Investigation of the response of a neutron moisture meter using a multigroup, two-dimensional diffusion theory code.

A multigroup diffusion code has been used to predict the count rate from a neutron moisture meter for a range of values of soil water content ω thermal neutron absorption cross section Sα (defined as SIGMA Σα/ρ) of the soil matrix and soil matrix density ρ two dimensions adequately approximated the geometry of the source detector and soil surrounding the detector. Seven energy groups the data for which were condensed from 128 group data set over the neutron energy spectrum appropriate to the soil-water mixture under study proved adequate to describe neutron slowing-down and diffusion. The soil-water mixture was an SiO2-water mixture with the absorption cross section of SiO2 increased to cover the range of SIGMA Σα required. The response to changes in matrix density is in general linear but the response to changes in water content is not linear over the range of parameter values investigated. Tabular results are presented which allow interpolation of the response for a particular ω, Sα and ρ. It is shown that R(ω.Sα. ρ)= ρ M(Sα) + C (ω)is a crude representation of the response over a very limited range of variation of ω and Sα. As the response is a slowly varying function of ρ, Sα, and ω a polynomial fit will provide a better estimate of the response for values of ρ, Sα and ω not tabulated

Analysis of InAs/GaAs quantum dot solar cells using Suns-V<inf>oc</inf> measurements

This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0927024814003833#.The performance of InAs/GaAs quantum dot solar cells was investigated up to an optical concentration of 500-suns. A high temperature spacer layer between successive layers of quantum dots was used to reduce the degradation in the open circuit voltage relative to a control device without quantum dots. This improvement is explained using optical data while structural imaging of quantum dot stacks confirm that the devices are not limited by strain. The evolution of the open circuit voltage as a function of number of suns concentration was observed to be nearly ideal when compared with a high performance single junction GaAs solar cell. Analysis of Suns-Voc measurements reveal diode ideality factors as low as 1.16 which is indicative of a low concentration of defects in the devices.The authors acknowledge financial support from the European Union under the Seventh Framework Programme under a contract for an Integrated Infrastructure Initiative. Reference 312483 – ESTEEM2

Analysis of InAs/GaAs quantum dot solar cells using Suns-Voc measurements

The performance of InAs/GaAs quantum dot solar cells was investigated up to an optical concentration of 500-suns. A high temperature spacer layer between successive layers of quantum dots was used to reduce the degradation in the open circuit voltage relative to a control device without quantum dots. This improvement is explained using optical data while structural imaging of quantum dot stacks confirm that the devices are not limited by strain. The evolution of the open circuit voltage as a function of number of suns concentration was observed to be nearly ideal when compared with a high performance single junction GaAs solar cell. Analysis of Suns-Voc measurements reveal diode ideality factors as low as 1.16 which is indicative of a low concentration of defects in the devices.The authors acknowledge financial support from the European Union under the Seventh Framework Programme under a contract for an Integrated Infrastructure Initiative. Reference 312483 – ESTEEM2.This is the final accepted version, the article was originally published in Solar Energy Materials & Solar Cells, Vol. 130, November 2014, Pages 241–245, doi:10.1016/j.solmat.2014.07.022

Paradoxical upgrading reaction in extra-pulmonary tuberculosis: association with vitamin D therapy

SETTING: Glasgow, Scotland, UK. BACKGROUND: Paradoxical reactions in tuberculosis (TB) are a notable example of our incomplete understanding of host-pathogen interactions during anti-tuberculosis treatment. OBJECTIVES: To determine risk factors for a TB paradoxical reaction, and specifically to assess for an independent association with vitamin D use. DESIGN: Consecutive human immunodeficiency virus (HIV) negative adult patients treated for extra-pulmonary TB were identified from an Extended Surveillance of Mycobacterial Infections database. In our setting, vitamin D was variably prescribed for newly diagnosed TB patients. A previously published definition of paradoxical TB reaction was retrospectively applied to, and data on all previously described risk factors were extracted from, centralised electronic patient records. The association with vitamin D use was assessed using multivariate logistic regression. RESULTS: Of the 249 patients included, most had TB adenopathy; 222/249 had microbiologically and/or histologically confirmed TB. Vitamin D was prescribed for 57/249 (23%) patients; 37/249 (15%) were classified as having paradoxical reactions. Younger age, acid-fast bacilli-positive invasive samples, multiple disease sites, lower lymphocyte count and vitamin D use were found to be independent risk factors. CONCLUSION: We speculate that vitamin D-mediated signalling of pro-inflammatory innate immune cells, along with high antigenic load, may mediate paradoxical reactions in anti-tuberculosis treatment

Internet-based psychoeducation for bipolar disorder: a qualitative analysis of feasibility, acceptability and impact

&lt;p&gt;Background: In a recent exploratory randomised trial we found that a novel, internet-based psychoeducation programme for bipolar disorder (Beating Bipolar) was relatively easy to deliver and had a modest effect on psychological quality of life. We sought to explore the experiences of participants with respect to feasibility, acceptability and impact of Beating Bipolar.&lt;/p&gt; &lt;p&gt;Methods: Participants were invited to take part in a semi-structured interview. Thematic analysis techniques were employed; to explore and describe participants’ experiences, the data were analysed for emerging themes which were identified and coded.&lt;/p&gt; &lt;p&gt;Results: The programme was feasible to deliver and acceptable to participants where they felt comfortable using a computer. It was found to impact upon insight into illness, health behaviour, personal routines and positive attitudes towards medication. Many participants regarded the programme as likely to be most beneficial for those recently diagnosed.&lt;/p&gt; &lt;p&gt;Conclusions: An online psychoeducation package for bipolar disorder, such as Beating Bipolar, is feasible and acceptable to patients, has a positive impact on self-management behaviours and may be particularly suited to early intervention. Alternative (non-internet) formats should also be made available to patients.&lt;/p&gt

Who knows best? A Q methodology study to explore perspectives of professional stakeholders and community participants on health in low-income communities

Abstract Background Health inequalities in the UK have proved to be stubborn, and health gaps between best and worst-off are widening. While there is growing understanding of how the main causes of poor health are perceived among different stakeholders, similar insight is lacking regarding what solutions should be prioritised. Furthermore, we do not know the relationship between perceived causes and solutions to health inequalities, whether there is agreement between professional stakeholders and people living in low-income communities or agreement within these groups. Methods Q methodology was used to identify and describe the shared perspectives (‘subjectivities’) that exist on i) why health is worse in low-income communities (‘Causes’) and ii) the ways that health could be improved in these same communities (‘Solutions’). Purposively selected individuals (n = 53) from low-income communities (n = 25) and professional stakeholder groups (n = 28) ranked ordered sets of statements – 34 ‘Causes’ and 39 ‘Solutions’ – onto quasi-normal shaped grids according to their point of view. Factor analysis was used to identify shared points of view. ‘Causes’ and ‘Solutions’ were analysed independently, before examining correlations between perspectives on causes and perspectives on solutions. Results Analysis produced three factor solutions for both the ‘Causes’ and ‘Solutions’. Broadly summarised these accounts for ‘Causes’ are: i) ‘Unfair Society’, ii) ‘Dependent, workless and lazy’, iii) ‘Intergenerational hardships’ and for ‘Solutions’: i) ‘Empower communities’, ii) ‘Paternalism’, iii) ‘Redistribution’. No professionals defined (i.e. had a significant association with one factor only) the ‘Causes’ factor ‘Dependent, workless and lazy’ and the ‘Solutions’ factor ‘Paternalism’. No community participants defined the ‘Solutions’ factor ‘Redistribution’. The direction of correlations between the two sets of factor solutions – ‘Causes’ and ‘Solutions’ – appear to be intuitive, given the accounts identified. Conclusions Despite the plurality of views there was broad agreement across accounts about issues relating to money. This is important as it points a way forward for tackling health inequalities, highlighting areas for policy and future research to focus on

Genetics of height and risk of atrial fibrillation: A Mendelian randomization study.

