Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.090
Lena Geißel , Adina Grimmert , Petra Wiederkehr
To prevent mechanical damage caused by process forces when grinding turbine blades for aerospace applications, the prediction of process forces is of major interest. Macroscopic grinding simulations utilizing suitable force models are a common method to predict process forces. However, the prediction accuracy of the simulation highly depends on determined model parameter values. In order to enable an efficient and precise model parameter estimation, this study presents a Bayesian Markov Chain Monte Carlo (MCMC) method based on hybrid data sources. By only using few measurements combined with simulated data, force model parameters are conditioned leading to accurate simulation results.
{"title":"Efficient parameter estimation for grinding force models using a Bayesian approach","authors":"Lena Geißel , Adina Grimmert , Petra Wiederkehr","doi":"10.1016/j.procir.2026.01.090","DOIUrl":"10.1016/j.procir.2026.01.090","url":null,"abstract":"<div><div>To prevent mechanical damage caused by process forces when grinding turbine blades for aerospace applications, the prediction of process forces is of major interest. Macroscopic grinding simulations utilizing suitable force models are a common method to predict process forces. However, the prediction accuracy of the simulation highly depends on determined model parameter values. In order to enable an efficient and precise model parameter estimation, this study presents a Bayesian Markov Chain Monte Carlo (MCMC) method based on hybrid data sources. By only using few measurements combined with simulated data, force model parameters are conditioned leading to accurate simulation results.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 522-527"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.069
Nuwan Rupasinghe , Julian Frederic Gerken , Andreas Baumann , Peter Eberhard , Dirk Biermann
Ejector deep hole drilling is advantageous due to its high material removal rate and bore quality without requiring a complex sealing system for drilling applications with large length to diameter ratios. Sufficient supply of metal working fluid and efficient removal of the swarf is crucial, which would otherwise lead to poor bore quality, increased friction, and tool wear. Based on experimentally obtained chip shapes, a coupled SPH-DEM simulation model was used to enhance the understanding of the highly complicated and dynamic chip evacuation conditions. A comparison of different tool head designs and their influence on the chip evacuation is presented.
{"title":"Investigation of Chip Evacuation in Ejector Deep Hole Drilling using Mesh-Free Simulation Methods","authors":"Nuwan Rupasinghe , Julian Frederic Gerken , Andreas Baumann , Peter Eberhard , Dirk Biermann","doi":"10.1016/j.procir.2026.01.069","DOIUrl":"10.1016/j.procir.2026.01.069","url":null,"abstract":"<div><div>Ejector deep hole drilling is advantageous due to its high material removal rate and bore quality without requiring a complex sealing system for drilling applications with large length to diameter ratios. Sufficient supply of metal working fluid and efficient removal of the swarf is crucial, which would otherwise lead to poor bore quality, increased friction, and tool wear. Based on experimentally obtained chip shapes, a coupled SPH-DEM simulation model was used to enhance the understanding of the highly complicated and dynamic chip evacuation conditions. A comparison of different tool head designs and their influence on the chip evacuation is presented.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 398-403"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.097
Alessandro Pellegrini , Marco Zaza , Maria Grazia Guerra , Fulvio Lavecchia , Luigi Maria Galantucci
In the present work a composite 316L filament was used to realize through Material extrusion debinding and sintering the simple cubic (SC) and the body-center-cubic (BCC) cells characterized by critical features as bridges and overhang angle. Two beam size were considered for each cell. The printing quality and dimensional accuracy of the cells was assessed with a visual inspection and through 3D scanning. The adoption of the cooling always improved the quality of the printed parts and influenced the dimensional accuracy of a smaller size of the beams for the BCC, instead a bigger size for the SC.
{"title":"Manufacturing of self-support thin structures with extrusion and sinter-based technology","authors":"Alessandro Pellegrini , Marco Zaza , Maria Grazia Guerra , Fulvio Lavecchia , Luigi Maria Galantucci","doi":"10.1016/j.procir.2026.01.097","DOIUrl":"10.1016/j.procir.2026.01.097","url":null,"abstract":"<div><div>In the present work a composite 316L filament was used to realize through Material extrusion debinding and sintering the simple cubic (SC) and the body-center-cubic (BCC) cells characterized by critical features as bridges and overhang angle. Two beam size were considered for each cell. The printing quality and dimensional accuracy of the cells was assessed with a visual inspection and through 3D scanning. The adoption of the cooling always improved the quality of the printed parts and influenced the dimensional accuracy of a smaller size of the beams for the BCC, instead a bigger size for the SC.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 564-567"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.007
Hendrik Mende , Henrik Heymann , Laura Battistella Fiorini , Gustavo Schewinski , Dennis Grunert , Albina Karimova , Hamidreza Paria , Christian Strobl , Robert H. Schmitt , Thomas Bergs
Hybrid Machine Learning (ML) models have potential for high performance, as they learn based on data and incorporate existing knowledge. In this work, an automated system is developed which creates the best possible hybrid ML model without Data Science expertise. First, the system architecture is defined including the breakdown of functionalities into a workflow along the sub-components of the system. Then, the system is validated on a use case from optics production, i.e., quality prediction during nonisothermal glass forming. A performance comparison between a baseline ML model with the automatically generated hybrid ML model is demonstrated.
