Model predictions of the occurrence of non-Maxwellian plasmas, and analysis of their effects on EISCAT data

The recent identification of non-thermal plasmas using EISCAT data has been made possible by their occurrence during large, short-lived flow bursts. For steady, yet rapid, ion convection the only available signature is the shape of the spectrum, which is unreliable because it is open to distortion by noise and sampling uncertainty and can be mimicked by other phenomena. Nevertheless, spectral shape does give an indication of the presence of non-thermal plasma, and the characteristic shape has been observed for long periods (of the order of an hour or more) in some experiments. To evaluate this type of event properly one needs to compare it to what would be expected theoretically. Predictions have been made using the coupled thermosphere-ionosphere model developed at University College London and the University of Sheffield to show where and when non-Maxwellian plasmas would be expected in the auroral zone. Geometrical and other factors then govern whether these are detectable by radar. The results are applicable to any incoherent scatter radar in this area, but the work presented here concentrates on predictions with regard to experiments on the EISCAT facility.

New-on-line method for water isotope analysis of speleothem fluid inclusions using laser absorption spectroscopy (WS-CRDS)

A new online method to analyse water isotopes of speleothem fluid inclusions using a wavelength scanned cavity ring down spectroscopy (WS-CRDS) instrument is presented. This novel technique allows us simultaneously to measure hydrogen and oxygen isotopes for a released aliquot of water. To do so, we designed a new simple line that allows the online water extraction and isotope analysis of speleothem samples. The specificity of the method lies in the fact that fluid inclusions release is made on a standard water background, which mainly improves the δ D robustness. To saturate the line, a peristaltic pump continuously injects standard water into the line that is permanently heated to 140 °C and flushed with dry nitrogen gas. This permits instantaneous and complete vaporisation of the standard water, resulting in an artificial water background with well-known δ D and δ18O values. The speleothem sample is placed in a copper tube, attached to the line, and after system stabilisation it is crushed using a simple hydraulic device to liberate speleothem fluid inclusions water. The released water is carried by the nitrogen/standard water gas stream directly to a Picarro L1102-i for isotope determination. To test the accuracy and reproducibility of the line and to measure standard water during speleothem measurements, a syringe injection unit was added to the line. Peak evaluation is done similarly as in gas chromatography to obtain &delta D; and δ18O isotopic compositions of measured water aliquots. Precision is better than 1.5 ‰ for δ D and 0.4 ‰ for δ18O for water measurements for an extended range (−210 to 0 ‰ for δ D and −27 to 0 ‰ for δ18O) primarily dependent on the amount of water released from speleothem fluid inclusions and secondarily on the isotopic composition of the sample. The results show that WS-CRDS technology is suitable for speleothem fluid inclusion measurements and gives results that are comparable to the isotope ratio mass spectrometry (IRMS) technique.

Capturing and sharing our collective expertise on climate data: the CHARMe project

For users of climate services, the ability to quickly determine the datasets that best fit one's needs would be invaluable. The volume, variety and complexity of climate data makes this judgment difficult. The ambition of CHARMe ("Characterization of metadata to enable high-quality climate services") is to give a wider interdisciplinary community access to a range of supporting information, such as journal articles, technical reports or feedback on previous applications of the data. The capture and discovery of this "commentary" information, often created by data users rather than data providers, and currently not linked to the data themselves, has not been significantly addressed previously. CHARMe applies the principles of Linked Data and open web standards to associate, record, search and publish user-derived annotations in a way that can be read both by users and automated systems. Tools have been developed within the CHARMe project that enable annotation capability for data delivery systems already in wide use for discovering climate data. In addition, the project has developed advanced tools for exploring data and commentary in innovative ways, including an interactive data explorer and comparator ("CHARMe Maps") and a tool for correlating climate time series with external "significant events" (e.g. instrument failures or large volcanic eruptions) that affect the data quality. Although the project focuses on climate science, the concepts are general and could be applied to other fields. All CHARMe system software is open-source, released under a liberal licence, permitting future projects to re-use the source code as they wish.

Production and on-line comprehension of definiteness in English and Dutch by monolingual and sequential bilingual children

The present article examines production and on-line processing of definite articles in Turkish-speaking sequential bilingual children acquiring English and Dutch as second languages (L2) in the UK and in the Netherlands, respectively. Thirty-nine 6–8-year-old L2 children and 48 monolingual (L1) age-matched children participated in two separate studies examining the production of definite articles in English and Dutch in conditions manipulating semantic context, that is, the anaphoric and the bridging contexts. Sensitivity to article omission was examined in the same groups of children using an on-line processing task involving article use in the same semantic contexts as in the production task. The results indicate that both L2 children and L1 controls are less accurate when definiteness is established by keeping track of the discourse referents (anaphoric) than when it is established via world knowledge (bridging). Moreover, despite variable production, all groups of children were sensitive to the omission of definite articles in the on-line comprehension task. This suggests that the errors of omission are not due to the lack of abstract syntactic representations, but could result from processes implicated in the spell-out of definite articles. The findings are in line with the idea that variable production in child L2 learners does not necessarily indicate lack of abstract representations (Haznedar and Schwartz, 1997).

Interactional dynamics in on-line and face-to-face peer-tutoring sessions for second language writers

This paper reports the results of a study comparing the interactional dynamics of face-to-face and on-line peer-tutoring in writing by university students in Hong Kong. Transcripts of face-to-face tutoring sessions, as well as logs of on-line sessions conducted by the same peer-tutors, were coded for speech functions using a system based on Halliday's functional-semantic view of dialogue. Results show considerable differences between the interactional dynamics in on-line and face-to-face tutoring sessions. In particular, face-to-face interactions involved more hierarchal encounters in which tutors took control of the discourse, whereas on-line interactions were more egalitarian, with clients controlling the discourse more. Differences were also found in the topics participants chose to focus on in the two modes, with issues of grammar, vocabulary, and style taking precedence in face-to-face sessions and more “global” writing concerns like content and process being discussed more in on-line sessions.

Benchmarking or business opportunity: Using milk recording data to expose your clients' weaknesses

Routine milk recording data, often covering many years, are available for approximately half the dairy herds of England and Wales. In addition to milk yield and quality, these data include production events that can be used to derive objective Key Performance Indicators (KPI) describing a herd's fertility and production. Recent developments in information systems give veterinarians and other technical advisers access to these KPIs on-line. In addition to reviewing individual herd performance, advisers can establish local benchmark groups to demonstrate the relative performance of similar herds in the vicinity. The use of existing milk recording data places no additional demands on farmer's time or resources. These developments could also readily be exploited by universities to introduce veterinary undergraduates to the realities of commercial dairy production.

Phylogenomics of eukaryotes: Impact of missing data on large alignments

Resolving the relationships between Metazoa and other eukaryotic groups as well as between metazoan phyla is central to the understanding of the origin and evolution of animals. The current view is based on limited data sets, either a single gene with many species (e.g., ribosomal RNA) or many genes but with only a few species. Because a reliable phylogenetic inference simultaneously requires numerous genes and numerous species, we assembled a very large data set containing 129 orthologous proteins (similar to30,000 aligned amino acid positions) for 36 eukaryotic species. Included in the alignments are data from the choanoflagellate Monosiga ovata, obtained through the sequencing of about 1,000 cDNAs. We provide conclusive support for choanoflagellates as the closest relative of animals and for fungi as the second closest. The monophyly of Plantae and chromalveolates was recovered but without strong statistical support. Within animals, in contrast to the monophyly of Coelomata observed in several recent large-scale analyses, we recovered a paraphyletic Coelamata, with nematodes and platyhelminths nested within. To include a diverse sample of organisms, data from EST projects were used for several species, resulting in a large amount of missing data in our alignment (about 25%). By using different approaches, we verify that the inferred phylogeny is not sensitive to these missing data. Therefore, this large data set provides a reliable phylogenetic framework for studying eukaryotic and animal evolution and will be easily extendable when large amounts of sequence information become available from a broader taxonomic range.

Knowledge-elicitation and data-mining: fusing human and industrial plant information

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process. (C) 2005 Elsevier Ltd. All rights reserved.

Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.

Rejoinder to 'Performance of different synchronisation measures in real data: A case study on electroencephalograhic signals

We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga et al. [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga et al. in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga et al. in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

Comment on "Performance of different synchronization measures in real data: A case study on electroencephalographic signals"

We agree with Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] and Quian Quiroga [Phys. Rev. E 67, 063902 (2003)] that mutual information (MI) is a useful measure of dependence for electroencephalogram (EEG) data, but we show that the improvement seen in the performance of MI on extracting dependence trends from EEG is more dependent on the type of MI estimator rather than any embedding technique used. In an independent study we conducted in search for an optimal MI estimator, and in particular for EEG applications, we examined the performance of a number of MI estimators on the data set used by Quian Quiroga in their original study, where the performance of different dependence measures on real data was investigated [Phys. Rev. E 65, 041903 (2002)]. We show that for EEG applications the best performance among the investigated estimators is achieved by k-nearest neighbors, which supports the conjecture by Quian Quiroga in Phys. Rev. E 67, 063902 (2003) that the nearest neighbor estimator is the most precise method for estimating MI.

PDM 2006: Proceedings of the International Workshop on Data Mining

Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.

History education in comprehensive schools: using school level data to interpret national patterns

This paper reports the findings from two large scale national on-line surveys carried out in 2009 and 2010, which explored the state of history teaching in English secondary schools. Large variation in provision was identified within comprehensive schools in response to national policy decisions and initiatives. Using the data from the surveys and school level data that is publicly available, this study examines situated factors, particularly the nature of the school intake, the numbers of pupils with special educational needs and the socio-economic status of the area surrounding the school, and the impact these have on the provision of history education. The findings show that there is a growing divide between those students that have access to the ‘powerful knowledge’, provided by subjects like history, and those that do not.

Representation errors and retrievals in linear and nonlinear data assimilation

This article shows how one can formulate the representation problem starting from Bayes’ theorem. The purpose of this article is to raise awareness of the formal solutions,so that approximations can be placed in a proper context. The representation errors appear in the likelihood, and the different possibilities for the representation of reality in model and observations are discussed, including nonlinear representation probability density functions. Specifically, the assumptions needed in the usual procedure to add a representation error covariance to the error covariance of the observations are discussed,and it is shown that, when several sub-grid observations are present, their mean still has a representation error ; socalled ‘superobbing’ does not resolve the issue. Connection is made to the off-line or on-line retrieval problem, providing a new simple proof of the equivalence of assimilating linear retrievals and original observations. Furthermore, it is shown how nonlinear retrievals can be assimilated without loss of information. Finally we discuss how errors in the observation operator model can be treated consistently in the Bayesian framework, connecting to previous work in this area.