Constraints on the thermal evolution of the Adriatic margin during Jurassic continental break-up: U–Pb dating of rutile from the Ivrea–Verbano Zone, Italy

The Ivrea–Verbano Zone (IVZ), northern Italy, exposes an attenuated section through the Permian lower crust that records high-temperature metamorphism under lower crustal conditions and a protracted history of extension and exhumation associated partly with the Jurassic opening of the Alpine Tethys ocean. This study presents SHRIMP U–Pb geochronology of rutile from seven granulite facies metapelites from the base of the IVZ, collected from locations spanning ~35 km along the strike of Paleozoic fabrics. Rutile crystallised during Permian high-temperature metamorphism and anatexis, yet all samples give Jurassic rutile U–Pb ages that record cooling through 650–550 °C. Rutile age distributions are dominated by a peak at ~160 Ma, with a subordinate peak at ~175 Ma. Both ~160 and ~175 Ma age populations show excellent agreement between samples, indicating that the two distinctive cooling stages they record were synchronous on a regional scale. The ~175 Ma population is interpreted to record cooling in the footwall of rift-related faults and shear zones, for which widespread activity in the Lower Jurassic has been documented along the western margin of the Adriatic plate. The ~160 Ma age population postdates the activity of all known rift-related structures within the Adriatic margin, but coincides with extensive gabbroic magmatism and exhumation of sub-continental mantle to the floor of the Alpine Tethys, west of the Ivrea Zone. We propose that this ~160 Ma early post-rift age population records regional cooling following episodic heating of the distal Adriatic margin, likely related to extreme lithospheric thinning and associated advection of the asthenosphere to shallow levels. The partial preservation of the ~175 Ma age cluster suggests that the post-rift (~160 Ma) heating pulse was of short duration. The regional consistency of the data presented here, which is in contrast to many other thermochronometers in the IVZ, demonstrates the value of the rutile U–Pb technique for probing the thermal evolution of high-grade metamorphic terrains. In the IVZ, a significant decoupling between Zr-in-rutile temperatures and U–Pb ages of rutile is observed, with the two systems recording events ~120 Ma apart.

Comet 67P/Churyumov-Gerasimenko: Constraints on its origin from OSIRIS observations

Context. One of the main aims of the ESA Rosetta mission is to study the origin of the solar system by exploring comet 67P/Churyumov-Gerasimenko at close range. Aims. In this paper we discuss the origin and evolution of comet 67P/Churyumov-Gerasimenko in relation to that of comets in general and in the framework of current solar system formation models. Methods. We use data from the OSIRIS scientific cameras as basic constraints. In particular, we discuss the overall bi-lobate shape and the presence of key geological features, such as layers and fractures. We also treat the problem of collisional evolution of comet nuclei by a particle-in-a-box calculation for an estimate of the probability of survival for 67P/Churyumov-Gerasimenko during the early epochs of the solar system. Results. We argue that the two lobes of the 67P/Churyumov-Gerasimenko nucleus are derived from two distinct objects that have formed a contact binary via a gentle merger. The lobes are separate bodies, though sufficiently similar to have formed in the same environment. An estimate of the collisional rate in the primordial, trans-planetary disk shows that most comets of similar size to 67P/Churyumov-Gerasimenko are likely collisional fragments, although survival of primordial planetesimals cannot be excluded. Conclusions. A collisional origin of the contact binary is suggested, and the low bulk density of the aggregate and abundance of volatile species show that a very gentle merger must have occurred. We thus consider two main scenarios: the primordial accretion of planetesimals, and the re-accretion of fragments after an energetic impact onto a larger parent body. We point to the primordial signatures exhibited by 67P/Churyumov-Gerasimenko and other comet nuclei as critical tests of the collisional evolution.

Asset Pricing with Heterogeneous Agents, Incomplete Markets and Trading Constraints

The consumption capital asset pricing model is the standard economic model used to capture stock market behavior. However, empirical tests have pointed out to its inability to account quantitatively for the high average rate of return and volatility of stocks over time for plausible parameter values. Recent research has suggested that the consumption of stockholders is more strongly correlated with the performance of the stock market than the consumption of non-stockholders. We model two types of agents, non-stockholders with standard preferences and stock holders with preferences that incorporate elements of the prospect theory developed by Kahneman and Tversky (1979). In addition to consumption, stockholders consider fluctuations in their financial wealth explicitly when making decisions. Data from the Panel Study of Income Dynamics are used to calibrate the labor income processes of the two types of agents. Each agent faces idiosyncratic shocks to his labor income as well as aggregate shocks to the per-share dividend but markets are incomplete and agents cannot hedge consumption risks completely. In addition, consumers face both borrowing and short-sale constraints. Our results show that in equilibrium, agents hold different portfolios. Our model is able to generate a time-varying risk premium of about 5.5% while maintaining a low risk free rate, thus suggesting a plausible explanation for the equity premium puzzle reported by Mehra and Prescott (1985).

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Changes of dissolved organic matter compositions in artifical and natural seawater during Pseudovibrio growth experiment

To study the consumption of dissolved organic matter (DOM) by bacteria living in untra-oligotrophic artificial or natural seawater, we analyzed the composition of DOM before (timepoint t0, directly after inoculation) and after (timepoint t2, 3 weeks of incubation) growth of the bacteria using Fourier transform ion cyclotron mass spectrometry (ESI FT-ICR-MS). The oligotrophic natural seawater used originates from the South Pacific Gyre. Our data show that the bacteria were able to utilize a variety of different organic compounds. These compounds belong to different chemical compound groups and likely fuel the bacterial energy, carbon and nitrogen requirements under the ultra-oligotrophic conditions.

Bacterial production in the eastern Mediteranean Sea in October 2008 during SES_GR2

The HCMR_SES_LAGRANGIAN_GR2_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during October 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Bacterial production was estimated by the 3H-leucine method (Kirchman et al. 1986, Kirchman 1993). At each depth, duplicate samples and a control were incubated with 20 nM L-[4,5 3H]-leucine. Samples were incubated in the dark, at in situ temperature.

Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus in the eastern Mediterranean Sea in March and April 2008 during SES_GR1

The dataset is based on samples collected in the framework of the project SESAME, in the Ionian, Libyan and Aegean Sea during March- April 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson).