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144 results on '"Hauer, L."'

1. Secukinumab Causing Medication-Related Osteonecrosis of the Jaw, in a Patient Diagnosed with Psoriasis and Rheumatoid Arthritis

Author

Hauer L, Moztarzadeh O, Baghalipour N, and Gencur J

Subjects
plaque psoriasis, anti-interleukin 17-a, immunomodulator, interleukins inhibitors, mronj, Dermatology, RL1-803
Abstract

Lukas Hauer,1 Omid Moztarzadeh,1,2 Nasimeh Baghalipour,1 Jiri Gencur1 1Department of Stomatology, University Hospital Pilsen, Faculty of Medicine in Pilsen, Charles University, Pilsen, 32300, Czech Republic; 2Department of Anatomy, Faculty of Medicine in Pilsen, Charles University, Pilsen, 32300, Czech RepublicCorrespondence: Omid Moztarzadeh, Department of Anatomy, Faculty of Medicine in Pilsen, Charles University, alej Svobody 1655/76, Pilsen, 32300, Czech Republic, Tel +420 377 593 306, Email Omid.moztarzadeh@lfp.cuni.cz; moztarzadeh@fnplzen.czAbstract: The use of antiangiogenic and antiresorptive medications, particularly in patients with cancer or osteoporosis, can lead to osteonecrosis of the jaw following tooth extraction, trauma or arising spontaneously- A condition known as medication-related osteonecrosis of the jaw (MRONJ). In this article, we present a unique case of MRONJ in a patient with no history of antiresorptive or antiangiogenic drug use, who was instead taking the anti-interleukin 17-A (Secukinumab) medication for severe psoriasis. This association has not been previously reported in the literature.Keywords: plaque psoriasis, anti-interleukin 17-A, immunomodulator, interleukins inhibitors, MRONJ

Published
2024

2. Diroximel Fumarate as a Novel Oral Immunomodulating Therapy for Relapsing Forms of Multiple Sclerosis: A Review on the Emerging Data

Author

Hauer L and Sellner J

Subjects
diroximel fumarate, dimethyl fumarate, multiple sclerosis, immunotherapy, sars-cov-2, tolerability, adherence., Therapeutics. Pharmacology, RM1-950
Abstract

Larissa Hauer,1 Johann Sellner2 1Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria; 2Department of Neurology, Landesklinikum Mistelbach-Gänserndorf, Mistelbach, AustriaCorrespondence: Johann Sellner, Department of Neurology, Landesklinikum Mistelbach-Gänserndorf, Liechtensteinstr. 67, Mistelbach, 2130, Austria, Tel +2572/9004-12850, Fax +2572/9004-49281, Email johann.sellner@mistelbach.lknoe.atAbstract: Multiple sclerosis (MS) is a chronic inflammatory, demyelinating and neurodegenerative disorder of the central nervous system. Disease-modifying drugs (DMDs) and subsequent adherence are crucial for preventing reversible episodes of neurological dysfunction and delayed onset of progressive accumulation of irreversible deficits. Yet, side effects may limit their usage in clinical practice. Gastrointestinal (GI) side effects are a significant limitation of the use of dimethyl fumarate (DMF), the most frequently prescribed oral DMD in MS worldwide. Diroximel fumarate (DRF) is a second-generation oral fumaric acid ester (FAE) that was developed as a formulation with better GI tolerability. The improved tolerability is assumed to be related to a lower synthesis of gut-irritating methanol. Other explanations for DRF’s lower extent of GI irritation include a more modest off-target activity due to its chemical structure. The superior GI tolerability of DRF compared to DMF could be proven in clinical trials and lead to approval of DRF for the treatment of relapsing forms of MS/relapsing-remitting MS (United States Food and Drug Administration and European Medicines Agency, respectively). Here, we summarize the mode of action of oral FAE and compare the chemical and physiological characteristics of DMF and DRF. Moreover, we discuss the adverse effects of FAE and introduce the emerging preclinical and trial data leading to the approval of DRF in MS. This article additionally reviews our current understanding of coronavirus disease 2019 (COVID-19) and the efficacy of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) vaccination in people treated with FAE.Keywords: diroximel fumarate, dimethyl fumarate, multiple sclerosis, immunotherapy, SARS-CoV-2, tolerability, adherence

Published
2022

4. Metaverse and Healthcare: Machine Learning-Enabled Digital Twins of Cancer.

Author

Moztarzadeh, O, Jamshidi, MB, Sargolzaei, S, Jamshidi, A, Baghalipour, N, Malekzadeh Moghani, M, Hauer, L, Moztarzadeh, O, Jamshidi, MB, Sargolzaei, S, Jamshidi, A, Baghalipour, N, Malekzadeh Moghani, M, and Hauer, L

Abstract

Medical digital twins, which represent medical assets, play a crucial role in connecting the physical world to the metaverse, enabling patients to access virtual medical services and experience immersive interactions with the real world. One serious disease that can be diagnosed and treated using this technology is cancer. However, the digitalization of such diseases for use in the metaverse is a highly complex process. To address this, this study aims to use machine learning (ML) techniques to create real-time and reliable digital twins of cancer for diagnostic and therapeutic purposes. The study focuses on four classical ML techniques that are simple and fast for medical specialists without extensive Artificial Intelligence (AI) knowledge, and meet the requirements of the Internet of Medical Things (IoMT) in terms of latency and cost. The case study focuses on breast cancer (BC), the second most prevalent form of cancer worldwide. The study also presents a comprehensive conceptual framework to illustrate the process of creating digital twins of cancer, and demonstrates the feasibility and reliability of these digital twins in monitoring, diagnosing, and predicting medical parameters.

Published
2023

5. Future of Drug Discovery: The Synergy of Edge Computing, Internet of Medical Things, and Deep Learning

Author

Jamshidi, M, Moztarzadeh, O, Jamshidi, A, Abdelgawad, A, El-Baz, AS, Hauer, L, Jamshidi, M, Moztarzadeh, O, Jamshidi, A, Abdelgawad, A, El-Baz, AS, and Hauer, L

Abstract

The global spread of COVID-19 highlights the urgency of quickly finding drugs and vaccines and suggests that similar challenges will arise in the future. This underscores the need for ongoing efforts to overcome the obstacles involved in the development of potential treatments. Although some progress has been made in the use of Artificial Intelligence (AI) in drug discovery, virologists, pharmaceutical companies, and investors seek more long-term solutions and greater investment in emerging technologies. One potential solution to aid in the drug-development process is to combine the capabilities of the Internet of Medical Things (IoMT), edge computing (EC), and deep learning (DL). Some practical frameworks and techniques utilizing EC, IoMT, and DL have been proposed for the monitoring and tracking of infected individuals or high-risk areas. However, these technologies have not been widely utilized in drug clinical trials. Given the time-consuming nature of traditional drug- and vaccine-development methods, there is a need for a new AI-based platform that can revolutionize the industry. One approach involves utilizing smartphones equipped with medical sensors to collect and transmit real-time physiological and healthcare information on clinical-trial participants to the nearest edge nodes (EN). This allows the verification of a vast amount of medical data for a large number of individuals in a short time frame, without the restrictions of latency, bandwidth, or security constraints. The collected information can be monitored by physicians and researchers to assess a vaccine’s performance.

Published
2023

6. Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation.

Author

Moztarzadeh, O, Jamshidi, MB, Sargolzaei, S, Keikhaee, F, Jamshidi, A, Shadroo, S, Hauer, L, Moztarzadeh, O, Jamshidi, MB, Sargolzaei, S, Keikhaee, F, Jamshidi, A, Shadroo, S, and Hauer, L

Abstract

Advanced mathematical and deep learning (DL) algorithms have recently played a crucial role in diagnosing medical parameters and diseases. One of these areas that need to be more focused on is dentistry. This is why creating digital twins of dental issues in the metaverse is a practical and effective technique to benefit from the immersive characteristics of this technology and adapt the real world of dentistry to the virtual world. These technologies can create virtual facilities and environments for patients, physicians, and researchers to access a variety of medical services. Experiencing an immersive interaction between doctors and patients can be another considerable advantage of these technologies, which can dramatically improve the efficiency of the healthcare system. In addition, offering these amenities through a blockchain system enhances reliability, safety, openness, and the ability to trace data exchange. It also brings about cost savings through improved efficiencies. In this paper, a digital twin of cervical vertebral maturation (CVM), which is a critical factor in a wide range of dental surgery, within a blockchain-based metaverse platform is designed and implemented. A DL method has been used to create an automated diagnosis process for the upcoming CVM images in the proposed platform. This method includes MobileNetV2, a mobile architecture that improves the performance of mobile models in multiple tasks and benchmarks. The proposed technique of digital twinning is simple, fast, and suitable for physicians and medical specialists, as well as for adapting to the Internet of Medical Things (IoMT) due to its low latency and computing costs. One of the important contributions of the current study is to use of DL-based computer vision as a real-time measurement method so that the proposed digital twin does not require additional sensors. Furthermore, a comprehensive conceptual framework for creating digital twins of CVM based on MobileNetV2 within a bloc

Published
2023

12. Biologické chování adenoidně cystického karcinomu velkých slinných žláz.

Author

Hyravý, M., Stárek, I., Salzman, R., Beláková, P., Kubec, V., and Hauer, L.

Abstract

Copyright of Otorhinolaryngology & Phoniatrics / Otorinolaryngologie a Foniatrie is the property of Czech Medical Association of JE Purkyne and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2020

18. Transcervical extended mediastinal lymphadenectomy—the new operative technique and early results in lung cancer staging

Author

Kuzdal, J, Zielinski, M, Papla, B, Szlubowski, A, Hauer, L, Nabialek, T, Sosnicki, W, Pankowski, J, and Elia, S

Subjects
Pulmonary and Respiratory Medicine, medicine.medical_specialty, medicine.diagnostic_test, business.industry, medicine.medical_treatment, Mediastinum, General Medicine, medicine.disease, lymph node excision, mediastinum, Mediastinoscopy, non small cell lung carcinoma, medicine.anatomical_structure, Cardiothoracic surgery, Medicine, Surgery, Lymphadenectomy, Radiology, Thoracotomy, Lung cancer staging, Cardiology and Cardiovascular Medicine, business, Lung cancer, Lymph node
Abstract

Objective: Mediastinal staging is one of the most important problems in thoracic surgery. Although the pathological examination is a generally accepted standard, none of the currently used techniques enables complete removal of all lymph node stations of the mediastinum. The aim of the study is to present a new technique of transcervical extended mediastinal lymphadenctomy (TEMLA) and to analyze its value in lung cancer staging. Methods: In the prospective study of consecutive group of non-small cell lung cancer (NSCLC) patients, operated on between January and August 2004, we evaluated the usefulness of this original technique of bilateral mediastinal lymphadenectomy, assessing its accuracy and safety. The operations were performed through the transcervical approach, were videomediastinoscopy-assisted, with sternum elevation. Lymph node stations 1, 2R, 2L, 3a, 4R, 4L, 5, 6, 7 and 8 were removed. In patients without mediastinal metastases thoracotomy with pulmonary resection was performed and mediastinum searched for any missed lymph nodes. Results: There were 83 patients operated on with the TEMLA technique. The mean number of nodes removed was 43 (range: 26–85). The sensitivity, specificity and accuracy of the presented method in detecting mediastinal node metastases were: 90, 100, and 96%, respectively, whereas the positive and negative predictive values were: 100 and 95%, respectively. Conclusions: The TEMLA technique is a safe and highly accurate method of mediastinal staging in NSCLC. q 2004 Elsevier B.V. All rights reserved.

Published
2005

20. STANOVENÍ BEZPEČNÝCH RESEKČNÍCH SLIZNIČNÍCH OKRAJŮ U ORÁLNÍCH DLAŽDICOBUNĚČNÝCH KARCINOMŮ.

Author

Pošta, P., Pivovarčíková, K., Liška, J., Genčur, J., Micopulos, Pěnkava, A., Frolo, M., Hes, O., and Hauer, L.

Abstract

Copyright of Czech Dental Journal / Ceská Stomatologie a Praktické Zubni Lékarstvi is the property of Czech Dental Chamber and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2022

21. Central Mucoepidermoid Carcinoma

Author

Andrle, P., primary, Hauer, L., additional, Hostička, L., additional, Hrušák, D., additional, Jambura, J., additional, Pošta, P., additional, and Skálová, A., additional

Published
2013
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32. Intraoseální mukoepidermoidní karcinom.

Author

Andrle, P., Hauer, L., Hostička, L., Hrušák, D., Jambura, J., Pošta, P., and Skálová, A.

Subjects
*SALIVARY gland cancer, *CANCER patients, *HISTOPATHOLOGY, *CANCER treatment, *MORTALITY
Abstract

Introduction: Intraosseous mucoepidermoid carcinoma is a relatively rare variant of the histologically identical malignant tumor affecting salivary glands. It is a recently described separate nosological entity with a clearly defined histopathological feature. To date, only hundreds of cases of this disease have been reported in the literature worldwide. According to its typical occurrence this tumor is classified as a primary intraosseous carcinoma of the jaw. Methods: In the present paper, the authors describe two patients with this diagnosis, in both cases with tumors afflicting upper jaw diagnosed and treated at the Department of maxillofacial surgery in Pilsen since the years 2008. The treatment outcomes are evaluated after five-year follow-up. Results: The first patient was treated by the radical surgical procedure and adjuvant cancer therapy. Longterm complete remission was achieved and today the patient is with no evidence of malignant disease. The second patient is of advanced age and with much co-morbidity. For this reason, only radiotherapy was indicated, but without any therapeutic response in terms of tumor regression. The subsequently indicated palliative chemotherapy led to the significant tumor shrinkage. Currently, the patient is in the partial remission of malignant disease, with no evidence of tumor progression or metastases. Conclusion: The pathogenesis of intraosseous mucoepidermoid carcinoma is still not well understood. The diagnosis is based on histological examination performed by experienced pathologist. Immunohistochemical examination seems to be of no benefit for the diagnosis. A squamous cell carcinoma and glandular odontogenic cyst is necessary to be considered in histopathological differential diagnosis. A clinician has to rule out metastasis of salivary mucoepidermoid carcinoma in the jaws. Most intraosseous mucoepidermoid carcinomas are classified as low-grade tumors with the little metastatic potential. The radical resection procedure should be the first choice for the treatment of this cancer. Radiotherapy and chemotherapy are only indicated as an adjuvant therapy, especially in high-grade tumors. Despite its clear malignant nature the intraosseous mucoepidermoid carcinoma is not an aggressive tumor with high mortality. [ABSTRACT FROM AUTHOR]

Published
2013

33. Využití zobrazovacích vyšetřovacích metod při diagnostice osteonekrózy čelistí vzniklé v souvislosti s léčbou bisfosfonáty.

Author

Hauer, L., Baxa, J., Hrušák, D., Hostiãka, L., and Andrle, P.

Subjects
*OSTEONECROSIS, *DIPHOSPHONATES, *ONCOLOGY, *PATIENTS, *JAW diseases
Abstract

Objectives: Osteonecrosis of the jaws is a rare side effect of bisphosphonate therapy, occurring especially in oncological patients but also in patients with metabolic bone diseases. Because it is a relatively recently described disease (year 2003), the etiopathogenesis of these lesions has not yet been fully clarified, there is also no consensus for their treatment. Conservative as well as surgical therapy leads to complete healing in a small percentage of cases only, the emphasis is therefore placed on preventive measures. The diagnosis is based primarily on patient's history and clinical examination, without the need of using imaging methods. Pathological changes in this jawbone necrosis imagined by any of known methods are nonspecific only, distinction of these lesions from other pathological condition is difficult. Imaging of jawbones is important for disease staging and determining the real extent of bone lesion, which does not correlate with the extent of exposed necrotic bone into the oral cavity. These information are useful mainly during the planning of surgical therapy, ie. resections of the jaws. Detection of associated complications such as pathological fractures, deep neck space infections or maxillary sinusitis is another kind of use. Some of the imaging methods seem to be good in early detection of subclinical lesions or even for differentiation of osteonecrosis from neoplastic jawbone disease. The ability to fulfill these criteria is different for each type of imaging examination, so far the most useful imaging methods are hybrid methods which combine functional and morphological imaging. This hybrid imaging gives information not only about structural pathological changes in the jaws and surrounding soft tissues, but also about osteoblast activity and bone metabolism. There is not enough reported cases of such an imaging in the indication of bisphosphonate-related osteonecrosis of the jaw. High price of some of these examinations is also a limiting factor. Aim of study: In this review article the authors summarize the current knowledge of the use of all available imaging methods in the diagnosis of bisphosphonate-related osteonecrosis of the jaw (radiography, computed tomography, cone beam computed tomography, magnetic resonance imaging, bone scintigraphy and single photon emission computed tomography, positron emission tomography and hybrid imaging methods) [ABSTRACT FROM AUTHOR]

Published
2012

34. Synthesis of a C-linked Antifreeze Glycoprotein (AFGP) Mimic:  Probes for Investigating the Mechanism of Action

Author

Ben, R. N., Eniade, A. A., and Hauer, L.

Abstract

A general convergent synthesis has been developed to afford a low molecular weight C-linked antifreeze glycoprotein (AFGP) mimic (9). Structural mimics of AFGPs have tremendous potential as probes to better understand how native AFGPs inhibit ice crystal growth in organisms that inhabit subzero environments.

Published
1999

36. HTLV-I/II infection in women with acute pelvic inflammatory disease.

Author

Safrin, Sharon, Ng, Valerie L., McGrath, Michael S., Dattel, Bonnie J., Hauer, Laurie, Sweet, Richard L., Safrin, S, Ng, V L, McGrath, M S, Dattel, B J, Hauer, L, and Sweet, R L

Subjects
T cells, IMMUNOGLOBULINS, PELVIC inflammatory disease, LETTERS to the editor
Abstract

Presents a letter to the editor in the April 25, 1990 issue of the 'Journal of the American Medical Association,' about the seroprevalence of human T-cell lymphotropic virus type I/II antibody in women admitted to the San Francisco General Hospital in California with acute pelvic inflammatory disease between January 1985 and December 1988.

Published
1990
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37. Unveiling the strong interaction among hadrons at the LHC

