五结合一回归教学模式在中医诊断学中的应用

依据中医诊断学课程特点,对接新时代中医药高等教育要求,课程组积极构建“五结合一回归”教学模式,将理论教学与实践教学相结合,线下教学与线上教学相结合,第一课堂与第二课堂相结合,课程思政与思政课程相结合,过程性与终结性考核相结合,授课回归中医经典,强化中医思维培养,实现了知识、能力、素质、情感态度与价值的融合式发展,为中医药传承创新人才培养提供了新思路。

营销活动中的概率统计模型的应用

数理统计知识应用于社会生活的各个方面,在市场营销活动中也运用到许多概率统计模型。在本文中主要介绍了市场调查中的抽样调查模型、市场预测中的回归分析方法及营销决策模型的简单应用。

Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982–2010

Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.

Probabilistic Teleportation of an Arbitrary Two-Particle State and Its Quantum Circuits

Two simple schemes for probabilistic teleportation of an arbitrary unknown two-particle state using a non-maximally entangled EPR pair and a non-maximally entangled GHZ state as quantum channels are proposed. After receiving Alice＇s Bell state measurement results, Bob performs a collective unitary transformation on his inherent particles without introducing the auxiliary qubit. The original state can be probabilistically teleported. Meanwhile, quantum circuits for realization of successful teleportation are also presented.

Influencing Factors of Seed Long-distance Dispersal on a Fragmented Forest Landscape on Changbai Mountains,China

Seed long-distance dispersal(LDD) events are typically rare, but are important in the population processes that determine large-scale forest changes and the persistence of species in fragmented landscapes. However, previous studies focused on species dispersed via animal-mediated LDD, and ignored those dispersed by wind. The aim of this study was to assess the effects of canopy openness, edge, seed source, and patch tree density on the LDD of seeds by wind in forest. We collected birch seeds, a typical wind-dispersed species, throughout a larch plantation. We then assessed the relationship between birch LDD and each factor that may influence LDD of seeds by wind including distance to edge, canopy openness size, distance to mature forest, and the tree density of the larch plantation. We used univariate linear regression analysis to assess the influence of those factors on birch LDD, and partial correlations to calculate the contribution of each factor to LDD. The results showed that both canopy openness and edge had significant influences on birch LDD. Specifically, a negative relationship was observed between distance to edge and birch LDD, whereas there was a positive correlation between canopy openness size and LDD. In contrast, the distance to the mature forest was not correlated with birch LDD. Our results suggest that patch tree density could potently affect the probability of LDD by wind vectors, which provides novel and revealing insights regarding the effect of fragmentation on wind dynamics. The data also provide compelling evidence for the previously undocumented effect of habitat fragmentation on wind-dispersed organisms. As such, these observations will facilitate reasonable conservation planning, which requires a detailed understanding of the mechanisms by which patch properties hamper the delivery of seeds of wind-dispersed plants to fragmented areas.

Mapping methods for output-based objective speech quality assessment using data mining

Objective speech quality is difficult to be measured without the input reference speech.Mapping methods using data mining are investigated and designed to improve the output-based speech quality assessment algorithm.The degraded speech is firstly separated into three classes(unvoiced,voiced and silence),and then the consistency measurement between the degraded speech signal and the pre-trained reference model for each class is calculated and mapped to an objective speech quality score using data mining.Fuzzy Gaussian mixture model(GMM)is used to generate the artificial reference model trained on perceptual linear predictive(PLP)features.The mean opinion score(MOS)mapping methods including multivariate non-linear regression(MNLR),fuzzy neural network(FNN)and support vector regression(SVR)are designed and compared with the standard ITU-T P.563 method.Experimental results show that the assessment methods with data mining perform better than ITU-T P.563.Moreover,FNN and SVR are more efficient than MNLR,and FNN performs best with 14.50% increase in the correlation coefficient and 32.76% decrease in the root-mean-square MOS error.

Application of Grey System GM (1,1) model and unary linear regression model in coal consumption of Jilin Province

The data on the coal production and consumption in Jilin Province for the last ten years were collected,and the Grey System GM( 1,1) model and unary linear regression model were applied to predict the coal consumption of Jilin Production in 2014 and 2015. Through calculation,the predictive value on the coal consumption of Jilin Province was attained,namely consumption of 2014 is 114. 84 × 106 t and of 2015 is 117. 98 ×106t,respectively. Analysis of error data indicated that the predicted accuracy of Grey System GM( 1,1) model on the coal consumption in Jilin Province improved 0. 21% in comparison to unary linear regression model.

MIMO Soft-sensor Model of Nutrient Content for Compound Fertil- izer Based on Hybrid Modeling Technique

In compound fertilizer production, several quality variables need to be monitored and controlled simultaneously. It is very diifficult to measure these variables on-line by existing instruments and sensors. So, soft-sensor technique becomes an indispensable method to implement real-time quality control. In this article, a new model of multi-inputs multi-outputs （MIMO） soft-sensor, which is constructed based on hybrid modeling technique, is proposed for these interactional variables. Data-driven modeling method and simplified first principle modelingmethod are combined in this model. Data-driven modeling method based on limited memory partial least squares（LM-PLS） al.gorithm is used to build soft-senor models for some secondary variables.then, the simplified first principle model is used to compute three primary variables on line. The proposed model has been used in practicalprocess; the results indicate that the proposed model is precise and efficient, and it is possible to realize on line quality control for compound fertilizer process.

Fiscal Decentralization and Economic Growth in China: A Meta-Regression Analysis

In order to test whether the major empirical results on the ＂relationship between fiscal decentralization and economic growth in China＂ are affected by study characteristics, this paper conducts a meta-analysis of the major existing empirical literature. Our analysis indicates that some empirical results on how China＇s jqscal decentralization affects economic growth are subject to different study characteristics. In particular, empirical results that fiscal decentralization has ＂significant positive effect＂ on economic growth are subject to such study characteristics as ＂region, labor and capital growth rate, other reforms and intra-budget capital.＂ Through the funnel plot asymmetry test, the problem of publication bias is found to exist in the sampled literature and is concentrated in spending decentralization.

Analysis of Factors Determining the Demand for Water： A Case Study of Sabie Administrative Post, Moamba District, Mozambique

Water is an important resource for human being. However, it has been increasingly becoming the limited resource. Therefore, the debate of water issues has been centered in mechanisms to implement sustainable water management. Hence, understanding the determinants of water demand might help design appropriate water management policies, however, they are not known in Mozambique. Due to the lack of knowledge about the determinants of water demand in Mozambique in general and in Sabi6 in particular, the present study was conducted to analyse the factors determining the water demand for irrigation and domestic use using a linear regression model and travel cost method, respectively. The results show that an increase in 1 h of irrigation time increases the quantity demanded of irrigation water by 362.04 m3 and an increase in one irrigation per week increases the quantity demanded of irrigation water by 1,065.61 m3. Additionally, the results show that an increase in 1% of time spent in water collection decreases the number of trips by 0.3% and an increase in 1% in the number of household members involved in water collection decreases the number of the water collection trips by 0.23%. Household having private taps have less number of trips collecting water compared to those collecting water from public taps and boreholes as well as rivers. Therefore, the water demand for irrigation is determined by time spent for irrigation per day and the number of irrigations per week, and water demand for domestic use is determined by time spent for water collection, number of household members involved in water collection, the volumes of the containers used to collect water, the number of containers used to collect water, the quantity of water consumed by the household as well as the main source of water （river, boreholes and public tap）.

Variable Selection Procedures in Linear Regression Models with Screening Consistency Property

There are two fundamental goals in statistical learning： identifying relevant predictors and ensuring high prediction accuracy. The first goal, by means of variable selection, is of particular importance when the true underlying model has a sparse representation. Discovering relevant predictors can enhance the performance of the prediction for the fitted model. Usually an estimate is considered desirable if it is consistent in terms of both coefficient estimate and variable selection. Hence, before we try to estimate the regression coefficients β , it is preferable that we have a set of useful predictors m hand. The emphasis of our task in this paper is to propose a method, in the aim of identifying relevant predictors to ensure screening consistency in variable selection. The primary interest is on Orthogonal Matching Pursuit（OMP）.

Theory of numerical modeling of constitutive relation for geotechnical materials

Under the direction of the principle of interaction between plastic volumetric and shear strains, the general expression of constitutive relation for geotechnical materials has been derived within the framework of irreversible thermo- dynamics. The constitutive modeling, in fact, is an inverse problem that belongs to the medium inverse problems of model identification, which is expressed as a reversion of coefficient of differential equation. Thus the constitutive modeling of geotechnical materials will become the reversion of coefficient functions of the general expression of constitutive relation, which is carried out in the stress field （p,q） by means Of numerical techniques, so that is called numerical modeling. Applying the numerical modeling, a number of plasticity-based models for clay and sand have been obtained, which are able to characterize the fundamental features of deformation for geotechnieal materials. In addition, the approach of numerical modeling also can be applied to the situation of unsaturated soils by means of the Bishop＇s effective stress formula and Khalili＇s expression of effective stress parameter.

A Modified Chi-Squared Goodness-of-Fit Test

In goodness-of-fit tests, Pearson＇s chi-squared test is one of most widely used tools of formal statistical analysis. However, Pearson＇s chi-squared test depends on the partition of the sample space. Different constructions of the partition of the sample space may lead to different conclusions. Based on an equiprobable partition of sample space, a modified chi^quared test is proposed. A method for constructing the modified chi-squared test is proposed. As an application, the proposed test is used to test whether vectorial data come from an uniformity distribution defined on the hypersphere. Some simulation studies show that the modified chisquared test against different alternative is robust.

Are There Differences in the Response of Natural Stand and Plantation Biomass to Changes in Temperature and Precipitation?A Case for Two-needled Pines in Eurasia

A comparative discussion of the advantages and disadvantages of natural stands and plantations,including in terms of their productivity and stability,began from the moment of the first forest plantings and continues to this day.In the context of the progressive replacement of natural forests by plantations due to deforestation,the question of how will change the carbon storage capacity of forest cover when replacing natural forests with artificial ones in a changing climate becomes extremely relevant.This article presents the first attempt to answer this question at the transcontinental level on a special case for two-needled pine trees(subgenus Pinus L.).The research was carried out using the database compiled by the authors on the single-tree biomass structure of forest-forming species of Eurasia,in particular,data of 1880 and 1967 of natural and plantation trees,respectively.Multi-factor regression models are calculated after combining the matrix of initial data on the structure of tree biomass with the mean January temperature and mean annual precipitation,and their adequacy indices allow us to consider them reproducible.It is found that the aboveground and stem biomass of equal-sized and equal-aged natural and plantation trees increases as the January temperature and precipitation rise.This pattern is only partially valid for the branches biomass,and it has a specific character for the foliage one.The biomass of all components of plantation trees is higher than that of natural trees,but the percent of this excess varies among different components and depends on the level of January temperatures,but does not depend at all on the level of annual precipitation.A number of uncertainties that arose during the modeling process,as well as the preliminary nature of the obtained regularities,are noted.