Equivalent Carbon Dioxide Capture and Storage Processes in Offshore Petroleum Production Facilities

The present study approaches the economic and technical evaluation of equivalent carbon dioxide (CO(2) eqv.) capture and storage processes, considered in a proposal case compared to a base case. The base case considers an offshore petroleum production facility, with high CO(2) content (4 vol%) in the composition of the produced gas and both CO(2) and natural gas emissions to the atmosphere, called CO(2) eqv. emissions. The results obtained with this study, by using a Hysys process simulator, showed a CO(2) emission reduction of 65% comparing the proposal case in relation to the base case.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - III. The integrated wheat model (I_WHEAT)

Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.

Genetic covariance between indices of body condition and immunocompetence in a passerine bird

Background: Condition-dependence is a ubiquitous feature of animal life histories and has important implications for both natural and sexual selection. Mate choice, for instance, is typically based on condition-dependent signals. Theory predicts that one reason why condition-dependent signals may be special is that they allow females to scan for genes that confer high parasite resistance. Such explanations require a genetic link between immunocompetence and body condition, but existing evidence is limited to phenotypic associations. It remains unknown, therefore, whether females selecting males with good body condition simply obtain a healthy mate, or if they acquire genes for their offspring that confer high immunocompetence. Results: Here we use a cross-foster experimental design to partition the phenotypic covariance in indices of body condition and immunocompetence into genetic, maternal and environmental effects in a passerine bird, the zebra finch Taeniopygia guttata. We show that there is significant positive additive genetic covariance between an index of body condition and an index of cell-mediated immune response. In this case, genetic variance in the index of immune response explained 56% of the additive genetic variance in the index of body condition. Conclusion: Our results suggest that, in the context of sexual selection, females that assess males on the basis of condition-dependent signals may gain genes that confer high immunocompetence for their offspring. More generally, a genetic correlation between indices of body condition and imuunocompetence supports the hypothesis that parasite resistance may be an important target of natural selection. Additional work is now required to test whether genetic covariance exists among other aspects of both condition and immunocompetence.

Malformations of Cortical Development in Patients With Mid line Facial Defects and Ocular Hypertelorism

Objectives: We studied the neuroimaging and neurophysiological aspects of 17 patients with midline facial defects with ocular hypertelorism (MFDH). Methods: The investigation protocol included a previous semistructured questionnaire about family history; gestational, neonatal, and postnatal development; and dysmorphologic and neurologic evaluation. Recognized monogenic disorders and individuals with other well-known conditions were excluded. All patients had high resolution magnetic resonance imaging (MRI) with multiplanar reconstruction (MPR) and routine electroencephalograms (EEGs). Results: We detected abnormalities in five patients whose MRIs had been previously reported as normal. MRI showed central nervous system (CNS) structural abnormalities in all patients, which included commissural alterations in 16/17 (94%), malformations of cortical development in 10/17 (58%), disturbances of neural tube closure in 7/17(42%), and posterior fossa anomalies in 6/17 (35%). Some patients had more than one type of malformation occurring at different stages of the embryonary process. EEGs showed epileptiform activity in 4/17 (24%) and background abnormalities in 5/17 (29%) of patients. Conclusion: This study clearly demonstrated the presence of structural and functional neurologic alterations related to MFDH. Therefore, the CNS anomalies cannot be considered incidental findings but an intrinsic part of this condition, which could be related to environmental effects and/or genetic mutations. These findings would provide a basis for future investigations on MFDH and should also be considered when planning rehabilitation.

Covariance functions for body weight from birth to maturity in Nellore cows

The objective of this study was to estimate (co)variance functions using random regression models on Legendre polynomials for the analysis of repeated measures of BW from birth to adult age. A total of 82,064 records from 8,145 females were analyzed. Different models were compared. The models included additive direct and maternal effects, and animal and maternal permanent environmental effects as random terms. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of animal age (cubic regression) were considered as random co-variables. Eight models with polynomials of third to sixth order were used to describe additive direct and maternal effects, and animal and maternal permanent environmental effects. Residual effects were modeled using 1 (i.e., assuming homogeneity of variances across all ages) or 5 age classes. The model with 5 classes was the best to describe the trajectory of residuals along the growth curve. The model including fourth- and sixth-order polynomials for additive direct and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects were the best. Estimates of (co) variance obtained with the multi-trait and random regression models were similar. Direct heritability estimates obtained with the random regression models followed a trend similar to that obtained with the multi-trait model. The largest estimates of maternal heritability were those of BW taken close to 240 d of age. In general, estimates of correlation between BW from birth to 8 yr of age decreased with increasing distance between ages.

Natural selection and quantitative genetics of life-history traits in Western women: A twin study

Whether contemporary human populations are still evolving as a result of natural selection has been hotly debated. For natural selection to cause evolutionary change in a trait, variation in the trait must be correlated with fitness and be genetically heritable and there must be no genetic constraints to evolution. These conditions have rarely been tested in human populations. In this study, data from a large twin cohort were used to assess whether selection Will cause a change among women in contemporary Western population for three life-history traits: age at menarche, age at first reproduction, and age at menopause. We control for temporal variation in fecundity (the baby boom phenomenon) and differences between women in educational background and religious affiliation. University-educated women have 35% lower fitness than those with less than seven years education, and Roman Catholic women have about 20% higher fitness than those of other religions. Although these differences were significant, education and religion only accounted for 2% and 1% of variance in fitness, respectively. Using structural equation modeling, we reveal significant genetic influences for all three life-history traits, with heritability estimates of 0.50, 0.23, and 0.45, respectively. However, strong genetic covariation with reproductive fitness could only be demonstrated for age at first reproduction, with much weaker covariation for age at menopause and no significant covariation for age at menarche. Selection may, therefore, lead to the evolution of earlier age at first reproduction in this population. We also estimate substantial heritable variation in fitness itself, with approximately 39% of the variance attributable to additive genetic effects, the remainder consisting of unique environmental effects and small effects from education and religion. We discuss mechanisms that could be maintaining such a high heritability for fitness. Most likely is that selection is now acting on different traits from which it did in pre-industrial human populations.

An integrative approach for studying the etiology of alcoholism and other addictions

Studies of alcoholism etiology often focus on genetic or psy-chosocial approaches, but not both. Greater understanding of the etiology of alcohol, tobacco and other addictions will come from integration of these research traditions. A research approach is outlined to test three models for the etiology of addictions — behavioral undercontrol, pharmacologic vulnerability, negative affect regulation — addressing key questions including (i) mediators of genetic effects, (ii) genotype-environment correlation effects, (iii) genotype x environment interaction effects, (iv) the developmental unfolding of genetic and environmental effects, (v) subtyping including identification of distinct trajectories of substance involvement, (vi) identification of individual genes that contribute to risk, and (vii) the consequences of excessive use. By using coordinated research designs, including prospective assessment of adolescent twins and their siblings and parents; of adult substance dependent and control twins and their MZ and DZ cotwins, the spouses of these pairs, and their adolescent offspring; and of regular families; by selecting for gene-mapping approaches sibships screened for extreme concordance or discordance on quantitative indices of substance use; and by using experimental (drug challenge) as well as survey approaches, a number of key questions concerning addiction etiology can be addressed. We discuss complementary strengths and weaknesses of different sampling strategies, as well as methods to implement such an integrated approach illustrated for the study of alcoholism etiology. A coordinated program of twin and family studies will allow a comprehensive dissection of the interplay of genetic and environmental risk-factors in the etiology of alcoholism and other addictions.

Genetic and non-genetic factors affecting birth-weight and adult body mass index

Birthweight affects neonatal mortality and morbidity and has been used as a marker of foetal undernutrition in studies of prenatal effects on adult characteristics. It is potentially influenced by genetic and environmental influences on the mother, and effects of foetal genotype, which is partially derived from the maternal genotype. Interpretations of variation in birthweight and associated characteristics as being due to prenatal environment ignore other possible modes of materno-foetal transmission. Subjects were adult twins recruited through the Australian Twin Registry, aged 17 to 87 years, and the sample comprised 1820 men and 4048 women. Twins reported their own birthweight as part of a health questionnaire. Body Mass Index (BMI) was calculated from self-reports of height and weight. Correlations between co-twins' birthweights were high for both monozygotic (r = 0.77) and dizygotic (r = 0.67) pairs, leading to substantial estimates of shared environmental effects (56% of variance) with significant additive genetic (23%) and non-shared environmental (21%) components. Adult BMI was mainly influenced by genetic factors, both additive (36% of variance) and nonadditive (35%). The correlation between birthweight and BMI was positive, in that heavier babies became on average more obese adults. A bivariate model of birthweight and adult BMI showed significant positive genetic (rg = 0.16, p = 0.005) and environmental (re = 0.08, p = 0.000011) correlations. Intra-uterine environmental or perinatal influences shared by cotwins exercise a strong influence on birthweight, but the factors which affect both birthweight and adult BMI are partly genetic and partly non-shared environmental.

Repeated blood pressure measurements in a sample of Swedish twins: heritabilities and associations with polymorphisms in the renin-angiotensin-aldosterone system Iliadou, Anastasia, Lichtenstein, Paul, Morgenstern, Ralf, Forsberg, Lena, Svensson, Richard, de Faire, Ulf, Martin, Nicholas, Pedersen, Nancy

