149 research outputs found

    A quantitative structure- property relationship of gas chromatographic/mass spectrometric retention data of 85 volatile organic compounds as air pollutant materials by multivariate methods

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    A quantitative structure-property relationship (QSPR) study is suggested for the prediction of retention times of volatile organic compounds. Various kinds of molecular descriptors were calculated to represent the molecular structure of compounds. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR) and artificial neural network (ANN). The stepwise regression was used for the selection of the variables which gives the best-fitted models. After variable selection ANN, MLR methods were used with leave-one-out cross validation for building the regression models. The prediction results are in very good agreement with the experimental values. MLR as the linear regression method shows good ability in the prediction of the retention times of the prediction set. This provided a new and effective method for predicting the chromatography retention index for the volatile organic compounds

    The Economic Impact of the Value Chain of a Marcellus Shale Well

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    The Economic Impact of the Value Chain of a Marcellus Shale Well Site examines the direct economic impact of a Marcellus Shale well located in Southwestern Pennsylvania. This study seeks to fill a critical information gap on the impact of gas drilling and extraction from Marcellus Shale deposits deep underground: an assessment of the economic impacts – emphasizing the direct economic impact, rather than just focusing on the perceived benefits and impacts affecting the region. Our analysis is based on extensive field research, including a site visit and interviews with industry participants. It is further cross-validated by examining similar costs for development of Marcellus Wells by a vertically-integrated exploration and production firm

    Evolutionary dynamics of group formation

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    This is an open access article distributed under the terms of the Creative Commons Attribution License CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Group formation is a quite ubiquitous phenomenon across different animal species, whose individuals cluster together forming communities of diverse size. Previous investigations suggest that, in general, this phenomenon might have similar underlying reasons across the interested species, despite genetic and behavioral differences. For instance improving the individual safety (e.g. from predators), and increasing the probability to get food resources. Remarkably, the group size might strongly vary from species to species, e.g. shoals of fishes and herds of lions, and sometimes even within the same species, e.g. tribes and families in human societies. Here we build on previous theories stating that the dynamics of group formation may have evolutionary roots, and we explore this fascinating hypothesis from a purely theoretical perspective, with a model using the framework of Evolutionary Game Theory. In our model we hypothesize that homogeneity constitutes a fundamental ingredient in these dynamics. Accordingly, we study a population that tries to form homogeneous groups, i.e. composed of similar agents. The formation of a group can be interpreted as a strategy. Notably, agents can form a group (receiving a ‘group payoff’), or can act individually (receiving an ‘individual payoff’). The phase diagram of the modeled population shows a sharp transition between the ‘group phase’ and the ‘individual phase’, characterized by a critical ‘individual payoff’. Our results then support the hypothesis that the phenomenon of group formation has evolutionary roots.Peer reviewedFinal Published versio

    Digital diplomacy : U.S. foreign policy in the information age/ Dizard

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