Research projects funded by the German Research Foundation

2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Achromatopsia - Exploring nature and plasticity of vision in the absence of functional cones
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Active learning for matrix completion
Matrix completion is an essential problem in modern machine learning, as it is e.g. important for the calibration of the recommendation systems. We consider the problem of matrix completion in the setting where the learner can choose where to sample. In this setting, it can be of interest to target more specifically parts of the matrix where it is discovered that the complexity is high (higher local rank), where the knowledge is limited (few sampled points), or where the noise is high. This project plans to consider first the problem of active learning for matrix completion when the matrix can be subdivided into block submatrices of small ranks that are known, and then in the more general case where this cannot be done.
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.
2016-2019
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
2018-2021
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
The interplay between autophagy and S. aureus infection
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
German Ultrahigh Field Imaging (GUFI II)
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).
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).
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.
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.
2016-2019
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.
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Infrasound and its relevance for audible sound
An increasing number of individuals are being exposed to infrasound. It is well known that certain individuals may be particularly sensitive and that their quality of life is considerably degraded by a range of symptoms (insomnia, concentration disorders, restlessness, migraine). It is, however, still not clear, how infrasound is processed by human beings. The project aims at investigating the perception mechanisms for infrasound and low-frequency sound. This will provide physicians and psychologists with essential information for an improved examination of the effects such sound has on humans.One hypothesis, how infrasound can be heard, is that the auditory system generates audible distortion products in the audio-frequency range. In order to investigate this hypothesis, it is crucial to rule out that these distortions are produced technically, i.e. by the infrasound stimulus presentation devices. Therefore, the project starts with developing both, distortion-free infrasound sources and sensitive ear canal sound measuring devices. The latter will be used in vivo to quantify the harmonic distortion produced by the human auditory system. Then we will explore the extent to which these distortions are the cause of the perception of infrasound that is, or is not, accompanied by external audio sound. An alternative infrasound perception hypothesis is that infrasound becomes audible because it modulates audio sounds. These two hypotheses will be critically validated by means of listening tests. The results of the latter as well as the technical ear canal sound measurements will be used as the basis for developing models of the infrasound perception processes within this project.The results of this project are believed to lay, in the long run, the ground for future safety regulations and for an adequate characterization of infrasound emission. The results will be important for both protection of health (protection against hazardous infrasound immission) and for economic development (infrasound emission, e.g. manufacturers and operators of wind turbines).
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
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
iPROMOTE: Impact of PReOperative Midazolam on OuTcome of Elderly patients
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.
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?
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
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Modelling and dynamic simulation of multistage particle cross-flow separations in a turbulent fluid flow
The experimental investigation, modelling, dynamic simulation and evaluation of multistage particle cross-flow separation in a turbulent fluid flow was selected specifically for the priority program 1679 DynSim . This typical separation process is used to separate a large number of raw materials, waste, intermediate and by-products in a lot of economic branches. Despite its proven good pro-cess performance, several unsolved processing problems are still connected with it, e.g. fluctuating (turbulent) air flow and particle contents in separation chamber, marked stochastic process dynam-ics as well as resulting insufficient process performance (separation efficiency) and product quality (purity).The thorough solution of these problems requires the development of physically founded, multi-scale and predictive models to evaluate and simulate the process dynamics of interlinked stochas-tic cross-flow separations that will be incorporated in efficient flow-sheet simulations of solid pro-cessing in future.During this project, time and spatially resolved analytical and numerical models will be developed for the process kinetics and interlinked dynamic cross-flow separation behaviour of particles taking into account relevant separation characteristics like size, density and shape. Additionally, steady and unsteady, spatially resolved, computationally efficient numerical simulations of the turbulent flow field will be carried out. By coupling the resulting flow field with the Newtonian and Eulerian equations describing motion and rotation of the particles thanks to the Discrete Element Method (DEM), the trajectories of the particles will be obtained in the real apparatus. After first one-way simulations with simple wall models, coupled computations involving more realistic particle-wall and particle-particle collisions will be considered. The quantitative validation of the employed mod-els will be possible thanks to comparison with time and spatially resolved, three-dimensional Parti-cle Tracking Velocimetry (PTV) measurements in the apparatus. If needed, additional Direct Nu-merical Simulations (DNS) will be considered for the two-phase flow at microscale. The processing and energetic performance (separation efficiency, specific energy consumption) and product quality of separation experiments and numerical tests will be model-aided evaluated and optimized. Next, the calculation and evaluation of dynamic changes of process performance and product quality will follow for step-wise and harmonic oscillations of feed flow, contents, and separation characteristics like particle size density and shape (2nd phase). Finally, these models will be incorporated in a multiscale, modular constructed processing system model able to describe any combined comminution, agglomeration and cross-flow separation processes (3rd phase).
