896 resultados para computation- and data-intensive applications


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Graphene and graphenic derivatives have rapidly emerged as an extremely promising system for electronic, optical, thermal, and electromechanical applications. Several approaches have been developed to produce these materials (i.e. scotch tape, CVD, chemical and solvent exfoliation). In this work we report a chemical approach to produce graphene by reducing graphene oxide (GO) via thermal or electrical methods. A morphological and electrical characterization of these systems has been performed using different techniques such as SPM, SEM, TEM, Raman and XPS. Moreover, we studied the interaction between graphene derivates and organic molecules focusing on the following aspects: - improvement of optical contrast of graphene on different substrates for rapid monolayer identification1 - supramolecular interaction with organic molecules (i.e. thiophene, pyrene etc.)4 - covalent functionalization with optically active molecules2 - preparation and characterization of organic/graphene Field Effect Transistors3-5 Graphene chemistry can potentially allow seamless integration of graphene technology in organic electronics devices to improve device performance and develop new applications for graphene-based materials. [1] E. Treossi, M. Melucci, A. Liscio, M. Gazzano, P. Samorì, and V. Palermo, J. Am. Chem. Soc., 2009, 131, 15576. [2] M. Melucci, E. Treossi, L. Ortolani, G. Giambastiani, V. Morandi, P. Klar, C. Casiraghi, P. Samorì, and V. Palermo, J. Mater. Chem., 2010, 20, 9052. [3] J.M. Mativetsky, E. Treossi, E. Orgiu, M. Melucci, G.P. Veronese, P. Samorì, and V. Palermo, J. Am. Chem. Soc., 2010, 132, 14130. [4] A. Liscio, G.P. Veronese, E. Treossi, F. Suriano, F. Rossella, V. Bellani, R. Rizzoli, P. Samorì and V. Palermo, J. Mater. Chem., 2011, 21, 2924. [5] J.M. Mativetsky, A. Liscio, E. Treossi, E. Orgiu, A. Zanelli, P. Samorì , V. Palermo, J. Am. Chem. Soc., 2011, 133, 14320

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The research presented in my PhD thesis is part of a wider European project, FishPopTrace, focused on traceability of fish populations and products. My work was aimed at developing and analyzing novel genetic tools for a widely distributed marine fish species, the European hake (Merluccius merluccius), in order to investigate population genetic structure and explore potential applications to traceability scenarios. A total of 395 SNPs (Single Nucleotide Polymorphisms) were discovered from a massive collection of Expressed Sequence Tags, obtained by high-throughput sequencing, and validated on 19 geographic samples from Atlantic and Mediterranean. Genome-scan approaches were applied to identify polymorphisms on genes potentially under divergent selection (outlier SNPs), showing higher genetic differentiation among populations respect to the average observed across loci. Comparative analysis on population structure were carried out on putative neutral and outlier loci at wide (Atlantic and Mediterranean samples) and regional (samples within each basin) spatial scales, to disentangle the effects of demographic and adaptive evolutionary forces on European hake populations genetic structure. Results demonstrated the potential of outlier loci to unveil fine scale genetic structure, possibly identifying locally adapted populations, despite the weak signal showed from putative neutral SNPs. The application of outlier SNPs within the framework of fishery resources management was also explored. A minimum panel of SNP markers showing maximum discriminatory power was selected and applied to a traceability scenario aiming at identifying the basin (and hence the stock) of origin, Atlantic or Mediterranean, of individual fish. This case study illustrates how molecular analytical technologies have operational potential in real-world contexts, and more specifically, potential to support fisheries control and enforcement and fish and fish product traceability.

