@article{ChloeMalyaranCraveiroetal.2022,
  author    = {Chlo{\´e}, Radermacher and Malyaran, Hanna and Craveiro, Rogerio Bastos and Peglow, Sarah and Behbahani, Mehdi and Pufe, Thomas and Wolf, Michael and Neuss, Sabine},
  title     = {Mechanical loading on cementoblasts: a mini review},
  series = {Osteologie},
  volume    = {31},
  journal   = {Osteologie},
  number    = {2},
  publisher = {Thieme},
  address   = {Stuttgart},
  issn      = {1019-1291},
  doi       = {10.1055/a-1826-0777},
  pages     = {111 -- 118},
  year      = {2022},
  abstract  = {Orthodontic treatments are concomitant with mechanical forces and thereby cause teeth movements. The applied forces are transmitted to the tooth root and the periodontal ligaments which is compressed on one side and tensed up on the other side. Indeed, strong forces can lead to tooth root resorption and the crown-to-tooth ratio is reduced with the potential for significant clinical impact. The cementum, which covers the tooth root, is a thin mineralized tissue of the periodontium that connects the periodontal ligament with the tooth and is build up by cementoblasts. The impact of tension and compression on these cells is investigated in several in vivo and in vitro studies demonstrating differences in protein expression and signaling pathways. In summary, osteogenic marker changes indicate that cyclic tensile forces support whereas static tension inhibits cementogenesis. Furthermore, cementogenesis experiences the same protein expression changes in static conditions as static tension, but cyclic compression leads to the exact opposite of cyclic tension. Consistent with marker expression changes, the singaling pathways of Wnt/ß-catenin and RANKL/OPG show that tissue compression leads to cementum degradation and tension forces to cementogenesis. However, the cementum, and in particular its cementoblasts, remain a research area which should be explored in more detail to understand the underlying mechanism of bone resorption and remodeling after orthodontic treatments.},
  language  = {en}
}
@inproceedings{BuesgenKloeserKohletal.2022,
  author    = {B{\"u}sgen, Andr{\´e} and Kl{\"o}ser, Lars and Kohl, Philipp and Schmidts, Oliver and Kraft, Bodo and Z{\"u}ndorf, Albert},
  title     = {Exploratory analysis of chat-based black market profiles with natural language processing},
  series = {Proceedings of the 11th International Conference on Data Science, Technology and Applications},
  booktitle = {Proceedings of the 11th International Conference on Data Science, Technology and Applications},
  isbn      = {978-989-758-583-8},
  issn      = {2184-285X},
  doi       = {10.5220/0011271400003269},
  pages     = {83 -- 94},
  year      = {2022},
  abstract  = {Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods.},
  language  = {en}
}
@article{SchneiderSchwabedalBialonski2022,
  author    = {Schneider, Jules and Schwabedal, Justus T. C. and Bialonski, Stephan},
  title     = {Schlafspindeln - Funktion, Detektion und Nutzung als Biomarker f{\"u}r die psychiatrische Diagnostik},
  series = {Der Nervenarzt},
  journal   = {Der Nervenarzt},
  publisher = {Springer},
  address   = {Berlin, Heidelberg},
  issn      = {1433-0407},
  doi       = {10.1007/s00115-022-01340-z},
  pages     = {1 -- 8},
  year      = {2022},
  abstract  = {Hintergrund: Die Schlafspindel ist ein Graphoelement des Elektroenzephalogramms (EEG), das im Leicht- und Tiefschlaf beobachtet werden kann. Ver{\"a}nderungen der Spindelaktivit{\"a}t wurden f{\"u}r verschiedene psychiatrische Erkrankungen beschrieben. Schlafspindeln zeigen aufgrund ihrer relativ konstanten Eigenschaften Potenzial als Biomarker in der psychiatrischen Diagnostik. Methode: Dieser Beitrag liefert einen {\"U}berblick {\"u}ber den Stand der Wissenschaft zu Eigenschaften und Funktionen der Schlafspindeln sowie {\"u}ber beschriebene Ver{\"a}nderungen der Spindelaktivit{\"a}t bei psychiatrischen Erkrankungen. Verschiedene methodische Ans{\"a}tze und Ausblicke zur Spindeldetektion werden hinsichtlich deren Anwendungspotenzial in der psychiatrischen Diagnostik erl{\"a}utert. Ergebnisse und Schlussfolgerung: W{\"a}hrend Ver{\"a}nderungen der Spindelaktivit{\"a}t bei psychiatrischen Erkrankungen beschrieben wurden, ist deren exaktes Potenzial f{\"u}r die psychiatrische Diagnostik noch nicht ausreichend erforscht. Diesbez{\"u}glicher Erkenntnisgewinn wird in der Forschung gegenw{\"a}rtig durch ressourcenintensive und fehleranf{\"a}llige Methoden zur manuellen oder automatisierten Spindeldetektion ausgebremst. Neuere Detektionsans{\"a}tze, die auf Deep-Learning-Verfahren basieren, k{\"o}nnten die Schwierigkeiten bisheriger Detektionsmethoden {\"u}berwinden und damit neue M{\"o}glichkeiten f{\"u}r die praktisch},
  language  = {de}
}
@article{PourshahidiEngelmannOffenhaeusseretal.2022,
  author    = {Pourshahidi, Ali Mohammad and Engelmann, Ulrich M. and Offenh{\"a}usser, Andreas and Krause, Hans-Joachim},
