One century record of contamination by polycyclic aromatic hydrocarbons and polychlorinated biphenyls in core sediments from the southern Yellow Sea

Sixteen polycyclic aromatic hydrocarbons (PAHs) and 28 polychlorinated biphenyls (PCBs) were measured at a 2-cm interval in a core sample from the middle of the southern Yellow Sea for elucidating their historical variations in inflow and sources. The chronology was obtained using the Pb-210 method. PAHs concentrations decreased generally with depth and two climax values occurred in 14-16 cm and 20-22 cm layers, demonstrating that the production and usage of PAHs might reach peaks in the periods of 1956-1962 and 1938-1944. The booming economy and the navy battles of the Second World War might explain why the higher levels were detected in the two layers. The result of principal component analysis (PCA) revealed that PAHs were primarily owing to the combustion product. Down-cored variation of PCB concentrations was complex. Higher concentrations besides the two peaks being the same as PAHs were detected from 4 to 8 cm, depositing from 1980 to 1992, which probably resulted from the disposal of the out-dated PCB-containing equipment. The average Cl percentage of PCBs detected was similar to that of the mixture of Aroclor 1254 and 1242, suggesting they might origin from the dielectrical and heat-transfer fluid. The total organic carbon (TOC) content played a prevalent role in the adsorption of high molecular weight PAHs (>= 4-ring), while no obvious relationship among total PCBs, the concentration of congeners, and TOC was found.

Phenotypic plasticity of gut structure and function during periods of inactivity in Apostichopus japonicus

Apostichopus japonicus is a common sea cucumber that undergoes seasonal inactivity phases and ceases feeding during the summer months. We used this sea cucumber species as a model in which to examine phenotypic plasticity of the digestive tract in response to food deprivation. We measured the body mass, gross gut morphology and digestive enzyme activities of A. japonicus before, during, and after the period of inactivity to examine the effects of food deprivation on the gut structure and function of this animal. Individuals were sampled semi-monthly from June to November (10 sampling intervals over 178 days) across temperature changes of more than 18 degrees C. On 5 September, which represented the peak of inactivity and lack of feeding, A. japonicus decreased its body mass, gut mass and gut length by 50%, 85%, and 70%, respectively, in comparison to values for these parameters preceding the inactive period. The activities of amylase, cellulase and lipase decreased by 77%, 98%, and 35% respectively, in comparison to mean values for these enzymes in June, whereas pepsin activity increased two-fold (luring the inactive phase. Alginase and trypsin activities were variable and did not change significantly across the 178-day experiment. With the exception of amylase and cellulase, all body size indices and digestive enzyme activities recovered and even surpassed the mean values preceding the inactive phase during the latter part of the experiment (October-November). Principal Component Analysis (PCA) utilizing the digestive enzyme activity and body size index data divided the physiological state of this cucumber into four phases: an active stage, prophase of inactivity peak inactivity, and a reversion phase. These phases are all consistent with previously suggested life stages for this species, but our data provide more defined characteristics of each phase. A. japonicus clearly exhibits phenotypic plasticity (or life-cycle staging) of the digestive tract during its annual inactive period. (C) 2008 Elsevier Inc. All rights reserved.

Spatial variations of size-fractionated chlorophyll, cyanobacteria and heterotrophic bacteria in the Central and Western Pacific

Geographic and vertical variations of size-fractionated (0.2-1 mu m, 1-10 mu m, and >10 mu m) Chlorophyll a (Chl.a) concentration, cyanobacteria abundance and heterotrophic bacteria abundance were investigated at 13 stations from 4 degrees S, 160 degrees W to 30 degrees N, 140 degrees E in November 1993. The results indicated a geographic distribution pattern of these parameters with instances of high values occurring in the equatorial region and offshore areas, and with instance of low values occurring in the oligotrophic regions where nutrients were almost undetectable. Cyanobacteria showed the highest geographic variation (ranging from 27x10(3) to 16,582x10(3) cell l(-1)), followed by Chl.a (ranging from 0.048 to 0.178 mu g l(-1)), and heterotrophic bacteria (ranging from 2.84x10(3) to 6.50 x 10(5) cell l(-1)). Positive correlations were observed between nutrients and Chl.a abundance. Correspondences of cyanobacteria and heterotrophic bacteria abundances to nutrients were less significant than that of Chl.a. The total Chl.a was accounted for 1.0-30.9%, 35.9-53.7%, and 28.1-57.3% by the >10 mu m, 1-10 mu m and 0.2-1 mu m fractions respectively. Correlation between size-fractionated Chl.a and nutrients suggest that the larger the cell size, the more nutrient-dependent growth and production of the organism. The ratio of pheophytin to chlorophyll implys that more than half of the > 10 mu m and about one third of the 1-10 mu m pigment-containing particles in the oligotrophic region were non-living fragments, while most of the 1-10 mu m fraction was living cells. In the depth profiles, cyanobacteria were distributed mainly in the surface layer, whereas heterotrophic bacteria were abundant from surface to below the euphotic zone. Chl.a peaked at the surface layer (0-20 m) in the equatorial area and at the nitracline (75-100 m) in the oligotrophic regions. Cyanobacteria were not the principle component of the picoplankton. The carbon biomass ratio of heterotroph to phytoplankton was greater than 1 in the eutrophic area and lower than 1 in oligotrophic waters.

