Modeling the stratospheric warming following the Mt. Pinatubo eruption: uncertainties in aerosol extinctions

In terms of atmospheric impact, the volcanic eruption of Mt. Pinatubo (1991) is the best characterized large eruption on record. We investigate here the model-derived stratospheric warming following the Pinatubo eruption as derived from SAGE II extinction data including recent improvements in the processing algorithm. This method, termed SAGE_4λ, makes use of the four wavelengths (385, 452, 525 and 1024 nm) of the SAGE II data when available, and uses a data-filling procedure in the opacity-induced "gap" regions. Using SAGE_4λ, we derived aerosol size distributions that properly reproduce extinction coefficients also at much longer wavelengths. This provides a good basis for calculating the absorption of terrestrial infrared radiation and the resulting stratospheric heating. However, we also show that the use of this data set in a global chemistry–climate model (CCM) still leads to stronger aerosol-induced stratospheric heating than observed, with temperatures partly even higher than the already too high values found by many models in recent general circulation model (GCM) and CCM intercomparisons. This suggests that the overestimation of the stratospheric warming after the Pinatubo eruption may not be ascribed to an insufficient observational database but instead to using outdated data sets, to deficiencies in the implementation of the forcing data, or to radiative or dynamical model artifacts. Conversely, the SAGE_4λ approach reduces the infrared absorption in the tropical tropopause region, resulting in a significantly better agreement with the post-volcanic temperature record at these altitudes.

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

Stochastic search for semiparametric linear regression models

This paper introduces and analyzes a stochastic search method for parameter estimation in linear regression models in the spirit of Beran and Millar [Ann. Statist. 15(3) (1987) 1131–1154]. The idea is to generate a random finite subset of a parameter space which will automatically contain points which are very close to an unknown true parameter. The motivation for this procedure comes from recent work of Dümbgen et al. [Ann. Statist. 39(2) (2011) 702–730] on regression models with log-concave error distributions.

A nonlinear QCT-based finite element model validation study for the human femur tested in two configurations in vitro

Purpose Femoral fracture is a common medical problem in osteoporotic individuals. Bone mineral density (BMD) is the gold standard measure to evaluate fracture risk in vivo. Quantitative computed tomography (QCT)-based homogenized voxel finite element (hvFE) models have been proved to be more accurate predictors of femoral strength than BMD by adding geometrical and material properties. The aim of this study was to evaluate the ability of hvFE models in predicting femoral stiffness, strength and failure location for a large number of pairs of human femora tested in two different loading scenarios. Methods Thirty-six pairs of femora were scanned with QCT and total proximal BMD and BMC were evaluated. For each pair, one femur was positioned in one-legged stance configuration (STANCE) and the other in a sideways configuration (SIDE). Nonlinear hvFE models were generated from QCT images by reproducing the same loading configurations imposed in the experiments. For experiments and models, the structural properties (stiffness and ultimate load), the failure location and the motion of the femoral head were computed and compared. Results In both configurations, hvFE models predicted both stiffness (R2=0.82 for STANCE and R2=0.74 for SIDE) and femoral ultimate load (R2=0.80 for STANCE and R2=0.85 for SIDE) better than BMD and BMC. Moreover, the models predicted qualitatively well the failure location (66% of cases) and the motion of the femoral head. Conclusions The subject specific QCT-based nonlinear hvFE model cannot only predict femoral apparent mechanical properties better than densitometric measures, but can additionally provide useful qualitative information about failure location.

Nuclear organization in the nematode C. elegans.

With its invariant cell lineage, easy genetics and small genome, the nematode Caenorhabditis elegans has emerged as one of the prime models in developmental biology over the last 50 years. Surprisingly however, until a decade ago very little was known about nuclear organization in worms, even though it is an ideal model system to explore the link between nuclear organization and cell fate determination. Here, we review the latest findings that exploit the repertoire of genetic tools developed in worms, leading to the identification of important sequences and signals governing the changes in chromatin tridimensional architecture. We also highlight parallels and differences to other model systems.

Effects of exogenous surfactant on the non-heart-beating donor lung graft in experimental lung transplantation - a stereological study.

