Equity and CO2 emissions distribution in climate change integrated assessment

Emissions distribution is a focus variable for the design of future international agreements to tackle global warming. This paper specifically analyses the future path of emissions distribution and its determinants in different scenarios. Whereas our analysis is driven by tools which are typically applied in the income distribution literature and which have recently been applied to the analysis of CO2 emissions distribution, a new methodological approach is that our study is driven by simulations run with a popular regionalised optimal growth climate change model over the 1995-2105 period. We find that the architecture of environmental policies, the implementation of flexible mechanisms and income concentration are key determinants of emissions distribution over time. In particular we find a robust positive relationship between measures of inequalities.

Caracteritaci�� de models funcionals d'��mfores romanes mitjan��ant Finite Element Analysis

Projecte de recerca elaborat a partir d���una estada al Laboratory of Archaeometry del National Centre of Scientific Research ���Demokritos��� d���Atenes, Gr��cia, entre juny i setembre 2006. Aquest estudi s���emmarca dins d���un context m��s ampli d���estudi del canvi tecnol��gic que es documenta en la producci�� d�����mfores de tipologia romana durant els segles I aC i I dC en els territoris costaners de Catalunya. Una part d���aquest estudi contempla el c��lcul de les propietats mec��niques d���aquestes ��mfores i la seva avaluaci�� en funci�� de la tipologia amforal, a partir de l���An��lisi d���Elements Finits (AEF). L���AEF ��s una aproximaci�� num��rica que t�� el seu origen en les ci��ncies d���enginyeria i que ha estat emprada per estimar el comportament mec��nic d���un model en termes, per exemple, de deformaci�� i estr��s. Aix��, un objecte, o millor dit el seu model, es dividit en sub-dominis anomenats elements finits, als quals se���ls atribueixen les propietats mec��niques del material en estudi. Aquests elements finits estan connectats formant una xarxa amb constriccions que pot ser definida. En el cas d���aplicar una for��a determinada a un model, el comportament de l���objecte pot ser estimat mitjan��ant el conjunt d���equacions lineals que defineixen el rendiment dels elements finits, proporcionant una bona aproximaci�� per a la descripci�� de la deformaci�� estructural. Aix��, aquesta simulaci�� per ordinador suposa una important eina per entendre la funcionalitat de cer��miques arqueol��giques. Aquest procediment representa un model quantitatiu per predir el trencament de l���objecte cer��mic quan aquest ��s sotm��s a diferents condicions de pressi��. Aquest model ha estat aplicat a diferents tipologies amforals. Els resultats preliminars mostren difer��ncies significatives entre la tipologia pre-romana i les tipologies romanes, aix�� com entre els mateixos dissenys amforals romans, d���importants implicacions arqueol��giques.

Aplicaciones Single Program Multiple Data (SPMD) en ambientes distribuidos

Un reto al ejecutar las aplicaciones en un cluster es lograr mejorar las prestaciones utilizando los recursos de manera eficiente, y este reto es mayor al utilizar un ambiente distribuido. Teniendo en cuenta este reto, se proponen un conjunto de reglas para realizar el c��mputo en cada uno de los nodos, basado en el an��lisis de c��mputo y comunicaciones de las aplicaciones, se analiza un esquema de mapping de celdas y un m��todo para planificar el orden de ejecuci��n, tomando en consideraci��n la ejecuci��n por prioridad, donde las celdas de fronteras tienen una mayor prioridad con respecto a las celdas internas. En la experimentaci��n se muestra el solapamiento del computo interno con las comunicaciones de las celdas fronteras, obteniendo resultados donde el Speedup aumenta y los niveles de eficiencia se mantienen por encima de un 85%, finalmente se obtiene ganancias de los tiempos de ejecuci��n, concluyendo que si se puede dise��ar un esquemas de solapamiento que permita que la ejecuci��n de las aplicaciones SPMD en un cluster se hagan de forma eficiente.

Performance analysis and tuning in multicore environments

Performance analysis is the task of monitor the behavior of a program execution. The main goal is to find out the possible adjustments that might be done in order improve the performance. To be able to get that improvement it is necessary to find the different causes of overhead. Nowadays we are already in the multicore era, but there is a gap between the level of development of the two main divisions of multicore technology (hardware and software). When we talk about multicore we are also speaking of shared memory systems, on this master thesis we talk about the issues involved on the performance analysis and tuning of applications running specifically in a shared Memory system. We move one step ahead to take the performance analysis to another level by analyzing the applications structure and patterns. We also present some tools specifically addressed to the performance analysis of OpenMP multithread application. At the end we present the results of some experiments performed with a set of OpenMP scientific application.

Estimating patterns of leaf herbivory along an altitudinal transect in NE Queensland rainforests: might global warming increase leaf herbivory in tropical rainforests?

Climate change has been taking place at unprecedented rates over the past decades. These fast alterations caused by human activities are leading to a global warming of the planet. Warmer temperatures are going to have important effects on vegetation and especially on tropical forests. Insects as well will be affected by climate change. This study tested the hypothesis that higher temperatures lead to a higher insect pressure on vegetation. Visual estimations of leaf damage were recorded and used to assess the extent of herbivory in nine 0.1ha plots along an altitudinal gradient, and therefore a temperature gradient. These estimations were made at both a community level and a species level, on 2 target species. Leaf toughness tests were performed on samples from the target species from each plot. Results showed a strong evidence of increasing insect damage along increasing temperature, with no significant effect from the leaf toughness.

Modelling dependence in a ratemaking procedure with multivariate Poisson regression models

When actuaries face with the problem of pricing an insurance contract that contains different types of coverage, such as a motor insurance or homeowner's insurance policy, they usually assume that types of claim are independent. However, this assumption may not be realistic: several studies have shown that there is a positive correlation between types of claim. Here we introduce different regression models in order to relax the independence assumption, including zero-inflated models to account for excess of zeros and overdispersion. These models have been largely ignored to multivariate Poisson date, mainly because of their computational di��culties. Bayesian inference based on MCMC helps to solve this problem (and also lets us derive, for several quantities of interest, posterior summaries to account for uncertainty). Finally, these models are applied to an automobile insurance claims database with three different types of claims. We analyse the consequences for pure and loaded premiums when the independence assumption is relaxed by using different multivariate Poisson regression models and their zero-inflated versions.

Effects of increased drought and selective thinning on growth and resprouting of two coexisting Mediterranean oaks with contrasting leaf habit (Quercus ilex and Quercus cerrioides)

According to the IPCC (2007), the Mediterranean basin is expected to suffer important changes in temperature and precipitation in the next few decades, leading the climate warmer and dryer. Therefore, it is necessary to determine the possible effects of increased drought on species with different structural and physiological traits, to be able to predict possible changes in the structure and composition of Mediterranean forests. Moreover, it will be necessary to assess whether traditional management practices can mitigate the effects of climate change on these forests. The main aim of this study has been to analyze the effects of increased drought on the mortality, growth and resprouting patterns of two co-occurring Mediterranean oak species with contrasting leaf habit (the evergreen Quercus ilex and the winter-deciduous Quercus cerrioides), and to assess the effects of selective thinning on their response to increased drought. Our results show a differential effect of increased drought between species: no differences were observed in the growth of Q. ilex while Q. cerrioides reduced its growth under increased drought conditions. Selective thinning reduced the negative effects of increased drought on tree growth, although this beneficial effect tended to decrease during the experiment. Our results show that increasing aridity in Mediterranean areas can be a constraining factor for deciduous oaks, thus potentially causing their decline in mixed forests and favouring their substitution by the evergreen congeneric species. However, as seen in this study, management can strongly encourage growth both for deciduous and evergreen species, thus reversing the effects of increased water stress on Mediterranean coppices.

Mesophyll conductance to CO2 and leaf morphological characteristics under drought stress during Quercus ilex L resprouting

��� Quercus ilex L., the dominant species in Mediterranean forests and one with a great capacity for resprouting after disturbances, is threatened by the expected increase in fire frequency and drought associated with climate change. ��� The aim of this study was to determine the contribution of photosynthesis limitants, especially mesophyll conductance (gmes ) during this species��� resprouting and under summer drought. ��� Resprouts showed 5.3-fold increased gmes and 3.8-fold increased stomatal conductance (gs) atmidday with respect to leaves of undisturbed individuals. With increased drought, structural changes (decreased density and increased thickness) in resprouts contributed to the observed higher photosynthesis and increased gmes. However, gmes only partially depended on leaf structure, and was also under physiological control. Resprouts also showed lower non-stomatal limitations (around 50% higher carboxylation velocity (Vc,max) and capacity for ribulose-1,5-bisphosphate regeneration (Jmax)). A significant contribution of gmes to leaf carbon isotope discrimination values was observed. ��� gmes exhibits a dominant role in photosynthesis limitation in Q. ilex and is regulated by factors other than morphology. During resprouting after disturbances, greater capacity to withstand drought, as evidenced by higher gmes , gs and lower non-stomatal limitants, enables increased photosynthesis and rapid growth.

Valor pron��stico de la densidad microvascular y de la expresi��n del VEGF, EGFR y HIF-1 en pacientes con c��ncer de c��rvix localmente avanzado tratados con quimioradiaci��n

Introducci��n: Colombia cuenta con poca informaci��n sobre el comportamiento del c��ncer, no obstante, el carcinoma de cuello uterino representa la segunda causa de muerte por la enfermedad entre las mujeres de nuestro entorno. El patr��n epidemiol��gico de la enfermedad es preocupante porque los estados localmente avanzados constituyen el estado m��s frecuente al momento del diagn��stico y la mortalidad siendo bastante alta a pesar de la presencia de un programa de cribado organizado. Objetivo: Describir el valor pron��stico de la densidad microvascular (DMV) y de la expresi��n proteica de varios genes relacionados con la supervivencia y proliferaci��n del c��ncer de c��rvix localmente avanzado en un grupo de mujeres tratadas con quimioradiaci��n y braquiterapia intracavitaria. Se estimaron la tasa de respuesta global (TRG), la supervivencia libre de progresi��n (SLP) y la supervivencia global (SG). Resultados: Se incluyeron 61 mujeres con una edad media de 52 �� 10 a��os; todas ten��an diagn��stico de c��ncer de c��rvix localmente avanzado (IIA 2.3%/IIB 47.5%/IIIA 4.9%/IIIB 37.7%/IVA 3.3%/no definido 3.3%), con un volumen tumoral promedio de 6.4cm (DE �� 1.8cm) e infecci��n por VPH en 46% de los casos; 58 sujetos (95%) ten��an un patr��n escamoso, dos fueron adenocarcinomas y &50% presentaba neoplasias moderada o pobremente diferenciadas. Todas fueron tratadas con quimioradiaci��n (interrupci��n transitoria en teleterapia por toxicidad y otras causas en 19% y 21.4%, respectivamente/media de ciclos de platino concomitante 4.8 series �� 1.0) y braquiterapia (77% completaron el tratamiento intracavitario). La mediana para la SLP y global fue de 6.6 meses (r, 4.0-9.1) y 30 meses (r, 11-48), respectivamente. Ninguna de las variables tuvo un efecto positivo sobre la SLP, mientras el an��lisis multivariado demostr�� que los niveles de expresi��n del VEGF (P=0.026), EGFR (P=0.030), y el volumen tumoral menor de 6 cm (P=0.02) influyeron positivamente sobre ��ste desenlace. Conclusi��n: Existe una influencia positiva sobre el pron��stico, de la tipificaci��n en el c��ncer de c��rvix localmente avanzado tratado con quimioradiaci��n basada en platino.

Including the workload effect in the parallel program signature

Performance prediction and application behavior modeling have been the subject of exten- sive research that aim to estimate applications performance with an acceptable precision. A novel approach to predict the performance of parallel applications is based in the con- cept of Parallel Application Signatures that consists in extract an application most relevant parts (phases) and the number of times they repeat (weights). Executing these phases in a target machine and multiplying its exeuction time by its weight an estimation of the application total execution time can be made. One of the problems is that the performance of an application depends on the program workload. Every type of workload affects differently how an application performs in a given system and so affects the signature execution time. Since the workloads used in most scientific parallel applications have dimensions and data ranges well known and the behavior of these applications are mostly deterministic, a model of how the programs workload affect its performance can be obtained. We create a new methodology to model how a program���s workload affect the parallel application signature. Using regression analysis we are able to generalize each phase time execution and weight function to predict an application performance in a target system for any type of workload within predefined range. We validate our methodology using a synthetic program, benchmarks applications and well known real scientific applications.

