With the advancement of technology, there has been a push to transition from the conventional electric grid to a smart grid. A smart grid is an electric delivery system that uses technology such as electronic sensors and digital communication networks to improve the reliability, resilience, and efficiency of the system. The transition toward a smart grid has increased the importance of networked control systems (NCS), which are the infrastructure that allows sensors, actuators and controllers to exchange information via a digital communication network. The research presents the development of an islanded generator NCS, and a grid connected NCS, and the investigation of the effects of cyberattacks on the NCS. This research considers two types of cyberattacks, such as Denial-of-Service (DoS) attack, and false data injection in the generator control loop. DoS attacks greatly increase the rate of packet loss and the duration of packet delay in a network. A high degree of packet drop and delay degrade the performance of the controller, which causes problems in the synchronization of the generator with the rest of the grid. False data injection in the sensors alters the generator terminal voltage and power output, and can cause the generator to lose synchronism. A mathematical model of the generator NCS systems is developed which includes the data acquisition and network characteristics, as well as the generator dynamics. The stability analysis of each NCS is performed which provides a mathematical approach to understanding the severity of cyberattacks that the system can tolerate before becoming unstable. The performance of the controllers, with respect to voltage control, is experimentally evaluated. / Educational Psychology

Embryonic development depends on the precise coordination of cell fate specification, patterning and morphogenesis. Although great strides have been made in the molecular understanding of each of these processes, how their interplay governs the formation of complex tissues remains poorly understood. New techniques for experimental manipulation and image quantification enable the study of development in unprecedented detail, resulting in new hypotheses on the interactions between known components. By expressing these hypotheses in terms of rules and equations, computational modeling and simulation allows one to test their consistency against experimental data. However, new computational methods are required to represent and integrate the network of interactions between gene regulation, signaling and biomechanics that extend over the molecular, cellular and tissue scales. In this thesis, I present a framework that facilitates computational modeling of multiscale multicellular systems and apply it to investigate pancreatic development and the formation of vascular networks. This framework is based on the integration of discrete cell-based models with continuous models for intracellular regulation and intercellular signaling. Specifically, gene regulatory networks are represented by differential equations to analyze cell fate regulation; interactions and distributions of signaling molecules are modeled by reaction-diffusion systems to study pattern formation; and cell-cell interactions are represented in cell-based models to investigate morphogenetic processes. A cell-centered approach is adopted that facilitates the integration of processes across the scales and simultaneously constrains model complexity. The computational methods that are required for this modeling framework have been implemented in the software platform Morpheus. This modeling and simulation environment enables the development, execution and analysis of multi-scale models of multicellular systems. These models are represented in a new domain-specific markup language that separates the biological model from the computational methods and facilitates model storage and exchange. Together with a user-friendly graphical interface, Morpheus enables computational modeling of complex developmental processes without programming and thereby widens its accessibility for biologists. To demonstrate the applicability of the framework to problems in developmental biology, two case studies are presented that address different aspects of the interplay between cell fate specification, patterning and morphogenesis. In the first, I focus on the interplay between cell fate stability and intercellular signaling. Specifically, two studies are presented that investigate how mechanisms of cell-cell communication affect cell fate regulation and spatial patterning in the pancreatic epithelium. Using bifurcation analysis and simulations of spatially coupled differential equations, it is shown that intercellular communication results in a multistability of gene expression states that can explain the scattered spatial distribution and low cell type ratio of nascent islet cells. Moreover, model analysis shows that disruption of intercellular communication induces a transition between gene expression states that can explain observations of in vitro transdifferentiation from adult acinar cells into new islet cells. These results emphasize the role of the multicellular context in cell fate regulation during development and may be used to optimize protocols for cellular reprogramming. The second case study focuses on the feedback between patterning and morphogenesis in the context of the formation of vascular networks. Integrating a cell-based model of endothelial chemotaxis with a reaction-diffusion model representing signaling molecules and extracellular matrix, it is shown that vascular network patterns with realistic morphometry can arise when signaling factors are retained by cell-modified matrix molecules. Through the validation of this model using in vitro assays, quantitative estimates are obtained for kinetic parameters that, when used in quantitative model simulations, confirm the formation of vascular networks under measured biophysical conditions. These results demonstrate the key role of the extracellular matrix in providing spatial guidance cues, a fact that may be exploited to enhance vascularization of engineered tissues. Together, the modeling framework, software platform and case studies presented in this thesis demonstrate how cell-centered computational modeling of multi-scale and multicellular systems provide powerful tools to help disentangle the complex interplay between cell fate specification, patterning and morphogenesis during embryonic development.

