Sequence Effects in the Valuation of Multiple Environmental Programs Using the Contingent Valuation Method

In contingent valuation, the willingness to pay for hypothetical programs may be affected by the order in which programs are presented to respondents. With inclusive lists, economic theory suggests that sequence effects should be expected. However, when policy makers allocate public budgets to several environmental programs, they may be interested in assessing the value of the programs without the valuations being affected by the order in which the programs are presented. Using single-bounded dichotomous choice contingent valuation questions, we show that if respondents have the possibility to revise their willingness-to-pay answers, sequence effects are mitigated. (JEL Q51, Q54)

Field test of multiple 1/10 scale tidal turbines in steady flows

Queen's University Belfast and Wave Barrier Ltd have developed a tidal testing platform to test hydrokinetic turbines at medium scale. Multiple turbines can be pushed through still water conditions, in steady-state pushing tests. Experiments were conducted to evaluate the interactions between two identical, mono-strut, horizontal axis tidal turbines (HATTs) of 1.5 m diameter (D) rotor. Their relative performance when located individually, in-plane and in-line are investigated. The data shows a high consistency in the power curves at different flow speeds, which indicates high repeatability in this Reynolds range. For an individual turbine, there is no performance difference when the rotor is mounted either upstream or downstream of the supporting structure. When placed in-plane, the turbines have no adverse effect on one another. When spaced in-line with 2D separation, there is a 63% reduction in the performance of the downstream turbine. At 6D downstream this performance reduction is still 59%, indicating some wake recovery between 2D and 6D, though the influence from the upstream rotor persists to at least 6D downstream of the first device. In contrast the performance of the downstream turbine when placed at 1.5D offset of the upstream device at 6D downstream is approximately recovered to the individual turbine performance.

The Combination of Multiple Classifiers Using an Evidential Reasoning Approach

In many domains when we have several competing classifiers available we want to synthesize them or some of them to get a more accurate classifier by a combination function. In this paper we propose a ‘class-indifferent’ method for combining classifier decisions represented by evidential structures called triplet and quartet, using Dempster's rule of combination. This method is unique in that it distinguishes important elements from the trivial ones in representing classifier decisions, makes use of more information than others in calculating the support for class labels and provides a practical way to apply the theoretically appealing Dempster–Shafer theory of evidence to the problem of ensemble learning. We present a formalism for modelling classifier decisions as triplet mass functions and we establish a range of formulae for combining these mass functions in order to arrive at a consensus decision. In addition we carry out a comparative study with the alternatives of simplet and dichotomous structure and also compare two combination methods, Dempster's rule and majority voting, over the UCI benchmark data, to demonstrate the advantage our approach offers. (A continuation of the work in this area that was published in IEEE Trans on KDE, and conferences)

A novel method of embedding distributed optical fiber sensor for structural health monitoring

A distributed optical fiber sensor based on Brillouin scattering (BOTDR or BOTDA) can measure and monitor strain and temperature generated along optical fiber. Because it can measure in real-time with high precision and stability, it is quite suitable for health monitoring of large-scale civil infrastructures. However, the main challenge of applying it to structural health monitoring is to ensure it is robust and can be repaired by adopting a suitable embedding method. In this paper, a novel method based on air-blowing and vacuum grouting techniques for embedding long-distance optical fiber sensors was developed. This method had no interference with normal concrete construction during its installation, and it could easily replace the long-distance embedded optical fiber sensor (LEOFS). Two stages of static loading tests were applied to investigate the performance of the LEOFS. The precision and the repeatability of the LEOFS were studied through an overloading test. The durability and the stability of the LEOFS were confirmed by a corrosion test. The strains of the LEOFS were used to evaluate the reinforcing effect of carbon fiber reinforced polymer and thereby the health state of the beams.

