TY - CHAP A1 - Chavez Bermudez, Victor Francisco A1 - Cruz Castanon, Victor Fernando A1 - Ruchay, Marco A1 - Wollert, Jörg ED - Leipzig, Hochschule für Technik, Wirtschaft und Kultur T1 - Rapid prototyping framework for automation applications based on IO-Link T2 - Tagungsband AALE 2022 N2 - The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source. KW - Rapid-prototyping KW - Arduino KW - IO-Link KW - Industrial Communication Y1 - 2022 SN - 978-3-910103-00-9 U6 - http://dx.doi.org/10.33968/2022.28 N1 - 18. AALE-Konferenz, Pforzheim, 09.03.-11.03.2022. CY - Leipzig ER - TY - JOUR A1 - Cheng, Chi-Tsun A1 - Wollert, Jörg A1 - Chen, Xi A1 - Fapojuwo, Abraham O. T1 - Guest Editorial : Circuits and Systems for Industry X.0 Applications JF - IEEE Journal on Emerging and Selected Topics in Circuits and Systems Y1 - 2023 U6 - http://dx.doi.org/10.1109/JETCAS.2023.3278843 SN - 2156-3357 (Print) SN - 2156-3365 (Online) VL - 13 SP - 457 EP - 460 PB - IEEE CY - New York ET - 2 ER - TY - JOUR A1 - Kuchler, Timon A1 - Günthner, Roman A1 - Ribeiro, Andrea A1 - Hausinger, Renate A1 - Streese, Lukas A1 - Wöhnl, Anna A1 - Kesseler, Veronika A1 - Negele, Johanna A1 - Assali, Tarek A1 - Carbajo-Lozoya, Javier A1 - Lech, Maciej A1 - Adorjan, Kristina A1 - Stubbe, Hans Christian A1 - Hanssen, Henner A1 - Kotliar, Konstantin A1 - Haller, Berhard A1 - Heemann, Uwe A1 - Schmaderer, Christoph T1 - Persistent endothelial dysfunction in post-COVID-19 syndrome and its associations with symptom severity and chronic inflammation N2 - Background Post-COVID-19 syndrome (PCS) is a lingering disease with ongoing symptoms such as fatigue and cognitive impairment resulting in a high impact on the daily life of patients. Understanding the pathophysiology of PCS is a public health priority, as it still poses a diagnostic and treatment challenge for physicians. Methods In this prospective observational cohort study, we analyzed the retinal microcirculation using Retinal Vessel Analysis (RVA) in a cohort of patients with PCS and compared it to an age- and gender-matched healthy cohort (n = 41, matched out of n = 204). Measurements and main results PCS patients exhibit persistent endothelial dysfunction (ED), as indicated by significantly lower venular flicker-induced dilation (vFID; 3.42% ± 1.77% vs. 4.64% ± 2.59%; p = 0.02), narrower central retinal artery equivalent (CRAE; 178.1 [167.5–190.2] vs. 189.1 [179.4–197.2], p = 0.01) and lower arteriolar-venular ratio (AVR; (0.84 [0.8–0.9] vs. 0.88 [0.8–0.9], p = 0.007). When combining AVR and vFID, predicted scores reached good ability to discriminate groups (area under the curve: 0.75). Higher PCS severity scores correlated with lower AVR (R = − 0.37 p = 0.017). The association of microvascular changes with PCS severity were amplified in PCS patients exhibiting higher levels of inflammatory parameters. Conclusion Our results demonstrate that prolonged endothelial dysfunction is a hallmark of PCS, and impairments of the microcirculation seem to explain ongoing symptoms in patients. As potential therapies for PCS emerge, RVA parameters may become relevant as clinical biomarkers for diagnosis and therapy management. KW - Endothelial dysfunction KW - Long COVID KW - Post-COVID-19 syndrome KW - retinal microvasculature Y1 - 2023 U6 - http://dx.doi.org/10.1007/s10456-023-09885-6 N1 - Corresponding author: Christoph Schmaderer VL - 26 SP - 547 EP - 563 PB - Springer Nature CY - Dordrecht ER - TY - INPR A1 - Greiner, Lasse A1 - Jeromin, Günter Erich A1 - Sithole, Patience A1 - Petersen, Soenke T1 - Preprint: Studies on the enzymatic reduction of levulinic acid using Chiralidon-R and Chiralidon-S T2 - ChemRxiv N2 - The enzymatic reduction of levulinic acid by the chiral catalysts Chiralidon-R and Chiralidon-S which are commercially available superabsorbed alcohol dehydrogenases is described. The Chiralidon®-R/S reduces the levulinic acid to the (R,S)-4-hydroxy valeric acid and the (R)- or (S)- gamma-valerolactone. KW - Levulinic acid KW - Chiralidon-R KW - Chiralidon-S KW - 4-hydroxy valeric acid KW - (R)- or (S)- gamma-valerolactone Y1 - 2023 U6 - http://dx.doi.org/10.26434/chemrxiv-2023-jlvcv ER - TY - CHAP A1 - Klöser, Lars A1 - Büsgen, André A1 - Kohl, Philipp A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - Explaining relation classification models with semantic extents T2 - DeLTA 2023: Deep Learning Theory and Applications N2 - In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relation classification. State-of-the-art systems are highly accurate on scientific benchmarks. A lack of explainability is currently a complicating factor in many real-world applications. Comprehensible systems are necessary to prevent biased, counterintuitive, or harmful decisions. We introduce semantic extents, a concept to analyze decision patterns for the relation classification task. Semantic extents are the most influential parts of texts concerning classification decisions. Our definition allows similar procedures to determine semantic extents for humans and models. We provide an annotation tool and a software framework to determine semantic extents for humans and models conveniently and reproducibly. Comparing both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the reliability and security of natural language processing systems. Semantic extents are an essential step in enabling applications in critical areas like healthcare or finance. Moreover, our work opens new research directions for developing methods to explain deep learning models. KW - Relation classification KW - Natural language processing KW - Natural language understanding KW - Information extraction KW - Trustworthy artificial intelligence Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-39059-3_13 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 189 EP - 208 PB - Springer CY - Cham ER - TY - CHAP A1 - Freyer, Nils A1 - Thewes, Dustin A1 - Meinecke, Matthias ED - Gusikhin, Oleg ED - Hammoudi, Slimane ED - Cuzzocrea, Alfredo T1 - GUIDO: a hybrid approach to guideline discovery & ordering from natural language texts T2 - Proceedings of the 12th International Conference on Data Science, Technology and Applications DATA - Volume 1 N2 - Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized process models is expensive. Therefore, there are only a few machine-learning-based extraction approaches. Rule-based approaches, in turn, require domain specificity to work well and can rarely distinguish relevant and irrelevant information in textual descriptions. In this paper, we present GUIDO, a hybrid approach to the process model extraction task that first, classifies sentences regarding their relevance to the process model, using a BERT-based sentence classifier, and second, extracts a process model from the sentences classified as relevant, using dependency parsing. The presented approach achieves significantly better resul ts than a pure rule-based approach. GUIDO achieves an average behavioral similarity score of 0.93. Still, in comparison to purely machine-learning-based approaches, the annotation costs stay low. KW - Natural Language Processing KW - Text Mining KW - Process Model Extraction KW - Business Process Intelligence Y1 - 2023 SN - 978-989-758-664-4 U6 - http://dx.doi.org/10.5220/0012084400003541 SN - 2184-285X N1 - Proceedings of the 12th International Conference on Data Science, Technology and Applications, July 11-13, 2023, in Rome, Italy. SP - 335 EP - 342 ER - TY - JOUR A1 - Kempt, Hendrik A1 - Freyer, Nils A1 - Nagel, Saskia K. T1 - Justice and the normative standards of explainability in healthcare JF - Philosophy & Technology N2 - Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability. KW - Clinical decision support systems KW - Justice KW - Medical AI KW - Explainability KW - Normative standards Y1 - 2022 U6 - http://dx.doi.org/10.1007/s13347-022-00598-0 VL - 35 IS - Article number: 100 SP - 1 EP - 19 PB - Springer Nature CY - Berlin ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Limpert, Nicolas A1 - Nessau, Hendrik A1 - Reke, Michael A1 - Ferrein, Alexander T1 - Model-predictive control with parallelised optimisation for the navigation of autonomous mining vehicles T2 - 2023 IEEE Intelligent Vehicles Symposium (IV) N2 - The work in modern open-pit and underground mines requires the transportation of large amounts of resources between fixed points. The navigation to these fixed points is a repetitive task that can be automated. The challenge in automating the navigation of vehicles commonly used in