Static analysis and process model transformation for an advanced business process to Petri net mapping

Verification of business processes typically relies on Petri net–based process models. While they allow for natural modeling and analysis of aspects such as parallelism and message exchange, such a process model is seldom complete and precise. This is mainly because the available techniques for deriving a Petri net model from the original model neglect process data in favor of feasible verification. In this paper, we present an approach for deriving more precise process models by leveraging a process‐to‐Petri‐net compiler, which takes as input a business process and generates as output a Petri net model for the process. This can be subsequently used for verification. However, in contrast to a conventional compiler, our compiler's objective is not to create the most efficient code but rather to produce a most precise but still effectively verifiable Petri net–based process model.     

Assessing two large area burnt area products across Australian Southern Forests

Burnt area is a critical parameter for estimating emissions of greenhouse gases associated with biomass burning. Several burnt area products (BAPs) derived from Earth Observation satellites/sensors have been released; these are based on different spatial resolutions and derived using different methodologies so that accuracies can vary amongst them. This study validates a global (MODIS) and a national (AVHRR) BAP across Australian southern forests using two reference datasets: state fire histories (SFHs) from 2000 to 2013 and a forest cover map derived through high resolution air photo interpretation (API). The spatial and temporal agreement between fires in the BAPs and reference SFH were analysed based on 2610 sample points representative of Australian southern forest types (successful detection was evaluated according to fire type: planned burn vs. wildfire, size of fire, and land tenure). Results show that both BAPs were most successful when identifying large wildfires (>5000 ha). Overall accuracy for AVHRR and MODIS was 73.9% and 62.5%, respectively. When compared to the API derived forest cover map as reference dataset, both products achieved higher overall accuracies (94.1% for AVHRR and 87.1% for MODIS); an expected result given that the fires detected in this dataset are known to be observable using Earth observation data. But regardless of reference dataset, the AVHRR BAP which is tailored to Australian conditions achieved better results than the MODIS global BAP. Also, the AVHRR archive in Australia goes back to 1988, which is an important consideration for calculating wildfire history for greenhouse gas accounting.     

Zebrafish Embryos Allow Prediction of Nanoparticle Circulation Times in Mice and Facilitate Quantification of Nanoparticle–Cell Interactions

The zebrafish embryo is a vertebrate well suited for visualizing nanoparticles at high resolution in live animals. Its optical transparency and genetic versatility allow noninvasive, real‐time observations of vascular flow of nanoparticles and their interactions with cells throughout the body. As a consequence, this system enables the acquisition of quantitative data that are difficult to obtain in rodents. Until now, a few studies using the zebrafish model have only described semiquantitative results on key nanoparticle parameters. Here, a MACRO dedicated to automated quantitative methods is described for analyzing important parameters of nanoparticle behavior, such as circulation time and interactions with key target cells, macrophages, and endothelial cells. Direct comparison of four nanoparticle (NP) formulations in zebrafish embryos and mice reveals that data obtained in zebrafish can be used to predict NPs' behavior in the mouse model. NPs having long or short blood circulation in rodents behave similarly in the zebrafish embryo, with low circulation times being a consequence of NP uptake into macrophages or endothelial cells. It is proposed that the zebrafish embryo has the potential to become an important intermediate screening system for nanoparticle research to bridge the gap between cell culture studies and preclinical rodent models such as the mouse.     

CuZr-based bulk metallic glass and glass matrix composites fabricated by selective laser melting

Monolithic bulk metallic glass and glass matrix composites with a relative density above 98 ％ were produced by processing Cu46Zr46Al8 (at.％) via selective laser melting (SLM).Their microstructures and mechanical properties were systematically examined.B2 CuZr nanocrystals (30-100 nm in diameter) are uniformly dispersed in the glassy matrix when SLM is conducted at an intermediate energy input.These B2 CuZr nanocrystals nucleate the oxygen-stabilized big cube phase during a remelting step.The presence of these nanocrystals increases the structural heterogeneity as indirectly revealed by mircrohardness and nanoindentation measurements.The corresponding maps in combination with calorimetric data indicate that the glassy phase is altered by the processing conditions.Despite the formation of crystals and a high overall free volume content,all additively manufactured samples fail at lower stress than the as-cast glass and without any plastic strain.The inherent brittleness is attributed to the presence of relatively large pores and the increased oxygen content after selective laser melting.     

Carbon‐Quantum‐Dots‐Loaded Ruthenium Nanoparticles as an Efficient Electrocatalyst for Hydrogen Production in Alkaline Media

Highly active, stable, and cheap Pt‐free catalysts for the hydrogen evolution reaction (HER) are facing increasing demand as a result of their potential use in future energy‐conversion systems. However, the development of HER electrocatalysts with Pt‐like or even superior activity, in particular ones that can function under alkaline conditions, remains a significant challenge. Here, the synthesis of a novel carbon‐loaded ruthenium nanoparticle electrocatalyst (Ru@CQDs) for the HER, using carbon quantum dots (CQDs), is reported. Electrochemical tests reveal that, even under extremely alkaline conditions (1 m KOH), the as‐formed Ru@CQDs exhibits excellent catalytic behavior with an onset overpotential of 0 mV, a Tafel slope of 47 mV decade^?1, and good durability. Most importantly, it only requires an overpotential of 10 mV to achieve the current density of 10 mA cm^?2. Such catalytic characteristics are superior to the current commercial Pt/C and most noble metals, non‐noble metals, and nonmetallic catalysts under basic conditions. These findings open a new field for the application of CQDs and add to the growing family of metal@CQDs with high HER performance.     

