49 resultados para automated instruments
Resumo:
Automatic keyword or keyphrase extraction is concerned with assigning keyphrases to documents based on words from within the document. Previous studies have shown that in a significant number of cases author-supplied keywords are not appropriate for the document to which they are attached. This can either be because they represent what the author believes a paper is about not what it actually is, or because they include keyphrases which are more classificatory than explanatory e.g., “University of Poppleton” instead of “Knowledge Discovery in Databases”. Thus, there is a need for a system that can generate an appropriate and diverse range of keyphrases that reflect the document. This paper proposes two possible solutions that examine the synonyms of words and phrases in the document to find the underlying themes, and presents these as appropriate keyphrases. Using three different freely available thesauri, the work undertaken examines two different methods of producing keywords and compares the outcomes across multiple strands in the timeline. The primary method explores taking n-grams of the source document phrases, and examining the synonyms of these, while the secondary considers grouping outputs by their synonyms. The experiments undertaken show the primary method produces good results and that the secondary method produces both good results and potential for future work. In addition, the different qualities of the thesauri are examined and it is concluded that the more entries in a thesaurus, the better it is likely to perform. The age of the thesaurus or the size of each entry does not correlate to performance.
Resumo:
The proteome of Salmonella enterica serovar Typhimurium was characterized by 2-dimensional HPLC mass spectrometry to provide a platform for subsequent proteomic investigations of low level multiple antibiotic resistance (MAR). Bacteria (2.15 +/- 0.23 x 10(10) cfu; mean +/- s.d.) were harvested from liquid culture and proteins differentially fractionated, on the basis of solubility, into preparations representative of the cytosol, cell envelope and outer membrane proteins (OMPs). These preparations were digested by treatment with trypsin and peptides separated into fractions (n = 20) by strong cation exchange chromatography (SCX). Tryptic peptides in each SCX fraction were further separated by reversed-phase chromatography and detected by mass spectrometry. Peptides were assigned to proteins and consensus rank listings compiled using SEQUEST. A total of 816 +/- 11 individual proteins were identified which included 371 +/- 33, 565 +/- 15 and 262 +/- 5 from the cytosolic, cell envelope and OMP preparations, respectively. A significant correlation was observed (r(2) = 0.62 +/- 0.10; P < 0.0001) between consensus rank position for duplicate cell preparations and an average of 74 +/- 5% of proteins were common to both replicates. A total of 34 outer membrane proteins were detected, 20 of these from the OMP preparation. A range of proteins (n = 20) previously associated with the mar locus in E. coli were also found including the key MAR effectors AcrA, TolC and OmpF.
Resumo:
In biological mass spectrometry (MS), two ionization techniques are predominantly employed for the analysis of larger biomolecules, such as polypeptides. These are nano-electrospray ionization [1, 2] (nanoESI) and matrix-assisted laser desorption/ionization [3, 4] (MALDI). Both techniques are considered to be “soft”, allowing the desorption and ionization of intact molecular analyte species and thus their successful mass-spectrometric analysis. One of the main differences between these two ionization techniques lies in their ability to produce multiply charged ions. MALDI typically generates singly charged peptide ions whereas nanoESI easily provides multiply charged ions, even for peptides as low as 1000 Da in mass. The production of highly charged ions is desirable as this allows the use of mass analyzers, such as ion traps (including orbitraps) and hybrid quadrupole instruments, which typically offer only a limited m/z range (< 2000–4000). It also enables more informative fragmentation spectra using techniques such as collisioninduced dissociation (CID) and electron capture/transfer dissociation (ECD/ETD) in combination with tandem MS (MS/MS). [5, 6] Thus, there is a clear advantage of using ESI in research areas where peptide sequencing, or in general, the structural elucidation of biomolecules by MS/MS is required. Nonetheless, MALDI with its higher tolerance to contaminants and additives, ease-of-operation, potential for highspeed and automated sample preparation and analysis as well as its MS imaging capabilities makes it an ionization technique that can cover bioanalytical areas for which ESI is less suitable. [7, 8] If these strengths could be combined with the analytical power of multiply charged ions, new instrumental configurations and large-scale proteomic analyses based on MALDI MS(/MS) would become feasible.