Author

Acharya, Shreyasi, Adamova, Dagmar, Ahn, Sang Un, Bhattacharjee, Buddhadeb, Yurchenko, Volodymyr, Zaccolo, Valentina, Zaman, Ali, Zampolli, Chiara, Correia Zanoli, Henrique Jose, Zardoshti, Nima, Zarochentsev, Andrey, Zavada, Petr, Zavyalov, Nikolay, Zbroszczyk, Hanna Paulina, Bianchi, Antonio, Zhalov, Mikhail, Zhang, Song, Zhang, Xiaoming, Zhang, Zuman, Zherebchevskii, Vladimir, Yu, Zhi, Zhou, Daicui, Zhou, You, Zhou, Zhuo, Zhu, Jianhui, Bianchi, Livio, Zhu, Ya, Zichichi, Antonino, Zinovjev, Gennady, Zurlo, Nicola, ALICE Collaboration, Bianchi, Nicola, Bielcik, Jaroslav, Bielcikova, Jana, Bilandzic, Ante, Biro, Gabor, Biswas, Rathijit, Biswas, Saikat, Akbar, Zaenal, Blair, Justin Thomas, Blau, Dmitry, Blume, Christoph, Boca, Gianluigi, Bock, Friederike, Bogdanov, Alexey, Boi, Stefano, Bok, Jeongsu, Boldizsar, Laszlo, Bolozdynya, Alexander, Akindinov, Alexander, Bombara, Marek, Bonomi, Germano, Borel, Herve, Borissov, Alexander, Bossi, Hannah, Botta, Elena, Bratrud, Lars, Braun-munzinger, Peter, Bregant, Marco, Broz, Michal, Al-turany, Mohammad, Bruna, Elena, Bruno, Giuseppe Eugenio, Buckland, Matthew Daniel, Budnikov, Dmitry, Buesching, Henner, Bufalino, Stefania, Bugnon, Ophelie, Buhler, Paul Alois, Buncic, Predrag, Buthelezi, Edith Zinhle, Alam, Sk Noor, Bashir Butt, Jamila, Bysiak, Sebastian Adam, Caffarri, Davide, Caliva, Alberto, Calvo Villar, Ernesto, Mejia Camacho, Juan Manuel, Soto Camacho, Rabi, Camerini, Paolo, De Moraes Canedo, Fabio, Capon, Aaron Allan, Silva De Albuquerque, Danilo, Carnesecchi, Francesca, Caron, Robin Albert Andre, Castillo Castellanos, Javier Ernesto, Castro, Andrew John, Casula, Ester Anna Rita, Catalano, Fabio, Ceballos Sanchez, Cesar, Chakraborty, Pritam, Chandra, Sinjini, Chang, Wan, Aleksandrov, Dmitry, Chapeland, Sylvain, Chartier, Marielle, Chattopadhyay, Subhasis, Chattopadhyay, Sukalyan, Chauvin, Alex Henri Jean, Cheshkov, Cvetan Valeriev, Cheynis, Brigitte, Chibante Barroso, Vasco Miguel, Dobrigkeit Chinellato, David, Cho, Soyeon, Alessandro, Bruno, Chochula, Peter, Chowdhury, Tasnuva, Christakoglou, Panagiotis, Christensen, Christian Holm, Christiansen, Peter, Chujo, Tatsuya, Cicalo, Corrado, Cifarelli, Luisa, De Cilladi, Lorenzo, Cindolo, Federico, Alfanda, Haidar Mas'ud, Ciupek, Michael Rudolf, Clai, Giulia, Cleymans, Jean Willy Andre, Colamaria, Fabio Filippo, Colella, Domenico, Collu, Alberto, Colocci, Manuel, Concas, Matteo, Conesa Balbastre, Gustavo, Conesa Del Valle, Zaida, Alfaro Molina, Jose Ruben, Contin, Giacomo, Contreras Nuno, Jesus Guillermo, Cormier, Thomas Michael, Corrales Morales, Yasser, Cortese, Pietro, Cosentino, Mauro Rogerio, Costa, Filippo, Costanza, Susanna, Crochet, Philippe, Cuautle Flores, Eleazar, Adler, Alexander, Ali, Bushra, Cui, Pengyao, Cunqueiro Mendez, Leticia, Dabrowski, Daniel, Dahms, Torsten, Dainese, Andrea, Damas, Florian Paul Andre, Danisch, Meike Charlotte, Danu, Andrea, Das, Debasish, Das, Indranil, Ali, Yasir, Das, Prottay, Das, Prottoy, Das, Supriya, Dash, Ajay Kumar, Dash, Sadhana, De, Sudipan, De Caro, Annalisa, De Cataldo, Giacinto, De Cuveland, Jan, De Falco, Alessandro, Alici, Andrea, De Gruttola, Daniele, De Marco, Nora, De Pasquale, Salvatore, Deb, Suman, Franz Degenhardt, Hermann, Deja, Kamil Rafal, Deloff, Andrzej, Delsanto, Silvia, Deng, Wenjing, Dhankher, Preeti, Alizadehvandchali, Negin, Di Bari, Domenico, Di Mauro, Antonio, Arteche Diaz, Raul, Dietel, Thomas, Raisig, Pascal, Ding, Yanchun, Divia, Roberto, Dixit, Dhruv Utpalkumar, Djuvsland, Oeystein, Dmitrieva, Uliana, Alkin, Anton, Dobrin, Alexandru Florin, Donigus, Benjamin, Dordic, Olja, Dubey, Anand Kumar, Dubla, Andrea, Dudi, Sandeep, Mallick, Dukhishyam, Dupieux, Pascal, Ehlers Iii, Raymond James, Eikeland, Viljar Nilsen, Alme, Johan, Elia, Domenico, Erazmus, Barbara Ewa, Erhardt, Filip, Erokhin, Andrey, Ersdal, Magnus Rentsch, Espagnon, Bruno, Eulisse, Giulio, Evans, David, Evdokimov, Sergey, Fabbietti, Laura, Alt, Torsten, Faggin, Mattia, Faivre, Julien, Fan, Feng, Fantoni, Alessandra, Fasel, Markus, Fecchio, Pietro, Feliciello, Alessandro, Feofilov, Grigorii, Fernandez Tellez, Arturo, Ferrero, Andrea, Altenkamper, Lucas, Ferretti, Alessandro, Festanti, Andrea, Feuillard, Victor Jose Gaston, Figiel, Jan, Filchagin, Sergey, Finogeev, Dmitry, Fionda, Fiorella, Fiorenza, Gabriele, Flor, Fernando Antonio, Flores, Amanda Nicole, Altsybeev, Igor, Foertsch, Siegfried Valentin, Foka, Panagiota, Fokin, Sergey, Fragiacomo, Enrico, Frankenfeld, Ulrich Michael, Fuchs, Ulrich, Furget, Christophe, Furs, Artur, Fusco Girard, Mario, Gaardhoeje, Jens Joergen, Anaam, Mustafa, Gagliardi, Martino, Gago Medina, Alberto Martin, Gal, Arthur Willem Jean, Duarte Galvan, Carlos, Ganoti, Paraskevi, Garabatos Cuadrado, Jose, Alvarado Garcia, Jesus Ricardo, Garcia-solis, Edmundo Javier, Garg, Kunal, Gargiulo, Corrado, Adolfsson, Jonatan, Andrei, Cristian, Garibli, Aydan, Garner, Katharina, Gasik, Piotr Jan, Gauger, Erin Frances, De Leone Gay, Maria Beatriz, Germain, Marie, Ghosh, Jhuma, Ghosh, Premomoy, Ghosh, Sanjay Kumar, Giacalone, Marco, Andreou, Dimitra, Gianotti, Paola, Giubellino, Paolo, Giubilato, Piero, Glaenzer, Aude Marie Camille, Glassel, Peter, Gomez Ramirez, Andres, Gonzalez, Victor, Gonzalez Trueba, Laura Helena, Gorbunov, Sergey, Gorlich, Lidia Maria, Andronic, Anton, Goswami, Ankita, Gotovac, Sven, Grabski, Varlen, Graczykowski, Lukasz Kamil, Graham, Katie Leanne, Greiner, Leo Clifford, Grelli, Alessandro, Grigoras, Costin, Grigoryev, Vladislav, Grigoryan, Ara, Angeletti, Massimo, Grigoryan, Smbat, Groettvik, Ola Slettevoll, Grosa, Fabrizio, Grosse-oetringhaus, Jan Fiete, Grosso, Raffaele, Guernane, Rachid, Guittiere, Manuel, Gulbrandsen, Kristjan Herlache, Gunji, Taku, Gupta, Anik, Anguelov, Venelin, Gupta, Ramni, Bautista Guzman, Irais, Haake, Rudiger, Habib, Michael Karim, Hadjidakis, Cynthia Marie, Hamagaki, Hideki, Hamar, Gergoe, Hamid, Mohammed, Hannigan, Ryan Patrick, Haque, Md Rihan, Anson, Christopher Daniel, Harlenderova, Alena, Harris, John William, Harton, Austin Vincent, Hasenbichler, Jan Anton, Hassan, Hadi, Hassan, Qamar Ul, Hatzifotiadou, Despina, Hauer, Philip, Havener, Laura Brittany, Hayashi, Shinichi, Anticic, Tome, Heckel, Stefan Thomas, Hellbar, Ernst, Helstrup, Haavard, Herghelegiu, Andrei Ionut, Herman, Tomas, Gonzalez Hernandez, Emma, Herrera Corral, Gerardo Antonio, Herrmann, Florian, Hetland, Kristin Fanebust, Hillemanns, Hartmut, Antinori, Federico, Hills, Christopher, Hippolyte, Boris, Hohlweger, Bernhard, Honermann, Jan, Horak, David, Hornung, Andrea, Hornung, Sebastian, Hosokawa, Ritsuya, Hristov, Peter Zahariev, Huang, Chun-lu, Antonioli, Pietro, Hughes, Charles, Huhn, Patrick, Humanic, Thomas, Hushnud, Hushnud, Husova, Lucia Anna, Hussain, Nur, Hussain, Syed Asad, Hutter, Dirk, Iddon, James Philip, Ilkaev, Radiy, Apadula, Nicole, Ilyas, Hira, Inaba, Motoi, Innocenti, Gian Michele, Ippolitov, Mikhail, Isakov, Artem, Islam, Md Samsul, Ivanov, Marian, Ivanov, Vladimir, Izucheev, Vladimir, Jacak, Barbara, Aggarwal, Madan Mohan, Aphecetche, Laurent Bernard, Jacazio, Nicolo, Jacobs, Peter Martin, Jadlovska, Slavka, Jadlovsky, Jan, Jaelani, Syaefudin, Jahnke, Cristiane, Jakubowska, Monika Joanna, Janik, Malgorzata Anna, Janson, Thomas, Jercic, Marko, Appelshaeuser, Harald, Jevons, Oliver Thomas, Jin, Muqing, Jonas, Florian, Jones, Peter Graham, Jung, Jerome, Jung, Michael, Jusko, Anton, Kalinak, Peter, Kalweit, Alexander Philipp, Kaplin, Vladimir, Arcelli, Silvia, Kar, Somnath, Karasu Uysal, Ayben, Karatovic, David, Karavichev, Oleg, Karavicheva, Tatiana, Karczmarczyk, Przemyslaw, Karpechev, Evgeny, Kazantsev, Andrey, Kebschull, Udo Wolfgang, Keidel, Ralf, Arnaldi, Roberta, Keil, Markus, Ketzer, Bernhard Franz, Khabanova, Zhanna, Khan, Ahsan Mehmood, Khan, Shaista, Khanzadeev, Alexei, Kharlov, Yury, Khatun, Anisa, Khuntia, Arvind, Kileng, Bjarte, Arratia Munoz, Miguel Ignacio, Kim, Beomkyu, Kim, Byungchul, Kim, Daehyeok, Kim, Dong Jo, Kim, Eun Joo, Kim, Hyeonjoong, Kim, Jaehyun, Kim, Jinsook, Kim, Jiyoung, Kim, Jungeol, Arsene, Ionut Cristian, Kim, Junlee, Kim, Minjung, Kim, Se Yong, Kim, Taejun, Kim, Taesoo, Kirsch, Stefan, Kisel, Ivan, Kiselev, Sergey, Kisiel, Adam Ryszard, Klay, Jennifer Lynn, Arslandok, Mesut, Klein, Carsten, Klein, Jochen, Klein, Spencer Robert, Klein-boesing, Christian, Kleiner, Matthias, Kluge, Alexander, Knichel, Michael Linus, Knospe, Anders Garritt, Kobdaj, Chinorat, Kohler, Markus Konrad, Augustinus, Andre, Kollegger, Thorsten Sven, Kondratyev, Andrey, Kondratyeva, Natalia, Kondratyuk, Evgeny, Konig, Joshua Leon, Konigstorfer, Stephan Alexander, Konopka, Piotr Jan, Kornakov, Georgui, Koska, Lukas, Kovalenko, Oleksandr, Averbeck, Ralf Peter, Kovalenko, Vladimir, Kowalski, Marek, Kralik, Ivan, Kravcakova, Adela, Kreis, Lukas, Krivda, Marian, Krizek, Filip, Krizkova Gajdosova, Katarina, Kruger, Mario, Kryshen, Evgeny, Aziz, Sizar, Krzewicki, Mikolaj, Kubera, Andrew Michael, Kucera, Vit, Kuhn, Christian Claude, Kuijer, Paulus Gerardus, Kumar, Lokesh, Kundu, Sourav, Kurashvili, Podist, Kurepin, Alexander, Kurepin, Alexey, Aglieri Rinella, Gianluca, Azmi, Mohd Danish, Kuryakin, Alexey, Kushpil, Svetlana, Kvapil, Jakub, Kweon, Min Jung, Kwon, Jiyeon, Kwon, Youngil, La Pointe, Sarah Louise, La Rocca, Paola, Lai, Yue Shi, Lamanna, Massimo, Badala, Angela, Langoy, Rune, Lapidus, Kirill, Lardeux, Antoine Xavier, Larionov, Pavel, Laudi, Elisa, Lavicka, Roman, Lazareva, Tatiana, Lea, Ramona, Leardini, Lucia, Lee, Joonil, Baek, Yongwook, Lee, Seongjoo, Lehner, Sebastian, Lehrbach, Johannes, Lemmon, Roy Crawford, Leon Monzon, Ildefonso, Lesser, Ezra Douglas, Lettrich, Michael, Levai, Peter, Li, Xiaomei, Li, Xing Long, Bagnasco, Stefano, Lien, Jorgen Andre, Lietava, Roman, Lim, Bong-hwi, Lindenstruth, Volker, Lindner, Amelia, Lippmann, Christian, Lisa, Michael Annan, Liu, Alwina Ruixin, Liu, Jian, Liu, Suyuan, Bai, Xiaozhi, Llope, William Joseph, Lofnes, Ingrid Mckibben, Loginov, Vitaly, Loizides, Constantinos, Loncar, Petra, Lopez Lopez, Jorge Andres, Lopez, Xavier Bernard, Lopez Torres, Ernesto, Luhder, Jens Robert, Lunardon, Marcello, Bailhache, Raphaelle Marie, Luparello, Grazia, Ma, Yugang, Maevskaya, Alla, Mager, Magnus, Mahmood, Sohail Musa, Mahmoud, Tariq, Maire, Antonin, Majka, Richard Daniel, Malaev, Mikhail, Malik, Qasim Waheed, Bala, Renu, Malinina, Liudmila, Mal Kevich, Dmitry, Malzacher, Peter, Mandaglio, Giuseppe, Manko, Vladislav, Manso, Franck, Manzari, Vito, Mao, Yaxian, Marchisone, Massimiliano, Mares, Jiri, Balbino, Alessandro, Margagliotti, Giacomo Vito, Margotti, Anselmo, Marin, Ana Maria, Markert, Christina, Marquard, Marco, De Martin, Chiara, Martin, Nicole Alice, Martinengo, Paolo, Martinez, Jacobb Lee, Martinez Hernandez, Mario Ivan, Baldisseri, Alberto, Martinez-garcia, Gines, Masciocchi, Silvia, Masera, Massimo, Masoni, Alberto, Massacrier, Laure Marie, Masson, Erwann, Mastroserio, Annalisa, Mathis, Andreas Michael, Matonoha, Oliver, Toledo Matuoka, Paula Fernanda, Ball, Markus, Matyja, Adam Tomasz, Mayer, Christoph, Mazzaschi, Francesco, Mazzilli, Marianna, Mazzoni, Alessandra Maria, Mechler, Adrian Florin, Meddi, Franco, Melikyan, Yury, Menchaca-rocha, Arturo Alejandro, Cai, Mengke, Agnello, Michelangelo, Balouza, Samah, Meninno, Elisa, Sasikumar Menon, Anjaly, Meres, Michal, Mhlanga, Sibaliso, Miake, Yasuo, Micheletti, Luca, Migliorin, Lucrezia Camilla, Mihaylov, Dimitar Lubomirov, Mikhaylov, Konstantin, Mishra, Aditya Nath, Banerjee, Debjani, Miskowiec, Dariusz Czeslaw, Modak, Abhi, Mohammadi, Naghmeh, Mohanty, Auro Prasad, Mohanty, Bedangadas, Khan, Mohammed Mohisin, Moravcova, Zuzana, Mordasini, Cindy, Moreira De Godoy, Denise Aparecida, Perez Moreno, Luis Alberto, Barbera, Roberto, Morozov, Igor, Morsch, Andreas, Mrnjavac, Teo, Muccifora, Valeria, Mudnic, Eugen, Muhlheim, Daniel Michael, Muhuri, Sanjib, Mulligan, James Declan, Mulliri, Alice, Gameiro Munhoz, Marcelo, Barioglio, Luca, Munzer, Robert Helmut, Murakami, Hikari, Murray, Sean, Musa, Luciano, Musinsky, Jan, Myers, Corey James, Myrcha, Julian Wojciech, Naik, Bharati, Nair, Rahul Ramachandran, Nandi, Basanta Kumar, Barnafoldi, Gergely Gabor, Nania, Rosario, Nappi, Eugenio, Naru, Muhammad Umair, Nassirpour, Adrian Fereydon, Nattrass, Christine, Nayak, Ranjit, Nayak, Tapan Kumar, Nazarenko, Sergey, Neagu, Alexandra, Negrao De Oliveira, Renato Aparecido, Barnby, Lee Stuart, Nellen, Lukas, Nesbo, Simon Voigt, Neskovic, Gvozden, Nesterov, Dmitrii, Neumann, Lukasz Tomasz, Nielsen, Borge Svane, Nikolaev, Sergey, Nikulin, Sergey, Nikulin, Vladimir, Noferini, Francesco, Ramillien Barret, Valerie, Nomokonov, Petr, Norman, Jaime, Novitzky, Norbert, Nowakowski, Piotr, Nyanin, Alexander, Nystrand, Joakim Ingemar, Ogino, Masanori, Ohlson, Alice Elisabeth, Oleniacz, Janusz, Oliveira Da Silva, Antonio Carlos, Bartalini, Paolo, Oliver, Michael Henry, Oppedisano, Chiara, Ortiz Velasquez, Antonio, Oskarsson, Anders Nils Erik, Otwinowski, Jacek Tomasz, Oyama, Ken, Pachmayer, Yvonne Chiara, Pacik, Vojtech, Padhan, Sonali, Pagano, Davide, Bartels, Clara, Paic, Guy, Pan, Jinjin, Panebianco, Stefano, Pareek, Pooja, Park, Jonghan, Parkkila, Jasper Elias, Parmar, Sonia, Pathak, Surya Prakash, Paul, Biswarup, Pazzini, Jacopo, Barth, Klaus, Pei, Hua, Peitzmann, Thomas, Peng, Xinye, Pereira, Luis Gustavo, Pereira Da Costa, Hugo Denis Antonio, Peresunko, Dmitry Yurevich, Mesa Perez, Guillermo, Perrin, Sebastien, Pestov, Yury, Petracek, Vojtech, Agrawal, Neelima, Bartsch, Esther, Petrovici, Mihai, Peretti Pezzi, Rafael, Piano, Stefano, Pikna, Miroslav, Pillot, Philippe, Pinazza, Ombretta, Pinsky, Lawrence, Pinto, Chiara, Pisano, Silvia, Pistone, Daniele, Baruffaldi, Filippo, Ploskon, Mateusz Andrzej, Planinic, Mirko, Pliquett, Fabian, Poghosyan, Martin, Polishchuk, Boris, Poljak, Nikola, Pop, Amalia, Porteboeuf, Sarah Julie, Pozdniakov, Valeriy, Prasad, Sidharth Kumar, Bastid, Nicole, Preghenella, Roberto, Prino, Francesco, Pruneau, Claude Andre, Pshenichnov, Igor, Puccio, Maximiliano, Putschke, Jorn Henning, Qiu, Shi, Quaglia, Luca, Quishpe Quishpe, Raquel Estefania, Ragoni, Simone, Basu, Sumit, Raha, Sibaji, Rajput, Sonia, Rak, Jan, Rakotozafindrabe, Andry Malala, Ramello, Luciano, Rami, Fouad, Rodriguez Ramirez, Saul Anibal, Raniwala, Rashmi, Raniwala, Sudhir, Rasanen, Sami Sakari, Batigne, Guillaume, Rath, Rutuparna, Ratza, Viktor, Ravasenga, Ivan, Read, Kenneth Francis, Redelbach, Andreas Ralph, Redlich, Krzysztof, Rehman, Attiq Ur, Reichelt, Patrick Simon, Reidt, Felix, Ren, Xiaowen, Batyunya, Boris, Renfordt, Rainer Arno Ernst, Jakubcinova, Zuzana, Reygers, Klaus Johannes, Riabov, Andrei, Riabov, Viktor, Richert, Tuva Ora Herenui, Richter, Matthias Rudolph, Riedler, Petra, Riegler, Werner, Riggi, Francesco, Bauri, Dibakar, Ristea, Catalin-lucian, Rode, Sudhir Pandurang, Rodriguez Cahuantzi, Mario, Roeed, Ketil, Rogalev, Roman, Rogochaya, Elena, Rohr, David Michael, Roehrich, Dieter, Fierro Rojas, Pablo, 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Hans Rudolf, Schmidt, Marten Ole, Schmidt, Martin, Schmidt, Nicolas, Schmier, Austin Robert, Schukraft, Jurgen, Schutz, Yves Roland, Belikov, Iouri, Schwarz, Kilian Eberhard, Schweda, Kai Oliver, Scioli, Gilda, Scomparin, Enrico, Seger, Janet Elizabeth, Sekiguchi, Yuko, Sekihata, Daiki, Selyuzhenkov, Ilya, Senyukov, Serhiy, Serebryakov, Dmitry, Bell Hechavarria, Ailec, Sevcenco, Adrian, Shabanov, Arseniy, Shabetai, Alexandre, Shahoyan, Ruben, Shaikh, Wadut, Shangaraev, Artem, Sharma, Anjali, Sharma, Ankita, Sharma, Himanshu, Sharma, Meenakshi, Bellini, Francesca, Sharma, Natasha, Sharma, Sheetal, Sheibani, Oveis, Shigaki, Kenta, Hachiya Shimomura, Maya, Shirinkin, Sergey, Shou, Qiye, Sibiryak, Yury, Siddhanta, Sabyasachi, Siemiarczuk, Teodor, Bellwied, Rene, Silvermyr, David Olle Rickard, Simatovic, Goran, Simonetti, Giuseppe, Singh, Bhawani, Singh, Ranbir, Singh, Randhir, Singh, Ravindra, Singh, Vivek, Singhal, Vikas, Sarkar - Sinha, Tinku, Belyaev, Vladimir, Sitar, Branislav, Sitta, Mario, Skaali, Bernhard, Slupecki, Maciej, Smirnov, Nikolai, Snellings, Raimond, Soncco Meza, Carlos, Song, Jihye, Songmoolnak, Arnon, Soramel, Francesca, Bencedi, Gyula, Sorensen, Soren Pontoppidan, Sputowska, Iwona Anna, Stachel, Johanna, Stan, Ionel, Steffanic, Patrick John, Stenlund, Evert Anders, Stiefelmaier, Stephan Friedrich, Stocco, Diego, Storetvedt, Maksim Melnik, Dello Stritto, Luigi, Beole, Stefania, Alarcon Do Passo Suaide, Alexandre, Sugitate, Toru, Suire, Christophe Pierre, Suleymanov, Mais Kazim Oglu, Suljic, Miljenko, Sultanov, Rishat, Sumbera, Michal, Sumberia, Vikash, Sumowidagdo, Suharyo, Swain, Sagarika, Bercuci, Alexandru, Szabo, Alexander, Szarka, Imrich, Tabassam, Uzma, Taghavi, Seyed Farid, Taillepied, Guillaume, Takahashi, Jun, Tambave, Ganesh Jagannath, Tang, Siyu, Tarhini, Mohamad, Tarzila, Madalina-gabriela, Ahmad, Shakeel, Berdnikov, Yaroslav, Tauro, Arturo, Tejeda Munoz, Guillermo, Telesca, Adriana, Terlizzi, Livia, Terrevoli, Cristina, Thakur, Dhananjaya, Thakur, Sanchari, Thomas, Deepa, Thoresen, Freja, Tieulent, Raphael Noel, Berenyi, Daniel, Tikhonov, Anatoly, Timmins, Anthony Robert, Toia, Alberica, Topilskaya, Nataliya, Toppi, Marco, Torales Acosta, Fernando, Rojas Torres, Solangel, Trifiro, Antonio, Tripathy, Sushanta, Tripathy, Tulika, Bertens, Redmer Alexander, Trogolo, Stefano, Trombetta, Giuseppe, Tropp, Lukas, Trubnikov, Victor, Trzaska, Wladyslaw Henryk, Trzcinski, Tomasz Piotr, Trzeciak, Barbara Antonina, Tumkin, Alexandr, Turrisi, Rosario, Tveter, Trine Spedstad, Berzano, Dario, Ullaland, Kjetil, Umaka, Ejiro Naomi, Uras, Antonio, Usai, Gianluca, Vala, Martin, Valle, Nicolo', Vallero, Sara, Van Der Kolk, Naomi, Van Doremalen, Lennart, Van Leeuwen, Marco, Besoiu, Mihaela Gabriela, Vande Vyvre, Pierre, Varga, Dezso, Varga, Zoltan, Varga-kofarago, Monika, Diozcora Vargas Trevino, Aurora, Vasileiou, Maria, Vasiliev, Andrey, Vazquez Doce, Oton, Vechernin, Vladimir, Vercellin, Ermanno, Betev, Latchezar, Vergara Limon, Sergio, Vermunt, Lucas Anne, Vernet, Renaud, Vertesi, Robert, Vickovic, Linda, Vilakazi, Zabulon, Villalobos Baillie, Orlando, Vino, Gioacchino, Vinogradov, Alexander, Virgili, Tiziano, Bhasin, Anju, Vislavicius, Vytautas, Vodopyanov, Alexander, Volkel, Benedikt, Volkl, Martin Andreas, Voloshin, Kirill, Voloshin, Sergey, Volpe, Giacomo, Von Haller, Barthelemy, Vorobyev, Ivan, Voscek, Dominik, Bhat, Inayat Rasool, Vrlakova, Janka, Wagner, Boris, Weber, Michael, Weber, Steffen Georg, Wegrzynek, Adam Tadeusz, Wenzel, Sandro Christian, Wessels, Johannes Peter, Wiechula, Jens, Wikne, Jon, Wilk, Grzegorz Andrzej, Bhat, Mohammad Asif, Wilkinson, Jeremy John, Willems, Guido Alexander, Willsher, Emily Jade, Windelband, Bernd Stefan, Winn, Michael Andreas, Witt, William Edward, Wright, Josephina Rae, Wu, Yitao, Xu, Ran, Yalcin Kuzu, Serpil, Bhatt, Himani, Yamaguchi, Yorito, Yamakawa, Kosei, Yang, Shiming, Yano, Satoshi, Yin, Zhongbao, Yokoyama, Hiroki, Yoo, In Kwon, Yoon, Jin Hee, Yuan, 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K., Karatovic, D., Karavichev, O., Karavicheva, T., Karczmarczyk, P., Karpechev, E., Kazantsev, A., Kebschull, U., Keidel, R., Keil, M., Ketzer, B., Khabanova, Z., Khan, A. M., Khan, S., Khanzadeev, A., Kharlov, Y., Khatun, A., Khuntia, A., Kileng, B., Kim, B., Kim, D., Kim, D. J., Kim, E. J., Kim, H., Kim, J., Kim, J. S., Kim, M., Kim, S., Kim, T., Kirsch, S., Kisel, I., Kiselev, S., Kisiel, A., Klay, J. L., Klein, C., Klein, J., Klein, S., Klein-Bosing, C., Kleiner, M., Kluge, A., Knichel, M. L., Knospe, A. G., Kobdaj, C., Kohler, M. K., Kollegger, T., Kondratyev, A., Kondratyeva, N., Kondratyuk, E., Konig, J., Konigstorfer, S. A., Konopka, P. J., Kornakov, G., Koska, L., Kovalenko, O., Kovalenko, V., Kowalski, M., Kralik, I., Kravcakova, A., Kreis, L., Krivda, M., Krizek, F., Gajdosova, K. K., Kruger, M., Kryshen, E., Krzewicki, M., Kubera, A. M., Kucera, V., Kuhn, C., Kuijer, P. G., Kumar, L., Kundu, S., Kurashvili, P., Kurepin, A., Kurepin, A. 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A., Martinengo, P., Martinez, J. L., Martinez, M. I., Garcia, G. M., Masciocchi, S., Masera, M., Masoni, A., Massacrier, L., Masson, E., Mastroserio, A., Mathis, A. M., Matonoha, O., Matuoka, P. F. T., Matyja, A., Mayer, C., Mazzaschi, F., Mazzilli, M., Mazzoni, M. A., Mechler, A. F., Meddi, F., Melikyan, Y., Menchaca-Rocha, A., Mengke, C., Meninno, E., Menon, A. S., Meres, M., Mhlanga, S., Miake, Y., Micheletti, L., Migliorin, L. C., Mihaylov, D. L., Mikhaylov, K., Mishra, A. N., Miskowiec, D., Modak, A., Mohammadi, N., Mohanty, A. P., Mohanty, B., Khan, M. M., Moravcova, Z., Mordasini, C., Moreira De Godoy, D. A., Moreno, L. A. P., Morozov, I., Morsch, A., Mrnjavac, T., Muccifora, V., Mudnic, E., Muhlheim, D., Muhuri, S., Mulligan, J. D., Mulliri, A., Munhoz, M. G., Munzer, R. H., Murakami, H., Murray, S., Musa, L., Musinsky, J., Myers, C. J., Myrcha, J. W., Naik, B., Nair, R., Nandi, B. K., Nania, R., Nappi, E., Naru, M. U., Nassirpour, A. F., Nattrass, C., Nayak, R., Nayak, T. K., Nazarenko, S., Neagu, A., Negrao De Oliveira, R. A., Nellen, L., Nesbo, S. V., Neskovic, G., Nesterov, D., Neumann, L. T., Nielsen, B. S., Nikolaev, S., Nikulin, S., Nikulin, V., Noferini, F., Nomokonov, P., Norman, J., Novitzky, N., Nowakowski, P., Nyanin, A., Nystrand, J., Ogino, M., Ohlson, A., Oleniacz, J., Da Silva, A. C. O., Oliver, M. H., Oppedisano, C., Velasquez, A. O., Oskarsson, A., Otwinowski, J., Oyama, K., Pachmayer, Y., Pacik, V., Padhan, S., Pagano, D., Paic, G., Pan, J., Panebianco, S., Pareek, P., Park, J., Parkkila, J. E., Parmar, S., Pathak, S. P., Paul, B., Pazzini, J., Pei, H., Peitzmann, T., Peng, X., Pereira, L. G., Da Costa, H. P., Peresunko, D., Perez, G. M., Perrin, S., Pestov, Y., Petracek, V., Petrovici, M., Pezzi, R. P., Piano, S., Pikna, M., Pillot, P., Pinazza, O., Pinsky, L., Pinto, C., Pisano, S., Pistone, D., Ploskon, M., Planinic, M., Pliquett, F., Poghosyan, M. 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C., Zardoshti, N., Zarochentsev, A., Zavada, P., Zaviyalov, N., Zbroszczyk, H., Zhalov, M., Zhang, S., Zhang, X., Zhang, Z., Zherebchevskii, V., Zhi, Y., Zhou, D., Zhou, Y., Zhou, Z., Zhu, J., Zhu, Y., Zichichi, A., Zinovjev, G., Zurlo, N., Laboratoire de physique subatomique et des technologies associées (SUBATECH), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Département de Physique Nucléaire (ex SPhN) (DPHN), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire de Physique de Clermont (LPC), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Institut Pluridisciplinaire Hubert Curien (IPHC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Institut de Physique Nucléaire de Lyon (IPNL), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre de Calcul de l'IN2P3 (CC-IN2P3), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), ALICE, Université de Nantes (UN)-Université de Nantes (UN)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Université de Strasbourg (UNISTRA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), S. 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A. Diaz, T. Dietel, P. Dillenseger, Y. Ding, R. Divià, D. U. Dixit, Ø. Djuvsland, U. Dmitrieva, A. Dobrin, B. Dönigus, O. Dordic, A. K. Dubey, A. Dubla, S. Dudi, M. Dukhishyam, P. Dupieux, R. J. Ehlers, V. N. Eikeland, D. Elia, B. Erazmus, F. Erhardt, A. Erokhin, M. R. Ersdal, B. Espagnon, G. Eulisse, D. Evans, S. Evdokimov, L. Fabbietti, M. Faggin, J. Faivre, F. Fan, A. Fantoni, M. Fasel, P. Fecchio, A. Feliciello, G. Feofilov, A. Fernández Téllez, A. Ferrero, A. Ferretti, A. Festanti, V. J. G. Feuillard, J. Figiel, S. Filchagin, D. Finogeev, F. M. Fionda, G. Fiorenza, F. Flor, A. N. Flores, S. Foertsch, P. Foka, S. Fokin, E. Fragiacomo, U. Frankenfeld, U. Fuchs, C. Furget, A. Furs, M. Fusco Girard, J. J. Gaardhøje, M. Gagliardi, A. M. Gago, A. Gal, C. D. Galvan, P. Ganoti, C. Garabatos, J. R. A. Garcia, E. Garcia-Solis, K. Garg, C. Gargiulo, A. Garibli, K. Garner, P. Gasik, E. F. Gauger, M. B. Gay Ducati, M. Germain, J. Ghosh, P. Ghosh, S. K. Ghosh, M. Giacalone, P. Gianotti, P. Giubellino, P. Giubilato, A. M. C. Glaenzer, P. Glässel, A. Gomez Ramirez, V. Gonzalez, L. H. González-Trueba, S. Gorbunov, L. Görlich, A. Goswami, S. Gotovac, V. Grabski, L. K. Graczykowski, K. L. Graham, L. Greiner, A. Grelli, C. Grigoras, V. Grigoriev, A. Grigoryan, S. Grigoryan, O. S. Groettvik, F. Grosa, J. F. Grosse-Oetringhaus, R. Grosso, R. Guernane, M. Guittiere, K. Gulbrandsen, T. Gunji, A. Gupta, R. Gupta, I. B. Guzman, R. Haake, M. K. Habib, C. Hadjidakis, H. Hamagaki, G. Hamar, M. Hamid, R. Hannigan, M. R. Haque, A. Harlenderova, J. W. Harris, A. Harton, J. A. Hasenbichler, H. Hassan, Q. U. Hassan, D. Hatzifotiadou, P. Hauer, L. B. Havener, S. Hayashi, S. T. Heckel, E. Hellbär, H. Helstrup, A. Herghelegiu, T. Herman, E. G. Hernandez, G. Herrera Corral, F. Herrmann, K. F. Hetland, H. Hillemanns, C. Hills, B. Hippolyte, B. Hohlweger, J. Honermann, D. Horak, A. Hornung, S. Hornung, R. Hosokawa, P. Hristov, C. Huang, C. Hughes, P. Huhn, T. J. Humanic, H. Hushnud, L. A. Husova, N. Hussain, S. A. Hussain, D. Hutter, J. P. Iddon, R. Ilkaev, H. Ilyas, M. Inaba, G. M. Innocenti, M. Ippolitov, A. Isakov, M. S. Islam, M. Ivanov, V. Ivanov, V. Izucheev, B. Jacak, N. Jacazio, P. M. Jacobs, S. Jadlovska, J. Jadlovsky, S. Jaelani, C. Jahnke, M. J. Jakubowska, M. A. Janik, T. Janson, M. Jercic, O. Jevons, M. Jin, F. Jonas, P. G. Jones, J. Jung, M. Jung, A. Jusko, P. Kalinak, A. Kalweit, V. Kaplin, S. Kar, A. Karasu Uysal, D. Karatovic, O. Karavichev, T. Karavicheva, P. Karczmarczyk, E. Karpechev, A. Kazantsev, U. Kebschull, R. Keidel, M. Keil, B. Ketzer, Z. Khabanova, A. M. Khan, S. Khan, A. Khanzadeev, Y. Kharlov, A. Khatun, A. Khuntia, B. Kileng, B. Kim, B. Kim, D. Kim, D. J. Kim, E. J. Kim, H. Kim, J. Kim, J. S. Kim, J. Kim, J. Kim, J. Kim, M. Kim, S. Kim, T. Kim, T. Kim, S. Kirsch, I. Kisel, S. Kiselev, A. Kisiel, J. L. Klay, C. Klein, J. Klein, S. Klein, C. Klein-Bösing, M. Kleiner, A. Kluge, M. L. Knichel, A. G. Knospe, C. Kobdaj, M. K. Köhler, T. Kollegger, A. Kondratyev, N. Kondratyeva, E. Kondratyuk, J. Konig, S. A. Konigstorfer, P. J. Konopka, G. Kornakov, L. Koska, O. Kovalenko, V. Kovalenko, M. Kowalski, I. Králik, A. Kravčáková, L. Kreis, M. Krivda, F. Krizek, K. Krizkova Gajdosova, M. Krüger, E. Kryshen, M. Krzewicki, A. M. Kubera, V. Kučera, C. Kuhn, P. G. Kuijer, L. Kumar, S. Kundu, P. Kurashvili, A. Kurepin, A. B. Kurepin, A. Kuryakin, S. Kushpil, J. Kvapil, M. J. Kweon, J. Y. Kwon, Y. Kwon, S. L. La Pointe, P. La Rocca, Y. S. Lai, M. Lamanna, R. Langoy, K. Lapidus, A. Lardeux, P. Larionov, E. Laudi, R. Lavicka, T. Lazareva, R. Lea, L. Leardini, J. Lee, S. Lee, S. Lehner, J. Lehrbach, R. C. Lemmon, I. León Monzón, E. D. Lesser, M. Lettrich, P. Lévai, X. Li, X. L. Li, J. Lien, R. Lietava, B. Lim, V. Lindenstruth, A. Lindner, C. Lippmann, M. A. Lisa, A. Liu, J. Liu, S. Liu, W. J. Llope, I. M. Lofnes, V. Loginov, C. Loizides, P. Loncar, J. A. Lopez, X. Lopez, E. López Torres, J. R. Luhder, M. Lunardon, G. Luparello, Y. G. Ma, A. Maevskaya, M. Mager, S. M. Mahmood, T. Mahmoud, A. Maire, R. D. Majka, M. Malaev, Q. W. Malik, L. Malinina, D. Mal’Kevich, P. Malzacher, G. Mandaglio, V. Manko, F. Manso, V. Manzari, Y. Mao, M. Marchisone, J. Mareš, G. V. Margagliotti, A. Margotti, A. Marín, C. Markert, M. Marquard, C. D. Martin, N. A. Martin, P. Martinengo, J. L. Martinez, M. I. Martínez, G. Martínez García, S. Masciocchi, M. Masera, A. Masoni, L. Massacrier, E. Masson, A. Mastroserio, A. M. Mathis, O. Matonoha, P. F. T. Matuoka, A. Matyja, C. Mayer, F. Mazzaschi, M. Mazzilli, M. A. Mazzoni, A. F. Mechler, F. Meddi, Y. Melikyan, A. Menchaca-Rocha, C. Mengke, E. Meninno, A. S. Menon, M. Meres, S. Mhlanga, Y. Miake, L. Micheletti, L. C. Migliorin, D. L. Mihaylov, K. Mikhaylov, A. N. Mishra, D. Miśkowiec, A. Modak, N. Mohammadi, A. P. Mohanty, B. Mohanty, M. Mohisin Khan, Z. Moravcova, C. Mordasini, D. A. Moreira De Godoy, L. A. P. Moreno, I. Morozov, A. Morsch, T. Mrnjavac, V. Muccifora, E. Mudnic, D. Mühlheim, S. Muhuri, J. D. Mulligan, A. Mulliri, M. G. Munhoz, R. H. Munzer, H. Murakami, S. Murray, L. Musa, J. Musinsky, C. J. Myers, J. W. Myrcha, B. Naik, R. Nair, B. K. Nandi, R. Nania, E. Nappi, M. U. Naru, A. F. Nassirpour, C. Nattrass, R. Nayak, T. K. Nayak, S. Nazarenko, A. Neagu, R. A. Negrao De Oliveira, L. Nellen, S. V. Nesbo, G. Neskovic, D. Nesterov, L. T. Neumann, B. S. Nielsen, S. Nikolaev, S. Nikulin, V. Nikulin, F. Noferini, P. Nomokonov, J. Norman, N. Novitzky, P. Nowakowski, A. Nyanin, J. Nystrand, M. Ogino, A. Ohlson, J. Oleniacz, A. C. Oliveira Da Silva, M. H. Oliver, C. Oppedisano, A. Ortiz Velasquez, A. Oskarsson, J. Otwinowski, K. Oyama, Y. Pachmayer, V. Pacik, S. Padhan, D. Pagano, G. Paić, J. Pan, S. Panebianco, P. Pareek, J. Park, J. E. Parkkila, S. Parmar, S. P. Pathak, B. Paul, J. Pazzini, H. Pei, T. Peitzmann, X. Peng, L. G. Pereira, H. Pereira Da Costa, D. Peresunko, G. M. Perez, S. Perrin, Y. Pestov, V. Petráček, M. Petrovici, R. P. Pezzi, S. Piano, M. Pikna, P. Pillot, O. Pinazza, L. Pinsky, C. Pinto, S. Pisano, D. Pistone, M. Płoskoń, M. Planinic, F. Pliquett, M. G. Poghosyan, B. Polichtchouk, N. Poljak, A. Pop, S. Porteboeuf-Houssais, V. Pozdniakov, S. K. Prasad, R. Preghenella, F. Prino, C. A. Pruneau, I. Pshenichnov, M. Puccio, J. Putschke, S. Qiu, L. Quaglia, R. E. Quishpe, S. Ragoni, S. Raha, S. Rajput, J. Rak, A. Rakotozafindrabe, L. Ramello, F. Rami, S. A. R. Ramirez, R. Raniwala, S. Raniwala, S. S. Räsänen, R. Rath, V. Ratza, I. Ravasenga, K. F. Read, A. R. Redelbach, K. Redlich, A. Rehman, P. Reichelt, F. Reidt, X. Ren, R. Renfordt, Z. Rescakova, K. Reygers, A. Riabov, V. Riabov, T. Richert, M. Richter, P. Riedler, W. Riegler, F. Riggi, C. Ristea, S. P. Rode, M. Rodríguez Cahuantzi, K. Røed, R. Rogalev, E. Rogochaya, D. Rohr, D. Röhrich, P. F. Rojas, P. S. Rokita, F. Ronchetti, A. Rosano, E. D. Rosas, K. Roslon, A. Rossi, A. Rotondi, A. Roy, P. Roy, O. V. Rueda, R. Rui, B. Rumyantsev, A. Rustamov, E. Ryabinkin, Y. Ryabov, A. Rybicki, H. Rytkonen, O. A. M. Saarimaki, R. Sadek, S. Sadhu, S. Sadovsky, K. Šafařík, S. K. Saha, B. Sahoo, P. Sahoo, R. Sahoo, S. Sahoo, P. K. Sahu, J. Saini, S. Sakai, S. Sambyal, V. Samsonov, D. Sarkar, N. Sarkar, P. Sarma, V. M. Sarti, M. H. P. Sas, E. Scapparone, J. Schambach, H. S. Scheid, C. Schiaua, R. Schicker, A. Schmah, C. Schmidt, H. R. Schmidt, M. O. Schmidt, M. Schmidt, N. V. Schmidt, A. R. Schmier, J. Schukraft, Y. Schutz, K. Schwarz, K. Schweda, G. Scioli, E. Scomparin, J. E. Seger, Y. Sekiguchi, D. Sekihata, I. Selyuzhenkov, S. Senyukov, D. Serebryakov, A. Sevcenco, A. Shabanov, A. Shabetai, R. Shahoyan, W. Shaikh, A. Shangaraev, A. Sharma, A. Sharma, H. Sharma, M. Sharma, N. Sharma, S. Sharma, O. Sheibani, K. Shigaki, M. Shimomura, S. Shirinkin, Q. Shou, Y. Sibiriak, S. Siddhanta, T. Siemiarczuk, D. Silvermyr, G. Simatovic, G. Simonetti, B. Singh, R. Singh, R. Singh, R. Singh, V. K. Singh, V. Singhal, T. Sinha, B. Sitar, M. Sitta, T. B. Skaali, M. Slupecki, N. Smirnov, R. J. M. Snellings, C. Soncco, J. Song, A. Songmoolnak, F. Soramel, S. Sorensen, I. Sputowska, J. Stachel, I. Stan, P. J. Steffanic, E. Stenlund, S. F. Stiefelmaier, D. Stocco, M. M. Storetvedt, L. D. Stritto, A. A. P. Suaide, T. Sugitate, C. Suire, M. Suleymanov, M. Suljic, R. Sultanov, M. Šumbera, V. Sumberia, S. Sumowidagdo, S. Swain, A. Szabo, I. Szarka, U. Tabassam, S. F. Taghavi, G. Taillepied, J. Takahashi, G. J. Tambave, S. Tang, M. Tarhini, M. G. Tarzila, A. Tauro, G. Tejeda Muñoz, A. Telesca, L. Terlizzi, C. Terrevoli, D. Thakur, S. Thakur, D. Thomas, F. Thoresen, R. Tieulent, A. Tikhonov, A. R. Timmins, A. Toia, N. Topilskaya, M. Toppi, F. Torales-Acosta, S. R. Torres, A. Trifiró, S. Tripathy, T. Tripathy, S. Trogolo, G. Trombetta, L. Tropp, V. Trubnikov, W. H. Trzaska, T. P. Trzcinski, B. A. Trzeciak, A. Tumkin, R. Turrisi, T. S. Tveter, K. Ullaland, E. N. Umaka, A. Uras, G. L. Usai, M. Vala, N. Valle, S. Vallero, N. van der Kolk, L. V. R. van Doremalen, M. van Leeuwen, P. Vande Vyvre, D. Varga, Z. Varga, M. Varga-Kofarago, A. Vargas, M. Vasileiou, A. Vasiliev, O. Vázquez Doce, V. Vechernin, E. Vercellin, S. Vergara Limón, L. Vermunt, R. Vernet, R. Vértesi, L. Vickovic, Z. Vilakazi, O. Villalobos Baillie, G. Vino, A. Vinogradov, T. Virgili, V. Vislavicius, A. Vodopyanov, B. Volkel, M. A. Völkl, K. Voloshin, S. A. Voloshin, G. Volpe, B. von Haller, I. Vorobyev, D. Voscek, J. Vrláková, B. Wagner, M. Weber, S. G. Weber, A. Wegrzynek, S. C. Wenzel, J. P. Wessels, J. Wiechula, J. Wikne, G. Wilk, J. Wilkinson, G. A. Willems, E. Willsher, B. Windelband, M. Winn, W. E. Witt, J. R. Wright, Y. Wu, R. Xu, S. Yalcin, Y. Yamaguchi, K. Yamakawa, S. Yang, S. Yano, Z. Yin, H. Yokoyama, I.-K. Yoo, J. H. Yoon, S. Yuan, A. Yuncu, V. Yurchenko, V. Zaccolo, A. Zaman, C. Zampolli, H. J. C. Zanoli, N. Zardoshti, A. Zarochentsev, P. Závada, N. Zaviyalov, H. Zbroszczyk, M. Zhalov, S. Zhang, X. Zhang, Z. Zhang, V. Zherebchevskii, Y. Zhi, D. Zhou, Y. Zhou, Z. Zhou, J. Zhu, Y. Zhu, A. Zichichi, G. Zinovjev & N. Zurlo, Helsinki Institute of Physics, Sub Subatomic Physics (SAP), Afd Subatomic Physics (SAP), Sub Algemeen Physics Education, and Subatomic Physics

Subjects
EXCHANGE-POTENTIAL APPROACH, Strange quark, ALICE Collaboration, Hadron, Nuclear Theory, Strong interaction, hadron collisions, Position and momentum space, hiukkasfysiikka, nucl-ex, 7. Clean energy, 01 natural sciences, VDP::Fysikk: 430, High Energy Physics - Experiment, High Energy Physics - Experiment (hep-ex), Hadron-Hadron scattering (experiments), scattering [hadron], p p scattering, [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex], scattering [p p], Nuclear Experiment (nucl-ex), Experimental nuclear physics, NUCLEON, Nuclear Experiment, VDP::Physics: 430, Physics, Multidisciplinary, Large Hadron Collider, strong interaction, lattice [space-time], Publisher Correction, PRIRODNE ZNANOSTI. Fizika, BARYON-BARYON SCATTERING, CERN LHC Coll, LHC, ddc:500, Nucleon, Particle Physics - Experiment, discrete [space-time], Quark, Particle physics, CERN Lab, General Science & Technology, FOS: Physical sciences, short-range, Hadron, strong interaction, LHC, 114 Physical sciences, Fysikk: 430 [VDP], Article, hadron scattering, quark, ultrarelativistic proton–proton collisions, LHC, ALICE, 0103 physical sciences, Nuclear Physics - Experiment, General, 010306 general physics, Physics: 430 [VDP], interaction [hadron hadron], hep-ex, 010308 nuclear & particles physics, High Energy Physics::Phenomenology, effect [strong interaction], hadron-hadron interaction, strong interaction: effect, space-time: discrete, space-time: lattice, correlation, NATURAL SCIENCES. Physics, Baryon, Hypernuclei, Neutron Stars, Strangeness, Physics::Accelerator Physics, High Energy Physics::Experiment, hadron, Experimental particle physics
Abstract

One of the key challenges for nuclear physics today is to understand from first principles the effective interaction between hadrons with different quark content. First successes have been achieved using techniques that solve the dynamics of quarks and gluons on discrete space-time lattices1,2. Experimentally, the dynamics of the strong interaction have been studied by scattering hadrons off each other. Such scattering experiments are difficult or impossible for unstable hadrons3–6 and so high-quality measurements exist only for hadrons containing up and down quarks7. Here we demonstrate that measuring correlations in the momentum space between hadron pairs8–12 produced in ultrarelativistic proton–proton collisions at the CERN Large Hadron Collider (LHC) provides a precise method with which to obtain the missing information on the interaction dynamics between any pair of unstable hadrons. Specifically, we discuss the case of the interaction of baryons containing strange quarks (hyperons). We demonstrate how, using precision measurements of proton–omega baryon correlations, the effect of the strong interaction for this hadron–hadron pair can be studied with precision similar to, and compared with, predictions from lattice calculations13,14. The large number of hyperons identified in proton–proton collisions at the LHC, together with accurate modelling15 of the small (approximately one femtometre) inter-particle distance and exact predictions for the correlation functions, enables a detailed determination of the short-range part of the nucleon-hyperon interaction., Correlations in momentum space between hadrons created by ultrarelativistic proton–proton collisions at the CERN Large Hadron Collider provide insights into the strong interaction, particularly the short-range dynamics of hyperons—baryons that contain strange quarks.

