Investigation of failures in Irish raised bogs

This paper presents the results of field geophysical testing and laboratory testing of peat from Carn Park and Roosky raised bogs in the Irish Midlands. The motivation for the work was highlight the importance of these areas and to begin to attempt to understand the reasons for the failure of the bogs despite them having surface slopes of some 1°. It was found that the peat is typical of that of Irish raised bogs being up to 8m thick towards the “high” dome of the bogs. The peat is characterised by low density, high water content, high organic content, low undrained shear strength and high compressibility. The peat is also relatively permeable at in situ stress. Geophysical electrical resistivity tomography and ground penetrating radar data shows a clear thinning of the peat in the area of the failures corresponding to a reduction in volume from dewatering by edge drains/peat harvesting. This finding is supported by detailed water content measurements. It was also shown that the peat base topography is relatively flat and indicates that the observed surface movement has come from within the peat rather than from the material below the peat. Potential causes of the failures include conventional slope instability, the effect of seepage forces or the release of built-up gas in the peat mass. Further measurements are required in order to study these in more detail.

Dataflow toolset for soft-core processors on FPGA for image processing applications

With security and surveillance, there is an increasing need to be able to process image data efficiently and effectively either at source or in a large data networks. Whilst Field Programmable Gate Arrays have been seen as a key technology for enabling this, they typically use high level and/or hardware description language synthesis approaches; this provides a major disadvantage in terms of the time needed to design or program them and to verify correct operation; it considerably reduces the programmability capability of any technique based on this technology. The work here proposes a different approach of using optimised soft-core processors which can be programmed in software. In particular, the paper proposes a design tool chain for programming such processors that uses the CAL Actor Language as a starting point for describing an image processing algorithm and targets its implementation to these custom designed, soft-core processors on FPGA. The main purpose is to exploit the task and data parallelism in order to achieve the same parallelism as a previous HDL implementation but avoiding the design time, verification and debugging steps associated with such approaches.

Design of a Dissolving Microneedle Platform for Transdermal Delivery of a Fixed-Dose Combination of Cardiovascular Drugs

Microneedles (MNs) are a minimally invasive drug delivery platform, designed to enhance transdermal drug delivery by breaching the stratum corneum. For the first time, this study describes the simultaneous delivery of a combination of three drugs using a dissolving polymeric MN system. In the present study, aspirin, lisinopril dihydrate, and atorvastatin calcium trihydrate were used as exemplar cardiovascular drugs and formulated into MN arrays using two biocompatible polymers, poly(vinylpyrrollidone) and poly(methylvinylether/maleic acid). Following fabrication, dissolution, mechanical testing, and determination of drug recovery from the MN arrays, in vitro drug delivery studies were undertaken, followed by HPLC analysis. All three drugs were successfully delivered in vitro across neonatal porcine skin, with similar permeation profiles achieved from both polymer formulations. An average of 126.3 ± 18.1 μg of atorvastatin calcium trihydrate was delivered, notably lower than the 687.9 ± 101.3 μg of lisinopril and 3924 ± 1011 μg of aspirin, because of the hydrophobic nature of the atorvastatin molecule and hence poor dissolution from the array. Polymer deposition into the skin may be an issue with repeat application of such a MN array, hence future work will consider more appropriate MN systems for continuous use, alongside tailoring delivery to less hydrophilic compounds.

Simulating reinforced concrete members. Part 2: displacement-based analyses

A companion paper described the partial-interaction localised properties that require the development of pseudo properties. If the quantification through experimental testing of these pseudo properties could be removed by the use of mechanics-based models, which is the subject of this paper, then this would: (a) substantially reduce the cost of developing new reinforced concrete products by reducing the amount of testing; (b) increase the accuracy of designing existing and novel reinforced concrete members and structures, bearing in mind that experimentally derived pseudo properties are only applicable within the range of the testing from which they were derived; and (c) reduce the cost and increase the accuracy of developing reinforced concrete design rules. This paper deals with the development of pseudo properties and behaviours directly through mechanics, as opposed to experimental testing, and their incorporation into member global simulations. It also addresses the need for a fundamental shift to displacement-based analyses as opposed to strain-based analyses.

Using interviewer random effects to remove selection bias from HIV prevalence estimates

Background: Selection bias in HIV prevalence estimates occurs if non-participation in testing is correlated with HIV status. Longitudinal data suggests that individuals who know or suspect they are HIV positive are less likely to participate in testing in HIV surveys, in which case methods to correct for missing data which are based on imputation and observed characteristics will produce biased results. Methods: The identity of the HIV survey interviewer is typically associated with HIV testing participation, but is unlikely to be correlated with HIV status. Interviewer identity can thus be used as a selection variable allowing estimation of Heckman-type selection models. These models produce asymptotically unbiased HIV prevalence estimates, even when non-participation is correlated with unobserved characteristics, such as knowledge of HIV status. We introduce a new random effects method to these selection models which overcomes non-convergence caused by collinearity, small sample bias, and incorrect inference in existing approaches. Our method is easy to implement in standard statistical software, and allows the construction of bootstrapped standard errors which adjust for the fact that the relationship between testing and HIV status is uncertain and needs to be estimated. Results: Using nationally representative data from the Demographic and Health Surveys, we illustrate our approach with new point estimates and confidence intervals (CI) for HIV prevalence among men in Ghana (2003) and Zambia (2007). In Ghana, we find little evidence of selection bias as our selection model gives an HIV prevalence estimate of 1.4% (95% CI 1.2% – 1.6%), compared to 1.6% among those with a valid HIV test. In Zambia, our selection model gives an HIV prevalence estimate of 16.3% (95% CI 11.0% - 18.4%), compared to 12.1% among those with a valid HIV test. Therefore, those who decline to test in Zambia are found to be more likely to be HIV positive. Conclusions: Our approach corrects for selection bias in HIV prevalence estimates, is possible to implement even when HIV prevalence or non-participation is very high or very low, and provides a practical solution to account for both sampling and parameter uncertainty in the estimation of confidence intervals. The wide confidence intervals estimated in an example with high HIV prevalence indicate that it is difficult to correct statistically for the bias that may occur when a large proportion of people refuse to test.

On the Assumption of Bivariate Normality in Selection Models: A Copula Approach Applied to Estimating HIV Prevalence

Background: Heckman-type selection models have been used to control HIV prevalence estimates for selection bias when participation in HIV testing and HIV status are associated after controlling for observed variables. These models typically rely on the strong assumption that the error terms in the participation and the outcome equations that comprise the model are distributed as bivariate normal.
Methods: We introduce a novel approach for relaxing the bivariate normality assumption in selection models using copula functions. We apply this method to estimating HIV prevalence and new confidence intervals (CI) in the 2007 Zambia Demographic and Health Survey (DHS) by using interviewer identity as the selection variable that predicts participation (consent to test) but not the outcome (HIV status).
Results: We show in a simulation study that selection models can generate biased results when the bivariate normality assumption is violated. In the 2007 Zambia DHS, HIV prevalence estimates are similar irrespective of the structure of the association assumed between participation and outcome. For men, we estimate a population HIV prevalence of 21% (95% CI = 16%–25%) compared with 12% (11%–13%) among those who consented to be tested; for women, the corresponding figures are 19% (13%–24%) and 16% (15%–17%).
Conclusions: Copula approaches to Heckman-type selection models are a useful addition to the methodological toolkit of HIV epidemiology and of epidemiology in general. We develop the use of this approach to systematically evaluate the robustness of HIV prevalence estimates based on selection models, both empirically and in a simulation study.

Adjusting HIV Prevalence Estimates for Non-participation: an Application to Demographic Surveillance

Introduction: HIV testing is a cornerstone of efforts to combat the HIV epidemic, and testing conducted as part of surveillance provides invaluable data on the spread of infection and the effectiveness of campaigns to reduce the transmission of HIV. However, participation in HIV testing can be low, and if respondents systematically select not to be tested because they know or suspect they are HIV positive (and fear disclosure), standard approaches to deal with missing data will fail to remove selection bias. We implemented Heckman-type selection models, which can be used to adjust for missing data that are not missing at random, and established the extent of selection bias in a population-based HIV survey in an HIV hyperendemic community in rural South Africa.

Methods: We used data from a population-based HIV survey carried out in 2009 in rural KwaZulu-Natal, South Africa. In this survey, 5565 women (35%) and 2567 men (27%) provided blood for an HIV test. We accounted for missing data using interviewer identity as a selection variable which predicted consent to HIV testing but was unlikely to be independently associated with HIV status. Our approach involved using this selection variable to examine the HIV status of residents who would ordinarily refuse to test, except that they were allocated a persuasive interviewer. Our copula model allows for flexibility when modelling the dependence structure between HIV survey participation and HIV status.

Results: For women, our selection model generated an HIV prevalence estimate of 33% (95% CI 27–40) for all people eligible to consent to HIV testing in the survey. This estimate is higher than the estimate of 24% generated when only information from respondents who participated in testing is used in the analysis, and the estimate of 27% when imputation analysis is used to predict missing data on HIV status. For men, we found an HIV prevalence of 25% (95% CI 15–35) using the selection model, compared to 16% among those who participated in testing, and 18% estimated with imputation. We provide new confidence intervals that correct for the fact that the relationship between testing and HIV status is unknown and requires estimation.

