented with a piecewise linear compensating circuit in order to reduce the temperature coefficient.The basic principle is to divide the whole operating temperature range into some sub ranges.At different temperature sub ranges the bandgap reference can be compensated by different linear functions.Since the temperature sub range is much narrower than the whole range,the compensation error can be reduced significantly.Theoretically,the precision can be improved unlimitedly if the sub ranges are narrow enough.In the given example,with only three temperature sub ranges,the temperature coefficient of a conventional bandgap reference drops from 1 5×10 -5 /℃ to 2×10 -6 /℃ over the -40℃ to 120℃ temperature range.

Studies on the Inheritance of Locule Formation in Tomatoes (Lycopersicon esculentum Mill.)

To fully understand the tomato ovary locule formation of inheritance, two varieties, ovary multi-locule （MLK1） and few-locule （FL1）, were used in these studies. Using reciprocal cross, self-cross, and backcross, we have constructed various groups to seek the genetic law and mechanisms of tomato locule formation, for modifying the tomato breeding theory. The parental and the resulting FI and F2 generations have been used to examine the heredity of the locule number. The results showed that few-locule was incompletely dominant. The data from backcross demonstrated a significant effect on the locule number, whereas, the reciprocal cross showed an insignificant effect. Not surprisingly, the locule number was controlled by nuclear genomes, not by exogenous substances. The model that inherited the locule number belonged to the additive-dominant model： additive effects played a very important role and were partially dominant. In addition, the results revealed that the locule number in tomato was mainly controlled by a single gene, whereas, it was modulated by a number of other genes. Finally, the general inheritability and narrow inheritability of the locule number were 69.44% and 52.98%, respectively.

Cardinal Numbers of Fuzzy Sets

Up to now, the study on the cardinal number of fuzzy sets has advanced at on pace since it is very hard to give it an appropriate definition. Althrough for it in [1], it is with some harsh terms and is not reasonable as we point out in this paper. In the paper, we give a general definition of fuzzy cardinal numbers. Based on this definition, we not only obtain a large part of results with re spect to cardinal numbers, but also give a few of new properties of fuzzy cardinal numbers.

Effect of Excited-state Substituent Constant on the UV Spectra of 1,4-disubstituted Benzenes

A correlation equation between the UV absorption wavenumbers of 1,4-disubstituted benzenes and the excited-state substituent constant was obtained. For 80 sorts of 1,4- disubstituted benzenes, the correlation coefficient was 0.9805, and the standard deviation was only 672.27 cm^-1. The results imply that the excited-state substituent constant can be used productively for research on UV energy of 1,4-disubstituted benzenes. The present method provides a new avenue to study the UV absorption spectra of aromatic systems with the excited-state substituent constant, and it is helpful to understand the effect of substituent electrostatic effects on the chemical and physical properties of conjugated compounds with multiple substituents in excited state.

Determination of undrained shear strength using piezocone penetration test in clayey soil for bridge foundation

In order to obtain the reasonable undrained shear strength Su for geotechnical analyses of bridge foundations in Yangtze River floodplain clayey soils, a site-specific study is conducted using the imported piezocone penetration test （CPTu） with dissipation phases at the Fourth Nanjing Yangtze River Bridge construction sites. Taking the values of Su from laboratory tests as references, several existing Su-predicted methods based on CPTu are compared and evaluated. To verify the presented cone factor Nk, additional test sites are selected and examined. The results show that the values of cone factors such as Nkt, Nke, and Nau, depend on the shear test mode and disturbance. Generally, the values of Nke show more scattering than those of Nkt and N△u. For the stratified and layered sediments of the Yangtze River floodplain, it is recommended using the net cone resistance qT to estimate Su and the preliminary cone factor values Nkt are from 7 to 16, with an average of 11. It is also confirmed that the CPTu test, as a new technique in site characterization, can present reasonable parameters for bridge foundations.

Research on Thermodynamic Properties of Polybrominated Diphenylamine by Neural Network

Based on the location of bromine substituents and conjugation matrix, a new substituent po- sition index ~X not only was defined, but also molecular shape indexes Km and electronega- tivity distance vectors Mm of diphenylamine and 209 kinds of polybrominated diphenylamine （PBDPA） molecules were calculated. Then the quantitative structure-property relationships （QSPR） among the thermodynamic properties of 210 organic pollutants and 0X, K3, M29, M36 were founded by Leaps-and-Bounds regression. Using the four structural parameters as input neurons of the artificial neural network, three satisfactory QSPR models with network structures of 4：21：1, 4：24：1, and 4：24：1 respectively, were achieved by the back-propagation algorithm. The total correlation coefficients R were 0.9999, 0.9997, and 0.9995 respectively and the standard errors S were 1.036, 1.469, and 1.510 respectively. The relative mean deviation between the predicted value and the experimental value of Sθ, AfHe and △fGθ- were 0.11%, 0.34% and 0.24% respectively, which indicated that the QSPR models had good stability and superior predictive ability. The results showed that there were good nonlinear correlations between the thermodynamic properties of PBDPAs and the four structural pa- rameters. Thus, it was concluded that the ANN models established by the new substituent position index were fully applicable to predict properties of PBDPAs.

Geophysical data sparse reconstruction based on L0-norm minimization

Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transform domain, we can improve the accuracy and stability of the reconstruction by transforming it to a sparse optimization problem. In this paper, we propose a mathematical model for the sparse reconstruction of data based on the LO-norm minimization. Furthermore, we discuss two types of the approximation algorithm for the LO- norm minimization according to the size and characteristics of the geophysical data： namely, the iteratively reweighted least-squares algorithm and the fast iterative hard thresholding algorithm. Theoretical and numerical analysis showed that applying the iteratively reweighted least-squares algorithm to the reconstruction of potential field data exploits its fast convergence rate, short calculation time, and high precision, whereas the fast iterative hard thresholding algorithm is more suitable for processing seismic data, moreover, its computational efficiency is better than that of the traditional iterative hard thresholding algorithm.

Identification of Quantitative Trait Loci for Cold Response of Seedling Vigor Traits in Rice

The quantitative trait loci （QTLs） for the seedling vigor traits under 12℃ cold water irrigation, such as the seedling height, the seedling fresh weight, the seedling dry weight, and their cold response index, were identified using an F2：3 population including 200 individuals and lines derived from a cross of indica and japonica ＂Milyang 23/Jileng 1＂ with microsatellite markers. All seedling vigor traits exhibited a continuous distribution near normal in F3 lines; these traits were quantitative traits controlled by multiple genes. Twelve QTLs conferring the seedling vigor traits under cold water irrigation were detected on chromosomes 1, 2, 7, 8, and 12, which explained the observed phenotypic variance from 5.2% to 17.9%. Among them, qCSH2 and qCSH12 were located in RM262-RM263 on chromosome 2 and RM270-RM17 on chromosome 12, respectively, which were associated with the seedling height, qSDW12 and qCSDW1 were located in RM19-RM270 on chromosome 12 and RM 129-RM9 on chromosome 1, respectively, which were correlated with the seedling dry weight and its cold response index, and the explained 16.6%, 17.9%, 15.9%, and 16.2% of the observed phenotypic variation, respectively. These QTLs alleles were derived from cold-tolerant parent Jileng 1; the gene actions of the two front genes showed their additive effect, and the two genes belind showed dominant and over dominant effects, respectively.

RBF-based cluster-head selection for wireless sensor networks

The radial basis function （RBF）, a kind of neural networks algorithm, is adopted to select clusterheads. It has many advantages such as simple parallel distributed computation, distributed storage, and fast learning. Four factors related to a node becoming a cluster-head are drawn by analysis, which are energy （ energy available in each node）, number （the number of neighboring nodes）, centrality （ a value to classify the nodes based on the proximity how central the node is to the cluster）, and location （the distance between the base station and the node）. The factors are as input variables of neural networks and the output variable is suitability that is the degree of a node becoming a cluster head. A group of cluster-heads are selected according to the size of network. Then the base station broadcasts a message containing the list of cluster-heads＇ IDs to all nodes. After that, each cluster-head announces its new status to all its neighbors and sets up a new cluster. If a node around it receives the message, it registers itself to be a member of the cluster. After identifying all the members, the cluster-head manages them and carries out data aggregation in each cluster. Thus data flowing in the network decreases and energy consumption of nodes decreases accordingly. Experimental results show that, compared with other algorithms, the proposed algorithm can significantly increase the lifetime of the sensor network.

QTL Mapping of Yield and Yield Components for Elite Hybrid Derived-RILs in Upland Cotton

A population of 180 recombinant inbred lines （RILs） was developed by single seed descended from the cross of high yield Upland cotton （Gossypium hirsutum L.） varieties Zhongmiansuo12 （ZMSI2） and 8891, the two parents of Xiangzamian2 （XZM2）. A genetic linkage map consisting of 132 loci and covering 865.20 cM was constructed using the RIL population chiefly with SSR markers. Yield and yield components were investigated for RILs in three environments in China. The purpose of the present research was to analyze the relationship between yield and its components and to map QTL for yield and yield components in cotton. QTL were tagged with data sets from single environment （separate analysis） and a set of data from means of the three environments （joint analysis）. A total of 34 QTL for yield and yield components were independently detected in three environments, whereas fifteen QTL were found in joint analysis. Notably, a stable lint percentage QTL qLP-A10-1 was detected both in joint analysis and in two environments of separate analysis, which might be of special value for marker-assisted selection. The QTL detected in the present study provide new information on improving yield and yield components. Results of path analysis showed that bolls/plant had the largest contribution to lint yield, which is consistent with the mid-parent heterosis value in F1. Accordingly, in cotton breeding, bolls/plant can be considered first and other yield components measured as a whole to implement variety enhancement and hybrid selection of cotton.

