158 research outputs found
Spectral approach to axisymmetric evolution of Einstein's equations
We present a new formulation of Einstein's equations for an axisymmetric
spacetime with vanishing twist in vacuum. We propose a fully constrained scheme
and use spherical polar coordinates. A general problem for this choice is the
occurrence of coordinate singularities on the axis of symmetry and at the
origin. Spherical harmonics are manifestly regular on the axis and hence take
care of that issue automatically. In addition a spectral approach has
computational advantages when the equations are implemented. Therefore we
spectrally decompose all the variables in the appropriate harmonics. A central
point in the formulation is the gauge choice. One of our results is that the
commonly used maximal-isothermal gauge turns out to be incompatible with tensor
harmonic expansions, and we introduce a new gauge that is better suited. We
also address the regularisation of the coordinate singularity at the origin.Comment: 6 pages, based on a talk given by one of the authors at the Spanish
Relativity Meeting ERE14 in Valencia, published versio
Comparison of Data Representations and Machine Learning Architectures for User Identification on Arbitrary Motion Sequences
Reliable and robust user identification and authentication are important and
often necessary requirements for many digital services. It becomes paramount in
social virtual reality (VR) to ensure trust, specifically in digital encounters
with lifelike realistic-looking avatars as faithful replications of real
persons. Recent research has shown that the movements of users in extended
reality (XR) systems carry user-specific information and can thus be used to
verify their identities. This article compares three different potential
encodings of the motion data from head and hands (scene-relative,
body-relative, and body-relative velocities), and the performances of five
different machine learning architectures (random forest, multi-layer
perceptron, fully recurrent neural network, long-short term memory, gated
recurrent unit). We use the publicly available dataset "Talking with Hands" and
publish all code to allow reproducibility and to provide baselines for future
work. After hyperparameter optimization, the combination of a long-short term
memory architecture and body-relative data outperformed competing combinations:
the model correctly identifies any of the 34 subjects with an accuracy of 100%
within 150 seconds. Altogether, our approach provides an effective foundation
for behaviometric-based identification and authentication to guide researchers
and practitioners. Data and code are published under
https://go.uniwue.de/58w1r.Comment: in press at IEEE VRAI 202
Ballistic transport in graphene antidot lattices
Graphene samples can have a very high carrier mobility if influences from the
substrate and the environment are minimized. Embedding a graphene sheet into a
heterostructure with hexagonal boron nitride (hBN) on both sides was shown to
be a particularly efficient way of achieving a high bulk mobility.
Nanopatterning graphene can add extra damage and drastically reduce sample
mobility by edge disorder. Preparing etched graphene nanostructures on top of
an hBN substrate instead of SiO2 is no remedy, as transport characteristics are
still dominated by edge roughness. Here we show that etching fully encapsulated
graphene on the nanoscale is more gentle and the high mobility can be
preserved. To this end, we prepared graphene antidot lattices where we observe
magnetotransport features stemming from ballistic transport. Due to the short
lattice period in our samples we can also explore the boundary between the
classical and the quantum transport regime
Extensible Motion-based Identification of XR Users with Non-Specific Motion
Recently emerged solutions demonstrate that the movements of users
interacting with extended reality (XR) applications carry identifying
information and can be leveraged for identification. While such solutions can
identify XR users within a few seconds, current systems require one or the
other trade-off: either they apply simple distance-based approaches that can
only be used for specific predetermined motions. Or they use
classification-based approaches that use more powerful machine learning models
and thus also work for arbitrary motions, but require full retraining to enroll
new users, which can be prohibitively expensive. In this paper, we propose to
combine the strengths of both approaches by using an embedding-based approach
that leverages deep metric learning. We train the model on a dataset of users
playing the VR game "Half-Life: Alyx" and conduct multiple experiments and
analyses. The results show that the embedding-based method 1) is able to
identify new users from non-specific movements using only a few minutes of
