801 resultados para Labeling hierarchical clustering
Resumo:
The intensity of regional specialization in specific activities, and conversely, the level of industrial concentration in specific locations, has been used as a complementary evidence for the existence and significance of externalities. Additionally, economists have mainly focused the debate on disentangling the sources of specialization and concentration processes according to three vectors: natural advantages, internal, and external scale economies. The arbitrariness of partitions plays a key role in capturing these effects, while the selection of the partition would have to reflect the actual characteristics of the economy. Thus, the identification of spatial boundaries to measure specialization becomes critical, since most likely the model will be adapted to different scales of distance, and be influenced by different types of externalities or economies of agglomeration, which are based on the mechanisms of interaction with particular requirements of spatial proximity. This work is based on the analysis of the spatial aspect of economic specialization supported by the manufacturing industry case. The main objective is to propose, for discrete and continuous space: i) a measure of global specialization; ii) a local disaggregation of the global measure; and iii) a spatial clustering method for the identification of specialized agglomerations.
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This PhD Thesis is part of a long-term wide research project, carried out by the "Osservatorio Astronomico di Bologna (INAF-OABO)", that has as primary goal the comprehension and reconstruction of formation mechanism of galaxies and their evolution history. There is now substantial evidence, both from theoretical and observational point of view, in favor of the hypothesis that the halo of our Galaxy has been at least partially, built up by the progressive accretion of small fragments, similar in nature to the present day dwarf galaxies of the Local Group. In this context, the photometric and spectroscopic study of systems which populate the halo of our Galaxy (i.e. dwarf spheroidal galaxy, tidal streams, massive globular cluster, etc) permits to discover, not only the origin and behaviour of these systems, but also the structure of our Galactic halo, combined with its formation history. In fact, the study of the population of these objects and also of their chemical compositions, age, metallicities and velocity dispersion, permit us not only an improvement in the understanding of the mechanisms that govern the Galactic formation, but also a valid indirect test for cosmological model itself. Specifically, in this Thesis we provided a complete characterization of the tidal Stream of the Sagittarius dwarf spheroidal galaxy, that is the most striking example of the process of tidal disruption and accretion of a dwarf satellite in to our Galaxy. Using Red Clump stars, extracted from the catalogue of the Sloan Digital Sky Survey (SDSS) we obtained an estimate of the distance, the depth along the line of sight and of the number density for each detected portion of the Stream (and more in general for each detected structure along our line of sight). Moreover comparing the relative number (i.e. the ratio) of Blue Horizontal Branch stars and Red Clump stars (the two features are tracers of different age/different metallicity populations) in the main body of the galaxy and in the Stream, in order to verify the presence of an age-metallicity gradient along the Stream. We also report the detection of a population of Red Clump stars probably associated with the recently discovered Bootes III stellar system. Finally, we also present the results of a survey of radial velocities over a wide region, extending from r ~ 10' out to r ~ 80' within the massive star cluster Omega Centauri. The survey was performed with FLAMES@VLT, to study the velocity dispersion profile in the outer regions of this stellar system. All the results presented in this Thesis, have already been published in refeered journals.
