Approximation-based feature selection and application for algae population estimation

Q. Shen and R. Jensen, 'Approximation-based feature selection and application for algae population estimation,' Applied Intelligence, vol. 28, no. 2, pp. 167-181, 2008. Sponsorship: EPSRC RONO: EP/E058388/1

An econometric analysis of international air travel demand in Saudi Arabia

Abed, S. Y., Ba-Fail, A. O., & Jasimuddin, S. (2001). An econometric analysis of international air travel demand in Saudi Arabia. Journal of Air Transport Management, 7(3), 143-148 RAE2008

A model for the simulation of macroalgal population dynamics and productivity

A mathematical model to simulate the population dynamics and productivity of macroalgae is described. The model calculates the biomass variation of a population divided into size-classes. Biomass variation in each class is estimated from the mass balance of carbon fixation, carbon release and demographic processes such as mortality and frond breakage. The transitions between the different classes are calculated in biomass and density units as a function of algal growth. Growth is computed from biomass variations using an allometric relationship between weight and length. Gross and net primary productivity is calculated from biomass production and losses over the period of simulation. The model allows the simulation of different harvesting strategies of commercially important species. The cutting size and harvesting period may be changed in order to optimise the calculated yields. The model was used with the agarophyte Gelidium sesquipedale (Clem.) Born. et Thur. This species was chosen because of its economic importance as a the main raw material for the agar industry. Net primary productivity calculated with it and from biomass variations over a yearly period, gave similar results. The results obtained suggest that biomass dynamics and productivity are more sensitive to the light extinction coefficient than to the initial biomass conditions for the model. Model results also suggest that biomass losses due to respiration and exudation are comparable to those resulting from mortality and frond breakage. During winter, a significant part of the simulated population has a negative net productivity. The importance of considering different parameters in the productivity light relationships in order to account for their seasonal variability is demonstrated with the model results. The model was implemented following an object oriented programming approach. The programming methodology allows a fast adaptation of the model to other species without major software development.

Retrieval by Shape Population: An Index Tree Approach

Based on our previous work in deformable shape model-based object detection, a new method is proposed that uses index trees for organizing shape features to support content-based retrieval applications. In the proposed strategy, different shape feature sets can be used in index trees constructed for object detection and shape similarity comparison respectively. There is a direct correspondence between the two shape feature sets. As a result, application-specific features can be obtained efficiently for shape-based retrieval after object detection. A novel approach is proposed that allows retrieval of images based on the population distribution of deformed shapes in each image. Experiments testing these new approaches have been conducted using an image database that contains blood cell micrographs. The precision vs. recall performance measure shows that our method is superior to previous methods.

Space, Time and Learning in the Hippocampus: How Fine Spatial and Temporal Scales Are Expanded into Population Codes for Behavioral Control

The hippocampus participates in multiple functions, including spatial navigation, adaptive timing, and declarative (notably, episodic) memory. How does it carry out these particular functions? The present article proposes that hippocampal spatial and temporal processing are carried out by parallel circuits within entorhinal cortex, dentate gyrus, and CA3 that are variations of the same circuit design. In particular, interactions between these brain regions transform fine spatial and temporal scales into population codes that are capable of representing the much larger spatial and temporal scales that are needed to control adaptive behaviors. Previous models of adaptively timed learning propose how a spectrum of cells tuned to brief but different delays are combined and modulated by learning to create a population code for controlling goal-oriented behaviors that span hundreds of milliseconds or even seconds. Here it is proposed how projections from entorhinal grid cells can undergo a similar learning process to create hippocampal place cells that can cover a space of many meters that are needed to control navigational behaviors. The suggested homology between spatial and temporal processing may clarify how spatial and temporal information may be integrated into an episodic memory.

Established cardiovascular disease and CVD risk factors in a primary care population of middle-aged Irish men and women

Contemporary Irish data on the prevalence of major cardiovascular disease (CVD) risk factors are sparse. The primary aims of this study were (1) to estimate the prevalence of major cardiovascular disease risk factors, including Type 2 Diabetes Mellitus, in the general population of men and women between the ages of 50 and 69 years; and (2) to estimate the proportion of individuals in this age group at high absolute risk of cardiovascular disease events on the basis of pre-existing cardiovascular disease or as defined by the Framingham equation. Participants were drawn from the practice lists of 17 general practices in Cork and Kerry using stratified random sampling. A total of 1018 people attended for screening (490 men, 48%) from 1473 who were invited, a response rate of 69.1%. Cardiovascular disease risk factors and glucose intolerance are common in the population of men and women aged between 50 and 69 years. Almost half the participants were overweight and a further quarter met current international criteria for obesity, one of the highest recorded prevalence rates for obesity in a European population sample. Forty per cent of the population reported minimal levels of physical activity and 19% were current cigarette smokers. Approximately half the sample had blood pressure readings consistent with international criteria for the diagnosis of hypertension, but only 38% of these individuals were known to be hypertensive. Eighty per cent of the population sample had a cholesterol concentration in excess of 5 mmol/l. Almost 4% of the population had Type 2 Diabetes Mellitus, of whom 30% were previously undiagnosed. A total of 137 participants (13.5%) had a history or ECG findings consistent with established cardiovascular disease. Of the remaining 881 individuals in the primary prevention population, a total of 20 high-risk individuals (19 male) had a risk of a coronary heart disease event 30% over ten years according to the Framingham risk equation, giving an overall population prevalence of 2.0% (95% CI 1.3 - 3.0). At a risk level 20% over ten years, an additional 91 individuals (8.9%) were identified. Thus a total of 24.4% of the population were at risk either through pre-existing CVD (13.5%) or an estimated 10-year risk exceeding 20% according to the Framingham risk equation (10.9%). Thus a substantial proportion of middle-aged men are at high risk of CVD. The findings emphasise the scale of the CVD epidemic in Ireland and the need for ongoing monitoring of risk factors at the population level and the need to develop preventive strategies at both the clinical and societal level.

Uncertainty in wind energy forecasting

Wind energy is the energy source that contributes most to the renewable energy mix of European countries. While there are good wind resources throughout Europe, the intermittency of the wind represents a major problem for the deployment of wind energy into the electricity networks. To ensure grid security a Transmission System Operator needs today for each kilowatt of wind energy either an equal amount of spinning reserve or a forecasting system that can predict the amount of energy that will be produced from wind over a period of 1 to 48 hours. In the range from 5m/s to 15m/s a wind turbine’s production increases with a power of three. For this reason, a Transmission System Operator requires an accuracy for wind speed forecasts of 1m/s in this wind speed range. Forecasting wind energy with a numerical weather prediction model in this context builds the background of this work. The author’s goal was to present a pragmatic solution to this specific problem in the ”real world”. This work therefore has to be seen in a technical context and hence does not provide nor intends to provide a general overview of the benefits and drawbacks of wind energy as a renewable energy source. In the first part of this work the accuracy requirements of the energy sector for wind speed predictions from numerical weather prediction models are described and analysed. A unique set of numerical experiments has been carried out in collaboration with the Danish Meteorological Institute to investigate the forecast quality of an operational numerical weather prediction model for this purpose. The results of this investigation revealed that the accuracy requirements for wind speed and wind power forecasts from today’s numerical weather prediction models can only be met at certain times. This means that the uncertainty of the forecast quality becomes a parameter that is as important as the wind speed and wind power itself. To quantify the uncertainty of a forecast valid for tomorrow requires an ensemble of forecasts. In the second part of this work such an ensemble of forecasts was designed and verified for its ability to quantify the forecast error. This was accomplished by correlating the measured error and the forecasted uncertainty on area integrated wind speed and wind power in Denmark and Ireland. A correlation of 93% was achieved in these areas. This method cannot solve the accuracy requirements of the energy sector. By knowing the uncertainty of the forecasts, the focus can however be put on the accuracy requirements at times when it is possible to accurately predict the weather. Thus, this result presents a major step forward in making wind energy a compatible energy source in the future.

Studies relating to the population dynamics of the European badger (Meles meles) in Ireland

European badgers (Meles meles) are an important part of the Irish ecosystem; they are a component of Ireland’s native fauna and are afforded protection by national and international laws. The species is also a reservoir host for bovine tuberculosis (bTB) and implicated in the epidemiology of bTB in cattle. Due to this latter point, badgers have been culled in the Republic of Ireland (ROI) in areas where persistent cattle bTB outbreaks exist. The population dynamics of badgers are therefore of great pure and applied interest. The studies within this thesis used large datasets and a number of analytical approaches to uncover essential elements of badger populations in the ROI. Furthermore, a review and meta-analysis of all available data on Irish badgers was completed to give a framework from which key knowledge gaps and future directions could be identified (Chapter 1). One main finding suggested that badger densities are significantly reduced in areas of repeated culling, as revealed through declining trends in signs of activity (Chapter 2) and capture numbers (Chapter 2 and Chapter 3). Despite this, the trappability of badgers was shown to be lower than previously thought. This indicates that management programmes would require repeated long-term efforts to be effective (Chapter 4). Mark-recapture modelling of a population (sample area: 755km2) suggested that mean badger density was typical of continental European populations, but substantially lower than British populations (Chapter 4). Badger movement patterns indicated that most of the population exhibited site fidelity. Long-distance movements were also recorded, the longest of which (20.1km) was the greatest displacement of an Irish badger currently known (Chapter 5). The studies presented in this thesis allows for the development of more robust models of the badger population at national scales (see Future Directions). Through the use of large-scale datasets future models will facilitate informed sustainable planning for disease control.

