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In order to help journalists investigate inside large audiovisual archives, as maintained by news broadcast agencies, the multimedia data must be indexed by text-based search engies. By automatically creating a transcript through automatic speech recognition (ASR), the spoken word becomes accessible to text search, and queries for keywords are made possible. But stil, important contextual information like the identity of the speaker is not captured. Especially when gathering original footage in the political domain, the identity of the speaker can be the most important query constraint, although this name may not be prominent in the words spoken. It is thus desireable to have this information provided explicitely to the search engine. To provide this information, the archive must be an alyzed by automatic Speaker Identification (SID). While this research topic has seen substantial gains in accuracy and robustness over last years, it has not yet established itself as a helpful, large-scale tool outside the research community. This thesis sets out to establish a workflow to provide automatic speaker identification. Its application is to help journalists searching on speeches given in the German parliament (Bundestag). This is a contribution to the News-Stream 3.0 project, a BMBF funded research project that addresses accessibility of various data sources for journalists.
DNA Sequencing
(2011)
The glomerulosclerosis gene Mpv17 encodes a peroxisomal protein producing reactive oxygen species
(1994)
Interactive Distributed Rendering of 3D Scenes on Multiple Xbox 360 Systems and Personal Computers
(2012)
Transient up-regulation of P2 receptors influence differentiation of human mesenchymal stem cells
(2012)
RNA is one of the most important molecules in living organisms. One of its main functions is to regulate gene expression. This involves binding to and forming a joint structure with a messenger RNA. An RNAs functions is determined by its sequence and the structure it folds into. Accordingly, the prediction of individual as well as joint structures is an important area of research. In this thesis a method for the prediction of RNA-RNA joint structure using their minimum free energy (mfe) structures was developed. It is able to extensively explore the joint structural landscape of two interacting RNAs by taking advantage of the locality of changes in the RNAs structures as well as natural and energetic constraints. The method predicts the mfe joint structure as well as alternative stable joint structures while also computing non-optimal folding pathways from the unbound individual mfe structures to the predicted joint structures. It is shown how an enumeration approach is used which is able to deal with the enormous search space as well as to avoid any cyclic behaviour. The method is evaluated using two standard datasets of known interacting RNAs and shows good results.
MOTIVATION: The genome projects produce a wealth of protein sequences. Theoretical methods to predict possible structures and functions are needed for screening purposes, large-scale comparisons and in-depth analysis to identify worthwhile targets for further experimental research. Sequence-structure alignment is a basic tool for the identification of model folds for protein sequences and the construction of crude structural models. Empirical contact potentials (potentials of mean force) are used to optimize and evaluate such alignments. RESULTS: We propose new scoring schemes based on a contact definition derived from Voronoi decompositions of the three-dimensional coordinates of protein structures. We demonstrate that Voronoi potentials are superior to pure distance-based contact potentials with respect to recognition rate and significance for native folds. Moreover, the scoring scheme has the potential to provide a reasonable balance of detail and ion such that it is also useful for the recognition of distantly related (both homologous and non-homologous) proteins. This is demonstrated here on a set of structural alignments showing much better correspondence of native and model scores for the Voronoi potentials as compared to conventional distance-based potentials.
Scientific or statistical research has long been the domain of dedicated programming languages such as R, SPSS or SAS. A few years other competitors entered the arena, among them Python with its powerful SciPy package. The following article introduces SciPy by applying a small subset of its functionality to a well-known dataset.
During space missions astronauts suffer from cardiovascular deconditioning, when they are exposed to microgravity conditions. Until now, no specific drugs are available for effective countermeasures, since the underlying mechanism is not completely understood. Endothelial cells (ECs) and smooth muscle cells (SMCs) play crucial roles in a variety of cardiovascular functions, many of which are regulated via P2 receptors. However, their function in ECs and SMCs under microgravity condition is still unknown. In this study, ECs and SMCs were isolated from bovine aorta and differentiated from human mesenchymal stem cells (hMSCs), respectively. Subsequently, the cells were verified based on specific markers. An altered P2 receptor expression pattern was detected during the commitment of hMSC towards ECs and SMCs. The administration of natural and artificial P2 receptor agonists and antagonists directly affected the differentiation process. By using EC growth medium as conditioned medium, a vessel cell model was created to culture SMCs and vice versa. Within this study, we were able to show for the first time that the expression of some P2 receptors were altered in ECs and SMCs grown for 24h under simulated microgravity conditions. On the other hand, in some P2 receptor expressions such as P2X7 conditioned medium compensated this change.
In conclusion, our data show that P2 receptors play an important functional role in hMSC differentiation towards ECs and SMCs. Since some P2 receptor artificial ligands are already used as drugs for patients with cardiovascular diseases, it is reasonable to assume that in the future they might be promising candidates for treating cardiovascular deconditioning.
Graph drawing with spring embedders employs a V x V computation phase over the graph's vertex set to compute repulsive forces. Here, the efficacy of forces diminishes with distance: a vertex can effectively only influence other vertices in a certain radius around its position. Therefore, the algorithm lends itself to an implementation using search data structures to reduce the runtime complexity. NVIDIA RT cores implement hierarchical tree traversal in hardware. We show how to map the problem of finding graph layouts with force-directed methods to a ray tracing problem that can subsequently be implemented with dedicated ray tracing hardware. With that, we observe speedups of 4x to 13x over a CUDA software implementation.