3D shape based reconstruction of experimental data in Diffuse Optical Tomography

Diffuse optical tomography (DOT) aims at recovering three-dimensional images of absorption and scattering parameters inside diffusive body based on small number of transmission measurements at the boundary of the body. This image reconstruction problem is known to be an ill-posed inverse problem, which requires use of prior information for successful reconstruction. We present a shape based method for DOT, where we assume a priori that the unknown body consist of disjoint subdomains with different optical properties. We utilize spherical harmonics expansion to parameterize the reconstruction problem with respect to the subdomain boundaries, and introduce a finite element (FEM) based algorithm that uses a novel 3D mesh subdivision technique to describe the mapping from spherical harmonics coefficients to the 3D absorption and scattering distributions inside a unstructured volumetric FEM mesh. We evaluate the shape based method by reconstructing experimental DOT data, from a cylindrical phantom with one inclusion with high absorption and one with high scattering. The reconstruction was monitored, and we found a 87% reduction in the Hausdorff measure between targets and reconstructed inclusions, 96% success in recovering the location of the centers of the inclusions and 87% success in average in the recovery for the volumes

The Low-Spin Black Hole in LMC X-3

Building upon a new dynamical model for the X-ray binary LMC X-3, we measure the spin of its black hole primary via the continuum-fitting method. We consider over one thousand thermal-state RXTE X-ray spectra of LMC X-3. Using a large subset of these spectra, we constrain the spin parameter of the black hole to be spin = 0.21(+0.18,-0.22), 90% confidence. Our estimate of the uncertainty in spin takes into account a wide range of systematic errors. We discuss evidence for a correlation between a black hole's spin and the complexity of its X-ray spectrum.Comment: Submitted to ApJL, 5 pages emulateapj, 2 figures and 1 tabl

Traditional and new sources of grain protein in the healthy and sustainable Nordic diet

Cereal foods provide carbohydrates and dietary fibre, but also protein. To support the goals of sustainable development, cereal grain proteins should be more efficiently used to replace animal proteins. In the Nordic countries, wheat is the major source of cereal protein, followed by rye, oats, and barley. Although oats have been traditionally consumed as many staple foods in the Nordic countries and new oat-based food concepts are emerging, the potential of oats as a healthy and sustainable protein source is still underused. Oat protein is high in nutritional quality, and oats also contain unique phytochemicals and dietary fibres with proven health effects. Therefore, utilization of traditional wholegrain oat products to replace animal protein sources would increase both health-supporting components and cereal diversity in Nordic diets. While novel oat-based meat, milk, and dairy analogues do not contribute as much to dietary fibre, vitamin and mineral intake as corresponding whole grain products, they provide valuable and effective means to reduce animal protein intake, and thus, the environmental burden

Using shared goal setting to improve access and equity: a mixed methods study of the Good Goals intervention

Background: Access and equity in children’s therapy services may be improved by directing clinicians’ use of resources toward specific goals that are important to patients. A practice-change intervention (titled ‘Good Goals’) was designed to achieve this. This study investigated uptake, adoption, and possible effects of that intervention in children’s occupational therapy services. Methods: Mixed methods case studies (n = 3 services, including 46 therapists and 558 children) were conducted. The intervention was delivered over 25 weeks through face-to-face training, team workbooks, and ‘tools for change’. Data were collected before, during, and after the intervention on a range of factors using interviews, a focus group, case note analysis, routine data, document analysis, and researchers’ observations. Results: Factors related to uptake and adoptions were: mode of intervention delivery, competing demands on therapists’ time, and leadership by service manager. Service managers and therapists reported that the intervention: helped therapists establish a shared rationale for clinical decisions; increased clarity in service provision; and improved interactions with families and schools. During the study period, therapists’ behaviours changed: identifying goals, odds ratio 2.4 (95% CI 1.5 to 3.8); agreeing goals, 3.5 (2.4 to 5.1); evaluating progress, 2.0 (1.1 to 3.5). Children’s LoT decreased by two months [95% CI −8 to +4 months] across the services. Cost per therapist trained ranged from £1,003 to £1,277, depending upon service size and therapists’ salary bands. Conclusions: Good Goals is a promising quality improvement intervention that can be delivered and adopted in practice and may have benefits. Further research is required to evaluate its: (i) impact on patient outcomes, effectiveness, cost-effectiveness, and (ii) transferability to other clinical contexts

