@unpublished{31545, abstract = {{Knowledge graph embedding research has mainly focused on learning continuous representations of entities and relations tailored towards the link prediction problem. Recent results indicate an ever increasing predictive ability of current approaches on benchmark datasets. However, this effectiveness often comes with the cost of over-parameterization and increased computationally complexity. The former induces extensive hyperparameter optimization to mitigate malicious overfitting. The latter magnifies the importance of winning the hardware lottery. Here, we investigate a remedy for the first problem. We propose a technique based on Kronecker decomposition to reduce the number of parameters in a knowledge graph embedding model, while retaining its expressiveness. Through Kronecker decomposition, large embedding matrices are split into smaller embedding matrices during the training process. Hence, embeddings of knowledge graphs are not plainly retrieved but reconstructed on the fly. The decomposition ensures that elementwise interactions between three embedding vectors are extended with interactions within each embedding vector. This implicitly reduces redundancy in embedding vectors and encourages feature reuse. To quantify the impact of applying Kronecker decomposition on embedding matrices, we conduct a series of experiments on benchmark datasets. Our experiments suggest that applying Kronecker decomposition on embedding matrices leads to an improved parameter efficiency on all benchmark datasets. Moreover, empirical evidence suggests that reconstructed embeddings entail robustness against noise in the input knowledge graph. To foster reproducible research, we provide an open-source implementation of our approach, including training and evaluation scripts as well as pre-trained models in our knowledge graph embedding framework.}}, author = {{Demir, Caglar and Lienen, Julian and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{arXiv:2205.06560}}, title = {{{Kronecker Decomposition for Knowledge Graph Embeddings}}}, year = {{2022}}, } @phdthesis{31556, abstract = {{Mehrzieloptimierung behandelt Probleme, bei denen mehrere skalare Zielfunktionen simultan optimiert werden sollen. Ein Punkt ist in diesem Fall optimal, wenn es keinen anderen Punkt gibt, der mindestens genauso gut ist in allen Zielfunktionen und besser in mindestens einer Zielfunktion. Ein notwendiges Optimalitätskriterium lässt sich über Ableitungsinformationen erster Ordnung der Zielfunktionen herleiten. Die Menge der Punkte, die dieses notwendige Kriterium erfüllen, wird als Pareto-kritische Menge bezeichnet. Diese Arbeit enthält neue Resultate über Pareto-kritische Mengen für glatte und nicht-glatte Mehrzieloptimierungsprobleme, sowohl was deren Berechnung betrifft als auch deren Struktur. Im glatten Fall erfolgt die Berechnung über ein Fortsetzungsverfahren, im nichtglatten Fall über ein Abstiegsverfahren. Anschließend wird die Struktur des Randes der Pareto-kritischen Menge analysiert, welcher aus Pareto-kritischen Mengen kleinerer Subprobleme besteht. Schlussendlich werden inverse Probleme betrachtet, bei denen zu einer gegebenen Datenmenge ein Zielfunktionsvektor gefunden werden soll, für den die Datenpunkte kritisch sind.}}, author = {{Gebken, Bennet}}, title = {{{Computation and analysis of Pareto critical sets in smooth and nonsmooth multiobjective optimization}}}, doi = {{10.17619/UNIPB/1-1327}}, year = {{2022}}, } @article{33009, abstract = {{Abstract Purpose The present work aimed to delineate (i) a revised protocol according to recent methodological developments in evidence generation, to (ii) describe its interpretation, the assessment of the overall certainty of evidence and to (iii) outline an Evidence to Decision framework for deriving an evidence-based guideline on quantitative and qualitative aspects of dietary protein intake. Methods A methodological protocol to systematically investigate the association between dietary protein intake and several health outcomes and for deriving dietary protein intake recommendations for the primary prevention of various non-communicable diseases in the general adult population was developed. Results The developed methodological protocol relies on umbrella reviews including systematic reviews with or without meta-analyses. Systematic literature searches in three databases will be performed for each health-related outcome. The methodological quality of all selected systematic reviews will be evaluated using a modified version of AMSTAR 2, and the outcome-specific certainty of evidence for systematic reviews with or without meta-analysis will be assessed with NutriGrade. The general outline of the Evidence to Decision framework foresees that recommendations in the derived guideline will be given based on the overall certainty of evidence as well as on