The background to this thesis is the impact of information technology on libraries and librarywork. If information technology causes changes in the tasks and work of libraries, thenlibrary organisations should also change. It is important to engage and inform the staff if suchchanges are to succeed. This thesis investigates the notions about library tasks and librarywork among eight "middle-managers" at Linkopings universitetsbibliotek.The investigation is based on interviews and then analysed with Soft Systems Methodology(SSM). By identifying the "Weltanschauung" of the staff, the thesis tries to create logicallydesirable and culturally feasible models of systems relevant to the situation at Linkopingsuniversitetsbibliotek. Based on the interviews, this thesis proposes two such models.The first model aims to make the library users competent to seek, find and evaluate their owninformation. The aim of the second model is to make library work more efficient by gettingthe staff to see themselves as parts of a process instead of isolated functions.

Der Trend auch für schnelle, zeitkritische Regelungsaufgaben geht zunehmend in Richtung Feldbusse und Industrial Ethernet. Dem unbestreitbaren Nutzen der Kosteneinsparung stehen Probleme gegenüber: Die unsicheren Zeitbedingungen im Netz verschlechtern die dynamischen Eigenschaften digitaler Regelungen in unvorhersehbarer Weise. Diese Arbeit stellt eine praktikable Methodik vor, um die Regelgüte solcher Systeme sicher und aufwandsarm vorherzusagen. / High dynamic, i.e. time-critical automatic feedback control systems are more and more implemented using field bus or industrial ethernet solutions. The cost-efficiency of these approaches is unchallengeable, but they also cause serious technical problems: Uncertain time behavior of data networks so far degrades the dynamic performance of digital closed-loop controls in an unpredictable manner. The research paper introduces a practicable, reliable and straightforward method to forecast the system behavior.

Real-time collaborative editing systems are groupware systems that allow members of a team to simultaneously edit shared documents from different sites. Shared objects involved in the team activity are subject to concurrent accesses and real-time constrains. Starting with the dOPT algorithm of Ellis and Gibbs various algorithms using operational transformation for maintaining consistency in collaborative systems have been proposed: adOPTed, GOT, GOTO and etc. All these algorithms are based on a linear representation of the document. In this work we discuses about algorithms based on a tree representation of the document. We propose several algorithms based on dOPT algorithms for operation transformations for XML based documents. Experimental development helps to evaluate and demonstrate practical application for algorithms testing. Detailed commented experiment supplements formal description with practical strategies and specifics.

No description available.