The use of non-heart-beating donor (NHBD) lungs may help to overcome the shortage of lung grafts in clinical lung transplantation, but warm ischaemia and ischaemia/reperfusion injury (I/R injury) resulting in primary graft dysfunction represent a considerable threat. Thus, better strategies for optimized preservation of lung grafts are urgently needed. Surfactant dysfunction has been shown to contribute to I/R injury, and surfactant replacement therapy is effective in enhancing lung function and structural integrity in related rat models. In the present study we hypothesize that surfactant replacement therapy reduces oedema formation in a pig model of NHBD lung transplantation. Oedema formation was quantified with (SF) and without (non-SF) surfactant replacement therapy in interstitial and alveolar compartments by means of design-based stereology in NHBD lungs 7 h after cardiac arrest, reperfusion and transplantation. A sham-operated group served as control. In both NHBD groups, nearly all animals died within the first hours after transplantation due to right heart failure. Both SF and non-SF developed an interstitial oedema of similar degree, as shown by an increase in septal wall volume and arithmetic mean thickness as well as an increase in the volume of peribron-chovascular connective tissue. Regarding intra-alveolar oedema, no statistically significant difference could be found between SF and non-SF. In conclusion, surfactant replacement therapy cannot prevent poor outcome after prolonged warm ischaemia of 7 h in this model. While the beneficial effects of surfactant replacement therapy have been observed in several experimental and clinical studies related to heart-beating donor lungs and cold ischaemia, it is unlikely that surfactant replacement therapy will overcome the shortage of organs in the context of prolonged warm ischaemia, for example, 7 h. Moreover, our data demonstrate that right heart function and dysfunctions of the pulmonary vascular bed are limiting factors that need to be addressed in NHBD.

In vitro fabrication of autologous living tissue-engineered vascular grafts based on prenatally harvested ovine amniotic fluid-derived stem cells

Amniotic fluid cells (AFCs) have been proposed as a valuable source for tissue engineering and regenerative medicine. However, before clinical implementation, rigorous evaluation of this cell source in clinically relevant animal models accepted by regulatory authorities is indispensable. Today, the ovine model represents one of the most accepted preclinical animal models, in particular for cardiovascular applications. Here, we investigate the isolation and use of autologous ovine AFCs as cell source for cardiovascular tissue engineering applications. Fetal fluids were aspirated in vivo from pregnant ewes (n = 9) and from explanted uteri post mortem at different gestational ages (n = 91). Amniotic non-allantoic fluid nature was evaluated biochemically and in vivo samples were compared with post mortem reference samples. Isolated cells revealed an immunohistochemical phenotype similar to ovine bone marrow-derived mesenchymal stem cells (MSCs) and showed expression of stem cell factors described for embryonic stem cells, such as NANOG and STAT-3. Isolated ovine amniotic fluid-derived MSCs were screened for numeric chromosomal aberrations and successfully differentiated into several mesodermal phenotypes. Myofibroblastic ovine AFC lineages were then successfully used for the in vitro fabrication of small- and large-diameter tissue-engineered vascular grafts (n = 10) and cardiovascular patches (n = 34), laying the foundation for the use of this relevant pre-clinical in vivo assessment model for future amniotic fluid cell-based therapeutic applications. Copyright © 2013 John Wiley & Sons, Ltd.

Predictive Margins and Marginal Effects in Stata

Tables of estimated regression coefficients, usually accompanied by additional information such as standard errors, t-statistics, p-values, confidence intervals or significance stars, have long been the preferred way of communicating results from statistical models. In recent years, however, the limits of this form of exposition have been increasingly recognized. For example, interpretation of regression tables can be very challenging in the presence of complications such as interaction effects, categorical variables, or nonlinear functional forms. Furthermore, while these issues might still be manageable in the case of linear regression, interpretational difficulties can be overwhelming in nonlinear models such as logistic regression. To facilitate sensible interpretation of such models it is often necessary to compute additional results such as marginal effects, predictive margins, or contrasts. Moreover, smart graphical displays of results can be very valuable in making complex relations accessible. A number of helpful commands geared at supporting these tasks have been recently introduced in Stata, making elaborate interpretation and communication of regression results possible without much extra effort. Examples of such commands are -margins-, -contrasts-, and -marginsplot-. In my talk, I will discuss the capabilities of these commands and present a range of examples illustrating their use.

Motivational patterns as an instrument for predicting success in promising young football players

Psychological characteristics are crucial to identifying talents, which is why these are being incorporated in today’s multidimensional talent models. In addition to multidimensionality, talent studies are increasingly drawing on holistic theories of development, leading to the use of person-oriented approaches. The present study adopts such an approach by looking at the influence that motivational characteristics have on the development of performance, in a person-oriented way. For this purpose, it looks at how the constructs achievement motive, achievement goal orientation and self-determination interact with one another, what patterns they form and how these patterns are linked to subsequent sports success. 97 top young football players were questioned twice. Another year later, it was enquired which of these players had been selected for the U15 national team. At both measuring points, four patterns were identified, which displayed a high degree of structural and individual stability. As expected, the highly intrinsically achievement-oriented players were significantly more likely to move up into the U15 national team. The results point to the importance of favourable patterns of motivational variables in the form of specific types, for medium-term performance development among promising football talents, and thus provide valuable clues for the selection and promotion of those.

