Numerical simulations of magma chamber dynamics at Campi Flegrei, and associated seismicity, deformation and gravity changes

Understanding the complex relationships between quantities measured by volcanic monitoring network and shallow magma processes is a crucial headway for the comprehension of volcanic processes and a more realistic evaluation of the associated hazard. This question is very relevant at Campi Flegrei, a volcanic quiescent caldera immediately north-west of Napoli (Italy). The system activity shows a high fumarole release and periodic ground slow movement (bradyseism) with high seismicity. This activity, with the high people density and the presence of military and industrial buildings, makes Campi Flegrei one of the areas with higher volcanic hazard in the world. In such a context my thesis has been focused on magma dynamics due to the refilling of shallow magma chambers, and on the geophysical signals detectable by seismic, deformative and gravimetric monitoring networks that are associated with this phenomenologies. Indeed, the refilling of magma chambers is a process frequently occurring just before a volcanic eruption; therefore, the faculty of identifying this dynamics by means of recorded signal analysis is important to evaluate the short term volcanic hazard. The space-time evolution of dynamics due to injection of new magma in the magma chamber has been studied performing numerical simulations with, and implementing additional features in, the code GALES (Longo et al., 2006), recently developed and still on the upgrade at the Istituto Nazionale di Geofisica e Vulcanologia in Pisa (Italy). GALES is a finite element code based on a physico-mathematical two dimensional, transient model able to treat fluids as multiphase homogeneous mixtures, compressible to incompressible. The fundamental equations of mass, momentum and energy balance are discretised both in time and space using the Galerkin Least-Squares and discontinuity-capturing stabilisation technique. The physical properties of the mixture are computed as a function of local conditions of magma composition, pressure and temperature.The model features enable to study a broad range of phenomenologies characterizing pre and sin-eruptive magma dynamics in a wide domain from the volcanic crater to deep magma feeding zones. The study of displacement field associated with the simulated fluid dynamics has been carried out with a numerical code developed by the Geophysical group at the University College Dublin (O’Brien and Bean, 2004b), with whom we started a very profitable collaboration. In this code, the seismic wave propagation in heterogeneous media with free surface (e.g. the Earth’s surface) is simulated using a discrete elastic lattice where particle interactions are controlled by the Hooke’s law. This method allows to consider medium heterogeneities and complex topography. The initial and boundary conditions for the simulations have been defined within a coordinate project (INGV-DPC 2004-06 V3_2 “Research on active volcanoes, precursors, scenarios, hazard and risk - Campi Flegrei”), to which this thesis contributes, and many researchers experienced on Campi Flegrei in volcanological, seismic, petrological, geochemical fields, etc. collaborate. Numerical simulations of magma and rock dynamis have been coupled as described in the thesis. The first part of the thesis consists of a parametric study aimed at understanding the eect of the presence in magma of carbon dioxide in magma in the convection dynamics. Indeed, the presence of this volatile was relevant in many Campi Flegrei eruptions, including some eruptions commonly considered as reference for a future activity of this volcano. A set of simulations considering an elliptical magma chamber, compositionally uniform, refilled from below by a magma with volatile content equal or dierent from that of the resident magma has been performed. To do this, a multicomponent non-ideal magma saturation model (Papale et al., 2006) that considers the simultaneous presence of CO2 and H2O, has been implemented in GALES. Results show that the presence of CO2 in the incoming magma increases its buoyancy force promoting convection ad mixing. The simulated dynamics produce pressure transients with frequency and amplitude in the sensitivity range of modern geophysical monitoring networks such as the one installed at Campi Flegrei . In the second part, simulations more related with the Campi Flegrei volcanic system have been performed. The simulated system has been defined on the basis of conditions consistent with the bulk of knowledge of Campi Flegrei and in particular of the Agnano-Monte Spina eruption (4100 B.P.), commonly considered as reference for a future high intensity eruption in this area. The magmatic system has been modelled as a long dyke refilling a small shallow magma chamber; magmas with trachytic and phonolitic composition and variable volatile content of H2O and CO2 have been considered. The simulations have been carried out changing the condition of magma injection, the system configuration (magma chamber geometry, dyke size) and the resident and refilling magma composition and volatile content, in order to study the influence of these factors on the simulated dynamics. Simulation results allow to follow each step of the gas-rich magma ascent in the denser magma, highlighting the details of magma convection and mixing. In particular, the presence of more CO2 in the deep magma results in more ecient and faster dynamics. Through this simulations the variation of the gravimetric field has been determined. Afterward, the space-time distribution of stress resulting from numerical simulations have been used as boundary conditions for the simulations of the displacement field imposed by the magmatic dynamics on rocks. The properties of the simulated domain (rock density, P and S wave velocities) have been based on data from literature on active and passive tomographic experiments, obtained through a collaboration with A. Zollo at the Dept. of Physics of the Federici II Univeristy in Napoli. The elasto-dynamics simulations allow to determine the variations of the space-time distribution of deformation and the seismic signal associated with the studied magmatic dynamics. In particular, results show that these dynamics induce deformations similar to those measured at Campi Flegrei and seismic signals with energies concentrated on the typical frequency bands observed in volcanic areas. The present work shows that an approach based on the solution of equations describing the physics of processes within a magmatic fluid and the surrounding rock system is able to recognise and describe the relationships between geophysical signals detectable on the surface and deep magma dynamics. Therefore, the results suggest that the combined study of geophysical data and informations from numerical simulations can allow in a near future a more ecient evaluation of the short term volcanic hazard.

Sustainable processes using heterogeneous acid catalysts. Some examples of industrial interest.

In recent years the need for the design of more sustainable processes and the development of alternative reaction routes to reduce the environmental impact of the chemical industry has gained vital importance. Main objectives especially regard the use of renewable raw materials, the exploitation of alternative energy sources, the design of inherently safe processes and of integrated reaction/separation technologies (e.g. microreactors and membranes), the process intensification, the reduction of waste and the development of new catalytic pathways. The present PhD thesis reports results derived during a three years research period at the School of Chemical Sciences of Alma Mater Studiorum-University of Bologna, Dept. of Industrial Chemistry and Materials (now Dept. of Industrial Chemistry “Toso Montanari”), under the supervision of Prof. Fabrizio Cavani (Catalytic Processes Development Group). Three research projects in the field of heterogeneous acid catalysis focused on potential industrial applications were carried out. The main project, regarding the conversion of lignocellulosic materials to produce monosaccharides (important intermediates for production of biofuels and bioplatform molecules) was financed and carried out in collaboration with the Italian oil company eni S.p.A. (Istituto eni Donegani-Research Center for non-Conventional Energies, Novara, Italy) The second and third academic projects dealt with the development of green chemical processes for fine chemicals manufacturing. In particular, (a) the condensation reaction between acetone and ammonia to give triacetoneamine (TAA), and (b) the Friedel-Crafts acylation of phenol with benzoic acid were investigated.

Impact of anthropogenic stressors on the population genetics of the common bioindicator Dreissena polymorpha (Pallas, 1771)

Toxicant inputs from agriculture, industry and human settlements have been shown to severely affect freshwater ecosystems. Pollution can lead to changes in population genetic patterns through various genetic and stochastic processes. In my thesis, I investigated the impact of anthropogenic stressors on the population genetics of the zebra mussel Dreissena polymorpha. In order to analyze the genetics of zebra mussel populations, I isolated five new highly polymorphic microsatellite loci. Out of those and other already existing microsatellite markers for this species, I established a robust marker set of six microsatellite loci for D. polymorpha. rnMonitoring the biogeographical background is an important requirement when integrating population genetic measures into ecotoxicological studies. I analyzed the biogeographical background of eleven populations in a section of the River Danube (in Hungary and Croatia) and some of its tributaries, and another population in the River Rhine as genetic outgroup. Moreover, I measured abiotic water parameters at the sampling sites and analyzed if they were correlated with the genetic parameters of the populations. The genetic differentiation was basically consistent with the overall biogeographical history of the populations in the study region. However, the genetic diversity of the populations was not influenced by the geographical distance between the populations, but by the environmental factors oxygen and temperature and also by other unidentified factors. I found strong evidence that genetic adaptation of zebra mussel populations to local habitat conditions had influenced the genetic constitution of the populations. Moreover, by establishing the biogeographical baseline of molecular variance in the study area, I laid the foundation for interpreting population genetic results in ecotoxicological experiments in this region.rnIn a cooperation project with the Department of Zoology of the University of Zagreb, I elaborated an integrated approach in biomonitoring with D. polymorpha by combining the analysis techniques of microsatellite analysis, Comet assay and micronucleus test (MNT). This approach was applied in a case study on freshwater contamination by an effluent of a wastewater treatment plant (WWTP) in the River Drava (Croatia) and a complementary laboratory experiment. I assessed and compared the genetic status of two zebra mussel populations from a contaminated and a reference site. Microsatellite analysis suggested that the contaminated population had undergone a genetic bottleneck, caused by random genetic drift and selection, whereas a bottleneck was not detected in the reference population. The Comet assay did not indicate any difference in DNA damage between the two populations, but MNT revealed that the contaminated population had an increased percentage of micronuclei in hemocytes in comparison to the reference population. The laboratory experiment with mussels exposed to municipal wastewater revealed that mussels from the contaminated site had a lower percentage of tail DNA and a higher percentage of micronuclei than the reference population. These differences between populations were probably caused by an overall decreased fitness of mussels from the contaminated site due to genetic drift and by an enhanced DNA repair mechanism due to adaptation to pollution in the source habitat. Overall, the combination of the three biomarkers provided sufficient information on the impact of both treated and non-treated municipal wastewater on the genetics of zebra mussels at different levels of biological organization.rnIn my thesis, I could show that the newly established marker set of six microsatellite loci provided reliable and informative data for population genetic analyses of D. polymorpha. The adaptation of the analyzed zebra mussel populations to the local conditions of their habitat had a strong influence on their genetic constitution. We found evidence that the different genetic constitutions of two populations had influenced the outcome of our ecotoxicological experiment. Overall, the integrated approach in biomonitoring gave comprehensive information about the impact of both treated and non-treated municipal wastewater on the genetics of zebra mussels at different levels of biological organization and was well practicable in a first case study.

