Evaluation of umami taste components of mushroom (Suillus granulatus) of different grades prepared by different drying methods

Suillus granulatus is a valuable wild edible mushroom with a strong umami taste.Different grades of S.granulatus were dried by different methods,including natural air drying(ND),hot air drying(HAD),vacuum drying(VD),and freeze drying(FD).Results showed that VD samples of all grades had the highest equivalent umami concentration(EUC)value(P<0.05).The second grade of ND samples showed the highest EUC value(P<0.05).The first grade of HAD samples showed the highest EUC value(P<0.05).The third grade of FD samples showed the highest EUC value(P<0.05).The third grade of VD samples had a higher EUC value than the other grades of samples dried by VD.Electronic tongue results indicated no significant differences between samples of all grades dried by all methods.Thus,umami taste components are affected by drying method and grade.VD is an appropriate drying method for all sample grades.ND,HAD,and FD are suitable for second-,first-,and third-grade samples,respectively.

Topological Optimization Method for Aeronautical Thin-Walled Component Fixture Locating Layout

Fixture locating layout has a direct and influential impact on aeronautical thin-walled component(ATWC)manufacturing quality.The purpose is to develop a topological optimization method for ATWC fixture locating layout to minimize the manufacturing deformation.Firstly,a topological optimization model that takes the stiffness of ATWC as the objective function and the volume of the locating structure as the constraint is established.Secondly,ATWC and the locating structure are regarded as an integrated entity,and the variable-density method based topological optimization approach is adopted for the optimization of the locating structure using ABAQUS topology optimization module(ATOM).Thirdly,through a subsequent model reconstruction referring to the obtained topological structure,the optimal fixture locating layout is achieved.Finally,a case study is conducted to verify the proposed method and the comparison results with firefly algorithm(FA)coupled with finite element analysis(FEA)indicate that the number and positions of the locators for ATWC can be optimized simultaneously and successfully by the proposed topological optimization model.

Transformer’s Condition Assessment Method Based on Combination of Cloud Matter Element and Principal Component Analysis

With the development of power grid, as one of the key equipment, the transformer’s condition assessment method has always receive attention from experts, scholars concern more and more about the method’s practicality and reliability. In the traditional condition assessment method, due to the characteristics of the transformer’s complex structure, the assessment system is not comprehensive enough, or the assessment system is too complex, the indexes are not easy to quantify, such problems are emerging. The traditional method is complex and the degree of quantification is not enough. Therefore it is necessary to propose a condition assessment method that is easy to carry out the condition assessment work and does not affect the assessment results. In this paper, we propose a method to assess the state of the transformer’s complex structure. First, we establish a comprehensive assessment system, then apply the method of principal component analysis to optimize the index system, and then use the theory of cloud-matter-element. Finally the reliability and rationality of the method are verified by an example.

Methods for estimating rotational components of seismic ground motion and their numerical comparisons

Rotational components play an important role in natural earthquake research,engineering seismic investigation,building monitoring,seismic exploration and other fields.Traditional researches mainly focus on three translational components,but less on rotational ones.As the precision of rotational sensing techniques has increased,many scholars have paid more attention to the seismic rotational motions.Because the rotational observations are not very popular before and now,approximately converting the translational components into rotational components is utilized in rotation analysis.Based on numerical six-component seismic data with the finite difference method,we compare three different conversion methods,the travelling-wave,frequency-domain and the difference method,to analyze their characteristics and feasibilities when they are applied to estimate rotational components with translational observations.

Effect of Planting Date, Spacing and Seeding Methods on Disease Development and Yield Components of Rice （Oryza sativa L.） in Southeastern Nigeria

To investigate the effect of planting date, spacing and seeding methods on disease development and yield components ofrice, a factorial experiment in randomized complete block design （RCBD） with four replications was conducted during 2011 plantingseason at Izzi Local Government Area （LGA） of Ebonyi State, Nigeria. This experiment was carried out with four levels of plantingdates （early June, late June, early July and late July）, three levels of spacing （15, 20 and 25 cm） and two levels of seeding method（direct seeding and seedling transplanting）. The studied traits included plant height （PH）, number of tillers （NT）, leaf area （LA）, rootlength （RL）, panicle length （PL）, 1,000 seed weight （SW）, disease incidence and severity. The result showed that all the factors hadsignificant effect on the parameters measured. Sowing in early July had the highest LA of 65.38 cm^2, PH of 122.00 cm, RL of 29.04cm and TN of 10.54, and the second largest PL of 25.08 cm and SW of 25.12 g. Also sowing in early July had the highest diseaseseverity of 3.21, followed by 3.14 which occurred in late July, while the least 2.17 occurred in early June. The direct seeding methodhad the highest disease incidence of 70.83%, followed by plant spacing of 15 cm × 15 cm which had the disease incidence of 69.72%,while sowing in early June had the least disease incidence of 57.50%. In conclusion, planting of rice in Southeastern Nigeria shouldbe done in early July, as the yield components were significantly better than in other dates though with the highest disease severity.

Primary component analysis method and reduction of seismicity parameters

In the paper, the primary component analysis is made using 8 seismicity parameters of earthquake frequency N (ML≥3.0), b-value, η-value, A(b)-value, Mf-value, Ac-value, C-value and D-value that reflect the characteristics of magnitude, time and space distribution of seismicity from different respects. By using the primary component analysis method, the synthesis parameter W reflecting the anomalous features of earthquake magnitude, time and space distribution can be gained. Generally, there is some relativity among the 8 parameters, but their variations are different in different periods. The earthquake prediction based on these parameters is not very well. However, the synthesis parameter W showed obvious anomalies before 13 earthquakes (MS≥5.8) occurred in North China, which indicates that the synthesis parameter W can reflect the anomalous characteristics of magnitude, time and space distribution of seismicity better. Other problems related to the conclusions drawn by the primary component analysis method are also discussed.

Fast Tensor Principal Component Analysis via Proximal Alternating Direction Method with Vectorized Technique

This paper studies the problem of tensor principal component analysis (PCA). Usually the tensor PCA is viewed as a low-rank matrix completion problem via matrix factorization technique, and nuclear norm is used as a convex approximation of the rank operator under mild condition. However, most nuclear norm minimization approaches are based on SVD operations. Given a matrix , the time complexity of SVD operation is O(mn2), which brings prohibitive computational complexity in large-scale problems. In this paper, an efficient and scalable algorithm for tensor principal component analysis is proposed which is called Linearized Alternating Direction Method with Vectorized technique for Tensor Principal Component Analysis (LADMVTPCA). Different from traditional matrix factorization methods, LADMVTPCA utilizes the vectorized technique to formulate the tensor as an outer product of vectors, which greatly improves the computational efficacy compared to matrix factorization method. In the experiment part, synthetic tensor data with different orders are used to empirically evaluate the proposed algorithm LADMVTPCA. Results have shown that LADMVTPCA outperforms matrix factorization based method.

Evaluation of Third-Order Method for the Tests of Variance Component in Linear Mixed Models

Mixed models provide a wide range of applications including hierarchical modeling and longitudinal studies. The tests of variance component in mixed models have long been a methodological challenge because of its boundary conditions. It is well documented in literature that the traditional first-order methods: likelihood ratio statistic, Wald statistic and score statistic, provide an excessively conservative approximation to the null distribution. However, the magnitude of the conservativeness has not been thoroughly explored. In this paper, we propose a likelihood-based third-order method to the mixed models for testing the null hypothesis of zero and non-zero variance component. The proposed method dramatically improved the accuracy of the tests. Extensive simulations were carried out to demonstrate the accuracy of the proposed method in comparison with the standard first-order methods. The results show the conservativeness of the first order methods and the accuracy of the proposed method in approximating the p-values and confidence intervals even when the sample size is small.

Study on Extraction of Effective Aroma Components from Formula Tobacco by the Supercritical CO2 Extraction Method and Its Aroma Composition

[Objectives]This study was conducted to improve the sensory quality and industrial availability of tobacco extracts.[Methods]The L9(34)design was adopted to carried out an extraction experiment,in which formula tobacco was extracted using supercritical CO2,and the extract was concentrated by vacuum distillation.Through sensory evaluation and chemical analysis,the function determination and chemical composition analysis of the tobacco extracts were carried out,and the optimal supercritical fluid extraction process was finally determined.[Results]The obtained optimal supercritical fluid extraction conditions were as follows:extraction temperature 55℃,extraction pressure 25 MPa,CO2 flow rate of 20 L/h,and entrainer of 95%ethanol.The tobacco extract obtained under the optimal conditions endowed the cigarettes with full and delicate aroma,less irritation and clean aftertaste and made the flavor of the cigarettes overall coordinated and softer,so the sensory quality was significantly improved.[Conclusions]The tobacco extract obtained by the supercritical CO2 extraction method from formula tobacco can effectively improve the quality of cigarettes.

Robust Variance Components Estimation in the PERG Mixed Distributions of Empirical Variances—PEROBVC Method

A mixed distribution of empirical variances, composed of two distributions the basic and contaminating ones, and referred to as PERG mixed distribution of empirical variances, is considered. In the paper a robust inverse problem solution is given, namely a (new) robust method for estimation of variances of both distributions—PEROBVC Method, as well as the estimates for the numbers of observations for both distributions and, in this way also the estimate of contamination degree.

"Three-Component" Digital Prospecting Method: A New Approach for Mineral Resources Quantitative Prediction and Assessment

Three-component' method consists of three close-connected aspects: geological anomaly, diversity of mineralization and mineral deposit spectrum. All these three concepts are not new separately, but it is a new approach to combine these three aspects in one single concept for quantitative mineral resources prediction and assessment and it is also the first time to conduct a more detailed study in each aspect. Investigation and clarification of geological anomalies, diversity of mineralization and spectrum of mineral deposits are realized by digitization and quantification of ore forming controlling factors, ore-existing symbols or marks, characteristics of mineralization and regulation of ore-genesis and laws of distribution. These procedures lead to construction of a 'digital model' for mineral resources prediction and assessment.

Improved Measurement Method of Circularly-Polarized Antennas Based on Linear-Component Amplitudes

An improved measurement method of circularly-polarized (CP) antennas based on linear-component amplitudes is proposed in this paper. By utilizing two sets of orthogonal linear polarization (LP) amplitudes, measurement on axial ratio (AR) of CP antennas can be realized without phase information. However, the rotation sense of the co-polarization cannot be determined due to the absence of the phase information. Above problem is discussed here for the first time, and a solution is presented to determine the rotation sense of the co-polarization by using common auxiliary CP antennas. In addition, there will be some particular cases with large errors in actual measurement. Here a corresponding solution method is given. Finally, co-polarization and cross-polarization patterns can be further obtained from AR results. To verify this improved method, a self-developed CP microstrip array was measured. The measured results are in agreement with the simulated results, which prove this method is correct, effective and practical.

Response Spectrum Method for Extreme Wave Loading With Higher Order Components of Drag Force

反应系列修理近海极端波浪影响的结构基于更高的顺序部件被调查非线性拖力量。这样，当一个团属于轻伸臂柱体，他们的相应变丑反应系列被利用自由系统的概括的单个度估计，钢夹克衫平台被简化。基于在波斯湾区域记录的波浪数据，相应于不同回来时期的极端波浪装载条件被施加在上近海结构。因此， drag 力量的更高的顺序部件的效果被考虑，与为不同的海的线性化的状态相比，表面铺平。什么时候基本时期近海结构是波浪装载的大约三分之一个主要时期，结果显示线性化拖学期不能够完成一个可靠变丑反应系列。

Higher-order principal component pursuit via tensor approximation and convex optimization

Recovering the low-rank structure of data matrix from sparse errors arises in the principal component pursuit （PCP）. This paper exploits the higher-order generalization of matrix recovery, named higher-order principal component pursuit （HOPCP）, since it is critical in multi-way data analysis. Unlike the convexification （nuclear norm） for matrix rank function, the tensorial nuclear norm is stil an open problem. While existing preliminary works on the tensor completion field provide a viable way to indicate the low complexity estimate of tensor, therefore, the paper focuses on the low multi-linear rank tensor and adopt its convex relaxation to formulate the convex optimization model of HOPCP. The paper further propose two algorithms for HOPCP based on alternative minimization scheme： the augmented Lagrangian alternating direction method （ALADM） and its truncated higher-order singular value decomposition （ALADM-THOSVD） version. The former can obtain a high accuracy solution while the latter is more efficient to handle the computationally intractable problems. Experimental results on both synthetic data and real magnetic resonance imaging data show the applicability of our algorithms in high-dimensional tensor data processing.

