Comparison of Nonmesonic Hypernuclear Decay Rates Computed in Laboratory and Center-of-Mass Coordinates

In this work we compute the one-nucleon-induced nonmesonic hypernuclear decay rates of He-5(Lambda), C-12(Lambda) and C-13(Lambda) using a formalism based on the independent particle shell model in terms of laboratory coordinates. To ascertain the correctness and precision of the method, these results are compared with those obtained using a formalism in terms of center-of-mass coordinates, which has been previously reported in the literature. The formalism in terms of laboratory coordinates will be useful in the shell-model approach to two-nucleon-induced transitions.

A Systematic Mapping on the Role-Permission Relationship in Role Based Access Control Models

Access control is a key component of security in any computer system. In the last two decades, the research on Role Basead Access Control Models was intense. One of the most important components of a Role Based Model is the Role-Permission Relationship. In this paper, the technique of systematic mapping is used to identify, extract and analyze many approaches applied to establish the Role-Permission Relationship. The main goal of this mapping is pointing directions of significant research in the area of Role Based Access Control Models.

A bayesian model for mixed responses and skew laten variable to measure HRQoL in children

The aim of the thesi is to formulate a suitable Item Response Theory (IRT) based model to measure HRQoL (as latent variable) using a mixed responses questionnaire and relaxing the hypothesis of normal distributed latent variable. The new model is a combination of two models already presented in literature, that is, a latent trait model for mixed responses and an IRT model for Skew Normal latent variable. It is developed in a Bayesian framework, a Markov chain Monte Carlo procedure is used to generate samples of the posterior distribution of the parameters of interest. The proposed model is test on a questionnaire composed by 5 discrete items and one continuous to measure HRQoL in children, the EQ-5D-Y questionnaire. A large sample of children collected in the schools was used. In comparison with a model for only discrete responses and a model for mixed responses and normal latent variable, the new model has better performances, in term of deviance information criterion (DIC), chain convergences times and precision of the estimates.

Aeolian geomorphodynamics in endorheic basins of the Mongolian Gobi Desert

Die vorliegende Arbeit ist im Zuge des DFG Projektes Spätpleistozäne, holozäne und aktuelle Geomorphodynamik in abflusslosen Becken der Mongolischen Gobi´´ entstanden. Das Arbeitsgebiet befindet sich in der südlichen Mongolei im nördlichen Teil der Wüste Gobi. Neben einigen Teilen der Sahara (Heintzenberg, 2009), beispielsweise das Bodélé Becken des nördlichen Tschads (z.B. Washington et al., 2006a; Todd et al., 2006; Warren et al., 2007) wird Zentralasien als ein Hauptliefergebiet für Partikel in die globale Zirkulation der Atmosphäre gesehen (Goudie, 2009). Hauptaugenmerk liegt hierbei besonders auf den abflusslosen Becken und deren Sedimentablagerungen. Die, der Deflation ausgesetzten Flächen der Seebecken, sind hauptsächliche Quelle für Partikel die sich in Form von Staub respektive Sand ausbreiten. Im Hinblick auf geomorphologische Landschaftsentwicklung wurde der Zusammenhang von Beckensedimenten zu Hangdepositionen numerisch simuliert. Ein von Grunert and Lehmkuhl (2004) publiziertes Model, angelehnt an Ideen von Pye (1995) wird damit in Betracht gezogen. Die vorliegenden Untersuchungen modellieren Verbreitungsmechanismen auf regionaler Ebene ausgehend von einer größeren Anzahl an einzelnen punktuellen Standorten. Diese sind repräsentativ für die einzelnen geomorphologischen Systemglieder mit möglicherweise einer Beteiligung am Budget aeolischer Geomorphodynamik. Die Bodenbedeckung durch das charakteristische Steinpflaster der Gobi - Region, sowie unter anderem Korngrößenverteilungen der Oberflächensedimente wurden untersucht. Des Weiteren diente eine zehnjährige Zeitreihe (Jan 1998 bis Dez 2007) meteorologischer Daten als Grundlage zur Analyse der Bedingungen für äolische Geomorphodynamik. Die Daten stammen von 32 staatlichen mongolischen Wetterstationen aus der Region und Teile davon wurden für die Simulationen verwendet. Zusätzlich wurden atmosphärische Messungen zur Untersuchung der atmosphärischen Stabilität und ihrer tageszeitlichen Variabilität mit Mess-Drachenaufstiegen vorgenommen. Die Feldbefunde und auch die Ergebnisse der Laboruntersuchungen sowie der Datensatz meteorologischer Parameter dienten als Eingangsparameter für die Modellierungen. Emissionsraten der einzelnen Standorte und die Partikelverteilung im 3D Windfeld wurden modelliert um die Konvektivität der Beckensedimente und Hangdepositionen zu simulieren. Im Falle hoher mechanischer Turbulenz der bodennahen Luftschicht (mit einhergehender hoher Wind Reibungsgeschwindigkeit), wurde generell eine neutrale Stabilität festgestellt und die Simulationen von Partikelemission sowie deren Ausbreitung und Deposition unter neutraler Stabilitätsbedingung berechnet. Die Berechnung der Partikelemission wurde auf der Grundlage eines sehr vereinfachten missionsmodells in Anlehnung an bestehende Untersuchungen (Laurent et al., 2006; Darmenova et al., 2009; Shao and Dong, 2006; Alfaro, 2008) durchgeführt. Sowohl 3D Windfeldkalkulationen als auch unterschiedliche Ausbreitungsszenarien äolischer Sedimente wurden mit dem kommerziellen Programm LASAT® (Lagrange-Simulation von Aerosol-Transport) realisiert. Diesem liegt ein Langargischer Algorithmus zugrunde, mittels dessen die Verbreitung einzelner Partikel im Windfeld mit statistischer Wahrscheinlichkeit berechnet wird. Über Sedimentationsparameter kann damit ein Ausbreitungsmodell der Beckensedimente in Hinblick auf die Gebirgsfußflächen und -hänge generiert werden. Ein weiterer Teil der Untersuchungen beschäftigt sich mit der geochemischen Zusammensetzung der Oberflächensedimente. Diese Proxy sollte dazu dienen die simulierten Ausbreitungsrichtungen der Partikel aus unterschiedlichen Quellregionen nach zu verfolgen. Im Falle der Mongolischen Gobi zeigte sich eine weitestgehende Homogenität der Minerale und chemischen Elemente in den Sedimenten. Laser Bebohrungen einzelner Sandkörner zeigten nur sehr leichte Unterschiede in Abhängigkeit der Quellregionen. Die Spektren der Minerale und untersuchten Elemente deuten auf graitische Zusammensetzungen hin. Die, im Untersuchungsgebiet weit verbreiteten Alkali-Granite (Jahn et al., 2009) zeigten sich als hauptverantwortlich für die Sedimentproduktion im Untersuchungsgebiet. Neben diesen Mineral- und Elementbestimmungen wurde die Leichtmineralfraktion auf die Charakteristik des Quarzes hin untersucht. Dazu wurden Quarzgehalt, Kristallisation und das Elektronen-Spin-Resonanz Signal des E’1 - Centers in Sauerstoff Fehlstellungen des SiO2 Gitters bestimmt. Die Untersuchungen sind mit dem Methodenvorschlag von Sun et al. (2007) durchgeführt worden und sind prinzipiell gut geeignet um Herkunftsanalysenrndurchzuführen. Eine signifikante Zuordnung der einzelnen Quellgebiete ist jedoch auch in dieser Proxy nicht zu finden gewesen.

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.

Agent-based simulation for renewable energy incentive design

In this thesis, we propose a novel approach to model the diffusion of residential PV systems. For this purpose, we use an agent-based model where agents are the families living in the area of interest. The case study is the Emilia-Romagna Regional Energy plan, which aims to increase the produc- tion of electricity from renewable energy. So, we study the microdata from the Survey on Household Income and Wealth (SHIW) provided by Bank of Italy in order to obtain the characteristics of families living in Emilia-Romagna. These data have allowed us to artificial generate families and reproduce the socio-economic aspects of the region. The families generated by means of a software are placed on the virtual world by associating them with the buildings. These buildings are acquired by analysing the vector data of regional buildings made available by the region. Each year, the model determines the level of diffusion by simulating the installed capacity. The adoption behaviour is influenced by social interactions, household’s economic situation, the environmental benefits arising from the adoption and the payback period of the investment.

Modelling and simulating in systems biology: an approach based on multi-agent systems

Systems Biology is an innovative way of doing biology recently raised in bio-informatics contexts, characterised by the study of biological systems as complex systems with a strong focus on the system level and on the interaction dimension. In other words, the objective is to understand biological systems as a whole, putting on the foreground not only the study of the individual parts as standalone parts, but also of their interaction and of the global properties that emerge at the system level by means of the interaction among the parts. This thesis focuses on the adoption of multi-agent systems (MAS) as a suitable paradigm for Systems Biology, for developing models and simulation of complex biological systems. Multi-agent system have been recently introduced in informatics context as a suitabe paradigm for modelling and engineering complex systems. Roughly speaking, a MAS can be conceived as a set of autonomous and interacting entities, called agents, situated in some kind of nvironment, where they fruitfully interact and coordinate so as to obtain a coherent global system behaviour. The claim of this work is that the general properties of MAS make them an effective approach for modelling and building simulations of complex biological systems, following the methodological principles identified by Systems Biology. In particular, the thesis focuses on cell populations as biological systems. In order to support the claim, the thesis introduces and describes (i) a MAS-based model conceived for modelling the dynamics of systems of cells interacting inside cell environment called niches. (ii) a computational tool, developed for implementing the models and executing the simulations. The tool is meant to work as a kind of virtual laboratory, on top of which kinds of virtual experiments can be performed, characterised by the definition and execution of specific models implemented as MASs, so as to support the validation, falsification and improvement of the models through the observation and analysis of the simulations. A hematopoietic stem cell system is taken as reference case study for formulating a specific model and executing virtual experiments.

Analysis and numerical solution of the Peterlin viscoelastic model

Liquids and gasses form a vital part of nature. Many of these are complex fluids with non-Newtonian behaviour. We introduce a mathematical model describing the unsteady motion of an incompressible polymeric fluid. Each polymer molecule is treated as two beads connected by a spring. For the nonlinear spring force it is not possible to obtain a closed system of equations, unless we approximate the force law. The Peterlin approximation replaces the length of the spring by the length of the average spring. Consequently, the macroscopic dumbbell-based model for dilute polymer solutions is obtained. The model consists of the conservation of mass and momentum and time evolution of the symmetric positive definite conformation tensor, where the diffusive effects are taken into account. In two space dimensions we prove global in time existence of weak solutions. Assuming more regular data we show higher regularity and consequently uniqueness of the weak solution. For the Oseen-type Peterlin model we propose a linear pressure-stabilized characteristics finite element scheme. We derive the corresponding error estimates and we prove, for linear finite elements, the optimal first order accuracy. Theoretical error of the pressure-stabilized characteristic finite element scheme is confirmed by a series of numerical experiments.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

ABCtoolbox: a versatile toolkit for approximate Bayesian computations

Background The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. Results Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. Conclusion ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.

Levels and determinants of inflammatory biomarkers in a Swiss population-based sample (CoLaus study)

Objective to assess the levels and determinants of interleukin (IL)-1β, IL-6, tumour necrosis factor (TNF)-α and C-reactive protein (CRP) in a healthy Caucasian population. Methods population sample of 2884 men and 3201 women aged 35 to 75. IL-1β, IL-6 and TNF-α were assessed by a multiplexed particle-based flow cytometric assay and CRP by an immunometric assay. Results Spearman rank correlations between duplicate cytokine measurements (N = 80) ranged between 0.89 and 0.96; intra-class correlation coefficients ranged between 0.94 and 0.97, indicating good reproducibility. Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1β, IL-6 and TNF-α levels below detection limits, respectively. Median (interquartile range) for participants with detectable values were 1.17 (0.48–3.90) pg/ml for IL-1β; 1.47 (0.71–3.53) pg/ml for IL-6; 2.89 (1.82–4.53) pg/ml for TNF-α and 1.3 (0.6–2.7) ng/ml for CRP. On multivariate analysis, greater age was the only factor inversely associated with IL-1β levels. Male sex, increased BMI and smoking were associated with greater IL-6 levels, while no relationship was found for age and leisure-time PA. Male sex, greater age, increased BMI and current smoking were associated with greater TNF-α levels, while no relationship was found with leisure-time PA. CRP levels were positively related to age, BMI and smoking, and inversely to male sex and physical activity. Conclusion Population-based levels of several cytokines were established. Increased age and BMI, and to a lesser degree sex and smoking, significantly and differentially impact cytokine levels, while leisure-time physical activity has little effect.

Tracing of 15N in a mountain spruce forest: comparison of experimental data with th TRACE model

Despite numerous studies about nitrogen-cycling in forest ecosystems, many uncertainties remain, especially regarding the longer-term nitrogen accumulation. To contribute to filling this gap, the dynamic process-based model TRACE, with the ability to simulate 15N tracer redistribution in forest ecosystems was used to study N cycling processes in a mountain spruce forest of the northern edge of the Alps in Switzerland (Alptal, SZ). Most modeling analyses of N-cycling and C-N interactions have very limited ability to determine whether the process interactions are captured correctly. Because the interactions in such a system are complex, it is possible to get the whole-system C and N cycling right in a model without really knowing if the way the model combines fine-scale interactions to derive whole-system cycling is correct. With the possibility to simulate 15N tracer redistribution in ecosystem compartments, TRACE features a very powerful tool for the validation of fine-scale processes captured by the model. We first adapted the model to the new site (Alptal, Switzerland; long-term low-dose N-amendment experiment) by including a new algorithm for preferential water flow and by parameterizing of differences in drivers such as climate, N deposition and initial site conditions. After the calibration of key rates such as NPP and SOM turnover, we simulated patterns of 15N redistribution to compare against 15N field observations from a large-scale labeling experiment. The comparison of 15N field data with the modeled redistribution of the tracer in the soil horizons and vegetation compartments shows that the majority of fine-scale processes are captured satisfactorily. Particularly, the model is able to reproduce the fact that the largest part of the N deposition is immobilized in the soil. The discrepancies of 15N recovery in the LF and M soil horizon can be explained by the application method of the tracer and by the retention of the applied tracer by the well developed moss layer, which is not considered in the model. Discrepancies in the dynamics of foliage and litterfall 15N recovery were also observed and are related to the longevity of the needles in our mountain forest. As a next step, we will use the final Alptal version of the model to calculate the effects of climate change (temperature, CO2) and N deposition on ecosystem C sequestration in this regionally representative Norway spruce (Picea abies) stand.

