Optimal performance assessment for a photo‐Fenton degradation pilot plant driven by solar energy using artificial neural networks

Artificial neural networks (ANN) were proposed as a multivariate experimental design tool for monitoring a photo‐Fenton treatment of wastewaters containing a synthetic mixture of pesticides. ANN and Nelder‐Mead simplex methods were used to find out the optimum operating parameters of a photo‐Fenton pilot plant. ANN was developed to predict the most important operating parameters (e.g., the total organic carbon and the initial mineralization kinetic rate constants of the reactions), which determine the photo‐catalytic degradation efficiency in photo‐Fenton processes. Experimental measurements of temperature, pH, hydrogen peroxide (H₂O₂) consumption, initial concentration of Fe²⁺, and the AE were used as input data for the ANN learning. A feed‐forward with one hidden layer, a Levenberg–Marquardt learning algorithm, a hyperbolic tangent sigmoidal transfer function and a linear transfer function were used to develop the ANN model. The best fitting of the training database was obtained with an ANN architecture constituted by seven neurons in the hidden layer. The simulated results were validated with experimental measurements, showing an acceptable agreement (R² > 0.99). The ANN was subsequently coupled with a Nelder–Mead simplex method to obtain the optimum operating parameters of the photo‐Fenton pilot plant. The H₂O₂ consumption was used as key variable for evaluating the optimization procedure. Errors less than 1% between simulated and experimental data were found. The obtained results showed that the use of ANN provides an excellent predictive performance tool with the additional capability to assess the influence of each operating parameter on the removal process of water pollutants. Copyright © 2011 John Wiley & Sons, Ltd.     

The CFVib Experiment: Control of Fluids in Microgravity with Vibrations

The Control of Fluids in Microgravity with Vibrations (CFVib) experiment was selected for the 2016 Fly Your Thesis! programme as part of the 65th ESA Parabolic Flight Campaign. The aim of the project is to observe the potentially complex behaviour of vibrated liquids in weightless environments and to investigate the extent to which small-amplitude vibrations can be used to influence and control this behaviour. Piezoelectric materials are used to generate high-frequency vibrations to drive surface waves and large-scale reorientation of the interface. The theory of vibroequilibria, which treats the quasi-stationary surface configurations achieved by this reorientation, was used to predict interesting parameter regimes and interpret fluid behaviour. Here we describe the scientific motivation, objectives, and design of the experiment.     

Effects of antimicrobial use in agricultural animals on drug-resistant foodborne salmonellosis in humans: A systematic literature review

Controversy continues concerning antimicrobial use in food animals and its relationship to drug-resistant infections in humans. We systematically reviewed published literature for evidence of a relationship between antimicrobial use in agricultural animals and drug-resistant meat or dairy-borne non-typhoidal salmonellosis in humans. Based on publications from the United States (U.S.), Canada, and Denmark from January 2010 to July 2014, 858 articles received title and abstract review, 104 met study criteria for full article review with 68 retained for which data are presented. Antibiotic exposure in both cattle and humans found an increased likelihood of Salmonella colonization, whereas in chickens, animals not exposed to antibiotics (organic) were more likely to be Salmonella positive and those that had antibiotic exposure were more likely to harbor antimicrobial resistant Salmonella organisms. In swine literature, only tylosin exposure was examined and no correlation was found among exposure, Salmonella colonization, or antimicrobial resistance. No studies that identified farm antimicrobial use also traced antimicrobial-resistant Salmonella from farm to fork.     

Secondary Metabolites in Ramalina terebrata Detected by UHPLC/ESI/MS/MS and Identification of Parietin as Tau Protein Inhibitor

Liquid chromatography coupled with mass spectrometry is an outstanding methodology for fast analysis of phenolic compounds in biological samples. Twenty two compounds were quickly and accurately identified in the methanolic extract of the Antarctic lichen Ramalina terebrata for the first time using ultra high pressure liquid chromatography coupled with photodiode array detector and high resolution mass spectrometry (UHPLC-PDA-Q/Orbitrap/MS/MS). In addition, the extract and the four compounds isolated from this species were tested for the inhibitory activity of tau protein aggregation, which is a protein involved in Alzheimer’s disease (AD). All compounds showed null activity with the exception of parietin, which it was able to inhibit aggregation process of tau in a concentration range between 3 µg/mL (10 µM) to 28 µg/mL (100 µM). In addition, we show how parietin interact with tau ³⁰⁶VQIVYK³¹¹ hexapeptide inside of the microtubule binding domain (4R) with the help of molecular docking experiments. Finally, the constituents present in the methanolic extract could possibly contribute to the established anti-aggregation activity for this extract and this in-depth analysis of the chemical composition of R. terebrata could guide further research into its medicinal properties and potential uses.     

Optimization of dopamine determination based on nanowires PEDOT/polydopamine hybrid film modified electrode

Poly(3,4-ethylenedioxythiophene) nanowires (nw-PEDOT), between 6.7–13.8 nm diameter, were obtained by electrochemical methods utilizing modified electrodes with silicon oxide as a template to afford a Pt/nw-PEDOT electrode. Dopamine electro-polymerization was next accomplished upon this electrode (Pt/nw-PEDOT/PDA). The Pt/nw-PEDOT/PDA assembly is capable of hindering interfering signals such as those from ascorbic and uric acid, enabling thus the selective detection of dopamine. Amperometric determination studies allowed limit of detection and limit of quantification limits of 0.47 and 1.59 µM, respectively, to be established. These limits were lower than those obtained with the same conducting polymer but without a nanowire structure.     

Critical Success Factors for New Product Development in Biotechnology Companies

The development of new products has become increasingly critical for the competitiveness of companies, due to increased diversity and variety of products, the reduction of product life cycles, and, primarily, globalization of markets. Thus, the identification and prioritization of critical success factors for developing new products is important, particularly for the high degree of risk and uncertainty involved. The main objective of this article is the identification and prioritization of critical success factors in new product development projects in biotechnology companies in the state of Minas Gerais, Brazil. The research method used was a survey questionnaire, which was sent to a sample of 31 biotechnology companies in Minas Gerais state. The principal findings of this research are that interpersonal skills/relationships of the project leader and technical skills are the most critical factors for successful new product development in this industry. The implications for the biotechnology industry in general, as well as for those responsible for managing new product development, are discussed.     

Comparisons Between the p--q and p--q--r Theories in Three-Phase Four-Wire Systems

This paper presents a comparative analysis between results from applications of the p-q and the p-q-r theories in shunt active power filters for three-phase four-wire systems, discussing aspects related to the influence of the system voltage in the control methods that calculate the compensating currents. It is shown that in some cases, a preprocessing of the system voltage is required if the goal is to achieve sinusoidal compensated currents. On the other hand, when the goal is to compensate zero-sequence current, the need of energy storage elements in the active filter is discussed. In this case, if zero-sequence components are present simultaneously in the system voltage and load current, they produce zero-sequence power flow, and the control methods based on both theories must contain additional calculations to allow the elimination of energy storage elements in the active filter. A control strategy based on the p-q theory is proposed to eliminate the neutral current without the need of energy storage elements, with the advantage of avoiding the extra transformation from alphabeta0 to pqr coordinates that is needed in the p-q-r theory. Simulation results are presented for the purpose of comparing the performance of both control methods.     

ISO 9001 certification in the American Continent: a statistical analysis and modelling

The ISO 9001 standard is considered as an effective tool to support a quality management system (QMS). A steady growth in the number of ISO 9001 issued certificates is observed worldwide, confirming the interest of companies in this approach. However, information regarding this behaviour over time in the American Continent is scarce. This paper presents a set of qualitative and quantitative analyses related to the ISO 9001 certification (globally and at the country level of the Americas), the use of this standard in countries that were part of the ISO Survey 2011 and modelling the ISO 9001 certification for American countries, in order to characterise through mathematical models, the evolution of the certification process and to identify factors that influence the ISO 9001 issued certificates in the various countries analysed. Based on the work developed, a positive relationship was found between the number of issued certificates in each country per 1000 inhabitants and the indicators of economic development (Gross National Income Per Capita). It is determined that the total reserves of a country is an economic variable that directly affects the number of issued certificates, a finding not observed in other forecasting models.     

Power flow solutions through tensor methods

This work deals with the application of tensor methods based on a quadratic model, to solve a set of nonlinear equations. Particular attention is given to the power flow problem, with emphasis on the modelling of the steady state electric network equations in rectangular coordinates. Two formulations of the power flow problem are used for the application of tensor methods. The first is the conventional approach based on active and reactive power mismatches. The second includes the equations of both power injection and the current injection balances. It is shown that the use of tensor models increases the robustness and can speed up the power flow iterative process if the computational effort for calculating the quadratic term is reduced. Numerical results obtained with power systems ranging from 6 to 1916 buses illustrate the application of the proposed methodology.