reference data, 2) can enroll new users within seconds, while retraining a
comparable classification-based approach takes almost a day, 3) is more
reliable than a baseline classification-based approach when only little
reference data is available, 4) can be used to identify new users from another
dataset recorded with different VR devices. Altogether, our solution is a
foundation for easily extensible XR user identification systems, applicable
even to non-specific movements. It also paves the way for production-ready
models that could be used by XR practitioners without the requirements of
expertise, hardware, or data for training deep learning models
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Highly resolved observations of trace gases in the lowermost stratosphere and upper troposphere from the Spurt project: an overview
During SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) we performed measurements of a wide range of trace gases with different lifetimes and sink/source characteristics in the northern hemispheric upper troposphere (UT) and lowermost stratosphere (LMS). A large number of in-situ instruments were deployed on board a Learjet 35A, flying at altitudes up to 13.7 km, at times reaching to nearly 380 K potential temperature. Eight measurement campaigns (consisting of a total of 36 flights), distributed over all seasons and typically covering latitudes between 35° N and 75° N in the European longitude sector (10° W–20° E), were performed. Here we present an overview of the project, describing the instrumentation, the encountered meteorological situations during the campaigns and the data set available from SPURT. Measurements were obtained for N2O, CH4, CO, CO2, CFC12, H2, SF6, NO, NOy, O3 and H2O. We illustrate the strength of this new data set by showing mean distributions of the mixing ratios of selected trace gases, using a potential temperature – equivalent latitude coordinate system. The observations reveal that the LMS is most stratospheric in character during spring, with the highest mixing ratios of O3 and NOy and the lowest mixing ratios of N2O and SF6. The lowest mixing ratios of NOy and O3 are observed during autumn, together with the highest mixing ratios of N2O and SF6 indicating a strong tropospheric influence. For H2O, however, the maximum concentrations in the LMS are found during summer, suggesting unique (temperature- and convection-controlled) conditions for this molecule during transport across the tropopause. The SPURT data set is presently the most accurate and complete data set for many trace species in the LMS, and its main value is the simultaneous measurement of a suite of trace gases having different lifetimes and physical-chemical histories. It is thus very well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the UT/LMS, as demonstrated in accompanying and elsewhere published studies
Highly resolved observations of trace gases in the lowermost stratosphere and upper troposphere from the Spurt project: an overview
During SPURT (Spurenstofftransport in der Tropopausenregion, trace gas transport in the tropopause region) we performed measurements of a wide range of trace gases with different lifetimes and sink/source characteristics in the northern hemispheric upper troposphere (UT) and lowermost stratosphere (LMS). A large number of in-situ instruments were deployed on board a Learjet 35A, flying at altitudes up to 13.7 km, at times reaching to nearly 380 K potential temperature. Eight measurement campaigns (consisting of a total of 36 flights), distributed over all seasons and typically covering latitudes between 35° N and 75° N in the European longitude sector (10° W–20° E), were performed. Here we present an overview of the project, describing the instrumentation, the encountered meteorological situations during the campaigns and the data set available from SPURT. Measurements were obtained for N2O, CH4, CO, CO2, CFC12, H2, SF6, NO, NOy, O3 and H2O. We illustrate the strength of this new data set by showing mean distributions of the mixing ratios of selected trace gases, using a potential temperature – equivalent latitude coordinate system. The observations reveal that the LMS is most stratospheric in character during spring, with the highest mixing ratios of O3 and NOy and the lowest mixing ratios of N2O and SF6. The lowest mixing ratios of NOy and O3 are observed during autumn, together with the highest mixing ratios of N2O and SF6 indicating a strong tropospheric influence. For H2O, however, the maximum concentrations in the LMS are found during summer, suggesting unique (temperature- and convection-controlled) conditions for this molecule during transport across the tropopause. The SPURT data set is presently the most accurate and complete data set for many trace species in the LMS, and its main value is the simultaneous measurement of a suite of trace gases having different lifetimes and physical-chemical histories. It is thus very well suited for studies of atmospheric transport, for model validation, and for investigations of seasonal changes in the UT/LMS, as demonstrated in accompanying and elsewhere published studies
