Bio Forschung Austria

This paper presents the concept of a tool (Information System Factory) which uses a Fourth Generation Language ($\mathbf{4 G L}$) environment for the production of Information Systems in an agile Software Development Style (RAD: Rapid Application Development). The production process follows the principle of a factory, which assembles the final product by reusing already developed components and adding new components either by in house development or by acquiring external components (Component Based Development). The final system follows a three layer architecture (MVC: Model View Control) separating Data Base (Model) Management, User Interaction (View), and Programming (Control). Modern Micro Computers can be used to execute this “4GL-RAD-Tool” locally on user’s premises or in the field (powered by a battery) without the need of accessing facilities in a global network (cloud). The power of a low cost, energy saving Single Board Computer (SBC) is enough e.g. for developing and running business information systems using this tool. SBCs are frequently used in embedded Systems, which interact with sensors and actuators to control physical processes. Since SBCs can be equipped with large storage devices, there is no need in many cases to use programs in the cloud for the further on processing of big data. A realization of this 4GL-RAD Tool is based on an INFORMIX-4GL compatible system, which is available as an open source productivity tool. The System provides a menu driven IDE, which supports a standard System Development Life Cycle (SDLC) as linear or iterative model. The different phases of the SDLC are delivering various artifacts like User Requirement Documents, Code, and Software User Manuals, which can be enhanced by using Artificial Intelligence (AI). Restricting the system development to classes like Business Administration, Cultural Heritage, IoT-Computing to name a few, can support the development process by introducing “domain ontologies” in the “DevOps"-Environment. The development of a Sensor Network provides a practical example in the field of Mechatronic Engineering.

Abstract Wireworms within the genus Agriotes (Coleoptera: Elateridae) can cause substantial damage to agricultural crops. The vertical movements of these pest insects in the soil make the timing of control measures a difficult task. The forecast model SIMAGRIO‐W utilizes soil temperature and moisture data to predict the migration of Agriotes wireworms to the upper soil layer. The model distinguishes between two risk levels: low risk (less than 30% of the wireworm population in the upper soil layer) and high risk (more than 30%), which are considered adequate for practical purposes. In German field sites, the model demonstrated an 80% success rate across four soil types. The SIMAGRIO‐W model was tested under the warm and dry climate in eastern Austria. The validation process revealed an overall accuracy of just 46%, primarily due to the fact that SIMAGRIO‐W assumes a maximum activity level for wireworms at 11°C. However, high activity levels were observed at soil temperatures of up to 26°C at the experimental sites. The discrepancy in the prediction power of the model between the German and Austrian field sites may be explained by differences in temperature tolerance between the Agriotes species occurring in eastern Austria (e.g. A. ustulatus) and in western Germany (e.g. A. obscurus). Our findings demonstrate that the thermal preferences of different wireworm species must be taken into account to make the SIMAGRIO‐W model a widely applicable decision support tool for predicting vertical movements of Agriotes wireworms.

Global climate change is a significant environmental concern, and reducing greenhouse gas emissions is crucial to mitigating this issue. Moreover, there is a need to exploit a prediction-based method to assess the future requirements of applications and (re-)schedule them with the aim of reducing completion time and energy consumption. Therefore, we consider the stochastic requirements of users and investigate an Energy-aware Prediction-based scheduling of dataflow processing on the cloud, fog, and edge method, named EPreMatch, for microservice scaling by applying a machine learning (ML) model based on gradient boosting regression (GBR) and scheduling due to ranking and matching game principles. Firstly, EPreMatch predicts the number of microservice replicas using GBR. Then, the ranking method orders the microservice replicas and devices based on completion times and energy consumption. Thereafter, the EPreMatch schedules microservice replicas requiring dataflow processing on computing devices. Experimental analysis reveals lower completion times, energy consumption, and CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> emission compared to a related prediction-based scheduling method.