Material properties of common suture materials in orthopaedic surgery

Suture materials in orthopaedic surgery are used for closure of wounds, repair of fascia, muscles, tendons, ligaments, joint capsules, and cerclage or tension band of certain fractures. The purpose of this study was to compare the biomechanical properties of eleven commonly used sutures in orthopaedic surgery. Three types of braided non-absorbable and one type of braided absorbable suture material with different calibers (n=77) underwent biomechanical testing for maximum load to failure, strain, and stiffness. All samples were tied by one surgeon with a single SMC (Seoul Medical Center) knot and three square knots. The maximum load to failure and strain were highest for #5 FiberWire and lowest for #0 Ethibond Excel (p<0.001). The stiffness was highest for #5 FiberWire and lowest for #2-0 Vicryl (p<0.001). In all samples, the failure of the suture material occurred at the knot There was no slippage of the knot in any of the samples tested. This data will assist the orthopaedic surgeon in selection and application of appropriate suture materials and calibers to specific tasks.

Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

POOR PERFORMANCE OF BOOTSTRAP CONFIDENCE INTERVALS FOR THE LOCATION OF A QUANTITATIVE TRAIT LOUCS

The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

Multiple Lab Comparison of Microarray Platforms

Microarray technology is a powerful tool able to measure RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of crossplatform meta-analysis studies rapidly increase, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we notice that none of the previously published papers consider differences between labs. For this paper, a consortium of ten labs from the Washington DC/Baltimore (USA) area was formed to compare three heavily used platforms using identical RNA samples: Appropriate statistical analysis demonstrates that relatively large differences exist between labs using the same platform, but that the results from the best performing labs agree rather well. Supplemental material is available from http://www.biostat.jhsph.edu/~ririzarr/techcomp/

A Cox Model for Biostatistics of the Future

Professor Sir David R. Cox (DRC) is widely acknowledged as among the most important scientists of the second half of the twentieth century. He inherited the mantle of statistical science from Pearson and Fisher, advanced their ideas, and translated statistical theory into practice so as to forever change the application of statistics in many fields, but especially biology and medicine. The logistic and proportional hazards models he substantially developed, are arguably among the most influential biostatistical methods in current practice. This paper looks forward over the period from DRC's 80th to 90th birthdays, to speculate about the future of biostatistics, drawing lessons from DRC's contributions along the way. We consider "Cox's model" of biostatistics, an approach to statistical science that: formulates scientific questions or quantities in terms of parameters gamma in probability models f(y; gamma) that represent in a parsimonious fashion, the underlying scientific mechanisms (Cox, 1997); partition the parameters gamma = theta, eta into a subset of interest theta and other "nuisance parameters" eta necessary to complete the probability distribution (Cox and Hinkley, 1974); develops methods of inference about the scientific quantities that depend as little as possible upon the nuisance parameters (Barndorff-Nielsen and Cox, 1989); and thinks critically about the appropriate conditional distribution on which to base infrences. We briefly review exciting biomedical and public health challenges that are capable of driving statistical developments in the next decade. We discuss the statistical models and model-based inferences central to the CM approach, contrasting them with computationally-intensive strategies for prediction and inference advocated by Breiman and others (e.g. Breiman, 2001) and to more traditional design-based methods of inference (Fisher, 1935). We discuss the hierarchical (multi-level) model as an example of the future challanges and opportunities for model-based inference. We then consider the role of conditional inference, a second key element of the CM. Recent examples from genetics are used to illustrate these ideas. Finally, the paper examines causal inference and statistical computing, two other topics we believe will be central to biostatistics research and practice in the coming decade. Throughout the paper, we attempt to indicate how DRC's work and the "Cox Model" have set a standard of excellence to which all can aspire in the future.