Resumo:
Keyphrases are added to documents to help identify the areas of interest they contain. However, in a significant proportion of papers author selected keyphrases are not appropriate for the document they accompany: for instance, they can be classificatory rather than explanatory, or they are not updated when the focus of the paper changes. As such, automated methods for improving the use of keyphrases are needed, and various methods have been published. However, each method was evaluated using a different corpus, typically one relevant to the field of study of the method’s authors. This not only makes it difficult to incorporate the useful elements of algorithms in future work, but also makes comparing the results of each method inefficient and ineffective. This paper describes the work undertaken to compare five methods across a common baseline of corpora. The methods chosen were Term Frequency, Inverse Document Frequency, the C-Value, the NC-Value, and a Synonym based approach. These methods were analysed to evaluate performance and quality of results, and to provide a future benchmark. It is shown that Term Frequency and Inverse Document Frequency were the best algorithms, with the Synonym approach following them. Following these findings, a study was undertaken into the value of using human evaluators to judge the outputs. The Synonym method was compared to the original author keyphrases of the Reuters’ News Corpus. The findings show that authors of Reuters’ news articles provide good keyphrases but that more often than not they do not provide any keyphrases.
Resumo:
In order to make best use of the opportunities provided by space missions such as the Radiation Belt Storm Probes, we determine the response of complementary subionospheric radiowave propagation measurements (VLF), riometer absorption measurements (CNA), and GPS-produced total electron content (vTEC) to different energetic electron precipitation (EEP). We model the relative sensitivity and responses of these instruments to idealised monoenergetic beams of precipitating electrons, and more realistic EEP spectra chosen to represent radiation belts and substorm precipitation. In the monoenergetic beam case, we find riometers are more sensitive to the same EEP event occurring during the day than during the night, while subionospheric VLF shows the opposite relationship, and the change in vTEC is independent. In general, the subionospheric VLF measurements are much more sensitive than the other two techniques for EEP over 200 keV, responding to flux magnitudes two-three orders of magnitude smaller than detectable by a riometer. Detectable TEC changes only occur for extreme monoenergetic fluxes. For the radiation belt EEP case, clearly detectable subionospheric VLF responses are produced by daytime fluxes that are ~10 times lower than required for riometers, while nighttime fluxes can be 10,000 times lower. Riometers are likely to respond only to radiation belt fluxes during the largest EEP events and vTEC is unlikely to be significantly disturbed by radiation belt EEP. For the substorm EEP case both the riometer absorption and the subionospheric VLF technique respond significantly, as does the change in vTEC, which is likely to be detectable at ~3-4 TECu.
Resumo:
Two aircraft instruments for the measurement of total odd nitrogen (NOy) were compared side by side aboard a Learjet A35 in April 2003 during a campaign of the AFO2000 project SPURT (Spurengastransport in der Tropopausenregion). The instruments albeit employing the same measurement principle (gold converter and chemiluminescence) had different inlet configurations. The ECO-Physics instrument operated by ETH-Zürich in SPURT had the gold converter mounted outside the aircraft, whereas the instrument operated by FZ-Jülich in the European project MOZAIC III (Measurements of ozone, water vapour, carbon monoxide and nitrogen oxides aboard Airbus A340 in-service aircraft) employed a Rosemount probe with 80 cm of FEP-tubing connecting the inlet to the gold converter. The NOy concentrations during the flight ranged between 0.3 and 3 ppb. The two data sets were compared in a blind fashion and each team followed its normal operating procedures. On average, the measurements agreed within 7%, i.e. within the combined uncertainty of the two instruments. This puts an upper limit on potential losses of HNO3 in the Rosemount inlet of the MOZAIC instrument. Larger transient deviations were observed during periods after calibrations and when the aircraft entered the stratosphere. The time lag of the MOZAIC instrument observed in these instances is in accordance with the time constant of the MOZAIC inlet line determined in the laboratory for HNO3.
Resumo:
Combining SNPs into allele scores provides a more powerful instrument for MR analysis than a single SNP in isolation. Population stratification and the potential for pleiotropic effects need to be considered in MR studies on vitamin D.
Resumo:
This technique paper describes a novel method for quantitatively and routinely identifying auroral breakup following substorm onset using the Time History of Events and Macroscale Interactions During Substorms (THEMIS) all-sky imagers (ASIs). Substorm onset is characterised by a brightening of the aurora that is followed by auroral poleward expansion and auroral breakup. This breakup can be identified by a sharp increase in the auroral intensity i(t) and the time derivative of auroral intensity i'(t). Utilising both i(t) and i'(t) we have developed an algorithm for identifying the time interval and spatial location of auroral breakup during the substorm expansion phase within the field of view of ASI data based solely on quantifiable characteristics of the optical auroral emissions. We compare the time interval determined by the algorithm to independently identified auroral onset times from three previously published studies. In each case the time interval determined by the algorithm is within error of the onset independently identified by the prior studies. We further show the utility of the algorithm by comparing the breakup intervals determined using the automated algorithm to an independent list of substorm onset times. We demonstrate that up to 50% of the breakup intervals characterised by the algorithm are within the uncertainty of the times identified in the independent list. The quantitative description and routine identification of an interval of auroral brightening during the substorm expansion phase provides a foundation for unbiased statistical analysis of the aurora to probe the physics of the auroral substorm as a new scientific tool for aiding the identification of the processes leading to auroral substorm onset.
