Performance assessment of Surrogate model integrated with sensitivity analysis in multi-objective optimization

This Thesis develops a new multi-objective heuristic algorithm. The optimum searching task is performed by a standard genetic algorithm. Furthermore, it is assisted by the Response Surface Methodology surrogate model and by two sensitivity analysis methods: the Variance-based, also known as Sobol’ analysis, and the Elementary Effects. Once built the entire method, it is compared on several multi-objective problems with some other algorithms

An in vitro and in silico study of altered airway smooth muscle structure and function in a remodelled asthmatic airway

Inflammatory processes in the airway lead to altered extracellular matrix (ECM) and increased airway smooth muscle (ASM), which is responsible for the rapid contraction of asthmatic airways during exacerbations. Increased ASM contributes substantially to the thickening of airways (airway remodelling), and a higher likelihood of experiencing potentially fatal attacks. In culture, ASM cells exhibit changes in shape and contractile ability between a spindle-shaped contractile phenotype and a more rounded proliferative phenotype with synthetic properties capable of depositing ECM. The link between phenotype switching and corresponding changes in structure, function and relative bio-mechanical abilities in vivo is unclear, but key in understanding remodelling. The aim of this project is to combine in silico and in vitro techniques in order to develop models that contribute to the identification of key mechanisms involved in airway remodelling and provide a framework for predicting dynamic mechanical changes in airway tissue. We first summarise and extend our previously developed ODE model accounting for ASM phenotype and ECM changes triggered by environmental stimuli, based on a newly discovered pathway of remodelling (Chapter 2). Bifurcation analysis of this model identifies a mechanism by which irreversible increases in ECM and ASM mass could occur, given a particular parameter range. We therefore develop two novel experimental serum deprivation protocols using cultured human ASM and microscopy to more accurately quantify the cell phenotype switching rates, as these are the parameters to which the model is most sensitive (Chapter 3). Our experimental results suggest that ASM contractility is increased and that there are structural changes in ASM cells upon switching to a contractile phenotype. Using this temporal data, we demonstrate the use of a Bayesian inference approach to estimate model parameters and inform future experimental design (Chapter 4). We then extend this work through the development of a new bio-mechanical vertex-based cell model represented by a network of damped springs and contractile elements, in combination with spatial traction force microscopy data, to investigate changes in mechanical properties of the altered tissue (Chapter 5). We incorporate a physical and functional change in contractile cells and find that the model replicates the elongation, stress and strain properties that we would expect of this cell phenotype. In order to replicate the ASM phenotype switching that we initiate experimentally through serum deprivation, we then further develop this model by adding the random switching of cell phenotypes over the simulation period. This allows us to explore the hypothesis that the mechanical environment of ASM cells and their neighbours drives changes in the structure and function of the tissue, and hence is key in the phenotype switching process (Chapter 6). The vertex-based bio-mechanical model is also used to test the impact of simulating an asthmatic exacerbation and, much like with the ODE model, results show a mechanism by which long-term changes to ASM cells could occur (Chapter 7). Having tested the impact of a single exacerbation event in isolation, we then mimic the full traction force microscopy experimental protocol using this model and appropriate cell numbers. We find that the model qualitatively agrees well with the dynamics displayed in the experimental results. This computational framework could be exploited to investigate whether cell signalling changes the alignment of internal contractile machinery (increases cell elongation) first, which then drives phenotype change, or vice versa. Understanding more about these processes and their impact on asthma development is key for the ultimate aim of finding new therapeutic targets. This and other scope for future work is discussed in Chapter 8

An in vitro and in silico study of altered airway smooth muscle structure and function in a remodelled asthmatic airway

Inflammatory processes in the airway lead to altered extracellular matrix (ECM) and increased airway smooth muscle (ASM), which is responsible for the rapid contraction of asthmatic airways during exacerbations. Increased ASM contributes substantially to the thickening of airways (airway remodelling), and a higher likelihood of experiencing potentially fatal attacks. In culture, ASM cells exhibit changes in shape and contractile ability between a spindle-shaped contractile phenotype and a more rounded proliferative phenotype with synthetic properties capable of depositing ECM. The link between phenotype switching and corresponding changes in structure, function and relative bio-mechanical abilities in vivo is unclear, but key in understanding remodelling. The aim of this project is to combine in silico and in vitro techniques in order to develop models that contribute to the identification of key mechanisms involved in airway remodelling and provide a framework for predicting dynamic mechanical changes in airway tissue. We first summarise and extend our previously developed ODE model accounting for ASM phenotype and ECM changes triggered by environmental stimuli, based on a newly discovered pathway of remodelling (Chapter 2). Bifurcation analysis of this model identifies a mechanism by which irreversible increases in ECM and ASM mass could occur, given a particular parameter range. We therefore develop two novel experimental serum deprivation protocols using cultured human ASM and microscopy to more accurately quantify the cell phenotype switching rates, as these are the parameters to which the model is most sensitive (Chapter 3). Our experimental results suggest that ASM contractility is increased and that there are structural changes in ASM cells upon switching to a contractile phenotype. Using this temporal data, we demonstrate the use of a Bayesian inference approach to estimate model parameters and inform future experimental design (Chapter 4). We then extend this work through the development of a new bio-mechanical vertex-based cell model represented by a network of damped springs and contractile elements, in combination with spatial traction force microscopy data, to investigate changes in mechanical properties of the altered tissue (Chapter 5). We incorporate a physical and functional change in contractile cells and find that the model replicates the elongation, stress and strain properties that we would expect of this cell phenotype. In order to replicate the ASM phenotype switching that we initiate experimentally through serum deprivation, we then further develop this model by adding the random switching of cell phenotypes over the simulation period. This allows us to explore the hypothesis that the mechanical environment of ASM cells and their neighbours drives changes in the structure and function of the tissue, and hence is key in the phenotype switching process (Chapter 6). The vertex-based bio-mechanical model is also used to test the impact of simulating an asthmatic exacerbation and, much like with the ODE model, results show a mechanism by which long-term changes to ASM cells could occur (Chapter 7). Having tested the impact of a single exacerbation event in isolation, we then mimic the full traction force microscopy experimental protocol using this model and appropriate cell numbers. We find that the model qualitatively agrees well with the dynamics displayed in the experimental results. This computational framework could be exploited to investigate whether cell signalling changes the alignment of internal contractile machinery (increases cell elongation) first, which then drives phenotype change, or vice versa. Understanding more about these processes and their impact on asthma development is key for the ultimate aim of finding new therapeutic targets. This and other scope for future work is discussed in Chapter 8

The Telecommunications and Data Acquisition Report

Deep Space Network (DSN) progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operation is discussed. In addition, developments in Earth-based radio technology as applied to geodynamics, astrophysics and the radio search for extraterrestrial intelligence are reported

COINSTAC: A Privacy Enabled Model and Prototype for Leveraging and Processing Decentralized Brain Imaging Data

The field of neuroimaging has embraced the need for sharing and collaboration. Data sharing mandates from public funding agencies and major journal publishers have spurred the development of data repositories and neuroinformatics consortia. However, efficient and effective data sharing still faces several hurdles. For example, open data sharing is on the rise but is not suitable for sensitive data that are not easily shared, such as genetics. Current approaches can be cumbersome (such as negotiating multiple data sharing agreements). There are also significant data transfer, organization and computational challenges. Centralized repositories only partially address the issues. We propose a dynamic, decentralized platform for large scale analyses called the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC). The COINSTAC solution can include data missing from central repositories, allows pooling of both open and ``closed'' repositories by developing privacy-preserving versions of widely-used algorithms, and incorporates the tools within an easy-to-use platform enabling distributed computation. We present an initial prototype system which we demonstrate on two multi-site data sets, without aggregating the data. In addition, by iterating across sites, the COINSTAC model enables meta-analytic solutions to converge to ``pooled-data'' solutions (i.e. as if the entire data were in hand). More advanced approaches such as feature generation, matrix factorization models, and preprocessing can be incorporated into such a model. In sum, COINSTAC enables access to the many currently unavailable data sets, a user friendly privacy enabled interface for decentralized analysis, and a powerful solution that complements existing data sharing solutions

Interference Modeling And Control In Wireless Networks

With the successful commercialization of IEEE802.11 standard, wireless networks have become a tight-knit of our daily life. As wireless networks are increasingly applied to real- time and mission-critical tasks, how to ensuring real-time, reliable data delivery emerges as an important problem. However, wireless communication is subject to various dynamics and uncertainties due to the broadcast nature of wireless signal. In particular, co-channel interfer- ence not only reduces the reliability and throughput of wireless networks, it also increases the variability and uncertainty in data communication [64, 80, 77]. A basis of interference control is the interference model which \emph{predicts} whether a set of concurrent transmissions may interfere with one another. Two commonly used models, the \textit{SINR model} and the \textit{radio-K model}, are thoroughly studied in our work. To address the limitations of those models, we propose the physical-ratio-K(PRK) interference model as a reliablility-oriented instantiation of the ratio-K model, where the link-specific choice of K adapts to network and environmental conditions as well as application QoS requirements to ensure certain minimum reliability of every link. On the other hand, the interference among the transmissions, limits the number of con- current transmissions. We formulate the concept of \emph{interference budget} that, given a set of scheduled transmissions in a time slot, characterizes the additional interference power that can be tolerated by all the receivers without violating the application requirement on link reliability. We propose the scheduling algorithm \emph{iOrder} that optimizes link ordering by considering both interference budget and queue length in scheduling. Through both simulation and real-world experiments, we observe that optimizing link ordering can improve the performance of existing algorithms by a significant. Based on the strong preliminary research result on interference modeling and control, we will extend our method into distributed protocol designs. One future work will focus on imple- menting the \textit{PRK model} in a distributed protocols. We will also explore the benefits of using multiple channels in the interference control

A Unifying Theory for Graph Transformation

The field of graph transformation studies the rule-based transformation of graphs. An important branch is the algebraic graph transformation tradition, in which approaches are defined and studied using the language of category theory. Most algebraic graph transformation approaches (such as DPO, SPO, SqPO, and AGREE) are opinionated about the local contexts that are allowed around matches for rules, and about how replacement in context should work exactly. The approaches also differ considerably in their underlying formal theories and their general expressiveness (e.g., not all frameworks allow duplication). This dissertation proposes an expressive algebraic graph transformation approach, called PBPO+, which is an adaptation of PBPO by Corradini et al. The central contribution is a proof that PBPO+ subsumes (under mild restrictions) DPO, SqPO, AGREE, and PBPO in the important categorical setting of quasitoposes. This result allows for a more unified study of graph transformation metatheory, methods, and tools. A concrete example of this is found in the second major contribution of this dissertation: a graph transformation termination method for PBPO+, based on decreasing interpretations, and defined for general categories. By applying the proposed encodings into PBPO+, this method can also be applied for DPO, SqPO, AGREE, and PBPO