935 resultados para MASS CLASSIFICATION SYSTEMS


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Aims. We present an inversion method based on Bayesian analysis to constrain the interior structure of terrestrial exoplanets, in the form of chemical composition of the mantle and core size. Specifically, we identify what parts of the interior structure of terrestrial exoplanets can be determined from observations of mass, radius, and stellar elemental abundances. Methods. We perform a full probabilistic inverse analysis to formally account for observational and model uncertainties and obtain confidence regions of interior structure models. This enables us to characterize how model variability depends on data and associated uncertainties. Results. We test our method on terrestrial solar system planets and find that our model predictions are consistent with independent estimates. Furthermore, we apply our method to synthetic exoplanets up to 10 Earth masses and up to 1.7 Earth radii, and to exoplanet Kepler-36b. Importantly, the inversion strategy proposed here provides a framework for understanding the level of precision required to characterize the interior of exoplanets. Conclusions. Our main conclusions are (1) observations of mass and radius are sufficient to constrain core size; (2) stellar elemental abundances (Fe, Si, Mg) are principal constraints to reduce degeneracy in interior structure models and to constrain mantle composition; (3) the inherent degeneracy in determining interior structure from mass and radius observations does not only depend on measurement accuracies, but also on the actual size and density of the exoplanet. We argue that precise observations of stellar elemental abundances are central in order to place constraints on planetary bulk composition and to reduce model degeneracy. We provide a general methodology of analyzing interior structures of exoplanets that may help to understand how interior models are distributed among star systems. The methodology we propose is sufficiently general to allow its future extension to more complex internal structures including hydrogen- and water-rich exoplanets.

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A census of 925 U.S. colleges and universities offering masters and doctorate degrees was conducted in order to study the number of elements of an environmental management system as defined by ISO 14001 possessed by small, medium and large institutions. A 30% response rate was received with 273 responses included in the final data analysis. Overall, the number of ISO 14001 elements implemented among the 273 institutions ranged from 0 to 16, with a median of 12. There was no significant association between the number of elements implemented among institutions and the size of the institution (p = 0.18; Kruskal-Wallis test) or among USEPA regions (p = 0.12; Kruskal-Wallis test). The proportion of U.S. colleges and universities that reported having implemented a structured, comprehensive environmental management system, defined by answering yes to all 16 elements, was 10% (95% C.I. 6.6%–14.1%); however 38% (95% C.I. 32.0%–43.8%) reported that they had implemented a structured, comprehensive environmental management system, while 30.0% (95% C.I. 24.7%–35.9%) are planning to implement a comprehensive environmental management system within the next five years. Stratified analyses were performed by institution size, Carnegie Classification and job title. ^ The Osnabruck model, and another under development by the South Carolina Sustainable Universities Initiative, are the only two environmental management system models that have been proposed specifically for colleges and universities, although several guides are now available. The Environmental Management System Implementation Model for U.S. Colleges and Universities developed is an adaptation of the ISO 14001 standard and USEPA recommendations and has been tailored to U.S. colleges and universities for use in streamlining the implementation process. In using this implementation model created for the U.S. research and academic setting, it is hoped that these highly specialized institutions will be provided with a clearer and more cost-effective path towards the implementation of an EMS and greater compliance with local, state and federal environmental legislation. ^

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Childhood overweight can increase the risk of chronic diseases later in life. To determine the prevalence, trends and determinants of overweight among children ages 6-15 years old in Vietnam, we assessed data on body mass index (BMI) and demographic and socio-economic characteristics obtained from the 1992 Vietnam Living Standard Survey (1992 VLSS), the 1997 Vietnam Living Standard Survey (1997 VLSS), and the 2000 General Nutrition Survey (2000 GNS). These surveys used multi-stage cluster sample designs to produce nationally representative samples of Vietnamese children ages 6-15 years in 1992-1993, 1997-1998 and 2000. BMI classification was determined using cut-off values set by the International Obesity Task Force (IOTF). The mean prevalence of at risk of overweight and overweight among Vietnamese children rapidly increased from 0.4% in 1992 to 2.0% in 2000, along with a high prevalence of underweight (33.4% in 2000). Increases in weight, height and BMI varied according to gender, area of residence and socioeconomic status. Age, areas of residence and education of the household head are statistically significant predictors of at risk of overweight and overweight. This study identified the prevalence and trends of weight among children crucial to understanding the prevention of child overweight in Vietnam. ^

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Background. In over 30 years, the prevalence of overweight for children and adolescents has increased across the United States (Barlow et al., 2007; Ogden, Flegal, Carroll, & Johnson, 2002). Childhood obesity is linked with adverse physiological and psychological issues in youth and affects ethnic/minority populations in disproportionate rates (Barlow et al., 2007; Butte et al., 2006; Butte, Cai, Cole, Wilson, Fisher, Zakeri, Ellis, & Comuzzie, 2007). More importantly, overweight in children and youth tends to track into adulthood (McNaughton, Ball, Mishra, & Crawford, 2008; Ogden et al., 2002). Childhood obesity affects body functions such as the cardiovascular, respiratory, gastrointestinal, and endocrine systems, including emotional health (Barlow et al., 2007, Ogden et al., 2002). Several dietary factors have been associated with the development of obesity in children; however, these factors have not been fully elucidated, especially in ethnic/minority children. In particular, few studies have been done to determine the effects of different meal patterns on the development of obesity in children. Purpose. The purpose of the study is to examine the relationships between daily proportions of energy consumed and energy derived from fat across breakfast, lunch, dinner, and snack, and obesity among Hispanic children and adolescents. Methods. A cross-sectional design was used to evaluate the relationship between dietary patterns and overweight status in Hispanic children and adolescents 4-19 years of age who participated in the Viva La Familia Study. The goal of the Viva La Familia Study was to evaluate genetic and environmental factors affecting childhood obesity and its co-morbidities in the Hispanic population (Butte et al., 2006, 2007). The study enrolled 1030 Hispanic children and adolescents from 319 families and examined factors related to increased body weight by focusing on a multilevel analysis of extensive sociodemographic, genetic, metabolic, and behavioral data. Baseline dietary intakes of the children were collected using 24-hour recalls, and body mass index was calculated from measured height and weight, and classified using the CDC standards. Dietary data were analyzed using a GEE population-averaged panel-data model with a cluster variable family identifier to include possible correlations within related data sets. A linear regression model was used to analyze associations of dietary patterns using possible covariates, and to examine the percentage of daily energy coming from breakfast, lunch, dinner, and snack while adjusting for age, sex, and BMI z-score. Random-effects logistic regression models were used to determine the relationship of the dietary variables with obesity status and to understand if the percent energy intake (%EI) derived from fat from all meals (breakfast, lunch, dinner, and snacks) affected obesity. Results. Older children (age 4-19 years) consumed a higher percent of energy at lunch and dinner and less percent energy from snacks compared to younger children. Age was significantly associated with percentage of total energy intake (%TEI) for lunch, as well as dinner, while no association was found by gender. Percent of energy consumed from dinner significantly differed by obesity status, with obese children consuming more energy at dinner (p = 0.03), but no associations were found between percent energy from fat and obesity across all meals. Conclusions. Information from this study can be used to develop interventions that target dietary intake patterns in obesity prevention programs for Hispanic children and adolescents. In particular, intervention programs for children should target dietary patterns with energy intake that is spread throughout the day and earlier in the day. These results indicate that a longitudinal study should be used to further explore the relationship of dietary patterns and BMI in this and other populations (Dubois et al., 2008; Rodriquez & Moreno, 2006; Thompson et al., 2005; Wilson et al., in review, 2008). ^

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The PS2644 deep-sea core sequence, retrieved from the northwestern margin of Iceland and covering the last 86 ka, exhibits high sedimentation rates during the last glacial cycle that allow the clear distinction of Greenland stadial (GS)/ interstadial (GI) cycles in the various proxy records. Abundance records of rhyolitic, basaltic and tachylytic tephra grains reveal several maxima. Tephra grains of all types were geochemically analyzed in 44 levels. A total of 92 tephras with a distinctive character have been defined within the glacial sequence of gravity core PS2644-5, whereas the Holocene record is dominated by reworked Vedde Ash grains and not suitable for tephra stratigraphic work. Of the 92 tephras only 19 geochemical populations have been linked with confidence to previously defined tephras such as from the Vedde Ash, Faeroe Marine Ash Zones (FMAZ) II and III and North Atlantic Ash Zone (NAAZ) II. For the glacial period informal names were given to 78 new tephras, most of which are basaltic tephras. Several of these layers have a unique geochemical character and might become new chronostratigraphic markers in the North Atlantic region. Linking the tephra populations to the volcanic system producing them, respectively, revealed that Icelandic eruptions dominate with 83 tephra geochemical populations and Jan Mayen with 9. Around 48% of the informal tephra layers linked to the Icelandic volcanic province are produced from either the Grimsvötn or the Veidivötn-Bardarbunga volcanic systems. The intervals spanning from Greenland Stadial (GS) 3 to Greenland Interstadial (GI) 4 (24.5-29 ka BP), from GI 8 to GS 10 (36.9-40.5 ka BP) and from GI 14 to GI 15.2 (50-56 ka BP) are the periods with the highest number of eruptions, all of which are associated with known tephra zones.

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Brownfield rehabilitation is an essential step for sustainable land-use planning and management in the European Union. In brownfield regeneration processes, the legacy contamination plays a significant role, firstly because of the persistent contaminants in soil or groundwater which extends the existing hazards and risks well into the future; and secondly, problems from historical contamination are often more difficult to manage than contamination caused by new activities. Due to the complexity associated with the management of brownfield site rehabilitation, Decision Support Systems (DSSs) have been developed to support problem holders and stakeholders in the decision-making process encompassing all phases of the rehabilitation. This paper presents a comparative study between two DSSs, namely SADA (Spatial Analysis and Decision Assistance) and DESYRE (Decision Support System for the Requalification of Contaminated Sites), with the main objective of showing the benefits of using DSSs to introduce and process data and then to disseminate results to different stakeholders involved in the decision-making process. For this purpose, a former car manufacturing plant located in the Brasov area, Central Romania, contaminated chiefly by heavy metals and total petroleum hydrocarbons, has been selected as a case study to apply the two examined DSSs. Major results presented here concern the analysis of the functionalities of the two DSSs in order to identify similarities, differences and complementarities and, thus, to provide an indication of the most suitable integration options.

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This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

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The east coast of the AP is highly influenced by cold and dry air masses stemming from the adjacent Weddell Sea. By the contrary, the west coast jointly with the South Shetland Islands are directly exposed to the humid and relatively warm air masses from the South Pacific Ocean carried by the strong and persistent westerly winds. Systematic glaciological field studies are very scarce on both sides of the AP, among them can be mentioned a mass-balance program performed continuously since summer 1998/99 by the Instituto Antártico Argentino (IAA) on Vega Island, James Ross Archipelago, on the northeastern flank of the AP. Another continuous plurianual glaciological research has been initiated in 2010 jointly by the University of Bonn and the IAA at the Fourcade Glacier on King George Island (KGI) within the framework of the ESF project IMCOAST (FK 03F0617B). Two transects of mass balance stakes were installed from the top of the Warszawa Ice Dome down to the border of the glaciers Fourcade and Polar Club, to serve for calibration and validation of modeling efforts. The stakes were measured at the beginning and end of each summer field campaign in November 2010, February - March 2011, January - March 2012, and especially during the austral winter 2012 up to March 2013 every 10 to 14 days depending on weather conditions. During the austral winter 2013 and until June 2014 the measurements were conducted every 20 to 30 days, weather permitting. Snow density was measured as well in every field trip from June 2012 until June 2104, establishing a rather homogeneous value along the different parts of the glacier. Snow density in late summer, rho_s is usually higher than the one in late winter, rho_w. Seasonal average values were calculated for the area covered by the mass balance stakes, being rho_s= 471 Kg/m**3 and rho_w = 363 Kg/m**3.

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This salinization simulation enables irrigation salinity, capillary rise, rainfall, leaching, salt mitigation strategies via fallowing, and other functions that are addressed in a coupled social-environment model applied to southern Mesopotamia. The simulation is applied to the Modeling Ancient Settlement Systems Project supported by the University of Chicago, Durham University, and Argonne National Laboratory. The simulation can be used for other regions.