Paradigms of retirement: the importance of health and ageing in the Whitehall II study

This paper evaluates four well established sociological theories of ageing using qualitative data from the British Whitehall II study. We attempt to apply the theories to contemporary retirement and through each theory examine the issue of health in retirement. The effect of lowered income in retirement is discussed in relation to Townsend's theory of structured dependency. Change in participant's health following retirement is examined in respect of the theory of disengagement by Cumming and Henry, adjustment to retirement in relation to Laslett's theory of the third age. Parson's role theory is used to examine how social interactions and relationships change for people who have recently retired. We discuss the need for a multifaceted theory of ageing which can accommodate the continually changing experience and age of retirement. We analysed interviews conducted with 25 male and female civil servants aged between 55 and 63 years, from different grades who had been retired for less than 2 years.     

On the Sequential Accumulation of Evidence

In this paper, we introduce a method for sequentially accumulating evidence as it pertains to an active observer seeking to identify an object in a known environment. We develop a probabilistic framework, based on a generalized inverse theory, where assertions are represented by conditional probability density functions. This leads to a sequential recognition strategy in which evidence is accumulated over successive viewpoints using Bayesian chaining until a definitive assertion can be made. To illustrate the theory we show how the characteristics of belief distributions can be exploited in a model-based recognition problem, where the task is to identify an unknown model from a database of known objects on the basis of parameter estimates. We illustrate the robustness of the algorithm through recognition experiments in two very different contexts: (1) a highly structured recognition context where 3-D parametric models can be estimated directly from range data, (2) a complex environment, where the relationship between the data and the model is learned through an appearance-based strategy. Specifically, the flow fields computed through the object's motion are used as structural signatures for recognition.     

Effect of stretching—shearing coupling on instability-related delamination growth

Results are presented from a combined theoretical and experimental investigation into the effect of stretching—shearing coupling on the buckling and growth of near-surface delaminated regions. Honeycomb sandwich laminates with graphite/epoxy face sheets containing preimplanted, through-width delaminations were tested in compression. Two layups were tested. Each layup contained delaminated regions with identical in-plane and flexural moduli; however, one layup exhibited stretching—shearing coupling, whereas the other did not. Delamination buckling was predicted using a cylindrical buckling analysis, and energy release rates and fracture mode ratios were obtained by a crack tip element analysis. Delamination growth was predicted using a linear, mixed-mode delamination growth law. Significantly different delamination buckling and growth strains were predicted for the two layups. Predicted delamination buckling and growth strains correlated well with experimental results.     

Investigation of the Embedded Element Technique for ModellingWavy CNT Composites

This paper presents a comparison of different finite element approaches to modelling polymers reinforced with wavy, hollow fibres with the aim of predicting the effective elastic stiffness tensors of the composites. The waviness of the tubes is described by sinusoidal models with different amplitude-to-wavelength parameters. These volume elements are discretized by structured volume meshes onto which fibres in the form of independently meshed beam, shell or volume elements are superimposed. An embedded element technique is used to link the two sets of meshes. Reference solutions are obtained from conventional three-dimensional volume models of the same phase arrangements. Periodicity boundary conditions are applied in all cases and fibre volume fractions of up to a few percent are considered. The results indicate that embedded element techniques using shell elements for discretizing the fibres may provide an attractive combination of accuracy, computational cost and flexibility for modelling composites reinforced by arbitrarily, three-dimensionally curved nanotubes.     

The Skeptical Explorer: A Multiple-Hypothesis Approach to Visual Modeling and Exploration

The primary intent of this work is to present a method for sequentially associating three-dimensional surface measurements acquired by an autonomous exploration agent with models that describe those surfaces. Traditional multiple-viewpoint registration approaches are concerned only with finding the transformation that maps data points to a chosen global frame. Given a parts-based object representation, and assuming that the view correspondence can be found, the problem of associating the registered data with the correct part models still needs to be solved. While traditional approaches are content to group segmented data sets that geometrically overlap one another with the same part, there are cases where this causes ambiguous situations. This paper addresses the model-data association problem as it applies to three-dimensional dynamic object modeling. By tracking the state of part models across subsequent views, we wish to identify possible events that explain model-data association ambiguities and represent them in a Bayesian framework. The model-data association problem is therefore relaxed to allow multiple interpretations of the object's structure, each being assigned a probability. Rather than making a decision at every iteration about an ambiguous mapping, we look to the future for the information needed to disambiguate it. Experimental results are presented to illustrate the effectiveness of the approach.     

Fluorescent Probes for Studying Thioamide Positional Effects on Proteolysis Reveal Insight into Resistance to Cysteine Proteases

Thioamide substitutions of the peptide backbone have been shown to reduce proteolytic degradation, and this property can be used to generate competitive protease inhibitors and to stabilize peptides toward degradation in vivo. Here, we present a straightforward sensor design that allows a systematic study of the positional effects of thioamide substitution by using real-time fluorescence. Thioamide scanning in peptide substrates of five papain family cysteine proteases demonstrates that a thioamide at or near the scissile bond can slow proteolysis in all cases, but that the magnitude of the effects varies with position and protease in spite of high sequence homology. Mechanistic investigation of papain proteolysis reveals that the thioamide effects derive from reductions in both affinity (K_M) and turnover number (k_cat). Computational modeling allows these effects to be understood based on disruption of key enzyme–substrate hydrogen bonds, providing a model for future rational use of thioamides to confer cysteine protease resistance.     

An integrated range-sensing, segmentation and registration framework for the characterization of intra-surgical brain deformations in image-guided surgery

Image-guided surgery (IGS) is a technique for localizing anatomical structures on the basis of volumetric image data and for determining the optimal surgical path to reach these structures, by the means of a localization device, or probe, whose position is tracked over time. The usefulness of this technology hinges on the accuracy of the transformation between the image volume and the space occupied by the patient anatomy and spanned by the probe. Unfortunately, in neurosurgery this transformation can be degraded by intra-surgical brain shift, which often measures more than 10 mm and can exceed 25 mm. We propose a method for characterizing brain shift that is based on non-rigid surface registration, and can be combined with a constitutively realistic finite element approach for volumetric displacement estimation. The proposed registration method integrates in a unified framework all of the stages required to estimate the movement of the cortical surface in the operating room: model-based segmentation of the pre-operative brain surface in magnetic resonance image data, range-sensing of the cortex in the OR, range–MR rigid transformation computation, and range-based non-rigid brain motion estimation. The brain segmentation technique is an adaptation of the surface evolution model. Its convergence to the brain boundary is the result of a speed term restricted to white and grey matter voxels made explicit by a classifier, and the final result is post-processed to yield a Closest Point Map of the brain surface in MR space. In turn, this Closest Point Map is used to produce the homologous pairs required to determine a highly efficient, 2D spline-based, Iterative Closest Point (ICP) non-rigid surface registration. The baseline for computing intra-operative brain displacement, as well as the initial starting point of the non-rigid ICP registration, is determined by a very good rigid range–MR transformation, produced by a simple procedure for relating the range coordinate system to that of the probe, and ultimately to that of the MR volume.