Using body mapping as part of the risk assessment process - a case study

This paper reports on a study undertaken to identify levels of MSD in relation to methods of waste collection. The need to quantify and eliminate ill health arising out of work is vital to reduce workplace absence leading to debate on associated relationships between the methods of waste collection and musculoskeletal disorders (MSDs). Body mapping is a participatory research tool that has been successfully used to investigate workplace ill health problems. Participatory body mapping exercises were carried out using staff at a UK District Council 2 years before and after the move from boxes and baskets to a wheeled bin recycling service. The study introduces the concept of Average Pain Count (APC). The data, supports previous studies showing wheeled bin based services (APC 2.07 & 2.80) are associated with less MSD outcomes than services including boxes, baskets and sacks (APC 4.02).The surveys provided compelling evidence to suggest that there are associations between age and self-reported pain although there appeared to be no patterns with regards length of service. These findings should help Local Authorities better understand critical factors regarding waste collection strategies and self-reported pain. There are recommendations regarding the use of body mapping and for industry practice

Bounding the graviton mass with binary pulsar observations

By comparing the observed orbital decay of the binary pulsars PSRB1913+16 and PSRB1534+12 to that predicted by general relativity due to gravitational-wave emission, we are able to bound the mass of the graviton to be less than $7.6\times10^{-20} \text{eV}/c^2$ at 90% confidence. This is the first such bound to be derived from dynamic gravitational fields. It is approximately two orders of magnitude weaker than the static-field bound from solar system observations, and will improve with further observations.Comment: 9 pages, 1 figure. Presented at Fourth Edoardo Amaldi Conference on Gravitational Waves, Perth, 200

How Polarized Have We Become? A Multimodal Classification of Trump Followers and Clinton Followers

Polarization in American politics has been extensively documented and analyzed for decades, and the phenomenon became all the more apparent during the 2016 presidential election, where Trump and Clinton depicted two radically different pictures of America. Inspired by this gaping polarization and the extensive utilization of Twitter during the 2016 presidential campaign, in this paper we take the first step in measuring polarization in social media and we attempt to predict individuals' Twitter following behavior through analyzing ones' everyday tweets, profile images and posted pictures. As such, we treat polarization as a classification problem and study to what extent Trump followers and Clinton followers on Twitter can be distinguished, which in turn serves as a metric of polarization in general. We apply LSTM to processing tweet features and we extract visual features using the VGG neural network. Integrating these two sets of features boosts the overall performance. We are able to achieve an accuracy of 69%, suggesting that the high degree of polarization recorded in the literature has started to manifest itself in social media as well.Comment: 16 pages, SocInfo 2017, 9th International Conference on Social Informatic

Attouch-Th\'era duality revisited: paramonotonicity and operator splitting

The problem of finding the zeros of the sum of two maximally monotone operators is of fundamental importance in optimization and variational analysis. In this paper, we systematically study Attouch-Th\'era duality for this problem. We provide new results related to Passty's parallel sum, to Eckstein and Svaiter's extended solution set, and to Combettes' fixed point description of the set of primal solutions. Furthermore, paramonotonicity is revealed to be a key property because it allows for the recovery of all primal solutions given just one arbitrary dual solution. As an application, we generalize the best approximation results by Bauschke, Combettes and Luke [J. Approx. Theory 141 (2006), 63-69] from normal cone operators to paramonotone operators. Our results are illustrated through numerous examples

Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data

Background: The tumour stroma -or tumour microenvironment- is an important constituent of solid cancers and it is thought to be one of the main obstacles to quantitative translation of drug activity between the preclinical and clinical phases of drug development. The tumour-stroma relationship has been described as being both pro- and antitumour in multiple studies. However, the causality of this complex biological relationship between the tumour and stroma has not yet been explored in a quantitative manner in complex tumour morphologies.Methods: To understand how these stromal and microenvironmental factors contribute to tumour physiology and how oxygen distributes within them, we have developed a lattice-based multiscalar cellular automaton model. This model uses principles of cytokine and oxygen diffusion as well as cell motility and plasticity to describe tumour-stroma landscapes. Furthermore, to calibrate the model, we propose an innovative modelling platform to extract model parameters from multiple in-vitro assays. This platform provides a novel way to extract meta-data that can be used to complement in-vivo studies and can be further applied in other contexts.Results: Here we show the necessity of the tumour-stroma opposing relationship for the model simulations to successfully describe the in-vivo stromal patterns of the human lung cancer cell lines Calu3 and Calu6, as models of clinical and preclinical tumour-stromal topologies. This is especially relevant to drugs that target the tumour microenvironment, such as antiangiogenics, compounds targeting the hedgehog pathway or immune checkpoint inhibitors, and is potentially a key platform to understand the mechanistic drivers for these drugs.Conclusion: The tumour-stroma automaton model presented here enables the interpretation of complex in-vitro data and uses it to parametrise a model for in-vivo tumour-stromal relationships

Community support for sex offender rehabilitation in Europe

It is assumed that the public holds negative attitudes towards sex offenders, yet an increasing number of European volunteers are involved in sex offender rehabilitation programmes through Circles of Support and Accountability (CoSA). Public attitudes and their correlates have been mainly studied in Anglo-Saxon countries; research in European countries other than the UK is scarce. To fill this gap, a web-based survey was held among web-panels in nine European countries (n = 200 per country). Measures included awareness and knowledge about sex offenders, community attitudes towards sex offenders in the community (CATSO), attitudes towards the treatment of sex offenders (ATTSO), public attitudes towards sex offender rehabilitation (PATSOR), support for CoSA, and attitudes towards volunteers working with sex offenders. Results indicated that clear misperceptions were held by a minority. Attitudes tended to be negative, but not extremely, and differences between countries were significant. The amount of support for CoSA was considerable and mean attitudes towards volunteers working with sex offenders were positive. The lower educated held more negative attitudes. Since webpanels were probably not representative on key demographic markers, the results are only indicative. Professionals should especially address the lower educated, correct key misperceptions about recidivism of sex offenders, and provide information about processes of change in convicted sex offender

Oxygen-Driven Tumour Growth Model : A Pathology-Relevant Mathematical Approach

We acknowledge Lucas Dias Fernandes and Dr Nicolas Rubido from the University of Aberdeen and Dr Neil Evans from the University of Warwick for the broad discussions on the mathematics.Peer reviewedPublisher PD