855 resultados para Pareto Frontier
Resumo:
The paper discusses the taxonomy and autogenesis of the cycle of early ‘barrow cultures’ developed by the local communities of the middle Dniester Area or, in a broader comparative context, the north-western Black Sea Coast, in the 4th/3rd-2nd millennium BC . The purpose of the study is to conduct an analytical and conceptual entry point to the research questions of the dniester Contact area, specifically the contacts between autochthonous ‘late Eneolithic’ communities (Yamnaya, Catacomb and Babyno cultures) and incoming communities from the Baltic basin . The discussion of these cultures continues in other papers presented in this volume of Baltic-Pontic Studies.
Resumo:
The article presents the present state of research on the general issue of the dniester region of cultural contacts between communities settling the Baltic and Pontic drainage basins . Some five domains of research shall be brought to discussion in which it is possible to see fresh opportunities for archaeological study, on the basis of ‘Yampil studies’ on dniester-Podolia (forest-steppe) barrow-culture ceremonial centres from the latter half of the 4th millennium and first half of the 3rd millennium BC . This relates to the peoples of the Eneolithic and the Early Bronze age . in terms of topogenesis, embracing the Pontic-Tripolye, Yamnaya and Catacomb cultures, as well as Globular amphora and Corded ware in central prehistoric Europe .
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An early decision market is governed by rules that allow each student to apply to (at most) one college and require the student to attend this college if admitted. This market is ubiquitous in college admissions in the United States. We model this market as an extensive-form game of perfect information and study a refinement of subgame perfect equilibrium (SPE) that induces undominated Nash equilibria in every subgame (SPUE). Our main result shows that this game can be used to define a decentralized matching mechanism that weakly Pareto dominates student-proposing deferred acceptance.
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In this paper, we consider Preference Inference based on a generalised form of Pareto order. Preference Inference aims at reasoning over an incomplete specification of user preferences. We focus on two problems. The Preference Deduction Problem (PDP) asks if another preference statement can be deduced (with certainty) from a set of given preference statements. The Preference Consistency Problem (PCP) asks if a set of given preference statements is consistent, i.e., the statements are not contradicting each other. Here, preference statements are direct comparisons between alternatives (strict and non-strict). It is assumed that a set of evaluation functions is known by which all alternatives can be rated. We consider Pareto models which induce order relations on the set of alternatives in a Pareto manner, i.e., one alternative is preferred to another only if it is preferred on every component of the model. We describe characterisations for deduction and consistency based on an analysis of the set of evaluation functions, and present algorithmic solutions and complexity results for PDP and PCP, based on Pareto models in general and for a special case. Furthermore, a comparison shows that the inference based on Pareto models is less cautious than some other types of well-known preference model.
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The present study explores EUropean geopolitical agency in a distinct spatio-temporal context: the Arctic region of the early 21st century. Thus, it provides an in-depth analysis of the European Union’s process to construct EUropean legitimacy and credibility in its ‘Northern Neighbourhood’ between 2008 and 2014. Embedded in a conceptual and methodological framework using critical geopolitics, this study assesses the strategic policy reasoning of the EU and the implicit geopolitical discourses that guide and determine a particular line of argumentation so as to claim a ‘legitimate’ role in the Arctic and accordingly construct a distinct ‘EUropean Arctic space’. In doing so, it establishes a clearer picture on the (narrated) regional interests of the EU and the related developed policy and concrete steps taken in order to get hold of these interests. Eventually, the analysis gets to the conceptual bottom of what exactly fashioned the EU with geopolitical agency in the circumpolar North. As a complementary explanation, this study provides a thick description of the area under scrutiny – the Arctic region – in order to explicate the systemic context that conditioned the EU’s regional demeanour and action. Elucidated along the lines of Arctic history and identity, rights, interests and responsibility, it delineates the emergence of the Arctic as a region of and for geopolitics. The findings indicate that the sui generis character of the Arctic as EUropean neighbourhood essentially determined the EU’s regional performance. It explicates that the Union’s ‘traditional’ geopolitical models of civilian or normative power got entangled in a fluid state of Arctic affairs: a distinct regional system, characterised by few strong state actors with pronounced national Arctic interests and identities, and an indefinite local context of environmental changes, economic uncertainties and social challenges. This study applies critical geopolitics in a Political Science context and essentially contributes to a broader understanding of EU foreign policy construction and behaviour. Ultimately, it offers an interdisciplinary approach on how to analyse EU external action by explicitly taking into account the internal and external social processes that ultimately condition a certain EUropean foreign policy performance.