mines is the systemic properties of such vehicles. Many mining vehicles, such as the one we have used in the research for this paper, use steering systems with an articulated joint bending the vehicle’s drive axis to change its course and a hydraulic drive system to actuate axial drive components or the movements of tippers if available. To address the difficulties of controlling such a vehicle, we present a model-predictive approach for controlling the vehicle. While the control optimisation based on a parallel error minimisation of the predicted state has already been established in the past, we provide insight into the design and implementation of an MPC for an articulated mining vehicle and show the results of real-world experiments in an open-pit mine environment. KW - Mpc KW - Control KW - Path-following KW - Navigation KW - Automation Y1 - 2023 SN - 979-8-3503-4691-6 (Online) SN - 979-8-3503-4692-3 (Print) U6 - http://dx.doi.org/10.1109/IV55152.2023.10186806 N1 - IEEE Symposium on Intelligent Vehicle, 4.-7. June 2023, Anchorage, AK, USA. PB - IEEE ER - TY - CHAP A1 - Kohl, Philipp A1 - Freyer, Nils A1 - Krämer, Yoka A1 - Werth, Henri A1 - Wolf, Steffen A1 - Kraft, Bodo A1 - Meinecke, Matthias A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - ALE: a simulation-based active learning evaluation framework for the parameter-driven comparison of query strategies for NLP T2 - Deep Learning Theory and Applications. DeLTA 2023. Communications in Computer and Information Science N2 - Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance. However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP. The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework. KW - Active learning KW - Query learning KW - Natural language processing KW - Deep learning KW - Reproducible research Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - http://dx.doi.org/978-3-031-39059-3 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 235 EP - 253 PB - Springer CY - Cham ER - TY - CHAP A1 - Büsgen, André A1 - Klöser, Lars A1 - Kohl, Philipp A1 - Schmidts, Oliver A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Cuzzocrea, Alfredo ED - Gusikhin, Oleg ED - Hammoudi, Slimane ED - Quix, Christoph T1 - From cracked accounts to fake IDs: user profiling on German telegram black market channels T2 - Data Management Technologies and Applications N2 - Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling. KW - Clustering KW - Natural language processing KW - Information extraction KW - Profile extraction KW - Text mining Y1 - 2023 SN - 978-3-031-37889-8 (Print) SN - 978-3-031-37890-4 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-37890-4_9 N1 - 10th International Conference, DATA 2021, Virtual Event, July 6–8, 2021, and 11th International Conference, DATA 2022, Lisbon, Portugal, July 11-13, 2022 SP - 176 EP - 202 PB - Springer CY - Cham ER - TY - JOUR A1 - Schulze, Sven A1 - Feyerl, Günter A1 - Pischinger, Stefan T1 - Advanced ECMS for hybrid electric heavy-duty trucks with predictive battery discharge and adaptive operating strategy under real driving conditions JF - Energies N2 - To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15% more efficiently by 2025 and 30% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks. KW - Energy management strategies KW - ECMS KW - CO2 emission reduction targets KW - Driving cycle recognition KW - Predictive battery discharge Y1 - 2023 U6 - http://dx.doi.org/10.3390/en16135171 SN - 1996-1073 N1 - The article belongs to the Special Issue "Energy Management Strategies of Electrified Vehicles toward the Real-World Driving". VL - 16 IS - 13 PB - MDPI CY - Basel ER - TY - CHAP A1 - Goh, Kheng Lim A1 - Topçu, Murat A1 - Madabhushi, Gopal S. P. A1 - Staat, Manfred ED - Maia, Fatima Raquel Azevedo ED - Miguel Oliveira, J. ED - Reis, Rui L. T1 - Collagen fibril reinforcement in connective tissue extracellular matrices T2 - Handbook of the extracellular matrix N2 - The connective tissues such as tendons contain an extracellular matrix (ECM) comprising collagen fibrils scattered within the ground substance. These fibrils are instrumental in lending mechanical stability to tissues. Unfortunately, our understanding of how collagen fibrils reinforce the ECM remains limited, with no