Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

Mandibular morphometric variation among Chinese cercopithecoids and the unique structure of the snub-nosed monkey (Rhinopithecus) mandible

In order to understand how mandibular structure differs among the Chinese cercopithecoids (Rhinopithecus, Trachypithecus and Macaca), particularly the uniqueness of the snub-nosed monkeys (Rhinopithecus), we analysed ten mandibular measurements by principal components analysis (PCA), and examined scaling patterns. The results provided by the PCA illustrated differences due to size among the cercopithecoids and the relationship between colobines (Trachypithecus and Rhinopithecus) and cercopithecines, in which macaques (Macaca) are included. Allometric analysis indicated that, biomechanically, there is not a marked difference between macaques and leaf-eating monkeys. This may be associated with the fact that both share some similar ecology and niches in south and southwest China. The snub-nosed monkeys exhibit a significantly more robust mandible, evident in the symphysis, corpus, condyle, and masticatory momentum arm. This supports the hypothesis, based on the study of dental structure, that Rhinopithecus is a unique group in Asian Old World monkeys (OWMs) and has developed some unique characteristics in order to adapt to the tough food available in the severe cold climate of the Plateaux of Qinghai-Tibet, Yun-Gui and Qingling in China.

黄土丘陵沟壑区纸坊沟小流域农业生态安全态势变化的驱动力分析

以黄土丘陵沟壑区纸坊沟小流域为研究对象,利用1985—2006年调查和监测资料,综合现有研究成果,将主成分分析和通径分析方法相结合,分析可能影响农业生态安全态势变化的各因子,探讨农业生态安全态势变化的驱动力。结果表明:自然条件是影响黄土丘陵沟壑区纸坊沟小流域农业生态安全态势变化的基础,人文社会经济条件是其变化的主要驱动力,具体可归纳为经济发展、人口压力、流域产业结构调整和农业科技进步4类因子;此外,国家和区域的相关政策、农业产业链与资源量相关度对农业生态安全也有一定影响。

荞麦(Fagopyrum tataricum Gaertn.和F. esculentum Moench.)对紫外线B辐射的响应研究

近二十多年来，基于对臭氧层衰减、紫外线B（UV-B）增强的担心，研究者希望了解到紫外线辐射对不同作物的影响情况，增强UV-B辐射条件下是否对作物的生长发育、产量质量构成威胁。在本试验中，我们首先探讨了双子叶作物黄瓜（Cucumis sativus）和大豆（Glycine max）对不同紫外波段的生物效应[分别为B-UVA（315-400 nm），N-UVA（315-340 nm），B-UVB（275-400 nm）和N-UVB（290-340 nm），UV-（>400nm）作对照]。我们观察到所有的UV波段处理都使黄瓜和大豆的生长受到抑制，并且细胞受到不同程度的氧化伤害；UV波段处理的作用效果与不同波段的紫外有效生物辐射剂量有关。处理差异在UV-B波段内部和UV-A波段内部同样存在。植物生长UV辐射公式（BSWF）能很好的预测本试验UV-B波段内的平均植物效应，但不能预测UV-A波段的植物效应。短波UV-A的生物作用强于长波UV-A。光合色素的变化与UV波谱差异和种间差异有关。在高的紫外/可见光背景下，UV-A处理同UV-B同样导致光合色素的降低，但黄瓜类胡萝卜素/叶绿素比例升高。与其他研究者的试验结果比较后，我们认为紫外线B辐射的生物效应一致性很高，但紫外线A波段的生物学效应存在较大争议。因此我们在本试验的基础上仅进行荞麦[苦荞(Fagopyrum tataricum Gaertn.)和甜荞(Fagopyrum esculentum Moench.)]对紫外线B波段的响应研究。 我们对苦荞品种-圆籽荞进行了连续两个生长季节的大田半控制试验以观察UV-B辐射对苦荞生长、发育、产量及叶片色素的影响；试验小区进行降低UV-B、近充足UV-B和增强UV-B辐射处理。我们的试验表明在不同强度UV-B辐射下苦荞的生长、地上部生物量积累及最终产量都有所下降，但苦荞的发育加快；当前条件下的日光紫外线B辐射对植物生长和产量也造成负面影响。植物光合色素被日光及增强UV-B辐射降低；UV化合物及卢丁含量在中低剂量的UV-B辐射强度下显著升高，但在高剂量的增强UV-B辐射下短期升高后迅速下降。我们的试验表明苦荞是一个对UV-B高度敏感的作物。苦荞对UV-B的敏感性与UV-B剂量、外界环境因素及生长季节有关。 单个苦荞品种的试验结果使我们认识到外界UV-B辐射已经对苦荞生长发育构成逆境条件，未来全球气候变化条件下增强紫外线B辐射可能使其处于更不利的生长环境中。因此我们有进行了多个种群进行UV-B响应观察并筛选耐性种群。我们对15个苦荞种群进行增强UV-B辐射处理（6.30 kJ m2 UV-BBE，模拟当地25%的臭氧衰减），我们观察苦荞UV-B辐射效应存在显著的种内差异，UV-B辐射对多数种群具有抑制作用，但对一些种群还有刺激作用。我们采用主成分分析方法与作物UV-B响应指数（RI）来评价苦荞作物UV-B辐射耐性。我们发现作物的UV-B耐性不仅与其原产地背景UV-B强度有关，而且与作物相对生长效率、次生代谢产物含量（如卢丁）及其他因素有关。我们观察到苦荞伸展叶总叶绿素变化与UV-B耐性成正相关；室内苦荞幼苗的UV-B辐射致死试验表明：苦荞种群死亡率与其UV-B耐性成负相关。 此外，我们对甜荞的UV-B辐射响应也进行了初步研究。选取美姑甜荞、巧家甜荞和云龙甜荞进行5个梯度的增强UV-B辐射室外模拟试验。我们观察到UV-B辐射显著降低了甜荞的生长、生物量及产量；并严重影响了甜荞的生殖生长，降低了花序数、种子数和结实率；并且UV-B辐射对甜荞的抑制作用存在显著的剂量效应。三种甜荞品种存在显著的种内差异，其中美姑品种UV-B耐性最强，且膜脂受UV-B辐射氧化伤害最小，这与该品种UV-B辐射下较高的GR酶活性、APX酶活性和PPO酶活性、以及含量更高的抗坏血酸有关。甜荞的次生代谢也受到增强UV-B辐射的影响，其香豆酰类化合物在UV-B辐射下升高显著，而槲皮素含量也在高剂量UV-B辐射下有所增加；卢丁含量依赖UV-B辐射剂量而变化，中低剂量UV-B辐射下其卢丁含量逐渐升高，但在高剂量辐射下逐渐下降。 通过对生长在高海拔地区的荞麦作物(苦荞和甜荞)进行的室外研究，我们认识到作物不同品种存在很大的耐性差异，这就为UV-B耐性育种创造了有利条件。进一步加大荞麦种质资源筛选力度并深入认识荞麦抗性机理，在此基础上通过杂交或其他基因融合手段培育抗性品种，对高剂量UV-B辐射地区的荞麦产量的提高将起到重要推动作用，并使荞麦生产能有效应对未来全球气候变化条件下UV-B辐射可能升高的威胁。 During last few decades, due to concern of ozone layer depletion and enhancement of ultraviolet B radiation（UV-B, 280-315 nm), the agronomist want to know the responses of different crop species to UV-B. In the first experiment of our study, the effect of different UV band [B-UVA（315-400 nm), N-UVA（315-340 nm), B-UVB（275-400 nm), N-UVB（290-340 nm）and UV-（>400nm, as control)] on the cucumber（Cucumis sativus）and soybean（Glycine max）were investigated in growth room. Spectra-dependent differences in growth and oxidation indices existed within UV-A bands as well as UV-B bands. The general biological effects of different band were UV- ＜ B-UVA＜ N-UVA＜N-UVB＜B-UVB. The plant growth biologically spectra weighting function（BSWF）matched well with average plant response in UV-B region, but not in UV-A region. Shorter UV-A wavelength imposed more negative impact than longer UV-A wavelength did in both species. The effect on photosynthetic pigment was related to different UV bands and different species. The photosynthetic pigment content was decreased by UV-A spectra as well as UV-B spectra. In comparison with the results of previous studies, we found that the wavelength-dependent biological effect of ultraviolet B radiation has high consistency, but the biological effect of ultraviolet-A radiation was inconsistent. We narrow our following study on the effect of ultraviolet B radiation on the buckwheat（tartary buckwheat and common buckwheat). The tartary buckwheat（Fagopyrum tataricum