The 50 most recently published documents
Manufacturing companies are forced to operate in an increasingly volatile and unpredictabl environment. The number of events that can have a potentially critical impact on a production system‘s economic performance have significantly increased. This forces companies to invest considerably more in flexible and robust production systems capable of withstanding a certain amount of change however unable to quantify the benefits in advance. The satisfactory quantification and assessment of these qualities – Flexibility and Robustness –has not been realized yet. This paper discusses commonality between Flexibility and Robustness and offers a new approach to connect changes in the environment with the elements of a production system and thus quantifying its flexibility and robustness.
This paper presents initial findings from aeroelastic studies conducted on a wing-propeller model, aimed at evaluating the impact of aerodynamic interactions on wing flutter mechanisms and overall aeroelastic performance. Utilizing a frequency domain method, the flutter onset within a specified flight speed range is assessed. Mid-fidelity tools with a time domain approach are then used to account for the complex aerodynamic interaction between the propeller and the wing. Specifically, open-source software DUST and MBDyn are leveraged for this purpose. This investigation covers both windmilling and thrusting conditions of the wing-propeller model. During the trim process, adjustments to the collective pitch of the blades are made to ensure consistency across operational points. Time histories are then analyzed to pinpoint flutter onset, and corresponding frequencies and damping ratios are meticulously identified. The results reveal a marginal destabilizing effect of aerodynamic interaction on flutter speed, approximately 5%. Notably, the thrusting condition demonstrates a greater destabilizing influence compared to windmilling. These comprehensive findings enhance the understanding of the aerodynamic behavior of such systems and offer valuable insights for early design predictions and the development of streamlined models for future endeavors.
This paper deals with the problem of determining the optimal capacity of concentrated solar power (CSP) plants, especially in the context of hybrid solar power plants. This work presents an innovative analytical approach to optimizing the capacity of concentrated solar plants. The proposed method is based on the use of additional non-dimensional parameters, in particular, the design factor and the solar multiple factor. This paper presents a mathematical optimization model that focuses on the capacity of concentrated solar power plants where thermal storage plays a key role in the energy source. The analytical approach provides a more complete understanding of the design process for hybrid power plants. In addition, the use of additional factors and the combination of the proposed method with existing numerical methods allows for more refined optimization, which allows for the more accurate selection of the capacity for specific geographical conditions. Importantly, the proposed method significantly increases the speed of computation compared to that of traditional numerical methods. Finally, the authors present the results of the analysis of the proposed system of equations for calculating the levelized cost of electricity (LCOE) for hybrid solar power plants. The nonlinearity of the LCOE on the main calculation parameters is shown
This paper presents initial findings from aeroelastic studies conducted on a wing-propeller model, aimed at evaluating the impact of aerodynamic interactions on wing flutter mechanisms and overall aeroelastic performance. The flutter onset is assessed using a frequency-domain method. Mid-fidelity tools based on the time-domain approach are then exploited to account for the complex aerodynamic interaction between the propeller and the wing. Specifically, the open-source software DUST and MBDyn are leveraged for this purpose. The investigation covers both windmilling and thrusting conditions. During the trim process, adjustments to the collective pitch of the blades are made to ensure consistency across operational points. Time histories are then analyzed to pinpoint flutter onset, and corresponding frequencies and damping ratios are identified. The results reveal a marginal destabilizing effect of aerodynamic interaction on flutter speed, approximately 5%. Notably, the thrusting condition demonstrates a greater destabilizing influence compared to the windmilling case. These comprehensive findings enhance the understanding of the aerodynamic behavior of such systems and offer valuable insights for early design predictions and the development of streamlined models for future endeavors.
Enhancement of succinic acid production by Actinobacillus succinogenes in an electro-bioreactor
(2024)
This work examines the electrochemically enhanced production of succinic acid using the bacterium Actinobacillus succinogenes. The principal objective is to enhance the metabolic potential of glucose and CO2 utilization via the C4 pathway in order to synthesize succinic acid. We report on the development of an electro-bioreactor system to increase succinic acid production in a power-2-X approach. The use of activated carbon fibers as electrode surfaces and contact areas allows A. succinogenes to self-initiate biofilm formation. The integration of an electrical potential into the system shifts the redox balance from NAD+ to NADH, increasing the efficiency of metabolic processes. Mediators such as neutral red facilitate electron transfer within the system and optimize the redox reactions that are crucial for increased succinic acid production. Furthermore, the role of carbon nanotubes (CNTs) in electron transfer was investigated. The electro-bioreactor system developed here was operated in batch mode for 48 h and showed improvements in succinic acid yield and concentration. In particular, a run with 100 µM neutral red and a voltage of −600 mV achieved a yield of 0.7 gsuccinate·gglucose−1. In the absence of neutral red, a higher yield of 0.72 gsuccinate·gglucose−1 was achieved, which represents an increase of 14% compared to the control. When a potential of −600 mV was used in conjunction with 500 µg∙L−1 CNTs, a 21% increase in succinate concentration was observed after 48 h. An increase of 33% was achieved in the same batch by increasing the stirring speed. These results underscore the potential of the electro-bioreactor system to markedly enhance succinic acid production.
