TY - JOUR A1 - Trapp, Svenja A1 - Lammers, Tom A1 - Engudar, Gokce A1 - Hoehr, Cornelia A1 - Denkova, Antonia G. A1 - Paulßen, Elisabeth A1 - de Kruijff, Robin M. T1 - Membrane-based microfluidic solvent extraction of Ga-68 from aqueous Zn solutions: towards an automated cyclotron production loop JF - EJNMMI Radiopharmacy and Chemistry KW - Microfluidic solvent extraction KW - Ga-68 KW - Cyclotron production KW - Medical radionuclide production KW - Metal contaminants Y1 - 2023 U6 - http://dx.doi.org/10.1186/s41181-023-00195-2 SN - 2365-421X VL - 2023 IS - 8, Article number: 9 SP - 1 EP - 14 PB - Springer Nature ER - TY - JOUR A1 - Cheenakula, Dheeraja A1 - Griebel, Kai A1 - Montag, David A1 - Grömping, Markus ED - Huang, Xiaowu T1 - Concept development of a mainstream deammonification and comparison with conventional process in terms of energy, performance and economical construction perspectives JF - Frontiers in Microbiology N2 - Deammonification for nitrogen removal in municipal wastewater in temperate and cold climate zones is currently limited to the side stream of municipal wastewater treatment plants (MWWTP). This study developed a conceptual model of a mainstream deammonification plant, designed for 30,000 P.E., considering possible solutions corresponding to the challenging mainstream conditions in Germany. In addition, the energy-saving potential, nitrogen elimination performance and construction-related costs of mainstream deammonification were compared to a conventional plant model, having a single-stage activated sludge process with upstream denitrification. The results revealed that an additional treatment step by combining chemical precipitation and ultra-fine screening is advantageous prior the mainstream deammonification. Hereby chemical oxygen demand (COD) can be reduced by 80% so that the COD:N ratio can be reduced from 12 to 2.5. Laboratory experiments testing mainstream conditions of temperature (8–20°C), pH (6–9) and COD:N ratio (1–6) showed an achievable volumetric nitrogen removal rate (VNRR) of at least 50 gN/(m3∙d) for various deammonifying sludges from side stream deammonification systems in the state of North Rhine-Westphalia, Germany, where m3 denotes reactor volume. Assuming a retained Norganic content of 0.0035 kgNorg./(P.E.∙d) from the daily loads of N at carbon removal stage and a VNRR of 50 gN/(m3∙d) under mainstream conditions, a resident-specific reactor volume of 0.115 m3/(P.E.) is required for mainstream deammonification. This is in the same order of magnitude as the conventional activated sludge process, i.e., 0.173 m3/(P.E.) for an MWWTP of size class of 4. The conventional plant model yielded a total specific electricity demand of 35 kWh/(P.E.∙a) for the operation of the whole MWWTP and an energy recovery potential of 15.8 kWh/(P.E.∙a) through anaerobic digestion. In contrast, the developed mainstream deammonification model plant would require only a 21.5 kWh/(P.E.∙a) energy demand and result in 24 kWh/(P.E.∙a) energy recovery potential, enabling the mainstream deammonification model plant to be self-sufficient. The retrofitting costs for the implementation of mainstream deammonification in existing conventional MWWTPs are nearly negligible as the existing units like activated sludge reactors, aerators and monitoring technology are reusable. However, the mainstream deammonification must meet the performance requirement of VNRR of about 50 gN/(m3∙d) in this case. KW - anammox KW - energy efficiency KW - mainstream deammonification KW - nitrogen elimination KW - wastewater Y1 - 2023 U6 - http://dx.doi.org/10.3389/fmicb.2023.1155235 SN - 1664-302X VL - 14 IS - 11155235 SP - 1 EP - 15 PB - Frontiers ER - TY - JOUR A1 - Grajewski, Matthias A1 - Kleefeld, Andreas T1 - Detecting and approximating decision boundaries in low-dimensional spaces JF - Numerical Algorithms N2 - A method for detecting and approximating fault lines or surfaces, respectively, or decision curves in two and three dimensions with guaranteed accuracy is presented. Reformulated as a classification problem, our method starts from a set of scattered points along with the corresponding classification algorithm to construct a representation of a decision curve by points with prescribed maximal distance to the true decision curve. Hereby, our algorithm ensures that the representing point set covers the decision curve in its entire extent and features local refinement based on the geometric properties of the decision curve. We demonstrate applications of our method to problems related to the detection of faults, to multi-criteria decision aid and, in combination with Kirsch’s factorization method, to solving an inverse acoustic scattering problem. In all applications we considered in this work, our method requires significantly less pointwise classifications than previously employed algorithms. KW - MCDA KW - Inverse scattering problem KW - Fault approximation KW - Fault detection Y1 - 2023 SN - 1572-9265 N1 - Corresponding author: Matthias Grajewski VL - 93 IS - 4 PB - Springer Science+Business Media CY - Dordrecht ER - TY - JOUR A1 - Falkenberg, Fabian A1 - Voß, Leonie A1 - Bott, Michael A1 - Bongaerts, Johannes A1 - Siegert, Petra T1 - New robust subtilisins from halotolerant and halophilic Bacillaceae JF - Applied Microbiology and Biotechnology N2 - The aim of the present study was the characterisation of three true subtilisins and one phylogenetically intermediate subtilisin from halotolerant and halophilic microorganisms. Considering the currently growing enzyme market for efficient and novel biocatalysts, data mining is a promising source for novel, as yet uncharacterised enzymes, especially from halophilic or halotolerant Bacillaceae, which offer great potential to meet industrial needs. Both halophilic bacteria Pontibacillus marinus DSM 16465ᵀ and Alkalibacillus haloalkaliphilus DSM 5271ᵀ and both halotolerant bacteria Metabacillus indicus DSM 16189 and Litchfieldia alkalitelluris DSM 16976ᵀ served as a source for the four new subtilisins SPPM, SPAH, SPMI and SPLA. The protease genes were cloned and expressed in Bacillus subtilis DB104. Purification to apparent homogeneity was achieved by ethanol precipitation, desalting and ion-exchange chromatography. Enzyme activity could be observed between pH 5.0–12.0 with an optimum for SPPM, SPMI and SPLA around pH 9.0 and for SPAH at pH 10.0. The optimal temperature for SPMI and SPLA was 70 °C and for SPPM and SPAH 55 °C and 50 °C, respectively. All proteases showed high stability towards 5% (w/v) SDS and were active even at NaCl concentrations of 5 M. The four proteases demonstrate potential for future biotechnological applications. KW - Biotechnological application KW - Bacillaceae KW - Subtilisin KW - Subtilases KW - Halotolerant protease Y1 - 2023 U6 - http://dx.doi.org/10.1007/s00253-023-12553-w SN - 1432-0614 N1 - Corresponding author: Petra Siegert VL - 107 SP - 3939 EP - 3954 PB - Springer Nature CY - Berlin 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 - 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 - 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 - 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 - 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 - Baier, Ralph A1 - Brauner, Philipp A1 - Brillowski, Florian A1 - Dammers, Hannah A1 - Liehner, Luca A1 - Pütz, Sebastian A1 - Schneider, Sebastian A1 - Schollemann, Alexander A1 - Steuer-Dankert, Linda A1 - Vervier, Luisa A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Mertens, Alexander A1 - Nagel, Saskia K. A1 - Schuh, Günther A1 - Ziefle, Martina A1 - Nitsch, Verena ED - Brecher, Christian ED - Schuh, Günther ED - van der Alst, Wil ED - Jarke, Matthias ED - Piller, Frank T. ED - Padberg, Melanie T1 - Human-centered work design for the internet of production T2 - Internet of production - fundamentals, applications and proceedings N2 - Like all preceding transformations of the manufacturing industry, the large-scale usage of production data will reshape the role of humans within the sociotechnical production ecosystem. To ensure that this transformation creates work systems in which employees are empowered, productive, healthy, and motivated, the transformation must be guided by principles of and research on human-centered work design. Specifically, measures must be taken at all levels of work design, ranging from (1) the work tasks to (2) the working conditions to (3) the organizational level and (4) the supra-organizational level. We present selected research across all four levels that showcase the opportunities and requirements that surface when striving for human-centered work design for the Internet of Production (IoP). (1) On the work task level, we illustrate the user-centered design of human-robot collaboration (HRC) and process planning in the composite industry as well as user-centered design factors for cognitive assistance systems. (2) On the working conditions level, we present a newly developed framework for the classification of HRC workplaces. (3) Moving to the organizational level, we show how corporate data can be used to facilitate best practice sharing in production networks, and we discuss the implications of the IoP for new leadership models. Finally, (4) on the supra-organizational level, we examine overarching ethical dimensions, investigating, e.g., how the new work contexts affect our understanding of responsibility and normative values such as autonomy and privacy. Overall, these interdisciplinary research perspectives highlight the importance and necessary scope of considering the human factor in the IoP. KW - Responsibility KW - Privacy KW - Digital leadership KW - Best practice sharing KW - Cognitive assistance system KW - Human-robot collaboration KW - Human-centered work design Y1 - 2023 SN - 978-3-030-98062-7 U6 - http://dx.doi.org/10.1007/978-3-030-98062-7_19-1 N1 - Part of the book series: Interdisciplinary Excellence Accelerator Series (IDEAS) SP - 1 EP - 23 PB - Springer CY - Cham 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 - 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 - 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 - 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 - Rhoden, Imke A1 - Ball, Christopher Stephen A1 - Grajewski, Matthias A1 - Kuckshinrich, Wilhelm T1 - Reverse engineering of stakeholder preferences – A multi-criteria assessment of the German passenger car sector JF - Renewable and Sustainable Energy Reviews N2 - Germany is a frontrunner in setting frameworks for the transition to a low-carbon system. The mobility sector plays a significant role in this shift, affecting different people and groups on multiple levels. Without acceptance from these stakeholders, emission targets are out of reach. This research analyzes how the heterogeneous preferences of various stakeholders align