Kernel Generalization of Multi-Rate Probabilistic Principal Component Analysis for Fault Detection in Nonlinear Process

In practical process industries,a variety of online and offline sensors and measuring instruments have been used for process control and monitoring purposes,which indicates that the measurements coming from different sources are collected at different sampling rates.To build a complete process monitoring strategy,all these multi-rate measurements should be considered for data-based modeling and monitoring.In this paper,a novel kernel multi-rate probabilistic principal component analysis(K-MPPCA)model is proposed to extract the nonlinear correlations among different sampling rates.In the proposed model,the model parameters are calibrated using the kernel trick and the expectation-maximum(EM)algorithm.Also,the corresponding fault detection methods based on the nonlinear features are developed.Finally,a simulated nonlinear case and an actual pre-decarburization unit in the ammonia synthesis process are tested to demonstrate the efficiency of the proposed method.

Heat Transfer Analysis of Two Kinds of Mechanically Jointed GBST1308/CuCrZr Plasma Facing Components of EAST

Doped graphite GBST1308, mechanically jointed to CuCrZr alloys, will be applied on EAST superconducting as plasma facing material （PFM）. Two joint structures called joint-1 and joint-2 were evaluated by means of thermal response tests using electron beam facility. The experimental results showed that the temperature differences of two joints were not significant, and the maximum surface temperature was about 1055℃ at a load of 4 MW/m^2, which had a good agreement with the simulated results by ANSYS code. The results indicated that the doped graphite GBST1308/CuCrZr mock-up can withstand heat flux deposition of 4 MW/m^2 except at the screw-fastened region, and joint-2 could be more suitable to higher heat flux region such as divertor target. But under the higher heat flux, both joints are unacceptable, an advanced PFM and its integration with the heat sink have to be developed, for example, vacuum plasma spraying tungsten coatings on the CuCrZr might be a good choice.

Efficient Fast Independent Component Analysis Algorithm with Fifth-Order Convergence

Independent component analysis （ICA） is the primary statistical method for solving the problems of blind source separation. The fast ICA is a famous and excellent algorithm and its contrast function is optimized by the quadratic convergence of Newton iteration method. In order to improve the convergence speed and the separation precision of the fast ICA, an improved fast ICA algorithm is presented. The algorithm introduces an efficient Newton＇s iterative method with fifth-order convergence for optimizing the contrast function and gives the detail derivation process and the corresponding condition. The experimental results demonstrate that the convergence speed and the separation precision of the improved algorithm are better than that of the fast ICA.

THREE-DIMENSIONAL STATIC ANALYSES FOR FGM PLATES WITH MEDIUM COMPONENTS AND DIFFERENT NET STRUCTURES

A new microelement method for the analyses of functionally graded structures was proposed. The key of this method is the maneuverable combination of two kinds of elements. Firstly, the macro elements are divided from the functionally graded material structures by the normal finite elements. In order to reflect the functionally graded distributions of materials and the microconstitutions in each macro-element, the microelement method sets up the dense microelements in every macro-element, and translates nodes to the same as the normal finite elements by the degrees of freedom of all microelemental the compatibility conditions. This microelement method can fully reflect the micro constitutions and different components of materials, and its computational elements are the same as the normal finite elements, so it is an effective numerical method for the analyses of the functionally graded material structures. The three-dimensional analyses of functionally graded plates with medium components and different micro net structures are given by using the microelement method in this paper. The differences of the stress contour in the plane of functionally graded plates with different net microstructures are especially given in this paper.