Sea surface height and transport stream function of the South China Sea from a variable-grid global ocean circulation model

A fine-grid model (1/6degrees) covering the South China Sea (SCS), East China Sea and Japan/East Sea, which is embedded into a coarse-grid (3degrees) global model, was established to study the SCS circulation. In the present paper, we report the model-produced monthly and annual mean transport stream functions and sea surface heights(SSH) and their anomalies of the SCS. Comparison to the TOPEX/Poseidon data shows that the model-produced monthly sea surface height anomalies (SSHA) are in good agreement with altimeter measurements. Based on the results, the circulation of the SCS, especially the upper layer circulation, is discussed. In the surface layer, the western Philippine Sea water intrudes into the SCS through the Luzon Strait in autumn, winter and spring, but not in summer. However, as far as the whole water column is concerned, the water intrudes into the SCS through the Luzon Strait all the year round. This indicates that in summer the water still intrudes into the SCS in the subsurface and intermediate layers. The area near the northern continental slope of the SCS is dominated by a cyclonic circulation all the year round. The SCS Southern Anticyclonic Gyre, SE Vietnam Off-Shore Current in summertime and SCS Southern Cyclonic Gyre in wintertime are reproduced reasonably. The difference between the monthly averaged SSH and SSHA is significant, indicating the importance of the mean SSH in the SCS circulation.

Statistical distribution of wave-surface elevation for second-order random directional ocean waves in finite water depth

Based on the second-order random wave solutions of water wave equations in finite water depth, a statistical distribution of the wave-surface elevation is derived by using the characteristic function expansion method. It is found that the distribution, after normalization of the wave-surface elevation, depends only on two parameters. One parameter describes the small mean bias of the surface produced by the second-order wave-wave interactions. Another one is approximately proportional to the skewness of the distribution. Both of these two parameters can be determined by the water depth and the wave-number spectrum of ocean waves. As an illustrative example, we consider a fully developed wind-generated sea and the parameters are calculated for various wind speeds and water depths by using Donelan and Pierson spectrum. It is also found that, for deep water, the dimensionless distribution reduces to the third-order Gram-Charlier series obtained by Longuet-Higgins [J. Fluid Mech. 17 (1963) 459]. The newly proposed distribution is compared with the data of Bitner [Appl. Ocean Res. 2 (1980) 63], Gaussian distribution and the fourth-order Gram-Charlier series, and found our distribution gives a more reasonable fit to the data. (C) 2002 Elsevier Science B.V. All rights reserved.

Second-order solutions for random interfacial waves in N-layer density-stratified fluid with steady uniform currents

In the present paper, the random inter facial waves in N-layer density-stratified fluids moving at different steady uniform speeds are researched by using an expansion technique, and the second-order a symptotic solutions of the random displacements of the density interfaces and the associated velocity potentials in N-layer fluid are presented based on the small amplitude wave theory. The obtained results indicate that the wave-wave second-order nonlinear interactions of the wave components and the second-order nonlinear interactions between the waves and currents are described. As expected, the solutions include those derived by Chen (2006) as a special case where the steady uniform currents of the N-layer fluids are taken as zero, and the solutions also reduce to those obtained by Song (2005) for second-order solutions for random interfacial waves with steady uniform currents if N=2.

Statistical distribution of nonlinear random wave height

A statistical model of random wave is developed using Stokes wave theory of water wave dynamics. A new nonlinear probability distribution function of wave height is presented. The results indicate that wave steepness not only could be a parameter of the distribution function of wave height but also could reflect the degree of wave height distribution deviation from the Rayleigh distribution. The new wave height distribution overcomes the problem of Rayleigh distribution that the prediction of big wave is overestimated and the general wave is underestimated. The prediction of small probability wave height value of new distribution is also smaller than that of Rayleigh distribution. Wave height data taken from East China Normal University are used to verify the new distribution. The results indicate that the new distribution fits the measurements much better than the Rayleigh distribution.

Probability distribution of random wave-current forces

Based on the second-order solutions obtained for the three-dimensional weakly nonlinear random waves propagating over a steady uniform current in finite water depth, the joint statistical distribution of the velocity and acceleration of the fluid particle in the current direction is derived using the characteristic function expansion method. From the joint distribution and the Morison equation, the theoretical distributions of drag forces, inertia forces and total random forces caused by waves propagating over a steady uniform current are determined. The distribution of inertia forces is Gaussian as that derived using the linear wave model, whereas the distributions of drag forces and total random forces deviate slightly from those derived utilizing the linear wave model. The distributions presented can be determined by the wave number spectrum of ocean waves, current speed and the second order wave-wave and wave-current interactions. As an illustrative example, for fully developed deep ocean waves, the parameters appeared in the distributions near still water level are calculated for various wind speeds and current speeds by using Donelan-Pierson-Banner spectrum and the effects of the current and the nonlinearity of ocean waves on the distribution are studied. (c) 2006 Elsevier Ltd. All rights reserved.

Tandem duplication-random loss is not a real feature of oyster mitochondrial genomes

Duplications and rearrangements of coding genes are major themes in the evolution of mitochondrial genomes, bearing important consequences in the function of mitochondria and the fitness of organisms. Yu et al. (BMC Genomics 2008, 9: 477) reported the complete mt genome sequence of the oyster Crassostrea hongkongensis (16,475 bp) and found that a DNA segment containing four tRNA genes (trnK(1), trnC, trnQ(1) and trnN), a duplicated (rrnS) and a split rRNA gene (rrnL5') was absent compared with that of two other Crassostrea species. It was suggested that the absence was a novel case of "tandem duplication-random loss" with evolutionary significance. We independently sequenced the complete mt genome of three C. hongkongensis individuals, all of which were 18,622 bp and contained the segment that was missing in Yu et al.'s sequence. Further, we designed primers, verified sequences and demonstrated that the sequence loss in Yu et al.'s study was an artifact caused by placing primers in a duplicated region. The duplication and split of ribosomal RNA genes are unique for Crassostrea oysters and not lost in C. hongkongensis. Our study highlights the need for caution when amplifying and sequencing through duplicated regions of the genome.

构造复杂区变速成图方法研究

In the complex structure areas, velocity field building and structure mapping are important for seismic exploration. With the development of seismic exploration, the methods of structure mapping, reservoir prediction and reservoir description all require high precious velocity field. And more accurate depth-structure maps are required for well site design. Aiming at the problems and defects in velocity analysis and structure mapping in oil seismic exploration, the paper which is based on the studies of real data in several areas combines the theories with practical application, and analyzes the precision and applicability of several methods of velocity model building. After that, the following methods are mainly studied: the coherence inversion methods based on the pre-stack CMP gathers or stacking velocity; the interval velocity inversion methods constrained by multi-well; the Random Simulation method; 3D Image Ray Map Migration method and the structure mapping in floating datum and in fixed datum, and then we conclude the method of building high precious seismic velocity field and structure mapping with variable velocity. Firstly, the paper analyses the distributing rule of the velocity variation in the areas with complex structures in the northwest of China, then points out that velocity is a crucial factor which influences the precision of structure mapping, and the velocity variations have something to do with the shapes of the structures, the variety of lithology and so on. The key point of improving the precision of seismic velocity field is to obtain a structure mapping with high precision. We also describe the range and conditions of these methods. Secondly, by comparing many popular methods of velocity model building, we propose a new method in the use of velocity model building. The new method is more effective in velocity model building under every kind of complex condition and is worthy of spreading. At last, the paper fingers out that it is a system engineering to study variable velocity mapping in every kind of complex structure areas. Every step of the work can affect the final results. So it is important to build high efficient and practical velocity model and the flows of mapping processing. The paper builds the flows and gives some examples. The method has been applied in more than ten exploring surveys. The application proves that this method could bring good effect on researching on low-amplitude trap, reservoir prediction, reservoir description and the integrated research of oil&gas geology. Keywords: structure mapping velocity model building complex structure variable velocity media

