An approach to palaeoseismicity in the Olkiluoto (sea) area during the early Holocene

Olkiluoto Island is situated in the northern Baltic Sea, near the southwestern coast of Finland, and is the proposed location of a spent nuclear fuel repository. This study examined Holocene palaeoseismicity in the Olkiluoto area and in the surrounding sea areas by computer simulations together with acoustic-seismic, sedimentological and dating methods. The most abundant rock type on the island is migmatic mica gneiss, intruded by tonalites, granodiorites and granites. The surrounding Baltic Sea seabed consists of Palaeoproterozoic crystalline bedrock, which is to a great extent covered by younger Mesoproterozoic sedimentary rocks. The area contains several ancient deep-seated fracture zones that divide it into bedrock blocks. The response of bedrock at the Olkiluoto site was modelled considering four future ice-age scenarios. Each scenario produced shear displacements of fractures with different times of occurrence and varying recovery rates. Generally, the larger the maximum ice load, the larger were the permanent shear displacements. For a basic case, the maximum shear displacements were a few centimetres at the proposed nuclear waste repository level, at proximately 500 m b.s.l. High-resolution, low-frequency echo-sounding was used to examine the Holocene submarine sedimentary structures and possible direct and indirect indicators of palaeoseismic activity in the northern Baltic Sea. Echo-sounding profiles of Holocene submarine sediments revealed slides and slumps, normal faults, debris flows and turbidite-type structures. The profiles also showed pockmarks and other structures related to gas or groundwater seepages, which might be related to fracture zone activation. Evidence of postglacial reactivation in the study area was derived from the spatial occurrence of some of the structures, especial the faults and the seepages, in the vicinity of some old bedrock fracture zones. Palaeoseismic event(s) (a single or several events) in the Olkiluoto area were dated and the palaeoenvironment was characterized using palaeomagnetic, biostratigraphical and lithostratigraphical methods, enhancing the reliability of the chronology. Combined lithostratigraphy, biostratigraphy and palaeomagnetic stratigraphy revealed an age estimation of 10 650 to 10 200 cal. years BP for the palaeoseismic event(s). All Holocene sediment faults in the northern Baltic Sea occur at the same stratigraphical level, the age of which is estimated at 10 700 cal. years BP (9500 radiocarbon years BP). Their movement is suggested to have been triggered by palaeoseismic event(s) when the Late Weichselian ice sheet was retreating from the site and bedrock stresses were released along the bedrock fracture zones. Since no younger or repeated traces of seismic events were found, it corroborates the suggestion that the major seismic activity occurred within a short time during and after the last deglaciation. The origin of the gas/groundwater seepages remains unclear. Their reflections in the echo-sounding profiles imply that part of the gas is derived from the organic-bearing Litorina and modern gyttja clays. However, at least some of the gas is derived from the bedrock. Additional information could be gained by pore water analysis from the pockmarks. Information on postglacial fault activation and possible gas and/or fluid discharges under high hydraulic heads has relevance in evaluating the safety assessment of a planned spent nuclear fuel repository in the region.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Determinants of Coronary and Carotid Atherosclerosis in Finnish Patients with Clinically Suspected Coronary Artery Disease. A Quantitative Angiography and Ultrasound Study

Background. Cardiovascular disease (CVD) remains the most serious threat to life and health in industrialized countries. Atherosclerosis is the main underlying pathology associated with CVD, in particular coronary artery disease (CAD), ischaemic stroke, and peripheral arterial disease. Risk factors play an important role in initiating and accelerating the complex process of atherosclerosis. Most studies of risk factors have focused on the presence or absence of clinically defined CVD. Less is known about the determinants of the severity and extent of atherosclerosis in symptomatic patients. Aims. To clarify the association between coronary and carotid artery atherosclerosis, and to study the determinants associated with these abnormalities with special regard to novel cardiovascular risk factors. Subjects and methods. Quantitative coronary angiography (QCA) and B-mode ultrasound were used to assess coronary and carotid artery atherosclerosis in 108 patients with clinically suspected CAD referred for elective coronary angiography. To evaluate anatomic severity and extent of CAD, several QCA parameters were incorporated into indexes. These measurements reflected CAD severity, extent, and overall atheroma burden and were calculated for the entire coronary tree and separately for different coronary segments (i.e., left main, proximal, mid, and distal segments). Maximum and mean intima-media thickness (IMT) values of carotid arteries were measured and expressed as mean aggregate values. Furthermore, the study design included extensive fasting blood samples, oral glucose tolerance test, and an oral fat-load test to be performed in each participant. Results. Maximum and mean IMT values were significantly correlated with CAD severity, extent, and atheroma burden. There was heterogeneity in associations between IMT and CAD indexes according to anatomical location of CAD. Maximum and mean IMT values, respectively, were correlated with QCA indexes for mid and distal segments but not with the proximal segments of coronary vessels. The values of paraoxonase-1 (PON1) activity and concentration, respectively, were lower in subjects with significant CAD and there was a significant relationship between PON1 activity and concentration and coronary atherosclerosis assessed by QCA. PON1 activity was a significant determinant of severity of CAD independently of HDL cholesterol. Neither PON1 activity nor concentration was associated with carotid IMT. The concentration of triglycerides (TGs), triglyceride-rich lipoproteins (TRLs), oxidized LDL (oxLDL), and the cholesterol content of remnant lipoprotein particle (RLP-C) were significantly increased at 6 hours after intake of an oral fatty meal as compared with fasting values. The mean peak size of LDL remained unchanged 6 hours after the test meal. The correlations between total TGs, TRLs, and RLP-C in fasting and postprandial state were highly significant. RLP-C correlated with oxLDL both in fasting and in fed state and inversely with LDL size. In multivariate analysis oxLDL was a determinant of severity and extent of CAD. Neither total TGs, TRLs, oxLDL, nor LDL size were linked to carotid atherosclerosis. Insulin resistance (IR) was associated with an increased severity and extent of coronary atherosclerosis and seemed to be a stronger predictor of coronary atherosclerosis in the distal parts of the coronary tree than in the proximal and mid parts. In the multivariate analysis IR was a significant predictor of the severity of CAD. IR did not correlate with carotid IMT. Maximum and mean carotid IMT were higher in patients with the apoE4 phenotype compared with subjects with the apoE3 phenotype. Likewise, patients with the apoE4 phenotype had a more severe and extensive CAD than individuals with the apoE3 phenotype. Conclusions. 1) There is an association between carotid IMT and the severity and extent of CAD. Carotid IMT seems to be a weaker predictor of coronary atherosclerosis in the proximal parts of the coronary tree than in the mid and distal parts. 2) PON1 activity has an important role in the pathogenesis of coronary atherosclerosis. More importantly, the study illustrates how the protective role of HDL could be modulated by its components such that equivalent serum concentrations of HDL cholesterol may not equate with an equivalent, potential protective capacity. 3) RLP-C in the fasting state is a good marker of postprandial TRLs. Circulating oxLDL increases in CAD patients postprandially. The highly significant positive correlation between postprandial TRLs and postprandial oxLDL suggests that the postprandial state creates oxidative stress. Our findings emphasize the fundamental role of LDL oxidation in the development of atherosclerosis even after inclusion of conventional CAD risk factors. 4) Disturbances in glucose metabolism are crucial in the pathogenesis of coronary atherosclerosis. In fact, subjects with IR are comparable with diabetic subjects in terms of severity and extent of CAD. 5) ApoE polymorphism is involved in the susceptibility to both carotid and coronary atherosclerosis.