An Analysis of the Link between Ethanol, Energy, and Crop Markets, November 2006

This study analyzes the impact of price shocks in three input and output markets critical to ethanol: gasoline, corn, and sugar. We investigate the impact of these shocks on ethanol and related agricultural markets in the United States and Brazil. We find that the composition of a country’s vehicle fleet determines the direction of the response of ethanol consumption to changes in the gasoline price. We also find that a change in feedstock costs affects the profitability of ethanol producers and the domestic ethanol price. In Brazil, where two commodities compete for sugarcane, changes in the sugar market affect the competing ethanol market.

The Impact of Industry Collaboration on Academic Research Output: A Dynamic Panel Data Analysis

The aim of this paper is to analyse the impact of university knowledge and technology transfer activities on academic research output. Specifically, we study whether researchers with collaborative links with the private sector publish less than their peers without such links, once controlling for other sources of heterogeneity. We report findings from a longitudinal dataset on researchers from two engineering departments in the UK between 1985 until 2006. Our results indicate that researchers with industrial links publish significantly more than their peers. Academic productivity, though, is higher for low levels of industry involvement as compared to high levels.

Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set

We evaluate conditional predictive densities for U.S. output growth and inflationusing a number of commonly used forecasting models that rely on a large number ofmacroeconomic predictors. More specifically, we evaluate how well conditional predictive densities based on the commonly used normality assumption fit actual realizationsout-of-sample. Our focus on predictive densities acknowledges the possibility that, although some predictors can improve or deteriorate point forecasts, they might have theopposite effect on higher moments. We find that normality is rejected for most modelsin some dimension according to at least one of the tests we use. Interestingly, however,combinations of predictive densities appear to be correctly approximated by a normaldensity: the simple, equal average when predicting output growth and Bayesian modelaverage when predicting inflation.

Input chains and industrialization

A key aspect of industrialization is theadoption of increasing-returns-to-scale, industrial,technologies. Two other, well-documented aspects arethat industrial technologies are adopted throughoutintermediate-input chains and that they use intermediateinputs intensively relative to the technologies theyreplace. These features of industrial technologiescombined imply that countries with access to similartechnologies may have very different levels ofindustrialization and income, even if the degree ofincreasing returns to scale at the firm level is relativelysmall. Furthermore, a small improvement in theproductivity of industrial technologies can trigger full-scaleindustrialization and a large increase in income.

The structural dynamics of US output and inflation: What explains the changes?

We examine the dynamics of US output and inflation using a structural time varyingcoefficient VAR. We show that there are changes in the volatility of both variables andin the persistence of inflation. Technology shocks explain changes in output volatility,while a combination of technology, demand and monetary shocks explain variations inthe persistence and volatility of inflation. We detect changes over time in the transmission of technology shocks and in the variance of technology and of monetary policyshocks. Hours and labor productivity always increase in response to technology shocks.

On the robust effects of technology shocks on hours worked and output

We analyze the effects of neutral and investment-specific technology shockson hours and output. Long cycles in hours are captured in a variety of ways.Hours robustly fall in response to neutral shocks and robustly increase inresponse to investment specific shocks. The percentage of the variance ofhours (output) explained by neutral shocks is small (large); the opposite istrue for investment specific shocks. News shocks are uncorrelated with theestimated technology shocks.

The structural dynamics of output growth and inflation: some international evidence

We examine the dynamics of output growth and inflation in the US, Euro area and UK using a structural time varying coefficient VAR. There are important similarities in structural inflation dynamics across countries; output growth dynamics differ. Swings in the magnitude of inflation and output growth volatilities and persistences are accounted for by a combination of three structural shocks. Changes over time in the structure of the economy are limited and permanent variations largely absent. Changes in the volatilities of structural shocks matter.

Inflation and output dynamics with firm-owned capital

We model firm-owned capital in a stochastic dynamic New-Keynesian generalequilibrium model à la Calvo. We find that this structure impliesequilibrium dynamics which are quantitatively di¤erent from the onesassociated with a benchmark case where households accumulate capital andrent it to firms. Our findings therefore stress the importance ofmodeling an investment decision at the firm level in addition to ameaningful price setting decision. Along the way we argue that the problemof modeling firm-owned capital with Calvo price-setting has not been solvedin a correct way in the previous literature.

A Gestão de Stock: O Fornecimento de OutPut como factor de redução de custo

O presente trabalho tem como objectivo mostrar a importância que a Gestão económica de Stock tem no processo de redução de custo, por via da implementação de um modelo. E para isso far-se-á um estudo de caso numa empresa inserida no ramo de transformação de pescado – FRESCOMAR. A metodologia adoptada para alcançar os objectivos propostos passou pela pesquisa bibliográfica, recolha de dados e de informação relevante junto da empresa e tratamento dos dados numa folha de Excel. O modelo de gestão de Stock a ser implementado depende essencialmente da componente procura, onde que para uma empresa com procura constante utiliza-se os modelos determinísticos e para uma com procura aleatória utiliza-se os modelos estocásticos (Nível de Encomenda e Revisão Cíclica). Nos modelos determinísticos temos 4 modelos diferenciados pela forma de reposição e a admissibilidade da procura. Com as informações recolhidas junto da empresa em estudo escolhemos implementar o modelo de reposição não instantânea com ruptura não permitida e obtivemos a optimização do Stock com níveis reduzidos de produção e consequentemente houve uma diminuição do custo. Com resultados obtiveram-se ainda valores da Quantidade Óptima a ser Produzida, do Stock Máximo e do Custo Total Óptimo por unidade de tempo. Devido a diversidade de produtos propomos à empresa a utilização da análise ABC para classificar os produtos reagrupando-os em classes A, B e C, conforme o peso no consumo de Stock.

Importância e Gestão de Informação Académica O caso da Escola Secundária Polivalente Cesaltina Ramos

A memória realizada no âmbito do regulamento dos Cursos de Graduação da Universidade Jean Piaget de Cabo Verde, apresenta um estudo sobre, Importância e Gestão d Informação Académica, mais concretamente, o estudo do tipo de informação académica face á sua importância, analisar o Sistemas de Informação/Tecnologias de Informação e Comunicação utilizadas nas instituições de ensino, como sendo um factor imprescindível no tratamento da informação (input, processamento, organização, output e os eventuais feedbacks), bem como, os estudos dos vários tipos de controlos feitos pela administração estratégica e, os mecanismos de protecção da informação utilizados, como forma de garantir a disponibilidade, integridade, confidencialidade e a autenticação da informação. É evidente que, desta forma qualquer organização consegue ter uma boa eficiência e eficácia em atingir os resultados previstos. Ainda, apresentamos um estudo de caso sobre a Escola Secundária Polivalente Cesaltina Ramos, cujas, conclusões indicam que a instituição, ainda tem muito o que fazer para que haja uma real partilha de informação numa “bagagem segura” e isto resulta de uma má gestão de informação devido à falta de recursos tecnológicos, humanos e de uma cultura organizacional adequada e flexível, o que é importante para uma boa gestão de informação.

Exact representation of antenna system diversity performance from input parameter description

A simplc formulation Io compute thc envelope correlation of anantenna divemiry system is dcrired. 11 is shown how to compute theenvelope correlation hom the S-parameter descnplian of the antennasystem. This approach has the advantage that i t does not require thecomputation nor the measurement of the radiation panem of theantenna system. It also offers the advantage of providing a clcaunderstanding ofthe effects ofmutual coupling and input match on thediversity performance of the antcnnii system.

10

This contribution introduces Data Envelopment Analysis (DEA), a performance measurement technique. DEA helps decision makers for the following reasons: (1) By calculating an efficiency score, it indicates if a firm is efficient or has capacity for improvement; (2) By setting target values for input and output, it calculates how much input must be decreased or output increased in order to become efficient; (3) By identifying the nature of returns to scale, it indicates if a firm has to decrease or increase its scale (or size) in order to minimise the average total cost; (4) By identifying a set of benchmarks, it specifies which other firms' processes need to be analysed in order to improve its own practices. This contribution presents the essentials about DEA, alongside a case study to intuitively understand its application. It also introduces Win4DEAP, a software package that conducts efficiency analysis based on DEA methodology. The methodical background of DEA is presented for more demanding readers. Finally, four advanced topics of DEA are treated: adjustment to the environment, preferences, sensitivity analysis and time series data.

Discordant increases in CD4+ T cells in human immunodeficiency virus-infected patients experiencing virologic treatment failure: role of changes in thymic output and T cell death.

Some patients infected with human immunodeficiency virus (HIV) who are experiencing antiretroviral treatment failure have persistent improvement in CD4+ T cell counts despite high plasma viremia. To explore the mechanisms responsible for this phenomenon, 2 parameters influencing the dynamics of CD4+ T cells were evaluated: death of mature CD4+ T cells and replenishment of the CD4+ T cell pool by the thymus. The improvement in CD4+ T cells observed in patients with treatment failure was not correlated with spontaneous, Fas ligand-induced, or activation-induced T cell death. In contrast, a significant correlation between the improvement in CD4+ T cell counts and thymic output, as assessed by measurement of T cell receptor excision circles, was observed. These observations suggest that increased thymic output contributes to the dissociation between CD4+ T cell counts and viremia in patients failing antiretroviral therapy and support a model in which drug-resistant HIV strains may have reduced replication rates and pathogenicity in the thymus.