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    <title language="eng">A flexible model of ordered random variables for non-metallic inclusions in steels and related statistical inference</title>
    <abstract language="eng">In a data set of non-metallic inclusion sizes in samples from engineering steel, common order statistics fail to serve as a suitable model for ascendingly ordered measurements within single samples. Therefore, a flexible model of ordered random variables is proposed, which allows for changes of distributions described by model parameters. Joint maximum likelihood estimation of these parameters and the shape parameter of an underlying left-truncated Weibull distribution is considered, and a model test is developed for the null-hypothesis of common order statistics being an adequate model. To overcome small data situations, a link-function approach is examined in order to reduce the number of involved model parameters as well as to propose to use a link-function parameter as a material indicator. An asymptotic test is provided to check for the presence of a linear link function, and tests for hypotheses about two link-function parameters are studied. Moreover, the construction of simultaneous confidence regions for the link-function parameters as well as of confidence bands for the entire graph of the link function are presented. Throughout, the findings are applied to the real metallurgical data set. Similar problems and data structures arise in other fields of material science and applications such as geology.</abstract>
    <parentTitle language="eng">Applied Mathematical Modelling</parentTitle>
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    <identifier type="doi">10.1016/j.apm.2025.116284</identifier>
    <note>Corresponding author der OTH Regensburg: Anja Bettina Schmiedt</note>
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    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Stefan Bedbur</author>
    <author>Udo Kamps</author>
    <author>Anja Bettina Schmiedt</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
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    <title language="eng">Development of a continuous fiber-reinforced 3D printing process with a 6-axis robot arm: Process design and equipment</title>
    <abstract language="eng">The utilisation of 3D printing processes in the fabrication of continuous fiber-reinforced composites confers a multitude of advantages, in particular flexible design based on structural requirements. In order to achieve greater flexibility, there is a necessity for 3D printing systems that allow for customisable material selection and fiber positioning. This paper presents the design of a robot-based 3D printing system that incorporates an in-situ impregnation line and flexibility regarding the machine code generation for fiber positioning. The development of the system enabled the attainment of an average fiber volume content of up to 37.12%. In the tensile tests, material characteristics up to E1 = 24.7 GPa and strength of up to RM1 = 0.51 GPa were determined.</abstract>
    <parentTitle language="eng">The International Journal of Advanced Manufacturing Technology</parentTitle>
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    <identifier type="doi">10.1007/s00170-025-17263-3</identifier>
    <note>Corresponding author der OTH Regensburg: Anna Afanasev</note>
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    <author>Anna Afanasev</author>
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    <title language="eng">Structural and functional evolution of HKUST-1 nanoparticles induced by ball milling</title>
    <abstract language="eng">In this study, the effect of post-synthetic ball milling on the structural and functional properties of as-synthesized nanoparticles of the copper-based metal-organic framework (MOF) HKUST-1 was investigated for the first time. Nanoparticles were synthesized using sodium formate as a capping agent. The crystalline particles were subjected to a controlled ball milling process, which induced significant structural changes. Powder X-ray diffraction (PXRD) revealed a reduction in crystallite size from 91 nm to 21 nm and the introduction of microstrain, partially disrupting the MOF's long-range crystalline order, as evidenced by peak broadening and the diminished intensity of high-angle reflections. Particle morphology pre- and post-milling was further studied with scanning electron microscopy (SEM) imaging, verifying a narrow particle size distribution of ± 22 nm after milling. Fourier-transform infrared spectroscopy (FTIR) indicated protonation of carboxylate groups in the larger pores of the framework, likely due to moisture incorporation during milling. Brunauer-Emmett-Teller (BET) surface area analysis showed a substantial decrease in specific surface area from 521 m²/g to 226 m²/g, suggesting a partial collapse of the porous framework. We discuss the applicability of ball milling as a versatile means of post-synthetic approach to reduce MOF particle sizes, a key element in the preparation of MOF-based thin films using inks or polymers.</abstract>
    <parentTitle language="eng">Next Materials</parentTitle>
    <identifier type="doi">10.1016/j.nxmate.2025.101544</identifier>
    <note>Corresponding author der OTH Regensburg: Alex Wolfgramm</note>
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    <author>Rafal Samp</author>
    <author>Jens Christoph Hoffmann</author>
    <author>Rainer Müller</author>
    <author>Martin Kammler</author>
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      <value>Ball milling</value>
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      <value>Copper-based metal-organic framework</value>
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      <language>eng</language>
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      <value>HKUST-1</value>
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      <value>Nitrogen adsorption</value>
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    <title language="eng">The role of hydrogen offtaker regulation in highly renewable electricity systems</title>
    <abstract language="eng">The growing demand for green hydrogen necessitates a rapid scale-up of production and exports to meet decarbonization targets globally. However, current ramp-up efforts remain insufficient, calling for policies that unlock the potential of hydrogen as a low-carbon energy carrier. A key lever is the offtaker regulation, which impacts the pace and sustainability of export projects.&#13;
This study investigates minimum renewable share requirements for hydrogen exports in countries with high renewable electricity shares. Using New Zealand as a case study, we develop a fully sector-coupled capacity expansion and dispatch model, integrating hydrogen and electricity network planning based on PyPSA-Earth. The model optimizes New Zealand’s energy system under varying export scenarios, renewable electricity shares, and resulting system impacts.&#13;
We find that domestic electricity demand and renewable expansion rates dominate long-term outcomes, while progressive regulation enables short-term hydrogen and Power-to-X exports. Relaxing the renewable threshold from 80% to 60% triples export volumes from 2.5 TWh to 8.2 TWh by 2030. We propose a two-stage requirement: an initially progressive threshold to attract investment with low consequential emissions, followed by stricter regulation to prevent high emissions, rising domestic electricity prices, and declining hydrogen competitiveness. This framework, demonstrated for New Zealand, can guide hydrogen-exporting countries worldwide.</abstract>
    <parentTitle language="eng">Energy</parentTitle>
    <identifier type="doi">10.1016/j.energy.2025.139513</identifier>
    <note>Corresponding author der OTH Regensburg: Leon Schumm</note>
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    <author>Leon Schumm</author>
    <author>Jannik Haas</author>
    <author>Rebecca Peer</author>
    <author>Michael Sterner</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Climate neutrality</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>e-fuels</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Emission intensity</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy systems modelling</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrogen exports</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrogen offtaker regulation</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Power-to-X</value>
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    <title language="eng">An analysis of the critical time step size for explicit dynamics using trimmed B-splines, LR-splines, and THB-splines</title>
    <abstract language="eng">Isogeometric analysis (IGA) combined with explicit dynamics is increasingly used in academia and has already been successfully applied in industrial simulations, including crash and sheet-metal forming. Since explicit schemes are only conditionally stable, accurate estimation of the critical time step is essential for both stability and efficiency. Adaptive mesh refinement is widely used to balance accuracy and computational cost. In IGA, THB- and LR-splines break the tensor-product structure of standard B-splines and enable local refinement, but their effect on the critical time step under trimming has not been systematically studied - a key requirement for reliable time step estimation.&#13;
We investigate the critical time step in explicit dynamic simulations using trimmed B-splines, LR-splines, and THB-splines, based on a lumped mass matrix obtained by simple row summation. One-dimensional bar, two-dimensional membrane, and trimmed shell models are analyzed to determine how trimming and local refinement influence element and system eigenfrequencies, which directly control the stable time step. Refined boundary elements in open knot vectors are identified as the main bottleneck. Trimming these elements can increase the stable time step, though certain trimming configurations introduce new restrictions.&#13;
Results show that LR- and THB-splines impose time step constraints similar to B-splines, making them equally suitable for explicit simulations. We also present a general method for computing element-wise Bézier extraction operators for LR- and THB-splines, enabling straightforward integration into standard finite element solvers. The findings are validated through nonlinear sheet-metal forming simulations in LS-DYNA using shells discretized with trimmed B-, LR-, and THB-splines. This represents the first such application and demonstrates their practical feasibility for industrial use.</abstract>
    <parentTitle language="eng">Computer Methods in Applied Mechanics and Engineering</parentTitle>
    <identifier type="issn">0045-7825</identifier>
    <identifier type="doi">10.1016/j.cma.2025.118656</identifier>
    <note>Corresponding author der OTH Regensburg: Christoph Hollweck</note>
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    <title language="eng">Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge</title>
    <abstract language="eng">Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, skill assessment, and autonomous assistance. However, robust performance under real-world conditions remains a significant challenge. Incorporating surgical context – such as the current procedural phase – has emerged as a promising strategy to improve robustness and interpretability.&#13;
To address these challenges, we organized the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) sub-challenge as part of the Endoscopic Vision (EndoVis) challenge at MICCAI 2024. We introduced a novel, multi-center dataset comprising thirteen full-length laparoscopic cholecystectomy videos collected from three distinct medical institutions, with unified annotations for three interrelated tasks: surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation. Unlike existing datasets, ours enables joint investigation of instrument localization and procedural context within the same data while supporting the integration of temporal information across entire procedures.&#13;
We report results and findings in accordance with the BIAS guidelines for biomedical image analysis challenges. The PhaKIR sub-challenge advances the field by providing a unique benchmark for developing temporally aware, context-driven methods in RAMIS and offers a high-quality resource to support future research in surgical scene understanding.</abstract>
    <parentTitle language="eng">Medical Image Analysis</parentTitle>
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    <identifier type="doi">10.1016/j.media.2026.103945</identifier>
    <note>Corresponding author der OTH Regensburg: Tobias Rueckert&#13;
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    <author>Shu Yang</author>
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    <author>Hao Chen</author>
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    <subject>
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      <value>Surgical phase recognition</value>
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      <value>Instrument keypoint estimation</value>
    </subject>
    <subject>
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      <type>uncontrolled</type>
      <value>Instrument instance segmentation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Robot-assisted surgery</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
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    <collection role="institutes" number="RCHST">Regensburg Center of Health Sciences and Technology - RCHST</collection>
    <collection role="persons" number="palmremic">Palm, Christoph (Prof. Dr.) - ReMIC</collection>
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    <title language="eng">Mechanical and structural characterization of heat-staked parts realized by selective laser sintering of polyamide 12</title>
    <abstract language="eng">Heat staking is a joining process in which thermoplastic pins are formed by heat and pressure in a form-fitting and insoluble way. This study evaluates the mechanical performance and microstructure of selective laser sintered (SLS) polyamide 12 (PA 12) components before and after heat staking, compared with conventionally turned reference specimens. The components were characterized using tensile tests, micrographs, microscopy, and micro-CT measurements. For the tests, the forces and temperatures during heat staking were varied to determine the best process parameters. Tensile tests revealed that SLS joints achieved strengths of up to 33.6 MPa, approaching the 39.9 MPa of the turned references. Microstructural analysis showed a marked reduction in porosity due to heat staking. Porosity decreased from 3.9% to 1.56% at a staking force of 300 N and from 4.29% to 0.81% at 1000 N, highlighting the beneficial effect of increased force. These results demonstrate that heat staking parameters significantly influence local densification and mechanical performance, and that, under suitable conditions, SLS components can achieve joint strengths comparable to conventionally manufactured parts. The study shows that the heat staking process parameters have a significant influence on the local microstructure and thus on the mechanical performance and provides a basis for optimizing SLS components for new heat staking applications.</abstract>
    <parentTitle language="eng">The International Journal of Advanced Manufacturing Technology</parentTitle>
    <identifier type="doi">10.1007/s00170-025-17319-4</identifier>
    <enrichment key="CorrespondingAuthor">Andreas Kuettner</enrichment>
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    <author>Andreas Kuettner</author>
    <author>Samuel Fischer</author>
    <author>Tobias Laumer</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Additive manufacturing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Heat staking</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Material qualification</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Polyamid 12 (PA)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Selective laser sintering (SLS)</value>
    </subject>
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    <pageNumber>22</pageNumber>
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    <volume>453</volume>
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    <title language="eng">Model order reduction for unbounded second-order vibroacoustic systems using infinite elements and Dirichlet-to-Neumann map</title>
    <abstract language="eng">This work addresses the efficient numerical simulation of time-harmonic vibroacoustic problems in unbounded domains, with a focus on fluid-structure interaction. The underlying mathematical model is a second-order dynamical system arising from the coupling of structural and acoustic domains, incorporating material damping effects, relevant in structural acoustics and noise control applications. A central novelty of the proposed method is its unified computational framework that supports two distinct strategies for treating unbounded fluid domains: (1) non-local absorbing boundary conditions based on Dirichlet-to-Neumann map, and (2) infinite elements, which extend the computational domain rather than truncate it. Both approaches are integrated into a consistent formulation that enables flexible and accurate modeling of exterior wave propagation. To efficiently evaluate frequency-domain transfer functions, the method employs model order reduction using the Padé-via-Lanczos technique. While this algorithm typically targets first-order systems, the present approach uses a Schur complement strategy to reduce the second-order system in a way that maintains computational efficiency and storage requirements comparable to first-order formulations. Importantly, the framework seamlessly embeds both interior structural damping and the additional dissipation introduced by the acoustic-domain truncation into the model-order reduction process. The exterior acoustic field is represented via spherical harmonic expansions, with expansion coefficients computed from the reduced system. Numerical results demonstrate the method’s accuracy, efficiency, and scalability, making it well-suited for high-fidelity vibroacoustic analysis in unbounded domains.</abstract>
    <parentTitle language="eng">Computer Methods in Applied Mechanics and Engineering</parentTitle>
    <identifier type="doi">10.1016/j.cma.2026.118846</identifier>
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    <enrichment key="CorrespondingAuthor">Christopher Sittl</enrichment>
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    <author>Christopher Sittl</author>
    <author>Steffen Marburg</author>
    <author>Elke Deckers</author>
    <author>Marcus Wagner</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Lanczos algorithm</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Krylov-subspace projection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Dirichlet-to-Neumann map</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Infinite elements</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Padé approximation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fluid-structure interaction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Acoustics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Spherical harmonics</value>
