TY - JOUR
A1 - Abdalla, H.
A1 - Adam, R.
A1 - Aharonian, Felix A.
A1 - Benkhali, F. Ait
A1 - Angüner, Ekrem Oǧuzhan
A1 - Arcaro, C.
A1 - Armand, C.
A1 - Armstrong, T.
A1 - Ashkar, H.
A1 - Backes, M.
A1 - Baghmanyan, V.
A1 - Martins, V. Barbosa
A1 - Barnacka, A.
A1 - Barnard, M.
A1 - Becherini, Y.
A1 - Berge, D.
A1 - Bernlohr, K.
A1 - Bi, B.
A1 - Bottcher, M.
A1 - Boisson, C.
A1 - Bolmont, J.
A1 - de Lavergne, M. de Bony
A1 - Bordas, Pol
A1 - Breuhaus, M.
A1 - Brun, F.
A1 - Brun, P.
A1 - Bryan, M.
A1 - Buchele, M.
A1 - Bulik, T.
A1 - Bylund, T.
A1 - Caroff, S.
A1 - Carosi, A.
A1 - Casanova, Sabrina
A1 - Chand, T.
A1 - Chandra, S.
A1 - Chen, A.
A1 - Cotter, G.
A1 - Curylo, M.
A1 - Mbarubucyeye, J. Damascene
A1 - Davids, I. D.
A1 - Davies, J.
A1 - Deil, C.
A1 - Devin, J.
A1 - deWilt, P.
A1 - Dirson, L.
A1 - Djannati-Atai, A.
A1 - Dmytriiev, A.
A1 - Donath, A.
A1 - Doroshenko, V.
A1 - Duffy, C.
A1 - Dyks, J.
A1 - Egberts, Kathrin
A1 - Eichhorn, F.
A1 - Einecke, S.
A1 - Emery, G.
A1 - Ernenwein, J. -P.
A1 - Feijen, K.
A1 - Fegan, S.
A1 - Fiasson, A.
A1 - de Clairfontaine, G. Fichet
A1 - Fontaine, G.
A1 - Funk, S.
A1 - Fussling, Matthias
A1 - Gabici, S.
A1 - Gallant, Y. A.
A1 - Giavitto, G.
A1 - Giunti, L.
A1 - Glawion, D.
A1 - Glicenstein, J. F.
A1 - Gottschall, D.
A1 - Grondin, M. -H.
A1 - Hahn, J.
A1 - Haupt, M.
A1 - Hermann, G.
A1 - Hinton, J. A.
A1 - Hofmann, W.
A1 - Hoischen, Clemens
A1 - Holch, T. L.
A1 - Holler, M.
A1 - Horbe, M.
A1 - Horns, D.
A1 - Huber, D.
A1 - Jamrozy, M.
A1 - Jankowsky, D.
A1 - Jankowsky, F.
A1 - Jardin-Blicq, A.
A1 - Joshi, V.
A1 - Jung-Richardt, I.
A1 - Kasai, E.
A1 - Kastendieck, M. A.
A1 - Katarzynski, K.
A1 - Katz, U.
A1 - Khangulyan, D.
A1 - Khelifi, B.
A1 - Klepser, S.
A1 - Kluzniak, W.
A1 - Komin, Nu.
A1 - Konno, R.
A1 - Kosack, K.
A1 - Kostunin, D.
A1 - Kreter, M.
A1 - Lamanna, G.
A1 - Lemiere, A.
A1 - Lemoine-Goumard, M.
A1 - Lenain, J. -P.
A1 - Levy, C.
A1 - Lohse, T.
A1 - Lypova, I.
A1 - Mackey, J.
A1 - Majumdar, J.
A1 - Malyshev, D.
A1 - Malyshev, D.
A1 - Marandon, V.
A1 - Marchegiani, P.
A1 - Marcowith, Alexandre
A1 - Mares, A.
A1 - Marti-Devesa, G.
A1 - Marx, R.
A1 - Maurin, G.
A1 - Meintjes, P. J.
A1 - Meyer, M.
A1 - Mitchell, A.
A1 - Moderski, R.
A1 - Mohamed, M.
A1 - Mohrmann, L.
A1 - Montanari, A.
A1 - Moore, C.
A1 - Morris, P.
A1 - Moulin, Emmanuel
A1 - Muller, J.
A1 - Murach, T.
A1 - Nakashima, K.
A1 - Nayerhoda, A.
A1 - de Naurois, M.
A1 - Ndiyavala, H.
A1 - Niederwanger, F.
A1 - Niemiec, J.
A1 - Oakes, L.
A1 - O'Brien, Patrick
A1 - Odaka, H.
A1 - Ohm, S.
A1 - Olivera-Nieto, L.
A1 - Wilhelmi, E. de Ona
A1 - Ostrowski, M.
A1 - Oya, I.
A1 - Panter, M.
A1 - Panny, S.
A1 - Parsons, R. D.
A1 - Peron, G.
A1 - Peyaud, B.
A1 - Piel, Q.
A1 - Pita, S.
A1 - Poireau, V.
A1 - Noel, A. Priyana
A1 - Prokhorov, D. A.
A1 - Prokoph, H.
A1 - Puhlhofer, G.
A1 - Punch, M.
A1 - Quirrenbach, A.
A1 - Raab, S.
A1 - Rauth, R.
A1 - Reichherzer, P.
A1 - Reimer, A.
A1 - Reimer, O.
A1 - Remy, Q.
A1 - Renaud, M.
A1 - Rieger, F.
A1 - Rinchiuso, L.
A1 - Romoli, C.
A1 - Rowell, G.
A1 - Rudak, B.
A1 - Ruiz-Velasco, E.
A1 - Sahakian, V.
A1 - Sailer, S.
A1 - Sanchez, D. A.
A1 - Santangelo, A.
A1 - Sasaki, M.
A1 - Scalici, M.
A1 - Schussler, F.
A1 - Schutte, H. M.
A1 - Schwanke, U.
A1 - Schwemmer, S.
A1 - Seglar-Arroyo, M.
A1 - Senniappan, M.
A1 - Seyffert, A. S.
A1 - Shafi, N.
A1 - Shiningayamwe, K.
A1 - Simoni, R.
A1 - Sinha, A.
A1 - Sol, H.
A1 - Specovius, A.
A1 - Spencer, S.
A1 - Spir-Jacob, M.
A1 - Stawarz, L.
A1 - Sun, L.
A1 - Steenkamp, R.
A1 - Stegmann, C.
A1 - Steinmassl, S.
A1 - Steppa, C.
A1 - Takahashi, T.
A1 - Tavernier, T.
A1 - Taylor, A. M.
A1 - Terrier, R.
A1 - Tiziani, D.
A1 - Tluczykont, M.
A1 - Tomankova, L.
A1 - Trichard, C.
A1 - Tsirou, M.
A1 - Tuffs, R.
A1 - Uchiyama, Y.
A1 - van der Walt, D. J.
A1 - van Eldik, C.
A1 - van Rensburg, C.
A1 - van Soelen, B.
A1 - Vasileiadis, G.
A1 - Veh, J.
A1 - Venter, C.
A1 - Vincent, P.
A1 - Vink, J.
A1 - Volk, H. J.
A1 - Vuillaume, T.
A1 - Wadiasingh, Z.
A1 - Wagner, S. J.
A1 - Watson, J.
A1 - Werner, F.
A1 - White, R.
A1 - Wierzcholska, A.
A1 - Wong, Yu Wun
A1 - Yusafzai, A.
A1 - Zacharias, M.
A1 - Zanin, R.
A1 - Zargaryan, D.
A1 - Zdziarski, A. A.
A1 - Zech, Alraune
A1 - Zhu, S. J.
A1 - Ziegler, A.
A1 - Zorn, J.
A1 - Zouari, S.
A1 - Zywucka, N.
T1 - An extreme particle accelerator in the Galactic plane
BT - HESS J1826-130
JF - Astronomy and astrophysics : an international weekly journal
N2 - The unidentified very-high-energy (VHE; E > 0.1 TeV) gamma -ray source, HESS J1826-130, was discovered with the High Energy Stereoscopic System (HESS) in the Galactic plane. The analysis of 215 h of HESS data has revealed a steady gamma -ray flux from HESS J1826-130, which appears extended with a half-width of 0.21 degrees +/- 0.02
(stat)degrees
stat degrees +/- 0.05
(sys)degrees sys degrees . The source spectrum is best fit with either a power-law function with a spectral index Gamma = 1.78 +/- 0.10(stat) +/- 0.20(sys) and an exponential cut-off at 15.2
(+5.5)(-3.2) -3.2+5.5 TeV, or a broken power-law with Gamma (1) = 1.96 +/- 0.06(stat) +/- 0.20(sys), Gamma (2) = 3.59 +/- 0.69(stat) +/- 0.20(sys) for energies below and above E-br = 11.2 +/- 2.7 TeV, respectively. The VHE flux from HESS J1826-130 is contaminated by the extended emission of the bright, nearby pulsar wind nebula, HESS J1825-137, particularly at the low end of the energy spectrum. Leptonic scenarios for the origin of HESS J1826-130 VHE emission related to PSR J1826-1256 are confronted by our spectral and morphological analysis. In a hadronic framework, taking into account the properties of dense gas regions surrounding HESS J1826-130, the source spectrum would imply an astrophysical object capable of accelerating the parent particle population up to greater than or similar to 200 TeV. Our results are also discussed in a multiwavelength context, accounting for both the presence of nearby supernova remnants, molecular clouds, and counterparts detected in radio, X-rays, and TeV energies.
KW - ISM: supernova remnants
KW - ISM: clouds
KW - gamma rays: general
KW - gamma rays:
KW - ISM
Y1 - 2020
U6 - https://doi.org/10.1051/0004-6361/202038851
SN - 0004-6361
SN - 1432-0746
VL - 644
PB - EDP Sciences
CY - Les Ulis
ER -
TY - JOUR
A1 - Abdalla, Hassan E.
A1 - Adam, Remi
A1 - Aharonian, Felix A.
A1 - Benkhali, Faical Ait
A1 - Angüner, Ekrem Oǧuzhan
A1 - Arakawa, Masanori
A1 - Arcaro, C
A1 - Armand, Catherine
A1 - Armstrong, T.
A1 - Egberts, Kathrin
T1 - Very high energy γ-ray emission from two blazars of unknown redshift and upper limits on their distance
JF - Monthly Notices of the Royal Astronomical Society
N2 - We report on the detection of very high energy (VHE; E > 100 GeV) gamma-ray emission from the BL Lac objects KUV 00311-1938 and PKS 1440-389 with the High Energy Stereoscopic System (H.E.S.S.). H.E.S.S. observations were accompanied or preceded by multiwavelength observations with Fermi/LAT, XRT and UVOT onboard the Swift satellite, and ATOM. Based on an extrapolation of the Fermi/LAT spectrum towards the VHE gamma-ray regime, we deduce a 95 per cent confidence level upper limit on the unknown redshift of KUV 00311-1938 of z < 0.98 and of PKS 1440-389 of z < 0.53. When combined with previous spectroscopy results, the redshift of KUV 00311-1938 is constrained to 0.51 <= z < 0.98 and of PKS 1440-389 to 0.14 (sic) z < 0.53.
KW - BL Lacertae objects: individual
KW - galaxies: high-redshift
KW - gamma-rays: general
KW - Resolved and unresolved sources as a function of wavelength
Y1 - 2020
VL - 494
IS - 4
PB - Wiley-Blackwell
CY - Oxford
ER -
TY - JOUR
A1 - Abdirashid, Hashim
A1 - Lenhard, Michael
T1 - Say it with double flowers
JF - Journal of experimental botany
N2 - Every year, lovers world-wide rely on mutants to show their feelings on Valentine's Day. This is because many of the most popular ornamental flowering plants have been selected to form extra petals at the expense of reproductive organs to enhance their attractiveness and aesthetic value to humans. This so-called 'double flower' (DF) phenotype, first described more than 2000 years ago (Meyerowitz et al., 1989) is present, for example, in many modern roses, carnations, peonies, and camellias. Gattolin et al. (2020) now identify a unifying explanation for the molecular basis of many of these DF cultivars.
KW - ABCE model
KW - APETALA2
KW - double flowers
KW - flower development
KW - homoeotic
KW - mutants
KW - microRNA172
Y1 - 2020
U6 - https://doi.org/10.1093/jxb/eraa109
SN - 0022-0957
SN - 1460-2431
VL - 71
IS - 9
SP - 2469
EP - 2471
PB - Oxford Univ. Press
CY - Oxford
ER -
TY - JOUR
A1 - Adam, Maurits
A1 - Elsner, Birgit
T1 - The impact of salient action effects on 6-, 7-, and 11-month-olds’ goal-predictive gaze shifts for a human grasping action
JF - PLOS ONE
N2 - When infants observe a human grasping action, experience-based accounts predict that all infants familiar with grasping actions should be able to predict the goal regardless of additional agency cues such as an action effect. Cue-based accounts, however, suggest that infants use agency cues to identify and predict action goals when the action or the agent is not familiar. From these accounts, we hypothesized that younger infants would need additional agency cues such as a salient action effect to predict the goal of a human grasping action, whereas older infants should be able to predict the goal regardless of agency cues. In three experiments, we presented 6-, 7-, and 11-month-olds with videos of a manual grasping action presented either with or without an additional salient action effect (Exp. 1 and 2), or we presented 7-month-olds with videos of a mechanical claw performing a grasping action presented with a salient action effect (Exp. 3). The 6-month-olds showed tracking gaze behavior, and the 11-month-olds showed predictive gaze behavior, regardless of the action effect. However, the 7-month-olds showed predictive gaze behavior in the action-effect condition, but tracking gaze behavior in the no-action-effect condition and in the action-effect condition with a mechanical claw. The results therefore support the idea that salient action effects are especially important for infants' goal predictions from 7 months on, and that this facilitating influence of action effects is selective for the observation of human hands.
KW - attention
KW - eye movements
KW - infants perception
KW - mechanisms
KW - origins
Y1 - 2020
U6 - https://doi.org/10.1371/journal.pone.0240165
SN - 1932-6203
VL - 15
IS - 10
PB - Public Library of Science
CY - San Fransisco
ER -
TY - JOUR
A1 - Adnan, Hassan Sami
A1 - Matthews, Sam
A1 - Hackl, M.
A1 - Das, P. P.
A1 - Manaswini, Manisha
A1 - Gadamsetti, S.
A1 - Filali, Maroua
A1 - Owoyele, Babajide
A1 - Santuber, Joaquín
A1 - Edelman, Jonathan
T1 - Human centered AI design for clinical monitoring and data management
JF - European journal of public health : official journal of the European Health Association
N2 - In clinical settings, significant resources are spent on data collection and monitoring patients' health parameters to improve decision-making and provide better care. With increased digitization, the healthcare sector is shifting towards implementing digital technologies for data management and in administration. New technologies offer better treatment opportunities and streamline clinical workflow, but the complexity can cause ineffectiveness, frustration, and errors. To address this, we believe digital solutions alone are not sufficient. Therefore, we take a human-centred design approach for AI development, and apply systems engineering methods to identify system leverage points. We demonstrate how automation enables monitoring clinical parameters, using existing non-intrusive sensor technology, resulting in more resources toward patient care. Furthermore, we provide a framework on digitization of clinical data for integration with data management.
Y1 - 2020
U6 - https://doi.org/10.1093/eurpub/ckaa165.225
SN - 1101-1262
SN - 1464-360X
VL - 30
IS - 5
SP - V86
EP - V86
PB - Oxford Univ. Press
CY - Oxford
ER -
TY - JOUR
A1 - Adnan, Hassan Sami
A1 - Srsic, Amanda
A1 - Venticich, Pete Milos
A1 - Townend, David M.R.
T1 - Using AI for mental health analysis and prediction in school surveys
JF - European journal of public health
N2 - Background:
Childhood and adolescence are critical stages of life for mental health and well-being. Schools are a key setting for mental health promotion and illness prevention. One in five children and adolescents have a mental disorder, about half of mental disorders beginning before the age of 14. Beneficial and explainable artificial intelligence can replace current paper- based and online approaches to school mental health surveys. This can enhance data acquisition, interoperability, data driven analysis, trust and compliance. This paper presents a model for using chatbots for non-obtrusive data collection and supervised machine learning models for data analysis; and discusses ethical considerations pertaining to the use of these models.
Methods:
For data acquisition, the proposed model uses chatbots which interact with students. The conversation log acts as the source of raw data for the machine learning. Pre-processing of the data is automated by filtering for keywords and phrases.
Existing survey results, obtained through current paper-based data collection methods, are evaluated by domain experts (health professionals). These can be used to create a test dataset to validate the machine learning models. Supervised learning
can then be deployed to classify specific behaviour and mental health patterns.
Results:
We present a model that can be used to improve upon current paper-based data collection and manual data analysis methods. An open-source GitHub repository contains necessary tools and components of this model. Privacy is respected through
rigorous observance of confidentiality and data protection requirements. Critical reflection on these ethics and law aspects is included in the project.
Conclusions:
This model strengthens mental health surveillance in schools. The same tools and components could be applied to other public health data. Future extensions of this model could also incorporate unsupervised learning to find clusters and patterns
of unknown effects.
KW - ethics
KW - artificial intelligence
KW - adolescent
KW - child
KW - confidentiality
KW - health personnel
KW - mental disorders
KW - mental health
KW - personal satisfaction
KW - privacy
KW - school (environment)
KW - statutes and laws
KW - public health medicine
KW - surveillance
KW - medical
KW - prevention
KW - datasets
KW - machine learning
KW - supervised machine learning
KW - data analysis
Y1 - 2020
U6 - https://doi.org/10.1093/eurpub/ckaa165.336
SN - 1101-1262
SN - 1464-360X
VL - 30
SP - V125
EP - V125
PB - Oxford Univ. Press
CY - Oxford [u.a.]
ER -
TY - JOUR
A1 - Aga-Barfknecht, Heja
A1 - Hallahan, Nicole
A1 - Gottmann, Pascal
A1 - Jähnert, Markus
A1 - Osburg, Sophie
A1 - Schulze, Gunnar
A1 - Kamitz, Anne
A1 - Arends, Danny
A1 - Brockmann, Gudrun
A1 - Schallschmidt, Tanja
A1 - Lebek, Sandra
A1 - Chadt, Alexandra
A1 - Al-Hasani, Hadi
A1 - Joost, Hans-Georg
A1 - Schürmann, Annette
A1 - Vogel, Heike
T1 - Identification of novel potential type 2 diabetes genes mediating beta-cell loss and hyperglycemia using positional cloning
JF - Frontiers in genetics
N2 - Type 2 diabetes (T2D) is a complex metabolic disease regulated by an interaction of genetic predisposition and environmental factors. To understand the genetic contribution in the development of diabetes, mice varying in their disease susceptibility were crossed with the obese and diabetes-prone New Zealand obese (NZO) mouse. Subsequent whole-genome sequence scans revealed one major quantitative trait loci (QTL),Nidd/DBAon chromosome 4, linked to elevated blood glucose and reduced plasma insulin and low levels of pancreatic insulin. Phenotypical characterization of congenic mice carrying 13.6 Mbp of the critical fragment of DBA mice displayed severe hyperglycemia and impaired glucose clearance at week 10, decreased glucose response in week 13, and loss of beta-cells and pancreatic insulin in week 16. To identify the responsible gene variant(s), further congenic mice were generated and phenotyped, which resulted in a fragment of 3.3 Mbp that was sufficient to induce hyperglycemia. By combining transcriptome analysis and haplotype mapping, the number of putative responsible variant(s) was narrowed from initial 284 to 18 genes, including gene models and non-coding RNAs. Consideration of haplotype blocks reduced the number of candidate genes to four (Kti12,Osbpl9,Ttc39a, andCalr4) as potential T2D candidates as they display a differential expression in pancreatic islets and/or sequence variation. In conclusion, the integration of comparative analysis of multiple inbred populations such as haplotype mapping, transcriptomics, and sequence data substantially improved the mapping resolution of the diabetes QTLNidd/DBA. Future studies are necessary to understand the exact role of the different candidates in beta-cell function and their contribution in maintaining glycemic control.
