Trade in intermediate goods and total factor productivity

We develop and calibrate a model where differences in factor endowments lead countries to trade intermediate goods, and gains from trade reflect in total factor productivity. We perform several output and growth decompositions, to assess the impact that barriers to trade, as well as changes in terms of trade, have on measured TFP. We find that for very poor economies gains from trade are large, in some cases representing a doubling of GDP. Also, that an improvement in the terms of trade - by allowing the use of a better mix of intermediate inputs in the production process - translates into productivity growth.

Gains from trade and measured total factor productivity

We develop and calibrate a model where diferences in factor en-dowments lead countries to trade di¤erent goods, so that the existence of international trade changes the sectorial composition of output from one country to another. Gains from trade re ect in total factor productivity. We perform a development decomposition, to assess the impact of trade and barriers to trade on measured TFP. In our sample, the median size of that e¤ect is about 6.5% of output, with a median of 17% and a maximum of 89%. Also, the model predicts that changes in the terms of trade cause a change of productivity, and that efect has an average elasticity of 0.71.

Development of Plurimetallic Electrocatalysts Prepared by Decomposition of Polymeric Precursors for EtOH/O-2 Fuel Cell

This work aimed to develop plurimetallic electrocatalysts composed of Pt, Ru, Ni, and Sn supported on C by decomposition of polymeric precursors (DPP), at a constant metal: carbon ratio of 40:60 wt.%, for application in direct ethanol fuel cell (DEFC). The obtained nanoparticles were physico-chemically characterized by X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDX). XRD results revealed a face-centered cubic crystalline Pt with evidence that Ni, Ru, and Sn atoms were incorporated into the Pt structure. Electrochemical characterization of the nanoparticles was accomplished by cyclic voltammetry (CV) and chronoamperometry (CA) in slightly acidic medium (0.05 mol L-1 H2SO4), in the absence and presence of ethanol. Addition of Sn to PtRuNi/C catalysts significantly shifted the ethanol and CO onset potentials toward lower values, thus increasing the catalytic activity, especially for the quaternary composition Pt64Sn15Ru13Ni8/C. Electrolysis of ethanol solutions at 0.4 V vs. RHE allowed determination of acetaldehyde and acetic acid as the main reaction products. The presence of Ru in alloys promoted formation of acetic acid as the main product of ethanol oxidation. The Pt64Sn15Ru13Ni8/C catalyst displayed the best performance for DEFC.

Development of plurimetallic electrocatalysts prepared by decomposition of polymeric precursors for EtOH/O2 fuel cell

This work aimed to develop plurimetallic electrocatalysts composed of Pt, Ru, Ni, and Sn supported on C by decomposition of polymeric precursors (DPP), at a constant metal:carbon ratio of 40:60 wt.%, for application in direct ethanol fuel cell (DEFC). The obtained nanoparticles were physico-chemically characterized by X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDX). XRD results revealed a face-centered cubic crystalline Pt with evidence that Ni, Ru, and Sn atoms were incorporated into the Pt structure. Electrochemical characterization of the nanoparticles was accomplished by cyclic voltammetry (CV) and chronoamperometry (CA) in slightly acidic medium (0.05 mol L-1 H2SO4), in the absence and presence of ethanol. Addition of Sn to PtRuNi/C catalysts significantly shifted the ethanol and CO onset potentials toward lower values, thus increasing the catalytic activity, especially for the quaternary composition Pt64Sn15Ru13Ni8/C. Electrolysis of ethanol solutions at 0.4 V vs. RHE allowed determination of acetaldehyde and acetic acid as the main reaction products. The presence of Ru in alloys promoted formation of acetic acid as the main product of ethanol oxidation. The Pt64Sn15Ru13Ni8/C catalyst displayed the best performance for DEFC.

