Foray search: An effective systematic dispersal strategy in fragmented landscapes

In the absence of evidence to the contrary, population models generally assume that the dispersal trajectories of animals are random, but systematic dispersal could be more efficient at detecting new habitat and may therefore constitute a more realistic assumption. Here, we investigate, by means of simulations, the properties of a potentially widespread systematic dispersal strategy termed "foray search." Foray search was more efficient in detecting suitable habitat than was random dispersal in most landscapes and was less subject to energetic constraints. However, it also resulted in considerably shorter net dispersed distances and higher mortality per net dispersed distance than did random dispersal, and it would therefore be likely to lead to lower dispersal rates toward the margins of population networks. Consequently, the use of foray search by dispersers could crucially affect the extinction-colonization balance of metapopulations and the evolution of dispersal rates. We conclude that population models need to take the dispersal trajectories of individuals into account in order to make reliable predictions

DLCSS: Dynamic Longest Common Subsequences

Autonomous driving is a key technology towards a brighter, more sustainable future. To enable such a future, it is necessary to utilize autonomous vehicles in shared mobility models. However, to evaluate, whether two or more route requests have the potential for a shared ride, is a compute-intensive task, if done by rerouting. In this work, we propose the Dynamic Longest Common Subsequences algorithm for fast and cost-efficient comparison of two routes for their compatibility, dynamically only incorporating parts of the routes which are suited for a shared trip. Based on this, one can also estimate, how many autonomous vehicles might be necessary to fulfill the local mobility demands. This can help providers to estimate the necessary fleet sizes, policymakers to better understand mobility patterns and cities to scale necessary infrastructure

Experiments on Anomaly Detection in Autonomous Driving by Forward-Backward Style Transfers

Great progress has been achieved in the community of autonomous driving in the past few years. As a safety-critical problem, however, anomaly detection is a huge hurdle towards a large-scale deployment of autonomous vehicles in the real world. While many approaches, such as uncertainty estimation or segmentation-based image resynthesis, are extremely promising, there is more to be explored. Especially inspired by works on anomaly detection based on image resynthesis, we propose a novel approach for anomaly detection through style transfer. We leverage generative models to map an image from its original style domain of road traffic to an arbitrary one and back to generate pixelwise anomaly scores. However, our experiments have proven our hypothesis wrong, and we were unable to produce significant results. Nevertheless, we want to share our findings, so that others can learn from our experiments

Multimodal Detection of Unknown Objects on Roads for Autonomous Driving

Tremendous progress in deep learning over the last years has led towards a future with autonomous vehicles on our roads. Nevertheless, the performance of their perception systems is strongly dependent on the quality of the utilized training data. As these usually only cover a fraction of all object classes an autonomous driving system will face, such systems struggle with handling the unexpected. In order to safely operate on public roads, the identification of objects from unknown classes remains a crucial task. In this paper, we propose a novel pipeline to detect unknown objects. Instead of focusing on a single sensor modality, we make use of lidar and camera data by combining state-of-the art detection models in a sequential manner. We evaluate our approach on the Waymo Open Perception Dataset and point out current research gaps in anomaly detection

Fabrication technology for high light-extraction ultraviolet thin-film flip-chip (UV TFFC) LEDs grown on SiC

The light output of deep ultraviolet (UV-C) AlGaN light-emitting diodes (LEDs) is limited due to their poor light extraction efficiency (LEE). To improve the LEE of AlGaN LEDs, we developed a fabrication technology to process AlGaN LEDs grown on SiC into thin-film flip-chip LEDs (TFFC LEDs) with high LEE. This process transfers the AlGaN LED epi onto a new substrate by wafer-to-wafer bonding, and by removing the absorbing SiC substrate with a highly selective SF6 plasma etch that stops at the AlN buffer layer. We optimized the inductively coupled plasma (ICP) SF6 etch parameters to develop a substrate-removal process with high reliability and precise epitaxial control, without creating micromasking defects or degrading the health of the plasma etching system. The SiC etch rate by SF6 plasma was ~46 \mu m/hr at a high RF bias (400 W), and ~7 \mu m/hr at a low RF bias (49 W) with very high etch selectivity between SiC and AlN. The high SF6 etch selectivity between SiC and AlN was essential for removing the SiC substrate and exposing a pristine, smooth AlN surface. We demonstrated the epi-transfer process by fabricating high light extraction TFFC LEDs from AlGaN LEDs grown on SiC. To further enhance the light extraction, the exposed N-face AlN was anisotropically etched in dilute KOH. The LEE of the AlGaN LED improved by ~3X after KOH roughening at room temperature. This AlGaN TFFC LED process establishes a viable path to high external quantum efficiency (EQE) and power conversion efficiency (PCE) UV-C LEDs.Comment: 22 pages, 6 figures. (accepted in Semiconductor Science and Technology, SST-105156.R1 2018

Simulation and optimisation of terahertz emission from InGaAs and InP photoconductive switches

We simulate the terahertz emission from laterally-biased InGaAs and InP using a three-dimensional carrier dynamics model in order to optimise the semiconductor material. Incident pump-pulse parameters of current Ti:Sapphire and Er:fibre lasers are chosen, and the simulation models the semiconductor's bandstructure using parabolic Gamma, L and X valleys, and heavy holes. The emitted terahertz radiation is propagated within the semiconductor and into free space using a model based on the Drude-Lorentz dielectric function. As the InGaAs alloy approaches InAs an increase in the emitted power is observed, and this is attributed to a greater electron mobility. Additionally, low-temperature grown and ion-implanted InGaAs are modelled using a finite carrier trapping time. At sub-picosecond trapping times the terahertz bandwidth is found to increase significantly at the cost of a reduced emission power.Comment: 9 pages, 7 figure

Exceptionally Slow Rise in Differential Reflectivity Spectra of Excitons in GaN: Effect of Excitation-induced Dephasing

Femtosecond pump-probe (PP) differential reflectivity spectroscopy (DRS) and four-wave mixing (FWM) experiments were performed simultaneously to study the initial temporal dynamics of the exciton line-shapes in GaN epilayers. Beats between the A-B excitons were found \textit{only for positive time delay} in both PP and FWM experiments. The rise time at negative time delay for the differential reflection spectra was much slower than the FWM signal or PP differential transmission spectroscopy (DTS) at the exciton resonance. A numerical solution of a six band semiconductor Bloch equation model including nonlinearities at the Hartree-Fock level shows that this slow rise in the DRS results from excitation induced dephasing (EID), that is, the strong density dependence of the dephasing time which changes with the laser excitation energy.Comment: 8 figure

All-electrical creation and control of spin-galvanic signal in graphene and molybdenum ditelluride heterostructures at room temperature

The ability to engineer new states of matter and control their spintronic properties by electric fields is at the heart of future information technology. Here, we report a gate-tunable spin-galvanic effect in van der Waals heterostructures of graphene with a semimetal of molybdenum ditelluride at room temperature due to an efficient spin-charge conversion process. Measurements in different device geometries with control over the spin orientations exhibit spin-switch and Hanle spin precession behavior, confirming the spin origin of the signal. The control experiments with the pristine graphene channels do not show any such signals. We explain the experimental spin-galvanic signals by theoretical calculations considering the spin-orbit induced spin-splitting in the bands of the graphene in the heterostructure. The calculations also reveal an unusual spin texture in graphene heterostructure with an anisotropic out-of-plane and in-plane spin polarization. These findings open opportunities to utilize graphene-based heterostructures for gate-controlled spintronic devices

Zinc Gallate Spinel Dielectric Function, Band-to-Band Transitions, and Γ-Point Effective Mass Parameters

We determine the dielectric function of the emerging ultrawide bandgap semiconductor ZnGa2O4 from the near-infrared (0.75 eV) into the vacuum ultraviolet (8.5 eV) spectral regions using spectroscopic ellipsometry on high quality single crystal substrates. We perform density functional theory calculations and discuss the band structure and the Brillouin zone Γ-point band-to-band transition energies, their transition matrix elements, and effective band mass parameters. We find an isotropic effective mass parameter (0.24me) at the bottom of the Γ-point conduction band, which equals the lowest valence band effective mass parameter at the top of the highly anisotropic and degenerate valence band (0.24me). Our calculated band structure indicates the spinel ZnGa2O4 is indirect, with the lowest direct transition at the Γ-point. We analyze the measured dielectric function using critical-point line shape functions for a three-dimensional, M0-type van Hove singularity, and we determine the direct bandgap with an energy of 5.27(3) eV. In our model, we also consider contributions from Wannier–Mott type excitons with an effective Rydberg energy of 14.8 meV. We determine the near-infrared index of refraction from extrapolation (1.91) in very good agreement with results from recent infrared ellipsometry measurements (√ε∞=1.94) [M. Stokey, Appl. Phys. Lett. 117, 052104 (2020)]