Developing Methods and Algorithms for Cloud Computing Management Systems in Industrial Polymer Synthesis Processes

To date, the resources and computational capacity of companies have been insufficient to evaluate the technological properties of emerging products based on mathematical modelling tools. Often, several calculations have to be performed with different initial data. A remote computing system using a high-performance cluster can overcome this challenge. This study aims to develop unified methods and algorithms for a remote computing management system for modelling polymer synthesis processes at a continuous production scale. The mathematical description of the problem-solving algorithms is based on a kinetic approach to process investigation. A conceptual scheme for the proposed service can be built as a multi-level architecture with distributed layers for data storage and computation. This approach provides the basis for a unified database of laboratory and computational experiments to address and solve promising problems in the use of neural network technologies in chemical kinetics. The methods and algorithms embedded in the system eliminate the need for model description. The operation of the system was tested by simulating the simultaneous statement and computation of 15 to 30 tasks for an industrially significant polymer production process. Analysis of the time required showed a nearly 10-fold increase in the rate of operation when managing a set of similar tasks. The analysis shows that the described formulation and solution of problems is more time-efficient and provides better production modes. Doi: 10.28991/esj-2021-01324 Full Text: PD

Bjorken sum rule at low Q^2

A description of the generalized Gerasimov-Drell-Hearn sum rules for proton and neutron is suggested, using their relation to the Bjorken sum rule. The results support an earlier conjecture, that the structure function g_T features a smooth Q^2-dependence, while the structure function g_2 is changing rapidly, due to the elastic contribution to the Burkhardt-Cottingham sum rule. A possible violation of this later sum rule is briefly discussed.Comment: 8 pages, 2 eps figure

Surface patterning of nanoparticles with polymer patches

Patterning of colloidal particles with chemically or topographically distinct surface domains (patches) has attracted intense research interest1–3. Surface-patterned particles act as colloidal analogues of atoms and molecules4,5, serve as model systems in studies of phase transitions in liquid systems6, behave as ‘colloidal surfactants’7 and function as templates for the synthesis of hybrid particles8. The generation of micrometre- and submicrometre-sized patchy colloids is now efficient9–11, but surface patterning of inorganic colloidal nanoparticles with dimensions of the order of tens of nanometres is uncommon. Such nanoparticles exhibit size- and shape-dependent optical, electronic and magnetic properties, and their assemblies show new collective properties12. At present, nanoparticle patterning is limited to the generation of two-patch nanoparticles13–15, and nanoparticles with surface ripples16 or a ‘raspberry’ surface morphology17. Here we demonstrate nanoparticle surface patterning, which utilizes thermodynamically driven segregation of polymer ligands from a uniform polymer brush into surface-pinned micelles following a change in solvent quality. Patch formation is reversible but can be permanently preserved using a photocrosslinking step. The methodology offers the ability to control the dimensions of patches, their spatial distribution and the number of patches per nanoparticle, in agreement with a theoretical model. The versatility of the strategy is demonstrated by patterning nanoparticles with different dimensions, shapes and compositions, tethered with various types of polymers and subjected to different external stimuli. These patchy nanocolloids have potential applications in fundamental research, the self-assembly of nanomaterials, diagnostics, sensing and colloidal stabilization

Genome-Wide Association Study Reveals a Novel Association Between MYBPC3 Gene Polymorphism, Endurance Athlete Status, Aerobic Capacity and Steroid Metabolism.

The genetic predisposition to elite athletic performance has been a controversial subject due to the underpowered studies and the small effect size of identified genetic variants. The aims of this study were to investigate the association of common single-nucleotide polymorphisms (SNPs) with endurance athlete status in a large cohort of elite European athletes using GWAS approach, followed by replication studies in Russian and Japanese elite athletes and functional validation using metabolomics analysis. The association of 476,728 SNPs of Illumina DrugCore Gene chip and endurance athlete status was investigated in 796 European international-level athletes (645 males, 151 females) by comparing allelic frequencies between athletes specialized in sports with high ( = 662) and low/moderate ( = 134) aerobic component. Replication of results was performed by comparing the frequencies of the most significant SNPs between 242 and 168 elite Russian high and low/moderate aerobic athletes, respectively, and between 60 elite Japanese endurance athletes and 406 controls. A meta-analysis has identified rs1052373 (GG homozygotes) in Myosin Binding Protein (; implicated in cardiac hypertrophic myopathy) gene to be associated with endurance athlete status ( = 1.43 × 10, odd ratio 2.2). Homozygotes carriers of rs1052373 G allele in Russian athletes had significantly greater VO than carriers of the AA + AG ( = 0.005). Subsequent metabolomics analysis revealed several amino acids and lipids associated with rs1052373 G allele (1.82 × 10) including the testosterone precursor androstenediol (3beta,17beta) disulfate. This is the first report of genome-wide significant SNP and related metabolites associated with elite athlete status. Further investigations of the functional relevance of the identified SNPs and metabolites in relation to enhanced athletic performance are warranted

Phenological shifts of abiotic events, producers and consumers across a continent

Ongoing climate change can shift organism phenology in ways that vary depending on species, habitats and climate factors studied. To probe for large-scale patterns in associated phenological change, we use 70,709 observations from six decades of systematic monitoring across the former Union of Soviet Socialist Republics. Among 110 phenological events related to plants, birds, insects, amphibians and fungi, we find a mosaic of change, defying simple predictions of earlier springs, later autumns and stronger changes at higher latitudes and elevations. Site mean temperature emerged as a strong predictor of local phenology, but the magnitude and direction of change varied with trophic level and the relative timing of an event. Beyond temperature-associated variation, we uncover high variation among both sites and years, with some sites being characterized by disproportionately long seasons and others by short ones. Our findings emphasize concerns regarding ecosystem integrity and highlight the difficulty of predicting climate change outcomes. The authors use systematic monitoring across the former USSR to investigate phenological changes across taxa. The long-term mean temperature of a site emerged as a strong predictor of phenological change, with further imprints of trophic level, event timing, site, year and biotic interactions.Peer reviewe

Chronicles of nature calendar, a long-term and large-scale multitaxon database on phenology

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.Peer reviewe

A Genome-Wide Association Study of Sprint Performance in Elite Youth Football Players

Pickering, C, Suraci, B, Semenova, EA, Boulygina, EA, Kostryukova, ES, Kulemin, NA, Borisov, OV, Khabibova, SA, Larin, AK, Pavlenko, AV, Lyubaeva, EV, Popov, DV, Lysenko, EA, Vepkhvadze, TF, Lednev, EM, Leońska-Duniec, A, Pająk, B, Chycki, J, Moska, W, Lulińska-Kuklik, E, Dornowski, M, Maszczyk, A, Bradley, B, Kana-ah, A, Cięszczyk, P, Generozov, EV, and Ahmetov, II. A genome-wide association study of sprint performance in elite youth football players. J Strength Cond Res XX(X): 000-000, 2019-Sprint speed is an important component of football performance, with teams often placing a high value on sprint and acceleration ability. The aim of this study was to undertake the first genome-wide association study to identify genetic variants associated with sprint test performance in elite youth football players and to further validate the obtained results in additional studies. Using micro-array data (600 K-1.14 M single nucleotide polymorphisms [SNPs]) of 1,206 subjects, we identified 12 SNPs with suggestive significance after passing replication criteria. The polymorphism rs55743914 located in the PTPRK gene was found as the most significant for 5-m sprint test (p = 7.7 × 10). Seven of the discovered SNPs were also associated with sprint test performance in a cohort of 126 Polish women, and 4 were associated with power athlete status in a cohort of 399 elite Russian athletes. Six SNPs were associated with muscle fiber type in a cohort of 96 Russian subjects. We also examined genotype distributions and possible associations for 16 SNPs previously linked with sprint performance. Four SNPs (AGT rs699, HSD17B14 rs7247312, IGF2 rs680, and IL6 rs1800795) were associated with sprint test performance in this cohort. In addition, the G alleles of 2 SNPs in ADRB2 (rs1042713 & rs1042714) were significantly over-represented in these players compared with British and European controls. These results suggest that there is a genetic influence on sprint test performance in footballers, and identifies some of the genetic variants that help explain this influence