Implementation of a probabilistic based framework for safety assessment of existing timber elements

The assessment of existing timber structures is often limited to information obtained from non or semi destructive testing, as mechanical testing is in many cases not possible due to its destructive nature. Therefore, the available data provides only an indirect measurement of the reference mechanical properties of timber elements, often obtained through empirical based correlations. Moreover, the data must result from the combination of different tests, as to provide a reliable source of information for a structural analysis. Even if general guidelines are available for each typology of testing, there is still a need for a global methodology allowing to combine information from different sources and infer upon that information in a decision process. In this scope, the present work presents the implementation of a probabilistic based framework for safety assessment of existing timber elements. This methodology combines information gathered in different scales and follows a probabilistic framework allowing for the structural assessment of existing timber elements with possibility of inference and updating of its mechanical properties, through Bayesian methods. The probabilistic based framework is based in four main steps: (i) scale of information; (ii) measurement data; (iii) probability assignment; and (iv) structural analysis. In this work, the proposed methodology is implemented in a case study. Data was obtained through a multi-scale experimental campaign made to old chestnut timber beams accounting correlations of non and semi-destructive tests with mechanical properties. Finally, different inference scenarios are discussed aiming at the characterization of the safety level of the elements.

Nonlinear behavior of gelatin networks reveals a hierarchical structure

We investigate the strain hardening behavior of various gelatin networks-namely physical gelatin gel, chemically cross-linked gelatin gel, and a hybrid gel made of a combination of the former two-under large shear deformations using the pre-stress, strain ramp, and large amplitude oscillations shear protocols. Further, the internal structures of physical gelatin gels and chemically cross-linked gelatin gels were characterized by small angle neutron scattering (SANS) to enable their internal structures to be correlated with their nonlinear rheology. The Kratky plots of SANS data demonstrate the presence of small cross-linked aggregates within the chemically cross-linked network whereas, in the physical gelatin gels, a relatively homogeneous structure is observed. Through model fitting to the scattering data, we were able to obtain structural parameters, such as the correlation length (ξ), the cross-sectional polymer chain radius (Rc) and the fractal dimension (df) of the gel networks. The fractal dimension df obtained from the SANS data of the physical and chemically cross-linked gels is 1.31 and 1.53, respectively. These values are in excellent agreement with the ones obtained from a generalized nonlinear elastic theory that has been used to fit the stress-strain curves. The chemical cross-linking that generates coils and aggregates hinders the free stretching of the triple helix bundles in the physical gels.

Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.

An application of MSIASM to Chinese exosomatic energy metabolism

The methodology of Multi-Scale Integrated The methodology of Multi-Scale Integrated Analysis of Societal Metabolism (MSIASM) is applied to analyze the Chinese economy. This paper presents four tasks: (i) identifying a set of benchmarks that makes it possible to compare various characteristics of the Chinese economy with those of other country groups and the world (level) average; (ii) explaining the differences over the selected set of benchmarks, by looking at the characteristics of the various sub-sectors of the Chinese economy; (iii) understanding existing trends and future feasible future development paths for China by studying the existence of reciprocal constraints between the whole economy and its sub-sectors; and (iv) examining plausible future scenarios of development.

Different trajectories of exosomatic energy metabolism for Brazil, Chile and Venezuela: using the MSIASM approach

Economic development goes hand in hand with an increase in the consumption of natural resources. Some analysts use material flows to describe such relationship [Eurostat 2001, Weisz et al., 2006], or exergy [Ayres et al., 2003]. Instead this paper will use a characterisation of the exosomatic energy metabolism based on expected benchmark values to describe possible constraints to economic development posed by available human time and energy. The aim of the paper is to identify types of exosomatic energy metabolism of different societies to interpret its consequences for economic development. This is done with the application of the accounting methodology called Multi-Scale Integrated Analysis of Societal Metabolism (MSIASM) to the particular case of energy metabolism for the analysis of the economies of Brazil, Chile and Venezuela.

Why Catalonia will see its energy metabolism increase in the near future: an application of MuSIASEM

This paper applies the so-called Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) to the economy of the Spanish region of Catalonia. By applying Georgescu-Roegen's fund-flow model, it arrives at the conclusion that within a context of the end of cheap oil, the current development model based on the growth of low productivity sectors such as services and construction must change. The change is needed not only because of the increasing scarcity of affordable energy carriers, or because of the increasing environmental impact that the present development represents, but also because of an ageing population that demands labour productivity gains. This will imply industry requiring more energy consumption per worker in order to increase its productivity, and therefore its competitiveness. Thus, we conclude that energy intensity, and exosomatic energy metabolism of Catalonia will increase dramatically in the near future unless major conservation efforts are implemented in both the household and transport sectors.

