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Research projects funded by the German Research Foundation

2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Adaptive Data Management in Evolving Heterogeneous Hardware/Software Systems
Currently, database systems face two big challenges: First, the application scenarios become more and more diverse ranging from purely relational to graph-shaped or stream-based data analysis. Second, the hardware landscape becomes more and more heterogeneous with standard multi-core Central Processing Units (CPUs) as well as specialized high-performance co-processors such as Graphics Processing Unit (GPUs) or Field Programmable Gate Arrays (FPGAs).
Recent research shows that operators designed for co-processors can outperform their CPU counterparts. However, most of the approaches focus on single-device processing to speedup single analyses not considering overall system performance. Consequently, they miss hidden performance potentials of parallel processing across all devices available in the system. Furthermore, current research results are hard to generalize and, thus, cannot be applied to other domains and devices.
In this project, we aim to provide integration concepts for diverse operators and heterogeneous hardware devices in adaptive database systems. We work on optimization strategies not only exploiting individual device-specific features but also the inherent cross-device parallelism in multi-device systems. Thereby we focus on operators from the relational and graph domain to derive concepts not limited to a certain application domain. To achieve the project goals, interfaces and abstraction concepts for operators and processing devices have to be defined. Furthermore, operator and device characteristics have to be made available to all system layers such that the software layer can account for device specific features and the hardware layer can adapt to the characteristics of the operators and data. The availability of device and operator characteristics is especially important for global query optimization to find a suitable execution strategy. Therefore, we also need to analyze the design space for query processing on heterogeneous hardware, in particular with regards to functional, data and cross-device parallelism. To handle the enormous complexity of the query optimization design space incurred by the parallelism, we follow a distributed optimization approach where optimization tasks are delegated to the lowest possible system layer. Lower layers also have a more precise view on device-specific features allowing to exploit them more efficiently. To avoid interferences of optimization decisions at different layers, a focus is also set on cross-layer optimizations strategies. These will incorporate learning-based techniques for evaluating optimization decisions at runtime to improve future optimization decisions. Moreover, we expect that learning-based strategies are best suited to integrate device-specific features not accounted for by the initial system design, such as it is often the case with the dynamic partial reconfiguration capabilities of FPGAs.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Adaptive Data Management in Evolving Heterogeneous Hardware/Software Systems
Currently, database systems face two big challenges: First, the application scenarios become more and more diverse ranging from purely relational to graph-shaped or stream-based data analysis. Second, the hardware landscape becomes more and more heterogeneous with standard multi-core Central Processing Units (CPUs) as well as specialized high-performance co-processors such as Graphics Processing Unit (GPUs) or Field Programmable Gate Arrays (FPGAs).
Recent research shows that operators designed for co-processors can outperform their CPU counterparts. However, most of the approaches focus on single-device processing to speedup single analyses not considering overall system performance. Consequently, they miss hidden performance potentials of parallel processing across all devices available in the system. Furthermore, current research results are hard to generalize and, thus, cannot be applied to other domains and devices.
In this project, we aim to provide integration concepts for diverse operators and heterogeneous hardware devices in adaptive database systems. We work on optimization strategies not only exploiting individual device-specific features but also the inherent cross-device parallelism in multi-device systems. Thereby we focus on operators from the relational and graph domain to derive concepts not limited to a certain application domain. To achieve the project goals, interfaces and abstraction concepts for operators and processing devices have to be defined. Furthermore, operator and device characteristics have to be made available to all system layers such that the software layer can account for device specific features and the hardware layer can adapt to the characteristics of the operators and data. The availability of device and operator characteristics is especially important for global query optimization to find a suitable execution strategy. Therefore, we also need to analyze the design space for query processing on heterogeneous hardware, in particular with regards to functional, data and cross-device parallelism. To handle the enormous complexity of the query optimization design space incurred by the parallelism, we follow a distributed optimization approach where optimization tasks are delegated to the lowest possible system layer. Lower layers also have a more precise view on device-specific features allowing to exploit them more efficiently. To avoid interferences of optimization decisions at different layers, a focus is also set on cross-layer optimizations strategies. These will incorporate learning-based techniques for evaluating optimization decisions at runtime to improve future optimization decisions. Moreover, we expect that learning-based strategies are best suited to integrate device-specific features not accounted for by the initial system design, such as it is often the case with the dynamic partial reconfiguration capabilities of FPGAs.
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Analysis and modelling the coating of solid particles
In the frame of the research project it is planned to analyse the fundamentals and to derive models for the collision of droplets with larger solid particles and their coating for Euler/Lagrange calculations. The elementary process of collisions between droplets and larger solid particles will be analysed experimentally using imaging techniques. For that purpose a droplet chain will be produced into which solid particles are shot with defined velocity and frequency. As a result of the collision of droplets with larger particles one may observe bouncing, deposition or disintegration. The collision event will be visualised using high-speed cameras and illumination by LED-arrays and a laser. The results will be analysed by image processing.
For all the relevant parameters of influence it is first required to determine the outcome of the collision and summarise them with respect to the important non-dimensional numbers, e.g. Ohnesorge-number and impact Reynolds-number. The considered parameters of influence are the size ratio (droplet/particle), droplet liquid properties (viscosity and surface tension), particle properties (temperature and surface roughness), impact velocity and impact location of the droplet on the particle surface (i.e. central and lateral impacts). As mentioned before, the droplets are smaller than the particles and the liquid is wetting. All these effects need to be considered for deriving physically-based boundaries between the collision outcomes using the relevant non-dimensional numbers. For the regime splashing or partial deposition the size distribution of the droplet fragments also will be analysed and modelled.
The next step is the experimental determination of the dimensions of the final liquid film on the particles, including film thickness and lateral dimension of the film. For that purpose the droplet liquid will be doped with fluorescing dye in order to allow a better distinction from the image of the particle. For the development of the coating model with respect to the impact conditions and the relevant non-dimensional numbers, physically based correlations shall be developed.
In addition, for analyzing the collision outcomes, theoretical studies will be conducted based on an energy balance. The liquid film formation on the particle will be studied based on film theory.
The developed coating model, which considers a broad range of parameters and also for the first time lateral impact, will be derived for being used in the frame of Lagrangian calculations of technical coating processes.
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Atomic layer deposition of dopant source layers for semiconductor doping - Characterization and modelling of drive-in processes
Atomic layer deposition processes for phosphorus-containing layers will be developed and investigated. Recently developed ALD processes for boron oxide and antimony oxide will be further improved and analyzed as well. These layers will be used as a dopant sources for silicon doping to produce ultra-shallow and homogeneous doped pn junctions, especially for applications, where doping on three-dimensional surface configurations is required.
In addition, suitable methods for stabilization of unstable dopant layers need to be found and analyzed. The deposited layers will be characterized and the diffusion processes in the silicon and in the oxide phase will be studied, and thus the doping processes will be modeled.
2016-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Atomic Layer Deposition of Germanium-Antimony-Telluride
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
COOPeR: Cross-device OLTP/OLAP PRocessing
Database Management Systems (DBMS) face two challenges today. On the one hand DBMS must handle Online Transaction Processing (OLTP), and Online Analytical Processing (OLAP) in combination to enable real-time analysis of business processes. The real-time analysis of business processes is necessary to improve the quality of reports and analyzes, since fresh data is favored for modern analysis rather than historical data only. On the other hand, computer systems become increasingly heterogeneous to provide better hardware performance. The architecture changes from single-core CPUs to multi-core CPUs supported by several co-processors. These trends must be considered in DBMS to improve the quality and performance, and to ensure that DBMS satisfy future requirements (e.g., more complex queries, or more increased data volume). Unfortunately, current research approaches address only one of these two challenges: either the combination of OLTP and OLAP workloads in traditional CPU-based systems, or co-processor acceleration for a single workload type is considered. Therefore, an unified approach addressing both challenges at once is missing. In this project we want to include both challenges of DBMS to enable efficient processing of combined OLTP / OLAP workloads in hybrid CPU / Co-processor systems. This is necessary in order to realize real-time business intelligence. The main challenge is guaranteeing the ACID properties for OLTP, while at the same time to combine and to process efficiently OLTP / OLAP workloads in such a hybrid systems.
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Cross-border interactions and trans-national identities
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
German Ultrahigh Field Imaging (GUFI)
The GUFI network was founded at the end of 2013 as DFG-funded Core Facility. The initial project duration was three years. The overall goal of GUFI is to facilitate and harmonize the access to German Ultra High Field (UHF) sites. GUFI has made important contributions to addressing these challenges and has identified several new areas of common interest to all German UHF sites. A number of unprecedented milestones have been achieved in building a national UHF Magnetic Resonance (MR) community including establishment of a common presentation and access portal for all UHF MR sites; initiation of regular QA; consensus on access procedures, implant handling and RF coil testing; and regular structured communication between all UHF sites. In a second funding phase, starting 2017, the following goals will be pursued:
  • Establishment of an online platform for MR safety training including examination questions to verify attainment of training goals.
  • Continuation and extension of establishment of procedures for safe examinations of subjects with implants. Continuation and refinement of QA activities.
  • Formulation and publication of White Papers.
  • Annual workshops with participation from all GUFI sites to foster communication.
  • Planning of first multicenter UHF trials.
  • Maintenance and extension of the online web-based communications platform.
  • Coordination activities with other international initiatives such as UK7T and Euro-Bioimaging.
  • Preparation of access procedures for the infrastructure to be established at National Biomedical Imaging Facilities in Jülich and Heidelberg that have been applied for as part of the National Roadmap for Research Infrastructures of the German Federal Ministry of Education and Research (BMBF).
2014-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
The role of the atypical NF-κB inhibitory protein IκBNS in effector T cells
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
The role of c-Rel and IκBNS in the development of regulatory T cells
Regulatory T-cells are key players for the maintenance of immune homeostasis. Moreover, they establish a threshold for the activation of effector T cells and regulate the duration and strength of an immune response. Loss of regulatory T cells leads to massive systemic autoimmune diseases. One example is the human immunodeficiency polyendocrinopathy X-linked (IPEX) syndrome, which is caused by functional mutations in the gene of the transcription factor Foxp3. Mutations in the murine Foxp3 gene result in the homologous phenotype scurfy. Different laboratories showed that Foxp3 is essential for the generation of CD4-positive regulatory T cells and the maintenance of their suppressive phenotype. In the periphery, autoreactive T cells can be converted into regulatory T cells, which are, thus, called induced regulatory T cells. In contrast, natural regulatory T cells are generated from autoreactive T cells during development in the thymus. They are not eliminated during negative selection by apoptosis but initiate expression of Foxp3 instead. The molecular mechanisms, which protect autoreactive cells from apoptosis and induce Foxp3 are not understood.

Recent studies demonstrated, that the transcription factor NF-kB and proteins regulating its activity are crucial for the development of regulatory T cells. Especially the NF-kB-subunit c‑Rel appears to be important, since c-Rel-deficient mice show a systemic reduction of regulatory T cells by 50%. It is believed that c-Rel leads to a direct induction of the Foxp3 gene during regulatory T cell differentiation in the thymus. The activity of NF-kB is regulated by so called inhibitors of NF-kB (IkB) proteins and IkBNS belongs to the group of unusual IkB proteins, that are inducible and obligatory nuclear. Remarkably, it has the potential to modulate transcription in both, an inducing and repressive manner. Our analyses revealed a 50% reduction of regulatory T cells in IkBNS-deficient mice. Interestingly, precursors of regulatory T-cells accumulate in the thymus, which we lead back to the delayed induction of Foxp3.
The phenotypical similarities of IkBNS- and c-Rel-deficient mice suggest a functional or molecular interaction of both proteins. The aim of this project is a detailed analysis of how IkBNS and c-Rel regulate Foxp3 induction and the development of regulatory T cells in vivo. To this end, we will investigate a potential functional interaction between IkBNS and c-Rel by analyzing mice, which are deficient for both genes. Moreover, we are planning to unravel the molecular mechanisms, by which c-Rel and IkBNS govern regulatory T cell development.
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Role of Neuropeptide S in animal models of pathological fear
Fear optimally prepares the brain and body for dangerous situations, which helps humans and animals cope with potentially dangerous events. Dysfunctions within the mechanisms underlying fear can lead to maladaptive fear. Some clinical manifestations of such maladaptive fear are post-traumatic stress disorder or panic disorder. Several clinical studies identified a polymorphism in the neuropeptide S (NPS) receptor gene that is associated with an increased incidence of panic disorder. Moreover, the identified risk allele of the NPS receptor interacts with unfavorable developmental conditions (here: childhood maltreatment). These findings motivated neuroscientists to investigate the role of NPS and its receptors in animal models of normal fear and anxiety. However, there is surprisingly little research on NPS and its receptor in animal models of pathological fear. Such models would be especially suitable to explore gene environment interactions.

Therefore, the aim of the proposed study is to explore the role of NPS and its receptor in animal models of pathological fear. First, the phenotype of transgenic mice with a deficiency of the NPS receptor will be characterized in animal models of post-traumatic stress disorder and panic disorder. Then, the additional effects of developmental conditions (enriched environment, social stress) on the phenotype of wildtype and NPS receptor-deficient animals will be studied. Lastly, we want to test if NPS injections can block the development of pathological fear.
The aim of the proposed study is to increase our understanding of the role of NPS and its receptor in normal and pathological fear. We hope that our data can contribute to the development of pharmacological therapies with NPS receptor agonists.
2014-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Dispersion and coalescence in stirred micellar three-phase systems
Reactions of hydrophobic educts with a water soluble catalyst can be carried out in micellar systems. For an economically acceptable reaction rate and for a fast product separation the operating conditions must be chosen such that a micellar three phase system occurs. The corresponding bi-disperse drop size distributions (DSD) caused by stirring are decisive for both process steps but not characterised up to now. DSD of bi-disperse systems will therefore be determined extending experimental (WG Kraume) and numerical methods (WG Thévenin).
2015-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Dynamics and interactions of colloidal particles in freely suspended smectic films
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Habenular (dys)function in decisions on approach and avoidance
This project addresses the role of the habenula (Hb) in motivated behaviour of humans. The Hb is an important relay on a major descending pathway from the forebrain to the brain stem with predominantly inhibitory influence on monoaminergic nuclei, thereby controlling release of dopamine and serotonin to the forebrain. The project aims at understanding the contribution of the Hb to active and passive avoidance and to learning from aversive events. This comprises studying habenular activity, its structural and functional embedding in pallido-habenulo-mesencephalo-striatal networks, and its neurochemical interactions. To this end, high-resolution structural, diffusion-weighted and functional MRI, pharmacological challenges, and in-vivo receptor density mapping using positron emission tomography will be performed in healthy volunteers. Understanding habenular functions is important not only for fundamental neurosciences but also for clinical neuropsychiatry, because dysfunction of the Hb has been suggested to contribute to the pathophysiology of psychiatric disorders, such as affective disorders and addiction. Therefore, we will search for volume and connectivity aberrations of the Hb in patients with addiction.
2014-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
A mixed multi-field representation of gradient-type problems in solid mechanics
The modeling of phase fields and size effects in solids, such as the width of shear bands or the grain size dependence of the plastic flow in poly-crystals, need to be based on non-standard continuum approaches which incorporate length-scales.
With the ongoing trend of miniaturization and nanotechnology, the predictive modeling of these effects play an increasingly important role.
The mixed multi-field representation of gradient-type problems is a recently introduced thermomechanically consistent framework for modeling such kind of phenomena. The key idea is to extend the field of constitutive state variables by micromechanical independents and further to derive the macro and micro balance equations in a closed form.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Influence of Y-box binding protein 1 (YB-1) on the signaling of the receptor Notch3 and cell differentiation in inflammatory kidney diseases
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Electron-Phonon Interaction in Semiconductor Nanostructures
The main focus of A6 is a deeper understanding of the interaction between the electronic and the phononic
system that governs the device performance of nitride based nanostructures. Our approach is a unique
combination and correlation of nanoscopic methods like tip-enhanced Raman spectroscopy (TERS), μPhotoluminescence (μPL), and scanning transmission electron microscopy (STEM) with Cathodo-luminescence(CL) capability. This phalanx of complementary, advanced spectroscopic techniques enables us to investigatethe electron-phonon coupling with unmatched spatial resolution, providing not only insight into devicelimitations, but also a fundamental understanding of carrier relaxation and dephasing processes.
With TERS we analyze how the tip-induced electric field and the plasmonic coupling between the metal tip
and the (doped) sample influence the Raman signature depending on the carrier concentration. Such measurementsare not only of importance for studying localized phonons in, e.g. nanowires (NWs) and singlequantum dots (QDs), but also for understanding the nature of the enhancement process itself. Hence, TERSis most valuable for the interpretation of μPL and CL results, directly reflecting the coupling between theelectronic and phononic states. Based on our combination of ultraviolet (UV) enhanced μPL and CL, bothproviding the capability for ps time-resolved and correlation spectroscopy, we identify, e.g. single-photonemitters in nitride QDs paving the way towards efficient single- and two-photon emitters. The exceptionallystrong coupling between e.g. excitons and phonons in nitride nanostructures even fosters the generation ofsingle, confined phonons, exploring new device concepts at the interface of photonics and phononics based on single phonon emission and storage. Our recent discovery of hybrid-quasiparticles with unconventionaltotal spin numbers is fundamentally related to phonon-induced spin flip process of carriers benefitting fromsizeable coupling constants in especially nitride-based quantum dots.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Emotional aspects of event learning in rats: Characterization and neural basis
Event learning consists of different learning phenomena with very different emotional and behavior consequences: fear learning, relief learning and safety learning. In the proposed project, we want to characterize these three learning phenomena in laboratory rodents, investigate their neural basis and dissociate them from each other. Since fear learning is already well investigated, we want to focus on relief and safety learning. Beside the neural, pharmacological, molecular and genetic basis of event learning, we are also interested in the question how trait anxiety affects event learning and related cognitive flexibility.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Development of a dynamic loudness model including perceptual weights
Loudness is the perceived intensity of a sound and is an important aspect of hearing. It plays a crucial role when assessing environmental noise. Several standards describe certain aspects of loudness perception. These build on loudness models which are based on hearing experiments with comparatively simple sounds. However, for some environmental sounds, large difference between perception and prediction are observed, especially for sound with strong temporal fluctuations. A reason for this discrepancy may be that not all aspects of loudness perception are included in these approaches. Hearing experiments showed that listeners assign different weights to different portions of the sound. For example, the initial portion of a sound is more important for loudness than later points in time. At present it is unclear if the position of the sound source in space (e.g., in front of the listener or from above) has an impact on loudness. The first aim of the project is to gain a better understanding of how weights are assigned by humans when evaluating the loudness of a sound. The second aim is to develop a new loudness model on the basis of existing data as well as on the data that will be collected in the project. In contrast to present loudness models, this new model will include a specific weighting of different components of the sound when calculating its loudness.
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Advanced Quality Metries in Information Visualization and Scientific Visualization
Quality metrics are a promising concept for the automatic analysis of visualizations from high-dimensional data.  ln order to completely visualize a high-dimensional  data set, a large number of visualizations are required.  Just a subset of them shows relevant structures  of the data and thus just a subset of  themis required to be seen by the user.  The idea of quality metrics is to automatically detect this subset of "good" visualizations.  For this, they mimic the visual perception system.  A couple of quality metrics are known aiming mostly at the analysis of bi-variate discrete visualizations of high-dimensional data.  This project extends the traditional approach of quality metrics in three ways. The concept of quality metrics will be extended to nonlinear embeddings  in multivariate projections, it will be extended to non-discrete visualizations (aka continuous visualizations), and it will be extended in order to measure the reliability of quality metrics.  As the conceptional extensions are mutually related, we propose their treatment within one project.
2016-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Extension of fictious domain methods of higher order ansatz functions to unstructured meshes (Leader of the project: Dr.-Ing. Sascha Duczek)
Dr.-Ing. Sascha Duczek has organized this research project, which is financially supported by the German Research Foundation. This project is aimed to extend the Spectral-Cell-Method (SCM) to  unstructured meshes. The investigation is focused on different types of unstructured meshes and the development of appropriate higher order nodal based ansatz functions. Tetrahedral elements offer a special place under the numerous elements for creating unstructured meshes, because any geometry can be simply meshed with help of available powerful software tools. Therefore, an important first step of the project is the development of the Tetrahedron SCM. But, the general approach to higher order elements and unstructured meshes is developed in such a way that new special elements, such as prismatic elements, pyramidal elements or any polygonal elements can be included step by step into the new simulation software.
2013-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Euler equations with phase transition
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Experimental development of strategies that effectively combine T cell immunotherapy with the inhibition of tumor-promoting signal transduction pathways for the treatment of melanoma
The development of strategies that effectively combine T cell directed immunotherapy with the inhibition of tumor-promoting signal transduction pathways for the treatment of melanoma represents one of the most important current clinical challenges. The principle goal of this proposal is to experimentally evaluate such strategies using state-of-the-art preclinical genetically engineered mouse models. In our work we will investigate the general hypothesis that IFN-driven cytotoxic CD8+ T cell immunity is limited locally in the melanoma microenvironment by both physiologic protective responses and by the immunosuppressive activity of melanoma cells. These counter-regulatory mechanisms include the recruitment of myeloid immune cells into injured tumor tissue, the stimulation of PD1/PDL1 immune-inhibitory receptor interactions, and the generation of an immunosuppressive milieu by the activity of oncogenic signalling pathways in tumor cells. The experimental work is directed at interfering with these mechanisms and is divided in three parts with the following aims: (i) to characterize the role of type I IFNs for the regulation of anti-tumoral CD8+ T cell responses; (ii) to establish in vivo bioluminescence imaging techniques to non-invasively evaluate the efficacy of therapeutic strategies that modulate both the infiltration of melanoma tissue with adoptively transferred cytotoxic CD8+ T cells and the subsequent recruitment of myeloid immune cells; and (iii) to expand our model system and explore treatment protocols that combine adoptive CD8+ T-cell therapies with BRAF(V600E) signal transduction inhibitors. The proposed experiments will yield fundamental insights into the possibilities to combine T cell immunotherapies with the inhibitors of tumor-promoting signal transduction pathways. This will provide valuable information for ongoing and future clinical translational studies in patients with metastatic melanoma.
2016-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
EXtracting Product Lines from vAriaNTs (EXPLANT)
Software product lines enable the strategic reuse of software and handle variability in a systematic way. In practice, however, reuse and variability are often implemented ad hoc, by copying and adapting artifacts (the clone-and-own approach). Due to a lack of automation, propagating changes (e.g. error corrections, performance improvements) to several cloned product variants and exchanging functionality between variants is time-consuming and error prone.


To solve these problems, we propose the stepwise migration of cloned product variants to a compositional software product line (SPL). First, all of the variants are integrated unaltered into an initial SPL. Subsequently, this SPL is transformed into a well-structured, modular target SPL by means of small, semantics-preserving steps. Compared to existing approaches to migrate product variants to an SPL, this course of action provides the following advantages:

1) The SPL can be used in production immediately. Up until now, production had to be halted for extended periods of time because migration could not be interrupted.

2) The composition-based implementation approach supports maintainability. This avoids the problems associated with annotation-based SPL implementation techniques (e. g. lack of modularization, hard to read program code), which are widely used in practice.

3) Semantics-preservation of the original variants is guaranteed.

The core of our project is the research of variant-preserving refactoring. By this, we mean consistent transformations on the model as well as the implementation level, which are semantics-preserving with respect to all possible products of the SPL. These refactorings are combined with code clone detection in order to increase reuse and thereby decrease maintenance costs and future defect rates. Moreover, we will research feature location techniques in multiple product variants. Combined with variant-preserving refactoring, these techniques allow for the stepwise extraction of functionality from multiple product variants. Not only can we reconstruct the original variants by composing the extracted features, but we can even create new variants. Thereby, new requirements are addressed even more effectively.
2014-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Functional role of immunoproteasomes in hematopoietic and neural cells
Proteasome complexes are important for the maintenance of cellular protein homeostasis. Upon different stimuli (e.g. interferon or lipopolysaccharide) specific proteasome isoforms are generated, so called immunoproteasomes (IPs) containing the immunosubunits (ISs) b1i (LMP2), b2i (MECL-1) and b5i (LMP7). We and others have shown that IPs display major cellular functions beyond mere MHC class I antigen presentation. IPs are constitutively expressed in lymphoid and myeloid cells indicating an important role of IPs in the regulation and termination of immune response. In addition, immunosubunit containing proteasomes are expressed in various tissues, including the brain.  However, the neural cell type(s) and function(s) of these proteasome subtypes are unknown to date. In this project we intend to clarify the role of IPs in immune and neural cells, i.e. neurons, astrocytes and microglia, using murine model systems for cerebral ischemia and infection. In detail, IP function will be characterized with regard to the outcome of cerebral infection/ischemia using IP subunit-deficient mice. In addition, we will determine the consequences of IP-deficiency for T cell activation and signaling and will identify the molecular composition, cellular distribution and cellular substrates of immunosubunit-containing proteasomes in neural cells. Finally, we will analyze the IP-dependent function of invading immune cells into the brain upon infection and after ischemia with regard to their cellular and intercellular signaling capacity, thereby clarifying the role of these infiltrating cells in pathophysiological events in the brain.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
GABAergic interneurons as mediators of cognitive flexibility
GABAergic interneurons are critical for the acquisition, consolidation, retrieval and extinction of aversive memories. Here  we want to address the role of the identified GABA interneuron populations in interactions of hippocampus and frontal cortex controlling cognitive flexibility. We propose that ventral hippocampal basket cells by determining the stability of previously acquired memories can restrict the degree of flexibility initiated in prefrontal and orbitofrontal areas. Dorsal hippocampal HIPP cells, in contrast, via the anterior cingulate may help adopting novel task solutions by disambiguating similar conditions and configurations. We will employ the established tools of immunohistochemical mapping, mRNA expression profiling with laser microdissection and quantitative PCR, and pharmacogenetic manipulation in cell-specific driver mice to examine the activation and function of GABA neurons with respect to cue/context balance and pattern separation during aversive learning, recruitment of spatial and non spatial learning strategies, reversal learning in spatial and go/nogo tasks. We will use both ex vivo slice preparations and in vivo recordings of hippocampus and frontal cortex to examine the neurophysiological correlates of such interneuron function. Thereby we expect to obtain a comprehensive picture of interneuron-mediated circuit activity and the involved molecular factors relevant for behavioral and cognitive flexibility.
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Agar-based gel-electrolytes for corrosion diagnostic
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Generation of Optimal and Efficient Designs of Experiments for Individualized Prediction in Hierarchical Models
The aim of the present project is to develop an analytical approach for the determination of optimal designs for the problem of prediction in hierarchical random coefficient regression models as well as in generalized linear and nonlinear mixed models. Such models were initially introduced in bio- and agricultural sciences and are nowadays utilized in an increasing number of fields in statistical applications.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Geometry of optimal designs for nonlinear models in statistics
Geometric descriptions of optimal design regions are of growing interest in times of an increasing complexity of statistical models. The aim of the project is in searching for optimality regions of experimental designs for such statistical models, especially for generalized linear models with Poisson or logistic response. These regions are described by systems of polynomial inequalities in the parameter space, which means that they are nothing else than semialgebraic sets. Hence algebraic geometry can be used to study the properties of these optimality regions. For example, in the Bradley-Terry paired comparison model, which is a statistical model for comparisons of alternatives depending on a logistic response, we are interested in the optimality regions of so called saturated designs, i.e. designs with a minimal number of support points.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
We are searching for optimality regions of experimental designs for statistical models, especially for generalized linear models with Poisson or logistic response. These regions are described by systems of polynomial inequalities in the parameter space, which means that they are nothing else than semialgebraic sets. Hence we can use algebraic geometry to study the properties of these optimality regions. For example, in the Bradley-Terry paired comparison model, which is a statistical model for comparisons of alternatives depending on logistic parameters, we are interested in the optimality regions of so called saturated designs.
2014-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Micro-Macro-Interactions in structured Media and Particle Systems
Many materials or media in nature and technology possess a microstructure, which determines their macro behaviour. Despite of possible difficulties to describe the morphology of this structure, the knowledge of the relevant mechanisms is often more comprehensive on the micro than on the macro scale. On the other hand, not all information on the micro level is relevant for the understanding of the macro behaviour. Therefore, averaging and homogenization methods are needed to select only the specific information from the micro scale, which influences the macro scale. These methods would also open the possibility to design or to influence microstructures with the objective to optimize their macro behaviour. Study and development of new methods in this interdisciplinary field of actual research will be under the supervision of professors from different engineering branches, applied mathematics, theoretical, and computational physics.
2016-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Highly Accelerated Distortion-Free Diffusion-Weighted MR Imaging at Ultra High Field (7T): Gray Matter Characterization (DFG)
Single-shot echo-planar imaging (EPI) is a well-established technique with moderate spatial resolution but high imaging efficiency. It is widely adapted in various brain imaging applications such as functional MRI (fMRI), perfusion weighted MRI, and diffusion tensor imaging (DTI). EPI, however, is very sensitive to inhomogeneities induced by the main magnetic field as well as magnetic susceptibility differences in the object. These effects cause phase disturbances due to the low effective bandwidth in the phase encoding direction, leading to distortions of the image geometry and signal intensity. Moreover, in EPI-based diffusion weighted imaging (DWI), these distortions additionally vary according to the diffusion encoding direction due to eddy currents induced by the rapid and large changes of the magnetic field associated with the ramp-up and ramp-down of these encoding gradients. Since field inhomogeneities are directly proportional to the strength of the main magnetic field, these distortions are increased at high field strengths of 3 Tesla and above, and become a significant obstacle for EPI-based applications at ultra high field (UHF) such as 7T. In this project, we propose the development, implementation and testing of an improved approach to measure, characterise, and compensate strong EPI distortions. The development and evaluation will be performed at 7T in phantoms and human subjects. The project covers an implementation of the improved method for fMRI applications and its further extension for reliable DTI applications. Significantly improved stability and imaging properties of EPI allowing more sensitive experimental results and higher positional accuracy are predicted for the proposed method. This will be achieved without prolonged scan times since all data directly enter the DTI results.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Integrated Research Training Group ¿Semiconductor Nanophotonics: Material, Models, Devices¿
The goal of the Integrated Research Training Group (RTG) School of Nanophotonics of the Collaborative

Research Center SFB 787 (CRC 787) is to attract young researchers and to promote their scientific development.The excellent research environment within the CRC 787 is combined with an in-depth scientific educationand a structured program to advance their professional skills. The RTG encourages the scientific independenceand visibility of its members, provides advanced training and transferable skills, and offers a stimulatingenvironment for scientific exchange, discussions, and education.
The key elements of the RTG are the Doktorandenseminar (participation is mandatory), specialized lectures,
and an annual 3-days CRC workshop for the scientific education. Moreover, transferable-skills workshops, the
annual Nanophotonics day a compact introduction to topics such as patents, career options, etc. , and
travel to international conferences as well as summer schools, in particular the iNOW, is essential for education
in a broader sense. The travel funds provided by the RTG to the PhD students are particularly important for
encouraging the scientific independence and international visibility of the PhD students.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Internal models of stimulus-response and action-outcome associations in ADHD
During normal development, children learn to refrain from prepotent response tendencies and to choose or withhold actions on the basis of likely action-outcome contingencies instead. Important prerequisites for this ability are intact sensory motor regulation, feedback processing and to model consequences of our own actions. In project A03, we will examine these fundamental aspects of human action in children and adolescents with attention deficit hyperactivity disorder (ADHD) using established behavioural paradigms in combination with electroencephalography and functional magnetic resonance imaging
2014-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Cascade transformations of unsaturated alcohols catalyzed by bifunctional ruthenium complexes
The development of new catalytic methods for the atom economic synthesis of complex structures from simple unsaturated alcohols is the main objective of the project. The research focuses on a rational catalyst design with targeted use of cooperative effects and sequentially catalyzed cascade reactions. Transition metal complexes of redox-active cyclopentadienone ligands with their particularly versatile catalytic properties are in the focus of the investigations. They catalyze diverse chemo- and regioselective transformations of bifunctional substrates and offer many possibilities for manipulations. The development of metal catalysed cascade processes is based on ruthenium catalyzed allylation-cycloisomerization-reactions of tertiary 1-vinyl propargylalcohols. The developed methods should be applied within the synthesis of polycyclic compounds and alkaloids. Asymmetric catalyzed reactions using axially chiral representatives of the complex series and sequentially catalyzed domino processes are especially addressed with regard to future applications in the field of natural product and drug synthesis. Organometallic studies to elucidate the reaction mechanisms will be carried out besides the product-oriented catalysis research. The focus here is on the isolation and characterization of organometallic key intermediates of the catalytic cycles as well as on labeling experiments. Ultimately, the processes should allow maximum diversity, flexibility, selectivity, atom and step economy and should be undoubtedly understood regarding mechanistic aspects to make a lasting contribution to the further development of the preparative organic chemistry.
2014-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Local control of melanocyte-specific CD4+ T cell effector functions in melanoma
The skin immune system plays an important role in the development of malignant tumors. It can both inhibit and promote skin tumor growth. CD4+ T cells play an important role in the regulation of melanoma immunity and can exert potent antitumor immunity on their own. To study the role of CD4+ T cells we established a  TCR-transgenic mouse strain specific for the melanocytic antigen TRP1. Adoptively transferred TRP1-specific CD4+ T cells can cause autoimmune destruction of melanocytes and regression of skin melanomas in the context of prior lymphocyte depletion and adjuvant innate immune stimulation. However melanomas relapse early. The principal goal of our project in the next funding period is to understand how melanocyte-specific CD4+ T cell functions are regulated in primary cutaneous melanomas using this experimental system. The planned work is based on the central hypothesis that the ability of CD4+ T cells to cause autoimmune destruction of melanocytes and regression of primary cutaneous melanomas can be enforced by promoting effector functions of the Th17-Th9-Th1 spectrum of phenotypes. We anticipate that TRP1-specific CD4+ T cells normally shift towards exhausted, memory and regulatory phenotypes in the tumor microenvironment which then support tumor progression and angiogenesis. In this project we will first examine the phenotypic plasticity of CD4+ T cells by restimulating them with immunogenic or tolerogenic dendritic cells in vitro and in vivo (Aim 1). We will then establish strategies involving immunostimulatory nucleic acids and RNA aptamers to locally activate innate anti-viral immune pathways and re-direct dendritic cell functions which maintain anti-tumor effector functions of CD4+ T cells (Aim 2). We will use genetic tracing techniques to follow the fate of adoptively transferred CD4+ T cells in vivo, visualize their migration towards and adhesion to dendritic cells and melanoma cells, and evaluate their heterogeneity under different conditions  (Aim 3). These experiments will provide important insights how effector functions of CD4+ T cells could be harnessed for the treatment of melanoma.
2017-2021
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Mathematical Complexity Reduction
In the context of the proposed RTG we understand complexity as an intrinsic property that makes
it difficult to determine an appropriate mathematical representation of a real world problem, to assess the fundamental structures and properties of mathematical objects, and to algorithmically solve a given mathematical problem. By complexity reduction we refer to all approaches that help to overcome these difficulties in a systematic way and to achieve the aforementioned goals more efficiently.

For many mathematical tasks, approximation and dimension reduction are the most important tools to obtain
a simpler representation and computational speedups. We see complexity reduction in a more general way and
will also, e.g., investigate liftings to higher-dimensional spaces and consider the costs of data observation.
Our research goals are the development of cross-disciplinary mathematical theory and methods for complexity
reduction and the identification of relevant problem classes and effective exploitation of their structures.

We aim at a comprehensive teaching and research program based on geometric, algebraic, stochastic, and
analytic approaches, complemented by efficient numerical and computational implementations. In order to
ensure the success of our doctoral students, they will participate in a tailored structured study program. It will
contain training units in form of compact courses and weekly seminars, and encourage early integration into the
scientific community and networking. We expect that the RTG will also serve as a catalyst for a dissemination
of these successful practices within the Faculty of Mathematics and improve the gender situation.

Complexity reduction is a fundamental aspect of the scientific backgrounds of the principal investigators.
The combination of expertise from different areas of mathematics gives the RTG a unique profile, with high
chances for scientific breakthroughs. The RTG will be linked to two faculties, a Max Planck Institute, and
several national and international research activities in different scientific communities.

The students of the RTG will be trained to become proficient in a breadth of mathematical methods, and
thus be ready to cope with challenging tasks in particular in cross-disciplinary research teams. We expect an
impact both in terms of research successes, and in the education of the next generation of leading scientists in
academia and industry.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Maximum-entropy method applied to the many-particle hierarchyproblem in quantum-dot-microcavity systems
The study of light-matter interaction in semiconductor quantum dots
embedded into optical microcavities is a topical research field in
condensed matter physics with many potential applications, such as
ultra-low threshold micro- and nanolasers, single-photon sources, and
sources of entangled photon pairs. The theoretical description of such
driven-dissipative quantum many-particle systems in terms of the
reduced density operator is, however, only feasible for small or highly
symmetric systems. Approaches based on equations of motion of
relevant expectation values are numerically much more efficient, but
require to truncate the many-particle hierarchy at a suitable level and
therefore only provide a subset of moments instead of the full
statistics. In this project, we propose to apply the maximum entropy
method, which was originally introduced in equilibrium statistical
mechanics, to the many-particle hierarchy problem of non-equilibrium
systems in two different ways. The first method still uses the results of
conventional equations-of-motion approaches and allows to
approximately determine the full statistics und substatistics such as
the photon statistics of a microcavity laser. The second method goes
much further by replacing the equations-of-motion approaches for
stationary non-equilibrium problems by a novel scheme which has
three important advantages: (i) it does not require any factorization
scheme to truncate the many-particle hierarchy, (ii) avoids the
numerical integration of equations of motion, and (iii) gives access to
the full statistics. The purpose of the project is to study in detail both
methods with focus on semiconductor quantum-dot microcavity
systems. Once completed, we expect not only to have developed an
highly efficient scheme to solve driven-dissipative quantum many-
particle problems, but also to have gained a deeper understanding of
the many-particle hierarchy and its truncation.
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Mechanisms of pregnancy success: Dendritic cells as mediators between human Chorionic Gonadotropin and regulatory T cells
Infertility or miscarriage can no longer be considered a personal problem but rather a public health problem. The inability to conceive a child not only results in personal conflicts but has also been associated with psychiatric disorders. Beside intensive costs for infertility treatments there are further costs involved managing mental health complications. For this reason a detailed understanding of mechanisms resulting in successful pregnancies is essential. Ultimately this will advance therapeutic interventions for patients suffering infertility or miscarriages and reduce the number of women developing mental disorders due to reproductive failure. During pregnancy the maternal immune system is challenged by the presence of foreign paternal antigens expressed by the semi-allogeneic fetus. Fetal survival within the hostile maternal uterus can only be achieved by a fine regulation of maternal immune responses towards fetal alloantigens. Here, pregnancy hormones like the human Chorionic Gonadotropin (hCG) are proposed to be important immune modulators. In previous studies we showed that hCG supports fetal tolerance by enhancing the number and activity of pregnancy-protective regulatory T cells (Treg). However, it has not been clarified whether hCG influences Treg directly or via indirect pathways. Tolerogenic dendritic cells (DCs) were described as potent inducers of Treg and there is evidence that hCG may retain a tolerogenic profile of DCs. However, in vitro data describing an influence of hCG on DCs is inconsistent and in vivo data is limited. Within this research project funded by the DFG we will test the hypothesis that hCG influences Treg via regulation of DCs during human pregnancy.
2013-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Mechanisms of nonverbal communication: Emotion recognition based on facial expressions and analysis of head and body postures
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Mechanisms of synaptic plasticity during cortex-dependent learning
Project B09 deals mainly with cortex-dependent auditory discrimination learning in rodents that is also part of the integrative paradigm. Based on our previous findings we will address the following questions: (i) What is the role of phospholipase Cβ signalling in the formation/consolidation of late memories? (ii) What is the role of bassoon-mediated presynaptic plasticity in learning and memory? (iii) What brain region- and cell type-specific changes in synaptic proteomes occur during memory formation? In particular, what are the molecular mechanistic differences between aversively and appetitively reinforced learning and memory processes?
2013-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Matellasilsesquioxanes
Functionalized disiloxanes and silsesquioxanes as building blocks for novel Si-O-based complex molecules and polymer materials

As part of this research project mono-functionalized or monoanionic disiloxanes and silsesquioxanes will be used to construct Si-O-based complex molecules and polymer materials. In the first part of the project a new class of f-element complexes containing anionic lithium disiloxanediolate ligands shall be established, which can be regarded as "inorganic lanthanide metallocenes". Main objective of this investigation is the synthesis of highly reactive metal alkyls and hydrides based on siloxanediolate ligands. In the second part of the projects the mono-functionalized silsesquioxane derivatives (c-C6H11)7Si8O12(OH) and (c-C6H11)7Si8O12(OLi) will play a central role. They will be used to construct novel two- and three-dimensional complex molecules such as e.g. silsesquioxane-substituted inorganic rings, cages, and dendrimers as well as polymer materials.
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Methods for the complementary design of the machine and the control in electric drive systems
The targets for designing a drive system include high torque density, high efficiency, low manufacturing/maintenance costs, high reliability and high performance motion control. The research and development of the drives are mainly split in the electric machines on one side and in the control and power electronic systems in the other.

In the usual approaches, the control system is designed assuming a given standard electrical machine or machine type. The machine on his part is designed assuming a standard control algorithm, like the field oriented control. The design of the machine and the design of the controller is generally performed by unrelated teams.


In the case of permanent magnet synchronous machines (PMSM), the machine is usually designed for obtaining a sinusoidal back electromotive force (EMF), as it is assumed that the control supplies sinusoidal current. The control on his side is designed for supplying sinusoidal current assuming the back EMF is sinusoidal. In this way, a ripple free torque is obtained. However, these assumptions constrain the design of the machine and does not make use of all the potential of the power electronic and control system.
It is expected that by designing the machine and the control in a complementary way, better characteristics can be obtained than when designed separately. This approach is rarely investigated and will be covered by the present proposal. There is a special potential to reach a simpler, however, still efficient drive system.
Machines designed with purposeful nonsinusoidal EMF will be investigated in relation with a three phase four wire inverter i.e. with connected neutral, and with a new non-sinusoidal reference frame transformations for the control. With the aim of obtaining a simpler drive system without position sensor, the self sensing control will also be investigated. As the performance of self sensing techniques depend specially on characteristics of the machine, method for improving the self sensing capability of the machine and the suitable self sensing methods will be researched.
2014-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Micro-Macro-Interactions in structured Media and Particle Systems
Many materials or media in nature and technology possess a microstructure, which determines their macro behaviour. Despite of possible difficulties to describe the morphology of this structure, the knowledge of the relevant mechanisms is often more comprehensive on the micro than on the macro scale. On the other hand, not all information on the micro level is relevant for the understanding of the macro behaviour. Therefore, averaging and homogenization methods are needed to select only the specific information from the micro scale, which influences the macro scale. These methods would also open the possibility to design or to influence microstructures with the objective to optimize their macro behaviour. Study and development of new methods in this interdisciplinary field of actual research will be under the supervision of professors from different engineering branches, applied mathematics, theoretical, and computational physics.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Modelling the influence of bubble dynamics on motion, mass transfer and chemical reaction
In the frame of the proposed project it is planned to account for the bubble dynamics (i.e. shape oscillations and tumbling motion) in the description of bubble motion, mass transfer and chemical reaction for numerical calculations of reacting bubbly flows by the Euler/Lagrange approach. As a result of bubble dynamics they will perform a tumbling motion and their interface as well as the flow in the vicinity of the bubbles will be continuously modified. This will also yield an increase in bubble residence time. As a consequence, mass transfer and reaction rates will be remarkably improved. So far the influence of bubble dynamics was not accounted for in the numerical calculation of bubbly flows by both the Euler/Euler- and Euler/Lagrange-approach. Hence, such models shall be developed in the proposed project, whereby the numerical calculation of reactive bubbly flows will be remarkably improved.
The numerical calculation of the fluid flow will be based on large eddy simulations (LES) using a dynamic sub-grid-scale (SGS) turbulence model. The influence of the bubbles on the fluid will be accounted for in the momentum equations and in SGS turbulence modelling (i.e. turbulence dissipation and bubble induced turbulence, BIT). The calculation of bubble motion will consider all relevant forces (i.e. base-line model of Liao et al. 2015) and bubble transport by SGS turbulence. In addition, the influence of the Basset force will be examined and a new bubble-wall interaction model will be developed. The bubble dynamics will be accounted for in all three levels of model development, bubble motion, mass transfer and chemical reaction. The dynamic bubble motion will be described through a stochastic variation of bubble eccentricity and orientation using a theoretically based bubble oscillation time scale. Regarding mass transfer and chemical reaction, bubble dynamics will be incorporated in the correlations of Sherwood number and enhancement factor. These correlations will be derived theoretically, supported by the direct numerical simulations of the working group Prof. Bothe (TU Darmstadt). In addition, the Lagrangian simulations will allow supporting the development of a bubble dynamics models in the frame of an Euler/Euler approach proposed by the group of Dr. Rzehak (HZD Rossendorf).
The models for bubble dynamics in bubble motion, mass transfer and chemical reactions (among others for the system Fe-NO) will be stepwise developed and implemented in OpenFOAM. In each working task a detailed validation will be performed based on the experimental studies conducted in various groups of the SPP 1740 (e.g. Prof. Schlüter, TU Hamburg-Harburg; Prof. Kraume TU Berlin; Prof. Hampel, TU Dresden).
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Modeling and analysis of interphase damage in carbon nanotube reinforced materials and structures
The principal objective of the proposed research is to expand the modeling capabilities of CNTRM¿s considered in the current project (and other composites with interphases) into an inelastic range. More specifically, the goal is to develop a method of evaluating the overall nonlinear behavior of CNTRM´s associated with damage of its interphases. This choice is made in recognition of the fact that damage, particularly damage of the interphases is an important aspect of nonlinear behavior of composites. As opposed to this approach, however, where discrete analysis of progressive debonding along the interphase was considered for representative unit cell (RUC) of a composite with regular arrangement of inhomogeneities, in this work a continuum approach to damage will be adopted. This appears to be a natural approach for composites with random microstructure, where RUC cannot be identified, and it is novel in the existing literature on the subject.


Another specific objective of the approach proposed here is to devise an approach suitable for materials with random arrangement of CNTs and their finite aspect ratio. Unlike random arrangement of spherical inhomogeneities, where the zones of debonding for a typical inhomogeneity can be associated with the principal directions of loading, such association cannot be realistically assumed in the case of CNTRM. In CNTRM the local elastic fields may very much more significantly and it is meaningful to describe the problem in terms of statistical averages. These averages represent the entire collection of CNTs in the material, each of them may have somewhat different pattern of damage. Collectively they should be equivalent to inhomogeneities whose interphases undergo homogeneous (smeared) damage. This assumption forms the basis for the approach proposed here, and, in fact, it parallels the thinking pursued in phenomenological 3D continuum description of damage. The difference is that the averages of elastic fields used in the formulation of the problem are based on the designed, or measured, statistical distribution of inhomogeneities (CNT) and are anticipated to lead to a material-tailored description
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Modeling and Simulation of photovoltaic systems
2014-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Molecular Organization of Celluar Communication within the Immune System
2016-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Neuronal mechanisms of errors and lapses of attention induced by sleep deprivation
To err is human. While cognitive neuroscience has made substantial progress in understanding the brain¿s ability to detect errors and to adapt behavior accordingly, the neurobiological reasons and conditions for making mistakes are still poorly understood. Sleep deprivation leads to lower task performance and increased error rates. The proposed project aims at investigating the brain mechanisms that underlie the commission of errors in goal-directed behavior in rested wakefulness and after sleep deprivation. Using combined EEG and fMRI, we will investigate whether different types of errors can be distinguished and predicted based on specific spatiotemporal patterns of brain activity evolving before the error occurs. An interference task has been designed such that perceptual processing of task-relevant and distracting stimuli can be decoded separately by means of machine learning techniques thereby providing a tool to  investigate the effects of arousal and selective attention. Thus, general disengagement from task can be distinguished from distraction and maladaptive misallocation of selective attention. The planned study will help predicting errors based on brain activity patterns and understanding the neurobiological mechanisms underlying the performance deficits after sleep deprivation. It will furthermore be the starting point of a long-term collaboration of two laboratories providing complementary expertise with respect to performance monitoring, attention, cognitive changes induced by sleep deprivation and multimodal cognitive neuroscience methods.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Neuronal representation of motivational value and context in explicit and implicit learning
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Nitride-based resonant cavity single photon sources
Nitride based single photon sources (SPS) for room temperature operation will be fabricated and characterized in this project. A novel approach based on position controlled single GaN/AlN quantum dots (QD) grown by MOVPE inside resonant cavity structures is pursued. Currently, GaN QDs are fabricated either by strained-layer epitaxy, by nanowire growth or by selective area growth Nitride based single photon sources (SPS) for room temperature operation will be fabricated and characterized in this project. A novel approach based on position controlled single GaN/AlN quantum dots (QD) grown by MOVPE inside resonant cavity structures is pursued. Currently, GaN QDs are fabricated either by strained-layer epitaxy, by nanowire growth or by selective area growth [1-3]. In established device fabrication technologies planar surfaces, as usually maintained during strained-layer epitaxy of GaN QDs, are preferable to the 3D surface structures resulting from other approaches. However, nucleation sites of GaN QDs in the self-assembling, planar approach occur at non-predictable random positions and are largely affected by the presence of dislocation networks. We want to overcome this limitation using a nitride-based buried stressor technology that introduces a considerable in-plane stress component at predefined positions at the growth surface of QDs ¿ adopting the successful approach of A2 from the arsenide system to the nitrides. We will therefore develop a well controlled selective lateral oxidation process following an approach by 4] to create a nitride-based buried stressor structure on AlN templates. The impact of such stressors on QD nucleation within a dislocation-rich environment will be studied, particularly making use of the nano-scale resolution of our unique (S)TEM-CL characterization facilities. A technology for single-photon emitter devices will be developed including monolithically-integrated optical elements such as mirrors and resonant microcavity structures as well as micro lenses for enhanced light extraction.
Electronic quantum dot states based on GaN/AlN provide optical transitions (intraband transitions) in telecom-munication regions at 1.3 and 1.55 μm wavelength ¿ an alternative approach to realize SPS for fiber-based secure data communication. For the first time, we will explore fundamental properties of such transitions for generating single photons.
2016-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Normative value generation for flow parameters in a group of healthy volunteers and 1-year follow-up examinations of selected semilunar valve pathologies using 4D PC-MRI
Four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) has great potential to improve diagnosis as well as progressmonitoring of cardiovascular diseases and support treatment
decisions. There is a lack of standardized and reliable evaluationmethods that facilitate usage in the clinical routine. Such methodsshall be developed in the proposed project. Above all, there are no
normative values of the parameters that are quantifiable in 4D PCMRIdata. In the proposed project, such normative values forquantitative measures such as peak velocities and stroke volumes
shall be obtained for a group of healthy volunteers. Additionally,patients with either an inherited bicuspid aortic valve or a surgicallycorrected tetralogy of Fallot with pulmonary insufficiency are
examined. 1 year follow-up examinations are planned that facilitateprognoses about the medium- and long-term disease progressions.
2014-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
On-the-fly postprocessing and feature extraction of flame and flow properties obtained by Direct Numerical Simulations
Direct Numerical Simulations (DNS) are presently recognized as the best possible solution to investigate numerically turbulent flows. However, DNS at high Reynolds numbers require billions of grid points and are pursued during thousands of time iterations. When considering even more complex flows involving chemical reactions, many variables have to be analyzed and correlated in space and time in order to test and develop reduced models. This leads to Terabytes or even Petabytes of raw data, which cannot be stored any more on existing disk space, nor transferred within an acceptable time using any existing computer network. It is therefore necessary to develop new approaches. A simultaneous analysis and postprocessing of the generated flow data during the corresponding DNS simulations (on-the-fly analysis) appears to be particularly promising in this regard, since significantly less data has to be stored and handled this way. This analysis is realized by on-the-fly feature extraction: features of the flow and scalar fields are extracted in parallel to data generation by DNS, such that the data files do not need to be stored any more. However, this is associated with considerable challenges concerning data analysis, feature extraction, parallelization and relevant numerical techniques.
2014-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Optimal Reactor Design and Operation for Liquid Multiphase Systems
This project concerns mainly the set-up and start-up of a segmented mini-plant scale multi-phase reactor realizing spatial distributed temperature control and reactant dosing, as technical approximation of the optimal reaction concept for the hydroformylation of 1-dodecene in TMS. Via experimental characterization of the chemical and fluid dynamic behavior of the reactor a detailed reactor model will be developed and will be used for model-based reactor optimization.
2016-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Optimal Design for online generated adaptive methode for intelligence testing (III)
In this project adaptive procedure are developed for intelligence tests, which aim at measuring the general intelligence. Test items will be generated automatically and online by a rule-based item generator and adaptively presented. The items will be selected according to the parameter estimates in generalized linear logistic test models. The parameter estimations will be based on optimal designs in order to obtain maximal precision in measuring the intelligence by a minimal number of items to be presented. In detail four types of rule-based test procedures will be constructed for measuring the general intelligence and the necessary basic principles of statistics wikll be developed.

In Phase I rule based items were developed for measuring the working speed and empirically calibrated based on D-optimal dsigns in linear logistic test models with fixed and random factors. Furthermore a programming system was developed for the automatic generation of these items, their adaptive presentation and the estimation of person parameters.
 
In Phase II of this project the work of Phase I has been continued. In analogy to the items on working capacity developed in Phase I rule based items on working speed were constructed, which are suitable for an adaptive testing of this intelligence component. As speed tests were considered, it was necessary to use some extended versions of the Rasch Poisson Count Model as the statistical basis instead of the Logistic Rasch Model of Phase I. For these models again optimal designs were developed for both item calibration and adaptive testing.
 
 
In Phase III of this project time trends will be considered for the modelling of intelligence components in longitudinal studies. Also for this situation optimal designs will be constructed which can be used adaptively both within one session as well as over time. Additionally, optimal designs will be provided for the generation of item pools under constraints on the number of rules used.
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Advancing reliability and specificity of automatic multimodal recognition of pressure and heat pain
Currently used methods for clinical pain assessment have limited reliability, validity, are time consuming and can only limited applied to patients with restricted communicative verbal abilities. If valid measurement of the pain is not possible, treating the pain may lead to cardiac stress in risk patients, underperfusion of the operating field, over- or under-usage of analgesics and other problems of mistreatment in acute or chronic pain.

Main goal of the project is the advancement of pain diagnosis and monitoring of pain states. With the use of multimodal sensor technology and highly effective data classification, reliable and valid automated pain recognition will be possible. To reach this goal the combination of experimental protocols and new powerful methods of data analysis, pattern recognition and machine learning will be a promising strategy for the development of objective pain measurement.  Biomedical, visual and audio data will be measured under experimentally controlled conditions in healthy controls. After measurement, the data will be pre-analyzed with a variety of complex filter and decomposition techniques to extract and select meaningful features. These features are the input for a robust automatic recognition of pain intensities in real-time.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Optical investigation of freely suspended smectic films under microgravity conditions on the ISS
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Religion and Conflict in South-Eastern Europe
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
OSCAR: Opinion Stream Classification with Ensembles and Active leaRners
With the rise of WEB 2.0, many people use social media to post opinions on almost any subject - events, products, topics. Opinion mining is used to draw conclusions on the attitude of people towards each subject; such insights are essential for product design and advertisement, for event planning, political campaigns etc. As opinions accumulate, though, changes occur and invalidate the models from which these conclusions are drawn. Changes concern the general sentiment towards a subject and towards specific facets of this subject, as well as the words used to express sentiment. Subjects also change over time. In OSCAR, the KMD lab of the University Magdeburg, in cooperation with the University Hannover, will develop opinion stream mining methods that deal with change and adapt the learned models continuously.

The first part of OSCAR is on leveraging stream mining methods to deal with vocabulary changes. In text mining, the vocabulary words constitute the feature space. A change in the feature space means that the model built upon the old words must be updated. It is impractical to do such an update whenever a new word appears or a word gets out of use. In OSCAR, we will rather accumulate information on the usage and sentiment of each word to highlight the long-term interplay between word polarity and document polarity. On this basis, we will design methods that assess the importance of a word for model adaptation, update the vocabulary by using only words that remain important for some time, and adapt models gradually.

Second, we will work on reducing the need for labeled documents. In stream classification, it is assumed that an expert is available at any time to label the arriving data instances. This assumption is waived in active learning, where only few instances are chosen for labeling - those expected to improve the model the most. Active learning methods assume a fixed feature space. In OSCAR, we will develop active stream learning methods that learn and adapt polarity models on an evolving feature space.

