Earthquake forecasting and seismic hazard analysis: some insights on the testing phase and the modeling

This thesis is divided in three chapters. In the first chapter we analyse the results of the world forecasting experiment run by the Collaboratory for the Study of Earthquake Predictability (CSEP). We take the opportunity of this experiment to contribute to the definition of a more robust and reliable statistical procedure to evaluate earthquake forecasting models. We first present the models and the target earthquakes to be forecast. Then we explain the consistency and comparison tests that are used in CSEP experiments to evaluate the performance of the models. Introducing a methodology to create ensemble forecasting models, we show that models, when properly combined, are almost always better performing that any single model. In the second chapter we discuss in depth one of the basic features of PSHA: the declustering of the seismicity rates. We first introduce the Cornell-McGuire method for PSHA and we present the different motivations that stand behind the need of declustering seismic catalogs. Using a theorem of the modern probability (Le Cam's theorem) we show that the declustering is not necessary to obtain a Poissonian behaviour of the exceedances that is usually considered fundamental to transform exceedance rates in exceedance probabilities in the PSHA framework. We present a method to correct PSHA for declustering, building a more realistic PSHA. In the last chapter we explore the methods that are commonly used to take into account the epistemic uncertainty in PSHA. The most widely used method is the logic tree that stands at the basis of the most advanced seismic hazard maps. We illustrate the probabilistic structure of the logic tree, and then we show that this structure is not adequate to describe the epistemic uncertainty. We then propose a new probabilistic framework based on the ensemble modelling that properly accounts for epistemic uncertainties in PSHA.

Action-based dynamical models of the Fornax dwarf spheroidal galaxy

Il lavoro presentato in questa Tesi si basa sul calcolo di modelli dinamici per Galassie Sferoidali Nane studiando il problema mediante l'utilizzo di funzioni di distribuzione. Si è trattato un tipo di funzioni di distribuzione, "Action-Based distribution functions", le quali sono funzioni delle sole variabili azione. Fornax è stata descritta con un'appropriata funzione di distribuzione e il problema della costruzione di modelli dinamici è stato affrontato assumendo sia un alone di materia oscura con distribuzione di densità costante nelle regioni interne sia un alone con cuspide. Per semplicità è stata assunta simmetria sferica e non è stato calcolato esplicitamente il potenziale gravitazionale della componente stellare (le stelle sono traccianti in un potenziale gravitazionale fissato). Tramite un diretto confronto con alcune osservabili, quali il profilo di densità stellare proiettata e il profilo di dispersione di velocità lungo la linea di vista, sono stati trovati alcuni modelli rappresentativi della dinamica di Fornax. Modelli calcolati tramite funzioni di distribuzione basati su azioni permettono di determinare in maniera autoconsistente profili di anisotropia. Tutti i modelli calcolati sono caratterizzati dal possedere un profilo di anisotropia con forte anisotropia tangenziale. Sono state poi comparate le stime di materia oscura di questi modelli con i più comuni e usati stimatori di massa in letteratura. E stato inoltre stimato il rapporto tra la massa totale del sistema (componente stellare e materia oscura) e la componente stellare di Fornax, entro 1600 pc ed entro i 3 kpc. Come esplorazione preliminare, in questo lavoro abbiamo anche presentato anche alcuni esempi di modelli sferici a due componenti in cui il campo gravitazionale è determinato dall'autogravità delle stelle e da un potenziale esterno che rappresenta l'alone di materia oscura.

Development of Dynamic Constraint Models for a Model Based Transient Calibration Process

Model based calibration has gained popularity in recent years as a method to optimize increasingly complex engine systems. However virtually all model based techniques are applied to steady state calibration. Transient calibration is by and large an emerging technology. An important piece of any transient calibration process is the ability to constrain the optimizer to treat the problem as a dynamic one and not as a quasi-static process. The optimized air-handling parameters corresponding to any instant of time must be achievable in a transient sense; this in turn depends on the trajectory of the same parameters over previous time instances. In this work dynamic constraint models have been proposed to translate commanded to actually achieved air-handling parameters. These models enable the optimization to be realistic in a transient sense. The air handling system has been treated as a linear second order system with PD control. Parameters for this second order system have been extracted from real transient data. The model has been shown to be the best choice relative to a list of appropriate candidates such as neural networks and first order models. The selected second order model was used in conjunction with transient emission models to predict emissions over the FTP cycle. It has been shown that emission predictions based on air-handing parameters predicted by the dynamic constraint model do not differ significantly from corresponding emissions based on measured air-handling parameters.

[(99m)Tc]Demomedin C, a radioligand based on human gastrin releasing peptide(18-27): synthesis and preclinical evaluation in gastrin releasing peptide receptor-expressing models

The synthesis and preclinical evaluation of [(99m)Tc]Demomedin C in GRPR-expressing models are reported. Demomedin C resulted by coupling a Boc-protected N(4)-chelator to neuromedin C (human GRP(18-27)), which, after (99m)Tc-labeling, afforded [(99m)Tc]Demomedin C. Demomedin C showed high affinity and selectivity for the GRPR during receptor autoradiography on human cancer samples (IC(50) in nM: GRPR, 1.4 ± 0.2; NMBR, 106 ± 18; and BB(3)R, >1000). It triggered GRPR internalization in HEK-GRPR cells and Ca(2+) release in PC-3 cells (EC(50) = 1.3 nM). [(99m)Tc]Demomedin C rapidly and specifically internalized at 37 °C in PC-3 cells and was stable in mouse plasma. [(99m)Tc]Demomedin C efficiently and specifically localized in human PC-3 implants in mice (9.84 ± 0.81%ID/g at 1 h pi; 6.36 ± 0.85%ID/g at 4 h pi, and 0.41 ± 0.07%ID/g at 4 h pi block). Thus, human GRP-based radioligands, such as [(99m)Tc]Demomedin C, can successfully target GRPR-expressing human tumors in vivo while displaying attractive biological features--e.g. higher GRPR-selectivity--vs their frog-homologues.

Defining new criteria for selection of cell-based intestinal models using publicly available databases

The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies.

Fastener-Based Computational Models of Cold-Formed Steel Shear Walls

Cold-formed steel (CFS) combined with wood sheathing, such as oriented strand board (OSB), forms shear walls that can provide lateral resistance to seismic forces. The ability to accurately predict building deformations in damaged states under seismic excitations is a must for modern performance-based seismic design. However, few static or dynamic tests have been conducted on the non-linear behavior of CFS shear walls. Thus, the purpose of this research work is to provide and demonstrate a fastener-based computational model of CFS wall models that incorporates essential nonlinearities that may eventually lead to improvement of the current seismic design requirements. The approach is based on the understanding that complex interaction of the fasteners with the sheathing is an important factor in the non-linear behavior of the shear wall. The computational model consists of beam-column elements for the CFS framing and a rigid diaphragm for the sheathing. The framing and sheathing are connected with non-linear zero-length fastener elements to capture the OSB sheathing damage surrounding the fastener area. Employing computational programs such as OpenSees and MATLAB, 4 ft. x 9 ft., 8 ft. x 9 ft. and 12 ft. x 9 ft. shear wall models are created, and monotonic lateral forces are applied to the computer models. The output data are then compared and analyzed with the available results of physical testing. The results indicate that the OpenSees model can accurately capture the initial stiffness, strength and non-linear behavior of the shear walls.

An early warning system for hypoglycemic/hyperglycemic events based on fusion of adaptive prediction models

Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia/hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy.