K-Surfer: a KNIME extension for the management and analysis of Human brain MRI FreeSurfer/FSL data

Human brain imaging techniques, such as Magnetic Resonance Imaging (MRI) or Diffusion Tensor Imaging (DTI), have been established as scientific and diagnostic tools and their adoption is growing in popularity. Statistical methods, machine learning and data mining algorithms have successfully been adopted to extract predictive and descriptive models from neuroimage data. However, the knowledge discovery process typically requires also the adoption of pre-processing, post-processing and visualisation techniques in complex data workflows. Currently, a main problem for the integrated preprocessing and mining of MRI data is the lack of comprehensive platforms able to avoid the manual invocation of preprocessing and mining tools, that yields to an error-prone and inefficient process. In this work we present K-Surfer, a novel plug-in of the Konstanz Information Miner (KNIME) workbench, that automatizes the preprocessing of brain images and leverages the mining capabilities of KNIME in an integrated way. K-Surfer supports the importing, filtering, merging and pre-processing of neuroimage data from FreeSurfer, a tool for human brain MRI feature extraction and interpretation. K-Surfer automatizes the steps for importing FreeSurfer data, reducing time costs, eliminating human errors and enabling the design of complex analytics workflow for neuroimage data by leveraging the rich functionalities available in the KNIME workbench.

Joint data assimilation of satellite reflectance and net ecosystem exchange data constrains ecosystem carbon fluxes at a high-elevation subalpine forest

We utilized an ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to estimate carbon fluxes of gross primary productivity and total ecosystem respiration of a high-elevation coniferous forest. The data assimilation routine incorporated aggregated twice-daily measurements of the net ecosystem exchange of CO2 (NEE) and satellite-based reflectance measurements of the fraction of absorbed photosynthetically active radiation (fAPAR) on an eight-day timescale. From these data we conducted a data assimilation experiment with fifteen different combinations of available data using twice-daily NEE, aggregated annual NEE, eight-day f AP AR, and average annual fAPAR. Model parameters were conditioned on three years of NEE and fAPAR data and results were evaluated to determine the information content from the different combinations of data streams. Across the data assimilation experiments conducted, model selection metrics such as the Bayesian Information Criterion and Deviance Information Criterion obtained minimum values when assimilating average annual fAPAR and twice-daily NEE data. Application of wavelet coherence analyses showed higher correlations between measured and modeled fAPAR on longer timescales ranging from 9 to 12 months. There were strong correlations between measured and modeled NEE (R2, coefficient of determination, 0.86), but correlations between measured and modeled eight-day fAPAR were quite poor (R2 = −0.94). We conclude that this inability to determine fAPAR on eight-day timescale would improve with the considerations of the radiative transfer through the plant canopy. Modeled fluxes when assimilating average annual fAPAR and annual NEE were comparable to corresponding results when assimilating twice-daily NEE, albeit at a greater uncertainty. Our results support the conclusion that for this coniferous forest twice-daily NEE data are a critical measurement stream for the data assimilation. The results from this modeling exercise indicate that for this coniferous forest, average annuals for satellite-based fAPAR measurements paired with annual NEE estimates may provide spatial detail to components of ecosystem carbon fluxes in proximity of eddy covariance towers. Inclusion of other independent data streams in the assimilation will also reduce uncertainty on modeled values.

Phosphorus fertilisation and large legume species affect jarrah forest restoration after bauxite mining

