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34 results on '"Elokhov, Aleksandr"'

1. Innovative Techniques of Ground Infiltration Characteristics Reduction with Chemical and Biotechnological Precipitation of Calcium Salts

Author

Maksimovich, Nikolay G., Kudryashova, Olga S., Khmurchik, Vadim T., Demenev, Artem D., Elokhov, Aleksandr M., Kistanova, Natalya S., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Rocha, Alvaro, editor, and Isaeva, Ekaterina, editor

Published
2022
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4. Long-term measurements of total NO2 and O3 column contents at stations of the A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences: observational methods, long-term trends and interannual variations of the species

Author

Gruzdev, Aleksandr N., primary, Elansky, Nikolay F., additional, Elokhov, Aleksandr S., additional, Savinykh, Vladimir V., additional, Arabov, Arab Y., additional, Borovski, Aleksandr N., additional, and Senik, Irina A., additional

Published
2022
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6. Optimization of insulation in ventilated hinged facade systems

Author

Maltseva Irina, Elokhov Aleksandr, Borisov Vitaliy, and Verkhovskiy Alexey

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

The system of hinged ventilated facades is available for a long time and is now widely used in the construction of new and reconstruction of existing buildings for various purposes. As practice shows, the problems associated with the operation of these facade systems are usually caused by mistakes in the design, selection of components and installation of the system. Ventilated facade is a multi-layered enclosing structure, which includes a layer of insulation. Mineral wool slabs are ideal for this facade system, as it has low thermal conductivity, resistance to temperature changes and excellent vapor permeability, which allows to fully open the potential of a ventilated air layer. In the article two ways of installation of thermal insulation are considered: single-layer and two-layer with different types of air interlayer: closed, weakly and strongly ventilated. In accordance with the requirements of Russian and European regulatory documents, the effect of gaps between the thermal insulation plates in a single-layer and two-layer design on the reduction of the heat transfer resistance of hinged facade systems with an air gap was estimated by calculating 2-dimensional temperature fields. The coefficient of thermotechnic uniformity was also defined. As a result, optimal variants of thermal insulation and types of bases for fixing thermal insulation are suggested.

Published
2019
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7. Design without thermal bridges

Author

Maltseva Irina, Elokhov Aleksandr, Tkachuk Konstantin, and Maltceva Kseniia

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

The main focus of the article is on the quality design and implementation of the thermal insulation of buildings. Shells of buildings consist not only of conventional structures (wall, roof, ceiling), but also of edges, corners, joints and places of disruption of the outer thermal insulation shell integrity (due to through passage of pipelines, ventilation ducts and etc.). In all these places, heat losses are generally increased in comparison with conventional surfaces. Some of them are easily taken into account by calculation, using a special method proposed by the authors. Other thermal bridges due to unfavorable structural details can be avoided by observing the rules and recommendations that are classified and discussed in detail in this article.

Published
2018
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11. Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author