Resumo:
An early decision market is governed by rules that allow each student to apply to (at most) one college and require the student to attend this college if admitted. This market is ubiquitous in college admissions in the United States. We model this market as an extensive-form game of perfect information and study a refinement of subgame perfect equilibrium (SPE) that induces undominated Nash equilibria in every subgame (SPUE). Our main result shows that this game can be used to define a decentralized matching mechanism that weakly Pareto dominates student-proposing deferred acceptance.
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In the last two decades, authors have begun to expand classical stochastic frontier (SF) models in order to include also some spatial components. Indeed, firms tend to concentrate in clusters, taking advantage of positive agglomeration externalities due to cooperation, shared ideas and emulation, resulting in increased productivity levels. Until now scholars have introduced spatial dependence into SF models following two different paths: evaluating global and local spatial spillover effects related to the frontier or considering spatial cross-sectional correlation in the inefficiency and/or in the error term. In this thesis, we extend the current literature on spatial SF models introducing two novel specifications for panel data. First, besides considering productivity and input spillovers, we introduce the possibility to evaluate the specific spatial effects arising from each inefficiency determinant through their spatial lags aiming to capture also knowledge spillovers. Second, we develop a very comprehensive spatial SF model that includes both frontier and error-based spillovers in order to consider four different sources of spatial dependence (i.e. productivity and input spillovers related to the frontier function and behavioural and environmental correlation associated with the two error terms). Finally, we test the finite sample properties of the two proposed spatial SF models through simulations, and we provide two empirical applications to the Italian accommodation and agricultural sectors. From a practical perspective, policymakers, based on results from these models, can rely on precise, detailed and distinct insights on the spillover effects affecting the productive performance of neighbouring spatial units obtaining interesting and relevant suggestions for policy decisions.
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Objetivou-se com este trabalho utilizar regras de associação para identificar forças de mercado que regem a comercialização de touros com avaliação genética pelo programa Nelore Brasil. Essas regras permitem evidenciar padrões implícitos nas transações de grandes bases de dados, indicando causas e efeitos determinantes da oferta e comercialização de touros. Na análise foram considerados 19.736 registros de touros comercializados, 17 fazendas e 15 atributos referentes às diferenças esperadas nas progênies dos reprodutores, local e época da venda. Utilizou-se um sistema com interface gráfica usuário-dirigido que permite geração e seleção interativa de regras de associação. Análise de Pareto foi aplicada para as três medidas objetivas (suporte, confiança e lift) que acompanham cada uma das regras de associação, para validação das mesmas. Foram geradas 2.667 regras de associação, 164 consideradas úteis pelo usuário e 107 válidas para lift ≥ 1,0505. As fazendas participantes do programa Nelore Brasil apresentam especializações na oferta de touros, segundo características para habilidade materna, ganho de peso, fertilidade, precocidade sexual, longevidade, rendimento e terminação de carcaça. Os perfis genéticos dos touros são diferentes para as variedades padrão e mocho. Algumas regiões brasileiras são nichos de mercado para touros sem registro genealógico. A análise de evolução de mercado sugere que o mérito genético total, índice oficial do programa Nelore Brasil, tornou-se um importante índice para comercialização dos touros. Com o uso das regras de associação, foi possível descobrir forças do mercado e identificar combinações de atributos genéticos, geográficos e temporais que determinam a comercialização de touros no programa Nelore Brasil.
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Context. The chemical composition of extremely metal-poor stars (EMP stars; [Fe/H] < similar to -3) is a unique tracer of early nucleosynthesis in the Galaxy. As such stars are rare, we wish to find classes of luminous stars which can be studied at high spectral resolution. Aims. We aim to determine the detailed chemical composition of the two EMP stars CS 30317-056 and CS 22881-039, originally thought to be red horizontal-branch (RHB) stars, and compare it to earlier results for EMP stars as well as to nucleosynthesis yields from various supernova (SN) models. In the analysis, we discovered that our targets are in fact the two most metal-poor RR Lyrae stars known. Methods. Our detailed abundance analysis, taking into account the variability of the stars, is based on VLT/UVES spectra (R similar or equal to 43 000) and 1D LTE OSMARCS model atmospheres and synthetic spectra. For comparison with SN models we also estimate NLTE corrections for a number of elements. Results. We derive LTE abundances for the 16 elements O, Na, Mg, Al, Si, S, Ca, Sc, Ti, Cr, Mn, Fe, Co, Ni, Sr and Ba, in good agreement with earlier values for EMP dwarf, giant and RHB stars. Li and C are not detected in either star. NLTE abundance corrections are newly calculated for O and Mg and taken from the literature for other elements. The resulting abundance pattern is best matched by model yields for supernova explosions with high energy and/or significant asphericity effects. Conclusions. Our results indicate that, except for Li and C, the surface composition of EMP RR Lyr stars is not significantly affected by mass loss, mixing or diffusion processes; hence, EMP RR Lyr stars should also be useful tracers of the chemical evolution of the early Galactic halo. The observed abundance ratios indicate that these stars were born from an ISM polluted by energetic, massive (25-40 M(circle dot)) and/or aspherical supernovae, but the NLTE corrections for Sc and certain other elements do play a role in the choice of model.
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We have developed a new procedure to search for carbon-enhanced metal-poor (CEMP) stars from the Hamburg/ESO (HES) prism-survey plates. This method employs an extended line index for the CH G band, which we demonstrate to have superior performance when compared to the narrower G-band index formerly employed to estimate G-band strengths for these spectra. Although CEMP stars have been found previously among candidate metal-poor stars selected from the HES, the selection on metallicity undersamples the population of intermediate-metallicity CEMP stars (-2.5 <= [Fe/H] <= -1.0); such stars are of importance for constraining the onset of the s-process in metal-deficient asymptotic giant branch stars (thought to be associated with the origin of carbon for roughly 80% of CEMP stars). The new candidates also include substantial numbers of warmer carbon-enhanced stars, which were missed in previous HES searches for carbon stars due to selection criteria that emphasized cooler stars. A first subsample, biased toward brighter stars (B < 15.5), has been extracted from the scanned HES plates. After visual inspection (to eliminate spectra compromised by plate defects, overlapping spectra, etc., and to carry out rough spectral classifications), a list of 669 previously unidentified candidate CEMP stars was compiled. Follow-up spectroscopy for a pilot sample of 132 candidates was obtained with the Goodman spectrograph on the SOAR 4.1 m telescope. Our results show that most of the observed stars lie in the targeted metallicity range, and possess prominent carbon absorption features at 4300 angstrom. The success rate for the identification of new CEMP stars is 43% (13 out of 30) for [Fe/H] < -2.0. For stars with [Fe/H] < -2.5, the ratio increases to 80% (four out of five objects), including one star with [Fe/H] < -3.0.
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We develop an automated spectral synthesis technique for the estimation of metallicities ([Fe/H]) and carbon abundances ([C/Fe]) for metal-poor stars, including carbon-enhanced metal-poor stars, for which other methods may prove insufficient. This technique, autoMOOG, is designed to operate on relatively strong features visible in even low- to medium-resolution spectra, yielding results comparable to much more telescope-intensive high-resolution studies. We validate this method by comparison with 913 stars which have existing high-resolution and low- to medium-resolution to medium-resolution spectra, and that cover a wide range of stellar parameters. We find that at low metallicities ([Fe/H] less than or similar to -2.0), we successfully recover both the metallicity and carbon abundance, where possible, with an accuracy of similar to 0.20 dex. At higher metallicities, due to issues of continuum placement in spectral normalization done prior to the running of autoMOOG, a general underestimate of the overall metallicity of a star is seen, although the carbon abundance is still successfully recovered. As a result, this method is only recommended for use on samples of stars of known sufficiently low metallicity. For these low- metallicity stars, however, autoMOOG performs much more consistently and quickly than similar, existing techniques, which should allow for analyses of large samples of metal-poor stars in the near future. Steps to improve and correct the continuum placement difficulties are being pursued.
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The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006-2050) impacts on carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO(2)-equivalents (CO(2)-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO(2)-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.
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The Cerrado and Amazon regions of Brazil are probably the largest agricultural frontier of the world, and Could be a sink or source for C depending on the net effect of land use change and subsequent management on soil organic C pools. We evaluated the effects of agricultural management systems on soil organic C (SOC) stocks in the Brazilian states of Rondonia and Mato Grosso, and derived regional specific factors for soil C stock change associated with different management systems. We used 50 observations (data points) in this study, including 42 dealing with annual cropping practices and 8 dealing with perennial cropping, and analyzed the data in linear mixed-effect models. No tillage (NT) systems in Cerrado areas increased SOC Storage by 1.08 +/- 0.06 relative to SOC stocks under native conditions, while SOC storage increased by a modest factor of 1.01 +/- 0.17 in Cerradao and Amazon Forest conditions. Full tillage (FT) had negative effect on SOC storage relative to NT, decreasing SOC stocks by a factor of 0.94 +/- 0.04. but did not significantly reduce SOC stocks relative to native levels when adopted in the Cerrado region. Perennial cropping had a minimal impact on SOC stocks, estimated at a factor Value of 0.98 +/- 0.14, suggesting these systems maintain about 98% of the SOC stock found under native vegetation. The results Suggest that NT adoption may be increasing SOC with land use change from native vegetation to cropland management in the Cerrado region of Brazil. (C) 2009 Elsevier B.V. All rights reserved.
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A rapid method for classification of mineral waters is proposed. The discrimination power was evaluated by a novel combination of chemometric data analysis and qualitative multi-elemental fingerprints of mineral water samples acquired from different regions of the Brazilian territory. The classification of mineral waters was assessed using only the wavelength emission intensities obtained by inductively coupled plasma optical emission spectrometry (ICP OES), monitoring different lines of Al, B, Ba, Ca, Cl, Cu, Co, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sb, Si, Sr, Ti, V, and Zn, and Be, Dy, Gd, In, La, Sc and Y as internal standards. Data acquisition was done under robust (RC) and non-robust (NRC) conditions. Also, the combination of signal intensities of two or more emission lines for each element were evaluated instead of the individual lines. The performance of two classification-k-nearest neighbor (kNN) and soft independent modeling of class analogy (SIMCA)-and preprocessing algorithms, autoscaling and Pareto scaling, were evaluated for the ability to differentiate between the various samples in each approach tested (combination of robust or non-robust conditions with use of individual lines or sum of the intensities of emission lines). It was shown that qualitative ICP OES fingerprinting in combination with multivariate analysis is a promising analytical tool that has potential to become a recognized procedure for rapid authenticity and adulteration testing of mineral water samples or other material whose physicochemical properties (or origin) are directly related to mineral content.
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The purpose of this paper is to propose a multiobjective optimization approach for solving the manufacturing cell formation problem, explicitly considering the performance of this said manufacturing system. Cells are formed so as to simultaneously minimize three conflicting objectives, namely, the level of the work-in-process, the intercell moves and the total machinery investment. A genetic algorithm performs a search in the design space, in order to approximate to the Pareto optimal set. The values of the objectives for each candidate solution in a population are assigned by running a discrete-event simulation, in which the model is automatically generated according to the number of machines and their distribution among cells implied by a particular solution. The potential of this approach is evaluated via its application to an illustrative example, and a case from the relevant literature. The obtained results are analyzed and reviewed. Therefore, it is concluded that this approach is capable of generating a set of alternative manufacturing cell configurations considering the optimization of multiple performance measures, greatly improving the decision making process involved in planning and designing cellular systems. (C) 2010 Elsevier Ltd. All rights reserved.