Piezoelectric MEMS Disk Resonator and Filter Based on Epitaxial Al0.3Ga0.7As Films

In this work, a new class of disk, contour-mode, piezoelectric, micromechanical resonators based on single-crystal Al0.3Ga0.7As films has been developed. The shape of the disk resonator is based on the velocity propagation profile of the elastic wave in the plane of the piezoelectric film, with lateral dimensions scaled to the half wave length of the desired resonance frequency. The resonators are designed with supports to emulate free-free boundary conditions. Finite element analysis (FEA) model for this resonator is created in Ansys software, the simulation results validate the design concept. The performance parameters extracted from the FEA models show that this novel disk resonator outperforms the beam type counterpart. A unique 7-mask MEMS fabrication process based on the epitaxial, heterostructure Al0.3Ga0.7As films has been developed and successfully implemented to produce the prototypes of the new disk resonators. Fully experimental characterizations on the prototypes were conducted and the measured results from the prototypes are: a Q factor of 7031 at 30.2 MHz with 1.11 kΩ intrinsic motional resistance; a Q factor of 6515 at 40.8 MHz with 1.26 kΩ intrinsic motional resistance; a Q factor of 3300 at 62.3 MHz with 2.43 kΩ intrinsic motional resistance. The measured power handling level is about 1.6 mW, which is the highest power handling capability to date. These measured performance aspects are better than that of the previously developed beam type resonators. Based on this new disk resonator, two novel, two-port resonators (i.e., filters) designs have been introduced. The FEA models of both designs were created and the simulation results verify these design concepts. Equivalent circuit models for these filters were established with the parameters obtained from the FEA models. Furthermore, the optimal electrode configuration to provide minimum insertion loss is obtained through the analytical transadmittance function of the equivalent circuit. The prototypes of the filters were successfully fabricated. Measured results on these prototypes are summarized here: for the circular patter design, the best insertion loss is -45.7 dB at 37.8 MHz with quality factor 4372; for the half plane electrode design, the best insertion loss is -42.8 dB at 38.1 MHz with quality factor 3632

Quantitative Bioluminescence Tomography-guided System for Conformal Irradiation In Vivo

Although cone-beam CT (CBCT) has been used to guide irradiation for pre-clinical radiotherapy(RT) research, it is limited to localize soft tissue target especially in a low imaging contrast environment. Knowledge of target shape is a fundamental need for RT. Without such information to guide radiation, normal tissue can be irradiated unnecessarily, leading to experimental uncertainties. Recognition of this need led us to develop quantitative bioluminescence tomography (QBLT), which provides strong imaging contrast to localize optical targets. We demonstrated its capability of guiding conformal RT using an orthotopic bioluminescent glioblastoma (GBM) model. With multi-projection and multi-spectral bioluminescence imaging and a novel spectral derivative method, our QBLT system is able to reconstruct GBM with localization accuracy <1mm. An optimal threshold was determined to delineate QBLT reconstructed gross target volume (GTV_{QBLT}), which provides the best overlap between the GTV_{QBLT} and CBCT contrast labeled GBM (GTV), used as the ground truth for the GBM volume. To account for the uncertainty of QBLT in target localization and volume delineation, we also innovated a margin design; a 0.5mm margin was determined and added to GTV_{QBLT} to form a planning target volume (PTV_{QBLT}), which largely improved tumor coverage from 75% (0mm margin) to 98% and the corresponding variation (n=10) of the tumor coverage was significantly reduced. Moreover, with prescribed dose 5Gy covering 95% of PTV_{QBLT}, QBLT-guided 7-field conformal RT can irradiate 99.4 \pm 1.0% of GTV vs. 65.5 \pm 18.5% with conventional single field irradiation (n=10). Our QBLT-guided system provides a unique opportunity for researchers to guide irradiation for soft tissue targets and increase rigorous and reproducibility of scientific discovery

Distanzlernen in Deutschland und Europa: Mobiler, adaptiver und synchroner Onlineunterricht mit ASYMPTOTE

Der Distanzunterricht im Zuge der Covid-19-Pandemie führte im Frühjahr 2020 zu einer raschen Neuorganisation des Lernens: Innerhalb kürzester Zeit musste der Unterricht vom gemeinsamen Lernort Schule in die Kinderzimmer verlagert werden. Jener rapide Wechsel vom Präsenz- zum Distanzlernen wird als Emergency Remote Teaching (ERT) (Hodges et al. 2020) bezeichnet.Im Beitrag werden zunächst einige Herausforderungen des Distanzlernen in der ERT-Phase dargestellt. Anschließend wird, basierend auf den benannten Problemen im Distanzunterricht, das ASYMPTOTE-Projekt vorgestellt: Dieses zielt auf die Entwicklung einer Online-Umgebung für mobilen, adaptiven und synchronen Distanzunterricht

Adaptive Lerngraphen im Digitalen Klassenzimmer: Synchrones Distanzlernen mit ASYMPTOTE

Mit der COVID-19-Pandemie und dem plötzlich erforderlichen Distanzunterricht im Frühjahr 2020 wurden verschiedenste Defizite in der digitalen Schulbildung sichtbar. So sahen sich viele Lehrkräfte mit mangelnder technischer Ausstattung als auch der fehlenden technischen Ausbildung konfrontiert (Forsa, 2020). Des Weiteren konnten sie nur auf ein unzureichendes Angebot an digitalen Lernplattformen zurückgreifen und berichteten von einem vermehrten Einsatz von Reproduktionsaufgaben (Barlovits et al., 2021). Sprunghaft rückte die Nutzung und Entwicklung von digitalen Lernplattformen in den vergangenen Jahren sowohl in den öffentlichen als auch den politischen Fokus (WELT, 2020). In einer Bestandsaufnahme einiger bestehender Lernplattformen von Thurm und Graewert (2022) wurde allerdings deutlich, dass das volle Potential von digitalen Lernangeboten bei weitem nicht ausgenutzt wird und auch in der Qualität der Lernangebote teils gravierende Unterschiede bestehen. Thurm und Graewert (2022) fordern daher eine Weiterentwicklung der digitalen Lehr-/Lernumgebungen beziehungsweise eine Neuentwicklung dieser unter Berücksichtigung verschiedener Kriterien. Zu Letzteren gehören mitunter die Qualität der Aufgaben in Bezug auf mögliche Aufgabenformate, die Qualität der Diagnostik, die Adaptivität an die Lernenden, soziales Lernen in Form von Teamarbeit sowie Teamkommunikation und nicht zuletzt die Möglichkeiten der Eigenregulation. Mit dem Wissen um diese Anforderungen für digitale Lernplattformen stellen wir das Projekt ASYMPTOTE und das gleichnamige System für synchrones Distanzlernen vor

Keck and ESO-VLT View of the Symmetry of the Ejecta of the XRF/SN 2006aj

Nebular-phase spectra of SN 2006aj, which was discovered in coincidence with X-ray flash 060218, were obtained with Keck in 2006 July and the Very Large Telescope in 2006 September. At the latter epoch spectropolarimetry was also attempted, yielding an upper limit of ~ 2% for the polarization. The spectra show strong emission lines of [OI] and MgI], as expected from a Type Ic supernova, but weak CaII lines. The [FeII] lines that were strong in the spectra of SN 1998bw are much weaker in SN 2006aj, consistent with the lower luminosity of this SN. The outer velocity of the line-emitting ejecta is ~ 8000 km/s in July and ~ 7400 km/s in September, consistent with the relatively low kinetic energy of expansion of SN 2006aj. All emission lines have similar width, and the profiles are symmetric, indicating that no major asymmetries are present in the ejecta at the velocities sampled by the nebular lines (v < 8000 km/s), except perhaps in the innermost part. The spectra were modelled with a non-LTE code. The mass of 56Ni required to power the emission spectrum is ~ 0.20 Msun, in excellent agreement with the results of early light curve modelling. The oxygen mass is ~ 1.5 Msun, again much less than in SN 1998bw but larger by ~ 0.7 Msun than the value derived from the early-time modelling. The total ejected mass is ~ 2 Msun below 8000 km/s. This confirms that SN 2006aj was only slightly more massive and energetic than the prototypical Type Ic SN 1994I, but also indicates the presence of a dense inner core, containing ~ 1 Msun of mostly oxygen and carbon. The presence of such a core is inferred for all broad-lined SNe Ic. This core may have the form of an equatorial oxygen-dominated region, but it is too deep to affect the early light curve and too small to affect the late polarization spectrum.Comment: 20 pages, 6 figures. Accepted for publication in the Astrophysical Journa

Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images

Many anomaly detection approaches, especially deep learning methods, have been recently developed to identify abnormal image morphology by only employing normal images during training. Unfortunately, many prior anomaly detection methods were optimized for a specific "known" abnormality (e.g., brain tumor, bone fraction, cell types). Moreover, even though only the normal images were used in the training process, the abnormal images were often employed during the validation process (e.g., epoch selection, hyper-parameter tuning), which might leak the supposed ``unknown" abnormality unintentionally. In this study, we investigated these two essential aspects regarding universal anomaly detection in medical images by (1) comparing various anomaly detection methods across four medical datasets, (2) investigating the inevitable but often neglected issues on how to unbiasedly select the optimal anomaly detection model during the validation phase using only normal images, and (3) proposing a simple decision-level ensemble method to leverage the advantage of different kinds of anomaly detection without knowing the abnormality. The results of our experiments indicate that none of the evaluated methods consistently achieved the best performance across all datasets. Our proposed method enhanced the robustness of performance in general (average AUC 0.956)