97 research outputs found
The Sludge Dewaterability in Advanced Wastewater Treatment: A Survey of Four Different Membrane BioReactor Pilot Plants
The wasted activated sludge dewaterability represents a major concern
for Wastewater Treatment Plants (WWTPs) managers. Indeed, whereas the
dewatered sludge could represents a re-usable matrix, the principal drawback
related to the wasted sludge dewaterability is the high water content due to the
presence of extracellular polymeric substances (EPS) that allow the trapping of
water molecules within the bio sludge flocs. In order to provide an outlook of
the dewaterability features of activated sludge derived from advanced WWTP,
the present research reports a long term survey (over two years) aimed at
assessing the principal dewaterability parameters of the sludge wasted from
different Membrane BioReactor pilot plants
Regional expression of the MAPT gene is associated with loss of hubs in brain networks and cognitive impairment in Parkinson disease and progressive supranuclear palsy.
Abnormalities of tau protein are central to the pathogenesis of progressive supranuclear palsy, whereas haplotype variation of the tau gene MAPT influences the risk of Parkinson disease and Parkinson's disease dementia. We assessed whether regional MAPT expression might be associated with selective vulnerability of global brain networks to neurodegenerative pathology. Using task-free functional magnetic resonance imaging in progressive supranuclear palsy, Parkinson disease, and healthy subjects (n = 128), we examined functional brain networks and measured the connection strength between 471 gray matter regions. We obtained MAPT and SNCA microarray expression data in healthy subjects from the Allen brain atlas. Regional connectivity varied according to the normal expression of MAPT. The regional expression of MAPT correlated with the proportionate loss of regional connectivity in Parkinson's disease. Executive cognition was impaired in proportion to the loss of hub connectivity. These effects were not seen with SNCA, suggesting that alpha-synuclein pathology is not mediated through global network properties. The results establish a link between regional MAPT expression and selective vulnerability of functional brain networks to neurodegeneration.Medical Research Council (Grant IDs: G1100464, MR/K020706/1, G0700503), Wellcome Trust (Grant ID: 103838), National Institute for Health Research Cambridge Biomedical Research Centre, Beverley Sackler fellowship scheme, NARSAD Young Investigator Award, Isaac Newton TrustThis is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.neurobiolaging.2016.09.00
An ant colony-based semi-supervised approach for learning classification rules
Semi-supervised learning methods create models from a few labeled instances and a great number of unlabeled instances. They appear as a good option in scenarios where there is a lot of unlabeled data and the process of labeling instances is expensive, such as those where most Web applications stand. This paper proposes a semi-supervised self-training algorithm called Ant-Labeler. Self-training algorithms take advantage of supervised learning algorithms to iteratively learn a model from the labeled instances and then use this model to classify unlabeled instances. The instances that receive labels with high confidence are moved from the unlabeled to the labeled set, and this process is repeated until a stopping criteria is met, such as labeling all unlabeled instances. Ant-Labeler uses an ACO algorithm as the supervised learning method in the self-training procedure to generate interpretable rule-based models—used as an ensemble to ensure accurate predictions. The pheromone matrix is reused across different executions of the ACO algorithm to avoid rebuilding the models from scratch every time the labeled set is updated. Results showed that the proposed algorithm obtains better predictive accuracy than three state-of-the-art algorithms in roughly half of the datasets on which it was tested, and the smaller the number of labeled instances, the better the Ant-Labeler performance
The Effect of Learning to Drum on Behaviour and Brain Function in Autistic Adolescents
There is an acknowledged need for improved service provision in the context of autism spectrum disorders. Previous studies have demonstrated the positive role drum training can play in improving behavioral outcomes for children and adolescents with emotional and behavioral difficulties. However, to date, none of these studies has explored how these behavioral changes translate at the neural level. Our study provides strong evidence that drumming not only reduces hyperactivity and inattention in autistic adolescents but also strengthens functional connectivity in brain regions responsible for inhibitory control and action outcome monitoring
Wireless technologies for the construction sector—Requirements, energy and cost efficiencies
