Probing the decay characteristics of the Pygmy Dipole Resonance in the semi-magic nucleus 140 Ce with gamma-gamma coincidence measurements

Im Rahmen dieser Arbeit wurde ein neuartiger Experimentaufbau -- das γ3 Experiment -- zur Messung von photoneninduzierten Kern-Dipolanregungen in stabilen Isotopen konzipiert und an der High Intensity γ-Ray Source (HIγS) an der Duke University installiert.rnDie hohe Energieauflösung und die hohe Nachweiseffizienz des Detektoraufbaus, welcher aus einer Kombination von LaBr Szintillatoren und hochreinen Germanium-Detektoren besteht, erlaubt erstmals die effiziente Messung von γ-γ-Koinzidenzen in Verbindung mit der Methode der Kernresonanzfluoreszenz.rnDiese Methode eröffnet den Zugang zum Zerfallsverhalten der angeregten Dipolzustände als zusätzlicher Observablen, die ein detaillierteres Verständnis der zugrunde liegenden Struktur dieser Anregungen ermöglicht.rnDer Detektoraufbau wurde bereits erfolgreich im Rahmen von zwei Experimentkampagnen in 2012 und 2013 für die Untersuchung von 13 verschiedenen Isotopen verwendet. Im Fokus dieser Arbeit stand die Analyse der Pygmy-Dipolresonanz (PDR) im Kern 140Ce im Energiebereich von 5,2 MeV bis 8,3 MeV basierend auf den mit dem γ3 Experimentaufbau gemessenen Daten. Insbesondere das Zerfallsverhalten der Zustände, die an der PDR beteiligt sind, wurde untersucht. Der Experimentaufbau, die Details der Analyse sowie die Resultate werden in der vorliegenden Arbeit präsentiert. Desweiteren erlaubt ein Vergleich der Ergebnisse mit theoretischen Rechnungen im quasi-particle phonon model (QPM) eine Interpretation des beobachteten Zerfallsverhaltens.

The sensitivity of the photostationary state of NOx and its implication for the oxidation capacity in a semi-rural and boreal forest region

Für das Vermögen der Atmosphäre sich selbst zu reinigen spielen Stickstoffmonoxid (NO) und Stickstoffdioxid (NO2) eine bedeutende Rolle. Diese Spurengase bestimmen die photochemische Produktion von Ozon (O3) und beeinflussen das Vorkommen von Hydroxyl- (OH) und Nitrat-Radikalen (NO3). Wenn tagsüber ausreichend Solarstrahlung und Ozon vorherrschen, stehen NO und NO2 in einem schnellen photochemischen Gleichgewicht, dem „Photostationären Gleichgewichtszustand“ (engl.: photostationary state). Die Summe von NO und NO2 wird deshalb als NOx zusammengefasst. Vorhergehende Studien zum photostationären Gleichgewichtszustand von NOx umfassen Messungen an unterschiedlichsten Orten, angefangen bei Städten (geprägt von starken Luftverschmutzungen), bis hin zu abgeschiedenen Regionen (geprägt von geringeren Luftverschmutzungen). Während der photochemische Kreislauf von NO und NO2 unter Bedingungen erhöhter NOx-Konzentrationen grundlegend verstanden ist, gibt es in ländlicheren und entlegenen Regionen, welche geprägt sind von niedrigeren NOx-Konzetrationen, signifikante Lücken im Verständnis der zugrundeliegenden Zyklierungsprozesse. Diese Lücken könnten durch messtechnische NO2-Interferenzen bedingt sein - insbesondere bei indirekten Nachweismethoden, welche von Artefakten beeinflusst sein können. Bei sehr niedrigen NOx-Konzentrationen und wenn messtechnische NO2-Interferenzen ausgeschlossen werden können, wird häufig geschlussfolgert, dass diese Verständnislücken mit der Existenz eines „unbekannten Oxidationsmittels“ (engl.: unknown oxidant) verknüpft ist. Im Rahmen dieser Arbeit wird der photostationäre Gleichgewichtszustand von NOx analysiert, mit dem Ziel die potenzielle Existenz bislang unbekannter Prozesse zu untersuchen. Ein Gasanalysator für die direkte Messung von atmosphärischem NO¬2 mittels laserinduzierter Fluoreszenzmesstechnik (engl. LIF – laser induced fluorescence), GANDALF, wurde neu entwickelt und während der Messkampagne PARADE 2011 erstmals für Feldmessungen eingesetzt. Die Messungen im Rahmen von PARADE wurden im Sommer 2011 in einem ländlich geprägten Gebiet in Deutschland durchgeführt. Umfangreiche NO2-Messungen unter Verwendung unterschiedlicher Messtechniken (DOAS, CLD und CRD) ermöglichten einen ausführlichen und erfolgreichen Vergleich von GANDALF mit den übrigen NO2-Messtechniken. Weitere relevante Spurengase und meteorologische Parameter wurden gemessen, um den photostationären Zustand von NOx, basierend auf den NO2-Messungen mit GANDALF in dieser Umgebung zu untersuchen. Während PARADE wurden moderate NOx Mischungsverhältnisse an der Messstelle beobachtet (10^2 - 10^4 pptv). Mischungsverhältnisse biogener flüchtige Kohlenwasserstoffverbindungen (BVOC, engl.: biogenic volatile organic compounds) aus dem umgebenden Wald (hauptsächlich Nadelwald) lagen in der Größenordnung 10^2 pptv vor. Die Charakteristiken des photostationären Gleichgewichtszustandes von NOx bei niedrigen NOx-Mischungsverhältnissen (10 - 10^3 pptv) wurde für eine weitere Messstelle in einem borealen Waldgebiet während der Messkampagne HUMPPA-COPEC 2010 untersucht. HUMPPA–COPEC–2010 wurde im Sommer 2010 in der SMEARII-Station in Hyytiälä, Süd-Finnland, durchgeführt. Die charakteristischen Eigenschaften des photostationären Gleichgewichtszustandes von NOx in den beiden Waldgebieten werden in dieser Arbeit verglichen. Des Weiteren ermöglicht der umfangreiche Datensatz - dieser beinhaltet Messungen von relevanten Spurengasen für die Radikalchemie (OH, HO2), sowie der totalen OH-Reaktivität – das aktuelle Verständnis bezüglich der NOx-Photochemie unter Verwendung von einem Boxmodell, in welches die gemessenen Daten als Randbedingungen eingehen, zu überprüfen und zu verbessern. Während NOx-Konzentrationen in HUMPPA-COPEC 2010 niedriger sind, im Vergleich zu PARADE 2011 und BVOC-Konzentrationen höher, sind die Zyklierungsprozesse von NO und NO2 in beiden Fällen grundlegend verstanden. Die Analyse des photostationären Gleichgewichtszustandes von NOx für die beiden stark unterschiedlichen Messstandorte zeigt auf, dass potenziell unbekannte Prozesse in keinem der beiden Fälle vorhanden sind. Die aktuelle Darstellung der NOx-Chemie wurde für HUMPPA-COPEC 2010 unter Verwendung des chemischen Mechanismus MIM3* simuliert. Die Ergebnisse der Simulation sind konsistent mit den Berechnungen basierend auf dem photostationären Gleichgewichtszustand von NOx.

Synthesis, characterization and catalytic performances of ruthenium-based catalysts for the acceptorless dehydrogenative coupling of butanol

A growing interest towards new sources of energy has led in recent years to the development of a new generation of catalysts for alcohol dehydrogenative coupling (ADC). This green, atom-efficient reaction is capable of turning alcohol derivatives into higher value and chemically more attractive ester molecules, and it finds interesting applications in the transformation of the large variety of products deriving from biomass. In the present work, a new series of ruthenium-PNP pincer complexes are investigated for the transformation of 1-butanol, one of the most challenging substrates for this type of reactions, into butyl butyrate, a short-chain symmetrical ester widely used in flavor industries. Since the reaction kinetics depends on hydrogen diffusion, the study aimed at identifying proper reactor type and right catalyst concentration to avoid mass transfer interferences and to get dependable data. A comparison between catalytic activities and productivities has been made to establish the role of the different ligands bonded both to the PNP binder and to the ruthenium metal center, and hence to find the best catalyst for this type of reaction.

Novel materials for direct X-ray detectors based on semiconducting organic polymers

Conventional inorganic materials for x-ray radiation sensors suffer from several drawbacks, including their inability to cover large curved areas, me- chanical sti ffness, lack of tissue-equivalence and toxicity. Semiconducting organic polymers represent an alternative and have been employed as di- rect photoconversion material in organic diodes. In contrast to inorganic detector materials, polymers allow low-cost and large area fabrication by sol- vent based methods. In addition their processing is compliant with fexible low-temperature substrates. Flexible and large-area detectors are needed for dosimetry in medical radiotherapy and security applications. The objective of my thesis is to achieve optimized organic polymer diodes for fexible, di- rect x-ray detectors. To this end polymer diodes based on two different semi- conducting polymers, polyvinylcarbazole (PVK) and poly(9,9-dioctyluorene) (PFO) have been fabricated. The diodes show state-of-the-art rectifying be- haviour and hole transport mobilities comparable to reference materials. In order to improve the X-ray stopping power, high-Z nanoparticle Bi2O3 or WO3 where added to realize a polymer-nanoparticle composite with opti- mized properities. X-ray detector characterization resulted in sensitivties of up to 14 uC/Gy/cm2 for PVK when diodes were operated in reverse. Addition of nanoparticles could further improve the performance and a maximum sensitivy of 19 uC/Gy/cm2 was obtained for the PFO diodes. Compared to the pure PFO diode this corresponds to a five-fold increase and thus highlights the potentiality of nanoparticles for polymer detector design. In- terestingly the pure polymer diodes showed an order of magnitude increase in sensitivity when operated in forward regime. The increase was attributed to a different detection mechanism based on the modulation of the diodes conductivity.

Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

Design of a semi-implantable hearing device for direct acoustic cochlear stimulation

A new hearing therapy based on direct acoustic cochlear stimulation was developed for the treatment of severe to profound mixed hearing loss. The device efficacy was validated in an initial clinical trial with four patients. This semi-implantable investigational device consists of an externally worn audio processor, a percutaneous connector, and an implantable microactuator. The actuator is placed in the mastoid bone, right behind the external auditory canal. It generates vibrations that are directly coupled to the inner ear fluids and that, therefore, bypass the external and the middle ear. The system is able to provide an equivalent sound pressure level of 125 dB over the frequency range between 125 and 8000 Hz. The hermetically sealed actuator is designed to provide maximal output power by keeping its dimensions small enough to enable implantation. A network model is used to simulate the dynamic characteristics of the actuator to adjust its transfer function to the characteristics of the middle ear. The geometry of the different actuator components is optimized using finite-element modeling.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

A Bootstrap Test for the Probability of Ruin in the Compound Poisson Risk Process

In this article we propose a bootstrap test for the probability of ruin in the compound Poisson risk process. We adopt the P-value approach, which leads to a more complete assessment of the underlying risk than the probability of ruin alone. We provide second-order accurate P-values for this testing problem and consider both parametric and nonparametric estimators of the individual claim amount distribution. Simulation studies show that the suggested bootstrap P-values are very accurate and outperform their analogues based on the asymptotic normal approximation.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Indigenous knowledge related to climate variability and change: insights from droughts in semi-arid areas of former Makueni District, Kenya

This article describes the indigenous knowledge (IK) that agro-pastoralists in larger Makueni District, Kenya hold and how they use it to monitor, mitigate and adapt to drought. It examines ways of integrating IK into formal monitoring, how to enhance its value and acceptability. Data was collected through target interviews, group discussions and questionnaires covering 127 households in eight villages. Daily rainfall data from 1961–2003 were analysed. Results show that agro-pastoralists hold IK on indicators of rainfall variability; they believe in IK efficacy and they rely on them. Because agro-pastoralists consult additional sources, the authors interpret that IK forms a basic knowledge frame within which agro-pastoralists position and interpret meteorological forecasts. Only a few agro-pastoralists adapt their practices in anticipation of IK-based forecasts partly due to the conditioning of the actors to the high rainfall variability characteristic of the area and partly due to lack of resources. Non-drought factors such as poverty, inadequate resources and lack of preparedness expose agro-pastoralists to drought impacts and limit their adaptive capacity. These factors need to be understood and effectively addressed to increase agro-pastoralists’ decision options and the influence of IK-based forecasts on their decision-making patterns. The limited intergenerational transfer of IK currently threatens its existence in the longer term. One way to ensure its continued existence and use is to integrate IK into the education curriculum and to link IK with formal climate change research through the participation of the local people. However, further studies are necessary to address the reliability and validity of the identified IK indicators of climate variability and change.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Faith and the Sublation of Modernity: Kierkegaard and the Transformation of Fideism

This article retraces the “genealogy” of the fideist perspective in philosophy as well as literature, especially within the writings of Søren Kierkegaard and the novel Don Quixote. It contends that a demythologized perspective of the fideist-humanist sort, based upon Erasmian tolerance and intellectual creativity and updated with the insights of post-analytic theory (e.g., the work of Alasdair MacIntyre, Richard Rorty, and Jeffrey Stout), without revoking the vocabulary of transcendence, can reinforce the weathered but still valuable post-Enlightenment moral vocabulary, and can reiterate the humaneness of liberal hope without undue encumbrance from the dogmatic baggage of traditional theological jargon and metaphysics.

Activation of the parieto-premotor network is associated with vivid motor imagery - a parametric FMRI study

The present study examined the neural basis of vivid motor imagery with parametrical functional magnetic resonance imaging. 22 participants performed motor imagery (MI) of six different right-hand movements that differed in terms of pointing accuracy needs and object involvement, i.e., either none, two big or two small squares had to be pointed at in alternation either with or without an object grasped with the fingers. After each imagery trial, they rated the perceived vividness of motor imagery on a 7-point scale. Results showed that increased perceived imagery vividness was parametrically associated with increasing neural activation within the left putamen, the left premotor cortex (PMC), the posterior parietal cortex of the left hemisphere, the left primary motor cortex, the left somatosensory cortex, and the left cerebellum. Within the right hemisphere, activation was found within the right cerebellum, the right putamen, and the right PMC. It is concluded that the perceived vividness of MI is parametrically associated with neural activity within sensorimotor areas. The results corroborate the hypothesis that MI is an outcome of neural computations based on movement representations located within motor areas.

Nanoparticle-based test measures overall propensity for calcification in serum

Vascular and soft tissue calcification contributes to cardiovascular morbidity and mortality in both the general population and CKD. Because calcium and phosphate serum concentrations are near supersaturation, the balance of inhibitors and promoters critically influences the development of calcification. An assay that measures the overall propensity for calcification to occur in serum may have clinical use. Here, we describe a nanoparticle-based assay that detects, in the presence of artificially elevated calcium and phosphate concentrations, the spontaneous transformation of spherical colloidal primary calciprotein particles (CPPs) to elongate crystalline secondary CPPs. We used characteristics of this transition to describe the intrinsic capacity of serum to inhibit the precipitation of calcium and phosphate. Using this assay, we found that both the sera of mice deficient in fetuin-A, a serum protein that inhibits calcification, and the sera of patients on hemodialysis have reduced intrinsic properties to inhibit calcification. In summary, we developed a nanoparticle-based test that measures the overall propensity for calcification in serum. The clinical use of the test requires evaluation in a prospective study.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.