基于MRF模型的油气储层属性随机建模方法研究

Stochastic reservoir modeling is a technique used in reservoir describing. Through this technique, multiple data sources with different scales can be integrated into the reservoir model and its uncertainty can be conveyed to researchers and supervisors. Stochastic reservoir modeling, for its digital models, its changeable scales, its honoring known information and data and its conveying uncertainty in models, provides a mathematical framework or platform for researchers to integrate multiple data sources and information with different scales into their prediction models. As a fresher method, stochastic reservoir modeling is on the upswing. Based on related works, this paper, starting with Markov property in reservoir, illustrates how to constitute spatial models for catalogued variables and continuum variables by use of Markov random fields. In order to explore reservoir properties, researchers should study the properties of rocks embedded in reservoirs. Apart from methods used in laboratories, geophysical means and subsequent interpretations may be the main sources for information and data used in petroleum exploration and exploitation. How to build a model for flow simulations based on incomplete information is to predict the spatial distributions of different reservoir variables. Considering data source, digital extent and methods, reservoir modeling can be catalogued into four sorts: reservoir sedimentology based method, reservoir seismic prediction, kriging and stochastic reservoir modeling. The application of Markov chain models in the analogue of sedimentary strata is introduced in the third of the paper. The concept of Markov chain model, N-step transition probability matrix, stationary distribution, the estimation of transition probability matrix, the testing of Markov property, 2 means for organizing sections-method based on equal intervals and based on rock facies, embedded Markov matrix, semi-Markov chain model, hidden Markov chain model, etc, are presented in this part. Based on 1-D Markov chain model, conditional 1-D Markov chain model is discussed in the fourth part. By extending 1-D Markov chain model to 2-D, 3-D situations, conditional 2-D, 3-D Markov chain models are presented. This part also discusses the estimation of vertical transition probability, lateral transition probability and the initialization of the top boundary. Corresponding digital models are used to specify, or testify related discussions. The fifth part, based on the fourth part and the application of MRF in image analysis, discusses MRF based method to simulate the spatial distribution of catalogued reservoir variables. In the part, the probability of a special catalogued variable mass, the definition of energy function for catalogued variable mass as a Markov random field, Strauss model, estimation of components in energy function are presented. Corresponding digital models are used to specify, or testify, related discussions. As for the simulation of the spatial distribution of continuum reservoir variables, the sixth part mainly explores 2 methods. The first is pure GMRF based method. Related contents include GMRF model and its neighborhood, parameters estimation, and MCMC iteration method. A digital example illustrates the corresponding method. The second is two-stage models method. Based on the results of catalogued variables distribution simulation, this method, taking GMRF as the prior distribution for continuum variables, taking the relationship between catalogued variables such as rock facies, continuum variables such as porosity, permeability, fluid saturation, can bring a series of stochastic images for the spatial distribution of continuum variables. Integrating multiple data sources into the reservoir model is one of the merits of stochastic reservoir modeling. After discussing how to model spatial distributions of catalogued reservoir variables, continuum reservoir variables, the paper explores how to combine conceptual depositional models, well logs, cores, seismic attributes production history.

不同类型量表的线上调查和传统纸笔调查的比较研究

During the past 11 years, with the rapid development of the Internet, more and more psychologists began to realize and take advantage of it, which led to a growing number of psychological test administrated on the internet for data collection. But there were some controversy about the reliability and representatively of this new method. To examine the applicability of the Online Survey and how different types of scales used on the internet, we first reversed the measurement instrument, then from three different levels to investigate the equivalence of online survey and paper-and-pencil assessment, namely, sample level, scale level and item level. Both Classical Test Theory and Item Response Theory were used to analyze the invariance of different types of scale applicability on the internet. The main conclusions of this study could be drawn as follows: 1. In the sample-based study, self-select sample of the online survey was compared to the random sampled sample of paper-and-pencil assessment. The results showed there were no gender difference between them (p>0.05), but the online survey sample was characterized with high qualifications, high-income and younger features (88% of the sample with post-secondary education or above, and 71% aged 20 -29 years). There were significant differences on the scores of all scales between online survey and paper-and-pencil assessment (p<0.01). With demographic controlled, there was no significant difference on the variable of Neurotic between different surveys (p>0.05). 2. With in-group design, it was proved equivalence of the scale of BI (Attitude toward Brand Importance), BT (Attitude toword Brand Switcher), Extraversion, and Conscientiousbess in the compared study in the reliability, construct validity and average scores. 3. On the item level, the results based on the Item Response Theory analysis showed that 2PLM is appropriate for personality and attitude scales. With regard to personality scale, there emerged some items with DIF in the dimensions of Openness to the experience subscale and Agreeable subscale. However, there were no significant differences about the test function. 4. Exploring the psychometrics properties of answer formats of five-, six-, seven-, ten-points, it was showed that different measurement validity between online survey and paper-and-pencil test. It was also described the lower reliability and validity of six-point scale. In conclusion, the results support the application of personality scale online, but for attitude scale, we need to choose prudently.

Contextual models for object detection using boosted random fields

We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which uses Boosting to learn the graph structure and local evidence of a conditional random field (CRF). The graph structure is learned by assembling graph fragments in an additive model. The connections between individual pixels are not very informative, but by using dense graphs, we can pool information from large regions of the image; dense models also support efficient inference. We show how contextual information from other objects can improve detection performance, both in terms of accuracy and speed, by using a computational cascade. We apply our system to detect stuff and things in office and street scenes.

Learning and Example Selection for Object and Pattern Detection

This thesis presents a learning based approach for detecting classes of objects and patterns with variable image appearance but highly predictable image boundaries. It consists of two parts. In part one, we introduce our object and pattern detection approach using a concrete human face detection example. The approach first builds a distribution-based model of the target pattern class in an appropriate feature space to describe the target's variable image appearance. It then learns from examples a similarity measure for matching new patterns against the distribution-based target model. The approach makes few assumptions about the target pattern class and should therefore be fairly general, as long as the target class has predictable image boundaries. Because our object and pattern detection approach is very much learning-based, how well a system eventually performs depends heavily on the quality of training examples it receives. The second part of this thesis looks at how one can select high quality examples for function approximation learning tasks. We propose an {em active learning} formulation for function approximation, and show for three specific approximation function classes, that the active example selection strategy learns its target with fewer data samples than random sampling. We then simplify the original active learning formulation, and show how it leads to a tractable example selection paradigm, suitable for use in many object and pattern detection problems.

Estimating random transverse velocities in the fast solar wind from EISCAT Interplanetary Scintillation measurements

Canals, A.; Breen, A. R.; Ofman, L.; Moran, P. J.; Fallows, R. A., Estimating random transverse velocities in the fast solar wind from EISCAT Interplanetary Scintillation measurements, Annales Geophysicae, vol. 20, Issue 9, pp.1265-1277

A trait specific model of competition in a spatially structured plant community

John Warren and Chris Topping (2004). A trait specific model of competition in a spatially structured plant community. Ecological Modelling, 180 pp.477-485 RAE2008

On the Emergence of Highly Variable Distributions in the Autonomous System Topology

Recent studies have noted that vertex degree in the autonomous system (AS) graph exhibits a highly variable distribution [15, 22]. The most prominent explanatory model for this phenomenon is the Barabási-Albert (B-A) model [5, 2]. A central feature of the B-A model is preferential connectivity—meaning that the likelihood a new node in a growing graph will connect to an existing node is proportional to the existing node’s degree. In this paper we ask whether a more general explanation than the B-A model, and absent the assumption of preferential connectivity, is consistent with empirical data. We are motivated by two observations: first, AS degree and AS size are highly correlated [11]; and second, highly variable AS size can arise simply through exponential growth. We construct a model incorporating exponential growth in the size of the Internet, and in the number of ASes. We then show via analysis that such a model yields a size distribution exhibiting a power-law tail. In such a model, if an AS’s link formation is roughly proportional to its size, then AS degree will also show high variability. We instantiate such a model with empirically derived estimates of growth rates and show that the resulting degree distribution is in good agreement with that of real AS graphs.