Rapid automated method for on-site determination of sulfadiazine in fish farming: a stainless steel veterinary syringe coated with a selective membrane of PVC serving as a potentiometric detector in a flow-injection-analysis system

Sulfadiazine is an antibiotic of the sulfonamide group and is used as a veterinary drug in fish farming. Monitoring it in the tanks is fundamental to control the applied doses and avoid environmental dissemination. Pursuing this goal, we included a novel potentiometric design in a flow-injection assembly. The electrode body was a stainless steel needle veterinary syringe of 0.8-mm inner diameter. A selective membrane of PVC acted as a sensory surface. Its composition, the length of the electrode, and other flow variables were optimized. The best performance was obtained for sensors of 1.5-cm length and a membrane composition of 33% PVC, 66% onitrophenyloctyl ether, 1% ion exchanger, and a small amount of a cationic additive. It exhibited Nernstian slopes of 61.0 mV decade-1 down to 1.0×10-5 mol L-1, with a limit of detection of 3.1×10-6 mol L-1 in flowing media. All necessary pH/ionic strength adjustments were performed online by merging the sample plug with a buffer carrier of 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid, pH 4.9. The sensor exhibited the advantages of a fast response time (less than 15 s), long operational lifetime (60 days), and good selectivity for chloride, nitrite, acetate, tartrate, citrate, and ascorbate. The flow setup was successfully applied to the analysis of aquaculture waters. The analytical results were validated against those obtained with liquid chromatography–tandem mass spectrometry procedures. The sampling rate was about 84 samples per hour and recoveries ranged from 95.9 to 106.9%.

Calibration Method for Underwater Visual Ground-Truth System

This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.

Step based physical activity guidelines for preschool-aged children

Objective Public health organizations recommend that preschool-aged children accumulate at least 3 h of physical activity (PA) daily. Objective monitoring using pedometers offers an opportunity to measure preschooler's PA and assess compliance with this recommendation. The purpose of this study was to derive step-based recommendations consistent with the 3 h PA recommendation for preschool-aged children. Method The study sample comprised 916 preschool-aged children, aged 3 to 6 years (mean age = 5.0 ± 0.8 years). Children were recruited from kindergartens located in Portugal, between 2009 and 2013. Children wore an ActiGraph GT1M accelerometer that measured PA intensity and steps per day simultaneously over a 7-day monitoring period. Receiver operating characteristic (ROC) curve analysis was used to identify the daily step count threshold associated with meeting the daily 3 hour PA recommendation. Results A significant correlation was observed between minutes of total PA and steps per day (r = 0.76, p < 0.001). The optimal step count for ≥ 3 h of total PA was 9099 steps per day (sensitivity (90%) and specificity (66%)) with area under the ROC curve = 0.86 (95% CI: 0.84 to 0.88). Conclusion Preschool-aged children who accumulate less than 9000 steps per day may be considered Insufficiently Active.

Alterações do equilíbrio em indivíduos com ou sem síndrome de Down em repouso e durante a execução de uma tarefa

O equilíbrio é fundamental para o desempenho de Actividades de Vida Diária e de Vida Diária Instrumentais que permitem aos indivíduos com Síndrome de Down manter a sua autonomia. O objectivo principal deste estudo foi verificar as características do estado de equilíbrio em indivíduos com e sem Síndrome de Down, em repouso e durante a execução de uma tarefa, de modo a compreender as implicações da alteração do estado de equilíbrio no desempenho de actividades. Neste estudo, foram seleccionadas duas amostras, de forma probabilística por conveniência, com indivíduos de ambos os sexos. A amostra do grupo experimental foi constituída por oito indivíduos com diagnóstico de Síndrome de Down, com idades compreendidas entre os 17 e os 39 anos de idade. A amostra do grupo de controlo foi constituída por doze indivíduos sem patologia, com idades compreendidas entre os 21 e os 37 anos. O equilíbrio foi avaliado com recurso a uma Plataforma de Forças (Bertec Corporation FP4060-10) para medir a deslocação do centro de pressão (CP) dos indivíduos. A avaliação do equilíbrio decorreu em dois momentos, na posição de pé: em repouso e no desempenho da tarefa segurar um saco de compras. Os resultados diferem entre os dois grupos em repouso e durante a execução da tarefa (segurar no saco). Os valores das variáveis área e distância de deslocação do CP e oscilações corporais, antero-posterior e médio-lateralmente apresentam resultados significativos, o que sugere diferenças do estado de equilíbrio entre as amostras.

Sistema de neurónios espelho no síndrome de down: estudo das variações dos ritmos Mu No Eeg

A capacidade de compreensão das acções dos outros e de imitação tem sido descrita como fundamental para a cognição social do ser humano. Recentemente tem sido atribuída a responsabilidade desta capacidade a um sistema neuronal denominado de Sistema de Neurónios Espelho, que se tem demonstrado estar afectado em perturbações mentais que se caracterizam por alterações severas da teoria da mente e da empatia, como é o caso do autismo. No caso do Síndrome de Down, verifica-se a coexistência de boas competências sociais e de capacidades práxicas e de imitação intactas, com dificuldades de interpretação de situações sociais e de reconhecimento de emoções, que nos levam a questionar acerca da actividade do seu Sistema de Neurónios Espelho. As oscilações do ritmo de frequências um (8-13 Hz) no córtex sensório-motor perante a observação de acções são consideradas um reflexo da actividade dos neurónios espelho, estando estabelecido que em pessoas saudáveis ocorre uma supressão mu na realização de movimentos com o membro superior e na sua observação quando realizados por outras pessoas. Neste estudo registou-se electroencefalograficamente a supressão dos ritmos mu em 11 pessoas com SD e em 20 pessoas sem SD nas seguintes condições: observação de um vídeo com duas bolas em movimento, observação de um vídeo com um movimento repetido de uma mão e realização movimentos com a mão. A baseline foi registada através da observação de um ponto estático. Constatamos que existe supressão dos ritmos mu na observação das acções dos outros em pessoas com Síndrome Down da mesma forma que ocorre na realização do próprio movimento, sugerindo uma relativa preservação do funcionamento dos neurónios espelho e dos mecanismos básicos de cognição social. Estes resultados vão de encontro aos estudos que apontam para a integridade das capacidades de imitação no Síndrome Down. Verificamos também que não se encontram diferenças significativas na supressão dos ritmos mu entre os grupos de pessoas com Síndrome Down e de Controlo em relação às condições usadas na investigação.

A novel framework for modeling value for the customer, an essay on negotiation

This paper proposes a novel framework for modelling the Value for the Customer, the so-called the Conceptual Model for Decomposing Value for the Customer (CMDVC). This conceptual model is first validated through an exploratory case study where the authors validate both the proposed constructs of the model and their relations. In a second step the authors propose a mathematical formulation for the CMDVC as well as a computational method. This has enabled the final quantitative discussion of how the CMDVC can be applied and used in the enterprise environment, and the final validation by the people in the enterprise. Along this research, we were able to confirm that the results of this novel quantitative approach to model the Value for the Customer is consistent with the company's empirical experience. The paper further discusses the merits and limitations of this approach, proposing that the model is likely to bring value to support not only the contract preparation at an Ex-Ante Negotiation Phase, as demonstrated, but also along the actual negotiation process, as finally confirmed by an enterprise testimonial.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Peer Instruction method in introductory math courses

Learning is not a spectator’s sport. Students do not learn much by just sitting in class listening their teachers, memorizing pre-packaged assignments and spitting out answers. The teaching-learning process has been a constant target of studies, particularly in Higher Education, in consequence of the annual increase of new students. The concern with maintaining a desired quality level in the training of these students, conjugated with the will to widen the access to all of those who finish Secondary School Education, has triggered a greater intervention from the education specialists, in partnership with the teachers of all Higher Education areas, in the analysis of this problem. Considering the particular case of Engineering, it has been witnessed a rising concern with the active learning strategies and forms of assessment. Research has demonstrated that students learn more if they are actively engaged with the material they are studying. In this presentation we describe, present and discuss the techniques and the results of Peer Instruction method in an introductory Calculus courses of an Engineering Bach

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

An efficient method for optimal location and sizing of fixed and switched shunt capacitors in large distribution systems

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.

Research on using the decision tree method in order to select the best alternative for the pharmacies supply

Introduction / Aims: Adopting the important decisions represents a specific task of the manager. An efficient manager takes these decisions during a sistematic process with well-defined elements, each with a precise order. In the pharmaceutical practice and business, in the supply process of the pharmacies, there are situations when the medicine distributors offer a certain discount, but require payment in a shorter period of time. In these cases, the analysis of the offer can be made with the help of the decision tree method, which permits identifying the decision offering the best possible result in a given situation. The aims of the research have been the analysis of the product offers of many different suppliers and the establishing of the most advantageous ways of pharmacy supplying. Material / Methods: There have been studied the general product offers of the following medical stores: A&G Med, Farmanord, Farmexim, Mediplus, Montero and Relad. In the case of medicine offers including a discount, the decision tree method has been applied in order to select the most advantageous offers. The Decision Tree is a management method used in taking the right decisions and it is generally used when one needs to evaluate the decisions that involve a series of stages. The tree diagram is used in order to look for the most efficient means to attain a specific goal. The decision trees are the most probabilistic methods, useful when adopting risk taking decisions. Results: The results of the analysis on the tree diagrams have indicated the fact that purchasing medicines with discount (1%, 10%, 15%) and payment in a shorter time interval (120 days) is more profitable than purchasing without a discount and payment in a longer time interval (160 days). Discussion / Conclusion: Depending on the results of the tree diagram analysis, the pharmacies would purchase from the selected suppliers. The research has shown that the decision tree method represents a valuable work instrument in choosing the best ways for supplying pharmacies and it is very useful to the specialists from the pharmaceutical field, pharmaceutical management, to medicine suppliers, pharmacy practitioners from the community pharmacies and especially to pharmacy managers, chief – pharmacists.

Bid definition method for electricity markets based on an adaptive multiagent system

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

A study on the authentication method for TAmI in ambient intelligence (secure group decision making toolkit)

It is difficult to get the decision about an opinion after many users get the meeting in same place. It used to spend too much time in order to find solve some problem because of the various opinions of each other. TAmI (Group Decision Making Toolkit) is the System to Group Decision in Ambient Intelligence [1]. This program was composed with IGATA [2], WebMeeting and the related Database system. But, because it is sent without any encryption in IP / Password, it can be opened to attacker. They can use the IP / Password to the bad purpose. As the result, although they make the wrong result, the joined member can’t know them. Therefore, in this paper, we studied the applying method of user’s authentication into TAmI.

Derivative-free optimization and filter methods to solve nonlinear constrained problems

In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.