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The common thread of this thesis is the will of investigating properties and behavior of assemblies. Groups of objects display peculiar properties, which can be very far from the simple sum of respective components’ properties. This is truer, the smaller is inter-objects distance, i.e. the higher is their density, and the smaller is the container size. “Confinement” is in fact a key concept in many topics explored and here reported. It can be conceived as a spatial limitation, that yet gives origin to unexpected processes and phenomena based on inter-objects communication. Such phenomena eventually result in “non-linear properties”, responsible for the low predictability of large assemblies. Chapter 1 provides two insights on surface chemistry, namely (i) on a supramolecular assembly based on orthogonal forces, and (ii) on selective and sensitive fluorescent sensing in thin polymeric film. In chapters 2 to 4 confinement of molecules plays a major role. Most of the work focuses on FRET within core-shell nanoparticles, investigated both through a simulation model and through experiments. Exciting results of great applicative interest are drawn, such as a method of tuning emission wavelength at constant excitation, and a way of overcoming self-quenching processes by setting up a competitive deactivation channel. We envisage applications of these materials as labels for multiplexing analysis, and in all fields of fluorescence imaging, where brightness coupled with biocompatibility and water solubility is required. Adducts of nanoparticles and molecular photoswitches are investigated in the context of superresolution techniques for fluorescence microscopy. In chapter 5 a method is proposed to prepare a library of functionalized Pluronic F127, which gives access to a twofold “smart” nanomaterial, namely both (i)luminescent and (ii)surface-functionalized SCSSNPs. Focus shifts in chapter 6 to confinement effects in an upper size scale. Moving from nanometers to micrometers, we investigate the interplay between microparticles flowing in microchannels where a constriction affects at very long ranges structure and dynamics of the colloidal paste.
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There are different ways to do cluster analysis of categorical data in the literature and the choice among them is strongly related to the aim of the researcher, if we do not take into account time and economical constraints. Main approaches for clustering are usually distinguished into model-based and distance-based methods: the former assume that objects belonging to the same class are similar in the sense that their observed values come from the same probability distribution, whose parameters are unknown and need to be estimated; the latter evaluate distances among objects by a defined dissimilarity measure and, basing on it, allocate units to the closest group. In clustering, one may be interested in the classification of similar objects into groups, and one may be interested in finding observations that come from the same true homogeneous distribution. But do both of these aims lead to the same clustering? And how good are clustering methods designed to fulfil one of these aims in terms of the other? In order to answer, two approaches, namely a latent class model (mixture of multinomial distributions) and a partition around medoids one, are evaluated and compared by Adjusted Rand Index, Average Silhouette Width and Pearson-Gamma indexes in a fairly wide simulation study. Simulation outcomes are plotted in bi-dimensional graphs via Multidimensional Scaling; size of points is proportional to the number of points that overlap and different colours are used according to the cluster membership.
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Il task del data mining si pone come obiettivo l'estrazione automatica di schemi significativi da grandi quantità di dati. Un esempio di schemi che possono essere cercati sono raggruppamenti significativi dei dati, si parla in questo caso di clustering. Gli algoritmi di clustering tradizionali mostrano grossi limiti in caso di dataset ad alta dimensionalità, composti cioè da oggetti descritti da un numero consistente di attributi. Di fronte a queste tipologie di dataset è necessario quindi adottare una diversa metodologia di analisi: il subspace clustering. Il subspace clustering consiste nella visita del reticolo di tutti i possibili sottospazi alla ricerca di gruppi signicativi (cluster). Una ricerca di questo tipo è un'operazione particolarmente costosa dal punto di vista computazionale. Diverse ottimizzazioni sono state proposte al fine di rendere gli algoritmi di subspace clustering più efficienti. In questo lavoro di tesi si è affrontato il problema da un punto di vista diverso: l'utilizzo della parallelizzazione al fine di ridurre il costo computazionale di un algoritmo di subspace clustering.
