Correlation analysis as a tool to investigate the bioaccessibility of nickel, vanadium and zinc in Northern Ireland soils

Correlation analyses were conducted on nickel (Ni), vanadium (V) and zinc (Zn) oral bioaccessible fractions (BAFs) and selected geochemistry parameters to identify specific controls exerted over trace element bioaccessibility. BAFs were determined by previous research using the unified BARGE method. Total trace element concentrations and soil geochemical parameters were analysed as part of the Geological Survey of Northern Ireland Tellus Project. Correlation analysis included Ni, V and Zn BAFs against their total concentrations, pH, estimated soil organic carbon (SOC) and a further eight element oxides. BAF data were divided into three separate generic bedrock classifications of basalt, lithic arenite and mudstone prior to analysis, resulting in an increase in average correlation coefficients between BAFs and geochemical parameters. Sulphur trioxide and SOC, spatially correlated with upland peat soils, exhibited significant positive correlations with all BAFs in gastric and gastro-intestinal digestion phases, with such effects being strongest in the lithic arenite bedrock group. Significant negative relationships with bioaccessible Ni, V and Zn and their associated total concentrations were observed for the basalt group. Major element oxides were associated with reduced oral trace element bioaccessibility, with Al2O3 resulting in the highest number of significant negative correlations followed by Fe2O3. spatial mapping showed that metal oxides were present at reduced levels in peat soils. The findings illustrate how specific geology and soil geochemistry exert controls over trace element bioaccessibility, with soil chemical factors having a stronger influence on BAF results than relative geogenic abundance. In general, higher Ni, V and Zn bioaccessibility is expected in peat soil types.

JISC Workshop Report: E-Research Resources, Tools and Methods for Historic Place Name Analysis

A substantial amount of the 'critical mass' of digital data available to scholarship contains place-names, and it is now recognised that spatial and temporal data points, including place-names, are a vital part of the e-research infrastructure that supports the use, re-use and advanced analysis of data using ICT tools and methods. Place-names can also be linked semantically to contribute to the web of data, and to enrich content through linking existing data, and identifying new collections for digitization to strategically enhance existing digital collections. However, existing e-projects rely on modern gazetteers limiting them to the modern and the near-contemporary. This workshop explored how to further integrate the wealth of historical place-name scholarship, and the resulting digital resources generated within UK academia, so enabling integration of local knowledge over much longer periods.

Three dimensional analysis of the lamina cribrosa in glaucoma

Background/aim: Structural changes in the lamina cribrosa have been implicated in the pathogenesis of glaucomatous optic atrophy. The aim of this study was to determine a measure the surface variability of the cup floor in normal subjects and patients with glaucoma. Methods: A sample of age matched normal subjects (NN), patients with low tension glaucoma (LTG), and primary open angle glaucoma (POAG) were included in the study. The glaucoma groups were matched for the severity of the visual field loss. Mean 10 degree topographic images of normal and glaucomatous eyes from the Heidelberg retina tomograph were imported into ERDAS image processing software where topographic analysis of the cup floor could be assessed. Each image was processed using customised spatial filters that calculated the surface depth variation in localised neighbourhood areas across each image. The local change in depth across the cup floor surface was determined and compared between the three clinical groups. Results: The depth variation in the cup floor was largest in normal subjects followed by LTG and POAG. Highly statistically significant differences in surface depth variability of the cup floor existed between normal and LTG (p=0.005), between normal and POAG (p

Relative role of deterministic and stochastic determinants of soil animal community: a spatially explicit analysis of oribatid mites

1. Ecologists are debating the relative role of deterministic and stochastic determinants of community structure. Although the high diversity and strong spatial structure of soil animal assemblages could provide ecologists with an ideal ecological scenario, surprisingly little information is available on these assemblages.
2. We studied species-rich soil oribatid mite assemblages from a Mediterranean beech forest and a grassland. We applied multivariate regression approaches and analysed spatial autocorrelation at multiple spatial scales using Moran's eigenvectors. Results were used to partition community variance in terms of the amount of variation uniquely accounted for by environmental correlates (e.g. organic matter) and geographical position. Estimated neutral diversity and immigration parameters were also applied to a soil animal group for the first time to simulate patterns of community dissimilarity expected under neutrality, thereby testing neutral predictions.
3. After accounting for spatial autocorrelation, the correlation between community structure and key environmental parameters disappeared: about 40% of community variation consisted of spatial patterns independent of measured environmental variables such as organic matter. Environmentally independent spatial patterns encompassed the entire range of scales accounted for by the sampling design (from tens of cm to 100 m). This spatial variation could be due to either unmeasured but spatially structured variables or stochastic drift mediated by dispersal. Observed levels of community dissimilarity were significantly different from those predicted by neutral models.
4. Oribatid mite assemblages are dominated by processes involving both deterministic and stochastic components and operating at multiple scales. Spatial patterns independent of the measured environmental variables are a prominent feature of the targeted assemblages, but patterns of community dissimilarity do not match neutral predictions. This suggests that either niche-mediated competition or environmental filtering or both are contributing to the core structure of the community. This study indicates new lines of investigation for understanding the mechanisms that determine the signature of the deterministic component of animal community assembly.

An Examination of Transformation Techniques to Investigate and Interpret Multivariate Geochemical Data Analysis: Tellus Case Study

This research aims to use the multivariate geochemical dataset, generated by the Tellus project, to investigate the appropriate use of transformation methods to maintain the integrity of geochemical data and inherent constrained behaviour in multivariate relationships. The widely used normal score transform is compared with the use of a stepwise conditional transform technique. The Tellus Project, managed by GSNI and funded by the Department of Enterprise Trade and Development and the EU’s Building Sustainable Prosperity Fund, involves the most comprehensive geological mapping project ever undertaken in Northern Ireland. Previous study has demonstrated spatial variability in the Tellus data but geostatistical analysis and interpretation of the datasets requires use of an appropriate methodology that reproduces the inherently complex multivariate relations. Previous investigation of the Tellus geochemical data has included use of Gaussian-based techniques. However, earth science variables are rarely Gaussian, hence transformation of data is integral to the approach. The multivariate geochemical dataset generated by the Tellus project provides an opportunity to investigate the appropriate use of transformation methods, as required for Gaussian-based geostatistical analysis. In particular, the stepwise conditional transform is investigated and developed for the geochemical datasets obtained as part of the Tellus project. The transform is applied to four variables in a bivariate nested fashion due to the limited availability of data. Simulation of these transformed variables is then carried out, along with a corresponding back transformation to original units. Results show that the stepwise transform is successful in reproducing both univariate statistics and the complex bivariate relations exhibited by the data. Greater fidelity to multivariate relationships will improve uncertainty models, which are required for consequent geological, environmental and economic inferences.

Application of factor analysis and geostatistics to identify processes controlling the distribution and bioaccessibility of trace elements in Northern Ireland soils

Geologic and environmental factors acting over varying spatial scales can control
trace element distribution and mobility in soils. In turn, the mobility of an element in soil will affect its oral bioaccessibility. Geostatistics, kriging and principal component analysis (PCA) were used to explore factors and spatial ranges of influence over a suite of 8 element oxides, soil organic carbon (SOC), pH, and the trace elements nickel (Ni), vanadium (V) and zinc (Zn). Bioaccessibility testing was carried out previously using the Unified BARGE Method on a sub-set of 91 soil samples from the Northern Ireland Tellus1 soil archive. Initial spatial mapping of total Ni, V and Zn concentrations shows their distributions are correlated spatially with local geologic formations, and prior correlation analyses showed that statistically significant controls were exerted over trace element bioaccessibility by the 8 oxides, SOC and pH. PCA applied to the geochemistry parameters of the bioaccessibility sample set yielded three principal components accounting for 77% of cumulative variance in the data
set. Geostatistical analysis of oxide, trace element, SOC and pH distributions using 6862 sample locations also identified distinct spatial ranges of influence for these variables, concluded to arise from geologic forming processes, weathering processes, and localised soil chemistry factors. Kriging was used to conduct a spatial PCA of Ni, V and Zn distributions which identified two factors comprising the majority of distribution variance. This was spatially accounted for firstly by basalt rock types, with the second component associated with sandstone and limestone in the region. The results suggest trace element bioaccessibility and distribution is controlled by chemical and geologic processes which occur over variable spatial ranges of influence.

Evidence and Spatial Planning for Sustainable Development: A Model for Spatially Allocating Material Flows

The aspiration the spatial planning should act as the main coordinating function for the transition to a sustainable society is grounded on the assumption that it is capable of incorporating both a strong evidence base of environmental accounting for policy, coupled with opportunities for open, deliberative decision-making. While there are a number of increasingly sophisticated methods (such as material flow analysis and ecological footprinting) that can be used to longitudinally determine the impact of policy, there are fewer that can provide a robust spatial assessment of sustainability policy. In this paper, we introduce the Spatial Allocation of Material Flow Analysis (SAMFA) model, which uses the concept of socio-economic metabolism to extrapolate the impact of local consumption patterns that may occur as a result of the local spatial planning process at multiple spatial levels. The initial application the SAMFA model is based on County Kildare in the Republic of Ireland, through spatial temporal simulation and visualisation of construction material flows and associated energy use in the housing sector. Thus, while we focus on an Ireland case study, the model is applicable to spatial planning and sustainability research more generally. Through the development and evaluation of alternative scenarios, the model appears to be successful in its prediction of the cumulative resource and energy impacts arising from consumption and development patterns. This leads to some important insights in relation to the differential spatial distribution of disaggregated allocation of material balance and energy use, for example that rural areas have greater resource accumulation (and are therefore in a sense “less sustainable”) than urban areas, confirming that rural housing in Ireland is both more material and energy intensive. This therefore has the potential to identify hotspots of higher material and energy use, which can be addressed through targeted planning initiatives or focussed community engagement. Furthermore, due to the ability of the model to allow manipulation of different policy criteria (increased density, urban conservation etc), it can also act as an effective basis for multi-stakeholder engagement.

