Durch alternierende oder simultane Plasmapolymerisation und Farbstoffsublimation wurden Plasmapolymerschichten mit eingelagerten Farbstoffmolekülen hergestellt. Als Farbstoff wurde Rhodamin 6G verwendet. Die Absorptions- und Fluoreszenzcharakteristika der Schichten wurden untersucht und mit denen einfacher Farbstoffschichten verglichen. Dabei wurde die Menge der eingelagerten Farbstoffmoleküle variiert. Es zeigt sich, daß sich die Absorptionsbande des eingelagerten Farbstoffs bei den unterschiedlichen Schichten kaum verändert. Die Fluoreszenzspektren der Schichten mit wenigen eingelagerten Farbstoffmolekülen zeigen dasgleiche Verhalten wie Rhodamin 6G in Lösung. Mit steigender Farbstoffmenge wird die Fluoreszenzbande rotverschoben und es entsteht eine weitere Fluoreszenzbande. Diese wird mit Hilfe eines sequentiellen Energietransfers zu modifizierten Molekülen beschrieben. Mit Hilfe der zeitaufgelösten Fluoreszenzspektroskopie konnte der zeitliche Verlauf der Fluoreszenzintensität gemessen werden. Dabei ist der Fluoreszenzzerfall deutlich nicht-exponentiell. Die Zerfallskurven wurden mit einer gestreckten Exponentialfunktion angepaßt.

The present study involves the determination of traces of thallium and mercury in aqueous solution by forming ion-association complexes of these metals with rhodamine 6G (R6G) in the presence of iodide. Thallium(lll) and mercury(Il) are able to quench the fluorescence of R6G in the presence of iodide by forming ion—association complexes, and the degree of quenching correlates with the thallium(III) or mercury(II) concentrations . By using this method, the minimum amount of thallium- (III) that can be determined in aqueous solutions is approximately 4.00 X 10-6m, while the minimum amount of mercury(II) is approximately 3.00 X 10-6m. Thallium(I) cannot be determined by this method because it is not possible to form ion-association complexes under similar experimental conditions therefore, this method can be used to differentiate between Tl(I) and Tl(III) in aqueous solution. To elucidate the composition of the ion-association complexes in aqueous solutions two spectrophotometric methods are used: the mole-ratio method and the continuous- variation method. The experimental results seem to indicate that two complexes are formed for the mercury(II)-R6G-iodide system. The empirical compositions of these complexes are tentatively determined to be [(R6G)HgI3] and [(R6G)2HgI4).

We address the problem of all-pairs shortest time communication of messages in futuregeneration 6G networks by modeling the highly dynamic characteristics of the network using a temporal graph. Based on this model, an elegant technique is proposed to devise an algorithm for finding the all-pairs shortest time paths in the temporal graph that can be used for all-pairs internodes communication of messages in the network. The proposed algorithm basically involves computations similar to only two matrix multiplication steps, once in the forward direction and then in the backward direction.

