World Water Day

Всемирный день водных ресурсов проводится с целью привлечения внимания к 2,2 млрд людей, живущих без доступа к чистой воде. Речь идет о принятии мер по борьбе с глобальным водным кризисом. Основным направлением Всемирного дня водных ресурсов является поддержка достижения 6-ой цели устойчивого развития: водоснабжение и санитария для всех к 2030 году. История этого международного дня берет начало в 1992 году, когда состоялась Конференция ООН по окружающей среде и развитию в Рио-де-Жанейро. В том же году Генеральная Ассамблея ООН приняла резолюцию, в которой 22 марта каждого года объявлялся Всемирным днем воды, который отмечается с 1993 года.World Water Day celebrates water and raises awareness of the 2.2 billion people living without access to safe water. It is about taking action to tackle the global water crisis. A core focus of World Water Day is to support the achievement of Sustainable Development Goal 6: water and sanitation for all by 2030. The idea for this international day goes back to 1992, the year in which the United Nations Conference on Environment and Development in Rio de Janeiro took place. That same year, the United Nations General Assembly adopted a resolution by which 22 March of each year was declared World Day for Water, to be observed starting in 1993

Вплив легувальної добавки на теплофізичні та реологічні властивості полімерної композиції, що не містить галогенів, для ізоляції та оболонок кабелів

Introduction. The demand for halogen-free fire-resistant compositions for the manufacture of fire-retardant wires and cables is constantly growing. Problem. Therefore, the creation and further processing of these materials is an urgent problem. Goal. The aim of the article is to study the effect of the doping additive on the thermophysical and rheological properties of halogen-free compositions for power cables with voltage 1 kV with the determination of both the temperatures of phase and structural transformations of polymer compositions. Methodology. Experiments investigating the phase transformations were carried out with the help device of thermogravimetric analysis and differential scanning calorimetry TGA/DSC 1/1100 SF of METTLER TOLEDO company. Rheological studies of polymeric materials were conducted by using the method of capillary viscosimetry in the device IIRT–AM. Results. The influence of the doping additive on the formation of the supramolecular structure of the filled polymer compositions for cable products was determined, that resulted in the temperature increase of the decomposition beginning by 11 °С and the end of decomposition by 7 °С. Originality. The effect of a doping additive on reducing the effective melt viscosity of a polymer composition from 6·104 to 1·104 Pa·s with increasing shear rate has been shown for the first time. The shear rate of the polymer composition containing the doping additive increases from 0.5 to 20 s–1 with increasing shear stress. Practical value. The research results provide an opportunity to reasonably approach the development of effective technological processes for the manufacture of the insulation and sheaths of power cables from halogen-free polymer compositions.Попит на вогнестійкі композиції, що не містять галогенів, для виготовлення пожежобезпечних проводів та кабелів безперервно зростає. Тому розробка цих матеріалів є актуальною проблемою. Метою статті є дослідження впливу легувальної добавки на теплофізичні та реологічні властивості композицій. Теплофізичні властивості визначено з використанням приладу TGA/DSC 1/1100 SF компанії METTLER TOLEDO. Реологічні дослідження полімерних матеріалів проведено методом капілярної віскозиметрії на приладі ИИРТ-АМ. Визначено вплив легувальної добавки на формування надмолекулярної структури наповнених полімерних композицій. Встановлено зниження ефективної в’язкості розплаву полімерної композиції в 6 разів зі зростанням швидкості зсуву в 40 разів при зміненні температури від 150 до 190 °С. Швидкість зсуву полімерної композиції з легувальною добавкою зростає в 40 разів з підвищенням напруження зсуву в 9 разів. Результати досліджень дають можливість обґрунтовано підходити до розроблення ефективних технологічних процесів виготовлення ізоляції та оболонок силових кабелів

Идентификация видов рыбы с помощью технологии секвенирования нового поколения (NGS)

