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Brain development is a complex and highly organized process that relies on the coordinated interaction between neurons and vessels. These cell systems form a neurovascular link that involves the exchange of oxygen, ions, and other physiological components necessary for proper neuronal and vascular function. This physiologically coupled process is executed through analogous structural and molecular signaling mechanisms shared by both cell types. At the neurovascular interface, the cellular crosstalk via these shared signaling mechanisms allows for the synchronized expansion and integration of neurons and vessels into complex cellular networks. This study investigated the role of VEGFR2, a receptor for vascular endothelial growth factor (VEGF), during postnatal neuronal development in the mouse hippocampus. Prior studies have revealed physiological roles of VEGF, a pro-angiogenic morphogen, in nervous system development. However, it was unclear if VEGF signaling had a direct effect on neuronal physiology and function through neuronal-expressing receptors. In this investigative work, we identified a previously unknown function of VEGFR2, whereby VEGF-induced signaling coordinates the development and circuitry integration of CA3 pyramidal neurons in the early postnatal mouse hippocampus. Mechanistically, we found that VEGFR2 signaling requires receptor endocytosis, a process mediated by ephrinB2. We also found that VEGF-induced cooperative signaling between VEGFR2 and ephrinB2 is functionally required for the dendritic arborization and spine maturation of developing CA3 neurons during the first few postnatal weeks. Moreover, in a collaborative effort with the research group of Carmen Ruiz de Almodovar, formerly at the University of Heidelberg, we simultaneously studied VEGF-induced VEGFR2 signaling in CA3 axonal development. Together, we aimed to gain a comprehensive understanding of the complex interplay between VEGF and VEGFR2 signaling during the early postnatal development of CA3 neurons. Ruiz de Almodovar’s research group found that, unlike the branch and spine development of CA3 dendrites, VEGF-VEGFR2 signaling promotes axonal development through mechanisms that are independent of ephrinB2 function. Our findings on CA3 dendritic development are reported in the published manuscript, Harde et al. (2019), and the complementary work on CA3 axonal development from Ruiz de Almodovar's group is presented in the co-published manuscript, Luck et al. (2019). Although the totality of Ruiz de Almodovar's group's work on CA3 axons is not fully discussed here, it is referenced where noted to provide biological context for our findings on CA3 dendritic development.
VEGFR2 signaling within neurovascular niches is known to play a role in the neurogenesis of neural progenitor cells during embryonic development and within the adult brain. However, the precise localization of neuronal VEGFR2 expression and functional role within the nervous system during postnatal brain development was unknown. To investigate this, we used immunohistochemistry to identify the spatial expression of VEGFR2 within the mouse hippocampus during the first few weeks after birth. Our results showed that VEGFR2 was predominantly expressed within the hippocampal vasculature, consistent with prior studies. However, we also observed localized VEGFR2 expression in pyramidal cell neurons of the hippocampal CA3 region by postnatal day 10 (P10). This spatially restricted postnatal expression of VEGFR2 in CA3 neurons suggested a potential role in the development of these neurons during this developmental stage.
The first two weeks after birth in the mouse hippocampus is a critical period for the development of neuronal circuits, as neurons undergo extensive dendritic arborization and spine formation. To explore the role of VEGFR2 in the postnatal nervous system, we used a Nes-cre VEGFR2lox/- mouse line to target the deletion of VEGFR2 expression within the nervous system while preserving normal receptor expression in all other cell types. We also generated corresponding control mice that were negative for Nes-cre. By breeding these mice with Thy1-GFP reporter mice, we could analyze the functional consequences of VEGFR2 by assessing the morphologies of CA3 dendritic trees and spine density and maturation at P10 and P15, respectively. Our analysis showed that CA3 neurons in Nes-cre VEGFR2lox/- mice had less complex dendritic arbors compared to control mice. There were significant reductions in total length and branch points, particularly in areas located 100-250 μm from the cell soma within the stratum radiatum layer. Additionally, Nes-cre VEGFR2lox/- mice exhibited a significant decrease in spine density accompanied by an increased proportion of immature spines. These findings suggest that VEGFR2 plays a crucial role in the proper development of CA3 dendrites and spines during the early postnatal weeks.
In view of a growing world population and the finite nature of fossil resources, the development of eco-friendly production processes is essential for the transition towards a sustainable industry. Methanol, which can be produced both petrochemically and from renewable resources, offers itself as bridging technology and attractive alternative raw material for biotechnological processes. This work describes developments for the progress of the well-studied methylotrophic α proteobacterium Methylorubrum extorquens AM1 towards an efficient methylotrophic cell factory. Although many homologous and heterologous production routes have already been described and realized for M. extorquens in a laboratory scale, no industrial process has yet been realized. Three major reasons can be identified for this: (1) A limited choice of tools for genetic modifications, (2) a lack of understanding of carbon fluxes and side reactions occurring in modified strains, such as product reimports, and (3) the lack of tailored production strains for profitable target products and optimized bioprocessing protocols. The aim of the present work was to achieve developments for the mentioned areas. As a model application, the high-level production of chiral dicarboxylic acids from the substrate methanol was chosen. Enantiomerically pure chiral compounds are of great interest, e.g., as building blocks for chiral drugs. The ethylmalonyl CoA metabolic pathway (EMCP) which is part of the primary metabolism of M. extorquens, harbors unique chiral CoA-ester intermediates. Their acid derivatives can be released by cleavage of the CoA-moiety using heterologous enzymes. The dicarboxylic acids 2 methylsuccinic acid and mesaconic acid were produced in a previous study by introducing the heterologous thioesterase YciA into M. extorquens. In the said study, a combined product titer of 0.65 g/L was obtained in shake flask experiments. These results serve as the basis for the developments in the present work.
First, the previously described reuptake of products was thoroughly investigated and dctA2, a gene encoding for an acid transporter, was identified as target for reducing the product reuptake. In addition, reuptake of mesaconic acid was prevented by converting it to (S)-citramalic acid, a product not metabolizable by M. extorquens, by the introduction of a heterologous mesaconase. Together with 2-methylsuccinic acid, for which a high enantiomeric excess of (S)-2-methylsuccinic acid was determined, a second chiral molecule was thus added to the product spectrum. For the release of dicarboxylic acid products, YciA, a broad-range thioesterase that accepts a variety of CoA-esters with different chain lengths as substrates, was chosen. The enzyme should theoretically be able to hydrolyze all CoA-esters of interest present in the EMCP. However, in culture supernatants of M. extorquens strains that were overexpressing the corresponding yciA gene, only mesaconic acid and 2 methylsuccinic acid could be detected. To expand the substrate spectrum of YciA thioesterase with respect to other EMCP intermediates, semi-rational enzyme engineering was attempted. Screening of the corresponding strains carrying the respective YciA variants did not result in strains capable of producing new dicarboxylic acid products. However, the experiments revealed an amino acid position that strongly affected the production of mesaconic acid and 2-methylsuccinic acid in vivo. By substituting the according amino acid in YciA, the maximum titers of mesaconic acid and 2-methylsuccinic acid could be increased substantially. Application of an improved thioesterase variant in a second E. coli-based process confirmed the enhanced activity of the enzyme. The desired extension of the product spectrum by another chiral molecule (2-hydroxy-3-methylsuccinic acid, presumably the (2S,3R)-form) was finally achieved by using an alternative thioesterase. Tailored fermentation strategies were developed for the high-level production of the above-mentioned products.
As second part of the work, two novel genetic tools for M. extorquens were developed and characterized. The pBBR1-derived plasmid pMis1_1B was shown to be stably maintained in M. extorquens cells. In addition, its suitability for co-transformations with other plasmids was demonstrated. The second tool, the cumate-inducible promoter Ps6, is tailored for expression of pathways with toxic products, as the transcription of genes controlled by Ps6 is strongly repressed in the absence of an inducer.
