The selection of a model microalgal species as biomaterial for a novel aquatic phytotoxicity assay

A phytotoxicity assay based on the ToxY-PAM dual-channel yield analyser has been developed and successfully incorporated into field assessments for the detection of phytotoxicants in water. As a means of further exploring the scope of the assay application and of selecting a model biomaterial to complement the instrument design, nine algal species were exposed to four chemical substances deemed of priority for water quality monitoring purposes (chlorpyrifos, copper, diuron and nonylphenol ethoxylate). Inter-species differences in sensitivity to the four toxicants varied by a factor of 1.9-100. Measurements of photosystem-II quantum yield using these nine single-celled microalgae as biomaterial corroborated previous studies which have shown that the ToxY-PAM dual-channel yield analyser is a highly sensitive method for the detection of PS-II impacting herbicides. Besides Phaeodactylum tricornutum, the previously applied biomaterial, three other species consistently performed well (Nitzschia closterium, Chlorella vulgaris and Dunaliella tertiolecta) and will be used in further test optimisation experiments. In addition to sensitivity, response time was evaluated and revealed a high degree of variation between species and toxicants. While most species displayed relatively weak and slow responses to copper, C. vulgaris demonstrated an IC10 of 51 μ g L-1, with maximum response measured within 25 minutes and inhibition being accompanied by a large decrease in fluorescence yield. The potential for this C vulgaris-based bioassay to be used for the detection of copper is discussed. There was no evidence that the standard ToxY-PAM protocol, using these unicellular algae species, could be used for the detection of chlorpyrifos or nonylphenol ethoxylate at environmentally relevant levels. © 2005 Elsevier B.V. All rights reserved.

Heavy tails, importance sampling and cross-entropy

We consider the problem of estimating P(Yi + (...) + Y-n > x) by importance sampling when the Yi are i.i.d. and heavy-tailed. The idea is to exploit the cross-entropy method as a toot for choosing good parameters in the importance sampling distribution; in doing so, we use the asymptotic description that given P(Y-1 + (...) + Y-n > x), n - 1 of the Yi have distribution F and one the conditional distribution of Y given Y > x. We show in some specific parametric examples (Pareto and Weibull) how this leads to precise answers which, as demonstrated numerically, are close to being variance minimal within the parametric class under consideration. Related problems for M/G/l and GI/G/l queues are also discussed.

A note on DEA models in technology selection:an improvement of Karsak and Ahiska's approach

This paper introduces a compact form for the maximum value of the non-Archimedean in Data Envelopment Analysis (DEA) models applied for the technology selection, without the need to solve a linear programming (LP). Using this method the computational performance the common weight multi-criteria decision-making (MCDM) DEA model proposed by Karsak and Ahiska (International Journal of Production Research, 2005, 43(8), 1537-1554) is improved. This improvement is significant when computational issues and complexity analysis are a concern.

A comprehensive portfolio construction under stochastic environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. ^ A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: (a) increase the efficiency of the portfolio optimization process, (b) implement large-scale optimizations, and (c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. ^ The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. ^ The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH). ^

The main criteria of biomass selection for energy generation in Brazil

The principal aim of this paper is to examine the criteria assisting in the selection of biomass for energy generation in Brazil. To reach the aim, this paper adopts case study and survey research methods to collect information from four biomass energy case companies and solicits opinions from experts. The data gathered are analysed in line with a wide range of related data, including selection criteria for biomass and its importance, energy policies in Brazil, availability of biomass feedstock in Brazil and its characteristics, as well as status quo of biomass-based energy in Brazil. The findings of the paper demonstrate that there are ten main criteria in biomass selection for energy generation in Brazil. They comprise geographical conditions, availability of biomass feedstock, demand satisfaction, feedstock costs and oil prices, energy content of biomass feedstock, business and economic growth, CO2 emissions of biomass end-products, effects on soil, water and biodiversity, job creation and local community support, as well as conversion technologies. Furthermore, the research also found that these main criteria cannot be grouped on the basis of sustainability criteria, nor ranked by their importance as there is correlation between each criterion such as a cause and effect relationship, as well as some overlapping areas. Consequently, this means that when selecting biomass more comprehensive consideration is advisable.

A Comprehensive Portfolio Construction Under Stochastic Environment

Prior research has established that idiosyncratic volatility of the securities prices exhibits a positive trend. This trend and other factors have made the merits of investment diversification and portfolio construction more compelling. A new optimization technique, a greedy algorithm, is proposed to optimize the weights of assets in a portfolio. The main benefits of using this algorithm are to: a) increase the efficiency of the portfolio optimization process, b) implement large-scale optimizations, and c) improve the resulting optimal weights. In addition, the technique utilizes a novel approach in the construction of a time-varying covariance matrix. This involves the application of a modified integrated dynamic conditional correlation GARCH (IDCC - GARCH) model to account for the dynamics of the conditional covariance matrices that are employed. The stochastic aspects of the expected return of the securities are integrated into the technique through Monte Carlo simulations. Instead of representing the expected returns as deterministic values, they are assigned simulated values based on their historical measures. The time-series of the securities are fitted into a probability distribution that matches the time-series characteristics using the Anderson-Darling goodness-of-fit criterion. Simulated and actual data sets are used to further generalize the results. Employing the S&P500 securities as the base, 2000 simulated data sets are created using Monte Carlo simulation. In addition, the Russell 1000 securities are used to generate 50 sample data sets. The results indicate an increase in risk-return performance. Choosing the Value-at-Risk (VaR) as the criterion and the Crystal Ball portfolio optimizer, a commercial product currently available on the market, as the comparison for benchmarking, the new greedy technique clearly outperforms others using a sample of the S&P500 and the Russell 1000 securities. The resulting improvements in performance are consistent among five securities selection methods (maximum, minimum, random, absolute minimum, and absolute maximum) and three covariance structures (unconditional, orthogonal GARCH, and integrated dynamic conditional GARCH).

Multi-Device Selection Scheduling in Non-Identically Distributed Fading Channels

Multiuser selection scheduling concept has been recently proposed in the literature in order to increase the multiuser diversity gain and overcome the significant feedback requirements for the opportunistic scheduling schemes. The main idea is that reducing the feedback overhead saves per-user power that could potentially be added for the data transmission. In this work, the authors propose to integrate the principle of multiuser selection and the proportional fair scheduling scheme. This is aimed especially at power-limited, multi-device systems in non-identically distributed fading channels. For the performance analysis, they derive closed-form expressions for the outage probabilities and the average system rate of the delay-sensitive and the delay-tolerant systems, respectively, and compare them with the full feedback multiuser diversity schemes. The discrete rate region is analytically presented, where the maximum average system rate can be obtained by properly choosing the number of partial devices. They optimise jointly the number of partial devices and the per-device power saving in order to maximise the average system rate under the power requirement. Through the authors’ results, they finally demonstrate that the proposed scheme leveraging the saved feedback power to add for the data transmission can outperform the full feedback multiuser diversity, in non-identical Rayleigh fading of devices’ channels.

Modelos autorregressivos com valores inteiros não negativos : aplicação em séries económicas de Cabo Verde

No estudo de séries temporais, os processos estocásticos usuais assumem que as distribuições marginais são contínuas e, em geral, não são adequados para modelar séries de contagem, pois as suas características não lineares colocam alguns problemas estatísticos, principalmente na estimação dos parâmetros. Assim, investigou-se metodologias apropriadas de análise e modelação de séries com distribuições marginais discretas. Neste contexto, Al-Osh and Alzaid (1987) e McKenzie (1988) introduziram na literatura a classe dos modelos autorregressivos com valores inteiros não negativos, os processos INAR. Estes modelos têm sido frequentemente tratados em artigos científicos ao longo das últimas décadas, pois a sua importância nas aplicações em diversas áreas do conhecimento tem despertado um grande interesse no seu estudo. Neste trabalho, após uma breve revisão sobre séries temporais e os métodos clássicos para a sua análise, apresentamos os modelos autorregressivos de valores inteiros não negativos de primeira ordem INAR (1) e a sua extensão para uma ordem p, as suas propriedades e alguns métodos de estimação dos parâmetros nomeadamente, o método de Yule-Walker, o método de Mínimos Quadrados Condicionais (MQC), o método de Máxima Verosimilhança Condicional (MVC) e o método de Quase Máxima Verosimilhança (QMV). Apresentamos também um critério automático de seleção de ordem para modelos INAR, baseado no Critério de Informação de Akaike Corrigido, AICC, um dos critérios usados para determinar a ordem em modelos autorregressivos, AR. Finalmente, apresenta-se uma aplicação da metodologia dos modelos INAR em dados reais de contagem relativos aos setores dos transportes marítimos e atividades de seguros de Cabo Verde.

