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16 results on '"Aleksandr Medvedev"'

1. «Природа вся персональна»: Франциск Ассизский в онтологии Михаила Пришвина

Author

Aleksandr Medvedev

Subjects
М. М. Пришвин, св. Франциск Ассизский, Серебряный век, онтологизм, персонализм, жизнетворчество, History of Russia. Soviet Union. Former Soviet Republics, DK1-4735
Abstract

Представлен анализ францисканских идей в творчестве М. Пришвина 1908–1953 гг. в контексте европейской и русской францискианы Серебряного века. В текстах выявляются прямые и скрытые отсылки к образу св. Франциска Ассизского и францисканским текстам («Гимн Брата Солнца», «Первое житие» Фомы Челанского, «Цветочки св. Франциска»). Устанавливается, что францисканские тексты становятся для Пришвина источником непосредственного, онтологического и персоналистического переживания мира как прекрасной и чудесной целостности, в которой рождается райская гармония человека и всего творения. Чувство жалости к природе в житиях св. Франциска становится одним из творческих импульсов «Жень-Шеня » (1933) и «Золотого Рога» (1934). Францисканское переживание природы в ее живой реальности и персоналистической уникальности (природа как субъект, а не объект) – один из важнейших источников «родственного внимания», главного онтологического и жизнетворческого принципа Пришвина. Писатель полемизирует с противоположным францисканству – с утилитарным, объектным отношением к природе в советской практике, в которой живая, онтологическая и персональная реальность природы воспринимается как объект и подменяется «патриотической» и утилитарной идеологией. В 1940‑е гг. Пришвин возвращается к культурному мифу о св. Франциске как ренессансной личности, сложившемуся в русском религиозно-философском Ренессансе рубежа ХIХ–ХХ вв.; в этом контексте св. Франциск своим приятием и оправданием мира как Божьего творения преодолевает средневековый аскетический дуализм (материя как зло, разрыв плоти и духа) и выражает гуманистические ценности (персонализм и онтологизм), тем самым соединяя Бога и мир, христианство и природу, христианство и культуру. Св. Франциск становится одним из ключевых источников пришвинской концепции целостности бытия (единства земного и небесного, плоти и духа). Со св. Франциском Пришвина сближает чувство радости, которая переживается писателем как сущностная основа бытия. Образ св. Франциска становится не только литературным, но и экзистенциальным, онтологическим и жизнетворческим ответом писателя на вызовы времени. Подводя итог своей жизни, Пришвин определяет свою жизнетворческую стратегию и миссию в трагическом ХХ в. в духе св. Франциска («жизнь есть счастье»).

Published
2024
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2. Efficacy of federated learning on genomic data: a study on the UK Biobank and the 1000 Genomes Project

Author

Dmitry Kolobkov, Satyarth Mishra Sharma, Aleksandr Medvedev, Mikhail Lebedev, Egor Kosaretskiy, and Ruslan Vakhitov

Subjects
federated learning (FL), phenotype prediction, ancestry prediction, machine learning, data collaboration, genomics, Information technology, T58.5-58.64
Abstract

Combining training data from multiple sources increases sample size and reduces confounding, leading to more accurate and less biased machine learning models. In healthcare, however, direct pooling of data is often not allowed by data custodians who are accountable for minimizing the exposure of sensitive information. Federated learning offers a promising solution to this problem by training a model in a decentralized manner thus reducing the risks of data leakage. Although there is increasing utilization of federated learning on clinical data, its efficacy on individual-level genomic data has not been studied. This study lays the groundwork for the adoption of federated learning for genomic data by investigating its applicability in two scenarios: phenotype prediction on the UK Biobank data and ancestry prediction on the 1000 Genomes Project data. We show that federated models trained on data split into independent nodes achieve performance close to centralized models, even in the presence of significant inter-node heterogeneity. Additionally, we investigate how federated model accuracy is affected by communication frequency and suggest approaches to reduce computational complexity or communication costs.

Published
2024
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3. Human genotype-to-phenotype predictions: Boosting accuracy with nonlinear models.

Author

Aleksandr Medvedev, Satyarth Mishra Sharma, Evgenii Tsatsorin, Elena Nabieva, and Dmitry Yarotsky

Subjects
Medicine, Science
Abstract

Genotype-to-phenotype prediction is a central problem of human genetics. In recent years, it has become possible to construct complex predictive models for phenotypes, thanks to the availability of large genome data sets as well as efficient and scalable machine learning tools. In this paper, we make a threefold contribution to this problem. First, we ask if state-of-the-art nonlinear predictive models, such as boosted decision trees, can be more efficient for phenotype prediction than conventional linear models. We find that this is indeed the case if model features include a sufficiently rich set of covariates, but probably not otherwise. Second, we ask if the conventional selection of single nucleotide polymorphisms (SNPs) by genome wide association studies (GWAS) can be replaced by a more efficient procedure, taking into account information in previously selected SNPs. We propose such a procedure, based on a sequential feature importance estimation with decision trees, and show that this approach indeed produced informative SNP sets that are much more compact than when selected with GWAS. Finally, we show that the highest prediction accuracy can ultimately be achieved by ensembling individual linear and nonlinear models. To the best of our knowledge, for some of the phenotypes that we consider (asthma, hypothyroidism), our results are a new state-of-the-art.

Published
2022
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4. The influence of a workpiece shape on residual stresses during linear friction welding

Author

Aleksandr Medvedev

Subjects
Materials Science (miscellaneous), Mechanical Engineering, Metals and Alloys, Industrial and Manufacturing Engineering
Abstract

Linear friction welding is an advanced technology for manufacturing titanium blisks for gas-turbine engine compressors, which are subjected to stringent requirements for cyclic strength and dimensional accuracy. Substitution of conventional butt joints with more technological T-shape joints is a promising area, which provides reducing of the pre-welding machining costs. The introduction of T-form joints requires additional research of thermal distribution specifics and strain-stress state formation in the welding process and after its end. Therefore, the study of residual stresses in titanium alloy T-shape joints produced by linear friction welding is topical. The paper investigates the residual stresses in imitating welded blisk joints. The authors consider the results of welding where the blade imitator has a reamed relief of a smaller section. The finite element model covering forging, cooling, and disassembly of welded specimens is offered. The authors developed the model in ANSYS Workbench to describe the strain-stress state of welded specimens, which allows for estimating the residual stress levels and spreading. The main distinctive feature of the model is an accounting of asymmetric temperature distribution obtained by finite-difference solving of a T-shape joint thermal problem and weld shape simulation obtained as a result of welded joints metallographic research. The presented model allows the evaluation of the residual stresses in joints. The distribution of residual stresses in T-shaped welded joints is specific – compressive stresses existing in a weld are balanced by tensile stresses acting at a distance of 1 mm from the joint. The formation of compressive stresses in a weld is caused by plastic deformation due to the forging force action.

Published
2022

5. Efficacy of federated learning on genomic data: a study on the UK Biobank and the 1000 Genomes Project

Author

Dmitry Kolobkov, Satyarth Mishra Sharma, Aleksandr Medvedev, Mikhail Lebedev, Egor Kosaretskiy, and Ruslan Vakhitov

Abstract

Combining training data from multiple sources increases sample size and reduces confounding, leading to more accurate and less biased machine learning models. In healthcare, however, direct pooling of data is often not allowed by data custodians who are accountable for minimizing the exposure of sensitive information. Federated learning offers a promising solution to this problem by training a model in a decentralized manner thus reducing the risks of data leak-age. Although there is increasing utilization of federated learning on clinical data, its efficacy on individual-level genomic data has not been studied. This study lays the groundwork for the adoption of federated learning for genomic data by investigating its applicability in two scenarios: phenotype prediction on the UK Biobank data and ancestry prediction on the 1000 Genomes Project data. We show that federated models trained on data split into independent nodes achieve performance close to centralized models, even in the presence of significant inter-node heterogeneity. This paper describes the experiments and provides recommendations on strategies that should be used to reduce computational complexity or communication costs.

Published
2023

6. Ancient 'Nomadology' – Knowledge of the Ancients About the Main Issues of Nomadic Studies

Author

Aleksandr Medvedev

Subjects
Cultural Studies, History, Sociology and Political Science, Political Science and International Relations
Abstract

Introduction. Based on the study of the ancient literary tradition, the article analyzes the fundamental beliefs of the ancient Greeks and Romans about early nomads, the Scythians and the Sarmatians: origins of nomadism and nomads, their lifestyle, relations with settled neighbors, patterns of historical development of nomadic societies, etc. The interest of the Greeks and Romans in their contemporary nomads was largely explained by the fact that their lifestyles were very different. Methods. The author discusses the formation of the image of a nomad from Homer to Herodotus, emergence of its mandatory attributes that eventually became a literary topos. Analysis. The researcher points out the fact that it was Herodotus who gave a brief but comprehensive description of the Scythian nomadism in the fourth book of his Histories. Moreover, in his third narration about of the Scythians origins he actually described a phenomenon that was later called the steppe pulsation law. The paper also provides the analysis of the views of Aristotle toward the nature of nomadism and natural causes of nomadic lifestyle (Dionysius Periegetes). Based on the works of ancient authors, the author specifies several types of nomadism and stages of historical development of early nomads. It appears that the full cycle was completed only by the Scythians who created an early state. The author reveals its socioeconomic nature based on the exopolitary mode of production dominated by so-called remote (war, plunder, extortion of gifts) and tributary forms of exploitation of dependent settled populations. Results. The analysis of the ancient narrative tradition shows that ancient authors who were contemporary to the Scythians and the Sarmatians made a number of important observations in the field of nomadology that later served as a theoretical basis for this emerging discipline.

Published
2020

7. Contemporary Management of Severe Symptomatic Aortic Stenosis

Author

Marc Eugène, Piotr Duchnowski, Bernard Prendergast, Olaf Wendler, Cécile Laroche, Jean-Luc Monin, Yannick Jobic, Bogdan A. Popescu, Jeroen J. Bax, Alec Vahanian, Bernard Iung, Jeroen Bax, Michele De Bonis, Victoria Delgado, Michael Haude, Gerhard Hindricks, Aldo P. Maggioni, Luc Pierard, Susanna Price, Raphael Rosenhek, Frank Ruschitzka, Stephan Windecker, Souad Mekhaldi, Katell Lemaitre, Sébastien Authier, Magdy Abdelhamid, Astrid Apor, Gani Bajraktari, Branko Beleslin, Alexander Bogachev-Prokophiev, Daniela Cassar Demarco, Agnes Pasquet, Sait Mesut Dogan, Andrejs Erglis, Arturo Evangelista, Artan Goda, Nikolaj Ihlemann, Huseyin Ince, Andreas Katsaros, Katerina Linhartova, Julia Mascherbauer, Erkin Mirrakhimov, Vaida Mizariene, Shelley Rahman-Haley, Regina Ribeiras, Fuad Samadov, Antti Saraste, Iveta Simkova, Elizabeta Srbinovska Kostovska, Lidia Tomkiewicz-Pajak, Christophe Tribouilloy, Eliverta Zera, Mimoza Metalla, Ervina Shirka, Elona Dado, Loreta Bica, Jorida Aleksi, Gerti Knuti, Lidra Gjyli, Rudina Pjeci, Eritinka Shuperka, Erviola Lleshi, Joana Rustemaj, Marsjon Qordja, Mirald Gina, Senada Husi, Daniel Basic, Regina Steringer-Mascherbauer, Charlotte Huber, Christian Ebner, Elisabeth Sigmund, Andrea Ploechl, Thomas Sturmberger, Veronica Eder, Tanja Koppler, Maria Heger, Andreas Kammerlander, Franz Duca, Christina Binder, Matthias Koschutnik, Leonard Perschy, Lisa Puskas, Chen-Yu Ho, Farid Aliyev, Vugar Guluzada, Galib Imanov, Firdovsi Ibrahimov, Abbasali Abbasaliyev, Tahir Ahmedov, Fargana Muslumova, Jamil Babayev, Yasmin Rustamova, Tofig Jahangirov, Rauf Samadov, Muxtar Museyibov, Elnur Isayev, Oktay Musayev, Shahin Xalilov, Saleh Huseynov, Madina Yuzbashova, Vuqar Zamanov, Vusal Mammadov, Gery Van Camp, Martin Penicka, Hedwig Batjoens, Philippe Debonnaire, Daniel Dendooven, Sebastien Knecht, Mattias Duytschaever, Yves Vandekerckhove, Luc Missault, Luc Muyldermans, René Tavernier, Tineke De Grande, Patrick Coussement, Joyce DeTroyer, Katrien Derycker, Kelly De Jaegher, Antoine Bondue, Christophe Beauloye, Céline Goffinet, Daniela Corina Mirica, Frédéric Vanden Eynden, Philippe Van de Borne, Béatrice Van Frachen, David Vancraeynest, Jean Louis Vanoverschelde, Sophie Pierard, Mihaela Malanca, Florence Sinnaeve, Séverine Tahon, Marie De Clippel, Frederic Gayet, Jacques Loiseau, Nico Van de Veire, Veronique Moerman, Anne-Marie Willems, Bernard Cosyns, Steven Droogmans, Andreea Motoc, Dirk Kerkhove, Daniele Plein, Bram Roosens, Caroline Weytjens, Patrizio Lancellotti, Elena Raluca Dulgheru, Ilona Parenicova, Helena Bedanova, Frantisek Tousek, Stepanka Sindelarova, Julia Canadyova, Milos Taborsky, Jiri Ostransky, null Ivona simkova, Marek Vicha, Libor Jelinek, Irena Opavska, Miroslav Homza, Miriam Kvrayola, Radim Brat, Dan Mrozek, Eva Lichnerova, Iveta Docekalova, Marta Zarybnicka, Marketa Peskova, Patrik Roucka, Vlasta Stastna, Dagmar Jungwirtova Vondrackova, Alfred Hornig, Matus Niznansky, Marian Branny, Alexandra Vodzinska, Miloslav Dorda, Libor Snkouril, Krystyna Kluz, Jana Kypusova, Radka Nezvalova, Niels Thue Olsen, Hosam Hasan Ali, Salma Taha, Mohamed Hassan, Ahmed Afifi, Hamza Kabil, Amr Mady, Hany Ebaid, Yasser Ahmed, Mohammad Nour, Islam Talaat, CairoMaiy El Sayed, Ahmad Elsayed Mostafa, CairoYasser Sadek, CairoSherif Eltobgi, Sameh Bakhoum, Ramy Doss, Mahmoud Sheashea, Abd Allah Elasry, Ahmed Fouad, Mahmoud Baraka, Sameh Samir, Alaa Roshdy, Yasmin AbdelRazek, Mostafa M. Abd Rabou, Ahmed Abobakr, Moemen Moaaz, Mohamed Mokhtar, Mohamed Ashry, Khaled Elkhashab, Haytham Soliman Ghareeb, Mostafa Kamal, Gomaa AbdelRazek, GizaNabil Farag, Giza:Ahmed Elbarbary, Evette Wahib, Ghada Kazamel, Diaa Kamal, Mahmoud Tantawy, Adel Alansary, Mohammed Yahia, Raouf Mahmoud, Tamer El Banna, Mohamed Atef, Gamela Nasr, Salah Ahmed, Ehab E. El Hefny, Islam Saifelyazal, Mostafa Abd El Ghany, Abd El Rahman El Hadary, Ahmed Khairy, Jyri Lommi, Mika Laine, Minna Kylmala, Katja Kankanen, Anu Turpeinen, Juha Hartikainen, Lari Kujanen, Juhani Airaksinen, Tuija Vasankari, Catherine Szymanski, Yohann Bohbot, Mesut Gun, Justine Rousseaux, Loic Biere, Victor Mateus, Martin Audonnet, Jérémy Rautureau, Charles Cornet, Emmanuel Sorbets, BourgesKarine Mear, Adi Issa, Florent Le Ven, Marie-Claire Pouliquen, Martine Gilard, Alice Ohanessian, Ali Farhat, Alina Vlase, Fkhar Said, Caroline Lasgi, Carlos Sanchez, Romain Breil, Marc Peignon, Jean-Philippe