Future 6G wireless communications network will increase the data capacity to unprecedented numbers and thus empower the deployment of new real-time applications. Millimeter-Wave (mmWave) band and Massive MIMO are considered as two of the main pillars of 6G to handle the gigantic influx in data traffic and number of mobile users and IoT devices. The small wavelengths at these frequencies mean that more antenna elements can be placed in the same area. Thereby, high spatial processing gains are achievable that can theoretically compensate for the higher isotropic path loss. The propagation characteristics at mmWave band, create sparse channels in typical scenarios, where only few paths convey significant power. Considering this feature, Hybrid (analog-digital) Beamforming introduces a new signal processing framework which enables energy and cost-efficient implementation of massive MIMO with innovative smart arrays. In this setup, the analog beamalignment via beam selection in link access phase, is the critical performance limiting step. Considering the variable operating condition in mmWave channels, a desirable solution should have the following features: efficiency in training (limited coherence time, delay constraints), adaptivity to channel conditions (large SNR range) and robustness to realized channels (LOS, NLOS, Multipath, non-ideal beam patterns). For the link access task, we present a new energy-detection framework based on variable length channel measurements with (orthogonal) beam codebooks. The proposed beam selection technique denoted as composite M-ary Sequential Competition Test (SCT) solves the beam selection problem when knowledge about the SNR operating point is not available. It adaptively changes the test length when the SNR varies to achieve an essentially constant performance level. In addition, it is robust to non-ideal beam patterns and different types of the realized channel. Compared to the conventional fixed length energy-detection techniques, the SCT can increase the training efficiency up to two times while reducing the delay if the channel condition is good. Having the flexibility to allocate resources for channel measurements through different beams adaptively in time, we improve the SCT to eliminate unpromising beams from the remaining candidate set as soon as possible. In this way, the Sequential Competition and Elimination Test (SCET) significantly further reduces training time by increasing the efficiency. The developed ideas can be applied with different codebook types considered for practical applications. The reliable performance of the beam selection technique is evident through experimental evaluation done using the state-of-the-art test-bed developed at the Vodafone Chair that combines a Universal Software Radio Peripheral (USRP) based platform with mmWave frontends.

Investigation of tumor growth has traditionally been studied focusing only on the cancer cells. However, tumors consist of a complex tissue organization where heterotypic signaling occurs between different cell types. The cross-talk between tumor cells and other surrounding cell types may ultimately prove to be as important for the tumor cell behavior as the internal signaling cascades in the tumor cell itself.Myeloid cells, such as granulocytes and monocytes, and thrombocytes play an important role in the tumor tissue, as a tumor can be compared to a wound healing process without the normal regulation mechanisms. Platelets are thought to facilitate tumor cell extravasation by binding to the tumor cell and recruiting myeloid cells that secrete factors aiding tumor migration through the endothelial cells. Studying the content of granules and vesicles of the platelets and myeloid cells can provide important knowledge about how the tumor interactions are mediated and which key proteins that controls these processes.Serglycin is an intracellular proteoglycan that attaches chains of negatively charged glycosaminoglycans. It is thought to have a function in retaining and storing proteins in hematipoietic cells. In this project the impact of the loss of serglycin on platelets and myeloid cells was investigated, using a spontaneous insulinoma serglycin knockout mouse model. The results suggests that serglycin does not affect the amount of neutrophil granulocytes and monocytes in peripheral blood, nor does it seem to affect the amount of platelets sequestered to the tumor tissue. A co-staining for platelets and MMP9 positive granulocytes was also performed in order to assess if granulocyte-platelet interactions in the tumor were affected by loss of serglycin. Interactions between these cells were observed in both genotypes. Von Willebrand factor levels in the tumor tissue also remained unchanged upon loss of serglycin. However, preliminary experiments indicated that serglycin seems to play a role in the intracellular amounts of vimentin and VEGFB in undifferentiated primary bone marrow derived monocytes.

This diploma thesis was focused on study of barrier and transport properties of selected polyelectrolytes in hydrogel matrices by using diffusion techniques. The study of these properties was performed in horizontal diffusion cells where is observed the change in diffusion probe concentration over time. Diffusion experiments were performed on an agarose hydrogel with the addition of alginate, hyaluronic acid, polystyrene sulfonate, humic acids and as a model probe rhodamine 6G was used. Important parts of this thesis are also the methods which characterize the substances and hydrogel matrices such as rheology and potentiometric titration. The main aim of this diploma thesis was to investigate the effect of interactions between passing model dye (rhodamine 6G) and the appropriate gel (agarose + polyelectrolyte) on the fundamental diffusion parameters (effective diffusion coefficient, lag time, etc.).

