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Glucose oxidase (GOx) is an enzyme frequently used in glucose biosensors. As increased temperatures can enhance the performance of electrochemical sensors, we investigated the impact of temperature pulses on GOx that was drop-coated on flattened Pt microwires. The wires were heated by an alternating current. The sensitivity towards glucose and the temperature stability of GOx was investigated by amperometry. An up to 22-fold increase of sensitivity was observed. Spatially resolved enzyme activity changes were investigated via scanning electrochemical microscopy. The application of short (<100 ms) heat pulses was associated with less thermal inactivation of the immobilized GOx than long-term heating.
Animal experiments and preliminary results in humans have indicated alterations of hippocampal muscarinic acetylcholine receptors (mAChR) in temporal lobe epilepsy. Patients with temporal lobe epilepsy often present with a reduction in hippocampal volume. The aim of this study was to investigate the influence of hippocampal atrophy on the quantification of mAChR with single photon emission tomography (SPET) in patients with temporal lobe epilepsy. Cerebral uptake of the muscarinic cholinergic antagonist [123I]4-iododexetimide (IDex) was investigated by SPET in patients suffering from temporal lobe epilepsy of unilateral (n=6) or predominantly unilateral (n=1) onset. Regions of interest were drawn on co-registered magnetic resonance images. Hippocampal volume was determined in these regions and was used to correct the SPET results for partial volume effects. A ratio of hippocampal IDex binding on the affected side to that on the unaffected side was used to detect changes in muscarinic cholinergic receptor density. Before partial volume correction a decrease in hippocampal IDex binding on the focus side was found in each patient. After partial volume no convincing differences remained. Our results indicate that the reduction in hippocampal IDex binding in patients with epilepsy is due to a decrease in hippocampal volume rather than to a decrease in receptor concentration.
Single-photon emission tomography (SPET) with the amino acid analogue l-3-[123I]iodo-α-methyl tyrosine (IMT) is helpful in the diagnosis and monitoring of cerebral gliomas. Radiolabelled amino acids seem to reflect tumour infiltration more specifically than conventional methods like magnetic resonance imaging and computed tomography. Automatic tumour delineation based on maximal tumour uptake may cause an overestimation of mean tumour uptake and an underestimation of tumour extension in tumours with circumscribed peaks. The aim of this study was to develop a program for tumour delineation and calculation of mean tumour uptake which takes into account the mean background activity and is thus optimised to the problem of tumour definition in IMT SPET. Using the frequency distribution of pixel intensities of the tomograms a program was developed which automatically detects a reference brain region and draws an isocontour region around the tumour taking into account mean brain radioactivity. Tumour area and tumour/brain ratios were calculated. A three-compartment phantom was simulated to test the program. The program was applied to IMT SPET studies of 20 patients with cerebral gliomas and was compared to the results of manual analysis by three different investigators. Activity ratios and chamber extension of the phantom were correctly calculated by the automatic analysis. A method based on image maxima alone failed to determine chamber extension correctly. Manual region of interest analysis in patient studies resulted in a mean inter-observer standard deviation of 8.7%±6.1% (range 2.7%–25.0%). The mean value of the results of the manual analysis showed a significant correlation to the results of the automatic analysis (r = 0.91, P<0.0001 for the uptake ratio; r = 0.87, P<0.0001 for the tumour area). We conclude that the algorithm proposed simplifies the calculation of uptake ratios and may be used for observer-independent evaluation of IMT SPET studies. Three-dimensional tumour recognition and transfer to co-registered morphological images based on this program may be useful for the planning of surgical and radiation treatment.
The quest for life on other planets is closely connected with the search for water in liquid state. Recent discoveries of deep oceans on icy moons like Europa and Enceladus have spurred an intensive discussion about how these waters can be accessed. The challenge of this endeavor lies in the unforeseeable requirements on instrumental characteristics both with respect to the scientific and technical methods. The TRIPLE/nanoAUV initiative is aiming at developing a mission concept for exploring exo-oceans and demonstrating the achievements in an earth-analogue context, exploring the ocean under the ice shield of Antarctica and lakes like Dome-C on the Antarctic continent.
