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In the 1960s, when most African nations gained their independence after the age of colonialism, several theories and strategies emerged with the goal of "developing" these apparently "underdeveloped" territories. One of the most influential approaches for this task was represented in Julius K. Nyerere´s idea of Ujamaa, the Tanzanian version of African socialism.
Even before the Arusha Declaration established Ujamaa as a national development strategy in 1967, several groups of politicized young farmers took to the empty countryside of Tanzania to implement their own version of cooperative development. From one of these attempts emerged the Ruvuma Development Association (RDA), which organized up to 18 villages in southwestern Tanzania. The RDA became the inspiration for Nyerere´s concretization of Ujamaa and its implementation on national level. Yet, the central state could not replicate the success of the peasants, which was based on voluntariness and intrinsic motivation.
In 2015, this exploratory study has revisited the Region of Ruvuma. Through a case study approach, relying mostly on qualitative methods, new insights into the local history of Ujamaa and its perception have been gathered. In particular, narrative interviews with contemporary witnesses and group interviews with the present-day farmers’ groups have been conducted. Furthermore, NGOs active within the region, as well as regional and local government institutions were among the key stakeholders identified to concretize the local narrative of Ujamaa development. All interviews were analyzed according to the principles of qualitative content analysis. Additionally, individual villager questionnaires were used to achieve a more holistic picture of the local perception of development, challenges and the Ujamaa era.
None of the original Ujamaa groups of the times of the RDA was still operational at the time of research and no case of village-wide organization of collective agriculture could be observed. Nevertheless, in all of the three case study villages, several farmers’ groups (vikundi) were active in organizing development activities for their members. Furthermore, the perception of the Ujamaa era was generally positive throughout all of the case study sites. Yet, there have been significant differences in this perception, based on the village, age, gender and field size of the recipients. Overall, the period of Ujamaa was seen as an inspiration for present-day group activities, and the idea of such activities as a remedy for the developmental challenges of these villages was common among all stakeholders.
This thesis concludes that the positive perception of group activities as a vehicle for village development and the perception of Ujamaa history as a positive asset for the inception and organization of farmers’ groups would be highly beneficial to further attempts to support such development activities. However, the limitations in market access and capital availability for these highly-motivated group members have to be addressed by public and private development institutions. Otherwise, "the smell of Ujamaa" will be of little use for the progress of these villages.
In this work, multi-particle quantum optimal control problems are studied in the framework of time-dependent density functional theory (TDDFT).
Quantum control problems are of great importance in both fundamental research and application of atomic and molecular systems. Typical applications are laser induced chemical reactions, nuclear magnetic resonance experiments, and quantum computing.
Theoretically, the problem of how to describe a non-relativistic system of multiple particles is solved by the Schrödinger equation (SE). However, due to the exponential increase in numerical complexity with the number of particles, it is impossible to directly solve the Schrödinger equation for large systems of interest. An efficient and successful approach to overcome this difficulty is the framework of TDDFT and the use of the time-dependent Kohn-Sham (TDKS) equations therein.
This is done by replacing the multi-particle SE with a set of nonlinear single-particle Schrödinger equations that are coupled through an additional potential.
Despite the fact that TDDFT is widely used for physical and quantum chemical calculation and software packages for its use are readily available, its mathematical foundation is still under active development and even fundamental issues remain unproven today.
The main purpose of this thesis is to provide a consistent and rigorous setting for the TDKS equations and of the related optimal control problems.
In the first part of the thesis, the framework of density functional theory (DFT) and TDDFT are introduced. This includes a detailed presentation of the different functional sets forming DFT. Furthermore, the known equivalence of the TDKS system to the original SE problem is further discussed.
To implement the TDDFT framework for multi-particle computations, the TDKS equations provide one of the most successful approaches nowadays. However, only few mathematical results concerning these equations are available and these results do not cover all issues that arise in the formulation of optimal control problems governed by the TDKS model.
It is the purpose of the second part of this thesis to address these issues such as higher regularity of TDKS solutions and the case of weaker requirements on external (control) potentials that are instrumental for the formulation of well-posed TDKS control problems. For this purpose, in this work, existence and uniqueness of TDKS solutions are investigated in the Galerkin framework and using energy estimates for the nonlinear TDKS equations.
In the third part of this thesis, optimal control problems governed by the TDKS model are formulated and investigated. For this purpose, relevant cost functionals that model the purpose of the control are discussed.
