Optimization of in situ derivatization SPME by experimental design for GC-MS multi-residue analysis of pharmaceutical drugs in wastewater

This paper presents the development of a procedure, which enables the analysis of nine pharmaceutical drugs in wastewater using gas chromatography-mass spectrometry (GC-MS) associated with solid-phase microextraction (SPME) for the sample preparation. Experimental design was applied to optimize the in situ derivatization and the SPME extraction conditions. Ethyl chloroformate (ECF) was employed as derivatizing agent and polydimethylsiloxane-divinylbenzene (PDMS-DVB) as the SPME fiber coating. A fractional factorial design was used to evaluate the main factors for the in situ derivatization and SPME extraction. Thereafter, a Doehlert matrix design was applied to find out the best experimental conditions. The method presented a linear range from 0.5 to 10 mu g/L, and the intraday and interday precision were lower than 16%. Applicability of the method was verified from real influent and effluent samples of a wastewater treatment plant, as well as from samples of an industry wastewater and a river.

FLOWS OF INFORMATION AND LANGUAGE IN ORGANIZATIONAL SETTINGS

Information flows are formed naturally or formally induced in organizational settings, passing from the strategic level to operational level, reflecting, and impacting in the processes that make up the organization, including the decision-making process and therefore the action strategies of organization. The management of organizational environments based on information requires careful attention to various kinds of languages used for communication between sectors and employees of the organization, whose goal is to share, disseminate and socialize the information produced in this environment.

STATISTICAL TEST FOR GENOTYPE AND ENVIRONMENT CONTRIBUTION IN THE GENOTYPES x ENVIRONMENTS INTERACTION MATRIX

The objective of the present work was to propose a method for testing the contribution of each level of the factors in a genotypes x environments (GxE) interaction using multi-environment trials analyses by means of an F test. The study evaluated a data set, with twenty genotypes and thirty-four environments, in a block design with four replications. The sum of squares within rows (genotypes) and columns (environments) of the GxE matrix was simulated, generating 10000 experiments to verify the empirical distribution. Results indicate a noncentral chi-square distribution for rows and columns of the GxE interaction matrix, which was also verified by the Kolmogorov-Smirnov test and Q-Q plot. Application of the F test identified the genotypes and environments that contributed the most to the GxE interaction. In this way, geneticists can select good genotypes in their studies.

A novel strategy for building interoperable MPI environment in heterogeneous high performance systems

Breakthrough advances in microprocessor technology and efficient power management have altered the course of development of processors with the emergence of multi-core processor technology, in order to bring higher level of processing. The utilization of many-core technology has boosted computing power provided by cluster of workstations or SMPs, providing large computational power at an affordable cost using solely commodity components. Different implementations of message-passing libraries and system softwares (including Operating Systems) are installed in such cluster and multi-cluster computing systems. In order to guarantee correct execution of message-passing parallel applications in a computing environment other than that originally the parallel application was developed, review of the application code is needed. In this paper, a hybrid communication interfacing strategy is proposed, to execute a parallel application in a group of computing nodes belonging to different clusters or multi-clusters (computing systems may be running different operating systems and MPI implementations), interconnected with public or private IP addresses, and responding interchangeably to user execution requests. Experimental results demonstrate the feasibility of this proposed strategy and its effectiveness, through the execution of benchmarking parallel applications.

Flares and variability from Sagittarius A(star): five nights of simultaneous multi-wavelength observations

Aims. We report on simultaneous observations and modeling of mid-infrared (MIR), near-infrared (NIR), and submillimeter (sub-mm) emission of the source Sgr A * associated with the supermassive black hole at the center of our Galaxy. Our goal was to monitor the activity of Sgr A* at different wavelengths in order to constrain the emitting processes and gain insight into the nature of the close environment of Sgr A*. Methods. We used the MIR instrument VISIR in the BURST imaging mode, the adaptive optics assisted NIR camera NACO, and the sub-mm antenna APEX to monitor Sgr A* over several nights in July 2007. Results. The observations reveal remarkable variability in the NIR and sub-mm during the five nights of observation. No source was detected in the MIR, but we derived the lowest upper limit for a flare at 8.59 mu m (22.4 mJy with A(8.59 mu m) = 1.6 +/- 0.5). This observational constraint makes us discard the observed NIR emission as coming from a thermal component emitting at sub-mm frequencies. Moreover, comparison of the sub-mm and NIR variability shows that the highest NIR fluxes (flares) are coincident with the lowest sub-mm levels of our five-night campaign involving three flares. We explain this behavior by a loss of electrons to the system and/or by a decrease in the magnetic field, as might conceivably occur in scenarios involving fast outflows and/or magnetic reconnection.

Multi-molecular markers and metals as tracers of organic matter inputs and contamination status from an Environmental Protection Area in the SW Atlantic (Laranjeiras Bay, Brazil)

The sources and concentrations of aliphatic hydrocarbons (AHs) and polycyclic aromatic hydrocarbons (PAHs), faecal and biogenic sterols, and trace metals at 10 sampling sites located in Laranjeiras Bay, a large Environmental Protection Area in the southern Atlantic region of Brazil, were determined to assess the sources of organic matter and the contamination status of estuarine sediments. Organic compounds were determined by GC-FID and GC-MS, and ICP-OES was used to evaluate trace metals. The total AHs concentration ranged from 0.28 to 8.19 mu g g(-1), and n-C-29 and n-C-31 alkanes were predominant, indicating significant inputs from higher terrestrial plants. Unresolved complex mixtures (UCM) were not detected at any site, suggesting that the study area was not significantly contaminated by fossil fuels. The total PAH concentration varied from 3.85 to 89.2 ng g(-1). The ratio between selected PAH isomers showed that combustion of biomass, coal, and petroleum is the rnain source of PAHs in the study area. The concentrations of the faecal sterols coprostanol and epicoprostanol were below the detection limits, suggesting that sewage was not a significant contributor to sedimentary organic matter. The concentrations of the trace metals (As, Cr, Cu, Ni, Pb and Zn) were low, except near sites located at the mouths of rivers that discharge into the study area and near urbanised regions (Paranagua city and the adjoining harbour). In general, the concentrations of PAHs were below the threshold effect concentrations (TEL) levels. Although the As, Cr and Ni concentrations were above the TEL levels, the study area can be considered as preserved from human activities.

Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

The objectives of the present study were to characterize and define homogenous production environments of composite beef cattle in Brazil in terms of climatic and geographic variables using multivariate exploratory techniques and to use them to assess the presence of G x E for birth weight (BW) and weaning weight (WW). Data from animals born between 1995 and 2008 on 36 farms located in 27 municipalities of the Brazilian states were used. Fifteen years of climate observations (mean minimum and maximum annual temperature and mean annual rainfall) and geographic (latitude, longitude and altitude) data were obtained for each municipality where the farms were located for characterization of the production environments. Hierarchical and nonhierarchical cluster analysis was used to group farms located in regions with similar environmental variables into clusters. Six clusters of farms were formed. The effect of sire-cluster interaction was tested by single-trait analysis using deviance information criterion (DIC). Genetic parameters were estimated by multi-trait analysis considering the same trait to be different in each cluster. According to the values of DIC, the inclusion of sire-cluster effect did not improve the fit of the genetic evaluation model for BW and WW. Estimates of genetic correlations among clusters ranged from -0.02 to 0.92. The low genetic correlation among the most studied regions permits us to suggest that a separate genetic evaluation for some regions should be undertaken. (C) 2012 Elsevier B.V. All rights reserved.

MR-Radix: a multi-relational data mining algorithm

Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.