Open Access

In Germany, administrative specifications must be strictly observed for N (nitrogen) and P (phosphorus) fertilization. There are several factors need to be taken into account when calculating nutrient fertilizer levels. The main calculation factor for the nutrient amounts for N, P and K (potassium) is the expected yield respectively a 3-year yield average. Furthermore, the soil nutrient contents have to be considered when calculating the P and K fertilizer quantities. Possible remaining harvest residues (for example, straw from the previous harvest) including the P and K values within these residues have to be subtracted from the current P and K fertilizer values.

This study presents a life cycle assessment (LCA) comparing laying hen to broiler chicken production. Sustainability and protein conversion efficiency are considered. The protein-to-protein conversion was calculated per 1t of feed protein consumed by birds and per 1 kg of protein in end products for human consumption. Additionally, a part of the commercial feed was replaced by live black soldier fly larvae, reared on Gainesville diet, and fruit and vegetable waste (FVW). Results of the LCA showed significant differences in integrated impacts between different production systems and different chicken feeds but not between different insect feeds. The most environmentally friendly scenario is insect (FVW) fed broiler. In protein conversion efficiency (PCE) assessment, laying hen production achieved better PCE than broiler chicken when protein quality is considered. Main influencing factors on results were feed production, composition, and protein content. Due to many assumptions made, results should be viewed critically.

Alloy 400 is a corrosion-resistant, NiCu-based material which is used in numerous industrial applications, especially in marine environments and the high-temperature chemical industry. As conventional manufacturing limits geometrical complexity, additive manufacturing (AM) of the present alloy system promises great potential. For this purpose, a robust process chain, consisting of powder production via gas atomization and a design of experiment (DoE) approach for laser powder bed fusion (LPBF), was developed. With a narrow particle size distribution, powders were found to be spherical, flowable, consistent in chemical composition, and, hence, generally applicable to the LPBF process. Copper segregations at grain boundaries were clearly detected in powders. For printed parts instead, low-intensity micro-segregations at cell walls were discovered, being correlated with the iterative thermal stress applied to solidified melt-pool-near grains during layer-by-layer manufacturing. For the production of nearly defect-free LPBF structures, DoE suggested a single optimum parameter set instead of a broad energy density range. The latter key figure was found to be misleading in terms of part densities, making it an outdated tool in modern, software-based process parameter optimization. On the microscale, printed parts showed an orientation of melt pools along the build direction with a slight crystallographic [101] texture. Micro-dendritic structures were detected on the nanoscale being intersected by a high number of dislocations. Checked against hot-extruded reference material, the LPBF variant performed better in terms of strength while lacking in ductility, being attributed to a finer grain structure and residual porosity, respectively.

Networked sensors are strategically deployed to gather real-world data, thereby facilitating the implementation of cutting-edge technologies like the Internet of Things (IoT) and Cyber Physical Systems (CPS). These devices, tailored to specific use-cases, often operate under strict resource constraints and must function optimally for extended periods. Concurrently, the sensitive data they collect must be safeguarded against unauthorized access, necessitating robust security measures. A range of security mechanisms is available to IoT system designers, with cryptographic algorithms, such as symmetric and asymmetric encryption, and hash functions being the cornerstone. They can select from multiple algorithm implementations and adjust configuration parameters to suit the device’s capabilities. However, determining the ideal configuration is a complex task, requiring a balance between security effectiveness and efficient resource utilization. While the security aspect is continually assessed by experts, the impact of these choices on resource consumption, particularly across diverse platforms, often receives less attention. This paper introduces an objective evaluation method that assesses not only the effect of different security algorithms, but also various implementations and configuration adjustments on the resource consumption across different platforms. To facilitate this, a composite performance indicator is computed, enabling the systematic ranking of candidate configurations. The approach bridges the gap in understanding the interplay between security measures and resource management in the realm of IoT devices.