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Institut
- Zentrale Einrichtungen (16)
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Thousands of chemicals from daily use are being discharged from civilization into the water cycle via different pathways. Ingredients of personal care products, detergents, pharmaceuticals, pesticides, and industrial chemicals thus find their way into the aquatic ecosystems and may cause adverse impacts on the ecology. Pharmaceuticals for instance, represent a central group of anthropogenic chemicals, because of their designed potency to interfere with physiological functions in organisms. Ecotoxicological effects from pharmaceutical burden have been verified in the past. Therapeutic groups with pronounced endocrine disrupting potentials such as steroid hormones gain increasing focus in environmental research as it was reported that they cause endocrine disruption in aquatic organisms even when exposed to environmentally relevant concentrations. This thesis considers the comprehensive investigation of the occurrence of corticosteroids and progestogens in wastewater treatment plant (WWTP) effluents and surface waters as well as the elucidation of the fate and biodegradability of these steroid families during activated sludge treatment. For the first goal of the thesis, a robust and highly sensitive analytical method based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed in order to simultaneously determine the occurrence of around 60 mineralocorticoids, glucocorticoids and progestogens in the aquatic environment. A special focus was set to the compound selection due to the diversity of marketed synthetic steroids. Some analytical challenges have been approved by individual approaches regarding sensitivity enhancement and compound stabilities. These results may be important for further research in environmental analysis of steroid hormones. Reliable and low quantification limits are the perquisite for the determination of corticosteroids and progestogens at relevant concentrations due to low consumption volumes and simultaneously low effect-based trigger values. Achieved quantification limits for all target analytes ranged between 0.02 ng/L and 0.5 ng/L in surface water and 0.05 ng/L to 5 ng/L in WWTP effluents. This sensitivity enabled the detection of three mineralocorticoids, 23 glucocorticoids and 10 progestogens within the sampling campaign around Germany. Many of them were detected for the first time in the environment, particularly in Germany and the EU. To the best of our knowledge, this in-depth steroid screening provided a good overview of single steroid burden and allowed for the identification of predominantly steroids of each steroid
type analyzed for the first time. The frequent detection of highly potent synthetic steroids (e.g. triamcinolone acetonide, clobetasol propionate, betamethasone valerate, dienogest, cyproterone acetate) highlighted insufficient removal during conventional Summary wastewater treatment and indicated the need for regulation to control their emission since the steroid concentrations were found to be above the reported effect-based trigger values for biota. Overall, the study revealed reliable environmental data of poorly or even not analyzed steroids. The results complement the existing knowledge in this field but also providednew information which can beused particularly for compound prioritization in ecotoxicological research and environmental analysis. Based on the data obtained from the monitoring campaign, incubation experiments were conducted to enable the comparison of the biodegradability and transformation processes in activated sludge treatment for structure-related steroids under aerobic and standardized experimental conditions. The compounds were accurately selected to cover manifold structural moieties of commonly used glucocorticoids, including non-halogenated and halogenated steroids, their mono- and diesters, and several acetonide-type steroids. This approach allowed for a structure-based interpretation of the results. The obtained biodegradation rate constants suggested large variations in the biodegradability (half-lifes ranged from < 0.5 h to > 14 d). An increasing stability was identified in the order from non-halogenated steroids (e.g. hydrocortisone), over 9α-halogenated steroids (e.g. betamethasone), to C17-monoesters (e.g. betamethasone 17-valerate, clobetasol propionate), and finally to acetonides (e.g. triamcinolone acetonide), thus suggesting a strong relationship of the biodegradability with the glucocorticoid structure. Some explanations for this behavior have been received by identifying the transformation products (TPs) and elucidating individual transformation pathways. The results revealed the identification of the likelihood of transformation reactions depending on the chemical steroid structure for the first time. Among the identified TPs, the carboxylates (e.g. TPs of fluticasone propionate, triamcinolone acetonide) have been shown persistency in the subsequent incubation experiments. The newly identified TPs furthermore were frequently detected in the effluents of full-scale wastewater treatment plants. These findings emphasized i) the transferability of the lab-scale degradation experiments to real world and that ii) insufficient removals may cause adverse effects in the aquatic environment due to the ability of the precursor steroids and TPs to interact with the endocrine system in biota. For the last goal, the conceptual study for glucocorticoids was applied to progestogens.