additional criteria such as sustainability. Conclusion The methodological protocol permits a systematic evaluation of published systematic reviews on dietary protein intake and its association with selected health-related outcomes. An Evidence to Decision framework will be the basis for the overall conclusions and the resulting recommendations for dietary protein intake. }}, author = {{Kroke, Anja and Schmidt, Annemarie and Amini, Anna M. and Kalotai, Nicole and Lehmann, Andreas and Haardt, Julia and Bauer, Jürgen M. and Bischoff-Ferrari, Heike A. and Boeing, Heiner and Egert, Sarah and Ellinger, Sabine and Kühn, Tilman and Louis, Sandrine and Lorkowski, Stefan and Nimptsch, Katharina and Remer, Thomas and Schulze, Matthias B. and Siener, Roswitha and Stangl, Gabriele I. and Volkert, Dorothee and Zittermann, Armin and Buyken, Anette E. and Watzl, Bernhard and Schwingshackl, Lukas}}, issn = {{1436-6207}}, journal = {{European Journal of Nutrition}}, keywords = {{Nutrition and Dietetics, Medicine (miscellaneous)}}, number = {{4}}, pages = {{2091--2101}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Dietary protein intake and health-related outcomes: a methodological protocol for the evidence evaluation and the outline of an evidence to decision framework underlying the evidence-based guideline of the German Nutrition Society}}}, doi = {{10.1007/s00394-021-02789-5}}, volume = {{61}}, year = {{2022}}, } @inproceedings{29934, abstract = {{Tire and road wear are a major source of emissions of nonexhaust particulate matter (PM) and make up the largest share of microplastics in the environment. To reduce tire wear through numerical optimization of a vehicle's suspension system, fast simulations of the representative usage of a vehicle are needed. Therefore, this contribution evaluates if instead of a full simulation of a representative test drive, only specific driving maneuvers resulting from a clustering of the driving data can be used to predict tire wear. As a measure for tire wear, the friction work between tire and road is calculated. It is shown that enough clusters result in negligible deviations between the total friction work of the full simulation and the cluster simulations as well as between the distributions of the friction work over the tire width. The calculation time can be reduced to about 1% of the full simulation.}}, author = {{Muth, Lars and Noll, Christian and Sextro, Walter}}, booktitle = {{Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021}}, editor = {{Orlova, Anna and Cole, David}}, isbn = {{978-3-031-07304-5}}, keywords = {{Tire Wear, Vehicle Dynamics, Clustering, Virtual Test}}, location = {{Saint Petersburg, Russia}}, publisher = {{Springer}}, title = {{{Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data}}}, doi = {{10.1007/978-3-031-07305-2_92}}, year = {{2022}}, } @article{33090, abstract = {{AbstractHeated tool butt welding is a method often used for joining thermoplastics, especially when the components are made out of different materials. The quality of the connection between the components crucially depends on a suitable choice of the parameters of the welding process, such as heating time, temperature, and the precise way how the parts are then welded. Moreover, when different materials are to be joined, the parameter values need to be tailored to the specifics of the respective material. To this end, in this paper, three approaches to tailor the parameter values to optimize the quality of the connection are compared: a heuristic by Potente, statistical experimental design, and Bayesian optimization. With the suitability for practice in mind, a series of experiments are carried out with these approaches, and their capabilities of proposing well-performing parameter values are investigated. As a result, Bayesian optimization is found to yield peak performance, but the costs for optimization are substantial. In contrast, the Potente heuristic does not require any experimentation and recommends parameter values with competitive quality.}}, author = {{Gevers, Karina and Tornede, Alexander and Wever, Marcel Dominik and Schöppner, Volker and Hüllermeier, Eyke}}, issn = {{0043-2288}}, journal = {{Welding in the World}}, keywords = {{Metals and Alloys, Mechanical Engineering, Mechanics of Materials}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials}}}, doi = {{10.1007/s40194-022-01339-9}}, year = {{2022}}, } @unpublished{33150, abstract = {{In this article, we build on previous work to present an optimization algorithm for nonlinearly constrained multi-objective optimization problems. The algorithm combines a surrogate-assisted derivative-free trust-region approach with the filter method known from single-objective optimization. Instead of the true objective and constraint functions, so-called fully linear models are employed and we show how to deal with the gradient inexactness in the composite step setting, adapted from single-objective optimization as well. Under standard assumptions, we prove convergence of a subset of iterates to a quasi-stationary point and if constraint qualifications hold, then the limit point is also a KKT-point of the multi-objective problem.}}, author = {{Berkemeier, Manuel Bastian and Peitz, Sebastian}}, booktitle = {{arXiv:2208.12094}}, title = {{{Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients}}}, year = {{2022}}, } @inproceedings{33240, author = {{Götte, Thorsten and Scheideler, Christian}}, booktitle = {{SPAA ’22: 34th ACM Symposium on Parallelism in Algorithms and Architectures, Philadelphia, PA, USA, July 11 - 14, 2022}}, editor = {{Agrawal, Kunal and Lee, I-Ting Angelina}}, pages = {{99–101}}, publisher = {{ACM}}, title = {{{Brief Announcement: The (Limited) Power of Multiple Identities: Asynchronous Byzantine Reliable Broadcast with Improved Resilience through Collusion}}}, doi = {{10.1145/3490148.3538556}}, year = {{2022}}, } @inbook{30941, abstract = {{Decision support systems are crucial in helping decision makers to quickly identify optimal business decisions in increasingly volatile and complex business environments. However, the ideal DSS for one decision maker may not optimally address the requirements for decision support of another decision maker. This is due to differences between decision makers in business goals, regulatory restrictions or availability of resources such as data. By using a suboptimal DSS, decision makers risk implementing suboptimal decision recommendations which endanger the success of their business. This presents DSS developers with the challenge to implement a customizable DSS which can be tailored to the individual requirements for decision support of a single decision maker. In order to address this challenge, we suggest a decision support ecosystem in which DSS developers, decision makers and other domain experts collaborate using a shared platform to provide and combine reusable decision support services into a tailored DSS. The contribution of our paper is twofold: First, we define the concept of a decision support ecosystem with respect to existing digital business ecosystems and discuss expected benefits and challenges. Second, we present a reference architecture for a shared platform supporting the realization of a decision support ecosystem. We demonstrate our contributions in the example application domain of regional energy distribution network planning.}}, author = {{Kirchhoff, Jonas and Weskamp, Christoph and Engels, Gregor}}, booktitle = {{Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs}}, publisher = {{Springer}}, title = {{{Decision Support Ecosystems: Definition and Platform Architecture}}}, doi = {{10.1007/978-3-031-06530-9_8}}, volume = {{447}}, year = {{2022}}, } @inproceedings{33508, abstract = {{In this work, methods will be evaluated to numerically calculate the passive electrical parameters of planar coils. These parameters can then be used to optimize inductive applications such as wireless power transmission. The focus here will be on inductive localization, which uses high-frequency magnetic fields and the resulting induced voltage to provide localization through the coupling parameter mutual inductance. To achieve localization with high accuracy and best possible operation (resonance, signal strength, etc.), the coil parameters need to be well known. For this reason, some numerical methods for the calculation of these quantities are presented and validated. In addition, the physical effects are thereby considered in more detail, allowing the localization procedure to be better optimized compared to simulative black-box methods. The goal should be a dedicated simulation platform for planar coils to be able to develop training data for neural networks and to test and optimize localization algorithms.}}, author = {{Lange, Sven and Hedayat, Christian and Kuhn, Harald and Hilleringmann, Ulrich}}, booktitle = {{2022 Smart Systems Integration (SSI)}}, keywords = {{Simulation Environment, Inductive Localization, Coil Parameters, Inductive Applications, Near-Field}}, location = {{Grenoble, France}}, publisher = {{IEEE}}, title = {{{Modeling and Characterization of a 3D Environment for the Design of an Inductively Based Locating Method by Coil Couplings}}}, doi = {{10.1109/ssi56489.2022.9901416}}, year = {{2022}}, } @article{33714, abstract = {{AbstractIndustry 4.0 promises many potentials in production. Examples are a data-driven optimization of production processes of individual machines, driverless transport systems, and assistance systems. Nevertheless, companies are still hesitant to invest in Industry 4.0 applications. Studies show that one of the main reasons for that is the unclear economic benefit. In this work, we present a systematic approach for the evaluation of Industry 4.0 applications in production. The main goal of the systematic is to create transparency over the evaluation process of an investment in an Industry 4.0 application in production. The evaluation of a concrete technical solution in an existing production system is supported. As a theoretical foundation, a characterization of investments in Industry 4.0 applications is given. From that, a procedure model is derived. It puts the activities to be carried out, the tools to be used and results in a temporal context. The application of the systematic is shown on the basis of an application example.