Refine
Year of publication
- 2012 (164) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (59)
- INB - Institut für Nano- und Biotechnologien (28)
- IfB - Institut für Bioengineering (28)
- Fachbereich Elektrotechnik und Informationstechnik (24)
- Fachbereich Chemie und Biotechnologie (15)
- Fachbereich Maschinenbau und Mechatronik (14)
- Solar-Institut Jülich (13)
- Fachbereich Luft- und Raumfahrttechnik (10)
- Fachbereich Wirtschaftswissenschaften (10)
- Fachbereich Bauingenieurwesen (9)
Language
- English (164) (remove)
Document Type
- Article (82)
- Conference Proceeding (59)
- Book (6)
- Part of a Book (5)
- Conference: Meeting Abstract (5)
- Doctoral Thesis (5)
- Other (1)
- Review (1)
Keywords
- (Bio)degradation (1)
- 802.15.4 (1)
- Acceleration (1)
- Afterload (1)
- Alginate beads (1)
- Anastomotic leakage (1)
- Autolysis (1)
- Avalanche (1)
- Bank-issued Warrants (1)
- Bio-Sensors (1)
In this paper we present CAESAR, an intelligent domestic service robot. In domestic settings for service robots complex tasks have to be accomplished. Those tasks benefit from deliberation, from robust action execution and from flexible methods for human–robot interaction that account for qualitative notions used in natural language as well as human fallibility. Our robot CAESAR deploys AI techniques on several levels of its system architecture. On the low-level side, system modules for localization or navigation make, for instance, use of path-planning methods, heuristic search, and Bayesian filters. For face recognition and human–machine interaction, random trees and well-known methods from natural language processing are deployed. For deliberation, we use the robot programming and plan language READYLOG, which was developed for the high-level control of agents and robots; it allows combining programming the behaviour using planning to find a course of action. READYLOG is a variant of the robot programming language Golog. We extended READYLOG to be able to cope with qualitative notions of space frequently used by humans, such as “near” and “far”. This facilitates human–robot interaction by bridging the gap between human natural language and the numerical values needed by the robot. Further, we use READYLOG to increase the flexible interpretation of human commands with decision-theoretic planning. We give an overview of the different methods deployed in CAESAR and show the applicability of a system equipped with these AI techniques in domestic service robotics
With its need for high SNR and short acquisition times, Cardiac MRI (CMR) is an intriguing target application for ultrahigh field MRI. Due to the sheer size of the upper torso, however, the known RF issues of 7T MRI are also most prominent in CMR. Recent years brought substantial progress but the full potential of the ultrahigh field for CMR is yet to be exploited. Parallel transmission (pTx) is a promising approach in this context and several groups have already reported B1 shimming for 7T CMR. In such a static pTx application amplitudes and phases of all Tx channels are adjusted individually but otherwise imaging techniques established in current clinical practice 1.5 T and 3 T are applied. More advanced forms of pTx as spatially selective excitation (SSE) using Transmit SENSE promise additional benefits like faster imaging with reduced fields of view or improved SAR control. SSE requires the full dynamic capabilities of pTx, however, and for the majority of today's implemented pTx hardware the internal synchronization of the Tx array does not easily permit external triggering as needed for CMR. Here we report a software solution to this problem and demonstrate the feasibility of CINE CMR at 7 T using a Tx array.
The assessment of the right ventricle (RV) is a challenge in today's cardiology, but of growing clinical impact regarding patient prognosis in different cardiac diseases. The detection and differentiation of small wall motion abnormalities may help to enhance the differentiation of cardiomyopathies including Arrhythmogenic Rightventricular Cardiomyopathy. Cardiovascular magnetic resonance (CMR) at 1.5T is the accepted gold standard for RV quantification. The higher spatial resolution achievable at ultrahigh field strength (UHF) offers the potential to gain new insights into the structure and function of the RV. To approach this goal accurate RV chamber quantification at 7T has to be proven. Consequently this study examines the feasibility of assessment of RV dimensions and function at 7T using improved spatial resolution enabled by the intrinsic sensitivity gain of UHF CMR. For this purpose, a dedicated 16 channel TX/RX RF coil array is used together with 2D CINE fast gradient echo (FGRE) imaging. For comparison RV chamber quantification is conducted at 1.5T using a SSFP based state of the art clinical protocol.
Characterisation of polymeric materials as passivation layer for calorimetric H2O2 gas sensors
(2012)
Calorimetric gas sensors for monitoring the H₂O₂ concentration at elevated temperatures in industrial sterilisation processes have been presented in previous works. These sensors are built up in form of a differential set-up of a catalytically active and passive temperature-sensitive structure. Although, various types of catalytically active dispersions have been studied, the passivation layer has to be established and therefore, chemically as well as physically characterised. In the present work, fluorinated ethylene propylene (FEP), perfluoralkoxy (PFA) and epoxy-based SU-8 photoresist as temperature-stable polymeric materials have been investigated for sensor passivation in terms of their chemical inertness against H₂O₂, their hygroscopic properties as well as their morphology. The polymeric materials were deposited via spin-coating on the temperature-sensitive structure, wherein spin-coated FEP and PFA show slight agglomerates. However, they possess a low absorption of humidity due to their hydrophobic surface, whereas the SU-8 layer has a closed surface but shows a slightly higher absorption of water. All of them were inert against gaseous H₂O₂ during the characterisation in H₂O₂ atmosphere that demonstrates their suitability as passivation layer for calorimetric H₂O₂ gas sensors.
In vitro studies of the degradation kinetic of biopolymers are essential for the design and optimization of implantable biomedical devices. In the presented work, a field-effect capacitive sensor has been applied for the real-time and in situ monitoring of degradation processes of biopolymers for the first time. The polymer-covered field-effect sensor is, in principle, capable to detect any changes in bulk, surface and interface properties of the polymer induced by degradation processes. The feasibility of this approach has been experimentally proven by using the commercially available biomedical polymer poly(D,L-lactic acid) (PDLLA) as a model system. PDLLA films of different thicknesses were deposited on the Ta₂O₅-gate surface of the field-effect structure from a polymer solution by means of spin-coating method. The polymer-modified field-effect sensors have been characterized by means of capacitance–voltage and impedance-spectroscopy method. The degradation of the PDLLA was accelerated by changing the degradation medium from neutral (pH 7.2) to alkaline (pH 9) condition, resulting in drastic changes in the capacitance and impedance spectra of the polymer-modified field-effect sensor.
The chemical imaging sensor is a chemical sensor which is capable of visualizing the spatial distribution of chemical species in sample solution. In this study, a novel measurement system based on the chemical imaging sensor was developed to observe the inside of a Y-shaped microfluidic channel while injecting two sample solutions from two branches. From the collected chemical images, it was clearly observed that the injected solutions formed laminar flows in the microfluidic channel. In addition, ion diffusion across the laminar flows was observed. This label-free method can acquire quantitative data of ion distribution and diffusion in microfluidic devices, which can be used to determine the diffusion coefficients, and therefore, the molecular weights of chemical species in the sample solution.
Real-time and reliable monitoring of the biogas process is crucial for a stable and efficient operation of biogas production in order to avoid digester breakdowns. The concentration of dissolved hydrogen (H₂) represents one of the key parameters for biogas process control. In this work, a one-chip integrated combined amperometric/field-effect sensor for monitoring the dissolved H₂ concentration has been developed for biogas applications. The combination of two different transducer principles might allow a more accurate and reliable measurement of dissolved H₂ as an early warning indicator of digester failures. The feasibility of the approach has been demonstrated by simultaneous amperometric/field-effect measurements of dissolved H₂ concentrations in electrolyte solutions. Both, the amperometric and the field-effect transducer show a linear response behaviour in the H₂ concentration range from 0.1 to 3% (v/v) with a slope of 198.4 ± 13.7 nA/% (v/v) and 14.9 ± 0.5 mV/% (v/v), respectively.