Developing an interatomic potential for martensitic phase transformations in zirconium by machine learning

Interatomic potentials: predicting phase transformations in zirconium Machine learning leads to a new interatomic potential for zirconium that can predict phase transformations. A team led by Hongxian Zong at Xi’an Jiaotong University, China, and Turab Lookman at Los Alamos National Laboratory, U.S.A, used a Gaussian-type machine learning approach to produce an interatomic potential that predicted phase transformations in zirconium. They expressed each atomic energy contribution via changes in the local atomic environment, such as bond length, shape, and volume. The resulting machine-learning potential successfully described pure zirconium’s physical properties. When used in molecular dynamics simulations, it predicted a zirconium phase diagram as a function of both temperature and pressure that agreed well with previous experiments and simulations. Developing learnt interatomic potentials in phase-transforming systems could help us better simulate complex systems

COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic

During the onset of the COVID-19 pandemic, the COVIDiSTRESS Consortium launched an open-access global survey to understand and improve individuals’ experiences related to the crisis. A year later, we extended this line of research by launching a new survey to address the dynamic landscape of the pandemic. This survey was released with the goal of addressing diversity, equity, and inclusion by working with over 150 researchers across the globe who collected data in 48 languages and dialects across 137 countries. The resulting cleaned dataset described here includes 15,740 of over 20,000 responses. The dataset allows cross-cultural study of psychological wellbeing and behaviours a year into the pandemic. It includes measures of stress, resilience, vaccine attitudes, trust in government and scientists, compliance, and information acquisition and misperceptions regarding COVID-19. Open-access raw and cleaned datasets with computed scores are available. Just as our initial COVIDiSTRESS dataset has facilitated government policy decisions regarding health crises, this dataset can be used by researchers and policy makers to inform research, decisions, and policy. © 2022, The Author(s).U.S. Department of Education, ED: P031S190304; Texas A and M International University, TAMIU; National Research University Higher School of Economics, ВШЭThe COVIDiSTRESS Consortium would like to acknowledge the contributions of friends and collaborators in translating and sharing the COVIDiSTRESS survey, as well as the study participants. Data analysis was supported by Texas A&M International University (TAMIU) Research Grant, TAMIU Act on Ideas, and the TAMIU Advancing Research and Curriculum Initiative (TAMIU ARC) awarded by the US Department of Education Developing Hispanic-Serving Institutions Program (Award # P031S190304). Data collection by Dmitrii Dubrov was supported within the framework of the Basic Research Program at HSE University, RF

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Not AvailableTHE PAPER DESCRIBES THE COMMONLY USED METHODS OF ESTIMATING EVAPORATION AND ALSO COMPARES THEM TO INDICATE THE CHOICE OF METHOD UNDER THE GIVEN SITUATION. EVAPORATION FROM BHADRA RESERVOIR OF KARNATAKA IN THE SEMI- ARID REGION OF THE COUNTRY HAS BEEN ESTIMATED BY THE MASS TRANSFER AND PENMAN METHOD USING THE AVAILABLE CLIMATOLOGICAL AND RESERVOIR WATER LEVEL FLUCTUATION DATA.Not Availabl

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Not AvailableNTo undertake this study nine trainings of week’s duration on buffalo husbandry were organized for different types of respondents in which 254 farmers, entrepreneurs, women and youth participated. Training needs of different categories of respondents were worked out. The farmers considered the topics on heat symptoms in buffaloes and artificial insemination, feeding and management of lactating animals and mastitis in buffaloes and its care and management as most important for their training module. As far as training contents for youth are concerned they specially desired to include nutrients in concentrate mixture and importance of reproduction in buffaloes. They also wanted that half of the time each should be devoted to theory and practicals respectively. Women evinced keen interest in feeding requirements of dry, milch and pregnant buffaloes, management and reproduction of buffaloes during heat and importance of AI in buffaloes. The entrepreneurs desired that they should be given information on some new technologies like preparation of mineral mixture, preparation of complete feed blocks, care and management of calves for meat production and importance of reproduction, heat detection and therapeutic control of estrous. The appropriateness of contents was confirmed when response was elicited from different categories of respondents in subsequent training programmes.ot AvailableNot Availabl

Pressure Effects on Single Wall Carbon Nanotube Bundles

We report high pressure Raman studies on single wall carbon nanotube bundles under hydrostatic conditions using two different pressure transmitting media, alcohol mixture and pure water. The radial and tangential modes show a blue shift when SWNT bundle is immersed in the liquids at ambient pressures. The pressure dependence of the radial modes is the same in both liquids. However, the pressure derivatives dw/dP of the tangential modes are slightly higher for the water medium. Raman results are compared with studies under non-hydrostatic conditions and with recent high-pressure X-ray studies. It is seen that the mode frequencies of the recovered sample after pressure cycling from 26 GPa are downshifted by $~7-10 cm^{-1}$ as compared to the starting sample

Structural changes in single-walled carbon nanotubes under non-hydrostatic pressures: x-ray and Raman studies

Using in situ x-ray diffraction and Raman scattering techniques, we have investigated the behaviour of single-walled carbon nanotubes bundles under non-hydrostatic pressures. It is seen that the diffraction line corresponding to the two-dimensional triangular lattice in the bundles is not reversible for pressures beyond 5 GPa, in sharp contrast to earlier results under hydrostatic pressure conditions. Most interestingly, radial breathing and tangential Raman modes of the pressure-cycled samples from 21 and 30 GPa match very well with those of the starting sample. Raman and x-ray results put together clearly suggest that the ordering of tubes in the bundles is only marginally regained with a very short coherence length on decompression