Yes / As 5th Generation research reaches the twilight, the research community must go beyond 5G and look towards the 2030 connectivity landscape, namely 6G. In this context, this work takes a step towards the 6G vision by proposing a next generation communication platform, which aims to extend the rigid coverage area of fixed deployment networks by considering virtual mobile small cells (MSC) that are created on demand. Relying on emerging computing paradigms such as NFV (Network Function Virtualization) and SDN (Software Defined Networking), these cells can harness radio and networking capability locally reducing protocol signalling latency and overhead. These MSCs constitute an intelligent pool of networking resources that can collaborate to form a wireless network of MSCs providing a communication platform for localized, ubiquitous and reliable connectivity. The technology enablers for implementing the MSC concept are also addressed in terms of virtualization, lightweight wireless security, and energy efficient RF. The benefits of the MSC architecture towards reliable and efficient cell-offloading are demonstrated as a use-case. / This project has received funding from the European Union's H2020 research and innovation program under grant agreement H2020-MCSAITN- 2016-SECRET 722424 [2].

Driven by the surging need for seamless connectivity, research in the wireless communication area has dramatically evolved over the years to meet the increasing demand for data rate and seamless coverage. Such evolvement concurs with a notable increase in data traffic and the widespread of data-hungry devices, thereby inflicting stringent requirements on terrestrial networks. Despite the tremendous advances achieved through the past generations of wireless systems, almost half of the world's population remains unconnected, leading to an accentuated digital divide problem. Therefore, this work invigorates a new connectivity solution that integrates aerial and terrestrial communications with a high-altitude platform station (HAPS) to promote a sustainable connectivity landscape. The connectivity solution adopted in this thesis specifically integrates terrestrial base stations with hot-air balloons under the framework of a cloud-enabled HAPS via a data-sharing fronthauling strategy. The aerial (hot-air balloons) and terrestrial base stations, grouped into disjoint clusters, coordinate their mutual transmission to serve aerial (i.e., drones) and terrestrial users. This work studies the downlink communication from the cloud-enabled HAPS to the aerial and terrestrial users under practical system considerations, namely the limited transmit power and the limited-capacity fronthaul link, per-base station. To this end, the first part of the thesis devises a specific optimization problem that maximizes the network sum-rate while accounting for system design constraints to determine the user association strategy, i.e., user to terrestrial clusters or user to air clusters, and the associated beamforming vectors. The second part of the thesis, then, designs a different resource allocations optimization problem that accounts for the fairness among the users, thus adopting a proportionally fair scheduling scheme to assign users on frequency tones to maximize the log of the long-term average rate. On this account, the work solves a handful of non-convex intricate optimization problems using techniques from optimization theory, namely, fractional programming and $\ell_0$-norm approximation. The work consequently outlines the gains realized by providing on-demand coverage in crowded and unserved areas. Moreover, the thesis illustrates the benefits of coordinating the operations of aerial and terrestrial base stations for interference management, load-balancing, and fairness measures.