The emergence of automotive-grade LiDARs has given rise to new potential methods to develop novel advanced driver assistance systems (ADAS). However, accurate and reliable parking slot detection (PSD) remains a challenge, especially in the low-light conditions typical of indoor car parks. Existing camera-based approaches struggle with these conditions and require sensor fusion to determine parking slot occupancy. This paper proposes a parking slot detection (PSD) algorithm which utilizes the intensity of a LiDAR point cloud to detect the markings of perpendicular parking slots. LiDAR-based approaches offer robustness in low-light environments and can directly determine occupancy status using 3D information. The proposed PSD algorithm first segments the ground plane from the LiDAR point cloud and detects the main axis along the driving direction using a random sample consensus algorithm (RANSAC). The remaining ground point cloud is filtered by a dynamic Otsu’s threshold, and the markings of parking slots are detected in multiple windows along the driving direction separately. Hypotheses of parking slots are generated between the markings, which are cross-checked with a non-ground point cloud to determine the occupancy status. Test results showed that the proposed algorithm is robust in detecting perpendicular parking slots in well-marked car parks with high precision, low width error, and low variance. The proposed algorithm is designed in such a way that future adoption for parallel parking slots and combination with free-space-based detection approaches is possible. This solution addresses the limitations of camera-based systems and enhances PSD accuracy and reliability in challenging lighting conditions.
Additive Manufacturing (AM) is a topic that is becoming more relevant to many companies globally. With AM's progressive development and use for series production, integrating the technology into existing production structures is becoming an important criterion for businesses. This study qualitatively examines the actual state and different perspectives on the integration of AM in production structures. Seven semi-structured interviews were conducted and analyzed. The interview partners were high-level experts in Additive Manufacturing and production systems from industry and science. Four main themes were identified. Key findings are the far-reaching interrelationships and implications of AM within production structures. Specific AM-related aspects were identified. Those can be used to increase the knowledge and practical application of the technology in the industry and as a foundation for economic considerations.
The fourth industrial revolution is on its way to reshape manufacturing and value creation in a profound way. The underlying technologies like cyber-physical systems (CPS), big data, collaborative robotics, additive manufacturing or artificial intelligence offer huge potentials for the optimization and evolution of production systems. However, many manufacturing companies struggle to implement these technologies. This can only in part be attributed to the lack of skilled personal within these companies or a missing digitalization strategy. Rather, there is a fundamental incompatibility between the way current production systems and companies (Industry 3.0) are structured across multiple dimensions compared to what is necessary for industry 4.0. This is especially true in manufacturing systems and their transition towards flexible, decentralized and autonomous value creation networks. This paper shows across various dimensions these incompatibilities within manufacturing systems, explores their reasons and discusses a different approach to create a foundation for Industry 4.0 in manufacturing companies.
Establishing high-performance polymers in additive manufacturing opens up new industrial applications. Polyetheretherketone (PEEK) was initially used in aerospace but is now widely applied in automotive, electronics, and medical industries. This study focuses on developing applications using PEEK and Fused Filament Fabrication for cost-efficient vulcanization injection mold production. A proof of concept confirms PEEK’s suitability for AM mold making, withstanding vulcanization conditions. Printing PEEK above its glass transition temperature of 145 °C is preferable due to its narrow process window. A new process strategy at room temperature is discussed, with micrographs showing improved inter-layer bonding at 410°C nozzle temperature and 0.1 mm layer thickness. Minimizing the layer thickness from 0.15 mm to 0.1 mm improves tensile strength by 16%.
In the face of the current trend towards larger and more complex production tasks in the SLM process and the current limitations in terms of maximum build space, the welding of SLM components to each other or to conventionally manufactured parts is becoming increasingly relevant. The fusion welding of SLM components made of 316L has so far been rarely investigated and if so, then for highly specialised laser welding processes. When welding with industrial gas welding processes such as MIG/MAG or TIG welding, distortions occur which are associated with the resulting residual stresses in the components. This paper investigates process-side influencing factors to avoid resulting residual stresses in SLM components made of 316L. The aim is to develop a strategy to build up SLM components as stress-free as possible in order to join them as profitably as possible with a downstream welding process. For this purpose, influencing parameters such as laser power, scan speed, but also scan vector length and different scan patterns are investigated with regard to their influence on residual stresses.
Air–water flows
(2024)
High Froude-number open-channel flows can entrain significant volumes of air, a phenomenon that occurs continuously in spillways, in free-falling jets and in hydraulic jumps, or as localized events, notably at the toe of hydraulic jumps or in plunging jets. Within these flows, turbulence generates millions of bubbles and droplets as well as highly distorted wavy air–water interfaces. This phenomenon is crucial from a design perspective, as it influences the behaviour of high-velocity flows, potentially impairing the safety of dam operations. This review examines recent scientific and engineering progress, highlighting foundational studies and emerging developments. Notable advances have been achieved in the past decades through improved sampling of flows and the development of physics-based models. Current challenges are also identified for instrumentation, numerical modelling and (up)scaling that hinder the formulation of fundamental theories, which are instrumental for improving predictive models, able to offer robust support for the design of large hydraulic structures at prototype scale.
Easy-read and large language models: on the ethical dimensions of LLM-based text simplification
(2024)
The production of easy-read and plain language is a challenging task, requiring well-educated experts to write context-dependent simplifications of texts. Therefore, the domain of easy-read and plain language is currently restricted to the bare minimum of necessary information. Thus, even though there is a tendency to broaden the domain of easy-read and plain language, the inaccessibility of a significant amount of textual information excludes the target audience from partaking or entertainment and restricts their ability to live life autonomously. Large language models can solve a vast variety of natural language tasks, including the simplification of standard language texts to easy-read or plain language. Moreover, with the rise of generative models like GPT, easy-read and plain language may be applicable to all kinds of natural language texts, making formerly inaccessible information accessible to marginalized groups like, a.o., non-native speakers, and people with mental disabilities. In this paper, we argue for the feasibility of text simplification and generation in that context, outline the ethical dimensions, and discuss the implications for researchers in the field of ethics and computer science.
The quest for scientifically advanced and sustainable solutions is driven by growing environmental and economic issues associated with coal mining, processing, and utilization. Consequently, within the coal industry, there is a growing recognition of the potential of microbial applications in fostering innovative technologies. Microbial-based coal solubilization, coal beneficiation, and coal dust suppression are green alternatives to traditional thermochemical and leaching technologies and better meet the need for ecologically sound and economically viable choices. Surfactant-mediated approaches have emerged as powerful tools for modeling, simulation, and optimization of coal-microbial systems and continue to gain prominence in clean coal fuel production, particularly in microbiological co-processing, conversion, and beneficiation. Surfactants (surface-active agents) are amphiphilic compounds that can reduce surface tension and enhance the solubility of hydrophobic molecules. A wide range of surfactant properties can be achieved by either directly influencing microbial growth factors, stimulants, and substrates or indirectly serving as frothers, collectors, and modifiers in the processing and utilization of coal. This review highlights the significant biotechnological potential of surfactants by providing a thorough overview of their involvement in coal biodegradation, bioprocessing, and biobeneficiation, acknowledging their importance as crucial steps in coal consumption.
Dieses Buch lädt dazu ein, die Welt um uns herum aus einem neuen Blickwinkel zu betrachten und dabei die spannende Verbindung zwischen der Mathematik und unserem täglichen Leben zu entdecken – denn um die Technologien und Entwicklungen unserer modernen Gesellschaft zu verstehen, benötigen wir ein intuitives Verständnis grundlegender mathematischer Ideen. In diesem Buch geht es um diese Grundlagen, vor allem aber um ihre praktische Anwendung im Alltag: Gemeinsam begeben wir uns auf eine unterhaltsame Reise und entdecken dabei, wie Mathematik in vielfältiger Weise allgegenwärtig ist. Anschauliche Beispiele zeigen, wie wir täglich – oft unbewusst – mathematische Ideen nutzen und wie wir mit Hilfe von Mathematik bessere Entscheidungen treffen können.
Nach einer Einführung in Algorithmen und Optimierungsprobleme, geht es im weiteren Verlauf um die Modellierung von Zufall und Unsicherheiten. Zum Ende des Buchs werden die Themen zusammengeführt und Algorithmen für Anwendungen besprochen, bei denen der Zufall eine entscheidende Rolle spielt.
Several unconnected laboratory experiments are usually offered for students in instrumental analysis lab. To give the students a more rational overview of the most common instrumental techniques, a new laboratory experiment was developed. Marketed pain relief drugs, familiar consumer products with one to three active components, namely, acetaminophen (paracetamol), acetylsalicylic acid (ASA), and caffeine, were selected. Common analytical methods were compared regarding the performance of qualitative and quantitative analysis of unknown tablets: UV–visible (UV–vis), infrared (IR), and nuclear magnetic resonance (NMR) spectroscopies, as well as high-performance liquid chromatography (HPLC). The students successfully uncovered the composition of formulations, which were divided into three difficulty categories. Students were shown that in addition to simple mixtures handled in theoretical classes, the composition of complex drug products can also be uncovered. By comparing the performance of different techniques, students deepen their understanding and compare the efficiency of analytical methods in the context of complex mixtures. The laboratory experiment can be adjusted for graduate level by including extra tasks such as method optimization, validation, and 2D spectroscopic techniques.
Ein Lehrbuch für die anwendungsorientierte Seite der Wirtschaftsinformatik. Dieses Lehrbuch der Wirtschaftsinformatik ist vor allem eines: anwendungsorientiert. Nutzen Sie die zahlreichen Fallbeispiele, um die Kerninhalte des Fachgebiets zu erlernen und einen Einblick in die umfassenden Einsatzmöglichkeiten der Informationstechnologien zu gewinnen, die in Zeiten der Digitalisierung für Wirtschaft und Gesellschaft unverzichtbar sind.
Von den Grundbegriffen der Informations- und Kommunikationstechnologie bis zur strategischen Planung, Nutzung und Entwicklung von Informationssystemen – dieses Buch bietet Ihnen alle Werkzeuge zur Integration neuer Konzepte in bestehende Softwarearchitekturen.
Die Website „Display Neuke“ macht den bisher unveröffentlichten Nachlass der Bildjournalistin Angela Neuke (1943-1997) aus der Sammlung des LVR-LandesMuseums Bonn digital und interaktiv zugänglich. Das Projekt beleuchtet insbesondere Neukes Dokumentation der Frauenbewegung der 1970er Jahre in Westdeutschland und regt zur Reflexion über historische sowie aktuelle Frauenbilder an. Durch die bewusste Zusammenführung und kontextuelle Einordnung des Materials wird sichtbar, wo, warum und unter welchen Umständen Fotostrecken und Magazinreportagen entstanden sind – das Archiv wird so als ein lebendiger Ort der Wissensvermittlung erfahrbar. Der Ansatz der programmierten und veröffentlichten Website ermöglicht es, Inhalte dynamisch anzupassen und zukünftig zu erweitern.
In this chapter, we report on our activities to create and maintain a fleet of autonomous load haul dump (LHD) vehicles for mining operations. The ever increasing demand for sustainable solutions and economic pressure causes innovation in the mining industry just like in any other branch. In this chapter, we present our approach to create a fleet of autonomous special purpose vehicles and to control these vehicles in mining operations. After an initial exploration of the site we deploy the fleet. Every vehicle is running an instance of our ROS 2-based architecture. The fleet is then controlled with a dedicated planning module. We also use continuous environment monitoring to implement a life-long mapping approach. In our experiments, we show that a combination of synthetic, augmented and real training data improves our classifier based on the deep learning network Yolo v5 to detect our vehicles, persons and navigation beacons. The classifier was successfully installed on the NVidia AGX-Drive platform, so that the abovementioned objects can be recognised during the dumper drive. The 3D poses of the detected beacons are assigned to lanelets and transferred to an existing map.
Das Projekt "Grafischer Aktivismus" verortet sich im Schnittpunkt von Design und sozialem Engagement. Es ist eine gestalterische Auseinandersetzung, wie visuelle Kommunikation genutzt werden kann, um soziale Ungerechtigkeiten sichtbar zu machen und Bewusstsein zu schaffen. Durch die Entwicklung einer visuellen Sprache können Missstände thematisiert werden. Ziel ist es, durch gestalterische Mittel einen Dialog zu initiieren und die öffentliche Wahrnehmung zu beeinflussen. Zu den Herangehensweisen gehören die Erstellung einer Schablone, die Entwicklung einer Schriftart und dessen Specimen. Diese Auseinandersetzung trägt dazu bei, gesellschaftliche Veränderungen anzustoßen und Gerechtigkeit zu fördern. Das Projekt bietet eine weitere Perspektive auf die Rolle von Grafikdesign im Aktivismus.
Sexism in online media comments is a pervasive challenge that often manifests subtly, complicating moderation efforts as interpretations of what constitutes sexism can vary among individuals. We study monolingual and multilingual open-source text embeddings to reliably detect sexism and misogyny in Germanlanguage online comments from an Austrian newspaper. We observed classifiers trained on text embeddings to mimic closely the individual judgements of human annotators. Our method showed robust performance in the GermEval 2024 GerMS-Detect Subtask 1 challenge, achieving an average macro F1 score of 0.597 (4th place, as reported on Codabench). It also accurately predicted the distribution of human annotations in GerMS-Detect Subtask 2, with an average Jensen-Shannon distance of 0.301 (2nd place). The computational efficiency of our approach suggests potential for scalable applications across various languages and linguistic contexts.
/SANO – eine App zur Gesundheitsoptimierung und langfristigem Wohlbefinden. In unserer schnelllebigen Welt führt täglicher Stress oft zur Vernachlässigung folgender Bereiche: Ernährung, Schlaf, Bewegung und Stress. Dieser Lebensstil fördert nicht übertragbare Krankheiten wie Krebs, Herz-Kreislauf-Erkrankungen, Diabetes und chronische Atemwegserkrankungen, die weltweit viele Todesfälle verursachen. Die Notwendigkeit umfassender Lösungen zur Förderung gesunder Gewohnheiten wird immer dringlicher. /SANO unterstützt mit einem Werkzeug für Achtsamkeit und Gesundheit, das gesunde Gewohnheiten und Ziele definiert. Durch Tracking-Möglichkeiten, Routinen und To-Do-Listen werden sie individuell gefördert. Diese Arbeit stellt sich den Herausforderungen des aktuellen Krankheitszustandes unserer Gesellschaft und eröffnet eine neue Perspektive im Well-Being und Gesundheitsbereich.
Die interaktive Dokumentation erzählt die sinnliche Wirkung des Gemeinschaftsgartens HirschGrün und teilt die Erfahrungen von vier Gärtner:innen in einer auditiven und visuellen Auseinandersetzung, innerhalb eines Open-World Ansatzes. Das Projekt stellt eine progressive Weise dar, sich mit journalistischen Inhalten zu beschäftigen. Es schafft Perspektiven für die sozialen und schöpferischen Potenziale eines Gemeinschaftsgartens. Interaktionen, visuelle und auditive Reize illustrieren die Atmosphäre. Grünflächen sind nicht nur klimarelevant, sondern schaffen für Stadtbewohner:innen vielfältige Wege, mit Leben in Kontakt zu treten. Besonders jene verbinden Gemeinschaft, Natur und Nachhaltigkeit. Die explorative Art technischer Informationsvermittlung und aktuelle Themen dieser Zeit werden auf einer Webseite vereint. Das Projekt zeigt eine Aussicht, multimedialen Journalismus zu gestalten.
To successfully develop and introduce concrete artificial intelligence (AI) solutions in operational practice, a comprehensive process model is being tested in the WIRKsam joint project. It is based on a methodical approach that integrates human, technical and organisational aspects and involves employees in the process. The chapter focuses on the procedure for identifying requirements for a work system that is implementing AI in problem-driven projects and for selecting appropriate AI methods. This means that the use case has already been narrowed down at the beginning of the project and must be completely defined in the following. Initially, the existing preliminary work is presented. Based on this, an overview of all procedural steps and methods is given. All methods are presented in detail and good practice approaches are shown. Finally, a reflection of the developed procedure based on the application in nine companies is given.
Effective government services rely on accurate population numbers to allocate resources. In Colombia and globally, census enumeration is challenging in remote regions and where armed conflict is occurring. During census preparations, the Colombian National Administrative Department of Statistics conducted social cartography workshops, where community representatives estimated numbers of dwellings and people throughout their regions. We repurposed this information, combining it with remotely sensed buildings data and other geospatial data. To estimate building counts and population sizes, we developed hierarchical Bayesian models, trained using nearby full-coverage census enumerations and assessed using 10-fold cross-validation. We compared models to assess the relative contributions of community knowledge, remotely sensed buildings, and their combination to model fit. The Community model was unbiased but imprecise; the Satellite model was more precise but biased; and the Combination model was best for overall accuracy. Results reaffirmed the power of remotely sensed buildings data for population estimation and highlighted the value of incorporating local knowledge.
Digitaler Marktplatz für Erzeuger:innen und Verbraucher:innen regionaler Produkte. Das Ziel dieses Projekts ist es, solidarische Landwirtschaft (SoLaWi) zu digitalisieren, um eine zeitgemäße Alternative zu den bestehenden Kauf- und Abonnementprozessen zu schaffen. Die dabei entstandene App „KoHof" ermöglicht landwirtschaftlichen Betrieben, sich online zu präsentieren, Abonnements zu verwalten und neue Mitglieder zu gewinnen. Gleichzeitig bietet die Plattform Verbraucher:innen eine unkomplizierte Möglichkeit, passende Betriebe und dazugehörige Produkte in der Region zu finden sowie ihre Mitgliedschaft zu verwalten. Insgesamt strebt das Projekt "KoHof" danach, die Solidarische Landwirtschaft digital zu transformieren und eine neue Perspektive für die regionale Erzeugung von Lebensmitteln zu eröffnen. Durch diese innovative Plattform wird die Vernetzung zwischen Erzeugerinnen und Verbraucherinnen in der SoLaWi-Bewegung auf eine neue Stufe gehoben.
Das Thema der Masterarbeit erläutert den Konflikt zwischen Konsum und Minimalismus. Überkonsum und Minimalismus sind gegensätzliche Extreme. Durch die Beziehung zwischen Mensch und Objekt lassen sich die beiden Gegensätze vereinen. Die Konzentration auf nur wenige Objekte hat eine Reduktion des Konsums und eine Fokussierung auf wenige Objekte zur Folge. Das Konzept „kubo“ gibt Objekten einen Raum. Das Regal „kubo“ ist mit verstellbaren Regalböden ausgestattet. So können die Gegenstände individuell platziert werden. Das Verstellen und Anordnen der Regalböden können Benutzer:innen nach eigenem Belieben vornehmen. Die Objekte werden im Regal hervorgehoben. Sie erhalten dadurch mehr Aufmerksamkeit. Ziel ist es, dass der Benutzer:innen mehr mit den Objekten interagieren und sich bewusst werden, was wirklich wichtig ist. „kubo“ versucht dem Problem des Überkonsums entgegenzuwirken. Durch die Hervorhebung wichtiger Objekte wird das Bewusstsein für den eigenen Konsum geschärft.
Climate Engineering : Entwicklung einer digitalen Plattform für Climate Engineering Maßnahmen
(2024)
Dieses Projekt hat zum Ziel, umfassend über Climate Engineering-Maßnahmen zu informieren und dabei insbesondere ihre Funktionsweise, Kosten und Risiken darzustellen. Die entstandene Plattform "Die Erde abkühlen!" bietet einen Einblick in die Lösungsansätze des Climate Engineerings durch die Verwendung von Storytelling. Sie ermöglicht Nutzer:innen einen Überblick über den aktuellen Stand der Klimaerwärmung sowie den Vergleich von Climate Engineering-Maßnahmen. Ein entwickeltes Bewertungssystem auf Grundlage der "Royal Society" sowie interaktive Infografiken geben Nutzer:innen einen umfassenden Einblick. Das Hauptziel des Projekts ist die digitale Transformation der Climate Engineering-Lösungsansätze. Dabei geht es nicht nur darum, über die Folgen der Klimaerwärmung zu informieren, sondern auch konkrete Lösungen aufzuzeigen. Durch die Entwicklung eines innovativen Storytellings wird die Thematik nicht nur dramaturgisch präsentiert, sondern ermöglicht es den Nutzer:innen auch, ihre eigene Wissensvertiefung zu steuern.
Das Masterprojekt DIE STUHL hebt die Unsichtbarkeit von Gestalterinnen im Stuhldesign hervor. Es werden 108 Designerinnen aus 40 Ländern vorgestellt, die vom Beginn des 20. Jahrhunderts bis heute innovative und richtungsweisende Entwürfe von Stühlen entwickelt haben. Die Arbeit beleuchtet den Beitrag, den sie geleistet haben und stellt gleichzeitig heraus, dass viele von ihnen im internationalen Designkanon übersehen wurden. Chronologisch nach dem Erscheinungsjahr der ersten entwickelten Stühle geordnet, werden die Objekte in einem Atlas illustriert und Kurzbiografien der Protagonistinnen gezeigt. Anhand von Informationsgrafiken werden die Stühle in das soziopolitische Geschehen ihrer Zeit eingebettet. DIE STUHL würdigt die Arbeit von Gestalterinnen und stellt Fragen zur strukturellen Ungleichheit der Geschlechter. Parallel zur Publikation ist außerdem eine Skulptur entstanden, die als Zeitstrahl fungiert und in abstrakter Form alle im Atlas erwähnten Stühle aufführt. Hierbei wird das ungleiche Verhältnis der von Gestalterinnen und Gestalter entworfenen Stühle sichtbar.
Die Abschlussarbeit thematisiert konzeptionelle Möglichkeiten für die Unterstützung in der Lehre. Lehrkräfte erfahren eine hohe Auslastung in ihrem Beruf. Besonders ein wachsender Fachkräftemangel verstärkt das Problem, welches wiederum Auswirkungen auf die Leistungen der Schülerinnen und Schüler haben kann. Somit kann auch der individuellen Förderung nicht ausreichend nachgegangen werden. Die Lösung der Arbeit ist Kinvi, ein digitaler KI-Lehrassistent. Kinvi soll leistungsschwache und leistungsstarke Schüler fördern. Dabei kann Kinvi Inhalte erklären, eine individuelle Lernstruktur vorgeben und sogar Übungen erstellen. Auch spielerische Inhalte und ein motivierendes Feedback sind inbegriffen. Lehrkräfte können Inhalte KI gestützt steuern und Leistungen überblicken. Dies soll zur Entlastung der Lehrkräfte führen und die Fähigkeiten der Schülerinnen und Schüler gezielt fördern.
RehaGlove ist ein Exoskelett, dass Menschen mit rheumatoider Arthritis oder Arthrose bei der Bewältigung des Alltags helfen soll. Die rheumatoide Arthritis zeichnet sich vorwiegend durch die chronischen Entzündungen des Gelenkapparats aus, während die Arthrose eine alters- oder belastungsinduzierte Degeneration des Gelenkgewebes darstellt. Bei beiden Erkrankungen sind die Fingergelenke besonders häufig betroffen. Es kommt zu sehr starken Schmerzen, Bewegungseinschränkungen und Kraftverlust. Da wir unsere Hände jedoch täglich brauchen, gestaltet sich der Alltag mit einer solch einschränkenden Krankheit als besonders schmerzhaft. Dabei soll RehaGlove Abhilfe schaffen. Mehrere Zug-/ Druck-Kabel unterstützen den Griff und steigern die Griffkraft. Außerdem ermöglichen sie die eigenständige Ausführung physiotehrapeutischer Aufgaben und erleichtern es die Gelenke mobil zu halten.