Re-establishing nutrient-cycling is often a key goal of mine-site restoration. This goal can be achieved by applying fertilisers (particularly P) in combination with seeding N-fixing legumes. However, the effect of this strategy on other key restoration goals such as the establishment and growth of non-leguminous species has received little attention. We investigated the effects of P-application rates either singly, or in combination with seeding seven large understorey legume species, on jarrah forest restoration after bauxite mining. Five years after P application and seeding, legume species richness, density and cover were higher in the legume-seeded treatment. However, the increased establishment of legumes did not lead to increased soil N. Increasing P-application rates from 0 to 80 kg P ha−1 did not affect legume species richness, but significantly reduced legume density and increased legume cover: cover was maximal (∼50%) where 80 kg P ha−1 had been applied with large legume seeds. Increasing P-application had no effect on species richness of non-legume species, but increased the density of weeds and native ephemerals. Cover of non-legume species decreased with increasing P-application rates and was lower in plots where large legumes had been seeded compared with non-seeded plots. There was a significant legume × P interaction on weed and ephemeral density: at 80 kg P ha−1 the decline in density of these groups was greatest where legumes were seeded. In addition, the decline in cover for non-legume species with increasing P was greatest when legumes were seeded. Applying 20 kg P ha−1 significantly increased tree growth compared with tree growth in unfertilised plots, but growth was not increased further at 80 kg ha−1 and tree growth was not affected by seeding large legumes. Taken together, these data indicate that 80 kg ha−1 P-fertiliser in combination with (seeding) large legumes maximised vegetation cover at five years but could be suboptimal for re-establishing a jarrah forest community that, like unmined forest, contains a diverse community of slow-growing re-sprouter species. The species richness and cover of non-legume understorey species, especially the resprouters, was highest in plots that received either 0 or 20 kg ha−1 P and where large legumes had not been seeded. Therefore, our findings suggest that moderation of P-fertiliser and legumes could be the best strategy to fulfil the multiple restoration goals of establishing vegetation cover, while at the same time maximising tree growth and species richness of restored forest.

Mining in a changing climate: what scope for forestry-based legacies?

This paper provides an interdisciplinary perspective on mine reclamation in forested areas of Ghana, a country characterised by conflicts between mining and forest conservation. A comparison was made between above ground biomass (AGB) and soil organic carbon (SOC) content from two reclaimed mine sites and adjacent undisturbed forest. Findings suggest that on decadal timescales, reclaimed mine sites contain approximately 40% of the total carbon and 10% the AGB carbon of undisturbed forest. This raises questions regarding the potential for decommissioning mine sites to provide forestry-based legacies. Such a move could deliver a host of benefits, including improving the longevity and success of reclamation, mitigating climate change and delivering corollary enumeration for local communities under carbon trading schemes. A discussion of the antecedents and challenges associated with establishing forest-legacies highlights the risk of neglecting the participation and heterogeneity of legitimate local representatives, which threatens the equity of potential benefits and sustainability of projects. Despite these risks, implementing pilot projects could help to address the lack of transparency and data which currently characterises mine reclamation.

Soil phosphorus dynamics and phytoavailability from sewage sludge at different stages in a treatment stream

The effect of different stages of sewage sludge treatment on phosphorus (P) dynamics in amended soils was determined using samples of undigested liquid (UL), anaerobically digested liquid (AD) and dewatered anaerobically digested (DC) sludge. Sludges were taken from three points in the same treatment stream and applied to a sandy loam soil in field-based mesocosms at 4, 8 and 16t ha−1 dry solids. Mesocosms were sown with perennial ryegrass (Lolium perenne cv. Melle), and the sward was harvested after 35 and 70 days to determine yield and foliar P concentration. Soils were also sampled during this period to measure P transformations and the activities of acid phosphomonoesterase and phosphodiesterase. Data show that the AD amended soils had the greatest plant-available and foliar P content up to the second harvest, but the UL amended soils had the greatest enzyme activity. Characterisation of control and 16t ha−1 soils and sludge using solution 31P nuclear magnetic resonance (NMR) spectroscopy after NaOH–EDTA extraction revealed that P was predominantly in the inorganic pool in all three sludge samples, with the highest proportion (of the total extracted P) as inorganic P in the anaerobically digested liquid sludge. After sludge incorporation, P was immobilised to organic species. The majority of organic P was in monoester-P forms, while the remainder of organic P (diester P and phosphonate P) was more susceptible to transformations through time and showed variation with sludge type. These results show that application of sewage sludge at rates as low as 4t ha−1 can have a significant nutritional benefit to ryegrass over an initial 35-day growth and subsequent 35-day re-growth periods. Differences in P transformation, and hence nutritional benefit, between sludge types were evident throughout the experiment. Thus, differences in sludge treatment process alter the edaphic mineralisation characteristics of biosolids derived from the same source material.

Nitrogen dynamics under Lolium perenne after a single application of different sewage sludge types from the same treatment stream

Three sludge types from the same treatment stream (undigested liquid, anaerobically digested liquid and dewatered, anaerobically digested cake) were used in a field based tub study. Amendments (4, 8, and 16 Mg dry solid (ds)ha(-1)) were incorporated into the upper 15 cm of a sandy loam soil prior to sowing with rye-grass (Lolium perenne L.). Nitrogen transformations in the soil were determined for the 80 d period following incorporation. Nitrogen uptake and crop yield were measured in the cut sward 35 and 70 d after sowing. The study showed that application of sewage sludge at rates as low as 4 Mgha(-1) can have a nutritional benefit to rye-grass over the two harvests. Differences in N transformation, and hence crop nutritional benefit, between sludge types were evident throughout the experiment. In particular, the dewatering process changed the mineral N characteristics of the anaerobically digested sludge, which, when not dewatered, outperformed the other sludges in terms of yield and mineralisation rate at both harvests. The dewatered sludge produced the lowest yield of rye-grass. The undigested liquid sludge had the lowest foliar N and soil NO(3)-N concentrations, possibly immobilised as the large oxidisable C component of this sludge was metabolised by the microbial biomass. Correlation data support the concept of preferential uptake of NH(4)-N over NO(3)-N in Lolium perenne. Results are discussed in the context of managing sludge type and application for a plant nutrient source and NO(3)-N release.

Comparing performance of instrumental drift correction by linear and quadratic adjusting in inductive electromagnetic data

Electromagnetic induction (EMI) method results are shown for vertical magnetic dipole (VMD) configuration by using the EM38 equipment. Performance in the location of metallic pipes and electrical cables is compared as a function of instrumental drift correction by linear and quadratic adjusting under controlled conditions. Metallic pipes and electrical cables are buried at the IAG/USP shallow geophysical test site in Sao Paulo City. Brazil. Results show that apparent electrical conductivity and magnetic susceptibility data were affected by ambient temperature variation. In order to obtain better contrast between background and metallic targets it was necessary to correct the drift. This correction was accomplished by using linear and quadratic relation between conductivity/susceptibility and temperature intending comparative studies. The correction of temperature drift by using a quadratic relation was effective, showing that all metallic targets were located as well deeper targets were also improved. (C) 2010 Elsevier B.V. All rights reserved.

Two-Phase Mapping for Projecting Massive Data Sets

Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.

Clustering Lab value working with medical data

Data mining is a relatively new field of research that its objective is to acquire knowledge from large amounts of data. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available [27]. On the one hand, practitioners are expected to use all this data in their work but, at the same time, such a large amount of data cannot be processed by humans in a short time to make diagnosis, prognosis and treatment schedules. A major objective of this thesis is to evaluate data mining tools in medical and health care applications to develop a tool that can help make rather accurate decisions. In this thesis, the goal is finding a pattern among patients who got pneumonia by clustering of lab data values which have been recorded every day. By this pattern we can generalize it to the patients who did not have been diagnosed by this disease whose lab values shows the same trend as pneumonia patients does. There are 10 tables which have been extracted from a big data base of a hospital in Jena for my work .In ICU (intensive care unit), COPRA system which is a patient management system has been used. All the tables and data stored in German Language database.

Simultaneous prediction of symptom severity and cause in data from a test battery for Parkinson patients, using machine learning methods

The main purpose of this thesis project is to prediction of symptom severity and cause in data from test battery of the Parkinson’s disease patient, which is based on data mining. The collection of the data is from test battery on a hand in computer. We use the Chi-Square method and check which variables are important and which are not important. Then we apply different data mining techniques on our normalize data and check which technique or method gives good results.The implementation of this thesis is in WEKA. We normalize our data and then apply different methods on this data. The methods which we used are Naïve Bayes, CART and KNN. We draw the Bland Altman and Spearman’s Correlation for checking the final results and prediction of data. The Bland Altman tells how the percentage of our confident level in this data is correct and Spearman’s Correlation tells us our relationship is strong. On the basis of results and analysis we see all three methods give nearly same results. But if we see our CART (J48 Decision Tree) it gives good result of under predicted and over predicted values that’s lies between -2 to +2. The correlation between the Actual and Predicted values is 0,794in CART. Cause gives the better percentage classification result then disability because it can use two classes.

Data based Calibration System for Radar used by Vehicle Activated Signs

The accurate measurement of a vehicle’s velocity is an essential feature in adaptive vehicle activated sign systems. Since the velocities of the vehicles are acquired from a continuous wave Doppler radar, the data collection becomes challenging. Data accuracy is sensitive to the calibration of the radar on the road. However, clear methodologies for in-field calibration have not been carefully established. The signs are often installed by subjective judgment which results in measurement errors. This paper develops a calibration method based on mining the data collected and matching individual vehicles travelling between two radars. The data was cleaned and prepared in two ways: cleaning and reconstructing. The results showed that the proposed correction factor derived from the cleaned data corresponded well with the experimental factor done on site. In addition, this proposed factor showed superior performance to the one derived from the reconstructed data.

Impact assessment and quality analysis of corporate social responsability (CSR) programs of mining companies and their contribution to sustainable development in the communities they operate: case study Tenke Fungurume Mining SA in the Democratic Republic of Congo (DRC)

Purpose – This case study presents an impact assessment of Corporate Social Responsibility (CSR) programs of the TFM Company in order to understand how they contribute to the sustainable development of communities in areas in which they operate. Design/Methodology/Approach - Data for this study was collected using qualitative data methods that included semi-structured interviews and Focus Group Discussions most of them audio and video recorded. Documentary analysis and a field visit were also undertaken for the purpose of quality analysis of the CSR programs on the terrain. Data collected was analyzed using the Seven Questions to sustainability (7Qs) framework, an evaluation tool developed by the Mining, Minerals and Sustainable Development (MMSD) North America chapter. Content analysis method was on the other hand used to examine the interviews and FGDs of the study participants. Findings - Results shows that CSR programs of TFM SA do contribute to community development, as there have been notable changes in the communities’ living conditions. But whether they have contributed to sustainable development is not yet the case as programs that enhance the capacity of communities and other stakeholders to support these projects development beyond the implementation stage and the mines operation lifetime need to be considered and implemented. Originality/Value – In DRC, there is paucity of information of research studies that focus on impact assessment of CSR programs in general and specifically those of mining companies and their contribution to sustainable development of local communities. Many of the available studies cover issues of minerals and conflict or conflict minerals as mostly referred to. This study addressees this gap.

Mercury contamination in fanned fish setup on former garimpo mining areas in the Northern Mato Grosso State, Amazonian region, Brazil

The garimpo gold mining activity has released about 2.500 tons of mercury in the Brazilian Amazonian environment in the 1980-1995 period. The northern region of Mato Grosso State, an important gold mining and trading area during the Arnazonian gold rush is now at a turning point regarding its economic future. Nowadays, the activities related to gold mining have only a low relevance on its economy. Thus, the local communities are looking for economic alternatives for the development of the region. Cooperative fish farming is one of such alternatives. However, some projects are directly implemented on areas degraded by the former garimpo activity and the mercury left behind still poses risks, especially by its potential accumulation in fish. The objective of the present study was to evaluate the levels of mercury contamination in two fish farming areas, Paranaita and Alta Floresta, with and without records of past gold-washing activity, respectively. Data such as mercury concentration in fish of different trophic level, size, and weight as well as the water physical and chemical parameters were measured and considered. These preliminary data have shown no significant difference between these two fish fanning areas, relatively to mercury levels in fish. (c) 2004 Elsevier B.V. All rights reserved.

Habitat use, reproductive traits and social interactions in a stream-dweller treefrog endemic to the Brazilian Cerrado

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Environmental adaptation of the source of the subbasin of Rico Stream, Monte Alto - SP, Brazil

Este trabalho teve como principal objetivo definir padrões fotográficos que representem o uso e a ocupação do solo da cabeceira de drenagem do Córrego Rico, localizada no Município de Monte Alto, Estado de São Paulo, para fins de adequação ambiental no que tange à legislação florestal brasileira. O mapeamento foi realizado utilizando técnicas de sensoriamento remoto e interpretação visual da imagem World View, seguida da digitalização da rede de drenagem e vegetações (naturais e agrícolas) no AutoCad, com auxílio de documentos e trabalho de campo. A área de estudo apresenta uma superfície de 2.141,53 ha, e os resultados permitiram constatar que a principal cultura é a cana-de-açúcar, com 546,34 ha, seguida de pastagens, com 251,22 ha, culturas perenes, com 191,71 ha, Eucalipto, com 57,31 ha, e a cebola, com 49,52 ha da área total, confirmando o avanço dos canaviais na região. A área possui 375,04 ha de áreas de preservação permanente (APPs), e desta superfície verificou-se que apenas 72,17 ha (19,24%) encontram-se compostos por vegetação arbórea ou mata, e destas 302,87 ha precisam ser enriquecidos e reflorestados com vegetação nativa da região, de acordo com legislação vigente. Os dados de área possibilitam futuras propostas de modelos de adequação ambiental para a microbacia, de acordo com a legislação ambiental vigente.