Henceforth, TDKS control problems result from the requirement of optimising the given cost functionals subject to the differential constraint given by the TDKS equations. The analysis of these problems is novel and represents one of the main contributions of the present thesis.
In particular, existence of minimizers is proved and their characterization by TDKS optimality systems is discussed in detail.
To this end, Fréchet differentiability of the TDKS model and of the cost functionals is addressed considering \(H^1\) cost of the control.
This part is concluded by deriving the reduced gradient in the \(L^2\) and \(H^1\) inner product.
While the \(L^2\) optimization is widespread in the literature, the choice of the \(H^1\) gradient is motivated in this work by theoretical consideration and by resulting numerical advantages.
The last part of the thesis is devoted to the numerical approximation of the TDKS optimality systems and to their solution by gradient-based optimization techniques.
For the former purpose, Strang time-splitting pseudo-spectral schemes are discussed including a review of some recent theoretical estimates for these schemes and a numerical validation of these estimates.
For the latter purpose, nonlinear (projected) conjugate gradient methods are implemented and are used to validate the theoretical analysis of this thesis with results of numerical experiments with different cost functional settings.
The progress which has been made in semiconductor chip production in recent years enables a multitude of cores on a single die. However, due to further decreasing structure sizes, fault tolerance and energy consumption will represent key challenges. Furthermore, an efficient communication infrastructure is indispensable due to the high parallelism at those systems. The predominant communication system at such highly parallel systems is a Network on Chip (NoC). The focus of this thesis is on NoCs which are based on deflection routing. In this context, contributions are made to two domains, fault tolerance and dimensioning of the optimal link width. Both aspects are essential for the application of reliable, energy efficient, and deflection routing based NoCs.
It is expected that future semiconductor systems have to cope with high fault probabilities. The inherently given high connectivity of most NoC topologies can be exploited to tolerate the breakdown of links and other components. In this thesis, a fault-tolerant router architecture has been developed, which stands out for the deployed interconnection architecture and the method to overcome complex fault situations. The presented simulation results show, all data packets arrive at their destination, even at high fault probabilities. In contrast to routing table based architectures, the hardware costs of the herein presented architecture are lower and, in particular, independent of the number of components in the network.
Besides fault tolerance, hardware costs and energy efficiency are of great importance. The utilized link width has a decisive influence on these aspects. In particular, at deflection routing based NoCs, over- and under-sizing of the link width leads to unnecessary high hardware costs and bad performance, respectively. In the second part of this thesis, the optimal link width at deflection routing based NoCs is investigated. Additionally, a method to reduce the link width is introduced. Simulation and synthesis results show, the herein presented method allows a significant reduction of hardware costs at comparable performance.
Host–microbe interactions are the key to understand why and how microbes inhabit specific environments. With the scientific fields of microbial genomics and metagenomics, evolving on an unprecedented scale, one is able to gain insights in these interactions on a molecular and ecological level. The goal of this PhD thesis was to make (meta–)genomic data accessible, integrate it in a comparative manner and to gain comprehensive taxonomic and functional insights into bacterial strains and communities derived from two different environments: the phyllosphere of Arabidopsis thaliana and the mesohyl interior of marine sponges.
This thesis focused first on the de novo assembly of bacterial genomes. A 5–step protocol was developed, each step including a quality control. The examination of different assembly software in a comparative way identified SPAdes as most suitable. The protocol enables the user to chose the best tailored assembly. Contamination issues were solved by an initial filtering of the data and methods normally used for the binning of metagenomic datasets. This step is missed in many published assembly pipelines. The described protocol offers assemblies of high quality ready for downstream analysis.
Subsequently, assemblies generated with the developed protocol were annotated and explored
in terms of their function. In a first study, the genome of a phyllosphere bacterium, Williamsia sp. ARP1, was analyzed, offering many adaptions to the leaf habitat: it can deal with temperature shifts, react to oxygen species, produces mycosporins as protection against UV–light, and is able to uptake photosynthates. Further, its taxonomic position within the Actinomycetales was infered from 16S rRNA and comparative genomics showing the close relation between the genera Williamsia and Gordonia.