}}, author = {{Joppen, Robert and Kühn, Arno and Förster, Magdalena and Dumitrescu, Roman}}, issn = {{1868-7865}}, journal = {{Journal of the Knowledge Economy}}, keywords = {{Economics and Econometrics}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Evaluation of Industry 4.0 Applications in Production}}}, doi = {{10.1007/s13132-022-00959-2}}, year = {{2022}}, } @article{33713, abstract = {{AbstractThe development of technical systems requires close cooperation of stakeholders from different disciplines. This collaboration takes place in workshops. Driven by digitalization and by the current pandemic such workshops take place primarily online. Suitable collaboration tools and methods are crucial to success. At the beginning of such workshops, use and damage scenarios are identified. In this paper, we presented a method and tool for identifying and modeling use and damage scenarios, which we evaluated in 14 online workshops with a total of 118 participants over a period of almost 3 years.}}, author = {{Japs, Sergej and Schmidt, Sebastian and Kargl, Frank and Kaiser, Lydia and Kharatyan, Aschot and Dumitrescu, Roman}}, issn = {{2732-527X}}, journal = {{Proceedings of the Design Society}}, pages = {{1599--1608}}, publisher = {{Cambridge University Press (CUP)}}, title = {{{Collaborative Modeling of Use Case & Damage Scenarios in Online Workshops Using a 3D Environment}}}, doi = {{10.1017/pds.2022.162}}, volume = {{2}}, year = {{2022}}, } @inbook{33728, author = {{Bielak, C. R. and Böhnke, M. and Bobbert, M. and Meschut, G.}}, booktitle = {{The Minerals, Metals & Materials Series}}, isbn = {{9783031062117}}, issn = {{2367-1181}}, publisher = {{Springer International Publishing}}, title = {{{Development of a Numerical 3D Model for Analyzing Clinched Joints in Versatile Process Chains}}}, doi = {{10.1007/978-3-031-06212-4_15}}, year = {{2022}}, } @article{20731, abstract = {{We present a novel algorithm that allows us to gain detailed insight into the effects of sparsity in linear and nonlinear optimization, which is of great importance in many scientific areas such as image and signal processing, medical imaging, compressed sensing, and machine learning (e.g., for the training of neural networks). Sparsity is an important feature to ensure robustness against noisy data, but also to find models that are interpretable and easy to analyze due to the small number of relevant terms. It is common practice to enforce sparsity by adding the ℓ1-norm as a weighted penalty term. In order to gain a better understanding and to allow for an informed model selection, we directly solve the corresponding multiobjective optimization problem (MOP) that arises when we minimize the main objective and the ℓ1-norm simultaneously. As this MOP is in general non-convex for nonlinear objectives, the weighting method will fail to provide all optimal compromises. To avoid this issue, we present a continuation method which is specifically tailored to MOPs with two objective functions one of which is the ℓ1-norm. Our method can be seen as a generalization of well-known homotopy methods for linear regression problems to the nonlinear case. Several numerical examples - including neural network training - demonstrate our theoretical findings and the additional insight that can be gained by this multiobjective approach.}}, author = {{Bieker, Katharina and Gebken, Bennet and Peitz, Sebastian}}, journal = {{IEEE Transactions on Pattern Analysis and Machine Intelligence}}, number = {{11}}, pages = {{7797--7808}}, publisher = {{IEEE}}, title = {{{On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation}}}, doi = {{10.1109/TPAMI.2021.3114962}}, volume = {{44}}, year = {{2022}}, } @inproceedings{33967, author = {{Aguiliera, Marcos and Richa, Andréa W. and Schwarzmann, Alexander A. and Panconesi, Alessandro and Scheideler, Christian and Woelfel, Philipp}}, booktitle = {{PODC ’22: ACM Symposium on Principles of Distributed Computing, Salerno, Italy, July 25 - 29, 2022}}, editor = {{Milani, Alessia and Woelfel, Philipp}}, pages = {{1}}, publisher = {{ACM}}, title = {{{2022 Edsger W. Dijkstra Prize in Distributed Computing}}}, doi = {{10.1145/3519270.3538411}}, year = {{2022}}, } @article{34256, abstract = {{The 3D shear