Asymmetric Cuts In The Contour Method For Residual Stress Measurement

The standard contour method is limited to sectioning test components into two symmetric halves. In this study a new approach is developed to deal with asymmetric cuts in the contour method of residual stress measurement. The proposed approach is demonstrated using finite element (FE) simulations and is validated experimentally using a series of asymmetric contour cuts and neutron diffraction measurements

Morphological operators for very low bit rate video coding

This paper deals with the use of some morphological tools for video coding at very low bit rates. Rather than describing a complete coding algorithm, the purpose of this paper is to focus on morphological connected operators and segmentation tools that have proved to be attractive for compression.Peer ReviewedPostprint (published version

No-arbitrage in discrete-time markets with proportional transaction costs and general information structure

We discuss the no-arbitrage conditions in a general framework for discrete-time models of financial markets with proportional transaction costs and general information structure. We extend the results of Kabanov and al. (2002), Kabanov and al. (2003) and Schachermayer (2004) to the case where bid-ask spreads are not known with certainty. In the "no-friction" case, we retrieve the result of Kabanov and Stricker (2003)

Spin constrained orbital angular momentum control in high-harmonic generation

The interplay between spin and orbital angular momentum in the up-conversion process allows us to control the macroscopic wave front of high harmonics by manipulating the microscopic polarizations of the driving field. We demonstrate control of orbital angular momentum in high harmonic generation from both solid and gas phase targets using the selection rules of spin angular momentum. The gas phase harmonics extend the control of angular momentum to extreme-ultraviolet wavelength. We also propose a bi-color scheme to produce spectrally separated extreme-ultraviolet radiation carrying orbital angular momentum

On Markovian solutions to Markov Chain BSDEs

We study (backward) stochastic differential equations with noise coming from a finite state Markov chain. We show that, for the solutions of these equations to be `Markovian', in the sense that they are deterministic functions of the state of the underlying chain, the integrand must be of a specific form. This allows us to connect these equations to coupled systems of ODEs, and hence to give fast numerical methods for the evaluation of Markov-Chain BSDEs

Physical activity monitoring in Europe : the European physical activity surveillance system (EUPASS) approach and indicator testing.

Objectives: The main objective of this paper is to describe the approach and specific findings of the European Physical Activity Surveillance System (EUPASS) research project. In particular, the analysis presented aims at testing the reliability, comparability and predictive power of different sets of physical activity (PA) indicators. Design: First, a panel study based on computer-aided telephone interview (CATI) was designed to report PA data of a representative, selected group of about 100 persons per country at three points in time. Second, a CATI time series survey was carried out with the goal of realising about 100 interviews per month over six consecutive months. Setting: The project was carried out in eight European countries to support the development of the European Union's (EU) Health Monitoring Programme. Subjects: Random population samples (subjects aged 18 years and older) were drawn from each participating country. Results: While many PA indicators used in EU countries to date as well as the psychosocial and environmental measures tested in the present study had acceptable to good reliability coefficients, the test–retest reliability scores of the International Physical Activity Questionnaire (IPAQ) version tested (the short (last 7 days) telephone interview IPAQ; IPAQ-S7T) were rather low. The comparability between extant national PA items and the IPAQ-S7T was low for all countries. The strongest predictors of perceived health were the psychosocial and environmental PA indicators. Conclusions: According to the results of the present study, more research is needed to further investigate and improve the quality of the IPAQ. In addition, the specific predictive power of the tested psychosocial and environmental PA indicators on perceived health should be of particular interest for designing health surveillance activities in the future

Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex.

A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from multiple single-trial measurements. This is often accomplished by learning a simple, linear transformations between neural features and features of the sensory stimuli or motor task. While successful in some early sensory processing areas, linear mappings are unlikely to be ideal tools for elucidating nonlinear, hierarchical representations of higher-order brain areas during complex tasks, such as the production of speech by humans. Here, we apply deep networks to predict produced speech syllables from a dataset of high gamma cortical surface electric potentials recorded from human sensorimotor cortex. We find that deep networks had higher decoding prediction accuracy compared to baseline models. Having established that deep networks extract more task relevant information from neural data sets relative to linear models (i.e., higher predictive accuracy), we next sought to demonstrate their utility as a data analysis tool for neuroscience. We first show that deep network's confusions revealed hierarchical latent structure in the neural data, which recapitulated the underlying articulatory nature of speech motor control. We next broadened the frequency features beyond high-gamma and identified a novel high-gamma-to-beta coupling during speech production. Finally, we used deep networks to compare task-relevant information in different neural frequency bands, and found that the high-gamma band contains the vast majority of information relevant for the speech prediction task, with little-to-no additional contribution from lower-frequency amplitudes. Together, these results demonstrate the utility of deep networks as a data analysis tool for basic and applied neuroscience

Oral health in relation to all-cause mortality: the IPC cohort study

We evaluated the association between oral health and mortality. The study population comprised 76,188 subjects aged 16–89 years at recruitment. The mean follow-up time was 3.4 ± 2.4 years. Subjects with a personal medical history of cancer or cardiovascular disease and death by casualty were excluded from the analysis. A full-mouth clinical examination was performed in order to assess dental plaque, dental calculus and gingival inflammation. The number of teeth and functional masticatory units 10 missing teeth and functional masticatory units 10 missing teeth (HR = 2.31, [95% CI: 1.40–3.82]) and functional masticatory units <5 (HR = 2.40 [95% CI 1.55–3.73]). Moreover, when ≥3 oral diseases were cumulated in the model, the risk increased for all-cause mortality (HR = 3.39, [95% CI: 2.51–5.42]), all-cancer mortality (HR = 3.59, [95% CI: 1.23–10.05]) and non-cardiovascular and non-cancer mortality (HR = 4.71, [95% CI: 1.74–12.7]). The present study indicates a postive linear association between oral health and mortality