BACKGROUND: Observational studies have identified height as a strong risk factor for atrial fibrillation, but this finding may be limited by residual confounding. We aimed to examine genetic variation in height within the Mendelian randomization (MR) framework to determine whether height has a causal effect on risk of atrial fibrillation. METHODS AND FINDINGS: In summary-level analyses, MR was performed using summary statistics from genome-wide association studies of height (GIANT/UK Biobank; 693,529 individuals) and atrial fibrillation (AFGen; 65,446 cases and 522,744 controls), finding that each 1-SD increase in genetically predicted height increased the odds of atrial fibrillation (odds ratio [OR] 1.34; 95% CI 1.29 to 1.40; p = 5 × 10-42). This result remained consistent in sensitivity analyses with MR methods that make different assumptions about the presence of pleiotropy, and when accounting for the effects of traditional cardiovascular risk factors on atrial fibrillation. Individual-level phenome-wide association studies of height and a height genetic risk score were performed among 6,567 European-ancestry participants of the Penn Medicine Biobank (median age at enrollment 63 years, interquartile range 55-72; 38% female; recruitment 2008-2015), confirming prior observational associations between height and atrial fibrillation. Individual-level MR confirmed that each 1-SD increase in height increased the odds of atrial fibrillation, including adjustment for clinical and echocardiographic confounders (OR 1.89; 95% CI 1.50 to 2.40; p = 0.007). The main limitations of this study include potential bias from pleiotropic effects of genetic variants, and lack of generalizability of individual-level findings to non-European populations. CONCLUSIONS: In this study, we observed evidence that height is likely a positive causal risk factor for atrial fibrillation. Further study is needed to determine whether risk prediction tools including height or anthropometric risk factors can be used to improve screening and primary prevention of atrial fibrillation, and whether biological pathways involved in height may offer new targets for treatment of atrial fibrillation

A novel approach to simulate gene-environment interactions in complex diseases

Background: Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results: We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions: By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study

Telecare motivational interviewing for diabetes patient education and support : a randomised controlled trial based in primary care comparing nurse and peer supporter delivery

Background: There is increasing interest in developing peer-led and 'expert patient'-type interventions, particularly to meet the support and informational needs of those with long term conditions, leading to improved clinical outcomes, and pressure relief on mainstream health services. There is also increasing interest in telephone support, due to its greater accessibility and potential availability than face to face provided support. The evidence base for peer telephone interventions is relatively weak, although such services are widely available as support lines provided by user groups and other charitable services. Methods/Design: In a 3-arm RCT, participants are allocated to either an intervention group with Telecare service provided by a Diabetes Specialist Nurse (DSN), an intervention group with service provided by a peer supporter (also living with diabetes), or a control group receiving routine care only. All supporters underwent a 2-day training in motivational interviewing, empowerment and active listening skills to provide telephone support over a period of up to 6 months to adults with poorly controlled type 2 diabetes who had been recommended a change in diabetes management (i.e. medication and/or lifestyle changes) by their general practitioner (GP). The primary outcome is self-efficacy; secondary outcomes include HbA1c, total and HDL cholesterol, blood pressure, body mass index, and adherence to treatment. 375 participants (125 in each arm) were sought from GP practices across West Midlands, to detect a difference in self-efficacy scores with an effect size of 0.35, 80% power, and 5% significance level. Adults living with type 2 diabetes, with an HbA1c > 8% and not taking insulin were initially eligible. A protocol change 10 months into the recruitment resulted in a change of eligibility by reducing HbA1c to > 7.4%. Several qualitative studies are being conducted alongside the main RCT to describe patient, telecare supporter and practice nurse experience of the trial. Discussion and implications of the research: With its focus on self-management and telephone peer support, the intervention being trialled has the potential to support improved self-efficacy and patient experience, improved clinical outcomes and a reduction in diabetes-related complications

Mapping structural diversity in networks sharing a given degree distribution and global clustering: Adaptive resolution grid search evolution with Diophantine equation-based mutations

Methods that generate networks sharing a given degree distribution and global clustering can induce changes in structural properties other than that controlled for. Diversity in structural properties, in turn, can affect the outcomes of dynamical processes operating on those networks. Since exhaustive sampling is not possible, we propose a novel evolutionary framework for mapping this structural diversity. The three main features of this framework are: (a) subgraph-based encoding of networks, (b) exact mutations based on solving systems of Diophantine equations, and (c) heuristic diversity-driven mechanism to drive resolution changes in the MapElite algorithm.We show that our framework can elicit networks with diversity in their higher-order structure and that this diversity affects the behaviour of the complex contagion model. Through a comparison with state of the art clustered network generation methods, we demonstrate that our approach can uncover a comparably diverse range of networks without needing computationally unfeasible mixing times. Further, we suggest that the subgraph-based encoding provides greater confidence in the diversity of higher-order network structure for low numbers of samples and is the basis for explaining our results with complex contagion model. We believe that this framework could be applied to other complex landscapes that cannot be practically mapped via exhaustive sampling