Outdoor Measurements of Leaf Water Content Using THz Quasi Time-Domain Spectroscopy

We report the first outdoor measurements for continuous in vivo leaf-water monitoring using THz spectroscopy. For this, we have developed a compact and portable THz quasi time-domain spectrometer which can be powered by a battery. We monitor the water status of a corn plant (Zea mays) and discuss the influence of the day-night variations of the outdoor temperature.     

Visual Analysis of Governing Topological Structures in Excitable Network Dynamics

To understand how topology shapes the dynamics in excitable networks is one of the fundamental problems in network science when applied to computational systems biology and neuroscience. Recent advances in the field discovered the influential role of two macroscopic topological structures, namely hubs and modules. We propose a visual analytics approach that allows for a systematic exploration of the role of those macroscopic topological structures on the dynamics in excitable networks. Dynamical patterns are discovered using the dynamical features of excitation ratio and co‐activation. Our approach is based on the interactive analysis of the correlation of topological and dynamical features using coordinated views. We designed suitable visual encodings for both the topological and the dynamical features. A degree map and an adjacency matrix visualization allow for the interaction with hubs and modules, respectively. A barycentric‐coordinates layout and a multi‐dimensional scaling approach allow for the analysis of excitation ratio and co‐activation, respectively. We demonstrate how the interplay of the visual encodings allows us to quickly reconstruct recent findings in the field within an interactive analysis and even discovered new patterns. We apply our approach to network models of commonly investigated topologies as well as to the structural networks representing the connectomes of different species. We evaluate our approach with domain experts in terms of its intuitiveness, expressiveness, and usefulness.     

Foveated Real‐Time Ray Tracing for Head‐Mounted Displays

Head‐mounted displays with dense pixel arrays used for virtual reality applications require high frame rates and low latency rendering. This forms a challenging use case for any rendering approach. In addition to its ability of generating realistic images, ray tracing offers a number of distinct advantages, but has been held back mainly by its performance. In this paper, we present an approach that significantly improves image generation performance of ray tracing. This is done by combining foveated rendering based on eye tracking with reprojection rendering using previous frames in order to drastically reduce the number of new image samples per frame. To reproject samples a coarse geometry is reconstructed from a G‐Buffer. Possible errors introduced by this reprojection as well as parts that are critical to the perception are scheduled for resampling. Additionally, a coarse color buffer is used to provide an initial image, refined smoothly by more samples were needed. Evaluations and user tests show that our method achieves real‐time frame rates, while visual differences compared to fully rendered images are hardly perceivable. As a result, we can ray trace non‐trivial static scenes for the Oculus DK2 HMD at 1182 × 1464 per eye within the the VSync limits without perceived visual differences.     

Defect Modulation Doping

The doping of semiconductor materials is a fundamental part of modern technology, but the classical approaches have in many cases reached their limits both in regard to achievable charge carrier density as well as mobility. Modulation doping, a mechanism that exploits the energy band alignment at an interface between two materials to induce free charge carriers in one of them, is shown to circumvent the mobility restriction. Due to an alignment of doping limits by intrinsic defects, however, the carrier density limit cannot be lifted using this approach. Here, a novel doping strategy using defects in a wide bandgap material to dope the surface of a second semiconductor layer of dissimilar nature is presented. It is shown that by depositing an insulator on a semiconductor material, the conductivity of the layer stack can be increased by 7 orders of magnitude, without the necessity of high‐temperature processes or epitaxial growth. This approach has the potential to circumvent limits to both carrier mobility and density, opening up new possibilities in semiconductor device fabrication, particularly for the emerging field of oxide thin film electronics.     

Illumination‐driven Mesh Reduction for Accelerating Light Transport Simulations

Progressive light transport simulations aspire a physically‐based, consistent rendering to obtain visually appealing illumination effects, depth and realism. Thereby, the handling of large scenes is a difficult problem, as in typical scene subdivision approaches the parallel processing requires frequent synchronization due to the bouncing of light throughout the scene. In practice, however, only few object parts noticeably contribute to the radiance observable in the image, whereas large areas play only a minor role. In fact, a mesh simplification of the latter can go unnoticed by the human eye. This particular importance to the visible radiance in the image calls for an output‐sensitive mesh reduction that allows to render originally out‐of‐core scenes on a single machine without swapping of memory. Thus, in this paper, we present a preprocessing step that reduces the scene size under the constraint of radiance preservation with focus on high‐frequency effects such as caustics. For this, we perform a small number of preliminary light transport simulation iterations. Thereby, we identify mesh parts that contribute significantly to the visible radiance in the scene, and which we thus preserve during mesh reduction.     

Spectroscopic Indications of Tunnel Barrier Charging as the Switching Mechanism in Memristive Devices

Resistive random access memory is a promising, energy‐efficient, low‐power “storage class memory” technology that has the potential to replace both flash storage and on‐chip dynamic memory. While the most widely employed systems exhibit filamentary resistive switching, interface‐type switching systems based on a tunable tunnel barrier are of increasing interest. They suffer less from the variability induced by the stochastic filament formation process and the choice of the tunnel barrier thickness offers the possibility to adapt the memory device current to the given circuit requirements. Heterostructures consisting of a yttria‐stabilized zirconia (YSZ) tunnel barrier and a praseodymium calcium manganite (PCMO) layer are employed. Instead of spatially localized filaments, the resistive switching process occurs underneath the whole electrode. By employing a combination of electrical measurements, in operando hard X‐ray photoelectron spectroscopy and electron energy loss spectroscopy, it is revealed that an exchange of oxygen ions between PCMO and YSZ causes an electrostatic modulation of the effective height of the YSZ tunnel barrier and is thereby the underlying mechanism for resistive switching in these devices.     

A Fluorescent RNA Forced‐Intercalation Probe as a Pan‐Selective Marker for Influenza A Virus Infection

The influenza A virus (IAV) genome is segmented into eight viral ribonucleoproteins, each expressing a negatively oriented viral RNA (vRNA). Along the infection cycle, highly abundant single‐stranded small viral RNAs (svRNA) are transcribed in a segment‐specific manner. The sequences of svRNAs and of the vRNA 5′‐ends are identical and highly conserved among all IAV strains. Here, we demonstrate that these sequences can be used as a target for a pan‐selective sensor of IAV infection. To this end, we used a complementary fluorescent forced‐intercalation RNA (IAV QB‐FIT) probe with a single locked nucleic acid substitution to increase brightness. We demonstrated by fluorescence in situ hybridization (FISH) that this probe is suitable and easy to use to detect infection of different cell types by a broad variety of avian, porcine, and human IAV strains, but not by other influenza virus types. IAV QB‐FIT also provides a useful tool to characterize different infection states of the host cell.     

Synthesis,photodegradation, and energy transfer in a series of poly(ethylene terephthalate–co–2,6-naphthalenedicarboxylate) copolymers

Triplet–triplet energy transfer has been shown to occur from poly(ethylene terephthalate) (PET) units to the 2,6-naphthalenedicarboxylate (2,6-ND) monomer units in a series of poly(ethylene terephthalate–co–2,6-naphthalenedicarboxylate) (PET–2,6-ND) copolymers, as filament yarns, by an exchange mechanism at 77°K. The radius of the “quenching sphere” has been calculated to be 19.7 Å, indicating the presence of triplet energy migration. Photostabilization was observed in the copolymer yarns with the concentration of the monomer dimethyl 2,6-naphthalenedicarboxylate (2,6-DMN) at or above 2 mol %; the rate of phototendering in an air atmosphere was shown to decrease from 2.0 × 10^?19% breaking strength loss/quantum absorbed/cm² in the homopolymer PET to 0.7 × 10^?19% breaking strength loss/quantum absorbed/cm² in the copolymer yarns. The photophysical processes in the monomers, dimethyl terephthalate and 2,6-DMN, were examined by absorption and luminescence studies. The lowest excited singlet and triplet in both monomers were identified to be the ¹(π, π^*) and ³(π, π^*) states, respectively. The phosphorescence of PET was shown to originate from a ³(π, π^*) state, while the complex fluorescence spectrum may arise from some oriented aggregates in the polymer matrix. In copolymer yarns, only the fluorescence emission from the 2,6-ND monomer units at 380 nm was observed. The phosphorescence spectra of the copolymer yarns showed phosphorescence emissions from the PET and 2,6-ND monomer units; in addition, delayed fluorescence from the 2,6-ND monomer was also observed.     

Visual Analysis of Time‐Series Similarities for Anomaly Detection in Sensor Networks

We present a system to analyze time‐series data in sensor networks. Our approach supports exploratory tasks for the comparison of univariate, geo‐referenced sensor data, in particular for anomaly detection. We split the recordings into fixed‐length patterns and show them in order to compare them over time and space using two linked views. Apart from geo‐based comparison across sensors we also support different temporal patterns to discover seasonal effects, anomalies and periodicities. The methods we use are best practices in the information visualization domain. They cover the daily, the weekly and seasonal and patterns of the data. Daily patterns can be analyzed in a clustering‐based view, weekly patterns in a calendar‐based view and seasonal patters in a projection‐based view. The connectivity of the sensors can be analyzed through a dedicated topological network view. We assist the domain expert with interaction techniques to make the results understandable. As a result, the user can identify and analyze erroneous and suspicious measurements in the network. A case study with a domain expert verified the usefulness of our approach.