    </subject>
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    <pageLast/>
    <pageNumber>10</pageNumber>
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    <title language="deu">KI erfolgreich einführen: Status quo und Erfolgsfaktoren in deutschen Großunternehmen</title>
    <abstract language="deu">Viele deutsche Großunternehmen experimentieren derzeit intensiv mit künstlicher Intelligenz (KI), stehen aber vor der Frage, wie sich erste Pilotprojekte in einen nachhaltigen, wirtschaftlich wirksamen Einsatz überführen lassen. Eine empirische Studie mit 34 Chief Information Officers (CIO) und IT-Entscheidern in deutschen Großunternehmen zeigt: 112 identifizierte KI-Use-Cases, ein klar erkennbarer Reifezuwachs – aber auch deutliche Hürden bei Daten, Kompetenzen und Akzeptanz. Der Beitrag fasst den Status quo zusammen, validiert zentrale Erfolgsfaktoren aus der Forschung und leitet konkrete Empfehlungen für die Praxis von IT- und Fachbereichsverantwortlichen ab.</abstract>
    <parentTitle language="deu">Wirtschaftsinformatik &amp; Management</parentTitle>
    <identifier type="doi">10.1365/s35764-026-00593-6</identifier>
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      <value>Künstliche Intelligenz</value>
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      <value>Generative KI</value>
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    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Wirtschaftsinformatik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Digitalisierung</value>
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    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Management</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>KI-Adoption</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>KI-Einführung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>KI-Use-Cases</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>KI-Reifegrad</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Großunternehmen</value>
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    <title language="eng">Eigenvalue perturbation in drivetrain analysis and redesign</title>
    <abstract language="eng">The optimisation of the dynamic behavior of drive systems often involves targeted modifications of the system characteristics. Structural and parametric modifications are used to satisfy the constraints of the dynamic requirements. However, many optimisations are still achieved by intuition or parameter variations, even though more streamlined and easy-to-implement tools such as the eigenvalue perturbation method are available. In this article, the eigenvalue perturbation method in the form of an eigenvalue sensitivity analysis is used to efficiently optimise the dynamic behavior for two different use cases using different optimisation measures. This paper demonstrates how eigenvalue perturbation theory can efficiently optimise drivetrain dynamics by systematically modifying system parameters. Two case studies show how eigenvalue sensitivity analysis achieves targeted frequency shifts to avoid resonances: (1) adapting shaft stiffness and control parameters in a torsional drivetrain, and (2) adjusting structural modifications in a wind turbine bedplate. The study introduces the eigenvector tensor product as a weighting matrix, identifying key parameters for effective redesign. Compared to conventional parameter studies, this method enables precise control over system dynamics with minimal computational effort, making it highly applicable for vibration mitigation and drivetrain optimisation.</abstract>
    <parentTitle language="eng">Multibody System Dynamics</parentTitle>
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    <identifier type="doi">10.1007/s11044-026-10155-8</identifier>
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    <title language="eng">Automated deep learning based detection of cellular deposits on clinically used ECMO membrane lungs</title>
    <abstract language="eng">Introduction:&#13;
&#13;
Despite the promising application of extracorporeal membrane oxygenation (ECMO) in the treatment of critically ill patients, coagulation-associated technical complications, primarily clot formation and critical bleeding, remain a major challenge during ECMO therapy. The deposition of nucleated cells on the surface has been shown, yet the role of these cells towards complication development is still matter of ongoing research. In particular, the membrane lung (MemL) is prone to clot formation. Therefore, the investigation of nuclear deposits on its hollow-fibers may provide insights for a better understanding of the cellular mechanisms involved in the development of ECMO complications.&#13;
&#13;
Methods:&#13;
&#13;
To support current research, this study aimed to develop a deep learning–based tool for the automated detection and quantitative analysis of nuclear depositions on MemL hollow-fiber mats. A customized fluorescence microscopy workflow, combined with a semi-automated iterative labeling strategy, was used to generate a high-quality dataset for model training.&#13;
&#13;
Results:&#13;
&#13;
Six configurations of instance segmentation models were evaluated, with a Mask R-CNN with ResNet 101 backbone using dilated convolution providing the most balanced performance in both nuclei count and area accuracy. Compared with U-Net–based approaches such as Cellpose or StarDist, the proposed model demonstrated superior segmentation of overlapping and low-intensity nuclei, maintaining accuracy even in densely packed cellular regions.&#13;
&#13;
Discussion:&#13;
&#13;
We present an automated image analysis tool for clinically used MemLs, which exhibit complex three-dimensional hollow-fiber architectures and irregular cellular deposits that challenge conventional tools. A dedicated graphical user interface enables streamlined detection, morphometric analysis, and spatial clustering of nuclei, establishing a reproducible workflow for high-throughput analysis of fluorescence microscopy images. This approach eliminates labor-intensive manual counting and facilitates large-scale studies on cell-fiber interactions and disease-related correlations.</abstract>
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