Semisupervised Dimensionality Reduction and Classification Through Virtual Label Regression

Semisupervised dimensionality reduction has been attracting much attention as it not only utilizes both labeled and unlabeled data simultaneously, but also works well in the situation of out-of-sample. This paper proposes an effective approach of semisupervised dimensionality reduction through label propagation and label regression. Different from previous efforts, the new approach propagates the label information from labeled to unlabeled data with a well-designed mechanism of random walks, in which outliers are effectively detected and the obtained virtual labels of unlabeled data can be well encoded in a weighted regression model. These virtual labels are thereafter regressed with a linear model to calculate the projection matrix for dimensionality reduction. By this means, when the manifold or the clustering assumption of data is satisfied, the labels of labeled data can be correctly propagated to the unlabeled data; and thus, the proposed approach utilizes the labeled and the unlabeled data more effectively than previous work. Experimental results are carried out upon several databases, and the advantage of the new approach is well demonstrated.

A field study on the conversion ratio of phytoplankton biomass carbon to chlorophyll-a in Jiaozhou Bay, China

A one-year field study was conducted to determine the conversion ratio of phytoplankton biomass carbon (Phyto-C) to chlorophyll-a (Chl-a) in Jiaozhou Bay, China. We measured suspended particulate organic carbon (POC) and phytoplankton Chl-a samples collected in surface water monthly from March 2005 to February 2006. The temporal and spatial variations of Chl-a and POC concentrations were observed in the bay. Based on the field measurements, a linear regression model II was used to generate the conversion ratio of Phyto-C to Chl-a. In most cases, a good linear correlation was found between the observed POC and Chl-a concentrations, and the calculated conversion ratios ranged from 26 to 250 with a mean value of 56 A mu g A mu g(-1). The conversion ratio in the fall was higher than that in the winter and spring months, and had the lowest values in the summer. The ratios also exhibited spatial variations, generally with low values in the near shore regions and relatively high values in offshore waters. Our study suggests that temperature was likely to be the main factor influencing the observed seasonal variations of conversion ratios while nutrient supply and light penetration played important roles in controlling the spatial variations.

Prediction of soil adsorption coefficients from retention parameters on three reversed-phase liquid chromatographic columns

Reversed-phase high-performance liquid chromatographic (RP-HPLC) retention parameters, which are determined by the intermolecular interactions in retention process, can be considered as the chemical molecular descriptors in linear free energy relationships (LFERs). On the basis of the characterization and comparison of octadecyl-bonded silica gel (ODS), cyano-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns with linear solvation energy relationships (LSERs), a new multiple linear regression model using RP-HPLC retention parameters on ODS and CN columns as variables for estimation of soil adsorption coefficients was developed. It was tested on a set of reference substances from various chemical classes. The results showed that the multicolumn method was more promising than a single-column method was for the estimation of soil adsorption coefficients. The accuracy of the suggested model is identical with that of LSERs.

Mechanical effects of the self-organization of dislocations and related critical characteristics

The effects of the dislocation pattern formed due to the self-organization of the dislocations in crystals on the macroscopic hardening and dynamic internal friction (DIF) during deformation are studied. The classic dislocation models for the hardening and DIF corresponding to the homogeneous dislocation configuration are extended to the case for the non-homogeneous one. In addition, using the result of dislocation patterning deduced from the non-linear dlislocation dynamics model for single slip, the correlation between the dislocation pattern and hardening as well as DIF is obtained. It is shown that in the case of the tension with a constant strain rate, the bifurcation point of dislocation patterning corresponds to the turning point in the stress versus strain and DIF versus strain curves. This result along with the critical characteristics of the macroscopic behavior near the bifurcation point is microscopically and macroscopically in agreement with the experimental findings on mono-crystalline pure aluminum at temperatures around 0.5T(m). The present study suggests that measuring the DIF would be a sensitive and useful mechanical means in order to study the critical phenomenon of materials during deformation.