Verhoelst, Tijl, Compernolle, Steven, Pinardi, Gaia, Lambert, Jean Christopher, Eskes, Henk J., Eichmann, Kai Uwe, Fjæraa, Ann Mari, Granville, José, Niemeijer, Sander, Cede, Alexander, Tiefengraber, Martin, Hendrick, François, Pazmiño, Andrea, Bais, Alkiviadis, Bazureau, Ariane, Boersma, K.F., Bognar, Kristof, Dehn, Angelika, Donner, Sebastian, Elokhov, Aleksandr, Gebetsberger, Manuel, Goutail, Florence, Grutter De La Mora, Michel, Gruzdev, Aleksandr, Gratsea, Myrto, Hansen, Georg H., Irie, Hitoshi, Jepsen, Nis, Kanaya, Yugo, Karagkiozidis, Dimitris, Kivi, Rigel, Kreher, Karin, Levelt, Pieternel F., Liu, Cheng, Müller, Moritz, Navarro Comas, Monica, Piters, Ankie J.M., Pommereau, Jean Pierre, Portafaix, Thierry, Prados-Roman, Cristina, Puentedura, Olga, Querel, Richard, Remmers, Julia, Richter, Andreas, Rimmer, John, Cárdenas, Claudia Rivera, De Miguel, Lidia Saavedra, Sinyakov, Valery P., Stremme, Wolfgang, Strong, Kimberly, Van Roozendael, Michel, Veefkind, J.P., Wagner, Thomas, Wittrock, Folkard, Yela González, Margarita, Zehner, Claus, Verhoelst, T. [0000-0003-0163-9984], Compernolle, S. [0000-0003-0872-0961], Pinardi, G. [0000-0001-5428-916X], Eskes, H. [0000-0002-8743-4455], Bais, A. [0000-0003-3899-2001], Folkert Boersma, K. [0000-0002-4591-7635], Bognar, K. [0000-0003-4619-2020], Donner, S. [0000-0001-8868-167X], Elokhov, A. [0000-0003-4725-9186], Grutter de la Mora, M. [0000-0001-9800-5878], Gruzdev, A. [0000-0003-3224-1012], Karagkiozidis, D. [0000-0002-3595-0538], Kivi, R. [0000-0001-8828-2759], Liu, C. [0000-0002-3759-9219], Müller, M. [0000-0001-5284-5425], Pommereau, J. P. [0000-0002-8285-9526], Prados Roman, C. [0000-0001-8332-0226], Puentedura, O. [0000-0002-4286-1867], Querel, R. [0000-0001-8792-2486], Richter, A. [0000-0003-3339-212X], Rivera Cárdenas, C. [0000-0002-8617-265X], Stremme, W. [0000-0003-0791-3833], Strong, K. [0000-0001-9947-1053], Pepijn Veefkind, J. [0000-0003-0336-6406], European Space Agency (ESA), French Institut National des Sciences de l'Univers (INSU), Centre National D'Etudes Spatiales (CNES), Centre National de la Recherche Scientifique (CNRS), Institut polaire français Paul Emile Victor (IPEV), and Belgian Science Policy Office (BELSPO)

Subjects
Meteorologie en Luchtkwaliteit, WIMEK, Meteorology and Air Quality, Copernicus Sentinel 5P, Life Science, Pandonia global networks
Abstract

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values. This research has been supported by the ESA/ESRIN (grant no. 4000117151/16/I-LG) and the BELSPO/ESA ProDEx (TROVA-E2 (PEA grant no. 4000116692)). Part of the reported work was carried out in the framework of the Copernicus Sentinel-5 Precursor Mission Performance Centre (S5P MPC), contracted by the European Space Agency and supported by the Belgian Federal Science Policy Office (BELSPO), the Royal Belgian Institute for Space Aeronomy (BIRA-IASB), the Netherlands Space Office (NSO), and the German Aerospace Centre (DLR). Part of this work was carried out also in the framework of the S5P Validation Team (S5PVT) AO projects NIDFORVAL (ID no. 28607, PI Gaia Pinardi, BIRA-IASB) and CESAR (ID no. 28596, PI Arnoud Apituley, KNMI). The authors express special thanks to Ann Mari Fjæraa, José Granville, Sander Niemeijer, and Olivier Rasson for post-processing of the network and satellite data and for their dedication to the S5P operational validation. The LATMOS real-time processing facility is acknowledged for fast delivery of ZSL-DOAS SAOZ data. Fast delivery of MAX-DOAS data tailored to the S5P validation was organized through the S5PVT AO project NIDFORVAL. The authors are grateful to ESA/ESRIN for supporting the ESA Validation Data Centre (EVDC) established at NILU and for running the Fiducial Reference Measurements (FRM) programme and in particular the FRM4DOAS and Pandonia projects. The PGN is a bilateral project between NASA and ESA, and the NASA funding for the PGN is provided through the NASA Tropospheric Composition Program and Goddard Space Flight Center Pandora project. The MAX-DOAS, ZSL-DOAS, and PGN instrument PIs and staff at the stations are thanked warmly for their sustained effort on maintaining high-quality measurements and for valuable scientific discussions. Aleksandr Elokhov and Aleksandr Gruzdev acknowledge national funding from RFBR through the project 20-95-00274. IUP Bremen acknowledges DLR Bonn for funding received through project 50EE1709A. The SAOZ network acknowledges funding from the French Institut National des Sciences de l'Univers (INSU) of the Centre National de la Recherche Scientifique (CNRS), Centre National d'Etudes Spatiales (CNES), and Institut polaire français Paul Emile Victor (IPEV). Work done by Hitoshi Irie was supported by the Environment Research and Technology Development Fund (2-1901) of the Environmental Restoration and Conservation Agency of Japan, JSPS KAKENHI (grant nos. JP19H04235 and JP17K00529), the JAXA 2nd Research Announcement on the Earth Observations (grant no. 19RT000351), and JST CREST (grant no. JPMJCR15K4). The University of Toronto ZSL-DOAS measurements at Eureka were made at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC), with support from the Canadian Space Agency (AVATARS project), the Natural Sciences and Engineering Research Council (PAHA project), and Environment and Climate Change Canada. Peerreview

Published
2021

13. Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author

Verhoelst, Tiji, Compernolle, Steven, Pinardi, Gala, Lambert, Jean-Christopher, Eskes, Henk J., Eichmann, Kai-Uwe, Fjæraa, Ann Mari, Granville, José, Niemeijer, Sander, Cede, Alexander, Tiefengraber, Martin, Hendrick, François, Pazmino, Andrea, Bais, Alkiviadis, Bazureau, Ariane, Boersma, Klaas Folkert, Bognar, Kristof, Dehn, Angelika, Donner, Sebastian, Elokhov, Aleksandr, Gebetsberger, Manuel, Goutail, Florence, Grutter de la Mora, Michel, Gruzdev, Aleksandr, Gratsea, Myrto, Hansen, Georg, Irie, Hitoshi, Jepsen, Nis, Kanaya, Yugo, Karagkiozidis, Dimitris, Kivi, Rigel, Kreher, Karin, Levelt, Pieternel F., Liu, Cheng, Müller, Moritz, Navarro-Comas, Monica, Piters, Ankie J. M., Pommereau, Jean-Pierre, Portafaix, Thierry, Puentedura, Olga, Querel, Richard, Remmers, Julia, Richter, Andreas, Rimmer, John, Rivera Cárdenas, Claudia, Saavedra De Miguel, Lidia, Sinyakov, Valery P., Strong, Kimberley, Van Roozendaël, Michel, Veefkind, Pepijn J., Wagner, Thomas, Wittrock, Folkard, Yela-González, Margarita, Zehner, Claus, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Royal Netherlands Meteorological Institute (KNMI), Institut für Umweltphysik [Bremen] (IUP), Universität Bremen, Norsk Institutt for Luftforskning (NILU), Science [&] Technology Corporation [Delft] (S [&] T), NASA Goddard Space Flight Center (GSFC), Institute of Meteorology and Geophysics [Innsbruck], University of Innsbruck, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Department of Physics [Toronto], University of Toronto, European Space Research Institute (ESRIN), European Space Agency (ESA), Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, A.M.Obukhov Institute of Atmospheric Physics (IAP), Russian Academy of Sciences [Moscow] (RAS), Centro de Ciencias de la Atmosfera [Mexico], Universidad Nacional Autónoma de México (UNAM), National Observatory of Athens (NOA), Center for Environmental Remote Sensing [Chiba] (CEReS), Chiba University, Danish Meteorological Institute (DMI), Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Space and Earth Observation Centre [Sodankylä], Finnish Meteorological Institute (FMI), BK Scientific GmbH, Delft University of Technology (TU Delft), Department of Precision Machinery and Precision Instrumentation [Hefei], University of Science and Technology of China [Hefei] (USTC), Instituto Nacional de Técnica Aeroespacial (INTA), Laboratoire de l'Atmosphère et des Cyclones (LACy), Météo France-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), University of Manchester [Manchester], Kyrgyz National University, Institute of Environmental Physics [Bremen] (IUP), and University of Bremen

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere
Abstract

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

Published
2020

15. Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author

Verhoelst, Tijl, primary, Compernolle, Steven, additional, Pinardi, Gaia, additional, Lambert, Jean-Christopher, additional, Eskes, Henk J., additional, Eichmann, Kai-Uwe, additional, Fjæraa, Ann Mari, additional, Granville, José, additional, Niemeijer, Sander, additional, Cede, Alexander, additional, Tiefengraber, Martin, additional, Hendrick, François, additional, Pazmiño, Andrea, additional, Bais, Alkiviadis, additional, Bazureau, Ariane, additional, Boersma, K. Folkert, additional, Bognar, Kristof, additional, Dehn, Angelika, additional, Donner, Sebastian, additional, Elokhov, Aleksandr, additional, Gebetsberger, Manuel, additional, Goutail, Florence, additional, Grutter de la Mora, Michel, additional, Gruzdev, Aleksandr, additional, Gratsea, Myrto, additional, Hansen, Georg H., additional, Irie, Hitoshi, additional, Jepsen, Nis, additional, Kanaya, Yugo, additional, Karagkiozidis, Dimitris, additional, Kivi, Rigel, additional, Kreher, Karin, additional, Levelt, Pieternel F., additional, Liu, Cheng, additional, Müller, Moritz, additional, Navarro Comas, Monica, additional, Piters, Ankie J. M., additional, Pommereau, Jean-Pierre, additional, Portafaix, Thierry, additional, Puentedura, Olga, additional, Querel, Richard, additional, Remmers, Julia, additional, Richter, Andreas, additional, Rimmer, John, additional, Rivera Cárdenas, Claudia, additional, Saavedra de Miguel, Lidia, additional, Sinyakov, Valery P., additional, Strong, Kimberley, additional, Van Roozendael, Michel, additional, Veefkind, J. Pepijn, additional, Wagner, Thomas, additional, Wittrock, Folkard, additional, Yela González, Margarita, additional, and Zehner, Claus, additional

Published
2020
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18. Design without thermal bridges

Author

Maltseva, Irina, Elokhov, Aleksandr, Tkachuk, Konstantin, Maltceva, Kseniia, Maltseva, Irina, Elokhov, Aleksandr, Tkachuk, Konstantin, and Maltceva, Kseniia

Published
2018

19. Methane emissions from an oil sands tailings pond: A quantitative comparison of fluxes derived by different methods.

Author

Verhoelst, Tijl, Compernolle, Steven, Pinardi, Gaia, Lambert, Jean-Christopher, Eskes, Henk J., Eichmann, Kai-Uwe, Fjæraa, Ann Mari, Granville, José, Niemeijer, Sander, Cede, Alexander, Tiefengraber, Martin, Hendrick, François, Pazmiño, Andrea, Bais, Alkiviadis, Bazureau, Ariane, Boersma, K. Folkert, Bognar, Kristof, Dehn, Angelika, Donner, Sebastian, and Elokhov, Aleksandr

Subjects
OIL sands, PONDS, FLUX (Energy), METHANE
Abstract

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically -23 to -37% in clean to slightly polluted conditions, but reaching values as high as -51% over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about -0.2Pmolec/cm2, i.e. approx. -2% in summer to -15% in winter; and (iii) a bias ranging from zero to -50% for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5Pmolec/cm2), but exceed those for the tropospheric column data (0.7Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79% larger than the OFFL values. [ABSTRACT FROM AUTHOR]

Published
2020
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21. Investigating differences in DOAS retrieval codes using MAD-CAT campaign data

Author

Peters, Enno, primary, Pinardi, Gaia, additional, Seyler, André, additional, Richter, Andreas, additional, Wittrock, Folkard, additional, Bösch, Tim, additional, Burrows, John P., additional, Van Roozendael, Michel, additional, Hendrick, François, additional, Drosoglou, Theano, additional, Bais, Alkis F., additional, Kanaya, Yugo, additional, Zhao, Xiaoyi, additional, Strong, Kimberly, additional, Lampel, Johannes, additional, Volkamer, Rainer, additional, Koenig, Theodore, additional, Ortega, Ivan, additional, Piters, Ankie, additional, Puentedura, Olga, additional, Navarro, Mónica, additional, Gómez, Laura, additional, Yela González, Margarita, additional, Remmers, Julia, additional, Wang, Yang, additional, Wagner, Thomas, additional, Wang, Shanshan, additional, Saiz-Lopez, Alfonso, additional, García-Nieto, David, additional, Cuevas, Carlos A., additional, Benavent, Nuria, additional, Querel, Richard, additional, Johnston, Paul, additional, Postylyakov, Oleg, additional, Borovski, Alexander, additional, Elokhov, Aleksandr, additional, Bruchkouski, Ilya, additional, Liu, Cheng, additional, Hong, Qianqian, additional, Liu, Haoran, additional, Rivera, Claudia, additional, Grutter, Michel, additional, Stremme, Wolfgang, additional, Khokhar, M. Fahim, additional, and Khayyam, Junaid, additional

Published
2016
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