Development of a domain decomposition method for computational aeroacoustics

Abstract not available

Development of new scenario decomposition techniques for linear and nonlinear stochastic programming

Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

Development of new scenario decomposition techniques for linear and nonlinear stochastic programming

Une approche classique pour traiter les problèmes d’optimisation avec incertitude à deux- et multi-étapes est d’utiliser l’analyse par scénario. Pour ce faire, l’incertitude de certaines données du problème est modélisée par vecteurs aléatoires avec des supports finis spécifiques aux étapes. Chacune de ces réalisations représente un scénario. En utilisant des scénarios, il est possible d’étudier des versions plus simples (sous-problèmes) du problème original. Comme technique de décomposition par scénario, l’algorithme de recouvrement progressif est une des méthodes les plus populaires pour résoudre les problèmes de programmation stochastique multi-étapes. Malgré la décomposition complète par scénario, l’efficacité de la méthode du recouvrement progressif est très sensible à certains aspects pratiques, tels que le choix du paramètre de pénalisation et la manipulation du terme quadratique dans la fonction objectif du lagrangien augmenté. Pour le choix du paramètre de pénalisation, nous examinons quelques-unes des méthodes populaires, et nous proposons une nouvelle stratégie adaptive qui vise à mieux suivre le processus de l’algorithme. Des expériences numériques sur des exemples de problèmes stochastiques linéaires multi-étapes suggèrent que la plupart des techniques existantes peuvent présenter une convergence prématurée à une solution sous-optimale ou converger vers la solution optimale, mais avec un taux très lent. En revanche, la nouvelle stratégie paraît robuste et efficace. Elle a convergé vers l’optimalité dans toutes nos expériences et a été la plus rapide dans la plupart des cas. Pour la question de la manipulation du terme quadratique, nous faisons une revue des techniques existantes et nous proposons l’idée de remplacer le terme quadratique par un terme linéaire. Bien que qu’il nous reste encore à tester notre méthode, nous avons l’intuition qu’elle réduira certaines difficultés numériques et théoriques de la méthode de recouvrement progressif.

Taguchi optimized synthesis of graphene films by copper catalyzed ethanol decomposition

Taguchi method is for the first time applied to optimize the synthesis of graphene films by copper-catalyzed decomposition of ethanol. In order to find the most appropriate experimental conditions for the realization of thin high-grade films, six experiments suitably designed and performed. The influence of temperature (1000–1070 °C) and synthesis duration (1–30 min) and hydrogen flow (0–100 sccm) on the number of graphene layers and defect density in the graphitic lattice was ranked by monitoring the intensity of the 2D- and D-bands relative to the G-band in the Raman spectra. After critical examination and adjusting of the conditions predicted to give optimal results, a continuous film consisting of 2–4 nearly defect-free graphene layers was obtained.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

Decomposition analysis of air pollution abatement in China: empirical study for ten industrial sectors from 1998 to 2009

This study analyzes the management of air pollutant substance in Chinese industrial sectors from 1998 to 2009. Decomposition analysis applying the logarithmic mean divisia index is used to analyze changes in emissions of air pollutants with a focus on the following five factors: coal pollution intensity (CPI), end-of-pipe treatment (EOP), the energy mix (EM), productive efficiency change (EFF), and production scale changes (PSC). Three pollutants are the main focus of this study: sulfur dioxide (SO2), dust, and soot. The novelty of this paper is focusing on the impact of the elimination policy on air pollution management in China by type of industry using the scale merit effect for pollution abatement technology change. First, the increase in SO2 emissions from Chinese industrial sectors because of the increase in the production scale is demonstrated. However, the EOP equipment that induced this change and improvements in energy efficiency has prevented an increase in SO2 emissions that is commensurate with the increase in production. Second, soot emissions were successfully reduced and controlled in all industries except the steel industry between 1998 and 2009, even though the production scale expanded for these industries. This reduction was achieved through improvements in EOP technology and in energy efficiency. Dust emissions decreased by nearly 65% between 1998 and 2009 in the Chinese industrial sectors. This successful reduction in emissions was achieved by implementing EOP technology and pollution prevention activities during the production processes, especially in the cement industry. Finally, pollution prevention in the cement industry is shown to result from production technology development rather than scale merit. © 2013 Elsevier Ltd. All rights reserved.

