Rossby waves with linear topography in barotropic fluids

Rossby waves are the most important waves in the atmosphere and ocean, and are parts of a large-scale system in fluid. The theory and observation show that, they satisfy quasi-geostrophic and quasi-static equilibrium approximations. In this paper, solitary Rossby waves induced by linear topography in barotropic fluids with a shear flow are studied. In order to simplify the problem, the topography is taken as a linear function of latitude variable y, then employing a weakly nonlinear method and a perturbation method, a KdV (Korteweg-de Vries) equation describing evolution of the amplitude of solitary Rossby waves induced by linear topography is derived. The results show that the variation of linear topography can induce the solitary Rossby waves in barotropic fluids with a shear flow, and extend the classical geophysical theory of fluid dynamics.

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.

基于模拟退火算法的挤出模参数优化

建立了塑料熔体在异型材挤出机头流道中的流动均匀性模型 ,阐明了模具结构参数与流动均匀性间的关系,确定了塑料挤出模优化设计的目标函数和设计变量 ,并将一种改进的模拟退火算法用于流线型塑料异型材挤出机头的优化设计。实例表明所用方法对挤出模优化设计的适用性,该方法在利用经验的同时 ,优化了模具结构参数 ,提高了模具设计的智能化

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.

文33块沙二下段油藏动态模型及剩余油预测

By applying synthetically multi-subject theories, methods and technology, such as petroleum geology, sedimentology, seep mechanics, geochemistry, geophysics and so on; and by making full use of computer; combining quantity and quality, macroscopic and microscopic, intensive static and active description, comprehensive studying and physical modeling, 3 dimension and 4 dimension description; the paper took Wen-33 block of Zhongyuan oil field as an example; and studied reservoir macroscopic and microscopic parameter changing rule and evolve mechanics in different water-blood stage. The reservoir dynamic model and remaining-oil distribution mode was established, and several results were achieved as follows: (1) Three types of parameter gaining, optimizing and whole data body of Wen33th reservoir were established. Strata framework, structure framework, reservoir types and distribution of Wen33th reservoir were discussed. Reservoir genesis types, space distribution law and evolve rule of Wen33th reservoir were explained. 4D dynamic model of macroscopic parameter of reservoir flow dynamic geologic function of Wen33th reservoir was established. The macroscopic remaining-oil distribution and control factor was revealed. The models of the microscopic matrix field, pore-throat network field, fluid field, clay mineral field of Wen-33 block were established. The characters, changing rules and controlled factors in different water stage were revealed. The evolve rule and mechanics of petroleum fluid field in Wen-33 block reservoir were revealed. Macroscopic and microscopic remaining oil distribution mode of Wen-33 block were established. Seven types, namely 12 shapes of dynamic model of microscopic remaining oil were discussed, and the distribution of mover remaining oil was predicted. Emulation model: mathematical model and prediction model of Wen-33 block were established. The changing mechanics of reservoir parameter and distribution of remaining-oil were predicted. Firstly, the paper putting forward that the dynamic geologic function of petroleum development is the factor of controlling remaining-oil, which is the main factor leading to matrix field, network field, clay mineral field, fluid field, physic and chemical field, stress field and fluid field forming and evolving. (10) A set of theories, methods and technologies of investigating, describing, characterizing and predicting complex fault-block petroleum were developed.

花岗岩风化土微观结构及其工程地质特性研究

Saprolite is the residual soil resulted from completely weathered or highly weathered granite and with corestones of parent rock. It is widely distributed in Hong Kong. Slope instability usually happens in this layer of residual soil and thus it is very important to study the engineering geological properties of Saprolite. Due to the relic granitic texture, the deformation and strength characteristics of Saprolite are very different from normal residual soils. In order to investigate the effects of the special microstructure on soil deformation and strength, a series of physical, chemical and mechanical tests were conducted on Saprolite at Kowloon, Hong Kong. The tests include chemical analysis, particle size analysis, mineral composition analysis, mercury injection, consolidation test, direct shear test, triaxial shear test, optical analysis, SEM & TEM analysis, and triaxial shear tests under real-time CT monitoring.Based on the testing results, intensity and degree of weathering were classified, factors affecting and controlling the deformation and strength of Saprolite were identified, and the interaction between those factors were analyzed.The major parameters describing soil microstructure were introduced mainly based on optical thin section analysis results. These parameters are of importance and physical meaning to describe particle shape, particle size distribution (PSD), and for numerical modeling of soil microstructure. A few parameters to depict particle geometry were proposed or improved. These parameters can be used to regenerate the particle shape and its distribution. Fractal dimension of particle shape was proposed to describe irregularity of particle shapes and capacity of space filling quantitatively. And the effect of fractal dimension of particle shape on soil strength was analyzed. At the same time, structural coefficient - a combined parameter which can quantify the overall microstructure of rock or soil was introduced to study Saprolite and the results are very positive. The study emphasized on the fractal characteristics of PSD and pore structure by applying fractal theory and method. With the results from thin section analysis and mercury injection, it was shown that at least two fractal dimensions Dfl(DB) and Df2 (Dw), exist for both PSD and pore structure. The reasons and physical meanings behind multi-fractal dimensions were analyzed. The fractal dimensions were used to calculate the formation depth and weathering rate of granite at Kowloon. As practical applications, correlations and mathematical models for fractal dimensions and engineering properties of soil were established. The correlation between fractal dimensions and mechanical properties of soil shows that the internal friction angle is mainly governed by Dfl 9 corresponding to coarse grain components, while the cohesion depends on Df2 , corresponding to fine grain components. The correlations between the fractal dimension, friction angle and cohesion are positive linear.Fractal models of PSD and pore size distribution were derived theoretically. Fragmentation mechanism of grains was also analyzed from the viewpoint of fractal. A simple function was derived to define the theoretical relationship between the water characteristic curve (WCC) and fractal dimension, based on a number of classical WCC models. This relationship provides a new analytical tool and research method for hydraulic properties in porous media and solute transportation. It also endues fractal dimensions with new physical meanings and facilitates applications of fractal dimensions in water retention characteristics, ground water movement, and environmental engineering.Based on the conclusions from the fractal characteristics of Saprolite, size effect on strength was expressed by fractal dimension. This function is in complete agreement with classical Weibull model and a simple function was derived to represent the relationship between them.In this thesis, the phenomenon of multi-fractal dimensions was theoretically analyzed and verified with WCC and saprolite PSD results, it was then concluded that multi-fractal can describe the characteristics of one object more accurately, compared to single fractal dimension. The multi-fractal of saprolite reflects its structural heterogeneity and changeable stress environment during the evolution history.

Retention behavior of hydrophobic organic chemicals as a function of temperature in soil leaching column chromatography

To study the transport mechanism of hydrophobic organic chemicals (HOCs) and the energy change in soil/solvent system, a soil leaching column chromatographic (SLCC) experiment at an environmental temperature range of 20-40 degreesC was carried out, which utilized a reference soil (SP 14696) packed column and a methanol-water (1:4 by volume ratio) eluent. The transport process quickens with the increase of column temperature. The ratio of retention factors at 30 and 40 degreesC (k'(30)/k'(40)) ranged from 1.08 to 1.36. The lower enthalpy change of the solute transfer in SLCC (from eluent to soil) than in conventional reversed-phase liquid chromatography (e.g., from eluent to C-18) is consistent with the hypothesis that HOCs were dominantly and physically partitioned between solvent and soil. The results were also verified by the linear solvation energy relationships analysis. The chief factor controlling the retention was found to be the solute solvophobic partition, and the second important factor was the solute hydrogen-bond basicity, while the least important factors were the solute polarizability-dipolarity and hydrogen-bond acidity. With the increase of temperature, the contributions of the solute solvophobic partition and hydrogen-bond basicity gradually decrease, and the latter decreases faster than the former. (C) 2002 Elsevier Science Ltd. All rights reserved.

A Radial Basis Function Approach to Financial Time Series Analysis

Nonlinear multivariate statistical techniques on fast computers offer the potential to capture more of the dynamics of the high dimensional, noisy systems underlying financial markets than traditional models, while making fewer restrictive assumptions. This thesis presents a collection of practical techniques to address important estimation and confidence issues for Radial Basis Function networks arising from such a data driven approach, including efficient methods for parameter estimation and pruning, a pointwise prediction error estimator, and a methodology for controlling the "data mining'' problem. Novel applications in the finance area are described, including customized, adaptive option pricing and stock price prediction.

Causal and Teleological Reasoning in Circuit Recognition

This thesis presents a theory of human-like reasoning in the general domain of designed physical systems, and in particular, electronic circuits. One aspect of the theory, causal analysis, describes how the behavior of individual components can be combined to explain the behavior of composite systems. Another aspect of the theory, teleological analysis, describes how the notion that the system has a purpose can be used to aid this causal analysis. The theory is implemented as a computer program, which, given a circuit topology, can construct by qualitative causal analysis a mechanism graph describing the functional topology of the system. This functional topology is then parsed by a grammar for common circuit functions. Ambiguities are introduced into the analysis by the approximate qualitative nature of the analysis. For example, there are often several possible mechanisms which might describe the circuit's function. These are disambiguated by teleological analysis. The requirement that each component be assigned an appropriate purpose in the functional topology imposes a severe constraint which eliminates all the ambiguities. Since both analyses are based on heuristics, the chosen mechanism is a rationalization of how the circuit functions, and does not guarantee that the circuit actually does function. This type of coarse understanding of circuits is useful for analysis, design and troubleshooting.

