Environmental and biological characteristics of lagoons on the southwest coast of Ireland

Coastal lagoons are defined as shallow coastal water bodies partially separated from the adjacent sea by a restrictive barrier. Coastal lagoons are protected under Annex I of the European Habitats Directive (92/43/EEC). Lagoons are also considered to be “transitional water bodies” and are therefore included in the “register of protected areas” under the Water Framework Directive (2000/60/EC). Consequently, EU member states are required to establish monitoring plans and to regularly report on lagoon condition and conservation status. Irish lagoons are considered relatively rare and unusual because of their North Atlantic, macrotidal location on high energy coastlines and have received little attention. This work aimed to assess the physicochemical and ecological status of three lagoons, Cuskinny, Farranamanagh and Toormore, on the southwest coast of Ireland. Baseline salinity, nutrient and biological conditions were determined in order to provide reference conditions to detect perturbations, and to inform future maintenance of ecosystem health. Accumulation of organic matter is an increasing pressure in coastal lagoon habitats worldwide, often compounding existing eutrophication problems. This research also aimed to investigate the in situ decomposition process in a lagoon habitat together with exploring the associated invertebrate assemblages. Re-classification of the lagoons, under the guidelines of the Venice system for the classifications of marine waters according to salinity, was completed by taking spatial and temporal changes in salinity regimes into consideration. Based on the results of this study, Cuskinny, Farranamanagh and Toormore lagoons are now classified as mesohaline (5 ppt – 18 ppt), oligohaline (0.5 ppt – 5 ppt) and polyhaline (18 ppt – 30 ppt), respectively. Varying vertical, longitudinal and transverse salinity patterns were observed in the three lagoons. Strong correlations between salinity and cumulative rainfall highlighted the important role of precipitation in controlling the lagoon environment. Maximum effect of precipitation on the salinity of the lagoon was observed between four and fourteen days later depending on catchment area geology, indicating the uniqueness of each lagoon system. Seasonal nutrient patterns were evident in the lagoons. Nutrient concentrations were found to be reflective of the catchment area and the magnitude of the freshwater inflow. Assessment based on the Redfield molar ratio indicated a trend towards phosphorus, rather than nitrogen, limitation in Irish lagoons. Investigation of the decomposition process in Cuskinny Lagoon revealed that greatest biomass loss occurred in the winter season. Lowest biomass loss occurred in spring, possibly due to the high density of invertebrates feeding on the thick microbial layer rather than the decomposing litter. It has been reported that the decomposition of plant biomass is highest in the preferential distribution area of the plant species; however, no similar trend was observed in this study with the most active zones of decomposition varying spatially throughout the seasons. Macroinvertebrate analysis revealed low species diversity but high abundance, indicating the dominance of a small number of species. Invertebrate assemblages within the lagoon varied significantly from communities in the adjacent freshwater or marine environments. Although carried out in coastal lagoons on the southwest coast of Ireland, it is envisaged that the overall findings of this study have relevance throughout the entire island of Ireland and possibly to many North Atlantic coastal lagoon ecosystems elsewhere.

Neonatal EEG classification using atomic decomposition

The electroencephalogram (EEG) is an important noninvasive tool used in the neonatal intensive care unit (NICU) for the neurologic evaluation of the sick newborn infant. It provides an excellent assessment of at-risk newborns and formulates a prognosis for long-term neurologic outcome.The automated analysis of neonatal EEG data in the NICU can provide valuable information to the clinician facilitating medical intervention. The aim of this thesis is to develop a system for automatic classification of neonatal EEG which can be mainly divided into two parts: (1) classification of neonatal EEG seizure from nonseizure, and (2) classifying neonatal background EEG into several grades based on the severity of the injury using atomic decomposition. Atomic decomposition techniques use redundant time-frequency dictionaries for sparse signal representations or approximations. The first novel contribution of this thesis is the development of a novel time-frequency dictionary coherent with the neonatal EEG seizure states. This dictionary was able to track the time-varying nature of the EEG signal. It was shown that by using atomic decomposition and the proposed novel dictionary, the neonatal EEG transition from nonseizure to seizure states could be detected efficiently. The second novel contribution of this thesis is the development of a neonatal seizure detection algorithm using several time-frequency features from the proposed novel dictionary. It was shown that the time-frequency features obtained from the atoms in the novel dictionary improved the seizure detection accuracy when compared to that obtained from the raw EEG signal. With the assistance of a supervised multiclass SVM classifier and several timefrequency features, several methods to automatically grade EEG were explored. In summary, the novel techniques proposed in this thesis contribute to the application of advanced signal processing techniques for automatic assessment of neonatal EEG recordings.