2015-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Modeling and Simulation of photovoltaic systems
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
MuSyAD on Anomaly Detection
Anomaly detection is an interdisciplinary domain, borrowing elements from mathematics, computer science, and engineering. The main aim is to develop efficient techniques for detecting anomalous behaviour of systems. In the classical scenario a monitor receives data from a system and compares this data to a reference system with some single ¿normal¿ behaviour. Ideally no strong assumptions are made on the nature of anomalous behaviours, so the problem of anomaly detection is by essence a non parametric problem. Here I propose to study a more complex scenario, which will be referred to as multisystem anomaly detection. In this setting, reference systems can have a variety of ¿normal¿ behaviours, and moreover, there are many systems under the monitor¿s surveillance, and the monitor must allocate its resources wisely among them. In this situation new theoretical and computational challenges arise. The overall objective of this proposal is to find efficient methods to solve the problem of multi-system anomaly detection. This aim will be reached by addressing the following sub-objectives. First, we will generalise the theoretical framework of anomaly detection to the broader setting of multi-system anomaly detection. Second, multi-system anomaly detection methods will be developed, by taking ideas from the non parametric testing field and applying them to the new framework. Third, we will study optimal monitoring strategies for cases where the multiple systems cannot be monitored simultaneously. Here, it is important that the monitor allocates its resources among the systems in a way that is as efficient as possible. To this end, sequential and adaptive sampling methods that target the anomaly detection problem will be designed. Since anomaly detection is a non parametric problem, elements in the theory of non parametric confidence sets will be used. Finally, the newly developed methods will be applied to practical problems: a methodological example in extreme value theory, an econometric application for speculative bubble detection and two applications in a Brain Computer Interface framework.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Simulating by DNS the nanoparticle production in a spray flame
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Neuronal representation of motivational value and context in explicit and implicit learning
2016-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Neuronal representation of motivational value and context in explicit and implicit learning
Recent work in this subproject has demonstrated that both implicit and explicit rewards are involved in the incidental learning of repeated spatial configurations. Implicitly, reward signals were obtained from the putamen when a search target was found at a learnt location within a repeated spatial search context. Explicit monetary reward led to enhanced search guidance in repeated configurations. Medial frontal and retrosplenial cortex were core areas of the underlying neural architecture. For the next funding period, we propose to further investigate the nature of reward enhancement of spatial contextual cueing with respect to the role of relative reward value and with respect to the role of reward versus punishment (monetary gain versus loss). In addition, the specificity of the reward-related enhancement will be tested by contrasting context learning and target location probability learning as well as by investigating the contribution of visual working memory capacity. A new aspect will consist of developmental studies of reward modulation of contextual cueing over the lifespan. In particular, we will study age-related changes during learning, expression of learning and relearning of incidentally acquired contextual cues in visual search and examine how the implicit processes interact with motivational factors and working memory capacity.
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.
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Numerical solution methods for coupled population balance systems for the dynamic simulation of multivariate particle processes at the example of the shape-selective crystallization
Solid state processes are described by population balance systems. These systems consist in general of coupled partial differential equations characterizing the continuous phase and a population balance equation to describe the dynamic evolution of the solid state.
In the framework of this project, new numerical techniques for the accurate and efficient solution of such systems are developed. This is done in cooperation with the WIAS-Berlin and the TU Hamburg Harburg at the example of the shape-selective crystallization. To simulate such crystallization processes not only adequate solution techniques are required by as well reliable shape dependent crystallization kinetics. These kinetics are determined in several experimental plants. Using the obtained results, new process concepts for the continuous shape-selective crystallization shall be developed and optimized.
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Online adaptation to the parameters of the problem in active learning
We consider the problem of active learning in the setting of classification and optimisation, which are baselines problems in applied mathematics and machine learning. The problem of adaptivity (to unknown distributional parameters) has remained opened in many contexts (e.g. smooth decision boundary for classification, or optimisation of the cumulative regret). While some recent advances on this problems established adaptive rates in some contexts, adaptivity in most of the real world setting has so far remained elusive. In this project, we plan to investigate the problem of adapting to the unknown parameters of the problem (e.g. smoothness, margin assumptions, measure of the near optimal points, etc), and intend to develop minimax rates on the learning efficiency with respect to an oracle learner.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Chirp-evoked auditory steady-state responses: Optimal parameters for rapid and objective tests of hearing
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.
2017-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Projekt on Data Assimilation
This project is concerned with the problem of learning sequentially, adaptively and in partial information on an uncertain environment. In this setting, the learner collects sequentially and actively the data, which is not available before-hand in a batch form. The process is as follows: at each time t, the learner chooses an action and receives a data point, that depends on the performed action. The learner collects data in order to learn the system, but also to achieve a goal (characterized by an objective function) that depends on the application. In this project, we will aim at solving this problem under general objective functions, and dependency in the data collecting process ¿ exploring variations of the so-called bandit setting which corresponds to this problem with a specific objective function.

As a motivating example, consider the problem of sequential and active attention detection through an eye tracker. A human user is looking at a screen, and the objective of an automatized monitor (learner) is to identify through an eye tracker zones of this screen where the user is not paying sufficient attention. In order to do so, the monitor is allowed at each time t to flash a small zone a t in the screen, e.g. light a pixel (action), and the eye tracker detects through the eye movement if the user has observed this flash. Ideally the monitor should focus on these difficult zones and flash more often there (i.e. choose more often specific actions corresponding to less identified zones). Therefore, sequential and adaptive learning methods are expected to improve the performances of the monitor.
2018-2021
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Control of CD4+ T cell effector functions in melanoma
Recent insights highlight that CD4+ T cells can contribute to effective tumor immune defense but also participate in tissue homeostasis, regeneration and tumor promotion. The goal of this proposal is to better understand the molecular and cellular mechanisms how the phenotypes and effector functions of CD4+ T cells are regulated in tumor tissues in vivo. We will use adoptive T cell immunotherapy protocols in our experimental mouse melanoma models established in the laboratory. A focus of our work is the immunoregulatory role of neutrophils both locally in the tumor microenvironment as well as systemically.
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
2013-2018
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Sharp Ridge Structures in Flow Visualization
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.
2018-2021
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
The role of the atypical NF-κB inhibitory protein IκBNS in effector cells
NF-kB is an important transcription factor for development and function of immune cells and is regulated by IkB proteins. IkBNS is an unusual IkB protein and functionally poorly characterized. During the 2nd funding period, we found that IkBNS-/- mice are resistant towards high-dose Listeria infection hinting towards alterations in innate immunity. Indeed, we found high expression of IkBNS in macrophages, neutrophils and NK cells using reporter mice. In the next funding period, we will decipher molecular and cellular functions of IkBNS in these cells using newly established conditional knockout mice that are currently being characterized. This includes IkBNS-dependent leucocyte migration during Listeria infection and functional characterization of target genes and microRNAs.
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.
2017-2020
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Structure and dynamics of nematic phases with strong smectic fluctuations formed by bent‐core mesogens
Mesophases formed by bent-core mesogens are unique Soft Matter systems exhibiting a rich variety of complex structures and self-assembly phenomena with remarkable electro-optical properties. Helical nanofilaments and sponge phases, chiral isotropic conglomerate phases and twist-bend structures are results of the molecular design and an intricate interplay between chirality and polarity in bent-core liquid crystals. Enhanced polar and smectic fluctuations,  driven by steric interactions of bent mesogens, result in the formation of cluster phases with strong susceptibility to external fields. This proposal continues the extensive and fruitful collaboration initiated in the first work period between the Department of Nonlinear Phenomena at Otto von Guericke University Magdeburg (PI EREMIN) and the Department of Organic Chemistry at Martin Luther University Halle (PI TSCHIERSKE).

The proposed research is aimed at expanding the studies of development of polar correlations in condensed smectic and nematic phases and providing a deeper insight into the physical properties and structure-property relations of mesophases formed by anisometric bent-core and dimeric mesogens. The goal is to gain a fundamental understanding of domain formation and cybotaxis for the development of polar order and spontaneous symmetry breaking and self-assembly phenomena in liquid crystalline phases composed of bent molecules. Apart from understanding the transition from short-range to long-range polar order, in the current proposal we shall focus on nematic-to-smectic transitions and new molecular structures of NTB materials in relation to chiral domain nematic and paraelectric smectic phases, interaction between molecular chirality, domain formation and polar order and the effects of confined geometry on self-assembly in bent-core systems.
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.
2018-2021
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
VR technology is being developed continuously and there are ever more applications in sports science, training and therapy. However, no studies were found concerning visual perception of own body, age, habituation effects, and transfer of training in VR to real world. The main aim of this research project is to get basic knowledge about self-perception of the own body, gaze behaviour, habituation effect, and influence of age to motor learning and sports training in VR. With these facts it should be possible to develop a theoretical approach of motor learning and sports training in VR. The objectives are as follows: 1. Influence of age to orientation skills, habituation to VR conditions and motor learning in virtual reality, 2. Influence of visual perception of own body to orientation skills and process of motor learning, 3. Characterisation of gaze behaviour in VR comparing to reality, 4. Comparison between training in VR and training in reality taking account transfer effects, 5. Derivation conclusions to scientifically sound training in VR. We assume from our research findings new knowledge about theory formation in processes of motor learning and sports training in virtual reality by using expanded embodiment approach.
2017-2019
Mittelgeber: Deutsche Forschungsgemeinschaft (DFG)
Two sample tests in structured networks
The study of networks leads to a wide range of high dimensional inference problems. In most practical scenarios, one needs to draw inference from a small population of large networks. The present paper studies hypothesis testing of graphs in this high-dimensional regime. We consider the problem of testing between two populations of inhomogeneous random graphs defined on the same set of vertices. We are interested in tests based on estimates of the Frobenius and operator norms of the difference between the population adjacency matrices, in both the "large graph, small sample" and "small graph, large sample" regimes. We aim at deriving lower bounds on the minimax separation rate for the associated testing problems, and show that the constructed tests are near optimal. We plan to focus on the structured graph setting (e.g. sparse graphs, etc).
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.

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