Applications of the MuSIASEM approach to study changes in the metabolic pattern of Catalonia

This document presents an integrated analysis of the performance of Catalonia based on an analysis of how the energy consumption (measured at the societal level for the Catalan Society) is used within both the productive sectors of the economy and the household, to generate added value, jobs, and to guarantee a given level of material standard of living to the population. The trends found in Catalonia are compared to the trends of other European Countries to contextualize the performance of Catalonia with respect to other societies that have followed different paths of economic development. The first part of the document consists of the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach that has been used to provide this integrated analysis of Catalan Society across different scales (starting from an analysis of the specific sectors of the Catalan economy as an Autonomous Community and scaling up to an intra-regional (European Union 14) comparison) and across different dimensions of analyses of energy consumption coupled with added value generation. Within the scope of this study, we observe the various trajectories of changes in the metabolic pattern for Catalonia and the EU14 countries in the Paid Work Sectors composed of namely, the Agricultural Sector, the Productive Sector and the Services and Government Sector also in comparison with the changes in the household sector. The flow intensities of the exosomatic energy and the added value generated for each specific sector are defined per hour of human activity, thus characterized as exosomatic energy (MJ/hour) (or Exosomatic Metabolic Rate) and added value (€/hour) (Economic Labour Productivity) across multiple levels. Within the second part of the document, the possible usage of the MuSIASEM approach to land use analyses (using a multi-level matrix of categories of land use) has been conducted.

Going beyond energy intensity to understand the energy metabolism of nations: the case of Argentina

The link between energy consumption and economic growth has been widely studied in the economic literature. Understanding this relationship is important from both an environmental and a socio-economic point of view, as energy consumption is crucial to economic activity and human environmental impact. This relevance is even higher for developing countries, since energy consumption per unit of output varies through the phases of development, increasing from an agricultural stage to an industrial one and then decreasing for certain service based economies. In the Argentinean case, the relevance of energy consumption to economic development seems to be particularly important. While energy intensity seems to exhibit a U-Shaped curve from 1990 to 2003 decreasing slightly after that year, total energy consumption increases along the period of analysis. Why does this happen? How can we relate this result with the sustainability debate? All these questions are very important due to Argentinean hydrocarbons dependence and due to the recent reduction in oil and natural gas reserves, which can lead to a lack of security of supply. In this paper we study Argentinean energy consumption pattern for the period 1990-2007, to discuss current and future energy and economic sustainability. To this purpose, we developed a conventional analysis, studying energy intensity, and a non conventional analysis, using the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) accounting methodology. Both methodologies show that the development process followed by Argentina has not been good enough to assure sustainability in the long term. Instead of improving energy use, energy intensity has increased. The current composition of its energy mix, and the recent economic crisis in Argentina, as well as its development path, are some of the possible explanations.

Italy's urban waste metabolism

The problem of waste management is causing growing concern due to increasing generation rates, the emissions into soil, water and air, the social conflicts derived from the election of disposal sites and the loss of resources and energy among others. In this work, an innovative methodology is used to enable a better understanding of the waste generation and management system in Italy. Two new waste indicators are built to complement the conventional indicators used by official statistics. Then a multi-scale analysis of the Density of Waste Disposed (DWD) is carried out to highlight the territorial diversity of waste performances and test its contribution to detect plausible risky areas. Starting from Italian regions, the scale down goes on to the provincial level and, only for the region of Campania, the municipal one. First, the analysis shows that the DWD is able to complement the information provided by the conventional waste indicators. Second, the analysis shows the limitations of using a unique institutional solution to waste management problems. In this sense the multi-scale analysis provides with a more realistic picture of Italian waste system than using a single scale.

Re-opening the black box in societal metabolism: the application of MuSIASEM to water

In this paper we address the complexity of the analysis of water use in relation to the issue of sustainability. In fact, the flows of water in our planet represent a complex reality which can be studied using many different perceptions and narratives referring to different scales and dimensions of analysis. For this reason, a quantitative analysis of water use has to be based on analytical methods that are semantically open: they must be able to define what we mean with the term “water” when crossing different scales of analysis. We propose here a definition of water as a resource that deal with the many services it provides to humans and ecosystems. WE argue that water can fulfil so many of them since the element has many characteristics that allow for the resource to be labelled with different attributes, depending on the end use –such as drinkable. Since the services for humans and the functions for ecosystems associated with water flows are defined on different scales but still interconnected it is necessary to organize our assessment of water use across different hierarchical levels. In order to do so we define how to approach the study of water use in the Societal Metabolism, by proposing the Water Metabolism, tganized in three levels: societal level, ecosystem level and global level. The possible end uses we distinguish for the society are: personal/physiological use, household use, economic use. Organizing the study of “water use” across all these levels increases the usefulness of the quantitative analysis and the possibilities of finding relevant and comparable results. To achieve this result, we adapted a method developed to deal with multi-level, multi-scale analysis - the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach - to the analysis of water metabolism. In this paper, we discuss the peculiar analytical identity that “water” shows within multi-scale metabolic studies: water represents a flow-element when considering the metabolism of social systems (at a small scale, when describing the water metabolism inside the society) and a fund-element when considering the metabolism o ecosystems (at a larger scale when describing the water metabolism outside the society). The theoretical analysis is illustrated using two case which characterize the metabolic patterns regarding water use of a productive system in Catalonia and a water management policy in Andarax River Basin in Andalusia.

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (R (adj) (2) > 0.5). 2) Models including PCNM variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation of non-model species under global change.

Kinematics and dynamic complexity of postural transitions in frail elderly subjects.

The aim of this study was to propose a methodology allowing a detailed characterization of body sit-to-stand/stand-to-sit postural transition. Parameters characterizing the kinematics of the trunk movement during sit-to-stand (Si-St) postural transition were calculated using one initial sensor system fixed on the trunk and a data logger. Dynamic complexity of these postural transitions was estimated by fractal dimension of acceleration-angular velocity plot. We concluded that this method provides a simple and accurate tool for monitoring frail elderly and to objectively evaluate the efficacy of a rehabilitation program.

Estimating Gross Value Added (GVA) across multiple scales: theoretical approach and empirical validation

This paper presents an application of the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach to the estimation of quantities of Gross Value Added (GVA) referring to economic entities defined at different scales of study. The method first estimates benchmark values of the pace of GVA generation per hour of labour across economic sectors. These values are estimated as intensive variables –e.g. €/hour– by dividing the various sectorial GVA of the country (expressed in € per year) by the hours of paid work in that same sector per year. This assessment is obtained using data referring to national statistics (top down information referring to the national level). Then, the approach uses bottom-up information (the number of hours of paid work in the various economic sectors of an economic entity –e.g. a city or a province– operating within the country) to estimate the amount of GVA produced by that entity. This estimate is obtained by multiplying the number of hours of work in each sector in the economic entity by the benchmark value of GVA generation per hour of work of that particular sector (national average). This method is applied and tested on two different socio-economic systems: (i) Catalonia (considered level n) and Barcelona (considered level n-1); and (ii) the region of Lima (considered level n) and Lima Metropolitan Area (considered level n-1). In both cases, the GVA per year of the local economic entity –Barcelona and Lima Metropolitan Area – is estimated and the resulting value is compared with GVA data provided by statistical offices. The empirical analysis seems to validate the approach, even though the case of Lima Metropolitan Area indicates a need for additional care when dealing with the estimate of GVA in primary sectors (agriculture and mining).

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

Characterization of lead-recycling facility emissions at various workplaces : major insights for sanitary risks assessment

Most available studies on lead smelter emissions deal with the environmental impact of outdoor particles, but only a few focus on air quality at workplaces. The objective of this study is to physically and chemically characterize the Pb-rich particles emitted at different workplaces in a lead recycling plant. A multi-scale characterization was conducted from bulk analysis to the level of individual particles, to assess the particles properties in relation with Pb speciation and availability. Process PM from various origins were sampled and then compared; namely Furnace and Refining PM respectively present in the smelter and at refinery workplaces, Emissions PM present in channeled emissions.These particles first differed by their morphology and size distribution, with finer particles found in emissions. Differences observed in chemical composition could be explained by the industrial processes. All PM contained the same major phases (Pb, PbS, PbO, PbSO4 and PbO·PbSO4) but differed on the nature and amount of minor phases. Due to high content in PM, Pb concentrations in the CaCl2 extractant reached relatively high values (40 mg.L-1). However, the ratios (soluble/total) of CaCl2 exchangeable Pb were relatively low (< 0.02%) in comparison with Cd (up to 18%). These results highlight the interest to assess the soluble fractions of all metals (minor and major) and discuss both total metal concentrations and ratios for risk evaluations. In most cases metal extractability increased with decreasing size of particles, in particular, lead exchangeability was highest for channeled emissions. Such type of study could help in the choice of targeted sanitary protection procedures and for further toxicological investigations. In the present context, particular attention is given to Emissions and Furnace PM. Moreover, exposure to other metals than Pb should be considered. [Authors]