Hide-and-seek in vegetation: time-to-detection is an efficient design for estimating detectability and occurrence

Ecology and conservation require reliable data on the occurrence of animals and plants. A major source of bias is imperfect detection, which, however, can be corrected for by estimation of detectability. In traditional occupancy models, this requires repeat or multi-observer surveys. Recently, time-to-detection models have been developed as a cost-effective alternative, which requires no repeat surveys and hence costs could be halved. We compared the efficiency and reliability of time-to-detection and traditional occupancy models under varying survey effort. Two observers independently searched for 17 plant species in 44100m(2) Swiss grassland quadrats and recorded the time-to-detection for each species, enabling detectability to be estimated with both time-to-detection and traditional occupancy models. In addition, we gauged the relative influence on detectability of species, observer, plant height and two measures of abundance (cover and frequency). Estimates of detectability and occupancy under both models were very similar. Rare species were more likely to be overlooked; detectability was strongly affected by abundance. As a measure of abundance, frequency outperformed cover in its predictive power. The two observers differed significantly in their detection ability. Time-to-detection models were as accurate as traditional occupancy models, but their data easier to obtain; thus they provide a cost-effective alternative to traditional occupancy models for detection-corrected estimation of occurrence.

Subjective well-being and exercise in the second halt of life: a critical review of theoretical approaches

Research has shown repeatedly that the “feeling better” effect of exercise is far more moderate than generally claimed. Examinations of subgroups in secondary analyses also indicate that numerous further variables influence this relationship. One reason for inconsistencies in this research field is the lack of adequate theoretical analyses. Well-being output variables frequently possess no construct definition, and little attention is paid to moderating and mediating variables. This article integrates the main models in an overview and analyzes how secondary analyses define well-being and which areas of the construct they focus on. It then applies a moderator and/or mediator framework to examine which person and environmental variables can be found in the existing explanatory approaches in sport science and how they specify the influence of these moderating and mediating variables. Results show that the broad understanding of well-being in many secondary analyses makes findings difficult to interpret. Moreover, physiological explanatory approaches focus more on affective changes in well-being, whereas psychological approaches also include cognitive changes. The approaches focus mostly on either physical or psychological person variables and rarely combine the two, as in, for example, the dual-mode model. Whereas environmental variables specifying the treatment more closely (e.g., its intensity) are comparatively frequent, only the social support model formulates variables such as the framework in which exercise is presented. The majority of explanatory approaches use simple moderator and/or mediator models such as the basic mediated (e.g., distraction hypothesis) or multiple mediated (e.g., monoamine hypotheses) model. The discussion draws conclusions for future research.

HDL Cholesterol Is Not Associated with Lower Mortality in Patients with Kidney Dysfunction

In the general population, HDL cholesterol (HDL-C) is associated with reduced cardiovascular events. However, recent experimental data suggest that the vascular effects of HDL can be heterogeneous. We examined the association of HDL-C with all-cause and cardiovascular mortality in the Ludwigshafen Risk and Cardiovascular Health study comprising 3307 patients undergoing coronary angiography. Patients were followed for a median of 9.9 years. Estimated GFR (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration eGFR creatinine-cystatin C (eGFRcreat-cys) equation. The effect of increasing HDL-C serum levels was assessed using Cox proportional hazard models. In participants with normal kidney function (eGFR>90 ml/min per 1.73 m(2)), higher HDL-C was associated with reduced risk of all-cause and cardiovascular mortality and coronary artery disease severity (hazard ratio [HR], 0.51, 95% confidence interval [95% CI], 0.26-0.92 [P=0.03]; HR, 0.30, 95% CI, 0.13-0.73 [P=0.01]). Conversely, in patients with mild (eGFR=60-89 ml/min per 1.73 m(2)) and more advanced reduced kidney function (eGFR<60 ml/min per 1.73 m(2)), higher HDL-C did not associate with lower risk for mortality (eGFR=60-89 ml/min per 1.73 m(2): HR, 0.68, 95% CI, 0.45-1.04 [P=0.07]; HR, 0.84, 95% CI, 0.50-1.40 [P=0.50]; eGFR<60 ml/min per 1.73 m(2): HR, 1.18, 95% CI, 0.60-1.81 [P=0.88]; HR, 0.82, 95% CI, 0.40-1.69 [P=0.60]). Moreover, Cox regression analyses revealed interaction between HDL-C and eGFR in predicting all-cause and cardiovascular mortality (P=0.04 and P=0.02, respectively). We confirmed a lack of association between higher HDL-C and lower mortality in an independent cohort of patients with definite CKD (P=0.63). In summary, higher HDL-C levels did not associate with reduced mortality risk and coronary artery disease severity in patients with reduced kidney function. Indeed, abnormal HDL function might confound the outcome of HDL-targeted therapies in these patients.

