Development of paper-based color test-strip for drug detection in aquatic environment: Application to oxytetracycline

The wide use of antibiotics in aquaculture has led to the emergence of resistant microbial species. It should be avoided/minimized by controlling the amount of drug employed in fish farming. For this purpose, the present work proposes test-strip papers aiming at the detection/semi-quantitative determination of organic drugs by visual comparison of color changes, in a similar analytical procedure to that of pH monitoring by universal pH paper. This is done by establishing suitable chemical changes upon cellulose, attributing the paper the ability to react with the organic drug and to produce a color change. Quantitative data is also enabled by taking a picture and applying a suitable mathematical treatment to the color coordinates given by the HSL system used by windows. As proof of concept, this approach was applied to oxytetracycline (OXY), one of the antibiotics frequently used in aquaculture. A bottom-up modification of paper was established, starting by the reaction of the glucose moieties on the paper with 3-triethoxysilylpropylamine (APTES). The so-formed amine layer allowed binding to a metal ion by coordination chemistry, while the metal ion reacted after with the drug to produce a colored compound. The most suitable metals to carry out such modification were selected by bulk studies, and the several stages of the paper modification were optimized to produce an intense color change against the concentration of the drug. The paper strips were applied to the analysis of spiked environmental water, allowing a quantitative determination for OXY concentrations as low as 30 ng/mL. In general, this work provided a simple, method to screen and discriminate tetracycline drugs, in aquaculture, being a promising tool for local, quick and cheap monitoring of drugs.

Development of paper-based color test-strip for drug detection in aquatic environment: Application to oxytetracycline

The wide use of antibiotics in aquaculture has led to the emergence of resistant microbial species. It should be avoided/minimized by controlling the amount of drug employed in fish farming. For this purpose, the present work proposes test-strip papers aiming at the detection/semi-quantitative determination of organic drugs by visual comparison of color changes, in a similar analytical procedure to that of pH monitoring by universal pH paper. This is done by establishing suitable chemical changes upon cellulose, attributing the paper the ability to react with the organic drug and to produce a color change. Quantitative data is also enabled by taking a picture and applying a suitable mathematical treatment to the color coordinates given by the HSL system used by windows. As proof of concept, this approach was applied to oxytetracycline (OXY), one of the antibiotics frequently used in aquaculture. A bottom-up modification of paper was established, starting by the reaction of the glucose moieties on the paper with 3-triethoxysilylpropylamine (APTES). The so-formed amine layer allowed binding to a metal ion by coordination chemistry, while the metal ion reacted after with the drug to produce a colored compound. The most suitable metals to carry out such modification were selected by bulk studies, and the several stages of the paper modification were optimized to produce an intense color change against the concentration of the drug. The paper strips were applied to the analysis of spiked environmental water, allowing a quantitative determination for OXY concentrations as low as 30 ng/mL. In general, this work provided a simple, method to screen and discriminate tetracycline drugs, in aquaculture, being a promising tool for local, quick and cheap monitoring of drugs.

Online versus postal questionnaires: a comparison between two data collection methods

Objectives : The purpose of this article is to find out differences between surveys using paper and online questionnaires. The author has deep knowledge in the case of questions concerning opinions in the development of survey based research, e.g. the limits of postal and online questionnaires. Methods : In the physician studies carried out in 1995 (doctors graduated in 1982-1991), 2000 (doctors graduated in 1982-1996), 2005 (doctors graduated in 1982-2001), 2011 (doctors graduated in 1977-2006) and 457 family doctors in 2000, were used paper and online questionnaires. The response rates were 64%, 68%, 64%, 49% and 73%, respectively. Results : The results of the physician studies showed that there were differences between methods. These differences were connected with using paper-based questionnaire and online questionnaire and response rate. The online-based survey gave a lower response rate than the postal survey. The major advantages of online survey were short response time; very low financial resource needs and data were directly loaded in the data analysis software, thus saved time and resources associated with the data entry process. Conclusions : The current article helps researchers with planning the study design and choosing of the right data collection method.

Desenvolvimento de métodos rápidos para deteção de drogas no meio aquático

A vasta aplicação de antibióticos em sistemas de aquacultura tem conduzido ao aparecimento de espécies microbianas resistentes, devendo ser evitada ou, se possível, minimizada. A minimização implica um controlo muito rigoroso das doses aplicadas, algo que só pode ser realizado se todo o processo analítico for simples, barato e puder ser implementado no local. O presente trabalho descreve para este efeito um sistema sensor constituído por papel quimicamente modificado, cujo procedimento analítico foi semelhante à monitorização de pH através das conhecidas tiras indicadoras de pH universal. O papel foi modificado com base em reacções de monocamadas e assumiu uma coloração típica após contacto com o antibiótico. A intensidade da coloração estava também relacionada com a concentração desse antibiótico. Como prova deste conceito, o sensor proposto foi desenhado tendo em vista a monitorização de oxitetraciclina, um dos antibióticos utilizados neste contexto com elevada frequência. A modificação do papel foi baseada na alteração química das unidades de glucose na matriz sólida por reacção covalente com reagentes apropriados. Foram utilizadas duas estratégias diferentes para este efeito: uma foi baseada em reacções de tipo sol-gel e a outra em reacção de adição nucleófila. Posteriormente, o papel foi modificado com espécies metálicas capazes de mudar de cor na presença da oxitetraciclina. Estas modificações químicas foram avaliadas e optimizadas relativamente a vários parâmetros, no sentido de promover uma variação de cor intensa face à concentração de antibiótico. Procedeu-se ainda ao controlo desta modificação por técnicas de espectroscopia de infravermelho. A variação de cor foi avaliada por comparação visual, mas registada por imagem digital. Os materiais sensores preparados foram ainda caracterizados do ponto de vista do seu desempenho analítico. Incluíram-se aqui a identificação de uma relação linear entre coordenadas de cor e concentração, a atribuição de uma gama de concentrações capaz de fornecer uma resposta previsível e resposta cruzada face a outros antibióticos. Procedeu-se ainda à aplicação dos sensores numa amostra de água ambiental dopada com antibiótico. De uma forma geral, foi possível estabelecer um processo simples de modificação de papel capaz de aferir a presença e a quantidade de tetraciclinas, mais concretamente a oxitetraciclina. O processo aqui estabelecido é promissor, antevendo a concretização de uma metodologia simples, barata e local para a monitorização de anitbióticos em águas.

Accounting education in an action-based learning environment: lessons learned

In the context of the Bologna Declaration a change is taking place in the teaching/learning paradigm. From teaching-centered education, which emphasizes the acquisition and transmission of knowledge, we now speak of learning-centered education, which is more demanding for students. This paradigm promotes a continuum of lifelong learning, where the individual needs to be able to handle knowledge, to select what is appropriate for a particular context, to learn permanently and to understand how to learn in new and rapidly changing situations. One attempt to face these challenges has been the experience of ISCAP regarding the teaching/learning of accounting in the course Managerial Simulation. This paper describes the process of teaching, learning and assessment in an action-based learning environment. After a brief general framework that focuses on education objectives, we report the strengths and limitations of this teaching/learning tool. We conclude with some lessons from the implementation of the project.

Learning to manage in knowledge based organizations: the role of portfolios

Paper presented at the 8th European Conference on Knowledge Management, Barcelona, 6-7 Sep. 2008 URL: http://www.academic-conferences.org/eckm/eckm2007/eckm07-home.htm

MASCEM improvement for agent based coalitions

This paper presents MASCEM - Multi-Agent Simulator for Electricity Markets improvement towards an enlarged model for Seller Agents coalitions. The simulator has been improved, both regarding its user interface and internal structure. The OOA, used as development platform, version was updated and the multi-agent model was adjusted for implementing and testing several negotiations regarding Seller agents’ coalitions. Seller coalitions are a very important subject regarding the increased relevance of Distributed Generation under liberalised electricity markets.

TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

Virtual power players demand response programs management based on locational marginal prices

Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

Cooperative scheduling system with emergent swarm based behavior

This paper presents a Swarm based Cooperation Mechanism for scheduling optimization. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to support decision making in agile manufacturing environments. Agents coordinate their actions automatically without human supervision considering a common objective – global scheduling solution taking advantages from collective behavior of species through implicit and explicit cooperation. The performance of the cooperation mechanism will be evaluated consider implicit cooperation at first stage through ACS, PSO and ABC algorithms and explicit through cooperation mechanism application.