Here, two sub-types of the steroid family frequently used for hormonal contraception were selected (17α-hydroxyprogesterone and 19-norstestosterone type). The progestogens showed a fast and complete degradation within six hours, and thus empathizes pronounced biodegradability. However, cyproterone acetate and dienogest Summary have been found to be more recalcitrant in activated sludge treatment. This was consistent with their ubiquitously occurrence during the previous monitoring campaign. The elucidation of TPs again revealed some crucial information regarding the observed behavior and highlighted furthermore the formation of hazardous TPs. It was shown that 19-nortestosterone type steroids are able to undergo aromatization at ring A in contact with activated sludge, leading to the formation of estrogen-like TPs with a phenolic moiety at ring A. In the case of norethisterone the formation of 17α-ethinylestradiol was confirmed, which is a well-known potent synthetic estrogen with elevated ecotoxicological potency. Thus, the results indicated for the very first time an unknown source of estrogenic compounds, particularly for 17α-ethinylestradiol. In conclusion, some steroids were found to be very stable in activated sludge treatment, others degrade well, and others which do degrade but predominantly to active TPs depending on their chemical structure. Fluorinated acetal steroids such as triamcinolone acetonide and fluocinolone acetonide are poorly biodegradable, which is reflected in high concentrations detected ubiquitously in WWTP effluents. Endogenous steroids and their most related synthetic once such as hydrocortisone, prednisolone or 17α-hydroxyprogesterone are readily biodegradable. Regardless their high influent concentrations, they are almost completely removed in conventional WWTPs. Steroids between this range have been found to form elevated quantities of TPs which are partially still active, which particularly the case for betamethasone, fluticasone propionate, cyproterone acetate or dienogest. The thesis illustrates the need for an extensive evaluation of the environmental risks and carried out that corticosteroids and progestogens merit more attention in environmental regulatory and research than it is currently the case
Der Wettbewerb um die besten Technologien zur Realisierung des autonomen Fahrens ist weltweit in vollem Gange.
Trotz großer Anstrengungen ist jedoch die autonome Navigation in strukturierter und vor allem unstrukturierter Umgebung bisher nicht gelöst.
Ein entscheidender Baustein in diesem Themenkomplex ist die Umgebungswahrnehmung und Analyse durch passende Sensorik und entsprechende Sensordatenauswertung.
Insbesondere bildgebende Verfahren im Bereich des für den Menschen sichtbaren Spektrums finden sowohl in der Praxis als auch in der Forschung breite Anwendung.
Dadurch wird jedoch nur ein Bruchteil des elektromagnetischen Spektrums genutzt und folglich ein großer Teil der verfügbaren Informationen zur Umgebungswahrnehmung ignoriert.
Um das vorhandene Spektrum besser zu nutzen, werden in anderen Forschungsbereichen schon seit Jahrzehnten \sog spektrale Sensoren eingesetzt, welche das elektromagnetische Spektrum wesentlich feiner und in einem größeren Bereich im Vergleich zu klassischen Farbkameras analysieren. Jedoch können diese Systeme aufgrund technischer Limitationen nur statische Szenen aufnehmen. Neueste Entwicklungen der Sensortechnik ermöglichen nun dank der \sog Snapshot-Mosaik-Filter-Technik die spektrale Abtastung dynamischer Szenen.
In dieser Dissertation wird der Einsatz und die Eignung der Snapshot-Mosaik-Technik zur Umgebungswahrnehmung und Szenenanalyse im Bereich der autonomen Navigation in strukturierten und unstrukturierten Umgebungen untersucht. Dazu wird erforscht, ob die aufgenommen spektralen Daten einen Vorteil gegenüber klassischen RGB- \bzw Grauwertdaten hinsichtlich der semantischen Szenenanalyse und Klassifikation bieten.
Zunächst wird eine geeignete Vorverarbeitung entwickelt, welche aus den Rohdaten der Sensorik spektrale Werte berechnet. Anschließend wird der Aufbau von neuartigen Datensätzen mit spektralen Daten erläutert. Diese Datensätze dienen als Basis zur Evaluation von verschiedenen Klassifikatoren aus dem Bereich des klassischen maschinellen Lernens.
