Development of MASH TL-3 Transition Between Guardrail and Portable Concrete Barriers, TPF-5(081), 2014

Often, road construction causes the need to create a work zone. In these scenarios, portable concrete barriers (PCBs) are typically installed to shield workers and equipment from errant vehicles as well as prevent motorists from striking other roadside hazards. For an existing W-beam guardrail system installed adjacent to the roadway and near the work zone, guardrail sections are removed in order to place the portable concrete barrier system. The focus of this research study was to develop a proper stiffness transition between W-beam guardrail and portable concrete barrier systems. This research effort was accomplished through development and refinement of design concepts using computer simulation with LS-DYNA. Several design concepts were simulated, and design metrics were used to evaluate and refine each concept. These concepts were then analyzed and ranked based on feasibility, likelihood of success, and ease of installation. The rankings were presented to the Technical Advisory Committee (TAC) for selection of a preferred design alternative. Next, a Critical Impact Point (CIP) study was conducted, while additional analyses were performed to determine the critical attachment location and a reduced installation length for the portable concrete barriers. Finally, an additional simulation effort was conducted in order to evaluate the safety performance of the transition system under reverse-direction impact scenarios as well as to select the CIP. Recommendations were also provided for conducting a Phase II study and evaluating the nested Midwest Guardrail System (MGS) configuration using three Test Level 3 (TL-3) full-scale crash tests according to the criteria provided in the Manual for Assessing Safety Hardware, as published by the American Association of Safety Highway and Transportation Officials (AASHTO).

An application of capital allocation principles to operational risk

The cost of operational risk refers to the capital needed to a fford the loss generated by ordinary activities of a firm. In this work we demonstrate how allocation principles can be used to the subdivision of the aggregate capital so that the firm can distribute this cost across its various constituents that generate operational risk. Several capital allocation principles are revised. Proportional allocation allows to calculate a relative risk premium to be charged to each unit. An example of fraud risk in the banking sector is presented and some correlation scenarios between business lines are compared. Keywords: solvency, quantile, value at risk, copulas

Susceptibilitat genètica al càncer gàstric: caracterització de les interaccions de segon ordre entre gens i variants identificades en l’estudi EPIC‐EURGAST

En aquest Treball de Final de Grau s’exposen els resultats de l’anàlisi de les dades genètiques del projecte EurGast2 "Genetic susceptibility, environmental exposure and gastric cancer risk in an European population”, estudi cas‐control niat a la cohort europea EPIC “European Prospective lnvestigation into Cancer and Nutrition”, que té per objectiu l’estudi dels factors genètics i ambientals associats amb el risc de desenvolupar càncer gàstric (CG). A partir de les dades resultants de l’estudi EurGast2, en el què es van analitzar 1.294 SNPs en 365 casos de càncer gàstric i 1.284 controls en l’anàlisi Single SNP previ, la hipòtesi de partida del present Treball de Final de Grau és que algunes variants amb un efecte marginal molt feble, però que conjuntament amb altres variants estarien associades al risc de CG, podrien no haver‐se detectat. Així doncs, l’objectiu principal del projecte és la identificació d’interaccions de segon ordre entre variants genètiques de gens candidats implicades en la carcinogènesi de càncer gàstric. L’anàlisi de les interaccions s’ha dut a terme aplicant el mètode estadístic Model‐based Multifactor Dimensionality Reduction Method (MB‐MDR), desenvolupat per Calle et al. l’any 2008 i s’han aplicat dues metodologies de filtratge per seleccionar les interaccions que s’exploraran: 1) filtratge d’interaccions amb un SNP significatiu en el Single SNP analysis i 2) filtratge d’interaccions segons la mesura Sinèrgia. Els resultats del projecte han identificat 5 interaccions de segon ordre entre SNPs associades significativament amb un major risc de desenvolupar càncer gàstric, amb p‐valor inferior a 10‐4. Les interaccions identificades corresponen a interaccions entre els gens MPO i CDH1, XRCC1 i GAS6, ADH1B i NR5A2 i IL4R i IL1RN (que s’ha validat en les dues metodologies de filtratge). Excepte CDH1, cap altre d’aquests gens s’havia associat significativament amb el CG o prioritzat en les anàlisis prèvies, el que confirma l’interès d’analitzar les interaccions genètiques de segon ordre. Aquestes poden ser un punt de partida per altres anàlisis destinades a confirmar gens putatius i a estudiar a nivell biològic i molecular els mecanismes de carcinogènesi, i orientades a la recerca de noves dianes terapèutiques i mètodes de diagnosi i pronòstic més eficients.