Gaertn.）cultivars Yuanziqiao was grown in the sheltered field plots for two consecutive seasons under reduced, near-ambient and two supplemental levels of UV-B radiation. The crop growth, photosynthetic pigments, total biomass, final seed yield and thousand-grain weight were decreased by near-ambient and enhanced UV-B radiation, while crop development was promoted by enhanced UV-B radiation. Leaf rutin concentration and UV-B absorbing compound was generally increased by UV-B with the exception of 8.50 kJ m-2 day-1 supplemental levels. Our results showed that tartary buckwheat is a potentially UV-B sensitive species. Study on one cultivars showed that ambient solar radiation had present a stress to tartary buckwheat. This makes it necessary to observe the UV-B response of many cultivars and screen tolerant cultivars. Fifteen populations of tartary buckwheat were experienced enhanced UV-B radiation simulating 25% depletion of the stratospheric ozone layer in Kunming region, and plant responses in growth, morphology and productivity were observed. Principal components analysis（PCA）was used to evaluate overall sensitivity of plant response to UV-B as well as response index. The different populations exhibited significant differences in responses to UV-B. The photosynthetic pigments of young seedlings were also affected significantly under field condition. On the other hand, the healthy seedlings of different populations were exposed to the high level of UV-B radiation in growth chambers to determine the plant lethality rate. The plant tolerance evaluated by multivariate analysis was positively related to total plant chlorophyll change, but negatively related to lethality rate. In other hand, the UV-B responses of the other important cultivated buckwheat species, common buckwheat（Fagopyrum esculentum Moench.), were also studied preliminarily. Three widespread cultivated variety（Meigu, Qiaojia and Yunlong cultivars）were provided with five level of enhanced UV-B radiation outdoors. We observed that the crop growth, development and production were significantly decreased, and reproductive production, like anthotaxy number, seed number and seed setting ratio, was also decreased. Dose-dependent inhibition effect caused by enhanced UV-B radiation also existed in common buckwheat. Significant intraspecific difference existed in those three cultivars. The Meigu cultivars with dwarfed growth and lower production have highest UV-B tolerance as well as lowest damage in cell membrane, this could be associated with profound enhancements of glutathione reductase（GR）activity, ascorbate peroxidase activity and polyphenol oxidase activity as well as higher ascorbic acid concentration. The secondary metabolism was also affected by UV-B radiation, with profound elevation of coumarin compound and moderate increase of quercetin concentration. Rutin concentration was peaked in 5kJ m-2 UV-B. The contrasting effect of UV-B radiation on different populations indicated that there existed abundant genetic resources for selecting tolerant populations of common and tartary buckwheat. Much effort needed be pose on screening of buckwheat germplasm and clarification of mechanism of buckwheat tolerance to UV-B. On this base the tolerant cultivars could be bred by hybridization and other gene transfusion method, this would help increase buckwheat yield in high ambient UV-B region and counteract the effect of possible enhanced UV-B radiation in future.