Flow-induced vibrations of long circular cylinders modeled by coupled nonlinear oscillators

The dynamics of long slender cylinders undergoing vortex-induced vibrations (VIV) is studied in this work. Long slender cylinders such as risers or tension legs are widely used in the field of ocean engineering. When the sea current flows past a cylinder, it will be excited due to vortex shedding. A three-dimensional time domain model is formulated to describe the response of the cylinder, in which the in-line (IL) and cross-flow (CF) deflections are coupled. The wake dynamics, including in-line and cross-flow vibrations, is represented using a pair of non-linear oscillators distributed along the cylinder. The wake oscillators are coupled to the dynamics of the long cylinder with the acceleration coupling term. A non-linear fluid force model is accounted for to reflect the relative motion of cylinder to current. The model is validated against the published data from a tank experiment with the free span riser. The comparisons show that some aspects due to VIV of long flexible cylinders can be reproduced by the proposed model, such as vibrating frequency, dominant mode number, occurrence and transition of the standing or traveling waves. In the case study, the simulations show that the IL curvature is not smaller than CF curvature, which indicates that both IL and CF vibrations are important for the structural fatigue damage.

中国主要森林生态系统碳储量和碳收支评估

森林作为陆地生态系统中主要的植被类型在全球碳循环研究中有着十分重要的作用，而森林资源清样调查资料以其系统性、科学性、连续性等优点在森林生态系统碳循环研究中具有十分重要的地位。本研究以中国主要森林植被类型为研究对象，基于中国森林资源清样调查资料（FID），采用建立的生物气候生产力模型和反映林龄和蓄积量共同影响的生产力回归模型分别估计了中国油松林和主要造林树种的生产力;利用改进的材积源生物量法估算了中国主要森林植被类型的碳储量;并基于多元线性回归方法和因子分析法探讨了林业用地以及气候因子对中国森林植被碳储量的影响;同时，结合生物地球化学循环模型CENTURY模型评估了中国森林生态系统的碳收支。主要研究结果如下： 1建立了中国油松林生物气候生产力模型NPPa=［0.331n（V／A）+0.18］*3000（1-e-0.00096‘哪，根据油松林的森林资源清样调查资料和气候资料估算的中国油松林生产力平均为7.82Mg•ha-1•yr-1，其变化幅度为3.32-11.87Mg•ha-1•yr-1，其分布表现为南高北低的趋势。生产力较高的区域主要分布在东部和南部（四川、湖北、河南、辽宁等省），均大于7.7Mg•ha-1•yr-1;生产力较低的区域主要分布在北部和西部较为干旱的区域（内蒙古），NPP均低于5.5Mg•ha-1•yr-1：油松林集中分布区（陕西、山西）生产力处于中等水平，在5.5-7.7Mg•ha-1•yr-1之间。 2基于森林资源清样调查资料评估了中国五种主要造林树种（落叶松Larix，油松Pinusstabulaeformis，马尾松Pinusmassoniana，杉木Cunninghamialanceolata，杨树Populus）的生产力，分别为8.43、5.75、4.42、4.41、7.33Mg•ha-1•yr-1，低于世界平均生产力水平，主要原因可能是这五种造林树种大都处于未成熟阶段，表明中国造林树种在提高中国森林生态系统的固碳能力方面有很大的潜力。 3基于两次（第三次和第四次）森林资源清查资料和改进的材积源生物量法评估了中国森林的碳储量，分别为3.48和3.78PgC（1Pg＝1015g）。 基于多元线性回归模型探讨了林业用地变化对森林植被碳储量的影响。分析表明：在森林平均林龄减小的情况下，森林植被碳储量有增加的趋势;而森林碳储量随森林面积的增加而增加。当平均林龄增加10年，全国森林面积增加1*104ha时，全国森林植被的碳储量将增加54.51Tg（1Tg＝1012g），表明我国森林植被碳储量取决于自然和人为因素共同作用。 采用因子分析方法探讨了气候变化对森林植被碳储量的影响，分析表明：气温是森林植被碳储量的主要限制因子。当气温升高时，森林植被碳储量有降低的趋势;降水与森林植被碳储量呈正相关，随降水的增加森林植被碳储量增加。在年均温升高4℃，年降水量增加10％;年均温升高4℃，年降水量不变;年均温升高4℃，年降水量减少10％三种气候变化情景下，我国森林植被碳储量的增加量分别为：9.19Tg、6.67Tg和4.15Tg。 4基于生物地球化学循环模型模拟的中国森林生态系统的碳收支为0.17PgC，中国森林表现为一个巨大的碳汇。其中，西南地区森林碳收支占44％，华东及西北地区的森林碳收支总和不足14%。

