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.

Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in Clouds: four kinds of schema.

The proposed research will focus on developing a novel approach to solve Software Service Evolution problems in Computing Clouds. The approach will support dynamic evolution of the software service in clouds via a set of discovered evolution patterns. An initial survey informed us that such an approach does not exist yet and is in urgent need. Evolution Requirement can be classified into evolution features; researchers can describe the whole requirement by using evolution feature typology, the typology will define the relation and dependency between each features. After the evolution feature typology has been constructed, evolution model will be created to make the evolution more specific. Aspect oriented approach can be used for enhance evolution feature-model modularity. Aspect template code generation technique will be used for model transformation in the end. Product Line Engineering contains all the essential components for driving the whole evolution process.

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

A model for the simulation of macroalgal population dynamics and productivity

A mathematical model to simulate the population dynamics and productivity of macroalgae is described. The model calculates the biomass variation of a population divided into size-classes. Biomass variation in each class is estimated from the mass balance of carbon fixation, carbon release and demographic processes such as mortality and frond breakage. The transitions between the different classes are calculated in biomass and density units as a function of algal growth. Growth is computed from biomass variations using an allometric relationship between weight and length. Gross and net primary productivity is calculated from biomass production and losses over the period of simulation. The model allows the simulation of different harvesting strategies of commercially important species. The cutting size and harvesting period may be changed in order to optimise the calculated yields. The model was used with the agarophyte Gelidium sesquipedale (Clem.) Born. et Thur. This species was chosen because of its economic importance as a the main raw material for the agar industry. Net primary productivity calculated with it and from biomass variations over a yearly period, gave similar results. The results obtained suggest that biomass dynamics and productivity are more sensitive to the light extinction coefficient than to the initial biomass conditions for the model. Model results also suggest that biomass losses due to respiration and exudation are comparable to those resulting from mortality and frond breakage. During winter, a significant part of the simulated population has a negative net productivity. The importance of considering different parameters in the productivity light relationships in order to account for their seasonal variability is demonstrated with the model results. The model was implemented following an object oriented programming approach. The programming methodology allows a fast adaptation of the model to other species without major software development.

A design pattern for integration of business process management systems

A cross-domain workflow application may be constructed using a standard reference model such as the one by the Workflow Management Coalition (WfMC) [7] but the requirements for this type of application are inherently different from one organization to another. The existing models and systems built around them meet some but not all the requirements from all the organizations involved in a collaborative process. Furthermore the requirements change over time. This makes the applications difficult to develop and distribute. Service Oriented Architecture (SOA) based approaches such as the BPET (Business Process Execution Language) intend to provide a solution but fail to address the problems sufficiently, especially in the situations where the expectations and level of skills of the users (e.g. the participants of the processes) in different organisations are likely to be different. In this paper, we discuss a design pattern that provides a novel approach towards a solution. In the solution, business users can design the applications at a high level of abstraction: the use cases and user interactions; the designs are documented and used, together with the data and events captured later that represents the user interactions with the systems, to feed an intermediate component local to the users -the IFM (InterFace Mapper) -which bridges the gaps between the users and the systems. We discuss the main issues faced in the design and prototyping. The approach alleviates the need for re-programming with the APIs to any back-end service thus easing the development and distribution of the applications

The assessment of a global marine ecosystem model on the basis of emergent properties and ecosystem function: a case study with ERSEM

Ecosystem models are often assessed using quantitative metrics of absolute ecosystem state, but these model-data comparisons are disproportionately vulnerable to discrepancies in the location of important circulation features. An alternative method is to demonstrate the models capacity to represent ecosystem function; the emergence of a coherent natural relationship in a simulation indicates that the model may have an appropriate representation of the ecosystem functions that lead to the emergent relationship. Furthermore, as emergent properties are large-scale properties of the system, model validation with emergent properties is possible even when there is very little or no appropriate data for the region under study, or when the hydrodynamic component of the model differs significantly from that observed in nature at the same location and time. A selection of published meta-analyses are used to establish the validity of a complex marine ecosystem model and to demonstrate the power of validation with emergent properties. These relationships include the phytoplankton community structure, the ratio of carbon to chlorophyll in phytoplankton and particulate organic matter, the ratio of particulate organic carbon to particulate organic nitrogen and the stoichiometric balance of the ecosystem. These metrics can also inform aspects of the marine ecosystem model not available from traditional quantitative and qualitative methods. For instance, these emergent properties can be used to validate the design decisions of the model, such as the range of phytoplankton functional types and their behaviour, the stoichiometric flexibility with regards to each nutrient, and the choice of fixed or variable carbon to nitrogen ratios.

Neurobiological model of visuo-spatial cognition in young Williams Syndrome children: measures of dorsal-stream and frontal function

We examine hypotheses for the neural basis of the profile of visual cognition in young children with Williams syndrome (WS). These are: (a) that it is a consequence of anomalies in sensory visual processing; (b) that it is a deficit of the dorsal relative to the ventral cortical stream; (c) that it reflects deficit of frontal function, in particular of fronto-parietal interaction; (d) that it is related to impaired function in the right hemisphere relative to the left. The tests reported here are particularly relevant to (b) and (c). They form part of a more extensive programme of investigating visual, visuospatial, and cognitive function in large group of children with WS children, aged 8 months to 15 years. To compare performance across tests, avoiding floor and ceiling effects, we have measured performance in children with WS in terms of the ‘age equivalence’ for typically developing children. In this paper the relation between dorsal and ventral function was tested by motion and form coherence thresholds respectively. We confirm the presence of a subgroup of children with WS who perform particularly poorly on the motion (dorsal) task. However, such performance is also characteristic of normally developingchildren up to 5 years: thus the WS performance may reflect an overall persisting immaturity of visuospatial processing which is particularly evident in the dorsal stream. Looking at the performance on the global coherence tasks of the entire WS group, we find that there is also a subgroup who have both high form and motion coherence thresholds, relative to the performance of children of the same chronological age and verbal age on the BPVS, suggesting a more general global processing deficit. Frontal function was tested by a counterpointing task, ability to retrieve a ball from a ‘detour box’, and the Stroop-like ‘day-night’ task, all of which require inhibition of a familiar response. When considered in relation to overall development as indexed by vocabulary, the day-night task shows little specific impairment, the detour box shows a significant delay relative to controls, and the counterpointing task shows a marked and persistent deficit in many children. We conclude that frontal control processes show most impairment in WS when they are associated with spatially directed responses, reflecting a deficit of fronto-parietal processing. However, children with WS may successfully reduce the effect of this impairment by verbally mediated strategies. On all these tasks we find a range of difficulties across individual children and a small subset of WS who show very good performance, equivalent to chronological age norms of typically developing children. Neurobiological models of visuo-spatial cognition in children with WS p.4 Overall, we conclude that children with WS have specific processing difficulties with tasks involving frontoparietal circuits within the spatial domain. However, some children with WS can achieve similar performance to typically developing children on some tasks involving the dorsal stream, although the strategies and processing may be different in the two groups.

System oriented neural networks - Problem formulation, methodology and application

A novel methodology is proposed for the development of neural network models for complex engineering systems exhibiting nonlinearity. This method performs neural network modeling by first establishing some fundamental nonlinear functions from a priori engineering knowledge, which are then constructed and coded into appropriate chromosome representations. Given a suitable fitness function, using evolutionary approaches such as genetic algorithms, a population of chromosomes evolves for a certain number of generations to finally produce a neural network model best fitting the system data. The objective is to improve the transparency of the neural networks, i.e. to produce physically meaningful