Coupling resolved and coarse-grain DEM models

The discrete element method (DEM) is a well-established approach to study granular flows in numerous fields of application; however, the DEM is a computationally demanding method. Thus, simulations of industrial scale systems are hardly feasible on today’s hardware. This situation is typically resolved by limiting the simulation domain or introducing a coarse-grain model. While the former approach does not provide information of the full system, the latter is especially problematic in systems, where geometric restrictions are in the range of particle size, so both are insufficient to adequately describe large-scale processes. To overcome this problem, we propose a novel technique that efficiently combines resolved and coarse-grain DEM models. The method is designed to capture the details of the granular system in spatially confined regions of interest while retaining the benefits of the coarse-grain model where a lower resolution is sufficient. To this end, our method establishes two-way coupling between resolved and coarse-grain parts by volumetric passing of boundary conditions.     

Josephson Effect in the Micron and Submicron YBCO Constrictions Fabricated Using the Femtosecond Laser Technique

A femtosecond laser was used successfully to fabricate planar micron and submicron-sized constrictiontype Josephson junctions on YBa₂Cu₃O_7?x thin films. A simple program using G-code (control systems) programming language was written to control the movement of the sample stage during the etching process. The constriction’s geometry was investigated using both atomic force microscopy (AFM) and scanning electron microscopy (SEM). Electrical transport measurements were performed at different temperatures. Shapiro steps were observed and analyzed. The micron-sized constriction shows a linear relationship for the measured critical current against the temperature which is consistent with the behavior of an S–s’–Stype Josephson junction where “S” stands for a bulk superconductive material that is untouched by the laser and “s”’ is superconducting material whose critical temperature is lower than the value of “S” In the case of the narrower submicronsized constriction, the measured critical current dependence with temperature shows an exponential decay, which is consistent with the behavior of the long S–N–Stype Josephson junction where “N” stands for a normal material. A model is proposed to describe the observed behavior by considering the effect of sample heating during the constriction’s fabrication.     

Fluorescent Diarylethene Photoswitches—A Universal Tool for Super‐Resolution Microscopy in Nanostructured Materials

Super‐resolution fluorescence microscopy allows for unprecedented in situ visualization of biological structures, but its application to materials science has so far been comparatively limited. One of the main reasons is the lack of powerful dyes that allow for labeling and photoswitching in materials science systems. In this study it is shown that appropriate substitution of diarylethenes bearing a fluorescent closed and dark open form paves the way for imaging nanostructured materials with three of the most popular super‐resolution fluorescence microscopy methods that are based on different concepts to achieve imaging beyond the diffraction limit of light. The key to obtain optimal resolution lies in a proper control over the photochemistry of the photoswitches and its adaption to the system to be imaged. It is hoped that the present work will provide researchers with a guide to choose the best photoswitch derivative for super‐resolution microscopy in materials science, just like the correct choice of a Swiss Army Knife's tool is essential to fulfill a given task.     

Design and Characterisation of Titanium Nitride Subarrays of Kinetic Inductance Detectors for Passive Terahertz Imaging

We report on the investigation of titanium nitride (TiN) thin films deposited via atomic layer deposition (ALD) for microwave kinetic inductance detectors (MKID). Using our in-house ALD process, we have grown a sequence of TiN thin films (thickness 15, 30, 60 nm). The films have been characterised in terms of superconducting transition temperature \(T_\mathrm{c}\), sheet resistance \(R_\mathrm{s}\) and microstructure. We have fabricated test resonator structures and characterised them at a temperature of 300 mK. At 350 GHz, we report an optical noise equivalent power \(\hbox {NEP}_\mathrm{opt} \approx 2.3\times 10^{-15}~\hbox {W}/\sqrt{\hbox {Hz}}\), which is promising for passive terahertz imaging applications.     

Modelling the Performance of Single-Photon Counting Kinetic Inductance Detectors

We present the first published results of near-infrared single-photon detection in aluminium lumped element kinetic inductance detectors (LEKIDs). Using aluminium as a well-understood material that follows conventional superconductor theory, we discuss and validate a model that describes the energy-resolving performance of a LEKID to single-photon absorption events. We also discuss data analysis techniques used to extract single-photon detections from noisy data. We measure an energy resolution of 662 meV for a 1550 nm photon source which is in close agreement to our model predictions for this non-optimised device limited by generation–recombination noise.