Investigation of the genetic susceptibility to osteoporosis in the Irish population

Osteoporosis is a complex skeletal disorder characterized by compromised bone strength. Variation in bone mineral density (BMD) is a contributing factor. The aim of this research as to select informative single nucleotide polymorphisms (SNPs) in potential candidate genes from loci suggestively linked to BMD variation for fine mapping. The gene regulated by oestrogen in breast cancer 1 (GREB1), located at 2p25.1, was selected. GREB1 transcription is initiated early in the oestrogen receptor alpha regulated pathway. There was significant association between GREB1_03 and BMD variation at the lumbar spine and femoral neck (FN) in the discovery cohort. Significant association was observed between GREB1_04 and FN BMD in the replication cohort. The development and differentiation enhancing factor 2, the integrin cytoplasmic domain associated protein 1 and A-disintegrin and metalloprotease 17 were selected due to their respective roles in cell mobility and adhesion. There was no linkage or association observed between the Chr2 cluster SNPs and BMD. Two factors in bone remodelling are the attraction of bone cell precursors and endocrine regulation of the process, primarily through the action of parathyroid hormone (PTH). The C-C chemokine receptor type 3 (CCR3) encodes a CC chemokine receptor expressed in osteoclast precursors. The PTH receptor type 1 (PTHR1) encodes a G-protein coupled receptor for PTH. Association was observed between CCR3 haplotypes and BMD variation at the FN. There was no linkage or association observed between PTHR1 SNPs and BMD variation. Population genetic studies with complex phenotypes endeavour to elucidate the traits genetic architecture. This study presents evidence of association between GREB1 and BMD variation and as such, introduces GREB1 as a novel gene target for osteoporosis genetics studies. It affirms that common genomic variants in PTHR1 are not associated with BMD variation in Caucasians and supports the evidence that CCR3 may be contributing to BMD variation

Assessment of dietary background exposure of the Irish adult population to dioxins and PCBs particularly taking into account additional exposure due to the 2008 Irish dioxin food contamination incident

Irish monitoring data on PCDD/Fs, DL-PCBs and Marker PCBs were collated and combined with Irish Adult Food Consumption Data, to estimate dietary background exposure of Irish adults to dioxins and PCBs. Furthermore, all available information on the 2008 Irish pork dioxin food contamination incident was collated and analysed with a view to evaluate any potential impact the incident may have had on general dioxin and PCB background exposure levels estimated for the adult population in Ireland. The average upperbound daily intake of Irish adults to dioxins Total WHO TEQ (2005) (PCDD/Fs & DLPCBs) from environmental background contamination, was estimated at 0.3 pg/kg bw/d and at the 95th percentile at 1 pg/kg bw/d. The average upperbound daily intake of Irish adults to the sum of 6 Marker PCBs from environmental background contamination ubiquitous in the environment was estimated at 1.6 ng/kg bw/d and at the 95th percentile at 6.8 ng/kg bw/d. Dietary background exposure estimates for both dioxins and PCBs indicate that the Irish adult population has exposures below the European average, a finding which is also supported by the levels detected in breast milk of Irish mothers. Exposure levels are below health based guidance values and/or Body Burdens associated with the TWI (for dioxins) or associated with a NOAEL (for PCBs). Given the current toxicological knowledge, based on biomarker data and estimated dietary exposure, general background exposure of the Irish adult population to dioxins and PCBs is of no human health concern. In 2008, a porcine fat sample taken as part of the national residues monitoring programme led to the detection of a major feed contamination incidence in the Republic of Ireland. The source of the contamination was traced back to the use of contaminated oil in a direct-drying feed operation system. Congener profiles in animal fat and feed samples showed a high level of consistency and pinpointed the likely source of fuel contamination to be a highly chlorinated commercial PCB mixture. To estimate additional exposure to dioxins and PCBs due to the contamination of pig and cattle herds, collection and a systematic review of all data associated with the contamination incident was conducted. A model was devised that took into account the proportion of contaminated product reaching the final consumer during the 90 day contamination incident window. For a 90 day period, the total additional exposure to Total TEQ (PCDD/F &DL-PCB) WHO (2005) amounted to 407 pg/kg bw/90d at the 95th percentile and 1911 pg/kg bw/90d at the 99th percentile. Exposure estimates derived for both dioxins and PCBs showed that the Body Burden of the general population remained largely unaffected by the contamination incident and approximately 10 % of the adult population in Ireland was exposed to elevated levels of dioxins and PCBs. Whilst people in this 10 % cohort experienced quite a significant additional load to the existing body burden, the estimated exposure values do not indicate approximation of body burdens associated with adverse health effects, based on current knowledge. The exposure period was also limited in time to approximately 3 months, following the FSAI recall of contaminated meat immediately on detection of the contamination. A follow up breast milk study on Irish first time mothers conducted in 2009/2010 did not show any increase in concentrations compared to the study conducted in 2002. The latter supports the conclusion that the majority of the Irish adult population was not affected by the contamination incident.

A craniometric study of population dynamics and social organisation in the European upper Palaeolithic and Mesolithic

The purpose of this study is to explore aspects of social organisation during the Upper Palaeolithic and Mesolithic periods using craniometric data. Different hypotheses were tested using geometric morphometrics, alongside traditional craniometric data. The clustering of individuals from the same site, as well as a correspondence to an isolation-by-distance model—particular in the Mesolithic samples—points to population structure within these groups. Moreover, discontinuities in cranial traits between the early Upper Palaeolithic and later periods could suggest that the Last Glacial Maximum had a disruptive effect on populations in Europe. Differences in social organisation can often result from cultural norms regarding post-marital residence. Such differences can be tested by comparing cranial data to that of geographic information. Greater variation in male cranial traits relative to females, after controlling for location, suggests that the overall pattern of residence during the Upper Palaeolithic and Mesolithic was one of matrilocality. It has been suggested that coastal occupation was density dependent and these populations show a greater degree of sedentism than their inland counterparts. Moreover, it has been proposed that coastal areas were not continuously occupied until the Late Pleistocene due to spatial restrictions that would adversely affect reproductive opportunities. This study corroborates the pattern seen in cranial traits corresponded with that of a more sedentary population. The results are consistent with the hypothesis that coastal populations are more sedentary than inland populations during these periods. This study adds new information regarding the social dynamics of prehistoric populations in Europe and sheds light on some of the conditions that may have paved the way for the transition to agriculture

Can population-level variation in early childhood development be measured in a manner that supports service planning and intervention?

Background: The Early Development Instrument (EDI) is a population-level measure of five developmental domains at school-entry age. The overall aim of this thesis was to explore the potential of the EDI as an indicator of early development in Ireland. Methods: A cross-sectional study was conducted in 47 primary schools in 2011 using the EDI and a linked parental questionnaire. EDI (teacher completed) scores were calculated for 1,344 children in their first year of full-time education. Those scoring in the lowest 10% of the sample population in one or more domains were deemed to be 'developmentally vulnerable'. Scores were correlated with contextual data from the parental questionnaire and with indicators of area and school-level deprivation. Rasch analysis was used to determine the validity of the EDI. Results: Over one quarter (27.5%) of all children in the study were developmentally vulnerable. Individual characteristics associated with increased risk of vulnerability were being male; under 5 years old; and having English as a second language. Adjusted for these demographics, low birth weight, poor parent/child interaction and mother’s lower level of education showed the most significant odds ratios for developmental vulnerability. Vulnerability did not follow the area-level deprivation gradient as measured by a composite index of material deprivation. Children considered by the teacher to be in need of assessment also had lower scores, which were not significantly different from those of children with a clinical diagnosis of special needs. all domains showed at least reasonable fit to the Rasch model supporting the validity of the instrument. However, there was a need for further refinement of the instrument in the Irish context. Conclusion: This thesis provides a unique snapshot of early development in Ireland. The EDI and linked parental questionnaires are promising indicators of the extent, distribution and determinants of developmental vulnerability.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Investigation of population genetic structure and mating system in the ant Pheidole pallidula

The origin of eusociality in haplo-diploid organisms such as Hymenoptera has been mostly explained by kin selection. However, several studies have uncovered decreased relatedness values within colonies, resulting primarily from multiple queen matings (polyandry) and/or from the presence of more than one functional queen (polygyny). Here, we report on the use of microsatellite data for the investigation of sociogenetic parameters, such as relatedness, and levels of polygyny and polyandry, in the ant Pheidole pallidula. We demonstrate, through analysis of mother-offspring combinations and the use of direct sperm typing, that each queen is inseminated by a single male. The inbreeding coefficient within colonies and the levels of relatedness between the queens and their mate are not significantly different from zero, indicating that matings occur between unrelated individuals. Analyses of worker genotypes demonstrate that 38% of the colonies are polygynous with 2-4 functional queens, and suggest the existence of reproductive skew, i.e. unequal respective contribution of queens to reproduction. Finally, our analyses indicate that colonies are genetically differentiated and form a population exhibiting significant isolation-by-distance, suggesting that some colonies originate through budding.