Investigations of cooperative interactions in template induced crystallization processes and kinetic studies of nucleation and growth by small-angle neutron scattering

Zusammenfassung Um zu einem besseren Verständnis des Prozesses der Biomineralisation zu gelangen, muss das Zusammenwirken der verschiedenen Typen biologischer Makromoleküle, die am Keimbildungs- und Wachstumsprozess der Minerale beteiligt sind, berücksichtigt werden. In dieser Arbeit wird ein neues Modellsystem eingeführt, das aus einem SAM (self-assembled monolayer) mit verschiedenen Funktionalitäten und unterschiedlichen, gelösten Makromolekülen besteht. Es konnte gezeigt werden, dass die Kristallisation von Vaterit (CaCO3) sowie Strontianit (SrCO3) Nanodrähten der Präsenz von Polyacrylat in Kooperation mit einer COOH-funktionalisierten SAM-Oberfläche zugeschrieben werden kann. Die Kombination bestehend aus einer polaren SAM-Oberfläche und Polyacrylat fungiert als Grenzfläche für die Struktur dirigierende Kristallisation von Nanodraht-Kristallen. Weiter konnte gezeigt werden, dass die Phasenselektion von CaCO3 durch die kooperative Wechselwirkung zwischen einer SAM-Oberfläche und einem daran adsorbierten hb-Polyglycerol kontrolliert wird. Auch die Funktionalität einer SAM-Oberfläche in Gegenwart von Carboxymethyl-cellulose übt einen entscheidenden Einfluss auf die Phasenselektion des entstehenden Produktes aus. In der vorliegenden Arbeit wurden Untersuchungen an CaCO3 zur homogenen Keimbildung, zur Nukleation in Gegenwart eines Proteins sowie auf Kolloiden, die als Template fungieren, mittels Kleinwinkel-Neutronenstreuung durchgeführt. Die homogene Kristallisation in wässriger Lösung stellte sich als ein mehrstufiger Prozess heraus. In Gegenwart des Eiweißproteins Ovalbumin konnten drei Phasen identifiziert werden, darunter eine anfänglich vorhandene amorphe sowie zwei kristalline Phasen.

A novel map-matching procedure for low-sampling GPS data with applications to traffic flow analysis

An extensive sample (2%) of private vehicles in Italy are equipped with a GPS device that periodically measures their position and dynamical state for insurance purposes. Having access to this type of data allows to develop theoretical and practical applications of great interest: the real-time reconstruction of traffic state in a certain region, the development of accurate models of vehicle dynamics, the study of the cognitive dynamics of drivers. In order for these applications to be possible, we first need to develop the ability to reconstruct the paths taken by vehicles on the road network from the raw GPS data. In fact, these data are affected by positioning errors and they are often very distanced from each other (~2 Km). For these reasons, the task of path identification is not straightforward. This thesis describes the approach we followed to reliably identify vehicle paths from this kind of low-sampling data. The problem of matching data with roads is solved with a bayesian approach of maximum likelihood. While the identification of the path taken between two consecutive GPS measures is performed with a specifically developed optimal routing algorithm, based on A* algorithm. The procedure was applied on an off-line urban data sample and proved to be robust and accurate. Future developments will extend the procedure to real-time execution and nation-wide coverage.

3D-Cryo-Elektronenmikroskopie des 4x6-Hämocyanins der Vogelspinne Eurypelma californicum unter Oxy- und Deoxybedingungen

Arthropodenhämocyanine und Molluskenhämocyanine, die extrazellulären Atmungsproteine der Arthropoden und Mollusken, unterscheiden sich grundsätzlich im Aufbau, besitzen aber ähnliche aktive Zentren, welche in ihrer oxydierten Form für die Blaufärbung der Hämocyanine verantwortlich sind. Sauerstoff wird im Bindungszentrum zwischen zwei, von sechs Histidinen ligandierten, Kupfer(I)Ionen gebunden. Arthropodenhämocyanine bauen sich artspezifisch aus 1, 2, 4, 6, oder 8 Hexameren mit D3-Symmetrie auf. Die Untereinheiten von je ca. 75 kDa falten sich in drei Domänen unterschiedlicher Funktionen. Der komplexe, hierarchische Zusammenbau der Arthropodenhämocyanine hängt von der Heterogenität der Untereinheiten ab. Die 7 verschieden Sequenzen des 4x6-Hämocyanins von Eurypelma californicum (EcHc) sind biochemisch in der Quartärstruktur lokalisiert. Bislang fehlte noch ein unabhängig erstelltes 3D-Modell der geometrischen Gesamtstruktur welche die hexamere und monomere Topographie eindeutig zeigt. Dessen Erstellung war Gegenstand dieser Arbeit, in Verbindung mit der Zielsetzung, die 3D-Rekonstruktion in den beiden extremen physiologischen Zuständen, mit und ohne gebundenen Sauerstoff, zu erzeugen. Dazu wurden in einer eigens entwickelten Atmosphären-Präparationskammer die Proteine in Lösung schockgefrorenen und mittels Cryo-3D-Elektronenmikroskopie gemessen. Aus den daraus gewonnen Projektionsbildern ließen sich mit der ”Single Particle Analyse“ die 3D-Informationen zurückberechnen. Die 3D-Rekonstruktionen wurden mit der publizierten Röntgenkristallstruktur des hexameren Referenz-Hämocyanins der Languste Panulirus interruptus verifiziert. Die Rekonstruktionen erlaubten die eindeutige Messung diverser in der Literatur diskutierter Parameter der Architektur des 4x6-EcHc und darüber hinaus weiterer geometrischer Parameter, welche hier erstmals veröffentlicht werden. SAXS-Daten sagen extreme Translationen und Rotationen von Teilquartärstrukturen zwischen oxy- und deoxy-EcHc voraus, was von den 3D-Rekonstruktionen der beiden Zustände nicht bestätigt werden konnte: Die 16 Å Rekonstruktion der Deoxyform weicht geometrisch nicht von der 21 Å Rekonstruktion der Oxyform ab. Die Einpassung der publizierten Röntgenstruktur der Untereinheit II des Hämocyanin des Pfeilschwanzkrebses Limulus polyphemus in die Rekonstruktionen unterstützt eine auf der hexameren Hierarchieebene lokalisierte Dynamik der Oxygenierung. Mittels Einpassung modellierter molekularer Strukturen der EcHc-Sequenzen konnte eine erste Vermutung zur Lokalisation der beiden zentralen Linker-Untereinheiten b und c des 4x6-Moleküls gemacht werden: Demnach würde Untereinheit b in den exponierten Hexameren des Moleküls liegen. Aussagen über die Quartärstrukturbindungen auf molekularer Ebene aufgrund der Einpassung modellierter molekularer Daten in die Rekonstruktionen sind als spekulativ einzustufen: a) Die Auflösung der Rekonstruktion ist verbesserungswürdig. b) Es gibt keine adäquate Vorlage für eine verlässliche Strukturvorhersage; die verschiedenen EcHc-Sequenzen liegen nur als Modellierung vor. c) Es wäre eine flexible Einpassung notwendig, um Ungenauigkeiten in den modellierten Strukturen durch Sekundärstrukturanpassung zu minimieren.

A clustering method for robust and reliable large scale functional and structural protein sequence annotation

Bioinformatics, in the last few decades, has played a fundamental role to give sense to the huge amount of data produced. Obtained the complete sequence of a genome, the major problem of knowing as much as possible of its coding regions, is crucial. Protein sequence annotation is challenging and, due to the size of the problem, only computational approaches can provide a feasible solution. As it has been recently pointed out by the Critical Assessment of Function Annotations (CAFA), most accurate methods are those based on the transfer-by-homology approach and the most incisive contribution is given by cross-genome comparisons. In the present thesis it is described a non-hierarchical sequence clustering method for protein automatic large-scale annotation, called “The Bologna Annotation Resource Plus” (BAR+). The method is based on an all-against-all alignment of more than 13 millions protein sequences characterized by a very stringent metric. BAR+ can safely transfer functional features (Gene Ontology and Pfam terms) inside clusters by means of a statistical validation, even in the case of multi-domain proteins. Within BAR+ clusters it is also possible to transfer the three dimensional structure (when a template is available). This is possible by the way of cluster-specific HMM profiles that can be used to calculate reliable template-to-target alignments even in the case of distantly related proteins (sequence identity < 30%). Other BAR+ based applications have been developed during my doctorate including the prediction of Magnesium binding sites in human proteins, the ABC transporters superfamily classification and the functional prediction (GO terms) of the CAFA targets. Remarkably, in the CAFA assessment, BAR+ placed among the ten most accurate methods. At present, as a web server for the functional and structural protein sequence annotation, BAR+ is freely available at http://bar.biocomp.unibo.it/bar2.0.

Essays on the Axiomatic Theory of Matching

This dissertation mimics the Turkish college admission procedure. It started with the purpose to reduce the inefficiencies in Turkish market. For this purpose, we propose a mechanism under a new market structure; as we prefer to call, semi-centralization. In chapter 1, we give a brief summary of Matching Theory. We present the first examples in Matching history with the most general papers and mechanisms. In chapter 2, we propose our mechanism. In real life application, that is in Turkish university placements, the mechanism reduces the inefficiencies of the current system. The success of the mechanism depends on the preference profile. It is easy to show that under complete information the mechanism implements the full set of stable matchings for a given profile. In chapter 3, we refine our basic mechanism. The modification on the mechanism has a crucial effect on the results. The new mechanism is, as we call, a middle mechanism. In one of the subdomain, this mechanism coincides with the original basic mechanism. But, in the other partition, it gives the same results with Gale and Shapley's algorithm. In chapter 4, we apply our basic mechanism to well known Roommate Problem. Since the roommate problem is in one-sided game patern, firstly we propose an auxiliary function to convert the game semi centralized two-sided game, because our basic mechanism is designed for this framework. We show that this process is succesful in finding a stable matching in the existence of stability. We also show that our mechanism easily and simply tells us if a profile lacks of stability by using purified orderings. Finally, we show a method to find all the stable matching in the existence of multi stability. The method is simply to run the mechanism for all of the top agents in the social preference.

Template-assisted patterning of functional polymers

In this thesis, anodic aluminum oxide (AAO) membranes, which provide well-aligned uniform mesoscopic pores with adjustable pore parameters, were fabricated and successfully utilized as templates for the fabrication of functional organic nanowires, nanorods and the respective well-ordered arrays. The template-assisted patterning technique was successfully applied for the realization of different objectives:rnHigh-density and well-ordered arrays of hole-conducting nanorods composed of cross-linked triphenylamine (TPA) and tetraphenylbenzidine (TPD) derivatives on conductive substrates like ITO/glass have been successfully fabricated. By applying a freeze-drying technique to remove the aqueous medium after the wet-chemical etching of the template, aggregation and collapsing of the rods was prevented and macroscopic areas of perfectly freestanding nanorods were feasible. Based on the hole-conducting nanorod arrays and their subsequent embedding into an electron-conducting polymer matrix via spin-coating, a novel routine concept for the fabrication of well-ordered all-organic bulk heterojunction for organic photovoltaic applications was successfully demonstrated. The increased donor/acceptor interface of the fabricated devices resulted in a remarkable increase of the photoluminescence quenching compared to a planar bilayer morphology. Further, the fundamental working principle of the templating approach for the solution-based all-organic photovoltaic device was demonstrated for the first time.rnFurthermore, in order to broaden the applicability of patterned surfaces, which are feasible via the template-based patterning of functional materials, AAO with hierarchically branched pores were fabricated and utilized as templates. By pursuing the common templating process hierarchically polymeric replicas, which show remarkable similarities with interesting biostructures, like the surface of the lotus leaf and the feet of a gecko, were successfully prepared.rnIn contrast to the direct infiltration of organic functional materials, a novel route for the fabrication of functional nanowires via post-modification of reactive nanowires was established. Therefore, reactive nanowires based on cross-linked pentafluorophenylesters were fabricated by utilizing AAO templates. The post-modification with fluorescent dyes was demonstrated. Furthermore, reactive wires were converted into well-dispersed poly(N-isopropylacrylamide) (PNIPAM) hydrogels, which exhibit a thermal-responsive reversible phase transition. The reversible thermal-responsible swelling of the PNIPAM nanowires exhibited a more than 50 % extended length than in the collapsed PNIPAM state. rnLast but not least, the shape-anisotropic pores of AAO were utilized to uniformly align the mesogens of a nematic liquid crystalline elastomer. Liquid crystalline nanowires with a narrow size distribution and uniform orientation of the liquid crystalline material were fabricated. It was shown that during the transition from the nematic to the isotropic phase the rod’s length shortened by roughly 40 percent. As such these liquid crystalline elastomeric nanowires may find application, as wire-shaped nanoactuators in various fields of research, like lab-on-chip systems, micro fluidics and biomimetics.rn

Kolloide und ihre Überstrukturen als Bausteine zur Herstellung funktioneller Materialien

In dieser Arbeit wird die Synthese von Polymerkolloiden mit unterschiedlichen Formen und Funktionalitäten sowie deren Verwendung zur Herstellung kolloidaler Überstrukturen beschrieben. Über emulgatorfreie Emulsionspolymerisation (SFEP) erzeugte monodisperse sphärische Kolloide dienen als Bausteine von Polymeropalen, die durch die Selbstorganisation dieser Kolloide über vertikale Kristallisation (mit Hilfe einer Ziehmaschine) oder horizontale Kristallisation (durch Aufschleudern oder Aufpipettieren) entstehen. Durch die Kontrolle der Kugelgröße über die Parameter der Emulsionspolymerisation sowie die Einstellung der Schichtdicke der Kolloidkristalle über die Anpassung der Kristallisationsparameter ist die Erzeugung von qualitativ hochwertigen Opalen mit definierter Reflektionswellenlänge möglich. Darüber hinaus kann die chemische und thermische Beständigkeit der Opale durch den Einbau von Vernetzern oder vernetzbaren Gruppen in die Polymere erhöht werden. Die Opalfilme können als wellenlängenselektive Reflektoren in auf Fluoreszenzkonzentratoren basierenden Solarzellensystemen eingesetzt werden, um Lichtverluste in diesen Systemen zu reduzieren. Sie können auch als Template für die Herstellung invertierter Opale aus verschiedenen anorganischen Oxiden (TiO2, Al2O3, ZnO) dienen. Über einen CVD-Prozess erzeugte ZnO-Replika besitzen dabei den Vorteil, dass sie nicht nur eine hohe optische Qualität sondern auch eine elektrische Leitfähigkeit aufweisen. Dies ermöglicht sowohl deren Einsatz als Zwischenreflektor in Tandemsolarzellen als auch die Herstellung hierarchischer Strukturen über die Elektroabscheidung von Nanokristallen. In einem weiteren Teil der Arbeit wird die Herstellung funktioneller formanisotroper Partikel behandelt. Durch die Entmischung von mit Monomer gequollenen vernetzten Partikeln in einer Saatpolymerisation sind mehrere Mikrometer große Kolloide zugänglich, die aus zwei interpenetrierenden Halbkugeln aus gleichen oder verschiedenen Polymeren bestehen. Dadurch sind unter anderem Glycidyl-, Alkin- und Carbonsäuregruppen in die eine oder die andere Halbkugel integrierbar. Diese funktionellen Gruppen erlauben die Markierung bestimmter Partikelhälften mit Farbstoffen, die Beschichtung von Partikelbereichen mit anorganischen Oxiden wie SiO2 sowie die Erzeugung amphiphiler formanisotroper Partikel, die sich an Grenzflächen ausrichten lassen. Das Synthesekonzept kann - ausgehend von mittels SFEP erzeugten stark vernetzten PMMA-Partikeln - auch auf kleine Kolloide mit Größen von mehreren hundert Nanometern übertragen werden.

IDACardOCR: App Android per la gestione di template di documenti di identità e l'acquisizione di dati anagrafici

Lo scopo di IDCardOCR è quello di permettere all'utente di acquisire i dati di una persona in formato strutturato eseguendo una semplice foto del suo documento di identità. I dati salvati saranno così a disposizione dell’utente in formato digitale. Permette, a differenze di altre applicazioni, la creazione di una maschera personalizzata dove è l’utente a decidere i dati da digitalizzare. Il riconoscimento ottico dei caratteri è implementato dal tool Tesseract-OCR Obiettivo della tesi è quello di approfondire lo studio dei sistemi di OCR e del loro funzionamento in ambiente Android, applicare tecniche di ritaglio e elaborazione delle immagini, approfondimento delle piattaforma di sviluppo. La tesi è cosi strutturata. Il primo capitolo contiene l’introduzione al problema, una panoramica sulle applicazioni esistenti e i motivi che ci hanno spinto ha scegliere la piattaforma di sviluppo Andriod. Il capitolo due tratta delle progettazione dell’applicazione attraverso diagrammi UML e introduce l’architettura del sistema. Il capitolo tre è incentrato sulla parte di sviluppo, infine nel quarto capitolo, si conclude la tesi con i risultati dei test effettuati e i possibili sviluppi futuri.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Metodi di map-matching per l'identificazione degli itinerari dei ciclisti

Negli ultimi anni si è assistito al considerevole aumento della disponibilità di dati GPS e della loro precisione, dovuto alla diffusione e all’evoluzione tecnologica di smartphone e di applicazioni di localizzazione. Il processo di map-matching consiste nell’integrare tali dati - solitamente una lista ordinata di punti, identificati tramite coordinate geografiche ricavate mediante un sistema di localizzazione, come il GPS - con le reti disponibili; nell’ambito dell’ingegneria dei trasporti, l’obiettivo è di identificare il percorso realmente scelto dall’utente per lo spostamento. Il presente lavoro si propone l’obiettivo di studiare alcune metodologie di map-matching per l’identificazione degli itinerari degli utenti, in particolare della mobilità ciclabile. Nel primo capitolo è esposto il funzionamento dei sistemi di posizionamento e in particolare del sistema GPS: ne sono discusse le caratteristiche, la suddivisione nei vari segmenti, gli errori di misurazione e la cartografia di riferimento. Nel secondo capitolo sono presentati i vari aspetti del procedimento di map-matching, le sue principali applicazioni e alcune possibili classificazioni degli algoritmi di map-matching sviluppati in letteratura. Nel terzo capitolo è esposto lo studio eseguito su diversi algoritmi di map-matching, che sono stati testati su un database di spostamenti di ciclisti nell’area urbana di Bologna, registrati tramite i loro smartphone sotto forma di punti GPS, e sulla relativa rete. Si analizzano altresì i risultati ottenuti in un secondo ambiente di testing, predisposto nell’area urbana di Catania, dove sono state registrate in modo analogo alcune tracce di prova, e utilizzata la relativa rete. La comparazione degli algoritmi è eseguita graficamente e attraverso degli indicatori. Vengono inoltre proposti e valutati due algoritmi che forniscono un aggiornamento di quelli analizzati, al fine di migliorarne le prestazioni in termini di accuratezza dei risultati e di costo computazionale.

Quantitative 1-Step DNA Methylation Analysis with Native Genomic DNA as Template

DNA methylation analysis currently requires complex multistep procedures based on bisulfite conversion of unmethylated cytosines or on methylation-sensitive endonucleases. To facilitate DNA methylation analysis, we have developed a quantitative 1-step assay for DNA methylation analysis.

Hierarchical clustering of flow cytometry data for the study of conventional central chondrosarcoma

We have investigated the use of hierarchical clustering of flow cytometry data to classify samples of conventional central chondrosarcoma, a malignant cartilage forming tumor of uncertain cellular origin, according to similarities with surface marker profiles of several known cell types. Human primary chondrosarcoma cells, articular chondrocytes, mesenchymal stem cells, fibroblasts, and a panel of tumor cell lines from chondrocytic or epithelial origin were clustered based on the expression profile of eleven surface markers. For clustering, eight hierarchical clustering algorithms, three distance metrics, as well as several approaches for data preprocessing, including multivariate outlier detection, logarithmic transformation, and z-score normalization, were systematically evaluated. By selecting clustering approaches shown to give reproducible results for cluster recovery of known cell types, primary conventional central chondrosacoma cells could be grouped in two main clusters with distinctive marker expression signatures: one group clustering together with mesenchymal stem cells (CD49b-high/CD10-low/CD221-high) and a second group clustering close to fibroblasts (CD49b-low/CD10-high/CD221-low). Hierarchical clustering also revealed substantial differences between primary conventional central chondrosarcoma cells and established chondrosarcoma cell lines, with the latter not only segregating apart from primary tumor cells and normal tissue cells, but clustering together with cell lines from epithelial lineage. Our study provides a foundation for the use of hierarchical clustering applied to flow cytometry data as a powerful tool to classify samples according to marker expression patterns, which could lead to uncover new cancer subtypes.