Elkaim, Virginie Jan-Blin, Sylvain Ropars BertrandM'Ban, Hélène Bardet, Samuel Sawadogo, Aurélie Muschoot, Dieudonné Tchatchoua, Simon Elhadad, Aline Maubert, Tahar Lazizi, Kais Ourghi, Philippe Bonnet, Clarisse Menager-Gangloff, Sofiene Gafsi, Djidjiga Mansouri, Victor Aboyans, Julien Magne, Elie Martins, Sarah Karm, Dania Mohty, Guillaume Briday, Amandine David, Sylvestre Marechaux, Caroline Le Goffic, Camille Binda, Aymeric Menet, Francois Delelis, Anne Ringlé, Anne-Laure Castel, Ludovic Appert, Domitille Tristram, Camille Trouillet, Yasmine Nacer, Lucas Ngoy, MarseilleGilbert Habib, Franck Thuny, Julie Haentjens, Jennifer Cautela, Cécile Lavoute, Floriane Robin, Pauline Armangau, Ugo Vergeylen, Khalil Sanhadji, Nessim Hamed Abdallah, Hassan Kerzazi, Mariana Perianu, François Plurien, Chaker Oueslati, Mathieu Debauchez, Zannis Konstantinos, Alain Berrebi, Alain Dibie, Emmanuel Lansac, Aurélie Veugeois, Christelle Diakov, Christophe Caussin, Daniel Czitrom, Suzanna Salvi, Nicolas Amabile, Patrice Dervanian, Stéphanie Lejeune, Imane Bagdadi, Yemmi Mokrane, Gilles Rouault, Jerome Abalea, Marion Leledy, Patrice Horen, Erwan Donal, Christian Bosseau, Elise Paven, Elena Galli, Edouard Collette, Jean-Marie Urien, Valentin Bridonneau, Renaud Gervais, Fabrice Bauer, Houzefa Chopra, Arthur Charbonnier, David Attias, Nesrine Dahouathi, Moukda Khounlaboud, Magalie Daudin, Christophe Thebault, Cécile Hamon, Philippe Couffon, Catherine Bellot, Maelle Vomscheid, Anne Bernard, Fanny Dion, Djedjiga Naudin, Mohammed Mouzouri, Mathilde Rudelin, Alain Berenfeld, Thibault Vanzwaelmen, Tarik Alloui, Marija Gjerakaroska Radovikj, Slavica Jordanova, Werner Scholtz, Eva Liberda-Knoke, Melanie Wiemer, Andreas Mugge, Georg Nickenig, Jan-Malte Sinning, Alexander Sedaghat, Matthias Heintzen, Jan Ballof, Daniel Frenk, Rainer Hambrecht, Harm Wienbergen, Annemarie Seidel, Rico Osteresch, Kirsten Kramer, Janna Ziemann, Ramona Schulze, Wolfgang Fehske, Clarissa Eifler, Bahram Wafaisade, Andreas Kuhn, Sören Fischer, Lutz Lichtenberg, Mareike Brunold, Judith Simons, Doris Balling, Thomas Buck, Bjoern Plicht, Wolfgang Schols, Henning Ebelt, Marwan Chamieh, Jelena Anacker, Tienush Rassaf, Alexander Janosi, Alexander Lind, Julia Lortz, Peter Lüdike, Philipp Kahlert, Harald Rittger, Gabriele Eichinger, Britta Kuhls, Stephan B. Felix, Kristin Lehnert, Ann-Louise Pedersen, Marcus Dorr, Klaus Empen, Sabine Kaczmarek, Mathias Busch, Mohammed Baly, Fikret Er, Erkan Duman, Linda Gabriel, Christof Weinbrenner, Johann Bauersachs, Julian Wider, Tibor Kempf, Michael Bohm, Paul-Christian Schulze, C. Tudor Poerner, Sven Möbius-Winkler, Karsten Lenk, Kerstin Heitkamp, Marcus Franz, Sabine Krauspe, Burghard Schumacher, Volker Windmuller, Sarah Kurwitz, Holger Thiele, Thomas Kurz, Roza Meyer-Saraei, Ibrahim Akin, Christian Fastner, Dirk Lossnitzer, Ursula Hoffmann, Martin Borggrefe, Stefan Baumann, Brigitte Kircher, Claudia Foellinger, Heike Dietz, Bernhard Schieffer, Feraydoon Niroomand, Harald Mudra, Lars Maier, Daniele Camboni, Christoph Birner, Kurt Debl, Michael Paulus, Benedikt Seither, Nour Eddine El Mokhtari, Alper Oner, Evren Caglayan, Mohammed Sherif, Seyrani Yucel, Florian Custodis, Robert Schwinger, Marc Vorpahl, Melchior Seyfarth, Ina Nover, Till Koehler, Sarah Christiani, David Calvo Sanchez, Barbel Schanze, Holger Sigusch, Athir Salman, Jane Hancock, John Chambers, Camelia Demetrescue, Claire Prendergast, Miles Dalby, Robert Smith, Paula Rogers, Cheryl Riley, Dimitris Tousoulis, Ioannis Kanakakis, Konstantinos Spargias, Konstantinos Lampropoulos, Tolis Panagiotis, Athanasios Koutsoukis, Lampros Michalis, Ioannis Goudevenos, Vasileios Bellos, Michail Papafaklis, Lampros Lakkas, George Hahalis, Athanasios Makris, Haralampos Karvounis, Vasileios Kamperidis, Vlasis Ninios, Vasileios Sachpekidis, Pavlos Rouskas, Leonidas Poulimenos, Georgios Charalampidis, Eftihia Hamodraka, Athanasios Manolis, Robert Gabor Kiss, Tunde Borsanyi, Zoltan Jarai, Andras Zsary, Elektra Bartha, Annamaria Kosztin, Alexandra Doronina, Attila Kovacs, Barabas Janos Imre, Chun Chao, Kalman Benke, Istvan Karoczkai, Kati Keltai, Zsolt Förchécz, Zoltán Pozsonyi, Zsigmond Jenei, Adam Patthy, Laszlo Sallai, Zsuzsanna Majoros, Tamás Pál, Jusztina Bencze, Ildiko Sagi, Andrea Molnar, Anita Kurczina, Gabor Kolodzey, Istvan Edes, Valeria Szatmari, Zsuzsanna Zajacz, Attila Cziraki, Adam Nemeth, Reka Faludi, Laszlone Vegh, Eva Jebelovszki, Geza Karoly Lupkovics, Zsofia Kovacs, Andras Horvath, Gezim