THREE· DIMENSIONAL STUDY OF STREAMFLOW DEVELOPING AROUND RADIAL WELLS

Based on the completed three dimensional electric analogous studies the following main points can be established: 1. In case of a radial well sited in an extensiye horizontal layer: a) the capacity of well is proportional to the 0.87th power of the thickness of the layer, b) the increase of the number of horizontal pipes with the same total length causes just a slight decrease in discharge, therefore, when determining the number of horizontal pipes, they are not the hydraulic aspects which are decisive, c) limiting the perforation just for the outer half length of the horizontal pipe causes about a 5% reduction in discharge only. 2. In case of a radial well sited near a river-bed. the horizontal pipe in the direction opposite to the river-bed can be omitted without any considerable decrease in discharge. 3. The horizontal pipe reaching under the riverbed considerably increases the discharge, but can result in a rapid colmation. 4. Colmation extends the influence of the well on a longer section of the riyer-bed, that is why its effect to decrease the discharge develops relatively slowly. 5. Enlightening the development of physical, chemical and biological colmation is by all means necessary to forecast and delay the "ageing" of wells

Antithrombin significantly influences platelet adhesion onto immobilized fibrinogen in an in-vitro system simulating low flow

BACKGROUND: Adhesion of platelets onto immobilized fibrinogen is of importance in initiation and development of thrombosis. According to a recent increase in evidence of a multiple biological property of antithrombin, we evaluated the influence of antithrombin on platelet adhesion onto immobilized fibrinogen using an in-vitro flow system. METHODS: Platelets in anticoagulated whole blood (29 healthy blood donors) were labelled with fluorescence dye and perfused through a rectangular flow chamber (shear rates of 13 s(-1 )to 1500 s(-1)). Platelet adhesion onto fibrinogen-coated slips was assessed using a fluorescence laser-scan microscope and compared to the plasma antithrombin activity. Additionally the effect of supraphysiological AT supplementation on platelets adhesion rate was evaluated. RESULTS: Within a first minute of perfusion, an inverse correlation between platelet adhesion and plasma antithrombin were observed at 13 s(-1 )and 50 s(-1 )(r = -0.48 and r = -0.7, p < 0.05, respectively). Significant differences in platelet adhesion related to low (92 ± 3.3%) and high (117 ± 4.1%) antithrombin activity (1786 ± 516 U vs. 823 ± 331 U, p < 0.05) at low flow rate (13 s(-1), within first minute) have been found. An in-vitro supplementation of whole blood with antithrombin increased the antithrombin activity up to 280% and platelet adhesion rate reached about 65% related to the adhesion rate in a non-supplemented blood (1.25 ± 0.17 vs. 1.95 ± 0.4 p = 0.008, respectively). CONCLUSION: It appears that antithrombin in a low flow system suppresses platelet adhesion onto immobilized fibrinogen independently from its antithrombin activity. A supraphysiological substitution of blood with antithrombin significantly reduces platelet adhesion rate. This inhibitory effect might be of clinical relevance

Partisanship, Propaganda and Post-Truth Politics: Quantifying Impact in Online Debate

The recent past has highlighted the influential role of social networks and online media in shaping public debate on current affairs and political issues. This paper is focused on studying the role of politically-motivated actors and their strategies for influencing and manipulating public opinion online: partisan media, state-backed propaganda, and post-truth politics. In particular, we present quantitative research on the presence and impact of these three `Ps' in online Twitter debates in two contexts: (i) the run up to the UK EU membership referendum (`Brexit'); and (ii) the information operations of Russia-backed online troll accounts. We first compare the impact of highly partisan versus mainstream media during the Brexit referendum, specifically comparing tweets by half a million `leave' and `remain' supporters. Next, online propaganda strategies are examined, specifically left- and right-wing troll accounts. Lastly, we study the impact of misleading claims made by the political leaders of the leave and remain campaigns. This is then compared to the impact of the Russia-backed partisan media and propaganda accounts during the referendum. In particular, just two of the many misleading claims made by politicians during the referendum were found to be cited in 4.6 times more tweets than the 7,103 tweets related to Russia Today and Sputnik and in 10.2 times more tweets than the 3,200 Brexit-related tweets by the Russian troll accounts.Comment: This is now published in the Journal of Web Science. Please cite accordingly. https://webscience-journal.net/webscience/article/view/8

The impact of digital technology on the development of the nancial market

The impact of digital technology on the nancial market has been signi cant and far- reaching. In recent years, we have seen a rapid adoption of digital technologies such as blockchain, arti cial intelligence, and big data analytics, which have transformed the way nancial services are delivered and consumed. Digital technologies are transforming the nancial sector and improving ef ciency and the quality of life for people. They allow for time-saving and improved labor productivity by intensifying processes and saving time at all stages of transactions, resulting in more transactions per unit of time

Energy efficiency of world's leading copper producers

This paper provides an overview of the leading role that energy efficiency plays in the development of modern socio-economic systems, which serve as the foundation for building green economies. The main purpose of the paper is to develop a methodological toolkit for assessing energy efficiency of large industrial complexes and test it on the world's largest metallurgical complexes. The central object of the research is the Ural Mining and Metallurgical Company (UMMC), which mainly specializes in the production of copper and copper-based products. The study follows a comparative analysis of a set of preliminary selected energy efficiency indicators obtained from UMMC with those of the world's leading copper manufacturers and copper-based products. At the same time, in accordance with the methodical approach, it is proposed to divide the energy efficiency indicators of an industrial complex into three levels: the level of an industrial complex as a whole (1); the level of certain types of products manufactured in the industrial complex (2); the level of the technological process (3). To obtain summarized (synthetic) energy efficiency estimates of the industrial complex, the hierarchy analysis method has been proposed. For the comparative analysis of energy efficiency indicators of UMMC, the authors chose the following companies: Norilsk Nickel and Russian Copper Company and leading world companies, such as Glencore Xstrata Plc (Switzerland), Codelco (Chile), KGHM Polska Miedz SA (Poland), and Vedanta Resources (India). The obtained results revealed that UMMC strongly lags behind in a number of key energy efficiency indicators. During 2010-2016, a negative trend was observed in the majority of UMMC enterprises. The results also showed the practical applicability of the given methodical approach and the possibility of its wide use in solving energy efficiency problems of Russian industrial complexes for their strategic development. © 2020 WIT Press, www.witpress.co

Large machine-building cluster competitiveness assessment

The authors show modern problems of the development and competitiveness of the Russian economy within the framework of the implementation of the resource model of economic development under conditions of an adverse external environment. The necessity of transition to an innovative model is justified that should result in a significant increase of the competitiveness of domestic hi-tech industries. Analysis is performed of existing approaches to assessing the competitiveness of enterprises and production complexes, the main advantages and disadvantages are highlighted. The authors propose a scientific and methodical approach to the study and management of competitiveness of large industrial clusters based on comprehensive consideration of various influencing factors; a description of the main blocks of the approach is given. A comprehensive method of assessing the competitiveness of industrial complexes is described which is the central element of the proposed scientific and methodical approach. The basic rules and algorithms that are used in the method and composition of the main blocks and indicators of competitiveness adapted to the machinery complexes are given. Using the developed methodological approach an assessment of the competitiveness of one of the largest power machinery-building clusters of Russia - the industrial group Uralelectrotyazhmash, which is the leading enterprise in the electrotechnical industry of Russia - is done. The evaluation identified the main problems and bottlenecks in the development of these group of enterprises, and their comparison with leading competitors is carried out. The obtained results made it possible to form the main directions of improving the competitiveness of the group of companies Uralelectrotyazhmash focusing on the improvement of its financial results. According to the results of the study the main conclusions and recommendations are drawn.Показаны современные проблемы развития и конкурентоспособности российской экономики в рамках реализации сырьевой модели экономического развития в условиях неблагоприятной внешней среды. Обоснована необходимость перехода на инновационную модель, основой которой должен стать существенный рост конкурентоспособности отечественных высокотехнологичных производств. Выполнен анализ существующих подходов к оценке конкурентоспособности предприятий и производственных комплексов, выделены их основные достоинства и недостатки. Предложен научно-методический подход к исследованию и управлению конкурентоспособностью крупных производственных комплексов, основанный на комплексном учете различных влияющих факторов; дано описание основных блоков подхода. Приведена комплексная методика оценки конкурентоспособности производственных комплексов, являющаяся центральным элементом предложенного научно-методического подхода. Рассмотрены основные правила и алгоритмы, используемые в методике, а также состав основных блоков и показателей конкурентоспособности, адаптированный к машиностроительным комплексам. С использованием разработанного методического подхода проведена оценка конкурентоспособности крупнейшего энергомашиностроительного комплекса России - группы предприятий «Уралэлектротяжмаш», являющихся ведущими предприятиями электротехнической промышленности России. По результатам оценки выявлены основные проблемы и «узкие места» в развитии указанных предприятий, а также выполнено их сопоставление с ведущими мировыми конкурентами. Полученные оценки позволили сформировать основные направления повышения конкурентоспособности группы предприятий «Уралэлектротяжмаш », ориентированные на росте финансовых результатов деятельности компании. По итогам проведенного исследования сформированы основные выводы и рекомендации

HFF-DeepSpace photometric catalogs of the 12 Hubble frontier fields, clusters, and parallels : photometry, photometric redshifts, and stellar masses

We present Hubble multi-wavelength photometric catalogs, including (up to) 17 filters with the Advanced Camera for Surveys and Wide Field Camera 3 from the ultra-violet to near-infrared for the Hubble Frontier Fields and associated parallels. We have constructed homogeneous photometric catalogs for all six clusters and their parallels. To further expand these data catalogs, we have added ultra-deep KS-band imaging at 2.2. mu m from the Very Large Telescope HAWK-I and Keck-I MOSFIRE instruments. We also add post-cryogenic Spitzer imaging at 3.6 and 4.5. mu m with the Infrared Array Camera (IRAC), as well as archival IRAC 5.8 and 8.0. mu m imaging when available. We introduce the public release of the multi-wavelength (0.2-8 mu m) photometric catalogs, and we describe the unique steps applied for the construction of these catalogs. Particular emphasis is given to the source detection band, the contamination of light from the bright cluster galaxies (bCGs), and intra-cluster light (ICL). In addition to the photometric catalogs, we provide catalogs of photometric redshifts and stellar population properties. Furthermore, this includes all the images used in the construction of the catalogs, including the combined models of bCGs and ICL, the residual images, segmentation maps, and more. These catalogs are a robust data set of the Hubble Frontier Fields and will be an important aid in designing future surveys, as well as planning follow-up programs with current and future observatories to answer key questions remaining about first light, reionization, the assembly of galaxies, and many more topics, most notably by identifying high-redshift sources to target

An untrained deep learning method for reconstructing dynamic magnetic resonance images from accelerated model-based data

The purpose of this work is to implement physics-based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerated data. The ConvDecoder neural network was trained with a physics-based regularization term incorporating the spoiled gradient echo equation that describes variable-flip angle (VFA) data. Fully-sampled VFA k-space data were retrospectively accelerated by factors of R={8,12,18,36} and reconstructed with ConvDecoder (CD), ConvDecoder with the proposed regularization (CD+r), locally low-rank (LR) reconstruction, and compressed sensing with L1-wavelet regularization (L1). Final images from CD+r training were evaluated at the \emph{argmin} of the regularization loss; whereas the CD, LR, and L1 reconstructions were chosen optimally based on ground truth data. The performance measures used were the normalized root-mean square error, the concordance correlation coefficient (CCC), and the structural similarity index (SSIM). The CD+r reconstructions, chosen using the stopping condition, yielded SSIMs that were similar to the CD (p=0.47) and LR SSIMs (p=0.95) across R and that were significantly higher than the L1 SSIMs (p=0.04). The CCC values for the CD+r T1 maps across all R and subjects were greater than those corresponding to the L1 (p=0.15) and LR (p=0.13) T1 maps, respectively. For R > 12 (<4.2 minutes scan time), L1 and LR T1 maps exhibit a loss of spatially refined details compared to CD+r. We conclude that the use of an untrained neural network together with a physics-based regularization loss shows promise as a measure for determining the optimal stopping point in training without relying on fully-sampled ground truth data.Comment: 45 pages, 7 figures, 2 Tables, supplementary material included (10 figures, 4 tables