In a second study, six sponge–derived actinomycete genomes were investigated for secondary metabolism. By use of state–of–the–art software, these strains exhibited numerous gene clusters, mostly linked to polykethide synthases, non–ribosomal peptide synthesis, terpenes, fatty acids and saccharides. Subsequent predictions on these clusters offered a great variety of possible produced compounds with antibiotic, antifungal or anti–cancer activity. These analysis highlight the potential for the synthesis of natural products and the use of genomic data as screening toolkit.
In a last study, three sponge–derived and one seawater metagenomes were functionally compared. Different signatures regarding the microbial composition and GC–distribution were observed between the two environments. With a focus on bacerial defense systems, the data indicates a pronounced repertoire of sponge associated bacteria for bacterial defense systems, in particular, Clustered Regularly Interspaced Short Palindromic Repeats, restriction modification system, DNA phosphorothioation and phage growth limitation. In addition, characterizing genes for secondary metabolite cluster differed between sponge and seawater microbiomes. Moreover, a variety of Type I polyketide synthases were only found within the sponge microbiomes. With that, metagenomics are shown to be a useful tool for the screening of secondary metabolite genes. Furthermore, enriched defense systems are highlighted as feature of sponge-associated microbes and marks them as a selective trait.
The current dissertation addresses the analysis of technology-enhanced learning processes by using Process Mining techniques. For this purpose, students’ coded think-aloud data served as the measurement of the learning process, in order to assess the potential of this analysis method for evaluating the impact of instructional support.
The increasing use of digital media in higher education and further educational sectors enables new potentials. However, it also poses new challenges to students, especially regarding the self-regulation of their learning process. To help students with optimally making progress towards their learning goals, instructional support is provided during learning. Besides the use of questionnaires and tests for the assessment of learning, researchers make use increasingly of process data to evaluate the effects of provided support. The analysis of observed behavioral traces while learning (e.g., log files, eye movements, verbal reports) allows detailed insights into the student’s activities as well as the impact of interventions on the learning process. However, new analytical challenges emerge, especially when going beyond the analysis of pure frequencies of observed events. For example, the question how to deal with temporal dynamics and sequences of learning activities arises. Against this background, the current dissertation concentrates on the application of Process Mining techniques for the detailed analysis of learning processes. In particular, the focus is on the additional value of this approach in comparison to a frequency-based analysis, and therefore on the potential of Process Mining for the evaluation of instructional support.
An extensive laboratory study with 70 university students, which was conducted to investigate the impact of a support measure, served as the basis for pursuing the research agenda of this dissertation. Metacognitive prompts supported students in the experimental group (n = 35) during a 40-minute hypermedia learning session; whereas the control group (n = 35) received no support. Approximately three weeks later, all students participated in another learning session; however, this time all students learned without any help. The participants were instructed to verbalize their learning activities concurrently while learning. In the three analyses of this dissertation, the coded think aloud data were examined in detail by using frequency-based methods as well as Process Mining techniques.
The first analysis addressed the comparison of the learning activities between the experimental and control groups during the first learning session. This study concentrated on the research questions whether metacognitive prompting increases the number of metacognitive learning activities, whether a higher number of these learning activities corresponds with learning outcome (mediation), and which differences regarding the sequential structure of learning activities can be revealed. The second analysis investigated the impact of the individual prompts as well as the conditions of their effectiveness on the micro level. In addition to Process Mining, we used a data mining approach to compare the findings of both analysis methods. More specifically, we classified the prompts by their effectiveness, and we examined the learning activities preceding and following the presentation of instructional support. Finally, the third analysis considered the long-term effects of metacognitive prompting on the learning process during another learning session without support. It was the key objective of this study to examine which fostered learning activities and process patterns remained stable during the second learning session.
Overall, all three analyses indicated the additional value of Process Mining in comparison to a frequency-based analysis. Especially when conceptualizing the learning process as a dynamic sequence of multiple activities, Process Mining allows identifying regulatory loops and crucial routing points of the process. These findings might contribute to optimizing intervention strategies. However, before drawing conclusions for the design of instructional support based on the revealed process patterns, additional analyses need to investigate the generalizability of results. Moreover, the application of Process Mining remains challenging because guidelines for analytical decisions and parameter settings in technology-enhanced learning context are currently missing. Therefore, future studies need to examine further the potential of Process Mining as well as related analysis methods to provide researchers with concrete recommendations for use. Nevertheless, the application of Process Mining techniques can already contribute to advance the understanding of the impact of instructional support through the use of fine-grained process data.
