Survival in dialysis patients is different between patients with diabetes as primary renal disease and patients with diabetes as a co-morbid condition.

AIMS/HYPOTHESIS:

A previous study in Dutch dialysis patients showed no survival difference between patients with diabetes as primary renal disease and those with diabetes as a co-morbid condition. As this was not in line with our hypothesis, we aimed to verify these results in a larger international cohort of dialysis patients.

METHODS:

For the present prospective study, we used data from the European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) Registry. Incident dialysis patients with data on co-morbidities (n?=?15,419) were monitored until kidney transplantation, death or end of the study period (5 years). Cox regression was performed to compare survival for patients with diabetes as primary renal disease, patients with diabetes as a co-morbid condition and non-diabetic patients.

RESULTS:

Of the study population, 3,624 patients (24%) had diabetes as primary renal disease and 1,193 (11%) had diabetes as a co-morbid condition whereas the majority had no diabetes (n?=?10,602). During follow-up, 7,584 (49%) patients died. In both groups of diabetic patients mortality was higher compared with the non-diabetic patients. Mortality was higher in patients with diabetes as primary renal disease than in patients with diabetes as a co-morbid condition, adjusted for age, sex, country and malignancy (HR 1.20, 95% CI 1.10, 1.30). An analysis stratified by dialysis modality yielded similar results.

CONCLUSIONS/INTERPRETATION:

Overall mortality was significantly higher in patients with diabetes as primary renal disease compared with those with diabetes as a co-morbid condition. This suggests that survival in diabetic dialysis patients is affected by the extent to which diabetes has induced organ damage.

Condition Assessment and Preservation of Open-Air Rock Art Panels During Climate Change

Thousands of Neolithic and Bronze Age open-air rock art panels exist across the countryside in northern England. However, desecration, pollution, and other factors are threatening the survival of these iconic stone monuments. Evidence suggest that rates of panel deterioration may be increasing, although it is not clear whether this is due to local factors or wider environmental influences accelerated by environmental change. To examine this question, 18 rock art panels with varied art motifs were studied at two major panel locations at Lordenshaw and Weetwood Moor in Northumberland. A condition assessment
tool was used to first quantify the level of deterioration of each panel (called “staging”). Stage estimates then were compared statistically with 27 geochemical and physical descriptors of local environments, such as soil moisture, salinity, pH, lichen coverage, soil anions and cation levels, and panel orientation, slope, and standing height. In parallel, climate modelling was performed using UKCP09 to assess how projected climatic conditions (to 2099) might affect the environmental descriptors most correlated with elevated stone deterioration. Only two descriptors significantly correlated (P < 0.05) with increased stage: the standing height of the panel and the exchangeable cation content of the local soils, although moisture conditions also were potentially influential at some panels. Climate modelling predicts warming temperatures, more seasonally variable precipitation, and increased wind speeds, which hint stone deterioration could accelerate in the future due to increased physiochemical weathering. We recommend key panels be targeted for immediate management intervention, focusing on reducing wind exposures, improving site drainage, and potentially immobilizing soil salts.

Stone-built heritage inventory and ‘performance in use’ condition assessment of stonework

An academic–industrial partnership was formed with the aim of constructing a natural stone database for Northern Ireland that could be used by the public and practitioners to understand both the characteristics of the stone used in construction across Northern Ireland and how it has performed in use, and, through a linked database of historical quarries, explore the potential for obtaining locally sourced replacement stone. The aims were to improve the level of conservation specification by those with a duty of care for historical structures, and to enhance the quality of the conservation work undertaken by archi- tects and contractors through their improved knowledge of stone and stone decay processes.

Electrooxidation of methanol in an alkaline fuel cell: determination of the nature of the initial adsorbate

It is essential to correctly determine the nature of the initial adsorbate in order to calculate the pathway for any given reaction. Recent literature provides conflicting information on the first step in the methanol decomposition pathway. This work sets out to establish what role the solution and the surface have to play in the initial adsorption-deprotonation process. Density functional theory (DFT) calculations, in combination with a cluster-continuum model approach are used to resolve the nature of the adsorbing species. We show that methanol is the dominant species in solution over methoxide, and also has a smaller barrier to adsorption. The nature of the surface species is revealed to be a methanol-OH complex.

Investigation of moisture condition and Autoclam sensitivity on air permeability measurements for both normal concrete and high performance concrete

While on site measurement of air permeability provides a useful approach for assessing the likely long term durability of concrete structures, no existing test method is capable of effectively determining the relative permeability of high performance concrete (HPC). Lack of instrument sensitivity and the influence of concrete moisture are proposed as two key reasons for this phenomenon. With limited systematic research carried out in this area to date, the aim if this study was to investigate the influence of instrument sensitivity and moisture condition on air permeability measurements for both normal concrete and HPC. To achieve a range of moisture conditions, samples were dried initially for between one and 5 weeks and then sealed in polythene sheeting and stored in an oven at 50 C to internally distribute moisture evenly. Moisture distribution was determined throughout using relative humidity probe and electrical resistance measurements. Concrete air permeability was subsequently measured using standardised air permeability (Autoclam) and water penetration (BS EN: 12390-8) tests to assess differences between the HPCs tested in this study. It was found that for both normal and high performance concrete, the influence of moisture on Autoclam air permeability results could be eliminated by pre-drying (50 ± 1 C, RH 35%) specimens for 3 weeks. While drying for 5 weeks alone was found not to result in uniform internal moisture distributions, this state was achieved by exposing specimens to a further 3 weeks of sealed pre-conditioning at 50 ± 1 C. While the Autoclam test was not able to accurately identify relative HPC quality due to low sensitivity at associated performance levels, an effective preconditioning procedure to obtain reliable air permeability of HPC concretes was identified. © 2013 The Authors

Distributed Adaptive Learning Framework for Wide Area Monitoring of Power Systems Integrated with Distributed Generations

This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.

"Getting-by', Coping and Resilience in Difficult Times: Initial Findings

A report provided the initial findings from a research project that examined the resilience of households in Northern Ireland. Drawing on baseline survey data and qualitative interviews with households across four neighbourhoods, it outlined a range of challenges and the strategies used by households to 'get by'. The report said that, for these households, resilience was not about 'bouncing back', 'flourishing', or 'thriving' in the face of adversity, but was about not being overcome, 'getting-by', enduring, surviving, just 'getting on with things', and 'keeping their heads above the water'. The report noted the susceptibility of households to future stressors, such as welfare reform, especially those on means-tested benefits or with long-term illness or disability. Place, and relationships with family and friends, appeared to be important for resilience and future work would investigate this further. The report highlighted issues around the measurement of resilience and noted the importance of qualitative work.

Earthmoving trucks condition level prediction using neural networks

Purpose: The purpose of this paper is to present an artificial neural network (ANN) model that predicts earthmoving trucks condition level using simple predictors; the model’s performance is compared to the respective predictive accuracy of the statistical method of discriminant analysis (DA).

Design/methodology/approach: An ANN-based predictive model is developed. The condition level predictors selected are the capacity, age, kilometers travelled and maintenance level. The relevant data set was provided by two Greek construction companies and includes the characteristics of 126 earthmoving trucks.

Findings: Data processing identifies a particularly strong connection of kilometers travelled and maintenance level with the earthmoving trucks condition level. Moreover, the validation process reveals that the predictive efficiency of the proposed ANN model is very high. Similar findings emerge from the application of DA to the same data set using the same predictors.

Originality/value: Earthmoving trucks’ sound condition level prediction reduces downtime and its adverse impact on earthmoving duration and cost, while also enhancing the maintenance and replacement policies effectiveness. This research proves that a sound condition level prediction for earthmoving trucks is achievable through the utilization of easy to collect data and provides a comparative evaluation of the results of two widely applied predictive methods.