KW - type 2 diabetes
KW - beta-cell loss
KW - insulin
KW - positional cloning
KW - transcriptomics
KW - haplotype
Y1 - 2020
U6 - https://doi.org/10.3389/fgene.2020.567191
SN - 1664-8021
VL - 11
PB - Frontiers Media
CY - Lausanne
ER -
TY - JOUR
A1 - Agarwal, Ankit
A1 - Marwan, Norbert
A1 - Maheswaran, Rathinasamy
A1 - Öztürk, Ugur
A1 - Kurths, Jürgen
A1 - Merz, Bruno
T1 - Optimal design of hydrometric station networks based on complex network analysis
JF - Hydrology and Earth System Sciences
N2 - Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few years in different areas such as brain networks, social networks, technological networks, or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node-ranking measure – the weighted degree–betweenness (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.
KW - identifying influential nodes
KW - climate networks
KW - rainfall
KW - streamflow
KW - synchronization
KW - precipitation
KW - classification
KW - events
Y1 - 2020
U6 - https://doi.org/10.5194/hess-24-2235-2020
SN - 1027-5606
SN - 1607-7938
VL - 24
IS - 5
SP - 2235
EP - 2251
PB - Copernicus Publ.
CY - Göttingen
ER -
TY - JOUR
A1 - Al-Naji, Majd
A1 - Schlaad, Helmut
A1 - Antonietti, Markus
T1 - New (and old) monomers from biorefineries to make polymer chemistry more sustainable
JF - Macromolecular rapid communications
N2 - This opinion article describes recent approaches to use the "biorefinery" concept to lower the carbon footprint of typical mass polymers, by replacing parts of the fossil monomers with similar or even the same monomer made from regrowing dendritic biomass. Herein, the new and green catalytic synthetic routes are for lactic acid (LA), isosorbide (IS), 2,5-furandicarboxylic acid (FDCA), and p-xylene (pXL). Furthermore, the synthesis of two unconventional lignocellulosic biomass derivable monomers, i.e., alpha-methylene-gamma-valerolactone (MeGVL) and levoglucosenol (LG), are presented. All those have the potential to enter in a cost-effective way, also the mass market and thereby recover lost areas for polymer materials. The differences of catalytic unit operations of the biorefinery are also discussed and the challenges that must be addressed along the synthesis path of each monomers.
KW - biodegradable polymers
KW - biorefineries
KW - carbohydrate‐ based
KW - monomers
KW - green polymers
KW - lignocellulosic biomass
Y1 - 2020
U6 - https://doi.org/10.1002/marc.202000485
SN - 1022-1336
SN - 1521-3927
VL - 42
IS - 3
PB - Wiley-VCH
CY - Weinheim
ER -
TY - JOUR
A1 - Al-Saedy, Ammar Jaffar Muhesin
A1 - Tarchanov, Nikolaj Nikolaevič
T1 - A degree theory for Lagrangian boundary value problems
JF - Žurnal Sibirskogo Federalʹnogo Universiteta = Journal of Siberian Federal University; mathematics & physics
N2 - We study those nonlinear partial differential equations which appear as Euler-Lagrange equations of variational problems. On defining weak boundary values of solutions to such equations we initiate the theory of Lagrangian boundary value problems in spaces of appropriate smoothness. We also analyse if the concept of mapping degree of current importance applies to Lagrangian problems.
N2 - Мы изучаем те нелинейные уравнения с частными производными, которые возникают как уравнения Эйлера-Лагранжа вариационных задач. Определяя слабые граничные значения решений таких уравнений, мы инициируем теорию лагранжевых краевых задач в функциональных пространствах подходящей гладкости. Мы также анализируем, применяется ли современная концепция степени отображения к лагранжевым проблемам.
KW - nonlinear equations
KW - Lagrangian system
KW - weak boundary values
KW - quasilinear Fredholm operators
KW - mapping degree
Y1 - 2020
U6 - https://doi.org/10.17516/1997-1397-2020-13-1-5-25
SN - 1997-1397
SN - 2313-6022
VL - 13
IS - 1
SP - 5
EP - 25
PB - Sibirskij Federalʹnyj Universitet
CY - Krasnojarsk
ER -