600 Technik, Technologie
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Active piezoelectric transducers are successfully deployed in recent years for structural health monitoring using guided elastic waves or electro-mechanical impedance (EMI). In both domains, damage detection can be hampered by operational/environmental conditions and low-power constraints. In both domains, processing can be divided into approaches (i) taking into account baselines of the pristine structure as reference, (ii) ingesting an extensive measurement history for clustering to explore anomalies, (iii) incorporating additional information to label a state. The latter approach requires data from complementary sensors, learning from laboratory/field experiments or knowledge from simulations which may be infeasible for complex structures. Semi-supervised approaches are thus gaining popularity: few initial annotations are needed, because labels emerge through clustering and are subsequently used for state classification. In our work, bending and combined bending/torsion studies on rudder stocks are considered regarding EMI-based damage detection in the presence of load. We discuss the underpinnings of our processing. Then, we follow strategy (i) by introducing frequency warping to derive an improved damage indicator (DI). Finally, in a semi-supervised manner, we develop simple rules which even in presence of varying loads need only two frequency points for reliable damage detection. This sparsity-enforcing low-complexity approach is particularly beneficial in energy-aware SHM scenarios.
Truck platooning is a promising approach for reducing fuel consumption, improving road safety, and optimizing transport logistics. This paper presents a drone-based decentralized truck platooning system that leverages the advantages of Ultra-Wideband (UWB) technology for precise positioning, robust communication, and real-time control. Our approach integrates UWB sensors on both trucks and drones, creating a scalable and resilient platooning system that can handle dynamic traffic conditions and varying road environments. The decentralized nature of the proposed system allows for increased flexibility and adaptability compared to traditional centralized platooning approaches. The core platooning algorithm employs multi-objective optimization, taking into account fuel efficiency, travel time, and safety. We propose a strategy for the formation and management of platoons based on UWB sensor data with an emphasis on maintaining optimal inter-vehicle secure distances and compatibility between trucks. Simulation results demonstrate the effectiveness of our approach in achieving efficient and stable platooning while addressing the challenges posed by real-world traffic scenarios. The proposed drone-based decentralized platooning system with UWB technology paves the way for the next generation of intelligent transportation systems that are more efficient, safer, and environment friendly.
The thickness of a material has a significant impact on its fracture load. The aim of the study was to find and describe a mathematical relationship between the material thickness and the fracture load for dental all-ceramics. In total, 180 specimens were prepared from a leucite silicate ceramic (ESS), a lithium disilicate ceramic (EMX), and a 3Y-TZP zirconia ceramic (LP) in five thicknesses (0.4, 0.7, 1.0, 1.3, and 1.6 mm; n = 12). The fracture load of all specimens was determined using the biaxial bending test according to the DIN EN ISO 6872. The regression analyses for the linear, quadratic, and cubic curve characteristics of the materials were conducted, and the cubic regression curves showed the best correlation (coefficients of determination (R2): ESS R2 = 0.974, EMX R2 = 0.947, LP R2 = 0.969) for the fracture load values as a function of the material thickness. A cubic relationship could be described for the materials investigated. Applying the cubic function and material-specific fracture-load coefficients, the respective fracture load values can be calculated for the individual material thicknesses. These results help to improve and objectify the estimation of the fracture loads of restorations, to enable a more patient- and indication-centered situation-dependent material choice.
Understanding the physics of strongly correlated electronic systems has been a central issue in condensed matter physics for decades. In transition metal oxides, strong correlations characteristic of narrow d bands are at the origin of remarkable properties such as the opening of Mott gap, enhanced effective mass, and anomalous vibronic coupling, to mention a few. SrVO3 with V4+ in a 3d1 electronic configuration is the simplest example of a 3D correlated metallic electronic system. Here, the authors' focus on the observation of a (roughly) quadratic temperature dependence of the inverse electron mobility of this seemingly simple system, which is an intriguing property shared by other metallic oxides. The systematic analysis of electronic transport in SrVO3 thin films discloses the limitations of the simplest picture of e–e correlations in a Fermi liquid (FL); instead, it is shown show that the quasi-2D topology of the Fermi surface (FS) and a strong electron–phonon coupling, contributing to dress carriers with a phonon cloud, play a pivotal role on the reported electron spectroscopic, optical, thermodynamic, and transport data. The picture that emerges is not restricted to SrVO3 but can be shared with other 3d and 4d metallic oxides.
The design of novel biomaterials should directly influence the host-immune system and steer it towards high biocompatibility. To date, new implants/materials have been tested for biocompatibility in vitro in cell cultures and in vivo in animal models. The current methods do not reflect reality (cell cultures) or are very time-consuming and deliver results only after weeks (animal model). In this proof-of-concept study, the suitability of a Whole Blood Stimulation Assay (WBSA) in combination with a Protein Profiler Array (PPA), as a readily available and cost-effective screening tool, was investigated. Three different biomaterials based on poly(lactic-co-glycolic acid (PLGA), calcium sulphate/-carbonate (CS) and poly(methyl methacrylate) (PMMA) were exposed to native whole blood from three volunteers and subsequently screened with a PPA. Individual reproducible protein profiles could be detected for all three materials after 24 h of incubation. The most intense reaction resulted from the use of PLGA, followed by CS. If even marginal differences in implants can be reflected in protein profiles, the combination of WBSA and PPA could serve as an early biocompatibility screening tool in the development of novel biomaterials. This may also lead to a reduction in costs and the amount of animal testing required.
A widespread application of 3D bioprinting in basic and translational research requires accessibility to affordable printers able to produce physiologically relevant tissue models. To facilitate the use of bioprinting as a standard technique in biology, an open-source device based on a consumer-grade 3D stereolithography apparatus (SLA) printer is developed. This SLA bioprinter can produce complex constructs that preserve cell viability and recapitulate the physiology of tissues. The detailed documentation of the modifications apported to the printer as well as a throughout performance analysis allow for a straightforward adoption of the device in other labs and its customization for specific applications. Given the low cost, several modified bioprinters could be simultaneously operated for a parallelized tissue production. To showcase the capability of the bioprinter, constructs consisting of patient-derived cholangiocarcinoma organoids encapsulated in a gelatin methacrylate (GelMA)/polyethylene glycol diacrylate (PEGDA) hydrogel are produced. A thorough characterization of different GelMA/PEGDA ratios reveals that the mechanical properties of the bioprinted tumor model can be accurately fine-tuned to mimic a specific tumor micro-environment. Immunofluorescence and gene expression analyses of tumor markers confirm that the bioprinted synthetic hydrogel provides a flexible and adequate replacement of animal-derived reconstituted extracellular matrix.
Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease causing dementia and poses significant health risks to middle-aged and elderly people. Brain magnetic resonance imaging (MRI) is the most widely used diagnostic method for AD. However, it is challenging to collect sufficient brain imaging data with high-quality annotations. Weakly supervised learning (WSL) is a machine learning technique aimed at learning effective feature representation from limited or low-quality annotations. In this paper, we propose a WSL-based deep learning (DL) framework (ADGNET) consisting of a backbone network with an attention mechanism and a task network for simultaneous image classification and image reconstruction to identify and classify AD using limited annotations. The ADGNET achieves excellent performance based on six evaluation metrics (Kappa, sensitivity, specificity, precision, accuracy, F1-score) on two brain MRI datasets (2D MRI and 3D MRI data) using fine-tuning with only 20% of the labels from both datasets. The ADGNET has an F1-score of 99.61% and sensitivity is 99.69%, outperforming two state-of-the-art models (ResNext WSL and SimCLR). The proposed method represents a potential WSL-based computer-aided diagnosis method for AD in clinical practice.
Cryovalues beyond high expectations: endurance and the construction of value in cord blood banking
(2022)
Cryopreservation attracts attention as a practice grounded in high expectations: current life is suspended for future use—to generate life, to save life, and to resurrect life. But what happens when high expectations in cryobanking give way to looming uselessness and the risk of failure? Based on ethnographic insights into the case of umbilical cord blood (CB) banking in Germany, this contribution investigates the liminal state of “non-failure.” Averting failure amid a lack of success in this field requires putting effort into the construction of value. The resulting practices and dynamics overflow generic stories of commercialization and instrumentalization of biological material and are best grasped as an expanded version of the recently coined notion of “cryovalue.” The long-term availability of cryopreserved CB facilitates the steady yield of social and economic capital beyond and after promise. Moreover, the value construction is reoriented from CB itself toward the socio-technical cryo-arrangements in which it is embedded. In exemplifying how it expands the understanding of the diversity of valuation and valorization practices, continuities, and economic endurance in cryoeconomies and bioeconomies, the paper advocates the study of their ambivalent and allegedly uneventful sites.
D-Galacturonic acid (GalA) is the major constituent of pectin-rich biomass, an abundant and underutilized agricultural byproduct. By one reductive step catalyzed by GalA reductases, GalA is converted to the polyhydroxy acid l-galactonate (GalOA), the first intermediate of the fungal GalA catabolic pathway, which also has interesting properties for potential applications as an additive to nutrients and cosmetics. Previous attempts to establish the production of GalOA or the full GalA catabolic pathway in Saccharomyces cerevisiae proved challenging, presumably due to the inefficient supply of NADPH, the preferred cofactor of GalA reductases. Here, we tested this hypothesis by coupling the reduction of GalA to the oxidation of the sugar alcohol sorbitol that has a higher reduction state compared to glucose and thereby yields the necessary redox cofactors. By choosing a suitable sorbitol dehydrogenase, we designed yeast strains in which the sorbitol metabolism yields a “surplus” of either NADPH or NADH. By biotransformation experiments in controlled bioreactors, we demonstrate a nearly complete conversion of consumed GalA into GalOA and a highly efficient utilization of the co-substrate sorbitol in providing NADPH. Furthermore, we performed structure-guided mutagenesis of GalA reductases to change their cofactor preference from NADPH towards NADH and demonstrated their functionality by the production of GalOA in combination with the NADH-yielding sorbitol metabolism. Moreover, the engineered enzymes enabled a doubling of GalOA yields when glucose was used as a co-substrate. This significantly expands the possibilities for metabolic engineering of GalOA production and valorization of pectin-rich biomass in general.