Processing network models of energy/environment systems

Processing networks are a variant of the standard linear programming network model which are especially useful for optimizing industrial energy/environment systems. Modelling advantages include an intuitive diagrammatic representation and the ability to incorporate all forms of energy and pollutants in a single integrated linear network model. Added advantages include increased speed of solution and algorithms supporting formulation. The paper explores their use in modelling the energy and pollution control systems in large industrial plants. The pollution control options in an ethylene production plant are analyzed as an example. PROFLOW, a computer tool for the formulation, analysis, and solution of processing network models, is introduced.

黄土丘陵区小流域表层土壤的有机碳密度及其空间分布

通过野外调查和室内分析,采用多元线性逐步回归和地理信息系统(GIS)相结合的方法,研究了黄土丘陵区燕沟流域表层(0~20 cm)土壤的有机碳密度、空间分布及其与土地利用类型和地形因子等的关系。结果表明,流域表层土壤有机碳密度平均为1.72 kg/m2,变幅为0.97~2.93 kg/m2;土地利用类型是影响土壤有机碳密度变化的首要因子;流域土壤有机碳密度呈镶嵌的树枝状和条带状空间分布格局,其高值斑块区与乔木林地和灌木林地的分布一致,中值斑块区与草地和川坝地的分布一致,低值斑块区与梯田、果园、坡耕地、疏林地和未成林地的分布一致。流域表层土壤有机碳总储量为76.81×103t。

中国水蚀土壤抗剪强度研究

利用野外测试数据、土壤样品的室内理化分析数据和参考文献数据 ,对水蚀区范围内水土流失过程中的土壤抗剪强度进行了初步研究 ,建立了中国水土流失土壤抗剪强度的回归模型 ,总结出水蚀区范围内水蚀过程中有关土壤抗剪强度的 3条结论 :影响水土流失过程中土壤抗剪强度的主导因素是容重、粉 /黏、土壤含水量、土壤有机质含量 ;抗剪强度随土壤类型发生有规律的变化 ;抗剪强度在中国水蚀区范围内有较明显的空间分异规律 (包括水平分异规律和垂直剖面构型规律 )

装配系统中缓冲区容量的研究

为了确定装配系统中的缓冲区容量,在建立缓冲区状态数学模型的基础上,根据随机过程的原理,提出了缓冲区被充满概率和缓冲区容量之间的函数关系。以缓冲区被充满概率最小化为目标,确定合理的缓冲区容量。最后给出一种递进算法,通过回归方程计算缓冲区对装配工位生产率的影响,逐步求出由多个工位组成的整个装配系统各个工位之间的缓冲区容量。