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Studies of organic fluorescent dyes are experiencing a renaissance related to the increasing demands posed by new microscopy techniques for high resolution and high sensitivity. While in the last decade single molecule equipment and methodology has significantly advanced and in some cases reached theoretical limits (e.g. detectors approaching unity quantum yields) unstable emission from chromophores and photobleaching become more and more the bottleneck of the advancement and spreading of single-molecule fluorescence studies. The main goal of this work was the synthesis of fluorophores that are water-soluble, highly fluorescent in an aqueous environment, have a reactive group for attachment to a biomolecule and posses exceptional photostability. An approach towards highly fluorescent, water-soluble and monofunctional perylene-3,4,9,10-tetracarboxdiimide and terrylene-3,4:11,12-tetra carboxidiimide chromophores was presented. A new synthetic strategy for the desymmetrization of perylenetetracarboximides was elaborated; water-solubility was accomplished by introducing sulfonyl substituents in the phenoxy ring. Two strategies have been followed relying on either non-specific or site specific labeling. For this purpose a series of new water-soluble monofunctional perylene and terrylene dyes, bearing amine or carboxy group were prepared. The reactivity and photophysical properties of these new chromophores were studied in aqueous medium. The most suitable chromophores were further derivatized with amine or thiol reactive groups, suitable for chemical modification of proteins. The performance of the new fluorescent probes was assessed by single molecule enzyme tracking, in this case phospholipase acting on phospholipid supported layers. Phospholipase-1 (PLA-1) was labeled with N-hydroxysuccinimide ester functionalized perylene and terrylene derivatives. The purification of the conjugates was accomplished by novel convenient procedure for the removal of unreacted dye from labeled enzymes, which involves capturing excess dye with a solid support. This novel strategy for purification of bioconjugates allows convenient and fast separation of labeled proteins without the need for performing time consuming chromatographic or electrophoretic purification steps. The outstanding photostability of the dyes and, associated therewith, the extended survival times under strong illumination conditions allow a complete characterization of enzyme action on its natural substrates and even connecting enzyme mobility to catalytic activity. For site-specific attachment of the rylene dyes to proteins the chromophores were functionalized with thioesters or nitrilotriacetic acid groups. This allowed attachment of the emitters to the N-terminus of proteins by native chemical ligation or complexation with His-tagged polypeptides at the N- or C-termini, respectively. The synthesis of a water-soluble perylenebis (dicarboximide) functionalized with a thioester group was presented. This chromophore exhibits an exceptional photostability and a functional unit for site-specific labeling of proteins. The suitability of the fluorophore as a covalent label was demonstrated via native chemical ligation with protein containing N-terminal cystein residue. We exploited also oligohisitidine sequences as recognition elements for site-selective labeling. The synthesis of a new water-soluble perylene chromophore, containing a nitrilotriacetic acid functional group was demonstrated, using solution-phase and solid-phase approaches. This chromophore combines the exceptional photophysical properties of the rylene dyes and a recognition unit for site-specific labeling of proteins. An important feature of the label is the unchanged emission of the dye upon complexation with nickel ions.
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In questo lavoro di tesi si è studiato il clustering degli ammassi di galassie e la determinazione della posizione del picco BAO per ottenere vincoli sui parametri cosmologici. A tale scopo si è implementato un codice per la stima dell'errore tramite i metodi di jackknife e bootstrap. La misura del picco BAO confrontata con i modelli cosmologici, grazie all'errore stimato molto piccolo, è risultato in accordo con il modelli LambdaCDM, e permette di ottenere vincoli su alcuni parametri dei modelli cosmologici.
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Non-invasive molecular-imaging technologies are playing a key role in drug discovery, development and delivery. Positron Emission Tomography (PET) is such a molecular imaging technology and a powerful tool for the observation of various deceases in vivo. However, it is limited by the availability of vectors with high selectivity to the target and radionuclides with a physical half-life which matches the biological half-life of the observed process. The 68Ge/68Ga radionuclide generator makes the PET-nuclide anywhere available without an on-site cyclotron. Besides the perfect availability 68Ga shows well suited nuclide properties for PET, but it has to be co-ordinated by a chelator to introduce it in a radiopharmaceuticals.rnHowever, the physical half-life of 68Ga (67.7 min) might limit the spectrum of clinical applications of 68Ga-labelled radiodiagnostics. Furthermore, 68Ga-labelled analogues of endoradiotherapeuticals of longer biological half-live such as 90Y- or 177Lu-labeled peptides and proteins cannot be used to determine individual radiation dosimetry directly. rnThus, radionuclide generator systems providing positron emitting daughters of extended physical half-life are of renewed interest. In this context, generator-derived positron emitters with longer physical half-life are needed, such as 72As (T½ = 26 h) from the 72Se/72As generator, or 44Sc (T½ = 3.97 h) from the 44Ti/44Sc generator.rnIn this thesis the implementation of radioactive gallium-68 and scandium-44 for molecular imaging and nuclear medical diagnosis, beginning with chemical separation and purification of 44Ti as a radionuclide mother, investigation of pilot generators with different elution mode, building a prototype generator, development and investigation of post-processing of the generator eluate, its concentration and further purification, the labeling chemistry under different conditions, in vitro and in vivo studies of labeled compounds and, finally, in vivo imaging experiments are described.