落叶栎树在中国的地理替代分布及其气候制约

栎属（Quercus L.）按落叶习性可自然分为落叶类型和常绿类型，我国落叶栎类共有20个种和9个变种。落叶栎是栎属中较为进化的一个类群，源于横断山区和云贵高原;除新疆外，全国各省都有落叶栎的天然分布，一些亲缘关系密切的树种之间呈现出较为明显的地理替代分布格局。本研究的目的在于：（1）应用BIOCLIM模型模拟预测落叶栎类植物的潜在分布区，分析其目前的分布格局以及下一步的发展趋势;（2）分析造成落叶栎树地理替代分布格局的主导气候因子，探讨气候因子对不同落叶栎树种地理分布格局的制约作用。 本文以16个在中国具有成片天然分布区的落叶栎树种（包括变种）为研究对象，利用已核对的标本数据以及13个栅格化环境变量图层（分辨率为1km×1km），按照分类（全国广布型、南方广布型、南方狭域型和北方狭域型）和不分类（全部16种）两种处理方式，通过BIOCLIM模型模拟得出了它们的潜在核心分布区和潜在边缘分布区。在运行模型之前，除必选的海拔高程图层外，采用了主成分分析（PCA）的方法从30个候选的气候变量图层中筛选出对相应落叶栎树种的地理分布格局有较大影响的12个图层作为输入图层。然后，本文通过比较两种处理所得模拟结果的ROC（Receiver Operator Characteristic）曲线下方面积AUC（Area Under the Curve），同时结合文献分析来推测不同落叶栎树种地理分布格局的稳定性及发展趋势。结果表明，在无人类活动干扰且种源传播不受阻碍的情况下，全国广布型和南方广布型落叶栎目前的分布格局在维持稳定的基础上有向周边地区扩展的趋势;南方狭域型和北方狭域型落叶栎的分布格局则基本保持稳定，短期内发生扩散的可能很小。 论文中计算了每个落叶栎树种所在分布范围的气候指标（共11个），以便进行下一步的研究。以蒙古栎（Q. mongolica）、辽东栎（Q. wutaishanica）与槲栎（Q. aliena）、锐齿槲栎（Q. aliena var. acuteserrata）、北京槲栎（Q. aliena var. pekingensis）这两组地理替代系列为研究对象，分别采用独立样本t检验和单因素方差分析的方法，分析了气候因子对其地理替代分布格局的主导作用。结果表明，冬季的低温、较高的气温年较差和大陆度是蒙古栎向东北替代辽东栎的主要原因;槲栎向北被北京槲栎和锐齿槲栎替代的主要原因是生长季高温和冬季高温对其分布的双重制约;除最暖月（7月）最高温外，北京槲栎的各项水热指标与另两种槲栎均存在极显著差异，对冬季低温和较大的年较差的适应可能是限制其向南分布的主要原因。 本研究最后部分的内容是对不同类型落叶栎分布区的气候参数进行的主成分分析。结果表明，生长季温度是制约落叶栎分布的最主要的气候因子;寒冷程度和冬季的低温则对其在大尺度范围的扩散有较大影响;另外，降水、年较差与大陆度对落叶栎的向北分布也起着重要的作用。

Mobility and profiles of polychlorinated dibenzo-p-dioxins and dibenzofurans in sediment of Ya-Er Lake, China

The sediment of Ya-Er Lake had been heavily polluted by polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) from the former chloralkali industry. The total amounts of PCDD/Fs and I-TEQ decreased along the water flow direction and also decreased from top to bottom layers of sediment cores. Sediment of Pond 1 was dominated by PCDF, especially TCDF. In contrast, in the other four ponds, PCDD dominated in all layers and octachlorinated dibenzo-p-dioxin (OCDD) predominated in all of the homologues. When homologue profiles from sediments and water samples were compared using principal component analysis (PCA), the first two principal components represented 95.2% of the variance in the data. The first component explained 75.9% of the variance and the second one 19.3%. Two clusters were most distinct, presenting a shift in PCDD/Fs composition from PCDF to heptachlorinated dibenzo-p-dioxin (HpCDD) and OCDD in sediments and water from Pond I to Ponds 2-5. The pattern variation between Pond 1 and Ponds 2-5 in Ya-Er Lake was most likely due to the change of process in the chemical plant after the dams between the ponds were built. The results of the present study also showed that log K-oc of PCDD/Fs calculated from data of sediment and water in the field were comparable with theoretical log K-oc. The results also implied that the concentrations of PCDD/Fs in water and sediments could be predicted from each other by log K-oc. (C) 2001 Elsevier Science Ltd. All rights reserved.

