Innovative Homogeneous and Heterogeneous Systems for Electrochemically Generated Luminescence Investigations: Towards One-Dimensional ECL

My research PhD work is focused on the Electrochemically Generated Luminescence (ECL) investigation of several different homogeneous and heterogeneous systems. ECL is a redox induced emission, a process whereby species, generated at electrodes, undergo a high-energy electron transfer reaction to form excited states that emit light. Since its first application, the ECL technique has become a very powerful analytical tool and has widely been used in biosensor transduction. ECL presents an intrinsically low noise and high sensitivity; moreover, the electrochemical generation of the excited state prevents scattering of the light source: for all these characteristics, it is an elective technique for ultrasensitive immunoassay detection. The majority of ECL systems involve species in solution where the emission occurs in the diffusion layer near to the electrode surface. However, over the past few years, an intense research has been focused on the ECL generated from species constrained on the electrode surface. The aim of my work is to study the behavior of ECL-generating molecular systems upon the progressive increase of their spatial constraints, that is, passing from isolated species in solution, to fluorophores embedded within a polymeric film and, finally, to patterned surfaces bearing “one-dimensional” emitting spots. In order to describe these trends, I use different “dimensions” to indicate the different classes of compounds. My thesis was mostly developed in the electrochemistry group of Bologna with the supervision of Prof Francesco Paolucci and Dr Massimo Marcaccio. With their help and also thanks to their long experience in the molecular and supramolecular ECL fields and in the surface investigations using scanning probe microscopy techniques, I was able to obtain the results herein described. Moreover, during my research work, I have established a new collaboration with the group of Nanobiotechnology of Prof. Robert Forster (Dublin City University) where I spent a research period. Prof. Forster has a broad experience in the biomedical field, especially he focuses his research on film surfaces biosensor based on the ECL transduction. This thesis can be divided into three sections described as follows: (i) in the fist section, homogeneous molecular and supramolecular ECL-active systems, either organic or inorganic species (i.e., corannulene, dendrimers and iridium metal complex), are described. Driving force for this kind of studies includes the search for new luminophores that display on one hand higher ECL efficiencies and on the other simple mechanisms for modulating intensity and energy of their emission in view of their effective use in bioconjugation applications. (ii) in the second section, the investigation of some heterogeneous ECL systems is reported. Redox polymers comprising inorganic luminophores were described. In such a context, a new conducting platform, based on carbon nanotubes, was developed aimed to accomplish both the binding of a biological molecule and its electronic wiring to the electrode. This is an essential step for the ECL application in the field of biosensors. (iii) in the third section, different patterns were produced on the electrode surface using a Scanning Electrochemical Microscopy. I developed a new methods for locally functionalizing an inert surface and reacting this surface with a luminescent probe. In this way, I successfully obtained a locally ECL active platform for multi-array application.

Homogeneous analysis of a sample of Open Clusters in the context of the BOCCE project and the Gaia-ESO Survey

The open clusters (OC) are gravitationally bound systems of a few tens or hundreds of stars. In our Galaxy, the Milky Way, we know about 3000 open clusters, of very different ages in the range of a few millions years to about 9 Gyr. OCs are mainly located in the Galactic thin disc, with distances from the Galactic centre in the range 4-22 kpc and a height scale on the disc of about 200 pc. Their chemical properties trace those of the environment in which they formed and the metallicity is in the range -0.5<[Fe/H]<+0.5 dex. Through photometry and spectroscopy it is possible to study relatively easily the properties of the OCs and estimate their age, distance, and chemistry. For these reasons they are considered primary tracers of the chemical properties and chemical evolution of the Galactic disc. The main subject of this thesis is the comprehensive study of several OCs. The research embraces two different projects: the Bologna Open Cluster Chemical Evolution project (BOCCE) and the Gaia-ESO Survey. The first is a long-term programme, aiming at studying the chemical evolution of the Milky Way disc by means of a homogeneous sample of OCs. The latter is a large public spectroscopy survey, conducted with the high-resolution spectrograph FLAMES@VLT and targeting about 10^5 stars in different part of the Galaxy and 10^4 stars in about 100 OCs. The common ground between the two projects is the study of the properties of the OCs as tracers of the disc's characteristics. The impressive scientific outcome of the Gaia-ESO Survey and the unique framework of homogeneity of the BOCCE project can propose, especially once combined together, a much more accurate description of the properties of the OCs. In turn, this will give fundamental constraints for the interpretation of the properties of the Galactic disc.

Numerical study of homogeneous and heterogeneous crystal nucleation in colloidal systems

Im Rahmen dieser Arbeit wurden Computersimulationen von Keimbildungs- und Kris\-tallisationsprozessen in rnkolloidalen Systemen durchgef\"uhrt. rnEine Kombination von Monte-Carlo-Simulationsmethoden und der Forward-Flux-Sampling-Technik wurde rnimplementiert, um die homogene und heterogene Nukleation von Kristallen monodisperser Hart\-kugeln zu untersuchen. rnIm m\"a\ss{ig} unterk\"uhlten Bulk-Hartkugelsystem sagen wir die homogenen Nukleationsraten voraus und rnvergleichen die Resultate mit anderen theoretischen Ergebnissen und experimentellen Daten. rnWeiterhin analysieren wir die kristallinen Cluster in den Keimbildungs- und Wachstumszonen, rnwobei sich herausstellt, dass kristalline Cluster sich in unterschiedlichen Formen im System bilden. rnKleine Cluster sind eher l\"anglich in eine beliebige Richtung ausgedehnt, w\"ahrend gr\"o\ss{ere} rnCluster kompakter und von ellipsoidaler Gestalt sind. rn rnIm n\"achsten Teil untersuchen wir die heterogene Keimbildung an strukturierten bcc (100)-W\"anden. rnDie 2d-Analyse der kristallinen Schichten an der Wand zeigt, dass die Struktur der rnWand eine entscheidende Rolle in der Kristallisation von Hartkugelkolloiden spielt. rnWir sagen zudem die heterogenen Kristallbildungsraten bei verschiedenen \"Ubers\"attigungsgraden voraus. rnDurch Analyse der gr\"o\ss{ten} Cluster an der Wand sch\"atzen wir zus\"atzlich den Kontaktwinkel rnzwischen Kristallcluster und Wand ab. rnEs stellt sich heraus, dass wir in solchen Systemen weit von der Benetzungsregion rnentfernt sind und der Kristallisationsprozess durch heterogene Nukleation stattfindet. rn rnIm letzten Teil der Arbeit betrachten wir die Kristallisation von Lennard-Jones-Kolloidsystemen rnzwischen zwei ebenen W\"anden. rnUm die Erstarrungsprozesse f\"ur ein solches System zu untersuchen, haben wir eine Analyse des rnOrdnungsparameters f\"ur die Bindung-Ausrichtung in den Schichten durchgef\"urt. rnDie Ergebnisse zeigen, dass innerhalb einer Schicht keine hexatische Ordnung besteht, rnwelche auf einen Kosterlitz-Thouless-Schmelzvorgang hinweisen w\"urde. rnDie Hysterese in den Erhitzungs-Gefrier\-kurven zeigt dar\"uber hinaus, dass der Kristallisationsprozess rneinen aktivierten Prozess darstellt.

Learning with Kernels on Graphs: DAG-based kernels, data streams and RNA function prediction.

In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.

Operating System Contribution to Composable Timing Behaviour in High-Integrity Real-Time Systems

The development of High-Integrity Real-Time Systems has a high footprint in terms of human, material and schedule costs. Factoring functional, reusable logic in the application favors incremental development and contains costs. Yet, achieving incrementality in the timing behavior is a much harder problem. Complex features at all levels of the execution stack, aimed to boost average-case performance, exhibit timing behavior highly dependent on execution history, which wrecks time composability and incrementaility with it. Our goal here is to restitute time composability to the execution stack, working bottom up across it. We first characterize time composability without making assumptions on the system architecture or the software deployment to it. Later, we focus on the role played by the real-time operating system in our pursuit. Initially we consider single-core processors and, becoming less permissive on the admissible hardware features, we devise solutions that restore a convincing degree of time composability. To show what can be done for real, we developed TiCOS, an ARINC-compliant kernel, and re-designed ORK+, a kernel for Ada Ravenscar runtimes. In that work, we added support for limited-preemption to ORK+, an absolute premiere in the landscape of real-word kernels. Our implementation allows resource sharing to co-exist with limited-preemptive scheduling, which extends state of the art. We then turn our attention to multicore architectures, first considering partitioned systems, for which we achieve results close to those obtained for single-core processors. Subsequently, we shy away from the over-provision of those systems and consider less restrictive uses of homogeneous multiprocessors, where the scheduling algorithm is key to high schedulable utilization. To that end we single out RUN, a promising baseline, and extend it to SPRINT, which supports sporadic task sets, hence matches real-world industrial needs better. To corroborate our results we present findings from real-world case studies from avionic industry.

Tridiagonal Reproducing Kernels and Subnormality

We consider analytic reproducing kernel Hilbert spaces H with orthonormal bases of the form {(a(n) + b(n)z)z(n) : n >= 0}. If b(n) = 0 for all n, then H is a diagonal space and multiplication by z, M-z, is a weighted shift. Our focus is on providing extensive classes of examples for which M-z is a bounded subnormal operator on a tridiagonal space H where b(n) not equal 0. The Aronszajn sum of H and (1 - z)H where H is either the Hardy space or the Bergman space on the disk are two such examples.

Calibration of a portal imaging device for high-precision dosimetry: a Monte Carlo study

Today electronic portal imaging devices (EPID's) are used primarily to verify patient positioning. They have, however, also the potential as 2D-dosimeters and could be used as such for transit dosimetry or dose reconstruction. It has been proven that such devices, especially liquid filled ionization chambers, have a stable dose response relationship which can be described in terms of the physical properties of the EPID and the pulsed linac radiation. For absolute dosimetry however, an accurate method of calibration to an absolute dose is needed. In this work, we concentrate on calibration against dose in a homogeneous water phantom. Using a Monte Carlo model of the detector we calculated dose spread kernels in units of absolute dose per incident energy fluence and compared them to calculated dose spread kernels in water at different depths. The energy of the incident pencil beams varied between 0.5 and 18 MeV. At the depth of dose maximum in water for a 6 MV beam (1.5 cm) and for a 18 MV beam (3.0 cm) we observed large absolute differences between water and detector dose above an incident energy of 4 MeV but only small relative differences in the most frequent energy range of the beam energy spectra. It is shown that for a 6 MV beam the absolute reference dose measured at 1.5 cm water depth differs from the absolute detector dose by 3.8%. At depth 1.2 cm in water, however, the relative dose differences are almost constant between 2 and 6 MeV. The effects of changes in the energy spectrum of the beam on the dose responses in water and in the detector are also investigated. We show that differences larger than 2% can occur for different beam qualities of the incident photon beam behind water slabs of different thicknesses. It is therefore concluded that for high-precision dosimetry such effects have to be taken into account. Nevertheless, the precise information about the dose response of the detector provided in this Monte Carlo study forms the basis of extracting directly the basic radiometric quantities photon fluence and photon energy fluence from the detector's signal using a deconvolution algorithm. The results are therefore promising for future application in absolute transit dosimetry and absolute dose reconstruction.

Development of a physically-based method for delineation of hydrologically homogeneous regions and flood quantile estimation in ungauged basins via the index flood method

Regional flood frequency techniques are commonly used to estimate flood quantiles when flood data is unavailable or the record length at an individual gauging station is insufficient for reliable analyses. These methods compensate for limited or unavailable data by pooling data from nearby gauged sites. This requires the delineation of hydrologically homogeneous regions in which the flood regime is sufficiently similar to allow the spatial transfer of information. It is generally accepted that hydrologic similarity results from similar physiographic characteristics, and thus these characteristics can be used to delineate regions and classify ungauged sites. However, as currently practiced, the delineation is highly subjective and dependent on the similarity measures and classification techniques employed. A standardized procedure for delineation of hydrologically homogeneous regions is presented herein. Key aspects are a new statistical metric to identify physically discordant sites, and the identification of an appropriate set of physically based measures of extreme hydrological similarity. A combination of multivariate statistical techniques applied to multiple flood statistics and basin characteristics for gauging stations in the Southeastern U.S. revealed that basin slope, elevation, and soil drainage largely determine the extreme hydrological behavior of a watershed. Use of these characteristics as similarity measures in the standardized approach for region delineation yields regions which are more homogeneous and more efficient for quantile estimation at ungauged sites than those delineated using alternative physically-based procedures typically employed in practice. The proposed methods and key physical characteristics are also shown to be efficient for region delineation and quantile development in alternative areas composed of watersheds with statistically different physical composition. In addition, the use of aggregated values of key watershed characteristics was found to be sufficient for the regionalization of flood data; the added time and computational effort required to derive spatially distributed watershed variables does not increase the accuracy of quantile estimators for ungauged sites. This dissertation also presents a methodology by which flood quantile estimates in Haiti can be derived using relationships developed for data rich regions of the U.S. As currently practiced, regional flood frequency techniques can only be applied within the predefined area used for model development. However, results presented herein demonstrate that the regional flood distribution can successfully be extrapolated to areas of similar physical composition located beyond the extent of that used for model development provided differences in precipitation are accounted for and the site in question can be appropriately classified within a delineated region.

Conformationally homogeneous heterocyclic pseudotetrapeptides as three-dimensional scaffolds for rational drug design: receptor-selective somatostatin analogues

A would-be amide: A 1,4-disubstituted 1,2,3-triazole was used as a surrogate for a trans amide bond to create a library of 16 diastereomeric pseudotetrapeptides as beta-turn mimetics. High-resolution structural analysis indicated that these scaffolds adopt distinct, rigid, conformationally homogeneous beta-turn-like structures (see example), some of which bind somatostatin receptor subtypes selectively, and some of which show broad-spectrum activity.