Multiscale assessment of plant diversity in wooded pastures of the Jura mountains

Résumé La diminution de la biodiversité, à toutes les échelles spatiales et sur l'ensemble de la planète, compte parmi les problèmes les plus préoccupants de notre époque. En terme de conservation, il est aujourd'hui primordial de mieux comprendre les mécanismes qui créent et maintiennent la biodiversité dans les écosystèmes naturels ou anthropiques. La présente étude a pour principal objectif d'améliorer notre compréhension des patrons de biodiversité végétale et des mécanismes sous jacents, dans un écosystème complexe, riche en espèces et à forte valeur patrimoniale, les pâturages boisés jurassiens. Structure et échelle spatiales sont progressivement reconnues comme des dimensions incontournables dans l'étude des patrons de biodiversité. De plus, ces deux éléments jouent un rôle central dans plusieurs théories écologiques. Toutefois, peu d'hypothèses issues de simulations ou d'études théoriques concernant le lien entre structure spatiale du paysage et biodiversité ont été testées de façon empirique. De même, l'influence des différentes composantes de l'échelle spatiale sur les patrons de biodiversité est méconnue. Cette étude vise donc à tester quelques-unes de ces hypothèses et à explorer les patrons spatiaux de biodiversité dans un contexte multi-échelle, pour différentes mesures de biodiversité (richesse et composition en espèces) à l'aide de données de terrain. Ces données ont été collectées selon un plan d'échantillonnage hiérarchique. Dans un premier temps, nous avons testé l'hypothèse élémentaire selon laquelle la richesse spécifique (le nombre d'espèces sur une surface donnée) est liée à l'hétérogénéité environnementale quelque soit l'échelle. Nous avons décomposé l'hétérogénéité environnementale en deux parties, la variabilité des conditions environnementales et sa configuration spatiale. Nous avons montré que, en général, la richesse spécifique augmentait avec l'hétérogénéité de l'environnement : elle augmentait avec le nombre de types d'habitats et diminuait avec l'agrégation spatiale de ces habitats. Ces effets ont été observés à toutes les échelles mais leur nature variait en fonction de l'échelle, suggérant une modification des mécanismes. Dans un deuxième temps, la structure spatiale de la composition en espèces a été décomposée en relation avec 20 variables environnementales et 11 traits d'espèces. Nous avons utilisé la technique de partition de la variation et un descripteur spatial, récemment développé, donnant accès à une large gamme d'échelles spatiales. Nos résultats ont montré que la structure spatiale de la composition en espèces végétales était principalement liée à la topographie, aux échelles les plus grossières, et à la disponibilité en lumière, aux échelles les plus fines. La fraction non-environnementale de la variation spatiale de la composition spécifique avait une relation complexe avec plusieurs traits d'espèces suggérant un lien avec des processus biologiques tels que la dispersion, dépendant de l'échelle spatiale. Dans un dernier temps, nous avons testé, à plusieurs échelles spatiales, les relations entre trois composantes de la biodiversité : la richesse spécifique totale d'un échantillon (diversité gamma), la richesse spécifique moyenne (diversité alpha), mesurée sur des sous-échantillons, et les différences de composition spécifique entre les sous-échantillons (diversité beta). Les relations deux à deux entre les diversités alpha, beta et gamma ne suivaient pas les relations attendues, tout du moins à certaines échelles spatiales. Plusieurs de ces relations étaient fortement dépendantes de l'échelle. Nos résultats ont mis en évidence l'importance du rapport d'échelle (rapport entre la taille de l'échantillon et du sous-échantillon) lors de l'étude des patrons spatiaux de biodiversité. Ainsi, cette étude offre un nouvel aperçu des patrons spatiaux de biodiversité végétale et des mécanismes potentiels permettant la coexistence des espèces. Nos résultats suggèrent que les patrons de biodiversité ne peuvent être expliqués par une seule théorie, mais plutôt par une combinaison de théories. Ils ont également mis en évidence le rôle essentiel joué par la structure spatiale dans la détermination de la biodiversité, quelque soit le composant de la biodiversité considéré. Enfin, cette étude souligne l'importance de prendre en compte plusieurs échelles spatiales et différents constituants de l'échelle spatiale pour toute étude relative à la diversité spécifique. Abstract The world-wide loss of biodiversity at all scales has become a matter of urgent concern, and improving our understanding of local drivers of biodiversity in natural and anthropogenic ecosystems is now crucial for conservation. The main objective of this study was to further our comprehension of the driving forces controlling biodiversity patterns in a complex and diverse ecosystem of high conservation value, wooded pastures. Spatial pattern and scale are central to several ecological theories, and it is increasingly recognized that they must be taken -into consideration when studying biodiversity patterns. However, few hypotheses developed from simulations or theoretical studies have been tested using field data, and the evolution of biodiversity patterns with different scale components remains largely unknown. We test several such hypotheses and explore spatial patterns of biodiversity in a multi-scale context and using different measures of biodiversity (species richness and composition), with field data. Data were collected using a hierarchical sampling design. We first tested the simple hypothesis that species richness, the number of species in a given area, is related to environmental heterogeneity at all scales. We decomposed environmental heterogeneity into two parts: the variability of environmental conditions and its spatial configuration. We showed that species richness generally increased with environmental heterogeneity: species richness increased with increasing number of habitat types and with decreasing spatial aggregation of those habitats. Effects occurred at all scales but the nature of the effect changed with scale, suggesting a change in underlying mechanisms. We then decomposed the spatial structure of species composition in relation to environmental variables and species traits using variation partitioning and a recently developed spatial descriptor, allowing us to capture a wide range of spatial scales. We showed that the spatial structure of plant species composition was related to topography at the coarsest scales and insolation at finer scales. The non-environmental fraction of the spatial variation in species composition had a complex relationship with several species traits, suggesting a scale-dependent link to biological processes, particularly dispersal. Finally, we tested, at different spatial scales, the relationships between different components of biodiversity: total sample species richness (gamma diversity), mean species .richness (alpha diversity), measured in nested subsamples, and differences in species composition between subsamples (beta diversity). The pairwise relationships between alpha, beta and gamma diversity did not follow the expected patterns, at least at certain scales. Our result indicated a strong scale-dependency of several relationships, and highlighted the importance of the scale ratio when studying biodiversity patterns. Thus, our results bring new insights on the spatial patterns of biodiversity and the possible mechanisms allowing species coexistence. They suggest that biodiversity patterns cannot be explained by any single theory proposed in the literature, but a combination of theories is sufficient. Spatial structure plays a crucial role for all components of biodiversity. Results emphasize the importance of considering multiple spatial scales and multiple scale components when studying species diversity.

Early pregnancy sex steroids and maternal risk of epithelial ovarian cancer.

Well-established associations between reproductive characteristics and epithelial ovarian cancer (EOC) support an involvement of sex steroid hormones in the etiology of EOC. Limited previous studies have evaluated circulating androgens and the risk of EOC, and estrogens and progesterone have been investigated in only one of the previous studies. Furthermore, there is little data on potential heterogeneity in the association between circulating hormones and EOC by histological subgroup. Therefore, we conducted a nested case-control study within the Finnish Maternity Cohort and the Northern Sweden Maternity Cohort to investigate the associations between circulating pre-diagnostic sex steroid concentrations and the histological subtypes of EOC. We identified 1052 EOC cases among cohort members diagnosed after recruitment (1975-2008) and before March 2011. Up to three controls were individually matched to each case (n=2694). Testosterone, androstenedione, 17-hydroxyprogesterone (17-OHP), progesterone, estradiol (E2), and sex hormone-binding globulin levels were measured in serum samples collected during the last pregnancy before EOC diagnosis. We used conditional logistic regression to estimate odds ratios (ORs) and 95% CIs. Associations between hormones and EOC differed with respect to tumor histology and invasiveness. Sex steroid concentrations were not associated with invasive serous tumors; however, doubling of testosterone and 17-OHP concentration was associated with approximately 40% increased risk of borderline serous tumors. A doubling of androgen concentrations was associated with a 50% increased risk of mucinous tumors. The risk of endometrioid tumors increased with higher E2 concentrations (OR: 1.89 (1.20-2.98)). This large prospective study in pregnant women supports a role of sex steroid hormones in the etiology of EOC arising in the ovaries.

Fatores de risco na transmissão do lentivírus caprino pelo sêmen

O objetivo deste trabalho foi avaliar a presença do DNA pró-viral do lentivírus caprino (LVC) em ejaculados de machos infectados naturalmente, e verificar a influência da lavagem do sêmen e da presença de inflamação testicular sobre a carga viral. Foram realizadas oito coletas de sêmen de sete reprodutores soropositivos para o LVC: quatro antes dos animais sofrerem dano testicular e quatro depois. Entre as coletas realizadas na mesma semana, em uma, o ejaculado era lavado, para retirada do plasma seminal, e na outra, não. O DNA pró-viral do LVC foi identificado pela reação em cadeia da polimerase Nested (PCR Nested), e pelo isolamento viral. O vírus foi isolado em 7,1% das amostras. A PCR identificou o DNA pró-viral em 35,7% do total das amostras: 17,9% nas amostras lavadas e 53,6% das amostras de sêmen integrais. O dano ao testículo permite maior fluxo do vírus para o sêmen, pois antes do dano, 21,4% das amostras foram positivas e pós-dano, 50%. A transmissão do LVC pelo sêmen de reprodutores caprinos é potencializada pela presença de inflamações testiculares e pelo fato de o sêmen criopreservado conter o LVC na forma infectante.

Deciphering the global organization of clustering in real complex networks

We uncover the global organization of clustering in real complex networks. To this end, we ask whether triangles in real networks organize as in maximally random graphs with given degree and clustering distributions, or as in maximally ordered graph models where triangles are forced into modules. The answer comes by way of exploring m-core landscapes, where the m-core is defined, akin to the k-core, as the maximal subgraph with edges participating in at least m triangles. This property defines a set of nested subgraphs that, contrarily to k-cores, is able to distinguish between hierarchical and modular architectures. We find that the clustering organization in real networks is neither completely random nor ordered although, surprisingly, it is more random than modular. This supports the idea that the structure of real networks may in fact be the outcome of self-organized processes based on local optimization rules, in contrast to global optimization principles.

Circulating sex steroids during pregnancy and maternal risk of non-epithelial ovarian cancer.

BACKGROUND: Sex steroid hormones have been proposed to play a role in the development of non-epithelial ovarian cancers (NEOC) but so far no direct epidemiological data are available.METHODS: A case-control study was nested within the Finnish Maternity Cohort, the world's largest bio-repository of serum specimens from pregnant women. Study subjects were selected among women who donated a blood sample during a singleton pregnancy that led to the birth of their last child preceding diagnosis of NEOC. Case subjects were 41 women with sex-cord stromal tumors (SCST) and 21 with germ cell tumors (GCT). Three controls, matching the index case for age, parity at the index pregnancy, and date at blood donation were selected (n=171). Odds ratios (OR) and 95% confidence intervals (CI) associated with concentrations of testosterone, androstenedione, 17-OH-progesterone, progesterone, estradiol and sex hormone binding globulin (SHBG) were estimated through conditional logistic regression.RESULTS: For SCST, doubling of testosterone, androstenedione and 17-OH-progesterone concentrations were associated with about 2-fold higher risk of SCST [ORs and 95% CI of 2.16 (1.25-3.74), 2.16 (1.20-3.87), and 2.62 (1.27-5.38), respectively]. These associations remained largely unchanged after excluding women within 2, 4 or 6 years lag-time between blood donation and cancer diagnosis. Sex steroid hormones concentrations were not related to maternal risk of GCT.CONCLUSIONS: This is the first prospective study providing initial evidence that elevated androgens play a role in the pathogenesis of SCST. Impact: Our study may note a particular need for larger confirmatory investigations on sex steroids and NEOC.

Selection of shrimp breeders free of white spot syndrome and infectious hypodermal and hematopoietic necrosis

The objective of this work was to select surviving breeders of Litopenaeus vannamei from white spot syndrome virus (WSSV) outbreak, adapted to local climatic conditions and negatively diagnosed for WSSV and infectious hypodermal and hematopoietic necrosis virus (IHHNV), and to evaluate if this strategy is a viable alternative for production in Santa Catarina, Brazil. A total of 800 males and 800 females were phenotypically selected in a farm pond. Nested-PCR analyses of 487 sexually mature females and 231 sexually mature males showed that 63% of the females and 55% of the males were infected with IHHNV. Animals free of IHHNV were tested for WSSV, and those considered double negative were used for breeding. The post-larvae produced were stocked in nine nursery tanks for analysis. From the 45 samples, with 50 post-larvae each, only two were positive for IHHNV and none for WSSV. Batches of larvae diagnosed free of virus by nested-PCR were sent to six farms. A comparative analysis was carried out in growth ponds, between local post-larvae and post-larvae from Northeast Brazil. Crabs (Chasmagnathus granulata), blue crabs (Callinectes sapidus), and sea hares (Aplysia brasiliana), which are possible vectors of these viruses, were also evaluated. The mean survival was 55% for local post-larvae against 23.4% for post-larvae from the Northeast. Sea hares showed prevalence of 50% and crabs of 67% of WSSV.

JC virus-specific immune responses in human immunodeficiency virus type 1 patients with progressive multifocal leukoencephalopathy.

Progressive multifocal leukoencephalopathy (PML) is a frequently fatal disease caused by uncontrolled polyomavirus JC (JCV) in severely immunodeficient patients. We investigated the JCV-specific cellular and humoral immunity in the Swiss HIV Cohort Study. We identified PML cases (n = 29), as well as three matched controls per case (n = 87), with prospectively cryopreserved peripheral blood mononuclear cells and plasma at diagnosis. Nested controls were matched according to age, gender, CD4(+) T-cell count, and decline. Survivors (n = 18) were defined as being alive for >1 year after diagnosis. Using gamma interferon enzyme-linked immunospot assays, we found that JCV-specific T-cell responses were lower in nonsurvivors than in their matched controls (P = 0.08), which was highly significant for laboratory- and histologically confirmed PML cases (P = 0.004). No difference was found between PML survivors and controls or for cytomegalovirus-specific T-cell responses. PML survivors showed significant increases in JCV-specific T cells (P = 0.04) and immunoglobulin G (IgG) responses (P = 0.005). IgG responses in survivors were positively correlated with CD4(+) T-cell counts (P = 0.049) and negatively with human immunodeficiency virus RNA loads (P = 0.03). We conclude that PML nonsurvivors had selectively impaired JCV-specific T-cell responses compared to CD4(+) T-cell-matched controls and failed to mount JCV-specific antibody responses. JCV-specific T-cell and IgG responses may serve as prognostic markers for patients at risk.

Prospective study of insulin-like growth factor-I, insulin-like growth factor-binding protein 3, genetic variants in the IGF1 and IGFBP3 genes and risk of coronary artery disease.

Although experimental studies have suggested that insulin-like growth factor I (IGF-I) and its binding protein IGFBP-3 might have a role in the aetiology of coronary artery disease (CAD), the relevance of circulating IGFs and their binding proteins in the development of CAD in human populations is unclear. We conducted a nested case-control study, with a mean follow-up of six years, within the EPIC-Norfolk cohort to assess the association between circulating levels of IGF-I and IGFBP-3 and risk of CAD in up to 1,013 cases and 2,055 controls matched for age, sex and study enrolment date. After adjustment for cardiovascular risk factors, we found no association between circulating levels of IGF-I or IGFBP-3 and risk of CAD (odds ratio: 0.98 (95% Cl 0.90-1.06) per 1 SD increase in circulating IGF-I; odds ratio: 1.02 (95% Cl 0.94-1.12) for IGFBP-3). We examined associations between tagging single nucleotide polymorphisms (tSNPs) at the IGF1 and IGFBP3 loci and circulating IGF-I and IGFBP-3 levels in up to 1,133 cases and 2,223 controls and identified three tSNPs (rs1520220, rs3730204, rs2132571) that showed independent association with either circulating IGF-I or IGFBP-3 levels. In an assessment of 31 SNPs spanning the IGF1 or IGFBP3 loci, none were associated with risk of CAD in a meta-analysis that included EPIC-Norfolk and eight additional studies comprising up to 9,319 cases and 19,964 controls. Our results indicate that IGF-I and IGFBP-3 are unlikely to be importantly involved in the aetiology of CAD in human populations.