Fast Discrimination of Commerical Corn Varieties Based on Near Infrared Spectra

The existing methods for the discrimination of varieties of commodity corn seed are unable to process batch data and speed up identification, and very time consuming and costly. The present paper developed a new approach to the fast discrimination of varieties of commodity corn by means of near infrared spectral data. Firstly, the experiment obtained spectral data of 37 varieties of commodity corn seed with the Fourier transform near infrared spectrometer in the wavenurnber range from 4 000 to 12 000 cm (1). Secondly, the original data were pretreated using statistics method of normalization in order to eliminate noise and improve the efficiency of models. Thirdly, a new way based on sample standard deviation was used to select the characteristic spectral regions, and it can search very different wavenumbers among all wavenumbers and reduce the amount of data in part. Fourthly, principal component analysis (PCA) was used to compress spectral data into several variables, and the cumulate reliabilities of the first ten components were more than 99.98%. Finally, according to the first ten components, recognition models were established based on BPR. For every 25 samples in each variety, 15 samples were randomly selected as the training set. The remaining 10 samples of the same variety were used as the first testing set, and all the 900 samples of the other varieties were used as the second testing set. Calculation results showed that the average correctness recognition rate of the 37 varieties of corn seed was 94.3%. Testing results indicate that the discrimination method had higher precision than the discrimination of various kinds of commodity corn seed. In short, it is feasible to discriminate various varieties of commodity corn seed based on near infrared spectroscopy and BPR.

A New Discrimination Method of Maize Seed Varieties Based on Near-Infrared Spectroscopy

A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed. The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer (12 000-4 000 cm(-1)). The original spectra data were preprocessed by first derivative method. Then the principal component analysis (PCA) was used to compress the spectra data. The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models. The model was established by Psi-3 neuron based on biomimetic pattern recognition (BPR). Especially, the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample. The authors tested the discrimination capability of the model through four groups of experiments. There were 10, 18, 26 and 34 varieties training the discrimination models in these experiments, respectively. Additionally, another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models. Each group of the experiment was repeated three times by selecting different training samples at random. The correct classification rates of the models in the four-group experiments were above 91. 8%. The correct rejection rates for the varieties not participating in training the models all attained above 95%. Furthermore, the performance of the discrimination models did not change obviously when using the different training samples. The results showed that this discrimination method can not only effectively recognize the maize seed varieties, but also reject the varieties not participating in training the model. It may be practical in the discrimination of maize seed varieties.

Broadband terahertz time-domain spectroscopy of drugs-of-abuse and the use of principal component analysis

EPSRC, the European Community IST FP6 Integrated, etc

PCA在语音检测中的应用研究

提出主元分析PCA(Principal Component Analysis)用于语音检测的方法研究．用主元分析法在多维空间中建立坐标轴，将待处理信号投影到该坐标轴中，通过分析投影结果判断是否为语音信号．通过将语音和非语音分别建立子空间，来区分语音和非语音信号．该方法不同于常规的语音时域、频域处理方法，而是在多维空间中对信号进行分析·实验结果表明，该方法准确率高、简单、容易实现，而且能区分多种非语音信号．

