Information Surfaces in Systems Biology and Applications to Engineering Sustainable Agriculture

Systems biology of plants offers myriad opportunities and many challenges in modeling. A number of technical challenges stem from paucity of computational methods for discovery of the most fundamental properties of complex dynamical systems. In systems engineering, eigen-mode analysis have proved to be a powerful approach. Following this philosophy, we introduce a new theory that has the benefits of eigen-mode analysis, while it allows investigation of complex dynamics prior to estimation of optimal scales and resolutions. Information Surfaces organizes the many intricate relationships among "eigen-modes" of gene networks at multiple scales and via an adaptable multi-resolution analytic approach that permits discovery of the appropriate scale and resolution for discovery of functions of genes in the model plant Arabidopsis. Applications are many, and some pertain developments of crops that sustainable agriculture requires.Comment: 24 Pages, DoCEIS 1

Exploring pathways for sustainable water management in river deltas in a changing environment

Exploring adaptation pathways into an uncertain future can support decisionmaking in achieving sustainable water management in a changing environment. Our objective is to develop and test a method to identify such pathways by including dynamics from natural variability and the interaction between the water system and society. Present planning studies on long-term water management often use a few plausible futures for one or two projection years, ignoring the dynamic aspect of adaptation through the interaction between the water system and society. Our approach is to explore pathways using multiple realisations of transient scenarios with an Integrated Assessment Meta Model (IAMM). This paper presents the first application of the method using a hypothetical case study. The case study shows how to explore and evaluate adaptation pathways. With the pathways it is possible to identify opportunities, threats, timing and sequence of policy options, which can be used by policymakers to develop water management roadmaps into the future. By including the dynamics between the water system and society, the influence of uncertainties in both systems becomes clearer. The results show, among others, that climate variability rather than climate change appears to be important for taking decisions in water management

A Model-Centric Framework for Advanced Operation of Crystallization Processes

Crystallization is the main physical separation process in many chemical industries. It is an old unit operation which can separate solids of high purity from liquids, and is widely applied in the production of food, pharmaceuticals, and fine chemicals. While industries in crystallization operation quite rely on rule-of-thumb techniques to fulfill their requirement, the move towards a scientific- and technological- based approach is becoming more important as it provides a mechanism for driving crystallization processes optimally and in more depth without increasing costs. Optimal operation of industrial crystallizers is a prerequisite these days for achieving the stringent requirements of the consumer-driven manufacturing. To achieve this, a generic and flexible model centric framework is developed for the advanced operation of crystallization processes. The framework deploys the modern software environment combined with the design of a state-of-the-art 1-L crystallization laboratory facility. The emphasis is on developing an economically and practically feasible implementation which can be applied for the optimal operation of various crystallization systems by pharmaceutical industries. The key developments in the framework have occurred in three broad categories: i. Modeling: Using an advanced modeling tool is intended for accurate representation of the behavior of the physical system. This is the cornerstone of any simulation, optimization or model-based control approach. ii. Monitoring: Applying a novel image-based technique for online characterization of the particulate processes. This is a promising method for direct tracking of particle size and size distribution with high adaptability for real-time application iii. Control: Proposing numerous model-based strategies for advanced control of the crystallization system. These strategies enable us to investigate the role of model complexity on real-time control design. Furthermore, the effect of model imperfections, process uncertainty and decision variables on optimal operation of the process can be evaluated. Overall, results from this work presents a robust platform for further research in the area of crystal engineering. Most of the developments described will pave the way for future set of activities being targeted towards extending and adapting advanced modeling, monitoring and control concepts for different crystallization processes

Parametrization of stochastic inputs using generative adversarial networks with application in geology

We investigate artificial neural networks as a parametrization tool for stochastic inputs in numerical simulations. We address parametrization from the point of view of emulating the data generating process, instead of explicitly constructing a parametric form to preserve predefined statistics of the data. This is done by training a neural network to generate samples from the data distribution using a recent deep learning technique called generative adversarial networks. By emulating the data generating process, the relevant statistics of the data are replicated. The method is assessed in subsurface flow problems, where effective parametrization of underground properties such as permeability is important due to the high dimensionality and presence of high spatial correlations. We experiment with realizations of binary channelized subsurface permeability and perform uncertainty quantification and parameter estimation. Results show that the parametrization using generative adversarial networks is very effective in preserving visual realism as well as high order statistics of the flow responses, while achieving a dimensionality reduction of two orders of magnitude

ReSCon '09, Research Student Conference: Book of Abstracts

The second SED Research Student Conference (ReSCon2009) was hosted over three days, 22-24 June 2009, in the Lecture Centre at Brunel University. The conference consisted of technical presentations, a poster session and social events. The abstracts and presentations were the result of ongoing research by postgraduate research students from the School of Engineering and Design at Brunel University. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Traffic Multiresolution Modeling and Consistency Analysis of Urban Expressway Based on Asynchronous Integration Strategy

