TY - JOUR A1 - Orcesi, André A1 - O'Connor, Alan A1 - Diamantidis, Dimitris A1 - Sýkora, Miroslav A1 - Wu, Teng A1 - Akiyama, Mitsuyoshi A1 - Alhamid, Abdul Kadir A1 - Schmidt, Franziska A1 - Pregnolato, Maria A1 - Li, Yue A1 - Salarieh, Babak A1 - Salman, Abdullahi M. A1 - Bastidas-Arteaga, Emilio A1 - Markogiannaki, Olga A1 - Schoefs, Franck T1 - Investigating the Effects of Climate Change on Structural Actions JF - Structural Engineering International N2 - The changing climate with resulting more extreme weather events will likely impact infrastructure assets and services. This phenomenon can present direct threats to the assets as well as significant indirect effects for those relying on the services those assets deliver. Such threats are path-dependent and place-specific, as they strongly depend on current and future climate variability, location, asset design life, function and condition. One key question is how climate change is likely to increase both the probability and magnitude of extreme weather events under different scenarios of climate change. To address this issue, this paper investigates selected effects of climate change and their consequences on structural performance, in the context of evolving loading scenarios in three different continental regions: Europe, North America, and Asia. The aim is to investigate some main place-specific changes of the exposure in terms of intensity/frequency of extreme events as well as the associated challenges, considering some recent activities of members of the IABSE TG6.1. Climate change can significantly affect built infrastructure and the society by increasing the occurrence and magnitude of extreme events and increasing potential losses. Therefore, specific relationships relating hazard levels and structural vulnerability to climate change effects should be determined. KW - climate change KW - extreme weather events KW - flooding KW - hurricanes KW - scour KW - sea-level rise KW - tsunami Y1 - 2022 U6 - https://doi.org/10.1080/10168664.2022.2098894 VL - 32 IS - 4 SP - 1 EP - 14 PB - Taylor & Francis ER - TY - JOUR A1 - Launhardt, M. A1 - Wörz, A. A1 - Loderer, A. A1 - Laumer, Tobias A1 - Drummer, Dietmar A1 - Hausotte, Tino A1 - Schmidt, Michael T1 - Detecting surface roughness on SLS parts with various measuring techniques JF - Polymer Testing N2 - Selective Laser Sintering (SLS) is an additive manufacturing technique whereby a laser melts polymer powder layer by layer to generate three-dimensional parts. It enables the fabrication of parts with high degrees of complexity, nearly no geometrical restrictions, and without the necessity of a tool or a mold. Due to the orientation in the building space, the processing parameters, and the powder properties, the resulting parts possess an increased surface roughness. In comparison to other manufacturing techniques, e.g. injection molding, the surface roughness of SLS parts results from partially melted powder particles on the surface layer. The actual surface roughness must thus be characterized with respect to the part's eventual application. At the moment, there is no knowledge regarding which measuring technique is most suitable for detecting and quantifying SLS parts' surface roughness. The scope of this paper is to compare tactile profile measurement methods, as established in industry, to optical measurement techniques such as Focus Variation, Fringe Projection Technique (FPT), and Confocal Laser Scanning Microscope (CLSM). The advantages and disadvantages of each method are presented and, additionally, the effect of tactile measurement on a part's surface is investigated. KW - Selective Laser Sintering (SLS) KW - PA12 KW - Surface roughness KW - Measuring technique Y1 - 2016 SN - 0142-9418 U6 - https://doi.org/10.1016/j.polymertesting.2016.05.022 SN - 1873-2348 VL - 53 SP - 217 EP - 226 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Orcesi, Andre A1 - Bastidas-Arteaga, Emilio A1 - Markogiannaki, Olga A1 - Li, Yue A1 - Schoefs, Franck A1 - Ballester, Jorge A1 - O'Connor, Alan A1 - Sýkora, Miroslav A1 - Imam, Boulent A1 - Pregnolato, Maria A1 - Stewart, Mark A1 - Ryan, Paraic A1 - Diamantidis, Dimitris A1 - Wu, Teng A1 - Schmidt, Franziska A1 - Kreislová, Kateřina A1 - Salman, Abdullahi M. T1 - Investigating the effects of climate change on structural resistance and actions T2 - IABSE Congress, Ghent 2021, Structural Engineering for Future Societal Needs: 22.02.2021 - 24.02.2021, Ghent, Belgium N2 - One major issue when considering the effects of climate change is to understand, qualify and quantify how natural hazards and the changing climate will likely impact infrastructure assets and services as it strongly depends on current and future climate variability, location, asset design life, function and condition. So far, there is no well-defined and agreed performance indicator that isolates the effects of climate change for structures. Rather, one can mention some key considerations on how climate change may produce changes of vulnerability due to physical and chemical actions affecting structural durability or changes of the exposure in terms of intensity/frequency of extreme events. This paper considers these two aspects and associated challenges, considering some recent activities of members of the IABSE TG6.1. KW - adaptation KW - climate change KW - Durability KW - extreme events KW - vulnerability Y1 - 2021 U6 - https://doi.org/10.2749/ghent.2021.0974 SP - 974 EP - 985 PB - International Association for Bridge and Structural Engineering (IABSE) CY - Zürich ER - TY - JOUR A1 - Klein, C. A1 - Nabbefeld, T. A1 - Hattab, H. A1 - Meyer, D. A1 - Jnawali, G. A1 - Kammler, Martin A1 - Meyer zu Heringdorf, Frank-Joachim A1 - Golla-Franz, A. A1 - Müller, B. H. A1 - Schmidt, Thomas A1 - Henzler, M. A1 - Horn-von Hoegen, Michael T1 - Lost in reciprocal space? Determination of the scattering condition in spot profile analysis low-energy electron diffraction JF - Review of scientific instruments N2 - The precise knowledge of the diffraction condition, i.e., the angle of incidence and electron energy, is crucial for the study of surface morphology through spot profile analysis low-energy electron diffraction (LEED). We demonstrate four different procedures to determine the diffraction condition: employing the distortion of the LEED pattern under large angles of incidence, the layer-by-layer growth oscillations during homoepitaxial growth, a G(S) analysis of a rough surface, and the intersection of facet rods with 3D Bragg conditions. Y1 - 2011 U6 - https://doi.org/10.1063/1.3554305 VL - 82 IS - 3 PB - American Institute of Physics ER - TY - JOUR A1 - Scheppach, Markus W. A1 - Mendel, Robert A1 - Muzalyova, Anna A1 - Rauber, David A1 - Probst, Andreas A1 - Nagl, Sandra A1 - Römmele, Christoph A1 - Yip, Hon Chi A1 - Lau, Louis Ho Shing A1 - Gölder, Stefan Karl A1 - Schmidt, Arthur A1 - Kouladouros, Konstantinos A1 - Abdelhafez, Mohamed A1 - Walter, Benjamin M. A1 - Meinikheim, Michael A1 - Chiu, Philip Wai Yan A1 - Palm, Christoph A1 - Messmann, Helmut A1 - Ebigbo, Alanna T1 - Artificial intelligence improves submucosal vessel detection during third space endoscopy JF - Endoscopy N2 - Background and study aims: While artificial intelligence (AI) shows high potential in decision support for diagnostic gastrointestinal endoscopy, its role in therapeutic endoscopy remains unclear. Third space endoscopic procedures pose the risk of intraprocedural bleeding. Therefore, we aimed to develop an AI algorithm for intraprocedural blood vessel detection. Patients and Methods: Using a test dataset with 101 standardized video clips containing 200 predefined submucosal blood vessels, 19 endoscopists were evaluated for the vessel detection rate (VDR) and time (VDT) with and without support of an AI algorithm. Test subjects were grouped according to experience in ESD. Results: With AI support, endoscopists VDR increased from 56.4% [CI 54.1–58.6] to 72.4% [CI 70.3–74.4]. Endoscopists‘ VDT dropped from 6.7sec [CI 6.2-7.1] to 5.2sec [CI 4.8-5.7]. False positive (FP) readings appeared in 4.5% of frames and were marked significantly shorter than true positives (6.0sec [CI 5.28-6.70] vs. 0.7sec [CI 0.55-0.87]). Conclusions: AI improved the vessel detection rate and time of endoscopists during third space endoscopy. While these data need to be corroborated by clinical trials, AI may prove to be an invaluable tool for the improvement of endoscopic interventions. KW - Artificial Intelligence KW - Third Space Endoscopy Y1 - 2025 U6 - https://doi.org/10.1055/a-2534-1164 PB - Thieme CY - Stuttgart ER - TY - GEN A1 - Schmidt, S. A1 - Weiser, A. A1 - Heyartz, M. A1 - Fernsimer, K. A1 - Osterried, S. A1 - Schedel, Valentin A1 - Pfingsten, Andrea T1 - Pain Neuroscience Education (PNE) - Anwendungsbereitschaft deutscher Physiotherapeut*innen T2 - physioscience N2 - Deutsche Physiotherapeut*innen scheinen in ihrem Arbeitsalltag von einer Implementierung des PNE- Konzepts tendenziell Abstand zu nehmen. Parallel zu dieser Vermutung offenbarte sich eine mehrheitliche Unsicherheit bei der Behandlung von chronischen Schmerzpatient*innen. Vor allem Therapeut*innen, welche sich weniger unsicher im Umgang mit chronischen Schmerzpatient*innen fühlen, neigen zur Verwendung der „Why-you-Hurt?“ – Karten. In diesem Falle wäre zu diskutieren, ob der Grund hierfür in der Tatsache liegt, dass diese Therapeut*innen eine geeignete und gut ergänzende Methode in dem Edukations-Tool sehen oder, ob ein sicherer Umgang mit chronischen Patient*innen die Voraussetzung für eine erfolgreiche Implementierung ist. Umfangreichere Erhebungen müssen durchgeführt werden, um diese Erkenntnisse zu festigen. Y1 - 2025 U6 - https://doi.org/10.1055/s-0045-1808215 N1 - Abstract/Poster-Beitrag zum 8. Forschungssymposium Physiotherapie der Deutschen Gesellschaft für Physiotherapiewissenschaft e. V., 22.–23. November 2025, Cottbus Senftenberg VL - 21 IS - S 01 SP - 79 PB - Thieme ER -