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This study investigated the anaerobic digestion of an algal–bacterial biofilm grown in artificial wastewater in an Algal Turf Scrubber (ATS). The ATS system was located in a greenhouse (50°54′19ʺN, 6°24′55ʺE, Germany) and was exposed to seasonal conditions during the experiment period. The methane (CH4) potential of untreated algal–bacterial biofilm (UAB) and thermally pretreated biofilm (PAB) using different microbial inocula was determined by anaerobic batch fermentation. Methane productivity of UAB differed significantly between microbial inocula of digested wastepaper, a mixture of manure and maize silage, anaerobic sewage sludge, and percolated green waste. UAB using sewage sludge as inoculum showed the highest methane productivity. The share of methane in biogas was dependent on inoculum. Using PAB, a strong positive impact on methane productivity was identified for the digested wastepaper (116.4%) and a mixture of manure and maize silage (107.4%) inocula. By contrast, the methane yield was significantly reduced for the digested anaerobic sewage sludge (50.6%) and percolated green waste (43.5%) inocula. To further evaluate the potential of algal–bacterial biofilm for biogas production in wastewater treatment and biogas plants in a circular bioeconomy, scale-up calculations were conducted. It was found that a 0.116 km2 ATS would be required in an average municipal wastewater treatment plant which can be viewed as problematic in terms of space consumption. However, a substantial amount of energy surplus (4.7–12.5 MWh a−1) can be gained through the addition of algal–bacterial biomass to the anaerobic digester of a municipal wastewater treatment plant. Wastewater treatment and subsequent energy production through algae show dominancy over conventional technologies.
Extension fractures are typical for the deformation under low or no confining pressure. They can be explained by a phenomenological extension strain failure criterion. In the past, a simple empirical criterion for fracture initiation in brittle rock has been developed. In this article, it is shown that the simple extension strain criterion makes unrealistic strength predictions in biaxial compression and tension. To overcome this major limitation, a new extension strain criterion is proposed by adding a weighted principal shear component to the simple criterion. The shear weight is chosen, such that the enriched extension strain criterion represents the same failure surface as the Mohr–Coulomb (MC) criterion. Thus, the MC criterion has been derived as an extension strain criterion predicting extension failure modes, which are unexpected in the classical understanding of the failure of cohesive-frictional materials. In progressive damage of rock, the most likely fracture direction is orthogonal to the maximum extension strain leading to dilatancy. The enriched extension strain criterion is proposed as a threshold surface for crack initiation CI and crack damage CD and as a failure surface at peak stress CP. Different from compressive loading, tensile loading requires only a limited number of critical cracks to cause failure. Therefore, for tensile stresses, the failure criteria must be modified somehow, possibly by a cut-off corresponding to the CI stress. Examples show that the enriched extension strain criterion predicts much lower volumes of damaged rock mass compared to the simple extension strain criterion.
This work is an attempt to answer the question: How to use convex programming in shakedown analysis of structures made of materials with temperature-dependent properties. Based on recently established shakedown theorems and formulations, a dual relationship between upper and lower bounds of the shakedown limit load is found, an algorithmfor shakedown analysis is proposed. While the original problem is neither convex nor concave, the algorithm presented here has the advantage of employing convex programming tools.
The importance of the availability of stored blood or blood cells, respectively, for urgent transfusion cannot be overestimated. Nowadays, blood storage becomes even more important since blood products are used for epidemiological studies, bio-technical research or banked for transfusion purposes. Thus blood samples must not only be processed, stored, and shipped to preserve their efficacy and safety, but also all parameters of storage must be recorded and reported for Quality Assurance. Therefore, blood banks and clinical research facilities are seeking more accurate, automated means for blood storage and blood processing.
The ANM’09 multi-disciplinary scientific program includes topics in the fields of "Nanotechnology and Microelectronics" ranging from "Bio/Micro/Nano Materials and Interfacing" aspects, "Chemical and Bio-Sensors", "Magnetic and Superconducting Devices", "MEMS and Microfluidics" over "Theoretical Aspects, Methods and Modelling" up to the important bridging "Academics meet Industry".
Sleep spindles are neurophysiological phenomena that appear to be linked to memory formation and other functions of the central nervous system, and that can be observed in electroencephalographic recordings (EEG) during sleep. Manually identified spindle annotations in EEG recordings suffer from substantial intra- and inter-rater variability, even if raters have been highly trained, which reduces the reliability of spindle measures as a research and diagnostic tool. The Massive Online Data Annotation (MODA) project has recently addressed this problem by forming a consensus from multiple such rating experts, thus providing a corpus of spindle annotations of enhanced quality. Based on this dataset, we present a U-Net-type deep neural network model to automatically detect sleep spindles. Our model’s performance exceeds that of the state-of-the-art detector and of most experts in the MODA dataset. We observed improved detection accuracy in subjects of all ages, including older individuals whose spindles are particularly challenging to detect reliably. Our results underline the potential of automated methods to do repetitive cumbersome tasks with super-human performance.