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Die vorliegende Arbeit ist motiviert durch biologische Fragestellungen bezüglich des Verhaltens von Membranpotentialen in Neuronen. Ein vielfach betrachtetes Modell für spikende Neuronen ist das Folgende. Zwischen den Spikes verhält sich das Membranpotential wie ein Diffusionsprozess X der durch die SDGL dX_t= beta(X_t) dt+ sigma(X_t) dB_t gegeben ist, wobei (B_t) eine Standard-Brown'sche Bewegung bezeichnet. Spikes erklärt man wie folgt. Sobald das Potential X eine gewisse Exzitationsschwelle S überschreitet entsteht ein Spike. Danach wird das Potential wieder auf einen bestimmten Wert x_0 zurückgesetzt. In Anwendungen ist es manchmal möglich, einen Diffusionsprozess X zwischen den Spikes zu beobachten und die Koeffizienten der SDGL beta() und sigma() zu schätzen. Dennoch ist es nötig, die Schwellen x_0 und S zu bestimmen um das Modell festzulegen. Eine Möglichkeit, dieses Problem anzugehen, ist x_0 und S als Parameter eines statistischen Modells aufzufassen und diese zu schätzen. In der vorliegenden Arbeit werden vier verschiedene Fälle diskutiert, in denen wir jeweils annehmen, dass das Membranpotential X zwischen den Spikes eine Brown'sche Bewegung mit Drift, eine geometrische Brown'sche Bewegung, ein Ornstein-Uhlenbeck Prozess oder ein Cox-Ingersoll-Ross Prozess ist. Darüber hinaus beobachten wir die Zeiten zwischen aufeinander folgenden Spikes, die wir als iid Treffzeiten der Schwelle S von X gestartet in x_0 auffassen. Die ersten beiden Fälle ähneln sich sehr und man kann jeweils den Maximum-Likelihood-Schätzer explizit angeben. Darüber hinaus wird, unter Verwendung der LAN-Theorie, die Optimalität dieser Schätzer gezeigt. In den Fällen OU- und CIR-Prozess wählen wir eine Minimum-Distanz-Methode, die auf dem Vergleich von empirischer und wahrer Laplace-Transformation bezüglich einer Hilbertraumnorm beruht. Wir werden beweisen, dass alle Schätzer stark konsistent und asymptotisch normalverteilt sind. Im letzten Kapitel werden wir die Effizienz der Minimum-Distanz-Schätzer anhand simulierter Daten überprüfen. Ferner, werden Anwendungen auf reale Datensätze und deren Resultate ausführlich diskutiert.

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Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

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In the last decades noble metal nanoparticles (NPs) arose as one of the most powerful tools for applications in nanomedicine field and cancer treatment. Glioblastoma multiforme (GBM), in particular, is one of the most aggressive malignant brain tumors that nowadays still presents a dramatic scenario concerning median survival. Gold nanorods (GNRs) and silver nanoparticles (AgNPs) could find applications such as diagnostic imaging, hyperthermia and glioblastoma therapy. During these three years, both GNRs and AgNPs were synthesized with the “salt reduction” method and, through a novel double phase transfer process, using specifically designed thiol-based ligands, lipophilic GNRs and AgNPs were obtained and separately entrapped into biocompatible and biodegradable PEG-based polymeric nanoparticles (PNPs) suitable for drug delivery within the body. Moreover, a synergistic effect of AgNPs with the Alisertib drug, were investigated thanks to the simultaneous entrapment of these two moieties into PNPs. In addition, Chlorotoxin (Cltx), a peptide that specifically recognize brain cancer cells, was conjugated onto the external surface of PNPs. The so-obtained novel nanosystems were evaluated for in vitro and in vivo applications against glioblastoma multiforme. In particular, for GNRs-PNPs, their safety, their suitability as optoacoustic contrast agents, their selective laser-induced cells death and finally, a high tumor retention were all demonstrated. Concerning AgNPs-PNPs, promising tumor toxicity and a strong synergistic effect with Alisertib was observed (IC50 10 nM), as well as good in vivo biodistribution, high tumor uptake and significative tumor reduction in tumor bearing mice. Finally, the two nanostructures were linked together, through an organic framework, exploiting the click chemistry azido-alkyne Huisgen cycloaddition, between two ligands previously attached to the NPs surface; this multifunctional complex nanosystem was successfully entrapped into PNPs with nanoparticles’ properties maintenance, obtaining in this way a powerful and promising tool for cancer fight and defeat.

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The aim of this work is to present various aspects of numerical simulation of particle and radiation transport for industrial and environmental protection applications, to enable the analysis of complex physical processes in a fast, reliable, and efficient way. In the first part we deal with speed-up of numerical simulation of neutron transport for nuclear reactor core analysis. The convergence properties of the source iteration scheme of the Method of Characteristics applied to be heterogeneous structured geometries has been enhanced by means of Boundary Projection Acceleration, enabling the study of 2D and 3D geometries with transport theory without spatial homogenization. The computational performances have been verified with the C5G7 2D and 3D benchmarks, showing a sensible reduction of iterations and CPU time. The second part is devoted to the study of temperature-dependent elastic scattering of neutrons for heavy isotopes near to the thermal zone. A numerical computation of the Doppler convolution of the elastic scattering kernel based on the gas model is presented, for a general energy dependent cross section and scattering law in the center of mass system. The range of integration has been optimized employing a numerical cutoff, allowing a faster numerical evaluation of the convolution integral. Legendre moments of the transfer kernel are subsequently obtained by direct quadrature and a numerical analysis of the convergence is presented. In the third part we focus our attention to remote sensing applications of radiative transfer employed to investigate the Earth's cryosphere. The photon transport equation is applied to simulate reflectivity of glaciers varying the age of the layer of snow or ice, its thickness, the presence or not other underlying layers, the degree of dust included in the snow, creating a framework able to decipher spectral signals collected by orbiting detectors.

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In this thesis the evolution of the techno-social systems analysis methods will be reported, through the explanation of the various research experience directly faced. The first case presented is a research based on data mining of a dataset of words association named Human Brain Cloud: validation will be faced and, also through a non-trivial modeling, a better understanding of language properties will be presented. Then, a real complex system experiment will be introduced: the WideNoise experiment in the context of the EveryAware european project. The project and the experiment course will be illustrated and data analysis will be displayed. Then the Experimental Tribe platform for social computation will be introduced . It has been conceived to help researchers in the implementation of web experiments, and aims also to catalyze the cumulative growth of experimental methodologies and the standardization of tools cited above. In the last part, three other research experience which already took place on the Experimental Tribe platform will be discussed in detail, from the design of the experiment to the analysis of the results and, eventually, to the modeling of the systems involved. The experiments are: CityRace, about the measurement of human traffic-facing strategies; laPENSOcosì, aiming to unveil the political opinion structure; AirProbe, implemented again in the EveryAware project framework, which consisted in monitoring air quality opinion shift of a community informed about local air pollution. At the end, the evolution of the technosocial systems investigation methods shall emerge together with the opportunities and the threats offered by this new scientific path.

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This thesis provides a thoroughly theoretical background in network theory and shows novel applications to real problems and data. In the first chapter a general introduction to network ensembles is given, and the relations with “standard” equilibrium statistical mechanics are described. Moreover, an entropy measure is considered to analyze statistical properties of the integrated PPI-signalling-mRNA expression networks in different cases. In the second chapter multilayer networks are introduced to evaluate and quantify the correlations between real interdependent networks. Multiplex networks describing citation-collaboration interactions and patterns in colorectal cancer are presented. The last chapter is completely dedicated to control theory and its relation with network theory. We characterise how the structural controllability of a network is affected by the fraction of low in-degree and low out-degree nodes. Finally, we present a novel approach to the controllability of multiplex networks

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One of the most undervalued problems by smartphone users is the security of data on their mobile devices. Today smartphones and tablets are used to send messages and photos and especially to stay connected with social networks, forums and other platforms. These devices contain a lot of private information like passwords, phone numbers, private photos, emails, etc. and an attacker may choose to steal or destroy this information. The main topic of this thesis is the security of the applications present on the most popular stores (App Store for iOS and Play Store for Android) and of their mechanisms for the management of security. The analysis is focused on how the architecture of the two systems protects users from threats and highlights the real presence of malware and spyware in their respective application stores. The work described in subsequent chapters explains the study of the behavior of 50 Android applications and 50 iOS applications performed using network analysis software. Furthermore, this thesis presents some statistics about malware and spyware present on the respective stores and the permissions they require. At the end the reader will be able to understand how to recognize malicious applications and which of the two systems is more suitable for him. This is how this thesis is structured. The first chapter introduces the security mechanisms of the Android and iOS platform architectures and the security mechanisms of their respective application stores. The Second chapter explains the work done, what, why and how we have chosen the tools needed to complete our analysis. The third chapter discusses about the execution of tests, the protocol followed and the approach to assess the “level of danger” of each application that has been checked. The fourth chapter explains the results of the tests and introduces some statistics on the presence of malicious applications on Play Store and App Store. The fifth chapter is devoted to the study of the users, what they think about and how they might avoid malicious applications. The sixth chapter seeks to establish, following our methodology, what application store is safer. In the end, the seventh chapter concludes the thesis.

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In this thesis, the author presents a query language for an RDF (Resource Description Framework) database and discusses its applications in the context of the HELM project (the Hypertextual Electronic Library of Mathematics). This language aims at meeting the main requirements coming from the RDF community. in particular it includes: a human readable textual syntax and a machine-processable XML (Extensible Markup Language) syntax both for queries and for query results, a rigorously exposed formal semantics, a graph-oriented RDF data access model capable of exploring an entire RDF graph (including both RDF Models and RDF Schemata), a full set of Boolean operators to compose the query constraints, fully customizable and highly structured query results having a 4-dimensional geometry, some constructions taken from ordinary programming languages that simplify the formulation of complex queries. The HELM project aims at integrating the modern tools for the automation of formal reasoning with the most recent electronic publishing technologies, in order create and maintain a hypertextual, distributed virtual library of formal mathematical knowledge. In the spirit of the Semantic Web, the documents of this library include RDF metadata describing their structure and content in a machine-understandable form. Using the author's query engine, HELM exploits this information to implement some functionalities allowing the interactive and automatic retrieval of documents on the basis of content-aware requests that take into account the mathematical nature of these documents.

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In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.

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Background Through this paper, we present the initial steps for the creation of an integrated platform for the provision of a series of eHealth tools and services to both citizens and travelers in isolated areas of thesoutheast Mediterranean, and on board ships travelling across it. The platform was created through an INTERREG IIIB ARCHIMED project called INTERMED. Methods The support of primary healthcare, home care and the continuous education of physicians are the three major issues that the proposed platform is trying to facilitate. The proposed system is based on state-of-the-art telemedicine systems and is able to provide the following healthcare services: i) Telecollaboration and teleconsultation services between remotely located healthcare providers, ii) telemedicine services in emergencies, iii) home telecare services for "at risk" citizens such as the elderly and patients with chronic diseases, and iv) eLearning services for the continuous training through seminars of both healthcare personnel (physicians, nurses etc) and persons supporting "at risk" citizens. These systems support data transmission over simple phone lines, internet connections, integrated services digital network/digital subscriber lines, satellite links, mobile networks (GPRS/3G), and wireless local area networks. The data corresponds, among others, to voice, vital biosignals, still medical images, video, and data used by eLearning applications. The proposed platform comprises several systems, each supporting different services. These were integrated using a common data storage and exchange scheme in order to achieve system interoperability in terms of software, language and national characteristics. Results The platform has been installed and evaluated in different rural and urban sites in Greece, Cyprus and Italy. The evaluation was mainly related to technical issues and user satisfaction. The selected sites are, among others, rural health centers, ambulances, homes of "at-risk" citizens, and a ferry. Conclusions The results proved the functionality and utilization of the platform in various rural places in Greece, Cyprus and Italy. However, further actions are needed to enable the local healthcare systems and the different population groups to be familiarized with, and use in their everyday lives, mature technological solutions for the provision of healthcare services.

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Jahnke and Asher explore workflows and methodologies at a variety of academic data curation sites, and Keralis delves into the academic milieu of library and information schools that offer instruction in data curation. Their conclusions point to the urgent need for a reliable and increasingly sophisticated professional cohort to support data-intensive research in our colleges, universities, and research centers.

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A confocal imaging and image processing scheme is introduced to visualize and evaluate the spatial distribution of spectral information in tissue. The image data are recorded using a confocal laser-scanning microscope equipped with a detection unit that provides high spectral resolution. The processing scheme is based on spectral data, is less error-prone than intensity-based visualization and evaluation methods, and provides quantitative information on the composition of the sample. The method is tested and validated in the context of the development of dermal drug delivery systems, introducing a quantitative uptake indicator to compare the performances of different delivery systems is introduced. A drug penetration study was performed in vitro. The results show that the method is able to detect, visualize and measure spectral information in tissue. In the penetration study, uptake efficiencies of different experiment setups could be discriminated and quantitatively described. The developed uptake indicator is a step towards a quantitative assessment and, in a more general view apart from pharmaceutical research, provides valuable information on tissue composition. It can potentially be used for clinical in vitro and in vivo applications.

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CONTEXT: Determination of arginine vasopressin (AVP) concentrations may be helpful to guide therapy in critically ill patients. A new assay analyzing copeptin, a stable peptide derived from the AVP precursor, has been introduced. OBJECTIVE: Our objective was to determine plasma copeptin concentrations. DESIGN: We conducted a post hoc analysis of plasma samples and data from a prospective study. SETTING: The setting was a 12-bed general and surgical intensive care unit (ICU) in a tertiary university teaching hospital. PATIENTS: Our subjects were 70 healthy volunteers and 157 ICU patients with sepsis, with systemic inflammatory response syndrome (SIRS), and after cardiac surgery. INTERVENTIONS: There were no interventions. MAIN OUTCOME MEASURES: Copeptin plasma concentrations, demographic data, AVP plasma concentrations, and a multiple organ dysfunction syndrome score were documented 24 h after ICU admission. RESULTS: AVP (P < 0.001) and copeptin (P < 0.001) concentrations were significantly higher in ICU patients than in controls. Patients after cardiac surgery had higher AVP (P = 0.003) and copeptin (P = 0.003) concentrations than patients with sepsis or SIRS. Independent of critical illness, copeptin and AVP correlated highly significantly with each other. Critically ill patients with sepsis and SIRS exhibited a significantly higher ratio of copeptin/AVP plasma concentrations than patients after cardiac surgery (P = 0.012). The American Society of Anesthesiologists' classification (P = 0.046) and C-reactive protein concentrations (P = 0.006) were significantly correlated with the copeptin/AVP ratio. CONCLUSIONS: Plasma concentrations of copeptin and AVP in healthy volunteers and critically ill patients correlate significantly with each other. The ratio of copeptin/AVP plasma concentrations is increased in patients with sepsis and SIRS, suggesting that copeptin may overestimate AVP plasma concentrations in these patients.