The construction sector has been rather reluctant with respect to the implementation of ITC innovations that other industries have adopted for years. One of the reasons could be the lack of services by the proposed innovations especially the RFID solutions. This technology is well‐researched within the building sector and is therefore used to analyse requirements for alternative technologies. The motivationof the current work is to find upcoming technologies that bring improvements into the sector, for example improved life cycle costs and energy efficiencies, increasing quality, construction and operation efficiency and reducing faults and losses.The paper also lays out requirements expected by the sector. It will be shown that the wireless sensor network technology is a strong competitor that may meet the requirements. By analysing the application of such technologies throughout the building lifecycle, the utilization can be manifold, hereby minimising overall economic costs and maximising the added values for all involved stakeholders.Based on the expectations of the sector, the experiences with the introduction of the RFID technology and by estimating the applicability of the extra services that follow the wireless sensor network, the paper will line up the requirements that the new technology has to meet to be introduced successfully
Accounting for the complex hierarchical topology of EEG phase-based functional connectivity in network binarisation
Research into binary network analysis of brain function faces a
methodological challenge in selecting an appropriate threshold to binarise edge
weights. For EEG phase-based functional connectivity, we test the hypothesis
that such binarisation should take into account the complex hierarchical
structure found in functional connectivity. We explore the density range
suitable for such structure and provide a comparison of state-of-the-art
binarisation techniques, the recently proposed Cluster-Span Threshold (CST),
minimum spanning trees, efficiency-cost optimisation and union of shortest path
graphs, with arbitrary proportional thresholds and weighted networks. We test
these techniques on weighted complex hierarchy models by contrasting model
realisations with small parametric differences. We also test the robustness of
these techniques to random and targeted topological attacks.We find that the
CST performs consistenty well in state-of-the-art modelling of EEG network
topology, robustness to topological network attacks, and in three real
datasets, agreeing with our hypothesis of hierarchical complexity. This
provides interesting new evidence into the relevance of considering a large
number of edges in EEG functional connectivity research to provide
informational density in the topology.Comment: Accepted for publication in PLOS One, 27th September 201
Estimating (combinations of) activated sludge model No. 1 parameters and components by respirometry
Use of metakaolin in grouts intended for soil nailing
The aim of this work was to carry out a feasibility study to evaluate the pertinence of using metakaolin in grout intended for soil nailing. After a first step of grout optimisation based on technical and environmental constraints, an in-situ study was performed to evaluate the compatibility of metakaolin with this kind of application. This part highlights the minimum performance levels necessary if grout is to fulfil its role of transferring stresses between soil and nail
Implementation and evaluation of automatic contour propagation in 4DCT of lung
National audiencePurposeTo implement and evaluate automatic contour propagation in 4DCT of lung Method and Material4DCT of lung cancer patients was acquired and GTV contoured in each of 10 respiratory phases. Demons-based deformable registration was performed to find the volumetric mapping from the exhale reference phase to each other phase. Contours were propagated using volumetric methods. Usually, the GTV is contoured on one reference phase (end-exhale for example) of the 4D-CT which is copied and edited on the others phases. This is a very important, but time consuming task that is inconvenient for every day clinical use. Using a deformation field computed between 4D-CT phases could accelerate the contouring process. The reference GTV contour would be deformed from one phase to another and the clinician would have to do only small adjustments. The contouring time spent would be significantly reduced. The question is if deformable registration could be used as a semi-automatic contouring tool. We compared differences between GTV reported with and without deformation from one 4D-CT phases to another. Three metrics were used to assess the quality of the contour propagation: the volume intersection and two volume differences. ResultsVolume intersections between manual and automatic contouring were generally between about 85 and 90 per cent, while volume differences were generally between 5 and 15 per cent. Differences between manual and automatic results were correlated with the variability of manual GTV volumes delineation between phases. ConclusionsDeformable registration is a viable option for contour propagation, and may be used to assist the clinician in defining the GTV for large 4DCT data sets. Conflict of InterestThis research was supported by Elekta Oncology Systems and Varian Medical System
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