CMS physics technical design report : Addendum on high density QCD with heavy ions

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Strategic opportunities for economic development of the Baltic Sea coastal zones and sea industrial and port complexes

Nowadays, one of the principal dimensions in attraction of the world economy structures is coastal territories as spaces where marine potential of a state is most pronounced. In this respect, it is vital to set the priorities of development of coastal zones taking into account the changes in the strategic situation in order to maintain the components of marine potential of the Russian Federation at the level of its national interests. The article aims to develop an indicator system of assessment of coastal zone potential, and sea industrial and port facilities in order to identify the characteristic and strategic capacities of the economic development of these territories in the complex approach. The research methodology is based on the assessment of marine potential of coastal territories as an indicator of the efficacy of its marine economic complex development with using the indicator methods as a multi-factor and multi-level spatial system. The proposed system is applied to a complex analysis of coastal territories of the Russian Baltic, the estimation of a socio-economic factor of coastal zone marine potential, as well as recommendations for long-term planning of the economic development of Russia’s coastal zones of the Baltic Sea and the organization of marine activities. This methodology can help to identify a role of coastal territories in the economy and reflect perspectives and directions of strategic development of coastal zones, and sea industrial and port facilities of the Russian Federation

Social and economic efficiency of dredging projects

This paper examines the problem of socio-economic impact of dredging projects in terms of comprehensive accounting of the long-and short-term factors during and after project completion. Due to the lack of methods to assess the efficiency for long-term factors, it’s proposed the indicator method for such assessments. As an example of the method it’s provided an assessment of the socio-economic impact of the project "St. Petersburg Marine Facade"

Urban green spaces as a factor in the sustainable development of megacities

This article examines the management of urban green spaces as a key factor in the sustainable development of megacities, with a special emphasis on the experience of Krasnoyarsk, a city with a population of over one million facing complex climatic and landscape conditions. It analyzes factors influencing the city’s greening strategy and explores parks, squares, and floral compositions as elements of the urban environment. Suggestions for optimizing greening in Krasnoyarsk are put forward, highlighting its crucial role in the city’s sustainable development

Quality Control of Human Pluripotent Stem Cell Colonies by Computational Image Analysis Using Convolutional Neural Networks

Human pluripotent stem cells are promising for a wide range of research and therapeutic purposes. Their maintenance in culture requires the deep control of their pluripotent and clonal status. A non-invasive method for such control involves day-to-day observation of the morphological changes, along with imaging colonies, with the subsequent automatic assessment of colony phenotype using image analysis by machine learning methods. We developed a classifier using a convolutional neural network and applied it to discriminate between images of human embryonic stem cell (hESC) colonies with “good” and “bad” morphological phenotypes associated with a high and low potential for pluripotency and clonality maintenance, respectively. The training dataset included the phase-contrast images of hESC line H9, in which the morphological phenotype of each colony was assessed through visual analysis. The classifier showed a high level of accuracy (89%) in phenotype prediction. By training the classifier on cropped images of various sizes, we showed that the spatial scale of ~144 μm was the most informative in terms of classification quality, which was an intermediate size between the characteristic diameters of a single cell (~15 μm) and the entire colony (~540 μm). We additionally performed a proteomic analysis of several H9 cell samples used in the computational analysis and showed that cells of different phenotypes differentiated at the molecular level. Our results indicated that the proposed approach could be used as an effective method of non-invasive automated analysis to identify undesirable developmental anomalies during the propagation of pluripotent stem cells

Quality Control of Human Pluripotent Stem Cell Colonies by Computational Image Analysis Using Convolutional Neural Networks