The laws relating to fish and fishery product labeling that require indication of the information about fish species exist in many world countries. These rules are conditioned by a significant growth in the number of the economic fraud cases in the field of production and trade of fishery products. The widespread ways of fraud are replacement and mislabeling of a product as confirmed by many studies. Analysis of scientific works shows that mislabeling in fishery product manufacture occurs in 30–70% of cases in different countries. The existing legislation about food traceability is insufficient for their prevention, which suggests a necessity of taking strict control measures ensuring effective species identification of fish and fishery products. At present, various laboratory tests are used for their species identification. They are based, mainly, on analysis of unique DNA profiles found in different species. In this work, we present the method for detection of fish species using next generation sequencing (NGS). NGS is an advanced technology in the field of quality control of fishery products, especially for fish species identification in multicomponent products, which contain DNA fragments of other species besides the target DNA. NGS was carried out on the platform Ion Torrent Ion GeneStudio S5 System. Twenty samples were analyzed: 17 commercial samples and three prepared experimental samples consisted of the mixture of two and more species. The universal primers, which were able to amplify the fragment 16S rRNA of the commercial fish species, were selected and prepared. In general, DNA of 11 families, 15 genera and 16 species was identified in the course of the analysis. The obtained result of NGS of 17 commercial samples confirmed the results of identification by other molecular diagnostic methods. Mislabeling was revealed in four samples. In three samples, all fish species present in the composition were identified. Possible reasons for fish replacement were assessed.Законы о маркировке рыбы и рыбной продукции, требующие указывать информацию о видовой принадлежности рыбы, есть во многих странах мира. Данные правила обусловлены высоким ростом количества случаев экономического мошенничества в области производства и оборота рыбных продуктов. Распространенными способами мошенничества являются подмена и  неправильная маркировка продукта, что подтверждается многочисленными исследованиями. Анализ научных работ показал, что применение неправильной маркировки при производстве рыбных продуктов в разных странах встречается в 30–70% случаев. Для их предотвращения имеющегося законодательства о прослеживаемости пищевых продуктов недостаточно, что указывает на необходимость принятия строгих мер контроля, обеспечивающих эффективную видовую идентификацию рыбы и рыбопродуктов. В настоящее время для идентификации их видовой принадлежности используют различные лабораторные тесты, главным образом основанные на анализе уникальных профилей ДНК, которые обнаружены у различных видов. В данной работе представлен метод определения видовой принадлежности рыб с использованием секвенирования нового поколения (NGS). Технология секвенирования NGS является передовой в области контроля качества рыбной продукции, особенно для идентификации видов рыб в многокомпонентной продукции, в которой помимо целевой ДНК присутствуют и фрагменты ДНК других видов. Секвенирование NGS проводили на платформе Ion Torrent Ion GeneStudio S5 System, были проанализированы двадцать образцов, 17 коммерческих образцов и 3 приготовленных опытных образца, состоящих их смеси двух и более видов. Были подобраны и подготовлены универсальные праймеры, способные амплифицировать фрагмент 16S rRNA промысловых видов рыб. В целом в ходе анализа была идентифицирована ДНК 11 семейств, 15 родов и 16 видов. Полученный результат секвенирования NGS17 коммерческих образцов подтверждал результаты идентификации другими молекулярно-диагностическими методами, была выявлена неправильная маркировка в 4 образцах. В 3 опытных образцах были идентифицированы все виды рыб, входящих в их состав. Была произведена оценка возможных причин замены рыбы

RESULTS AND PERSPECTIVES OF STUDYING THE OCCUPATIONAL DISEASES IN WORKERS OF AIRCRAFT INDUSTRY IN EAST SIBERIA

The materials of the long-studies among the employees working in the aircraft industry, of both the patients with occupational diseases and the practically healthy persons are discussed in the paper. Using the method of the biological feedback for the vibration-induced disease prevention has been grounded. The preliminary results of the experimental studies using the animals are presented in this paper

Report on the sixth blind test of organic crystal structure prediction methods.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z' = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr. Peter Horton (XXII), Dr. Brian Samas (XXIII), Prof. Bruce Foxman (XXIV), and Prof. Kraig Wheeler (XXV and XXVI). We are also grateful to Dr. Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of XXVI, as well as numerous colleagues at the CCDC for assistance in organising the blind test. Submission 2: We acknowledge Dr. Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements n. 307358 (ERC-stG- 2012-ANGLE) and n. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures on Gaussian 98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6: We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organisation for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge the support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr. Bouke van Eijck for his valuable advice on our predicted structure of XXV. We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial supports from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 “Toward Crystal Engineering from First Principles”, by the NSF award # EPS-1003897 “The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)”, and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from Khalifa University’s College of Engineering. I would like to acknowledge Prof. Robert Bennell and Prof. Bayan Sharif for supporting me in acquiring the resources needed to carry out this research. Dr. Louise Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous e-mail exchanges concerning the blind test. Prof. Sarah Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: R. J. N. acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/J017639/1]. R. J. N. and C. J. P. acknowledge use of the Archer facilities of the U.K.’s national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/1]). C. J. P. also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. B. M. acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, though grant ESPRC EP/K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project no. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: J.H. and A.T. acknowledge the support from the Deutsche Forschungsgemeinschaft under the program DFG-SPP 1807. H-Y.K., R.A.D., and R.C. acknowledge support from the Department of Energy (DOE) under Grant Nos. DE-SC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1107/S2052520616007447

Report on the sixth blind test of organic crystal-structure prediction methods

The sixth blind test of organic crystal-structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal, and a bulky flexible molecule. This blind test has seen substantial growth in the number of submissions, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and "best practices" for performing CSP calculations. All of the targets, apart from a single potentially disordered Z` = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms