Towards a parallel computationally efficient approach to scaling up data stream classification

Advances in hardware technologies allow to capture and process data in real-time and the resulting high throughput data streams require novel data mining approaches. The research area of Data Stream Mining (DSM) is developing data mining algorithms that allow us to analyse these continuous streams of data in real-time. The creation and real-time adaption of classification models from data streams is one of the most challenging DSM tasks. Current classifiers for streaming data address this problem by using incremental learning algorithms. However, even so these algorithms are fast, they are challenged by high velocity data streams, where data instances are incoming at a fast rate. This is problematic if the applications desire that there is no or only a very little delay between changes in the patterns of the stream and absorption of these patterns by the classifier. Problems of scalability to Big Data of traditional data mining algorithms for static (non streaming) datasets have been addressed through the development of parallel classifiers. However, there is very little work on the parallelisation of data stream classification techniques. In this paper we investigate K-Nearest Neighbours (KNN) as the basis for a real-time adaptive and parallel methodology for scalable data stream classification tasks.

How well can we model stream phosphorus concentrations in agricultural catchments?

Mechanistic catchment-scale phosphorus models appear to perform poorly where diffuse sources dominate. We investigate the reasons for this for one model, INCA-P, testing model output against 18 months of daily data in a small Scottish catchment. We examine key model processes and provide recommendations for model improvement and simplification. Improvements to the particulate phosphorus simulation are especially needed. The model evaluation procedure is then generalised to provide a checklist for identifying why model performance may be poor or unreliable, incorporating calibration, data, structural and conceptual challenges. There needs to be greater recognition that current models struggle to produce positive Nash–Sutcliffe statistics in agricultural catchments when evaluated against daily data. Phosphorus modelling is difficult, but models are not as useless as this might suggest. We found a combination of correlation coefficients, bias, a comparison of distributions and a visual assessment of time series a better means of identifying realistic simulations.

Changes in sewage sludge carbon forms along a treatment stream

The behaviour and fate of macronutrients and pollutants in sewage sludge applied to the land are affected by the chemical composition of the sludge organic matter, which in turn is influenced by both sewage source and by sewage treatment processes. In this study, 13C nuclear magnetic resonance (NMR) spectroscopy was used to characterise the organic matter of sludges collected at three different points along the treatment stream of a municipal sewage works with a domestic catchment. Sludge at the first point, an undigested liquid (UL) sludge, had a substantially different composition to the anaerobically digested (AD) and dewatered sludge cake (DC) materials, which were similar to each other. In particular, the UL sludge contained more alkyl C than the AD or DC sludges. All three sludges were found to contain mobile alkyl C that is poorly observed using the cross polarisation (CP) technique, necessitating the use of the less sensitive, but more quantitatively reliable direct polarisation (DP) technique to obtain accurate distributions of C types.

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.

Big social data and political sentiment: the tweet stream during the UK General Election 2015 campaign

The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.

Chemically tagging the Hyades stream: does it partly originate from the Hyades cluster?

The Hyades stream has long been thought to be a dispersed vestige of the Hyades cluster. However, recent analyses of the parallax distribution, of the mass function, and of the action-space distribution of stream stars have shown it to be rather composed of orbits trapped at a resonance of a density disturbance. This resonant scenario should leave a clearly different signature in the element abundances of stream stars than the dispersed cluster scenario, since the Hyades cluster is chemically homogeneous. Here, we study the metallicity as well as the element abundances of Li, Na, Mg, Fe, Zr, Ba, La, Ce, Nd and Eu for a random sample of stars belonging to the Hyades stream, and compare them with those of stars from the Hyades cluster. From this analysis: (i) we independently confirm that the Hyades stream cannot be solely composed of stars originating in the Hyades cluster; (ii) we show that some stars (namely 2/21) from the Hyades stream nevertheless have abundances compatible with an origin in the cluster; (iii) we emphasize that the use of Li as a chemical tag of the cluster origin of main-sequence stars is very efficient in the range 5500 K <= T(eff) <= 6200 K, since the Li sequence in the Hyades cluster is very tight, while at the same time spanning a large abundance range; (iv) we show that, while this evaporated population has a metallicity excess of similar to 0.2 dex with respect to the local thin-disc population, identical to that of the Hyades cluster, the remainder of the Hyades stream population has still a metallicity excess of similar to 0.06-0.15 dex, consistent with an origin in the inner Galaxy and (v) we show that the Hyades stream can be interpreted as an inner 4:1 resonance of the spiral pattern: this then also reproduces an orbital family compatible with the Sirius stream, and places the origin of the Hyades stream up to 1 kpc inwards from the solar radius, which might explain the observed metallicity excess of the stream population.

Fungal community associated with marine macroalgae from Antarctica

Filamentous fungi and yeasts associated with the marine algae Adenocystis utricularis, Desmarestia anceps, and Palmaria decipiens from Antarctica were studied. A total of 75 fungal isolates, represented by 27 filamentous fungi and 48 yeasts, were isolated from the three algal species and identified by morphological, physiological, and sequence analyses of the internal transcribed spacer region and D1/D2 variable domains of the large-subunit rRNA gene. The filamentous fungi and yeasts obtained were identified as belonging to the genera Geomyces, Antarctomyces, Oidiodendron, Penicillium, Phaeosphaeria, Aureobasidium, Cryptococcus, Leucosporidium, Metschnikowia, and Rhodotorula. The prevalent species were the filamentous fungus Geomyces pannorum and the yeast Metschnikowia australis. Two fungal species isolated in our study, Antarctomyces psychrotrophicus and M. australis, are endemic to Antarctica. This work is the first study of fungi associated with Antarctic marine macroalgae, and contributes to the taxonomy and ecology of the marine fungi living in polar environments. These fungal species may have an important role in the ecosystem and in organic matter recycling.

RECOVERY OF p-TBC FROM A BUTADIENE WASHING STREAM IN A PILOT PLANT

Results obtained in a pilot-scale unit designed for COD removal and p-TBC (p-tert-butylcatechol) recovery from a butadiene washing stream (pH 14, 200,000 mg COD L(-1), highly toxic) at a petrochemical industry are presented. By adding H(3)PO(4), phase separation is achieved and p-TBC is successfully recovered (88 g L(-1) of washing stream). Information (time for phase separation and organic phase characterization) was gathered for designing a future industrial unit. The estimated heat generation rate was 990 kJ min(-1) and 15 min were enough to promote phase separation for a liquid column of approximately 1.15 m.