The cell is the central functional unit of life. Cell behaviors, such as cell division, movements, differentiation, cell death as well as cell shape and size changes, determine how tissues change shape and grow during regeneration and development. However, a generally applicable framework to measure and describe the behavior of the multitude of cells in a developing tissue is still lacking. Furthermore, the specific contribution of individual cell behaviors, and how exactly these cell behaviors collectively lead to the morphogenesis and growth of tissues are not clear for many developmental and regenerative processes. A promising strategy to fill these gaps is the continuing effort of making developmental biology a quantitative science. Recent advances in methods, especially in imaging, enable measurements of cell behaviors and tissue shapes in unprecedented detail and accuracy. Consequently, formalizing hypotheses in terms of mathematical models to obtain testable quantitative predictions is emerging as a powerful tool. Tests of the hypotheses involve the comparison of model predictions to experimentally observed data. The available data is often noisy and based on only few samples. Hence, this comparison of data and model predictions often requires very careful use of statistical inference methods. If one chooses this quantitative approach, the challenges are the choice of observables, i.e. what to measure, and the design of appropriate data-driven models to answer relevant questions. In this thesis, I applied this data-driven modeling approach to vertebrate morphogenesis, growth and regeneration. In particular, I study spinal cord and muscle regeneration in axolotl, muscle development in zebrafish, and neuron development and maintenance in the adult human brain. To do so, I analyzed images to quantify cell behaviors and tissue shapes. Especially for cell behaviors in post-embryonic tissues, measurements of some cell behavior parameters, such as the proliferation rate, could not be made directly. Hence, I developed mathematical models that are specifically designed to infer these parameters from indirect experimental data. To understand how cell behaviors shape tissues, I developed mechanistic models that causally connect the cell and tissue scales. Specifically, I first investigated the behaviors of neural stem cells that underlie the regenerative outgrowth of the spinal cord after tail amputation in the axolotl. To do so, I quantified all relevant cell behaviors. A detailed analysis of the proliferation pattern in space and time revealed that the cell cycle is accelerated between 3-4 days after amputation in a high-proliferation zone, initially spanning from 800 µm anterior to the amputation plane. The activation of quiescent stem cells and cell movements into the high-proliferation zone also contribute to spinal cord growth but I did not find contributions by cellular rearrangements or cell shape changes. I developed a mathematical model of spinal cord outgrowth involving all contributing cell behaviors which revealed that the acceleration of the cell cycle is the major driver of spinal cord outgrowth. To compare the behavior of neural stem cells with cell behaviors in the regenerating muscle tissue that surrounds the spinal cord, I also quantified proliferation of mesenchymal progenitor cells and found similar proliferation parameters. I showed that the zone of mesenchymal progenitors that gives rise to the regenerating muscle segments is at least 350 µm long, which is consistent with the length of the high-proliferation zone in the spinal cord. Second, I investigated shape changes in developing zebrafish muscle segments by quantifying time-lapse movies of developing zebrafish embryos. These data challenged or ruled out a number of previously proposed mechanisms. Motivated by reported cellular behaviors happening simultaneously in the anterior segments, I had previously proposed the existence of a simple tension-and-resistance mechanism that shapes the muscle segments. Here, I could verify the predictions of this mechanism for the final segment shape pattern. My results support the notion that a simple physical mechanism suffices to self-organize the observed spatiotemporal pattern in the muscle segments. Third, I corroborated and refined previous estimates of neuronal cell turnover rates in the adult human hippocampus. Previous work approached this question by combining quantitative data and mathematical modeling of the incorporation of the carbon isotope C-14. I reanalyzed published data using the published deterministic neuron turnover model but I extended the model by a better justified measurement error model. Most importantly, I found that human adult neurogenesis might occur at an even higher rate than currently believed. The tools I used throughout were (1) the careful quantification of the involved processes, mainly by image analysis, and (2) the derivation and application of mathematical models designed to integrate the data through (3) statistical inference. Mathematical models were used for different purposes such as estimating unknown parameters from indirect experiments, summarizing datasets with a few meaningful parameters, formalizing mechanistic hypotheses, as well as for model-guided experimental planning. I venture an outlook on how additional open questions regarding cell turnover measurements could be answered using my approach. Finally, I conclude that the mechanistic understanding of development and regeneration can be advanced by comparing quantitative data to the predictions of specifically designed mathematical models by means of statistical inference methods.

South Africa is located in the sub tropics with an elevated plateau which is located approximately 1500 m above mean sea level (a.m.s.l). Every year, snow occurs on the mountains of Lesotho, but on occasions this snow descends to lower elevations which impacts on the livelihood of people. Severe weather originating from extra-tropical weather systems has been well documented in South Africa and yet very little research has been done to predict significant snowfall from these weather systems. The main aim of this research is to identify those weather systems responsible for snow and to understand the processes causing snow to form when these systems occur. A comprehensive database of significant snowfall events is supplied from 1981 to 2011. The database is subjectively classified into characteristic synoptic patterns. The snow cases are then objectively classified using self-organising maps (SOMs) to obtain synoptic configurations most typically associated with significant snowfall over South Africa. Case studies which aim to explain the synoptic conditions, formation mechanisms as well as critical surface temperature and relative humidity during snowfall events are described. This is done by analysing each case study with respect to synoptic circulations, surface observations, atmospheric soundings, satellite imagery as well as atmospheric thickness. Conclusions are drawn and critical threshold values of atmospheric thickness, surface temperature and humidity are identified when snowfall occurs. A methodical snow forecasting decision tree is devised. It takes the synoptic classification of circulation patterns during significant snowfall, atmospheric thickness, height of the freezing level, surface temperature, and relative humidity into account. This process is explained by case studies. It is recommended that results from this dissertation are made available to weather forecasters in South Africa and that the results are implemented in the operational forecasting environment. Further case study investigations are suggested, taking the mesoscale processes effects into account. / Dissertation (MSc)--University of Pretoria, 2013. / am2013 / Geography, Geoinformatics and Meteorology / MSc / Unrestricted

The cell is the central functional unit of life. Cell behaviors, such as cell division, movements, differentiation, cell death as well as cell shape and size changes, determine how tissues change shape and grow during regeneration and development. However, a generally applicable framework to measure and describe the behavior of the multitude of cells in a developing tissue is still lacking. Furthermore, the specific contribution of individual cell behaviors, and how exactly these cell behaviors collectively lead to the morphogenesis and growth of tissues are not clear for many developmental and regenerative processes. A promising strategy to fill these gaps is the continuing effort of making developmental biology a quantitative science. Recent advances in methods, especially in imaging, enable measurements of cell behaviors and tissue shapes in unprecedented detail and accuracy. Consequently, formalizing hypotheses in terms of mathematical models to obtain testable quantitative predictions is emerging as a powerful tool. Tests of the hypotheses involve the comparison of model predictions to experimentally observed data. The available data is often noisy and based on only few samples. Hence, this comparison of data and model predictions often requires very careful use of statistical inference methods. If one chooses this quantitative approach, the challenges are the choice of observables, i.e. what to measure, and the design of appropriate data-driven models to answer relevant questions. In this thesis, I applied this data-driven modeling approach to vertebrate morphogenesis, growth and regeneration. In particular, I study spinal cord and muscle regeneration in axolotl, muscle development in zebrafish, and neuron development and maintenance in the adult human brain. To do so, I analyzed images to quantify cell behaviors and tissue shapes. Especially for cell behaviors in post-embryonic tissues, measurements of some cell behavior parameters, such as the proliferation rate, could not be made directly. Hence, I developed mathematical models that are specifically designed to infer these parameters from indirect experimental data. To understand how cell behaviors shape tissues, I developed mechanistic models that causally connect the cell and tissue scales. Specifically, I first investigated the behaviors of neural stem cells that underlie the regenerative outgrowth of the spinal cord after tail amputation in the axolotl. To do so, I quantified all relevant cell behaviors. A detailed analysis of the proliferation pattern in space and time revealed that the cell cycle is accelerated between 3-4 days after amputation in a high-proliferation zone, initially spanning from 800 µm anterior to the amputation plane. The activation of quiescent stem cells and cell movements into the high-proliferation zone also contribute to spinal cord growth but I did not find contributions by cellular rearrangements or cell shape changes. I developed a mathematical model of spinal cord outgrowth involving all contributing cell behaviors which revealed that the acceleration of the cell cycle is the major driver of spinal cord outgrowth. To compare the behavior of neural stem cells with cell behaviors in the regenerating muscle tissue that surrounds the spinal cord, I also quantified proliferation of mesenchymal progenitor cells and found similar proliferation parameters. I showed that the zone of mesenchymal progenitors that gives rise to the regenerating muscle segments is at least 350 µm long, which is consistent with the length of the high-proliferation zone in the spinal cord. Second, I investigated shape changes in developing zebrafish muscle segments by quantifying time-lapse movies of developing zebrafish embryos. These data challenged or ruled out a number of previously proposed mechanisms. Motivated by reported cellular behaviors happening simultaneously in the anterior segments, I had previously proposed the existence of a simple tension-and-resistance mechanism that shapes the muscle segments. Here, I could verify the predictions of this mechanism for the final segment shape pattern. My results support the notion that a simple physical mechanism suffices to self-organize the observed spatiotemporal pattern in the muscle segments. Third, I corroborated and refined previous estimates of neuronal cell turnover rates in the adult human hippocampus. Previous work approached this question by combining quantitative data and mathematical modeling of the incorporation of the carbon isotope C-14. I reanalyzed published data using the published deterministic neuron turnover model but I extended the model by a better justified measurement error model. Most importantly, I found that human adult neurogenesis might occur at an even higher rate than currently believed. The tools I used throughout were (1) the careful quantification of the involved processes, mainly by image analysis, and (2) the derivation and application of mathematical models designed to integrate the data through (3) statistical inference. Mathematical models were used for different purposes such as estimating unknown parameters from indirect experiments, summarizing datasets with a few meaningful parameters, formalizing mechanistic hypotheses, as well as for model-guided experimental planning. I venture an outlook on how additional open questions regarding cell turnover measurements could be answered using my approach. Finally, I conclude that the mechanistic understanding of development and regeneration can be advanced by comparing quantitative data to the predictions of specifically designed mathematical models by means of statistical inference methods.

Chez les bactéries à Gram-négatif, deux systèmes très bien conservés et essentiels à la survie de la cellule bactérienne ont été identifiés : les systèmes Tol et TonB. Ces deux systèmes utilisent la force proton motrice, issue de la membrane interne et transfert l’énergie associée pour le transport actif de molécules (TonB) ou nécessaire au maintien de l’intégrité membranaire (Tol). Ces 2 systèmes ont été détournés de leurs fonctions initiales et parasités par les colicines, leur conférant un rôle primordial dans le mécanisme d’import de la colicine. Une colicine est une bactériocine (toxine) produite par Escherichia coli pour tuer des souches apparentées. Ce sont des toxines spécifiques et hautement actives. Cependant E.coli a développé des mécanismes de protection afin de résister à l’action cytotoxique des colicines. Ces mécanismes de résistance consistent essentiellement à produire des protéines d’immunité, qui vont pour la plupart se fixer sur le domaine catalytique de la colicine et l’empêcher d’exercer son action létale. La bactérie Yersinia pestis, agent de la peste, possède une colicin-like bactériocine, la pesticine, dont l’activité est de dégrader le peptidoglycane. L’action de la pesticine est inhibée par une protéine d’immunité, Pim, localisée dans le périplasme. Le principal objectif de ce projet est de comprendre les mécanismes d’inhibition de la pesticine par sa protéine d’immunité, grâce à des données biochimiques et structurales, mais aussi d’apporter des solutions pour contourner ce problème de résistance. La structure de la pesticine révèle des homologies structurales avec le T4 lysozyme du bactériophage T4. Pour contourner le problème de la résistance bactérienne liée à la protéine d’immunité, une solution a été de fusionner le domaine de réception/translocation de la pesticine avec le T4 lysozyme. Nous avons ainsi pu créer et résoudre la structure tridimensionnelle d’une protéine chimère fonctionnelle, capable de se fixer sur FyuA (récepteur de la pesticine) et tuer une souche exprimant ce récepteur et dont l’activité létale n’est pas inhibée par Pim. / In Gram-negative bacteria, two essential systems for cell survival have been characterized: the Tol and TonB system. Both Ton and Tol systems are very well conserved in Gram-negative bacteria and coupled to the proton motive force across the inner membrane, acting as energy transducers for active transport (Ton) or maintenance of outer envelope integrity (Tol). Both systems have been embezzled from their primary function and hijacked by colicins as part of the colicin killing pathway. Colicin is a bacteriocin (toxin) produced by and toxic to some strains of Escherichia coli. Colicins are highly effective toxins. However E.coli could develop protective mechanisms to resist to colicin cytotoxic effect. These mechanisms essentially consist to produce an immunity protein. These proteins bind to colicin catalytic domain and inhibit its lethal activity. Yersinia pestis, plague agent, possesses its own colicin-like bacteriocin, Pesticin, which degrades murein. Pesticin activity is inhibited by an immunity protein, Pim, localized in the periplasm. The main goal of this project is to understand inhibition mechanisms between Pim and Pesticin by biochemical and structural data and to provide solution to overcome the resistance issue, since Pesticin was thought to be used as antimicrobial agent. The Pesticin structure has revealed that Pesticin share structural homologies with the T4 lysozyme from the bacteriophage T4. To overcome the resistance issue due to the immunity protein, one solution has been to fuse the Pesticin binding/translocation domain with the T4 lysozyme. Thus, we could engineered and solved the three-dimensional structure of a chimera protein, able to bind FyuA (Pesticin physiological receptor) and kill a FyuA expressing strain, in which the lethal activity is not affected by Pim.