1,285 research outputs found

    Computer Modelling Of The UK Wind Energy Resource: UK Wind Speed Data Package And User Manual

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    A software package has been developed for IBM-PC or true compatibles. It is designed to provide easy access to the results of a programme of work, funded by the UK Department of Energy, to estimate the UK wind energy resource. Mean wind speed maps and quantitative resource estimates were obtained using the NOABL mesoscale (1 km resolution) numerical model for the prediction of wind flow over complex terrain. NOABL was used in conjunction with digitised terrain data and wind data from surface meteorological stations for a ten year period (1975-1984) to provide digital UK maps of mean wind speed at 10m, 25m and 45m above ground level. Also included in the derivation of these maps was the use of the Engineering Science Data Unit (ESDU) method to model the effect on wind speed of the abrupt change in surface roughness that occurs at the coast. With the wind speed software package, the user is able to obtain a display of the modelled wind speed at 10m, 25m and 45m above ground level for any location in the UK. The required co-ordinates (Ordnance Survey Easting and Northing) are simply supplied by the user, and the package displays the selected wind speed. This user manual summarises the methodology used in the generation of these UK maps and shows computer generated plots of the 25m wind speeds in 200 x 200 km regions covering the whole UK. The uncertainties inherent in the derivation of these maps are also described, and notes given on their practical usage. Existing isovent maps, based on standard meteorological data which take no account of terrain effects, indicate that 10m annual mean wind speeds vary between about 4.5 and 7 m/s over the UK with only a few coastal areas over 6 m/s. The present study indicated that 23 % of the UK land area had speeds over 6 m/s, with many hill sites having 10m speeds over 10m/s. It is concluded that these 'first order' resource estimates represent a substantial improvement over the presently available 'zero order' estimates. The results will be useful for broad resource studies and initial site screening. Detailed resource evaluation for local sites will require more detailed local modelling or ideally long term field measurements

    Natural organic matter in sedimentary basins and its relation to arsenic in anoxic ground water: the example of West Bengal and its worldwide implications

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    In order to investigate the mechanism of As release to anoxic ground water in alluvial aquifers, the authors sampled ground waters from 3 piezometer nests, 79 shallow (80 m) wells, in an area 750 m by 450 m, just north of Barasat, near Kolkata (Calcutta), in southern West Bengal. High concentrations of As (200-1180 mug L-1) are accompanied by high concentrations of Fe (3-13.7 mgL(-1)) and PO4 (1-6.5 mg L-1). Ground water that is rich in Mn (1-5.3 mg L-1) contains <50 mug L-1 of As. The composition of shallow ground water varies at the 100-m scale laterally and the metre-scale vertically, with vertical gradients in As concentration reaching 200 mug L-1 m(-1). The As is supplied by reductive dissolution of FeOOH and release of the sorbed As to solution. The process is driven by natural organic matter in peaty strata both within the aquifer sands and in the overlying confining unit. In well waters, thermotolerant coliforms, a proxy for faecal contamination, are not present in high numbers (<10 cfu/100 ml in 85% of wells) showing that faecally-derived organic matter does not enter the aquifer, does not drive reduction of FeOOH, and so does not release As to ground water.Arsenic concentrations are high (much greater than50 mug L-1) where reduction of FeOOH is complete and its entire load of sorbed As is released to solution, at which point the aquifer sediments become grey in colour as FeOOH vanishes. Where reduction is incomplete, the sediments are brown in colour and resorption of As to residual FeOOH keeps As concentrations below 10 mug L-1 in the presence of dissolved Fe. Sorbed As released by reduction of Mn oxides does not increase As in ground water because the As resorbs to FeOOH. High concentrations of As are common in alluvial aquifers of the Bengal Basin arise because Himalayan erosion supplies immature sediments, with low surface-loadings of FeOOH on mineral grains, to a depositional environment that is rich in organic mater so that complete reduction of FeOOH is common. (C) 2004 Published by Elsevier Ltd

    Att-TasNet: attending to encodings in time-domain audio speech separation of noisy, reverberant speech mixtures

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    Separation of speech mixtures in noisy and reverberant environments remains a challenging task for state-of-the-art speech separation systems. Time-domain audio speech separation networks (TasNets) are among the most commonly used network architectures for this task. TasNet models have demonstrated strong performance on typical speech separation baselines where speech is not contaminated with noise. When additive or convolutive noise is present, performance of speech separation degrades significantly. TasNets are typically constructed of an encoder network, a mask estimation network and a decoder network. The design of these networks puts the majority of the onus for enhancing the signal on the mask estimation network when used without any pre-processing of the input data or post processing of the separation network output data. Use of multihead attention (MHA) is proposed in this work as an additional layer in the encoder and decoder to help the separation network attend to encoded features that are relevant to the target speakers and conversely suppress noisy disturbances in the encoded features. As shown in this work, incorporating MHA mechanisms into the encoder network in particular leads to a consistent performance improvement across numerous quality and intelligibility metrics on a variety of acoustic conditions using the WHAMR corpus, a data-set of noisy reverberant speech mixtures. The use of MHA is also investigated in the decoder network where it is demonstrated that smaller performance improvements are consistently gained within specific model configurations. The best performing MHA models yield a mean 0.6 dB scale invariant signal-to-distortion (SISDR) improvement on noisy reverberant mixtures over a baseline 1D convolution encoder. A mean 1 dB SISDR improvement is observed on clean speech mixtures

    Low-Cost Aquifer Storage and Recovery: Implications for Improving Drinking Water Access for Rural Communities in Coastal Bangladesh

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    Fresh water resources are scarce in rural communities in the southern deltaic plains of Bangladesh where both shallow and deep groundwater is frequently brackish, and fresh water ponds have been increasingly salinized by inundation during storm surges and brackish-water aquaculture. Low-cost aquifer storage and recovery (ASR) schemes were constructed at 13 villages in three coastal districts by developing storage in shallow confined fine to medium sand aquifers overlain by variable thicknesses of silt and clay. A typical ASR scheme consisted of a double-chambered graded sand filtration tank with a volume of 19.5  m3 that feeds filtered pond water to four to six large diameter (d=30.5 or 56 cm) infiltration wells through PVC pipes fitted with stop valves and flow meters. The infiltration wells were completed at 18–31 m below ground and filled with well-sorted gravel capped with a thin layer of fine sand that acts as a second stage filter. Infiltration rates at 13 sites averaged 3  m3/day (range: 3–6  m3/day) over one year of operation. At 11 sites where water was abstracted, the recovery rate ranged from 5 to 40%. The source pond source water frequently had turbidity values of ≥100  NTU. After sand filtration, the turbidity is typically 5 NTU. Despite this, clogging management involving frequent (monthly to weekly) manual washing to remove fine materials deposited in the sand filtration tank and the infiltration wells is found to be necessary and effective, with post-manual-washing operational infiltration rates restored to annual average values. E. coli counts in recovered water are greatly reduced compared to raw pond water, although E. coli is still detected in about half of the samples. Arsenic in recovered water was detected to be at level of > 100  μg/L repeatedly at three sites, suggesting that As risks must be carefully managed and require further investigation

    The eventization of leisure and the strange death of alternative Leeds

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    The communicative potential of city spaces as leisure spaces is a central assumption of political activism and the creation of alternative, counter-cultural and subcultural scenes. However, such potential for city spaces is limited by the gentrification, privatization and eventization of city centres in the wake of wider societal and cultural struggles over leisure, work and identity formation. In this paper, we present research on alternative scenes in the city of Leeds to argue that the eventization of the city centre has led to a marginalization and of alternative scenes on the fringes of the city. Such marginalization has not caused the death of alternative Leeds or political activism associated with those scenes—but it has changed the leisure spaces (physical, political and social) in which alternative scenes contest the mainstream

