Multi-Photon Fluorescence Microscopy of Polymeric Systems

Die Arbeit beschäftigt sich mit der Anwendung von fluoreszenzmikroskopischen Analysemethoden auf polymere Systeme. Im ersten Teil der Arbeit werden Polymere nach Behandlung in einem DBD-Plasma auf durch den Plasmaprozess eingeführte Aminogruppen auf der Substratoberfläche untersucht. Neben ortselektiv behandelten Folien und Kompositen werden auch poröse Strukturen (Polymermembrane) und Textilfasern untersucht. Die Multiphotonen-Fluoreszenzmikroskopie eignet sich besonders gut, um die Aminogruppen dreidimensional ortsaufgelöst in Submikrometerauflösung zu vermessen. Es kann gezeigt werden, dass sich durch Doppellabeling primäre und sekundäre Aminogruppen simultan detektieren lassen. Durch Referenzmessungen wird erfolgreich die ortsaufgelöste absolute Dichte primärer und sekundärer Amine ermittelt. Außerdem können über Fluoreszenzanisotropiemessungen Aussagen über die molekulare Umgebung der Aminogruppen getroffen werden. Im zweiten Teil werden Hydrogele auf ihre Eignung als Drug Delivery System hin untersucht. Dabei sollen die eingeschlossenen therapeutischen Moleküle langsam durch Gelabbau kontrolliert und möglichst quantitativ freigesetzt werden. Zur Überprüfung wird Grün fluoreszierendes Protein (GFP) als Sensormolekül in das Hydrogel inkorporiert und bezüglich seiner Translations- und Rotationsdiffusion untersucht. Die Translation der GFP-Moleküle kann über die Methode des Fluorescence Recovery After Photobleaching (FRAP) bestimmt werden, die Rotationsdiffusion hingegen über Fluoreszenzanisotropiemessungen. Die Ergebnisse zur Rotationsdiffusion zeigen, dass nur eine mäßige Einschränkung der Rotationsmobilität aufgrund des Polymergehalts im Hydrogel zu beobachten ist und Adsorptionseffekte keine entscheidende Rolle spielen werden. Die Ergebnisse zur Translationsdiffusion machen deutlich, dass das GFP effektiv durch die Quervernetzung des verwendeten Polymers zum Hydrogel immobilisiert ist und damit fast ausschließlich über den Gelabbau freigesetzt wird.This work deals with the application of fluorescence microscopic analytical methods on polymeric systems. The first part focuses on the investigation of amino groups on substrate surfaces which have been introduced by a DBD plasma process. Area-selective PP-foils and PP-composites are investigated as well as porous structures (polymer membranes) and textile fibers (PET, cotton). Multi-photon fluorescence microscopy is advantageous for three-dimensional investigation of amino groups with sub-micrometer resolution. It can be shown that with help of double labeling primary and secondary amines can be detected simultaneously. With help of reference measurements the spatially resolved absolute density of primary and secondary amino groups can be determined. Furthermore, fluorescence anisotropy experiments yield information on the molecular environment of the amino groups. The second part is occupied with investigation of hydrogels as drug delivery system. These hydrogels are supposed to enable a slow controlled and as possible quantitative release of incorporated therapeutic molecules. This is verified by incorporating green fluorescent protein (GFP) as reporter molecule and analysis of its translational and rotational diffusion behavior. The translational diffusion of GFP can be determined by means of fluorescence recovery after photobleaching (FRAP), the rotational diffusion is probed by fluorescence anisotropy experiments. The experiments of rotational diffusion show a moderate restriction of rotational mobility due to the polymer content of the hydrogels, adsorption effects do not play an essential role. The results of translational diffusion investigation reveal that GFP is effectively immobilized by polymer crosslinking in the hydrogel, hence the release is almost completely due to gel degradation

Hybrid State Estimation in a Semitrailer for Different Loading Conditions

For state and parameter estimation in vehicles, Kalman filters, especially nonlinear extensions like the extended Kalman filter (EKF) and unscented Kalman filter (UKF), are very common. However, the estimation accuracy is highly dependent on the quality of the model used in the process update of the Kalman filter. Model errors can result from non-modeled dynamics that are either unknown or very difficult to describe. In recent years data-driven approaches for state estimation are the subject of research with promising results in estimation accuracy and reduced implementation effort. In this work, both a model-based method with an UKF and a data-driven approach based on recurrent neural networks (RNN) are implemented and combined to two hybrid methods for the application of state and parameter estimation in a truck-semitrailer for three different loading conditions. Hybrid estimation architectures promise to combine the advantages of model-based and data-driven methods to achieve better estimation accuracy than their standalone components. To the best knowledge of the authors, this work is the first to extend the field of hybrid state estimation to semitrailers estimating the truck steering angle, articulation angle, and the trailer's lateral and vertical tire forces. Four estimation architectures (an UKF, one purely data-driven method, and two hybrid methods) are optimized and compared to each other regarding estimation accuracy. The UKF is optimized with a particle swarm optimization (PSO) while the hyperparameters of the data-driven method are tuned with the asynchronous successive halving algorithm (ASHA) to result in a fair comparison. All methods are developed and compared based on an experimental data set from a test vehicle

Land-use intensification and agroforestry in the Kenyan highland: impacts on soil microbial community composition and functional capacity

This study investigates microbial communities in soil from sites under different land use in Kenya. We sampled natural forest, forest plantations, agricultural fields of agroforestry farms,agricultural fields with traditional farming and eroded soil on the slopes of Mount Elgon,Kenya. We hypothesised that microbial decomposition capacity, biomass and diversity 1)decreases with intensified cultivation; and 2)can be restored by soil and land management in agroforestry. Functional capacity of soil microbial communities was estimated by degradation of 31 substrates on Biolog EcoPlates™. Microbial community composition and biomass were characterised by phospholipid fatty acid (PLFA)and microbial C and N analyses. All 31 substrates were metabolised in all studied soil types, i.e. functional diversity did not differ. However,both the substrate utilisation rates and the microbial biomass decreased with intensification of land use, and the biomass was positively correlated with organic matter content. Multivariate analysis of PLFA and Biolog EcoPlate™ data showed clear differences 25 between land uses, also indicated by different relative abundance of PLFA markers for certain microorganism groups. In conclusion, our results show that vegetation and land use control the substrate utilisation capacity and microbial community composition and that functional capacity of depleted soils can be restored by active soil management, e.g. forest plantation. However, although 20 to 30 years of agroforestry farming practises did result in improved soil microbiological and chemical conditions of agricultural soil as compared to traditional agricultural fields, the change was not statistically significant

Continuous Monitoring of Software Services: Design and Application of the Kieker Framework

In addition to studying the construction and evolution of software services, the software engineering discipline needs to address the operation of continuously running software services. A requirement for its robust operation are means for effective monitoring of software runtime behavior. In contrast to profiling for construction activities, monitoring of operational services should only impose a small performance overhead. Furthermore, instrumentation should be non-intrusive to the business logic, as far as possible. We present the Kieker framework for monitoring software runtime behavior, e.g., internal performance or (distributed) trace data. The flexible architecture allows to replace or add framework components, including monitoring probes, analysis components, and monitoring record types shared by logging and analysis. As a non-intrusive instrumentation technique, Kieker currently employs, but is not restricted to, aspect-oriented programming. An extensive lab study evaluates and quantifies the low overhead caused by the framework components. Qualitative evaluations provided by industrial case studies demonstrate the practicality of the approach with a telecommunication customer self service and a digital photo submission service. Kieker is available as open-source software, where both the academic and industrial partners contribute to the code. Our experiment data is publicly available, allowing interested researchers to repeat and extend our lab experiments

Optimized Tuning of an EKF for State and Parameter Estimation in a Semitrailer

The Extended Kalman Filter (EKF) is a well-known method for state and parameter estimation in vehicle dynamics. However, for tuning the EKF, knowledge about the process and measurement noise is needed, which is usually unknown. Tuning the noise parameters manually is very time consuming, especially for systems with many states. Automated optimization based on the filtering errors promises less application time and better estimation performance, but also requires computing resources. This work presents two approaches for estimating the noise parameters of an EKF: A particle swarm optimization (PSO) and a gradient-based optimization. The EKF is applied to a nonlinear vehicle model of a tractor-semitrailer for estimating the steering and articulation angle as well as lateral and vertical tire forces based on real measurement data with different trailer loadings. Both methods are compared to each other to achieve the best estimation performance

Clinical skills of veterinary students - a cross-sectional study of the self-concept and exposure to skills training in Hannover, Germany

Background: Students of veterinary medicine should achieve basic professional competences required to practise their profession. A main focus of veterinary education is on developing clinical skills. The present study used the guidelines of the "Day-One Skills" list of European Association of Establishments for Veterinary Education (EAEVE) to create an online questionnaire for assessing the skills acquired by students at the University of Veterinary Medicine Hannover (TiHo). The theoretical and practical veterinary knowledge levels of the students and postgraduates are determined and compared. Results: In two batches, 607 people responded (response batch 1, 23.78%; response batch 2, 23.83%). From 49 defined skills, 28 are actually practised during training at the university and 21 activities are known only theoretically. Furthermore, the students showed great willingness to use simulators and models in a clinical skills lab. Conclusions: The results of this survey highlight that the opening of a clinical skills lab at the University of Veterinary Medicine Hannover and its incorporation into the study programme are ideal tools to promote practical competences and foster the motivation to learn

Analysis of cost effectiveness of screening Danish men aged 65 for abdominal aortic aneurysm

Objective To assess the cost effectiveness of screening men aged 65 for abdominal aortic aneurysm