Perennial ryegrass (Lolium perenne) is an underutilized lignocellulosic biomass that has several benefits such as high availability, renewability, and biomass yield. The grass press-juice obtained from the mechanical pretreatment can be used for the bio-based production of chemicals. Lactic acid is a platform chemical that has attracted consideration due to its broad area of applications. For this reason, the more sustainable production of lactic acid is expected to increase. In this work, lactic acid was produced using complex medium at the bench- and reactor scale, and the results were compared to those obtained using an optimized press-juice medium. Bench-scale fermentations were carried out in a pH-control system and lactic acid production reached approximately 21.84 ± 0.95 g/L in complex medium, and 26.61 ± 1.2 g/L in press-juice medium. In the bioreactor, the production yield was 0.91 ± 0.07 g/g, corresponding to a 1.4-fold increase with respect to the complex medium with fructose. As a comparison to the traditional ensiling process, the ensiling of whole grass fractions of different varieties harvested in summer and autumn was performed. Ensiling showed variations in lactic acid yields, with a yield up to 15.2% dry mass for the late-harvested samples, surpassing typical silage yields of 6–10% dry mass.
Purpose: Impaired paravascular drainage of β-Amyloid (Aβ) has been proposed as a contributing cause for sporadic Alzheimer’s disease (AD), as decreased cerebral blood vessel pulsatility and subsequently reduced propulsion in this pathway could lead to the accumulation and deposition of Aβ in the brain. Therefore, we hypothesized that there is an increased impairment in pulsatility across AD spectrum.
Patients and Methods: Using transcranial color-coded duplex sonography (TCCS) the resistance and pulsatility index (RI; PI) of the middle cerebral artery (MCA) in healthy controls (HC, n=14) and patients with AD dementia (ADD, n=12) were measured. In a second step, we extended the sample by adding patients with mild cognitive impairment (MCI) stratified by the presence (MCI-AD, n=8) or absence of biomarkers (MCI-nonAD, n=8) indicative for underlying AD pathology, and compared RI and PI across the groups. To control for atherosclerosis as a confounder, we measured the arteriolar-venular-ratio of retinal vessels.
Results: Left and right RI (p=0.020; p=0.027) and left PI (p=0.034) differed between HC and ADD controlled for atherosclerosis with AUCs of 0.776, 0.763, and 0.718, respectively. The RI and PI of MCI-AD tended towards ADD, of MCI-nonAD towards HC, respectively. RIs and PIs were associated with disease severity (p=0.010, p=0.023).
Conclusion: Our results strengthen the hypothesis that impaired pulsatility could cause impaired amyloid clearance from the brain and thereby might contribute to the development of AD. However, further studies considering other factors possibly influencing amyloid clearance as well as larger sample sizes are needed.
Purpose: A precise determination of the corneal diameter is essential for the diagnosis of various ocular diseases, cataract and refractive surgery as well as for the selection and fitting of contact lenses. The aim of this study was to investigate the agreement between two automatic and one manual method for corneal diameter determination and to evaluate possible diurnal variations in corneal diameter.
Patients and Methods: Horizontal white-to-white corneal diameter of 20 volunteers was measured at three different fixed times of a day with three methods: Scheimpflug method (Pentacam HR, Oculus), placido based topography (Keratograph 5M, Oculus) and manual method using an image analysis software at a slitlamp (BQ900, Haag-Streit).
Results: The two-factorial analysis of variance could not show a significant effect of the different instruments (p = 0.117), the different time points (p = 0.506) and the interaction between instrument and time point (p = 0.182). Very good repeatability (intraclass correlation coefficient ICC, quartile coefficient of dispersion QCD) was found for all three devices. However, manual slitlamp measurements showed a higher QCD than the automatic measurements with the Keratograph 5M and the Pentacam HR at all measurement times.
Conclusion: The manual and automated methods used in the study to determine corneal diameter showed good agreement and repeatability. No significant diurnal variations of corneal diameter were observed during the period of time studied.
Transgenic plants have the potential to produce recombinant proteins on an agricultural scale, with yields of several tons per year. The cost-effectiveness of transgenic plants increases if simple cultivation facilities such as greenhouses can be used for production. In such a setting, we expressed a novel affinity ligand based on the fluorescent protein DsRed, which we used as a carrier for the linear epitope ELDKWA from the HIV-neutralizing antibody 2F5. The DsRed-2F5-epitope (DFE) fusion protein was produced in 12 consecutive batches of transgenic tobacco (Nicotiana tabacum) plants over the course of 2 years and was purified using a combination of blanching and immobilized metal-ion affinity chromatography (IMAC). The average purity after IMAC was 57 ± 26% (n = 24) in terms of total soluble protein, but the average yield of pure DFE (12 mg kg−1) showed substantial variation (± 97 mg kg−1, n = 24) which correlated with seasonal changes. Specifically, we found that temperature peaks (>28°C) and intense illuminance (>45 klx h−1) were associated with lower DFE yields after purification, reflecting the loss of the epitope-containing C-terminus in up to 90% of the product. Whereas the weather factors were of limited use to predict product yields of individual harvests conducted for each batch (spaced by 1 week), the average batch yields were well approximated by simple linear regression models using two independent variables for prediction (illuminance and plant age). Interestingly, accumulation levels determined by fluorescence analysis were not affected by weather conditions but positively correlated with plant age, suggesting that the product was still expressed at high levels, but the extreme conditions affected its stability, albeit still preserving the fluorophore function. The efficient production of intact recombinant proteins in plants may therefore require adequate climate control and shading in greenhouses or even cultivation in fully controlled indoor farms.
Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.
Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.
The book covers various numerical field simulation methods, nonlinear circuit technology and its MF-S- and X-parameters, as well as state-of-the-art power amplifier techniques. It also describes newly presented oscillators and the emerging field of GHz plasma technology. Furthermore, it addresses aspects such as waveguides, mixers, phase-locked loops, antennas, and propagation effects, in combination with the bachelor's book 'High-Frequency Engineering,' encompassing all aspects related to the current state of GHz technology.
Metathese von Ölsäure und Derivaten ist ein interessanter Weg für die Synthese bifunktioneller Verbindungen aus nachwachsenden Rohstoffen. Verwendet wurden Ru-Katalysatoren der zweiten Generation, welche eine hohe Toleranz gegenüber funktionellen Gruppen und Verunreinigungen aufweisen. Trotz des Einsatzes technischer Edukte waren Umsetzungen mit niedrigen Katalysatormengen (0.001 – 0.01 mol-%) möglich, mit Ausbeuten entsprechend der Literatur. Kreuzmetathesen ermöglichten variable Kettenlängen und Funktionalitäten der Monomere, die Produktgewinnung ist jedoch aufwändig. Selbstmetathese lieferte C18-bifunktionelle Verbindungen, welche einfach durch Destillation oder Kristallisation isoliert werden können. Neben der katalystischen Umsetzung wurde auch die Produktgewinnung untersucht und für ausgewählte Produkte auch im größeren Maßstab durchgeführt.
Self metathesis of oleochemicals offers a variety of bifunctional compounds, that can be used as monomer for polymer production. Many precursors are in huge scales available, like oleic acid ester (biodiesel), oleyl alcohol (tensides), oleyl amines (tensides, lubricants). We show several ways to produce and separate and purify C18-α,ω-bifunctional compounds, using Grubbs 2nd Generation catalysts, starting from technical grade educts.
Die Bereitstellung von nachhaltig erzeugtem Wasserstoff als Energieträger und Rohstoff ist eine wichtige Schlüsseltechnologie sowohl als Ersatz für fossile Energieträger, aber auch als Produkt im Zusammenhang mit Kreislaufprozessen. In der Abwasserbehandlung bestehen verschiedene Möglichkeiten Wasserstoff herzustellen. Mehrere Wege, mögliche Synergien, aber auch deren Nachteile werden vorgestellt.
Die Erfindung liegt auf dem Gebiet der Enzymtechnologie. Die Erfindung betrifft Proteasen aus Metabacillus indicus, die insbesondere im Hinblick auf den Einsatz in Wasch- und Reinigungsmitteln verwendet werden können, alle hinreichend ähnlichen Proteasen mit einer entsprechend ähnlichen Sequenz zu SEQ ID NO:1 und für sie codierende Nukleinsäuren. Die Erfindung betrifft ferner deren Herstellung sowie Verfahren zur Verwendung dieser Proteasen, deren Verwendung als solche sowie diese enthaltende Mittel, insbesondere Wasch- und Reinigungsmittel.
Die Erfindung liegt auf dem Gebiet der Enzymtechnologie. Die Erfindung betrifft Proteasen aus Fictibacillus arsenicus, die insbesondere im Hinblick auf den Einsatz in Wasch- und Reinigungsmitteln verwendet werden können, alle hinreichend ähnlichen Proteasen mit einer entsprechend ähnlichen Sequenz zu SEQ ID NO:1 und für sie codierende Nukleinsäuren. Die Erfindung betrifft ferner deren Herstellung sowie Verfahren zur Verwendung dieser Proteasen, deren Verwendung als solche sowie diese enthaltende Mittel, insbesondere Wasch- und Reinigungsmittel.
1. Auswirkungen des europäischen Data Act: Untersuchung des Verhältnisses zwischen Datenzugang und Datenschutz
- Olivia Sohn | Seite 4-58
2. Detecting companies’ willingness to invest in their sustainable transformation – relevant factors and their evaluation
- Titus Thamm |Seite 59-107
3. Unterschiede in den arbeitsbezogenen Wertvorstellungen der Generation Y und Z? Don ́t believe the hype
- Lara Heimann | Seite 108-199
4. Die virtuelle Mitgliederversammlung beim eingetragenen Verein – ein Modell für die Zukunft?
- Abdullah Andug | Seite 200-253
5. Die AGB-Kontrolle von Rechtswahlklauseln in der deutschen und europäischen Kontrollpraxis – Effektiver Verbraucherschutz oder zusätzliche Rechtsunsicherheit?
- Johannes Stahl | Seite 254-325
6. Datenzugangs-und Nutzungsrechte durch den EU Data Act am Beispiel der Automobilbranche
- Tim Schultwessel | Seite 326-380