Conclusions: We confirm the feasibility and value of adopting selection models to account for missing data in population-based HIV surveys and surveillance systems. Elements of survey design, such as interviewer identity, present the opportunity to adopt this approach in routine applications. Where non-participation is high, true confidence intervals are much wider than those generated by standard approaches to dealing with missing data suggest.

Next generation Bridge weigh-in-motion using fibre optic sensors

There have been over 3000 bridge weigh-in-motion (B-WIM) installations in 25 countries worldwide, this has led vast improvements in post processing of B-WIM systems since its introduction in the 1970’s. Existing systems are based on electrical resistance strain gauges which can be prohibitive in achieving data for long term monitoring of rural bridges due to power consumption. This paper introduces a new low-power B-WIM system using fibre optic sensors (FOS). The system consisted of a series of FOS which were attached to the soffit of an existing integral bridge with a single span of 19m. The site selection criteria and full installation process has been detailed in the paper. A method of calibration was adopted using live traffic at the bridge site and based on this calibration the accuracy of the system was determined. New methods of axle detection for B-WIM were investigated and verified in the field.

Mode of prostate cancer detection is associated with the psychological wellbeing of survivors: results from the PiCTure study

Purpose: Many men with prostate cancer are asymptomatic, diagnosed following prostate specific antigen (PSA) testing. We investigate whether mode of detection, i.e. ‘PSA detected’ or ‘clinically detected’, was associated with psychological wellbeing among prostate cancer survivors. Methods: A cross-sectional postal questionnaire was administered in 2012 to 6559 prostate cancer (ICD10 C61) survivors up to 18 years post-diagnosis, identified through population-based cancer registries in Ireland. Psychological wellbeing was assessed using the Depression Anxiety Stress Scale-21. Logistic regression was used to investigate associations between mode of detection and depression, anxiety and stress, adjusting for socio-demographic and clinical confounders. Results: The response rate was 54 % (3348/6262). Fifty-nine percent of survivors were diagnosed with asymptomatic PSA-tested disease. Prevalence of depression (13.8 vs 20.7 %; p < 0.001), anxiety (13.6 vs 20.9 %; p < 0.001) and stress (8.7 vs 13.8 %; p < 0.001) were significantly lower among survivors diagnosed with PSA-detected, than clinically detected disease. After adjusting for clinical and socio-demographic factors, survivors with clinically detected disease had significantly higher risk of depression (odds ratio (OR) = 1.46 95 % CI 1.18, 1.80; p = 0.001), anxiety (OR = 1.36 95 % CI 1.09, 1.68; p = 0.006) and stress (OR = 1.43 95 % CI 1.11, 1.85; p = 0.006) than survivors with PSA-detected disease. Conclusions: These findings contribute to the ongoing debate on benefits and risks of PSA testing and may be considered by policy makers formulating population-based prostate cancer screening policies. The relatively high prevalence of negative psychological states among survivors means that a ‘risk-adapted approach’ should be implemented to screen survivors most at risk of psychological morbidity for psychological health, and mode of detection could be considered as a risk stratum.

Pupillary threshold as an index of population vitamin A status among children in India

Two hundred seven vitamin A-deficient southern Indian children aged 1-7 y (mean age: 56.9 mo) underwent testing of dark-adapted visual and pupillary thresholds in their village setting according to a previously reported protocol. One hundred thirty (62.8%) of the children also underwent serum retinol testing, and 178 (86.0%) participated in a randomized, placebo-controlled vitamin A dosing trial with pre- and postdose testing of dark-adaptation threshold. Most subjects (184 of 207, 88.9%) were able to complete pupillary testing, an objective sign requiring minimal cooperation, including a high proportion of the youngest children (72.2% of subjects aged 2 y). The proportion of children completing visual threshold testing, which requires greater understanding and cooperation, was significantly smaller than that able to complete pupillary testing (131 of 207, 63.3%; P < 0.0001, chi square). At baseline (predosing), the mean serum retinol concentration declined in linear fashion with a higher pupillary threshold (0.73 mumol/L with a score < or = 4; 0.47 mumol/L with a score > or = 8; P < 0.01). The mean pupillary threshold for these highly vitamin A-deficient Indian children (-0.622 log cd/m2) was significantly higher than that for 136 more moderately deficient Indonesian children (-0.985 log cd/m2; P < 0.001, two-sample t test) and 56 normal American children (-1.335 log cd/m2; P < 0.0001, two-sample t test). The improvement in pupillary dark-adaptation testing was not significant for children receiving vitamin A or placebo, though there was a nonsignificant trend toward greater improvement in children receiving vitamin A (P = 0.2, two-sample t test). Pupillary threshold testing represents a new, noninvasive, practical, and seemingly valid approach to assessing the vitamin A status of a moderately to severely deficient preschool population.

Ophthalmology. 2011 Dec;118(12):2343-50. doi: 10.1016/j.ophtha.2011.06.016. Epub 2011 Sep 1. Randomized, controlled trial of an educational intervention to promote spectacle use in rural China: the see well to learn well study.