  title     = {Resolving ambiguities in core size determination of magnetic nanoparticles from magnetic frequency mixing data},
  series = {Journal of Magnetism and Magnetic Materials},
  volume    = {563},
  journal   = {Journal of Magnetism and Magnetic Materials},
  number    = {In progress, Art. No. 169969},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0304-8853},
  doi       = {10.1016/j.jmmm.2022.169969},
  year      = {2022},
  abstract  = {Frequency mixing magnetic detection (FMMD) has been widely utilized as a measurement technique in magnetic immunoassays. It can also be used for the characterization and distinction (also known as "colourization") of different types of magnetic nanoparticles (MNPs) based on their core sizes. In a previous work, it was shown that the large particles contribute most of the FMMD signal. This leads to ambiguities in core size determination from fitting since the contribution of the small-sized particles is almost undetectable among the strong responses from the large ones. In this work, we report on how this ambiguity can be overcome by modelling the signal intensity using the Langevin model in thermodynamic equilibrium including a lognormal core size distribution fL(dc,d0,σ) fitted to experimentally measured FMMD data of immobilized MNPs. For each given median diameter d0, an ambiguous amount of best-fitting pairs of parameters distribution width σ and number of particles Np with R2 > 0.99 are extracted. By determining the samples' total iron mass, mFe, with inductively coupled plasma optical emission spectrometry (ICP-OES), we are then able to identify the one specific best-fitting pair (σ, Np) one uniquely. With this additional externally measured parameter, we resolved the ambiguity in core size distribution and determined the parameters (d0, σ, Np) directly from FMMD measurements, allowing precise MNPs sample characterization.},
  language  = {en}
}
@article{EngelmannPourshahidiShalabyetal.2022,
  author    = {Engelmann, Ulrich M. and Pourshahidi, Mohammad Ali and Shalaby, Ahmed and Krause, Hans-Joachim},
  title     = {Probing particle size dependency of frequency mixing magnetic detection with dynamic relaxation simulation},
  series = {Journal of Magnetism and Magnetic Materials},
  volume    = {563},
  journal   = {Journal of Magnetism and Magnetic Materials},
  number    = {In progress, Art. No. 169965},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0304-8853},
  doi       = {10.1016/j.jmmm.2022.169965},
  year      = {2022},
  abstract  = {Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles' magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing.},
  language  = {en}
}
@article{PhilippEfthimiouPaganoetal.2022,
  author    = {Philipp, Mohr and Efthimiou, Nikos and Pagano, Fiammetta and Kratochwil, Nicolaus and Pizzichemi, Marco and Tsoumpas, Charalampos and Auffray, Etiennette and Ziemons, Karl},
  title     = {Image reconstruction analysis for positron emission tomography with heterostructured scintillators},
  series = {IEEE Transactions on Radiation and Plasma Medical Sciences},
  volume    = {7},
  journal   = {IEEE Transactions on Radiation and Plasma Medical Sciences},
  number    = {1},
  publisher = {IEEE},
  address   = {New York, NY},
  issn      = {2469-7311},
  doi       = {10.1109/TRPMS.2022.3208615},
  pages     = {41 -- 51},
  year      = {2022},
  abstract  = {The concept of structure engineering has been proposed for exploring the next generation of radiation detectors with improved performance. A TOF-PET geometry with heterostructured scintillators with a pixel size of 3.0×3.1×15 mm3 was simulated using Monte Carlo. The heterostructures consisted of alternating layers of BGO as a dense material with high stopping power and plastic (EJ232) as a fast light emitter. The detector time resolution was calculated as a function of the deposited and shared energy in both materials on an event-by-event basis. While sensitivity was reduced to 32\% for 100 μm thick plastic layers and 52\% for 50 μm, the CTR distribution improved to 204±49 ps and 220±41 ps respectively, compared to 276 ps that we considered for bulk BGO. The complex distribution of timing resolutions was accounted for in the reconstruction. We divided the events into three groups based on their CTR and modeled them with different Gaussian TOF kernels. On a NEMA IQ phantom, the heterostructures had better contrast recovery in early iterations. On the other hand, BGO achieved a better contrast to noise ratio (CNR) after the 15th iteration due to the higher sensitivity. The developed simulation and reconstruction methods constitute new tools for evaluating different detector designs with complex time responses.},
  language  = {en}
}
@article{UysalCreutzFiratetal.2022,
  author    = {Uysal, Karya and Creutz, Till and Firat, Ipek Seda and Artmann, Gerhard and Teusch, Nicole and Temiz Artmann, Ayseg{\"u}l},
  title     = {Bio-functionalized ultra-thin, large-area and waterproof silicone membranes for biomechanical cellular loading and compliance experiments},
  series = {Polymers},
  volume    = {14},
  journal   = {Polymers},
  number    = {11},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2073-4360},
  pages     = {2213},
  year      = {2022},
  abstract  = {Biocompatibility, flexibility and durability make polydimethylsiloxane (PDMS) membranes top candidates in biomedical applications. CellDrum technology uses large area, <10 µm thin membranes as mechanical stress sensors of thin cell layers. For this to be successful, the properties (thickness, temperature, dust, wrinkles, etc.) must be precisely controlled. The following parameters of membrane fabrication by means of the Floating-on-Water (FoW) method were investigated: (1) PDMS volume, (2) ambient temperature, (3) membrane deflection and (4) membrane mechanical compliance. Significant differences were found between all PDMS volumes and thicknesses tested (p < 0.01). They also differed from the calculated values. At room temperatures between 22 and 26 °C, significant differences in average thickness values were found, as well as a continuous decrease in thicknesses within a 4 °C temperature elevation. No correlation was found between the membrane thickness groups (between 3-4 µm) in terms of deflection and compliance. We successfully present a fabrication method for thin bio-functionalized membranes in conjunction with a four-step quality management system. The results highlight the importance of tight regulation of production parameters through quality control. The use of membranes described here could also become the basis for material testing on thin, viscous layers such as polymers, dyes and adhesives, which goes far beyond biological applications.},
  language  = {en}
}
@inproceedings{TranTrinhDaoetal.2022,
  author    = {Tran, Ngoc Trinh and Trinh, Tu Luc and Dao, Ngoc Tien and Giap, Van Tan and Truong, Manh Khuyen and Dinh, Thuy Ha and Staat, Manfred},
  title     = {Limit and shakedown analysis of structures under random strength},
  series = {Proceedings of (NACOME2022) The 11th National Conference on Mechanics, Vol. 1. Solid Mechanics, Rock Mechanics, Artificial Intelligence, Teaching and Training, Hanoi, December 2-3, 2022},
  booktitle = {Proceedings of (NACOME2022) The 11th National Conference on Mechanics, Vol. 1. Solid Mechanics, Rock Mechanics, Artificial Intelligence, Teaching and Training, Hanoi, December 2-3, 2022},
  publisher = {Nha xuat ban Khoa hoc tu nhien va Cong nghe (Verlag Naturwissenschaft und Technik)},
  address   = {Hanoi},
  isbn      = {978-604-357-084-7},
  pages     = {510 -- 518},
  year      = {2022},
  abstract  = {Direct methods comprising limit and shakedown analysis is a branch of computational mechanics. It plays a significant role in mechanical and civil engineering design. The concept of direct method aims to determinate the ultimate load bearing capacity of structures beyond the elastic range. For practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and onstraints. If strength and loading are random quantities, the problem of shakedown analysis is considered as stochastic programming. This paper presents a method so called chance constrained programming, an effective method of stochastic programming, to solve shakedown analysis problem under random condition of strength. In this our investigation, the loading is deterministic, the strength is distributed as normal or lognormal variables.},
  language  = {en}
}
@inproceedings{WeldenSeverinsPoghossianetal.2022,
  author    = {Welden, Melanie and Severins, Robin and Poghossian, Arshak and Wege, Christina and Siegert, Petra and Keusgen, Michael and Sch{\"o}ning, Michael Josef},
  title     = {Studying the immobilization of acetoin reductase with Tobacco mosaic virus particles on capacitive field-effect sensors},
  series = {2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN)},
  booktitle = {2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN)},
  publisher = {IEEE},
  isbn      = {978-1-6654-5860-3 (Online)},
  doi       = {10.1109/ISOEN54820.2022.9789657},
  pages     = {4 Seiten},
  year      = {2022},
  abstract  = {A capacitive electrolyte-insulator-semiconductor (EISCAP) biosensor modified with Tobacco mosaic virus (TMV) particles for the detection of acetoin is presented. The enzyme acetoin reductase (AR) was immobilized on the surface of the EISCAP using TMV particles as nanoscaffolds. The study focused on the optimization of the TMV-assisted AR immobilization on the Ta 2 O 5 -gate EISCAP surface. The TMV-assisted acetoin EISCAPs were electrochemically characterized by means of leakage-current, capacitance-voltage, and constant-capacitance measurements. The TMV-modified transducer surface was studied via scanning electron microscopy.},
  language  = {en}
}
@book{Laack2022,
  author    = {Laack, Walter van},
  title     = {Greater Than the Entire Universe},
  publisher = {van Laack GmbH},
  address   = {Aachen},
  isbn      = {978-3-936624-52-6},
  pages     = {120 Seiten},
  year      = {2022},
  language  = {en}
}