Investor Relations on the Internet: A Survey of the Euronext Zone

This study investigates the investor relations activities on the Internet of companies listed on the Euronext stock exchange. For this purpose, the homepages of the 50 largest listed companies in each of the countries Belgium, France and the Netherlands were searched and screened for investor relations items. Results obtained by using a three stages model show that most companies in the Euronext zone are in the second stage of Internet investorrelations. In this stage, information available through other sources is combined to better inform investors. In the third stage companies use the full interactive possibilities of the Internet for investor relations purposes. French and Dutch companies use the Internet for investor relations purposes more widely and more intensely than do Belgian companies. The study also revealed a size effect; large companies use the Internet for investor relations purposes more extensively than do smaller companies. This conclusion holds for each of the three countries. The leading companies in France and the Netherlands are either in the third stage of Internet investor relations or they are ready to enter it.accounting and auditing ;

20-Sim ANSI-C code on a 8051 target

In the forth-coming version of 20-sim the option code-generation for targets will be available. After selection of a template, it’s filled in with model specific information. Then this adapted template can be compiled and linked such that it can be run on the target. Theo Lammerink designed around the often-used 8051 microcontroller a target with 64-Kb data and code memory.\ud The goal of this project was to implement a template for this target such that 20-sim code can run on it. The implementation of simulation elements within 20-sim of the target functions is completed successfully. This is shown by several simulation tests. Also the realisation of the template is accomplished.\ud Although the correct working of the template could not yet been shown, it is very likely that it will work. However some strong comments have to be made considering the speed on which the code will run and the restricted complexity of the controller that can be designed.\ud Also this project was a practical evaluation of the code-generation option of 20-sim. And some recommendations to improve it have been made:\ud - Code generation not only with floats but also with integers.\ud - Better replacement of simulation code with target c-code concerning target elements (like ADC, DAC, etc).\ud - Point out which functions are used so that only the necessary functions are compiled

Origin of power-law behaviour in the size distribution of extreme events of gross primary productivity

Tese de Mestrado, Ciências Geofísicas (Meteorologia e Oceanografia), 2021, Universidade de Lisboa, Faculdade de CiênciasA quite interesting find by Zscheischler et al. in 2013 [1] was that the size distribution of extreme events in observation data of gross primary productivity (GPP) follows a power-law in the form p(x) ∼ x −α . This power-law holds for different regions in the world with similar values for the scaling parameter α. The goal of this thesis is to unravel the origin of this power-law behaviour. This behaviour might originate from the GPP distribution itself, or perhaps have a more mathematical origin. Thus, the main research question to be answered in this study is: ”What is the origin of the power-law behaviour in the size distribution of GPP extreme events?” With data from a control simulation from CMIP6 (Coupled Model Intercomparison Project Phase 6), I used the methodology from Zscheischler et al. for finding extreme events in simulation data for GPP. The power-law is not found in the distribution of GPP itself, thus its origins are sought in the clustering mechanisms behind the extreme event analysis. Percolation theory is hypothesised as an explanation behind the power-law behaviour, based on the fact that both GPP extremes and percolation theory are concerned with clusters made out of a certain fraction of the data. This certain fraction is made up by ”percentiles” for GPP extremes and ”probability” in percolation theory. The exponent α for the power law in the size distribution of GPP is related to the exponent τ describing cluster sizes in percolation theory by the relation τ = α +1. However, there are some differences in the power-law scaling behaviour between GPP extremes and percolation theory, namely concerning the difference in the value of the voxels (i.e. 3D pixels) of GPP, correlations in time and space, and the restriction of GPP values to land. The GPP data is altered step by step to eliminate these differences to make the data more akin to the situation of percolation theory, which assumes uncorrelated data. This is done by considering cluster sizes instead of event sizes, randomizing the data by ”shuffling” and using synthetic datasets, producing results of power-law scaling behaviour that are closer to percolation theory. The most rigorous shuffled data and the synthetic data had power-law scaling behaviour that was especially close to percolation theory. Based on this, it can be said that the clustering mechanisms behind extreme event analysis are similar to the clustering in percolation theory and that therefore percolation theory can be considered as a reasonable explanation behind the power-law in GPP extremes. The size distribution of precipitation, sensible heat and latent heat also display power-law behaviour similar to GPP, indicating that this powerlaw is not exclusive to GPP. All in all it can be concluded that the origin of the power-law behaviour does not depend on GPP, in general it does not depend on the data itself but on the clustering mechanisms underlying percolation theory.Uma descoberta bastante interessante de Zscheischler et al. em 2013 [1] foi de que a distribuição do tamanho de eventos extremos em dados de observação de produtividade primária bruta (GPP, do inglês gross primary productivity) segue uma lei de potência na forma p(x) ∼ x −α . Tal lei de potência é válida em diferentes regiões do mundo, com valores semelhantes para o parâmetro de escala α. O objectivo desta tese é revelar a origem deste comportamento de lei de potência. Este comportamento pode originar-se da própria distribuição de GPP ou talvez ter uma origem mais matemática. Assim, a principal questão de investigação a ser respondida neste estudo é: ”Qual é a origem do comportamento de lei de potência da distribuição do tamanho de eventos extremos na GPP”? Com dados de uma simulação de controle do CMIP6 (Coupled Model Intercomparison Project Phase 6), utilizei a metodologia de Zscheischler et al. para encontrar eventos extremos nos dados de simulação de GPP. A lei de potência não é encontrada na distribuição da própria GPP, pelo que as suas origens são procuradas nos mecanismos de aglomeração por detrás da análise de eventos extremos. A teoria da percolação é colocada como hipótese para explicar o comportamento de lei de potência, com base no facto de que tanto os extremos de GPP quanto a teoria da percolação estão relacionados a aglomerados compostos a partir de uma certa fracção dos dados. Esta certa fracção é constituída por ”percentis” no caso dos extremos de GPP e por ”probabilidade” no caso da teoria da percolação. O expoente α da lei de potência na distribuição de tamanho de GPP está associado ao expoente τ, que descreve tamanhos de aglomerados na teoria da percolação, pela relação τ = α +1. Contudo, existem algumas diferenças no comportamento de lei de potência entre os extremos de GPP e a teoria da percolação, nomeadamente no que diz respeito à diferença no valor dos voxels (i.e. pixels em 3D) de GPP, correlações no tempo e espaço, e à restrição dos valores de GPP aos continentes. Os dados de GPP são alterados passo a passo para eliminar estas diferenças de modo a torná-los mais semelhantes à situação da teoria da percolação, que assume dados não correlacionados. Isto é feito considerando os tamanhos dos aglomerados ao invés dos tamanhos dos eventos, randomizando os dados através de um processo de “embaralhamento”, e utilizando conjuntos de dados sintéticos, produzindo resultados de comportamentos de lei de potência que estão mais próximos à teoria da percolação. Os dados embaralhados mais rigorosamente e os dados sintéticos apresentaram um comportamento de lei de potência especialmente próximo daquele na teoria da percolação. Com base nisto, pode-se dizer que os mecanismos de aglomeração por detrás da análise de eventos extremos são semelhantes à aglomeração na teoria da percolação e que, portanto, a teoria da percolação pode ser considerada como uma explicação razoável por detrás da lei de potência nos extremos de GPP. As distribuições de tamanho de precipitação, calor sensível e calor latente também apresentam um comportamento de lei de potência semelhante ao da GPP, indicando que esta lei de potência não ocorre unicamente para a GPP. Em suma, pode-se concluir que a origem do comportamento de lei de potencia não depende da GPP, em geral não depende dos dados em si, mas sim dos mecanismos de aglomeração subjacentes à teoria da percolação

A Visual Analysis of Rosey E. Pool's Correspondence Archives. Biographical Data, Intersectionality, and Social Network Analysis

This paper explores the use of Social Network Analysis (SNA) for individual historians, by focusing on the correspondence archives of Rosey E. Pool (1905-1971). Pool’s position in her international network of writers and scholars will be examined through her contacts with Hoyt W. Fuller and Robert Hayden over the period 1966 to 1971. The different positions these three actors held towards The First World Festival of Negro Arts (Dakar, April 1966) will be examined. The Dakar Festival was an important and symbolic event in the transnational Négritude movement.Using the theories of ‘intersectionality’ and ‘collective identity,’ Pool’s network will be analysed by focusing on specific religious and personal features that have influenced the dynamics of her network. A deeper insight of this specific period will be provided by performing a close reading of key letters and by placing the correspondence in its historical context. At the same time, the use of distant reading will be discussed, by dissecting and inspecting a visualisation (made with Gephi) of a database based on Pool’s ego-centred network. I will argue that the two approaches of close and distant reading are inseparable in historical research that makes use of Social Network Analysis

Psychometric methods for automated test design

Flexible forms of testing, such as adaptive testing and testing on demand, usually require large item pools to avoid overexposure of the items. After an initial investment in the development of an item generator, test items can be (semi-)automatically generated in a negligible amount of time. A distinction can be made between item generation rules that have a fixed effect on item difficulty and rules that result in variations in surface features of the items only. The combination of these two types of rules results in clusters ("families") of items with similar psychometric properties. Between-family variation is then caused by the former type of rules and within-family variation by the latter. In this thesis, item response theory models are discussed that can be used to estimate the psychometric properties of item families, based on responses to samples of their items. A distinction is made between models that assume equal parameters for all items within a family, and models that allow item-specific deviations from their family means. Knowledge of the applied item generation rules is used to define covariates for the family difficulty parameters of the models. Bayesian parameter estimation and model fit assessment methods are discussed, as well as methods for designing new tests based on a Fisher information measure for item families. The methodology is illustrated using simulated data and real datasets on intelligence test items and statistical word problems