1,930 research outputs found
State-Space Inference and Learning with Gaussian Processes
No full text18.10.13 KB. Ok to add author version to spiral, authors hold copyright.State-space inference and learning with Gaussian processes (GPs) is an unsolved problem. We propose a new, general methodology for inference and learning in nonlinear state-space models that are described probabilistically by non-parametric GP models. We apply the expectation maximization algorithm to iterate between inference in the latent state-space and learning the parameters of the underlying GP dynamics model. Copyright 2010 by the authors
Systematic Reconstruction of Molecular Cascades Regulating GP Development Using Single-Cell RNA-Seq
No full textSummaryThe growth plate (GP) comprising sequentially differentiated cell layers is a critical structure for bone elongation and regeneration. Although several key regulators in GP development have been identified using genetic perturbation, systematic understanding is still limited. Here, we used single-cell RNA-sequencing (RNA-seq) to determine the gene expression profiles of 217 single cells from GPs and developed a bioinformatics pipeline named Sinova to de novo reconstruct physiological GP development in both temporal and spatial high resolution. Our unsupervised model not only confirmed prior knowledge, but also enabled the systematic discovery of genes, potential signal pathways, and surface markers CD9/CD200 to precisely depict development. Sinova further identified the effective combination of transcriptional factors (TFs) that regulates GP maturation, and the result was validated using an in vitro EGFP-Col10a screening system. Our case systematically reconstructed molecular cascades in GP development through single-cell profiling, and the bioinformatics pipeline is applicable to other developmental processes.Video Abstrac
Performances of authorial presence and absence : the author dies hard
No full textThis book takes Roland Barthes’s famous proclamation of ‘The Death of the Author’ as a starting point to investigate concepts of authorial presence and absence on various levels of text and performance. By offering a new understanding of ‘the author’ as neither a source of unquestioned authority nor an obsolete construct, but rather as a performative figure, the book illuminates wide-ranging aesthetic and political aspects of ‘authorial death’ by asking: how is the author constructed through cultural and political imaginaries and erasures, intertextual and intertheatrical references, re-performances and self-referentiality? And what are the politics and ethics of these constructions
User-defined parameters for the ELM, ANN and GP models.
No full text<p>User-defined parameters for the ELM, ANN and GP models.</p
Vliv Moto GP na cestovní ruch v Brně
No full textThe main aim of the bachelor thesis is find out how Moto GP influence tourism in Brno, what is the availability of accommodation facilities, what is the increase in prices during this period. In the theoretical part, analyse the tourism as a whole, destination of tourism, Moto GP. Practical part examines using a questionnaire how residents perceive the action Moto GP. There is unfortunately not sufficient statistical data to determine the icrease in prices as well as occupancy of acommodation capacities in the period when Moto GP race takes place in Brno. That is the reason why the author of this thesis has decided to conduct a research by using a sample of 10 % of hotels in Brno to be able to answer these questions
Comparison of performance statistics of the ELM, ANN and GP bone age assessment models.
No full text<p>Comparison of performance statistics of the ELM, ANN and GP bone age assessment models.</p
Danger in discharge summaries: abbreviations create confusion for both author and recipient
No full textBackground: The transition from hospital inpatient care to medical care in the community is a high-risk period for adverse events. Inadequate communication, including low-quality or unavailable discharge summaries, has been shown to impact patient care. Aims: To assess use of abbreviations in clinical handover documents from inpatient hospital teams to general practitioners (GP), and the interpretation of these abbreviations by GP and hospital-based junior doctors. Methods: This is a retrospective audit of 802 discharge summaries completed during a 1-week period in 2017 by a Queensland regional health service. GP and local junior doctors then attempted interpretation of 20 relevant abbreviations. Results: A total of 99% (794) discharge summaries included abbreviations. A total of 1612 different abbreviations was used on 16 327 occasions. The median number of abbreviations per discharge summary was 17 (range 0–86). A total of 254 GP and 62 junior doctors responded to a survey, which found that no abbreviation was interpreted the same by all respondents. GP and junior doctors were unable to offer any interpretation in 17.9% and 15.2% of cases respectively. GP offered a greater range of interpretations than junior doctors, with a median of 9 and 3 different interpretations per abbreviation respectively. A total of 94% (239) of GP felt that the use of abbreviations in discharge summaries had the potential to impact patient care. A total of 152 (60%) GP felt that time spent clarifying abbreviations in discharge summaries could be excessive. Conclusions: Abbreviations are often used in discharge summaries, yet poorly understood. This has the potential to impact patient care in the transition period after hospitalisation.No Full Tex
The logarithmic class group package in PARI/GP
No full textInternational audienceThis note presents our implementation in the PARI/GP system of the various arithmetic invariants attached to logarithmic classes and units of number fields. Our algorithms simplify and improve on works of Diaz y Diaz, Pauli, Pohst, Soriano and the second author
The logarithmic class group package in PARI/GP
No full textInternational audienceThis note presents our implementation in the PARI/GP system of the various arithmetic invariants attached to logarithmic classes and units of number fields. Our algorithms simplify and improve on works of Diaz y Diaz, Pauli, Pohst, Soriano and the second author
Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors
No full textThe recently introduced Gene-pool Optimal Mixing Evolutionary Algorithm for Genetic Programming (GP-GOMEA) has been shown to find much smaller solutions of equally high quality compared to other state-of-the-art GP approaches. This is an interesting aspect as small solutions better enable human interpretation. In this paper, an adaptation of GP-GOMEA to tackle real-world symbolic regression is proposed, in order to find small yet accurate mathematical expressions, and with an application to a problem of clinical interest. For radiotherapy dose reconstruction, a model is sought that captures anatomical patient similarity. This problem is particularly interesting because while features are patient-specific, the variable to regress is a distance, and is defined over patient pairs. We show that on benchmark problems as well as on the application, GP-GOMEA outperforms variants of standard GP. To find even more accurate models, we further consider an evolutionary meta learning approach, where GP-GOMEA is used to construct small, yet effective features for a different machine learning algorithm. Experimental results show how this approach significantly improves the performance of linear regression, support vector machines, and random forest, while providing meaningful and interpretable features
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