Biologically Inspired Tensor Features

According to the research results reported in the past decades, it is well acknowledged that face recognition is not a trivial task. With the development of electronic devices, we are gradually revealing the secret of object recognition in the primate's visual cortex. Therefore, it is time to reconsider face recognition by using biologically inspired features. In this paper, we represent face images by utilizing the C1 units, which correspond to complex cells in the visual cortex, and pool over S1 units by using a maximum operation to reserve only the maximum response of each local area of S1 units. The new representation is termed C1 Face. Because C1 Face is naturally a third-order tensor (or a three dimensional array), we propose three-way discriminative locality alignment (TWDLA), an extension of the discriminative locality alignment, which is a top-level discriminate manifold learning-based subspace learning algorithm. TWDLA has the following advantages: (1) it takes third-order tensors as input directly so the structure information can be well preserved; (2) it models the local geometry over every modality of the input tensors so the spatial relations of input tensors within a class can be preserved; (3) it maximizes the margin between a tensor and tensors from other classes over each modality so it performs well for recognition tasks and (4) it has no under sampling problem. Extensive experiments on YALE and FERET datasets show (1) the proposed C1Face representation can better represent face images than raw pixels and (2) TWDLA can duly preserve both the local geometry and the discriminative information over every modality for recognition.

生态研究数据库系统的设计与开发

列表类型数据是生态研究中最为常见的数据形式。在分析列表类型数据特征及其与元数据关系,数据安全和共享策略等问题基础上,提出了生态研究列表类数据管理系统设计和开发方案。研究认为数据集的元数据不仅是对数据集实体的说明,而且一定程度上决定着数据集实体的内容和数量,以及数据集实体之间的内在联系,这种联系正是进行列表类型数据管理依据所在。

Crossing the phantom divide in brane cosmology with curvature corrections and brane-bulk energy transfer

We consider the Randall-Sundrum brane-world model with bulk-brane energy transfer where the Einstein-Hilbert action is modified by curvature correction terms: a four-dimensional scalar curvature from induced gravity on the brane, and a five-dimensional Gauss-Bonnet curvature term. It is remarkable that these curvature terms will not change the dynamics of the brane universe at low energy. Parameterizing the energy transfer and taking the dark radiation term into account, we find that the phantom divide of the equation of state of effective dark energy could be crossed, without the need of any new dark energy components. Fitting the two most reliable and robust SNIa datasets, the 182 Gold dataset and the Supernova Legacy Survey (SNLS), our model indeed has a small tendency of phantom divide crossing for the Gold dataset, but not for the SNLS dataset. Furthermore, combining the recent detection of the SDSS baryon acoustic oscillations peak (BAO) with lower matter density parameter prior, we find that the SNLS dataset also mildly favors phantom divide crossing.

Comparison of steroid substrates and inhibitors of P-glycoprotein by 3D-QSAR analysis

Steroid derivatives show a complex interaction with P-glycoprotein (Pgp). To determine the essential structural requirements of a series of structurally related and functionally diverse steroids for Pgp-mediated transport or inhibition, a three-dimensional quantitative structure activity relationship study was performed by comparative similarity index analysis modeling. Twelve models have been explored to well correlate the physiochemical features with their biological functions with Pgp on basis of substrate and inhibitor datasets, in which the best predictive model for substrate gave cross-validated q(2) = 0.720, non-cross-validated r(2) = 0.998, standard error of estimate SEE = 0.012, F = 257.955, and the best predictive model for inhibitor gave q(2) = 0.536, r(2) = 0.950, SEE = 1.761 and F = 45.800. The predictive ability of all models was validated by a set of compounds that were not included in the training set. The physiochemical similarities and differences of steroids as Pgp substrate and inhibitor, respectively, were analyzed to be helpful in developing new steroid-like compounds. (C) 2004 Elsevier B.V. All rights reserved.

Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data

As a recently developed and powerful classification tool, probabilistic neural network was used to distinguish cancer patients from healthy persons according to the levels of nucleosides in human urine. Two datasets (containing 32 and 50 patterns, respectively) were investigated and the total consistency rate obtained was 100% for dataset 1 and 94% for dataset 2. To evaluate the performance of probabilistic neural network, linear discriminant analysis and learning vector quantization network, were also applied to the classification problem. The results showed that the predictive ability of the probabilistic neural network is stronger than the others in this study. Moreover, the recognition rate for dataset 2 can achieve to 100% if combining, these three methods together, which indicated the promising potential of clinical diagnosis by combining different methods. (C) 2002 Elsevier Science B.V. All rights reserved.