A QUANTITATIVE ASSESSMENT OF SOURCE CONTRIBUTIONS TO INHALABLE PARTICULATE MATTER POLLUTION IN METROPOLITAN BOSTON

In this paper, source apportionment techniques are employed to identify and quantify the major particle pollution source classes affecting a monitoring site in metropolitan Boston, MA. A Principal Component Analysis (PCA) of paniculate elemental data allows the estimation of mass contributions for five fine mass panicle source classes (soil, motor vehicle, coal related, oil and salt aerosols), and six coarse panicle source classes (soil, motor vehicle, refuse incineration, residual oil, salt and sulfate aerosols). Also derived are the elemental characteristics of those source aerosols and their contributions to the total recorded elemental concentrations (i.e. an elemental mass balance). These are estimated by applying a new approach to apportioning mass among various PCA source components: the calculation of Absolute Principal Component Scores, and the subsequent regression of daily mass and elemental concentrations on these scores.

Studies on principal components and antioxidant activity of different Radix Astragali samples using high-performance liquid chromatography/electrospray ionization multiple-stage tandem mass spectrometry

The principal components, isoflavonoids and astragalosides, in the extract of Radix Astragali were detected by a high-performance liquid chromatography Couple to electrospray ionization ion trap multiple-stage tandem mass spectrometry (HPLC-ESI-IT-MSn) method. By comparing the retention time (t(R)) of HPLC, the ESI-MSn data and the structures of analyzed Compounds with the data of reference compounds and in the literature, 17 isoflavonoids and 12 astragalosides have been identified or tentatively deduced. By Virtue of the extracted ion chromatogram (EIC) mode, simultaneous determination of isoflavonoids and astragalosides could be achieved when the different components formed overlapped peaks. And this method has been utilized to analyze the constituents in extracts of Radix Astragali from Helong City and of different growth years. Then the antioxidant activity of different samples has been Successfully investigated by HPLC-ESI-MS method in multiple selected ion monitoring(MIM) mode, applying the spin trapping technology, and the Ferric Reducing Antioxidant Power (FRAP) assay was applied to support the result.

基于独立分量分析的地震属性分析方法研究

Conventional seismic attribute analysis is not only time consuming, but also has several possible results. Therefore, seismic attribute optimization and multi-attribute analysis are needed. In this paper, Fuyu oil layer in Daqing oil field is our main studying object. And there is much difference between seismic attributes and well logs. So under this condition, Independent Component Analysis (ICA) and Kohonen neural net are introduced to seismic attribute optimization and multi-attribute analysis. The main contents are as follows: (1) Now the method of seismic attribute compression is mainly principal component analysis (PCA). In this article, independent component analysis (ICA), which is superficially related to PCA, but much more powerful, is used to seismic reservoir characterizeation. The fundamental, algorithms and applications of ICA are surveyed. And comparation of ICA with PCA is stydied. On basis of the ne-entropy measurement of independence, the FastICA algorithm is implemented. (2) Two parts of ICA application are included in this article: First, ICA is used directly to identify sedimentary characters. Combined with geology and well data, ICA results can be used to predict sedimentary characters. Second, ICA treats many attributes as multi-dimension random vectors. Through ICA transform, a few good new attributes can be got from a lot of seismic attributes. Attributes got from ICA optimization are independent. (3) In this paper, Kohonen self-organizing neural network is studied. First, the characteristics of neural network’s structure and algorithm is analyzed in detail, and the traditional algorithm is achieved which has been used in seism. From experimental results, we know that the Kohonen self-organizing neural network converges fast and classifies accurately. Second, the self-organizing feature map algorithm needs to be improved because the result of classification is not very exact, the boundary is not quite clear and the velocity is not fast enough, and so on. Here frequency sensitive principle is introduced. Combine it with the self-organizing feature map algorithm, then get frequency sensitive self-organizing feature map algorithm. Experimental results show that it is really better. (4) Kohonen self-organizing neural network is used to classify seismic attributes. And it can be avoided drawing confusing conclusions because the algorithm’s characteristics integrate many kinds of seismic features. The result can be used in the division of sand group’s seismic faces, and so on. And when attributes are extracted from seismic data, some useful information is lost because of difference and deriveative. But multiattributes can make this lost information compensated in a certain degree.