Univariate versus multivariate modeling of panel data

Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LFand WF). The two formats suggest two alternative model approaches for analyzing paneldata: (i) univariate regression with varying intercept; and (ii) multivariate regression withlatent variables (a particular case of structural equation model, SEM). The present papercompares the two approaches showing in which circumstances they yield equivalent?insome cases, even numerically equal?results. We show that the univariate approach givesresults equivalent to the multivariate approach when restrictions of time invariance (inthe paper, the TI assumption) are imposed on the parameters of the multivariate model.It is shown that the restrictions implicit in the univariate approach can be assessed bychi-square difference testing of two nested multivariate models. In addition, commontests encountered in the econometric analysis of panel data, such as the Hausman test, areshown to have an equivalent representation as chi-square difference tests. Commonalitiesand differences between the univariate and multivariate approaches are illustrated usingan empirical panel data set of firms' profitability as well as a simulated panel data.

Measuring the relative effect of factors affecting species distribution model predictions

1. Species distribution models are increasingly used to address conservation questions, so their predictive capacity requires careful evaluation. Previous studies have shown how individual factors used in model construction can affect prediction. Although some factors probably have negligible effects compared to others, their relative effects are largely unknown. 2. We introduce a general "virtual ecologist" framework to study the relative importance of factors involved in the construction of species distribution models. 3. We illustrate the framework by examining the relative importance of five key factors-a missing covariate, spatial autocorrelation due to a dispersal process in presences/absences, sample size, sampling design and modeling technique-in a real study framework based on plants in a mountain landscape at regional scale, and show that, for the parameter values considered here, most of the variation in prediction accuracy is due to sample size and modeling technique. Contrary to repeatedly reported concerns, spatial autocorrelation has only comparatively small effects. 4. This study shows the importance of using a nested statistical framework to evaluate the relative effects of factors that may affect species distribution models.

Problems of allometric scaling analysis: examples from mammalian reproductive biology.

Biological scaling analyses employing the widely used bivariate allometric model are beset by at least four interacting problems: (1) choice of an appropriate best-fit line with due attention to the influence of outliers; (2) objective recognition of divergent subsets in the data (allometric grades); (3) potential restrictions on statistical independence resulting from phylogenetic inertia; and (4) the need for extreme caution in inferring causation from correlation. A new non-parametric line-fitting technique has been developed that eliminates requirements for normality of distribution, greatly reduces the influence of outliers and permits objective recognition of grade shifts in substantial datasets. This technique is applied in scaling analyses of mammalian gestation periods and of neonatal body mass in primates. These analyses feed into a re-examination, conducted with partial correlation analysis, of the maternal energy hypothesis relating to mammalian brain evolution, which suggests links between body size and brain size in neonates and adults, gestation period and basal metabolic rate. Much has been made of the potential problem of phylogenetic inertia as a confounding factor in scaling analyses. However, this problem may be less severe than suspected earlier because nested analyses of variance conducted on residual variation (rather than on raw values) reveals that there is considerable variance at low taxonomic levels. In fact, limited divergence in body size between closely related species is one of the prime examples of phylogenetic inertia. One common approach to eliminating perceived problems of phylogenetic inertia in allometric analyses has been calculation of 'independent contrast values'. It is demonstrated that the reasoning behind this approach is flawed in several ways. Calculation of contrast values for closely related species of similar body size is, in fact, highly questionable, particularly when there are major deviations from the best-fit line for the scaling relationship under scrutiny.

Personality and job stress: a comparison of direct effects on parenting

The impact of personality and job characteristics on parental rearing styles was compared in 353 employees. Hypotheses concerning the relationships between personality and job variables were formulated in accordance with findings in past research and the Belsky’s model (1984). Structural equation nested models showed that Aggression-hostility, Sociability and job Demand were predictive of Rejection and Emotional Warmth parenting styles, providing support for some of the hypothesized relationships. The findings suggest a well-balanced association of personality variables with both parenting styles: Aggression-Hostility was positively related to Rejection and negatively to Emotional Warmth, whereas Sociability was positively related to Emotional Warmth and negatively related to Rejection. Personality dimensions explained a higher amount of variance in observed parenting styles. However, a model that considered both, personality and job dimensions as antecedent variables of parenting was the best representation of observed data, as both systems play a role in the prediction of parenting behavior.