Integrating life cycle costs and environmental impacts of composite rail car-bodies for a Korean train

Background, aim, and scope A coupled Life Cycle Costing and life cycle assessment has been performed for car-bodies of the Korean Tilting Train eXpress (TTX) project using European and Korean databases, with the objective of assessing environmental and cost performance to aid materials and process selection. More specifically, the potential of polymer composite car-body structures for the Korean Tilting Train eXpress (TTX) has been investigated. Materials and methods This assessment includes the cost of both carriage manufacturing and use phases, coupled with the life cycle environmental impacts of all stages from raw material production, through carriage manufacture and use, to end-of-life scenarios. Metallic carriages were compared with two composite options: hybrid steel-composite and full-composite carriages. The total planned production for this regional Korean train was 440 cars, with an annual production volume of 80 cars. Results and discussion The coupled analyses were used to generate plots of cost versus energy consumption and environmental impacts. The results show that the raw material and manufacturing phase costs are approximately half of the total life cycle costs, whilst their environmental impact is relatively insignificant (3-8%). The use phase of the car-body has the largest environmental impact for all scenarios, with near negligible contributions from the other phases. Since steel rail carriages weigh more (27-51%), the use phase cost is correspondingly higher, resulting in both the greatest environmental impact and the highest life cycle cost. Compared to the steel scenario, the hybrid composite variant has a lower life cycle cost (16%) and a lower environmental impact (26%). Though the full composite rail carriage may have the highest manufacturing cost, it results in the lowest total life cycle costs and lowest environmental impacts. Conclusions and recommendations This coupled cost and life cycle assessment showed that the full composite variant was the optimum solution. This case study showed that coupling of technical cost models with life cycle assessment offers an efficient route to accurately evaluate economic and environmental performance in a consistent way.

Geochemical compositions of Neogene phosphatic brachiopods: Implications for ancient environmental and marine conditions

Isotopic and trace element compositions of Miocene and Pliocene phosphatic brachiopods (Lingulidae and Discinidae) from southern North Sea, the Central Paratethys and the Atlantic coast of Europe were investigated in order to trace past environmental conditions and marine connections between the northern boreal and the southern subtropical-tropical marine basins. The North Sea genus Glottidia yielded low epsilon(Nd) and high delta O-18(PO4) values through the Mio-Pliocene indicating cold habitat temperature where the local seawater was dominated by the Atlantic Ocean. In contrast, the Middle Miocene Lingulidae and Discinidae of the Paratethys inhabited warm subtropical seawater with the possible influence of the Indian Ocean via the Mediterranean, as supported by their average epsilon(Nd) value of -8.3. The combined geochemical data support a thermal and marine separation of the Paratethys from the North Sea with no direct connection or major exchange of water from the Miocene onwards. The temperature in the Paratethys was very similar to that inferred from brachiopods from the Middle Miocene of western France, but the seawater epsilon(Nd) value here is identical to that of contemporaneous Atlantic Ocean. A Late Miocene lingulid brachiopod from southern Portugal has a high delta O-18(PO4), similar to the specimens investigated from the North Sea, reflecting either a deep water habitat or formation after the onset of major global cooling that resulted in an increased delta O-18 value of seawater. The epsilon(Nd) value of -8.4 for this site is compatible with an influence of Mediterranean outflow. (C) 2012 Elsevier B.V. All rights reserved.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Making better biogeographical predictions of species' distributions

1. Biogeographical models of species' distributions are essential tools for assessing impacts of changing environmental conditions on natural communities and ecosystems. Practitioners need more reliable predictions to integrate into conservation planning (e.g. reserve design and management). 2. Most models still largely ignore or inappropriately take into account important features of species' distributions, such as spatial autocorrelation, dispersal and migration, biotic and environmental interactions. Whether distributions of natural communities or ecosystems are better modelled by assembling individual species' predictions in a bottom-up approach or modelled as collective entities is another important issue. An international workshop was organized to address these issues. 3. We discuss more specifically six issues in a methodological framework for generalized regression: (i) links with ecological theory; (ii) optimal use of existing data and artificially generated data; (iii) incorporating spatial context; (iv) integrating ecological and environmental interactions; (v) assessing prediction errors and uncertainties; and (vi) predicting distributions of communities or collective properties of biodiversity. 4. Synthesis and applications. Better predictions of the effects of impacts on biological communities and ecosystems can emerge only from more robust species' distribution models and better documentation of the uncertainty associated with these models. An improved understanding of causes of species' distributions, especially at their range limits, as well as of ecological assembly rules and ecosystem functioning, is necessary if further progress is to be made. A better collaborative effort between theoretical and functional ecologists, ecological modellers and statisticians is required to reach these goals.

Environmental and T cell-intrinsic factors limit the expansion of neonatal follicular T helper cells but may be circumvented by specific adjuvants.

Follicular Th (T(FH)) cells have emerged as a new Th subset providing help to B cells and supporting their differentiation into long-lived plasma cells or memory B cells. Their differentiation had not yet been investigated following neonatal immunization, which elicits delayed and limited germinal center (GC) responses. We demonstrate that neonatal immunization induces CXCR5(high)PD-1(high) CD4(+) T(FH) cells that exhibit T(FH) features (including Batf, Bcl6, c-Maf, ICOS, and IL-21 expression) and are able to migrate into the GCs. However, neonatal T(FH) cells fail to expand and to acquire a full-blown GC T(FH) phenotype, as reflected by a higher ratio of GC T(FH)/non-GC CD4(+) T cells in immunized adults than neonates (3.8 × 10(-3) versus 2.2 × 10(-3), p = 0.01). Following the adoptive transfer of naive adult OT-II CD4(+) T cells, OT-II T(FH) cells expand in the vaccine-draining lymph nodes of immunized adult but not infant recipients, whereas naive 2-wk-old CD4(+) OT-II cells failed to expand in adult hosts, reflecting the influence of both environmental and T cell-intrinsic factors. Postponing immunization to later in life increases the number of T(FH) cells in a stepwise manner, in direct correlation with the numbers of GC B cells and plasma cells elicited. Remarkably, adjuvantation with CpG oligonucleotides markedly increased GC T(FH) and GC B cell neonatal responses, up to adult levels. To our knowledge, this is the first demonstration that the T(FH) cell development limits early life GC responses and that adjuvants/delivery systems supporting T(FH) differentiation may restore adultlike early life GC B cell responses.

Network governance and the domestic adoption of soft rules

European regulatory networks (ERNs) are in charge of producing and disseminating non-bindings standards, guidelines and recommendations in a number of important domains, such as banking and finance, electricity and gas, telecommunications, and competition regulation. The goal of these soft rules is to promote 'best practices', achieve co-ordination among regulatory authorities and ensure the consistent application of harmonized pro-competition rules across Europe. This contribution examines the domestic adoption of the soft rules developed within the four main ERNs. Different factors are expected to influence the process of domestic adoption: the resources of regulators; the existence of a review panel; and the interdependence of the issues at stake. The empirical analysis supports hypotheses about the relevance of network-level factors: monitoring and public reporting procedures increase the final level of adoption, while soft rules concerning highly interdependent policy areas are adopted earlier.

Contribution of isotope ratio mass spectrometry to the investigation of improvised explosives: isotopic study of black powders ans ammonium nitrates

The establishment of legislative rules about explosives in the eighties has reduced the illicit use of military and civilian explosives. However, bomb-makers have rapidly taken advantage of substances easily accessible and intended for licit uses to produce their own explosives. This change in strategy has given rise to an increase of improvised explosive charges, which is moreover assisted by the ease of implementation of the recipes, widely available through open sources. While the nature of the explosive charges has evolved, instrumental methods currently used in routine, although more sensitive than before, have a limited power of discrimination and allow mostly the determination of the chemical nature of the substance. Isotope ratio mass spectrometry (IRMS) has been applied to a wide range of forensic materials. Conclusions drawn from the majority of the studies stress its high power of discrimination. Preliminary studies conducted so far on the isotopic analysis of intact explosives (pre-blast) have shown that samples with the same chemical composition and coming from different sources could be differentiated. The measurement of stable isotope ratios appears therefore as a new and remarkable analytical tool for the discrimination or the identification of a substance with a definite source. However, much research is still needed to assess the validity of the results in order to use them either in an operational prospect or in court. Through the isotopic study of black powders and ammonium nitrates, this research aims at evaluating the contribution of isotope ratio mass spectrometry to the investigation of explosives, both from a pre-blast and from a post-blast approach. More specifically, the goal of the research is to provide additional elements necessary to a valid interpretation of the results, when used in explosives investigation. This work includes a fundamental study on the variability of the isotopic profile of black powder and ammonium nitrate in both space and time. On one hand, the inter-variability between manufacturers and, particularly, the intra-variability within a manufacturer has been studied. On the other hand, the stability of the isotopic profile over time has been evaluated through the aging of these substances exposed to different environmental conditions. The second part of this project considers the applicability of this high-precision technology to traces and residues of explosives, taking account of the characteristics specific to the field, including their sampling, a probable isotopic fractionation during the explosion, and the interferences with the matrix of the site.

Micronucleus test on Triturus carnifex as a tool for environmental biomonitoring.

The amphibian micronucleus test has been widely used during the last 30 years to test the genotoxic properties of several chemicals and as a tool for ecogenotoxic monitoring. The vast majority of these studies were performed on peripheral blood of urodelan larvae and anuran tadpoles and to a lesser extent adults were also used. In this study, we developed protocols for measuring micronuclei in adult shed skin cells and larval gill cells of the Italian crested newt (Triturus carnifex). Amphibians were collected from ponds in two protected areas in Italy that differed in their radon content. Twenty-three adult newts and 31 larvae were captured from the radon-rich pond, while 20 adults and 27 larvae were taken from the radon-free site. The animals were brought to the laboratory and the micronucleus test was performed on peripheral blood and shed skins taken from the adults and on larval gills. Samples from the radon-rich site showed micronucleus frequencies higher than those from the radon-free site and the difference was statistically significant in gill cells (P < 0.00001). Moreover, the larval gills seem to be more sensitive than the adult tissues. This method represents an easy (and noninvasive in the case of the shed skin) application of the micronucleus assay that can be useful for environmental studies in situ. Environ. Mol. Mutagen. 56:412-417, 2015. © 2014 Wiley Periodicals, Inc.

Comment on reversal of hypogonadotropic hypogonadism in a Chinese cohort.

The reversal of congenital hypogonadotropic hypogonadism (CHH) is a relatively recent phenomenon that has gained increasing attention over the past 10 years. Yet to date, only one prospective study has been conducted estimating that 10% (95% confidence interval [CI]: 2%-18%) of cases undergo reversal. [1] Other retrospective studies have reported rates in the range of 5%-8% [2],[3] and a recent study showed 44/308 (14%, 95% CI: 11%-19%) CHH patients underwent reversal. [4] Moreover, a time-to-event analysis in this large cohort revealed a lifetime reversal incidence of 22%. The article by Mao and colleagues presented in this issue is a meaningful contribution to our understanding of reversal as it examines the largest retrospective cohort to date. [5] Interestingly, they report the rate of reversal as 5% (95% CI: 3%-8%) in this Chinese cohort. It is difficult to reconcile the discrepancies in rates of reversibility and direct comparisons are hampered by the variable definitions employed. Using a novel definition for reversal (i.e, either endogenous testosterone (T) >270 ng dl−1 , serum T gradually increasing above 150 ng dl−1 with increased testicular volume, or normal spontaneous sperm production/normal erectile function/ejaculation), Mao and colleagues posit that testicular size and triptorelin-stimulated LH levels are reliable predictive factors for reversal. However, these cannot be considered as hard and fast rules for predicting reversal as the groups intersect - akin to the overlap observed between CHH patients and those with delayed puberty. Indeed, the fact that approximately half (44%, 95% CI: 25%-66%) of the reversal patients in the study by Mao et al.[5] were diagnosed between 17 and 19 years of age, underscores the challenge in differentiating CHH from extreme normal variants of puberty. This study further lends credence the recently reported observations that reversals may relapse. [4],[6] The notion that reversal may not be lasting highlights the vulnerability of the reproductive axis among CHH patients. While the mechanism(s) for relapse are unclear, it seems plausible that environmental, metabolic or psychiatric stressors could contribute. The factors that Mao and colleagues identify as significantly different in cases of reversal, were not informative for identifying those cases that relapsed back to a hypogonadal state. Notably, reversal has been reported in probands harboring mutations in genes underlying CHH. [1],[3],[4],[6] Unfortunately, comprehensive genetic screening on the Chinese cohort is not available. The reversal phenomenon is fascinating for its glimpse into the plasticity of the neuroendocrine control of reproduction. Future directions will almost certainly include investigation of specific genetic signatures and novel biomarkers for predicting reversal (and relapse). Yet CHH is a rare condition and to fully elucidate the biology of reversible CHH, it will be important to harmonize definitions of what constitutes a reversal, carefully phenotype patients and chart the natural history of their CHH. In this way, this unique human disease model may offer further insights into the control of human reproduction and provide opportunities to translate discoveries into enhanced approaches to improve the care and quality of life for these patients.

Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models

Aim: Modelling species at the assemblage level is required to make effective forecast of global change impacts on diversity and ecosystem functioning. Community predictions may be achieved using macroecological properties of communities (MEM), or by stacking of individual species distribution models (S-SDMs). To obtain more realistic predictions of species assemblages, the SESAM framework suggests applying successive filters to the initial species source pool, by combining different modelling approaches and rules. Here we provide a first test of this framework in mountain grassland communities. Location: The western Swiss Alps. Methods: Two implementations of the SESAM framework were tested: a "Probability ranking" rule based on species richness predictions and rough probabilities from SDMs, and a "Trait range" rule that uses the predicted upper and lower bound of community-level distribution of three different functional traits (vegetative height, specific leaf area and seed mass) to constraint a pool of environmentally filtered species from binary SDMs predictions. Results: We showed that all independent constraints expectedly contributed to reduce species richness overprediction. Only the "Probability ranking" rule allowed slightly but significantly improving predictions of community composition. Main conclusion: We tested various ways to implement the SESAM framework by integrating macroecological constraints into S-SDM predictions, and report one that is able to improve compositional predictions. We discuss possible improvements, such as further improving the causality and precision of environmental predictors, using other assembly rules and testing other types of ecological or functional constraints.

Morph-specific genetic and environmental variation in innate and acquired immune response in a color polymorphic raptor.

Genetic color polymorphism is widespread in nature. There is an increasing interest in understanding the adaptive value of heritable color variation and trade-off resolution by differently colored individuals. Melanin-based pigmentation is often associated with variation in many different life history traits. These associations have recently been suggested to be the outcome of pleiotropic effects of the melanocortin system. Although pharmacological research supports that MC1R, a gene with a major role in vertebrate pigmentation, has important immunomodulatory effects, evidence regarding pleiotropy at MC1R in natural populations is still under debate. We experimentally assessed whether MC1R-based pigmentation covaries with both inflammatory and humoral immune responses in the color polymorphic Eleonora's falcon. By means of a cross-fostering experiment, we disentangled potential genetic effects from environmental effects on the covariation between coloration and immunity. Variation in both immune responses was primarily due to genetic factors via the nestlings' MC1R-related color genotype/phenotype, although environmental effects via the color morph of the foster father also had an influence. Overall, dark nestlings had lower immune responses than pale ones. The effect of the color morph of the foster father was also high, but in the opposite direction, and nestlings raised by dark eumelanic foster fathers had higher immune responses than those raised by pale foster fathers. Although we cannot completely discard alternative explanations, our results suggest that MC1R might influence immunity in this species. Morph-specific variation in immunity as well as pathogen pressure may therefore contribute to the long-term maintenance of genetic color polymorphism in natural populations.