Search

Airlines are faced with the challenge of reducing their environmental footprint in an effort to push for climate-neutral initiatives that comply with international regulations. In the past, the aviation industry has followed the approach of incremental improvement of fuel efficiency while simultaneously experiencing significant growth in annual air traffic. With the increase in air traffic negating any reduction in Greenhouse Gas (GHG) emissions, more disruptive technologies such as hydrogen-based onboard power generation are required to reduce the environmental impact of airline operations. However, despite initial euphoria and first conceptual studies for hydrogen-powered aircraft several decades ago, there still has been no mass adoption to this day. Besides the challenges of a suitable ground infrastructure, this can partly be attributed to uncertainties with the associated maintenance requirements and the expected operating costs to demonstrate the economic viability of this technology. With this study, we address this knowledge gap by estimating changes towards scheduled maintenance activities for an airborne hydrogen storage and distribution system. In particular, we develop a detailed system design for a hydrogen-powered, fuel-cell-based auxiliary power generation and perform a comparative analysis with an Airbus A320 legacy system. That analysis allows us to (a) identify changes for the expected maintenance effort to enhance subsequent techno-economic assessments, (b) identify implications of specific design assumptions with corresponding maintenance activities while ensuring regulatory compliance and (c) describe the impact on the resulting task execution. The thoroughly examined interactions between system design and subsequent maintenance requirements of this study can support practitioners in the development of prospective hydrogen-powered aircraft. In particular, it allows the inclusion of maintenance implications in early design stages of corresponding system architectures. Furthermore, since the presented methodology is transferable to different design solutions, it provides a blueprint for alternative operating concepts such as the complete substitution of kerosene by hydrogen to power the main engines. • Hydrogen in aviation requires strict safety measures to comply with regulations. • Systems will become technically more complex and demanding towards maintenance. • The substitution of kerosene with hydrogen is likely to increase maintenance costs. • Without prior experience, maintenance has to be estimated across industry sectors. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) initially responds to inhibition of androgen receptor (AR) signaling, but inevitably progresses to hormone ablation-resistant disease. Much effort is focused on optimizing this androgen deprivation strategy by improving hormone depletion and AR antagonism. However we found that bicalutamide, a clinically used antiandrogen, actually resembles a selective AR modulator (SARM), as it partially regulates 24% of endogenously 5α-dihydrotestosterone (DHT)-responsive genes in AR(+) MDA-MB-453 breast cancer cells. These data suggested that passive blocking of all AR functions is not required for PCa therapy. Hence, we adopted an active strategy that calls for the development of novel SARMs, which induce a unique gene expression profile that is intolerable to PCa cells. Therefore, we screened 3000 SARMs for the ability to arrest the androgen-independent growth of AR(+) 22Rv1 and LNCaP PCa cells but not AR(−) PC3 or DU145 cells. We identified only one such compound; the 4-aza-steroid, MK-4541, a potent and selective SARM. MK-4541 induces caspase-3 activity and cell death in both androgen-independent, AR(+) PCa cell lines but spares AR(−) cells or AR(+) non-PCa cells. This activity correlates with its promoter context- and cell-type dependent transcriptional effects. In rats, MK-4541 inhibits the trophic effects of DHT on the prostate, but not the levator ani muscle, and triggers an anabolic response in the periosteal compartment of bone. Therefore, MK-4541 has the potential to effectively manage prostatic hypertrophic diseases owing to its antitumor SARM-like mechanism, while simultaneously maintaining the anabolic benefits of natural androgens. [ABSTRACT FROM AUTHOR]

The aviation industry is facing an ever-increasing competition to lower its operating cost. Simultaneously, new factors, such as sustainability and customer experience, become more important to differentiate from competitors. As aircraft maintenance contributes about 20% to the overall cost of airline operations and can significantly influence other objectives of an airline as well, maintenance providers are required to constantly lower their cost share and contribute to a more reliable and sustainable aircraft operation. Subsequently, new condition-monitoring technologies have emerged that are expected to improve maintenance operations by reducing cost and increasing the aircraft's availability. As many of these technologies are still in their technological infancy, it is necessary to determine the expected benefit for the airline operations with the given technological maturity and to develop suitable maintenance strategies that incorporate the newly gained insights. With this paper, a discrete-event simulation framework is developed that uses established parameters to describe a condition-monitoring technology's performance and subsequently develops a suitable prescriptive maintenance strategy. Therefore, it enables the adjustment of the optimization goal for the developed strategy to incorporate performance features beyond the frequently used financial indicators. The developed capabilities will be demonstrated for the tire pressure measurement task of an Airbus A320. • Prescriptive maintenance extends the scope of legacy maintenance strategies. • Discrete-event simulation framework proposed for holistic stakeholder modeling. • Inclusion of technical maturity levels and fleet utilization degrees of PHM systems. • Consideration of economic and ecologic aspects of maintenance decision making. • Results indicate minimum fleet utilization of PHM systems to achieve cost advantage. [ABSTRACT FROM AUTHOR]

Estimating the damage state of composites is essential since carbon fibre reinforced polymers (CFRP) have a complex damage and propagation behaviour. Accordingly, a comprehensive study of the effects of matrix cracks – e.g. their size and crack density – and the influence of different damage types and their interaction on the vibro-acoustic modulation (VAM) behaviour of CFRP specimens under fatigue loading was carried out. These effects were evaluated in two sets of commonly employed laminate layups. Firstly, in a cross-ply (CP) layup, the number of 90°layers was varied, with a constant areal weight (268 g/m 2). Secondly, quasi-isotropic (QI) specimens were tested, where the areal weight was reduced from thick-ply to thin-ply (30–268 g/m 2), changing the failure mode from a delamination-dominated to a brittle failure. After damage introduction under tension–tension loading (R=0.1), high-frequency Lamb waves are introduced via piezoceramic actuators and modulated by a low-frequency vibration using a servo-hydraulic testing machine. VAM correlates with the different damage behaviour and damage conditions in CFRP. For this purpose, the evolution of the sideband amplitudes, the modulation index, the signal in time domain and X-ray scans are used. Regardless of the layup, the degree of stiffness-reducing inter-fibre fractures and large-scale delaminations can be detected. • Reliable health monitoring of thin- and thickply CFRP with varied lay-ups via VAM measurements • Modulation envelope and sideband amplitudes provide damage progression during fatigue • Detection of delaminations and the degree of stiffness-reducing inter-fibre fractures, highly sensitive to crack size • Enabling a VAM threshold prior to delamination occurrence to predict failures [ABSTRACT FROM AUTHOR]

Abstract: A series of partial agonists of the Glucocorticoid Receptor were prepared targeting reduced transactivation activity, while maintaining significant transrepression activity. Incorporation of an ortho-aryl amide produced compounds with the desired in vitro profile. Bioreactors consisting of Suspension cultures of Sf21 cells co expressing a CYP3A4 and NADPH-cytochrome P450 oxireductase were used to prepare the major metabolites of these compounds and revealed that oxidative N-dealkylation provided a pathway for formation of metabolites that were more agonistic than the parent partial agonists. Oxidative N-dealkylation was blocked in a new series of compounds, however oxidation alone was capable of producing full agonist metabolites. Incorporation of an ortho-primary amide and utilization of fluorine to modulate agonism afforded partial agonist MK-5932. Synthesis of the major metabolites of MK-5932 using bioreactor technology revealed that no significant GR-active metabolites were formed. Orally administered MK-5932 displayed anti-inflammatory efficacy in a Rat Oxazolone-induced chronic dermatitis model, while sparing plasma insulin. [Copyright &y& Elsevier]

Abstract: On interannual to decadal times scales, model simulations suggest a strong relationship between anomalies in the deep water formation rate, the strength of the subpolar gyre, and the meridional overturning circulation in the North Atlantic. Whether this is valid, can only be confirmed by continuous, long observational time series. Several measurement components are already in place, but crucial arrays to obtain time series of the meridional volume and heat transport in the subpolar North Atlantic are still missing. Here we summarize the recent developments of the deep water formation rates and the subpolar gyre transports. We discuss how existing observational components in the subpolar North Atlantic could be supplemented to provide long-term monitoring of the meridional heat and volume transport. Through a combined analysis of observations and model results the temporal and spatial scales that had to be covered with instruments are discussed, together with the key regions with the highest variability in the velocity and temperature fields. [Copyright &y& Elsevier]

Androgen replacement therapy is a promising strategy for the treatment of frailty; however, androgens pose risks for unwanted effects including virilization and hypertrophy of reproductive organs. Selective Androgen Receptor Modulators (SARMs) retain the anabolic properties of androgens in bone and muscle while having reduced effects in other tissues. We describe two structurally similar 4-aza-steroidal androgen receptor (AR) ligands, Cl-4AS-1, a full agonist, and TFM-4AS-1, which is a SARM. TFM-4AS-1 is a potent AR ligand (IC50, 38 nM) that partially activates an AR-dependent MMTV promoter (55% of maximal response) while antagonizing the N-terminal/C-terminal interaction within AR that is required for full receptor activation. Microarray analyses of MDA-MB-453 cells show that whereas Cl-4AS- 1 behaves like 5a-dihydrotestosterone (DHT), TFM-4AS-1 acts as a gene-selective agonist, inducing some genes as effectively as DHT and others to a lesser extent or not at all. This gene-selective agonism manifests as tissue-selectivity: in ovariectomized rats, Cl-4AS-1 mimics DHT while TFM-4AS-1 promotes the accrual of bone and muscle mass while having reduced effects on reproductive organs and sebaceous glands. Moreover, TFM-4A5-1 does not promote prostate growth and antagonizes DHT in seminal vesicles. To confirm that the biochemical properties of TFM-4AS-1 confer tissue selectivity, we identified a structurally unrelated compound, FTBU-1, with partial agonist activity coupled with antagonism of the N-terminal/C-terminal interaction and found that it also behaves as a SARM. TFM-4AS-1 and FTBU-1 represent two new classes of SARMs and will allow for comparative studies aimed at understanding the biophysical and physiological basis of tissue-selective effects of nuclear receptor ligands. [ABSTRACT FROM AUTHOR]

Abstract: Potent, novel 7-oxo αvβ3 antagonists have been prepared. These antagonists offer decreased plasma protein binding and excellent pharmacokinetic profiles. [Copyright &y& Elsevier]

Antagonists of the integrin receptor αvβ3 are expected to have utility in the treatment of osteoporosis through inhibition of bone resorption. A series of potent, chain-shortened, pyrrolidinone-containing αvβ3 receptor antagonists is described. Two sets of diasteromeric pairs of high-affinity antagonists demonstrated marked differences in log P values, which translated into differing dog pharmacokinetic properties. One member of this set was demonstrated to be effective in reducing bone resorption in rats. [Copyright &y& Elsevier]

• Robust and reproducible artificial weak-bond creation in single-lap shear specimens. • Combination of vibroacoustic modulation analysis with machine learning to identify weak-bonds. • Improved classification of weak-bonds using a neural network resulted in 97% accuracy and prediction of shear strength by the neural network results is in general possible. • Neural network decisions are based on modulations traditionally not evaluated in previous approaches. Adhesive bonding is a well-established technique for composite materials. Despite advanced surface treatments and preparations, surface contamination and application errors still occur, resulting in localised areas with a reduced adhesion. The dramatic reduction of the bond strength limits the applicability of adhesive bonds and hampers further industrial adaptation. This study aims to detect weak-bonds due to manufacturing errors or contamination by analysing and interpreting the vibroacoustic modulation signals with the aid of machine learning. An ultrasonic signal is introduced into the specimen by a piezoceramic actuator and modulated through a low frequency vibration excited by a servo-hydraulic testing system. Tested samples are single-lap shear specimens, according to ASTM D5868-01, with artificial circular debonding areas introduced as PTFE-films or a release agent contamination. It is shown that an artificial neural network can identify various defects in the bonded joint robustly and is able to predict residual strengths and hence demonstrates great potential for non-destructive testing of adhesive joints. [ABSTRACT FROM AUTHOR]

[Display omitted] • Magnesium degradation rate correlates with calcium-containing precipitates. • Solution stability is important for the formation of hydroxyapatite. • A stable protective layer forms when the degradation rate is lower than 2 mm/yr. • The ionic interactions are complex and strongly non-linear. We have studied the degradation of pure magnesium wire in simulated body fluid and its subsets under physiological conditions to enable the prediction of the degradation rate based on the medium's ionic composition. To this end, micro-computed tomography and scanning electron microscopy with energy-dispersive X-ray spectroscopy were used, followed by a tree regression analysis. A non-linear relationship was found between degradation rate and the precipitation of calcium salts. The mean absolute error for predicting the degradation rate was 1.35 mm/yr. This comparatively high value indicates that ionic interactions were exceedingly complex or that an unknown parameter determining the degradation may exist. [ABSTRACT FROM AUTHOR]

Until now, detecting weak spots in composite structures remains a key challenge in the aviation industry. The correct assessment of the load-bearing capability after structural overloading or the occurrence of barely-visible damages is particularly important to maintain structural integrity. Nonetheless, a reliable and overarching non-destructive inspection method to estimate the residual mechanical properties while covering all major damage scenarios has not been found yet. Several non-destructive techniques have been proposed to approach these challenges and are already in place for specific damage cases. However, each technique has its sources of information and therefore, limitations in practice due to a lack of generalisation. In this work, we present a concept and approach to gain access to the residual mechanical properties of a thermosetting polymer solely based on its inherent material state independent from its life-cycle history. Therefore, the material state is obtained by combining Fourier-transformed infrared spectroscopy with feature extraction algorithms based on Gaussian peak fitting. As proof of concept, tensile, creep, and cyclic tests are conducted to demonstrate this approach's advantage. A complementary theoretical investigation using quantum chemical calculations is employed to support the experimental work by identifying the investigated polymer's characteristic vibrational modes and predicting their evolution during the experiments. The results show that the quantification of molecular changes can estimate the material state and that the method is suitable to improve the understanding of the degradation processes and severity. This publication shall particularly serve as the basis for further research to study the interaction between molecular forces and material properties. [Display omitted] • Thermosetting polymers can undergo significant plastic deformation at certain conditions. • Infrared spectroscopy peak-shifts can be applied to estimate the molecular stress distribution of thermosetting polymers. • Feature extraction algorithms contribute to discover correlations with material properties and predict future behavior. • Quantum chemical calculations enable an estimation of characteristic vibrational modes and a prediction of their evolution. [ABSTRACT FROM AUTHOR]

• Artificial neural network predicts performance of corrosion modulating agents for Mg. • Calculated HOMO LUMO gap correlates well with inhibition efficiencies for CP Mg. • Model predictions validated by subsequent investigation of untested compounds. • Trained model facilitates performance prediction for material of similar composition. The vast number of small molecules with potentially useful dissolution modulating properties (inhibitors or accelerators) renders currently used experimental discovery methods time- and resource-consuming. Fortunately, emerging computer-assisted methods can explore large areas of chemical space with less effort. Here we show how density functional theory calculations and machine learning methods can work synergistically to generate robust and predictive models that recapitulate experimentally-derived corrosion inhibition efficiencies of small organic compounds for pure magnesium. We further validate our methods by predicting a priori the corrosion modulation properties of seven hitherto untested small molecules and confirm the prediction in subsequent experiments. [ABSTRACT FROM AUTHOR]