Overall, the present work demonstrates the enormous potential of using M. extorquens as a methylotrophic cell factory. In the applications shown, the biotechnological production of high-priced chiral molecules is combined with the use of an attractive alternative substrate. In addition, new achievements and approaches are presented to facilitate the development of future M. extorquens production strains.
The single-source shortest-path problem is a fundamental problem in computer science. We consider a generalization of the shortest-path problem, the $k$-shortest path problem. Let $G$ be a directed edge-weighted graph with $n$ nodes and $m$ edges and $s,t$ be two fixed nodes. The goal is to compute $k$ paths $P_1,\dots,P_k$ between two fixed nodes $s$ and $t$ in non-decreasing order of their length such that all other paths between $s$ and $t$ are at least as long as the $k$\nth path $P_k$. We focus on the version of the $k$-shortest path problem where the paths are not allowed to visit nodes multiple times, sometime referred to as $k$-shortest simple path problem.
The probably best known $k$-shortest path algorithm is Yen's algorithm. It has a worst-case time complexity of O(kn\cdot scp(n,m)), where scp(n,m) is the complexity of the single-source shortest-path algorithm used as a subroutine. In case of Dijkstra's algorithm scp(n,m) is O(m + n\log n). One of the more recent improvements of Yen's algorithm is by Feng.
Even though Feng's algorithm is much faster in practice, it has the same worst-case complexity as Yen's algorithm.
The main results presented in this thesis are upper bounds on the average-case of Yen's and Feng's algorithm, as well as practical improvements and a parallel implementation of Yen's and Feng's algorithms including these improvements. The implementation is publicly available under GPLv3 open source license.
We show in our analysis that Yen's algorithm has an average-case complexity of O(k \log(n)\cdot scp(n,m)) on G(n,p) graphs with at least logarithmic average-degree and random edge weights following a distribution with certain properties.
On G(n,p) graphs with constant to logarithmic average-degree and uniform random edge-weights over $[0;1]$, we show an average-case complexity of O(k\cdot\frac{\log^2 n}{np}\cdot scp(n,m)). Feng's algorithm has an even better average-case complexity of O(k\cdot scp(n,m)) on unweighted G(n,p) graphs with logarithmic average-degree and for constant values of $k$. We further provide evidence that the same holds true for G(n,p) graphs with uniform random edge-weights over $[0;1]$.
On the practical side, we suggest new heuristics to prune even more single-source shortest-path computations than Feng's algorithm and evaluate all presented algorithms on G(n,p) and Grid graphs with up to 256 million nodes. We demonstrate speedups by a factor of up to 40 compared to Feng's algorithm.
Finally we discuss two ways to parallelize the suggested algorithms and evaluate them on grid graphs showing speedups by a factor of 2 using 4 threads and by a factor of up to 8 using 16 threads, respectively.
Artificial intelligence in heavy-ion collisions : bridging the gap between theory and experiments
(2023)
Artificial Intelligence (AI) methods are employed to study heavy-ion collisions at intermediate collision energies, where high baryon density and moderate temperature QCD matter is produced. The experimental measurements of various conventional observables such as collective flow, particle number fluctuations, etc. are usually compared with expensive model calculations to infer the physics governing the evolution of the matter produced in the collisions. Various experimental effects and processing algorithms can greatly affect the sensitivity of these observables. AI methods are used to bridge this gap between theory and experiments of heavy-ion collisions. The problems with conventional methods of analyzing experimental data are illustrated in a comparative study of the Glauber MC model and the UrQMD transport model. It is found that the centrality determination and the estimated fluctuations of the number of participant nucleons suffer from strong model dependencies for Au-Au collisions at 1.23 AGeV. This can bias the results of the experimental analysis if the number of participant nucleons used is not consistent throughout the analysis and in the final model-to-data comparison. The measurable consequences of this model dependence of the number of participant nucleons are also discussed. In this context, PointNet-based AI models are developed to accurately reconstruct the impact parameter or the number of participant nucleons in a collision event from the hits and/or reconstructed track of particles in 10 AGeV Au-Au collisions at the CBM experiment. In the last part of the thesis, different AI methods to study the equation of state (EoS) at high baryon densities are discussed. First, a Bayesian inference is performed to constrain the density dependence of the EoS from the available experimental measurements of elliptical flow and mean transverse kinetic energy of mid rapidity protons in intermediate energy collisions. The UrQMD model was augmented to include arbitrary potentials (or equivalently the EoSs) in the QMD part to provide a consistent treatment of the EoS throughout the evolution of the system. The experimental data constrain the posterior constructed for the EoS for densities up to four times saturation density. However, beyond three times saturation density, the shape of the posterior depends on the choice of observables used. There is a tension in the measurements at a collision energy of about 4 GeV. This could indicate large uncertainties in the measurements, or alternatively the inability of the underlying model to describe the observables with a given input EoS. Tighter constraints and fully conclusive statements on the EoS require accurate, high statistics data in the whole beam energy range of 2-10 GeV, which will hopefully be provided by the beam energy scan programme of STAR-FXT at RHIC, the upcoming CBM experiment at FAIR, and future experiments at HIAF and NICA. Finally, it is shown that the PointNet-based models can also be used to identify the equation of state in the CBM experiment. Despite the uncertainties due to limited detector acceptance and biases in the reconstruction algorithms, the PointNet-based models are able to learn the features that can accurately identify the underlying physics of the collision. The PointNet-based models are an ideal AI tool to study heavy-ion collisions, not only to identify the geometric event features, such as the impact parameter or the number of participant nucleons, but also to extract abstract physical features, such as the EoS, directly from the detector outputs.
The EMT-transcription factor ZEB1 has been intensively studied in solid cancers, where it is expressed at the invasive front and in cancer-associated fibroblasts (CAFs). In tumour cells, ZEB1 has been involved in multiple steps of cancer progression including stemness, metastasis and therapy resistance, yet its role in the tumour-microenvironment is largely unknown. Here, the role of Zeb1 in CAFs was investigated using mouse models reflecting different tumour stages in immunocompetent fibroblast specific Zeb1 KO mice. Fibroblast-specific depletion of Zeb1 accelerated tumour growth in the inflammation driven AOM/DSS tumour initiation model, reduced tumour growth and invasion in the sporadic AOM/P53 model and reduced liver metastasis in a progressed orthotopic transplantation model. Immunohistochemical and single cell RNA-sequencing analysis showed that Zeb1 ablation resulted in attenuated expression of the myofibroblast marker aSMA and reduced ECM deposition, indicating a shift among fibroblast subpopulations. Modulation of CAFs was furthermore associated with increased inflammatory signaling in fibroblasts resulting in immune infiltration into primary tumours and exaggerated inflammatory signaling in T cells, B cells and macrophages. These changes in the tumour microenvironment were associated with increased efficacy of immune checkpoint inhibition therapy. In summary, Zeb1 expression in CAFs was identified as a potential target to block immunosuppression and metastatic dissemination in colon cancer.
A synchrotron is a particular type of cyclic particle accelerator and the first accelerator concept to enable the construction of large-scale facilities [10], such as the largest particle accelerator in the world, the 27-kilometre-circumference Large Hadron Collider (LHC) by CERN near Geneva, Switzerland, the European Synchrotron Radiation Facility (ESRF) in Grenoble, France for the synchrotron radiation, the superconducting, heavy ion synchrotron SIS100 under construction for the FAIR facility at GSI, Darmstadt, Germany and so on. Unlike a cyclotron, which can accelerate particles starting at low kinetic energy, a synchrotron needs a pre-acceleration facility to accelerate particles to an appropriate initial value before synchrotron injection. A pre-acceleration can be realized by a chain of other accelerator structures like a linac, a microtron in case of electrons, for example, Proton and ion injectors Linac 4 and Linac 3 for the LHC, UNLAC as the injector for the SIS18 in GSI and in future the SIS18 as injector for the SIS100. The linac is a commonly used injector for the ion synchrotron and consists of some key components. The three main parts of a linac are: An ion source creating the particles, a buncher system or an RFQ followed by the main drift tube accelerator DTL. In order to meet the energy and the beam current requirement of a synchrotron injector linac, its cost is a remarkable percentage of the total facility costs.