deformation and failure behaviour of a glass fibre reinforced polypropylene in a shear strain rate range of γ˙=2.2×10−4 to 3.4 1s is investigated. An Iosipescu testing setup on a servo-hydraulic high speed testing unit is used to experimentally characterise the in-plane and out-of-plane behaviour utilising three specimen configurations (12-, 13- and 31-direction). The experimental procedure as well as the testing results are presented and discussed. The measured shear stress–shear strain relations indicate a highly nonlinear behaviour and a distinct rate dependency. Two methods are investigated to derive according material characteristics: a classical engineering approach based on moduli and strengths and a data driven approach based on the curve progression. In all cases a Johnson–Cook based formulation is used to describe rate dependency. The analysis methodologies as well as the derived model parameters are described and discussed in detail. It is shown that a phenomenologically enhanced regression can be used to obtain material characteristics for a generalising constitutive model based on the data driven approach.}}, author = {{Gerritzen, Johannes and Hornig, Andreas and Gröger, Benjamin and Gude, Maik}}, issn = {{2504-477X}}, journal = {{Journal of Composites Science}}, keywords = {{Engineering (miscellaneous), Ceramics and Composites}}, number = {{10}}, publisher = {{MDPI AG}}, title = {{{A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters}}}, doi = {{10.3390/jcs6100318}}, volume = {{6}}, year = {{2022}}, } @article{34251, abstract = {{Joining by forming operations presents powerful and complex joining techniques. Clinching is a well-known joining process for use in sheet metalworking. Currently, clinched joints are focusing on mechanically enhanced connections. Additionally, the demand for integrating electrical requirements to transmit electrical currents will be increased in the future. This integration is particularly important, for instance, in the e-mobility sector. It enables connecting battery cells with electrical joints of aluminum and copper. Systematic use of the process-specific advantages of this joining method opens up the possibility to find and create electrically optimized connections. The optimization for the transmission of electrical currents will be demonstrated for clinched joints by adapting the tool geometry and the clinched joint design. Based on a comparison of the electrical joint resistance, the limit use temperature is defined for the joining materials used based on the microstructural condition and the aging condition due to artificial aging. As a result of the investigations carried out, reliable current transmission at a constant conductor temperature of up to 120 °C can be achieved for clinched copper–copper joints. In the case of pure aluminum joints and mixed joints of aluminum and copper, long-term stable current transmission can be ensured up to a conductor temperature of 100 °C.}}, author = {{Kalich, Jan and Matzke, Marcus and Pfeiffer, Wolfgang and Schlegel, Stephan and Kornhuber, Ludwig and Füssel, Uwe}}, issn = {{2075-4701}}, journal = {{Metals}}, keywords = {{General Materials Science, Metals and Alloys}}, number = {{10}}, publisher = {{MDPI AG}}, title = {{{Long-Term Behavior of Clinched Electrical Contacts}}}, doi = {{10.3390/met12101651}}, volume = {{12}}, year = {{2022}}, } @article{34254, abstract = {{A virtual test setup for investigating single fibres in a transverse shear flow based on a parallel-plate rheometer is presented. The investigations are carried out to verify a numerical representation of the fluid–structure interaction (FSI), where Arbitrary Lagrangian–Eulerian (ALE) and computational fluid dynamics (CFD) methods are used and evaluated. Both are suitable to simulate flexible solid structures in a transverse shear flow. Comparative investigations with different model setups and increasing complexity are presented. It is shown, that the CFD method with an interface-based coupling approach is not capable of handling small fibre diameters in comparison to large fluid domains due to mesh dependencies at the interface definitions. The ALE method is more suited for this task since fibres are embedded without any mesh restrictions. Element types beam, solid, and discrete are considered for fibre modelling. It is shown that the beam formulation for ALE and 3D solid elements for the CFD method are the preferred options.