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Orthodontic treatments are concomitant with mechanical forces and thereby cause teeth movements. The applied forces are transmitted to the tooth root and the periodontal ligaments which is compressed on one side and tensed up on the other side. Indeed, strong forces can lead to tooth root resorption and the crown-to-tooth ratio is reduced with the potential for significant clinical impact. The cementum, which covers the tooth root, is a thin mineralized tissue of the periodontium that connects the periodontal ligament with the tooth and is build up by cementoblasts. The impact of tension and compression on these cells is investigated in several in vivo and in vitro studies demonstrating differences in protein expression and signaling pathways. In summary, osteogenic marker changes indicate that cyclic tensile forces support whereas static tension inhibits cementogenesis. Furthermore, cementogenesis experiences the same protein expression changes in static conditions as static tension, but cyclic compression leads to the exact opposite of cyclic tension. Consistent with marker expression changes, the singaling pathways of Wnt/ß-catenin and RANKL/OPG show that tissue compression leads to cementum degradation and tension forces to cementogenesis. However, the cementum, and in particular its cementoblasts, remain a research area which should be explored in more detail to understand the underlying mechanism of bone resorption and remodeling after orthodontic treatments.
Additive Manufacturing (AM) of metallic workpieces faces a continuously rising technological relevance and market size. Producing complex or highly strained unique workpieces is a significant field of application, making AM highly relevant for tool components. Its successful economic application requires systematic workpiece based decisions and optimizations. Considering geometric and technological requirements as well as the necessary post-processing makes deciding effortful and requires in-depth knowledge. As design is usually adjusted to established manufacturing, associated technological and strategic potentials are often neglected. To embed AM in a future proof industrial environment, software-based self-learning tools are necessary. Integrated into production planning, they enable companies to unlock the potentials of AM efficiently. This paper presents an appropriate methodology for the analysis of process-specific AM-eligibility and optimization potential, added up by concrete optimization proposals. For an integrated workpiece characterization, proven methods are enlarged by tooling-specific figures.
The first stage of the approach specifies the model’s initialization. A learning set of tooling components is described using the developed key figure system. Based on this, a set of applicable rules for workpiece-specific result determination is generated through clustering and expert evaluation. Within the following application stage, strategic orientation is quantified and workpieces of interest are described using the developed key figures. Subsequently, the retrieved information is used for automatically generating specific recommendations relying on the generated ruleset of stage one. Finally, actual experiences regarding the recommendations are gathered within stage three. Statistic learning transfers those to the generated ruleset leading to a continuously deepening knowledge base. This process enables a steady improvement in output quality.
Wettbewerbsregeln (§§ 24-27)
(2022)
Eye movement modelling examples (EMME) are instructional videos that display a
teacher’s eye movements as “gaze cursor” (e.g. a moving dot) superimposed on the
learning task. This study investigated if previous findings on the beneficial effects of EMME would extend to online lecture videos and compared the effects of displaying the teacher’s gaze cursor with displaying the more traditional mouse cursor as a tool to guide learners’ attention. Novices (N = 124) studied a pre-recorded video lecture on how to model business processes in a 2 (mouse cursor absent/present) × 2 (gaze cursor absent/present) between-subjects design. Unexpectedly, we did not find significant effects of the presence of gaze or mouse cursors on mental effort and learning. However, participants who watched videos with the gaze cursor found it easier to follow the teacher. Overall, participants responded positively to the gaze cursor, especially when the mouse cursor was not displayed in the video.
In this study, the performance of an integrated body-imaging array for 7 T with 32 radiofrequency (RF) channels under consideration of local specific absorption rate (SAR), tissue temperature, and thermal dose limits was evaluated and the imaging performance was compared with a clinical 3 T body coil.
Thirty-two transmit elements were placed in three rings between the bore liner and RF shield of the gradient coil. Slice-selective RF pulse optimizations for B1 shimming and spokes were performed for differently oriented slices in the body under consideration of realistic constraints for power and local SAR. To improve the B1+ homogeneity, safety assessments based on temperature and thermal dose were performed to possibly allow for higher input power for the pulse optimization than permissible with SAR limits.
The results showed that using two spokes, the 7 T array outperformed the 3 T birdcage in all the considered regions of interest. However, a significantly higher SAR or lower duty cycle at 7 T is necessary in some cases to achieve similar B1+ homogeneity as at 3 T. The homogeneity in up to 50 cm-long coronal slices can particularly benefit from the high RF shim performance provided by the 32 RF channels. The thermal dose approach increases the allowable input power and the corresponding local SAR, in one example up to 100 W/kg, without limiting the exposure time necessary for an MR examination.
In conclusion, the integrated antenna array at 7 T enables a clinical workflow for body imaging and comparable imaging performance to a conventional 3 T clinical body coil.
Digitale Lehrmaterialien werden seit mehreren Jahren in den Hochschulen eingesetzt und eröffnen ganz neue Wege zur Vermittlung des Lehrstoffs. Die Erstellung dieser Lehrmaterialien kann allerdings je nach Art und Qualität sehr zeitintensiv sein und für Lehrende einen großen Mehraufwand bedeuten. Im Rahmen eines Kooperationsprojekts zur Erstellung von Lehrvideos für geotechnische Feld- und Laborversuche haben die Autoren dieses Beitrags allerdings die Erfahrung gemacht, dass das gemeinsame, hochschulübergreifende Erstellen von Lehrmaterialien viele Vorteile mit sich bringt. Dadurch inspiriert, führten die Autoren dieses Berichts eine Umfrage unter den deutschsprachigen Geotechnik-Lehrstühlen der (Technischen) Universitäten und (Fach-)Hochschulen durch. Nach drei Semestern, in denen Lehrveranstaltungen an den Hochschulen aufgrund der Corona-Pandemie überwiegend digital durchgeführt werden mussten, war es ein Ziel dieser Umfrage, den Bestand und den Einsatz digitaler Lehrmaterialien im Fachgebiet Geotechnik zu erheben. Ein weiteres Ziel war die Initiierung eines Netzwerks, in dem sich Geotechnik-Professorinnen und -Professoren zu Lehrthemen austauschen können und gemeinsam (digitale) Lehrmaterialien erstellen und nutzen. Der vorliegende Beitrag stellt das gemeinsame Lehrprojekt der Autoren vor, präsentiert die Ergebnisse der durchgeführten Umfrage und berichtet über die ersten Aktivitäten des neuen Netzwerks.
Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruptions.
Werkstatt Zukunft - Die FH Aachen versteht sich als interdisziplinäre Ideenschmiede
04| Aufbruch ins Ungewisse
08| Mit Altpapierresten aus der Energiekrise
14| Mehr Power für die Energiewende
20| Pfadfinder im Datendschungel
23| Ein historischer Schritt
24| Gemeinsam vorwärts
30| Für eine gerechte Hochschule. Für alle.
32| Der grüne Reiter
34| Vom Flugsimulator bis zum Roboter
36| Unsere Azubis sind top!
38| WIR sind ein Sportteam!
40| Effizient und sicher: Der Bergbau der Zukunft
46| Mit Sonnenlicht zu sauberem Trinkwasser
48| Neue Brandmeldeanlage für den Dom zu Aachen
50| Auszeichnung für außergewöhnliches Engagement
52| Neue Ideen für Schloss Lichtenburg
55| Kopfnuss
56| One-Man-Show
60| Kämpferin für das Schöne
61| Ein charmanter Diplomat
62| Teamplay für die Zukunft
63| Impressum
Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability.