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| 2. |
- Billstein, Mats, et al.
(author)
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Development and Validation of a Numerical Model of Flow Through Embankment Dams – Comparisons with Experimental Data and Analytical Solutions
- 1999
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In: Transport in Porous Media. - 0169-3913 .- 1573-1634. ; 35:3, s. 395-406
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Journal article (peer-reviewed)abstract
- The development and validation of a numerical simulation model of the flow through embankment dams is described. The paper focuses on basic verification studies, that is, comparisons with analytical solutions and data from laboratory experiments. Two experimental studies, one dealing with the flow in a Hele-Shaw cell and the other with the flow through a bed of packed glass beads, are also described. Comparisons are carried out with respect to the phreatic surfaces, pressure profiles, seepage levels and discharges. It is concluded that the agreement between experimental, analytical and numerical results is generally satisfactory.
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| 3. |
- Billsten, Helena, et al.
(author)
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Dynamics of vibrational relaxation in the S-1 state of carotenoids having 11 conjugated C=C bonds
- 2002
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In: Chemical Physics Letters. - 0009-2614. ; 355:5-6, s. 465-470
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Journal article (peer-reviewed)abstract
- Transient absorption spectra and kinetics in the 470-650 nm region were recorded for lycopene, P-carotene and zeaxanthin, all carotenoids with 11 conjugated double bonds, in two solvents with different polarity. Analysis of the red wing of the carotenoid SI-S, transition revealed presence of a pronounced shoulder at early delay times. The kinetics recorded at this low-energy shoulder of the SI-S, transition yields an additional decay component of 500-800 fs in addition to the main S, decay. This dynamics is ascribed to a vibrational relaxation in the S, state of the carotenoids. (C) 2002 Elsevier Science B.V. All rights reserved.
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| 4. |
- Nevalainen, Nina, et al.
(author)
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Dopamine release from serotonergic nerve fibers is reduced in L-DOPA-induced dyskinesia
- 2011
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In: Journal of Neurochemistry. - : Wiley. - 0022-3042 .- 1471-4159. ; 118:1, s. 12-23
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Journal article (peer-reviewed)abstract
- L-DOPA is the most commonly used treatment for symptomatic control in patients with Parkinson's disease. Unfortunately, most patients develop severe side-effects, such as dyskinesia, upon chronic l-DOPA treatment. The patophysiology of dyskinesia is unclear; however, involvement of serotonergic nerve fibers in converting l-DOPA to dopamine has been suggested. Therefore, potassium-evoked dopamine release was studied after local application of l-DOPA in the striata of normal, dopamine- and dopamine/serotonin-lesioned l-DOPA naïve, and dopamine-denervated chronically l-DOPA-treated dyskinetic rats using in vivo chronoamperometry. The results revealed that local l-DOPA administration into normal and intact hemisphere of dopamine-lesioned l-DOPA naïve animals significantly increased the potassium-evoked dopamine release. l-DOPA application also increased the dopamine peak amplitude in the dopamine-depleted l-DOPA naïve striatum, although these dopamine levels were several-folds lower than in the normal striatum, whereas no increased dopamine release was found in the dopamine/serotonin-denervated striatum. In dyskinetic animals, local l-DOPA application did not affect the dopamine release, resulting in significantly attenuated dopamine levels compared with those measured in l-DOPA naïve dopamine-denervated striatum. To conclude, l-DOPA is most likely converted to dopamine in serotonergic nerve fibers in the dopamine-depleted striatum, but the dopamine release is several-fold lower than in normal striatum. Furthermore, l-DOPA loading does not increase the dopamine release in dyskinetic animals as found in l-DOPA naïve animals, despite similar density of serotonergic innervation. Thus, the dopamine overflow produced from the serotonergic nerve fibers appears not to be the major cause of dyskinetic behavior.
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| 6. |
- Skeppstedt, Maria
(author)
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Enhancing Medical Named Entity Recognition with Features Derived from Unsupervised Methods
- 2014
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In: Proceedings of the Student Research Workshop at the 14th Conference of the European Chapter of the Association for Computational Linguistics. - Stroudsburg, PA : Association for Computational Linguistics. ; , s. 21-30
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Conference paper (peer-reviewed)abstract
- A study of the usefulness of features extracted from unsupervised methods is pro- posed. The usefulness of these features will be studied on the task of performing named entity recognition within one clinical sub-domain as well as on the task of adapting a named entity recognition model to a new clinical sub-domain. Four named entity types, all very relevant for clinical information extraction, will be studied: Disorder, Finding, Pharmaceutical Drug and Body Structure. The named entity recognition will be performed using conditional random fields. As unsupervised features, a clustering of the semantic representation of words obtained from a ran- dom indexing word space will be used.
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| 7. |
- Skeppstedt, Maria, 1977-, et al.
(author)
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Finding Reasons for Vaccination Hesitancy : Evaluating Semi-Automatic Coding of Internet Discussion Forums
- 2019
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In: MEDINFO 2019: Health and Wellbeing e-Networks for All. - : IOS Press. - 9781643680033 - 9781643680026 ; , s. 348-352
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Conference paper (peer-reviewed)abstract
- Computer-assisted text coding can facilitate the analysis of large text collections. To evaluate the functionality of providing an analyst with a ranked list of suggestions for suitable text codes, we used a data set of discussion posts, which had been manually coded for reasons given for taking a stance on the topic of vaccination. We trained a logistic regression classifier to rank these reasons according to the probability that they would be present in the post. The approach was evaluated for its ability to include the expected reasons among the n top-ranked reasons, using an n between 1 and 6. The logistic regression-based ranking was more effective than the baseline, which ranked reasons according to their frequency in the training data. To provide such a list of possible codes, ranked by logistic regression, could therefore be a useful feature in a tool for text coding.
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| 8. |
- Skeppstedt, Maria, Dr. 1977-, et al.
(author)
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From word clouds to Word Rain: Revisiting the classic word cloud to visualize climate change texts
- 2024
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In: Information Visualization. - : Sage Publications. - 1473-8716 .- 1473-8724. ; 23:3, s. 217-238
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Journal article (peer-reviewed)abstract
- Word Rain is a development of the classic word cloud. It addresses some of the limitations of word clouds, in particular the lack of a semantically motivated positioning of the words, and the use of font size as a sole indicator of word prominence. Word Rain uses the semantic information encoded in a distributional semantics-based language model – reduced into one dimension – to position the words along the x-axis. Thereby, the horizontal positioning of the words reflects semantic similarity. Font size is still used to signal word prominence, but this signal is supplemented with a bar chart, as well as with the position of the words on the y-axis. We exemplify the use of Word Rain by three concrete visualization tasks, applied on different real-world texts and document collections on climate change. In these case studies, word2vec models, reduced to one dimension with t-SNE, are used to encode semantic similarity, and TF-IDF is used for measuring word prominence. We evaluate the technique further by carrying out domain expert reviews.
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