Multiscale methods for shape constraints in deconvolution: Confidence statements for qualitative features

We derive multiscale statistics for deconvolution in order to detect qualitative features of the unknown density. An important example covered within this framework is to test for local monotonicity on all scales simultaneously. We investigate the moderately ill-posed setting, where the Fourier transform of the error density in the deconvolution model is of polynomial decay. For multiscale testing, we consider a calibration, motivated by the modulus of continuity of Brownian motion. We investigate the performance of our results from both the theoretical and simulation based point of view. A major consequence of our work is that the detection of qualitative features of a density in a deconvolution problem is a doable task, although the minimax rates for pointwise estimation are very slow.

The influence of yield surface shape and damage in the depth-dependent response of bone tissue to nanoindentation using spherical and Berkovich indenters

Prevention and treatment of osteoporosis rely on understanding of the micromechanical behaviour of bone and its influence on fracture toughness and cell-mediated adaptation processes. Postyield properties may be assessed by nonlinear finite element simulations of nanoindentation using elastoplastic and damage models. This computational study aims at determining the influence of yield surface shape and damage on the depth-dependent response of bone to nanoindentation using spherical and conical tips. Yield surface shape and damage were shown to have a major impact on the indentation curves. Their influence on indentation modulus, hardness, their ratio as well as the elastic-to-total work ratio is well described by multilinear regressions for both tip shapes. For conical tips, indentation depth was not statistically significant (p<0.0001). For spherical tips, damage was not a significant parameter (p<0.0001). The gained knowledge can be used for developing an inverse method for identification of postelastic properties of bone from nanoindentation.

Comparison of partial least squares regression and principal component regression for pelvic shape prediction.

This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).

Expectation Conditional Maximization-Based Deformable Shape Registration

This paper addresses the issue of matching statistical and non-rigid shapes, and introduces an Expectation Conditional Maximization-based deformable shape registration (ECM-DSR) algorithm. Similar to previous works, we cast the statistical and non-rigid shape registration problem into a missing data framework and handle the unknown correspondences with Gaussian Mixture Models (GMM). The registration problem is then solved by fitting the GMM centroids to the data. But unlike previous works where equal isotropic covariances are used, our new algorithm uses heteroscedastic covariances whose values are iteratively estimated from the data. A previously introduced virtual observation concept is adopted here to simplify the estimation of the registration parameters. Based on this concept, we derive closed-form solutions to estimate parameters for statistical or non-rigid shape registrations in each iteration. Our experiments conducted on synthesized and real data demonstrate that the ECM-DSR algorithm has various advantages over existing algorithms.

Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.

How Welfare States Shape the Democratic Public: Policy Feedback, Participation, Voting and Attitudes

This crucial volume significantly advances the study of policy feedbacks. With contributions from many subfields and methodological approaches, it offers both sophisticated theorizing and new empirical examples that show how policies make politics in a variety of ways. Innovative research designs provide more convincing inference than ever. And the normative questions engaged about welfare performance, evaluation, participation, and accountability could not be more important or timely in this era of austerity and discord over the future of welfare states.’

Rolling stones and tree rings: A state of research on dendrogeomorphic reconstructions of rockfall

This progress report focuses on the contribution of tree-ring series to rockfall research and on recent development and challenges in the field. Dendrogeomorphic techniques have been used extensively since the early 2000s and several approaches have been developed to extract rockfall signals from tree-ring records of conifer trees. The reconstruction of rockfall chronologies has been hampered in the past by sample sizes that decrease as one goes back in time, as well as by a paucity of studies that include broadleaved tree species, which are in fact quite common in rockfall-prone environments. In this report, we propose a new approach considering impact probability and quantification of uncertainty in the reconstruction of rockfall time series as well as a quantitative estimate of presumably missed events. In addition, we outline new approaches and future perspectives for the inclusion of woody vegetation in hazard assessment procedures, and end with future thematic perspectives.

Volume and shape in feature space on adaptive FCM in MRI segmentation.

Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.

Scheduling the production of rolling ingots: Industrial context, model, and solution method

We study a real-world scheduling problem arising in the context of a rolling ingots production. First we review the production process and discuss peculiarities that have to be observed when scheduling a given set of production orders on the production facilities. We then show how to model this scheduling problem using prescribed time lags between operations, different kinds of resources, and sequence-dependent changeovers. A branch-and-bound solution procedure is presented in the second part. The basic principle is to relax the resource constraints by assuming infinite resource availability. Resulting resource conflicts are then stepwise resolved by introducing precedence relationships among operations competing for the same resources. The algorithm has been implemented as a beam search heuristic enumerating alternative sets of precedence relationships.

Metabolites from intestinal microbes shape Treg

Intestinal bacterial metabolites are an important communication tool between the host immune system and the commensal microbiota to establish mutualism. In a recent paper published in Science, Wendy Garrett and her colleagues report an exciting role of the three most abundant microbial-derived short-chain fatty acids (SCFA), acetic acid, propionic acid and butyric acid, in colonic regulatory T cell (cTreg) homeostasis.

Choosing the Path of Austerity: How Policy Coalitions Shape Welfare-policy Choices in Periods of Fiscal Consolidation

In general, fiscal adjustments are associated with significant reductions in social spending. Hence, the welfare state is not spared from austerity. Because the welfare state is still central to party competition, this is electorally risky. The paper addresses the following questions: Do left parties differ from their centrist and rightist competitors in the design of austerity measures? And does government type has an impact on the extent to which austerity policies rely on social spending cuts? By comparing 17 OECD countries between 1982 and 2009 we show that if governments embark on a path to austerity, their ideology does not have a significant effect on the magnitude of welfare state retrenchment. However, if major opposition parties and interest groups rally against social spending cuts, a broad pro-reform coalition is a crucial precondition for large fiscal consolidation programs to rely on substantial cuts to social security.