Pancreatic and adrenal development and function in an ovine model of polycystic ovary syndrome.

Polycystic Ovary Syndrome (PCOS) is a complex disorder encompassing reproductive and metabolic dysfunction. Ovarian hyperandrogenism is an endocrine hallmark of human PCOS. In animal models, PCOS-like abnormalities can be recreated by in utero over-exposure to androgenic steroid hormones. This thesis investigated pancreatic and adrenal development and function in a unique model of PCOS. Fetal sheep were directly exposed (day 62 and day 82 of gestation) to steroidal excesses - androgen excess (testosterone propionate - TP), estrogen excess (diethylstilbestrol - DES) or glucocorticoid excess (dexamethasone - DEX). At d90 gestation there was elevated expression of genes involved in β- cell development and function: PDX-1 (P<0.001), and INS (P<0.05), INSR (P<0.05) driven by androgenic excess only in the female fetal pancreas. β- cell numbers (P<0.001) and in vitro insulin secretion (P<0.05) were also elevated in androgen exposed female fetuses. There was a significant increase in insulin secreting β-cell numbers (P<0.001) and in vivo insulin secretion (glucose stimulated) (P<0.01) in adult female offspring, specifically associated with prenatal androgen excess. At d90 gestation, female fetal adrenal gene expression was perturbed by fetal estrogenic exposure. Male fetal adrenal gene expression was altered more dramatically by fetal glucocorticoid exposure. In female adult offspring from androgen exposed pregnancies there was increased adrenal steroidogenic gene expression and in vivo testosterone secretion (P<0.01). This highlights that the adrenal glands may contribute towards excess androgen secretion in PCOS, but such effects might be secondary to other metabolic alterations driven by prenatal androgen exposure, such as excess insulin secretion Thus there may be dialogue between the pancreas and adrenal gland, programmed during early life, with implications for adult health Given both hyperinsulinaemia and hyperandrogenism are common features in PCOS, we suggest that their origins may be at least partially due to altered fetal steroidal environments, specifically excess androgenic stimulation

Domain 4: The Education Function.

This chapter examines the role of the advanced nurse practitioner (ANP) within the domains of practice identified by the Royal College of Nursing (2002) as the teaching and coaching function. (Note that this is referred to by the NMC as the education function. It approaches the analysis against the backdrop of three policy documents: The Expert Patient: a new approach to chronic disease management for the 21st century(DoH 2001), Choosing Health: making healthy choices easier (DoH 2004), Our health, our care, our say (DoH 2006). It draws into the frame the experiences of ANP students as they work with patients, clients and carers, with the intention of enabling health and managing illness. It uses examples from a range of everyday practice setting to illustrate the inherent challenges of the teaching and coaching function of the ANP, at the same time as recognising its significance if patients, clients and carers are to be enabled to make choices that might optimize their well-being. Before this, however, some statistics are presented to focus thinking on why education is an invaluable component of advanced nursing practice.

Muscle function and body composition profile in adolescents withrestrictive anorexia nervosa: Does resistance training help?

The aim of this study was to analyze the effects of short-term resistance training on the body composition profile and muscle function in a group of Anorexia Nervosa restricting type (AN-R) patients. The sample consisted of AN-R female adolescents (12.8 ± 0.6 years) allocated into the control and intervention groups (n¼18 each). Body composition and relative strength were assessed at baseline, after 8 weeks and 4 weeks following the intervention. Body mass index (BMI) increased throughout the study (p = 0.011). Significant skeletal muscle mass (SMM) gains were found in the intervention group (p = 0.045, d = 0.6) that correlated to the change in BMI (r = 0.51, p < 0.031). Meanwhile, fat mass (FM) gains were significant in the control group (p = 0.047, d = 0.6) and correlated (r > 0.60) with change in BMI in both the groups. Significant relative strength increases (p < 0.001) were found in the intervention group and were sustained over time.

Confirmation of Data Mining Based Predictions of Protein Function

King, R. D. and Wise, P. H. and Clare, A. (2004) Confirmation of Data Mining Based Predictions of Protein Function. Bioinformatics 20(7), 1110-1118

Predicting gene function in Saccharomyces cerevisiae

Clare, A. and King R.D. (2003) Predicting gene function in Saccharomyces cerevisiae. 2nd European Conference on Computational Biology (ECCB '03). (published as a journal supplement in Bioinformatics 19: ii42-ii49)