The role of subpolar deep water formation and Nordic Seas overflows in simulated multidecadal variability of the Atlantic meridional overturning circulation

We investigate the respective role of variations in subpolar deep water formation and Nordic Seas overflows for the decadal to multidecadal variability of the Atlantic meridional overturning circulation (AMOC). This is partly done by analysing long (order of 1000 years) control simulations with five coupled climate models. For all models, the maximum influence of variations in subpolar deep water formation is found at about 45° N, while the maximum influence of variations in Nordic Seas overflows is rather found at 55 to 60° N. Regarding the two overflow branches, the influence of variations in the Denmark Strait overflow is, for all models, substantially larger than that of variations in the overflow across the Iceland–Scotland Ridge. The latter might, however, be underestimated, as the models in general do not realistically simulate the flow path of the Iceland–Scotland overflow water south of the Iceland–Scotland Ridge. The influence of variations in subpolar deep water formation is, on multimodel average, larger than that of variations in the Denmark Strait overflow. This is true both at 45° N, where the maximum standard deviation of decadal to multidecadal AMOC variability is located for all but one model, and at the more classical latitude of 30° N. At 30° N, variations in subpolar deep water formation and Denmark Strait overflow explain, on multimodel average, about half and one-third respectively of the decadal to multidecadal AMOC variance. Apart from analysing multimodel control simulations, we have performed sensitivity experiments with one of the models, in which we suppress the variability of either subpolar deep water formation or Nordic Seas overflows. The sensitivity experiments indicate that variations in subpolar deep water formation and Nordic Seas overflows are not completely independent. We further conclude from these experiments that the decadal to multidecadal AMOC variability north of about 50° N is mainly related to variations in Nordic Seas overflows. At 45° N and south of this latitude, variations in both subpolar deep water formation and Nordic Seas overflows contribute to the AMOC variability, with neither of the processes being very dominant compared to the other.

Applications of random set theory in econometrics

In recent years, the econometrics literature has shown a growing interest in the study of partially identified models, in which the object of economic and statistical interest is a set rather than a point. The characterization of this set and the development of consistent estimators and inference procedures for it with desirable properties are the main goals of partial identification analysis. This review introduces the fundamental tools of the theory of random sets, which brings together elements of topology, convex geometry, and probability theory to develop a coherent mathematical framework to analyze random elements whose realizations are sets. It then elucidates how these tools have been fruitfully applied in econometrics to reach the goals of partial identification analysis.

Search for direct third-generation squark pair production in final states with missing transverse momentum and two b-jets in sqrts = 8 TeV pp collisions with the ATLAS detector

The results of a search for pair production of supersymmetric partners of the Standard Model third-generation quarks are reported. This search uses 20.1 fb(-1) of pp collisions at root s = 8 TeV collected by the ATLAS experiment at the Large Hadron Collider. The lightest bottom and top squarks ((b) over tilde (1) and (t) over tilde (1) respectively) are searched for in a final state with large missing transverse momentum and two jets identified as originating from b-quarks. No excess of events above the expected level of Standard Model background is found. The results are used to set upper limits on the visible cross section for processes beyond the Standard Model. Exclusion limits at the 95% confidence level on the masses of the third-generation squarks are derived in phenomenological supersymmetric R-parity-conserving models in which either the bottom or the top squark is the lightest squark. The (b) over tilde (1) is assumed to decay via (b) over tilde (1) -> b (chi) over tilde (0)(1) and the (t) over tilde (1) via (t) over tilde (1) b (chi) over tilde (+/-)(1), with undetectable products of the subsequent decay of the (chi) over tilde (+/-)(1) due to the small mass splitting between the (chi) over tilde (+/-)(1) and the (chi) over tilde (0)(1)