Comparison of Disposable Pipette Extraction and Dispersive Solid-Phase Extraction in the QuEChERS Method for Analysis of Pesticides in Strawberries

In this study, we sought to assess the applicability of GC–MS/MS for the identification and quantification of 36 pesticides in strawberry from integrated pest management (IPM) and organic farming (OF). Citrate versions of QuEChERS (quick, easy, cheap, effective, rugged and safe) using dispersive solid-phase extraction (d-SPE) and disposable pipette extraction (DPX) for cleanup were compared for pesticide extraction. For cleanup, a combination of MgSO4, primary secondary amine and C18 was used for both the versions. Significant differences were observed in recovery results between the two sample preparation versions (DPX and d-SPE). Overall, 86% of the pesticides achieved recoveries (three spiking levels 10, 50 and 200 µg/kg) in the range of 70–120%, with <13% RSD. The matrix effects were also evaluated in both the versions and in strawberries from different crop types. Although not evidencing significant differences between the two methodologies were observed, however, the DPX cleanup proved to be a faster technique and easy to execute. The results indicate that QuEChERS with d-SPE and DPX and GC–MS/MS analysis achieved reliable quantification and identification of 36 pesticide residues in strawberries from OF and IPM.

Enzyme linked immunosorbent assay for rubella antibodies: a simple method of antigen production. A preliminary report

A simple method of rubella antigen production by treatment with sodium desoxycholate for use in enzyme immunoassay (IMT-ELISA) is presented. When this assay was compared with a commercial test (Enzygnost-Rubella, Behring), in the study of 108 sera and 118 filter paper blood samples, 96.9% (219/226) overall agreement and correlation coefficient of 0.90 between absorbances were observed. Seven samples showed discordant results, negative by the commercial kit and positive by our test. Four of those 7 samples were available, being 3 positive by HI.

DNA nanoprobes for molecular detection

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Biológica – especialidade Engenharia Genética, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

A simple and inexprensive method to generate a microaerophilic atmosphere for the isolation of Campylobacter sp

Faeces of 138 chickens were inoculated on Blaser agar plates. One set of plates was incubated in jars with CampyPak envelopes. The others were incubated in "Zip-lock" plastic bags (7 x X in.) and a microaerophilic atmosphere was generated exhaling into the "Zip-lock" plastic bag, after holding the breath for 20 sec. Then, the bag was pressed to evacuate its atmosphere, inflated again, and pressed (4 times), and finally sealed. Campylobacter was isolated from 127 (96.2%) of samples incubated in jars with gas generator envelopes and from 129 (98%) of the specimens incubated into the bags. The proposed methodology offers good savings for cost-conscious laboratories.

Studies on prevalence of Strongyloides infection in Holambra and Maceió, Brazil, by the agar plate faecal culture method

Prevalence of Strongyloides stercoralis infection in three areas of Brazil was surveyed by a recently developed faecal culture method (an agar plate culture). The Strongyloides infection was confirmed in 11.3% of 432 subjects examined. The diagnostic efficacy of the agar plate culture was as high as 93.9% compared to only 28.5% and 26.5% by the Harada-Mori filter paper culture and faecal concentration methods, when faecal samples were examined simultaneously by these three methods. Among the 49 positive samples, about 60% were confirmed to be positive only by the agar plate culture. These results indicate that the agar plate culture is a sensitive new tool for the correct diagnosis of chronic Strongyloides infection.

A single method to stain Malassezia furfur and Corynebacterium minutissimum in scales

A single and practical method to slain Malassezia furfur and Corynebacterium minutissimum in lesions' scales is described. The scales are collected by pressing small pieces of scotch tape (about 4 cm lenght and 2 cm width) onto the lesions and following withdrawl the furfuraceous scales will remain on the glue side. These pieces are then immersed for some minutes in lactophenol-cotton blue stain. Following absorption of the stain the scales are washed in current water to remove the excess of blue stain, dried with filter paper, dehydrated via passage in two bottles containing absolute alcohol and then placed in xylene in a centrifugation tube. The xylene dissolves the scotch tape glue and the scales fall free in the tube. After centrifugation and decantation the scales concentrated on the bottom of the tube are collected with a platinum-loop, placed in Canada balsam on a microscopy slide and closed with a cover slip. The preparations are then ready to be submitted to microscopic examination. Other stains may also be used instead of lactophenol-cotton blue. This method is simple, easily performed, and offers good conditions to study these fungi as well as being useful for the diagnosis of the diseases that they cause.

Application of the EcoBlock method to eco-design - electric hand dryers versus paper towels

Sustainable Construction, Materials and Practice, p. 426-432

Adaptive Learning in Games: Defining Profiles of Competitor Players

Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

Detection and identification of dengue virus isolates from Brazil by a simplified reverse transcription - polymerase chain reaction (RT-PCR) method

We show here a simplified RT-PCR for identification of dengue virus types 1 and 2. Five dengue virus strains, isolated from Brazilian patients, and yellow fever vaccine 17DD as a negative control, were used in this study. C6/36 cells were infected and supernatants were collected after 7 days. The RT-PCR, done in a single reaction vessel, was carried out following a 1/10 dilution of virus in distilled water or in a detergent mixture containing Nonidet P40. The 50 µl assay reaction mixture included 50 pmol of specific primers amplifying a 482 base pair sequence for dengue type 1 and 210 base pair sequence for dengue type 2. In other assays, we used dengue virus consensus primers having maximum sequence similarity to the four serotypes, amplifying a 511 base pair sequence. The reaction mixture also contained 0.1 mM of the four deoxynucleoside triphosphates, 7.5 U of reverse transcriptase, 1U of thermostable Taq DNA polymerase. The mixture was incubated for 5 minutes at 37ºC for reverse transcription followed by 30 cycles of two-step PCR amplification (92ºC for 60 seconds, 53ºC for 60 seconds) with slow temperature increment. The PCR products were subjected to 1.7% agarose gel electrophoresis and visualized by UV light after staining with ethidium bromide solution. Low virus titer around 10 3, 6 TCID50/ml was detected by RT-PCR for dengue type 1. Specific DNA amplification was observed with all the Brazilian dengue strains by using dengue virus consensus primers. As compared to other RT-PCRs, this assay is less laborious, done in a shorter time, and has reduced risk of contamination