An Integrated Approach to Quantifying Groundwater and Surface Water Contributions of Stream Flow

The management of water resources in Ireland prior to the Water Framework Directive (WFD) has focussed on surface water and groundwater as separate entities. A critical element to the successful implementation of the
WFD is to improve our understanding of the interaction between the two and flow mechanisms by which groundwaters discharge to surface waters. An improved understanding of the contribution of groundwater to surface water is required for the classification of groundwater body status and the determination of groundwater quality thresholds. The results of the study will also have a wider application to many areas of the WFD.
A subcommittee of the WFD Groundwater Working Group (GWWG) has been formed to develop a methodology to estimate the groundwater contribution to Irish Rivers. The group has selected a number of analytical techniques to quantify components of stream flow in an Irish context (Master Recession Curve, Unit Hydrograph, Flood Studies Report methodologies and
hydrogeological analytical modelling). The components of stream flow that can be identified include deep groundwater, intermediate and overland. These analyses have been tested on seven pilot catchments that have a variety of hydrogeological settings and have been used to inform and constrain a mathematical model. The mathematical model used was the NAM (NedbØr-AfstrØmnings-Model) rainfall-runoff model which is a module of DHIs MIKE 11 modelling suite. The results from these pilot catchments have been used to develop a decision model based on catchment descriptors from GIS datasets for the selection of NAM parameters. The datasets used include the mapping of aquifers, vulnerability and subsoils, soils, the Digital Terrain Model, CORINE and lakes. The national coverage of the GIS datasets has allowed the extrapolation of the mathematical model to regional catchments across Ireland.

A simple inhibition coefficient for quantifying potency of biocontrol agents against plant-pathogenic fungi

Microbial interactions depend on a range of biotic and environmental variables, and are both dynamic and unpredictable. For some purposes, and under defined conditions, it is nevertheless imperative to evaluate the inhibitory efficacy of microbes, such as those with potential as biocontrol agents. We selected six, phylogenetically diverse microbes to determine their ability to inhibit the ascomycete Fusarium
coeruleum, a soil-dwelling pathogen of potato tubers that causes the storage disease dry rot. Interaction assays, where colony development was quantified (for both fungal pathogen and potential control agents), were therefore carried out on solid media. The key parameters that contributed to, and were indicative of, inhibitory efficacy were identified as: fungal growth-rates (i) prior to contact with the biocontrol
agent and (ii) if/once contact with the biocontrol agent was established (i.e. in the zone of mixed
culture), and (iii) the ultimate distance traveled by the fungal mycelium. It was clear that there was no correlation between zones of fungal inhibition and the overall reduction in the extent of fungal colony development. An inhibition coefficient was devised which incorporated the potential contributions of distal inhibition of fungal growth-rate; prevention of mycelium development in the vicinity of the biocontrol
agent; and ability to inhibit plant-pathogen growth-rate in the zone of mixed culture (in a ratio of 2:2:1). The values derived were 84.2 for Bacillus subtilis (QST 713), 74.0 for Bacillus sp. (JC12GB42), 30.7 for Pichia anomala (J121), 19.3 for Pantoea agglomerans (JC12GB34), 13.9 for Pantoea sp. (S09:T:12), and
21.9 (indicating a promotion of fungal growth) for bacterial strain (JC12GB54). This inhibition coefficient, with a theoretical maximum of 100, was consistent with the extent of F. coeruleum-colony development (i.e. area, in cm2) and assays of these biocontrol agents carried out previously against Fusarium
spp., and other fungi. These findings are discussed in relation to the dynamics and inherent complexity of natural ecosystems, and the need to adapt models for use under specific sets of conditions.

Magnetic mirror cavities as terahertz radiation sources and a means of quantifying radiation friction

We propose a radiation source based on a magnetic mirror cavity. Relativistic electrons are simulated entering the cavity and their trajectories and resulting emission spectra are calculated. The uniformity of the particle orbits is found to result in a frequency comb in terahertz range, the precise energies of which are tunable by varying the electron's gamma-factor. For very high energy particles, radiation friction causes the spectral harmonics to broaden and we suggest this as a possible way to verify competing classical equations of motion.

Quantifying heritable variation in fitness-related traits of wild, farmed and hybrid Atlantic salmon families in a wild river environment

Farmed fish are typically genetically different from wild conspecifics. Escapees from fish farms may contribute one-way gene flow from farm to wild gene pools, which can depress population productivity, dilute local adaptations and disrupt coadapted gene complexes. Here, we reanalyse data from two experiments (McGinnity et al., 1997, 2003) where performance of Atlantic salmon (Salmo salar) progeny originating from experimental crosses between farm and wild parents (in three different cohorts) were measured in a natural stream under common garden conditions. Previous published analyses focussed on group-level differences but did not account for pedigree structure, as we do here using modern mixed-effect models. Offspring with one or two farm parents exhibited poorer survival in their first and second year of life compared with those with two wild parents and these group-level inferences were robust to excluding outlier families. Variation in performance among farm, hybrid and wild families was generally similar in magnitude. Farm offspring were generally larger at all life stages examined than wild offspring, but the differences were moderate (5–20%) and similar in magnitude in the wild versus hatchery environments. Quantitative genetic analyses conducted using a Bayesian framework revealed moderate heritability in juvenile fork length and mass and positive genetic correlations (>0.85) between these morphological traits. Our study confirms (using more rigorous statistical techniques) previous studies showing that offspring of wild fish invariably have higher fitness and contributes fresh insights into family-level variation in performance of farm, wild and hybrid Atlantic salmon families in the wild. It also adds to a small, but growing, number of studies that estimate key evolutionary parameters in wild salmonid populations. Such information is vital in modelling the impacts of introgression by escaped farm salmon.

A novel method of quantifying root exudation in the presence of soil microflora

A microcosm is described in which root exudation may be estimated in the presence of microorganisms. Ryegrass seedlings are grown in microcosms in which roots were spatially separated from a microbial inoculant by a Millipore membrane. Seedlings grown in the microcosms were labelled with [¹⁴C]-CO₂, and the fate of the label within the plant and rhizosphere was determined. Inoculation of the microcosms with Cladosporium resinae increased net fixation of the [¹⁴C] label compared to plants grown under sterile conditions. Inoculation also increased root exudation. The use of the microcosm was illustrated and its applications discussed. © 1991 Kluwer Academic Publishers.

Quantifying consumer portion control practices. A cross-sectional study

The use of portion control practices has rarely been quantified. The present study aimed to: (1) explore which portion control practices are actually used by the general population and their association with cognitive restraint, demographic background and general health interest (GHI), and (2) examine how the usage of portion control practices predicts the estimated consumption of an energy dense food (i.e. pizza). Twenty-two portion control practices were rated in terms of their frequency of use from 'never' to 'very often' by a representative sample of 1012 consumers from the island of Ireland. Three factors were extracted and named: measurement-strategy scale, eating-strategy scale, and purchasing-strategy scale. The eating-strategy scale score was the highest, while the measurement-strategy scale carried the lowest frequency score. For each strategy scale score, the strongest predictor was GHI, followed by gender. Having higher GHI and being female were independently associated with more frequent portion control. Both the eating-strategy scale score and the purchasing-strategy scale score were negatively associated with pizza portion size consumption estimates. In conclusion, while this study demonstrates that the reported use of portion control practices is low, the findings provide preliminary evidence for their validity. Further studies are needed to explore how portion control practices are used in different kinds of portion size decisions and what their contribution is to the intake of food over an extended period of time.

Squirrelpox virus in Northern Ireland: quantifying the risk to red squirrels.

Information and collated statistical analysis on the decline of red squirrels.

Quantifying Aflatoxin B1 in peanut oil using fabricating fluorescence probes based on upconversion nanoparticles

Rare earth doped upconversion nanoparticles convert near-infrared excitation light into visible emission light. Compared to organic fluorophores and semiconducting nanoparticles, upconversion nanoparticles (UCNPs) offer high photochemical stability, sharp emission bandwidths, and large anti-Stokes shifts. Along with the significant light penetration depth and the absence of autofluorescence in biological samples under infrared excitation, these UCNPs have attracted more and more attention on toxin detection and biological labelling. Herein, the fluorescence probe based on UCNPs was developed for quantifying Aflatoxin B₁ (AFB₁) in peanut oil. Based on a specific immunity format, the detection limit for AFB₁ under optimal conditions was obtained as low as 0.2 ng·ml^{- 1}, and in the effective detection range 0.2 to 100 ng·ml^{- 1}, good relationship between fluorescence intensity and AFB₁ concentration was achieved under the linear ratios up to 0.90. Moreover, to check the feasibility of these probes on AFB₁ measurements in peanut oil, recovery tests have been carried out. A good accuracy rating (93.8%) was obtained in this study. Results showed that the nanoparticles can be successfully applied for sensing AFB₁ in peanut oil.

Expanding Agri-Food Production and Employment in the Presence of Climate Policy Constraints: Quantifying the Trade-Off in Ireland

This chapter explores the trade-off between competing objectives of employment creation and climate policy commitments in Irish agriculture. A social accounting matrix (SAM) multiplier model is linked with a partial equilibrium agricultural sector model to simulate the impact of a number of GHG emission reduction scenarios, assuming these are achieved through a constraint on beef production. Limiting the size of the beef sector helps to reduce GHG emissions with a very limited impact on the value of agricultural income at the farm level. However, the SAM multiplier analysis shows that there would be significant employment losses in the wider economy. From a policy perspective, a pragmatic approach to GHG emissions reductions in the agriculture sector, which balances opportunities for economic growth in the sector with opportunities to reduce associated GHG emissions, may be required.

Women of an uncertain age: quantifying human capital accumulation in rural Ireland in the nineteenth century

Geary and Stark find that Ireland’s post-Famine per capita GDP converged with British levels, and that this convergence was largely due to total factor productivity growth rather than mass emigration. In this article, new long-run measurements of human capital accumulation in Ireland are devised in order to facilitate a better assessment of sources of this productivity growth, including the relative contribution of men and women. This is done by exploiting the frequency at which age data heap at round ages, widely interpreted as an indicator of a population’s basic numeracy skills. Because Földvári, van Leeuwen, and van Leeuwen-Li find that gender-specific trends in this measure derived from census returns are biased by who is reporting and recording the age information, any computed numeracy trends are corrected using data from prison and workhouse registers, sources in which women ostensibly self-reported their age. The findings show that rural Irish women born early in the nineteenth century had substantially lower levels of human capital than uncorrected census data would otherwise suggest. These results are large in magnitude and thus economically significant. The speed at which women converged is consistent with Geary and Stark’s interpretation of Irish economic history; Ireland probably graduated to Europe’s club of advanced economies thanks in part to rapid advances in female human capital.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

Geometry- and diffraction-independent ionization probabilities in intense laser fields: Probing atomic ionization mechanisms with effective intensity matching

We report an experimental technique for the comparison of ionization processes in ultrafast laser pulses irrespective of pulse ellipticity. Multiple ionization of xenon by 50 fs 790 nm, linearly and circularly polarized laser pulses is observed over the intensity range 10 TW/cm(2) to 10 PW/cm(2) using effective intensity matching (EIM), which is coupled with intensity selective scanning (ISS) to recover the geometry-independent probability of ionization. Such measurements, made possible by quantifying diffraction effects in the laser focus, are compared directly to theoretical predictions of multiphoton, tunnel and field ionization, and a remarkable agreement demonstrated. EIM-ISS allows the straightforward quantification of the probability of recollision ionization in a linearly polarized laser pulse. Furthermore, the probability of ionization is discussed in terms of the Keldysh adiabaticity parameter gamma, and the influence of the precursor ionic states present in recollision ionization is observed.