Third, we will work on dealing with different types of change simultaneously. To this purpose, we will use ensembles. We will dedicate some ensemble members to the identification of topic trends, others to changes in the vocabulary and others to temporal changes, including periodical ones. We will investigate ways of coordinating the ensemble members to ensure a smooth adaption of the final ensemble model at any time.

The output of OSCAR will be a complete framework, encompassing active ensemble learning methods that deal with different forms of change and learn with limited expert involvement. The framework will also encompass coordinating components that weigh the contribution of individual models to the final one, and regulate the exchange of information between ensemble members and active learners.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Resolving and manipulating neuronal networks in the mammalian brain - from correlative to causal analysis. TP: Causative mechanisms of mesoscopic activity patterns in auditory category discrimination
2016-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
www.uni-ulm.de/sfb-trr-62
Fusion of situation data from speech, gesture, mimics, and psychobiological data   will give
advanced classification results.  Multimodal information fusion architectures are generated.
2016-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
SFB / Transregio 62: Recognition of emotion from speech
Emotions will be recognized from  speech. Features are subsymbolic and biologically inspired. Emotion classes are being identified.  Fusion with other information sources will give
advanced classification results. Intention recognition is a further goal. Emotional Speech will be provoked. Emotion-annotated data bases will be generated.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Research Training Group
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
CRC 779, Project A07 "Functional control of dopamine release in humans: changes in aging and the modifying role of the locus coeruleus (LC)"
The goal of project A07 is to delineate the functional network level regulation of dopamine release in response to novelty and action for reward and to investigate the relationship between dopamine release and memory consolidation in young and old adults. To achieve these goals, we will continue our successfully established multimodal approach of combining imaging at 3T, 7T and PET. We will achieve a direct integration of fMRI and dopamine release by using a new, truly simultaneous MR-PET facility in Magdeburg. We will also determine whether a norardrenergic brain region, the locus coeruleus, may be a bottleneck for dopamine-release in the hippocampus.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
CRC 779, Project A12 "Habenular (dys)function in decisions on approach and avoidance" (Prof. Speck/Prof. Ullsperger)
Project A12 addresses the role of the habenula (Hb) in motivated behaviour of humans. The Hb is an important relay on a major descending pathway from the forebrain to the brain stem with predominantly inhibitory influence on monoaminergic nuclei, thereby controlling release of dopamine and serotonin to the forebrain. The project aims at understanding the contribution of the Hb to active and passive avoidance and to learning from aversive events. This comprises studying habenular activity, its structural and functional embedding in pallido-habenulo-mesencephalo-striatal networks, and its neurochemical interactions. To this end, high-resolution structural, diffusion-weighted and functional MRI, pharmacological challenges, and in-vivo receptor density mapping using positron emission tomography will be performed in healthy volunteers. Understanding habenular functions is important not only for fundamental neurosciences but also for clinical neuropsychiatry, because dysfunction of the Hb has been suggested to contribute to the pathophysiology of psychiatric disorders, such as affective disorders and addiction. Therefore, we will search for volume and connectivity aberrations of the Hb in patients with addiction.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Anticipation, Processing, and Control of primary rewards
This project investigates the perception and neural representation of primary rewards, i.e. tastes, of their visual correspondences (secondary rewards) and of their (mis)matched combination in the human brain. Aims of this project are: (1) to identify the motivational, hedonic and category-specific representations (sweet, sour etc.) of primary rewards, (2) to identify the influence of secondary reinforcers on these representations and (3) to identify the effects of overlearned and novel visuo-gustatory correspondences on these and their functional interplay by means of univariate fMRI-approaches, plus functional connectivity, classification analysis and functional hyperalignment.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
SFB787 - TP8 GaN based resonant cavity structures
Nitride based UV single photon sources for room temperature operation will be fabricated and characterized in this project. Our approach is based on position controlled single GaN/AlN quantum dots grown by MOVPE inside resonant cavity structures using a nitride-based buried stressor. The optical and electronic properties of the individual single quantum dots are analyzed and directly correlated to their atomic real structure by in-TEM cathodoluminescence. Single-photon emitter devices will be developed including monolithically-integra­ted optical elements (mirrors, resonant microcavity structures, micro lenses) for enhanced light extraction. GaN quantum dot intraband transitions will be explored for IR single photon generation at 1.3 and 1.55 µm.
2014-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Influence of cold shock Y-box (YB) protein-1 on the proinflammatory mesangial cell phenotype and inflammatory cell activation
The orchestration of inflammatory reactions by the cold shock Y-box protein-1 (YB-1) and its role in the development of specific organ damage are investigated. In the kidney, a secreted form of YB-1 interacts with membrane-anchored receptors that initiate autoregulatory loops which enhance the expression of YB-1 in mesangial cells, alter gene transcription, and link intra- with extracellular activities. Our results demonstrate proteolysis and posttranslational modifications of intracellular YB-1 that are linked to inflammation. Acetylated YB-1 is secreted and YB-1-mediated receptor signaling enhances immune cell proliferation and chemotaxis. We hypothesize that YB-1 is centrally involved in the orchestration of immune responses and will elucidate the pathways leading to the processing of YB-1, characterize the subcellular distribution of YB-1 fragments, as well as the effects they mediate. The involvement of extracellular YB-1 in cell-cell communication will be determined with respect to receptor:ligand interaction(s) and downstream signaling pathways. Questions relating to misdirected and pathophysiological roles of extracellular YB-1, including autoantibody formation as well as YB-1-oligomerization in the context of (auto-) immune diseases will be addressed. In conditional YB-1fl/fl knockout and transgenic YB-1K299A/K302A knockin mice, with a suspected secretion deficiency, YB-1-dependent effects will be assessed in vivo in disease models.
2014-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Role of DNA-dependent protein kinase (DNA-PK) for inflammation and proliferation in the atherosclerotic plaque
Atherosclerosis constitutes an inflammatory and proliferative vascular disease promoted by local milieu factors, in particular growth factors and cytokines, but also genotoxic stress. During the last funding period we have identified DNA-dependent protein kinase (DNA-PK) as an enzyme crucial for smooth muscle cell proliferation in vitro and neointima formation in vivo. As well, the NF-κB Essential Modifier (IKKγ/NEMO) subunit of the NF-κB-system was found phosphorylated by DNA-PK and the serine/threonine kinase glycogen synthase kinase-3b (GSK-3b). We determined that NEMO phosphorylation is critically important for its stability and appearance within multi-vesicular bodies.  In turn, the integrity of these vesicles was found required for NF-κB activation.


The aim of the next funding period is to clarify the differential role of DNA-PK and GSK-3b in the spatial (cytosolic vs. nuclear) and temporal NEMO regulation. We will further investigate whether multi-vesicular bodies function as a signalosome for NF-κB activation or signal termination. In this context, we will study intracellular transport, nuclear translocation, protein interactions, protein-degradation and posttranslational modification of NEMO but also other subunits of NF-κB. The in vivo relevance of NEMO phosphorylation will be tested by generation of a constitutive or, if not viable, inducible knock-in mouse. These mice will be characterized and then studied under the pathophysiological condition of vascular proliferative disease induction.
2017-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
SidyW - Simulation of dynamical resistances during the operation of construction and conveying machines
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Steadification of Unsteady Vector Fields for Flow Visualization
For visualizing unsteady flow data, the tracing and representation of particle trajectories or path lines is a

standard approach. Treating path lines is still less researched than considering stream lines, leading to
the fact that stream line based techniques are much better developed than path line techniques.
This project provides a generic approach to convert path lines of an unsteady vector field v to stream
lines of another (steady or unsteady) vector field w. With this, existing stream line techniques can be used to to visually analyze the path line behavior in v. Based on this, we will develop an approach to texture based Flow Visualization that allows to study the path line behavior in a single image. Also, we intend to contribute to interactive particle tracing in large 3D unsteady flow data sets. Finally, a user study will be designed to evaluate the perception of path lines 2D unsteady vector fields.
2014-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Manipulation of memory responses in allergy
2016-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Perturbative analysis of optical microdisk cavities with boundary deformation
In the recent decade, the study of optical microcavities has become an important subject of research in physics. Most prominent are whispering-gallery cavities, e.g. microdisk cavities, where light is confined on a micrometer scale by total internal reflection at the boundary of the cavity. Deforming the boundary of such cavities has led to a variety of applications and interesting physics.


In this project, we are going to employ a perturbation theory to analyze several important aspects of deformed microdisk cavities. We will introduce and study the inverse problem where the far-field emission pattern is given and the corresponding cavity deformation has to be determined. Moreover, we will use the perturbation theory to derive handy formulas for frequency splitting and Q-spoiling. We plan to study the effect of mode coupling on decay rates and relate the perturbation theory to the theory of resonance-assisted tunneling in nearly-integrable quantum systems. Finally, we will use the perturbation theory to analyze the effects of surface roughness.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Binomial ideals are important objects in algebraic statistics. A frequent question is whether a given family of binomial ideals stabilizes up to symmetry when some of the parameters grow unboundedly. If this is the case, then the complexity of these models is reduced, therefore computations with them can be carried out more efficiently. In this project we study stabilization up to symmetry. We aim to find a detailed way to work with families of toric varieties with up to symmetry finite Markov bases and to extend the understanding of the polyhedral cones and lattice point configurations modulo symmetries. We envision efficient theoretical and algorithmic methods resulting from a better understanding of how to deal with polyhedral objects modulo symmetry.
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
The role of BDNF in LTP in the amygdala during fear conditioning
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Technology-aware Asymmetric 3D-Inteconnect Architectures: Templates and Design Methods
New production methods enable the design of heterogeneous 3D-System-on-Chips (3D-SoCs), which consist of stacked silicon dies manufactured with different technologies. In contrast to homogeneous SoCs, this allows to adjust the technological characteristics of each die to the specific requirements of the components placed in each layer. Heterogeneous 3D-SoCs provide unprecedented integration possibilities for embedded and high performance systems. To exploit that potential, powerful, flexible, and scalable communication infrastructures are required. Yet, current interconnect architectures (IAs) tacitly assume a multilayer homogeneous 3D-SoC and do not consider the influence of different technology parameters on the topology, architectural, and micro-architectural level of the IA.

In this project, we aim to develop architectural templates and design methods for 3D-interconnect architectures for heterogeneous 3D-SoCs. We target two main innovations: First, we will exploit the specific technology characteristics of individual chip layers in heterogeneous 3D-SoCs. Therefore, we will re-evaluate and extend existing approaches for heterogeneous and hybrid 2D-interconnect architectures. Second, we aim at discovering
new interaction mechanisms among components, which may be spatially distributed even at the micro-architectural level, to exploit their diverse features when manufactured in different technologies. The combination of these aspects leads to technology asymmetric 3D-interconnect architectures (TA-3D-IAs), as defined in this proposal for the first time.

The main outcome of the project will be a deeper understanding of TA-3D-IAs as part of heterogeneous 3D-SoCs. Further, we will develop systematic design methodologies and a set of architectural templates for the design of TA-3D-IAs. Therefor we will create a full-fledged simulation framework for the analysis of TA-3D-IAs' design space, which will be capable of accounting for technology-specific parameters for all components of the communication infrastructure. In addition, we will provide reference benchmarks and selected TA-3D-IAs, which will allow other research teams to evaluate and compare their ideas.
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Inequality, Status Anxiety, and Quality of Life. An Examination and Extension of the Spirit-Level Theory for Europe
The Spirit-Level theory as recently developed by Richard Wilkinson and Kate Pickett claims that egalitarian societies have less social problems and allow their citizens better lives than inegalitarian societies. The assumed causal mechanism is inequality-induced status anxiety, which leads to behavior by which individuals harm themselves and society at large. However, neither Wilkinson and Pickett¿s book nor follow-up research has provided convincing evidence for this causal mechanism. To fill this gap, this project proposes to examine the impact inequalities have on status anxiety and further on individual and societal quality of life, in a cross-national perspective involving the member states of the European Union. The following key questions are addressed: (1.) How widespread is status anxiety in Europe, and which groups of people are especially affected by it? (2.) Which societal conditions cause status anxiety, and how important are social inequalities in this respect? (3.) Which consequences does status anxiety have for individual and societal quality of life? (4.) Provided status anxiety does not mediate between societal conditions and (low) quality of life: what else could be the key socio-psychological mechanism? The project is designed as a quantitative cross-country comparison, covering the member states of the European Union. The main data source is the European Quality of Life Surveys (EQLS) from 2003, 2007 und 2011/12. The project promises to provide new insights into how society should be organized so that all citizens feel respected.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Investigation of Staphylococcus aureus intracellular survival strategies using a newgenetically encoded proliferation reporter system
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Improving Spatial Perception for Medical Augmented Reality using Illustrative Rendering and Auditory Display
This project shall offer new findings for the encoding of spatial information in medical augmented reality (AR) illustrations. New methods for AR distance encoding via illustrative shadows and glyphs shall be investigated. Furthermore, context-adaptive methods for the delineation as well as methods for the encoding of spatial information via auditive feedback are developed. The results can be used to reduce incorrect spatial interpretations in medical AR, to expand existing AR visualization methods and to support physicians during image-guided interventions to reduce the risk of future medical interventions.
2016-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Vulnerability and resilience to pathological fear memory - a role for neuropetidergic modulation in the dentate gyrus
Memories for stressful and fear-inducing events are of vital importance for behavioral adaptation to a potentially dangerous environment. However, exaggerated fear memories can develop following the experience of a traumatic stressor and lead to diseases such as post-traumatic stress disorder. Thus, experimental fear conditioning paradigms have been instrumental in resolving fundamental mechanisms of information storage in the nervous system and in studying the development of stress-induced psychopathology.

The dentate gyrus as a gateway to the hippocampal formation plays a critical role in the formation and retrieval of contextual fear memory. Activity and plasticity in the dentate gyrus are modulated by stress and are under control of stress-responsive neural circuits. GABAergic local circuit neurons appear to play a pivotal role in this regulation, controlling information flow and excitability in the dentate gyrus in a stress-dependent manner.
In the proposed project we aim to determine how two populations of GABAergic interneurons and their associated neuropeptides, neuropeptide Y and cholecystokinin, control adaptive and maladaptive fear memory formation. In specific pre-experiments to this project we found that stress exposure induces lasting expression alterations in these two neuropeptides, which are not only markers for distinct populations of interneurons but themselves act as potent modifiers of anxiety state.
We will therefore utilize an established animal model of juvenile stress-induced pathological fear in combination with a novel behavioral profiling approach to determine how individual fear levels relate to the expression and function of neuropeptide Y and cholecystokinin in the dentate gyrus. The partners in this project combine their expertise in the analysis of molecular and physiological mechanisms of fear in order to delineate and functionally characterize the interneuron circuits that utilize these peptides and their recruitment by different stress experiences. We will determine how psychological parameters, in particular of controllability as a predisposing factor for maladaptive fear memory, act on local circuit components and may lead to pathology or lasting adaptation. Activation mechanisms acting on these interneuron populations will be examined with high resolution profiling of receptor expression and through amygdala priming experiments that we have previously shown to simulate stress-related modification of dentate gyrus activity and plasticity. Finally, we will recruit specific and selective molecular intervention tools to examine the function of those neuropeptides in the local circuitry and their control of fear behavior and fear memory.
We expect that this interdisciplinary study will yield critical understanding of the neural mechanisms of fear adaptation, the individual vulnerability to stress and stress-related psychopathology. 
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
The cold shock protein YB-1 (Y-box protein-1) in chronic T cell responses and systemic lupus erythematosus (SLE)
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Searching for the engram at the proteome level
Memories of events long past bear on our present motivations and behaviour. Malfunctioning of such long-term mnemonic function has significant clinical consequences. In project B15N, we deal with the ¿where¿ and ¿what¿ of long-term memory. We aim (i) at localizing a long-term associative engram by visualizing de novo protein synthesis → ¿where¿ and (ii) at characterizing this engram¿s molecular content by identifying the newly synthesized proteins → ¿what¿. Requirement for de novo protein synthesis is a characteristic of long-term memory. The respective proteins should be critical for both memory consolidation and the long-lasting storage. Notwithstanding their importance, a comprehensive, cell-specific inventory of these proteins so far does not exist in any organism. To fill this gap, uniquely in Drosophila, we can combine a well-established long-term memory paradigm with in vivo, cell-specific metabolic protein labeling using click chemistry. Converging evidence point to the mushroom body Kenyon cells as the site of coincidence detection for olfactory associative learning in the fly. Individual Kenyon cell-afferent and -efferent neurons have been identified for reinforcement signaling and memory retrieval, respectively. We will metabolically label proteins that are acutely synthesized in Kenyon cells and their critical post-synaptic partners upon olfactory learning. These proteins will be (i) visualized using fluorescent non-canonical amino acid tagging (FUNCAT) to monitor a ¿systems consolidation¿-like process, including its temporal dynamics as reflected in critical time-windows as well as global protein synthesis and turnover rates. The proteins made de novo upon learning will also be (ii) purified using bioorthogonal non-canonical amino acid tagging (BONCAT) and ¿inventoried¿ by mass spectrometry. As a side-track, we will apply these two approaches also to the glial cells as these critically contribute to neuronal function, including long-term memory. Finally, we will (iii) validate the emerging candidate proteins in terms of their causal role in long-term memory using reverse genetics. Given that molecular mechanisms of learning and memory are well-conserved across phyla, we can reasonably hope for translational value of our results.
2014-2017
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
in vitro and in vivo analyses of posttranslational modifications of the Src family kinases Lck and Fyn
Src family kinases (SFKs) such as p56lck (referred to as Lck) and p59fyn (referred to as Fyn) Fyn are crucial in TCR-mediated signaling. Targeting of SFKs has recently become a novel therapeutic option to treat T-cell mediated diseases. Regulation of SFK activity occurs via phosphorylation of two conserved tyrosine residues (Y394 and Y505 in Lck). In addition to these two well-characterized sites, SFKs possess additional amino acid residues which are modified posttranslationally. The functional significance of the latter is not yet completely understood. We have recently focused our investigations on S59 and Y192 in Lck and on Y214 (homologous to Y192 of Lck) in Fyn. Preliminary data show that phosphorylation of Lck on S59 is required for sustained TCR-mediated signaling. Phosphorylation of Y192 in Lck and Y214 in Fyn has been proposed to enhance SFK activity. However, the functional significance of these phosphorylations remains elusive. In addition to phosphorylation, we have also shown that Lck undergoes sulfenylation (cysteine oxidation) upon TCR stimulation. Sulfenylation is a reversible process akin to phosphorylation. Oxidation of cysteine residues in the C-terminus of Src and Lyn (homologues to C465 and C476 in Lck) has been proposed to regulate their kinase activity. The aim of this project is to further investigate the role of phosphorylation and sulfenylation in the regulation of Lck and Fyn activity. By generating Lck and Fyn constructs carrying mutations of selected amino acid residues (S, Y, and C), we will characterize their function in TCR-mediated signaling. Taking advantage of an Lck-biosensor and FLIM, which we have used in a recently published study, we will further assess whether posttranslational modifications of Lck affect its conformation and activation in mouse and human T cells. We will finally generate mouse models to assess the relevance of the selected amino acid residues in vivo.

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