Threshold-based substream selection for closed-loop spatial multiplexing

We propose a low-complexity closed-loop spatial multiplexing method with limited feedback over multi-input-multi-output (MIMO) fading channels. The transmit adaptation is simply performed by selecting transmit antennas (or substreams) by comparing their signal-to-noise ratios to a given threshold with a fixed nonadaptive constellation and fixed transmit power per substream. We analyze the performance of the proposed system by deriving closed-form expressions for spectral efficiency, average transmit power, and bit error rate (BER). Depending on practical system design constraints, the threshold is chosen to maximize the spectral efficiency (or minimize the average BER) subject to average transmit power and average BER (or spectral efficiency) constraints, respectively. We present numerical and Monte Carlo simulation results that validate our analysis. Compared to open-loop spatial multiplexing and other approaches that select the best antenna subset in spatial multiplexing, the numerical results illustrate that the proposed technique obtains significant power gains for the same BER and spectral efficiency. We also provide numerical results that show improvement over rate-adaptive orthogonal space-time block coding, which requires highly complex constellation adaptation. We analyze the impact of feedback delay using analytical and Monte Carlo approaches. The proposed approach is arguably the simplest possible adaptive spatial multiplexing system from an implementation point of view. However, our approach and analysis can be extended to other systems using multiple constellations and power levels.

An analysis of the masking of speech by competing speech using self-report data (L)

Many of the items in the “Speech, Spatial, and Qualities of Hearing” scale questionnaire [S. Gatehouse and W. Noble, Int. J. Audiol.43, 85–99 (2004)] are concerned with speech understanding in a variety of backgrounds, both speech and nonspeech. To study if this self-report data reflected informational masking, previously collected data on 414 people were analyzed. The lowest scores (greatest difficulties) were found for the two items in which there were two speech targets, with successively higher scores for competing speech (six items), energetic masking (one item), and no masking (three items). The results suggest significant masking by competing speech in everyday listening situations.

A long-term analysis of pumped hydro storage to firm wind power

Although pumped hydro storage is seen as a strategic key asset by grid operators, financing it is complicated in new liberalised markets. It could be argued that the optimum generation portfolio is now determined by the economic viability of generators based on a short to medium term return on investment. This has meant that capital intensive projects such as pumped hydro storage are less attractive for wholesale electricity companies because the payback periods are too long. In tandem a significant amount of wind power has entered the generation mix, which has resulted in operating and planning integration issues due to wind's inherent uncertain, varying spatial and temporal nature. These integration issues can be overcome using fast acting gas peaking plant or energy storage. Most analysis of wind power integration using storage to date has used stochastic optimisation for power system balancing or arbitrage modelling to examine techno-economic viability. In this research a deterministic dynamic programming long term generation expansion model is employed to optimise the generation mix, total system costs and total carbon dioxide emissions, and unlike other studies calculates reserve to firm wind power. The key finding of this study is that the incentive to build capital-intensive pumped hydro storage to firm wind power is limited unless exogenous market costs come very strongly into play. Furthermore it was demonstrated that reserve increases with increasing wind power showing the importance of ancillary services in future power systems. © 2014 Elsevier Ltd. All rights reserved.

Kinetostatic-model-based Stiffness Analysis of Exechon PKM

As a comparative newly-invented PKM with over-constraints in kinematic chains, the Exechon has attracted extensive attention from the research society. Different from the well-recognized kinematics analysis, the research on the stiffness characteristics of the Exechon still remains as a challenge due to the structural complexity. In order to achieve a thorough understanding of the stiffness characteristics of the Exechon PKM, this paper proposed an analytical kinetostatic model by using the substructure synthesis technique. The whole PKM system is decomposed into a moving platform subsystem, three limb subsystems and a fixed base subsystem, which are connected to each other sequentially through corresponding joints. Each limb body is modeled as a spatial beam with a uniform cross-section constrained by two sets of lumped springs. The equilibrium equation of each individual limb assemblage is derived through finite element formulation and combined with that of the moving platform derived with Newtonian method to construct the governing kinetostatic equations of the system after introducing the deformation compatibility conditions between the moving platform and the limbs. By extracting the 6 x 6 block matrix from the inversion of the governing compliance matrix, the stiffness of the moving platform is formulated. The computation for the stiffness of the Exechon PKM at a typical configuration as well as throughout the workspace is carried out in a quick manner with a piece-by-piece partition algorithm. The numerical simulations reveal a strong position-dependency of the PKM's stiffness in that it is symmetric relative to a work plane due to structural features. At the last stage, the effects of some design variables such as structural, dimensional and stiffness parameters on system rigidity are investigated with the purpose of providing useful information for the structural optimization and performance enhancement of the Exechon PKM. It is worthy mentioning that the proposed methodology of stiffness modeling in this paper can also be applied to other overconstrained PKMs and can evaluate the global rigidity over workplace efficiently with minor revisions.

