Développement de méthodes d’analyse directe de polluants organiques volatils à l’état de traces dans l’air et les biogaz

Il est reconnu que le benzène, le toluène, l’éthylbenzène et les isomères du xylène, composés organiques volatils (COVs) communément désignés BTEX, produisent des effets nocifs sur la santé humaine et sur les végétaux dépendamment de la durée et des niveaux d’exposition. Le benzène en particulier est classé cancérogène et une exposition à des concentrations supérieures à 64 g/m3 de benzène peut être fatale en 5–10 minutes. Par conséquent, la mesure en temps réel des BTEX dans l’air ambiant est essentielle pour détecter rapidement un danger associé à leur émission dans l’air et pour estimer les risques potentiels pour les êtres vivants et pour l’environnement. Dans cette thèse, une méthode d’analyse en temps réel des BTEX dans l’air ambiant a été développée et validée. La méthode est basée sur la technique d’échantillonnage direct de l’air couplée avec la spectrométrie de masse en tandem utilisant une source d’ionisation chimique à pression atmosphérique (APCI-MS/MS directe). La validation analytique a démontré la sensibilité (limite de détection LDM 1–2 μg/m3), la précision (coefficient de variation CV < 10%), l’exactitude (exactitude > 95%) et la sélectivité de la méthode. Des échantillons d’air ambiant provenant d’un site d’enfouissement de déchets industriels et de divers garages d’entretien automobile ont été analysés par la méthode développée. La comparaison des résultats avec ceux obtenus par la technique de chromatographie gazeuse on-line couplée avec un détecteur à ionisation de flamme (GC-FID) a donné des résultats similaires. La capacité de la méthode pour l’évaluation rapide des risques potentiels associés à une exposition aux BTEX a été prouvée à travers une étude de terrain avec analyse de risque pour la santé des travailleurs dans trois garages d’entretien automobile et par des expériences sous atmosphères simulées. Les concentrations mesurées dans l’air ambiant des garages étaient de 8,9–25 µg/m3 pour le benzène, 119–1156 µg/m3 pour le toluène, 9–70 µg/m3 pour l’éthylbenzène et 45–347 µg/m3 pour les xylènes. Une dose quotidienne environnementale totale entre 1,46 10-3 et 2,52 10-3 mg/kg/jour a été déterminée pour le benzène. Le risque de cancer lié à l’exposition environnementale totale au benzène estimé pour les travailleurs étudiés se situait entre 1,1 10-5 et 1,8 10-5. Une nouvelle méthode APCI-MS/MS a été également développée et validée pour l’analyse directe de l’octaméthylcyclotétrasiloxane (D4) et le décaméthylcyclopentasiloxane (D5) dans l’air et les biogaz. Le D4 et le D5 sont des siloxanes cycliques volatils largement utilisés comme solvants dans les processus industriels et les produits de consommation à la place des COVs précurseurs d’ozone troposphérique tels que les BTEX. Leur présence ubiquitaire dans les échantillons d’air ambiant, due à l’utilisation massive, suscite un besoin d’études de toxicité. De telles études requièrent des analyses qualitatives et quantitatives de traces de ces composés. Par ailleurs, la présence de traces de ces substances dans un biogaz entrave son utilisation comme source d’énergie renouvelable en causant des dommages coûteux à l’équipement. L’analyse des siloxanes dans un biogaz s’avère donc essentielle pour déterminer si le biogaz nécessite une purification avant son utilisation pour la production d’énergie. La méthode développée dans cette étude possède une bonne sensibilité (LDM 4–6 μg/m3), une bonne précision (CV < 10%), une bonne exactitude (> 93%) et une grande sélectivité. Il a été également démontré qu’en utilisant cette méthode avec l’hexaméthyl-d18-disiloxane comme étalon interne, la détection et la quantification du D4 et du D5 dans des échantillons réels de biogaz peuvent être accomplies avec une meilleure sensibilité (LDM ~ 2 μg/m3), une grande précision (CV < 5%) et une grande exactitude (> 97%). Une variété d’échantillons de biogaz prélevés au site d’enfouissement sanitaire du Complexe Environnemental de Saint-Michel à Montréal a été analysée avec succès par cette nouvelle méthode. Les concentrations mesurées étaient de 131–1275 µg/m3 pour le D4 et 250–6226 µg/m3 pour le D5. Ces résultats représentent les premières données rapportées dans la littérature sur la concentration des siloxanes D4 et D5 dans les biogaz d’enfouissement en fonction de l’âge des déchets.

Determination of yield and quality parameters of energy crops applying laboratory and field spectroscopy

A real-time analysis of renewable energy sources, such as arable crops, is of great importance with regard to an optimised process management, since aspects of ecology and biodiversity are considered in crop production in order to provide a sustainable energy supply by biomass. This study was undertaken to explore the potential of spectroscopic measurement procedures for the prediction of potassium (K), chloride (Cl), and phosphate (P), of dry matter (DM) yield, metabolisable energy (ME), ash and crude fibre contents (ash, CF), crude lipid (EE), nitrate free extracts (NfE) as well as of crude protein (CP) and nitrogen (N), respectively in pretreated samples and undisturbed crops. Three experiments were conducted, one in a laboratory using near infrared reflectance spectroscopy (NIRS) and two field spectroscopic experiments. Laboratory NIRS measurements were conducted to evaluate to what extent a prediction of quality parameters is possible examining press cakes characterised by a wide heterogeneity of their parent material. 210 samples were analysed subsequent to a mechanical dehydration using a screw press. Press cakes serve as solid fuel for thermal conversion. Field spectroscopic measurements were carried out with regard to further technical development using different field grown crops. A one year lasting experiment over a binary mixture of grass and red clover examined the impact of different degrees of sky cover on prediction accuracies of distinct plant parameters. Furthermore, an artificial light source was used in order to evaluate to what extent such a light source is able to minimise cloud effects on prediction accuracies. A three years lasting experiment with maize was conducted in order to evaluate the potential of off-nadir measurements inside a canopy to predict different quality parameters in total biomass and DM yield using one sensor for a potential on-the-go application. This approach implements a measurement of the plants in 50 cm segments, since a sensor adjusted sideways is not able to record the entire plant height. Calibration results obtained by nadir top-of-canopy reflectance measurements were compared to calibration results obtained by off-nadir measurements. Results of all experiments approve the applicability of spectroscopic measurements for the prediction of distinct biophysical and biochemical parameters in the laboratory and under field conditions, respectively. The estimation of parameters could be conducted to a great extent with high accuracy. An enhanced basis of calibration for the laboratory study and the first field experiment (grass/clover-mixture) yields in improved robustness of calibration models and allows for an extended application of spectroscopic measurement techniques, even under varying conditions. Furthermore, off-nadir measurements inside a canopy yield in higher prediction accuracies, particularly for crops characterised by distinct height increment as observed for maize.

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of household expenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that try to add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spending excluding alcohol/tobacco similar for teetotal and non-teetotal households? In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than one component, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durables within the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small. While this analysis is based on around economic data, the ideas carry over to many other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Mejoramiento Productivo "Apparel Basic Ltda"

Para el presente trabajo realizado en la Universidad del Rosario, buscamos hacer un mejoramiento productivo de la empresa Apparel Basic Ltda. Teniendo en cuenta todas las herramientas aprehendidas durante la academia y aplicando esto a una empresa del sector real de confecciones. Se centrara el análisis principalmente en las tres áreas donde se observan los mayores problemas organizacionales: Producción, manejo de inventarios y entrega de producto. En el primer análisis se realizara todo el estudio del proceso de producción, teniendo en cuenta la distribución en planta, las rutas críticas de proceso, los diagramas de flujo de producto, el análisis de las principales referencias, entre otros. Todo esto con el fin de identificar los principales errores y poder proponer herramientas y procesos de mejora que sean de ayuda para esta organización. El siguiente análisis se desarrollara en el manejo de inventarios; dentro de este aspecto se analizaran la distribución de las bodegas de producto, la identificación de los productos de mayor rotación, el planteamiento de indicadores de gestión, entre otros procesos, con el fin de identificar procesos benéficos para la empresa que aceleren y mejoren el flujo de producto al interior de la organización. Luego de esto, se analiza todo el proceso de alistamiento y entrega de producto ya que es uno de los principales problemas dentro de la organización porque se esta incumpliendo con los pedidos de los clientes lo que genera un problema de insatisfacción por parte de los clientes.

The distributed work of local action: interaction amongst virtually collocated research teams

Existing research on synchronous remote working in CSCW has highlighted the troubles that can arise because actions at one site are (partially) unavailable to remote colleagues. Such ‘local action’ is routinely characterised as a nuisance, a distraction, subordinate and the like. This paper explores interconnections between ‘local action’ and ‘distributed work’ in the case of a research team virtually collocated through ‘MiMeG’. MiMeG is an e-Social Science tool that facilitates ‘distributed data sessions’ in which social scientists are able to remotely collaborate on the real-time analysis of video data. The data are visible and controllable in a shared workspace and participants are additionally connected via audio conferencing. The findings reveal that whilst the (partial) unavailability of local action is at times problematic, it is also used as a resource for coordinating work. The paper considers how local action is interactionally managed in distributed data sessions and concludes by outlining implications of the analysis for the design and study of technologies to support group-to-group collaboration.

Prediction of coagulation properties, titratable acidity and pH of bovine milk using mid-infrared spectroscopy

This study investigated the potential application of mid-infrared spectroscopy (MIR 4,000–900 cm−1) for the determination of milk coagulation properties (MCP), titratable acidity (TA), and pH in Brown Swiss milk samples (n = 1,064). Because MCP directly influence the efficiency of the cheese-making process, there is strong industrial interest in developing a rapid method for their assessment. Currently, the determination of MCP involves time-consuming laboratory-based measurements, and it is not feasible to carry out these measurements on the large numbers of milk samples associated with milk recording programs. Mid-infrared spectroscopy is an objective and nondestructive technique providing rapid real-time analysis of food compositional and quality parameters. Analysis of milk rennet coagulation time (RCT, min), curd firmness (a30, mm), TA (SH°/50 mL; SH° = Soxhlet-Henkel degree), and pH was carried out, and MIR data were recorded over the spectral range of 4,000 to 900 cm−1. Models were developed by partial least squares regression using untreated and pretreated spectra. The MCP, TA, and pH prediction models were improved by using the combined spectral ranges of 1,600 to 900 cm−1, 3,040 to 1,700 cm−1, and 4,000 to 3,470 cm−1. The root mean square errors of cross-validation for the developed models were 2.36 min (RCT, range 24.9 min), 6.86 mm (a30, range 58 mm), 0.25 SH°/50 mL (TA, range 3.58 SH°/50 mL), and 0.07 (pH, range 1.15). The most successfully predicted attributes were TA, RCT, and pH. The model for the prediction of TA provided approximate prediction (R2 = 0.66), whereas the predictive models developed for RCT and pH could discriminate between high and low values (R2 = 0.59 to 0.62). It was concluded that, although the models require further development to improve their accuracy before their application in industry, MIR spectroscopy has potential application for the assessment of RCT, TA, and pH during routine milk analysis in the dairy industry. The implementation of such models could be a means of improving MCP through phenotypic-based selection programs and to amend milk payment systems to incorporate MCP into their payment criteria.

Access to the countryside of England and Wales: popular leisure; commodified culture

Risk and uncertainty are, to say the least, poorly considered by most individuals involved in real estate analysis - in both development and investment appraisal. Surveyors continue to express 'uncertainty' about the value (risk) of using relatively objective methods of analysis to account for these factors. These methods attempt to identify the risk elements more explicitly. Conventionally this is done by deriving probability distributions for the uncontrolled variables in the system. A suggested 'new' way of "being able to express our uncertainty or slight vagueness about some of the qualitative judgements and not From its modern origins, associated with the urbanising effect of industrialisation, walking has remained a popular form of outdoor recreation. It has, furthermore, remained an important site of class struggle, with the 'landless' seeking to establish their moral 'citizen' right to roam over open country in contradistinction to the 'landed', who have successfully limited this right to legally-defined public rights of way. In the face of declining farm incomes, however, farmers and landowners have, apparently, modified their attitudes towards public access, but only in return for compensation and management payments under grant schemes such as Countryside Stewardship and the Countryside Premium Scheme. With the Ministry of Agriculture, Fisheries and Food now seeking to extend paid access arrangements to other grant schemes, as part of its response to the European Union's Agri-Environment Regulations, access 'rights' are assuming an increasingly commodified form, thereby questioning, if not undermining, the former citizen claims. For rather than being a benefit of citizenship, the existence of limited, often poorly maintained and inadequately signposted, public rights of way has tied inextricably the extension of legally-enforceable access to the needs of the landowners and farmers. At a time of falling prosperity in agriculture, therefore, they have now exercised their discretion by annexing the populism of consumer culture to reproduce the bourgeois liberal values of the market as a principal determinant of the extension of citizen rights of access to the countryside.

eRules: a modular adaptive classification rule learning algorithm for data streams

Advances in hardware and software in the past decade allow to capture, record and process fast data streams at a large scale. The research area of data stream mining has emerged as a consequence from these advances in order to cope with the real time analysis of potentially large and changing data streams. Examples of data streams include Google searches, credit card transactions, telemetric data and data of continuous chemical production processes. In some cases the data can be processed in batches by traditional data mining approaches. However, in some applications it is required to analyse the data in real time as soon as it is being captured. Such cases are for example if the data stream is infinite, fast changing, or simply too large in size to be stored. One of the most important data mining techniques on data streams is classification. This involves training the classifier on the data stream in real time and adapting it to concept drifts. Most data stream classifiers are based on decision trees. However, it is well known in the data mining community that there is no single optimal algorithm. An algorithm may work well on one or several datasets but badly on others. This paper introduces eRules, a new rule based adaptive classifier for data streams, based on an evolving set of Rules. eRules induces a set of rules that is constantly evaluated and adapted to changes in the data stream by adding new and removing old rules. It is different from the more popular decision tree based classifiers as it tends to leave data instances rather unclassified than forcing a classification that could be wrong. The ongoing development of eRules aims to improve its accuracy further through dynamic parameter setting which will also address the problem of changing feature domain values.

An extension of the generalized Birnbaum-Saunders distribution

In this paper we present an extension of the generalized Birnbaum-Saunders distribution family introduced in [Diaz-Garcia, J.A., Leiva-Sanchez, V., 2005. A new family of life distributions based on the contoured elliptically distributions. Journal of Statistical Planning and Inference 128 (2), 445-457] with a view to make it even more flexible in terms of its kurtosis coefficient. Properties involving moments and asymmetry and kurtosis indexes are studied for some special members of this family such as the slash Birnbaum-Saunders and slash-t Birnbaum-Saunders. Simulation studies for some particular cases and a real data analysis are also reported, illustrating the usefulness of the extension considered. (C) 2008 Elsevier B.V. All rights reserved.

En jämförelse av molnbaserade realtidsanalystjänster : Skillnader i användbarhet mellan multi-tenant och single-tenant arkitekturer

Internet of Things är ett samlingsbegrepp för den utveckling som innebär att olika typer av enheter kan förses med sensorer och datachip som är uppkopplade mot internet. En ökad mängd data innebär en ökad förfrågan på lösningar som kan lagra, spåra, analysera och bearbeta data. Ett sätt att möta denna förfrågan är att använda sig av molnbaserade realtidsanalystjänster. Multi-tenant och single-tenant är två typer av arkitekturer för molnbaserade realtidsanalystjänster som kan användas för att lösa problemen med hanteringen av de ökade datamängderna. Dessa arkitekturer skiljer sig åt när det gäller komplexitet i utvecklingen. I detta arbete representerar Azure Stream Analytics en multi-tenant arkitektur och HDInsight/Storm representerar en single-tenant arkitektur. För att kunna göra en jämförelse av molnbaserade realtidsanalystjänster med olika arkitekturer, har vi valt att använda oss av användbarhetskriterierna: effektivitet, ändamålsenlighet och användarnöjdhet. Vi kom fram till att vi ville ha svar på följande frågor relaterade till ovannämnda tre användbarhetskriterier: • Vilka likheter och skillnader kan vi se i utvecklingstider? • Kan vi identifiera skillnader i funktionalitet? • Hur upplever utvecklare de olika analystjänsterna? Vi har använt en design and creation strategi för att utveckla två Proof of Concept prototyper och samlat in data genom att använda flera datainsamlingsmetoder. Proof of Concept prototyperna inkluderade två artefakter, en för Azure Stream Analytics och en för HDInsight/Storm. Vi utvärderade dessa genom att utföra fem olika scenarier som var för sig hade 2-5 delmål. Vi simulerade strömmande data genom att låta en applikation kontinuerligt slumpa fram data som vi analyserade med hjälp av de två realtidsanalystjänsterna. Vi har använt oss av observationer för att dokumentera hur vi arbetade med utvecklingen av analystjänsterna samt för att mäta utvecklingstider och identifiera skillnader i funktionalitet. Vi har även använt oss av frågeformulär för att ta reda på vad användare tyckte om analystjänsterna. Vi kom fram till att Azure Stream Analytics initialt var mer användbart än HDInsight/Storm men att skillnaderna minskade efter hand. Azure Stream Analytics var lättare att arbeta med vid simplare analyser medan HDInsight/Storm hade ett bredare val av funktionalitet.

Likelihood estimate of treatment effects under selection bias

We consider methods for estimating causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, simple comparison of treated and control outcomes will not generally yield valid estimates of casual effects. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based onsome strong assumptions, which are not directly testable. In this paper, we present an alternative modeling approachto draw causal inference by using share random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but it is also less sensitive to model misspecifications, which we consider, than the existing methods.

