Refine
H-BRS Bibliography
- yes (45)
Departments, institutes and facilities
- Präsidium (29)
- Fachbereich Informatik (8)
- Fachbereich Angewandte Naturwissenschaften (5)
- Stabsstelle Kommunikation und Marketing (2)
- Fachbereich Ingenieurwissenschaften und Kommunikation (1)
- Fachbereich Wirtschaftswissenschaften (1)
- Institut für Verbraucherinformatik (IVI) (1)
- Institut für funktionale Gen-Analytik (IFGA) (1)
- Institute of Visual Computing (IVC) (1)
- Verwaltung (1)
Document Type
- Part of Periodical (29)
- Article (9)
- Report (3)
- Part of a Book (2)
- Bachelor Thesis (1)
- Master's Thesis (1)
Year of publication
- 2012 (45) (remove)
Has Fulltext
- yes (45) (remove)
Keywords
- 3D-Scanner (2)
- ARRs (1)
- Assistenzsystem (1)
- Aufklärung (1)
- Augmented Reality (1)
- Bildungsmanagement (1)
- Calcium (1)
- Calcium Intracellular Release (1)
- Cardiovascular Disease (1)
- Cell Cycle (1)
- Cell Differentiation (1)
- Cell Signaling (1)
- DNA Transcription (1)
- DOI (1)
- Data Publication (1)
- DataCite (1)
- Digital Object Identifier (1)
- Electromagnetic Fields (1)
- Environmental Data (1)
- Erwachsenwerden (1)
- FDI (1)
- GC/MS (1)
- Gruppendiskussion (1)
- Hochschulentwicklung (1)
- Hochschulgesetz (1)
- Hochschulprofilierung (1)
- Hybrid models of engineering systems (1)
- Hybrid systems (1)
- Jugendfernsehen (1)
- Jugendliche (1)
- Jugendzentrum (1)
- Köln (1)
- Meteorological Data (1)
- Mobiler Roboter (1)
- Morphologie (1)
- Polymers (1)
- Pubertät (1)
- Pubertätskrise (1)
- Pyrolysis (1)
- Risikomanagement (1)
- Robotik (1)
- Software Architecture (1)
- Software Framework (1)
- Transcription Regulation (1)
- Tvision GmbH (1)
- Vascular Smooth Muscle Cells (1)
- Virtual Reality (1)
- Westdeutscher Rundfunk (1)
- Workflow Management (1)
- analytical redundancy relation residuals (1)
- averaged bond graph models (1)
- binary classification (1)
- bond graphs (1)
- e-Research (1)
- external faults (1)
- fault scenarios (1)
- fault detection (1)
- isolation (1)
- mobile manipulators (1)
- operation mode independent causalities (1)
- power electronic systems (1)
- residual sinks (1)
- switched three-phase power inverter (1)
- system mode independent bond graph representation (1)
- öffentlich-rechtlich (1)
Human mesenchymal stem cells (hMSCs) are considered a promising cell source for regenerative medicine, because they have the potential to differentiate into a variety of lineages among which the mesoderm-derived lineages such adipo- or osteogenesis are investigated best. Human MSCs can be harvested in reasonable to large amounts from several parts of the patient’s body and due to this possible autologous origin, allorecognition can be avoided. In addition, even in allogenic origin-derived donor cells, hMSCs generate a local immunosuppressive microenvironment, causing only a weak immune reaction. There is an increasing need for bone replacement in patients from all ages, due to a variety of reasons such as a new recreational behavior in young adults or age-related diseases. Adipogenic differentiation is another interesting lineage, because fat tissue is considered to be a major factor triggering atherosclerosis that ultimately leads to cardiovascular diseases, the main cause of death in industrialized countries. However, understanding the differentiation process in detail is obligatory to achieve a tight control of the process for future clinical applications to avoid undesired side effects. In this review, the current findings for adipo- and osteo-differentiation are summarized together with a brief statement on first clinical trials.
This article concerns with the accessibility of Business process modelling tools (BPMo tools) and business process modelling languages (BPMo languages). Therefore the reader will be introduced to business process management and the authors' motivation behind this inquiry. Afterwards, the paper will reflect problems when applying inaccessible BPMo tools. To illustrate these problems the authors distinguish between two different categories of issues and provide practical examples. Finally the article will present three approaches to improve the accessibility of BPMo tools and BPMo languages.
The biological effects of bilirubin, still poorly understood, are concentration-dependent ranging from cell protection to toxicity. Here we present data that at high nontoxic physiological concentrations, bilirubin inhibits growth of proliferating human coronary artery smooth muscle cells by three events. It impairs the activation of Raf/ERK/MAPK pathway and the cellular Raf and cyclin D1 content that results in retinoblastoma protein hypophosphorylation on amino acids S608 and S780. These events impede the release of YY1 to the nuclei and its availability to regulate the expression of genes and to support cellular proliferation. Moreover, altered calcium influx and calpain II protease activation leads to proteolytical degradation of transcription factor YY1. We conclude that in the serum-stimulated human vascular smooth muscle primary cell cultures, bilirubin favors growth arrest, and we propose that this activity is regulated by its interaction with the Raf/ERK/MAPK pathway, effect on cyclin D1 and Raf content, altered retinoblastoma protein profile of hypophosphorylation, calcium influx, and YY1 proteolysis. We propose that these activities together culminate in diminished 5 S and 45 S ribosomal RNA synthesis and cell growth arrest. The observations provide important mechanistic insight into the molecular mechanisms underlying the transition of human vascular smooth muscle cells from proliferative to contractile phenotype and the role of bilirubin in this transition.
In a research project funded by the German Research Foundation, meteorologists, data publication experts, and computer scientists optimised the publication process of meteorological data and developed software that supports metadata review. The project group placed particular emphasis on scientific and technical quality assurance of primary data and metadata. At the end, the software automatically registers a Digital Object Identifier at DataCite. The software has been successfully integrated into the infrastructure of the World Data Center for Climate, but a key was to make the results applicable to data publication processes in other sciences as well.
In service robotics, tasks without the involvement of objects are barely applicable, like in searching, fetching or delivering tasks. Service robots are supposed to capture efficiently object related information in real world scenes while for instance considering clutter and noise, and also being flexible and scalable to memorize a large set of objects. Besides object perception tasks like object recognition where the object’s identity is analyzed, object categorization is an important visual object perception cue that associates unknown object instances based on their e.g. appearance or shape to a corresponding category. We present a pipeline from the detection of object candidates in a domestic scene over the description to the final shape categorization of detected candidates. In order to detect object related information in cluttered domestic environments an object detection method is proposed that copes with multiple plane and object occurrences like in cluttered scenes with shelves. Further a surface reconstruction method based on Growing Neural Gas (GNG) in combination with a shape distribution-based descriptor is proposed to reflect shape characteristics of object candidates. Beneficial properties provided by the GNG such as smoothing and denoising effects support a stable description of the object candidates which also leads towards a more stable learning of categories. Based on the presented descriptor a dictionary approach combined with a supervised shape learner is presented to learn prediction models of shape categories.
Experimental results, of different shapes related to domestically appearing object shape categories such as cup, can, box, bottle, bowl, plate and ball, are shown. A classification accuracy of about 90% and a sequential execution time of lesser than two seconds for the categorization of an unknown object is achieved which proves the reasonableness of the proposed system design. Additional results are shown towards object tracking and false positive handling to enhance the robustness of the categorization. Also an initial approach towards incremental shape category learning is proposed that learns a new category based on the set of previously learned shape categories.
We present our approach to extend a Virtual Reality software framework towards the use for Augmented Reality applications. Although VR and AR applications have very similar requirements in terms of abstract components (like 6DOF input, stereoscopic output, simulation engines), the requirements in terms of hardware and software vary considerably. In this article we would like to share the experience gained from adapting our VR software framework for AR applications. We will address design issues for this task. The result is a VR/AR basic software that allows us to implement interactive applications without fixing their type (VR or AR) beforehand. Switching from VR to AR is a matter of changing the configuration file of the application. We also give an example of the use of the extended framework: Augmenting the magnetic field of bar magnets in physics classes. We describe the setup of the system and the real-time calculation of the magnetic field, using a GPU.
The work presented in this paper focuses on the comparison of well-known and new fault-diagnosis algorithms in the robot domain. The main challenge for fault diagnosis is to allow the robot to effectively cope not only with internal hardware and software faults but with external disturbances and errors from dynamic and complex environments as well. Based on a study of literature covering fault-diagnosis algorithms, I selected four of these methods based on both linear and non-linear models, analysed and implemented them in a mathematical robot-model, representing a four-wheels-OMNI robot. In experiments I tested the ability of the algorithms to detect and identify abnormal behaviour and to optimize the model parameters for the given training data. The final goal was to point out the strengths of each algorithm and to figure out which method would best suit the demands of fault diagnosis for a particular robot.
One of the most common problems in Regenerative Medicine is the regeneration of damaged bone with the aim of repairing or replacing lost or damaged bone tissue by stimulating the natural regenerative process. Particularly in the fields of orthopedic, plastic, reconstructive, maxillofacial and craniofacial surgery there is need for successful methods to restore bone. From a regenerative point of view two different bone replacement problems can be distinguished: large bone defects and small bone defects. Currently, no perfect system exists for the treatment of large bone defects.