Inter-kingdom Signaling by the Legionella Quorum Sensing Molecule LAI-1 Modulates Cell Migration through an IQGAP1-Cdc42-ARHGEF9-Dependent Pathway
Small molecule signaling promotes the communication between bacteria as well as between bacteria and eukaryotes. The opportunistic pathogenic bacterium Legionella pneumophila employs LAI-1 (3-hydroxypentadecane-4-one) for bacterial cell-cell communication. LAI-1 is produced and detected by the Lqs (Legionella quorum sensing) system, which regulates a variety of processes including natural competence for DNA uptake and pathogen-host cell interactions. In this study, we analyze the role of LAI-1 in inter-kingdom signaling. L. pneumophila lacking the autoinducer synthase LqsA no longer impeded the migration of infected cells, and the defect was complemented by plasmid-borne lqsA. Synthetic LAI-1 dose-dependently inhibited cell migration, without affecting bacterial uptake or cytotoxicity. The forward migration index but not the velocity of LAI-1-treated cells was reduced, and the cell cytoskeleton appeared destabilized. LAI-1-dependent inhibition of cell migration involved the scaffold protein IQGAP1, the small GTPase Cdc42 as well as the Cdc42-specific guanine nucleotide exchange factor ARHGEF9, but not other modulators of Cdc42, or RhoA, Rac1 or Ran GTPase. Upon treatment with LAI-1, Cdc42 was inactivated and IQGAP1 redistributed to the cell cortex regardless of whether Cdc42 was present or not. Furthermore, LAI-1 reversed the inhibition of cell migration by L. pneumophila, suggesting that the compound and the bacteria antagonistically target host signaling pathway(s). Collectively, the results indicate that the L. pneumophila quorum sensing compound LAI-1 modulates migration of eukaryotic cells through a signaling pathway involving IQGAP1, Cdc42 and ARHGEF9
T Lymphocytes Influence the Mineralization Process of Bone
Bone is a unique organ able to regenerate itself after injuries. This
regeneration requires the local interplay between different biological systems
such as inflammation and matrix formation. Structural reconstitution is
initiated by an inflammatory response orchestrated by the host immune system.
However, the individual role of T cells and B cells in regeneration and their
relationship to bone tissue reconstitution remain unknown. Comparing bone and
fracture healing in animals with and without mature T and B cells revealed the
essential role of these immune cells in determining the tissue mineralization
and thus the bone quality. Bone without mature T and B cells is stiffer when
compared to wild-type bone thus lacking the elasticity that helps to absorb
forces, thus preventing fractures. In-depth analysis showed dysregulations in
collagen deposition and osteoblast distribution upon lack of mature T and B
cells. These changes in matrix deposition have been correlated with T cells
rather than B cells within this study. This work presents, for the first time,
a direct link between immune cells and matrix formation during bone healing
after fracture. It illustrates specifically the role of T cells in the
collagen organization process and the lack thereof in the absence of T cells
Injection Molding of Magnesium Aluminate Spinel Nanocomposites for High‐Throughput Manufacturing of Transparent Ceramics
Transparent ceramics like magnesium aluminate spinel (MAS) are considered the next step in material evolution showing unmatched mechanical, chemical and physical resistance combined with high optical transparency. Unfortunately, transparent ceramics are notoriously difficult to shape, especially on the microscale. Therefore, a thermoplastic MAS nanocomposite is developed that can be shaped by polymer injection molding at high speed and precision. The nanocomposite is converted to dense MAS by debinding, pre-sintering, and hot isostatic pressing yielding transparent ceramics with high optical transmission up to 84 % and high mechanical strength. A transparent macroscopic MAS components with wall thicknesses up to 4 mm as well as microstructured components with single micrometer resolution are shown. This work makes transparent MAS ceramics accessible to modern high-throughput polymer processing techniques for fast and cost-efficient manufacturing of macroscopic and microstructured components enabling a plethora of potential applications from optics and photonics, medicine to scratch and break-resistant transparent windows for consumer electronics
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