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = ��f + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix ��.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ����T + �� (2)where �� = Cov(e) has a diagonal form. The diagonal elements of �� as well as theloadings matrix �� are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of �� and �� in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

A compositional data analysis package for R providing multiple approaches

���compositions��� is a new R-package for the analysis of compositional and positive data.It contains four classes corresponding to the four different types of compositional andpositive geometry (including the Aitchison geometry). It provides means for computation,plotting and high-level multivariate statistical analysis in all four geometries.These geometries are treated in an fully analogous way, based on the principle of workingin coordinates, and the object-oriented programming paradigm of R. In this way,called functions automatically select the most appropriate type of analysis as a functionof the geometry. The graphical capabilities include ternary diagrams and tetrahedrons,various compositional plots (boxplots, barplots, piecharts) and extensive graphical toolsfor principal components. Afterwards, ortion and proportion lines, straight lines andellipses in all geometries can be added to plots. The package is accompanied by ahands-on-introduction, documentation for every function, demos of the graphical capabilitiesand plenty of usage examples. It allows direct and parallel computation inall four vector spaces and provides the beginner with a copy-and-paste style of dataanalysis, while letting advanced users keep the functionality and customizability theydemand of R, as well as all necessary tools to add own analysis routines. A completeexample is included in the appendix

Exploration of geological variability and possible processes through the use of compositional data analysis: an example using scottish metamorphosed

Developments in the statistical analysis of compositional data over the last twodecades have made possible a much deeper exploration of the nature of variability,and the possible processes associated with compositional data sets from manydisciplines. In this paper we concentrate on geochemical data sets. First we explainhow hypotheses of compositional variability may be formulated within the naturalsample space, the unit simplex, including useful hypotheses of subcompositionaldiscrimination and specific perturbational change. Then we develop through standardmethodology, such as generalised likelihood ratio tests, statistical tools to allow thesystematic investigation of a complete lattice of such hypotheses. Some of these tests are simple adaptations of existing multivariate tests but others require specialconstruction. We comment on the use of graphical methods in compositional dataanalysis and on the ordination of specimens. The recent development of the conceptof compositional processes is then explained together with the necessary tools for astaying- in-the-simplex approach, namely compositional singular value decompositions. All these statistical techniques are illustrated for a substantial compositional data set, consisting of 209 major-oxide and rare-element compositions of metamorphosed limestones from the Northeast and Central Highlands of Scotland.Finally we point out a number of unresolved problems in the statistical analysis ofcompositional processes

Economic and environmental effects of the CO2 taxation: an input-output analysis for Spain

CO2 emissions induced by human activities are the major cause of climate change; hence, strong environmental policy that limits the growing dependence on fossil fuel is indispensable. Tradable permits and environmental taxes are the usual tools used in CO2 reduction strategies. Such economic tools provide incentives to polluting industries to reduce their emissions through market signals. The aim of this work is to investigate the direct and indirect effects of an environmental tax on Spanish products and services. We apply an environmentally extended input-output (EIO) model to identify CO2 emission intensities of products and services and, accordingly, we estimate the tax proportional to these intensities. The short-term price effects are analyzed using an input-output price model. The effect of tax introduction on consumption prices and its influence on consumers��� welfare are determined. We also quantify the environmental impacts of such taxation in terms of the reduction in CO2 emissions. The results, based on the Spanish economy for the year 2007, show that sectors with relatively poor environmental profile are subjected to high environmental tax rates. And consequently, applying a CO2 tax on these sectors, increases production prices and induces a slight increase in consumer price index and a decrease in private welfare. The revenue from the tax could be used to counter balance the negative effects on social welfare and also to stimulate the increase of renewable energy shares in the most impacting sectors. Finally, our analysis highlights that the environmental and economic goals cannot be met at the same time with the environmental taxation and this shows the necessity of finding other (complementary or alternative) measures to ensure both the economic and ecological efficiencies. Keywords: CO2 emissions; environmental tax; input-output model, effects of environmental taxation.