with the transformation of the mobility sector, looking at the extent to which the German transformation paths are supported and where stakeholders are located. Under the research objective of comparing stakeholders' preferences to identify which car segments require additional support for a successful climate transition, a status quo of stakeholders and car performance criteria is the foundation for the analysis. Stakeholders' hidden preferences hinder the derivation of criteria weightings from stakeholders; therefore, a ranking from observed preferences is used. This study's inverse multi-criteria decision analysis means that weightings can be predicted and used together with a recalibrated performance matrix to explore future preferences toward car segments. Results show that stakeholders prefer medium-sized cars, with the trend pointing towards the increased potential for alternative propulsion technologies and electrified vehicles. These insights can guide the improved targeting of policy supporting the energy and mobility transformation. Additionally, the method proposed in this work can fully handle subjective approaches while incorporating a priori information. A software implementation of the proposed method completes this work and is made publicly available. KW - Regionalization KW - Multi-criteria decision analysis KW - Preference assessment KW - E-Mobility KW - Mobility transition Y1 - 2023 U6 - http://dx.doi.org/10.1016/j.rser.2023.113352 SN - 1364-0321 VL - 181 IS - July 2023 SP - Article number: 113352 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Maurer, Florian A1 - Rieke, Christian A1 - Schemm, Ralf A1 - Stollenwerk, Dominik T1 - Analysis of an urban grid with high photovoltaic and e-mobility penetration JF - Energies N2 - This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub. KW - distribution grid simulation KW - smart-charging KW - e-mobility Y1 - 2023 U6 - http://dx.doi.org/10.3390/en16083380 SN - 1996-1073 N1 - This article belongs to the Special Issue "Advanced Solutions for the Efficient Integration of Electric Vehicles in Electricity Grids" N1 - Corresponding author: Florian Maurer VL - 16 IS - 8 PB - MDPI CY - Basel ER - TY - JOUR A1 - Fayyazi, Mojgan A1 - Sardar, Paramjotsingh A1 - Thomas, Sumit Infent A1 - Daghigh, Roonak A1 - Jamali, Ali A1 - Esch, Thomas A1 - Kemper, Hans A1 - Langari, Reza A1 - Khayyam, Hamid T1 - Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles N2 - Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed. KW - optimization system KW - intelligent control KW - fuel cell vehicle KW - machine learning KW - artificial intelligence KW - intelligent energy management Y1 - 2023 U6 - http://dx.doi.org/10.3390/su15065249 N1 - This article belongs to the Special Issue "Circular Economy and Artificial Intelligence" VL - 15 IS - 6 SP - 38 PB - MDPI CY - Basel ER - TY - INPR A1 - Bornheim, Tobias A1 - Niklas, Grieger A1 - Blaneck, Patrick Gustav A1 - Bialonski, Stephan T1 - Preprint: Speaker attribution in German parliamentary debates with QLoRA-adapted large language models T2 - Journal for Language Technology and Computational Linguistics N2 - The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems. Y1 - 2023 U6 - http://dx.doi.org/10.48550/arXiv.2309.09902 N1 - Veröffentlichte Version verfügbar unter: https://doi.org/10.21248/jlcl.37.2024.244 ER - TY - JOUR A1 - Eggert, Mathias A1 - Kling, Rene T1 - How to distribute charging requests of electronic vehicles? A reservation-based approach JF - International Journal of Intelligent Transportation Systems Research N2 - The number of electronic vehicles increase steadily while the space for extending the charging infrastructure is limited. In particular in urban areas, where parking spaces in attractive areas are famous, opportunities to setup new charging stations is very limited. This leads to an overload of some very attractive charging stations and an underutilization of less attractive ones. Against this background, the paper at hand presents the design of an e-vehicle reservation system that aims at distributing the utilization of the charging infrastructure, particularly in urban areas. By applying a design science approach, the requirements for a reservation-based utilization approach are elicited and a model for a suitable distribution approach and its instantiation are developed. The artefact is evaluated by simulating the distribution effects based on data of real charging station utilizations. KW - Simulation KW - Parking KW - Charging station KW - Utilization improvement KW - Reservation system KW - Electronic vehicle Y1 - 2023 U6 - http://dx.doi.org/10.1007/s13177-023-00367-z SN - 1868-8659 N1 - Corresponding author: Mathias Eggert VL - 21 IS - 2023 SP - 437 EP - 460 PB - Springer CY - Berlin, Heidelberg, New York ER - TY - JOUR A1 - Adels, Klaudia A1 - Elbers, Gereon A1 - Diehl, Bernd A1 - Monakhova, Yulia T1 - Multicomponent analysis of dietary supplements containing glucosamine and chondroitin: comparative low- and high-field NMR spectroscopic study JF - Analytical Sciences N2 - 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. KW - Glucosamine KW - Chondroitin sulfate KW - Polysaccharides KW - Dietary supplements KW - High-field NMR Y1 - 2023 U6 - http://dx.doi.org/10.1007/s44211-023-00433-2 SN - 1348-2246 (Online) SN - 0910-6340 (Print) N1 - Corresponding author: Yulia Monakhova VL - 2023 PB - Springer Verlag CY - Cham ER -