Abstract. Ecological stoichiometry examines the balance and ratios of multiple elements in ecological processes. In shrubs, characterized by their adaptability to extreme environments such as alpine and arid, stoichiometric traits likely differ from those in trees and grasses, reflecting unique ecological adaptations of shrubs. However, this hypothesis remains underexplored. Here we review the state of the art of stoichiometry in shrubs and then identify research hotspots of shrub stoichiometry. Then, we summarize the effects of climate, soil properties, phylogeny, ontogenetic differences, and human activities on stoichiometry of shrub leaves. In addition, we compared the stoichiometry of shrublands with that of forests and grasslands. The development process of shrubland stoichiometry research can be roughly divided into three main periods: the initial development stage (before 2010), the fast development stage (2011–2018), and the high-quality development stage (from 2019 to the present), with the two turning points occurring in 2011 and 2019 possibly related to the launch of major projects associated with shrublands in China. Current studies predominantly focus on shrub leaves, with limited attention to stems, roots, and seeds. Mean values of C, N, P, C:N, and N:P in shrub leaves globally were 454.66 mg g⁻¹, 18.93 mg g⁻¹, 1.20 mg g⁻¹, 23.4, and 15.8, respectively. Shrub leaf N and P content were higher than those of trees and lower than herbs, while C content and C:N ratio showed opposite trends. N and P content correlated positively with soil nutrients and precipitation and negatively with temperature. Functional types also influenced stoichiometry, with deciduous and leguminous shrub species showing higher N and P content than evergreen and non-leguminous shrubs. Overall, shrubs showed C and N content intermediate between trees and grasses, while P content was similar across life forms. Higher N:P ratios in shrublands and grasslands suggest stronger P limitation than in forests. Future studies should integrate above- and below-ground stoichiometry, consider phylogenetic influences, and investigate evolutionary processes to better understand shrubland adaptation and formation mechanisms under global change.

• Straightforward preparation of crystalline NH 4 + 6:2 fluorotelomer sulfonate. • Unique hydrogen bonding network provides extraordinary physicochemical stability. • Affordable volumetric primary standard for PFAS trace analysis. • Ideal PFOS- and PFOA proxy for screening PFAS remediation sorbents. • Convenient starting material for related salts of 6:2 fluorotelomer sulfonic acid. Alkali salts of the common fluorosurfactant 3,3,4,4,5,5,6,6,7,7,8,8,8-tridecafluoro-1-octanesulfonic acid ( 6:2 FTSA ) exhibit a remarkably low solubility in water, which enables the precipitation of these salts from water. The same applies for the corresponding ammonium salt 6:2 FTS NH 4 which can be obtained in crystalline form by slowly adding aqueous ammonia to an aqueous solution of FTSA . To understand the cause of this behavior on a molecular basis, an X-ray single crystal structure determination of 6:2 FTS NH 4 was performed, allowing to further examine the molecular interactions in the solid state responsible for its low solubility. A hydrogen-bonded layer structure results from four distinct N‒H···O interactions, that involve all four NH groups, the given ammonium ion and sulfonate-O atoms belonging to four different anion units. Columns of parallel aligned fluoroalkyl chains dominate the packing of molecules in the crystal. The characterization was accompanied by thermal as well as spectroscopic analysis. The lack of hygroscopicity and its high thermal stability make 6:2 FTS NH 4 a suitable gravimetric standard substance for analytical applications. HPLC MS/MS measurements showed that 6:2 FTS NH 4 can adequately substitute commercial 13 C labelled compounds at least for routine analysis of common perfluorinated contaminants using standard internal calibration.

Increasingly Findable, Accessible, Reusable and Interoperable (FAIR) nanomaterials environmental health and safety (nanoEHS) data and demoncratised access to nanoinformatics models will directly support 12 SDGs and indireclty benefit the other 5 SDGs.

Staphylococcus aureus is a human and animal pathogen as well as a commensal bacterium. It can be a causative agent of severe, life-threatening infections with high mortality, e.g., toxic shock syndrome, septic shock, and multi-organ failure. S. aureus strains secrete a number of toxins. Exotoxins/enterotoxins are considered important in the pathogenesis of the above-mentioned conditions. Exotoxins, e.g., superantigen toxins, cause uncontrolled and polyclonal T cell activation and unregulated activation of inflammatory cytokines. Here we show the importance of genomic analysis of infectious strains in order to identify disease-causing exotoxins. Further, we show through functional analysis of superantigenic properties of staphylococcal exotoxins that even very small amounts of a putative superantigenic contaminant can have a significant mitogenic effect. The results show expression and production of two distinct staphylococcal exotoxins, SEC and SEL, in several strains from clinical isolates. Antibodies against both toxins are required to neutralise the superantigenic activity of staphylococcal supernatants and purified staphylococcal toxins.