However, the normal conducting linac operation at cryogenic temperatures can be a promising solution in improving the efficiency and reducing the costs of a linac. Synchrotron injectors operate at very low duty factor with beam pulse lengths in 1 micros to 100 micros range, as most of the time is needed to perform the synchrotron cycle. Superconducting linacs are not convenient, as they cannot efficiently operate at low duty factor and high beam currents.
The cryogenic operation of ion linacs is discussed and investigated at IAP in Frankfurt since around 2012 [1, 37]. The motivation was to develop very compact synchrotron injectors at reduced overall linac costs per MV of acceleration voltage. As the needed beam currents for new facilities are increasing as well, the new technology will also allow an efficient realization of higher injector linac energies, which is needed in that case. Operating normal conducting structures at cryogenic temperature exploits the significantly higher conductivity of copper at temperatures of liquid nitrogen and below. On the other hand, the anomalous skin effect reduces the gain in shunt impedance quite a bit[25, 31, 9]. Some intense studies and experiments were performed recently, which are encouraging with respect to increased field levels at linac operation temperatures between 30 K and 70 K [17, 24, 4, 23, 5, 8]. While these studies are motivated by applications in electron acceleration at GHz-frequencies, the aim of this paper is to find applications in the 100 to 700 MHz range, typical for proton and ion acceleration. At these frequencies, a higher impact in saving RF power is expected due to the larger skin depth, which is proportional to the frequency to the power of negative half with respect to the normal skin effect. On the other hand, it is assumed that the improvement in maximum surface field levels will be similar to what was demonstrated already for electron accelerator cavities. This should allow to find a good compromise between reduced RF power needs for achieving a given accelerator voltage and a reduced total linac length to save building costs.
A very important point is the temperature stability of the cavity surface during the RF pulse. This is of increasing importance the lower the operating temperature is chosen: the temperature dependence of the electric conductivity in copper gets rather strong below 80 K, as long as the RRR - value of the copper is adequate. It is very clear, that this technology is suited for low duty cycle operated cavities only - with RF pulse lengths below one millisecond. At longer pulses the cavity surface will be heated within the pulse to temperatures, where the conductivity advantage is reduced substantially. These conditions fit very well to synchrotron injectors or to pulsed beam power applications.
H – Mode structures of the IH – and of the CH – type are well-known to have rather small cavity diameters at a given operating frequency. Moreover, they can achieve effective acceleration voltage gains above 10 MV/m even at low beam energies, and already at room temperature operation[29]. With the new techniques of 3d – printing of stainless steel and copper components one can reduce cavity sizes even further – making the realization of complex cooling channels much easier.
Another topic are copper components in superconducting cavities – like power couplers. It is of great importance to know exactly the thermal losses at these surfaces, which can’t be cooled efficiently in an easy way.
Aktivierende Mutationen der Fms-like tyrosine kinase (FLT3) treten bei 25 % der Patienten mit akuter myeloischer Leukämie (AML) auf und begünstigen die unkontrollierte Proliferation maligner Blasten. Autophagie ist ein intrazellulärer Prozess, durch den zytoplasmatische Bestandteile lysosomal abgebaut werden und fungiert als intrazellulärer Homöostase-Mechanismus unter Stress-Bedingungen.
Ziel dieser Arbeit war es, herauszufinden, ob FLT3-ITD+-AML-Zellen vulnerabel gegenüber Autophagie-Hemmung sind.