direct experimental evidence substantiating current theories. Earlier theoretical studies on collagen fibril reinforcement in the ECM have relied predominantly on the assumption of uniform cylindrical fibers, which is inadequate for modelling collagen fibrils, which possessed tapered ends. Recently, Topçu and colleagues published a paper in the International Journal of Solids and Structures, presenting a generalized shear-lag theory for the transfer of elastic stress between the matrix and fibers with tapered ends. This paper is a positive step towards comprehending the mechanics of the ECM and makes a valuable contribution to formulating a complete theory of collagen fibril reinforcement in the ECM. KW - Connective tissues KW - Extracellular matrix (ECM) KW - Collagen fibrils KW - Mechanical stability KW - Tapered ends Y1 - 2023 SN - 978-3-030-92090-6 (Print) SN - 978-3-030-92090-6 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-92090-6_6-1 SP - 1 EP - 20 PB - Springer Nature CY - Cham ER - TY - CHAP A1 - Mohan, Nijanthan A1 - Groß, Rolf Fritz A1 - Menzel, Karsten A1 - Theis, Fabian T1 - Opportunities and Challenges in the Implementation of Building Information Modeling for Prefabrication of Heating, Ventilation and Air Conditioning Systems in Small and Medium-Sized Contracting Companies in Germany – A Case Study T2 - WIT Transactions on The Built Environment, Vol. 205 N2 - FEven though BIM (Building Information Modelling) is successfully implemented in most of the world, it is still in the early stages in Germany, since the stakeholders are sceptical of its reliability and efficiency. The purpose of this paper is to analyse the opportunities and obstacles to implementing BIM for prefabrication. Among all other advantages of BIM, prefabrication is chosen for this paper because it plays a vital role in creating an impact on the time and cost factors of a construction project. The project stakeholders and participants can explicitly observe the positive impact of prefabrication, which enables the breakthrough of the scepticism factor among the small-scale construction companies. The analysis consists of the development of a process workflow for implementing prefabrication in building construction followed by a practical approach, which was executed with two case studies. It was planned in such a way that, the first case study gives a first-hand experience for the workers at the site on the BIM model so that they can make much use of the created BIM model, which is a better representation compared to the traditional 2D plan. The main aim of the first case study is to create a belief in the implementation of BIM Models, which was succeeded by the execution of offshore prefabrication in the second case study. Based on the case studies, the time analysis was made and it is inferred that the implementation of BIM for prefabrication can reduce construction time, ensures minimal wastes, better accuracy, less problem-solving at the construction site. It was observed that this process requires more planning time, better communication between different disciplines, which was the major obstacle for successful implementation. This paper was carried out from the perspective of small and medium-sized mechanical contracting companies for the private building sector in Germany. KW - building information modelling KW - HVAC KW - prefabrication KW - construction KW - small and medium scaled companies Y1 - 2021 U6 - http://dx.doi.org/10.2495/BIM210101 SN - 1743-3509 N1 - 4th International Conference on Building Information Modelling (BIM) in Design, Construction and Operations, 1–3 September 2021. Santiago de Compostela, Spain SP - 117 EP - 126 PB - WIT Press CY - Southampton ER - TY - CHAP A1 - Schulze-Buxloh, Lina A1 - Groß, Rolf Fritz T1 - Miniature urban farming plant: a complex educational “Toy” for engineering students T2 - The Future of Education 11th Edition 2021 N2 - Urban farming is an innovative and sustainable way of food production and is becoming more and more important in smart city and quarter concepts. It also enables the production of certain foods in places where they usually dare not produced, such as production of fish or shrimps in large cities far away from the coast. Unfortunately, it is not