Darauf aufbauend werden Methoden und Architekturen aus dem Bereich des Deep-Learnings vorgestellt. Anhand ausgewählter Architekturen wird untersucht, ob diese auch mit spektralen Daten trainiert werden können. Weiterhin wird die Verwendung von Deep-Learning-Methoden zur Datenkompression thematisiert. In einem nächsten Schritt werden die komprimierten Daten genutzt, um damit Netzarchitekturen zu trainieren, welche bisher nur mit RGB-Daten kompatibel sind. Abschließend wird analysiert, ob die hochdimensionalen spektralen Daten bei der Szenenanalyse Vorteile gegenüber RGB-Daten bieten
In dieser Arbeit wird die Geschwindigkeit des Simulationscodes zur Pho-
tonenausbreitung beim IceCube-Projekt (clsim) optimiert. Der Prozess der
GPU-Code-Analyse und Leistungsoptimierung wird im Detail beschrie-
ben. Wenn beide Codes auf der gleichen Hardware ausgeführt werden,
wird ein Speedup von etwa 3x gegenüber der ursprünglichen Implemen-
tierung erreicht. Vergleicht man den unveränderten Code auf der derzeit
von IceCube verwendeten Hardware (NVIDIA GTX 1080) mit der opti-
mierten Version, die auf einer aktuellen GPU (NVIDIA A100) läuft, wird
ein Speedup von etwa 9,23x beobachtet. Alle Änderungen am Code wer-
den vorgestellt und deren Auswirkung auf die Laufzeit und Genauigkeit
der Simulation diskutiert.
Der für die Optimierung verfolgte Weg wird dann in einem Schema
verallgemeinert. Programmierer können es als Leitfaden nutzen, um große
und komplexe GPU-Programme zu optimieren. Darüber hinaus wird die
per warp job-queue, ein Entwurfsmuster für das load balancing innerhalb
eines CUDA-Thread-Blocks, im Detail besprochen.
Scientific and public interest in epidemiology and mathematical modelling of disease spread has increased significantly due to the current COVID-19 pandemic. Political action is influenced by forecasts and evaluations of such models and the whole society is affected by the corresponding countermeasures for containment. But how are these models structured?
Which methods can be used to apply them to the respective regions, based on real data sets? These questions are certainly not new. Mathematical modelling in epidemiology using differential equations has been researched for quite some time now and can be carried out mainly by means of numerical computer simulations. These models are constantly being refinded and adapted to corresponding diseases. However, it should be noted that the more complex a model is, the more unknown parameters are included. A meaningful data adaptation thus becomes very diffcult. The goal of this thesis is to design applicable models using the examples of COVID-19 and dengue, to adapt them adequately to real data sets and thus to perform numerical simulations. For this purpose, first the mathematical foundations are presented and a theoretical outline of ordinary differential equations and optimization is provided. The parameter estimations shall be performed by means of adjoint functions. This procedure represents a combination of static and dynamical optimization. The objective function corresponds to a least squares method with L2 norm which depends on the searched parameters. This objective function is coupled to constraints in the form of ordinary differential equations and numerically minimized, using Pontryagin's maximum (minimum) principle and optimal control theory. In the case of dengue, due to the transmission path via mosquitoes, a model reduction of an SIRUV model to an SIR model with time-dependent transmission rate is performed by means of time-scale separation. The SIRUV model includes uninfected (U) and infected (V ) mosquito compartments in addition to the susceptible (S), infected (I) and recovered (R) human compartments, known from the SIR model. The unknwon parameters of the reduced SIR model are estimated using data sets from Colombo (Sri Lanka) and Jakarta (Indonesia). Based on this parameter estimation the predictive power of the model is checked and evaluated. In the case of Jakarta, the model is additionally provided with a mobility component between the individual city districts, based on commuter data. The transmission rates of the SIR models are also dependent on meteorological data as correlations between these and dengue outbreaks have been demonstrated in previous data analyses. For the modelling of COVID-19 we use several SEIRD models which in comparison to the SIR model also take into account the latency period and the number of deaths via exposed (E) and deaths (D) compartments. Based on these models a parameter estimation with adjoint functions is performed for the location Germany. This is possible because since the beginning of the pandemic, the cumulative number of infected persons and deaths
are published daily by Johns Hopkins University and the Robert-Koch-Institute. Here, a SEIRD model with a time delay regarding the deaths proves to be particularly suitable. In the next step, this model is used to compare the parameter estimation via adjoint functions with a Metropolis algorithm. Analytical effort, accuracy and calculation speed are taken into account. In all data fittings, one parameter each is determined to assess the estimated number of unreported cases.
