Learning about knowledge management for improving environmental impact assessment in a government agency: The Western Australian experience

How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency`s knowledge accumulated over the years. Part of an agency`s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks. Key elements of KM are the preparation of substantive guidance and spatial information management. It was found that treatment of cumulative impacts on the environment is very limited and information derived from project follow-up is not properly captured and stored, thus not used to create new knowledge and to improve practice and effectiveness. Other opportunities for improving organizational learning include the use of after-action reviews. The learning about knowledge management in EIA practice gained from Western Australian experience should be of value to agencies worldwide seeking to understand where best to direct their resources for their own knowledge repositories and environmental management practice. (C) 2011 Elsevier Ltd. All rights reserved.

In-Line Monitoring of Particle Size during Emulsion Polymerization under Different Operational Conditions using NIR Spectroscopy

In the present work, the sensitivity of NIR spectroscopy toward the evolution of particle size was studied during emulsion homopolymerization of styrene (Sty) and emulsion copolymerization of vinyl acetate-butyl acrylate conducted in a semibatch stirred tank and a tubular pulsed sieve plate reactor, respectively. All NIR spectra were collected online with a transflectance probe immersed into the reaction medium. The spectral range used for the NIR monitoring was from 9 500 to 13 000 cm(-1), where the absorbance of the chemical components present is minimal and the changes in the NIR spectrum can be ascribed to the effects of light scattering by the polymer particles. Off-line measurements of the average diameter of the polymer particles by DLS were used as reference values for the development of the multi-variate NIR calibration models based on partial least squares. Results indicated that, in the spectral range studied, it is possible to monitor the evolution of the average size of the polymer particles during emulsion polymerization reactions. The inclusion of an additional spectral range, from 5 701 to 6 447 cm(-1), containing information on absorbances (""chemical information"") in the calibration models was also evaluated.

On Building a Memory Evolutive System for Application to Learning and Cognition Modeling

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

Biogeochemical cycles of nutrients in tropical Eucalyptus plantations Main features shown by intensive monitoring in Congo and Brazil

The sustainability of fast-growing tropical Eucalyptus plantations is of concern in a context of rising fertilizer costs, since large amounts of nutrients are removed with biomass every 6-7 years from highly weathered soils. A better understanding of the dynamics of tree requirements is required to match fertilization regimes to the availability of each nutrient in the soil. The nutrition of Eucalyptus plantations has been intensively investigated and many studies have focused on specific fluxes in the biogeochemical cycles of nutrients. However, studies dealing with complete cycles are scarce for the Tropics. The objective of this paper was to compare these cycles for Eucalyptus plantations in Congo and Brazil, with contrasting climates, soil properties, and management practices. The main features were similar in the two situations. Most nutrient fluxes were driven by crown establishment the two first years after planting and total biomass production thereafter. These forests were characterized by huge nutrient requirements: 155, 10, 52, 55 and 23 kg ha(-1) of N, P, K, Ca and Mg the first year after planting at the Brazilian study site, respectively. High growth rates the first months after planting were essential to take advantage of the large amounts of nutrients released into the soil solutions by organic matter mineralization after harvesting. This study highlighted the predominant role of biological and biochemical cycles over the geochemical cycle of nutrients in tropical Eucalyptus plantations and indicated the prime importance of carefully managing organic matter in these soils. Limited nutrient losses through deep drainage after clear-cutting in the sandy soils of the two study sites showed the remarkable efficiency of Eucalyptus trees in keeping limited nutrient pools within the ecosystem, even after major disturbances. Nutrient input-output budgets suggested that Eucalyptus plantations take advantage of soil fertility inherited from previous land uses and that long-term sustainability will require an increase in the inputs of certain nutrients. (C) 2009 Elsevier B.V. All rights reserved.

Tree-ring characterization of Araucaria columnaris Hook and its applicability as a lead indicator in environmental monitoring

Tree-rings have frequently been used for dating of trees and to determine annual growth increments and forest dynamics, but little is known in tropical conditions about their utilization for environmental monitoring. This paper presents the results of Araucaria columnaris tree-ring characterization by wood anatomy and X-ray densitometric analysis and the determination of Pb concentration. Core samples from twelve araucaria trees were extracted from two sites exposed to air pollution due to intense traffic of vehicles and industrial activities. The tree-rings distinctly presented radial variation in early-latewood thickness and density, and characteristics of juvenile and mature wood. Anatomical and X-ray densitometric analysis were useful to delimit the tree-ring boundaries and to date the tree-rings, as well as to prove the annual formation. The lead concentration in annual araucaria tree-rings, analyzed with graphite furnace atomic absorption spectrometry, indicated the seasonal presence of the heavy metal in the environment during the 30 years studied, although the Pb did not affect tree growth. (c) 2008 Elsevier GmbH. All rights reserved.

MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

The introduction of the Salmonella/microsome mutagenicity assay in a groundwater monitoring program

The objective of this study was to verify the possible inclusion of the Salmonella/microsome mutagenicity assay in a groundwater monitoring program as a complementary assay to assess water quality. Groundwater samples belonging to seven wells from different types of aquifers were analyzed. Three different methods for sample preparation were used: membrane filtration; liquid-liquid and XAD-4 extraction. The filtered samples were tested using TA98, TA100, YG1041 and YG1042 and the water extracts only with TA98 and TA100. No mutagenic activity was observed in any of the 16 filtered samples tested. Out of the 10 samples analyzed using XAD-4 extraction, five showed mutagenic activity with potency ranging from 130 to 1500 revertants/L. Concerning the liquid-liquid extraction, from the 11 samples analyzed, 3 showed mutagenicity. The XAD-4 extraction was the most suitable sample preparation. TA98 without S9 was found to be the most sensitive testing condition. The wells presenting water samples with mutagenic activity belonged to unconfined aquifers, which are more vulnerable to contamination. The data suggest that Salmonella/microsome assay can be used as an efficient screening tool to monitor groundwater for mutagenic activity. (C) 2009 Elsevier B.V. All rights reserved.

Micromethod for Quantification of Carbamazepine, Phenobartital and Phenytoin in Human Plasma by HPLC-UV Detection for Therapeutic Drug Monitoring Application

A simple, rapid, selective and sensitive analytical method by HPLC with UV detection was developed for the quantification of carbamazepine, phenobarbital and phenytoin in only 0.2 mL of plasma. A C18 column (150 x 3.9 mm, 4 micra) using a binary mobile phase consisting of water and acetonitrile (70:30, v/v) at a flow rate of 0.5 mL/min were proposed. Validation of the analytical method showed a good linearity (0.3 to 20.0 mg/L for CBZ, 0.9 to 60.0 mg/L for PB and 0.6 to 40.0 mg/L for PHT), high sensitivity (LOQ: 0.3, 0.9 and 0.6 mg/L respectively). The method was applied for drug monitoring of antiepileptic drugs (AED) in 27 patients with epilepsy under polytherapy.

Monitoring the authenticity of Brazilian UHT milk: A chemometric approach

In this work, chemometric methods are reported as potential tools for monitoring the authenticity of Brazilian ultra-high temperature (UHT) milk processed in industrial plants located in different regions of the country. A total of 100 samples were submitted to the qualitative analysis of adulterants such as starch, chlorine, formal. hydrogen peroxide and urine. Except for starch, all the samples reported, at least, the presence of one adulterant. The use of chemometric methodologies such as the Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) enabled the verification of the occurrence of certain adulterations in specific regions. The proposed multivariate approaches may allow the sanitary agency authorities to optimise materials, human and financial resources, as they associate the occurrence of adulterations to the geographical location of the industrial plants. (c) 2010 Elsevier Ltd. All rights reserved.

Information Society, Teaching, and Learning: Education Reforms in Brazil

This article examines the subject matter of learning within the context of information society, through an inquiry concerning both the reforms in education adopted in Brazil in the last thirty years and their results. It provides a revision on the explanations of school failure based on assumptions of learning problems due to cognitive and linguistic deficits. From the guidelines related with written school forms as well as the constant cultural oppression accomplished inside the school, the article claims the necessity of changing the psychological and pedagogic views that, under the label of democratic practices, determine school institutions and its daily life, by means of instrumental relations with knowledge that disregard the reading practices which are congenial to popular culture.

Corporate Education and the Role of the Chief Learning Officer

This paper aims to present an overview on characteristics, roles and responsibilities of those who arc in charge. of the Corporate Educational Systems in several organizations from distinct industries in Brazil, based on a research carried out by the authors. The analysis compares what is available in the literature on this subject so that it may provide insights on how Brazilian companies have dealt with the difficult task of developing competences in their employees. Special attention is given to the Chief Learning Officer`s role (or the lack of it) - someone who was supposed to be in charge of the employees` development processes in a given organization. The results show that this role has not been a clear or unanimous concept yet, neither in terms of the functions to be performed nor the so-called strategic importance given to this sort of executive. This research is both exploratory and descriptive, and due to the use of intentional sample, the inferences are limited. Despite these limitations, its comments may enrich the discussion on this subject.

Real-time monitoring and kinetic parameter estimation of the affinity interaction of jArtinM and rArtinM with peroxidase glycoprotein by the electrogravimetric technique

ArtinM is a D-mannose binding lectin that has been arousing increasing interest because of its biomedical properties, especially those involving the stimulation of Th1 immune response, which confers protection against intracellular pathogens The potential pharmaceutical applications of ArtinM have motivated the production of its recombinant form (rArtinM) so that it is important to compare the sugar-binding properties of jArtinM and rArtinM in order to take better advantage of the potential applications of the recombinant lectin. In this work, a biosensor framework based on a Quartz Crystal Microbalance was established with the purpose of making a comparative study of the activity of native and recombinant ArtinM protein The QCM transducer was strategically functionalized to use a simple model of protein binding kinetics. This approach allowed for the determination of the binding/dissociation kinetics rate and affinity equilibrium constant of both forms of ArtinM with horseradish peroxidase glycoprotein (HRP), a N-glycosylated protein that contains the trimannoside Man alpha 1-3[Man alpha 1-6]Man, which is a known ligand for jArtinM (Jeyaprakash et al, 2004). Monitoring of the real-time binding of rArtinM shows that it was able to bind HRP, leading to an analytical curve similar to that of jArtinM, with statistically equivalent kinetic rates and affinity equilibrium constants for both forms of ArtinM The lower reactivity of rArtinM with HRP than jArtinM was considered to be due to a difference in the number of Carbohydrate Recognition Domains (CRDs) per molecule of each lectin form rather than to a difference in the energy of binding per CRD of each lectin form. (C) 2010 Elsevier B V. All rights reserved

Effects of postnatal protein malnutrition on learning and memory procedures

Protein malnutrition induces structural, neurochemical and functional changes in the central nervous system leading to alterations in cognitive and behavioral development of rats. The aim of this work was to investigate the effects of postnatal protein malnutrition on learning and memory tasks. Previously malnourished (6% protein) and well-nourished rats (16% protein) were tested in three experiments: working memory tasks in the Morris water maze (Experiment I), recognition memory of objects (Experiment II), and working memory in the water T-maze (Experiment III). The results showed higher escape latencies in malnourished animals in Experiment I, lower recognition indexes of malnourished animals in Experiment II, and no differences due to diet in Experiment III. It is suggested that protein malnutrition imposed on early life of rats can produce impairments on both working memory in the Morris maze and recognition memory in the open field tests.

Evaluation of the aquatic macroinvertebrate community as a tool for monitoring a reservoir in the Pitangui river basin, Parana, Brazil

Evaluation of the aquatic macroinvertebrate community as a tool for monitoring a reservoir in the Pitangui river basin, Parana, Brazil. Benthic and nektonic macroinvertebrates play an important role in the structure and function of aquatic ecosystems and their distribution is influenced by chemical features of the substrate, vegetation composition, and water depth. Knowledge on the fauna contributes to the assessment of water quality and development of biodiversity conservation activities. Different biotic factors affecting the invertebrate community were evaluated in the Alagados reservoir, the main water source of the city of Ponta Grossa, Parana. In five different sampling points, 18,473 specimens of aquatic or semiaquatic macroinvertebrates were collected, belonging to 46 taxa of the phylla Annelida (Hirudinea and Oligochaeta), Mollusca (Gastropoda), Platyhelminthes (Turbellaria), Nematoda and Arthropoda (Arachnida, Crustacea and Insecta). This community was composed mainly of predators (45.7% of the taxa sampled), collectors and/or filterers (23.9%), scrapers (15.2%), shredders (13.0%) and detritivores (2.2%). Diversity (H`) and evenness (J) indices were significantly low for the sites examined, and H` ranged between 0.3301 and 1.0396. Regarding tolerance of organisms to organic pollution, more sensitive taxa were very rare (Plecoptera) or unusual (Trichoptera and Ephemeroptera). Among the more resistant groups are Chironomidae and Hirudinea, both fairly common in the samples. This study corroborates the importance of bioindicators as a tool to assess water quality for human consumption and for the conservation of aquatic environments, integrating physical, chemical and biological factors in monitoring programs.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.