always possible to show students such concepts and systems in real life as part of courses: visits of such industry plants are sometimes not possible because of distance or are permitted by the operator for hygienic reasons. In order to give the students the opportunity of getting into contact with such an urban farming system and its complex operation, an industrial urban farming plant was set up on a significantly smaller scale. Therefore, all needed technical components like water aeriation, biological and mechanical filtration or water circulation have been replaced either by aquarium components or by self-designed parts also using a 3D-printer. Students from different courses like mechanical engineering, smart building engineering, biology, electrical engineering, automation technology and civil engineering were involved in this project. This “miniature industrial plant” was also able to start operation and has now been running for two years successfully. Due to Corona pandemic, home office and remote online lectures, the automation of this miniature plant should be brought to a higher level in future for providing a good control over the system and water quality remotely. The aim of giving the student a chance to get to know the operation of an urban farming plant was very well achieved and the students had lots of fun in “playing” and learning with it in a realistic way. KW - urban farming KW - food production KW - smart engineering KW - 3D printing KW - sustainability Y1 - 2021 N1 - FOE 2021 : The Future of Education International Conference – Fully Virtual Edition; 01.07.2021-02.07.2021; Florence, Italy ER - TY - JOUR A1 - Vögele, Stefan A1 - Josyabhatla, Vishnu Teja A1 - Ball, Christopher A1 - Rhoden, Imke A1 - Grajewski, Matthias A1 - Rübbelke, Dirk A1 - Kuckshinrichs, Wilhelm T1 - Robust assessment of energy scenarios from stakeholders' perspectives JF - Energy N2 - Using scenarios is vital in identifying and specifying measures for successfully transforming the energy system. Such transformations can be particularly challenging and require the support of a broader set of stakeholders. Otherwise, there will be opposition in the form of reluctance to adopt the necessary technologies. Usually, processes for considering stakeholders' perspectives are very time-consuming and costly. In particular, there are uncertainties about how to deal with modifications in the scenarios. In principle, new consulting processes will be required. In our study, we show how multi-criteria decision analysis can be used to analyze stakeholders' attitudes toward transition paths. Since stakeholders differ regarding their preferences and time horizons, we employ a multi-criteria decision analysis approach to identify which stakeholders will support or oppose a transition path. We provide a flexible template for analyzing stakeholder preferences toward transition paths. This flexibility comes from the fact that our multi-criteria decision aid-based approach does not involve intensive empirical work with stakeholders. Instead, it involves subjecting assumptions to robustness analysis, which can help identify options to influence stakeholders' attitudes toward transitions. Y1 - 2023 U6 - http://dx.doi.org/10.1016/j.energy.2023.128326 SN - 1873-6785 (Online) SN - 0360-5442 (Print) IS - In Press, Article 128326 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Waldvogel, Janice A1 - Freyler, Kathrin A1 - Helm, Michael A1 - Monti, Elena A1 - Stäudle, Benjamin A1 - Gollhofer, Albert A1 - Narici, Marco V. A1 - Ritzmann, Ramona A1 - Albracht, Kirsten T1 - Changes in gravity affect neuromuscular control, biomechanics, and muscle-tendon mechanics in energy storage and dissipation tasks JF - Journal of Applied Physiology N2 - This study evaluates neuromechanical control and muscle-tendon interaction during energy storage and dissipation tasks in hypergravity. During parabolic flights, while 17 subjects performed drop jumps (DJs) and drop landings (DLs), electromyography (EMG) of the lower limb muscles was combined with in vivo fascicle dynamics of the gastrocnemius medialis, two-dimensional (2D) kinematics, and kinetics to measure and analyze changes in energy management. Comparisons were made between movement modalities executed