Self-organized vegetation patterning as a fingerprint of climate and human impact on semi-arid ecosystems

Spatially periodic vegetation patterns are well known in arid and semi-arid regions around the world. Mathematical models have been developed that attribute this phenomenon to a symmetry-breaking instability. Such models are based on the interplay between competitive and facilitative influences that the vegetation exerts on its own dynamics when it is constrained by arid conditions, but evidence for these predictions is still lacking. Moreover, not all models can account for the development of regularly spaced spots of bare ground in the absence of a soil prepattern. We applied Fourier analysis to high-resolution, remotely sensed data taken at either end of a 40-year interval in southern Niger. Statistical comparisons based on this textural characterization gave us broad-scale evidence that the decrease in rainfall over recent decades in the sub-Saharan Sahel has been accompanied by a detectable shift from homogeneous vegetation cover to spotted patterns marked by a spatial frequency of about 20 cycles km-1. Wood cutting and grazing by domestic animals have led to a much more marked transition in unprotected areas than in a protected reserve. Field measurements demonstrated that the dominant spatial frequency was endogenous rather than reflecting the spatial variation of any pre-existing heterogeneity in soil properties. All these results support the use of models that can account for periodic vegetation patterns without invoking substrate heterogeneity or anisotropy, and provide new elements for further developments, refinements and tests. This study underlines the potential of studying vegetation pattern properties for monitoring climatic and human impacts on the extensive fragile areas bordering hot deserts. Explicit consideration of vegetation self-patterning may also improve our understanding of vegetation and climate interactions in arid areas. © 2006 The Authors.

Scale-wise evolution of rainfall probability density functions fingerprints the rainfall generation mechanism

© 2010 by the American Geophysical Union.The cross-scale probabilistic structure of rainfall intensity records collected over time scales ranging from hours to decades at sites dominated by both convective and frontal systems is investigated. Across these sites, intermittency build-up from slow to fast time-scales is analyzed in terms of heavy tailed and asymmetric signatures in the scale-wise evolution of rainfall probability density functions (pdfs). The analysis demonstrates that rainfall records dominated by convective storms develop heavier-Tailed power law pdfs toward finer scales when compared with their frontal systems counterpart. Also, a concomitant marked asymmetry build-up emerges at such finer time scales. A scale-dependent probabilistic description of such fat tails and asymmetry appearance is proposed based on a modified q-Gaussian model, able to describe the cross-scale rainfall pdfs in terms of the nonextensivity parameter q, a lacunarity (intermittency) correction and a tail asymmetry coefficient, linked to the rainfall generation mechanism.

Triangular flow in event-by-event ideal hydrodynamics in Au+Au collisions at √SNN = 200A GeV

The first calculation of triangular flow ν3 in Au+Au collisions at √sNN = 200A GeV from an event-by-event (3 + 1) d transport+hydrodynamics hybrid approach is presented. As a response to the initial triangularity Ie{cyrillic, ukrainian}3 of the collision zone, ν3 is computed in a similar way to the standard event-plane analysis for elliptic flow ν2. It is found that the triangular flow exhibits weak centrality dependence and is roughly equal to elliptic flow in most central collisions. We also explore the transverse momentum and rapidity dependence of ν2 and ν3 for charged particles as well as identified particles. We conclude that an event-by-event treatment of the ideal hydrodynamic evolution startingwith realistic initial conditions generates the main features expected for triangular flow. © 2010 The American Physical Society.

Intensification of summer rainfall variability in the southeastern United States during recent decades

The variability of summer precipitation in the southeastern United States is examined in this study using 60-yr (1948-2007) rainfall data. The Southeast summer rainfalls exhibited higher interannual variability with more intense summer droughts and anomalous wetness in the recent 30 years (1978-2007) than in the prior 30 years (1948-77). Such intensification of summer rainfall variability was consistent with a decrease of light (0.1-1 mm day-1) and medium (1-10 mm day-1) rainfall events during extremely dry summers and an increase of heavy (.10 mm day-1) rainfall events in extremely wet summers. Changes in rainfall variability were also accompanied by a southward shift of the region of maximum zonal wind variability at the jet stream level in the latter period. The covariability between the Southeast summer precipitation and sea surface temperatures (SSTs) is also analyzed using the singular value decomposition (SVD) method. It is shown that the increase of Southeast summer precipitation variability is primarily associated with a higher SST variability across the equatorial Atlantic and also SST warming in the Atlantic. © 2010 American Meteorological Society.

Changes to the North Atlantic subtropical high and its role in the intensification of summer rainfall variability in the southeastern United States

This study investigates the changes of the North Atlantic subtropical high (NASH) and its impact on summer precipitation over the southeastern (SE) United States using the 850-hPa geopotential height field in the National Centers forEnvironmental Prediction (NCEP) reanalysis, the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), long-term rainfall data, and Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) model simulations during the past six decades (1948-2007). The results show that the NASH in the last 30 yr has become more intense, and its western ridge has displaced westward with an enhanced meridional movement compared to the previous 30 yr. When the NASH moved closer to the continental United States in the three most recent decades, the effect of the NASH on the interannual variation of SE U.S. precipitation is enhanced through the ridge's north-south movement. The study's attribution analysis suggested that the changes of the NASH are mainly due to anthropogenic warming. In the twenty-first century with an increase of the atmospheric CO2 concentration, the center of the NASH would be intensified and the western ridge of the NASH would shift farther westward. These changes would increase the likelihood of both strong anomalously wet and dry summers over the SEUnited States in the future, as suggested by the IPCC AR4 models. © 2011 American Meteorological Society.

