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4CH TX/RX Surface Coil for 7T: Design, Optimization and Application for Cardiac Function Imaging
(2010)
Practical impediments of ultra high field cardiovascular MR (CVMR) can be catalogued in exacerbated magnetic field and radio frequency (RF) inhomogeneities, susceptibility and off-resonance effects, conductive and dielectric effects in tissue, and RF power deposition constraints, which all bear the potential to spoil the benefit of CVMR at 7T. Therefore, a four element cardiac transceive surface coil array was developed. Cardiac imaging provided clinically acceptable signal homogeneity with an excellent blood myocardium contrast. Subtle anatomic structures, such as pericardium, mitral and tricuspid valves and their apparatus, papillary muscles, and trabecles were accurately delineated.
A High-Throughput Functional Complementation Assay for Classification of BRCA1 Missense Variants
(2013)
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.
With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.
Lifting propellers are of increasing interest for Advanced Air Mobility. All propellers and rotors are initially twisted beams, showing significant extension–twist coupling and centrifugal twisting. Torsional deformations severely impact aerodynamic performance. This paper presents a novel approach to assess different reasons for torsional deformations. A reduced-order model runs large parameter sweeps with algebraic formulations and numerical solution procedures. Generic beams represent three different propeller types for General Aviation, Commercial Aviation, and Advanced Air Mobility. Simulations include solid and hollow cross-sections made of aluminum, steel, and carbon fiber-reinforced polymer. The investigation shows that centrifugal twisting moments depend on both the elastic and initial twist. The determination of the centrifugal twisting moment solely based on the initial twist suffers from errors exceeding 5% in some cases. The nonlinear parts of the torsional rigidity do not significantly impact the overall torsional rigidity for the investigated propeller types. The extension–twist coupling related to the initial and elastic twist in combination with tension forces significantly impacts the net cross-sectional torsional loads. While the increase in torsional stiffness due to initial twist contributes to the overall stiffness for General and Commercial Aviation propellers, its contribution to the lift propeller’s stiffness is limited. The paper closes with the presentation of approximations for each effect identified as significant. Numerical evaluations are necessary to determine each effect for inhomogeneous cross-sections made of anisotropic material.
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.
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.
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.
This paper compares several blade element theory (BET) method-based propeller simulation tools, including an evaluation against static propeller ground tests and high-fidelity Reynolds-Average Navier Stokes (RANS) simulations. Two proprietary propeller geometries for paraglider applications are analysed in static and flight conditions. The RANS simulations are validated with the static test data and used as a reference for comparing the BET in flight conditions. The comparison includes the analysis of varying 2D aerodynamic airfoil parameters and different induced velocity calculation methods. The evaluation of the BET propeller simulation tools shows the strength of the BET tools compared to RANS simulations. The RANS simulations underpredict static experimental data within 10% relative error, while appropriate BET tools overpredict the RANS results by 15–20% relative error. A variation in 2D aerodynamic data depicts the need for highly accurate 2D data for accurate BET results. The nonlinear BET coupled with XFOIL for the 2D aerodynamic data matches best with RANS in static operation and flight conditions. The novel BET tool PropCODE combines both approaches and offers further correction models for highly accurate static and flight condition results.
Comparison of solar hot water systems in solar settlements - decentralized or centralized systems?
(2004)
Research on robotic lunar exploration has seen a broad revival, especially since the Google Lunar X-Prize increasingly brought private endeavors into play. This development is supported by national agencies with the aim of enabling long-term lunar infrastructure for in-situ operations and the establishment of a moon village. One challenge for effective exploration missions is developing a compact and lightweight robotic rover to reduce launch costs and open the possibility for secondary payload options. Existing micro rovers for exploration missions are clearly limited by their design for one day of sunlight and their low level of autonomy. For expanding the potential mission applications and range of use, an extension of lifetime could be reached by surviving the lunar night and providing a higher level of autonomy. To address this objective, the paper presents a system design concept for a lightweight micro rover with long-term mission duration capabilities, derived from a multi-day lunar mission scenario at equatorial regions. Technical solution approaches are described, analyzed, and evaluated, with emphasis put on the harmonization of hardware selection due to a strictly limited budget in dimensions and power.
In the paper a lightning protection design concept for renewable energy hybrid-systems without power mains connection is described. Based on a risk analysis protection measures against direct strikes and overvoltages are shown in an overview. The design concept is realized exemplarily for the hybrid-system VATALI on the Greek island Crete. VATALI, not lightning protected at that time, was a victim of a lightning strike in the year 2000 causing destructions and damages of some mechanical and electrical components with costs of approx. 60.000 €. The hardware costs for the protection measures were about 15.000 €: about 50% of the costs are due to protection measures against direct strikes, 50% are due to overvoltage protection.
Purpose
To design and evaluate a four-channel cardiac transceiver coil array for functional cardiac imaging at 7T.
Materials and Methods
A four-element cardiac transceiver surface coil array was developed with two rectangular loops mounted on an anterior former and two rectangular loops on a posterior former. specific absorption rate (SAR) simulations were performed and a Burn:x-wiley:10531807:media:JMRI22451:tex2gif-stack-1 calibration method was applied prior to obtain 2D FLASH CINE (mSENSE, R = 2) images from nine healthy volunteers with a spatial resolution of up to 1 × 1 × 2.5 mm3.
Results
Tuning and matching was found to be better than 10 dB for all subjects. The decoupling (S21) was measured to be >18 dB between neighboring loops, >20 dB for opposite loops, and >30 dB for other loop combinations. SAR values were well within the limits provided by the IEC. Imaging provided clinically acceptable signal homogeneity with an excellent blood-myocardium contrast applying the Burn:x-wiley:10531807:media:JMRI22451:tex2gif-stack-2 calibration approach.
Conclusion
A four-channel cardiac transceiver coil array for 7T was built, allowing for cardiac imaging with clinically acceptable signal homogeneity and an excellent blood-myocardium contrast. Minor anatomic structures, such as pericardium, mitral, and tricuspid valves and their apparatus, as well as trabeculae, were accurately delineated.
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.
Information technologies, such as big data analytics, cloud computing,
cyber physical systems, robotic process automation, and the internet of things, provide a sustainable impetus for the structural development of business sectors as well as the digitalization of markets, enterprises, and processes. Within the consulting industry, the proliferation of these technologies opened up the new segment of digital transformation, which focuses on setting up, controlling, and implementing projects for enterprises from a broad range of sectors. These recent developments raise the question, which requirements evolve for IT consultants as important success factors of those digital transformation projects. Therefore, this empirical contribution provides indications regarding the qualifications and competences necessary for IT consultants in the era of digital transformation from a labor market perspective. On the one hand, this knowledge base is interesting for the academic education of consultants, since it supports a market-oriented design of adequate training measures. On the other hand, insights into the competence requirements for consultants are considered relevant for skill and talent management processes in consulting practice. Assuming that consulting companies pursue a strategic human resource management approach, labor market information may also be useful to discover strategic behavioral patterns.
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.
The benefits of robotic process automation (RPA) are highly related to the usage of commercial off-the-shelf (COTS) software products that can be easily implemented and customized by business units. But, how to find the best fitting RPA product for a specific situation that creates the expected benefits? This question is related to the general area of software evaluation and selection. In the face of more than 75 RPA products currently on the market, guidance considering those specifics is required. Therefore, this chapter proposes a criteria-based selection method specifically for RPA. The method includes a quantitative evaluation of costs and benefits as well as a qualitative utility analysis based on functional criteria. By using the visualization of financial implications (VOFI) method, an application-oriented structure is provided that opposes the total cost of ownership to the time savings times salary (TSTS). For the utility analysis a detailed list of functional criteria for RPA is offered. The whole method is based on a multi-vocal review of scientific and non-scholarly literature including publications by business practitioners, consultants, and vendors. The application of the method is illustrated by a concrete RPA example. The illustrated
structures, templates, and criteria can be directly utilized by practitioners in their real-life RPA implementations. In addition, a normative decision process for selecting RPA alternatives is proposed before the chapter closes with a discussion and outlook.
Digital Shadows as the aggregation, linkage and abstraction of data relating to physical objects are a central vision for the future of production. However, the majority of current research takes a technocentric approach, in which the human actors in production play a minor role. Here, the authors present an alternative anthropocentric perspective that highlights the potential and main challenges of extending the concept of Digital Shadows to humans. Following future research methodology, three prospections that illustrate use cases for Human Digital Shadows across organizational and hierarchical levels are developed: human-robot collaboration for manual work, decision support and work organization, as well as human resource management. Potentials and challenges are identified using separate SWOT analyses for the three prospections and common themes are emphasized in a concluding discussion.
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through the presentation layer of existing application systems. For this simple emulation of user input and output by software robots, no changes of the systems and architecture is required. However, considering strategic aspects of aligning business and technology on an enterprise level as well as the growing capabilities of RPA driven by artificial intelligence, interrelations between RPA and Enterprise Architecture (EA) become visible and pose new questions. In this paper we discuss the relationship between RPA and EA in terms of perspectives and implications. As workin- progress we focus on identifying new questions and research opportunities related to RPA and EA.
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.
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.
Inkompressible Strömungen
(2012)
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.
In this chapter, the key technologies and the instrumentation required for the subsurface exploration of ocean worlds are discussed. The focus is laid on Jupiter’s moon Europa and Saturn’s moon Enceladus because they have the highest potential for such missions in the near future. The exploration of their oceans requires landing on the surface, penetrating the thick ice shell with an ice-penetrating probe, and probably diving with an underwater vehicle through dozens of kilometers of water to the ocean floor, to have the chance to find life, if it exists. Technologically, such missions are extremely challenging. The required key technologies include power generation, communications, pressure resistance, radiation hardness, corrosion protection, navigation, miniaturization, autonomy, and sterilization and cleaning. Simpler mission concepts involve impactors and penetrators or – in the case of Enceladus – plume-fly-through missions.