Nanolithography for metallic quasi crystals for nanobio applications

There is currently an urgent need to develop micro and nanotechnique for the fabrications of quasi periodic crystals in a plane for the study and applications of novel optical properties when light propagating in or through such a photonic structures with fold symmetries (10 fold symmetry in this work). It has been clear that quasi periodical crystals in dielectrics with various fold symmetries also exhibits complete photonic band gap (PBG) property as periodical photonic crystals do. However, the novel physical properties related to the interactions of electromagnetic waves with metallic holes arrays in quasi periodical order (metallic quasi crystals) is being discovered both theoretically and experimentally, which demands technical development for the construction of theoretically designed structures. [1] In this work, we report a nanofabrication technique recently developed for the replication of quasi crystal in 100 nm Al on a slab (quartz wafer in this work) by electron beam lithography using chemically amplified resist, UVN-30. A wealth of novel photonic behaviours of lights vertically incident through the q-crystal were observed

Neural Volumetric Blendshapes: Computationally Efficient Physics-Based Facial Blendshapes

Computationally weak systems and demanding graphical applications are still mostly dependent on linear blendshapes for facial animations. The accompanying artifacts such as self-intersections, loss of volume, or missing soft tissue elasticity can be avoided by using physics-based animation models. However, these are cumbersome to implement and require immense computational effort. We propose neural volumetric blendshapes, an approach that combines the advantages of physics-based simulations with realtime runtimes even on consumer-grade CPUs. To this end, we present a neural network that efficiently approximates the involved volumetric simulations and generalizes across human identities as well as facial expressions. Our approach can be used on top of any linear blendshape system and, hence, can be deployed straightforwardly. Furthermore, it only requires a single neutral face mesh as input in the minimal setting. Along with the design of the network, we introduce a pipeline for the challenging creation of anatomically and physically plausible training data. Part of the pipeline is a novel hybrid regressor that densely positions a skull within a skin surface while avoiding intersections. The fidelity of all parts of the data generation pipeline as well as the accuracy and efficiency of the network are evaluated in this work. Upon publication, the trained models and associated code will be released

Asymmetric transmission of light through a planar chiral metamaterial

We report that normal incidence transmission of circularly polarized light through lossy anisotropic planar chiral meta-material is asymmetric for opposite directions. The new effect is fundamentally distinct from conventional gyrotropy of bulk chiral media and the Faraday Effect

At loggerheads : an examination of afforestation as a climate change prevention tool and environmental policy : a 60-credit Journalism project presented in partial fulfilment of the requirements for the degree of Master of Journalism at Massey University, New Zealand

This project examines the impacts of afforestation as a policy tool for mitigating climate change. Additionally, it examines the New Zealand media coverage of the One Billion Trees programme, and how this is influenced by access to sources and the use of framing. It will explore the programme’s tensions between farming and forestry, and native versus exotic tree planting and its implications as a policy to address climate change

Es wächst zusammen, was zusammengehört‘.: Die Konzeptualisierung von Narrativität und Performativität als wesentliche Konstituenten des Theaters in Jan Horstmanns Theaternarratologie

Jan Horstmann: Theaternarratologie. Ein erzähltheoretisches Analyseverfahren für Theaterinszenierungen. Berlin / New York: de Gruyter 2018 (= Narratologia Bd. 64). 275 S. EUR 89,95. ISBN 978-3-11-059500-

Neural Deformable Cone Beam CT

In oral and maxillofacial cone beam computed tomography (CBCT), patient motion is frequently observed and, if not accounted for, can severely affect the usability of the acquired images. We propose a highly flexible, data driven motion correction and reconstruction method which combines neural inverse rendering in a CBCT setting with a neural deformation field. We jointly optimize a lightweight coordinate based representation of the 3D volume together with a deformation network. This allows our method to generate high quality results while accurately representing occurring patient movements, such as head movements, separate jaw movements or swallowing. We evaluate our method in synthetic and clinical scenarios and are able to produce artefact-free reconstructions even in the presence of severe motion. While our approach is primarily developed for maxillofacial applications, we do not restrict the deformation field to certain kinds of motion. We demonstrate its flexibility by applying it to other scenarios, such as 4D lung scans or industrial tomography settings, achieving state-of-the art results within minutes with only minimal adjustments

An Open-World Extension to Knowledge Graph Completion Models

We present a novel extension to embedding-based knowledge graph completion models which enables them to perform open-world link prediction, i.e. to predict facts for entities unseen in training based on their textual description. Our model combines a regular link prediction model learned from a knowledge graph with word embeddings learned from a textual corpus. After training both independently, we learn a transformation to map the embeddings of an entity's name and description to the graph-based embedding space. In experiments on several datasets including FB20k, DBPedia50k and our new dataset FB15k-237-OWE, we demonstrate competitive results. Particularly, our approach exploits the full knowledge graph structure even when textual descriptions are scarce, does not require a joint training on graph and text, and can be applied to any embedding-based link prediction model, such as TransE, ComplEx and DistMult.Comment: 8 pages, accepted to AAAI-201

Near-field polarization conversion in planar chiral nanostructures

Enantiomeric-sensitive optical polarization conversion has been observed in the near-field above a planar chiral nanostructures consisting of an array of gammadions cut in a metal film. Formation of the far-field scattered light rotated with respect to the incident linear polarized light has been visualized