Analysis of spatio-temporal dynamic pattern and driving forces of urban land in China in 1990s using TM images and GIS

China has witnessed fast urban growth in the recent decade. This study analyzes spatio-temporal characteristics of urban expansion in China using satellite images and regionalization methods. Landsat TM images at three time periods, 1990/1991, 1995/1996, and 1999/2000, are interpreted to get 1:100000 vector land use datasets. The study calculates the urban land percentage and urban land expansion index of every 1 km(2) cell throughout China. The study divides China into 27 urban regions to conceive dynamic patterns of urban land changes. Urban development was achieving momentum in the western region, expanding more noticeably than in the previous five years, and seeing an increased growth percentage. Land use dynamic changes reflect the strong impacts of economic growth environments and macro-urban development policies. The paper helps to distinguish the influences of newly market-oriented forces from traditional administrative controls on China's urban expansion. (c) 2005 Elsevier Ltd. All rights reserved.

Uncertainties in estimates of cropland area in China: a comparison between an AVHRR-derived dataset and a Landsat TM-derived dataset

The large uncertainties in estimates of cropland area in China may have significant implications for major cross-cutting themes of global environmental change-food production and trade, water resources, and the carbon and nitrogen cycles. Many earlier studies have indicated significant under-reporting of cropland area in China from official agricultural census statistics datasets. Space-borne remote sensing analyses provide an alternative and independent approach for estimating cropland area in China. In this study, we report estimates of cropland area from the National Land Cover Dataset (NLCD-96) at the 1:100,000 scale, which was generated by a multi-year National Land Cover Project in China through visual interpretation and digitization of Landsat TM images acquired mostly in 1995 and 1996. We compared the NLCD-96 dataset to another land cover dataset at I-km spatial resolution (the IGBP DIScover dataset version 2.0), which was generated from monthly Advanced Very High Resolution Radiometer (AVHRR)-derived Normalized Difference Vegetation Index (NDVI) from April, 1992 to March, 1993. The data comparison highlighted the limitation and uncertainty of cropland area estimates from the DIScover dataset. (C) 2003 Elsevier Science B.V. All rights reserved.

Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data

Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

Robust Tensor Analysis With L1-Norm

Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based tensor analysis (TPCA-L1), which is robust to outliers. Experimental results upon face and other datasets demonstrate the advantages of the proposed approach.

Rare earth elements in bottom sediments of major rivers around the Yellow Sea: implications for sediment provenance

Rare earth elements (REEs) of 91 fine-grained bottom sediment samples from five major rivers in Korea (the Han, Keum, and Yeongsan) and China (the Changjiang and Huanghe) were studied to investigate their potential as source indicator for Yellow Sea shelf sediments, this being the first synthetic report on REE trends for bottom sediments of these rivers. The results show distinct differences in REE contents and their upper continental crust (UCC)-normalized patterns: compared to heavy rare earth elements (HREEs), light rare earth elements (LREEs) are highly enriched in Korean river sediments, in contrast to Chinese river sediments that have a characteristic positive Eu anomaly. This phenomenon is observed also in primary source rocks within the river catchments. This suggests that source rock composition is the primary control on the REE signatures of these river sediments, due largely to variations in the levels of chlorite and monazite, which are more abundant in Korean bottom river sediments. Systematic variations in I LREE pound/I HREE pound ratios, and in (La/Yb)-(Gd/Yb)(UCC) but also (La/Lu)-(La/Y)(UCC) and (La/Y)-(Gd/Lu)(UCC) relations have the greatest discriminatory power. These findings are consistent with, but considerably expand on the limited datasets available to date for suspended sediments. Evidently, the REE fingerprints of these river sediments can serve as a useful diagnostic tool for tracing the provenance of sediments in the Yellow Sea, and for reconstructing their dispersal patterns and the circulation system of the modern shelf, as well as the paleoenvironmental record of this and adjoining marginal seas.

Radiation and diversification within the Ligularia-Cremanthodium-Parasenecio complex (Asteraceae) triggered by uplift of the Qinghai-Tibetan Plateau

The Ligularia-Cremanthodium-Parasenecio (L-C-P) complex of the Tussilagininae (Asteraceae: Senecioneae) contains more than 200 species that are endemic to the Qinghai-Tibetan Plateau in eastern Asia. These species are morphologically distinct; however, their relationships appear complex. A phylogenetic analysis of members of the complex and selected taxa, of the tribe Senecioneae was conducted using chloroplast (ndhF and trnL-F) and nuclear (ITS) sequences. Phylogenetic trees were constructed from individual and combined datasets of the three different sequences. All analyses suggested that Doronicum, a genus that has been included in the Tussilagininae, should be excluded from this subtribe and placed at the base of the tribe Senecioneae. In addition, the Tussilagininae should be broadly circumscribed to include the Tephroseridinae. Within the expanded Tussilagininae containing all 13 genera occurring in eastern Asia, Tussilago and NSPetasites diverged early as a separate lineage, while the remaining I I genera comprise an expanded L-C-P complex clade. We suggest that the L-C-P clade, which is largely unresolved, most likely originated as a consequence of an explosive radiation. The few monophyletic subclades identified in the L-C-P clade with robust support further suggest that some genera of Tussilagininae from eastern Asia require generic re-circumscriptions given the occurrence of subclades containing species of the same genus in different parts of the phylogentic tree due to homoplasy of important morphological characters used to delimit them. Molecular-clock analyses suggest that the explosive radiation of the L-C-P complex occurred mostly within the last 20 million years, which falls well within the period of recent major uplifts of the Qinghai-Tibetan Plateau between the early Miocene to the Pleistocene. It is proposed that significant increases in geological and ecological diversity that accompanied such uplifting, most likely promoted rapid and continuous allopatric speciation in small and isolated populations, and allowed fixation or acquisition of similar morphological characters within unrelated lineages. This phenomenon, possibly combined with interspecific diploid hybridization because of secondary sympatry during relatively stable stages between different uplifts, could be a major cause of high species diversity in the Qinghai-Tibetan Plateau and adjacent areas of eastern Asia. (c) 2005 Elsevier Inc. All rights reserved.

湖南、广西泥盆纪硅岩地球化学与沉积构造背景

During the Devonian, a complicated carbonate platform-basin configuration was created through transtensional rifting in the context of opening of Devonian South China Sea; extensive bedded chert, commonly interbedded with tuffaceous beds, occurred in the narrow, elongate interplatform basins (or troughs) in South China, where they occurred earlier (Early Devonian) in southern Guangxi and later (early Late Devonian) in northern Guangxi-south central Hunan. In order to unravel the origin and distribution of the bedded chert successions, and their relationships to basement faulting activities during the opening of the Devonian South China Sea, studies of element (major, minor and REE) geochemistry and Rb-Sr, Sm-Nd isotopic systematics are carried out upon the chert deposits. These chert deposits commonly have high SiO2 contents and (average 94.01%) and low TFe2O3 (average 0.55%), together with other geochemical parameters, suggestive of both biogenic and hydrothermal origins. However, Fe/Ti ratio are high along the elongate interplatform basins(troughs) to the northwest along Wuxiangling-Zhaisha-Chengbu, and to the southeast along Xiaodong-Mugui-Xinpu, suggesting relatively intense hydrothermal activities there. They generally contain very low total REE contents (∑REE average 31.21ug/g) with mediate negative Ce anomalies (mean Ce/Ce*=0.83) and low Lan/Cen values (average 1.64), indicating an overall continental margin basin where they precipitated. The northward increases in Ce/Ce* values, particularly along the elongate troughs bounded both to the east and west of the Guangxi-Huanan rift basin, suggest a northward enhancement of terrigenous influences, thereby reflecting a gradual northward propagation of open marine setting. Generally low positive Eu anomalies in the chert, except for the apparently high Eu anomalies in the chert from Chengbu (Eu/Eu* up to 4.6), suggest mild hydrothermal venting activities in general, except for those at Chengbu. The initial 87Sr/86Sr (0) ratios of chert generally vary from 0.712000 to 0.73000 , suggesting influences both from terrigenous influx and seawater. The Nd isotopic model ages (tDM or t2DM) and initial εNd (0) values of chert vary mostly from 1.5 to 2.1 Ga, and from –16 to –21, respectively, implying that the silica sources were derived from the provenances of the Palaeoproterozoic crust relics at depth. The high εNd (0) values of chert (-0.22 to 14.7) in some localities, mostly along the elongate troughs, suggest that silica sources may have been derived from deeper-seated mantle, being channeled through the interplate boundary fault zones extending downwards to the mantle. At Wuxiangling, Nanning, chert occurs extensively from the Emsian through the Frasnian strata, both U/Th ratios and tDM ages of chert reached up to a maximum in the early Frasnian corresponding to the extensive development of chert in South China, pointing to a maximum extensional stage of Devonian South China basin, which is supported by the Ce/Ce* values as is opposed to the previous datasets as the coeval minimum values.

叠前时间偏移：各向异性、多次波衰减及应用

At present, in order to image complex structures more accurately, the seismic migration methods has been developed from isotropic media to the anisotropic media. This dissertation develops a prestack time migration algorithm and application aspects for complex structures systematically. In transversely isotropic media with a vertical symmetry axis (VTI media), the dissertation starts from the theory that the prestack time migration is an approximation of the prestack depth migration, based on the one way wave equation and VTI time migration dispersion relation, by combining the stationary-phase theory gives a wave equation based VTI prestack time migration algorithm. Based on this algorithm, we can analytically obtain the travel time and amplitude expression in VTI media, as while conclude how the anisotropic parameter influence the time migration, and by analyzing the normal moveout of the far offset seismic data and lateral inhomogeneity of velocity, we can update the velocity model and estimate the anisotropic parameter model through the time migration. When anisotropic parameter is zero, this algorithm degenerates to the isotropic time migration algorithm naturally, so we can propose an isotopic processing procedure for imaging. This procedure may keep the main character of time migration such as high computational efficiency and velocity estimation through the migration, and, additionally, partially compensate the geometric divergence by adopting the deconvolution imaging condition of wave equation migration. Application of this algorithm to the complicated synthetic dataset and field data demonstrates the effectiveness of the approach. In the dissertation we also present an approach for estimating the velocity model and anisotropic parameter model. After analyzing the velocity and anisotropic parameter impaction on the time migration, and based on the normal moveout of the far offset seismic data and lateral inhomogeneity of velocity, through migration we can update the velocity model and estimate the anisotropic parameter model by combining the advantages of velocity analysis in isotropic media and anisotropic parameter estimation in VTI media. Testing on the synthetic and field data, demonstrates the method is effective and very steady. Massive synthetic dataset、2D sea dataset and 3D field datasets are used for VTI prestack time migration and compared to the stacked section after NMO and prestack isotropic time migration stacked section to demonstrate that VTI prestack time migration method in this paper can obtain better focusing and less positioning errors of complicated dip reflectors. When subsurface is more complex, primaries and multiples could not be separated in the Radon domain because they can no longer be described with simple functions (parabolic). We propose an attenuating multiple method in the image domain to resolve this problem. For a given velocity model，since time migration takes the complex structures wavefield propagation in to account, primaries and multiples have different offset-domain moveout discrepancies, then can be separated using techniques similar to the prior migration with Radon transform. Since every individual offset-domain common-reflection point gather incorporates complex 3D propagation effects, our method has the advantage of working with 3D data and complicated geology. Testing on synthetic and real data, we demonstrate the power of the method in discriminating between primaries and multiples after prestack time migration, and multiples can be attenuated in the image space considerably.

社会形势预警的几种建模方法比较

Based on social survey data conducted by local research group in some counties executed in the nearly past five years in China, the author proposed and solved two kernel problems in the field of social situation forecasting: i) How can the attitudes’ data on individual level be integrated with social situation data on macrolevel; ii) How can the powers of forecasting models’ constructed by different statistic methods be compared? Five integrative statistics were applied to the research: 1) algorithm average (MEAN); 2) standard deviation (SD); 3) coefficient variability (CV); 4) mixed secondary moment (M2); 5) Tendency (TD). To solve the former problem, the five statistics were taken to synthesize the individual and mocrolevel data of social situations on the levels of counties’ regions, and form novel integrative datasets, from the basis of which, the latter problem was accomplished by the author: modeling methods such as Multiple Regression Analysis (MRA), Discriminant Analysis (DA) and Support Vector Machine (SVM) were used to construct several forecasting models. Meanwhile, on the dimensions of stepwise vs. enter, short-term vs. long-term forecasting and different integrative (statistic) models, meta-analysis and power analysis were taken to compare the predicting power of each model within and among modeling methods. Finally, it can be concluded from the research of the dissertation: 1) Exactly significant difference exists among different integrative (statistic) models, in which, tendency (TD) integrative models have the highest power, but coefficient variability (CV) ones have the lowest; 2) There is no significant difference of the power between stepwise and enter models as well as short-term and long-term forecasting models; 3) There is significant difference among models constructed by different methods, of which, support vector machine (SVM) has the highest statistic power. This research founded basis in all facets for exploring the optimal forecasting models of social situation’s more deeply, further more, it is the first time methods of meta-analysis and power analysis were immersed into the assessments of such forecasting models.