Published
2020
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38. Phase separation dynamics in wetting ridges of polymer surfaces swollen with oils of different viscosities.

Author

Cai Z, Badr RGM, Hauer L, Chaudhuri K, Skabeev A, Schmid F, and Pham JT

Abstract

When drops are placed on a sufficiently soft surface, the drop surface tension drives an out of plane deformation around the contact line ( i.e. , a wetting ridge). For soft elastomeric surfaces that are swollen with a liquid, capillarity from a drop can induce a phase separation in the wetting ridge. Using confocal microscopy, we study the dynamics of phase separation at the wetting ridge of glycerol drops on silicone elastomers, which are swollen with silicone oils of varying viscosity ( i.e. , molecular weight). We show that the viscosity of the swelling oil plays a large role in the oil separation size and separation rate. For networks swollen to near their maximum swelling ( i.e. , saturated), lower viscosity oil separates more and separates faster at early times compared to larger viscosity oil. During late-stage wetting, the growth rate of the separation is a function of viscosity and swelling ratio, which can be described by a simple diffusive model and a defined wetting ridge geometry. In this late-stage wetting, the higher viscosity oil evidently grows faster, likely because it is further from reaching equilibrium. Interestingly, the separated oil phase region grows with a nearly constant, geometrically similar shape. Understanding how phase separation occurs on swollen substrates should provide information on how to control drop spreading, sliding, adhesion, or friction on such surfaces.

Published
2024
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39. Wetting on silicone surfaces.

Author

Hauer L, Naga A, Badr RGM, Pham JT, Wong WSY, and Vollmer D

Abstract

Silicone is frequently used as a model system to investigate and tune wetting on soft materials. Silicone is biocompatible and shows excellent thermal, chemical, and UV stability. Moreover, the mechanical properties of the surface can be easily varied by several orders of magnitude in a controlled manner. Polydimethylsiloxane (PDMS) is a popular choice for coating applications such as lubrication, self-cleaning, and drag reduction, facilitated by low surface energy. Aiming to understand the underlying interactions and forces, motivated numerous and detailed investigations of the static and dynamic wetting behavior of drops on PDMS-based surfaces. Here, we recognize the three most prevalent PDMS surface variants, namely liquid-infused (SLIPS/LIS), elastomeric, and liquid-like (SOCAL) surfaces. To understand, optimize, and tune the wetting properties of these PDMS surfaces, we review and compare their similarities and differences by discussing (i) the chemical and molecular structure, and (ii) the static and dynamic wetting behavior. We also provide (iii) an overview of methods and techniques to characterize PDMS-based surfaces and their wetting behavior. The static and dynamic wetting ridge is given particular attention, as it dominates energy dissipation, adhesion, and friction of sliding drops and influences the durability of the surfaces. We also discuss special features such as cloaking and wetting-induced phase separation. Key challenges and opportunities of these three surface variants are outlined.

Published
2024
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40. Dynamics of Droplets Moving on Lubricated Polymer Brushes.

Author

Badr RGM, Hauer L, Vollmer D, and Schmid F

Abstract

Understanding the dynamics of drops on polymer-coated surfaces is crucial for optimizing applications such as self-cleaning materials or microfluidic devices. While the static and dynamic properties of deposited drops have been well characterized, a microscopic understanding of the underlying dynamics is missing. In particular, it is unclear how drop dynamics depends on the amount of uncross-linked chains in the brush, because experimental techniques fail to quantify those. Here we use coarse-grained simulations to study droplets moving on a lubricated polymer brush substrate under the influence of an external body force. The simulation model is based on the many body dissipative particle dynamics (MDPD) method and designed to mimic a system of water droplets on poly(dimethylsiloxane) (PDMS) brushes with chemically identical PDMS lubricant. In agreement with experiments, we find a sublinear power law dependence between the external force F and the droplet velocity v , F ∝ v α with α < 1; however, the exponents differ (α ∼ 0.6-0.7 in simulations versus α ∼ 0.25 in experiments). With increasing velocity, the droplets elongate and the receding contact angle decreases, whereas the advancing contact angle remains roughly constant. Analyzing the flow profiles inside the droplet reveals that the droplets do not slide but roll, with vanishing slip at the substrate surface. Surprisingly, adding lubricant has very little effect on the effective friction force between the droplet and the substrate, even though it has a pronounced effect on the size and structure of the wetting ridge, especially above the cloaking transition.

Published
2024
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41. Dental Implant Placement in Medically Compromised Patients: A Literature Review.

Author

Samara W, Moztarzadeh O, Hauer L, and Babuska V

Abstract

As a discipline of dentistry, oral implantology deals with the diagnosis, design, insertion, restoration, and/or management of alloplastic or autogenous oral structures for the purpose of regaining contour, function, aesthetics, and speech in a partially or completely edentulous patient. The present review aims to provide the currently available knowledge about the impact of certain systemic disorders and the usage of some medications on the survival rate of dental implant therapy and to highlight the importance of patient management under these conditions. Diabetes, osteoporosis, cardiovascular diseases, and the intake of some medications can increase the risk of the failure of a dental implant. Even though there are relatively few medical contraindications to dental implant treatment, certain conditions may increase the risk of failure or complications., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Samara et al.)

Published
2024
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42. Carotid Artery Stenosis on Panoramic Radiographs and CT Scans in Patients With Malignancies After Radiotherapy.

Author

Samara W, Moztarzadeh O, Pernicky J, Baghalipour N, Samara MN, Gencur J, and Hauer L

Subjects
Humans, Radiography, Panoramic adverse effects, Tomography, X-Ray Computed adverse effects, Risk Factors, Radiotherapy adverse effects, Carotid Stenosis diagnostic imaging, Carotid Stenosis etiology, Head and Neck Neoplasms diagnostic imaging, Head and Neck Neoplasms radiotherapy, Head and Neck Neoplasms complications, Diabetes Mellitus, Hyperlipidemias complications, Hypertension complications, Hypertension epidemiology
Abstract

Background/aim: This study aimed to identify the progression of carotid artery stenosis (CAS) in patients with head and neck cancer following radiation therapy (RT) by characterizing associated risk factors., Patients and Methods: Panoramic radiographs (OPG), computed tomography (CT) scans, cone-beam CT (CBCT) scans, and ultrasonography (US) of 69 patients with head and neck tumors were selected and analyzed to identify the presence of CAS. Data on tumor location, smoking status, hypertension (HTN), hyperlipidemia (HLD), diabetes mellitus (DM), and treatment were collected from the patients' medical records. Patients who received chemotherapy or no treatment were excluded from the study. The differential diagnosis of other radiopacities and anatomical landmarks were excluded. Patients were divided into two groups: those with CAS (group1) and those without CAS (group 2) and their clinical information was compared., Results: The overall prevalence of CAS on the panoramic radiographs was 16%. Of the 69 patients, 44 underwent radiography before and after radiotherapy, only seven had mild CAS on radiographs after radiotherapy, and no significant difference in CAS was identified before and after radiotherapy. There were also no differences between the groups regarding age, sex, smoking, hypertension, diabetes mellitus, hyperlipidemia, tumor location, and RT dose before and after radiation (p>0.05)., Conclusion: Radiotherapy does not seem to affect the prevalence of CAS, although it has been identified in some patients after radiotherapy completion., (Copyright © 2023 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Published
2023
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43. Predicting Chronic Hyperplastic Candidiasis Retro-Angular Mucosa Using Machine Learning.