Berisha, Pranvera Ibrahimi, Luan Percuku, Rano Arapova, Elmira Laahunova, Kseniia Neronova, Zarema Zhakypova, Gulira Naizabekova, Gulnazik Muratova, Iveta Sime, Nikolajs Sorokins, Ginta Kamzola, Irina Cgojeva-Sproge, Gita Rancane, Ramune Valentinaviciene, Laima Rudiene, Rasa Raugaliene, Aiste Bardzilauske, Regina Jonkaitiene, Jurate Petrauskaite, Monika Bieseviciene, Raimonda Verseckaite, Ruta Zvirblyte, Danute Kalibatiene, Greta Radauskaite, Gabija Janaviciute-Matuzeviciene, Dovile Jancauskaite, Deimile Balkute, Juste Maneikyte, Ingrida Mileryte, Monika Vaisvilaite, Lina Gedvilaite, Mykolas Biliukas, Vaiva Karpaviciene, Robert George Xuereb, Elton Pllaha, Roxana Djaberi, Klaudiusz Komor, Agnieszka Gorgon-Komor, Beata Loranc, Jaroslaw Myszor, Katarzyna Mizia-Stec, Adrianna Berger-Kucza, Magdalena Mizia, Mateusz Polak, Piotr Bogacki, Piotr Podolec, Monika Komar, Ewa Sedziwy, Dorota Sliwiak, Bartosz Sobien, Beata Rog, Marta Hlawaty, Urszula Gancarczyk, Natasza Libiszewska, Danuta Sorysz, Andrzej Gackowski, Malgorzata Cieply, Agnieszka Misiuda, Franciszek Racibor, Anna Nytko, Kazimierz Widenka, Maciej Kolowca, Janusz Bak, Andrzej Curzytek, Mateusz Regulski, Malgorzata Kamela, Mateusz Wisniowski, Tomasz Hryniewiecki, Piotr Szymanski, Monika Rozewicz, Maciej Grabowski, Andrzej Budaj, Beata Zaborska, Ewa Pilichowska-Paskiet, Malgorzata Sikora-Frac, Tomasz Slomski, Isabel Joao, Ines Cruz, Hélder Pereira, Rita Cale, Ana Marques, Ana Rita Pereira, Carlos Morais, Antonio Freitas, David Roque, Nuno Antunes, Antonio Costeira Pereira, Catarina Vieira, Nuno Salome, Juliana Martins, Isabel Campos, Goncalo Cardoso, Claudia Silva, Afonso Oliveira, Mariana Goncalves, Rui Martins, Nuno Quintal, Bruno Mendes, Joseline Silva, Joao Ferreira, James Milner, Patricia Alves, Vera Marinho, Paula Gago, Jose Amado, Joao Bispo, Dina Bento, Inocencia Machado, Margarida Oliveira, Lucy Calvo, Pedro von Hate, Bebiana Faria, Ana Galrinho, Luisa Branco, Antonio Goncalves, Tiago Mendonca, Mafalda Selas, Filipe Macedo, Carla Sousa, Sofia Cabral, Filomena Oliveira, Maria Trepa, Marta Fontes-Oliveira, Alzira Nunes, Paulo Araújo, Vasco Gama Ribeiro, Joao Almeida, Alberto Rodrigues, Pedro Braga, Sonia Dias, Sofia Carvalho, Catarina Ferreira, Alberto Ferreira, Pedro Mateus, Miguel Moz, Silvia Leao, Renato Margato, Ilidio Moreira, Jose Guimanaes, Joana Ribeiro, Fernando Goncalves, Jose Cabral, Ines Almeida, Luisa Goncalves, Mariana Tarusi, Calin Pop, Claudia Matei, Diana Tint, Sanziana Barbulescu, Sorin Micu, Ioana Pop, Costica Baba, Doina Dimulescu, Maria Dorobantu, Carmen Ginghina, Roxana Onut, Andreea Popescu, Brandusa Zamfirescu, Raluca Aflorii, Mihaela Popescu, Liviu Ghilencea, Andreeea Rachieru, Monica Stoian, Nicoleta Oprescu, Silvia Iancovici, Iona Petre, Anca Doina Mateescu, Andreea Calin, Simona Botezatu, Roxana Enache, Monica Rosca, Daniela Ciuperca, Evelyn Babalac, Ruxandra Beyer, Laura Cadis, Raluca Rancea, Raluca Tomoaia, Adela Rosianu, Emese Kovacs, Constantin Militaru, Alina Craciun, Oana Mirea, Mihaela Florescu, Lucica Grigorica, Daniela Dragusin, Luiza Nechita, Mihai Marinescu, Teodor Chiscaneanu, Lucia Botezatu, Costela Corciova, Antoniu Octavian Petris, Catalina Arsenescu-Georgescu, Delia Salaru, Dan Mihai Alexandrescu, Carmjen Plesoianu, Ana Tanasa, Ovidiu Mitu, Irina Iuliana Costache, Ionut Tudorancea, Catalin Usurelu, Gabriela Eminovici, Ioan Manitiu, Oana Stoia, Adriana Mitre, Dan-Octavian Nistor, Anca Maier, Silvia Lupu, Mihaela Opris, Adina Ionac, Irina Popescu, Simina Crisan, Cristian Mornos, Flavia Goanta, Liana Gruescu, Oana Voinescu, Madalina Petcu, Ramona Cozlac, Elena Damrina, Liliya Khilova, Irina Ryazantseva, Dmitry Kozmin, Maria Kiseleva, Marina Goncharova, Kamila Kitalaeva, Victoria Demetskay, Artem Verevetinov, Mikhail Fomenko, Elena Skripkina, Viktor Tsoi, Georgii Antipov, Yuri Schneider, Denis Yazikov, Marina Makarova, Aleksei Cherkes, Natalya Ermakova, Aleksandr Medvedev, Anastasia Sarosek, Mikhail Isayan, Tatyana Voronova, Oleg Kulumbegov, Alina Tuchina, Sergei Stefanov, Margarita Klimova, Konstantin Smolyaninov, Zhargalma Dandarova, Victoriya Magamet, Natalia Spiropulos, Sergey Boldyrev, Kirill Barbukhatty, Dmitrii Buyankov, Vladimir Yurin, Yuriy Gross, Maksim Boronin, Mariya Mikhaleva, Mariya Shablovskaya, Alex Zotov, Daniil Borisov, Vasily Tereshchenko, Ekaterina Zubova, A. Kuzmin, Ivan Tarasenko, Alishir Gamzaev, Natalya Borovkova, Tatyana Koroleva, Svetlana Botova, Ilya Pochinka, Vera Dunaeva, Victoria Teplitskaya, Elena I. Semenova, Olga V. Korabel'Nikova, Denis S. Simonov, Elena Denisenko, Natalia Harina, Natalia Yarohno, Svetlana Alekseeva, Julia Abydenkova, Lyubov Shabalkina, Olga Mayorova, Valeriy Tsechanovich, Igor Medvedev, Michail Lepilin, PenzaEvgenii Nemchenko, Vadim Karnahin, Vasilya Safina, Yaroslav Slastin, Venera Gilfanova, Roman Gorbunov, Ramis Jakubov, Aigul Fazylova, Mansur Poteev, Laysan Vazetdinova, Indira Tarasova, Rishat Irgaliyev, Olga Moiseeva, Mikhail Gordeev, Olga Irtyuga, Raisa Moiseeva, Nina Ostanina, Dmitry Zverev, Patimat Murtazalieva, Dmitry Kuznetsov, Mariya Skurativa, Larisa Polyaeva, Kirill Mihaiilov, Biljana Obrenovic-Kircanski, Svetozar Putnik, Dragan Simic, Milan Petrovic, Natasa Markovic Nikolic, Ljiljana Jovovic, Dimitra Kalimanovska Ostric, Milan Brajovic, Milica Dekleva Manojlovic, Vladimir Novakovic, Danijela Zamaklar-Trifunovic, Bojana Orbovic, Olga Petrovic, Marija Boricic-Kostic, Kristina Andjelkovic, Marko Milanov, Maja Despotovic-Nikolic, Sreten Budisavljevic, Sanja Veljkovic, Nataša Cvetinovic, Daniijela Lepojevic, Aleksandra Todorovic, Aleksandra Nikolic, Branislava Borzanovic, Ljiljana Trkulja, Slobodan Tomic, Milan Vukovic, Jelica Milosavljevic, Mirjana Milanovic, Vladan Stakic, Aleksandra Cvetkovic, Suzana Milutinovic, Olivera Bozic, Miodrag Miladinovic, Zoran Nikolic, Dinka Despotovic, Dimitrije Jovanovic, Anastazija Stojsic-Milosavljevic, Aleksandra Ilic, Mirjana Sladojevic, Stamenko Susak, Srdjan Maletin, Salvo Pavlovic, Vladimir Kuzmanovic, Nikola Ivanovic, Jovana Dejanovic, Dusan Ruzicic, Dragana Drajic, Danijel Cvetanovic, Marija Mirkovic, Jon Omoran, Roman Margoczy, Katarina Sedminova, Adriana Reptova, Eva Baranova, Tatiana Valkovicova, Gabriel Valocik, Marian Kurecko, Marianna Vachalcova, Alzbeta Kollarova, Martin Studencan, Daniel Alusik, Marek Kozlej, Jana Macakova, Sergio Moral, Merce Cladellas, Daniele Luiso, Alicia Calvo, Jordi Palet, Juli Carballo, Gisela Teixido Tura, Giuliana Maldonado, Laura Gutierrez, Teresa Gonzalez-Alujas, Rodriguez Palomares Jose Fernando, Nicolas Villalva, Ma Jose Molina-Mora, Ramon Rubio Paton, Juan Jose Martinez Diaz, Pablo Ramos Ruiz, Alfonso Valle, Ana Rodriguez, Edgardo Alania, Emilio Galcera, Julia Seller, Gonzalo de la Morena Valenzuela, Daniel Saura Espin, Dolores Espinosa Garcia, Maria Jose Oliva Sandoval, Josefa Gonzalez, Miguel Garcia Navarro, Maria Teresa Perez-Martinez, Jose Ramon Ortega Trujillo, Irene Menduina Gallego, Daniel San Roman, Eliu David Perez Nogales, Olga Medina, Rodolfo Antonio Montiel Quintero, Pablo Felipe Bujanda Morun, Marta Lopez Perez, Jimmy Plasencia Huaripata, Juan Jose Morales Gonzalez, Veronica Quevedo Nelson, Jose Luis Zamorano, Ariana Gonzalez Gomez, Alfonso Fraile, Maria Teresa Alberca, Joaquin Alonso Martin, Covadonga Fernandez-Golfin, Javier Ramos, Sergio Hernandez Jimenez, Cristina Mitroi, Pedro L. Sanchez Fernandez, Elena Diaz-Pelaez, Beatriz Garde, Luis Caballero, Fermin Martinez Garcia, Francisco Cambronero, Noelia Castro, Antonio Castro, Alejandro De La Rosa, Pastora Gallego, Irene Mendez, David Villagomez Villegas, Manuel Gonzalez Correa, Roman Calvo, Francisco Florian, Rafael Paya, Esther Esteban, Francisco Buendia, Andrés Cubillos, Carmen Fernandez, Juan Pablo Cárdenas, José Leandro Pérez-Boscá, Joan Vano, Joaquina Belchi, Cristina Iglesia-Carreno, Francisco Calvo Iglesias, Aida Escudero-Gonzalez, Sergio Zapateria-Lucea, Juan Sterling Duarte, Lara Perez-Davila, Rafael Cobas-Paz, Rosario Besada-Montenegro, Maribel Fontao-Romeo, Elena Lopez-Rodriguez, Emilio Paredes-Galan, Berenice Caneiro-Queija, Alba Guitian Gonzalez, Abdi Bozkurt, Serafettin Demir, Durmus Unlu, Caglar Emre Cagliyan, Muslum Firat Ikikardes, Mustafa Tangalay, Osman Kuloglu, Necla Ozer, Ugur Canpolat, Melek Didem Kemaloglu, Abdullah Orhan Demirtas, Didar Elif Akgün, Eyup Avci, Gokay Taylan, Mustafa Adem Yilmaztepe, Fatih Mehmet Ucar, Servet Altay, Muhammet Gurdogan, Naile Eris Gudul, Mujdat Aktas, Mutlu Buyuklu, Husnu Degirmenci, Mehmet Salih Turan, Kadir Ugur Mert, Gurbet Ozge Mert, Muhammet Dural, Sukru Arslan, Nurten Sayar, Batur Kanar, Beste Ozben Sadic, Ahmet Anil Sahin, Ahmet Buyuk, Onur Kilicarslan, Cem Bostan, Tarik Yildirim, Seda Elcim Yildirim, Kahraman Cosansu, Perihan Varim, Ersin Ilguz, Recep Demirbag, Asuman Yesilay, Abdullah Cirit, Eyyup Tusun, Emre Erkus, Muhammet Rasit Sayin, Zeynep Kazaz, Selim Kul, Turgut Karabag, Belma Kalayci, Clinical sciences, Cardio-vascular diseases, and Cardiology

Subjects
Male, medicine.medical_specialty, Multivariate analysis, Clinical Decision-Making, Risk Assessment, Severity of Illness Index, decision making, surgery, Risk Factors, Internal medicine, Intervention (counseling), medicine, Clinical endpoint, Humans, 03.02. Klinikai orvostan, guidelines, Symptomatic aortic stenosis, Aged, Retrospective Studies, Aged, 80 and over, business.industry, valvular heart disease, Disease Management, aortic stenosis, Aortic Valve Stenosis, Odds ratio, medicine.disease, Europe, Stenosis, Treatment Outcome, Echocardiography, Aortic Valve, Charlson comorbidity index, transcatheter aortic valve replacement, Female, Morbidity, Cardiology and Cardiovascular Medicine, business, Follow-Up Studies, surgical aortic valve replacement
Abstract

BACKGROUND There were gaps between guidelines and practice when surgery was the only treatment for aortic stenosis (AS). OBJECTIVES This study analyzed the decision to intervene in patients with severe AS in the EORP VHD (EURObservational Research Programme Valvular Heart Disease) II survey. METHODS Among 2,152 patients with severe AS, 1,271 patients with high-gradient AS who were symptomatic fulfilled a Class I recommendation for intervention according to the 2012 European Society of Cardiology guidelines; the primary end point was the decision for intervention. RESULTS A decision not to intervene was taken in 262 patients (20.6%). In multivariate analysis, the decision not to intervene was associated with older age (odds ratio [OR]: 1.34 per 10-year increase; 95% CI: 1.11 to 1.61; P = 0.002), New York Heart Association functional classes I and II versus III (OR: 1.63; 95% CI: 1.16 to 2.30; P = 0.005), higher age adjusted Charlson comorbidity index (OR: 1.09 per 1-point increase; 95% CI: 1.01 to 1.17; P = 0.03), and a lower transaortic mean gradient (OR: 0.81 per 10-mm Hg decrease; 95% CI: 0.71 to 0.92; P < 0.001). During the study period, 346 patients (40.2%, median age 84 years, median EuroSCORE II [European System for Cardiac Operative Risk Evaluation II] 3.1%) underwent transcatheter intervention and 515 (59.8%, median age 69 years, median EuroSCORE II 1.5%) underwent surgery. A decision not to intervene versus intervention was associated with lower 6-month survival (87.4%; 95% CI: 82.0 to 91.3 vs 94.6%; 95% CI: 92.8 to 95.9; P < 0.001). CONCLUSIONS A decision not to intervene was taken in 1 in 5 patients with severe symptomatic AS despite a Class I recommendation for intervention and the decision was particularly associated with older age and combined comorbidities. Transcatheter intervention was extensively used in octogenarians. (J Am Coll Cardiol 2021;78:2131-2143) (c) 2021 by the American College of Cardiology Foundation.