Design of passive methane oxidation biosystems considering their response to the presence of capillary barrier effect

La construction des biosystèmes d’oxydation passive du méthane (BOPM) est une option économique et durable pour réduire les émissions de méthane des sites d’enfouissement de déchets et des effets subséquents du réchauffement climatique. Les BOPM sont constitués de deux couches principales: la couche d'oxydation du méthane (MOL) et la couche de distribution du gaz (GDL). L'oxydation du méthane se produit dans la MOL par les réactions biochimiques des bactéries méthanotrophes, et la GDL est construite sous la MOL pour intercepter et distribuer les émissions fugitives de biogaz à la base de la MOL. Fondamentalement, l'efficacité d'un BOPM est définie en fonction de l'efficacité d'oxydation du méthane dans la MOL. Par conséquent, il est indispensable de fournir des conditions adéquates pour les activités bactériennes des méthanotrophes. En plus des paramètres environnementaux, l'intensité et la distribution du biogaz influencent l'efficacité des BOPM, et ils peuvent rendre le matériau de la MOL - avec une grande capacité d'accueillir les activités bactériennes - inutilisables en termes d'oxydation du méthane sur place. L'effet de barrière capillaire le long de l'interface entre la GDL et la MOL peut provoquer des émissions localisées de méthane, due à la restriction ou la distribution non uniforme de l’écoulement ascendant du biogaz à la base de la MOL. L'objectif principal de cette étude est d'incorporer le comportement hydraulique non saturé des BOPM dans la conception des BOPM, afin d’assurer la facilité et la distribution adéquates de l'écoulement du biogaz à la base de la MOL. Les fonctions de perméabilité à l'air des matériaux utilisés pour construire la MOL des BOPM expérimentaux au site d’enfouissement des déchets de St Nicéphore (Québec, Canada), ainsi que celles d'autres de la littérature technique, ont été étudiés pour évaluer le comportement d'écoulement non saturé du gaz dans les matériaux et pour identifier le seuil de migration sans restriction du gaz. Ce dernier seuil a été introduit en tant que un paramètre de conception avec lequel le critère de conception recommandé ici, c’est à dire la longueur de la migration sans restriction de gaz (LMSG), a été défini. La LMSG est considérée comme la longueur le long de l'interface entre la GDL et la MOL où le biogaz peut migrer à travers la MOL sans restriction. En réalisant des simulations numériques avec SEEP/W, les effets de la pente de l'interface, des paramètres définissant la courbe de rétention d'eau, de la fonction de la conductivité hydraulique du matériau de la MOL sur la valeur de la LMSG (représentant la facilité d'écoulement du biogaz à l'interface) et de la distribution de l'humidité (et par conséquent celle du biogaz) ont été évalués. Selon les résultats des simulations, la conductivité hydraulique saturée et la distribution des tailles de pores du matériau de la MOL sont les paramètres les plus importants sur la distribution de l'humidité le long de l'interface. Ce dernier paramètre influe également sur la valeur du degré de saturation et donc la facilité du biogaz à la base de la MOL. La densité sèche du matériau de MOL est un autre paramètre qui contrôle la facilité d'écoulement ascendant du biogaz. Les limitations principales de la présente étude sont associées au nombre de matériaux de MOL testés et à l'incapacité de SEEP/W de considérer l'évapotranspiration. Toutefois, compte tenu des hypothèses raisonnables dans les simulations et en utilisant les données de la littérature, on a essayé de réduire ces limitations. En utilisant les résultats des expériences et des simulations numériques, des étapes et des considérations de conception pour la sélection du matériau de MOL et de la pente d'interface ont été proposées. En effet,le comportement hydraulique non saturé des matériaux serait intégré dans les nécessités de conception pour un BOPM efficace, de sorte que la capacité maximale possible d'oxydation du méthane du matériau de la MOL soit exploitée.

Selection of ionic liquids to be used as separation agents for terpenes and terpenoids

In this work, ionic liquids are evaluated for the first time as solvents for extraction and entrainers in separation processes involving terpenes and terpenoids. For that purpose, activity coefficients at infinite dilution, γ13 ∞, of terpenes and terpenoids, in the ionic liquids [C4mim]Cl, [C4mim][CH3SO3], [C4mim][(CH3)2PO4] and [C4mim][CF3SO3] were determined by gas−liquid chromatography at six temperatures in the range 398.15 to 448.15 K. On the basis of the experimental values, a correlation of γ13 ∞ with an increase of the solubility parameters is proposed. The infinite dilution thermodynamic functions were calculated showing the entropic effect is dominant over the enthalpic. Gas−liquid partition coefficients give indications about the recovery and purification of terpenes and terpenoids from ionic liquid solutions. Presenting a strong innovative character, COSMO-RS was evaluated for the description of the selectivities and capacities, showing to be a useful tool for the screening of ionic liquids in order to find suitable candidates for terpenes and terpenoids extraction, and separation. COSMO-RS predictions show that in order to achieve the maximum separation efficiency, polar anions should be used such as bis(2,4,4-trimethylpentyl)phosphinate or acetate, whereas high capacities require nonpolar cations such as phosphonium.

Modelos autorregressivos com valores inteiros não negativos : aplicação em séries económicas de Cabo Verde

No estudo de séries temporais, os processos estocásticos usuais assumem que as distribuições marginais são contínuas e, em geral, não são adequados para modelar séries de contagem, pois as suas características não lineares colocam alguns problemas estatísticos, principalmente na estimação dos parâmetros. Assim, investigou-se metodologias apropriadas de análise e modelação de séries com distribuições marginais discretas. Neste contexto, Al-Osh and Alzaid (1987) e McKenzie (1988) introduziram na literatura a classe dos modelos autorregressivos com valores inteiros não negativos, os processos INAR. Estes modelos têm sido frequentemente tratados em artigos científicos ao longo das últimas décadas, pois a sua importância nas aplicações em diversas áreas do conhecimento tem despertado um grande interesse no seu estudo. Neste trabalho, após uma breve revisão sobre séries temporais e os métodos clássicos para a sua análise, apresentamos os modelos autorregressivos de valores inteiros não negativos de primeira ordem INAR (1) e a sua extensão para uma ordem p, as suas propriedades e alguns métodos de estimação dos parâmetros nomeadamente, o método de Yule-Walker, o método de Mínimos Quadrados Condicionais (MQC), o método de Máxima Verosimilhança Condicional (MVC) e o método de Quase Máxima Verosimilhança (QMV). Apresentamos também um critério automático de seleção de ordem para modelos INAR, baseado no Critério de Informação de Akaike Corrigido, AICC, um dos critérios usados para determinar a ordem em modelos autorregressivos, AR. Finalmente, apresenta-se uma aplicação da metodologia dos modelos INAR em dados reais de contagem relativos aos setores dos transportes marítimos e atividades de seguros de Cabo Verde.

A Multi-Criteria GIS-Based Route Selection Tool for Hazardous Material Transport: Consideration of Environmental Consequence, Traffic Congestions and Costs

Hazardous materials are substances that, if not regulated, can pose a threat to human populations and their environmental health, safety or property when transported in commerce. About 1.5 million tons of hazardous material shipments are transported by truck in the US annually, with a steady increase of approximately 5% per year. The objective of this study was to develop a routing tool for hazardous material transport in order to facilitate reduced environmental impacts and less transportation difficulties, yet would also find paths that were still compelling for the shipping carriers as a matter of trucking cost. The study started with identification of inhalation hazard impact zones and explosion protective areas around the location of hypothetical hazardous material releases, considering different parameters (i.e., chemicals characteristics, release quantities, atmospheric condition, etc.). Results showed that depending on the quantity of release, chemical, and atmospheric stability (a function of wind speed, meteorology, sky cover, time and location of accidents, etc.) the consequence of these incidents can differ. The study was extended by selection of other evaluation criteria for further investigation because health risk as an evaluation criterion would not be the only concern in selection of routes. Transportation difficulties (i.e., road blockage and congestion) were incorporated as important factor due to their indirect impact/cost on the users of transportation networks. Trucking costs were also considered as one of the primary criteria in selection of hazardous material paths; otherwise the suggested routes would have not been convincing for the shipping companies. The last but not least criterion was proximity of public places to the routes. The approach evolved from a simple framework to a complicated and efficient GIS-based tool able to investigate transportation networks of any given study area, and capable of generating best routing options for cargos. The suggested tool uses a multi-criteria-decision-making method, which considers the priorities of the decision makers in choosing the cargo routes. Comparison of the routing options based on each criterion and also the overall suitableness of the path in regards to all the criteria (using a multi-criteria-decision-making method) showed that using similar tools as the one proposed by this study can provide decision makers insights in the area of hazardous material transport. This tool shows the probable consequences of considering each path in a very easily understandable way; in the formats of maps and tables, which makes the tradeoffs of costs and risks considerably simpler, as in some cases slightly compromising on trucking cost may drastically decrease the probable health risk and/or traffic difficulties. This will not only be rewarding to the community by making cities safer places to live, but also can be beneficial to shipping companies by allowing them to advertise as environmental friendly conveyors.

An automatic classifier of emotions built from entropy of noise

The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase. In addition, it can lead to the loss of important information that is usually considered as noise and, consequently, discarded from the analysis. The goal of this study was to evaluate if the ECG noise allows for the classification of emotions, while using its entropy as an input in a decision tree classifier. We collected the ECG signal from 25 healthy participants while they were presented with videos eliciting negative (fear and disgust) and neutral emotions. The results indicated that the neutral condition showed a perfect identification (100%), whereas the classification of negative emotions indicated good identification performances (60% of sensitivity and 80% of specificity). These results suggest that the entropy of noise contains relevant information that can be useful to improve the analysis of the physiological correlates of emotion.