Use of genetic decompositions to scaffold the development of a structurally sequenced curriculum for mathematics acceleration

The authors have collaboratively used a graphical language to describe their shared knowledge of a small domain of mathematics, which has in turn scaffolded their re-development of a related curriculum for mathematics acceleration. This collaborative use of the graphical language is reported as a simple descriptive case study. This leads to an evaluation of the graphical language’s usefulness as a tool to support the articulation of the structure of mathematics knowledge. In turn, implications are drawn for how the graphical language may be utilised as the detail of the curriculum is further elaborated and communicated to teachers.

European aspen and hybrid aspen under changing environment : Leaf traits, growth and litter decomposition

Understanding the responses of species and ecosystems to human-induced global environmental change has become a high research priority. The main aim of this thesis was to investigate how certain environmental factors that relate to global change affect European aspen (Populus tremula), a keystone species in boreal forests, and hybrid aspen (P. tremula × P. tremuloides), cultivated in commercial plantations. The main points under consideration were the acclimatization potential of aspen through changes in leaf morphology, as well as effects on growth, leaf litter chemistry and decomposition. The thesis is based on two experiments, in which young aspen (< 1 year) were exposed either to an atmospheric pollutant [elevated ozone (O3)] or variable resource availability [water, nitrogen (N)]; and two field studies, in which mature trees (> 8 years) were growing in environments exposed to multiple environmental stress factors (roadside and urban environments). The field studies included litter decomposition experiments. The results show that young aspen, especially the native European aspen, was sensitive to O3 in terms of visible leaf injuries. Elevated O3 resulted in reduced biomass allocation to roots and accelerated leaf senescence, suggesting negative effects on growth in the long term. Water and N availability modified the frost hardening of young aspen: High N supply, especially when combined with drought, postponed the development of frost hardiness, which in turn may predispose trees to early autumn frosts. This effect was more pronounced in European aspen. The field studies showed that mature aspen acclimatized to roadside and urban environments by producing more xeromorphic leaves. Leaf morphology was also observed to vary in response to interannual climatic variation, which further indicates the ability of aspen for phenotypic plasticity. Intraspecific variation was found in several of the traits measured, although intraspecific differences in response to the abiotic factors examined were generally small throughout the studies. However, some differences between clones were found in sensitivity to O3 and the roadside environment. Aspen leaf litter decomposition was retarded in the roadside environment, but only initially. By contrast, decomposition was found to be faster in the urban than the rural environment throughout the study. The higher quality of urban litter (higher in N, lower in lignin and phenolics), as well as higher temperature, N deposition and humus pH at the urban site were factors likely to promote decay. The phenotypic plasticity combined with intraspecific variation found in the studies imply that aspen has potential for withstanding environmental changes, although some global change factors, such as rising O3 levels, may adversely affect its performance. The results also suggest that the multiple environmental changes taking place in urban areas which correspond closely with the main drivers of global change can modify ecosystem functioning by promoting litter decomposition, mediated partly by alterations in leaf litter quality.

A new parallel overlapped domain decomposition method for nonlinear dynamic finite element analysis

In this paper a new parallel algorithm for nonlinear transient dynamic analysis of large structures has been presented. An unconditionally stable Newmark-beta method (constant average acceleration technique) has been employed for time integration. The proposed parallel algorithm has been devised within the broad framework of domain decomposition techniques. However, unlike most of the existing parallel algorithms (devised for structural dynamic applications) which are basically derived using nonoverlapped domains, the proposed algorithm uses overlapped domains. The parallel overlapped domain decomposition algorithm proposed in this paper has been formulated by splitting the mass, damping and stiffness matrices arises out of finite element discretisation of a given structure. A predictor-corrector scheme has been formulated for iteratively improving the solution in each step. A computer program based on the proposed algorithm has been developed and implemented with message passing interface as software development environment. PARAM-10000 MIMD parallel computer has been used to evaluate the performances. Numerical experiments have been conducted to validate as well as to evaluate the performance of the proposed parallel algorithm. Comparisons have been made with the conventional nonoverlapped domain decomposition algorithms. Numerical studies indicate that the proposed algorithm is superior in performance to the conventional domain decomposition algorithms. (C) 2003 Elsevier Ltd. All rights reserved.

Development and Application of Embedding Methods for the Simulation of Large Chemical Systems

The high computational cost of correlated wavefunction theory (WFT) calculations has motivated the development of numerous methods to partition the description of large chemical systems into smaller subsystem calculations. For example, WFT-in-DFT embedding methods facilitate the partitioning of a system into two subsystems: a subsystem A that is treated using an accurate WFT method, and a subsystem B that is treated using a more efficient Kohn-Sham density functional theory (KS-DFT) method. Representation of the interactions between subsystems is non-trivial, and often requires the use of approximate kinetic energy functionals or computationally challenging optimized effective potential calculations; however, it has recently been shown that these challenges can be eliminated through the use of a projection operator. This dissertation describes the development and application of embedding methods that enable accurate and efficient calculation of the properties of large chemical systems.

Chapter 1 introduces a method for efficiently performing projection-based WFT-in-DFT embedding calculations on large systems. This is accomplished by using a truncated basis set representation of the subsystem A wavefunction. We show that naive truncation of the basis set associated with subsystem A can lead to large numerical artifacts, and present an approach for systematically controlling these artifacts.

Chapter 2 describes the application of the projection-based embedding method to investigate the oxidative stability of lithium-ion batteries. We study the oxidation potentials of mixtures of ethylene carbonate (EC) and dimethyl carbonate (DMC) by using the projection-based embedding method to calculate the vertical ionization energy (IE) of individual molecules at the CCSD(T) level of theory, while explicitly accounting for the solvent using DFT. Interestingly, we reveal that large contributions to the solvation properties of DMC originate from quadrupolar interactions, resulting in a much larger solvent reorganization energy than that predicted using simple dielectric continuum models. Demonstration that the solvation properties of EC and DMC are governed by fundamentally different intermolecular interactions provides insight into key aspects of lithium-ion batteries, with relevance to electrolyte decomposition processes, solid-electrolyte interphase formation, and the local solvation environment of lithium cations.

Reducing organic substances from anaerobic decomposition of hydrophytes

Oxidation-reduction properties of surface sediments are tightly associated with the geochemistry of substances, and reducing organic substances (ROS) from hydrophytes residues may play an important role in these processes. In this study, composition, dynamics, and properties of ROS from anaerobic decomposition of Eichhornia crassipes (Mart.) Solms, Potamogenton crispus Linn, Vallisneria natans (Lour.) Hara, Lemna trisulca Linn and Microcystis flos-aquae (Wittr) Kirch were investigated using differential pulse voltammetry (DPV). The type of hydrophytes determined both the reducibility and composition of ROS. At the peak time of ROS production, the anaerobic decomposition of M. flos-aquae produced 6 types of ROS, among which 3 belonged to strongly reducing organic substance (SROS), whereas there were only 3-4 types of ROS from the other hydrophytes, 2 of them exhibiting strong reducibility. The order of potential of hydrophytes to produce ROS was estimated to be: M. flos-aquae > E. crassipes > L. trisulca > P. crispus approximate to V. natans, based on the summation of SROS and weakly reducing organic substances (WROS). The dynamic pattern of SROS production was greatly different from WROS. The total SROS appeared periodic fluctuation with reducibility gradually weakening with incubation time, whereas the total WROS increased with incubation time. Reducibility of ROS from hydrophytes was readily affected by acid, base and ligands, suggesting that their properties were related to these aspects. In addition to the reducibility, we believe that more attention should be paid to the other behaviors of ROS in surface sediments.