Author

Moztarzadeh O, Liska J, Liskova V, Skalova A, Topolcan O, Jamshidi A, and Hauer L

Abstract

Chronic hyperplastic candidiasis (CHC) presents a distinctive and relatively rare form of oral candidal infection characterized by the presence of white or white-red patches on the oral mucosa. Often mistaken for leukoplakia or erythroleukoplakia due to their appearance, these lesions display nonhomogeneous textures featuring combinations of white and red hyperplastic or nodular surfaces. Predominant locations for such lesions include the tongue, retro-angular mucosa, and buccal mucosa. This paper aims to investigate the potential influence of specific anatomical locations, retro-angular mucosa, on the development and occurrence of CHC. By examining the relationship between risk factors, we present an approach based on machine learning (ML) to predict the location of CHC occurrence. In this way, we employ Gradient Boosting Regression (GBR) to classify CHC lesion locations based on important risk factors. This estimator can serve both research and diagnostic purposes effectively. The findings underscore that the proposed ML technique can be used to predict the occurrence of CHC in retro-angular mucosa compared to other locations. The results also show a high rate of accuracy in predicting lesion locations. Performance assessment relies on Mean Squared Error (MSE), Root Mean Squared Error (RMSE), R-squared (R 2 ), and Mean Absolute Error (MAE), consistently revealing favorable results that underscore the robustness and dependability of our classification method. Our research contributes valuable insights to the field, enhancing diagnostic accuracy and informing treatment strategies.

Published
2023
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44. Clinical Experience with Autofluorescence Guided Oral Squamous Cell Carcinoma Surgery.

Author

Pošta P, Kolk A, Pivovarčíková K, Liška J, Genčur J, Moztarzadeh O, Micopulos C, Pěnkava A, Frolo M, Bissinger O, and Hauer L

Abstract

In our study, the effect of the use of autofluorescence (Visually Enhanced Lesion Scope-VELscope) on increasing the success rate of surgical treatment in oral squamous carcinoma (OSCC) was investigated. Our hypothesis was tested on a group of 122 patients suffering from OSCC, randomized into a study and a control group enrolled in our study after meeting the inclusion criteria. The preoperative checkup via VELscope, accompanied by the marking of the range of a loss of fluorescence in the study group, was performed before the surgery. We developed a unique mucosal tattoo marking technique for this purpose. The histopathological results after surgical treatment, i.e., the margin status, were then compared. In the study group, we achieved pathological free margin (pFM) in 55 patients, pathological close margin (pCM) in 6 cases, and we encountered no cases of pathological positive margin (pPM) in the mucosal layer. In comparison, the control group results revealed pPM in 7 cases, pCM in 14 cases, and pFM in 40 of all cases in the mucosal layer. This study demonstrated that preoperative autofluorescence assessment of the mucosal surroundings of OSCC increased the ability to achieve pFM resection 4.8 times in terms of lateral margins.

Published
2023
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45. Biomechanical Analysis of Palateless Splinted and Unsplinted Maxillary Implant-Supported Overdentures: A Three-Dimensional Finite Element Analysis.

Author

Frolo M, Řehounek L, Jíra A, Pošta P, and Hauer L

Abstract

The objective of this study was to compare the distribution of stress in the maxillary bone, dental implants, and prosthetic components supporting implant-supported maxillary overdentures with partial palatal coverage, in both splinted and unsplinted designs. Two models of maxillary overdentures were designed using the Exocad Dental CAD program, which included cancellous and cortical bone. The complete denture design and abutments (locator abutments in the unsplinted and Hader bar with Vertix attachments placed distally in the splinted variant) were also designed. The denture material was PEEK (Polyetheretherketone), and the method used to analyze patient-specific 3D X-ray scans was 3D QCT/FEA (three-dimensional quantitative computed tomography-based finite element analysis). Loading was divided into three load cases, in the frontal region (both incisors of the denture) and distal region (both molars and first premolar of the denture). The forces applied were 150 N with an oblique component with a buccal inclination of 35° in the frontal region, and 600 N with a buccal inclination of 5° (molars) or solely vertical (premolar) in the distal region. The model with locator abutments showed higher stresses in all load cases in both analyzed implant variants and in the maxilla. The differences in stress distribution between the splinted and unsplinted variants were more significant in the distal region. According to the results of the present study, the amount of stress in bone tissue and dental implant parts was smaller in the splinted, bar-retained variant. The findings of this study can be useful in selecting the appropriate prosthetic design for implant-supported maxillary overdentures with partial palatal coverage.

Published
2023
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46. Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation.

Author

Moztarzadeh O, Jamshidi MB, Sargolzaei S, Keikhaee F, Jamshidi A, Shadroo S, and Hauer L

Abstract

Advanced mathematical and deep learning (DL) algorithms have recently played a crucial role in diagnosing medical parameters and diseases. One of these areas that need to be more focused on is dentistry. This is why creating digital twins of dental issues in the metaverse is a practical and effective technique to benefit from the immersive characteristics of this technology and adapt the real world of dentistry to the virtual world. These technologies can create virtual facilities and environments for patients, physicians, and researchers to access a variety of medical services. Experiencing an immersive interaction between doctors and patients can be another considerable advantage of these technologies, which can dramatically improve the efficiency of the healthcare system. In addition, offering these amenities through a blockchain system enhances reliability, safety, openness, and the ability to trace data exchange. It also brings about cost savings through improved efficiencies. In this paper, a digital twin of cervical vertebral maturation (CVM), which is a critical factor in a wide range of dental surgery, within a blockchain-based metaverse platform is designed and implemented. A DL method has been used to create an automated diagnosis process for the upcoming CVM images in the proposed platform. This method includes MobileNetV2, a mobile architecture that improves the performance of mobile models in multiple tasks and benchmarks. The proposed technique of digital twinning is simple, fast, and suitable for physicians and medical specialists, as well as for adapting to the Internet of Medical Things (IoMT) due to its low latency and computing costs. One of the important contributions of the current study is to use of DL-based computer vision as a real-time measurement method so that the proposed digital twin does not require additional sensors. Furthermore, a comprehensive conceptual framework for creating digital twins of CVM based on MobileNetV2 within a blockchain ecosystem has been designed and implemented, showing the applicability and suitability of the introduced approach. The high performance of the proposed model on a collected small dataset demonstrates that low-cost deep learning can be used for diagnosis, anomaly detection, better design, and many more applications of the upcoming digital representations. In addition, this study shows how digital twins can be performed and developed for dental issues with the lowest hardware infrastructures, reducing the costs of diagnosis and treatment for patients.

Published
2023
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47. Metaverse and Healthcare: Machine Learning-Enabled Digital Twins of Cancer.

Author

Moztarzadeh O, Jamshidi MB, Sargolzaei S, Jamshidi A, Baghalipour N, Malekzadeh Moghani M, and Hauer L

Abstract

Medical digital twins, which represent medical assets, play a crucial role in connecting the physical world to the metaverse, enabling patients to access virtual medical services and experience immersive interactions with the real world. One serious disease that can be diagnosed and treated using this technology is cancer. However, the digitalization of such diseases for use in the metaverse is a highly complex process. To address this, this study aims to use machine learning (ML) techniques to create real-time and reliable digital twins of cancer for diagnostic and therapeutic purposes. The study focuses on four classical ML techniques that are simple and fast for medical specialists without extensive Artificial Intelligence (AI) knowledge, and meet the requirements of the Internet of Medical Things (IoMT) in terms of latency and cost. The case study focuses on breast cancer (BC), the second most prevalent form of cancer worldwide. The study also presents a comprehensive conceptual framework to illustrate the process of creating digital twins of cancer, and demonstrates the feasibility and reliability of these digital twins in monitoring, diagnosing, and predicting medical parameters.

Published
2023
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48. Phase Separation in Wetting Ridges of Sliding Drops on Soft and Swollen Surfaces.

Author

Hauer L, Cai Z, Skabeev A, Vollmer D, and Pham JT

Abstract

Drops in contact with swollen, elastomeric substrates can induce a capillary mediated phase separation in wetting ridges. Using confocal microscopy, we visualize phase separation of oligomeric silicone oil from a cross-linked silicone network during steady-state sliding of water drops. We find an inverse relationship between the oil tip height and the drop sliding speed, which is rationalized by competing transport timescales of the oil molecules: separation rate versus drop-advection speed. Separation rates in highly swollen networks are as fast as diffusion in pure melts.

Published
2023
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49. 3D maxillofacial surgery planning - one decade development of technology.

Author

Hrušák D, Hauer L, Genčur J, Pěnkava A, and Micopulos

Subjects
Humans, Fibula surgery, Printing, Three-Dimensional, Computer-Aided Design, Plastic Surgery Procedures, Surgery, Oral
Abstract

Nowadays, techniques and the use of patient specific implants seem to be the recent high technology standard in reconstructive surgery. Surgery planning is as old as the surgery procedures themselves. Any good surgeon, before entering the operating theatre, has a plan for how to proceed. It is based on knowledge and experience in combination of evaluation of all case relevant information. In fact, virtual surgery planning and CAD/CAM reflects the technological "state of the art" into the medical daily practice. Recently, 3D printing technologies became easy and accessible for everyone. Virtual 3D images substituted the plaster models, the film profile analysis switched to digital, 3D printed bone models of the case helped to understand the morphology of the deformity and prepare the osteotomies with "hands on the bone". The authors' own 20 years of experience on surgical planning, the development of digital technologies in oral and maxillofacial surgery is traced and comments on case examples are presented.

Published
2023
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50. Novel Local Chimeric Flap Based on Tunnelized Facial Artery Myomucosal Island Flap and Submandibular Gland Flap for Reconstructions After Oral Squamous Cell Carcinoma Surgery.

Author

Hauer L, Posta P, Gencur J, Micopulos C, Liska J, Podesvova J, Pivovarcikova K, and Moztarzadeh O

Subjects
Humans, Squamous Cell Carcinoma of Head and Neck, Retrospective Studies, Submandibular Gland surgery, Submandibular Gland pathology, Quality of Life, Surgical Flaps blood supply, Arteries, Mouth Neoplasms surgery, Mouth Neoplasms pathology, Carcinoma, Squamous Cell surgery, Carcinoma, Squamous Cell pathology, Head and Neck Neoplasms
Abstract

The reconstruction of oral tongue and floor of mouth defects after resections of squamous cell carcinoma is a challenging task in reconstructive surgery aiming for appropriate restoration of oral function and quality of life improvement. In this study, the authors introduce the innovative reconstruction technique of medium-sized defects consisting of tunnelized facial artery myomucosal island flap and submandibular gland flap as the local chimeric flap pedicled on facial vessels. A retrospective case series evaluation of 4 patients suffering from oral cavity cancer (stages III and IVa), who underwent transoral tumor excision with neck dissection and immediate reconstruction in the time period September 2020 to July 2021, was conducted. No flap losses or flap-related complications were identified. No recurrences occurred during the follow-up at 11.0±4.5 months (range: 6-16 mo, median=11 mo). Tunnelized facial artery myomucosal island flap and submandibular gland flap local chimeric flap expands the reconstruction options of medium-sized defects after ablative oral cancer surgery in carefully selected patients primarily not suitable for free flap reconstructions., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of Mutaz B. Habal, MD.)

Published
2023
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