    A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

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    Background Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations are necessary to understand the physiology, development and adaptation of a plant and its interaction with the environment. Results RiceCyc is a metabolic pathway networks database for rice. It is a snapshot of the substrates, metabolites, enzymes, reactions and pathways of primary and intermediary metabolism in rice. RiceCyc version 3.3 features 316 pathways and 6,643 peptide-coding genes mapped to 2,103 enzyme-catalyzed and 87 protein-mediated transport reactions. The initial functional annotations of rice genes with InterPro, Gene Ontology, MetaCyc, and Enzyme Commission (EC) numbers were enriched with annotations provided by KEGG and Gramene databases. The pathway inferences and the network diagrams were first predicted based on MetaCyc reference networks and plant pathways from the Plant Metabolic Network, using the Pathologic module of Pathway Tools. This was enriched by manually adding metabolic pathways and gene functions specifically reported for rice. The RiceCyc database is hierarchically browsable from pathway diagrams to the associated genes, metabolites and chemical structures. Through the integrated tool OMICs Viewer, users can upload transcriptomic, proteomic and metabolomic data to visualize expression patterns in a virtual cell. RiceCyc, along with additional species-specific pathway databases hosted in the Gramene project, facilitates comparative pathway analysis. Conclusions Here we describe the RiceCyc network development and discuss its contribution to rice genome annotations. As a case study to demonstrate the use of RiceCyc network as a discovery environment we carried out an integrated bioinformatic analysis of rice metabolic genes that are differentially regulated under diurnal photoperiod and biotic stress treatments. The analysis of publicly available rice transcriptome datasets led to the hypothesis that the complete tryptophan biosynthesis and its dependent metabolic pathways including serotonin biosynthesis are induced by taxonomically diverse pathogens while also being under diurnal regulation. The RiceCyc database is available online for free access at http://www.gramene.org/pathway

    The University of Sheffield CHiME-7 UDASE challenge speech enhancement system

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    The CHiME-7 unsupervised domain adaptation speech enhancement (UDASE) challenge targets domain adaptation to unlabelled speech data. This paper describes the University of Sheffield team’s system submitted to the challenge. A generative adversarial network (GAN) methodology based on a conformer-based metric GAN (CMGAN) is employed as opposed to the unsupervised RemixIT strategy used in the CHiME-7 baseline system. The discriminator of the GAN is trained to predict the output score of a Deep Noise Suppression Mean Opinion Score (DNSMOS) metric. Additional data augmentation strategies are employed which provide the discriminator with historical training data outputs as well as more diverse training examples from an additional pseudo-generator. The proposed approach, denoted as CMGAN+/+, achieves significant improvement in DNSMOS evaluation metrics with the best proposed system achieving 3.51 OVR-MOS, a 24% improvement over the baseline

    Perceive and predict: self-supervised speech representation based loss functions for speech enhancement

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    Recent work in the domain of speech enhancement has explored the use of self-supervised speech representations to aid in the training of neural speech enhancement models. However, much of this work focuses on using the deepest or final outputs of self supervised speech representation models, rather than the earlier feature encodings. The use of self supervised representations in such a way is often not fully motivated. In this work it is shown that the distance between the feature encodings of clean and noisy speech correlate strongly with psychoacoustically motivated measures of speech quality and intelligibility, as well as with human Mean Opinion Score (MOS) ratings. Experiments using this distance as a loss function are performed and improved performance over the use of STFT spectrogram distance based loss as well as other common loss functions from speech enhancement literature is demonstrated using objective measures such as perceptual evaluation of speech quality (PESQ) and short-time objective intelligibility (STOI)

    Perceive and predict: self-supervised speech representation based loss functions for speech enhancement

    Get PDF
    Recent work in the domain of speech enhancement has explored the use of self-supervised speech representations to aid in the training of neural speech enhancement models. However, much of this work focuses on using the deepest or final outputs of self supervised speech representation models, rather than the earlier feature encodings. The use of self supervised representations in such a way is often not fully motivated. In this work it is shown that the distance between the feature encodings of clean and noisy speech correlate strongly with psychoacoustically motivated measures of speech quality and intelligibility, as well as with human Mean Opinion Score (MOS) ratings. Experiments using this distance as a loss function are performed and improved performance over the use of STFT spectrogram distance based loss as well as other common loss functions from speech enhancement literature is demonstrated using objective measures such as perceptual evaluation of speech quality (PESQ) and short-time objective intelligibility (STOI)
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