Bacterial lipopolysaccharides (endotoxins) show strong biological effects at very low concentrations in human beings and many animals when entering the blood stream. These include affecting structure and function of organs and cells, changing metabolic functions, raising body temperature, triggering the coagulation cascade, modifying hemodynamics and causing septic shock. Because of this toxicity, the removal of even minute amounts is essential for safe parenteral administration of drugs and also for septic shock patients' care. The absence of a general method for endotoxin removal from liquid interfaces urgently requires finding new methods and materials to overcome this gap. Nanostructured carbonized plant parts is a promising material that showed good adsorption properties due to its vast pore network and high surface area. The aim of this study was comparative measurement of endotoxin- and blood proteins-related adsorption rate and adsorption capacity for different carboneous materials produced at different temperatures and under different surface modifications. As a main surface modificator, positively cbarged polymer, polyethileneimine (PEl) was used. Activated carbon materials showed good adsorption properties for LPS and some proteins used in the experiments. During the batch experiments, several techniques (dust removal, autoclaving) were used and optimized for improving the material's adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics. Modification of the surface apparently has not affected hemoglobin binding to the adsorbent's surface. Obtained adsorption isotherms can be used as a powerful tool for designing of future column-based setups for blood purification from LPS, which is especially important for septic shock treatment.
Sustainability is playing an increasingly important role. Not least due to the definition of the sustainable development goals (SDGs) in the framework of the agenda 2030 by the United Nations (UN) in 2015 (United Nations, n.d.), it has become clear that the cooperation of different actors is needed to achieve the defined 17 goals. Industry, as a global actor, has a special role to play in this. In the course of sustainable production processes and chains, the industry is confronted with the responsibility of reflecting on the consequences of its own trade on an ecological, economic, and also social level and deriving measures that, according to the definition of sustainability (Hauff, 1987), will also enable future generations to satisfy their needs. While the ecological pillar of sustainability is already being addressed by different industrial initiatives (Deloitte, 2021), it is questionable to what extent the economic and, above all, the social pillars of sustainability also play a decisive role. Accordingly, it is questionable to what extent sustainability in its triad of social, ecological, and economic aspects is taken into account holistically at all, and thus to what extent the industry contributes to achieving the 17 goals defined by the UN.
This paper presents a qualitative study that explores these questions. Interviewing 31 representatives from the manufacturing industry in Germany, results indicate a Paradox of Sustainable Production expressed by a theoretical reflection of the need for focusing on people in production processes on the one hand and a lack of addressing the social pillar of sustainability in concepts on the other hand. However, while it is a troublesome finding given the striking need for sustainable development (The-Sustainable-Development-Goals-Report-2022; Kropp 2019; von Hauff 2021; Roy and Singh 2017), the paradox directly lays out a path of resolving it. This is because, given its nature, we can see that we could resolve it via the implementation of strong educational efforts trying to help the respective people of the manufacturing industry to understand the holistic and interdependent character of sustainable development (The-Sustainable-Development-Goals-Report-2022).
An optimization method is developed to describe the mechanical behaviour of the human cancellous bone. The method is based on a mixture theory. A careful observation of the behaviour of the bone material leads to the hypothesis that the bone density is controlled by the principal stress trajectories (Wolff’s law). The basic idea of the developed method is the coupling of a scalar value via an eigenvalue problem to the principal stress trajectories. On the one hand this theory will permit a prediction of the reaction of the biological bone structure after the implantation of a prosthesis, on the other hand it may be useful in engineering optimization problems. An analytical example shows its efficiency.
Quantitative nuclear magnetic resonance (qNMR) is considered as a powerful tool for multicomponent mixture analysis as well as for the purity determination of single compounds. Special attention is currently paid to the training of operators and study directors involved in qNMR testing. To assure that only qualified personnel are used for sample preparation at our GxP-accredited laboratory, weighing test was proposed. Sixteen participants performed six-fold weighing of the binary mixture of dibutylated hydroxytoluene (BHT) and 1,2,4,5-tetrachloro-3-nitrobenzene (TCNB). To evaluate the quality of data analysis, all spectra were evaluated manually by a qNMR expert and using in-house developed automated routine. The results revealed that mean values are comparable and both evaluation approaches are free of systematic error. However, automated evaluation resulted in an approximately 20% increase in precision. The same findings were revealed for qNMR analysis of 32 compounds used in pharmaceutical industry. Weighing test by six-fold determination in binary mixtures and automated qNMR methodology can be recommended as efficient tools for evaluating staff proficiency. The automated qNMR method significantly increases throughput and precision of qNMR for routine measurements and extends application scope of qNMR.