4 resultados para Project 2005-003-B : Learning System for Life Prediction of Infrastructure

em ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha


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Ziel der Arbeit war die Quantifizierung einer Reihe von Lebenszyklusmerkmalen der beiden tropischen Grasmückenarten Sylvia boehmi und S. lugens (Aves: Sylviidae; frühere Gattung Parisoma). 13 Brutpaare beider Arten wurden von 2000 bis 2002 in Kenia beobachtet. Die Daten wurden mit multivariater Statistik und multistate mark-recapture Modellen ausgewertet. Die Lebenszyklusmerkmale der beiden untersuchten Sylvia Arten sind im Vergleich zu den temperaten Sylvia-Arten gekennzeichnet durch kleine Gelege von zwei Eiern, lange Inkubationsperioden (S. boehmi (b.) 15.0 Tage, S. lugens (l.) 14.5 Tage), lange Nestlingsperioden (b. 12.9 Tage, l. 16.0 Tage), und niedrige Nesterfolgsraten (b. 19.4%, l. 33.2%). Der Zeitraum vom Ausfliegen der Jungen bis zu ihrer Unabhängigkeit war mit 58.5 Tagen bei S. boehmi und 37.5 Tagen bei S. lugens vergleichsweise lang und die Überlebensrate der flüggen Jungen in dieser Zeit war relativ hoch (b. 69.2%, l. 55.4%). Die jährliche Überlebensrate der brütenden adulten Tiere betrug bei S. boehmi 71.2% und bei S. lugens 57.2%. Die Saisonalität des Habitats, bedingt durch Regen- und Trockenzeiten, hatte keinen Einfluss auf die monatliche Überlebensrate im Laufe eines Jahres. Trotz hoher Nestprädationsraten gab es keinen klaren Zusammenhang zwischen Prädation und Fütterungsrate, Nestbewachung oder Neststandort.

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The subject of this thesis is the development of a Gaschromatography (GC) system for non-methane hydrocarbons (NMHCs) and measurement of samples within the project CARIBIC (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container, www.caribic-atmospheric.com). Air samples collected at cruising altitude from the upper troposphere and lowermost stratosphere contain hydrocarbons at low levels (ppt range), which imposes substantial demands on detection limits. Full automation enabled to maintain constant conditions during the sample processing and analyses. Additionally, automation allows overnight operation thus saving time. A gas chromatography using flame ionization detection (FID) together with the dual column approach enables simultaneous detection with almost equal carbon atom response for all hydrocarbons except for ethyne. The first part of this thesis presents the technical descriptions of individual parts of the analytical system. Apart from the sample treatment and calibration procedures, the sample collector is described. The second part deals with analytical performance of the GC system by discussing tests that had been made. Finally, results for measurement flight are assessed in terms of quality of the data and two flights are discussed in detail. Analytical performance is characterized using detection limits for each compound, using uncertainties for each compound, using tests of calibration mixture conditioning and carbon dioxide trap to find out their influence on analyses, and finally by comparing the responses of calibrated substances during period when analyses of the flights were made. Comparison of both systems shows good agreement. However, because of insufficient capacity of the CO2 trap the signal of one column was suppressed due to breakthroughed carbon dioxide so much that its results appeared to be unreliable. Plausibility tests for the internal consistency of the given data sets are based on common patterns exhibited by tropospheric NMHCs. All tests show that samples from the first flights do not comply with the expected pattern. Additionally, detected alkene artefacts suggest potential problems with storing or contamination within all measurement flights. Two last flights # 130-133 and # 166-169 comply with the tests therefore their detailed analysis is made. Samples were analyzed in terms of their origin (troposphere vs. stratosphere, backward trajectories), their aging (NMHCs ratios) and detected plumes were compared to chemical signatures of Asian outflows. In the last chapter a future development of the presented system with focus on separation is drawn. An extensive appendix documents all important aspects of the dissertation from theoretical introduction through illustration of sample treatment to overview diagrams for the measured flights.

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Im Forschungsgebiet der Künstlichen Intelligenz, insbesondere im Bereich des maschinellen Lernens, hat sich eine ganze Reihe von Verfahren etabliert, die von biologischen Vorbildern inspiriert sind. Die prominentesten Vertreter derartiger Verfahren sind zum einen Evolutionäre Algorithmen, zum anderen Künstliche Neuronale Netze. Die vorliegende Arbeit befasst sich mit der Entwicklung eines Systems zum maschinellen Lernen, das Charakteristika beider Paradigmen in sich vereint: Das Hybride Lernende Klassifizierende System (HCS) wird basierend auf dem reellwertig kodierten eXtended Learning Classifier System (XCS), das als Lernmechanismus einen Genetischen Algorithmus enthält, und dem Wachsenden Neuralen Gas (GNG) entwickelt. Wie das XCS evolviert auch das HCS mit Hilfe eines Genetischen Algorithmus eine Population von Klassifizierern - das sind Regeln der Form [WENN Bedingung DANN Aktion], wobei die Bedingung angibt, in welchem Bereich des Zustandsraumes eines Lernproblems ein Klassifizierer anwendbar ist. Beim XCS spezifiziert die Bedingung in der Regel einen achsenparallelen Hyperquader, was oftmals keine angemessene Unterteilung des Zustandsraumes erlaubt. Beim HCS hingegen werden die Bedingungen der Klassifizierer durch Gewichtsvektoren beschrieben, wie die Neuronen des GNG sie besitzen. Jeder Klassifizierer ist anwendbar in seiner Zelle der durch die Population des HCS induzierten Voronoizerlegung des Zustandsraumes, dieser kann also flexibler unterteilt werden als beim XCS. Die Verwendung von Gewichtsvektoren ermöglicht ferner, einen vom Neuronenadaptationsverfahren des GNG abgeleiteten Mechanismus als zweites Lernverfahren neben dem Genetischen Algorithmus einzusetzen. Während das Lernen beim XCS rein evolutionär erfolgt, also nur durch Erzeugen neuer Klassifizierer, ermöglicht dies dem HCS, bereits vorhandene Klassifizierer anzupassen und zu verbessern. Zur Evaluation des HCS werden mit diesem verschiedene Lern-Experimente durchgeführt. Die Leistungsfähigkeit des Ansatzes wird in einer Reihe von Lernproblemen aus den Bereichen der Klassifikation, der Funktionsapproximation und des Lernens von Aktionen in einer interaktiven Lernumgebung unter Beweis gestellt.

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Glioblastoma multiforme (GBM) is the most common and most aggressive astrocytic tumor of the central nervous system (CNS) in adults. The standard treatment consisting of surgery, followed by a combinatorial radio- and chemotherapy, is only palliative and prolongs patient median survival to 12 to 15 months. The tumor subpopulation of stem cell-like glioma-initiating cells (GICs) shows resistance against radiation as well as chemotherapy, and has been suggested to be responsible for relapses of more aggressive tumors after therapy. The efficacy of immunotherapies, which exploit the immune system to specifically recognize and eliminate malignant cells, is limited due to strong immunosuppressive activities of the GICs and the generation of a specialized protective microenvironment. The molecular mechanisms underlying the therapy resistance of GICs are largely unknown. rnThe first aim of this study was to identify immune evasion mechanisms in GICs triggered by radiation. A model was used in which patient-derived GICs were treated in vitro with fractionated ionizing radiation (2.5 Gy in 7 consecutive passages) to select for a more radio-resistant phenotype. In the model cell line 1080, this selection process resulted in increased proliferative but diminished migratory capacities in comparison to untreated control GICs. Furthermore, radio-selected GICs downregulated various proteins involved in antigen processing and presentation, resulting in decreased expression of MHC class I molecules on the cellular surface and diminished recognition potential by cytotoxic CD8+ T cells. Thus, sub-lethal fractionated radiation can promote immune evasion and hamper the success of adjuvant immunotherapy. Among several immune-associated proteins, interferon-induced transmembrane protein 3 (IFITM3) was found to be upregulated in radio-selected GICs. While high expression of IFITM3 was associated with a worse overall survival of GBM patients (TCGA database) and increased proliferation and migration of differentiated glioma cell lines, a strong contribution of IFITM3 to proliferation in vitro as well as tumor growth and invasiveness in a xenograft model could not be observed. rnMultiple sclerosis (MS) is the most common autoimmune disease of the CNS in young adults of the Western World, which leads to progressive disability in genetically susceptible individuals, possibly triggered by environmental factors. It is assumed that self-reactive, myelin-specific T helper cell 1 (Th1) and Th17 cells, which have escaped the control mechanisms of the immune system, are critical in the pathogenesis of the human disease and its animal model experimental autoimmune encephalomyelitis (EAE). It was observed that in vitro differentiated interleukin 17 (IL-17) producing Th17 cells co-expressed the Th1-phenotypic cytokine Interferon-gamma (IFN-γ) in combination with the two respective lineage-associated transcription factors RORγt and T-bet after re-isolation from the CNS of diseased mice. Pathogenic molecular mechanisms that render a CD4+ T cell encephalitogenic have scarcely been investigated up to date. rnIn the second part of the thesis, whole transcriptional changes occurring in in vitro differentiated Th17 cells in the course of EAE were analyzed. Evaluation of signaling networks revealed an overrepresentation of genes involved in communication between the innate and adaptive immune system and metabolic alterations including cholesterol biosynthesis. The transcription factors Cebpa, Fos, Klf4, Nfatc1 and Spi1, associated with thymocyte development and naïve T cells were upregulated in encephalitogenic CNS-isolated CD4+ T cells, proposing a contribution to T cell plasticity. Correlation of the murine T-cell gene expression dataset to putative MS risk genes, which were selected based on their proximity (± 500 kb; ensembl database, release 75) to the MS risk single nucleotide polymorphisms (SNPs) proposed by the most recent multiple sclerosis GWAS in 2011, revealed that 67.3% of the MS risk genes were differentially expressed in EAE. Expression patterns of Bach2, Il2ra, Irf8, Mertk, Odf3b, Plek, Rgs1, Slc30a7, and Thada were confirmed in independent experiments, suggesting a contribution to T cell pathogenicity. Functional analysis of Nfatc1 revealed that Nfatc1-deficient CD4+ T cells were restrained in their ability to induce clinical signs of EAE. Nfatc1-deficiency allowed proper T cell activation, but diminished their potential to fully differentiate into Th17 cells and to express high amounts of lineage cytokines. As the inducible Nfatc1/αA transcript is distinct from the other family members, it could represent an interesting target for therapeutic intervention in MS.rn