Opções reais em decisões de investimento de exploração e produção

Este trabalho faz uma revisão dos principais conceitos que definem a Teoria de Opções Reais. Tem como objetivo discutir o problema da decisão de investimento sob incerteza aplicado a problemas de Exploração e Produção de petróleo (E&P). Foram priorizados modelos simples que podem ser facilmente implantados no dia a dia de uma empresa, incluindo o clássico de Paddock, Siegel e Smith (1988). Os modelos discutidos são elaborados com Movimento Geométrico Browniano, que pode ser uma aproximação razoável para a modelagem de preços, a depender dos parâmetros considerados. Em particular, é apresentado um modelo de opção composta para exploração, que se revela mais apropriado por considerar o risco geológico e os estágios da opção com expiração diferenciada. A priorização de investimentos com auxílio de OR para uma carteira representativa de um portfolio de projetos de Produção também é testada, resultando numa maior relação VPL / Investimento da carteira selecionada.

Opções reais: exemplo de aplicação para avaliação de reservas petrolíferas

Este trabalho teve como objetivo incluir flexibilidades gerenciais (tais como técnicas de injeção de gás e água) na avaliação de reservatórios. Concluimos que esta técnicas podem aumentar o valor dos reservatórios em até 25% segundo a teoria de opções reais. A principal vantagem da metodologia de teoria de opções face a tradicional técnica de fluxo de caixa descontado é levar em conta as questões operacionais da indústria do petróleo. Utilizamos dois modelos clássicos para a precificação de reservatórios de petróleo, e aplicamos uma análise de sensibilidade para determinarmos quais fatores são mais relevantes no seu valor econômico. Como era de se esperar em ambos os modelos, o tempo de concessão, bem como a taxa de convenience e/ou dividend yield foram os fatores mais importantes.

A utilização da teoria de opções reais na determinação do valor econômico de investimentos em empresas e projetos

Este trabalho objetivou estudar o modelo de avaliação de empresas e projetos fundamentado na Teoria de Opções Reais. Foi demonstrado que, dado a existência de incertezas sobre os acontecimentos futuros e a possibilidade de os investidores modificarem suas decisões no decorrer do tempo, os modelos tradicionais de avaliação erram, pois desconsideram as modificações que a taxa de desconto utilizada sofre em função de uma decisão tomada sobre uma opção qualquer existente. Por outro lado, com a utilização da Teoria de Opções Reais é possível identificar estas opções e avaliá-las de forma correta. Apresentou-se um exemplo em que determinado investimento foi avaliado pelo modelo de Desconto dos Fluxos de Caixa e pela Teoria de Opções Reais, o qual demonstrou que os modelos tradicionais erram ao não considerar e valorar as opções reais existentes, confirmando desta forma a proposição inicial do trabalho.

Opções reais em projetos de investimentos: o caso de uma planta de liquefação de gás natural com flexibilidade de troca de mercado e de troca de produto

O objetivo deste trabalho é revisar os principais aspectos teóricos para a aplicação de Opções Reais em avaliação de projetos de investimento e analisar, sob esta metodologia, um caso real de projeto para investir na construção de uma Planta de Liquefação de gás natural. O estudo do caso real considerou a Opção de Troca de Mercado, ao avaliar a possibilidade de colocação de cargas spot de GNL em diferentes mercados internacionais e a Opção de Troca de Produto, devido à flexibilidade gerencial de não liquefazer o gás natural, deixando de comercializar GNL no mercado internacional e passando a vender gás natural seco no mercado doméstico. Para a valoração das Opções Reais foi verificado, através da série histórica dos preços de gás natural, que o Movimento Geométrico Browniano não é rejeitado e foram utilizadas simulações de Monte Carlo do processo estocástico neutro ao risco dos preços. O valor da Opção de Troca de Mercado fez o projeto estudado mais que dobrar de valor, sendo reduzido com o aumento da correlação dos preços. Por outro lado, o valor da Opção de Troca de Produto é menos relevante, mas também pode atingir valores significativos com o incremento de sua volatilidade. Ao combinar as duas opções simultaneamente, foi verificado que as mesmas não são diretamente aditivas e que o efeito do incremento da correlação dos preços, ao contrário do que ocorre na Opção de Troca de Mercado, é inverso na Opção de Troca de Produto, ou seja, o derivativo aumenta de valor com uma maior correlação, apesar do valor total das opções integradas diminuir.