Event memory: A theory of memory for laboratory, autobiographical, and fictional events.

An event memory is a mental construction of a scene recalled as a single occurrence. It therefore requires the hippocampus and ventral visual stream needed for all scene construction. The construction need not come with a sense of reliving or be made by a participant in the event, and it can be a summary of occurrences from more than one encoding. The mental construction, or physical rendering, of any scene must be done from a specific location and time; this introduces a "self" located in space and time, which is a necessary, but need not be a sufficient, condition for a sense of reliving. We base our theory on scene construction rather than reliving because this allows the integration of many literatures and because there is more accumulated knowledge about scene construction's phenomenology, behavior, and neural basis. Event memory differs from episodic memory in that it does not conflate the independent dimensions of whether or not a memory is relived, is about the self, is recalled voluntarily, or is based on a single encoding with whether it is recalled as a single occurrence of a scene. Thus, we argue that event memory provides a clearer contrast to semantic memory, which also can be about the self, be recalled voluntarily, and be from a unique encoding; allows for a more comprehensive dimensional account of the structure of explicit memory; and better accounts for laboratory and real-world behavioral and neural results, including those from neuropsychology and neuroimaging, than does episodic memory.

Component Neural Systems for the Creation of Emotional Memories during Free Viewing of a Complex, Real-World Event.

To investigate the neural systems that contribute to the formation of complex, self-relevant emotional memories, dedicated fans of rival college basketball teams watched a competitive game while undergoing functional magnetic resonance imaging (fMRI). During a subsequent recognition memory task, participants were shown video clips depicting plays of the game, stemming either from previously-viewed game segments (targets) or from non-viewed portions of the same game (foils). After an old-new judgment, participants provided emotional valence and intensity ratings of the clips. A data driven approach was first used to decompose the fMRI signal acquired during free viewing of the game into spatially independent components. Correlations were then calculated between the identified components and post-scanning emotion ratings for successfully encoded targets. Two components were correlated with intensity ratings, including temporal lobe regions implicated in memory and emotional functions, such as the hippocampus and amygdala, as well as a midline fronto-cingulo-parietal network implicated in social cognition and self-relevant processing. These data were supported by a general linear model analysis, which revealed additional valence effects in fronto-striatal-insular regions when plays were divided into positive and negative events according to the fan's perspective. Overall, these findings contribute to our understanding of how emotional factors impact distributed neural systems to successfully encode dynamic, personally-relevant event sequences.

The centrality of event scale: a measure of integrating a trauma into one's identity and its relation to post-traumatic stress disorder symptoms.

We introduce a new scale that measures how central an event is to a person's identity and life story. For the most stressful or traumatic event in a person's life, the full 20-item Centrality of Event Scale (CES) and the short 7-item scale are reliable (alpha's of .94 and .88, respectively) in a sample of 707 undergraduates. The scale correlates .38 with PTSD symptom severity and .23 with depression. The present findings are discussed in relation to previous work on individual differences related to PTSD symptoms. Possible connections between the CES and measures of maladaptive attributions and rumination are considered along with suggestions for future research.

Are the reference values of B cell subpopulations used in adults for classification of common variable immunodeficiencies appropriate for children?

Detailed phenotypic characterization of B cell subpopulations is of utmost importance for the diagnosis and management of humoral immunodeficiencies, as they are used for classification of common variable immunodeficiencies. Since age-specific reference values remain scarce in the literature, we analysed by flow cytometry the proportions and absolute values of total, memory, switched memory and CD21(-/low) B cells in blood samples from 168 healthy children (1 day to 18 years) with special attention to the different subpopulations of CD21(low) B cells. The percentages of total memory B cells and their subsets significantly increased up to 5-10 years. In contrast, the percentages of immature CD21(-) B cells and of immature transitional CD21(low)CD38(hi) B cells decreased progressively with age, whereas the percentage of CD21(low) CD38(low) B cells remained stable during childhood. Our data stress the importance of age-specific reference values for the correct interpretation of B cell subsets in children as a diagnostic tool in immunodeficiencies.

Sheep carcasse classification as a tool to improve the marketing system

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Sheep carcasse classification as a tool to improve the marketing system

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Temporal modelling of short-term rainfall using Cox processes

We study two marked point process models based on the Cox process. These models are used to describe the probabilistic structure of the rainfall intensity process. Mathematical formulation of the models is described and some second-moment characteristics of the rainfall depth, and aggregated processes are considered. The derived second-order properties of the accumulated rainfall amounts at different levels of aggregation are used in order to examine the model fit. A brief data analysis is presented. Copyright © 1998 John Wiley & Sons, Ltd.