Nonlinear approach to difference imaging in diffuse optical tomography

Difference imaging aims at recovery of the change in the optical properties of a body based on measurements before and after the change. Conventionally, the image reconstruction is based on using difference of the measurements and a linear approximation of the observation model. One of the main benefits of the linearized difference reconstruction is that the approach has a good tolerance to modeling errors, which cancel out partially in the subtraction of the measurements. However, a drawback of the approach is that the difference images are usually only qualitative in nature and their spatial resolution can be weak because they rely on the global linearization of the nonlinear observation model. To overcome the limitations of the linear approach, we investigate a nonlinear approach for difference imaging where the images of the optical parameters before and after the change are reconstructed simultaneously based on the two datasets. We tested the feasibility of the method with simulations and experimental data from a phantom and studied how the approach tolerates modeling errors like domain truncation, optode coupling errors, and domain shape errors

Decentralization's impact on the health workforce: Perspectives of managers, workers and national leaders

Designers and implementers of decentralization and other reform measures have focused much attention on financial and structural reform measures, but ignored their human resource implications. Concern is mounting about the impact that the reallocation of roles and responsibilities has had on the health workforce and its management, but the experiences and lessons of different countries have not been widely shared. This paper examines evidence from published literature on decentralization's impact on the demand side of the human resource equation, as well as the factors that have contributed to the impact. The elements that make such an impact analysis exceptionally complex are identified. They include the mode of decentralization that a country is implementing, the level of responsibility for the salary budget and pay determination, and the civil service status of transferred health workers. The main body of the paper is devoted to examining decentralization's impact on human resource issues from three different perspectives: that of local health managers, health workers themselves, and national health leaders. These three groups have different concerns in the human resource realm, and consequently, have been differently affected by decentralization processes. The paper concludes with recommendations regarding three key concerns that national authorities and international agencies should give prompt attention to. They are (1) defining the essential human resource policy, planning and management skills for national human resource managers who work in decentralized countries, and developing training programs to equip them with such skills; (2) supporting research that focuses on improving the knowledge base of how different modes of decentralization impact on staffing equity; and (3) identifying factors that most critically influence health worker motivation and performance under decentralization, and documenting the most cost-effective best practices to improve them. Notable experiences from South Africa, Ghana, Indonesia and Mexico are shared in an annex

Exercise Frequency and Levels of Anxiety and Stress during the COVID-19 Pandemic are mediated by Craves to Move and to Rest

The concept of craves to move and to rest is a psychological construct that has recently been proposed as a key predictor for exercise adherence and a more active lifestyle in the fi eld of motivation research. During the COVID-19 pandemic lockdown, we observed that individuals who engaged in regular exercise reported better levels of psychological health and wellbeing. Based on this observation, our hypothesis was that craves to move and to rest could also mediate the relationship between the frequency of physical exercise and anxiety and perceived stress. To test our hypothesis, we recruited 574 volunteers who completed four online questionnaires assessing state anxiety, perceived stress, craves to move and to rest, and sociodemographic information (including weekly frequency of exercise) during the COVID-19 lockdown. We used a structural equation model, specifi cally a mediation analysis, which revealed a signifi cant mediating eff ect of craves to move and to rest between the frequency of physical exercise and anxiety and perceived stress levels. In other words, the weekly frequency of exercise was not directly associated with state anxiety, but rather through its eff ect on craves to move and to rest. Our results suggest that understanding the role of craves to move and to rest is crucial in comprehending the relationship between physical exercise and anxiety

Clinicians' caseload management behaviours as explanatory factors in patients' length of time on caseloads : a predictive multilevel study in paediatric community occupational therapy

Peer reviewedPublisher PD

Fast Gibbs sampling for high-dimensional Bayesian inversion

Solving ill-posed inverse problems by Bayesian inference has recently attracted considerable attention. Compared to deterministic approaches, the probabilistic representation of the solution by the posterior distribution can be exploited to explore and quantify its uncertainties. In applications where the inverse solution is subject to further analysis procedures, this can be a significant advantage. Alongside theoretical progress, various new computational techniques allow to sample very high dimensional posterior distributions: In [Lucka2012], a Markov chain Monte Carlo (MCMC) posterior sampler was developed for linear inverse problems with $\ell_1$-type priors. In this article, we extend this single component Gibbs-type sampler to a wide range of priors used in Bayesian inversion, such as general $\ell_p^q$ priors with additional hard constraints. Besides a fast computation of the conditional, single component densities in an explicit, parameterized form, a fast, robust and exact sampling from these one-dimensional densities is key to obtain an efficient algorithm. We demonstrate that a generalization of slice sampling can utilize their specific structure for this task and illustrate the performance of the resulting slice-within-Gibbs samplers by different computed examples. These new samplers allow us to perform sample-based Bayesian inference in high-dimensional scenarios with certain priors for the first time, including the inversion of computed tomography (CT) data with the popular isotropic total variation (TV) prior.Comment: submitted to "Inverse Problems