3D anisotropic modeling and identification for airborne EM systems based on the spectral-element method

The airborne electromagnetic （AEM） method has a high sampling rate and survey flexibility. However, traditional numerical modeling approaches must use high-resolution physical grids to guarantee modeling accuracy, especially for complex geological structures such as anisotropic earth. This can lead to huge computational costs. To solve this problem, we propose a spectral-element （SE） method for 3D AEM anisotropic modeling, which combines the advantages of spectral and finite-element methods. Thus, the SE method has accuracy as high as that of the spectral method and the ability to model complex geology inherited from the finite-element method. The SE method can improve the modeling accuracy within discrete grids and reduce the dependence of modeling results on the grids. This helps achieve high-accuracy anisotropic AEM modeling. We first introduced a rotating tensor of anisotropic conductivity to Maxwell＇s equations and described the electrical field via SE basis functions based on GLL interpolation polynomials. We used the Galerkin weighted residual method to establish the linear equation system for the SE method, and we took a vertical magnetic dipole as the transmission source for our AEM modeling. We then applied fourth-order SE calculations with coarse physical grids to check the accuracy of our modeling results against a 1D semi-analytical solution for an anisotropic half-space model and verified the high accuracy of the SE. Moreover, we conducted AEM modeling for different anisotropic 3D abnormal bodies using two physical grid scales and three orders of SE to obtain the convergence conditions for different anisotropic abnormal bodies. Finally, we studied the identification of anisotropy for single anisotropic abnormal bodies, anisotropic surrounding rock, and single anisotropic abnormal body embedded in an anisotropic surrounding rock. This approach will play a key role in the inversion and interpretation of AEM data collected in regions with anisotropic geology.

Numerical modeling of tidal current of LNG terminal in Caofeidian,Bohai Sea

In order to reasonably simulate tidal currents around small structures such as piles in a large-scale model domain, a 2-D hydrodynamic integrated model for Bohai Sea is established with the finite element method. The grid can be discretionarily refined as a non-structure triangle or quadrilateral so that piers can be treated as one or several impermeable elements with an area of 20 to 30 km^2 in a model domain over 85 700 km^2. The computational results of tidal levels and horizontal velocities are in good agreement with the field data. Based on the computed results by the model, the layout of an open 105 DWT liquefied natural gas （LNG）terminal in Caofeidian, Bohal Sea is effectively and reasonably optimized. It can be concluded that the model is suitable and reasonable for direct simulation of tidal currents around small structures in projects.

An Entropy-based Index for Fine-scale Mapping of Disease Genes

By comparing the entropy and the conditional entropy in a marker, an entropy-based index has been presented for fine-scale linkage disequilibrium gene mapping using high-density marker maps for human disease genes. The index can quantify the level of linkage disequilibrium （LD） between the marker and the disease susceptibility locus （DSL） of genes. The advantage of using the index is attributed to the fact that it does not depend on marker allele frequencies across loci. Moreover, it is parallel to Hardy-Weinberg disequilibrium （HWD） measure for DSL fine mapping. Through various simulations, the fine mapping perform- ances of the proposed entropy-based index was extensively investigated under various genetic parameters. The results show that the index presented is both robust and powerful for DSL mapping in genes.

Measurement of Coordinate Parameter by Multi-baseline Digital Close-range Photogrammetry System and Data Analysis for Jujube

[Objective] The aim was to explore the measurement of coordinate parameter by multi-baseline digital close-range photogrammetry system.[Method] The 3-dimensional coordinate of 8-year-old Jujube was measured by using Lensphoto multi-baseline digital close-range photogrammetry system,and through comparing with measured data of Total Station,the error and accuracy of photogrammetry data were analyzed.[Result] The absolute error of X,Y and Z coordinate was 0-0.014,0-0.018 and 0-0.004 m respectively,and the relative error of X,Y and Z coordinate was less than 0.145%.The significance test of pairs for the photogrammetry data and measured data of Total Station indicated that the space coordinate data of stumpage were accurately measured by using the multi-baseline digital close-range photogrammetry method,and the photogrammetry data meet the need of space coordinate measurement for virtual plant growth simulation.[Conclusion] This study had provided theoretical basis for the growth measurement of virtual plant growth simulation.

Spatial interpolation method based on integrated RBF neural networks for estimating heavy metals in soil of a mountain region

A novel spatial interpolation method based on integrated radial basis function artificial neural networks （IRBFANNs） is proposed to provide accurate and stable predictions of heavy metals concentrations in soil at un- sampled sites in a mountain region. The IRBFANNs hybridize the advantages of the artificial neural networks and the neural networks integration approach. Three experimental projects under different sampling densities are carried out to study the performance of the proposed IRBFANNs-based interpolation method. This novel method is compared with six peer spatial interpolation methods based on the root mean square error and visual evaluation of the distribution maps of Mn elements. The experimental results show that the proposed method performs better in accuracy and stability. Moreover, the proposed method can provide more details in the spatial distribution maps than the compared interpolation methods in the cases of sparse sampling density.

Detection of Exogenous Gene Copies in Transgenic Soybean by Taqman Quantitative PCR Technique

[Objective] Taqman Quantitative PCR technique was adopted to detect the copies of exogenous nos terminator in transgenic hybrid soybean.[Method] With soybean Lectin as the endogenous reference gene,and gene complex DNA in non-GMO soybeans as the endogenous reference standard,the method of gradient dilution was used for separately calculate Ct value of endogenous reference gene and plasmid DNA and correlation standard curve equation of logarithm of copies,and then to calculate the copies of samples through substituting thus-obtained Ct into the standard curve equation.[Result] The standard curve equation of endogenous reference gene is y=-3.422x＋35.201,R2=0.998;and the standard curve equation of exogenous gene is y=-3.348x＋34.890,R2=0.999.Nos terminator and its lower boundary sequences in transgenic soybean is of single copy.[Conclusion] The study has provided a theoretical basis for determining exogenous gene copies in transgenic soybean.

An Entropy-based Index for Fine-scale Mapping of QTL

By comparing the entropy and conditional entropy in a marker, an entropy-based index for fine-scale linkage-disequilibrium gene mapping is presented using high-density marker maps in extreme samples for quantitative trait. The entropy-based index is the function of LD between the marker and the traitlocus and does not depend on marker allele frequencies across the loci. It is parallel to Hardy-Weinberg disequilibrium （HWD） measure for QTL fine mapping, but its power of fine mapping QTL is higher than that of HWD measure. Through simulations, the fine mapping performance of this entropy-based index is investigated extensively under various genetic parameters. The results show that the indices presented here are both robust and powerful.

Recycling of metals from waste Sn-based alloys by vacuum separation

In order to recycle waste Sn-based alloys, the vapor-liquid phase equilibrium composition diagrams of Sn-Pb, Sn-Sb and Sn-Zn binary systems were calculated. The calculated results indicate that Pb, Sb and Zn can be separated from Sn effectively. Based on the above calculation, the industrial experiments of vacuum distillation of Sn-Pb alloy, Sn-Pb-Sb alloy, Sn-Pb-Sb-As alloy, crude Sn and Sn-Zn alloy with different contents were carried out. The experimental results show that Pb(>99% Pb) and Sn(≤0.003% Pb) were obtained simultaneously while Sn-Pb alloy was subjected to vacuum distillation; the crude Sn(>90% Sn, ≤ 2% Pb, ≤6% Sb) and crude Pb(≤2% Sn) were obtained simultaneously while a single vacuum distillation was carried out for Sn-Pb-Sb alloy; the Pb and Bi contents in the Sn ingot(99.99% Sn) achieve the grade A of GB/T 728—2010 standard, more than 50% of As and Sb was removed after vacuum distillation of crude Sn; Zn(<0.002% Sn) and Sn(about 3% Zn) were obtained while vacuum distillation of Sn-Zn alloy was conducted at 1173 K, 20-30 Pa for 8-10 h.

Analysis of radial basis function interpolation approach

The radial basis function （RBF） interpolation approach proposed by Freedman is used to solve inverse problems encountered in well-logging and other petrophysical issues. The approach is to predict petrophysical properties in the laboratory on the basis of physical rock datasets, which include the formation factor, viscosity, permeability, and molecular composition. However, this approach does not consider the effect of spatial distribution of the calibration data on the interpolation result. This study proposes a new RBF interpolation approach based on the Freedman＇s RBF interpolation approach, by which the unit basis functions are uniformly populated in the space domain. The inverse results of the two approaches are comparatively analyzed by using our datasets. We determine that although the interpolation effects of the two approaches are equivalent, the new approach is more flexible and beneficial for reducing the number of basis functions when the database is large, resulting in simplification of the interpolation function expression. However, the predicted results of the central data are not sufficiently satisfied when the data clusters are far apart.