Anionic Adducts
Sp2-sp3 tetraalkoxy diboron compounds have gained attention due to the development of new, synthetically useful catalytic reactions either with or without transition-metals. Lewis-base adducts of the diboron(4) compounds were suggested as possible intermediates in Cu catalyzed borylation reactions some time ago. However, intermolecular adducts of tetraalkoxy diboron compounds have not been studied yet in great detail. In preliminary studies, we have synthesized a series of anionic sp2-sp3 adducts of B2pin2 with alkoxy-groups (L = [OMe]–, [OtBu]–), a phenoxy-group (L = [4-tBuC6H4O]–) and fluoride (L = [F]–, with [nBu4N]+ as the counter ion) as Lewis-bases.
Neutral Adducts
Since their isolation and characterization, applications of N-heterocyclic carbenes (NHCs) and related molecules, e.g., cyclic alkylaminocarbenes (CAACs) and acyclic diaminocarbenes (aDCs), have grown rapidly. Their use as ligands in homogeneous catalysis and directly in organocatalysis, including recently developed borylation reactions, is now well established. Recently, several examples of ring expansion reactions (RER) involving NHCs were reported to take place at elevated temperatures, involving Be, B, and Si.
Furthermore, preliminary studies in the group of Marder et al. showed the presence of neutral sp2-sp3 diboron compounds with B2pin2 and the NHC Cy2Im. In this work, we focused on the synthesis and characterization of further neutral sp2-sp3 as well as sp3-sp3 diboron adducts with B2cat2 and B2neop2 and different NHCs. Whereas the mono-NHC adduct is stable for several hours at temperatures up to 60 °C, the bis-NHC adducts undergo thermally induced rearrangement to form the ring expanded products compound 26 and 27. B2neop2 is much more reactive than B2cat2 giving ring expanded product 29 at room temperature in quantitative yields, demonstrating that NHC ring expansion and B–B bond cleavage can be very facile processes.
Whereas the mono-NHC adduct is stable for several hours at temperatures up to 60 °C, the bis-NHC adducts undergo thermally induced rearrangement to form the ring expanded products compound 26 and 27. B2neop2 is much more reactive than B2cat2 giving ring expanded product 29 at room temperature in quantitative yields, demonstrating that NHC ring expansion and B–B bond cleavage can be very facile processes.
Neoplasms of the skin represent the most frequent tumors worldwide; fortunately, most of them are benign or semi-malignant and well treatable. However, the two most aggressive and deadly forms of malignant skin-neoplasms are melanoma and Merkel cell carcinoma (MCC), being responsible for more than 90% of skin-cancer related deaths. The last decade has yielded enormous progress in melanoma therapy with the advent of targeted therapies, like BRAF or MEK inhibitors, and immune-stimulating therapies, using checkpoint antibodies targeting CTLA- 4, PD-1 or PD-L1. Very recent studies suggest that also MCC patients benefit from a treatment with checkpoint antibodies. Nevertheless, in an advanced metastatic stage, a cure for both of these aggressive malignancies is still hard to achieve: while only a subset of patients experience durable benefit from the immune-based therapies, the widely applicable targeted therapies struggle with development of resistances that inevitably occur in most patients, and finally lead to their death. The four articles included in this thesis addressed current questions concerning therapy and carcinogenesis of melanoma and MCC. Moreover, they are discussed in the light of the up-to-date research regarding targeted and immune-based therapies. In article I we demonstrated that besides apoptosis, MAPK pathway inhibition in BRAF-mutated melanoma cells also induces senescence, a permanent cell cycle arrest. These cells may provide a source for relapse, as even permanently arrested cancer cells can contribute to a pro-tumorigenic milieu. To identify molecular factors determining the differential response, we established M14 melanoma cell line derived single cell clones that either undergo cell death or arrest when treated with BRAF/MEK inhibitors. Using these single cell clones, we demonstrated in article IV that downregulation of the pro-apoptotic BH3-only protein BIK via epigenetic silencing is involved in apoptosis deficiency, which can be overcome by HDAC inhibitors. These observations provide a possible explanation for the lack of a complete and durable response to MAPK inhibitor treatment in melanoma patients, and suggest the application of HDAC inhibitors as a complimentary therapy to MAPK pathway inhibition. Concerning MCC, we scrutinized the interactions between the Merkel cell polyomavirus’ (MCV) T antigens (TA) and the tumor suppressors p53 and Rb in article II and III, respectively. In article III, we demonstrated that the cell cycle master regulator Rb is the crucial target of MCV large T (LT), while it - in contrast to other polyomavirus LTs - exhibits much lower affinity to the related proteins p107 and p130. Knockdown of MCV LT led to proliferation arrest in MCC cells, which can be rescued by knockdown of Rb, but not by knockdown of p107 and p130. Contrary to Rb, restriction of p53 in MCC seems to be independent of the MCV TAs, as we demonstrated in article II. In conclusion, the presented thesis has revealed new molecular details, regarding the response of melanoma cells towards an important treatment modality and the mechanisms of viral carcinogenesis in MCC.
This thesis contributes to several issues in the context of SDN and NFV, with an emphasis on performance and management.
The main contributions are guide lines for operators migrating to software-based networks, as well as an analytical model for the packet processing in a Linux system using the Kernel NAPI.
The thesis deals with the automated generation and efficient evaluation of scattering amplitudes in general relativistic quantum field theories at one-loop order in perturbation theory. At the
present time we lack signals beyond the Standard Model which, in the past, have guided the
high-energy physics community, and ultimately led to the discovery of new physics phenomena.
In the future, precision tests could acquire this guiding role by systematically probing the Standard Model and constraining Beyond the Standard Model theories. As current experimental
constraints strongly favour Standard Model-like theories, only small deviations with respect to the Standard Model are expected which need to be studied in detail. The required precision
demands one-loop corrections in all future analyses, ideally in a fully automated way, allowing
to test a variety of observables in different models and in an effective field theory approach.
In the process of achieving this goal we have developed an enhanced version of the tool
Recola and on this basis the generalization Recola2. These tools represent fully automated
tree- and one-loop-amplitude providers for the Standard Model, or in the case of Recola2
for general models. Concerning the algorithm, we use a purely numerical and fully recursive
approach allowing for extreme calculations of yet unmatched complexity. Recola has led to the first computation involving 9-point functions. Beyond the Standard Model theories and Effective Field theories are integrated into the Recola2 framework as model files. Renormalized model files are produced with the newly developed tool Rept1l, which can perform the renormalization in a fully automated way, starting from nothing but Feynman rules. In view of validation, we have extended Recola2 to new gauges such as the Background-Field Method and the class of Rxi gauges. In particular, the Background-Field Method formulation for new theories serves as an automated validation, and is very useful in practical calculations and the formulation of renormalization conditions. We have applied the system to produce the first results for Higgs-boson production in Higgs strahlung and vector-boson fusion in the Two-Higgs-Doublet Model and the Higgs-Singlet Extension of the Standard Model. All in all, we have laid the foundation for an automated generation and computation of one-loop amplitudes within a large class of phenomenologically interesting theories. Furthermore, we enable the use of our system via a very flexible and dynamic control which does not require any intermediate intervention.
Multiple sclerosis (MS) is the most prevalent neurological disease of the central nervous system (CNS) in young adults and is characterized by inflammation, demyelination and axonal pathology that result in multiple neurological and cognitive deficits. The focus of MS research remains on modulating the immune response, but common therapeutic strategies are only effective in slowing down disease progression and attenuating the symptoms; they cannot cure the disease. Developing an option to prevent neurodegeneration early on would be a valuable addition to the current standard of care for MS. Based on our results we suggest that application of nimodipine could be an effective way to target both neuroinflammation and neurodegeneration. We performed detailed analyses of neurodegeneration in experimental autoimmune encephalomyelitis (EAE), an animal model of MS, and in in vitro experiments regarding the effect of the clinically well-established L-type calcium channel antagonist nimodipine. Nimodipine treatment attenuated the course of EAE and spinal cord histopathology. Furthermore, it promoted remyelination. The latter could be due to the protective effect on oligodendrocytes and oligodendrocyte precursor cells (OPCs) we observed in response to nimodipine treatment. To our surprise, we detected calcium channel-independent effects on microglia, resulting in apoptosis. These effects were cell type-specific and independent of microglia polarization. Apoptosis was accompanied by decreased levels of nitric oxide (NO) and inducible NO synthase (iNOS) in cell culture as well as decreased iNOS expression and reactive oxygen species (ROS) activity in EAE. Overall, application of nimodipine seems to generate a favorable environment for regenerative processes and could therefore be a novel treatment option for MS, combining immunomodulatory effects while promoting neuroregeneration.