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- Morales, J. C., et al.
(författare)
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A giant exoplanet orbiting a very-low-mass star challenges planet formation models
- 2019
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 365:6460, s. 1441-1445
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Tidskriftsartikel (refereegranskat)abstract
- Surveys have shown that super-Earth and Neptune-mass exoplanets are more frequent than gas giants around low-mass stars, as predicted by the core accretion theory of planet formation. We report the discovery of a giant planet around the very-low-mass star GJ 3512, as determined by optical and near-infrared radial-velocity observations. The planet has a minimum mass of 0.46 Jupiter masses, very high for such a small host star, and an eccentric 204-day orbit. Dynamical models show that the high eccentricity is most likely due to planet-planet interactions. We use simulations to demonstrate that the GJ 3512 planetary system challenges generally accepted formation theories, and that it puts constraints on the planet accretion and migration rates. Disk instabilities may be more efficient in forming planets than previously thought.
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| 2. |
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| 3. |
- Pavlou, AK, et al.
(författare)
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An intelligent rapid odour recognition model in discrimination of Helicobacter pylori and other gastroesophageal isolates in vitro
- 2000
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Ingår i: Biosensors & bioelectronics. - : Elsevier Science B.V., Amsterdam.. - 0956-5663 .- 1873-4235. ; 15:08-jul, s. 333-342
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Tidskriftsartikel (refereegranskat)abstract
- Two series of experiments are reported which result in the discrimination between Helicobacter pylori and other bacterial gastroesophageal isolates using a newly developed odour generating system, an electronic nose and a hybrid intelligent odour recognition system. In the first series of experiments, after 5 h of growth (37 degreesC), 53 volatile sniffs were collected over the headspace of complex broth cultures of the following clinical isolates: Staphylococcus aureus, Klebsiella sp., H. pylori, Enterococcus faecalis (10(7) ml(-1)), Mixed infection (Proteus mirabilis, Escherichia coli, and E. faecalis 3 x 10(6) mi each) and sterile cultures. Fifty-six normalised variables were extracted from 14 conductive polymer sensor responses and analysed by a 3-layer back propagation neural network (NN). The NN prediction rate achieved was 98% and the test data (37.7% of all data) was recognised correctly. Successful clustering of bacterial classes was also achieved by discriminant analysis (DA) of a normalised subset of sensor data. Cross-validation identified correctly seven unknown samples. In the second series of experiments after 150 min of microaerobic growth at 37 degreesC, 24 volatile samples were collected over the headspace of H. pylori cultures in enriched (HPP) and normal (HP) media and 11 samples over sterile (N) cultures. Forty-eight sensor parameters were extracted from 12 sensor responses and analysed by a 3-layer NN previously optimised by a genetic algorithm (GA). GA-NN analysis achieved a 94% prediction rate or unknown data. Additionally the genetically selected 16 input neurones were used to perform DA-cross validation that showed a clear clustering of three groups and reclassified correctly nine sniffs. It is concluded that the most important factors that govern the performance of an intelligent bacterial odour detection system are: (a) an odour generation mechanism, (b) a rapid odour delivery system similar to the mammalian olfactory system, (c) a gas sensor array of high reproducibility and (d) a hybrid intelligent model (expert system) which will enable the parallel use of GA-NNs and multivariate techniques. (C) 1999 Elsevier Science S.A. All rights reserved.
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| 4. |
- Pavlou, A, et al.
(författare)
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Recognition of anaerobic bacterial isolates in vitro using electronic nose technology
- 2002
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Ingår i: Letters in Applied Microbiology. - : Blackwell Publishing Ltd. - 0266-8254 .- 1472-765X. ; 35:5, s. 366-369
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Tidskriftsartikel (refereegranskat)abstract
- Aims: Use of an electronic nose (e.nose) system to differentiation between anaerobic bacteria grown in vitro on agar media. Methods and Results: Cultures of Clostridium spp. (14 strains) and Bacteroides fragilis (12 strains) were grown on blood agar plates and incubated in sampling bags for 30 min before head space analysis of the volatiles. Qualitative analyses of the volatile production patterns was carried out using an e.nose system with 14 conducting polymer sensors. Using data analysis techniques such as principal components analysis (PCA), genetic algorithms and neural networks it was possible to differentiate between agar blanks and individual species which accounted for all the data. A total of eight unknowns were correctly discriminated into the bacterial groups. Conclusions: This is the first report of in vitro complex volatile pattern recognition and differentiation of anaerobic pathogens. Significance and Impact of the Study: These results suggest the potential for application of e.nose technology in early diagnosis of microbial pathogens of medical importance.
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| 5. |
- Pavlou, AK, et al.
(författare)
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Use of an electronic nose system for diagnoses of urinary tract infections
- 2002
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Ingår i: Biosensors & bioelectronics. - : Elsevier Science B.V., Amsterdam.. - 0956-5663 .- 1873-4235. ; 17:10, s. 893-899
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Tidskriftsartikel (refereegranskat)abstract
- The use of volatile production patterns produced by bacterial contaminants in urine samples were examined using electronic nose technology. In two experiments 25 and 45 samples from patients were analysed for specific bacterial contaminants using agar culture techniques and the major UTI bacterial species identified. These samples were also analysed by incubation in a volatile generation test tube system for 4-5 h. The volatile production patterns were then analysed using an electronic nose system with 14 conducting polymer sensors. In the first experiment analysis of the data using a neural network (NN) enabled identification of all but one of the samples correctly when compared to the culture information. Four groups could be distinguished, i.e. normal urine, Escherichia coli infected, Proteus spp. and Staphylococcus spp. In the second experiment it was again possible to use NN systems to examine the volatile production patterns and identify 18 of 19 unknown UTI cases. Only one normal patient sample was mis-identified as an E coli infected sample. Discriminant function analysis also differentiated between normal urine samples, that infected with E coli and with Staphylococcus spp. This study has shown the potential for early detection of microbial contaminants in urine samples using electronic nose technology for the first time. These findings will have implications for the development of rapid systems for use in clinical practice. (C) 2002 Elsevier Science B.V. All rights reserved.
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