Resumo:
A method of automatically identifying and tracking polar-cap plasma patches, utilising data inversion and feature-tracking methods, is presented. A well-established and widely used 4-D ionospheric imaging algorithm, the Multi-Instrument Data Assimilation System (MIDAS), inverts slant total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers to produce images of the free electron distribution in the polar-cap ionosphere. These are integrated to form vertical TEC maps. A flexible feature-tracking algorithm, TRACK, previously used extensively in meteorological storm-tracking studies is used to identify and track maxima in the resulting 2-D data fields. Various criteria are used to discriminate between genuine patches and "false-positive" maxima such as the continuously moving day-side maximum, which results from the Earth's rotation rather than plasma motion. Results for a 12-month period at solar minimum, when extensive validation data are available, are presented. The method identifies 71 separate structures consistent with patch motion during this time. The limitations of solar minimum and the consequent small number of patches make climatological inferences difficult, but the feasibility of the method for patches larger than approximately 500 km in scale is demonstrated and a larger study incorporating other parts of the solar cycle is warranted. Possible further optimisation of discrimination criteria, particularly regarding the definition of a patch in terms of its plasma concentration enhancement over the surrounding background, may improve results.
Resumo:
Currently, infrared filters for astronomical telescopes and satellite radiometers are based on multilayer thin film stacks of alternating high and low refractive index materials. However, the choice of suitable layer materials is limited and this places limitations on the filter performance that can be achieved. The ability to design materials with arbitrary refractive index allows for filter performance to be greatly increased but also increases the complexity of design. Here a differential algorithm was used as a method for optimised design of filters with arbitrary refractive indices, and then materials are designed to these specifications as mono-materials with sub wavelength structures using Bruggeman’s effective material approximation (EMA).
Resumo:
We present the first comprehensive intercomparison of currently available satellite ozone climatologies in the upper troposphere/lower stratosphere (UTLS) (300–70 hPa) as part of the Stratosphere-troposphere Processes and their Role in Climate (SPARC) Data Initiative. The Tropospheric Emission Spectrometer (TES) instrument is the only nadir-viewing instrument in this initiative, as well as the only instrument with a focus on tropospheric composition. We apply the TES observational operator to ozone climatologies from the more highly vertically resolved limb-viewing instruments. This minimizes the impact of differences in vertical resolution among the instruments and allows identification of systematic differences in the large-scale structure and variability of UTLS ozone. We find that the climatologies from most of the limb-viewing instruments show positive differences (ranging from 5 to 75%) with respect to TES in the tropical UTLS, and comparison to a “zonal mean” ozonesonde climatology indicates that these differences likely represent a positive bias for p ≤ 100 hPa. In the extratropics, there is good agreement among the climatologies regarding the timing and magnitude of the ozone seasonal cycle (differences in the peak-to-peak amplitude of <15%) when the TES observational operator is applied, as well as very consistent midlatitude interannual variability. The discrepancies in ozone temporal variability are larger in the tropics, with differences between the data sets of up to 55% in the seasonal cycle amplitude. However, the differences among the climatologies are everywhere much smaller than the range produced by current chemistry-climate models, indicating that the multiple-instrument ensemble is useful for quantitatively evaluating these models.
Resumo:
Petasis and Ugi reactions are used successively without intermediate purification, effectively accomplishing a six-component reaction. The examined reactions are transferred from traditional batch reactors to an automated continuous flow microreactor setup, where optimization and kinetic analyses are performed, proposed mechanisms evaluated, and rate-limiting steps determined.
Resumo:
Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.
Resumo:
Contamination of the electroencephalogram (EEG) by artifacts greatly reduces the quality of the recorded signals. There is a need for automated artifact removal methods. However, such methods are rarely evaluated against one another via rigorous criteria, with results often presented based upon visual inspection alone. This work presents a comparative study of automatic methods for removing blink, electrocardiographic, and electromyographic artifacts from the EEG. Three methods are considered; wavelet, blind source separation (BSS), and multivariate singular spectrum analysis (MSSA)-based correction. These are applied to data sets containing mixtures of artifacts. Metrics are devised to measure the performance of each method. The BSS method is seen to be the best approach for artifacts of high signal to noise ratio (SNR). By contrast, MSSA performs well at low SNRs but at the expense of a large number of false positive corrections.
Resumo:
A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing. The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g. electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged auto-mutual information clustering (LAMIC) and Fully automated statistical thresholding (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.