An analysis of wind curtailment and constraint at a nodal level

Many countries have set challenging wind power targets to achieve by 2020. This paper implements a realistic analysis of curtailment and constraint of wind energy at a nodal level using a unit commitment and economic dispatch model of the Irish Single Electricity Market in 2020. The key findings show that significant reduction in curtailment can be achieved when the system non-synchronous penetration limit increases from 65% to 75%. For the period analyzed, this results in a decreased total generation cost and a reduction in the dispatch-down of wind. However, some nodes experience significant dispatch-down of wind, which can be in the order of 40%. This work illustrates the importance of implementing analysis at a nodal level for the purpose of power system planning.

Isotopic variation complicates analysis of trophic relations within the fish community of Plußsee: a small, deep, stratifying lake

Analysis of carbon and nitrogen stable isotopes has allowed freshwater ecologists to examine lake food webs in increasing detail. Many such studies have highlighted the existence of separate within-lake pelagic and benthic-littoral food webs but are typically conducted on large (> 10 km2) lakes, whereas the majority of lakes are actually relatively small. We used stable isotope analysis (δ13C & δ15N) to examine trophic interactions between fish and their prey in Plu�see, as an example of a small, stratifying lake, and to determine whether separate pelagic/benthic-littoral food webs could be distinguished in such systems. Our results indicate that the Plu�see food web was complicated, and due to extensive intra-annual isotopic variation in zooplankton (e.g. cladoceran δ13C annual range = 25.6�), it may be impossible to definitively assign consumers from small, eutrophic stratified lakes to pelagic or benthic-littoral food webs. We present evidence that some components of the Plu�see food web (large bream) may be subsidised by carbon of methanogenic origin.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

Job strain as a risk factor for coronary heart disease:a collaborative meta-analysis of individual participant data

BACKGROUND: Published work assessing psychosocial stress (job strain) as a risk factor for coronary heart disease is inconsistent and subject to publication bias and reverse causation bias. We analysed the relation between job strain and coronary heart disease with a meta-analysis of published and unpublished studies. METHODS: We used individual records from 13 European cohort studies (1985-2006) of men and women without coronary heart disease who were employed at time of baseline assessment. We measured job strain with questions from validated job-content and demand-control questionnaires. We extracted data in two stages such that acquisition and harmonisation of job strain measure and covariables occurred before linkage to records for coronary heart disease. We defined incident coronary heart disease as the first non-fatal myocardial infarction or coronary death. FINDINGS: 30?214 (15%) of 197?473 participants reported job strain. In 1·49 million person-years at risk (mean follow-up 7·5 years [SD 1·7]), we recorded 2358 events of incident coronary heart disease. After adjustment for sex and age, the hazard ratio for job strain versus no job strain was 1·23 (95% CI 1·10-1·37). This effect estimate was higher in published (1·43, 1·15-1·77) than unpublished (1·16, 1·02-1·32) studies. Hazard ratios were likewise raised in analyses addressing reverse causality by exclusion of events of coronary heart disease that occurred in the first 3 years (1·31, 1·15-1·48) and 5 years (1·30, 1·13-1·50) of follow-up. We noted an association between job strain and coronary heart disease for sex, age groups, socioeconomic strata, and region, and after adjustments for socioeconomic status, and lifestyle and conventional risk factors. The population attributable risk for job strain was 3·4%. INTERPRETATION: Our findings suggest that prevention of workplace stress might decrease disease incidence; however, this strategy would have a much smaller effect than would tackling of standard risk factors, such as smoking. FUNDING: Finnish Work Environment Fund, the Academy of Finland, the Swedish Research Council for Working Life and Social Research, the German Social Accident Insurance, the Danish National Research Centre for the Working Environment, the BUPA Foundation, the Ministry of Social Affairs and Employment, the Medical Research Council, the Wellcome Trust, and the US National Institutes of Health.

Comparison of lagrangian and eulerian simulations of slurry flows in a sudden expansion

From a review of technical literature, it was not apparent if the Lagrangian or the Eulerian dispersed phase modeling approach was more valid to simulate dilute erosive slurry flow. In this study, both modeling approaches were employed and a comparative analysis of performances and accuracy between the two models was carried out. Due to an impossibility to define, for the Eulerian model already implemented in FLUENT, a set of boundary conditions consistent with the Lagrangian impulsive equations, an Eulerian dispersed phase model was integrated in the FLUENT code using subroutines and user-defined scalar equations. Numerical predictions obtained from the two different approaches for two-phase flow in a sudden expansion were compared with the measured data. Excellent agreement was attained between the predicted and observed fluid and particle velocity in the axial direction and for the kinetic energy. Erosion profiles in a sudden expansion computed using the Lagrangian scheme yielded good qualitative agreement with measured data and predicted a maximum impact angle of 29 deg at the fluid reattachment point. The Eulerian model was adversely affected by the reattachment of the fluid phase to the wall and the simulated erosion profiles were not in agreement with the Lagrangian or measured data. Furthermore, the Eulerian model under-predicted the Lagrangian impact angle at all locations except the reattachment point. © 2010 American Society of Mechanical Engineers.

Prognostic and therapeutic relevance of FLIP and procaspase-8 overexpression in non-small cell lung cancer

Non-small cell lung carcinoma remains by far the leading cause of cancer-related deaths worldwide. Overexpression of FLIP, which blocks the extrinsic apoptotic pathway by inhibiting caspase-8 activation, has been identified in various cancers. We investigated FLIP and procaspase-8 expression in NSCLC and the effect of HDAC inhibitors on FLIP expression, activation of caspase-8 and drug resistance in NSCLC and normal lung cell line models. Immunohistochemical analysis of cytoplasmic and nuclear FLIP and procaspase-8 protein expression was carried out using a novel digital pathology approach. Both FLIP and procaspase-8 were found to be significantly overexpressed in tumours, and importantly, high cytoplasmic expression of FLIP significantly correlated with shorter overall survival. Treatment with HDAC inhibitors targeting HDAC1-3 downregulated FLIP expression predominantly via post-transcriptional mechanisms, and this resulted in death receptor- and caspase-8-dependent apoptosis in NSCLC cells, but not normal lung cells. In addition, HDAC inhibitors synergized with TRAIL and cisplatin in NSCLC cells in a FLIP- and caspase-8-dependent manner. Thus, FLIP and procaspase-8 are overexpressed in NSCLC, and high cytoplasmic FLIP expression is indicative of poor prognosis. Targeting high FLIP expression using HDAC1-3 selective inhibitors such as entinostat to exploit high procaspase-8 expression in NSCLC has promising therapeutic potential, particularly when used in combination with TRAIL receptor-targeted agents.

Women (Re)Negotiating Care across Family Generations: Intersections of Gender and Socioeconomic Status

Changing Generations, a study of intergenerational relations in Ireland undertaken between 2011 and 2013 by the Social Policy and Ageing Research Centre (SPARC), Trinity College, Dublin, and the Irish Centre for Social Gerontology (ICSG), NUI Galway, used the Constructivist Grounded Theory method to interrogate support and care provision between generations. This article draws on interviews with 52 women ages 18 to 102, allowing for simultaneous analysis of older and younger women’s perspectives. The intersectionality of gender and class emerged as central to the analysis. Socioeconomic positions shape contrasting forms of interdependency among family generations, ranging from “enmeshed” lives among lower socioeconomic groups to “freed” lives among higher socioeconomic groups. Women are initiating changes in how care and support flow across generations. Older women in higher socioeconomic groups are attuned to how emotional capital women expend across family generations can constrain (young) women’s lives. In an expression of solidarity, older women are renegotiating the place of care labor in their own lives and in the lives of younger women. A new reciprocity emerges that amounts to women “undoing gender.” This process is, however, deeply classed as it is women in higher socioeconomic groups whose resources best place them to renegotiate care.

On Passive Intermodulation Test of Analog and Digital Systems

This paper presents initial results of evaluating suitability of the conventional two-tone CW passive intermodulation (PIM) test for characterization of modulated signal distortion by passive nonlinearities in base station antennas and RF front-end. A comprehensive analysis of analog and digitally modulated waveforms in the transmission lines with weak distributed nonlinearity has been performed using the harmonic balance analysis and X-parameters in Advanced Design System (ADS) simulator. The nonlinear distortion metrics used in the conventional two-tone CW PIM test have been compared with the respective spectral metrics applied to the modulated waveforms, such as adjacent channel power ratio (ACPR) and error vector magnitude (EVM). It is shown that the results of two-tone CW PIM tests are consistent with the metrics used for assessment of signal integrity of both analog and digitally modulated waveforms.

Frequency of mutations and polymorphisms in borderline ovarian tumors of known cancer genes.

Borderline ovarian tumors represent an understudied subset of ovarian tumors. Most studies investigating aberrations in borderline tumors have focused on KRAS/BRAF mutations. In this study, we conducted an extensive analysis of mutations and single-nucleotide polymorphisms (SNPs) in borderline ovarian tumors. Using the Sequenom MassArray platform, we investigated 160 mutations/polymorphisms in 33 genes involved in cell signaling, apoptosis, angiogenesis, cell cycle regulation and cellular senescence. Of 52 tumors analyzed, 33 were serous, 18 mucinous and 1 endometrioid. KRAS c.35G>A p.Gly12Asp mutations were detected in eight tumors (six serous and two mucinous), BRAF V600E mutations in two serous tumors, and PIK3CA H1047Y and PIK3CA E542K mutations in a serous and an endometrioid BOT, respectively. CTNNB1 mutation was detected in a serous tumor. Potentially functional polymorphisms were found in vascular endothelial growth factor (VEGF), ABCB1, FGFR2 and PHLPP2. VEGF polymorphisms were the most common and detected at four loci. PHLPP2 polymorphisms were more frequent in mucinous as compared with serous tumors (P=0.04), with allelic imbalance in one case. This study represents the largest and most comprehensive analysis of mutations and functional SNPs in borderline ovarian tumors to date. At least 25% of borderline ovarian tumors harbor somatic mutations associated with potential response to targeted therapeutics.

Outlier effects on robust joint modelling of longitudinal and survival data

Robust joint modelling is an emerging field of research. Through the advancements in electronic patient healthcare records, the popularly of joint modelling approaches has grown rapidly in recent years providing simultaneous analysis of longitudinal and survival data. This research advances previous work through the development of a novel robust joint modelling methodology for one of the most common types of standard joint models, that which links a linear mixed model with a Cox proportional hazards model. Through t-distributional assumptions, longitudinal outliers are accommodated with their detrimental impact being down weighed and thus providing more efficient and reliable estimates. The robust joint modelling technique and its major benefits are showcased through the analysis of Northern Irish end stage renal disease patients. With an ageing population and growing prevalence of chronic kidney disease within the United Kingdom, there is a pressing demand to investigate the detrimental relationship between the changing haemoglobin levels of haemodialysis patients and their survival. As outliers within the NI renal data were found to have significantly worse survival, identification of outlying individuals through robust joint modelling may aid nephrologists to improve patient's survival. A simulation study was also undertaken to explore the difference between robust and standard joint models in the presence of increasing proportions and extremity of longitudinal outliers. More efficient and reliable estimates were obtained by robust joint models with increasing contrast between the robust and standard joint models when a greater proportion of more extreme outliers are present. Through illustration of the gains in efficiency and reliability of parameters when outliers exist, the potential of robust joint modelling is evident. The research presented in this thesis highlights the benefits and stresses the need to utilise a more robust approach to joint modelling in the presence of longitudinal outliers.

Joint Analysis of Multiple Algorithms and Performance Measures

There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers is used to show a practical application of our tests.