Evaluation of an in situ spatial resolution instrument for fixed beds through the assessment of the invasiveness of probes and a comparison with a micro-kinetic model

This paper reports the detailed description and validation of a fully automated, computer controlled analytical method to spatially probe the gas composition and thermal characteristics in packed bed systems. This method has been designed to limit the invasiveness of the probe, a characteristic assessed using CFD. The thermocouple is aligned with the sampling holes to enable simultaneous recording of the gas composition and temperature profiles. This analysis technique has been validated by studying CO oxidation over a 1% Pt/Al2O3 catalyst. The resultant profiles have been compared with a micro-kinetic model, to further assess the strength of the technique. 

Optimal wafer site selection using forward selection component analysis

Reducing wafer metrology continues to be a major target in semiconductor manufacturing efficiency initiatives due to it being a high cost, non-value added operation that impacts on cycle-time and throughput. However, metrology cannot be eliminated completely given the important role it plays in process monitoring and advanced process control. To achieve the required manufacturing precision, measurements are typically taken at multiple sites across a wafer. The selection of these sites is usually based on a priori knowledge of wafer failure patterns and spatial variability with additional sites added over time in response to process issues. As a result, it is often the case that in mature processes significant redundancy can exist in wafer measurement plans. This paper proposes a novel methodology based on Forward Selection Component Analysis (FSCA) for analyzing historical metrology data in order to determine the minimum set of wafer sites needed for process monitoring. The paper also introduces a virtual metrology (VM) based approach for reconstructing the complete wafer profile from the optimal sites identified by FSCA. The proposed methodology is tested and validated on a wafer manufacturing metrology dataset. © 2012 IEEE.

Consideration of coastal risk in the Irish spatial planning process

The vulnerability of coastal areas to associated hazards is increasing due to population growth, development pressure and climate change. It is incumbent on coastal governance regimes to address the vulnerability of coastal inhabitants to these hazards. This is especially so at the local level where development planning and control has a direct impact on the vulnerability of coastal communities. To reduce the vulnerability of coastal populations, risk mitigation and adaptation strategies need to be built into local spatial planning processes. Local government, however, operates within a complex hierarchal governance framework which may promote or limit particular actions. It is important, therefore, to understand how local coastal planning practices are shaped by national and supranational entities. Local governments also have to respond to the demands of local populations. Consequently, it is important to understand local populations’ perceptions of coastal risk and its management. Adopting an in-depth study of coastal planning in County Mayo, Ireland, this paper evaluates: (a) how European and national policies and legislation shape coastal risk management at local level; (b) the incorporation of risk management strategies into local plans; and (c) local perception of coastal risks and risk management. Despite a strong steer from supranational and national legislation and policy, statutory local plans are found to be lacking in appropriate risk mitigation or adaptation strategies. Local residents appear to be lulled into a sense of complacency towards these risks because of the low level of attention afforded to them by the local planning authorities. To avoid potentially disastrous consequences for local residents and businesses, it is imperative that this situation is redressed urgently. Based on our analysis, we recommend: the development and implementation of a national ICZM strategy, supported by detailed local ICZM plans; and obliging local government to address known risks in their plans rather than defer them to project level decision making.

Pattern Recognition Approach for Road Collision Hotspots Analysis: Case Study of Northern Ireland

In order to address road safety effectively, it is essential to understand all the factors, which
attribute to the occurrence of a road collision. This is achieved through road safety
assessment measures, which are primarily based on historical crash data. Recent advances
in uncertain reasoning technology have led to the development of robust machine learning
techniques, which are suitable for investigating road traffic collision data. These techniques
include supervised learning (e.g. SVM) and unsupervised learning (e.g. Cluster Analysis).
This study extends upon previous research work, carried out in Coll et al. [3], which
proposed a non-linear aggregation framework for identifying temporal and spatial hotspots.
The results from Coll et al. [3] identified Lisburn area as the hotspot, in terms of road safety,
in Northern Ireland. This study aims to use Cluster Analysis, to investigate and highlight any
hidden patterns associated with collisions that occurred in Lisburn area, which in turn, will
provide more clarity in the causation factors so that appropriate countermeasures can be put
in place.