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This book is based on a multimedia course for biological and chemical engineers, which is designed to trigger students' curiosity and initiative. A solid basic knowledge of thermodynamics and kinetics is necessary for understanding many technical, chemical, and biological processes.
The one-semester basic lecture course was divided into 12 workshops (chapters). Each chapter covers a practically relevant area of physical chemistry and contains the following didactic elements that make this book particularly exciting and understandable:
- Links to Videos at the start of each chapter as preparation for the workshop
- Key terms (in bold) for further research of your own
- Comprehension questions and calculation exercises with solutions as learning checks
- Key illustrations as simple, easy-to-replicate blackboard pictures
Humorous cartoons for each workshop (by Faelis) additionally lighten up the text and facilitate the learning process as a mnemonic. To round out the book, the appendix includes a summary of the most popular experiments in basic physical chemistry courses, as well as suggestions for designing workshops with exhibits, experiments, and "questions of the day."
Suitable for students minoring in chemistry; chemistry majors are sure to find this slimmed-down, didactically valuable book helpful as well. The book is excellent for self-study.
In times of social climate protection movements, such as Fridays for Future, the priorities of society, industry and higher education are currently changing. The consideration of sustainability challenges is increasing. In the context of sustainable development, social skills are crucial to achieving the United Nations Sustainable Development Goals (SDGs). In particular, the impact that educational activities have on people, communities and society is therefore coming to the fore. Research has shown that people with high levels of social competence are better able to manage stressful situations, maintain positive relationships and communicate effectively. They are also associated with better academic performance and career success. However, especially in engineering programs, the social pillar is underrepresented compared to the environmental and economic pillars.
In response to these changes, higher education institutions should be more aware of their social impact - from individual forms of teaching to entire modules and degree programs. To specifically determine the potential for improvement and derive resulting change for further development, we present an initial framework for social impact measurement by transferring already established approaches from the business sector to the education sector. To demonstrate the applicability, we measure the key competencies taught in undergraduate engineering programs in Germany.
The aim is to prepare the students for success in the modern world of work and their future contribution to sustainable development. Additionally, the university can include the results in its sustainability report. Our method can be applied to different teaching methods and enables their comparison.
Amino acid-based surfactants are valuable compounds for cosmetic formulations. The chemical synthesis of acyl-amino acids is conventionally performed by the Schotten-Baumann reaction using fatty acyl chlorides, but aminoacylases have also been investigated for use in biocatalytic synthesis with free fatty acids. Aminoacylases and their properties are diverse; they belong to different peptidase families and show differences in substrate specificity and biocatalytic potential. Bacterial aminoacylases capable of synthesis have been isolated from Burkholderia, Mycolicibacterium, and Streptomyces. Although several proteases and peptidases from S. griseus have been described, no aminoacylases from this species have been identified yet. In this study, we investigated two novel enzymes produced by S. griseus DSM 40236ᵀ . We identified and cloned the respective genes and recombinantly expressed an α-aminoacylase (EC 3.5.1.14), designated SgAA, and an ε-lysine acylase (EC 3.5.1.17), designated SgELA, in S. lividans TK23. The purified aminoacylase SgAA was biochemically characterized, focusing on its hydrolytic activity to determine temperature- and pH optima and stabilities. The aminoacylase could hydrolyze various acetyl-amino acids at the Nα -position with a broad specificity regarding the sidechain. Substrates with longer acyl chains, like lauroyl-amino acids, were hydrolyzed to a lesser extent. Purified aminoacylase SgELA specific for the hydrolysis of Nε -acetyl-L-lysine was unstable and lost its enzymatic activity upon storage for a longer period but could initially be characterized. The pH optimum of SgELA was pH 8.0. While synthesis of acyl-amino acids was not observed with SgELA, SgAA catalyzed the synthesis of lauroyl-methionine.
Exposure to prolonged periods in microgravity is associated with deconditioning of the musculoskeletal system due to chronic changes in mechanical stimulation. Given astronauts will operate on the Lunar surface for extended periods of time, it is critical to quantify both external (e.g., ground reaction forces) and internal (e.g., joint reaction forces) loads of relevant movements performed during Lunar missions. Such knowledge is key to predict musculoskeletal deconditioning and determine appropriate exercise countermeasures associated with extended exposure to hypogravity.
This paper introduces an inexpensive Wiegand-sensor-based rotary encoder that avoids rotating magnets and is suitable for electrical-drive applications. So far, Wiegand-sensor-based encoders usually include a magnetic pole wheel with rotating permanent magnets. These encoders combine the disadvantages of an increased magnet demand and a limited maximal speed due to the centripetal force acting on the rotating magnets. The proposed approach reduces the total demand of permanent magnets drastically. Moreover, the rotating part is manufacturable from a single piece of steel, which makes it very robust and cheap. This work presents the theoretical operating principle of the proposed approach and validates its benefits on a hardware prototype. The presented proof-of-concept prototype achieves a mechanical resolution of 4.5 ° by using only 4 permanent magnets, 2Wiegand sensors and a rotating steel gear wheel with 20 teeth.
With the prevalence of glucosamine- and chondroitin-containing dietary supplements for people with osteoarthritis in the marketplace, it is important to have an accurate and reproducible analytical method for the quantitation of these compounds in finished products. NMR spectroscopic method based both on low- (80 MHz) and high- (500–600 MHz) field NMR instrumentation was established, compared and validated for the determination of chondroitin sulfate and glucosamine in dietary supplements. The proposed method was applied for analysis of 20 different dietary supplements. In the majority of cases, quantification results obtained on the low-field NMR spectrometer are similar to those obtained with high-field 500–600 MHz NMR devices. Validation results in terms of accuracy, precision, reproducibility, limit of detection and recovery demonstrated that the developed method is fit for purpose for the marketed products. The NMR method was extended to the analysis of methylsulfonylmethane, adulterant maltodextrin, acetate and inorganic ions. Low-field NMR can be a quicker and cheaper alternative to more expensive high-field NMR measurements for quality control of the investigated dietary supplements. High-field NMR instrumentation can be more favorable for samples with complex composition due to better resolution, simultaneously giving the possibility of analysis of inorganic species such as potassium and chloride.
AI-based systems are nearing ubiquity not only in everyday low-stakes activities but also in medical procedures. To protect patients and physicians alike, explainability requirements have been proposed for the operation of AI-based decision support systems (AI-DSS), which adds hurdles to the productive use of AI in clinical contexts. This raises two questions: Who decides these requirements? And how should access to AI-DSS be provided to communities that reject these standards (particularly when such communities are expert-scarce)? This chapter investigates a dilemma that emerges from the implementation of global AI governance. While rejecting global AI governance limits the ability to help communities in need, global AI governance risks undermining and subjecting health-insecure communities to the force of the neo-colonial world order. For this, this chapter first surveys the current landscape of AI governance and introduces the approach of relational egalitarianism as key to (global health) justice. To discuss the two horns of the referred dilemma, the core power imbalances faced by health-insecure collectives (HICs) are examined. The chapter argues that only strong demands of a dual strategy towards health-secure collectives can both remedy the immediate needs of HICs and enable them to become healthcare independent.
Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis.
Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine.
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).