in hypergravity (1.8 G) and gravity on ground (1 G). In 1.8 G, ankle dorsiflexion, knee joint flexion, and vertical center of mass (COM) displacement are lower in DJs than in DLs; within each movement modality, joint flexion amplitudes and COM displacement demonstrate higher values in 1.8 G than in 1 G. Concomitantly, negative peak ankle joint power, vertical ground reaction forces, and leg stiffness are similar between both movement modalities (1.8 G). In DJs, EMG activity in 1.8 G is lower during the COM deceleration phase than in 1 G, thus impairing quasi-isometric fascicle behavior. In DLs, EMG activity before and during the COM deceleration phase is higher, and fascicles are stretched less in 1.8 G than in 1 G. Compared with the situation in 1 G, highly task-specific neuromuscular activity is diminished in 1.8 G, resulting in fascicle lengthening in both movement modalities. Specifically, in DJs, a high magnitude of neuromuscular activity is impaired, resulting in altered energy storage. In contrast, in DLs, linear stiffening of the system due to higher neuromuscular activity combined with lower fascicle stretch enhances the buffering function of the tendon, and thus the capacity to safely dissipate energy. KW - electromyography KW - locomotion KW - overload KW - stretch-shortening cycle KW - ultrasound Y1 - 2023 U6 - http://dx.doi.org/10.1152/japplphysiol.00279.2022 SN - 1522-1601 (Onlineausgabe) SN - 8750-7587 (Druckausgabe) VL - 134 IS - 1 SP - 190 EP - 202 PB - American Physiological Society CY - Bethesda, Md. ER - TY - JOUR A1 - Luft, Angela A1 - Bremen, Sebastian A1 - Luft, Nils T1 - A cost/benefit and flexibility evaluation framework for additive technologies in strategic factory planning JF - Processes N2 - There is a growing demand for more flexibility in manufacturing to counter the volatility and unpredictability of the markets and provide more individualization for customers. However, the design and implementation of flexibility within manufacturing systems are costly and only economically viable if applicable to actual demand fluctuations. To this end, companies are considering additive manufacturing (AM) to make production more flexible. This paper develops a conceptual model for the impact quantification of AM on volume and mix flexibility within production systems in the early stages of the factory-planning process. Together with the model, an application guideline is presented to help planners with the flexibility quantification and the factory design process. Following the development of the model and guideline, a case study is presented to indicate the potential impact additive technologies can have on manufacturing flexibility Within the case study, various scenarios with different production system configurations and production programs are analyzed, and the impact of the additive technologies on volume and mix flexibility is calculated. This work will allow factory planners to determine the potential impacts of AM on manufacturing flexibility in an early planning stage and design their production systems accordingly. KW - additive manufacturing KW - factory planning KW - manufacturing flexibility KW - volume flexibility KW - mix flexibility Y1 - 2023 U6 - http://dx.doi.org/10.3390/pr11071968 SN - 2227-9717 VL - 11 IS - 7 PB - MDPI CY - Basel ER - TY - CHAP A1 - Eggert, Mathias A1 - Weber, Jannik T1 - What drives the purchase decision in Instagram stores? T2 - ECIS 2023 Research Papers N2 - The popularity of social media and particularly Instagram grows steadily. People use the different platforms to share pictures as well as videos and to communicate with friends. The potential of social media platforms is also being used for marketing purposes and for selling products. While for Facebook and other online social media platforms the purchase decision factors are investigated several times, Instagram stores remain mainly unattended so far. The present research work closes this gap and sheds light into decisive factors for purchasing products offered in Instagram stores. A theoretical research model, which contains selected constructs that are assumed to have a significant influence on Instagram user´s purchase intention, is developed. The hypotheses are evaluated by applying structural equation modelling on survey data containing 127 relevant participants. The results of the study reveal that ‘trust’, ‘personal recommendation’, and ‘usability’ significantly influences user’s buying intention in Instagram stores. KW - Instagram store KW - shopping behavior KW - purchase factor KW - PLS KW - structural equation model Y1 - 2023 N1 - ECIS 2023, European Conference on Information Systems, Kristiansand, Norway, June 11.-16. SP - 1 EP - 17 ER - TY - CHAP A1 - Steuer-Dankert, Linda T1 - Training future skills - sustainability, interculturality & innovation in a digital design thinking format T2 - Proceedings of the 19th International CDIO Conference N2 - The complex questions of today for a world of tomorrow are characterized by their global impact. Solutions must therefore not only be sustainable in the sense of the three pillars of sustainability (economic, environmental, and social) but must also function globally. This goes hand in hand with the need for intercultural acceptance of developed services and products. To achieve this, engineers, as the problem solvers of the future, must be able to work in intercultural teams on appropriate solutions, and be sensitive to intercultural perspectives. To equip the engineers of the future with the so-called future skills, teaching concepts are needed in which students can acquire these methods and competencies in application-oriented formats. The presented course "Applying Design Thinking - Sustainability, Innovation and Interculturality" was developed to teach future skills from the competency areas Digital Key Competencies, Classical Competencies and Transformative Competencies. The CDIO Standard 3.0, in particular the standards 5, 6, 7 and 8, was used as a guideline. The course aims to prepare engineering students from different disciplines and cultures for their future work in an international environment by combining a digital teaching format with an interdisciplinary, transdisciplinary and intercultural setting for solving sustainability challenges. The innovative moment lies in the digital application of design thinking and the inclusion of intercultural as well as trans- and interdisciplinary perspectives in innovation development processes. In this paper, the concept of the course will be presented in detail and the particularities of a digital implementation of design thinking will be addressed. Subsequently, the potentials and challenges will be reflected and practical advice for integrating design thinking in engineering education will be given. KW - Design Thinking KW - Sustainability KW - Future Skills KW - Interculturality KW - Interdisciplinarity Y1 - 2023 N1 - Proceedings of the 19th International CDIO Conference, hosted by NTNU, Trondheim, Norway, June 26-29, 2023 ER - TY - JOUR A1 - Rabehi, Amine A1 - Garlan, Benjamin A1 - Achtsnicht, Stefan A1 - Krause, Hans-Joachim A1 - Offenhäusser, Andreas A1 - Ngo, Kieu A1 - Neveu, Sophie A1 - Graff-Dubois, Stephanie A1 - Kokabi, Hamid T1 - Magnetic detection structure for Lab-on-Chip applications based on the frequency mixing technique JF - Sensors N2 - A magnetic frequency mixing technique with a set of miniaturized planar coils was investigated for use with a completely integrated Lab-on-Chip (LoC) pathogen sensing system. The system allows the detection and quantification of superparamagnetic beads. Additionally, in terms of magnetic nanoparticle characterization ability, the system can be used for immunoassays using the beads as markers. Analytical calculations and simulations for both excitation and pick-up coils are presented; the goal was to investigate the miniaturization of simple and cost-effective planar spiral coils. Following these calculations, a Printed Circuit Board (PCB) prototype was designed, manufactured, and tested for limit of detection, linear response, and validation of theoretical concepts. Using the magnetic frequency mixing technique, a limit of detection of 15 µg/mL of 20 nm core-sized nanoparticles was achieved without any shielding. KW - Lab-on-Chip KW - magnetic sensing KW - frequency mixing KW - superparamagnetic nanoparticles KW - magnetic beads Y1 - 2018 U6 - http://dx.doi.org/10.3390/s18061747 SN - 1424-8220 VL - 18 IS - 6 PB - MDPI CY - Basel ER -