}}, author = {{Gröger, Benjamin and Wang, Jingjing and Bätzel, Tim and Hornig, Andreas and Gude, Maik}}, issn = {{1996-1944}}, journal = {{Materials}}, keywords = {{General Materials Science}}, number = {{20}}, publisher = {{MDPI AG}}, title = {{{Modelling and Simulation Strategies for Fluid–Structure-Interactions of Highly Viscous Thermoplastic Melt and Single Fibres—A Numerical Study}}}, doi = {{10.3390/ma15207241}}, volume = {{15}}, year = {{2022}}, } @article{34414, abstract = {{Given a steadily increasing demand on multi-material lightweight designs, fast and cost-efficient production technologies, such as the mechanical joining process clinching, are becoming more and more relevant for series production. Since the application of such joining techniques often base on the ability to reach similar or even better joint loading capacities compared to established joining processes (e.g., spot welding), few contributions investigated the systematic improvement of clinch joint characteristics. In this regard, the use of data-driven methods in combination with optimization algorithms showed already high potentials for the analysis of individual joints and the definition of optimal tool configurations. However, the often missing consideration of uncertainties, such as varying material properties, and the related calculation of their impact on clinch joint properties can lead to poor estimation results and thus to a decreased reliability of the entire joint connection. This can cause major challenges, especially for the design and dimensioning of safety-relevant components, such as in car bodies. Motivated by this, the presented contribution introduces a novel method for the robust estimation of clinch joint characteristics including uncertainties of varying and versatile process chains in mechanical joining. Therefore, the utilization of Gaussian process regression models is demonstrated and evaluated regarding the ability to achieve sufficient prediction qualities.}}, author = {{Zirngibl, Christoph and Schleich, Benjamin and Wartzack, Sandro}}, issn = {{0268-3768}}, journal = {{The International Journal of Advanced Manufacturing Technology}}, keywords = {{Industrial and Manufacturing Engineering, Computer Science Applications, Mechanical Engineering, Software, Control and Systems Engineering}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Robust estimation of clinch joint characteristics based on data-driven methods}}}, doi = {{10.1007/s00170-022-10441-7}}, year = {{2022}}, } @misc{33287, author = {{Moritzer, Elmar and Held, Christian and Hillemeyer, Johannes}}, booktitle = {{Joining Plastic}}, issn = {{1864-3450}}, pages = {{84--90}}, title = {{{Dimensionierung und Optimierung von im FDM-Verfahren 3D-gedruckten Direktverschraubungen aus ABS}}}, year = {{2022}}, } @article{35308, abstract = {{IntroductionIn 2012, the estimated global prevalence of pre-diabetes was 280 million, and the prevalence is expected to rise to 400 million by 2030. Oat-based foods are a good source of beta-glucans, which have been shown to lower postprandial blood glucose. Studies to evaluate the effectiveness of the long-term intake of beta-glucan-enriched bread as part of a habitual diet among individuals with pre-diabetes are needed. Therefore, we designed a multicentre intervention study in adults with pre-diabetes to investigate the effects of consumption of an oat-derived beta-glucan-enriched bread as part of a normal diet on glycated haemoglobin (HbA1c) in comparison to consumption of whole-grain wheat bread.Methods and analysisThe CarbHealth trial is a multicentre double-blind randomised controlled 16-week dietary intervention trial in participants 40–70 years of age with a body mass index of ≥27 kg/m2 and HbA1c of 35–50 mmol/mol. The study is conducted at four universities located in Norway, Sweden and Germany and uses intervention breads specifically designed for the trial by Nofima AS. The aim is to recruit 250 participants. The primary outcome is the difference in HbA1c between the intervention and the control groups. The main analysis will include intervention group, study centre and baseline HbA1c as independent variables in an analysis of covariance model.Ethics and disseminationThe study protocol was approved by respective ethical authorities in participating countries. The results of the study will be communicated through publication in international scientific journals and presentations at (inter)national conferences.Trial registration numberNCT04994327.}}, author = {{Hjorth, Therese and Schadow, Alena and Revheim, Ingrid and Spielau, Ulrike and Thomassen, Lise M and Meyer, Klara and Piotrowski, Katja and Rosendahl-Riise, Hanne and Rieder, Anne and Varela, Paula and Lysne, Vegard and Ballance, Simon and Koerner, Antje and Landberg, Rikard and Buyken, Anette and Dierkes, Jutta}}, issn = {{2044-6055}}, journal = {{BMJ Open}}, keywords = {{General Medicine}}, number = {{8}}, publisher = {{BMJ}}, title = {{{Sixteen-week multicentre randomised controlled trial to study the effect of the consumption of an oat beta-glucan-enriched bread versus a whole-grain wheat bread on glycaemic control among persons with pre-diabetes: a study protocol of the CarbHealth study}}}, doi = {{10.1136/bmjopen-2022-062066}}, volume = {{12}}, year = {{2022}}, }