Crystal growth and elasticity

The purpose of this paper is to review some elasticity effects in epitaxial growth. We start by a description of the main ingredients needed to describe elasticity effects (elastic interactions, surface stress, bulk and surface elasticity, thermodynamics of stressed solids). Then we describe how bulk and surface elasticity affect growth mode and surface morphology by means of stress-driven instability. At last stress-strain evolution during crystal growth is reported.Comment: 12 page

Long-term periarticular bone adaptation in a feline knee injury model for post-traumatic experimental osteoarthritis

SummaryObjectivesThis study investigates the long-term changes of the periarticular bone, including cancellous bone and the subchondral plate, in an anterior cruciate ligament (ACL)-transected cat for post-traumatic osteoarthritis (OA). These periarticular bone changes are related to the health of all knee tissues including articular cartilage degeneration and may be a key component of osteoarthritic development.MethodsThirteen cats (mean mass 4.9±1.9kg) were divided into three experimental groups: (1) normal controls, (2) 16 week, and (3) 5 year post unilateral ACL-transection (ACLT). Micro-computed tomography was used to scan the three-dimensional (3D) bone architecture of the proximal tibia, and analysis was performed on the subchondral plate and cancellous bone in the epiphyseal and metaphyseal regions of each bone.ResultsA decrease in cancellous bone mass (BV/TV) and subchondral plate thickness (Ct.Th) was observed 16 week post-ACLT, and the trend was statistically significant for the long-term animals (>5 year post-ACLT: BV/TV decreased 16.8%, P<0.003; Ct.Th decreased 36.8%, P<0.03). A decrease in bone mass was also observed as a function of animal age by comparing the young and aged normal control animals, however ACLT intensified those changes, particularly Ct.Th (P<0.009) and anisotropy (P<0.045). It was speculated that decreased internal joint loading despite normal kinematics may play an important role in the long-term reduction of cancellous bone volume and subchondral plate thinning.ConclusionsThe periarticular bone changes measured in this study were concurrent with articular cartilage degeneration, and suggest that bone may be a contributing factor in the aetiology of post-traumatic OA development

The Effect of Marker-less Augmented Reality on Task and Learning Performance

Augmented Reality (AR) technologies have evolved rapidly over the last years, particularly with regard to user interfaces, input devices, and cameras used in mobile devices for object and gesture recognition. While early AR systems relied on pre-defined trigger images or QR code markers, modern AR applications leverage machine learning techniques to identify objects in their physical environments. So far, only few empirical studies have investigated AR\u27s potential for supporting learning and task assistance using such marker-less AR. In order to address this research gap, we implemented an AR application (app)with the aim to analyze the effectiveness of marker-less AR applied in a mundane setting which can be used for on-the-job training and more formal educational settings. The results of our laboratory experiment show that while participants working with AR needed significantly more time to fulfill the given task, the participants who were supported by AR learned significantly more

Three-Dimensional Simulations of Mixing Instabilities in Supernova Explosions

We present the first three-dimensional (3D) simulations of the large-scale mixing that takes place in the shock-heated stellar layers ejected in the explosion of a 15.5 solar-mass blue supergiant star. The outgoing supernova shock is followed from its launch by neutrino heating until it breaks out from the stellar surface more than two hours after the core collapse. Violent convective overturn in the post-shock layer causes the explosion to start with significant asphericity, which triggers the growth of Rayleigh-Taylor (RT) instabilities at the composition interfaces of the exploding star. Deep inward mixing of hydrogen (H) is found as well as fast-moving, metal-rich clumps penetrating with high velocities far into the H-envelope of the star as observed, e.g., in the case of SN 1987A. Also individual clumps containing a sizeable fraction of the ejected iron-group elements (up to several 0.001 solar masses) are obtained in some models. The metal core of the progenitor is partially turned over with Ni-dominated fingers overtaking oxygen-rich bullets and both Ni and O moving well ahead of the material from the carbon layer. Comparing with corresponding 2D (axially symmetric) calculations, we determine the growth of the RT fingers to be faster, the deceleration of the dense metal-carrying clumps in the He and H layers to be reduced, the asymptotic clump velocities in the H-shell to be higher (up to ~4500 km/s for the considered progenitor and an explosion energy of 10^{51} ergs, instead of <2000 km/s in 2D), and the outward radial mixing of heavy elements and inward mixing of hydrogen to be more efficient in 3D than in 2D. We present a simple argument that explains these results as a consequence of the different action of drag forces on moving objects in the two geometries. (abridged)Comment: 15 pages, 8 figures, 30 eps files; significantly extended and more figures added after referee comments; accepted by The Astrophysical Journa

Champion-level drone racing using deep reinforcement learning

First-person view (FPV) drone racing is a televised sport in which professional competitors pilot high-speed aircraft through a 3D circuit. Each pilot sees the environment from the perspective of their drone by means of video streamed from an onboard camera. Reaching the level of professional pilots with an autonomous drone is challenging because the robot needs to fly at its physical limits while estimating its speed and location in the circuit exclusively from onboard sensors. Here we introduce Swift, an autonomous system that can race physical vehicles at the level of the human world champions. The system combines deep reinforcement learning (RL) in simulation with data collected in the physical world. Swift competed against three human champions, including the world champions of two international leagues, in real-world head-to-head races. Swift won several races against each of the human champions and demonstrated the fastest recorded race time. This work represents a milestone for mobile robotics and machine intelligence, which may inspire the deployment of hybrid learning-based solutions in other physical systems

Elaborated Modeling of Synchrotron Motion in Vlasov-Fokker-Planck Solvers

Solving the Vlasov-Fokker-Planck equation is a well-tested approach to simulate dynamics of electron bunches self-interacting with their own wake-field. Typical implementations model the dynamics of a charge density in a damped harmonic oscillator, with a small perturbation due to collective effects. This description imposes some limits to the applicability: Because after a certain simulation time coherent synchrotron motion will be damped down, effectively only the incoherent motion is described. Furthermore – even though computed - the tune spread is typically masked by the use of a charge density instead of individual particles. As a consequence, some effects are not reproduced. In this contribution, we present methods that allow to consider single-particle motion, coherent synchrotron oscillations, non-linearities of the accelerating voltage, higher orders of the momentum compaction factor, as well as modulations of the accelerating voltage. We also provide exemplary studies – based on the KIT storage ring KARA (KArlsruhe Research Accelerator) - to show the potentiality of the methods

Atypically diffuse functional connectivity between caudate nuclei and cerebral cortex in autism

BACKGROUND: Autism is a neurodevelopmental disorder affecting sociocommunicative behavior, but also sensorimotor skill learning, oculomotor control, and executive functioning. Some of these impairments may be related to abnormalities of the caudate nuclei, which have been reported for autism. METHODS: Our sample was comprised of 8 high-functioning males with autism and 8 handedness, sex, and age-matched controls. Subjects underwent functional MRI scanning during performance on simple visuomotor coordination tasks. Functional connectivity MRI (fcMRI) effects were identified as interregional blood oxygenation level dependent (BOLD) signal cross-correlation, using the caudate nuclei as seed volumes. RESULTS: In the control group, fcMRI effects were found in circuits with known participation of the caudate nuclei (associative, orbitofrontal, oculomotor, motor circuits). Although in the autism group fcMRI effects within these circuits were less pronounced or absent, autistic subjects showed diffusely increased connectivity mostly in pericentral regions, but also in brain areas outside expected anatomical circuits (such as visual cortex). CONCLUSION: These atypical connectivity patterns may be linked to developmental brain growth disturbances recently reported in autism and suggest inefficiently organized functional connectivity between caudate nuclei and cerebral cortex, potentially accounting for stereotypic behaviors and executive impairments

PanopticNDT: Efficient and Robust Panoptic Mapping

As the application scenarios of mobile robots are getting more complex and challenging, scene understanding becomes increasingly crucial. A mobile robot that is supposed to operate autonomously in indoor environments must have precise knowledge about what objects are present, where they are, what their spatial extent is, and how they can be reached; i.e., information about free space is also crucial. Panoptic mapping is a powerful instrument providing such information. However, building 3D panoptic maps with high spatial resolution is challenging on mobile robots, given their limited computing capabilities. In this paper, we propose PanopticNDT - an efficient and robust panoptic mapping approach based on occupancy normal distribution transform (NDT) mapping. We evaluate our approach on the publicly available datasets Hypersim and ScanNetV2. The results reveal that our approach can represent panoptic information at a higher level of detail than other state-of-the-art approaches while enabling real-time panoptic mapping on mobile robots. Finally, we prove the real-world applicability of PanopticNDT with qualitative results in a domestic application.Comment: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 202

The relationship between trait procrastination, Internet use, and psychological functioning : results from a community sample of German adolescents

Adolescents with a strong tendency for irrational task delay (i.e., high trait procrastination) may be particularly prone to use Internet applications simultaneously to other tasks (e.g., during homework) and in an insufficiently controlled fashion. Both Internet multitasking and insufficiently controlled Internet usage may thus amplify the negative mental health implications that have frequently been associated with trait procrastination. The present study explored this role of Internet multitasking and insufficiently controlled Internet use for the relationship between trait procrastination and impaired psychological functioning in a community sample of N = 818 early and middle adolescents. Results from multiple regression analyses indicate that trait procrastination was positively related to Internet multitasking and insufficiently controlled Internet use. Insufficiently controlled Internet use, but not Internet multitasking, was found to partially statistically mediate the association between trait procrastination and adolescents’ psychological functioning (i.e., stress, sleep quality, and relationship satisfaction with parents). The study underlines that adolescents with high levels of trait procrastination may have an increased risk for negative outcomes of insufficiently controlled Internet use