Managing a system of network services is a complex and large-scale task that often lacks a trivial optimal solution. Deep Reinforcement Learning (RL) has shown great potential in being able to solve these tasks in static settings. However, in practice, the RL agents struggle to generalize their control policies enough to work in more dynamic real-world environments. To achieve a generality between environments, multiple contributions are made by this thesis. Low-level metrics are collected from each node in the system to help explain changes in the end-to-end delay of the system. To achieve generality in its control policy, more ways to observe and understand the dynamic environment and how it changes are provided to the RL agent by introducing the end-to-end delay of each service in the system to its observation space. Another approach to achieving more generality in RL policies is Model-Agnostic Meta-Learning (MAML), a type of Meta-Learning approach where instead of learning to solve a specific task, the model learns to learn how to quickly solve a new task based on prior knowledge. Results show that low-level metrics yield a much greater generality when helping to explain the delay of a system. Applying MAML to the problem is beneficial in adding generality to a learned RL policy and making the adaptation to a new task faster. If the RL agent can observe the changes to the underlying dynamics of the environment between tasks by itself, the policy can achieve this generality by itself without the need for a more complex method. However, if acquiring or observing the necessary data is too expensive or complex, switching to a Meta-Learning approach might be beneficial to increase generality. / Hanteringen av ett system med nätverksstjänster är ett komplext och stor skaligt problem där den optimal lösning inte är trivial. Djup förstärkningsinlärning har visat stor potential i att kunna lösa dessa problem i statiska miljöer. Dock är det svårt att generalisera lösningarna tillräckligt för att fungera i mer komplicerade och realistiska dynamiska miljöer. För att uppnå mer generella lösningar mellan miljöer presenterar denna masteruppsats flera möjliga lösningar. Lågnivåmetrik samlas in från varje nod i systemet för att hjälpa förklara skillnader i den totala responstiden för varje tjänst i systemet. För att generalisera förstärkningsinlärningsmodellen kan den förses med fler sätt att observera miljön, och därmed lära sig förstå hur den dynamiska miljön förändras. En annan metod för att uppnå mer generalitet inom förstärkningsinlärning är Model-Agnostic Meta-Learning (MAML), en typ av Meta-Learning där istället för att lära sig att lösa en specifik uppgift, modellen lär sig att lära sig att snabbt lösa en ny uppgift baserat på sin tidigare kunskap. Resultaten visar att lågnivåmetriken leder till en mycket högre generalitet i att hjälpa till att förklara responstiden av ett system. Att applicera MAML till problemet hjälper att bidra med generalitet till en förstärkningsinlärningsmodell och gör anpassningen till en ny uppgift snabbare. Om modellen själv kan observera ändringarna i underliggande dynamiken bakom miljön mellan uppgifter kan den uppnå mer generalitet utan ett behov av en mer komplex metod som MAML. Däremot, om det är svårt eller dyrt att få tag på eller observera den nödvändiga datan, kan ett byte till en Meta-Learning baserad metod vara mer fördelaktig för att öka generaliteten.

Im Mittelpunkt dieser Arbeit steht die selektive Funktionalisierung von Siliziumoxidnanostrukturen auf alkyl-passivierten Siliziumoberflächen welche durch rasterkraftmikroskopisch induzierte lokale anodische Oxidation (LAO) erzeugt werden. Bei der gezielten Immobilisierung von funktionalen Molekülen auf den Strukturen werden zwei verschiedene Routen verfolgt – Anbindung von ionischen Farbstoffen über elektrostatische Wechselwirkungen sowie stufenweise kovalente chemische Anbindung von bi-funktionalen Verbindermolekülen und Farbstoffen. Eine Untersuchung der hergestellten funktionalen Strukturen erfolgt mittels Rasterkraftmikroskopie, Raster-Kelvin-Mikroskopie sowie zeitaufgelöster Fluoreszenzmikroskopie und-spektroskopie. Durch zwei unabhängige Methoden kann gezeigt werden dass die Ladungen im lokalen Oxide vergleichsweise stabil sind und die elektrostatische Anbindung somit auch noch nach Tagen möglich sein sollte. Das Verhalten der elektrostatisch angebundenen Farbstoffe hängt stark von deren Art ab. Während es bei Rhodamin 6G nur zu einer minimalen spektralen Änderung im Vergleich zur Lösung kommt so zeigen spermin-funktionalisierte Perylenbisimidfarbstoffe eine deutliche H-Aggregation und Ausbildung von Excimerzuständen. Diese Zustände sind eindeutig thermisch aktiviert und zeigen eine wesentlich höhere Aktivierungsenergie als bei allen anderen bisher untersuchten Perylenaggregaten sowie eine Hysterese bei Temperaturveränderung. Die physikalische Ursache für dieses Phänomen liegt allem Anschein nach in der elektrostatischen Anbindung selbst welche ein instabiles Gleichgewicht mit der Wechselwirkung der Moleküle untereinander bildet. Eine geordnete kovalente Anbindung von funktionalen Silanmolekülen an die mittels LAO erzeugten Strukturen erfordert sehr definierte Prozessparameter. Die spektroskopische Untersuchung von an die funktionalen Silane chemisch angebundenen Fluoresceinfarbstoffen lässt indirekte Schlüsse auf deren Belegungsdichte und damit die Qualität der Silanmonolage zu.