Background Twin and family studies have shown that genetic effects explain a relatively high amount of the phenotypic variation in blood pressure. However, many studies have not been able to replicate findings of association between specific polymorphisms and diastolic and systolic blood pressure. Methods In a structural equation-modelling framework the authors investigated longitudinal changes in repeated measures of blood pressures in a sample of 298 like-sexed twin pairs from the population-based Swedish Twin Registry. Also examined was the association between blood pressure and polymorphisms in the angiotensin-I converting enzyme and the angiotensin 11 receptor type 1 with the 'Fulker' test Both linkage and association were tested simultaneously revealing whether the polymorphism is a Quantitative Trait Locus (QTL) or in linkage disequilibrium with the QTL. Results Genetic influences explained up to 46% of the phenotypic variance in diastolic and 63% of the phenotypic variance in systolic blood pressure. Genetic influences were stable over time and contributed up to 78% of the phenotypic correlation in both diastolic and systolic blood pressure. Non-shared environmental effects were characterised by time specific influences and little transmission from one time point to the next. There was no significant linkage and association between the polymorphisms and blood pressure. Conclusions There is a considerable genetic stability in both diastolic and systolic blood pressure for a 6-year period of time in adult life. Non-shared environmental influences have a small long-term effect Although associations with the polymorphisms could not be replicated, results should be interpreted with caution due to power considerations. (C) 2002 Lippincott Williams Wilkins.

The validity and heritability of self-report osteoarthritis in an Australian older twin sample

In order to investigate the genetic and environmental antecedents of osteoarthritis (CA), self-report measures of joint pain, stiffness and swelling were obtained from a population-based sample of 1242 twin pairs over 50 years of age. In order to provide validation for these self-report measures, a subsample of 118 twin pairs were examined according to the American College of Rheumatology clinical and radiographic criteria for the classification of osteoarthritis. A variety of statistical methods were employed to identify the model derived from self-report variables which would provide optimal prediction of these standardised assessments, and structural equation modelling was used to determine the relative influences of genetic and environmental influences on the development of osteoarthritis. Significant genetic effects were found to contribute to osteoarthritis of the hands, hips and knees in women, with heritability estimates ranging from 30-46% depending on the site. In addition, the additive genetic effects contributing to osteoarthritis in various parts of the body were confirmed to be the same. Statistically significant familial aggregation of osteoarthritis in men was also observed, but it was not possible to determine whether this was due to genetic or shared environmental effects.

Stream-bank shade and larval distribution of the Philippine malaria vector Anopheles flavirostris

The principal malaria vector in the Philippines, Anopheles flavirostris (Ludlow) (Diptera: Culicidae), is regarded as 'shade-loving' for its breeding sites, i.e. larval habitats. This long-standing belief, based on circumstantial observations rather than ecological analysis, has guided larval control methods such as 'stream-clearing' or the removal of riparian vegetation, to reduce the local abundance of An. flavirostris . We measured the distribution and abundance of An. flavirostris larvae in relation to canopy vegetation cover along a stream in Quezon Province, the Philippines. Estimates of canopy openness and light measurements were obtained by an approximation method that used simplified assumptions about the sun, and by hemispherical photographs analysed using the program hemiphot(C) . The location of larvae, shade and other landscape features was incorporated into a geographical information system (GIS) analysis. Early larval instars of An. flavirostris were found to be clustered and more often present in shadier sites, whereas abundance was higher in sunnier sites. For later instars, distribution was more evenly dispersed and only weakly related to shade. The best predictor of late-instar larvae was the density of early instars. Distribution and abundance of larvae were related over time (24 days). This pattern indicates favoured areas for oviposition and adult emergence, and may be predictable. Canopy measurements by the approximation method correlated better with larval abundance than hemispherical photography, being economical and practical for field use. Whereas shade or shade-related factors apparently have effects on larval distribution of An. flavirostris , they do not explain it completely. Until more is known about the bionomics of this vector and the efficacy and environmental effects of stream-clearing, we recommend caution in the use of this larval control method.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

Direction of Causation Modeling Between Cross-Sectional Measures of Parenting and Psychological Distress in Female Twins

Under certain conditions, cross-sectional analysis of cross-twin intertrait correlations can provide important information about the direction of causation (DOC) between two variables. A community-based sample of Australian female twins aged 18 to 45 years was mailed an extensive Health and Lifestyle Questionnaire (HLQ) that covered a wide range of personality and behavioral measures. Included were self-report measures of recent psychological distress and perceived childhood environment (PBI). Factor analysis of the PBI yielded three interpretable dimensions: Coldness, Overprotection, and Autonomy. Univariate analysis revealed that parental Overprotection and Autonomy were best explained by additive genetic, shared, and nonshared environmental effects (ACE), whereas the best-fitting model for PBI Coldness and the three measures of psychological distress (Depression, Phobic Anxiety, and Somatic Distress) included only additive genetic and nonshared environmental effects (AE). A common pathway model best explained the covariation between (1) the three PBI dimensions and (2) the three measures of psychological distress. DOC modeling between latent constructs of parenting and psychological distress revealed that a model which specified recollected parental behavior as the cause of psychological distress provided a better fit than a model which specified psychological distress as the cause of recollected parental behavior. Power analyses and limitations of the findings are discussed.

AI in power systems and energy markets

In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.