863 resultados para multi-attribute analysis
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A multi-residue gas chromatography-mass spectrometry method was developed in order to evaluate the presence of 39 pesticides of different chemical families (organophosphorus, triazines, imidazole, organochlorine), as well as some of their transformation products, in surface water samples from Ria de Aveiro. Ria de Aveiro is an estuarine coastal lagoon, located in the northern west region of Portugal, which receives inputs from agriculture, urban and industrial activities. The analytical method was developed and validated according international guidelines and showed good linearity, with correlation coefficients higher than 0.9949 for all compounds, adequate precision and accuracy, and high sensitivity. Pesticides were chosen from the priority pollutants list of the Directive 2008/105/EC of the European Parliament and of the Council (on environmental quality standards in the field of water policy), or were selected due their common use in agricultural practices. Some of these 39 pesticides are, or are suspected to be, endocrine disruptor compounds (EDCs), being capable of altering the endocrine system of wildlife and humans, causing form malfunction and ultimately health problems. Even those pesticides which are not EDCs, are known to be awfully toxic and have a recognised impact in human health. The aquatic environment is particularly susceptible to pollution due to intentional and accidental release of chemicals to water [3]. Pesticide contamination of surface water is a national issue as it is often used as drinking water. This concern is especially important in rural agricultural areas where population uses small private water supplies, regularly without any laboratory surveillance. The study was performed in seven sampling points and the results showed a considerable concern pesticide contamination of all samples.
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Landslides are common features of the landscape of the north-central Apennine mountain range and cause frequent damage to human facilities and infrastructure. Most of these landslides move periodically with moderate velocities and, only after particular rainfall events, some accelerate abruptly. Synthetic aperture radar interferometry (InSAR) provides a particularly convenient method for studying deforming slopes. We use standard two-pass interferometry, taking advantage of the short revisit time of the Sentinel-1 satellites. In this paper we present the results of the InSAR analysis developed on several study areas in central and Northern Italian Apennines. The aims of the work described within the articles contained in this paper, concern: i) the potential of the standard two-pass interferometric technique for the recognition of active landslides; ii) the exploration of the potential related to the displacement time series resulting from a two-pass multiple time-scale InSAR analysis; iii) the evaluation of the possibility of making comparisons with climate forcing for cognitive and risk assessment purposes. Our analysis successfully identified more than 400 InSAR deformation signals (IDS) in the different study areas corresponding to active slope movements. The comparison between IDSs and thematic maps allowed us to identify the main characteristics of the slopes most prone to landslides. The analysis of displacement time series derived from monthly interferometric stacks or single 6-day interferograms allowed the establishment of landslide activity thresholds. This information, combined with the displacement time series, allowed the relationship between ground deformation and climate forcing to be successfully investigated. The InSAR data also gave access to the possibility of validating geographical warning systems and comparing the activity state of landslides with triggering probability thresholds.
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In the mid-long-term after a nuclear accident, the contamination of drinking water sources, fish and other aquatic foodstuffs, irrigation supplies and people?s exposure during recreational activities may create considerable public concern, even though dose assessment may in certain situations indicate lesser importance than for other sources, as clearly experienced in the aftermath of past accidents. In such circumstances there are a number of available countermeasure options, ranging from specific chemical treatment of lakes to bans on fish ingestion or on the use of water for crop irrigation. The potential actions can be broadly grouped into four main categories, chemical, biological, physical and social. In some cases a combination of actions may be the optimal strategy and a decision support system (DSS) like MOIRA-PLUS can be of great help to optimise a decision. A further option is of course not to take any remedial actions, although this may also have significant socio-economic repercussions which should be adequately evaluated. MOIRA-PLUS is designed to allow for a reliable assessment of the long-term evolution of the radiological situation and of feasible alternative rehabilitation strategies, including an objective evaluation of their social, economic and ecological impacts in a rational and comprehensive manner. MOIRA-PLUS also features a decision analysis methodology, making use of multi-attribute analysis, which can take into account the preferences and needs of different types of stakeholders. The main functions and elements of the system are described summarily. Also the conclusions from end-user?s experiences with the system are discussed, including exercises involving the organizations responsible for emergency management and the affected services, as well as different local and regional stakeholders. MOIRAPLUS has proven to be a mature system, user friendly and relatively easy to set up. It can help to better decisionmaking by enabling a realistic evaluation of the complete impacts of possible recovery strategies. Also, the interaction with stakeholders has allowed identifying improvements of the system that have been recently implemented.
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Concern regarding hydrological resources has been a theme of growing importance in Brazil, associating the development of new management policies and maintenance of natural areas related to rivers. An efficient way to maintain natural areas around rivers has been the development of greenways, and some cites have already adopted specific legislation in this respect. Following this growing evolution in the treatment of hydrological resources, this study was carried out to demarcate a greenway along the Corumbatai River in the state of São Paulo, Using multi-criteria analysis in a GIS environment. First, thematic maps were elaborated based on Landsat 7 satellite, aerial photographs and digital topographic base, Supported by field activities. With the use of multi-criteria analysis, for which ad hoe consultations were conducted to attribute weights to the thematic maps, a suitability map was elaborated for the allocation of the greenway. Sites that should be included in the greenway were also selected, such as areas appropriate for leisure activities, and ecologically important areas. Based on the suitability map, a pathway analysis was done, connecting the relevant points of interest, thus generating a greenway that runs along the Corumbatai River, with the aim of contributing to the conservation of this important hydrological resource. (c) 2007 Elsevier B.V. All rights reserved.
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Decisions taken in modern organizations are often multi-dimensional, involving multiple decision makers and several criteria measured on different scales. Multiple Criteria Decision Making (MCDM) methods are designed to analyze and to give recommendations in this kind of situations. Among the numerous MCDM methods, two large families of methods are the multi-attribute utility theory based methods and the outranking methods. Traditionally both method families require exact values for technical parameters and criteria measurements, as well as for preferences expressed as weights. Often it is hard, if not impossible, to obtain exact values. Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of methods designed to help in this type of situations where exact values are not available. Different variants of SMAA allow handling all types of MCDM problems. They support defining the model through uncertain, imprecise, or completely missing values. The methods are based on simulation that is applied to obtain descriptive indices characterizing the problem. In this thesis we present new advances in the SMAA methodology. We present and analyze algorithms for the SMAA-2 method and its extension to handle ordinal preferences. We then present an application of SMAA-2 to an area where MCDM models have not been applied before: planning elevator groups for high-rise buildings. Following this, we introduce two new methods to the family: SMAA-TRI that extends ELECTRE TRI for sorting problems with uncertain parameter values, and SMAA-III that extends ELECTRE III in a similar way. An efficient software implementing these two methods has been developed in conjunction with this work, and is briefly presented in this thesis. The thesis is closed with a comprehensive survey of SMAA methodology including a definition of a unified framework.
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Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université de Technologie de Troyes
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Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.
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Hypothyroidism is a complex clinical condition found in both humans and dogs, thought to be caused by a combination of genetic and environmental factors. In this study we present a multi-breed analysis of predisposing genetic risk factors for hypothyroidism in dogs using three high-risk breeds-the Gordon Setter, Hovawart and the Rhodesian Ridgeback. Using a genome-wide association approach and meta-analysis, we identified a major hypothyroidism risk locus shared by these breeds on chromosome 12 (p = 2.1x10-11). Further characterisation of the candidate region revealed a shared ~167 kb risk haplotype (4,915,018-5,081,823 bp), tagged by two SNPs in almost complete linkage disequilibrium. This breed-shared risk haplotype includes three genes (LHFPL5, SRPK1 and SLC26A8) and does not extend to the dog leukocyte antigen (DLA) class II gene cluster located in the vicinity. These three genes have not been identified as candidate genes for hypothyroid disease previously, but have functions that could potentially contribute to the development of the disease. Our results implicate the potential involvement of novel genes and pathways for the development of canine hypothyroidism, raising new possibilities for screening, breeding programmes and treatments in dogs. This study may also contribute to our understanding of the genetic etiology of human hypothyroid disease, which is one of the most common endocrine disorders in humans.
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This work explores the multi-element capabilities of inductively coupled plasma - mass spectrometry with collision/reaction cell technology (CCT-ICP-MS) for the simultaneous determination of both spectrally interfered and non-interfered nuclides in wine samples using a single set of experimental conditions. The influence of the cell gas type (i.e. He, He+H2 and He+NH3), cell gas flow rate and sample pre-treatment (i.e. water dilution or acid digestion) on the background-equivalent concentration (BEC) of several nuclides covering the mass range from 7 to 238 u has been studied. Results obtained in this work show that, operating the collision/reaction cell with a compromise cell gas flow rate (i.e. 4 mL min−1) improves BEC values for interfered nuclides without a significant effect on the BECs for non-interfered nuclides, with the exception of the light elements Li and Be. Among the different cell gas mixtures tested, the use of He or He+H2 is preferred over He+NH3 because NH3 generates new spectral interferences. No significant influence of the sample pre-treatment methodology (i.e. dilution or digestion) on the multi-element capabilities of CCT-ICP-MS in the context of simultaneous analysis of interfered and non-interfered nuclides was observed. Nonetheless, sample dilution should be kept at minimum to ensure that light nuclides (e.g. Li and Be) could be quantified in wine. Finally, a direct 5-fold aqueous dilution is recommended for the simultaneous trace and ultra-trace determination of spectrally interfered and non-interfered elements in wine by means of CCT-ICP-MS. The use of the CCT is mandatory for interference-free ultra-trace determination of Ti and Cr. Only Be could not be determined when using the CCT due to a deteriorated limit of detection when compared to conventional ICP-MS.
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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica
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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial
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Based on the presentation and discussion at the 3rd Winter School on Technology Assessment, December 2012, Universidade Nova de Lisboa (Portugal), Caparica Campus, PhD programme on Technology Assessment
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We analysed the relationship between changes in land cover patterns and the Eurasian otter occurrence over the course of about 20 years (1985-2006) using multi-temporal Species Distribution Models (SDMs). The study area includes five river catchments covering most of the otter's Italian range. Land cover and topographic data were used as proxies of the ecological requirements of the otter within a 300-m buffer around river courses. We used species presence, pseudo-absence data, and environmental predictors to build past (1985) and current (2006) SDMs by applying an ensemble procedure through the BIOMOD modelling package. The performance of each model was evaluated by measuring the area under the curve (AUC) of the receiver-operating characteristic (ROC). Multi-temporal analyses of species distribution and land cover maps were performed by comparing the maps produced for 1985 and 2006. The ensemble procedure provided a good overall modelling accuracy, revealing that elevation and slope affected the otter's distribution in the past; in contrast, land cover predictors, such as cultivations and forests, were more important in the present period. During the transition period, 20.5% of the area became suitable, with 76% of the new otter presence data being located in these newly available areas. The multi-temporal analysis suggested that the quality of otter habitat improved in the last 20 years owing to the expansion of forests and to the reduction of cultivated fields in riparian belts. The evidence presented here stresses the great potential of riverine habitat restoration and environmental management for the future expansion of the otter in Italy