In Situ Formation of Micron-Scale Li-Metal Anodes with High Cyclability

Scanning probe microscopy methods have been used to electrodeposit and cycle micron-scale Li anodes deposited electrochemically under nanofabricated Au current collectors. An average Li volume of 5 x 10(8) nm(3) was deposited and cycled with 100% coulombic efficiency for similar to 160 cycles. Integrated charge/discharge values agree with before/after topography, as well as in situ dilatometry, suggesting this is a reliable method to study solid-state electrochemical processes. In this work we illustrate the possibility to deposit highly cyclable nanometer thick Li electrodes by mature SPM and nanofab techniques which can pave the way for inexpensive nanoscale battery arrays. 

Integrating geophysical data and upscaling techniques to support regional groundwater flow modelling: A practical example of the Lagan Valley, Northern Ireland

When studying heterogeneous aquifer systems, especially at regional scale, a degree of generalization is anticipated. This can be due to sparse sampling regimes, complex depositional environments or lack of accessibility to measure the subsurface. This can lead to an inaccurate conceptualization which can be detrimental when applied to groundwater flow models. It is important that numerical models are based on observed and accurate geological information and do not rely on the distribution of artificial aquifer properties. This can still be problematic as data will be modelled at a different scale to which it was collected. It is proposed here that integrating geophysics and upscaling techniques can assist in a more realistic and deterministic groundwater flow model. In this study, the sedimentary aquifer of the Lagan Valley in Northern Ireland is chosen due to intruding sub-vertical dolerite dykes. These dykes are of a lower permeability than the sandstone aquifer. The use of airborne magnetics allows the delineation of heterogeneities, confirmed by field analysis. Permeability measured at the field scale is then upscaled to different levels using a correlation with the geophysical data, creating equivalent parameters that can be directly imported into numerical groundwater flow models. These parameters include directional equivalent permeabilities and anisotropy. Several stages of upscaling are modelled in finite element. Initial modelling is providing promising results, especially at the intermediate scale, suggesting an accurate distribution of aquifer properties. This deterministic based methodology is being expanded to include stochastic methods of obtaining heterogeneity location based on airborne geophysical data. This is through the Direct Sample method of Multiple-Point Statistics (MPS). This method uses the magnetics as a training image to computationally determine a probabilistic occurrence of heterogeneity. There is also a need to apply the method to alternate geological contexts where the heterogeneity is of a higher permeability than the host rock.

A sting in the spit: widespread cross-infection of multiple RNA viruses across wild and managed bees

Declining populations of bee pollinators are a cause of concern, with major repercussions for biodiversity loss and food security. RNA viruses associated with honeybees represent a potential threat to other insect pollinators, but the extent of this threat is poorly understood. This study aims to attain a detailed understanding of the current and ongoing risk of emerging infectious disease (EID) transmission between managed and wild pollinator species across a wide range of RNA viruses. Within a structured large-scale national survey across 26 independent sites, we quantify the prevalence and pathogen loads of multiple RNA viruses in co-occurring managed honeybee (Apis mellifera) and wild bumblebee (Bombus spp.) populations. We then construct models that compare virus prevalence between wild and managed pollinators. Multiple RNA viruses associated with honeybees are widespread in sympatric wild bumblebee populations. Virus prevalence in honeybees is a significant predictor of virus prevalence in bumblebees, but we remain cautious in speculating over the principle direction of pathogen transmission. We demonstrate species-specific differences in prevalence, indicating significant variation in disease susceptibility or tolerance. Pathogen loads within individual bumblebees may be high and in the case of at least one RNA virus, prevalence is higher in wild bumblebees than in managed honeybee populations. Our findings indicate widespread transmission of RNA viruses between managed and wild bee pollinators, pointing to an interconnected network of potential disease pressures within and among pollinator species. In the context of the biodiversity crisis, our study emphasizes the importance of targeting a wide range of pathogens and defining host associations when considering potential drivers of population decline.