一种基于新型数据预测方法的MICA仿真研究

在多元统计过程监控中,为解决因未知过程数据统计分布而产生误报漏报的现象,提出一种结合多向独立元分析法(MICA)和广义相关系数(GCC)数据预测的综合方法,进行在线监控过程的仿真。MICA分析方法能有效分解各变量的关联关系,且不需考虑建模数据是否符合正态分布,用此方法计算的独立元变量能更好地描述过程的变化规律。为提高预报未来过程故障的能力,提出用广义相关系数法进行数据预测:确定与运行轨迹相似的监控模型库中的轨迹,并使其相应部分承接于运行轨迹之后。现场采集聚氯乙烯聚合过程的数据进行仿真,仿真结果显示:对于在线监控和在线故障诊断方面,这种新型预测方法优于其它传统处理预测问题的方法。

基于改进的OFA-MPCA的监控方法

多向主元分析(MPCA)是利用多变量统计方法从纷杂的海量数据信息中提取出能够准确表征数据信息的几个主元,并通过投影法来降低数据的维数,主要应用于间歇生产过程中.在实际的间歇生产过程中,由于各种原因导致各批次异步造成它们运行时间的不一致,而无法直接建立有效的统计模型,正交函数近似(OFA)是一种基于正交基的投影变换技术,通过对原始数据进行OFA处理后,可以用投影系数来描述原始数据所具有的特征,并且可以达到轨迹同步化和压缩数据量的目的.对OFA法进行了部分改进,并结合MPCA法对典型的间歇过程——青霉素发酵过程进行了仿真研究.结果表明,改进的OFA计算速度有了极大的提高,且改进的OFA-MPCA法能完好地对各批次进行同步、建模并得出准确的监视结果.

基于独立成分分析和模糊支持向量机的人脸识别方法

成分分析(PCA)只能从2阶上去消除数据的相关性，传统支持向量机在解决多类问题时会出现分类的盲区问题，针对这两种情况，首先采用独立成分分析(ICA)方法解决了高阶上的数据相关性问题；同时在传统支持向量机中引入模糊隶属度函数，用模糊支持向量机解决了传统支持向量机在多类数据识别中的盲区问题。通过实验证明了该方法在人脸识别率上取得了显著提高。

角速率陀螺在海洋机器人“海人1号”航向控制中的应用

本文给出“海人1号”航向控制的流体动力学模型、航向控制系统结构,海上实验记录以及角速率陀螺作用原理和分析。这将对从事海洋机器人控制系统的设计研究,有一定的考参值价。

基于改进SICA的人脸特征提取方法研究

独立分量分析是一种有效的人脸特征提取方法。考虑到人脸样本的对称性,本文采用对称独立分量分析的方法对人脸样本进行特征提取。为了提高独立分量分析法表征人脸特征空间的能力,本文采用遗传算法对特征空间进行选择优化,获得最优的人脸特征子集。仿真实验表明,本文提出方法的识别率明显的好于独立分量分析方法的识别率。

基于可复制性的独立成分分析——应用于功能磁共振成像数据

This dissertation systematically depicted and improved the application of Independent Component Analysis (ICA) to Functional Magnetic Resonance Imaging (fMRI), following the logic of verification, improvement, extension, and application. The concept of “reproducibility” was the philosophy throughout its four concluded studies. In the “verification” study, ICA was applied to the resting-state fMRI data, verified the resultant components with reproducibility, and examined the consistency of the results from ICA and traditional “seed voxel” method. At the meantime, the limitation of ICA application on fMRI data analysis was presented. In the “improvement” study, an improved ICA algorithm based on reproducibility, RAICAR, was developed to aid some of the limitations of ICA application. RAICAR was able to rank ICA components by reproducibility, determine the number of reliable components, and obtain more stable results. RAICAR provided useful tools for validation and interpretation of ICA results. In the “extension” study, RAICAR as well as the concept of “reproducibility” was extended to multi-subject ICA analysis, and gRAICAR algorithm was developed. gRAICAR allows some variation across subjects, examining common components among subjects. gRAICAR is also capable to detect potential subject grouping on some components. It is a new way for exploratory group analysis on fMRI. In the “application” study, two newly developed methods, RAICAR and gRAICAR, were used to investigate the effect of early music training on the brain mechanism of memory and learning. The results showed brain mechanism difference in memory retrieval and learning process between two groups of subjects. This study also verified the usefulness and importance of the new methods.

Clinical significance and prognostic value of urinary nucleosides in breast cancer patients

Objective: Thirteen urinary nucleosides, primarily degradation products of tRNA, were evaluated as potential tumor markers for breast cancer patients.