Published
2021

11. On a New Group of Post-Sarmatian Burials in the Middle Don Region

Author

Aleksandr Medvedev and Valeriy Berezutskiy

Subjects
Cultural Studies, History, catacombs, Sarmatians, lcsh:History of Russia. Soviet Union. Former Soviet Republics, Sociology and Political Science, Tanais Alans, lcsh:International relations, Ancient history, Geography, forest steppe, Group (periodic table), barrows, Middle Don region, Political Science and International Relations, lcsh:DK1-4735, Late Sarmatian culture, lcsh:JZ2-6530
Abstract

The paper raises the question of a separate group of barrow burials following the classical Late Sarmatian culture in the Middle Don region. The recently excavated sites include a T-shaped catacomb discovered on the right bank of the Don River (Losevo). Most likely, it belonged to a Tanais Alan who survived the Hunnic massacre and moved off to the north, to remote areas of the Don region not affected by the Hunnic invasion. On the left bank of the Don River (Berezovka), we have studied undercut burials synchronous to the catacomb from Losevo, with the rite and grave goods continuing the Late Sarmatian traditions (type of burial structure, northward orientation of buried people, artificial skull deformation, remnants of sacrificial food in the form of sheep and goat bones, etc.). The ceramic complex of these burials includes Late Sarmatian and Central Caucasian moulded and pottery ware. A warrior’s burial in barrow 9 near the village of Berezovka contained not only typical Late Sarmatian ceramics, but also coarse moulded ware most likely connected with more northern traditions. It could belong to the settled population of the Middle Khoper region that left the sites of the Inyasevo type. Both groups of burials contain some indicators (metal parts of horse harness, belt buckles, a Chernyakhov-type fibula) dating them back to the second half of the 4th – early 5th centuries AD. But at the same time they do not contain any specific features of the Hunnic culture. According to the traditional periodization, the above-mentioned complexes can be qualified as belonging to the final stage of the Late Sarmatian culture. However, we think that it is better to use such a definition as the ‘post-Sarmatian age’ (or ‘post- Sarmatian horizon’). The analyzed barrow burials were immediately antecedent to the Hunnic-age burial grounds of the first half of the 5th century AD in the Upper Don region (Zhivotinnoye, Ksizovo, Mukhino, etc.).

Published
2018

13. Training algorithms for artificial neural networks for time series forecasting of greenhouse gas concentrations

Author

Aleksandr Medvedev, Alexander Buevich, Alexandra Kosachenko, Alexander Sergeev, Marina Sergeeva, Anastasia Moskaleva, and Andrey Shichkin

Subjects
Nonlinear autoregressive exogenous model, Autoregressive model, Artificial neural network, Greenhouse gas, Training (meteorology), Environmental science, Interval (mathematics), Time series, Gradient descent, Algorithm
Abstract

When studying the processes associated with global warming, forecasts of time series are very important. The present study used data of the concentration of greenhouse gas methane in the surface layer of atmospheric air on the Arctic island Belyi, Russia. For the work, a time interval of 170 hours was chosen. For the modelling, a model based on a nonlinear autoregressive neural network with an external input (NARX) was used. As a training algorithm three types were applied: Levenberg-Marquart (LM), LM with Bayesian regularization (BR), and a gradient descent with a speed parameter setting (GDA). Methane concentrations corresponding to the first 150 hours of the interval used to train the NARX network, then the concentrations were predicted for the next 20 hours. The model using the training algorithm LM was the most accurate.

Published
2019

14. Comparative Tests of Decision Making Algorithms for a Multiversion Execution Environment of the Fault Tolerance Software

Author

Aleksandr Medvedev, Igor V. Kovalev, Anna A Voroshilova, M. N. Chuvashova, M. V. Saramud, and Vasiliy V. Losev

Subjects
Computer science, business.industry, media_common.quotation_subject, Fault tolerance, Software quality, Software, Voting, Management system, Component-based software engineering, Redundancy (engineering), N-version programming, business, Algorithm, media_common
Abstract

many areas are currently experiencing rapid growth, requiring reliable and fault-tolerant software in general and, in particular, management systems. The most effective today is multiversion programming, one of the approaches to improve the reliability of software by introducing redundancy. With this approach, there arises the problem of choosing the right variant from the collection by the answer of multiple versions, which is solved by various decision algorithms, most often based on voting. The reliability of this solution greatly affects the reliability of the redundant system as a whole. The article considers existing decision-making algorithms in multiversion execution environments and suggests own modifications of existing voting algorithms and t / (n-1) algorithm. A software implementation of the simulation environment that implements simulations of versions with specified characteristics and proposed modified algorithms is considered. The results of the simulation are considered, the dependence of the reliability indicators of the system on its input parameters is shown, a comparative analysis of various decision algorithms is made on the basis of simulation results. The obtained results show the effectiveness of the proposed modifications of the voting algorithms by an agreed majority and the specificity of the t / (n-1) decision algorithm, which makes sense to apply not in all systems. Most importantly, the simulation results show the possibility of creating a reliable system from not reliable software components, which is very important, especially for areas where there are currently no highly reliable algorithms or software components.

Published
2017

16. Kind and Quiet: Vasilii Rozanov's Reading of Chekhov

Author

Aleksandr Medvedev

Subjects
Literature, business.industry, Reading (process), media_common.quotation_subject, Character (symbol), Psychology, business, media_common
Abstract

Apart from numerous references in other places, Rozanov devoted five essays to Chekhov. In his first essay, written not long before Chekhov's death in 1904, Rozanov, while considering Russia's fate, gives a historic-cultural reading of The Cherry Orchard . In this, Chekhov's last play, Rozanov sees a reflection of the crisis among the Russian people, of not being able to set targets and aspirations in their personal lives: ‘Do you not understand, for what purpose serve love, thoughts, home life, morals, money – for all these people? You cannot take these things with you.’ This crisis leads to the passivity and lack of will in Chekhov's heroes: ‘Lopakhin also saves money, reads Buckle just like Epikhodov (an excellent character, especially upon the stage), Liubov Andreevna is attached to her Parisian gigolo, and Trofimov studies at the university. Each of them is not defined by his role. On stage, however, the figure of the student Trofimov is sympathetic, although idle and passive. He is unable to finish his course, and at the end cannot even find his own boots (which Varia eventually finds for him).’ This crisis of values is witnessed not only in the passive, but in the more active characters: ‘The only aspiration anyone shows is when Lopakhin tries to get hold of money: but it is totally incomprehensible why he needs it: money for money's sake?

Published
2010

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