Towards automated configuration of stream clustering algorithms

Clustering is an important technique in data analysis which can reveal hidden patterns and unknown relationships in the data. A common problem in clustering is the proper choice of parameter settings. To tackle this, automated algorithm configuration is available which can automatically find the best parameter settings. In practice, however, many of our today’s data sources are data streams due to the widespread deployment of sensors, the internet-of-things or (social) media. Stream clustering aims to tackle this challenge by identifying, tracking and updating clusters over time. Unfortunately, none of the existing approaches for automated algorithm configuration are directly applicable to the streaming scenario. In this paper, we explore the possibility of automated algorithm configuration for stream clustering algorithms using an ensemble of different configurations. In first experiments, we demonstrate that our approach is able to automatically find superior configurations and refine them over time

confstream: automated algorithm selection and configuration of stream clustering algorithms

Machine learning has become one of the most important tools in data analysis. However, selecting the most appropriate machine learning algorithm and tuning its hyperparameters to their optimal values remains a difficult task. This is even more difficult for streaming applications where automated approaches are often not available to help during algorithm selection and configuration. This paper proposes the first approach for automated algorithm selection and configuration of stream clustering algorithms. We train an ensemble of different stream clustering algorithms and configurations in parallel and use the best performing configuration to obtain a clustering solution. By drawing new configurations from better performing ones, we are able to improve the ensemble performance over time. In large experiments on real and artificial data we show how our ensemble approach can improve upon default configurations and can also compete with a-posteriori algorithm configuration. Our approach is considerably faster than a-posteriori approaches and applicable in real-time. In addition, it is not limited to stream clustering and can be generalised to all streaming applications, including stream classification and regression

Multi-task learning with a natural metric for quantitative structure activity relationship learning

The goal of Quantitative Structure Activity Relationship (QSAR) Learning is to learn a function that, given the structure of a small molecule (a potential drug), outputs the predicted activity of the compound. We employed multi-task learning (MTL) to exploit commonalities in drug targets and assays. We used datasets containing curated records about the activity of speci c compounds on drug targets provided by ChEMBL. Totally, 1091 assays have been analysed. As a baseline, a single task learning approach that trains random forest to predict drug activity for each drug target individually was considered. We then carried out feature-based and instance-based MTL to predict drug activities. We introduced a natural metric of evolutionary distance between drug targets as a measure of tasks relatedness. Instance-based MTL signi cantly outperformed both, feature-based MTL and the base learner, on 741 drug targets out of 1091. Feature-based MTL won on 179 occasions and the base learner performed best on 171 drug targets. We conclude that MTL QSAR is improved by incorporating the evolutionary distance between targets. These results indicate that QSAR learning can be performed effectively, even if little data is available for speci c drug targets, by leveraging what is known about similar drug targets

Effects of tidal-forcing variations on tidal properties along a narrow convergent estuary

A 1D analytical framework is implemented in a narrow convergent estuary that is 78 km in length (the Guadiana, Southern Iberia) to evaluate the tidal dynamics along the channel, including the effects of neap-spring amplitude variations at the mouth. The close match between the observations (damping from the mouth to ∼ 30 km, shoaling upstream) and outputs from semi-closed channel solutions indicates that the M2 tide is reflected at the estuary head. The model is used to determine the contribution of reflection to the dynamics of the propagating wave. This contribution is mainly confined to the upper one third of the estuary. The relatively constant mean wave height along the channel (< 10% variations) partly results from reflection effects that also modify significantly the wave celerity and the phase difference between tidal velocity and elevation (contradicting the definition of an “ideal” estuary). Furthermore, from the mouth to ∼ 50 km, the variable friction experienced by the incident wave at neap and spring tides produces wave shoaling and damping, respectively. As a result, the wave celerity is largest at neap tide along this lower reach, although the mean water level is highest in spring. Overall, the presented analytical framework is useful for describing the main tidal properties along estuaries considering various forcings (amplitude, period) at the estuary mouth and the proposed method could be applicable to other estuaries with small tidal amplitude to depth ratio and negligible river discharge.info:eu-repo/semantics/publishedVersio

Maternal TLR4 and NOD2 Gene Variants, Pro-Inflammatory Phenotype and Susceptibility to Early-Onset Preeclampsia and HELLP Syndrome

Background: Altered maternal inflammatory responses play a role in the development of preeclampsia and the hemolysis, elevated liver enzymes and low platelets (HELLP) syndrome. We examined whether allelic variants of the innate immune receptors toli-like receptor 4 (TLR4) and nucleotide-binding oligomerization domain (NOD2), that impair the inflammatory response to endotexin are related to preeclampsia and HELLP syndrome. Methods and Finding: We determined five common mutations in TLR4 (D299G and T399I and NOD2 (R70W, G908R and L1007fs) in 340 primiparous women with a histo

Human melanoma-initiating cells express neural crest nerve growth factor receptor CD271.

The question of whether tumorigenic cancer stem cells exist in human melanomas has arisen in the last few years. Here we show that in melanomas, tumour stem cells (MTSCs, for melanoma tumour stem cells) can be isolated prospectively as a highly enriched CD271(+) MTSC population using a process that maximizes viable cell transplantation. The tumours sampled in this study were taken from a broad spectrum of sites and stages. High-viability cells isolated by fluorescence-activated cell sorting and re-suspended in a matrigel vehicle were implanted into T-, B- and natural-killer-deficient Rag2(-/-)gammac(-/-) mice. The CD271(+) subset of cells was the tumour-initiating population in 90% (nine out of ten) of melanomas tested. Transplantation of isolated CD271(+) melanoma cells into engrafted human skin or bone in Rag2(-/-)gammac(-/-) mice resulted in melanoma; however, melanoma did not develop after transplantation of isolated CD271(-) cells. We also show that in mice, tumours derived from transplanted human CD271(+) melanoma cells were capable of metastatsis in vivo. CD271(+) melanoma cells lacked expression of TYR, MART1 and MAGE in 86%, 69% and 68% of melanoma patients, respectively, which helps to explain why T-cell therapies directed at these antigens usually result in only temporary tumour shrinkage

Neuromuscular training to enhance sensorimotor and functional deficits in subjects with chronic ankle instability: A systematic review and best evidence synthesis

<p>Abstract</p> <p>Objective</p> <p>To summarise the available evidence for the efficacy of neuromuscular training in enhancing sensorimotor and functional deficits in subjects with chronic ankle instability (CAI).</p> <p>Design</p> <p>Systematic review with best evidence synthesis.</p> <p>Data Sources</p> <p>An electronic search was conducted through December 2009, limited to studies published in the English language, using the Pubmed, CINAHL, Embase, and SPORTDiscus databases. Reference screening of all included articles was also undertaken.</p> <p>Methods</p> <p>Studies were selected if the design was a RCT, quasi RCT, or a CCT; the patients were adolescents or adults with confirmed CAI; and one of the treatment options consisted of a neuromuscular training programme. The primary investigator independently assessed the risk of study bias and extracted relevant data. Due to clinical heterogeneity, data was analysed using a best-evidence synthesis.</p> <p>Results</p> <p>Fourteen studies were included in the review. Meta-analysis with statistical pooling of data was not possible, as the studies were considered too heterogeneous. Instead a best evidence synthesis was undertaken. There is limited to moderate evidence to support improvements in dynamic postural stability, and patient perceived functional stability through neuromuscular training in subjects with CAI. There is limited evidence of effectiveness for neuromuscular training for improving static postural stability, active and passive joint position sense (JPS), isometric strength, muscle onset latencies, shank/rearfoot coupling, and a reduction in injury recurrence rates. There is limited evidence of no effectiveness for improvements in muscle fatigue following neuromuscular intervention.</p> <p>Conclusion</p> <p>There is limited to moderate evidence of effectiveness in favour of neuromuscular training for various measures of static and dynamic postural stability, active and passive JPS, isometric strength, muscle onset latencies, shank/rearfoot coupling and injury recurrence rates. Strong evidence of effectiveness was lacking for all outcome measures. All but one of the studies included in the review were deemed to have a high risk of bias, and most studies were lacking sufficient power. Therefore, in future we recommend conducting higher quality RCTs using appropriate outcomes to assess for the effectiveness of neuromuscular training in overcoming sensorimotor deficits in subjects with CAI.</p

A point mutation in cpsE renders Streptococcus pneumoniae nonencapsulated and enhances its growth, adherence and competence.

BACKGROUND: The polysaccharide capsule is a major virulence factor of the important human pathogen Streptococcus pneumoniae. However, S. pneumoniae strains lacking capsule do occur. RESULTS: Here, we report a nasopharyngeal isolate of Streptococcus pneumoniae composed of a mixture of two phenotypes; one encapsulated (serotype 18C) and the other nonencapsulated, determined by serotyping, electron microscopy and fluorescence isothiocyanate dextran exclusion assay.By whole genome sequencing, we demonstrated that the phenotypes differ by a single nucleotide base pair in capsular gene cpsE (C to G change at gene position 1135) predicted to result in amino acid change from arginine to glycine at position 379, located in the cytoplasmic, enzymatically active, region of this transmembrane protein. This SNP is responsible for loss of capsule production as the phenotype is transferred with the capsule operon. The nonencapsulated variant is superior in growth in vitro and is also 117-fold more adherent to and more invasive into Detroit 562 human epithelial cells than the encapsulated variant.Expression of six competence pathway genes and one competence-associated gene was 11 to 34-fold higher in the nonencapsulated variant than the encapsulated and transformation frequency was 3.7-fold greater. CONCLUSIONS: We identified a new single point mutation in capsule gene cpsE of a clinical S. pneumoniae serotype 18C isolate sufficient to cause loss of capsule expression resulting in the co-existence of the encapsulated and nonencapsulated phenotype. The mutation caused phenotypic changes in growth, adherence to epithelial cells and transformability. Mutation in capsule gene cpsE may be a way for S. pneumoniae to lose its capsule and increase its colonization potential