Organization and management of German-Russian joint ventures. Bock, Jürgen; Thielemann, Frank
(1994)
Comparison of solar hot water systems in solar settlements - decentralized or centralized systems?
(2004)
Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents.
In the context of the increasing digitalization, the Internet of Things (IoT) is seen as a technological driver through which completely new business models can emerge in the interaction of different players. Identified key players include traditional industrial companies, municipalities and telecommunications companies. The latter, by providing connectivity, ensure that small devices with tiny batteries can be connected almost anywhere and directly to the Internet. There are already many IoT use cases on the market that provide simplification for end users, such as Philips Hue Tap. In addition to business models based on connectivity, there is great potential for information-driven business models that can support or enhance existing business models. One example is the IoT use case Park and Joy, which uses sensors to connect parking spaces and inform drivers about available parking spaces in real time. Information-driven business models can be based on data generated in IoT use cases. For example, a telecommunications company can add value by deriving more decision-relevant information – called insights – from data that is used to increase decision agility. In addition, insights can be monetized. The monetization of insights can only be sustainable, if careful attention is taken and frameworks are considered. In this chapter, the concept of information-driven business models is explained and illustrated with the concrete use case Park and Joy. In addition, the benefits, risks and framework conditions are discussed.
As researchers continue to seek the expansion of the material base for additive manufacturing, there is a need to focus attention on the Ni–Cu group of alloys which conventionally has wide industrial applications. In this work, the G-NiCu30Nb casting alloy, a variant of the Monel family of alloys with Nb and high Si content is, for the first time, processed via the laser powder bed fusion process (LPBF). Being novel to the LPBF processes, optimum LPBF parameters were determined, and hardness and tensile tests were performed in as-built conditions and after heat treatment at 1000 °C. Microstructures of the as-cast and the as-built condition were compared. Highly dense samples (99.8% density) were achieved after varying hatch distance (80 µm and 140 µm) with scanning speed (550 mm/s–1500 mm/s). There was no significant difference in microhardness between varied hatch distance print sets. Microhardness of the as-built condition (247 HV0.2) exceeded the as-cast microhardness (179 HV0.2.). Tensile specimens built in vertical (V) and horizontal (H) orientations revealed degrees of anisotropy and were superior to conventionally reported figures. Post heat treatment increased ductility from 20% to 31% (V), as well as from 16% to 25% (H), while ultimate tensile strength (UTS) and yield strength (YS) were considerably reduced.
An interdisciplinary view on humane interfaces for digital shadows in the internet of production
(2022)
Digital shadows play a central role for the next generation industrial internet, also known as Internet of Production (IoP). However, prior research has not considered systematically how human actors interact with digital shadows, shaping their potential for success. To address this research gap, we assembled an interdisciplinary team of authors from diverse areas of human-centered research to propose and discuss design and research recommendations for the implementation of industrial user interfaces for digital shadows, as they are currently conceptualized for the IoP. Based on the four use cases of decision support systems, knowledge sharing in global production networks, human-robot collaboration, and monitoring employee workload, we derive recommendations for interface design and enhancing workers’ capabilities. This analysis is extended by introducing requirements from the higher-level perspectives of governance and organization.
This work presents a methodology for automated
damage-sensitive feature extraction and anomaly
detection under multivariate operational variability
for in-flight assessment of wings. The
method uses a passive excitation approach, i. e.
without the need for artificial actuation. The
modal system properties (natural frequencies and
damping ratios) are used as damage-sensitive
features. Special emphasis is placed on the use
of Fiber Bragg Grating (FBG) sensing technology
and the consideration of Operational and
Environmental Variability (OEV). Measurements
from a wind tunnel investigation with a composite
cantilever equipped with FBG and piezoelectric
sensors are used to successfully detect an impact
damage. In addition, the feasibility of damage
localisation and severity estimation is evaluated
based on the coupling found between damageand
OEV-induced feature changes.
Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions.