Investigating Formations on Titanium Surfaces for Enhanced Fluid-Surface Interactions

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Data Enabled Failure Management Process (DEFMP) across the Product Value Chain

The continuously increasing amount of production data and the advancing development of digitization solutions promote advanced data analytics as a promising approach for failure management. Beyond the consideration of single units, examining the end-to-end value chain, including development, production, and usage, offers potential for failure in management-related investigations. Nonetheless, challenges regarding data integration from different entities along the value creation process, data volume and formats handling, effective analytics, and decision support arise. The CRISP-DM approach has become a widely established reference as a conceptual framework for data-driven solutions. However, the linkage between existing failure management procedures and the subsequent development of data-driven solutions needs to be specified. Accordingly, this paper presents a cross-value chain Data Enabled Failure Management Process (DEFMP). The central element is a process model to implement a cross-value chain data-enabled failure management, considering established quality management and data analytics approaches. Based on available failure, product, and process knowledge along the value chain, a path towards developing a comprehensive decision support system is shown. DEFMP combines a reactive failure process with a data-driven approach to incorporate data analytics for proactive improvements. Using DEFMP, the failure management process of a commercial vehicle manufacturer is adapted. With this, partial automation of failure management is made possible. In addition, the potential for improvements is identified and prioritized

An End-to-End HW/SW Co-Design Methodology to Design Efficient Deep Neural Network Systems using Virtual Models

End-to-end performance estimation and measurement of deep neural network (DNN) systems become more important with increasing complexity of DNN systems consisting of hardware and software components. The methodology proposed in this paper aims at a reduced turn-around time for evaluating different design choices of hardware and software components of DNN systems. This reduction is achieved by moving the performance estimation from the implementation phase to the concept phase by employing virtual hardware models instead of gathering measurement results from physical prototypes. Deep learning compilers introduce hardware-specific transformations and are, therefore, considered a part of the design flow of virtual system models to extract end-to-end performance estimations. To validate the run-time accuracy of the proposed methodology, a system processing the DilatedVGG DNN is realized both as virtual system model and as hardware implementation. The results show that up to 92 % accuracy can be reached in predicting the processing time of the DNN inference

High-speed, low drive-voltage silicon-organic hybrid modulator based on a binary-chromophore electro-optic material

We report on the hybrid integration of silicon-on-insulator slot waveguides with organic electro-optic materials. We investigate and compare a polymer composite, a dendron-based material, and a binary-chromophore organic glass (BCOG). A record-high in-device electro-optic coefficient of 230 pm/V is found for the BCOG approach resulting in silicon-organic hybrid Mach-Zehnder modulators that feature low UpL-products of down to 0.52 Vmm and support data rates of up to 40 Gbit/

Emergent Trion-Phonon Coupling in Atomically-Reconstructed MoSe2_2-WSe2_2 Heterobilayers

In low-temperature resonant Raman experiments on MoSe$_2$-WSe$_2$ heterobilayers, we identify a hybrid interlayer shear mode (HSM) with an energy, close to the interlayer shear mode (SM) of the heterobilayers, but with a much broader, asymmetric lineshape. The HSM shows a pronounced resonance with the intralayer hybrid trions (HX$^-$) of the MoSe$_2$ and WSe$_2$ layers, only. No resonance with the neutral intralayer excitons is found. First-principles calculations reveal a strong coupling of Q-valley states, which are delocalized over both layers and participate in the HX$^-$, with the SM. This emerging trion-phonon coupling may be relevant for experiments on gate-controlled heterobilayers.Comment: 6 pages, 3 figure

Telemedicine across the globe-position paper from the COVID-19 pandemic health system resilience PROGRAM (REPROGRAM) international consortium (Part 1)

Coronavirus disease 2019 (COVID-19) has accelerated the adoption of telemedicine globally. The current consortium critically examines the telemedicine frameworks, identifies gaps in its implementation and investigates the changes in telemedicine framework/s during COVID-19 across the globe. Streamlining of global public health preparedness framework that is interoperable and allow for collaboration and sharing of resources, in which telemedicine is an integral part of the public health response during outbreaks such as COVID-19, should be pursued. With adequate reinforcement, telemedicine has the potential to act as the “safety-net” of our public health response to an outbreak. Our focus on telemedicine must shift to the developing and under-developing nations, which carry a disproportionate burden of vulnerable communities who are at risk due to COVID-19

Absence of a giant spin Hall effect in plasma-hydrogenated graphene

The weak spin-orbit interaction in graphene was predicted to be increased, e.g., by hydrogenation. This should result in a sizable spin Hall effect (SHE). We employ two different methods to examine the spin Hall effect in weakly hydrogenated graphene. For hydrogenation we expose graphene to a hydrogen plasma and use Raman spectroscopy to characterize this method. We then investigate the SHE of hydrogenated graphene in the H-bar method and by direct measurements of the inverse SHE. Although a large nonlocal resistance can be observed in the H-bar structure, comparison with the results of the other method indicate that this nonlocal resistance has a non-spin-related origin

Large-Scale Mapping of Moiré Superlattices by Hyperspectral Raman Imaging.

Moiré superlattices can induce correlated-electronic phases in twisted van der Waals materials: strongly correlated quantum phenomena emerge, such as superconductivity and the Mott-insulating state. However, moiré superlattices produced through artificial stacking can be quite inhomogeneous, which hampers the development of a clear correlation between the moiré period and the emerging electrical and optical properties. Here, it is demonstrated in twisted-bilayer transition-metal dichalcogenides that low-frequency Raman scattering can be utilized not only to detect atomic reconstruction, but also to map out the inhomogeneity of the moiré lattice over large areas. The method is established based on the finding that both the interlayer-breathing mode and moiré phonons are highly susceptible to the moiré period and provide characteristic fingerprints. Hyperspectral Raman imaging visualizes microscopic domains of a 5° twisted-bilayer sample with an effective twist-angle resolution of about 0.1°. This ambient methodology can be conveniently implemented to characterize and preselect high-quality areas of samples for subsequent device fabrication, and for transport and optical experiments

Blockade of MCAM/CD146 impedes CNS infiltration of T cells over the choroid plexus

Background: Very late antigen 4 (VLA-4;integrin alpha 4 beta 1) is critical for transmigration of T helper (T-H) 1 cells into the central nervous system (CNS) under inflammatory conditions such as multiple sclerosis (MS). We have previously shown that VLA-4 and melanoma cell adhesion molecule (MCAM) are important for trans-endothelial migration of human T(H)17 cells in vitro and here investigate their contribution to pathogenic CNS inflammation. Methods: Antibody blockade of VLA-4 and MCAM is assessed in murine models of CNS inflammation in conjunction with conditional ablation of alpha 4-integrin expression in T cells. Effects of VLA-4 and MCAM blockade on lymphocyte migration are further investigated in the human system via in vitro T cell transmigration assays. Results: Compared to the broad effects of VLA-4 blockade on encephalitogenic T cell migration over endothelial barriers, MCAM blockade impeded encephalitogenic T cell migration in murine models of MS that especially depend on CNS migration across the choroid plexus (CP). In transgenic mice lacking T cell alpha 4-integrin expression (CD4::/tga4(-/-)), MCAM blockade delayed disease onset. Migration of MCAM-expressing T cells through the CP into the CNS was restricted, where laminin 411 (composed of alpha 4, beta 1, gamma 1 chains), the proposed major ligand of MCAM, is detected in the endothelial basement membranes of murine CP tissue. This finding was translated to the human system;blockade of MCAM with a therapeutic antibody reduced in vitro transmigration of MCAM-expressing T cells across a human fibroblast-derived extracellular matrix layer and a brain-derived endothelial monolayer, both expressing laminin alpha 4. Larninin alpha 4 was further detected in situ in CP endothelial-basement membranes in MS patients' brain tissue. Conclusions: Our findings suggest that MCAM-laminin 411 interactions facilitate trans-endothelial migration of MCAM-expressing T cells into the CNS, which seems to be highly relevant to migration via the CP and to potential future clinical applications in neuroinflammatory disorders