High temperature, low cycle fatigue of a hybrid particulate/fiber aluminum metal-matrix composite

The effect of shot particles on the high temperature, low cycle fatigue of a hybrid fiber/particulate metal-matrix composite (MMC) was studied. Two hybrid composites with the general composition A356/35%SiC particle/5%Fiber (one without shot) were tested. It was found that shot particles acting as stress concentrators had little effect on the fatigue performance. It appears that fibers with a high silica content were more likely to debond from the matrix. Final failure of the composite was found to occur preferentially in the matrix. SiC particles fracture progressively during fatigue testing, leading to higher stress in the matrix, and final failure by matrix overload. A continuum mechanics based model was developed to predict failure in fatigue based on the tensile properties of the matrix and particles. By accounting for matrix yielding and recovery, composite creep and particle strength distribution, failure of the composite was predicted.

A model of the roles of essential kinases in the induction and expression of late long-term potentiation.

The induction of late long-term potentiation (L-LTP) involves complex interactions among second-messenger cascades. To gain insights into these interactions, a mathematical model was developed for L-LTP induction in the CA1 region of the hippocampus. The differential equation-based model represents actions of protein kinase A (PKA), MAP kinase (MAPK), and CaM kinase II (CAMKII) in the vicinity of the synapse, and activation of transcription by CaM kinase IV (CAMKIV) and MAPK. L-LTP is represented by increases in a synaptic weight. Simulations suggest that steep, supralinear stimulus-response relationships between stimuli (e.g., elevations in [Ca(2+)]) and kinase activation are essential for translating brief stimuli into long-lasting gene activation and synaptic weight increases. Convergence of multiple kinase activities to induce L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply with the number of brief (tetanic) electrical stimuli. The model simulates tetanic, -burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to delineate mechanisms underlying L-LTP induction and expression. For example, the cAMP antagonist RpcAMPs, which inhibits L-LTP induction, is predicted to inhibit ERK activation. The model also appears useful to clarify similarities and differences between hippocampal L-LTP and long-term synaptic strengthening in other systems.

Multi-scale micro-structure generation strategy for up-scaling transport in clays

Clays and claystones are used as backfill and barrier materials in the design of waste repositories, because they act as hydraulic barriers and retain contaminants. Transport through such barriers occurs mainly by molecular diffusion. There is thus an interest to relate the diffusion properties of clays to their structural properties. In previous work, we have developed a concept for up-scaling pore-scale molecular diffusion coefficients using a grid-based model for the sample pore structure. Here we present an operational algorithm which can generate such model pore structures of polymineral materials. The obtained pore maps match the rock’s mineralogical components and its macroscopic properties such as porosity, grain and pore size distributions. Representative ensembles of grains in 2D or 3D are created by a lattice Monte Carlo (MC) method, which minimizes the interfacial energy of grains starting from an initial grain distribution. Pores are generated at grain boundaries and/or within grains. The method is general and allows to generate anisotropic structures with grains of approximately predetermined shapes, or with mixtures of different grain types. A specific focus of this study was on the simulation of clay-like materials. The generated clay pore maps were then used to derive upscaled effective diffusion coefficients for non-sorbing tracers using a homogenization technique. The large number of generated maps allowed to check the relations between micro-structural features of clays and their effective transport parameters, as is required to explain and extrapolate experimental diffusion results. As examples, we present a set of 2D and 3D simulations and investigated the effects of nanopores within particles (interlayer pores) and micropores between particles. Archie’s simple power law is followed in systems with only micropores. When nanopores are present, additional parameters are required; the data reveal that effective diffusion coefficients could be described by a sum of two power functions, related to the micro- and nanoporosity. We further used the model to investigate the relationships between particle orientation and effective transport properties of the sample.