{"title":"Automated Hybrid Machine Learning System for Production","authors":"Hendrik Mende , Henrik Heymann , Laura Battistella Fiorini , Gustavo Schewinski , Dennis Grunert , Albina Karimova , Hamidreza Paria , Christian Strobl , Robert H. Schmitt , Thomas Bergs","doi":"10.1016/j.procir.2026.01.007","DOIUrl":"10.1016/j.procir.2026.01.007","url":null,"abstract":"<div><div>Hybrid Machine Learning (ML) models have potential for high performance, as they learn based on data and incorporate existing knowledge. In this work, an automated system is developed which creates the best possible hybrid ML model without Data Science expertise. First, the system architecture is defined including the breakdown of functionalities into a workflow along the sub-components of the system. Then, the system is validated on a use case from optics production, i.e., quality prediction during nonisothermal glass forming. A performance comparison between a baseline ML model with the automatically generated hybrid ML model is demonstrated.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 30-35"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.010
Flavio Tonelli , Massimo Paolucci , Antonio Giovannetti , Marco Mosca , Livia Torterolo
Comprehensive frameworks for end-to-end digital supply chain planning are leveraging on 3D simulation and digital twin technologies to enhance production process design and planning also in small and medium enterprises (SMEs). The proposed system empowers production engineers by facilitating bill of material (BOM) generation, production routing, and fostering a collaborative co-design approach with external suppliers. Inspired by Product Lifecycle Management (PLM) principles, the framework is particularly geared towards quality management, emphasizing work instruction generation, and providing a seamless Industrial Internet of Things (IIoT) digital representation of the production process during the execution phase. The integration of these technologies not only optimizes production efficiency but also promotes a holistic and collaborative approach to manufacturing, ensuring SMEs can navigate the challenges of modern digital supply chains with agility and precision.
{"title":"Integrated 3D Simulation and Digital Twin Framework for Collaborative Production Process Design and Planning in Small and Medium Enterprises: a Use Case Analysis","authors":"Flavio Tonelli , Massimo Paolucci , Antonio Giovannetti , Marco Mosca , Livia Torterolo","doi":"10.1016/j.procir.2026.01.010","DOIUrl":"10.1016/j.procir.2026.01.010","url":null,"abstract":"<div><div>Comprehensive frameworks for end-to-end digital supply chain planning are leveraging on 3D simulation and digital twin technologies to enhance production process design and planning also in small and medium enterprises (SMEs). The proposed system empowers production engineers by facilitating bill of material (BOM) generation, production routing, and fostering a collaborative co-design approach with external suppliers. Inspired by Product Lifecycle Management (PLM) principles, the framework is particularly geared towards quality management, emphasizing work instruction generation, and providing a seamless Industrial Internet of Things (IIoT) digital representation of the production process during the execution phase. The integration of these technologies not only optimizes production efficiency but also promotes a holistic and collaborative approach to manufacturing, ensuring SMEs can navigate the challenges of modern digital supply chains with agility and precision.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 48-53"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.046
Rico Löser , Leutrim Gjakova , Marco Schumann , Philipp Klimant , Martin Dix , Yunqi Gu , Ruth Maria Otto
In order to become climate neutral, significant energy savings must be achieved in European factories while preserving the economic strength. Simultaneously, new technologies are needed to enable the transition from mass production to mass customization. Cognitive robotics is a key component of this proposition to recognize the environment and dynamically adapt manufacturing behavior. The present paper discusses and evaluates a developed position control for tracking operation of NC-robots based on 2D image processing using ECC algorithm. This approach based on one-shot learning in combination with continuous movement of NC-robots allows to reduce cycle time, respectively energy consumption. Finally, the benefits of the proposed solutions are extended to on-the-fly assembly processes.
{"title":"Rule-based one-shot object tracking for NC-robots under consideration of energy consumption","authors":"Rico Löser , Leutrim Gjakova , Marco Schumann , Philipp Klimant , Martin Dix , Yunqi Gu , Ruth Maria Otto","doi":"10.1016/j.procir.2026.01.046","DOIUrl":"10.1016/j.procir.2026.01.046","url":null,"abstract":"<div><div>In order to become climate neutral, significant energy savings must be achieved in European factories while preserving the economic strength. Simultaneously, new technologies are needed to enable the transition from mass production to mass customization. Cognitive robotics is a key component of this proposition to recognize the environment and dynamically adapt manufacturing behavior. The present paper discusses and evaluates a developed position control for tracking operation of NC-robots based on 2D image processing using ECC algorithm. This approach based on one-shot learning in combination with continuous movement of NC-robots allows to reduce cycle time, respectively energy consumption. Finally, the benefits of the proposed solutions are extended to on-the-fly assembly processes.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 263-268"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.054
Marco Hussong , Marcel Nunziatino , Matthias Klar , Jan C. Aurich
The recognition of features is important in computer-aided engineering (CAE) across different applications, such as computer aided process planning (CAPP) or computer aided manufacturing (CAM). While deep learning has become a widely used approach for the recognition of features, it necessitates large datasets that are still difficult to compile. To facilitate the annotation of 3D CAD models, a novel annotation tool is introduced. The CADLabel annotation tool offers direct and indirect manual labeling modules for 3D CAD models, but it also contains a recommendation system leveraging geometrical and topological analysis with a graph neural network (GNN) to propose potential features, streamlining the annotation workflow. Additional attributes include support for multiple STEP file formats, integration to add further information to the 3D CAD model such as Product and Manufacturing Information (PMI), and the ability to export annotations in different file formats suitable for deep learning.
{"title":"CADLabel: Development of an annotation tool for deep learning tasks on 3D CAD models","authors":"Marco Hussong , Marcel Nunziatino , Matthias Klar , Jan C. Aurich","doi":"10.1016/j.procir.2026.01.054","DOIUrl":"10.1016/j.procir.2026.01.054","url":null,"abstract":"<div><div>The recognition of features is important in computer-aided engineering (CAE) across different applications, such as computer aided process planning (CAPP) or computer aided manufacturing (CAM). While deep learning has become a widely used approach for the recognition of features, it necessitates large datasets that are still difficult to compile. To facilitate the annotation of 3D CAD models, a novel annotation tool is introduced. The CADLabel annotation tool offers direct and indirect manual labeling modules for 3D CAD models, but it also contains a recommendation system leveraging geometrical and topological analysis with a graph neural network (GNN) to propose potential features, streamlining the annotation workflow. Additional attributes include support for multiple STEP file formats, integration to add further information to the 3D CAD model such as Product and Manufacturing Information (PMI), and the ability to export annotations in different file formats suitable for deep learning.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 310-315"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.041
Patrick Rückert , Naemi Wassermann , Kirsten Tracht
Semantic world models are experiencing increasing attention as a relevant field of research in robotics. They extend classical world models by describing the state of an environment based on information that has a tangible meaning for humans. This includes, for example, the class membership of objects located within the environment and their spatial relationship. Thus, semantic models bridge the gap between humans and robots and open up new possibilities for the industrial application of mobile robotics. In this paper, a software architecture is presented that implements a semantic world model focusing on the localization and identification of object instances.
{"title":"Semantic world models for object identification and localization in mobile robotics","authors":"Patrick Rückert , Naemi Wassermann , Kirsten Tracht","doi":"10.1016/j.procir.2026.01.041","DOIUrl":"10.1016/j.procir.2026.01.041","url":null,"abstract":"<div><div>Semantic world models are experiencing increasing attention as a relevant field of research in robotics. They extend classical world models by describing the state of an environment based on information that has a tangible meaning for humans. This includes, for example, the class membership of objects located within the environment and their spatial relationship. Thus, semantic models bridge the gap between humans and robots and open up new possibilities for the industrial application of mobile robotics. In this paper, a software architecture is presented that implements a semantic world model focusing on the localization and identification of object instances.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 234-239"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.071
Jonas M. Werner , Hendrik Liborius , Welf-Guntram Drossel , Andreas Schubert
Performance of components or systems can be significantly enhanced by surface microstructuring. Ultrasonic vibration superimposed turning is a highly efficient method for this, including the microstructuring in finish machining. However, control of these processes under varying loads is difficult and requires constant regulation of the systems operating frequency and vibration amplitude. Applying sensors to measure mechanical vibrations and using them to control the system offers benefits over conventional approaches like phase-locked-loop (PLL) or autoresonant control. In the experimental investigations, two sonotrodes are designed to integrate a variety of sensors for vibration measurement. Strain gauges, fiber-optical sensors, an accelerometer, and a passive piezoelectric disk in the ultrasonic transducer have been chosen. The performance of the sensors is examined for a free vibration as well as in an ultrasonic vibration superimposed turning process. The sensors are evaluated at different operating frequencies and power levels as well as varied loads during manufacturing resulting from different feeds (0.05 mm and 0.1 mm). Furthermore, the cutting speed is varied (120 m/min and 480 m/min) to change the rotational frequency of the spindle. Results show that all of the sensors prove useful in measuring the vibrations and determining the resonance frequency of the system during operation. The research improves understanding of the benefits of measuring different mechanical properties (strain, acceleration) in ultrasonic vibration superimposed turning, allowing for a more accurate in-process monitoring of the ultrasonic vibration and the control of the system in the future.
{"title":"In-process measurement of vibrations in ultrasonic vibration superimposed turning using mechanical feedback signals","authors":"Jonas M. Werner , Hendrik Liborius , Welf-Guntram Drossel , Andreas Schubert","doi":"10.1016/j.procir.2026.01.071","DOIUrl":"10.1016/j.procir.2026.01.071","url":null,"abstract":"<div><div>Performance of components or systems can be significantly enhanced by surface microstructuring. Ultrasonic vibration superimposed turning is a highly efficient method for this, including the microstructuring in finish machining. However, control of these processes under varying loads is difficult and requires constant regulation of the systems operating frequency and vibration amplitude. Applying sensors to measure mechanical vibrations and using them to control the system offers benefits over conventional approaches like phase-locked-loop (PLL) or autoresonant control. In the experimental investigations, two sonotrodes are designed to integrate a variety of sensors for vibration measurement. Strain gauges, fiber-optical sensors, an accelerometer, and a passive piezoelectric disk in the ultrasonic transducer have been chosen. The performance of the sensors is examined for a free vibration as well as in an ultrasonic vibration superimposed turning process. The sensors are evaluated at different operating frequencies and power levels as well as varied loads during manufacturing resulting from different feeds (0.05 mm and 0.1 mm). Furthermore, the cutting speed is varied (120 m/min and 480 m/min) to change the rotational frequency of the spindle. Results show that all of the sensors prove useful in measuring the vibrations and determining the resonance frequency of the system during operation. The research improves understanding of the benefits of measuring different mechanical properties (strain, acceleration) in ultrasonic vibration superimposed turning, allowing for a more accurate in-process monitoring of the ultrasonic vibration and the control of the system in the future.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 409-414"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.procir.2026.01.072
Gustavo Laydner de Melo Rosa , Alexander Gwose , Philipp Ganser , Thomas Bergs
Metal cutting tool wear evaluation is a time- and cost-consuming task. Direct measurements (manual microscopic imaging) generate sensitive microscopic tool wear images (MTWI) which, on one hand, can inaugurate this measurement’s automation and, on the other hand, hold confidential information about the cutting process. This article contains an approach for collaboratively automating tool condition monitoring (TCM) while individually preserving the privacy of clients’ images. The method developed consists of a cohort of tool wear image owners and a Federated Learning (FL) pipeline for processing synergistically the owners’ images without sharing proprietary images. Both cohort data setting and training scenario are investigated, evaluated and discussed.
{"title":"Security-enhanced cutting tool wear segmentation with federated learning","authors":"Gustavo Laydner de Melo Rosa , Alexander Gwose , Philipp Ganser , Thomas Bergs","doi":"10.1016/j.procir.2026.01.072","DOIUrl":"10.1016/j.procir.2026.01.072","url":null,"abstract":"<div><div>Metal cutting tool wear evaluation is a time- and cost-consuming task. Direct measurements (manual microscopic imaging) generate sensitive microscopic tool wear images (MTWI) which, on one hand, can inaugurate this measurement’s automation and, on the other hand, hold confidential information about the cutting process. This article contains an approach for collaboratively automating tool condition monitoring (TCM) while individually preserving the privacy of clients’ images. The method developed consists of a cohort of tool wear image owners and a Federated Learning (FL) pipeline for processing synergistically the owners’ images without sharing proprietary images. Both cohort data setting and training scenario are investigated, evaluated and discussed.</div></div>","PeriodicalId":20535,"journal":{"name":"Procedia CIRP","volume":"138 ","pages":"Pages 415-420"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146162079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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