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The country-of-origin is the “nationality” of a food when it goes through customs in a foreign country, and is a “brand” when the food is for sale in a foreign market. My research on country-of-origin labeling (COOL) started from a case study on the extra virgin olive oil exported from Italy to China; the result shows that asymmetric and imperfect origin information may lead to market inefficiency, even market failure in emerging countries. Then, I used the Delphi method to conduct qualitative and systematic research on COOL; the panel of experts in food labeling and food policy was composed of 19 members in 13 countries; the most important consensus is that multiple countries of origin marking can provide accurate information about the origin of a food produced by two or more countries, avoiding misinformation for consumers. Moreover, I enhanced the research on COOL by analyzing the rules of origin and drafting a guideline for the standardization of origin marking. Finally, from the perspective of information economics I estimated the potential effect of the multiple countries of origin labeling on the business models of international trade, and analyzed the regulatory options for mandatory or voluntary COOL of main ingredients. This research provides valuable insights for the formulation of COOL policy.
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Lo scopo del clustering è quindi quello di individuare strutture nei dati significative, ed è proprio dalla seguente definizione che è iniziata questa attività di tesi , fornendo un approccio innovativo ed inesplorato al cluster, ovvero non ricercando la relazione ma ragionando su cosa non lo sia. Osservando un insieme di dati ,cosa rappresenta la non relazione? Una domanda difficile da porsi , che ha intrinsecamente la sua risposta, ovvero l’indipendenza di ogni singolo dato da tutti gli altri. La ricerca quindi dell’indipendenza tra i dati ha portato il nostro pensiero all’approccio statistico ai dati , in quanto essa è ben descritta e dimostrata in statistica. Ogni punto in un dataset, per essere considerato “privo di collegamenti/relazioni” , significa che la stessa probabilità di essere presente in ogni elemento spaziale dell’intero dataset. Matematicamente parlando , ogni punto P in uno spazio S ha la stessa probabilità di cadere in una regione R ; il che vuol dire che tale punto può CASUALMENTE essere all’interno di una qualsiasi regione del dataset. Da questa assunzione inizia il lavoro di tesi, diviso in più parti. Il secondo capitolo analizza lo stato dell’arte del clustering, raffrontato alla crescente problematica della mole di dati, che con l’avvento della diffusione della rete ha visto incrementare esponenzialmente la grandezza delle basi di conoscenza sia in termini di attributi (dimensioni) che in termini di quantità di dati (Big Data). Il terzo capitolo richiama i concetti teorico-statistici utilizzati dagli algoritimi statistici implementati. Nel quarto capitolo vi sono i dettagli relativi all’implementazione degli algoritmi , ove sono descritte le varie fasi di investigazione ,le motivazioni sulle scelte architetturali e le considerazioni che hanno portato all’esclusione di una delle 3 versioni implementate. Nel quinto capitolo gli algoritmi 2 e 3 sono confrontati con alcuni algoritmi presenti in letteratura, per dimostrare le potenzialità e le problematiche dell’algoritmo sviluppato , tali test sono a livello qualitativo , in quanto l’obbiettivo del lavoro di tesi è dimostrare come un approccio statistico può rivelarsi un’arma vincente e non quello di fornire un nuovo algoritmo utilizzabile nelle varie problematiche di clustering. Nel sesto capitolo saranno tratte le conclusioni sul lavoro svolto e saranno elencati i possibili interventi futuri dai quali la ricerca appena iniziata del clustering statistico potrebbe crescere.
Resumo:
Atmosphärische Aerosolpartikel wirken in vielerlei Hinsicht auf die Menschen und die Umwelt ein. Eine genaue Charakterisierung der Partikel hilft deren Wirken zu verstehen und dessen Folgen einzuschätzen. Partikel können hinsichtlich ihrer Größe, ihrer Form und ihrer chemischen Zusammensetzung charakterisiert werden. Mit der Laserablationsmassenspektrometrie ist es möglich die Größe und die chemische Zusammensetzung einzelner Aerosolpartikel zu bestimmen. Im Rahmen dieser Arbeit wurde das SPLAT (Single Particle Laser Ablation Time-of-flight mass spectrometer) zur besseren Analyse insbesondere von atmosphärischen Aerosolpartikeln weiterentwickelt. Der Aerosoleinlass wurde dahingehend optimiert, einen möglichst weiten Partikelgrößenbereich (80 nm - 3 µm) in das SPLAT zu transferieren und zu einem feinen Strahl zu bündeln. Eine neue Beschreibung für die Beziehung der Partikelgröße zu ihrer Geschwindigkeit im Vakuum wurde gefunden. Die Justage des Einlasses wurde mithilfe von Schrittmotoren automatisiert. Die optische Detektion der Partikel wurde so verbessert, dass Partikel mit einer Größe < 100 nm erfasst werden können. Aufbauend auf der optischen Detektion und der automatischen Verkippung des Einlasses wurde eine neue Methode zur Charakterisierung des Partikelstrahls entwickelt. Die Steuerelektronik des SPLAT wurde verbessert, so dass die maximale Analysefrequenz nur durch den Ablationslaser begrenzt wird, der höchsten mit etwa 10 Hz ablatieren kann. Durch eine Optimierung des Vakuumsystems wurde der Ionenverlust im Massenspektrometer um den Faktor 4 verringert.rnrnNeben den hardwareseitigen Weiterentwicklungen des SPLAT bestand ein Großteil dieser Arbeit in der Konzipierung und Implementierung einer Softwarelösung zur Analyse der mit dem SPLAT gewonnenen Rohdaten. CRISP (Concise Retrieval of Information from Single Particles) ist ein auf IGOR PRO (Wavemetrics, USA) aufbauendes Softwarepaket, das die effiziente Auswertung der Einzelpartikel Rohdaten erlaubt. CRISP enthält einen neu entwickelten Algorithmus zur automatischen Massenkalibration jedes einzelnen Massenspektrums, inklusive der Unterdrückung von Rauschen und von Problemen mit Signalen die ein intensives Tailing aufweisen. CRISP stellt Methoden zur automatischen Klassifizierung der Partikel zur Verfügung. Implementiert sind k-means, fuzzy-c-means und eine Form der hierarchischen Einteilung auf Basis eines minimal aufspannenden Baumes. CRISP bietet die Möglichkeit die Daten vorzubehandeln, damit die automatische Einteilung der Partikel schneller abläuft und die Ergebnisse eine höhere Qualität aufweisen. Daneben kann CRISP auf einfache Art und Weise Partikel anhand vorgebener Kriterien sortieren. Die CRISP zugrundeliegende Daten- und Infrastruktur wurde in Hinblick auf Wartung und Erweiterbarkeit erstellt. rnrnIm Rahmen der Arbeit wurde das SPLAT in mehreren Kampagnen erfolgreich eingesetzt und die Fähigkeiten von CRISP konnten anhand der gewonnen Datensätze gezeigt werden.rnrnDas SPLAT ist nun in der Lage effizient im Feldeinsatz zur Charakterisierung des atmosphärischen Aerosols betrieben zu werden, während CRISP eine schnelle und gezielte Auswertung der Daten ermöglicht.
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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.
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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.