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Johnston, Robert C. A pilgrim on the trails of the Earth: that's how Gerbertus appears to us in the years preceding his pontificate as well in those, brief and intense, in which he was Pope.

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An ardent pilgrim of faith moved at the same time by vast intellectual interests that allowed him to come into contact with the most important schools of the time, of any cultural tradition; a pilgrim full of love, willing to transmit the enormous heritage of faith and knowledge of which he was custodian. The presence of the illustrious Benedictine is not explicitly documented in the Abbey of San Michele della Chiusa, but the signs of its cultural and ideological influence are evident both in historical memory as in the artistical vestiges of the Sacra: we investigate here, this presence, authoritative, original and versatile, to outline another aspect, still little investigated, of the lesson of Gerbert, monk, scientist, teacher and pastor.

This document, made available in English, French, and Swahili, is one such resource. The focus of this document is a comprehensive behavior change approach that concentrates on the development of skills needed for life, such as… NASA Astrophysics Data System ADS Moreau, Vincent The main objective of the research work is to improve éco slim vartojimas quality of life cycle inventory data by developing a method to estimate missing data and corresponding uncertainties.

Contrary to process-based models of mass and energy balance, this approach consists of statistical estimators which model processes from relatively small samples of usually high variability.

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The research hypothesis is as follows: the so called kriging estimator allows the combined estimation of missing data and their uncertainties in such ways that are more reliable than other linear estimators.

Borrowed from spatial statistics, kriging is an estimator with several advantages, the flexibility associated with a éco slim vartojimas of model function and the exact estimator property.

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In other words, kriging shows no statistical errors when estimating observed values, no data is averaged out. An interpretation of the kriging parameters specific to the problems of data uncertainty, offers more advantages. One parameter of the covariance function accounts for small scale variations of the data and taken as a proxy for uncertainty.

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Whether it be the variety of data sources, the scarcity of the data itself or both, each and every source adds to data variability and uncertainty. The kriging system of equations is therefore modified such as to integrate a factor of uncertainty specific to each observations. Comparisons between the modified and conventional forms of kriging can be drawn.

The procedure is based on the relationship between technical specifications, more readily available independent variables, and the dependent material and energy flows of the processes under consideration. Such material and energy requirements as well as emissions are estimated over the entire life cycle of products and processes. The needs for additional data are relatively low compared to other approaches, namely extended input output analysis.

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For many products, processes and services, electricity generation and consumption éco slim vartojimas for a sizable share of the impacts. Hydroelectricity in particular is poorly represented within existing inventory data since production facilities vary considerably from one location to another.

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In other words, generic hydropower plants do not exist. Contrary to inventory flows, the technical specifications or characteristic variables of hydropower plants, such as the installed capacity, annual production or surface area of adjacent reservoirs, are usually publicly available.

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The kriging model is first tested on a data set which represents windmills of varying power capacity before it is applied to hydroelectricity.

The experiment is divided according to data availability, on one hand the energy and materials required during construction, operation and maintenance of hydropower plants.

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The results show that estimation of inventory data can be improved thanks to kriging. When comparing different forms of kriging and linear regression, the kriging estimates are not only more precise but the standard deviations also cover the data more accurately.

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Where éco slim vartojimas observed data are incomplete, that is where inventory flows are missing for part of the observations, the estimation errors are lower for éco slim vartojimas than linear regression.

Moreover, univariate kriging of inventory flows based on two characteristic variables, shows lower errors than its multivariate kin, cokriging. On average the statistical errors calculated from cross-validation are lower for kriging than they are for linear regression, whether the observed data are complete or not.

The application of several characteristic variables improves the quality of the estimates when they are positively correlated. In addition, the modified form of kriging which accounts for degrees of uncertainty specific to each observations, results in a reduction in the variations of the estimated inventory data.

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That is, data variability is incorporated directly in the model. Estimates closer to more reliable observations are shown to be less uncertain and vice versa.

Je souhaite la bienvenue à M. Ernest Urtasun, ponente. Por ello, el papel del BEI va a ser esencial y esto hace especial este año el informe, también porque estamos a las puertas del inicio del denominado Plan Juncker. El hecho de que este informe se haya redactado en paralelo —como decía— al Plan Juncker ha hecho que esto ocupe nuestra atención, obviamente. El segundo bloque de cuestiones que tratamos en el informe es la evaluación de la Project Bond Initiative, que ha supuesto una buena parte de nuestro trabajo.

For each of the data éco slim vartojimas, different relationships between dependent and independent variables are tested, for example the linear, exponential, spherical and cubic éco slim vartojimas functions as well as a range of parameter values. For the analysis of electrical generation technologies, perte de poids avant et après tumblr 2021 results imply better estimates for data that are difficult to sample and therefore a simplified data collection process.

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In the case of site specific or variable processes such as hydroelectricity, the estimation of éco slim vartojimas data with kriging accounting for such data variability, proves more representative of the geographical or technological context. The quality of inventory data is consequently higher.

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Even if kriging has several advantages and its estimation errors are lower on average, some limitations to its application exist. Abstract shortened by UMI.