Therkildsenwinters2024

Finally, the future directions for the metamaterials-based HMI applications are outlined and discussed.Electronic and geometric structures of Y, La and Lu complexes with porphyrazine (Pz) and tetrakis(1,2,5-thiadiazole)porphyrazine (TTDPz) were investigated by density functional theory (DFT) calculations and compared. The nature of the bonds between metal atoms and nitrogen atoms has been described using the analysis of the electron density distribution in the frame of Bader's quantum theory of atoms in molecule (QTAIM). Simulation and interpretation of electronic spectra were performed with use of time-dependent density functional theory (TDDFT) calculations. Description of calculated IR spectra was carried out based on the analysis of the distribution of the potential energy of normal vibrations by natural vibrational coordinates.Traffic congestion is, on a daily basis, responsible for a significant amount of economic and social costs. One of the critical examples is the obstruction of priority vehicles during fast trajectories, which potentially costs lives and property in case of delay that is too great. By means of visual sensing methods, solutions and schedules have already been proposed for adjusting traffic light sequences depending on a priority vehicle's position. However, these mechanisms are computation and power intensive. Deploying and powering a large-scale network will have a crucial economical cost. Furthermore, these devices will not always have access to sufficient power. To provide a solution, we developed an acoustic and self-powered device that can detect priority vehicles and can be cost effectively deployed to define a sensor network. The device combines the detection of priority vehicles and the harvesting of sound energy through triboelectrification. This paper will introduce the use of triboelectric energy harvesting, specifically in a self-powered wireless sensor network for priority vehicle detection. Furthermore, it shows how to increase the power performance of such a generator. Finally, the results are analyzed.Vehicle-to-everything (V2X) communication is seen as one of the main enabling technologies for automated vehicles. Collective perception is especially promising, as it allows connected traffic participants to "see through the eyes of others" by sharing sensor-detected objects via V2X communication. Its benefit is typically assessed in terms of the increased object update rate, redundancy, and awareness. To determine the safety improvement thanks to collective perception, the authors introduce new metrics, which quantify the environmental risk awareness of the traffic participants. The performance of the V2X service is then analyzed with the help of the test platform TEPLITS, using real traffic traces from German highways, amounting to over 100 h of total driving time. The results in the considered scenarios clearly show that collective perception not only contributes to the accuracy and integrity of the vehicles' environmental perception, but also that a V2X market penetration of at least 25% is necessary to increase traffic safety from a "risk of serious traffic accidents" to a "residual hypothetical risk of collisions without minor injuries" for traffic participants equipped with non-redundant 360° sensor systems. These results support the ongoing worldwide standardization efforts of the collective perception service.There is a huge potential for nutrient recovery from organic waste materials for soil fertility restoration as well as negative environmental emission mitigation. Previous research has found vermicomposting the optimal choice for converting organic waste into beneficial organic fertilizer while reducing reactive N loss. However, a great deal of the processes of greenhouse gases (GHG) and ammonia volatilization during vermicomposting are not well-documented. selleck A field vermicomposting experiment was conducted by deploying earthworms (Eisenia fetida) with three types of agricultural by-products-namely, cow manure (VCM), pig manure (VPM), and biochar (VBC)-and crop (maize) residues compared with traditional composting (COM) without earthworms in the Sichuan Basin, China. Results showed that vermicomposting caused a decrease in electrical conductivity (EC) and total organic carbon (TOC) while increasing total nitrogen (TN). The greatest TN increase was found with VCM. The cumulative NH3 volatilization in COM, VCM, VPM, and VBC during experimental duration was 9.00, 8.02, 15.16, and 8.91 kg N ha-1, respectively. The cumulative CO2 emissions in COM, VCM, VPM, and VBC were 2369, 2814, 3435, and 2984 (g·C·m-2), while for CH4, they were 0.36, 0.28, 4.07, and 0.19 (g·C·m-2) and, for N2O, they were 0.12, 0.06, 0.76, and 0.04 (g·N m-2), respectively. Lower emissions of N2O, CH4, and NH3 were observed in VBC. We concluded that earthworms, as ecological engineers, enhanced reactive nutrients and reduced ammonia volatilization during vermicomposting in our test system. Overall, vermicomposting is proposed as an eco-friendly, sustainable technique that helps to reduce environmental impacts and associated health risks.Gathering data and monitoring performance are at the heart of energy efficiency and comfort securing strategies in smart buildings. Therefore, it is crucial to present the obtained data to the user or administrator of such a building in an appropriate form. Moreover, evaluating the data in real time not only helps to maintain comfort, but also allows for a timely response from the user or operator to a possible fault. Continuous online monitoring and analysis of process behaviour, which is referred to as advanced supervision, is addressed in this paper by developing a procedure that will form an artificial operator autonomously supervising process. After introducing several techniques that are used for signal analysis, we propose an approach to advanced supervision of processes in smart buildings or other industrial control systems. The developed procedure is implemented on a control system platform that is particularly suitable for this purpose. Moreover, this platform includes a framework that provides support for the implementation of advanced control techniques and it is based on open-source tools, which is rarely seen in industrial applications.