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Spontaneous language has rarely been subjected to neuroimaging studies. This study therefore introduces a newly developed method for the analysis of linguistic phenomena observed in continuous language production during fMRI.
Most neuroimaging studies investigating language have so far focussed on single word or — to a smaller extent — sentence processing, mostly due to methodological considerations. Natural language production, however, is far more than the mere combination of words to larger units. Therefore, the present study aimed at relating brain activation to linguistic phenomena like word-finding difficulties or syntactic completeness in a continuous language fMRI paradigm. A picture description task with special constraints was used to provoke hesitation phenomena and speech errors. The transcribed speech sample was segmented into events of one second and each event was assigned to one category of a complex schema especially developed for this purpose. The main results were: conceptual planning engages bilateral activation of the precuneus. Successful lexical retrieval is accompanied – particularly in comparison to unsolved word-finding difficulties – by the left middle and superior temporal gyrus. Syntactic completeness is reflected in activation of the left inferior frontal gyrus (IFG) (area 44). In sum, the method has proven to be useful for investigating the neural correlates of lexical and syntactic phenomena in an overt picture description task. This opens up new prospects for the analysis of spontaneous language production during fMRI.
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.
In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.
Purpose
To demonstrate that high quality T₂-weighted (T2w) turbo spin-echo (TSE) imaging of the complete prostate can be achieved routinely and within safety limits at 7 T, using an external transceive body array coil only.
Methods
Nine healthy volunteers and 12 prostate cancer patients were scanned on a 7 T whole-body system. Preparation consisted of B₀ and radiofrequency shimming and localized flip angle calibration. T₁ and T₂ relaxation times were measured and used to define the T2w-TSE protocol. T2w imaging was performed using a TSE sequence (pulse repetition time/echo time 3000–3640/71 ms) with prolonged excitation and refocusing pulses to reduce specific absorption rate.
Results
High quality T2w TSE imaging was performed in less than 2 min in all subjects. Tumors of patients with gold-standard tumor localization (MR-guided biopsy or prostatectomy) were well visualized on 7 T imaging (n = 3). The number of consecutive slices achievable within a 10-g averaged specific absorption rate limit of 10 W/kg was ≥28 in all subjects, sufficient for full prostate coverage with 3-mm slices in at least one direction.
Conclusion
High quality T2w TSE prostate imaging can be performed routinely and within specific absorption rate limits at 7 T with an external transceive body array.
Purpose
To assess potential cognitive deficits under the influence of static magnetic fields at various field strengths some studies already exist. These studies were not focused on attention as the most vulnerable cognitive function. Additionally, mostly no magnetic resonance imaging (MRI) sequences were performed.
Materials and Methods
In all, 25 right-handed men were enrolled in this study. All subjects underwent one MRI examination of 63 minutes at 1.5 T and one at 7 T within an interval of 10 to 30 days. The order of the examinations was randomized. Subjects were referred to six standardized neuropsychological tests strictly focused on attention immediately before and after each MRI examination. Differences in neuropsychological variables between the timepoints before and after each MRI examination were assessed and P-values were calculated
Results
Only six subtests revealed significant differences between pre- and post-MRI. In these tests the subjects achieved better results in post-MRI testing than in pre-MRI testing (P = 0.013–0.032). The other tests revealed no significant results.
Conclusion
The improvement in post-MRI testing is only explicable as a result of learning effects. MRI examinations, even in ultrahigh-field scanners, do not seem to have any persisting influence on the attention networks of human cognition immediately after exposure.
Planning the layout and operation of a technical system is a common task
for an engineer. Typically, the workflow is divided into consecutive stages: First,
the engineer designs the layout of the system, with the help of his experience or of
heuristic methods. Secondly, he finds a control strategy which is often optimized
by simulation. This usually results in a good operating of an unquestioned sys-
tem topology. In contrast, we apply Operations Research (OR) methods to find a
cost-optimal solution for both stages simultaneously via mixed integer program-
ming (MILP). Technical Operations Research (TOR) allows one to find a provable
global optimal solution within the model formulation. However, the modeling error
due to the abstraction of physical reality remains unknown. We address this ubiq-
uitous problem of OR methods by comparing our computational results with mea-
surements in a test rig. For a practical test case we compute a topology and control
strategy via MILP and verify that the objectives are met up to a deviation of 8.7%.
The conference center darmstadtium in Darmstadt is a prominent example of energy efficient buildings. Its heating system consists of different source and consumer circuits connected by a Zortström reservoir. Our goal was to reduce the energy costs of the system as much as possible. Therefore, we analyzed its supply circuits. The first step towards optimization is a complete examination of the system: 1) Compilation of an object list for the system, 2) collection of the characteristic curves of the components, and 3) measurement of the load profiles of the heat and volume-flow demand. Instead of modifying the system manually and testing the solution by simulation, the second step was the creation of a global optimization program. The objective was to minimize the total energy costs for one year. We compare two different topologies and show opportunities for significant savings.
Ground or aerial robots equipped with advanced sensing technologies, such as three-dimensional laser scanners and advanced mapping algorithms, are deemed useful as a supporting technology for first responders. A great deal of excellent research in the field exists, but practical applications at real disaster sites are scarce. Many projects concentrate on equipping robots with advanced capabilities, such as autonomous exploration or object manipulation. In spite of this, realistic application areas for such robots are limited to teleoperated reconnaissance or search. In this paper, we investigate how well state-of-the-art and off-the-shelf components and algorithms are suited for reconnaissance in current disaster-relief scenarios. The basic idea is to make use of some of the most common sensors and deploy some widely used algorithms in a disaster situation, and to evaluate how well the components work for these scenarios. We acquired the sensor data from two field experiments, one from a disaster-relief operation in a motorway tunnel, and one from a mapping experiment in a partly closed down motorway tunnel. Based on these data, which we make publicly available, we evaluate state-of-the-art and off-the-shelf mapping approaches. In our analysis, we integrate opinions and replies from first responders as well as from some algorithm developers on the usefulness of the data and the limitations of the deployed approaches, respectively. We discuss the lessons we learned during the two missions. These lessons are interesting for the community working in similar areas of urban search and rescue, particularly reconnaissance and search.
Mechatronics consist of the integration of mechanical
engineering, electronic integration and computer science/
engineering. These broad fields are essential for robotic
systems, yet it makes it difficult for the researchers to specialize
and be experts in all these fields. Collaboration between
researchers allow for the integration of experience and specialization,
to allow optimized systems. Collaboration between the
European countries and South Africa is critical, as each country
has different resources available, which the other countries
might not have. Applications with the need for approval of
any restrictions, can also be obtained easier in some countries
compared to others, thus preventing the delays of research.
Some problems that have been experienced are discussed, with
the Robotics Center of South Africa as a possible solution.
Because of customer churn, strong competition, and operational inefficiencies, the telecommunications operator ME Telco (fictitious name due to confidentiality) launched a strategic transformation program that included a Business Process Management (BPM) project. Major problems were silo-oriented process management and missing cross-functional transparency. Process improvements were not consistently planned and aligned with corporate targets. Measurable inefficiencies were observed on an operational level, e.g., high lead times and reassignment rates of the incident management process.
In this work, we report on our attempt to design and implement an early introduction to basic robotics principles for children at kindergarten age. One of the main challenges of this effort is to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. The humanoid robot Pepper from Softbank, which is a great platform for human–robot interaction experiments, was used to present a lecture on robotics by reading out the contents to the children making use of its speech synthesis capability. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. In this quiz, two LEGO Mindstorm EV3 robots were used to implement a strongly interactive scenario. Besides the thrill of being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. We got very positive feedback from the children as well as from their educators. To the best of our knowledge, this is one of only few attempts to use a robot like Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents.
Enhanced system architecture for rugged wide band data transmission / Sadeghfam, A. ; Heuermann, H.
(2009)
The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design.
This article describes an Internet of things (IoT) sensing device with a wireless interface which is powered by the energy-harvesting method of the Wiegand effect. The Wiegand effect, in contrast to continuous sources like photovoltaic or thermal harvesters, provides small amounts of energy discontinuously in pulsed mode. To enable an energy-self-sufficient operation of the sensing device with this pulsed energy source, the output energy of the Wiegand generator is maximized. This energy is used to power up the system and to acquire and process data like position, temperature or other resistively measurable quantities as well as transmit these data via an ultra-low-power ultra-wideband (UWB) data transmitter. A proof-of-concept system was built to prove the feasibility of the approach. The energy consumption of the system during start-up was analysed, traced back in detail to the individual components, compared to the generated energy and processed to identify further optimization options. Based on the proof of concept, an application prototype was developed.
Energieeffizienz und Energiemanagement : ein Überblick heutiger Möglichkeiten und Notwendigkeiten
(2012)
Due to the high number of customer contacts, fault clearances, installations, and product provisioning per year, the automation level of operational processes has a significant impact on financial results, quality, and customer experience. Therefore, the telecommunications operator Deutsche Telekom (DT) has defined a digital strategy with the objectives of zero complexity and zero complaint, one touch, agility in service, and disruptive thinking. In this context, Robotic Process Automation (RPA) was identified as an enabling technology to formulate and realize DT’s digital strategy through automation of rule-based, routine, and predictable tasks in combination with structured and stable data.
Subject of this case is Deutsche Telekom Services Europe (DTSE), a service center for administrative processes. Due to the high volume of repetitive tasks (e.g., 100k manual uploads of offer documents into SAP per year), automation was identified as an important strategic target with a high management attention and commitment. DTSE has to work with various backend application systems without any possibility to change those systems. Furthermore, the complexity of administrative processes differed. When it comes to the transfer of unstructured data (e.g., offer documents) to structured data (e.g., MS Excel files), further cognitive technologies were needed.
Embedding fuzzy controllers in golog / Ferrein, Alexander ; Schiffer, Stefan ; Lakemeyer, Gerhard
(2009)
Use of textile structures for reinforcement of pelvic floor structures has to consider mechanical forces to the implant, which are quite different to the tension free conditions of the abdominal wall. Thus, biomechanical analysis of textile devices has to include the impact of strain on stretchability and effective porosity. Prolift® and Prolift + M®, developed for tension free conditions, were tested by measuring stretchability and effective porosity applying mechanical strain. For comparison, we used Dynamesh-PR4®, which was designed for pelvic floor repair to withstand mechanical strain. Prolift® at rest showed moderate porosity with little stretchability but complete loss of effective porosity at strain of 4.9 N/cm. Prolift + M® revealed an increased porosity at rest, but at strain showed high stretchability, with subsequent loss of effective porosity at strain of 2.5 N/cm. Dynamesh PR4® preserved its high porosity even under strain, but as consequence of limited stretchability. Though in tension free conditions Prolift® and Prolift + M® can be considered as large pore class I meshes, application of mechanical strain rapidly lead to collapse of pores. The loss of porosity at mechanical stress can be prevented by constructions with high structural stability. Assessment of porosity under strain was found helpful to define requirements for pelvic floor devices. Clinical studies have to prove whether devices with high porosity as well as high structural stability can improve the patients' outcome.
Harmful effects of electromagnetic fields (EMF) on cognitive and behavioural features of humans and rodents have been controversially discussed and raised persistent concern about adverse effects of EMF on general brain functions. In the present study we applied radio-frequency (RF) signals of the Universal Mobile Telecommunications System (UMTS) to full brain exposed male Wistar rats in order to elaborate putative influences on stress hormone release (corticosteron; CORT and adrenocorticotropic hormone; ACTH) and on hippocampal derived synaptic long-term plasticity (LTP) and depression (LTD) as electrophysiological hallmarks for memory storage and memory consolidation. Exposure was computer controlled providing blind conditions. Nominal brain-averaged specific absorption rates (SAR) as a measure of applied mass-related dissipated RF power were 0, 2, and 10 W/kg over a period of 120 min. Comparison of cage exposed animals revealed, regardless of EMF exposure, significantly increased CORT and ACTH levels which corresponded with generally decreased field potential slopes and amplitudes in hippocampal LTP and LTD. Animals following SAR exposure of 2 W/kg (averaged over the whole brain of 2.3 g tissue mass) did not differ from the sham-exposed group in LTP and LTD experiments. In contrast, a significant reduction in LTP and LTD was observed at the high power rate of SAR (10 W/kg). The results demonstrate that a rate of 2 W/kg displays no adverse impact on LTP and LTD, while 10 W/kg leads to significant effects on the electrophysiological parameters, which can be clearly distinguished from the stress derived background. Our findings suggest that UMTS exposure with SAR in the range of 2 W/kg is not harmful to critical markers for memory storage and memory consolidation, however, an influence of UMTS at high energy absorption rates (10 W/kg) cannot be excluded.
Ga-doped Li7La3Zr2O12 garnet solid electrolytes exhibit the highest Li-ion conductivities among the oxide-type garnet-structured solid electrolytes, but instabilities toward Li metal hamper their practical application. The instabilities have been assigned to direct chemical reactions between LiGaO2 coexisting phases and Li metal by several groups previously. Yet, the understanding of the role of LiGaO2 in the electrochemical cell and its electrochemical properties is still lacking. Here, we are investigating the electrochemical properties of LiGaO2 through electrochemical tests in galvanostatic cells versus Li metal and complementary ex situ studies via confocal Raman microscopy, quantitative phase analysis based on powder X-ray diffraction, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and electron energy loss spectroscopy. The results demonstrate considerable and surprising electrochemical activity, with high reversibility. A three-stage reaction mechanism is derived, including reversible electrochemical reactions that lead to the formation of highly electronically conducting products. The results have considerable implications for the use of Ga-doped Li7La3Zr2O12 electrolytes in all-solid-state Li-metal battery applications and raise the need for advanced materials engineering to realize Ga-doped Li7La3Zr2O12for practical use.
Clinical assessment of newly developed sensors is important for ensuring their validity. Comparing recordings of emerging electrocardiography (ECG) systems to a reference ECG system requires accurate synchronization of data from both devices. Current methods can be inefficient and prone to errors. To address this issue, three algorithms are presented to synchronize two ECG time series from different recording systems: Binned R-peak Correlation, R-R Interval Correlation, and Average R-peak Distance. These algorithms reduce ECG data to their cyclic features, mitigating inefficiencies and minimizing discrepancies between different recording systems. We evaluate the performance of these algorithms using high-quality data and then assess their robustness after manipulating the R-peaks. Our results show that R-R Interval Correlation was the most efficient, whereas the Average R-peak Distance and Binned R-peak Correlation were more robust against noisy data.
The telecommunications industry is currently going through a major transformation. In this context, the enhanced Telecom Operations Map (eTOM) is a domain-specific process reference model that is offered by the industry organization TM Forum. In practice, eTOM is well accepted and confirmed as de facto standard. It provides process definitions and process flows on different levels of detail. This article discusses the reference modeling of eTOM, i.e., the design, the resulting artifact, and its evaluation based on three project cases. The application of eTOM in three projects illustrates the design approach and concrete models on strategic and operational levels. The article follows the Design Science Research (DSR) paradigm. It contributes with concrete design artifacts to the transformational needs of the telecommunications industry and offers lessons-learned from a general DSR perspective.
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.
Digital forensics of smartphones is of utmost importance in many criminal cases. As modern smartphones store chats, photos, videos etc. that can be relevant for investigations and as they can have storage capacities of hundreds of gigabytes, they are a primary target for forensic investigators. However, it is exactly this large amount of data that is causing problems: extracting and examining the data from multiple phones seized in the context of a case is taking more and more time. This bears the risk of wasting a lot of time with irrelevant phones while there is not enough time left to analyze a phone which is worth examination. Forensic triage can help in this case: Such a triage is a preselection step based on a subset of data and is performed before fully extracting all the data from the smartphone. Triage can accelerate subsequent investigations and is especially useful in cases where time is essential. The aim of this paper is to determine which and how much data from an Android smartphone can be made directly accessible to the forensic investigator – without tedious investigations. For this purpose, an app has been developed that can be used with extremely limited storage of data in the handset and which outputs the extracted data immediately to the forensic workstation in a human- and machine-readable format.
Dielectric Properties of Polyolefins Stressed by High Electrical Fields. Fruth, B. ; Krause, G.
(1987)
Dielectric Properties of Polyolefins Stressed by High Electrical Fields / Fruth, B. ; Krause, G.
(1988)
The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example
system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient
system behaviour.
In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant.
Development of a subject-oriented reference process model for the telecommunications industry
(2016)
Generally the usage of reference models can be structured top-down or bottom-up. The practical need of agile change and flexible organizational implementation requires a consistent mapping to an operational level. In this context, well-established reference process models are typically structured top-down. The subject-oriented Business Process Management (sBPM) offers a modeling concept that is structured bottom-up and concentrates on the process actors on an
operational level. This paper applies sBPM to the enhanced Telecom Operations Map (eTOM), a well-accepted reference process model in the telecommunications industry. The resulting design artifact is a concrete example for a combination of a bottom-up and top-down developed reference model. The results are evaluated and confirmed in practical context through the involvement of the industry body TMForum.
Objective
The purpose of this study is to (i) design a small and mobile Magnetic field ALert SEnsor (MALSE), (ii) to carefully evaluate its sensors to their consistency of activation/deactivation and sensitivity to magnetic fields, and (iii) to demonstrate the applicability of MALSE in 1.5 T, 3.0 T and 7.0 T MR fringe field environments.
Methods
MALSE comprises a set of reed sensors, which activate in response to their exposure to a magnetic field. The activation/deactivation of reed sensors was examined by moving them in/out of the fringe field generated by 7TMR.
Results
The consistency with which individual reed sensors would activate at the same field strength was found to be 100% for the setup used. All of the reed switches investigated required a substantial drop in ambient magnetic field strength before they deactivated.
Conclusions
MALSE is a simple concept for alerting MRI staff to a ferromagnetic object being brought into fringe magnetic fields which exceeds MALSEs activation magnetic field. MALSE can easily be attached to ferromagnetic objects within the vicinity of a scanner, thus creating a barrier for hazardous situations induced by ferromagnetic parts which should not enter the vicinity of an MR-system to occur.
Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis.
A novel method to determine the extruded length of a metallic wire for a directed energy deposition (DED) process using a microwave (MW) plasma jet with a straight-through wire feed is presented. The method is based on the relative comparison of the measured frequency response obtained by the large-signal scattering parameter (Hot-S) technique. In the practical working range, repeatability of less than 6% for a nonactive plasma and 9% for the active plasma state is found. Measurements are conducted with a focus on a simple solution to decrease the processing time and reduce the integration time of the process into the existing hardware. It is shown that monitoring a single frequency for magnitude and phase changes is sufficient to achieve good accuracy. A combination of different measurement values to determine the length is possible. The applicability to different diameter of the same material is shown as well as a contact detection of the wire and metallic substrate.
Purpose:
To investigate the feasibility of using magnetohydrodynamic (MHD) effects for synchronization of magnetic resonance imaging (MRI) with the cardiac cycle.
Materials and Methods:
The MHD effect was scrutinized using a pulsatile flow phantom at B0 = 7.0 T. MHD effects were examined in vivo in healthy volunteers (n = 10) for B0 ranging from 0.05–7.0 T. Noncontrast-enhanced MR angiography (MRA) of the carotids was performed using a gated steady-state free-precession (SSFP) imaging technique in conjunction with electrocardiogram (ECG) and MHD synchronization.
Results:
The MHD potential correlates with flow velocities derived from phase contrast MRI. MHD voltages depend on the orientation between B0 and the flow of a conductive fluid. An increase in the interelectrode spacing along the flow increases the MHD potential. In vivo measurement of the MHD effect provides peak voltages of 1.5 mV for surface areas close to the common carotid artery at B0 = 7.0 T. Synchronization of MRI with the cardiac cycle using MHD triggering is feasible. MHD triggered MRA of the carotids at 3.0 T showed an overall image quality and richness of anatomic detail, which is comparable to ECG-triggered MRAs.
Conclusion:
This feasibility study demonstrates the use of MHD effects for synchronization of MR acquisitions with the cardiac cycle. J. Magn. Reson. Imaging 2012;36:364–372. © 2012 Wiley Periodicals, Inc.