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A High-Throughput Functional Complementation Assay for Classification of BRCA1 Missense Variants
(2013)
IT-Sicherheit im Automobil
(2014)
The constitutive androstane receptor (CAR) and the pregnane X receptor (PXR) are closely related nuclear receptors involved in drug metabolism and play important roles in the mechanism of phenobarbital (PB)-induced rodent nongenotoxic hepatocarcinogenesis. Here, we have used a humanized CAR/PXR mouse model to examine potential species differences in receptor-dependent mechanisms underlying liver tissue molecular responses to PB. Early and late transcriptomic responses to sustained PB exposure were investigated in liver tissue from double knock-out CAR and PXR (CARᴷᴼ-PXRᴷᴼ), double humanized CAR and PXR (CARʰ-PXRʰ), and wild-type C57BL/6 mice. Wild-type and CARʰ-PXRʰ mouse livers exhibited temporally and quantitatively similar transcriptional responses during 91 days of PB exposure including the sustained induction of the xenobiotic response gene Cyp2b10, the Wnt signaling inhibitor Wisp1, and noncoding RNA biomarkers from the Dlk1-Dio3 locus. Transient induction of DNA replication (Hells, Mcm6, and Esco2) and mitotic genes (Ccnb2, Cdc20, and Cdk1) and the proliferation-related nuclear antigen Mki67 were observed with peak expression occurring between 1 and 7 days PB exposure. All these transcriptional responses were absent in CARᴷᴼ-PXRᴷᴼ mouse livers and largely reversible in wild-type and CARʰ-PXRʰ mouse livers following 91 days of PB exposure and a subsequent 4-week recovery period. Furthermore, PB-mediated upregulation of the noncoding RNA Meg3, which has recently been associated with cellular pluripotency, exhibited a similar dose response and perivenous hepatocyte-specific localization in both wild-type and CARʰ-PXRʰ mice. Thus, mouse livers coexpressing human CAR and PXR support both the xenobiotic metabolizing and the proliferative transcriptional responses following exposure to PB.
Unsteady flow measurements in the wake behind a wind-tunnel car model by using high-speed planar PIV
(2015)
This study investigates unsteady characteristics of the wake behind a 28%-scale car model in a wind tunnel using highspeed planar particle image velocimetry (PIV). The car model is based on a hatchback passenger car that is known to have relatively high fluctuations in its aerodynamic loads. This study primarily focuses on the lateral motion of the flow on the horizontal plane to determine the effect of the flow motion on the straight-line stability and the initial steering response of the actual car on a track. This paper first compares the flow fields in the wake behind the above mentioned model obtained using conventional and high-speed planar PIV, with sampling frequencies of 8 Hz and 1 kHz, respectively. Large asymmetrically coherent flow structures, which fluctuate at frequencies below 2 Hz, are observed in the results of highspeed PIV measurements, whereas conventional PIV is unable to capture these features of the flow owing to aliasing. This flow pattern with a laterally swaying motion is represented by opposite signs of cross-correlation coefficients of streamwise velocity fluctuations for the two sides of the car model. Effects of two aerodynamic devices that are known to reduce the
fluctuation levels of the aerodynamic loads are then extensively investigated. The correlation analyses reveal that these devices indeed reduce the fluctuation levels of the flow and the correlation values around the rear combination-lamp, but it is found that the effects of these devices are different around the c-pillar.
Inkompressible Strömungen
(2015)
Operational Modal Analysis (OMA) is a promising candidate for flutter testing and Structural Health Monitoring (SHM) of aircraft wings that are passively excited by wind loads. However, no studies have been published where OMA is tested in transonic flows, which is the dominant condition for large civil aircraft and is characterized by complex and unique aerodynamic phenomena. We use data from the HIRENASD large-scale wind tunnel experiment to automatically extract modal parameters from an ambiently excited wing operated in the transonic regime using two OMA methods: Stochastic Subspace Identification (SSI) and Frequency Domain Decomposition (FDD). The system response is evaluated based on accelerometer measurements. The excitation is investigated from surface pressure measurements. The forcing function is shown to be non-white, non-stationary and contaminated by narrow-banded transonic disturbances. All these properties violate fundamental OMA assumptions about the forcing function. Despite this, all physical modes in the investigated frequency range were successfully identified, and in addition transonic pressure waves were identified as physical modes as well. The SSI method showed superior identification capabilities for the investigated case. The investigation shows that complex transonic flows can interfere with OMA. This can make existing approaches for modal tracking unsuitable for their application to aircraft wings operated in the transonic flight regime. Approaches to separate the true physical modes from the transonic disturbances are discussed.
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.
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.