Soziale Netzwerke spielen im Alltagsleben der Schülerinnen und Schüler eine entscheidende Rolle. Im Rahmen der vorliegenden Masterarbeit wurde ein Konzept für die Anzeige von Profilvorschlägen innerhalb des sozialen Netzwerks „InstaHub“, welches ein speziell für den Informatikunterricht programmiertes Werkzeug zum Thema „Datenbanken“ darstellt, entwickelt. Als Hürde stellte sich dabei dar, dass von den etablierten sozialen Netzwerken nur wenig bis gar keine Informationen über die Berechnung von Profil- oder Freundschaftsvorschlägen preisgegeben werden. Daher wurde zunächst das Wesen von Beziehungen zwischen Menschen in nicht-internetbasierten und in internetbasierten sozialen Netzwerken sowie die Gründe für Beziehungen zwischen Menschen in diesen Netzwerken dargelegt. Anhand der Beobachtung von Vorschlägen in anderen sozialen Netzwerken sowie der in InstaHub gespeicherten Nutzerdaten wurde ein Algorithmus für Profilvorschläge in InstaHub entworfen und mitsamt einer passenden Visualisierung entsprechend implementiert. Den zweiten Teil der Arbeit bildete eine Unterrichtseinheit für die Sekundarstufe II mit dem Thema Gefahren der Erzeugung und Verarbeitung von personenbezogenen Daten. In der Unterrichtseinheit dienen die Profilvorschläge in InstaHub, die auf von InstaHub über dessen Nutzer gesammelten Daten aufbauen, als Einstieg in die Thematik. Anschließend wird der Fokus von sozialen Netzwerken auf andere Online-Dienste erweitert und auf die Verarbeitung und Weitergabe dieser Daten eingegangen.
This thesis focuses on approximate inference in assumption-based argumentation frameworks. Argumentation provides a significant idea in the computerization of theoretical and practical reasoning in AI. And it has a close connection with AI, engaging in arguments to perform scientific reasoning. The fundamental approach in this field is abstract argumentation frameworks developed by Dung. Assumption-based argumentation can be regarded as an instance of abstract argumentation with structured arguments. When facing a large scale of data, a challenge of reasoning in assumption-based argumentation is how to construct arguments and resolve attacks over a given claim with minimal cost of computation and acceptable accuracy at the same time. This thesis proposes and investigates approximate methods that randomly select and construct samples of frameworks based on graphical dispute derivations to solve this problem. The presented approach aims to improve reasoning performance and get an acceptable trade-off between computational time and accuracy. The evaluation shows that for reasoning in assumption-based argumentation, in general, the running time is reduced with the cost of slightly low accuracy by randomly sampling and constructing inference rules for potential arguments over a query.
Mathematical models of species dispersal and the resilience of metapopulations against habitat loss
(2021)
Habitat loss and fragmentation due to climate and land-use change are among the biggest threats to biodiversity, as the survival of species relies on suitable habitat area and the possibility to disperse between different patches of habitat. To predict and mitigate the effects of habitat loss, a better understanding of species dispersal is needed. Graph theory provides powerful tools to model metapopulations in changing landscapes with the help of habitat networks, where nodes represent habitat patches and links indicate the possible dispersal pathways between patches.
This thesis adapts tools from graph theory and optimisation to study species dispersal on habitat networks as well as the structure of habitat networks and the effects of habitat loss. In chapter 1, I will give an introduction to the thesis and the different topics presented in this thesis. Chapter 2 will then give a brief summary of tools used in the thesis.
In chapter 3, I present our model on possible range shifts for a generic species. Based on a graph-based dispersal model for a generic aquatic invertebrate with a terrestrial life stage, we developed an optimisation model that models dispersal directed to predefined habitat patches and yields a minimum time until these patches are colonised with respect to the given landscape structure and species dispersal capabilities. We created a time-expanded network based on the original habitat network and solved a mixed integer program to obtain the minimum colonisation time. The results provide maximum possible range shifts, and can be used to estimate how fast newly formed habitat patches can be colonised. Although being specific for this simulation model, the general idea of deriving a surrogate can in principle be adapted to other simulation models.
Next, in chapter 4, I present our model to evaluate the robustness of metapopulations. Based on a variety of habitat networks and different generic species characterised by their dispersal traits and habitat demands, we modeled the permanent loss of habitat patches and subsequent metapopulation dynamics. The results show that species with short dispersal ranges and high local-extinction risks are particularly vulnerable to the loss of habitat across all types of networks. On this basis, we then investigated how well different graph-theoretic metrics of habitat networks can serve as indicators of metapopulation robustness against habitat loss. We identified the clustering coefficient of a network as the only good proxy for metapopulation robustness across all types of species, networks, and habitat loss scenarios.
Finally, in chapter 5, I utilise the results obtained in chapter 4 to identify the areas in a network that should be improved in terms of restoration to maximise the metapopulation robustness under limited resources. More specifically, we exploit our findings that a network’s clustering coefficient is a good indicator for metapopulation robustness and develop two heuristics, a Greedy algorithm and a deducted Lazy Greedy algorithm, that aim at maximising the clustering coefficient of a network. Both algorithms can be applied to any network and are not specific to habitat networks only.
In chapter 6, I will summarize the main findings of this thesis, discuss their limitations and give an outlook of future research topics.
Overall this thesis develops frameworks to study the behaviour of habitat networks and introduces mathematical tools to ecology and thus narrows the gap between mathematics and ecology. While all models in this thesis were developed with a focus on aquatic invertebrates, they can easily be adapted to other metapopulations.
Previous research concerned with early science education revealed that guided play can support young children’s knowledge acquisition. However, the questions whether guided play maintains other important prerequisites such as children’s science self-concept and how guided play should be implemented remain unanswered. The present dissertation encompasses three research articles that investigated 5- to 6-year-old children’s science knowledge, science theories, and science self-concept in the stability domain and their relation to interindividual prerequisites. Moreover, the articles examined whether children’s science knowledge, science theories, and science self-concept can be supported by different play forms, i.e., guided play with material and verbal scaffolds, guided play with material scaffolds, and free play. The general introduction of the present dissertation first highlights children’s cognitive development, their science self-concept, and interindividual prerequisites, i.e., fluid and crystallised intelligence, mental rotation ability, and interest in block play. These prerequisites are applied to possible ways of supporting children during play. The first article focused on the measurement of 5-to-6-year-old children’s stability knowledge and its relation to interindividual prerequisites. Results suggested that children’s stability knowledge could be measured reliably and validly, and was related to their fluid and crystallised intelligence. The second article was concerned with the development of children’s intuitive stability theories over three points of measurement and the effects of guided and free play, children’s prior theories as well as their intelligence on these intuitive theories. Results implied that guided play with material and verbal scaffolds supported children’s stability theories more than the other two play forms, i.e., guided play with material scaffolds and free play. Moreover, consistency of children’s prior theories, their fluid and crystallised intelligence were related to children’s theory adaptation after the intervention. The third article focused on the effect of the playful interventions on children’s stability knowledge and science self-concept over three points of measurement. Furthermore, the reciprocal effects between knowledge acquisition and science self-concept were investigated. Results implied that guided play supported knowledge acquisition and maintained children’s science self-concept. Free play did not support children’s stability knowledge and decreased children’s science self-concept. No evidence for reciprocal effects between children’s stability knowledge and their science self-concept was found. Last, in a general discussion, the findings of the three articles are combined and reflected amidst children’s cognitive development. Summarising, the present dissertation shows that children’s science knowledge, science theories, and science self-concept can be supported through guided play that considers children’s cognitive development.
Die Raytracing-Beschleunigung durch dedizierte Datenstrukturen ist schon lange ein wichtiges Thema der Computergrafik. Im Allgemeinen werden dafür zwei unterschiedliche Ansätze vorgeschlagen: räumliche und richtungsbezogene Beschleunigungsstrukturen. Die vorliegende Arbeit stellt einen innovativen kombinierten Ansatz dieser beiden Bereiche vor, welcher weitere Beschleunigung der Strahlenverfolgung ermöglicht. Dazu werden moderne räumliche Datenstrukturen als Basisstrukturen verwendet und um vorberechnete gerichtete Sichtbarkeitsinformationen auf Basis von Schächten innerhalb einer originellen Struktur, dem Line Space, ergänzt.
Im Laufe der Arbeit werden neuartige Ansätze für die vorberechneten Sichtbarkeitsinformationen vorgeschlagen: ein binärer Wert, der angibt, ob ein Schacht leer oder gefüllt ist, sowie ein einzelner Vertreter, der als repräsentativer Kandidat die tatsächliche Oberfläche approximiert. Es wird gezeigt, wie der binäre Wert nachweislich in einer einfachen, aber effektiven Leerraumüberspringungs-Technik (Empty Space Skipping) genutzt wird, welche unabhängig von der tatsächlich verwendeten räumlichen Basisdatenstruktur einen Leistungsgewinn beim Raytracing von bis zu 40% ermöglicht. Darüber hinaus wird gezeigt, dass diese binären Sichtbarkeitsinformationen eine schnelle Technik zur Berechnung von weichen Schatten und Umgebungsverdeckung auf der Grundlage von Blockerapproximationen ergeben. Obwohl die Ergebnisse einen gewissen Ungenauigkeitsfehler enthalten, welcher auch dargestellt und diskutiert wird, zeigt sich, dass eine weitere Traversierungsbeschleunigung von bis zu 300% gegenüber der Basisstruktur erreicht wird. Als Erweiterung zu diesem Ansatz wird die repräsentative Kandidatenvorberechnung demonstriert, welche verwendet wird, um die indirekte Lichtberechnung durch die Integration von kaum wahrnehmbaren Bildfehlern signifikant zu beschleunigen. Schließlich werden Techniken vorgeschlagen und bewertet, die auf zweistufigen Strukturen und einer Nutzungsheuristik basieren. Diese reduzieren den Speicherverbrauch und die Approximationsfehler bei Aufrechterhaltung des Geschwindigkeitsgewinns und ermöglichen zusätzlich weitere Möglichkeiten mit Objektinstanziierungen und starren Transformationen.
Alle Beschleunigungs- und Speicherwerte sowie die Näherungsfehler werden gemessen, dargestellt und diskutiert. Insgesamt zeigt sich, dass durch den Line Space eine deutliche Erhöhung der Raytracing Leistung auf Kosten eines höheren Speicherverbrauchs und möglicher Annäherungsfehler erreicht wird. Die vorgestellten Ergebnisse zeigen damit die Leistungsfähigkeit des kombinierten Ansatzes und eröffnen weitere Möglichkeiten für zukünftige Arbeiten.
Seit der Bologna-Reform wird von Bund und Ländern eine kontinuierliche Verbesserung der Qualität des Unterrichts in der Schule, die häufig mit der Professionalisierung der zukünftigen Lehrer und der Lehramtsausbildung verbunden wird, angestrebt. Die Qualität des Unterrichts wird mit der Professionalisierung der angehenden Lehrer und der Lehramtsausbildung verbunden. In den meisten Studien zur Qualitätsverbesserung erfolgt die Betrachtung überwiegend aus universitärer Sicht und selten auf das Unterrichtsfach Sport bezogen. An diesen beiden Punkten knüpft die qualitative Studie an und führt zu der zentralen Fragestellung: Bestehen Unterschiede in den Sichtweisen von Lehrenden und Lernenden zur Professionalisierung von Sportlehrkräften zu den einzelnen Ausbildungsphasen in Rheinland-Pfalz?
Mithilfe von 101 Leitfadeninterviews und der Auswertung nach der Grounded Theory kann diese Ausgangsfrage gezielt beantwortet werden. Befragt werden Lehrende der Universitäten, der staatlichen Studienseminare und der Schule sowie Lernende, dazu zählen Referendare/innen sowie Studierende. Im Verlauf der Studie kristallisiert sich in allen Personengruppen einheitlich der „fehlende Schulbezug“ als Schlüsselelement (Kernkategorie) in der ersten und zweiten Ausbildungsphase heraus. Die Interviewten, die verschiedenen Schulformen angehören, geben diesbezüglich konkrete, sportspezifische und teilweise fächerübergreifende Optimierungsvorschläge. Ein Schwerpunkt bildet dabei, frühzeitig den Bezug zum Schulalltag herzustellen und gleichzeitig Unterrichtserfahrungen mit schulischen Lerngruppen zu sammeln, um ihre unterschiedlichen motorischen Fähigkeiten und Fertigkeiten kennenzulernen. Die Verbesserungsansätze betreffen die universitäre Phase und die Ausbildungszeit in den Studienseminaren und Schulen, wobei die Beteiligten eine intensivere Vernetzung der einzelnen Institutionen für nötig erachten. An einer gemeinsamen, kontinuierlichen Zusammenarbeit zur Professionalisierung in der Sportlerausbildung und somit der Optimierung der Sportlehrerausbildung ist allen Beteiligten gelegen.