| 1. |
- Svensson, Lennart
(författare)
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Image analysis and interactive visualization techniques for electron microscopy tomograms
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Images are an important data source in modern science and engineering. A continued challenge is to perform measurements on and extract useful information from the image data, i.e., to perform image analysis. Additionally, the image analysis results need to be visualized for best comprehension and to enable correct assessments. In this thesis, research is presented about digital image analysis and three-dimensional (3-D) visualization techniques for use with transmission electron microscopy (TEM) image data and in particular electron tomography, which provides 3-D reconstructions of the nano-structures. The electron tomograms are difficult to interpret because of, e.g., low signal-to-noise ratio, artefacts that stem from sample preparation and insufficient reconstruction information. Analysis is often performed by visual inspection or by registration, i.e., fitting, of molecular models to the image data. Setting up a visualization can however be tedious, and there may be large intra- and inter-user variation in how visualization parameters are set. Therefore, one topic studied in this thesis concerns automatic setup of the transfer function used in direct volume rendering of these tomograms. Results indicate that histogram and gradient based measures are useful in producing automatic and coherent visualizations. Furthermore, research has been conducted concerning registration of templates built using molecular models. Explorative visualization techniques are presented that can provide means of visualizing and navigating model parameter spaces. This gives a new type of visualization feedback to the biologist interpretating the TEM data. The introduced probabilistic template has an improved coverage of the molecular flexibility, by incorporating several conformations into a static model. Evaluation by cross-validation shows that the probabilistic template gives a higher correlation response than using a Protein Databank (PDB) devised model. The software ProViz (for Protein Visualization) is also introduced, where selected developed techniques have been incorporated and are demonstrated in practice.
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| 2. |
- Nilsson, R. Henrik, 1976, et al.
(författare)
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Mycobiome diversity: high-throughput sequencing and identification of fungi.
- 2019
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Ingår i: Nature reviews. Microbiology. - : Springer Science and Business Media LLC. - 1740-1534 .- 1740-1526. ; 17, s. 95-109
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Forskningsöversikt (refereegranskat)abstract
- Fungi are major ecological players in both terrestrial and aquatic environments by cycling organic matter and channelling nutrients across trophic levels. High-throughput sequencing (HTS) studies of fungal communities are redrawing the map of the fungal kingdom by hinting at its enormous - and largely uncharted - taxonomic and functional diversity. However, HTS approaches come with a range of pitfalls and potential biases, cautioning against unwary application and interpretation of HTS technologies and results. In this Review, we provide an overview and practical recommendations for aspects of HTS studies ranging from sampling and laboratory practices to data processing and analysis. We also discuss upcoming trends and techniques in the field and summarize recent and noteworthy results from HTS studies targeting fungal communities and guilds. Our Review highlights the need for reproducibility and public data availability in the study of fungal communities. If the associated challenges and conceptual barriers are overcome, HTS offers immense possibilities in mycology and elsewhere.
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| 3. |
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| 4. |
- Wahlberg, Fredrik, et al.
(författare)
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Data Mining Medieval Documents by Word Spotting
- 2011
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Ingår i: Proceedings of the 2011 Workshop on Historical Document Imaging and Processing. - New York : ACM. - 9781450309165 ; , s. 75-82
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Konferensbidrag (refereegranskat)abstract
- This paper presents novel results for word spotting based on dynamic time warping applied to medieval manuscripts in Latin and Old Swedish. A target word is marked by a user, and the method automatically finds similar word forms in the document by matching them against the target. The method automatically identifies pages and lines. We show that our method improves accuracy compared to earlier proposals for this kind of handwriting. An advantage of the new method is that it performs matching within a text line without presupposing that the difficult problem of segmenting the text line into individual words has been solved. We evaluate our word spotting implementation on two medieval manuscripts representing two script types. We also show that it can be useful by helping a user find words in a manuscript and present graphs of word statistics as a function of page number.
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| 5. |
- Monteiro, Leonardo A., et al.
(författare)
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Potential Use of Data-Driven Models to Estimate and Predict Soybean Yields at National Scale in Brazil
- 2022
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Ingår i: International Journal of Plant Production. - : Springer Science and Business Media LLC. - 1735-8043 .- 1735-6814. ; 16:4, s. 691-703
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Tidskriftsartikel (refereegranskat)abstract
- Large-scale assessment of crop yields plays a fundamental role for agricultural planning and to achieve food security goals. In this study, we evaluated the robustness of data-driven models for estimating soybean yields at 120 days after sow (DAS) in the main producing regions in Brazil; and evaluated the reliability of the “best” data-driven model as a tool for early prediction of soybean yields for an independent year. Our methodology explicitly describes a general approach for wrapping up publicly available databases and build data-driven models (multiple linear regression—MLR; random forests—RF; and support vector machines—SVM) to predict yields at large scales using gridded data of weather and soil information. We filtered out counties with missing or suspicious yield records, resulting on a crop yield database containing 3450 records (23 years × 150 “high-quality” counties). RF and SVM had similar results for calibration and validation steps, whereas MLR showed the poorest performance. Our analysis revealed a potential use of data-driven models for predict soybean yields at large scales in Brazil with around one month before harvest (i.e. 90 DAS). Using a well-trained RF model for predicting crop yield during a specific year at 90 DAS, the RMSE ranged from 303.9 to 1055.7 kg ha–1 representing a relative error (rRMSE) between 9.2 and 41.5%. Although we showed up robust data-driven models for yield prediction at large scales in Brazil, there are still a room for improving its accuracy. The inclusion of explanatory variables related to crop (e.g. growing degree-days, flowering dates), environment (e.g. remotely-sensed vegetation indices, number of dry and heat days during the cycle) and outputs from process-based crop simulation models (e.g. biomass, leaf area index and plant phenology), are potential strategies to improve model accuracy.
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| 6. |
- Patxot, Marion, et al.
(författare)
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Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits
- 2021
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only ≤10% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32–44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having ≥95% probability of contributing ≥0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.
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| 7. |
- Ren, Keni, 1983-, et al.
(författare)
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Where do we find missing data in a commercial real-time location system? Evidence from 2 dairy farms
- 2021
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Ingår i: JDS Communications. - : American Dairy Science Association. - 2666-9102. ; 2, s. 345-350
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Tidskriftsartikel (refereegranskat)abstract
- Real-time indoor positioning using ultra-wideband devices provides an opportunity for modern dairy farms to monitor the behavior of individual cows; however, missing data from these devices hinders reliable continuous monitoring and analysis of animal movement and social behavior. The objective of this study was to examine the data quality, in terms of missing data, in one commercially available ultra-wideband–based real-time location system for dairy cows. The focus was on detecting major obstacles, or sections, inside open freestall barns that resulted in increased levels of missing data. The study was conducted on 2 dairy farms with an existing commercial real-time location system. Position data were recorded for 6 full days from 69 cows on farm 1 and from 59 cows on farm 2. These data were used in subsequent analyses to determine the locations within the dairy barns where position data were missing for individual cows. The proportions of missing data were found to be evenly distributed within the 2 barns after fitting a linear mixed model with spatial smoothing to logit-transformed proportions (mean = 18% vs. 4% missing data for farm 1 and farm 2, respectively), with the exception of larger proportions of missing data along one of the walls on both farms. On farm 1, the variation between individual tags was large (range: 9–49%) compared with farm 2 (range: 12–38%). This greater individual variation of proportions of missing data indicates a potential problem with the individual tag, such as a battery malfunction or tag placement issue. Further research is needed to guide researchers in identifying problems relating to data capture problems in real-time monitoring systems on dairy farms. This is especially important when undertaking detailed analyses of animal movement and social interactions between animals.
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| 8. |
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| 9. |
- Svensson, Lennart, 1980-, et al.
(författare)
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Rigid template registration in MET images using CUDA
- 2012
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Ingår i: VISAPP 2012. - Rome : SciTePress. - 9789898565037 ; 2, s. 418-422
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Konferensbidrag (refereegranskat)abstract
- Rigid registration is a basic tool in many applications, especially in Molecular Electron Tomography (MET), and also in, e.g., registration of rigid implants in medical images and as initialization for deformable registration. As MET volumes have a low signal to noise ratio, a complete search of the six-dimensional (6D) parameter space is often employed. In this paper, we describe how rigid registration with normalized cross-correlation can be implemented on the GPU using NVIDIA's parallel computing architecture CUDA. We compare the performance to the Colores software and two Matlab implementations, one of which is using the GPU accelerated JACKET library. With well-aligned padding and using CUDA, the performance increases by an order of a magnitude, making it feasible to work with three-dimensional fitness landscapes, here denoted scoring volumes, that are generated on the fly. This will eventually enable the biologists to interactively register macromolecule chains in MET volumes piece by piece.
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| 10. |
- Ekenberg, Love, et al.
(författare)
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Deliberation, representation, equity : research approaches, tools and algorithms for participatory processes
- 2017
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Bok (övrigt vetenskapligt/konstnärligt)abstract
- What can we learn about the development of public interaction in e-democracy from a drama delivered by mobile headphones to an audience standing around a shopping center in a Stockholm suburb? In democratic societies there is widespread acknowledgment of the need to incorporate citizens' input in decision-making processes in more or less structured ways. But participatory decision making is balancing on the borders of inclusion, structure, precision and accuracy. To simply enable more participation will not yield enhanced democracy, and there is a clear need for more elaborated elicitation and decision analytical tools. This rigorous and thought-provoking volume draws on a stimulating variety of international case studies, from flood risk management in the Red River Delta of Vietnam, to the consideration of alternatives to gold mining in Ro?ia Montana in Transylvania, to the application of multi-criteria decision analysis in evaluating the impact of e-learning opportunities at Uganda's Makerere University. Editors Love Ekenberg (senior research scholar, International Institute for Applied Systems Analysis [IIASA], Laxenburg, professor of Computer and Systems Sciences, Stockholm University), Karin Hansson (artist and research fellow, Department of Computer and Systems Sciences, Stockholm University), Mats Danielson (vice president and professor of Computer and Systems Sciences, Stockholm University, affiliate researcher, IIASA) and Göran Cars (professor of Societal Planning and Environment, Royal Institute of Technology, Stockholm) draw innovative collaborations between mathematics, social science, and the arts. They develop new problem formulations and solutions, with the aim of carrying decisions from agenda setting and problem awareness through to feasible courses of action by setting objectives, alternative generation, consequence assessments, and trade-off clarifications. As a result, this book is important new reading for decision makers in government, public administration and urban planning, as well as students and researchers in the fields of participatory democracy, urban planning, social policy, communication design, participatory art, decision theory, risk analysis and computer and systems sciences.
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