Human pluripotent stem cells are promising for a wide range of research and therapeutic purposes. Their maintenance in culture requires the deep control of their pluripotent and clonal status. A non-invasive method for such control involves day-to-day observation of the morphological changes, along with imaging colonies, with the subsequent automatic assessment of colony phenotype using image analysis by machine learning methods. We developed a classifier using a convolutional neural network and applied it to discriminate between images of human embryonic stem cell (hESC) colonies with “good” and “bad” morphological phenotypes associated with a high and low potential for pluripotency and clonality maintenance, respectively. The training dataset included the phase-contrast images of hESC line H9, in which the morphological phenotype of each colony was assessed through visual analysis. The classifier showed a high level of accuracy (89%) in phenotype prediction. By training the classifier on cropped images of various sizes, we showed that the spatial scale of ~144 μm was the most informative in terms of classification quality, which was an intermediate size between the characteristic diameters of a single cell (~15 μm) and the entire colony (~540 μm). We additionally performed a proteomic analysis of several H9 cell samples used in the computational analysis and showed that cells of different phenotypes differentiated at the molecular level. Our results indicated that the proposed approach could be used as an effective method of non-invasive automated analysis to identify undesirable developmental anomalies during the propagation of pluripotent stem cells

Proceedings of UK-Russia workshop on developing a training network for preparing for climate change in Russia

The UK Foreign and Commonwealth Office has initiated a programme of partnership between UK and Russian Institutions to develop a training network on preparing for climate change in Russia. This will bring together expertise from a number of different partner institutions across different sectors to develop an on-line training resource that can be accessed by Russian professionals working in these key sectors to better inform their decision making when planning for climate change adaptation. The training material will be based on a core set of modules on climate change, climate impacts and climate services already taught at the University of Reading (UoR), linked to material on more applied aspects of climate impacts across specific sectors developed by Russian participants working the Moscow State University (MSU), the European University of St Petersburg (EUSP), St Petersburg State University (SPSU), The Institute of Soil Science (ISS) and the Russian Hydrometeorological Society (RHMS). UoR also has an on-line course team with experience in developing on-line training material across a wide range of academic sectors, including meteorology. The RHMS has experience of developing distance learning materials across weather forecasting and meteorological hazards to aviation

Novel multi-targeting anthra[2,3-b]thiophene-5,10-diones with guanidine-containing side chains: Interaction with telomeric G-quadruplex, inhibition of telomerase and topoisomerase I and cytotoxic properties

Novel generations of antitumor anthraquinones are expected to be advantageous over the conventional chemotherapeutic agents. Previous structure-activity relationship studies demonstrated an importance of the positively charged side chains conjugated to anthra[2,3-b]thiophene-5,10-dione scaffolds. Exploring a role of individual side chain moieties in binding to the duplex and G-quadruplex DNA, modulation of telomerase and topoisomerase I activities, intracellular accumulation and cytostatic potency, we herein analyzed a series of reported and newly synthesized guanidine-containing derivatives of anthra[2,3-b]thiophene-5,10-dione. We found that the number of cationic side chains (namely, two) is critical for a tight interaction with human telomeric G-quadruplex (TelQ). Along with a larger drug-TelQ association constant, the telomerase attenuation by anthrathiophenediones with two basic groups in the side chains was more pronounced than by the analogs bearing one basic group. For mono-guanidinated compounds the substituent with the amino group in the side chain provided better TelQ affinity than the methylamine residue. The intracellular uptake of the mono-guanidino derivative with two side chains was >2-fold higher than the respective value for the bis(guanidino) derivative. This difference can explain a lower antiproliferative potency of bis(guanidine) containing compounds. Thus, the modifications of side chains of anthra[2,3-b]thiophene-5,10-dione differently modulated drug-target interactions and cellular effects. Nevertheless, the selected compound 11-(3-aminopropylamino)-4-(2-guanidinoethylamino)anthra[2,3-b]thiophene-5,10-dione 13 demonstrated a high affinity to TelQ and the ability to stabilize the quadruplex structure. These properties were paralleled by reasonable potency of 13 as a telomerase/topoisomerase I inhibitor and an antiproliferative agent. These results indicate that the structural elements of anthra[2,3-b]thiophene-5,10-dione derivatives can be balanced to yield a candidate for further preclinical study.status: publishe