A Novel Semi-Automated Method of Tracking Fetal Movements

We have designed software that can â€â€™look’’ at recorded ultrasound sequences. We analyzed fifteen video sequences representing recorded ultrasound scans of nine fetuses. Our method requires a small amount of user labelled pixels for processing the first frame. These initialize GrowCut 1 , a background removal algorithm, which was used for separating the fetus from its surrounding environment (segmentation). For each subsequent frame, user input is no longer necessary as some of the pixels will inherit labels from the previously processed frame. This results in our software’s ability to track movement. Two sonographers rated the results of our computer’s â€vision’ on a scale from 1 (poor fit) to 10 (excellent fit). They assessed tracking accuracy for the entire video as well as segmentation accuracy (the ability to identify fetus from non-fetus) for every 100th processed frame. There was no appreciable deterioration in the software’s ability to track the fetus over time. I

A novel method of microsatellite genotyping-by-sequencing using individual combinatorial barcoding

This study examines the potential of next-generation sequencing based ‘genotyping-by-sequencing’ (GBS) of microsatellite loci for rapid and cost-effective genotyping in large-scale population genetic studies. The recovery of individual genotypes from large sequence pools was achieved by PCR-incorporated combinatorial barcoding using universal primers. Three experimental conditions were employed to explore the possibility of using this approach with existing and novel multiplex marker panels and weighted amplicon mixture. The GBS approach was validated against microsatellite data generated by capillary electrophoresis. GBS allows access to the underlying nucleotide sequences that can reveal homoplasy, even in large datasets and facilitates cross laboratory transfer. GBS of microsatellites, using individual combinatorial barcoding, is potentially faster and cheaper than current microsatellite approaches and offers better and more data.

Multivariate analysis of regional-scale geochemical data for environmental monitoring

A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.

A literature review to Examine the Validity and Reliability of group poster presentations as an assessment method of a module in an undergraduate nursing degree programme

The introduction of a poster presentation as a formative assessment method over a multiple choice examination after the first phase of a three phase “health and well-being” module in an undergraduate nursing degree programme was greeted with a storm of criticism from fellow lecturers stating that poster presentations are not valid or reliable and totally irrelevant to the assessment of learning in the module. This paper seeks to investigate these criticisms by investigating the literature regarding producing nurses fit for practice, nurse curriculum development and wider nurse education, the purpose of assessment, validity and reliability to critically evaluate the poster presentation as a legitimate assessment method for these aims.

Using hypnosis to facilitate direct observation of multiple tics and self-monitoring in a typically developing teenager

A hypnotic induction technique was used to facilitate direct observation of multiple tics in a typically developing teenager in a home setting. A comprehensive habit reversal program then was implemented, including awareness training, competing response training, relaxation training, self-monitoring, social support and contingency management. Duration of relaxation was then self-monitored using a changing criterion design. The procedure eliminated multiple tics and achieved long-term maintenance of treatment gains. Implications for assessing and treating tics are discussed.

Upregulation of osteopontin and alpha B crystallin in the normal-appearing white matter of multiple sclerosis: an immunohistochemical study utilizing tissue microarrays

Tissue microarrays assembled from control and multiple sclerosis (MS) brain tissue have been used to assess the expression patterns and cellular distribution of two antigens, the proinflammatory cytokine osteopontin and the inducible heat shock protein alpha B -crystallin, which have previously been implicated in MS pathogenesis. Tissue cores were taken from paraffin-embedded donor blocks containing chronic active or chronic inactive plaques and normal-appearing white matter (NAWM) in seven MS cases, and white matter (WM) in five control cases. Expression patterns of both proteins were assessed against myelin density and microglial activation in the different tissue categories. Both proteins showed increased expression in all categories of MS tissue compared with control WM. The results indicate progressive up-regulation of expression of osteopontin with increased plaque activity, while elevation of alpha B-crystallin expression in MS tissue was independent of demyelination. In MS NAWM a significant correlation was observed between high levels of expression of osteopontin and alpha B -crystallin. Osteopontin expression was predominantly confined to astrocytes throughout MS tissues. alpha B -crystallin was expressed on astrocytes, oligodendrocytes and occasionally on demyelinated axons. Taken together, these data indicate a wider distribution of osteopontin and alpha B -crystallin in MS tissues than previously described and support their proposed role in MS pathogenesis.