OBJECTIVE: To test an educational intervention promoting the purchase of spectacles among Chinese children. DESIGN: Randomized, controlled trial. PARTICIPANTS: Children in years 1 and 2 of all 20 junior and senior high schools (ages 12-17 years) in 3 rural townships in Guangdong, China. METHODS: Children underwent visual acuity (VA) testing, and parents of participants with presenting VA worse than 6/12 in either eye improving by more than 2 lines with cycloplegic refraction were recommended to purchase glasses. Children at 10 randomly selected schools received a lecture, video, and classroom demonstration promoting spectacle purchase. MAIN OUTCOME MEASURES: Self-reported purchase of spectacles (primary outcome) and observed wear or possession of newly purchased glasses (secondary outcome) at follow-up examinations (mean, 219 ± 87 days after the baseline visit). RESULTS: Among 15 404 eligible children, examinations were completed for 6379 (74.6%) at intervention schools and 5044 (73.6%) at control schools. Spectacles were recommended for 2236 (35.1%) children at intervention schools and for 2212 (43.9%) at control schools. Of these, 417 (25.7%) intervention schools children and 537 (34.0%, P = 0.45) control schools children reported buying glasses. Predictors of purchase in regression models included female gender (P = 0.02), worse uncorrected VA (P < 0.001), and higher absolute value of refractive error (P = 0.001). Neither the rate of self-reported purchase of glasses or observed wear or possession of newly purchased glasses differed between control schools and intervention schools in mixed-effect logistic regression models. Among children not purchasing glasses, 21.7% had better-eye VA of worse than 6/18. CONCLUSIONS: An intervention based on extensive pilot testing and focus groups in the area failed to promote spectacle purchase or wear. The high burden of remaining uncorrected poor vision underscores the need to develop better interventions. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Sustainable non-automotive vehicles: The simulation challenges

Simulation is a well-established and effective approach to the development of fuel-efficient and low-emissions vehicles in both on-highway and off-highway applications.

The simulation of on-highway automotive vehicles is widely reported in literature, whereas research relating to non-automotive and off-highway vehicles is relatively sparse. This review paper focuses on the challenges of simulating such vehicles and discusses the differences in the approach to drive cycle testing and experimental validation of vehicle simulations. In particular, an inner-city diesel-electric hybrid bus and an ICE (Internal Combustion Engine) powered forklift truck will be used as case studies.

Computer prediction of fuel consumption and emissions of automotive vehicles on standardised drive cycles is well-established and commercial software packages such as AVL CRUISE have been specifically developed for this purpose. The vehicles considered in this review paper present new challenges from both the simulation and drive-cycle testing perspectives. For example, in the case of the forklift truck, the drive cycles involve reversing elements, variable mass, lifting operations, and do not specify a precise velocity-time profile. In particular, the difficulties associated with the prediction of productivity, i.e. the maximum rate of completing a series of defined operations, are discussed. In the case of the hybrid bus, the standardised drive cycles are unrepresentative of real-life use and alternative approaches are required in the development of efficient and low-emission vehicles.

Two simulation approaches are reviewed: the adaptation of a standard automotive vehicle simulation package, and the development of bespoke models using packages such as MATLAB/Simulink.

Dimensioning of multilayer optical networks

Este trabalho apresenta um estudo sobre o dimensionamento de redes ópticas, com vistas a obter um modelo de dimensionamento para redes de transporte sobreviventes. No estudo utilizou-se uma abordagem estatística em detrimento à determinística. Inicialmente, apresentam-se as principais tecnologias e diferentes arquitecturas utilizadas nas redes ópticas de transporte. Bem como os principais esquemas de sobrevivência e modos de transporte. São identificadas variáveis necessárias e apresenta-se um modelo dimensionamento para redes de transporte, tendo-se dado ênfase às redes com topologia em malha e considerando os modos de transporte opaco, transparente e translúcido. É feita uma análise rigorosa das características das topologias de redes de transporte reais, e desenvolve-se um gerador de topologias de redes de transporte, para testar a validade dos modelos desenvolvidos. Também é implementado um algoritmo genético para a obtenção de uma topologia optimizada para um dado tráfego. São propostas expressões para o cálculo de variáveis não determinísticas, nomeadamente, para o número médio de saltos de um pedido, coeficiente de protecção e coeficiente de restauro. Para as duas últimas, também é analisado o impacto do modelo de tráfego. Verifica-se que os resultados obtidos pelas expressões propostas são similares às obtidas por cálculo numérico, e que o modelo de tráfego não influencia significativamente os valores obtidos para os coeficientes. Finalmente, é demonstrado que o modelo proposto é útil para o dimensionamento e cálculo dos custos de capital de redes com informação incompleta.