Automatic Generation of Coherent Image Galleries in Virtual Reality

With the rapidly increasing size of digitized and born-digital multimedia collections in archives, museums and private collections, manually curating collections becomes a nearly impossible task without disregarding large parts of the collection. In this paper, we propose the use of Self-Organizing Maps (SOMs) to automatically generate coherent image galleries that allow intuitive, user-driven exploration of large multimedia collections in virtual reality (VR). We extend the open-source VR museum VIRTUE to support such exhibitions and apply it on different collections using various image features. A successful pilot test took place at the Basel Historical Museum with more than 300 participants

Learning-based Calibration of Flux Crosstalk in Transmon Qubit Arrays

Superconducting quantum processors comprising flux-tunable data and coupler qubits are a promising platform for quantum computation. However, magnetic flux crosstalk between the flux-control lines and the constituent qubits impedes precision control of qubit frequencies, presenting a challenge to scaling this platform. In order to implement high-fidelity digital and analog quantum operations, one must characterize the flux crosstalk and compensate for it. In this work, we introduce a learning-based calibration protocol and demonstrate its experimental performance by calibrating an array of 16 flux-tunable transmon qubits. To demonstrate the extensibility of our protocol, we simulate the crosstalk matrix learning procedure for larger arrays of transmon qubits. We observe an empirically linear scaling with system size, while maintaining a median qubit frequency error below $300$ kHz

FPGA-Based Smart Sensor for Online Displacement Measurements Using a Heterodyne Interferometer

The measurement of small displacements on the nanometric scale demands metrological systems of high accuracy and precision. In this context, interferometer-based displacement measurements have become the main tools used for traceable dimensional metrology. The different industrial applications in which small displacement measurements are employed requires the use of online measurements, high speed processes, open architecture control systems, as well as good adaptability to specific process conditions. The main contribution of this work is the development of a smart sensor for large displacement measurement based on phase measurement which achieves high accuracy and resolution, designed to be used with a commercial heterodyne interferometer. The system is based on a low-cost Field Programmable Gate Array (FPGA) allowing the integration of several functions in a single portable device. This system is optimal for high speed applications where online measurement is needed and the reconfigurability feature allows the addition of different modules for error compensation, as might be required by a specific application

Ambient and substrate energy influence decomposer diversity differentially across trophic levels

The species-energy hypothesis predicts increasing biodiversity with increasing energy in ecosystems. Proxies for energy availability are often grouped into ambient energy (i.e., solar radiation) and substrate energy (i.e., non-structural carbohydrates or nutritional content). The relative importance of substrate energy is thought to decrease with increasing trophic level from primary consumers to predators, with reciprocal effects of ambient energy. Yet, empirical tests are lacking. We compiled data on 332,557 deadwood-inhabiting beetles of 901 species reared from wood of 49 tree species across Europe. Using host-phylogeny-controlled models, we show that the relative importance of substrate energy versus ambient energy decreases with increasing trophic levels: the diversity of zoophagous and mycetophagous beetles was determined by ambient energy, while non-structural carbohydrate content in woody tissues determined that of xylophagous beetles. Our study thus overall supports the species-energy hypothesis and specifies that the relative importance of ambient temperature increases with increasing trophic level with opposite effects for substrate energy

Ambient and substrate energy influence decomposer diversity differentially across trophic levels.

The species-energy hypothesis predicts increasing biodiversity with increasing energy in ecosystems. Proxies for energy availability are often grouped into ambient energy (i.e., solar radiation) and substrate energy (i.e., non-structural carbohydrates or nutritional content). The relative importance of substrate energy is thought to decrease with increasing trophic level from primary consumers to predators, with reciprocal effects of ambient energy. Yet, empirical tests are lacking. We compiled data on 332,557 deadwood-inhabiting beetles of 901 species reared from wood of 49 tree species across Europe. Using host-phylogeny-controlled models, we show that the relative importance of substrate energy versus ambient energy decreases with increasing trophic levels: the diversity of zoophagous and mycetophagous beetles was determined by ambient energy, while non-structural carbohydrate content in woody tissues determined that of xylophagous beetles. Our study thus overall supports the species-energy hypothesis and specifies that the relative importance of ambient temperature increases with increasing trophic level with opposite effects for substrate energy

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

G-protein signaling: back to the future

Heterotrimeric G-proteins are intracellular partners of G-protein-coupled receptors (GPCRs). GPCRs act on inactive Gα·GDP/Gβγ heterotrimers to promote GDP release and GTP binding, resulting in liberation of Gα from Gβγ. Gα·GTP and Gβγ target effectors including adenylyl cyclases, phospholipases and ion channels. Signaling is terminated by intrinsic GTPase activity of Gα and heterotrimer reformation — a cycle accelerated by ‘regulators of G-protein signaling’ (RGS proteins). Recent studies have identified several unconventional G-protein signaling pathways that diverge from this standard model. Whereas phospholipase C (PLC) β is activated by Gαq and Gβγ, novel PLC isoforms are regulated by both heterotrimeric and Ras-superfamily G-proteins. An Arabidopsis protein has been discovered containing both GPCR and RGS domains within the same protein. Most surprisingly, a receptor-independent Gα nucleotide cycle that regulates cell division has been delineated in both Caenorhabditis elegans and Drosophila melanogaster. Here, we revisit classical heterotrimeric G-protein signaling and explore these new, non-canonical G-protein signaling pathways

The impact of human expert visual inspection on the discovery of strong gravitational lenses

We investigate the ability of human ’expert’ classifiers to identify strong gravitational lens candidates in Dark Energy Survey like imaging. We recruited a total of 55 people that completed more than 25% of the project. During the classification task, we present to the participants 1489 images. The sample contains a variety of data including lens simulations, real lenses, non-lens examples, and unlabeled data. We find that experts are extremely good at finding bright, well-resolved Einstein rings, whilst arcs with g-band signal-to-noise less than ∼25 or Einstein radii less than ∼1.2 times the seeing are rarely recovered. Very few non-lenses are scored highly. There is substantial variation in the performance of individual classifiers, but they do not appear to depend on the classifier’s experience, confidence or academic position. These variations can be mitigated with a team of 6 or more independent classifiers. Our results give confidence that humans are a reliable pruning step for lens candidates, providing pure and quantifiably complete samples for follow-up studies