Pg震相走时的各向异性影响及各向异性结构成像

As the first arrival of seismic phase in deep seismic sounding, Pg is the important data for studying the attributes of the sedimentary layers and the shape of crystalline basement because of its high intensity and reliable detection. Conventionally, the sedimentary cover is expressed as isotropic, linear increasing model in the interpretation of Pg event. Actually, the sedimentary medium should be anisotropic as preferred cracks or fractures and thin layers are common features in the upper crust, so the interpretation of Pg event needs to be taken account of seismic velocity anisotropy. Traveltime calculation is the base of data processing and interpretation. Here, we only study the type of elliptical anisotropy for the poor quality and insufficiency of DSS data. In this thesis, we first investigate the meaning of elliptical anisotropy in the study of crustal structure and attribute, then derive Pg event’s traveltime-offset relationship by assuming a linear increasing velocity model with elliptical anisotropy and present the invert scheme from Pg traveltime-offset dataset to seismic velocity and its anisotropy of shallow crustal structure. We compare the Pg traveltime calculated by our analytic formula with numerical calculating method to test the accuracy. To get the lateral variation of elliptical anisotropy along the profiling, a tomography inversion method with the derived formula is presented, where the profile is divided into rectangles. Anisotropic imaging of crustal structure and attribute is efficient method for crust study. The imaging result can help us interprete the seismic data and discover the attribute of the rock to analyze the interaction between layers. Traveltime calculation is the base of image. Base on the ray tracing equations, the paper present a realization of three dimension of layer model with arbitrary anisotropic type and an example of Pg traveltime calculation in arbitrary anisotropic type is presented. The traveltime calculation method is complex and it only adapts to nonlinear inversion. Perturbation method of travel-time calculation in anisotropy is the linearization approach. It establishes the direct relation between seismic parameters and travetime and it is fit for inversion in anisotropic structural imaging. The thesis presents a P-wave imaging method of layer media for TTI. Southeastern China is an important part of the tectonic framework concerning the continental margin of eastern China and is commonly assumed to comprise the Yangtze block and the Cathaysia block, the two major tectonic units in the region. It’s a typical geological and geophysical zone. In this part, we fit the traveltime of Pg phase by the raytracing numerical method. But the method is not suitable here because the inefficiency of numerical method and the method itself. By the analytic method, we fit the Pg and Sg and get the lateral variation of elliptical anisotropy and then discuss its implication. The northeastern margin of Qinghai-Tibetan plateau is typical because it is the joint area of Eurasian plate and Indian plate and many strong earthquakes have occurred there in recent years．We use the Pg data to get elliptical anisotropic variation and discuss the possible meaning.

地理信息系统支持下的滑坡灾害空间分析预测-以云南小江流域为例

As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.

对癌症生存者应对资源的研究

A survey study of cancer survivors was conducted to explore the coping resources, which buffers the life of cancer survivors against stressful situation. Participants reported coping strategies, positive affect and negative affect, personality, perceived social support, fighting spirit and helpless/hopeless as well as quality of life through a set of self-assessment questionnaire. The results indicated that the frequency of coping strategies used by cancer survivors from high to low were: growing, problem solving, seeking support,self-controlling, wishful thinking, and distancing. The correlational analysis indicated that among the six sets of coping strategies, growing was positively correlated most strongly with most of the dimensions in quality of life as well as positive affect. Among the five personality, Neuroticism was positively correlated most strongly with helpless/hopeless and negative affect; and was negatively correlated most strongly with fighting spirit and positive affect. Extraversion was positively correlated most strongly with positive affect and negatively correlated most strongly with helpless/hopeless; Agreeableness was negatively correlated most strongly with negative affect; Conscientiousness was positively correlated most strongly with fighting spirit. Subjects with higher score in quality of life reported higher frequency of coping strategies in growing and problem solving and less in wishful thinking. They also reported higher scores in Extraversion, Agreeableness, Conscientiousness as well as lower scores in Neuroticism. The regression analysis displayed that not negative affect but positive affect entered the regression model when all the psychological and social variables in the study were accounted for. Taken together, these data suggested that, growing was the most effective coping strategy among the six sets of strategies for cancer survivors to improve quality of life, to maintain positive affect and to enhance fighting spirit. Neuroticism was vulnerable to resist stressors; Extraversion, Agreeableness, and Conscientiousness were stress-resisted factors. Positive affect may has more adaptational significance than negative affect during chronic stress. These data also implicated that positive affect should be paid more attention to in coping research.