879 resultados para Multi Criteria Decision Analysis
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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.
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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.
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The recognition of pathogen-derived structures by C-type lectins and the chemotactic activity mediated by the CCL2/CCR2 axis are critical steps in determining the host immune response to fungi. The present study was designed to investigate whether the presence of single nucleotide polymorphisms (SNPs) within DC-SIGN, Dectin-1, Dectin-2, CCL2 and CCR2 genes influence the risk of developing Invasive Pulmonary Aspergillosis (IPA). Twenty-seven SNPs were selected using a hybrid functional/tagging approach and genotyped in 182 haematological patients, fifty-seven of them diagnosed with proven or probable IPA according to the 2008 EORTC/MSG criteria. Association analysis revealed that carriers of the Dectin-1(rs3901533 T/T) and Dectin-1(rs7309123 G/G) genotypes and DC-SIGN(rs4804800 G), DC-SIGN(rs11465384 T), DC-SIGN(7248637 A) and DC-SIGN(7252229 C) alleles had a significantly increased risk of IPA infection (OR = 5.59 95%CI 1.37-22.77; OR = 4.91 95%CI 1.52-15.89; OR = 2.75 95%CI 1.27-5.95; OR = 2.70 95%CI 1.24-5.90; OR = 2.39 95%CI 1.09-5.22 and OR = 2.05 95%CI 1.00-4.22, respectively). There was also a significantly increased frequency of galactomannan positivity among patients carrying the Dectin-1(rs3901533_T) allele and Dectin-1(rs7309123_G/G) genotype. In addition, healthy individuals with this latter genotype showed a significantly decreased level of Dectin-1 mRNA expression compared to C-allele carriers, suggesting a role of the Dectin-1(rs7309123) polymorphism in determining the levels of Dectin-1 and, consequently, the level of susceptibility to IPA infection. SNP-SNP interaction (epistasis) analysis revealed significant interactions models including SNPs in Dectin-1, Dectin-2, CCL2 and CCR2 genes, with synergistic genetic effects. Although these results need to be further validated in larger cohorts, they suggest that Dectin-1, DC-SIGN, Dectin-2, CCL2 and CCR2 genetic variants influence the risk of IPA infection and might be useful in developing a risk-adapted prophylaxis.
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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).
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Landscape is an example of a non-market good where no metrics exist to measure its quality. The paper proposes an original methodology to nevertheless estimate scope variables in those circumstances, allowing then to better test if people's willingnesstopay for such good is sensitive to the scope. The methodology is based on techniques developed in the context of multicriteria decision analysis. It is applied to assess the quality of the landscape of several Swiss alpine resorts. This assessment is then used as an explanatory variable in a hedonic price function to explain the rent of apartments and to derive an implicit price of the landscape quality.
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This document contains a report and summary of the field research activities in a rural community of rice farmers in Kampot province, Cambodia in 2011, which I conducted within the context of my PhD research at ICTA-UAB (Institute of Environmental Science and Technology, Autonomous University of Barcelona, Spain). The purpose of the field research was to gather data for a MuSIASEM analysis (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism) at the village and household level, in order to analyze the multidimensional challenges that small farmers may face nowadays within the context of global rural change and declining access to land. While the literature on MuSIASEM offers a great variety of theoretical explanations and practical applications, there is little information available for students regarding the practical steps required for doing a MuSIASEM analysis at the local level. Within this context, this report offers not only a documentation of the field research design and data collection methods, but further provides a general overview on some organizational and preparative aspects, including some personal reflections, that one may face when preparing and conducting field research for MuSIASEM analysis. In summary, this document thus serves three objectives: (i) to assure methodological transparency for the future work, based on the collected data during field research, (ii) to share my personal experience on the preparative and practical steps required for field research and data collection for a MuSIASEM analysis at the local level, and (iii) to make available for the further interested reader some more detailed background information on the case study village.
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When one wishes to implement public policies, there is a previous need of comparing different actions and valuating and evaluating them to assess their social attractiveness. Recently the concept of well-being has been proposed as a multidimensional proxy for measuring societal prosperity and progress; a key research topic is then on how we can measure and evaluate this plurality of dimensions for policy decisions. This paper defends the thesis articulated in the following points: 1. Different metrics are linked to different objectives and values. To use only one measurement unit (on the grounds of the so-called commensurability principle) for incorporating a plurality of dimensions, objectives and values, implies reductionism necessarily. 2. Point 1) can be proven as a matter of formal logic by drawing on the work of Geach about moral philosophy. This theoretical demonstration is an original contribution of this article. Here the distinction between predicative and attributive adjectives is formalised and definitions are provided. Predicative adjectives are further distinguished into absolute and relative ones. The new concepts of set commensurability and rod commensurability are introduced too. 3. The existence of a plurality of social actors, with interest in the policy being assessed, causes that social decisions involve multiple types of values, of which economic efficiency is only one. Therefore it is misleading to make social decisions based only on that one value. 4. Weak comparability of values, which is grounded on incommensurability, is proved to be the main methodological foundation of policy evaluation in the framework of well-being economics. Incommensurability does not imply incomparability; on the contrary incommensurability is the only rational way to compare societal options under a plurality of policy objectives. 5. Weak comparability can be implemented by using multi-criteria evaluation, which is a formal framework for applied consequentialism under incommensurability. Social Multi-Criteria Evaluation, in particular, allows considering both technical and social incommensurabilities simultaneously.
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Expected utility theory (EUT) has been challenged as a descriptive theoryin many contexts. The medical decision analysis context is not an exception.Several researchers have suggested that rank dependent utility theory (RDUT)may accurately describe how people evaluate alternative medical treatments.Recent research in this domain has addressed a relevant feature of RDU models-probability weighting-but to date no direct test of this theoryhas been made. This paper provides a test of the main axiomatic differencebetween EUT and RDUT when health profiles are used as outcomes of riskytreatments. Overall, EU best described the data. However, evidence on theediting and cancellation operation hypothesized in Prospect Theory andCumulative Prospect Theory was apparent in our study. we found that RDUoutperformed EU in the presentation of the risky treatment pairs in whichthe common outcome was not obvious. The influence of framing effects onthe performance of RDU and their importance as a topic for future researchis discussed.
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This paper studies two important reasons why people violate procedure invariance, loss aversion and scale compatibility. The paper extends previous research on loss aversion and scale compatibility by studying loss aversion and scale compatibility simultaneously, by looking at a new decision domain, medical decision analysis, and by examining the effect of loss aversion and scale compatibility on "well-contemplated preferences." We find significant evidence both of loss aversion and scale compatibility. However, the sizes of the biases due to loss aversion and scale compatibility vary over trade-offs and most participants do not behave consistently according to loss aversion or scale compatibility. In particular, the effect of loss aversion in medical trade-offs decreases with duration. These findings are encouraging for utility measurement and prescriptive decision analysis. There appear to exist decision contexts in which the effects of loss aversion and scale compatibility can be minimized and utilities can be measured that do not suffer from these distorting factors.
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This paper presents a comparison of the changes in the energetic metabolic pattern of China and India, the two most populated countries in the world, with two economies undergoing an important economic transition. The comparison of the changes in the energetic metabolic pattern has the scope to characterize and explain a bifurcation in their evolutionary path in the recent years, using the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach. The analysis shows an impressive transformation of China’s energy metabolism determined by the joining of the WTO in 2001. Since then, China became the largest factory of the world with a generalized capitalization of all sectors ―especially the industrial sector― boosting economic labor productivity as well as total energy consumption. India, on the contrary, lags behind when considering these factors. Looking at changes in the household sector (energy metabolism associated with final consumption) in the case of China, the energetic metabolic rate (EMR) soared in the last decade, also thanks to a reduced growth of population, whereas in India it remained stagnant for the last 40 years. This analysis indicates a big challenge for India for the next decade. In the light of the data analyzed both countries will continue to require strong injections of technical capital requiring a continuous increase in their total energy consumption. When considering the size of these economies it is easy to guess that this may induce a dramatic increase in the price of energy, an event that at the moment will penalize much more the chance of a quick economic development of India.
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Summary: Assessing the impacts of ditch network maintenance on water ecosystems onthe basis of expert knowledge and integrating the assessments into decision analysis
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Abstract: Inverse decision analysis methods in enviromental decision-making - inverse methods
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Embankment subgrade soils in Iowa are generally rated as fair to poor as construction materials. These soils can exhibit low bearing strength, high volumetric instability, and freeze/thaw or wet/dry durability problems. Cement stabilization offers opportunities to improve these soils conditions. The objective of this study was to develop relationships between soil index properties, unconfined compressive strength and cement content. To achieve this objective, a laboratory study was conducted on 28 granular and non-granular materials obtained from 9 active construction sites in Iowa. The materials consisted of glacial till, loess, and alluvium sand. Type I/II portland cement was used for stabilization. Stabilized and unstabilized specimens were prepared using Iowa State University 2 in. by 2 in. compaction apparatus. Specimens were prepared, cured, and tested for unconfined compressive strength (UCS) with and without vacuum saturation. Percent fines content (F200), AASHTO group index (GI), and Atterberg limits were tested before and after stabilization. The results were analyzed using multi-variate statistical analysis to assess influence of the various soil index properties on post-stabilization material properties. Results indicated that F200, liquid limit, plasticity index, and GI of the materials generally decreased with increasing cement content. The UCS of the stabilized specimens increased with increasing cement content, as expected. The average saturated UCS of the unstabilized materials varied between 0 and 57 psi. The average saturated UCS of stabilized materials varied between 44 and 287 psi at 4% cement content, 108 and 528 psi at t 8% cement content, and 162 and 709 psi at 12% cement content. The UCS of the vacuum saturated specimens was on average 1.5 times lower than that of the unsaturated specimens. Multi-variate statistical regression models are provided in this report to predict F200, plasticity index, GI, and UCS after treatment, as a function of cement content and soil index properties.
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PURPOSE: Positron emission tomography with (18)F-fluorodeoxyglucose (FDG-PET) was used to evaluate treatment response in patients with gastrointestinal stromal tumors (GIST) after administration of sunitinib, a multitargeted tyrosine kinase inhibitor, after imatinib failure. PATIENTS AND METHODS: Tumor metabolism was assessed with FDG-PET before and after the first 4 weeks of sunitinib therapy in 23 patients who received one to 12 cycles of sunitinib therapy (4 weeks of 50 mg/d, 2 weeks off). Treatment response was expressed as the percent change in maximal standardized uptake values (SUV). The primary end point of time to tumor progression was compared with early PET results on the basis of traditional Response Evaluation Criteria in Solid Tumors (RECIST) criteria. RESULTS: Progression-free survival (PFS) was correlated with early FDG-PET metabolic response (P < .0001). Using -25% and +25% thresholds for SUV variations from baseline, early FDG-PET response was stratified in metabolic partial response, metabolically stable disease, or metabolically progressive disease; median PFS rates were 29, 16, and 4 weeks, respectively. Similarly, when a single FDG-PET positive/negative was considered after 4 weeks of sunitinib, the median PFS was 29 weeks for SUVs less than 8 g/mL versus 4 weeks for SUVs of 8 g/mL or greater (P < .0001). None of the patients with metabolically progressive disease subsequently responded according to RECIST criteria. Multivariate analysis showed shorter PFS in patients who had higher residual SUVs (P < .0001), primary resistance to imatinib (P = .024), or nongastric GIST (P = .002), regardless of the mutational status of the KIT and PDGFRA genes. CONCLUSION: Week 4 FDG-PET is useful for early assessment of treatment response and for the prediction of clinical outcome. Thus, it offers opportunities to individualize and optimize patient therapy.
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There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current paper proposes an approach for obtaining further numerical evidence on the importance of the results, complementing the substantive criteria, visual analysis, and primary summary measures. This additional evidence consists of obtaining the statistical significance of the outcome when referred to the corresponding sampling distribution. This sampling distribution is formed by the values of the outcomes (expressed as data nonoverlap, R-squared, etc.) in case the intervention is ineffective. The approach proposed here is intended to offer the outcome"s probability of being as extreme when there is no treatment effect without the need for some assumptions that cannot be checked with guarantees. Following this approach, researchers would compare their outcomes to reference values rather than constructing the sampling distributions themselves. The integration of single-case studies is problematic, when different metrics are used across primary studies and not all raw data are available. Via the approach for assigning p values it is possible to combine the results of similar studies regardless of the primary effect size indicator. The alternatives for combining probabilities are discussed in the context of single-case studies pointing out two potentially useful methods one based on a weighted average and the other on the binomial test.