The paper studies multiresolution traffic flow simulation model of urban expressway. Firstly, compared with two-level hybrid model, three-level multiresolution hybrid model has been chosen. Then, multiresolution simulation framework and integration strategies are introduced. Thirdly, the paper proposes an urban expressway multiresolution traffic simulation model by asynchronous integration strategy based on Set Theory, which includes three submodels: macromodel, mesomodel, and micromodel. After that, the applicable conditions and derivation process of the three submodels are discussed in detail. In addition, in order to simulate and evaluate the multiresolution model, “simple simulation scenario” of North-South Elevated Expressway in Shanghai has been established. The simulation results showed the following. (1) Volume-density relationships of three submodels are unanimous with detector data. (2) When traffic density is high, macromodel has a high precision and smaller error and the dispersion of results is smaller. Compared with macromodel, simulation accuracies of micromodel and mesomodel are lower but errors are bigger. (3) Multiresolution model can simulate characteristics of traffic flow, capture traffic wave, and keep the consistency of traffic state transition. Finally, the results showed that the novel multiresolution model can have higher simulation accuracy and it is feasible and effective in the real traffic simulation scenario

System Engineering Applied to Fuenmayor Karst Aquifer (San Julián de Banzo, Huesca) and Collins Glacier (King George Island, Antarctica)

La ingeniería de sistemas, definida generalmente como arte y ciencia de crear soluciones integrales a problemas complejos, se aplica en el presente documento a dos sistemas naturales, a saber, un sistema acuífero kárstico y un sistema glaciar, desde una perspectiva hidrológica. Las técnicas de identificación, desarrolladas típicamente en ingeniería para representar sistemas artificiales por medio de modelos lineales y no lineales, pueden aplicarse en el estudio de los sistemas naturales donde se producen fenómenos de acoplamiento entre el clima y la hidrosfera. Los métodos evolucionan para afrontar nuevos campos de identificación donde se requieren estrategias para encontrar el modelo idóneo adaptado a las peculiaridades del sistema. En este sentido, se han considerado especialmente las herramientas basadas en la transformada wavelet utilizadas en la preparación de series temporales, suavizado de señales, análisis espectral, correlación cruzada y predicción, entre otros. Bajo este enfoque, una aplicación a mencionar entre las tratadas en esta tesis, es la determinación analítica del núcleo efectivo estacional (SEC) a través del estudio de la coherencia wavelet entre temperatura del aire y la descarga del glaciar, que establece un conjunto de períodos de muestreo aceptablemente coherentes, a partir del cual se crearán los modelos del sistema glacial. El estudio está dirigido específicamente a estimar la influencia de la precipitación sobre la descarga del acuífero kárstico de Fuenmayor, en San Julián de Banzo, Huesca, España. De la misma manera, se ocupa de las consecuencias de la temperatura del aire en la fusión del hielo glaciar, que se manifiesta en la corriente de drenaje del glaciar Collins, isla King George, Antártida. En el proceso de identificación paramétrica y no paramétrica se buscan los modelos que mejor representen la dinámica interna del sistema. Eso conduce a pruebas iterativas, donde se van creando modelos que se verifican sistemáticamente con los datos reales del muestreo, de acuerdo a un criterio de eficiencia dado. La solución mejor valorada según los resultados obtenidos en los casos tratados apuntan a estructuras de modelos en bloques. Esta tesis significa una exposición formal de la metodología de identificación de sistemas propios de la ingeniería en el contexto de los sistemas naturales, que mejoran los resultados obtenidos en muchos casos de la hidrología kárstica que comúnmente usaban métodos ad hoc ocasionales de carácter estadístico; así mismo, los enfoques propuestos en los casos de glaciología con el análisis wavelet y los modelos orientados a datos raramente considerados en la literatura, revelan información esencial ante la imposibilidad de precisar la totalidad de la física que rige el sistema. Notables resultados se derivan en la caracterización de la respuesta del manantial de Fuenmayor y su correlación con la precipitación, desde la perspectiva de un sistema lineal, que se complementa con los métodos de identificación basados en técnicas no lineales. Así mismo, la implementación del modelo para el glaciar Collins, obtenido también mediante métodos de identificación de caja negra, puede revelar una inestabilidad de los límites de los periodos activos de la descarga, y consecuentemente la variabilidad en la tendencia actual en el cambio climático global

Wave Propagation

A wave is one of the basic physics phenomena observed by mankind since ancient time. The wave is also one of the most-studied physics phenomena that can be well described by mathematics. The study may be the best illustration of what is “science”, which approximates the laws of nature by using human defined symbols, operators, and languages. Having a good understanding of waves and wave propagation can help us to improve the quality of life and provide a pathway for future explorations of the nature and universe. This book introduces some exciting applications and theories to those who have general interests in waves and wave propagations, and provides insights and references to those who are specialized in the areas presented in the book