The design of hazard risk assessment matrices for ranking occupational health risks and their application in mining and minerals processing

Two hazard risk assessment matrices for the ranking of occupational health risks are described. The qualitative matrix uses qualitative measures of probability and consequence to determine risk assessment codes for hazard-disease combinations. A walk-through survey of an underground metalliferous mine and concentrator is used to demonstrate how the qualitative matrix can be applied to determine priorities for the control of occupational health hazards. The semi-quantitative matrix uses attributable risk as a quantitative measure of probability and uses qualitative measures of consequence. A practical application of this matrix is the determination of occupational health priorities using existing epidemiological studies. Calculated attributable risks from epidemiological studies of hazard-disease combinations in mining and minerals processing are used as examples. These historic response data do not reflect the risks associated with current exposures. A method using current exposure data, known exposure-response relationships and the semi-quantitative matrix is proposed for more accurate and current risk rankings.

New arsenite-oxidizing bacteria isolated from Australian gold mining environments - Phylogenetic relationships

Nine novel arsenite-oxidizing bacteria have been isolated from two different gold mine environments in Australia. Four of these organisms grow chemolithoautotrophically with oxygen as the terminal electron acceptor, arsenite as the electron donor, and carbon dioxide-bicarbonate as the sole carbon source. Five heterotrophic arsenite-oxidizing bacteria were also isolated, one of which was found to be both phylogenetically and physiologically identical to the previously described heterotrophic arsenite oxidizer misidentified as Alcaligenes faecalis. The results showed that this strain belongs to the genus Achromobacter. Phylogenetically, the arsenite-oxidizing bacteria fall within two separate subdivisions of the Proteobacteria. Interestingly, the chemolithoautotrophic arsenite oxidizers belong to the alpha-Proteobacteria, whereas the heterotrophic arsenite oxidizers belong to the beta-Proteobacteria.

Remuneração executiva e desempenho: evidências empíricas no mercado de capitais brasileiro

O objetivo desta dissertação é analisar a relação existente entre remuneração executiva e desempenho em companhias brasileiras de capital aberto listadas na BM&FBOVESPA. A linha teórica parte do pressuposto que o contrato de incentivos corrobora com o alinhamento de interesses entre acionistas e executivos e atua como um mecanismo de governança corporativa a fim de direcionar os esforços dos executivos para maximização de valor da companhia. A amostra foi composta pelas 100 companhias mais líquidas listadas em quantidade de negociações de ações na BM&FBOVESPA durante o período 2010-2012, totalizando 296 observações. Os dados foram extraídos dos Formulários de Referência disponibilizados pela CVM e a partir dos softwares Economática® e Thomson Reuters ®. Foram estabelecidas oito hipóteses de pesquisa e estimados modelos de regressão linear múltipla com a técnica de dados em painel desbalanceado, empregando como variável dependente a remuneração total e a remuneração média individual e como regressores variáveis concernentes ao desempenho operacional, valor de mercado, tamanho, estrutura de propriedade, governança corporativa, além de variáveis de controle. Para verificar os fatores que explicam a utilização de stock options, programa de bônus e maior percentual de remuneração variável foram estimados modelos de regressão logit. Os resultados demonstram que, na amostra selecionada, existe relação positiva entre remuneração executiva e valor de mercado. Verificou-se também que os setores de mineração, química, petróleo e gás exercem influência positiva na remuneração executiva. Não obstante, exerce relação inversa com a remuneração total à concentração acionária, o controle acionário público e o fato da companhia pertencer ao nível 2 ou novo mercado conforme classificação da BMF&BOVESPA. O maior valor de mercado influencia na utilização de stock options, assim como no emprego de bônus, sendo que este também é impactado pelo maior desempenho contábil. Foram empregados também testes de robustez com estimações por efeitos aleatórios, regressões com erros-padrão robustos clusterizados, modelos dinâmicos e os resultados foram similares. Conclui-se que a remuneração executiva está relacionada com o valor corporativo gerando riqueza aos acionistas, mas que a ausência de relação com o desempenho operacional sugere falhas no sistema remuneratório que ainda depende de maior transparência e outros mecanismos de governança para alinhar os interesses entre executivos e acionistas.

The impact of size and age of the company on assessing financial risk

Textiles and tourism sectors are two important sectors in Portuguese economy. Its high exposure to both internal and international economy volatility transform the companies operating in these economic sectors especially vulnerable to recent economic crises in Portugal and European Union. The objective of this paper is to evaluate and understand the impact of size and age on the financial health of textile and tourism companies, measured by economic indices. An empirical based model is proposed. Its implications are derived and tested on a sample of 4061 Portuguese companies from textile and tourism sector, during the period 2005-2009. The results conclude that age has a stronger impact on the risk of failure than size. Whereas the effect of age is generally positive regarding the financial health of the company, the effect of size is less clear and depends on the age of the company.

Economic analysis of occupational risk prevention: a case study in a textile company

Work accidents affect business and society as a whole. Fewer accidents mean fewer sick leaves, which results in lower costs and less disruption in the production process, with clear advantages for the employer. But workers and their households bear also a significant burden following a work accident, only partially compen-sated by insurance systems. Furthermore, the consequences of work accidents to the State and Society need also to be considered. When an organization performs an integrated risk analysis in evaluating its Occupational Health and Safety Management System, several steps are suggested to address the identified risk situations. Namely, to avoid risks, a series of preventive measures are identified. The organization should make a detailed analysis of the monetary impact (positive or negative) for the organization of each of the measures considered. Particularly, it is also important to consider the impact of each measure on society, involving an adequate eco-nomic cost-benefit analysis. In the present paper, a case study in a textile finishing company is presented. The study concentrates on the dyeing and printing sections. For each of the potential risks, several preventive measures have been identified and the corresponding costs and benefits have been estimated. Subsequently, the Benefit/Cost ratio (B/C) of these measures has been calculated, both in financial terms (from the organisa-tion’s perspective) and in economic terms (including the benefits for the worker and for the Society). Results show that, while the financial analysis in terms of the company does not justify the preventive measures, when the externalities are taken into account, the B/C ratio increases significantly and investments are fully justified.

The impact of size and age of the company on assessing financial risk.

Textiles and tourism sectors are two important sectors in Portuguese economy. Its high exposure to both internal and international economy volatility transform the companies operating in these economic sectors especially vulnerable to recent economic crises in Portugal and European Union. The objective of this paper is to evaluate and understand the impact of size and age on the financial health of textile and tourism companies, measured by economic indices. An empirical based model is proposed. Its implications are derived and tested on a sample of 4061 Portuguese companies from textile and tourism sector, during the period 2005-2009. The results conclude that age has a stronger impact on the risk of failure than size. Whereas the effect of age is generally positive regarding the financial health of the company, the effect of size is less clear and depends on the age of the company.

Gestão do conhecimento usando data mining: estudo de caso na Universidade Federal de Lavras

A gestão do conhecimento abrange toda a forma de gerar, armazenar, distribuir e utilizar o conhecimento, tornando necessária a utilização de tecnologias de informação para facilitar esse processo, devido ao grande aumento no volume de dados. A descoberta de conhecimento em banco de dados é uma metodologia que tenta solucionar esse problema e o data mining é uma técnica que faz parte dessa metodologia. Este artigo desenvolve, aplica e analisa uma ferramenta de data mining, para extrair conhecimento referente à produção científica das pessoas envolvidas com a pesquisa na Universidade Federal de Lavras. A metodologia utilizada envolveu a pesquisa bibliográfica, a pesquisa documental e o método do estudo de caso. As limitações encontradas na análise dos resultados indicam que ainda é preciso padronizar o modo do preenchimento dos currículos Lattes para refinar as análises e, com isso, estabelecer indicadores. A contribuição foi gerar um banco de dados estruturado, que faz parte de um processo maior de desenvolvimento de indicadores de ciência e tecnologia, para auxiliar na elaboração de novas políticas de gestão científica e tecnológica e aperfeiçoamento do sistema de ensino superior brasileiro.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.