Impacts of sewage outfalls on rocky shores: incorporating scale, biotic assemblage structure and variability into monitoring tools.

Coastal systems, such as rocky shores, are among the most heavily anthropogenically-impacted marine ecosystems and are also among the most productive in terms of ecosystem functioning. One of the greatest impacts on coastal ecosystems is nutrient enrichment from human activities such as agricultural run-off and discharge of sewage. The aim of this study was to identify and characterise potential effects of sewage discharges on the biotic diversity of rocky shores and to test current tools for assessing the ecological status of rocky shores in line with the EU Water Framework Directive (WFD). A sampling strategy was designed to test for effects of sewage outfalls on rocky shore assemblages on the east coast of Ireland and to identify the scale of the putative impact. In addition, a separate sampling programme based on the Reduced algal Species List (RSL), the current WFD monitoring tool for rocky shores in Ireland and the UK, was also completed by identifying algae and measuring percent cover in replicate samples on rocky shores during Summer. There was no detectable effect of sewage outfalls on benthic taxon diversity or assemblage structure. However, spatial variability of assemblages was greater at sites proximal or adjacent to sewage outfalls compared to shores without sewage outfalls present. Results based on the RSL, show that algal assemblages were not affected by the presence of sewage outfalls, except when classed into functional groups when variability was greater at the sites with sewage outfalls. A key finding of both surveys, was the prevalence of spatial and temporal variation of assemblages. It is recommended that future metrics of ecological status are based on quantified sampling designs, incorporate changes in variability of assemblages (indicative of community stability), consider shifts in assemblage structure and include both benthic fauna and flora to assess the status of rocky shores.

A critical appraisal of tools available for monitoring epigenetic changes in clinical samples from patients with myeloid malignancies

Research over the past decade has confirmed that epigenetic alterations act in concert with genetic lesions to deregulate gene expression in acute myeloid leukemia and myelodysplastic syndromes. In addition, we now have the capability to pharmaceutically target epigenetic modifications, and there is an urgent need forearly validation of the efficacy of the drugs. Also, an improved understanding of the functionality of epigenetic modifications may further pave the road towards an individualized therapy. Here, we provide the pros and cons of the currently most feasible methods used for characterizing the methylome in clinical samples, and give a brief introduction to novel approaches to sequencing that may revolutionize our abilities to characterize the genomes and epigenomes in acute myeloid leukemia and myelodysplastic syndrome patients.

Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

A comparison of nitogen fate and transport in catchments underlain by high and low permeability aquifers using chemical and isotopic tools.

Variability in nitrogen fate and transport in different catchments types is often not considered. This research considers the importance of such nitrogen processes within groundwater pathways in two agricultural catchments in Ireland; a well drained catchment, underlain by karstified Carboniferous limestone, and a poorly drained catchment, underlain by Silurian greywacke.
Depth specific low-flow groundwater sampling was used to evaluate the hydrochemical stratification in groundwater. Groundwater samples, as well as surface water samples, along river courses were analysed for nitrogen species (NO3, NH4 and NO2) and nitrate isotopes (d15N and d18O) as well as field parameters and major ions
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The dominant nitrate (NO3) groundwater pathway in the poorly drained greywacke catchment is through the shallow weathered bedrock, as indicated by transmissivity values and the ionic and isotopic signatures, and a clear reduction in NO3 concentration is observed with depth. A similar chloride trend would suggest dilution is a major factor, however d15N and d18O isotopic values producing an enrichment ratio of 1.8 indicate that denitrification is also an important process involved in the fate of the NO3 within the groundwater flow system. This consistent trend with depth is in contrast to the stratification pattern observed in the karstified catchment. NO3 was not detected in the shallow groundwater pathway; the dominant groundwater pathway is in the deeper groundwater where there is little change in the nitrate isotope values with depth (d15N values range between 4.1 and 4.6 ‰). This deeper groundwater contributes the dominant proportion of the river flow through a number of springs. As a result, the deeper groundwater, springs and river have a similar ionic signature and NO3 concentration range (23 ± 3 mg/l). Despite this pattern, the NO3 isotopes show a distinct difference in isotopic values between the deeper groundwater in the diffuse karst and the springs indicating some denitrification is occurring during groundwater discharge into the river. Furthermore the isotopes give an indication of the variability of the spatial extent of the springs and the complexities of the fissures through which they are fed. The results of this study clearly show the importance of the geology in the fate and transport of NO3 in agricultural catchments.

Managing i-branding to create brand equity

Purpose: Given the emergent nature of i-branding as an academic field of study and a lack of applied research output, the aim of this paper is to explain how businesses manage i-branding to create brand equity.

Design/methodology/approach: Within a case-study approach, seven cases were developed from an initial sample of 20 food businesses. Additionally, utilising secondary data, the analysis of findings introduces relevant case examples from other industrial sectors.

Findings: Specific internet tools and their application are discussed within opportunities to create brand equity for products classified by experience, credence and search characteristics. An understanding of target customers will be critical in underpinning the selection and deployment of relevant i-branding tools. Tools facilitating interactivity – machine and personal – are particularly significant.

Research limitations/implications: Future research positioned within classification of goods constructs could provide further contributions that recognise potential moderating effects of product/service characteristics on the development of brand equity online. Future studies could also employ the i-branding conceptual framework to test its validity and develop it further as a means of explaining how i-branding can be managed to create brand equity.

Originality/value: While previous research has focused on specific aspects of i-branding, this paper utilises a conceptual framework to explain how diverse i-branding tools combine to create brand equity. The literature review integrates fragmented literature around a conceptual framework to produce a more coherent understanding of extant thinking. The location of this study within a classification of goods context proved critical to explaining how i-branding can be managed.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

Kinematic Analysis and Dimensional Synthesis of Exechon Parallel Kinematic Machine for Large Volume Machining

A parallel kinematic machine (PKM) topology can only give its best performance when its geometrical parameters are optimized. In this paper, dimensional synthesis of a newly developed PKM is presented for the first time. An optimization method is developed with the objective to maximize both workspace volume and global dexterity of the PKM. Results show that the method can effectively identify design parameter changes under different weighted objectives. The PKM with optimized dimensions has a large workspace to footprint ratio and a large well-conditioned workspace, hence justifies its suitability for large volume machining.

Assessing health service needs:tools for health planning.

As fiscal pressures mount, health-planning and decision-making at smaller geographics scales must be more effective. Involving local constituents in needs assessments, it is believed, would lead to better identification and serving of regional demands and needs for health services. This article examines needs assessment as a tool to determine a community's service needs and establish priorities for the creation of programs. Various approaches used in needs assessments are described, including survey methods, structured groups and geographic information systems.