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From the perspective of manufacturing companies, the political, media and economic discourse on decarbonisation in the recent years manifests itself as an increasing social expectation of action. In Germany, in particular, this discourse is also being driven forward by powerful companies, respectively sectors, most notably the automotive industry. Against this background, the present paper examines how German manufacturing companies react to rising societal pressure and emerging policies. It examines which measures the companies have taken or plan to take to reduce their carbon footprint, which aspirations are associated with this and the structural characteristics (company size, energy intensity, and sector) by which these are influenced. A mix methods approach is applied, utilising data gathered from approx. 900 companies in context of the Energy Efficiency Index of German Industry (EEI), along with media research focusing on the announced decarbonisation plans and initiatives. We demonstrate that one-size-serves-all approaches are not suitable to decarbonise industry, as the situation and ambitions differ considerably depending on size, energy intensity and sector. Even though the levels of ambition and urgency are high, micro and energy intensive companies, in particular, are challenged. The present research uncovers a series of questions that call for attention to materialise the ambitions and address the challenges outlined.
The physicochemical properties of synthetically produced bone substitute materials (BSM) have a major impact on biocompatibility. This affects bony tissue integration, osteoconduction, as well as the degradation pattern and the correlated inflammatory tissue responses including macrophages and multinucleated giant cells (MNGCs). Thus, influencing factors such as size, special surface morphologies, porosity, and interconnectivity have been the subject of extensive research. In the present publication, the influence of the granule size of three identically manufactured bone substitute granules based on the technology of hydroxyapatite (HA)-forming calcium phosphate cements were investigated, which includes the inflammatory response in the surrounding tissue and especially the induction of MNGCs (as a parameter of the material degradation). For the in vivo study, granules of three different size ranges (small = 0.355–0.5 mm; medium = 0.5–1 mm; big = 1–2 mm) were implanted in the subcutaneous connective tissue of 45 male BALB/c mice. At 10, 30, and 60 days post implantationem, the materials were explanted and histologically processed. The defect areas were initially examined histopathologically. Furthermore, pro- and anti-inflammatory macrophages were quantified histomorphometrically after their immunohistochemical detection. The number of MNGCs was quantified as well using a histomorphometrical approach. The results showed a granule size-dependent integration behavior. The surrounding granulation tissue has passivated in the groups of the two bigger granules at 60 days post implantationem including a fibrotic encapsulation, while a granulation tissue was still present in the group of the small granules indicating an ongoing cell-based degradation process. The histomorphometrical analysis showed that the number of proinflammatory macrophages was significantly increased in the small granules at 60 days post implantationem. Similarly, a significant increase of MNGCs was detected in this group at 30 and 60 days post implantationem. Based on these data, it can be concluded that the integration and/or degradation behavior of synthetic bone substitutes can be influenced by granule size.
Polymeric micelle-like nanoparticles have demonstrated effectiveness for the delivery of some poorly soluble or hydrophobic anticancer drugs. In this study, a hydrophobic moiety, deoxycholic acid (DCA) was first bonded on a polysaccharide, chitosan (CS), for the preparation of amphiphilic chitosan (CS-DCA), which was further modified with a cationic glycidyltrimethylammounium chloride (GTMAC) to form a novel soluble chitosan derivative (HT-CS-DCA). The cationic amphiphilic HT-CS-DCA was easily self-assembled to micelle-like nanoparticles about 200 nm with narrow size distribution (PDI 0.08–0.18). The zeta potential of nanoparticles was in the range of 14 to 24 mV, indicating higher positive charges. Then, doxorubicin (DOX), an anticancer drug with poor solubility, was entrapped into HT-CS-DCA nanoparticles. The DOX release test was performed in PBS (pH 7.4) at 37 °C, and the results showed that there was no significant burst release in the first two hours, and the cumulative release increased steadily and slowly in the following hours. HT-CS-DCA nanoparticles loaded with DOX could easily enter into MCF-7 cells, as observed by a confocal microscope. As a result, DOX-loaded HT-CS-DCA nanoparticles demonstrated a significant inhibition activity on MCF-7 growth without obvious cellular toxicity in comparison with blank nanoparticles. Therefore, the anticancer efficacy of these cationic HT-CS-DCA nanoparticles showed great promise for the delivery of DOX in cancer therapy.
Energy efficiency optimization techniques for steady state operation of induction machines are the state-of-the-art, and many methods have already been developed. However, many real-world industrial and electric vehicle applications cannot be considered to be in steady state operation. The focus of this contribution is on the efficiency optimization of induction machines in dynamic operation. Online dynamic operation is challenging due to the computational complexity and the required low sample times in an inverter. An offline optimization is therefore conducted to gain knowledge. Based on this offline optimal solution, a simple and easy to implement template based solution is developed. This approach aims at replicating the solution found by the offline optimization by resembling the shape and anticipative characteristics of the optimal flux trajectory. The energy efficiency improvement of the template based solution is verified by simulations and measurements on a test bench and using a real-world drive cycle scenario. For comparison, a model predictive numerical online optimization is investigated too.