Hierzu wurde zunächst untersucht, wie sich FLT3-ITD-Signaling und Autophagie unter basalen Wachstumsbedingungen gegenseitig beeinflussen. In einem genetischen Modell zeigte sich, dass FLT3-ITD-transformierte wachstumsfaktorunabhängige Zellen während ihrer fortgesetzten Proliferation vermehrt Autophagie betreiben. Lysosomale Autophagie-Inhibitoren zeigten jedoch unter diesen Bedingungen keine erhöhte Wirksamkeit gegenüber FLT3-ITD-positiven Zellen. Humane FLT3-ITD-positive AML-Zellen zeigten nach genetischer Deletion von ULK1 ebenfalls nur transiente und milde Proliferationsdefizite. Unter basalen Wachstumsbedingungen zeigte sich also keine erhöhte Vulnerabilität FLT3-ITD-exprimierender Zellen gegenüber Autophagie-Inhibition.
Daraufhin wurde die Bedeutung von Autophagie während pharmakologischer Hemmung von FLT3 untersucht. FLT3-Inhibition mittels AC220, einem FLT3-spezifischer Tyrosinkinase-Inhibitor, induzierte bzw. steigerte die autophagische Aktivität ähnlich stark wie eine direkte mTOR-Inhibition. Dies ließ sich im Zellmodell therapeutisch ausnutzen: eine Kombinationsbehandlung mit AC220 und einem lysosomalen Autophagie-Inhibitor zeigte eine synergistische antiproliferative Wirkung. Dies stellt möglicherweise einen neuen rationalen Kombinationsbehandlungsansatz für die Therapie FLT3-ITD-positiver AML-Patienten dar.
Hintergrund: Anämie gehört zu den häufigsten Erkrankungen weltweit und stellt daher ein zentrales globales Gesundheitsproblem dar. Etwa ein Drittel aller chirurgischen Patienten weisen präoperativ eine Anämie auf. Dies wird als unabhängiger Risikofaktor für eine erhöhte Morbidität und Mortalität sowie für das vermehrte Auftreten postoperativer Komplikationen angesehen. Vor diesem Hintergrund wurde von der Weltgesundheitsorganisation (World Health Organization, WHO) ein patientenzentriertes Behandlungskonzept namens Patient Blood Management (PBM) gefordert, um unter anderem Anämien frühzeitig zu diagnostizieren und einen rationalen Einsatz von Fremdblutprodukten zu fördern. Trotz der Tatsache, dass PBM vor etwa 10 Jahren eingeführt wurde, scheint Deutschland im internationalen Vergleich eine überdurchschnittlich hohe Menge an Erythrozytenkonzentrat-(EK)Einheiten pro Kopf zu transfundieren. Die Ursachen dafür sind bislang unklar und könnten möglicherweise durch eine erhöhte Anämie- Prävalenz bei chirurgischen Patienten und dem damit verbundenen erhöhten Bedarf an Transfusionen einhergehen.
Zielsetzung: Ziel dieser Arbeit ist die multizentrische Erfassung der präoperativen Anämie-Prävalenz innerhalb des Zeitraums 2007-2019 in Deutschland.
Methoden: In dieser retrospektiven, multizentrischen Beobachtungsstudie wurden alle Patienten jeden Alters, die im Monat März der Jahre 2007, 2012, 2015, 2017 und 2019 in acht teilnehmenden Krankenhäusern operiert wurden, erfasst. Patientencharakteristika und klinische Daten wurden aus den Krankenhausinformationssystemen der teilnehmenden Krankenhäuser entnommen. Primäres Ziel war die Prävalenz der Anämie bei Krankenhausaufnahme. Sekundäre Endpunkte waren der Zusammenhang zwischen Anämie und Anzahl der transfundierten EKs, Dauer des Krankenhausaufenthalts und Sterblichkeit im Krankenhaus.
Ergebnisse: Von insgesamt 30.763 Patienten konnten 23.836 Patienten aus acht Krankenhäusern in die Analyse eingeschlossen werden. Im untersuchten Zeitraum zeigte sich eine Reduktion der präoperativen Anämie-Prävalenz erwachsener Patienten von 37% auf 32,2%. Die Zahl, der mit Erythrozytenkonzentraten -5- transfundierten Patienten, ging signifikant von 16,5 % im Jahr 2007 auf 7,8 % im Jahr 2019 zurück, wobei Patienten mit präoperativer Anämie im Vergleich zu Patienten ohne Anämie sechsmal mehr EKs erhielten. Insgesamt verkürzte sich die Krankenhausverweildauer seit 2007 deutlich, zeigte jedoch eine signifikante Verlängerung bei Vorliegen einer präoperativen Anämie. Die Sterblichkeitsrate war über die Jahre hinweg konstant, dennoch signifikant höher bei anämischen Patienten. Eine multivariate Regressionsanalyse mit festen Effekten ergab, dass präoperative Anämie und EK-Transfusion Prädiktoren für die Sterblichkeitsrate waren.
Diskussion: Die Prävalenz der präoperativen Anämie lag in unserer Studienpopulation im Jahr 2019 bei 32,2 %, was der weltweiten Prävalenz entspricht. Das Implementieren von PBM-Strategien, um präoperative Anämien frühzeitig zu identifizieren und zu therapieren sowie Blutprodukte rational einzusetzen, nimmt daher weiterhin einen großen Stellenwert ein. Diese perioperativen Maßnahmen sind für alle chirurgischen Patienten von zentraler Bedeutung, da eine präoperative Anämie den Bedarf an EK-Transfusionen erhöhen, die Liegezeit verlängern und mit einer erhöhten Sterblichkeitsrate assoziiert sein kann.
Cyber Physical Systems (CPS) are growing more and more complex due to the availability of cheap hardware, sensors, actuators and communication links. A network of cooperating CPSs (CPN) additionally increases the complexity. This poses challenges as well as it offers chances: the increasing complexity makes it harder to design, operate, optimize and maintain such CPNs. However, on the other side an appropriate use of the increasing resources in computational nodes, sensors, actuators can significantly improve the system performance, reliability and flexibility. Therefore, self-X features like self-organization, self-adaptation and self-healing are key principles for such systems.
Additionally, CPNs are often deployed in dynamic, unpredictable environments and safety-critical domains, such as transportation, energy, and healthcare. In such domains, usually applications of different criticality level exist. In an automotive environment for example, the brake has a higher criticality level regarding safety as the infotainment. As a result of mixed-criticality, applications requiring hard real-time guarantees compete with those requiring soft real-time guarantees and best-effort application for the given resources within the overall system. This leads to the need to accommodate multiple levels of criticality while ensuring safety and reliability, which increases the already high complexity even more.
This thesis deals with the question on how to conveniently, effectively and efficiently handle the management and complexity of mixed-critical CPNs (MC-CPNs). Since this cannot be done by the system developer without the assistance of the system itself any longer, it is essential to develop new approaches and techniques to ensure that such systems can operate under a range of conditions while meeting stringent requirements.
Based on five research hypothesis, this thesis introduces a comprehensive adaptive mixed-criticality supporting middleware for Cyber-Physical Networks (Chameleon), which efficiently and autonomously takes care of the management and complexity of CPNs with regard to the mixed-criticality aspect.
Chameleon contributes to the state-of-art by introducing and combining the following concepts:
- A comprehensive self-adaption mechanism on all levels of the system model is provided.
- This mechanism allows a flexible combination of parametric and structural adaptation actions (relocation, scheduling, tuning, ...) to modify the behavior of the system.
- Real-time constraints of mixed-critical applications (hard real-time, soft real-time, best-effort) are considered in all possible adaptation conditions and actions by the use of the importance parameter.
- CPNs are supported by the introduction of different scopes (local, system, global) for the adaptation conditions and actions. This also enables the combination of different scopes for conditions and actions.
- The realization of the adaptation with a MAPE-K loop instantiated by a distributed LCS allows for real-time capable reasoning of adaptation actions which also works on resource-spare systems.
- The developed rule language Rango offers an intuitive way to specify an initial rule set for LCS in the context of CPS/CPNs and supports the system administrators in the process of rule set generation.